Universität für Bodenkultur Wien

University of Natural Resources and Life Sciences, Vienna

Department of Biotechnology Institute of Applied Microbiology

ACBR

Bioremediation of waste gas and soil by black extremotolerant fungi

Master Thesis

submitted by Caroline Poyntner, Bakk. techn.

Vienna, 2014

Supervisor: Katja Sterflinger-Gleixner, Assoc. Prof. Dr.

Acknowledgement

I would like to thank my supervisor, Prof. Sterflinger-Gleixner, for giving me the opportunity, support and trust to conduct this thesis in her group and in the collaborating group in Spain. Thanks for always having an open door and advice during the last years. I also want to thank the group members of the ACBR, who helped to create a good atmosphere in the lab and who always tried to help and became friends. Also thankful thoughts go to my supervisor in Spain, Prof. Prenafeta-Boldú, and his colleagues Miriam and Laura, who were great support in a new (Catalonian) environment. I would also like to thank the institute of biotechnology of the University of Natural Resources and Applied Life Sciences Vienna and the FWF for supporting this project Of course, I also want to thank my parents and my brother Lukas, who not only gave me financial backing but also the freedom to find my own way even if this meant that I would be out of town another time and an end of my education further out of reach. Supporters in different kind of ways were my friends who had time for me when I was worried, unhappy or unsatisfied during my studies, spent their precious free time with correcting my thesis, or distracted my with climbing and snowboarding. Thank you, Dani, Vicky, LFs, Clara and Gabriel.

What you do

makes a difference,

and you have to decide

what kind of difference you want to make.

Jane Goodall

Abstract Around the world there are a lot of polluted sites which need treatment because they are dangerous to human and environmental health. A possible treatment is bioremediation, where the focus lies on engineered microorganism, mostly bacteria. As remediation with bacteria has some disadvantages, this study focuses on finding fungal strains for bioremediation. Next to bioremediation, the usage of the strains on biofilters is a target. Biofilters could be used for treatment of waste gases in industry. In this study, three different pollutants of the group of hydrocarbons were tested. Hydrocarbons were chosen, because it is already known that some fungal strains are able to degrade them. Another factor is that the chemicals, toluene, hexadecane and polychlorinated biphenyl 126, are often found in polluted sites, as they are very abundant chemicals in petrol and oils. Therefore treatment is necessary. In this study, screenings were conducted to see which fungal strains are able to live in the presence of the three hydrocarbons and furthermore are able to degrade them. The focus lied on fungal strains from extreme environment, especially the group of black fungi, as they are known to be very stress resistant. Therefore they are good candidates for bioremediation. In this study, 163 different strains from the Centraalbureau voor Schimmelcultures (CBS) were screened. The screening was performed in two steps. First, a general microtiter plate screening with the help of a Tecan reader was carried out. The Tecan reader observed growth through measuring the change of absorption during the test period. Second step was a detailed screening to detect the detailed degradation. This was done with gas chromatography, which measured concentrations of the hydrocarbons and the production of CO2. The first screening was done at the ACBR in Austria and the second one at IRTA in Spain. The screening methods for the studies were successfully developed and we were able to find two strains which showed a good degradation performance for toluene, growing on this compound as the sole source of carbon and energy and, thus, converting it into water and carbon dioxide. Therefore they are promising candidates for bioremediations applications. Keywords: Bioremediation, biofilters, extremotolerant fungi, black fungi, hydrocarbons, microtiter plate screening, Gas Chromatography Screening

Zusammenfassung

Weltweit gibt es eine große Anzahl an Altlasten und Deponien, die einer Sanierung bedürfen, da sie eine Bedrohung für die Gesundheit des Menschen und der Umwelt darstellen. Bei der Sanierung wird in vielen Fällen zum Mittel der biologischen Altlastensanierung gegriffen. Hierbei wird meist mit Hilfe modifizierter Bakterien die Verschmutzung abgebaut. Da jedoch die Methode mit Bakterien auch Nachteile hat, wird oftmals nach Alternativen gesucht. In dieser Studie wurden daher verschiedene Pilzstämme untersucht, um sie als alternative Kandidaten in der biologischen Altlastensanierung einzusetzen. Eine andere Anwendung wäre der Einsatz von Pilzstämmen in sogenannten Biofiltern, die zur Reinigung von Abgasen eingesetzt werden könnten. In der Arbeit wurde der Fokus auf extremotolerante Pilzstämme gerichtet, da diese unter sehr viel Stress und extremen Umwelteinflüssen wachsen zu können. Vor allem Vertreter der Gruppe schwarze Pilze wurden untersucht, da von ihnen bereits einige bekannt sind, die Kohlenwasserstoffe abbauen können. Als Kontaminationsstoffe wurde Kohlenwasserstoffe gewählt, da diese sehr oft als langlebige Schadstoffe in Altlasten zu finden sind. 163 Pilzstämme des Centraalbureau voor Schimmelcultures (CBS) wurden mit drei verschiedenen Kohlenwasserstoffen, Toluol, Hexadekan und polychloriertes Biphenyl 126 in zwei verschiedenen Screenings auf ihre Abbaueigenschaften getestet. Im ersten Screening wurde das Wachstum der Stämme in Anwesenheit der Kohlenwasserstoffe mit Hilfe von Mikrotiterplatten getestet. Das Wachstum wurde durch Absorptionsmessungen mit einem Tecan Reader analysiert und am ACBR in Österreich durchgeführt. Im nachfolgenden Screening am IRTA in Spanien wurde der Abbau der Kohlenwasserstoffe mit Gaschromatographiemessung gemessen. Mit der Chromatographiemethode konnten genaue Konzentration der Kohlenwasserstoffe und CO2 Konzentrationen gemessen werden. Die Screening Methoden wurden erfolgreich entwickelt und am Ende konnten zwei Stämme gefunden werden, die gute Abbauergebnisse von Toluol erzielten. Sie nutzten diesen Kohlenwasserstoff als einzige Kohlenstoff und Energiequelle und konnten es zu Kohlendioxid und Wasser abbauen. Daher sind die Stämme vielversprechende Kandidaten für Bodensanierung. Schlagwörter: Bodensanierung, Biofilter, Kohlenwasserstoffe, extremotolerante Pilze, schwarze Pilze, Mikrotiterplatten Screening, Gas Chromatographie

List of contents

1 Introduction ..................................................................................................................................... 9 1.1 Aim of the thesis ......................................................................................................................9 1.2 Bioremediation ........................................................................................................................9 1.3 Choice of microorganism: fungi or bacteria?........................................................................ 10 1.4 Black fungi ............................................................................................................................. 11 1.5 Species .................................................................................................................................. 13 1.6 Pathways ............................................................................................................................... 13 1.7 Hydrocarbons ........................................................................................................................ 14

1.7.1 Toluene .............................................................................................................................. 15 1.7.2 Hexadecane ....................................................................................................................... 15 1.7.3 Polychlorinated biphenyl 126 ............................................................................................ 16

2 Materials and Methods ................................................................................................................. 17 2.1 Materials ............................................................................................................................... 17

2.1.1 Equipment ......................................................................................................................... 17 2.1.2 Media Micotiter Plates ...................................................................................................... 18 2.1.3 Media Screening Teflon coated bottles ............................................................................ 19 2.1.4 Media for cultivation of fungi ............................................................................................ 20 2.1.5 Hydrocarbons .................................................................................................................... 21 2.1.6 Microorganisms ................................................................................................................. 21

2.2 Methods ................................................................................................................................ 22 2.2.1 Pre-tests ............................................................................................................................ 22

4.2.1.1 Cultivation of strains __________________________________________________ 22 4.2.1.2 Microtiter plates Pre-tests _____________________________________________ 22

a. Hexadecane ____________________________________________________ 22 b. PCB 126 ________________________________________________________ 22 c. Toluene ________________________________________________________ 22

2.2.1.3 Inoculum _________________________________________________________ 23 2.2.1.4 TTC ______________________________________________________________ 23

2.2.2 Microtiterplate screening .................................................................................................. 23 4.2.2.1 Cultivation of strains __________________________________________________ 23 2.2.2.2 Preparation of microtiter plates _______________________________________ 24

2.2.3 Screening with Gas-Chromatography (GC) ....................................................................... 24 2.2.3.1 Teflon bottles _____________________________________________________ 24

Negative Control_________________________________________________ 25

Positive Control _________________________________________________ 25

Hydrocarbon ____________________________________________________ 25 2.2.3.2 GC-measurements __________________________________________________ 25 2.2.3.3 GC-FID ___________________________________________________________ 25 4.2.3.4 GC-TCD_____________________________________________________________ 26

3 Results ........................................................................................................................................... 27 3.1 Pre-tests ................................................................................................................................ 27 3.2 Microtiter plate screening .................................................................................................... 27 3.3 Results of GC - screening ...................................................................................................... 30

3.3.1 Negative results ................................................................................................................. 31 3.3.2 Positive results for toluene degradation ........................................................................... 32

3.3.2.1 Cladophialophora immunda __________________________________________ 32 3.3.2.2 Exophiala mesophila ________________________________________________ 34

3.3.3 Toxicity .............................................................................................................................. 36 4 Discussion ...................................................................................................................................... 39 5 Conclusion and Outlook ................................................................................................................ 43

6 References ..................................................................................................................................... 44 7 Appendix: ...................................................................................................................................... 48

7.1 Diagrams microtiter plate pre-tests ...................................................................................... 48 7.2 Diagrams microtiter plate screening .................................................................................... 50

7.2.1 PCB 126 .............................................................................................................................. 50 7.2.2 Toluene .............................................................................................................................. 69 7.2.3 Hexadecane ....................................................................................................................... 88

7.3 Diagrams GC screening ....................................................................................................... 107

List of tables Table 1: Equipment ACBR, University of Natural Resources and Applied Life Sciences, Austria ...... 17 Table 2: Equipment IRTA, Spain ........................................................................................................... 17 Table 3: Gas Chromatographs (GC) ...................................................................................................... 18 Table 4: Trace element solution ........................................................................................................... 18 Table 5: Vitamin solution ..................................................................................................................... 19 Table 6: Growth medium ...................................................................................................................... 19 Table 7: Glucose vitamin/trace element media .................................................................................. 19 Table 8: Glucose medium ..................................................................................................................... 19 Table 9: Ingrediens vitamin solution .................................................................................................... 20 Table 10: Solution A .............................................................................................................................. 20 Table 11: Solution B .............................................................................................................................. 20 Table 12: Malt extract agar .................................................................................................................. 20 Table 13: Malt-Pepton Solution / Glycerin Solution ........................................................................... 20 Table 14: Hydrocarbon used for Screening .......................................................................................... 21 Table 15: Strains pre-test ..................................................................................................................... 22 Table 16: Results Microtiter plate screening: ...................................................................................... 28

List of figures

Figure 1: Phylogenetic tree based on 1700 positions of small subunit ribosomal DNA .................... 12 Figure 2: Three different black yeast species: Exophiala sideris, Exophiala spinifera, Cladophialophora minourae(from left to right) .................................................................................... 13 Figure 3: Different metabolic pathways starting form toluene, styrene, ethylbenzene and benzene. ............................................................................................................................................................... 14 Figure 4: Various ways how hydrocarbons can penetrate soil (Young & Cerniglia 1995, p. 83). ....... 14 Figure 5: Chemical formula for toluene (National Institutes of Health, 2012). ................................... 15 Figure 6: Chemical formula of hexadecane (National Institutes of Health, 2012). ............................. 15 Figure 7: Chemical formula of PCB 126 (Royal Society of Chemistry, 2014). ....................................... 16 Figure 8 Lyophilized vials, tubes with tilted agar ................................................................................ 23 Figure 9: Toluene Plates in desiccator, Tecan Reader. ........................................................................ 24 Figure 10 GC-FID and GC-TCD ............................................................................................................... 26 Figure 11: A, B, C: Microtiter plate screening of strain 114, Pseudallescheria boydii, with the hydrocarbons PCB126 (A), toluene (B) and hexadecane (C). .............................................................. 31 Figure 12: Teflon coated bottle: ........................................................................................................... 32 Figure 13: GC-results ............................................................................................................................. 32 Figure 14 A, B, C: Microtiter plate screening of strain 17, Cladophialophora immunda, with the hydrocarbons PCB126 (A), toluene (B) and hexadecane (C). OD 700 plotted against the days of measurement. ....................................................................................................................................... 33 Figure 15: Teflon coated bottles: ......................................................................................................... 33 Figure 16: GC-results: ............................................................................................................................ 34 Figure 17 A, B, C: Microtiter plate screening of strain 64, Exophiala mesophila, with the hydrocarbons PCB126 (A), toluene (B) and hexadecane (C).OD 700 plotted against the days of measurement. ....................................................................................................................................... 35 Figure 18: Teflon coated bottles: ......................................................................................................... 35 Figure 19: GC-results: ............................................................................................................................ 36 Figure 20 A, B, C: Microtiter plate screening of strain 25, Exophiala jeanselmei, with the hydrocarbons PCB126 (A), toluene (B) and hexadecane (C).OD 700 plotted against the days of measurement. ....................................................................................................................................... 37 Figure 21: GC-results: ............................................................................................................................ 38 Figure 22: Two different microtiter plates with different fungal strains; .......................................... 40

1 Introduction

1.1 Aim of the thesis

A series of fungal strains were screened for their ability to degrade hydrocarbons. Screenings were carried out at the ACBR, Vienna and at IRTA, Caldes. The aim of the study was to find promising fungal strains, which could be used for bioremediation purposes in soil, water or in biofilters. Hydrocarbons are regulated as pollutants in the EU as they are toxic to humans and environment. Strategies to treat those pollutions are searched strongly. One of them is remediation. Hydrocarbons are classified in different groups, one of them are aromatic hydrocarbons. Aromatic hydrocarbons like benzene, toluene, ethyl benzene and the xylene isomers (collectively known as BTEX) are among the most abundant components from the water soluble fraction of crude oil and refined fuels(Prenafeta-Boldú et al., 2001a). Due to their toxicity and persistence, aromatic hydrocarbons are regarded as one of the major environmental pollutant group and have therefore been subjected to stringent environmental regulations (Mehlman et al. 1992). Treating those toxic compounds is challenging, because of wide dispersal and concentrations that cannot be treated chemically or physically due to high expenses. Hydrocarbon pollution can result from leaking gasoline tanks, gasoline accidents and other sources. BTEX and additive methyl-tert-butyl ether (MTBE) are the most water-soluble components of gasoline. Therefore these compounds predominate groundwater contaminant plumes from recent gasoline spills (Prenafeta-Boldú et al., 2004). Existing bioremediation techniques are mostly using bacteria as degradation organisms, while using fungi is a rather new approach. Bacteria have a high metabolic diversity and can assimilate a great variety of organic chemicals. Their disadvantage is to have a low physiological flexibility. If environmental conditions like pH, water availability or temperature change, they have problems to adapt.

Fungal strains mostly metabolize xenobiotics by co-metabolism which leads to low degradation rates and the need of co-substrates but they can grow on under more stringent conditions. Therefore they are able to grow on solid matrixes, extreme pH, low water content, low/high temperatures and can adapt if conditions change. The chosen organisms for this study, extremotolerant fungi, can live in extreme conditions and are therefore good candidates for bioremediation applications. The extremotolerant fungi used for the screening carried out in the frame of this thesis, mostly belong to the group of black yeasts-also called microcolonial fungi (MCF) which are among the most stress-tolerant organism on the Earth (de Hoog and Grube M., 2008). In the experiments of the thesis it was screened for strains which are able to degrade the hydrocarbons completely to carbondioxide and water and therefore no additional inputs of co-substrates in the bioremediation application is needed. The application in bioremediation would be either as living strains or in well-known genetically modified host organisms, where their attributes are expressed.

1.2 Bioremediation

In Austria, currently 65.586 hazardous sites are registered and only 3-9% treated (Granzin and Valtl, 2013; Skala et al., 2007) either by excavation, chemical, physical, biological cleaning methods or a combination of these. As this is not only the case for Austria but a problem all around the world, finding good waste treatment solutions is urgent. A big focus lies on remediation technologies, which are currently already working in some sites and different novel approaches are searched. Remediation technologies serve to immobilize contaminants, separate them from the soil, or destroy those (Caliman et al., 2010). They can be divided into in situ and ex situ methods. The U.S. Environmental Protection Agency (Engineering Forum, 2006) differentiates the in situ techniques into

9

biological-treatments

thermal-treatments

physical/chemical treatments

The aim in this study belongs to the so called bioremediation, a remediation with the use of microorganisms. This treatment is defined as biological treatment. Biological treatments can be further differentiated into:

bio-augmentation: a bioremediation option for hydrocarbon-contaminated, oily-sludge restoration (Ayotamuno et al., 2007)

biosparging: pressurized air is injected under the water table and therefore enhances the rate of biological degradation of contaminant by naturally occurring bacteria (Gavrilescu, 2005; Kao et al., 2008)

bioventing: oxygen is enriched through a system of extraction and injection wells, which lasts from several months to years (Caliman et al., 2010)

composting

and several other less frequently applied methods;

The method aimed for this study is bioaugmentation. Bioaugmentation is not an easy technique, as lot of criteria have to be taken in account when working with microbes. Critical points in bioremediation are the bioavailability of the contaminant for the microorganisms, the degradation to less toxic compounds and the opportunity for optimization of biological activity (Crawford et al., 2004; Dua et al., 2002; Gavrilescu, 2005; Ward and Sing, 2004).

1.3 Choice of microorganism: fungi or bacteria?

The well-known bioremediation techniques which are using engineered bacteria have the disadvantages to show slow dispersal, long processes and are less effective if conditions change. Also nitrogen as well as phosphor are limiting factors. Contaminated soil is often lacking microorganisms with the ability to degrade the pollutants. Therefore in usage of bioaugmention additional microbial colonies are added to contaminated soil. Bacteria are often too slow to fill the open spaces in the soil and as a consequence, less effective microorganisms take over the place. This leads to very long processes in bioremediation, where conditions change until bacteria colonies are not able to adapt anymore. Fungi, on the other hand, can survive changing environmental conditions. This is an important factor in industrial spills. They can survive low amount of oxygen, changes in pH, water availability and temperature as well as limited access to nitrogen and phosphor. Fungal enzymes are more abundant than bacterial enzymes. Furthermore, fungal strains which live in extreme environments can produce so called extremozymes, for example laccases. Laccases can be a contribution to biodegradation for a wide range of aromatic pollutants (Hölker et al., 2004). All this listed advantages lead to the conclusion that fungal strains could be good candidates for bioremediation. Nevertheless, there are some disadvantages. A big disadvantage of fungal strains is, that most of them are not able to completely degrade contaminants. In partial degradations, they produce co-metabolites, which need to be studied in advance to know if they are toxic. Some strains are just able to degrade the toxic contaminant in presence of another substance, which means that additional inputs can be necessary. This leads to lower metabolic rates and biomagnification and therefore makes the process more difficult. In this thesis, two screenings were conducted with 163 fungal strains. The mentioned disadvantages are the reason why so many different isolates were tested. A lot of species adapt to their environment and differ between their isolation sources. In the first screening, the strains were tested on their ability to grow in the presence of hydrocarbons while in the second screening the detailed metabolic process was examined.

10

1.4 Black fungi

Fungi represent the greatest eukaryotic diversity on earth and they are among the primary decomposers in ecosystems (Tsui et al., 2011). They share a long history with us, being useful producers of antibiotics or being a threat to our health in form of mycosis (Galagan et al., 2005). There is a huge amount of different species and groups differentiating themselves through different attributes like morphologies, genetics and reproduction. The group of black fungi was chosen for the purpose of bioremediation, as they are found in extreme environments and are therefore resistant to stress conditions. On one hand numerous species exhibit a significant human-pathogenic potential (de Hoog et al., 2003; Zeng et al., 2007), which can affect skin, lungs and nervous systems of humans and on the other hand, they have the unique ability to thrive in environments enriched with toxic hydrocarbons (benzene and xylene; Prenafeta-Boldú et al. 2006). For example, three different species of Exophiala have been isolated from sites polluted with hydrocarbons or with the aid of alkyl benzene enrichment (Zhao et al., 2010). A study of Badali (Badali et al., 2011) suggests that the two attributes of being pathogen and of being able to live on hydrocarbons are not necessarily combined in the same species. The stress resistance is the major argument for using them in bioremediation. Recent experiments showed that the stress resistance of MCF against solar radiation, radioactivity, desiccation and oligothophic conditions even allow them to survive space and Martian conditions (Zakharova et al., 2013). “Black yeast” is a terminus technicus subscribing a group of fungi that is quite heterogeneous from the taxonomic and phylogenetic point of view. They have a melanized cell wall in common and the formation of daughter cells by yeast-like multilateral and polar budding (Sterflinger, 2005). The umbrella term is used to indicate heterogeneous lineages of Chaetothyriomycetidae and Dothideomycetidae. The different orders can be seen in the phylogenetic tree in Figure 1. “Meristematic fungi” is another term to describe fungi with melanized cell walls, which grow and reproduce in isodiametric division. MCF describes a growth pattern, by both kinds – black yeasts and meristematic fungi. They characteristically grow in small, clump-like colonies which can survive stress like desiccation, pH difference, solar radiation and even radioactivity. They are also known to be hydrocarbonoclastic. The surface-volume-ratio is kept small to save water and survive UV-radiation. Some are even able to do micro- and macropitting on the rocks and stones they are living, to absorb minerals, which is a problem in cultural heritage protection. It is known that on rock surfaces, where microbial interactions occur, there are constant changes in atmospheric conditions (Zakharova et al., 2013). In this sense, as assumed by Gorbushina (Gorbushina et al., 2008), ubiquitous subaerial biofilms are bioindicators that are continually subjected to climate change. Therefore we can determine climate change by monitoring biofilms of fungi and other microorganisms on rocks. Another term for the attributes of black yeasts is “poikilo tolerant”. The term poikilo-tolerant (resistant to variable stress; from poikilos: variegated) has been used to describe the behaviour of living organisms in environments, where tolerance to multiply and variable parameters is essential for survival (Gorbushina, 2007). Living on filter membranes or as soil inoculation, they could degrade pollutants without getting disturbed by the environment easily.

11

12

Figure 1: Phylogenetic tree based on 1700 positions of small subunit ribosomal DNA (tree modified from Sterflinger 2005).MCF; growing on rock are highlighted. Bootstrap values were generated from 1000 trees using the Felsenstein method (Sterflinger et al., 2012)

1.5 Species

163 strains from the Centraalbureau voor Schimmelcultures (CBS, Netherlands Royal Academy of Science, www.cbs.knaw.nl) were chosen for the screening in the thesis. Recent studies (Prenafeta-boldu et al. 2001a; Prenafeta-Boldú et al. 2004; Prenafeta-Boldú et al. 2006; Isola et al. 2013) showed that a high diversity of fungi have degrading abilities, most of them belonging to the group of black yeasts. Therefore also for the screening as seen in Figure 2, the majority of strains belonged to that group. The groups which were used belonged to black yeast-like organisms (order Chaeotrhyriales) and Scedosporium species (order: Microascales). Scedosporium species are associated with alkane-contaminated sites and degrade linear aliphatic compounds (April et al., 1998; Claussen and Schmidt, 1998; Janda-Ulfig et al., 2008; Onodera et al., 1990). For both orders various publications show that they are able to live in polluted sites. Belonging to the black yeast-like group, they have melanin as a protection attribute, which helps them to survive in stressful environments. Next to their habitats in extreme niches, they are also found as human pathogens, forming life threatening mycoses.

13

Figure 2: Three different black yeast species: Exophiala sideris, Exophiala spinifera, Cladophialophora minourae(from left to right)

1.6 Pathways

While degradation of polyaromatic compounds by fungi is well studied, the metabolism of monoaromatic hydrocarbons is still poorly understood and studies on this are rare (Prenafeta-Boldú et al. 2001b). Two enzymatic systems are suggested to take part in the oxidation of aromatic hydrocarbons. These are the enzymatic systems of the detoxifying cytochrome P450 monooxygenases, laccases and the lignin-decomposing peroxidase (Luykx et al., 2003). In Figure 3, the different mentioned pathways (Luykx et al. 2003; Rustler et al. 2008) are described. For benzene, the assimilatory pathway is not known yet.

Figure 3: Different metabolic pathways starting form toluene, styrene, ethylbenzene and benzene.

1.7 Hydrocarbons

For the screening, three different hydrocarbons were applied. They were used as representatives for the groups of alkenes, aromatic hydrocarbons and polychlorinated biphenyls. Hydrocarbons are substances in mineral oil, which next to heavy metals is suspected to be the most frequent soil contamination at investigated sites. Mineral oil and chlorinated hydrocarbons are the most frequent contaminants found in groundwater (EEA 2007). Distribution ways for the example of oil pollution in soil are shown in Figure 4.

14

Figure 4: Various ways how hydrocarbons can penetrate soil (Young & Cerniglia 1995, p. 83).

1.7.1 Toluene

15

Figure 5: Chemical formula for toluene (National Institutes of Health, 2012).

Toluene is a chemical compound, which can be found in natural crude oil. It is used as a solvent found in aviation gasoline, spray and wall paints, paint thinner, medicine, dyes, explosives, detergents, fingernail polish, spot removers , lacquers, adhesives, rubber and antifreeze (Tox Town, 2002). It can affect health, depending on exposure levels to the chemical. While the inhalation of high levels of toluene cause unconsciousness, low levels lead to headache, dizziness, fatigue, nausea and other short term affects. Long-time exposure can affect kidneys, nervous system, liver, brain and the heart. Any gasoline pollution can contain toluene and is therefore a substance, which should be removed from the environment. It is already known that fungal species are able to live with toluene as sole carbon source. For instance Weber et al., 1995, were able to find Cladosporium sphaerospermum, which is able to grow on toluene. Later it was reclassified as Cladophialophora saturnica through molecularbiological techniques (Badali et al., 2009), while before it was classified morphologically.

1.7.2 Hexadecane

Figure 6: Chemical formula of hexadecane (National Institutes of Health, 2012).

As toluene, hexadecane can be found in gasoline and diesel, rubber, shale oil production, coal combustion, biomass and refuse combustion and tobacco smoke (National Institutes of Health, 2012). Not only exposure due to inhalation is problematic, but also pollution of water, which leads to a hexadecane intake of fishes as well as seafood and furthermore to human intake through food.

1.7.3 Polychlorinated biphenyl 126

Figure 7: Chemical formula of PCB 126 (Royal Society of Chemistry, 2014). Polychlorinated biphenyls are proved to be toxic in animals(National Institutes of Health, 2012). Due to their widespread, uncontrolled industrial applications, PCB's have become a ubiquitous contaminant in the environment (National Institutes of Health, 2012). Especially in foods coming from animal sources, a lot of PCBs can be detected and are therefore a critical health risks. They can affect the immune, reproductive, nervous and endocrine systems and have been linked to low intelligence quotients in children (Van Emon et al., 2013). Although banned in many countries, PCB is very persistent and can be found in air, soil, dusts and sediments. In-situ bioremediation is an attractive alternative for the treatment of PCB-contaminated soils and sediments (Ruiz-Aguilar et al., 2002), but only aerobic bioremediation with bacteria has been studied extensively (Fiebig et al., 1993; Quensen et al., 1990; Rojas-Avelizapa et al., 1999). Some fungi were found to be able to degrade PCB (Ruiz-Aguilar et al., 2002).

16

2 Materials and Methods

2.1 Materials

2.1.1 Equipment

The Equipment used at ACBR, University of Natural Resources and Applied Life Science, Austria and at GIRO, IRTA, Spain is listed in Table 1 and Table 2. The parameters used for the gas chromatography are listed in Table 3. Table 1: Equipment ACBR, University of Natural Resources and Applied Life Sciences, Austria

17

device supplier Tecan reader TECAN reader infinite® M1000 reader, Tecan group Ltd. (switzerland) laminar flow bench Thermo scientifc MSC advantage pipettes/ multichannel pipettes Eppendorf / VWR microtiter plate shaker Stuart SSL5 microtiter plate shaker, Bibby Scientific Limited desiccator Glaswerk-Wertheim microtiter plates Cellstar, Greiner-Bio-One, 655180 sterile syringe filter Rotilab ®, CARL ROTH GMBH + CO. KG ribolyzer MP Fast Prep 24 autoclave CertoClav sterilizer GmbH scale Santorius AG

Table 2: Equipment IRTA, Spain device supplier 250 mL boston flask with Teflon Waddinxveen, the Netherlands mininert valves

hydrocarbon chamber Captair by Erlab bio safety cabinet Telstar Bio IIA Burdinola sterile syringe Thermo Scientific, USA pipettes Eppendorf microsyringes 1705-1710 (Luer-Lock), Hamilton Bonaduz AG Needle P/N 7729-07/00.

autoclave JP SELECTA S.A. incubator Memmert GmbH scale Scaltec SBC 51

Table 3: Gas Chromatographs (GC)

18

device supplier / properties name Trace 2000 series Thermo Quest CE Instruments column TRB624 N° series NF8261 gas carrier He (2 mL/min) septum Diskobolus/Teknokroma Septa

Marathon 12 mm TR-D033064 slope isothermal initial temperature 180 °C (toluene)

220 °C (hexadecane) end temperature 180 °C (toluene) 220 °C (hexadecane) injector temperature 250 °C

temperature detector 250 °C injection split/ split less split 1:50 (toluene)

1:5 (hexadecane) injection volume 100 µL hold time 2.00 min (toluene)

6.00 min (hexadecane) split flow 100 mL/min gas saver flow 20 mL/min

Varian CP-3800 Varian Inc. column Haysep Q 80-100 method CO2measurement Front_2013, Software Galaxie N° series 320056731-17 gas carrier He (45 mL/min) septum DISKOLBOLUS Green Septa 9mm TR-

D033032 slope isothermal initial temperature 90 °C end temperature 90 °C injector temperature 180 °C temperature detector 180 °C injection on column pressure 26.7 kPa-psi injection volume 200 µL hold time 1 min

2.1.2 Media Micotiter Plates

For the microtiter plate screening, two solutions were needed as described in Table 4 and Table 5, a vitamin solution and a trace element solution respectively. The vitamin solution was sterile filtrated and then stored at 4°C while the trace element solution was kept at room temperature. Those two basic solutions were needed to prepare the three working solutions: growth medium (Table 6), glucose vitamin/trace element medium (Table 7) and glucose medium (Table 8). All three solutions were sterilized at 120 °C for 15 minutes and the vitamin solution was added in sterile conditions after cooling down of the medium. PH was adjusted to 5.5 with potassium hydroxide. The three media were kept at room temperature. Table 4: Trace element solution ingredients concentration (per L) supplier magnesium chloride hexahydrate 40 g Merck GesmbH calcium chloride 10 g Merck GesmbH sodium chloride 10 g AppliChem GmbH iron(III) chloride hexahydrate 200 mg Merck GesmbH hydrogen borate 50mg Sigma Aldrich GmbH copper sulphate 10 mg Merck GesmbH manganese chloride 40mg Merck GesmbH potassium iodide 10mg AppliChem GmbH sodium molybdate 20mg Alfa Aesar GmbH zinc sulphate 40mg Merck GesmbH hydrogen chloride for dissolving Merck GesmbH

Table 5: Vitamin solution

19

ingredients concentration (per 0.1L) supplier biotin 2mg Merck GesmbH calcium - panthothenate 200 mg Merck GesmbH folic acid 0.2 mg Merck GesmbH myo-inositol 1 g Merck GesmbH niacin 40 mg Merck GesmbH 4-aminobenzoic acid 20 mg AppliChem GmbH pyridoxine hydrochloride 40 mg AppliChem GmbH riboflavin 20 mg Merck GesmbH thiamine hydrochloride 40 mg Merck GesmbH

Table 6: Growth medium ingredients concentration (per L) supplier potassium dihydrogen phosphate (KH2PO4) 9.5 g Merck GesmbH dipottasium hydrogen phosphate (K2HPO4) 0.5 g AppliChem GmbH magnesium sulphate heptahydrate (MgSO4*7H2O) 0.1 g Merck GesmbH ammonium chloride (NH4Cl) 2 g AppliChem GmbH trace element solution 10 mL vitamin solution 1 mL

Table 7: Glucose vitamin/trace element media ingredients concentration (per L) supplier KH2PO4 9.5 g Merck GesmbH K2HPO4 0.5 g AppliChem GmbH MgSO4*7H2O 0.1 g Merck GesmbH NH4Cl 2 g AppliChem GmbH glucose 2 % AppliChem GmbH trace element solution 10mL vitamin solution 1 mL

Table 8: Glucose medium ingredients concentration (per L) supplier KH2PO4 9.5 g Merck GesmbH K2HPO4 0.5 g AppliChem GmbH MgSO4*7H2O 0.1 g Merck GesmbH NH4Cl 2 g AppliChem GmbH glucose 2 % AppliChem GmbH

Next to those three media a tetrazolium chloride (TTC) solution (0.2 %, Serva Chemicals) was prepared and sterilized through a filter (Roth, 0.22 µm). It was kept shielded from light at room temperature.

2.1.3 Media Screening Teflon coated bottles

In the Teflon coated bottles, a mineral medium (Hartmans and Tramper 1991) and a solution of vitamins (2 mL/L, Table Table 9) were used. The mineral medium was composed of solution A and B (see Table 10: Solution A and Table 11: Solution B respectively), which were mixed in a proportion of A: 10 mL and B: 25 mL in one litre. Solution A and B were autoclaved, afterwards the vitamin solution was added. The sterile filtration was done with a sterile filter (Roth, 0, 22 µm) under sterile conditions.

Table 9: Ingredients vitamin solution

20

ingredients concentration (per L) supplier

nicotinic acid 100 mg Sigma Aldrich GmbH calcium Pantothenate 200 mg Scharlau cyanocobalamin 25 mg Scharlau inositol 100 mg Sigma Aldrich GmbH p-aminobenzoate 20 mg Sigma Aldrich GmbH thiamine 50 mg Sigma Aldrich GmbH pyridoxine 25 mg Scharlau biotin 10 mg Scharlau riboflavin 10 mg Scharlau folic acid 10 mg Sigma Aldrich GmbH thioctic acid 10 mg Sigma Aldrich GmbH

Table 10: Solution A ingredients concentration (per L) supplier ammonium sulphate 200 g Sigma Aldrich GmbH magnesia chloride hexahydrate 10 g Fluka Chemicals ethylenediaminetetraacetic acid 1 g Sigma Aldrich GmbH zinc sulphate heptahydrate 0.2 g Sigma Aldrich GmbH calcium chloride dehydrate 0.1 g Scharlau iron sulphate heptahydrate 0.5 g Scharlau sodium molybdate Dihydrate 0.02 g Sigma Aldrich GmbH copper sulphate 0.02 g Sigma Aldrich GmbH cobalt chloride hexahydrate 0.04 g Sigma Aldrich GmbH manganese chloride 0.1 g Sigma Aldrich GmbH

Table 11: Solution B ingredients concentration (per L) supplier potassium phosphate 155 g Sigma Aldrich GmbH sodium dihydrogen Phosphate 85 g Fluka Chemicals

.

2.1.4 Media for cultivation of fungi

The different strains were grown on Petridishes filled with Malt extract agar (MEA, Table 12). The agar was sterilized at 120°C and then poured into the Petri dishes under sterile conditions. Table 12: Malt extract agar ingredients concentration (per L) supplier maltextract 20 g/L AppliChem GmbH glucose 20 g AppliChem GmbH agar agar 15 g AppliChem GmbH bacto pepton 0,1 % Difco

The freeze-dried cultures were homogenised in malt-peptone solution as described in Table 13. The malt-peptone solution was sterilized at 120°C for 15min. Glycerine (70 %, Table 13) was autoclaved and used for freezing of the cultures.

Table 13: Malt-Pepton Solution / Glycerine Solution ingredients concentration supplier malt extract 2% AppliChem GmbH bacto peptone 0,1% Difco glycerine 70% Sigma Aldrich GmbH

2.1.5 Hydrocarbons

The hydrocarbons (Table 14) used for the screenings were 99 % analytical grade. Polychlorinated biphenyl (PCB) 126 was also 99 % analytical grade but 10ng dissolved in Isooctane. Table 14: Hydrocarbon used for Screening

21

hydrocarbon used for supplier toluene Teflon coated bottle screening Scharlau hexadecane Teflon coated bottle screening Scharlau toluene microtiterplate screening Merck KGaA hexadecane microtiterplate screening Alfa Aesar – A Johnson

Matthey Company PCB 126 microtiterplate screening Dr.Ehrenstorfer GmbH

2.1.6 Microorganisms

The fungal strains tested in this study were distributed by the Centraalbureau voor Schimmelcultures (CBS), Utrecht, Netherlands). Each fungal strain was marked with a CBS number and their growth conditions. All strains came from different isolates and made up 163 different species out of 9 genera. Most of them were so-called “black yeasts”.

Order: Chaetothyriales

• Exophiala

• Cladophialophora

• Pseudallescheria

• Phialophora

• Rhinocladiella

• Selenophoma

Order: Dothideales • Aureobasidium

Order: Microascales • Scedosporium

• Graphium

2.2 Methods

2.2.1 Pre-tests

The first microtiter plate-tests performed were used as pre-tests to develop the method. For this, two strains (Table 15) of the ACBR culture collection were tested for the growth in presence of hexadecane, PCB 126 or toluene. The designed method was based on two publications: (Wrenn and Venosa, 1996) and Strong-Gunderson and Palumbo, 1994 and experiments done before at the ACBR (Sterflinger, personal communication).

4.2.1.1 Cultivation of strains

The cultivation was done through three point inoculation of pre-existing plates. Depending on the strain, different temperatures were chosen for incubation as indicated in Table 15. Table 15: Strains pre-test

22

Strain CBS/MA Nr. temperature/humidity Exophiala xenobiotica MA 2883 25°C Exophiala dermatididis CBS 525.76 38°C, high humidity

4.2.1.2 Microtiter plates Pre-tests

The approach for PCB 126 and hexadecane was to fill the wells with 150 µL of the growth media and 50µL of the hydrocarbon solution. For toluene 200µL of media were used due to the volatility of toluene.

a. Hexadecane

Into each well 150 µL of growth medium and 50 µL of hexadecane were pipetted. As positive control 200 µL of glucose media with and without vitamin + trace element solution were used. Plates were kept at room temperature on a shaker (Stuart SSL5, 250 rpm), sealed with parafilm. Additionally, one row was added with TTC and one in which TTC was added at a later time point.

b. PCB 126

Similar to the experimental setup of the hexadecane plates, the PCB 126 plates were prepared: 150 µL of growth medium, 50 µL PCB 126 solution (10 ng/ µL PCB 126 in isooctane), positive Control: 200µL of glucose media with and without vitamin + trace element solution. Also two rows for TTC were done. Together with the hexadecane plates, they were kept on a shaker at room temperature, sealed with parafilm.

c. Toluene

The setup for toluene differs from the other two hydrocarbon plates: in case of toluene 200 µL of growth medium, glucose media with and without vitamin + trace element solution was used. The plates were kept in a desiccator as toluene is a volatile chemical. A saturated solution of toluene should reach a value of 515 ppm in a closed environment. As the environment should be the same for all the plates it was not possible to have a positive control as in the other hydrocarbon trials. The

volatile toluene reaches all wells including the positive control (growth control with only glucose as carbon source). For this reason the wells for positive control in the other hydrocarbon plates were used as growth control for the toluene experiment.

2.2.1.3 Inoculum

For the inoculum, one cm2 biomass was taken from the Petridishes and added in a 2mL Eppendorf tube, where 0.5 mL of glass beads and 1 mL of NaCl were added before. The eppendorf tube and the glass beads were sterilized before. The biomass was ribolyzed (4.0 m/s for 5 sec) in order to get a homogenic distribution of cells in the NaCl solution which could then be used for inoculation of the microtiter plates. For each strain the homogenisation step had to be optimized and was checked under the light microscope. Afterwards, 20 µL of the homogenic cell suspension were added into the wells of the microtiter plates.

2.2.1.4 TTC

One row was created where 50 µL of TTC (0.2 %) where added to the normal setup of different media and a second additional row where TTC was added at the end of the test.

2.2.2 Microtiterplate screening

4.2.2.1 Cultivation of strains

The strains were sent from the CBS as freeze-dried cultures in glass ampoules. Those ampoules were handled according to the CBS instruction for reviving freeze-dried-cultures. The lyophilized vials were cleaned with ethanol, cut on the top with a glass cutter near the Bunsen flame and poured into 2 ml of malt peptone solution. This suspension was kept at room temperature for at least 5 hours. One mL was then poured on two malt extract agar plates and was plated with single-use spatulas. To the remaining one mL of suspension, one mL of 70 % glycerine was added and frozen at 4 °C. The cultures which were delivered in tubes with tilted agar were seeded on malt extract agar-plates. Each strain was cultivated in duplicate. All plates were inoculated at room temperature and sealed with parafilm except for Cladophialophora chaetospira, which was incubated with access to sunlight due to the need of UV light for growth. A visible growth of the different strains was achieved after 1 to 3 weeks, which varied within the different strains. Once there was a significant amount of biomass, they were treated further.

Figure 8 Lyophilized vials, tubes with tilted agar

23

2.2.2.2 Preparation of microtiter plates

On each measured plate three blanks were prepared. Two wells with growth medium, one well with glucose and vitamin+ trace element solution and in one well the glucose solution was appended. Concerning the samples, for each strain two wells with media and hydrocarbon, one with Glucose and Vitamin + Trace element solution and one with Glucose solution alone were done. The two different glucose wells were done to see if vitamins or trace elements do inhibit growth. To each well 20 µl of inoculum were added, 150 µl of medium and 50 µl of hydrocarbon. As in the pre-test, the amounts for toluene were different (200 µl medium for all three, 20 µl inoculum). Plates with hexadecane and PCB 126 were sealed with parafilm and placed on a shaker (Stuart SSL5, 250 rpm). The measurement was done every second day at 700 nm with the Tecan reader a total period of 40 days under the following conditions: 24 °C, shaking: 1 sec, 2 mm amplitude, linear, multiple reads, 25 flashes, settle time: 10 ms. By measuring the OD 700 the growth of the cultures was detected. Due to condensation, evaporation due to heat and growth of the fungi, there was a loss of media during the measured time. In those cases, the wells were refilled with sterilized water. For toluene plates (see Figure 9), the desiccator was cleaned carefully with ethanol to avoid any contaminations. The silica gel was dried in an incubator at 120°C for at least one hour until it had changed colour from red to blue. The toluene was poured into a beaker (250 ml) and placed next to the opened microtiter plates. In those wells that were desiccated, water was added. For the OD measurement, lids were placed on the toluene plates and the plates were measured under the same conditions as the hexadecane and PCB plates.

Figure 9: Toluene Plates in desiccator, Tecan Reader.

2.2.3 Screening with Gas-Chromatography (GC)

This second screening was done at IRTA, Caldes, Spain, where the positive strains of the microtiter plate screening were used.

2.2.3.1 Teflon bottles

To determine the growth kinetics, 250 mL Boston flasks were used. Those bottles were sealed with Teflon Miniert valves (Phase Separations, Waddinxveen, The Netherlands) to have a closed system. The bottles where filled with 25 mL of buffered mineral media (Hartmans & Tramper 1991) with a pH of 7. The bottles were cleaned and rinsed with desalinated water, then the media was added and the bottles were autoclaved at 120 °C. The sterile filtrated vitamin solution was added with a pipette afterwards under sterile conditions. Toluene was added based on its toxicity level for black yeast and the known water/air partition coefficient (Amoore & Hautala 1983). The concentration of 6.6x10-8 mol was added with a Hamilton microsyringe. The injection was done in Captair by Erlab to capture the volatile hydrocarbons. The volume of hexadecane containing the same amount of carbon was calculated (1.2x10-5 mol) and added to through the injection valve.

24

For the first ten strains three types of bottle contents where used:

Negative Control

25 mL mineral media + 0.3 mL of inoculum

Positive Control

25 mL mineral media + 0.3 % glucose + hydrocarbons + 0.3 mL inoculum

Hydrocarbon

25 mL mineral media + hydrocarbons + 0.3 mL inoculum A spore solution of the fungal strains was taken as inoculum which was done by taking one cm2 biomass from the MEA plate, soling it in sterile water, vortex it and inject it with a sterile needle under sterile conditions. The inoculation was done after the bottle substrates reached equilibrium. The bottles were kept at 25 °C in the incubator. Another 15 strains were treated, where just the hydrocarbon was used as substrate and neither a positive nor a negative control was performed. Due to the fact that Cladiophialophora immunda is known from literature (Prenafeta-Boldú et al. 2001a) to be able to degrade toluene, it was taken as positive control for the whole experiment.

2.2.3.2 GC-measurements

The growth was monitored by visual observation and GC measurements of the headspace. For the GC measurements, the consumption of hydrocarbons in the headspace was measured with GC –FID (Trace 2000 series, Thermo Quest CE Instruments). The production of CO2 was measured with GC-TCD. Measurement was done over 30 days where starting point for hydrocarbon measurements was day 0. The CO2 measurement was started when hydrocarbon depletion was measured or growth could be seen optically.

2.2.3.3 GC-FID

Two methods were elaborated: Toluene: Oven temperature: 180 °C hold Time: 2.00 min, Split: 50, Peak around 1.45 min Hexadecane: Oven Temperature: 220 °C, Hold Time: 6.00min, Split: 5.1 min 100 µL of the headspace was injected with a Hamilton microsyringe into the column. To calculate the amount of toluene/hexadecane, a calibration curve was done beforehand. The calibration curve was performed with following concentrations: Toluene: 2, 4, 6, 8 µL of toluene in 25 µL of desalinated water, Hexadecane: 2, 10 µL of hexadecane in 25 mL of desalinated water. To define the method, the different bottles of the calibration curve were measured and the different parameters of the GC were changed until an optimal peak was received. For correcting the daily variations of the instrument, two standards with known amounts of hydrocarbon were measured before and after the whole measurement. Those results were used for calculations afterwards. Additionally, the column was cleaned with injection of a sample volume of air in between measurements.

25

For hexadecane, the pure substance was injected in liquid form and diluted in pentane (1ml pentane, 10µL hexadecane) to see the expected retention time. Having a low vapor pressure, hexadecane signal peaks were rather small and hard to detect. In the used mineral medium, hexadecane could not dissolve properly and built droplets. Therefore it was hardly detectable it in the headspace. To develop the best method, different injection volumes (100 – 500 µl) and heating the samples up to 70°C before measuring were checked. Although heating up the sample would increase detectability, this treatment was not possible as heating up growing fungi to higher temperatures results in a growth disturbance. Finally the method used was to inject 100 µL at 220 °C oven temperature. The amount of hexadecane could not be measured quantitatively because only a small peak was detectable in this sequence. For this reason, the small peak was taken as a qualitative indicator for the presence of hexadecane. Moreover a stable amount of toluene in combination with an increase of CO2 would have been a second proof for the degradation of hexadecane.

4.2.3.4 GC-TCD

For measurement of CO2 production the GC-TCD (Varian CP-3800) was used. The method was already defined, named Front 2013. This method uses the column at 90°C and the detector and injector temperature was set as 180°C. For injecting the sample volume of 200 µL a Hamilton SGE was used. Furthermore, two standards were measured to determine the performance of the instrument. One standard contained a known content of N2, air, CH4 and H2 and the second one CO2 and N2. The standards were injected with different volumes and analyzed with the same method.

Figure 10 GC-FID and GC-TCD

26

3 Results

3.1 Pre-tests

The pre-tests were performed to receive the best method for the microtiter screening of 163 fungal strains of the CBS. For the screening, conditions remained the same as in the pre-test, apart from TTC. Those rows did not show a noticeable colour change caused redox-reduction of TTC due to fungal growth which made the method not useful. The screening was therefore performed as described in chapter2.2.2.

3.2 Microtiter plate screening

The plates were measured for a time period of 40 days and data were analysed in Excel. For calculating the change in OD 700, the blanks were subtracted from the OD 700 values of all 163 strains. Growth curves were plotted in diagrams, resulting in 9 diagrams per strain (3 hydrocarbons, plate 1, 2 and the average of the two plates). In the analysed data set, 114 strains out of 163 showed growth in the microtiter plate screening (see Table 16). Some fungal strains were able to grow up to levels comparable to the positive controls, while others just showed a slight rise in OD 700 from the beginning to the end of the measurements. In Table 16 the results were divided into + for growth, ~ for little growth and – for no growth and different hydrocarbons. There was found one strain which was able show growth in presence of all the three hydrocarbons, 14 with two hydrocarbons and 19 with one hydrocarbon (marked with + in Table 16). The two positive controls, glucose with vitamins and trace elements and glucose without vitamins and trace elements, conducted themselves in most cases similar. Therefore the vitamins and trace elements did not inhibit growth of the strains, although sometimes growth was slower or less. Just in very few cases it inhibited growth. Optically, it was possible to check for contaminations, for example if there was growth outside of the wells or on the plate cover. The results for the toluene curves showed unexpected variations which may be a result of the toxic impact of toluene for some fungal species. Furthermore, deviations were also seen due to desiccation of the wells and a refill with sterile water. The different diagrams of the plates can be seen in chapter 3.3 and the appendix. Bold marked strains in Table 16 were used to do further screening at IRTA. They were chosen by their performance in the microtiter plate screening and by their isolation source. Some strains were not able to grow after reviving them from the freeze dried culture. These are also mentioned in the table below but their hydrocarbon cells are empty.

27

Table 16: Results Microtiter plate screening: strains ordered by name, +=growth, ~= little growth, x= no growth, strains written bold are the ones, which were used for the screening at IRTA, strains with empty cells for Hexadecane (Hex), Toluene (Tol) and PCB 126 (PCB) were not able to grow after the freeze dried culture

28

Nr Name CBS N° Hex Tol PCB

1 Exophiala dermatidtidis 122239 x + X 2 Exophiala xenobiotica 102455 ~ + X 3 Pseudallescheria agusta 254.72 x ~ X 4 Exophiala sideris 121838 ~ + X 5 Cladophialophora carrionii 260.83 x x X 6 Cladophialophora saturnica 118724 x + X 7 Exophiala castellanii 109812 ~ ~ ~ 8 Phialophora verrucosa 138.67 x x X 9 Exophiala exophialae 668.76 x x X 10 Selenophoma mahoniae 388.92 x + X 10 Exophiala sideris 121819 x ~ X 11 Exophiala oligosperma 109807 x + X 12 Exophiala alcalophila 122256 x x X 13 Scedosporium apiospermum 117407 + ~ ~ 14 Pseudallescheria ellipsoidea 219.85 + + ~ 15 Rhinocladiella basitona 101460 16 Cladophialophora arxii 409.96 x ~ X 17 Cladophialophora immunda 110551 x + ~ 18 Pseudallescheria boydii 116899 ~ + X 19 Graphium eumorphum 987.73 + ~ + 20 Exophiala bergeri 119100 x x X 21 Exophiala lecanii-corni 102400 x x X 22 Cladophialophora yegresii 114407 ~ ~ ~ 23 Cladophialophora samoёnsis 259.83 x x X 24 Cladophialophora minourae 987.96 x x X 25 Exophiala jeanselmei 507.90 + x + 26 Pseudallescheria fusoidea 106.53 + ~ X 27 Cladiophialophora boppii 110029 x + ~ 28 Aureobasidium pullulans var. pullulans 100524 x x X 29 Cladophialophora subtilis 122642 ~ ~ ~ 30 Phialophora americana 840.69 x x X 31 Exophiala spinifera 899.68 x + + 32 Rhinocladiella similis 116299 + x + 33 Exophiala spinifera 110628 x ~ ~ 34 Exophiala heteromorpha 648.76A x ~ X 35 Pseudallescheria minutispora 116911 + x ~ 36 Cladophialophora australiensis 112793 x x X 37 Cladophialophora emmonsii 979.96 x ~ X 38 Exophiala mesophila 121964 39 Cladophialophora mycetomatis 454.82 x x X 40 Exophiala alcalophila 520.82 x x X 41 Exophiala sideris 121834 x x X 42 Pseudallescheria ellipsoidea 332.75 + + X 43 Exophiala oligosperma 265.49 + x X 44 Pseudallescheria boydii 316.54 45 Exophiala spinifera 425.92 ~ x X 46 Aureobasidium pullulans 110374 x x X 47 Exophiala dermatitidis 115663 x ~ ~ 48 Phialophora verrucosa 286.47 x x X 49 Cladophialophora carrionii 114392 x x X 50 Exophiala jeanselmei 117.86 51 Exophiala xenobiotica 118157 x ~ ~ 52 Exophiala bergeri 121846 x ~ X 53 Exophiala mesophila 836.95 x x X 54 Exophiala dermatitidis 748.88 55 Cladophialophora immunda 122255 x ~ X 56 Exophiala lecanii-corni 232.39 x ~ X 57 Cladophialophora boppii 126.86 x + ~

29

Nr Name CBS N° Hex Tol PCB

58 Cladophialophora immunda 834.96 x + X 59 Cladophialophora yegresii 114406 x x X 60 Exophiala oligosperma 725.88 + x X 61 Pseudallescheria boydii 119709 + x X 62 Cladophialophora arxii 306.94 x + X 63 Exophiala dermatitidis 149.90 x x ~ 64 Exophiala mesophila 120910 + ~ ~ 65 Exophiala heteromorpha 633.69 x x X 66 Pseudallescheria boydii 117405 + + X 67 Cladophialophora minourae 556.83 x x X 68 Exophiala sideris 121813 x x X 69 Cladophialophora emmonsii 640.96 70 Exophiala mesophila 121509 x + X 71 Pseudallescheria boydii 101720 + + ~ 72 Pseudallescheria angusta 116914 + ~ X 73 Exophiala castellanii 581.76 x x ~ 74 Rhinocladiella similis 111763 + ~ X 75 Pseudallescheria boydii 115829 + + x 76 Cladophialophora immunda 122257 x + x 77 Pseudallescheria boydii 375.77 78 Aureobasidium pullans 584.75 x ~ + 79 Exophiala xenobiotica 117672 x ~ x 80 Pseudalleschria boydii 119696 + + ~ 81 Pseudalleschria boydii 116894 + x x 82 Pseudalleschria boydii 593.73 + x x 83 Exophiala jeanselmei 122339 x x x 84 Cladophialophora immunda 109797 x + ~ 85 Exophiala jeanselmei 109635 x x ~ 86 Pseudalleschria boydii 101721 + ~ + 87 Exophila oligosperma 537.76 + ~ x 88 Pseudallescheria boydii 116658 + ~ x 89 Exophiala dermatitidis 116.97 x x x 90 Pseudallescheria boydii 116421 + + x 91 Cladophialophora immunda 122636 x ~ x 92 Pseudalleschria boydii 115.59 + + + 93 Aureobasidium pullulans 110373 x x x 94 Pseudalleschria ellipsoidea 301.79 + + x 95 Exophiala sideris 121818 x x ~ 96 Exophiala heteromorpha 232.33 ~ ~ ~ 97 Exophiala oligosperma 115966 + ~ x 98 Cladophialophora carrionii 160.54 x ~ ~ 99 Aureobasidium pullulans var. Subglaciale 123388 100 Aureobasidium pullulans var. Pullulans 701.76 ~ ~ ~ 102 Pseudallescheria boydii 108.54 + ~ x 103 Exophiala dermatitidis 150.90 x x ~ 104 Exophiala spinifera 269.28 x ~ x 105 Pseudallescheria boydii 117387 + + x 106 Cladophialophora carrionii 114398 x ~ ~ 107 Pseudallescheria boydii 116595 + ~ x 108 Exophiala xenobiotica 117647 + + x 109 Pseudalleschria boydii 329.93 + ~ ~ 110 Pseudalleschria boydii 117395 + ~ x 111 Exophiala mesophila 120907 x x x 112 Exophialophora alcalophila 118723 113 Exophiala bergeri 102241 ~ x ~ 114 Pseudalleschria boydii 117404 + + x 115 Exophiala spinifera 194.61 + x x 116 Cladophialophora chaetospira 491.70 + x x 117 Cladophialophora potuelntorum 114772 x x x 118 Cladophialophora chaetospira 114747 x ~ x 119 Exophiala castellanii 110025 x x x 120 Pseudallescheria boydii 101723 + + x 121 Aureobasidium pullulans 122385 x ~ ~ 122 Pseudallescheria desertorum 489.72 + ~ ~ 123 Exophiala moniliae 520.76 x x x

30

Nr Name CBS N° Hex Tol PCB

124 Cladophialophora potulentorum 112222 ~ ~ ~ 125 Cladophialophora potulentroum 115144 x x x 126 Exophiala lecanii-corni 122266 x ~ x 127 Fonsecaea 109628 x + ~ 128 Pseudallescheria boydii 116594 + x ~ 129 Exophiala alcalophila 118722 x x x 130 Exophiala alcalophila 521.82 x x x 131 Pseudallescheria boydii 116410 + ~ ~ 132 Pseudallescheria boydii 322.51 + x x 133 Pseudallescheria boydii 117393 ~ + x 134 Exophiala bergeri 119094 x ~ x 135 Pseudallescheria boydii 116898 + ~ x 136 Exophiala sideris 121832 x + x 137 Pseudallescheria boydii 116897 x + ~ 138 Cladophialophora mycetomatis 122637 x ~ x 139 Pseudallescheria boydii 101.22 + ~ ~ 140 Pseudallescheria boydii 117417 + ~ x 141 Exophiala dermatitidis 109148 x ~ ~ 142 Exophiala bergeri 353.52 x x x 143 Pseudallescheria boydii 117408 + + x 144 Exophiala mesophila 121497 ~ ~ x 145 Pseudallescheria ellipsoidea 418.73 + + x 146 Fonsecaea 109630 x + x 147 Pseudallescheria boydii 117415 + x x 148 Exophiala jeanselmei 528.76 x x x 149 Exophiala xenobiotica 117754 x ~ x 150 Cladophialophora 102230 x + ~ 151 Pseudallescheria boydii 116403 + + ~ 152 Exophiala jeanselmei 677.76 x ~ ~ 153 Exophiala spinifera 667.76 x ~ x 154 Exophiala dermatitidis 120479 x ~ x 155 Pseudallescheria boydii 100396 + x ~ 156 Exophiala mesophila 121507 x x x 157 Pseudallescheria boydii 330.93 + ~ x 158 Pseudallescheria boydii 499.90 + ~ x 159 Pseudallescheria boydii 117403 ~ ~ x 160 Exophiala sideris 121820 x ~ ~ 161 Exophiala dermatitidis 116726 x x x 162 Exophiala heteromorpha 102696 x x x 163 Wangiella 110555 x x x

3.3 Results of GC - screening

For the GC-screening at IRTA, Spain, 25 strains were chosen from the fungal strains listed in Table 16. They were chosen by their performance in the first screening and by their isolate source. One strain, Cladophialophora immunda, 17, served as positive control as it was known from literature that this strain can degrade toluene (Prenafeta-Boldu et al., 2001 a). After a few days it was possible to see strong growth in all glucose controls, which could be compared to the bottles with sole hydrocarbon source. Additionally, a comparison with the negative controls was useful, as some of the fungal strains were able to sporulate without any carbon source. Three different cases were observed: negative results (shown in chapter 3.3.1), positive results for toluene degradation (shown in chapter 3.3.2) and toxicity (shown in chapter3.3.3). Results were analysed in Excel and were corrected by a daily factor. This factor was calculated by measuring two standards before and after the daily measurements. The difference to the actual concentration of toluene in the standards was calculated. The measurements were then corrected.

3.3.1 Negative results

Negative results were expressed by missing CO2 production and hydrocarbon degradation. This applied to the strains with following numbers: 26, 19, 14, 31, 71, 32, 25, 110, 114, 158, 94, 139, 75, 159, 143, 97, 90, 105, 107, 86, 92 and 81 (presented in Table 16). As an example the strain 114, Pseudalleschria boydii, exhibited an increase in OD in the presence of hexadecane (Figure 11 C) and toluene (Figure 11 B) in the microtiter plate screening. In the GC – screening, no growth was detected (Figure 12). The GC - FID measurements showed a slight decrease in toluene concentration. CO2 values (presented in Figure 13) did not increase but showed slight variation due to equipment variations.

A B

C Figure 11: A, B, C: Microtiter plate screening of strain 114, Pseudallescheria boydii, with the hydrocarbons PCB126 (A), toluene (B) and hexadecane (C). OD 700 plotted against the days of measurement. The graphs consist of the average data points of duplicates. They show 4 curves, medium plus hydrocarbon (M), medium plus glucose (G), medium plus glucose, vitamins and trace elements (GVT). M curves are, as expected, quite similar In Figure A, a big difference between G, GVT curves and M curve is seen. The values of the M curves were not increasing. The strain was not able to grow in presence of the PCB126. In the graphs B and C, there were increasing values of OD 700. The strain was able to grow in presence of the hydrocarbons.

M; day 0; 0,15457

M; day 2; 0,147145

M; day 4; 0,169235

M; day 7; 0,251935

M; day 9; 0,26473

M; day 11;

0,431725

M; day 14;

0,411855

M; day 16;

0,37814

M; day 18;

0,34843

M; day 21;

0,33322

M; day 23;

0,315985

M; day 25;

0,299025

M; day 28;

0,31373

M; day 30;

0,30855

M; day 32;

0,31232

M; day 35;

0,30697

M; day 37;

0,30901

M; day 39;

0,324105

M; day 43;

0,40534

M; day 44;

0,414995

M; day 46;

0,40863 M; day 0; 0,112885

M; day 2; 0,098245

M; day 4; 0,11782

M; day 7; 0,19966

M; day 9; 0,207765

M; day 11;

0,208075

M; day 14;

0,207115

M; day 16;

0,18897

M; day 18;

0,183455

M; day 21;

0,192475

M; day 23;

0,19196

M; day 25;

0,188545

M; day 28;

0,223035

M; day 30;

0,209165

M; day 32;

0,206245

M; day 35;

0,20453

M; day 37;

0,20442

M; day 39;

0,23531

M; day 43;

0,37075

M; day 44;

0,3799

M; day 46;

0,378685 G; day 0; 0,184315

G; day 2; 0,216835

G; day 4; 0,37081

G; day 7; 0,97743

G; day 9; 1,041025

G; day 11;

0,98427

G; day 14;

0,96181

G; day 16;

0,976155

G; day 18;

0,988935

G; day 21;

1,019875

G; day 23;

1,018905

G; day 25;

1,011155

G; day 28;

1,00815

G; day 30;

0,99647

G; day 32;

1,00043

G; day 35;

1,175415

G; day 37;

1,34074

G; day 39;

1,491925

G; day 43;

1,571695

G; day 44;

1,55189

G; day 46;

1,546785

GVT; day 0;

0,14467

GVT; day 2;

0,18028

GVT; day 4;

0,312605

GVT; day 7; 0,4371

GVT; day 9;

0,488665

GVT; day 11;

0,53715

GVT; day 14;

0,590605

GVT; day 16;

0,64497

GVT; day 18;

0,698765

GVT; day 21;

0,76212

GVT; day 23;

0,790395

GVT; day 25;

0,816805

GVT; day 28;

0,86374

GVT; day 30;

0,874745

GVT; day 32;

0,8968

GVT; day 35;

0,92827

GVT; day 37; 0,952

GVT; day 39;

0,97079

GVT; day 43;

1,01577

GVT; day 44;

1,028265

GVT; day 46;

1,03877

M

M

G

GVT

M; day 0;

0,108515

M; day 2;

0,117375

M; day 4;

0,135255

M; day 7;

0,18489

M; day 9;

0,20609

M; day 11;

0,205135

M; day 14;

0,230905

M; day 16;

0,248275

M; day 18;

0,24943

M; day 21;

0,28307

M; day 23;

0,301235

M; day 25;

0,32858

M; day 28;

0,367385

M; day 30;

0,37851

M; day 32;

0,37531

M; day 35;

0,455775

M; day 37;

0,428745

M; day 39;

0,433045

M; day 43;

0,531675

M; day 44;

0,505675

M; day 46;

0,48674

M; day 0;

0,062035

M; day 2;

0,067415

M; day 4;

0,08224

M; day 7;

0,119645

M; day 9;

0,13642

M; day 11;

0,125415

M; day 14;

0,15331

M; day 16;

0,166255

M; day 18;

0,16568

M; day 21;

0,190465

M; day 23;

0,20707

M; day 25;

0,233565

M; day 28;

0,26714

M; day 30;

0,277755

M; day 32;

0,285885

M; day 35;

0,37579

M; day 37;

0,35032

M; day 39;

0,352345

M; day 43;

0,44739

M; day 44;

0,414455

M; day 46;

0,39764

G; day 0; 0,0903

G; day 2; 0,10702

G; day 4; 0,16283

5

G; day 7; 0,34927

5

G; day 9; 0,46936

5

G; day 11;

0,61191

G; day 14;

0,672345

G; day 16;

0,71691

G; day 18;

0,73366

G; day 21;

0,76356

G; day 23;

0,76892

G; day 25;

0,780905

G; day 28;

0,78786

G; day 30;

0,79948

G; day 32;

0,77908

G; day 35;

0,79536

G; day 37;

0,792565

G; day 39;

0,79182

G; day 43;

0,825165

G; day 44;

0,813995

G; day 46;

0,772805

GVT; day 0;

0,061875

GVT; day 2;

0,064435

GVT; day 4;

0,102245

GVT; day 7;

0,26606

GVT; day 9;

0,333085

GVT; day 11; 0,39652

GVT; day 14; 0,46683

GVT; day 16; 0,49363

5

GVT; day 18; 0,49104

5

GVT; day 21; 0,52631

GVT; day 23; 0,54722

5

GVT; day 25; 0,56957

5

GVT; day 28; 0,59145

5

GVT; day 30; 0,62025

5

GVT; day 32; 0,612

GVT; day 35; 0,64338

5

GVT; day 37; 0,64583

GVT; day 39; 0,66338

5

GVT; day 43; 0,70482

5

GVT; day 44; 0,70020

5

GVT; day 46; 0,67488

5

M

M

G

GVT

M; day 0; 0,148275 M; day 2; 0,142835 M; day 4; 0,17841

M; day 7; 0,3995

M; day 9; 0,61329

M; day 11; 0,78686

M; day 14; 0,90021 M; day 16; 0,94927

M; day 18; 0,988295 M; day 21; 1,01549 M; day 23; 1,03849 M; day 25; 1,0333 M; day 28; 1,04847 M; day 30; 1,044305 M; day 32; 1,05824 M; day 35; 1,05115 M; day 37; 1,05097 M; day 39; 1,03697 M; day 43; 1,029385 M; day 44; 1,023585 M; day 46; 1,023875

M; day 0; 0,130945 M; day 2; 0,13937 M; day 4; 0,163375

M; day 7; 0,375895

M; day 9; 0,586845

M; day 11; 0,783435

M; day 14; 0,90185 M; day 16; 0,96199

M; day 18; 1,008685 M; day 21; 1,061185 M; day 23; 1,084255 M; day 25; 1,091885 M; day 28; 1,106975 M; day 30; 1,11327 M; day 32; 1,12521 M; day 35; 1,12463 M; day 37; 1,118685 M; day 39; 1,118925 M; day 43; 1,123915 M; day 44; 1,12151 M; day 46; 1,12383

G; day 0; 0,124955 G; day 2; 0,16534

G; day 4; 0,291415

G; day 7; 0,70829 G; day 9; 0,77756 G; day 11; 0,78301 G; day 14; 0,78049 G; day 16; 0,7991215

G; day 18; 0,750215 G; day 21; 0,727085 G; day 23; 0,71548

G; day 25; 0,8007255 G; day 28; 0,8272455 G; day 30; 0,84408 G; day 32; 0,889935 G; day 35; 0,863485 G; day 37; 0,864405 G; day 39; 0,87479

G; day 43; 0,9156245 G; day 44; 0,9429895 G; day 46; 0,890855

GVT; day 0; 0,135945 GVT; day 2; 0,15523

GVT; day 4; 0,28257

GVT; day 7; 0,421395

GVT; day 9; 0,496075 GVT; day 11; 0,55954

GVT; day 14; 0,658795

GVT; day 16; 0,734258 GVT; day 18; 0,742455 GVT; day 21; 0,80053

GVT; day 23; 0,83196 GVT; day 25; 0,834875 GVT; day 28; 0,87095

GVT; day 30; 0,912165 GVT; day 32; 0,972795 GVT; day 35; 0,986383 GVT; day 37; 0,999355 GVT; day 39; 1,01345

GVT; day 43; 1,079457 GVT; day 44; 1,118384 GVT; day 46; 1,089675

M

M

G

GVT

31

32

Figure 12: Teflon coated bottle: No visible growth could be detected in the medium.

T; 0,00; 3,89087E

-09

T; 4,00; 4,11327E

-09

T; 5,01; 3,75858E

-09

T; 9,00; 3,88915E

-09 T; 12,00; 2,97341E

-09

T; 15,01; 3,35744E

-09

T; 17,00; 3,17596E

-09

T; 18,01; 3,10307E

-09

T CO2; 5,00;

8,53E-11

T CO2; 9,01;

2,96E-10

T CO2; 11,00;

2,96E-10

T CO2; 15,01;

5,43E-10

T CO2; 17,01;

2,86E-10

T CO2; 18,00;

1,96E-10

T

T CO2

Figure 13: GC-results Toluene (T) degradation and CO2 (T CO2) production by Pseudallescheria boydii, 114. Carbon equivalence [mol] of the two molecules plotted against runtime [days]. The toluene was decreasing slightly while CO2 remained stable.

3.3.2 Positive results for toluene degradation

Two strains, Cladophialophora immunda, 17, (presented in chapter 3.3.2.1) and Exophiala mesophila, 64, (presented in chapter Fehler! Verweisquelle konnte nicht gefunden werden.), showed the ability to grow on toluene as the sole carbon and energy source. This was confirmed by an increase of CO2and a toluene decrease. Cladophialophora immunda, was already known to be able to assimilate toluene (Prenafeta-Boldú et al., 2001a) and therefore served as positive control for the whole experiment. Some strains seemed to be optically growing, but measurements showed, that those strains were not able to produce CO2. The optically seen growth was sporulation.

3.3.2.1 Cladophialophora immunda

For this strain, the results of the microtiter plate screening were negative for hexadecane and PCB 126. The OD 700 for toluene varied in both plates but showed an increasing trend. Optical detection also showed more growth in the bottle with sole hydrocarbon source than in the negative control (see Figure 15). The graph of the GC results shows a decrease in toluene and increase in CO2. At the point where toluene is degraded completely, CO2 also reached maxima and stayed stable for the next measuring points. 70% of the toluene was recovered in CO2. In figure 20 it can be seen, that the bottle with hydrocarbons as carbon source behaved similar to the positive control.

A B

M; day 0;

0,0426015

M; day 1;

0,05077

M; day 2;

0,032595

M; day 4;

0,107055

M; day 11;

0,136955

M; day 14;

0,126055

M; day 17;

0,126055

M; day 20,;

0,113305

M; day 22;

0,092055

M; day 24;

0,07314

M; day 29;

0,09568

M; day 31;

0,12065

M; day 33;

0,14763

M; day 36;

0,14542

M; day 0;

0,04641

M; day 1;

0,1187125

M; day 2;

0,074405

M; day 4;

0,19057

M; day 11;

0,44591

M; day 14;

0,416985

M; day 17;

0,416985

M; day 20,;

0,437825

M; day 22;

0,41806

M; day 24;

0,458655

M; day 29;

0,39149

M; day 31;

0,28472

M; day 33;

0,405395

M; day 36;

0,39565 G; day 0; 0,02587

G; day 1; 0,14981

5

G; day 2; 0,08009

5

G; day 4;

0,368745

G; day 11;

2,14423

G; day 14;

2,27213

G; day 17;

2,27213

G; day 20,;

2,13063

G; day 22;

2,13403

G; day 24;

2,02967

G; day 29;

1,83336

G; day 31;

1,810645

G; day 33;

1,64435

G; day 36;

1,5578

GVT; day 0;

0,00979

GVT; day 1;

0,109285

GVT; day 2;

0,090315

GVT; day 4;

0,278035

GVT; day 11; 0,5247

GVT; day 14; 0,56566

5

GVT; day 17; 0,56566

5

GVT; day 20,; 0,58713

5

GVT; day 22; 0,57295

5

GVT; day 24; 0,60978

5

GVT; day 29; 0,61938

5

GVT; day 31; 0,68426

5

GVT; day 33; 0,58722

5

GVT; day 36; 0,69865

5

M

M

G

GVT

M; day 0;

0,04203

M; day 1;

0,068825

M; day 2;

0,055665

M; day 7;

0,061565

M; day 10;

0,096345

M; day 11;

0,068695

M; day 14;

0,10008

M; day 17;

0,1105235

M; day 18;

0,103935

M; day 19;

0,09831

M; day 21;

0,09482

M; day 28;

0,1166745

M; day 31;

0,1204015

M; day 34;

0,2099035

M; day 37;

0,15417

M; day 39;

0,16207

M; day 41;

0,21176

M; day 0;

0,0292

M; day 1;

0,041355

M; day 2;

0,033525

M; day 7;

0,027855

M; day 10;

0,06844

M; day 11;

0,045065

M; day 14;

0,07593

M; day 17;

0,098205

M; day 18;

0,069255

M; day 19;

0,06899

M; day 21;

0,069715

M; day 28;

0,093501

M; day 31;

0,0965225

M; day 34;

0,11961

M; day 37;

0,129095

M; day 39;

0,13607

M; day 41;

0,18067

G; day 0;

0,014475

G; day 1;

0,02416

G; day 2;

0,019715

G; day 7;

0,017235

G; day 10;

0,046205

G; day 11;

0,017685

G; day 14;

0,02512

G; day 17;

0,04624

G; day 18;

0,0398

G; day 19;

0,036265

G; day 21;

0,041525

G; day 28;

0,046675

G; day 31;

0,04692

G; day 34;

0,02199

G; day 37;

0,057955

G; day 39;

0,07451

G; day 41;

0,10817 GVT; day 0;

0,042785

GVT; day 1;

0,05202

GVT; day 2;

0,049595

GVT; day 7;

0,044395

GVT; day 10; 0,0672

GVT; day 11; 0,05880

5

GVT; day 14; 0,06829

GVT; day 17; 0,08428

5

GVT; day 18; 0,08401

GVT; day 19; 0,08229

5

GVT; day 21; 0,08064

GVT; day 28; 0,09144

5

GVT; day 31; 0,08871 GVT; day 34; 0,01737

5

GVT; day 37; 0,07316

GVT; day 39; 0,09119

5

GVT; day 41; 0,12845

M

M

G

GVT

M; day 0;

0,05367

M; day 1;

0,050715

M; day 2;

0,064865

M; day 7;

0,126715

M; day 10;

0,11336

M; day 11;

0,14128

M; day 14;

0,147005

M; day 17;

0,17895

M; day 18;

0,1839

M; day 19;

0,196245

M; day 21;

0,154165

M; day 28;

0,144555

M; day 31;

0,10973

M; day 34;

0,14667

M; day 37;

0,12284

M; day 39;

0,19806

M; day 41;

0,14946

M; day 0;

0,077215

M; day 1;

0,075315

M; day 2;

0,09738

M; day 7;

0,15113

M; day 10;

0,17376

M; day 11;

0,14857

M; day 14;

0,15789

M; day 17;

0,180745

M; day 18;

0,184295

M; day 19;

0,191185

M; day 21;

0,15887

M; day 28;

0,15387

M; day 31;

0,11589

M; day 34;

0,155695

M; day 37;

0,10227

M; day 39;

0,191835

M; day 41;

0,15396

G; day 0;

0,00596

G; day 1;

0,03701

G; day 2;

0,042885

G; day 7;

0,891255

G; day 10;

1,552215

G; day 11;

1,736885

G; day 14;

2,161945

G; day 17;

2,430795

G; day 18;

2,476935

G; day 19;

2,50972

G; day 21;

2,59997

G; day 28;

2,59188

G; day 31;

2,574705

G; day 34;

2,553415

G; day 37;

2,512115

G; day 39;

2,131935

G; day 41;

2,523745

GVT; day 0;

0,03426

GVT; day 1;

0,07292

GVT; day 2;

0,11053

GVT; day 7;

0,676875

GVT; day 10; 0,84945

5

GVT; day 11; 0,91408

GVT; day 14; 1,04284

GVT; day 17; 1,18482

5

GVT; day 18; 1,20517

5

GVT; day 19; 1,21617

GVT; day 21; 1,27484

GVT; day 28; 1,39087

5

GVT; day 31; 1,47441

GVT; day 34; 1,53255

5

GVT; day 37; 1,6215

GVT; day 39; 1,52990

5

GVT; day 41; 1,65765

M

M

G

GVT

C Figure 14 A, B, C: Microtiter plate screening of strain 17, Cladophialophora immunda, with the hydrocarbons PCB126 (A), toluene (B) and hexadecane (C). OD 700 plotted against the days of measurement. The graphs consist of the average data points of duplicates. They show 4 curves, medium plus hydrocarbon (M), medium plus glucose (G), medium plus glucose, vitamins and trace elements (GVT). M curves are, as expected, quite similar. In figure A, a big difference between the G curve and M curve is seen. There was still a slight increase of the OD 700 values from the beginning. All the curves in figure B increased drastically during the 41 days of the measurement. The strain was able to grow in presence of toluene. Figure C shows growth with hexadecane. The values for the M curve stayed around 0 as result of no growth with hexadecane.

33

Figure 15: Teflon coated bottles: negative control, positive control, bottle with hydrocarbons (from left to right). Higher growth than in the negative control was shown in positive control and hydrocarbon bottle.

Toluene + Glucose ;

0,00; 4,3912E-09

Toluene + Glucose ;

13,00; 3,51925E-

09

Toluene + Glucose ;

14,00; 2,8234E-09

Toluene + Glucose ;

15,01; 2,52602E-

09

Toluene + Glucose ;

19,00; 1,74633E-

09

Toluene + Glucose ;

21,00; 1,90599E-

09

Toluene; 0,00;

4,3146E-09

Toluene; 13,00;

2,60646E-09

Toluene; 14,00;

2,17209E-09

Toluene; 15,01;

1,79783E-09

Toluene; 19,00;

4,3196E-11

Toluene; 25,01; -

2,8601E-10

G+T CO2; 7,00;

2,40818E-10

G+T CO2; 8,00;

7,99866E-10

G+T CO2; 13,01;

6,08205E-10

G+T CO2; 14,01;

7,36696E-10

G+T CO2; 15,00;

1,62794E-09

G+T CO2; 19,01;

1,26712E-09

G+T CO2; 20,00;

1,26E-09

G+T CO2; 25,00;

2,30E-09

G+T CO2; 27,01;

2,20E-09

G+T CO2; 28,00;

2,11E-09 G+T CO2; 33,00;

1,41E-09

T CO2; 8,00; -

2,67853E-10

T CO2; 13,01;

3,6562E-10

T CO2; 14,01;

5,71652E-10

T CO2; 15,00;

1,02761E-09

T CO2; 19,01;

1,3044E-09

T CO2; 20,00;

1,51E-09

T CO2; 25,00;

2,07E-09

T CO2; 27,01;

1,82E-09

T CO2; 28,00;

1,77E-09

T CO2; 33,00;

1,40853E-09

Toluene + Glucose

Toluene

G+T CO2

T CO2

34

Figure 16: GC-results: Toluene and CO2 values by Cladophialophora immunda, 17. Carbon equivalence [mol] of the two molecules was plotted against runtime [days]. There were 4 different growth curves:

Toluene + Glucose: toluene of the positive control

G+T CO2: CO2 of the positive control

Toluene: toluene of bottles with hexadecane and toluene as sole carbon source

T CO2: CO2 of bottles with hexadecane and toluene as sole carbon source For the positive control, there can be seen a harsh decline in toluene and an increase in CO2. The trend of the curves of both bottles was quite similar. The CO2 curves of both bottles reached a maximum, when no more toluene could be degraded.

3.3.2.2 Exophiala mesophila

In the microtiter plate screening, the strain Exophiala mesophila, 64, exhibited an obvious growth in case of toluene and hexadecane while no growth could be detected in presence of PCB 126 (Figure 17). Optically, it was possible to see growth in the Teflon coated bottles (see Figure 15). The GC analysis of the headspace (see Figure 16) showed, that the strain was able to degrade toluene; 40% of the hydrocarbon was recovered in CO2.

A B

M; day 0;

0,1902665

M; day 1;

0,25193

M; day 2;

0,21972

M; day 4;

0,251365

M; day 11;

0,30848

M; day 14;

0,2215

M; day 17;

0,2215

M; day 20,;

0,280755

M; day 22;

0,17603

M; day 24;

0,20477

M; day 29;

0,16603

M; day 31;

0,14902

M; day 33;

0,178175

M; day 36;

0,200725

M; day 0;

0,18114

M; day 1;

0,2336625

M; day 2;

0,20347

M; day 4;

0,24896

M; day 11;

0,2741

M; day 14;

0,20199

M; day 17;

0,20199

M; day 20,;

0,26549

M; day 22;

0,2668

M; day 24;

0,22262

M; day 29;

0,157995

M; day 31;

0,133405

M; day 33;

0,14114

M; day 36;

0,13649

G; day 0;

0,14329

G; day 1;

0,26747

G; day 2;

0,313945

G; day 4;

0,58231

G; day 11;

1,56583

G; day 14;

1,46528

G; day 17;

1,46528

G; day 20,;

1,29793

G; day 22;

1,33813

G; day 24;

1,23812

G; day 29;

1,09011

G; day 31;

1,049195

G; day 33;

0,89565

G; day 36;

0,8336

GVT; day 0;

0,15037

GVT; day 1; 0,2718

GVT; day 2;

0,33201

GVT; day 4;

0,43496

GVT; day 11; 0,55977

GVT; day 14; 0,52142

GVT; day 17; 0,52142

GVT; day 20,; 0,53063

5

GVT; day 22; 0,49662

5

GVT; day 24; 0,53798

5

GVT; day 29; 0,55688

5

GVT; day 31; 0,53421

5

GVT; day 33; 0,58767

5

GVT; day 36; 0,57110

5

M

M

G

GVT

M; day 0;

0,206415

M; day 1;

0,186415

M; day 2;

0,20785

M; day 7;

0,278965

M; day 10;

0,26403

M; day 11;

0,25512

M; day 14;

0,251765

M; day 17;

0,2593385

M; day 18;

0,25923

M; day 19;

0,260095

M; day 21;

0,263055

M; day 28;

0,3572295

M; day 31;

0,3177065

M; day 34;

0,4781535

M; day 37;

0,3256

M; day 39;

0,295415

M; day 41;

0,29816

M; day 0;

0,199225

M; day 1;

0,17976

M; day 2;

0,20091

M; day 7;

0,24669

M; day 10;

0,241785

M; day 11;

0,23266

M; day 14;

0,230835

M; day 17;

0,22954

M; day 18;

0,2326

M; day 19;

0,237855

M; day 21;

0,250295

M; day 28;

0,308061

M; day 31;

0,2837275

M; day 34;

0,412735

M; day 37;

0,37283

M; day 39;

0,35218

M; day 41;

0,33899 G; day 0;

0,20065

G; day 1;

0,22534

G; day 2;

0,3046

G; day 7;

0,46393

G; day 10;

0,49435

G; day 11;

0,492825

G; day 14;

0,500475

G; day 17;

0,500105

G; day 18;

0,49536

G; day 19;

0,49554

G; day 21;

0,509395

G; day 28;

0,586255

G; day 31;

0,595075

G; day 34;

0,63911

G; day 37;

0,667565

G; day 39;

0,682975

G; day 41;

0,677645

GVT; day 0;

0,22849

GVT; day 1;

0,24562

GVT; day 2;

0,317925

GVT; day 7;

0,42359

GVT; day 10; 0,43818

GVT; day 11; 0,43957

GVT; day 14; 0,45531

GVT; day 17; 0,45198

GVT; day 18; 0,4502

GVT; day 19; 0,45093

GVT; day 21; 0,45543

GVT; day 28; 0,50783

GVT; day 31; 0,51226

5

GVT; day 34; 0,49609

GVT; day 37; 0,60667

GVT; day 39; 0,61669

5

GVT; day 41; 0,61108

M

M

G

GVT

M; day 0;

0,26142

M; day 1;

0,28733

M; day 2;

0,29546

M; day 7;

0,285355

M; day 10;

0,25918

M; day 11;

0,29999

M; day 14;

0,302415

M; day 17;

0,3132

M; day 18;

0,37266

M; day 19;

0,385525

M; day 21;

0,360795

M; day 28;

0,42202

M; day 31;

0,42125

M; day 34;

0,47475

M; day 37;

0,521555

M; day 39;

0,48902

M; day 41;

0,62839

M; day 0;

0,318385

M; day 1;

0,297965

M; day 2;

0,298915

M; day 7;

0,27197

M; day 10;

0,2747

M; day 11;

0,27724

M; day 14;

0,295955

M; day 17;

0,323995

M; day 18;

0,37136

M; day 19;

0,384085

M; day 21;

0,38811

M; day 28;

0,48502

M; day 31;

0,509615

M; day 34;

0,61157

M; day 37;

0,643475

M; day 39;

0,694555

M; day 41;

0,78883 G; day 0; 0,22276

G; day 1;

0,285645

G; day 2;

0,365595

G; day 7;

1,74426

G; day 10;

2,109915

G; day 11;

2,235635

G; day 14;

2,342895

G; day 17;

2,378895

G; day 18;

2,362485

G; day 19;

2,34282

G; day 21;

2,47547

G; day 28;

2,49693

G; day 31;

2,484305

G; day 34;

2,477265

G; day 37;

2,387765

G; day 39;

2,108185

G; day 41;

2,435645

GVT; day 0;

0,229475

GVT; day 1;

0,280315

GVT; day 2;

0,355535

GVT; day 7;

0,66723

GVT; day 10; 0,76155

5

GVT; day 11; 0,79344

GVT; day 14; 0,85957

GVT; day 17; 0,92237

5

GVT; day 18; 0,92037

5

GVT; day 19; 0,92307

GVT; day 21; 0,95739

GVT; day 28; 1,05012

5

GVT; day 31; 1,08761

GVT; day 34; 1,12460

5

GVT; day 37; 1,15605

GVT; day 39; 1,16315

5

GVT; day 41; 1,1906

M

M

G

GVT

C Figure 17 A, B, C: Microtiter plate screening of strain 64, Exophiala mesophila, with the hydrocarbons PCB126 (A), toluene (B) and hexadecane (C).OD 700 plotted against the days of measurement. Those graphs consist of the average data points of duplicates. They show 4 curves, medium plus hydrocarbon (M), medium plus glucose (G), medium plus glucose, vitamins and trace elements (GVT). M curves are, as expected, quite similar in in all figures. In figure A, the M curves varied around 0.2 OD 700 and did not increase during the period of measurement while the G and GVT curves increased. This strain was not able to grow with PCB 126. In figure B, an increase in the M curve is seen. For the hexadecane (C), an increase of the M values can be seen.

Figure 18: Teflon coated bottles: negative control, positive control, bottle with hydrocarbons (from left to right). Higher growth was seen in positive control and hydrocarbon bottle than in the negative control. The medium seemed blurred in the two bottles with growth.

35

G+T; 0,00; 5,17712E-

09 G+T; 13,00; 3,95012E-

09

G+T; 14,00; 3,44108E-

09

G+T; 15,01; 3,12963E-

09 G+T; 19,00; 1,80301E-

09 G+T; 22,00; 1,2353E-09

T; 0,00; 4,8935E-09

T; 8,00; 2,63481E-

09

T; 13,00; 2,16954E-

09

T; 14,00; 2,0919E-09

T; 15,01; 7,0367E-10

T; 19,00; 4,81711E-

10

G+T CO2; 7,00;

1,63474E-09

G+T CO2; 8,00; 1,5E-

09

G+T CO2; 13,01;

3,54855E-09

G+T CO2; 14,01;

3,54855E-09

G+T CO2; 15,00;

8,31996E-09

G+T CO2; 19,01;

6,95492E-09

G+T CO2; 21,00;

5,69E-09

T CO2; 8,00;

3,33E-10

T CO2; 13,01;

9,54861E-10

T CO2; 14,01;

7,04492E-10

T CO2; 15,00;

1,48356E-09

T CO2; 19,01;

2,43275E-09

T CO2; 21,00;

1,43E-09

G+T

T

G+T CO2

T CO2

Figure 19: GC-results: Toluene and CO2 values by Exophiala mesophila, 64.Carbon equivalence [mol] of the two molecules was plotted against runtime [days]. There are 4 different growth curves:

G+T: toluene of the positive control

G+T CO2: CO2 of the positive control

T: toluene of bottles with hexadecane and toluene as sole carbon source

T CO2: CO2 of bottles with hexadecane and toluene as sole carbon source The curve for toluene decreased very quickly in both bottles while CO2 production differed. For the positive control the curve reached higher levels of C equivalence than gas samples of the sole hydrocarbon bottle.

3.3.3 Toxicity

One strain, Exophiala jeanselmei, 25, showed an unexpected curve during the GC-screening as concentration of toluene was toxic for this strain. It showed neither an increase of CO2in the sole hydrocarbon bottle nor in the positive control bottle (Figure 21). During the microtiter plate screening, the strain was able to grow in presence of hexadecane and PCB 126 (Figure 20 A, C). In the case of toluene (Figure 20B), the strain did not show growth in wells with toluene as sole carbon source nor in the wells with additional glucose. Also optically, no growth was seen.

36

A B

C Figure 20 A, B, C: Microtiter plate screening of strain 25, Exophiala jeanselmei, with the hydrocarbons PCB126 (A), toluene (B) and hexadecane (C).OD 700 plotted against the days of measurement. The graphs consist of the average data points of duplicates. They show 4 curves, medium plus hydrocarbon (M), medium plus glucose (G), medium plus glucose, vitamins and trace elements (GVT). M curves are, as expected, quite similar in in all figures. In figure A all curves were plotted in the same area and did not differ a lot. Exophiala jeanselmei was able to grow in wells with glucose as in well with PCB 126. The G curve showed minus values in the end of the measurement. Figure B shows no OD 700 increase in all wells. The fungal strain was not able to grow in presence of toluene, also if glucose was available as additional carbon source. In figure C wells without glucose showed an increase in OD 700 after a few days of incubation time. The strain was able to grow in presence of hexadecane.

M; day 0 ; -

0,049305

M; day 3;

0,121275

M; day 4;

0,142895

M; day 5;

0,2347

M; day 6;

0,55525

M; day 7;

0,6281

M; day 12;

0,652135

M; day 15;

0,61858

M; day 16;

0,64297

M; day 19;

0,708705

M; day 22;

0,708705

M; day 23;

0,716255

M; day 24;

0,720285

M; day 26;

0,6893

M; day 33;

0,6268

M; day 36;

0,50878

M; day 40;

0,572965

M; day 43;

0,56357

M; day 45;

0,524285

M; day 0 ;

0,136595

M; day 3;

0,12777

M; day 4;

0,152245

M; day 5;

0,191355

M; day 6;

0,57572

M; day 7;

0,64689

M; day 12;

0,719075

M; day 15;

0,720205

M; day 16;

0,73437

M; day 19;

0,85623

M; day 22;

0,85623

M; day 23;

0,884545

M; day 24;

0,893795

M; day 26;

0,8517

M; day 33;

0,821915

M; day 36;

0,66842

M; day 40;

0,769095

M; day 43;

0,773835

M; day 45;

0,737675

G; day 0 ;

0,155505

G; day 3; 0,20897

G; day 4; 0,36849

G; day 5; 0,52747

G; day 6; 1,01492

5

G; day 7; 1,11706

5

G; day 12;

0,92684

G; day 15;

0,7941

G; day 16;

0,730455

G; day 19;

0,644855

G; day 22;

0,644855

G; day 23;

0,539935

G; day 24;

0,498035

G; day 26;

0,44784

G; day 33; -

0,77715

G; day 36; -

0,748

G; day 40; -

0,93655

G; day 43; -

0,93755

G; day 45; -

0,9987

GVT; day 0 ;

0,21494

GVT; day 3;

0,116835

GVT; day 4;

0,11615

GVT; day 5;

0,15327

GVT; day 6;

0,29766

GVT; day 7;

0,3161

GVT; day 12;

0,686825

GVT; day 15;

0,759675

GVT; day 16;

0,720585

GVT; day 19;

0,732495

GVT; day 22;

0,732495

GVT; day 23;

0,96011

GVT; day 24;

1,008855

GVT; day 26;

1,116785

GVT; day 33;

0,95108

GVT; day 36;

0,831815

GVT; day 40;

0,86777

GVT; day 43;

0,830795

GVT; day 45;

0,810925

M

M

G

GVT

M; day 0; -

0,049305

M; day 03; -

0,008315

M; day 4; 0,2347

M; day 05; -

0,007095

M; day 06; -

0,006375

M; day 07; -

0,00627

M; day 12; -

0,008655

M; day 15; -

0,00062

M; day 16;

0,008155

M; day 19; -

0,006975

M; day 22;

0,00768

M; day 23;

0,000325

M; day 24; -

0,003065

M; day 26;

0,000575

M; day 33;

0,00963

M; day 36; -

0,00534

M; day 40; -

0,009715

M; day 43; -

0,01529

M; day 45; -

0,018145

M; day 0; 0,136595

M; day 03; -

0,00121

M; day 4; 0,191355

M; day 05; -

0,00272

M; day 06; -

0,00308

M; day 07; -

0,002805

M; day 12; -

0,006165

M; day 15;

0,002485

M; day 16;

0,01961

M; day 19; -

0,00148

M; day 22;

0,00813

M; day 23;

0,00425

M; day 24; -

0,009365

M; day 26;

0,003295

M; day 33;

0,011105

M; day 36;

0,000235

M; day 40; -

0,008535

M; day 43; -

0,01539

M; day 45; -

0,02203

G; day 0; 0,155505

G; day 03;

0,001795

G; day 4; 0,52747

G; day 05; -

0,002905

G; day 06; -

0,001985

G; day 07; -

0,001435

G; day 12; -

0,003745

G; day 15;

0,00434

G; day 16;

0,008405

G; day 19; -

0,00649

G; day 22; -

0,0022

G; day 23; -

0,01187

G; day 24; -

0,022615

G; day 26; -

0,01592

G; day 33; -

0,000145

G; day 36; -

0,01015

G; day 40; -

0,018825

G; day 43; -

0,01982

G; day 45; -

0,020095

GVT; day 0;

0,21494

GVT; day 03; -

0,001095

GVT; day 4;

0,15327 GVT; day 05; -

0,003785

GVT; day 06; 8E-05

GVT; day 07; -

0,00409

GVT; day 12; -

0,01005

GVT; day 15;

0,01087

GVT; day 16;

0,01375

GVT; day 19; -

0,012905

GVT; day 22; -

0,008915

GVT; day 23; -

0,016525

GVT; day 24; -

0,023975

GVT; day 26; -

0,018905

GVT; day 33;

0,00155

GVT; day 36; -

0,00782

GVT; day 40; -

0,017955

GVT; day 43; -

0,02227

GVT; day 45; -

0,01946

M

M

G

GVT

M; day 0; -

0,003315

M; day 03;

0,02759

M; day 04; -

0,014645

M; day 05;

0,043935

M; day 06;

0,052385

M; day 07;

0,066605

M; day 15;

0,40489

M; day 16;

0,50126

M; day 19;

0,68935

M; day 22;

0,766265

M; day 23;

0,720795

M; day 24;

0,773495

M; day 26;

0,786035

M; day 33;

0,78393

M; day 36;

0,773495

M; day 40;

0,7605

M; day 43;

0,787425

M; day 45;

0,72309

M; day 0;

0,02118

M; day 03;

0,03161

M; day 04;

0,023785

M; day 05;

0,04205

M; day 06;

0,05326

M; day 07;

0,06912

M; day 15;

0,44069

M; day 16;

0,529795

M; day 19;

0,67614

M; day 22;

0,72883

M; day 23;

0,705285

M; day 24;

0,73316

M; day 26;

0,729875

M; day 33;

0,73731

M; day 36;

0,73316

M; day 40;

0,72916

M; day 43;

0,749607

M; day 45;

0,652435

G; day 0; 0,00326

5

G; day 03;

0,097465

G; day 04;

0,247335

G; day 05;

0,50534

G; day 06;

0,6504

G; day 07;

0,637785

G; day 15;

0,602275

G; day 16;

0,591135

G; day 19;

0,540205

G; day 22;

0,53068

G; day 23;

0,51627

G; day 24;

0,51766

G; day 26;

0,49168

G; day 33;

0,45465

G; day 36;

0,51766

G; day 40;

0,4867315

G; day 43;

0,4205 G; day

45; 0,29647

GVT; day 0; -0,005

GVT; day 03;

0,07122

GVT; day 04;

0,19263

GVT; day 05;

0,258005

GVT; day 06;

0,39555

GVT; day 07;

0,3644

GVT; day 15;

0,610115

GVT; day 16;

0,61429

GVT; day 19;

0,500935

GVT; day 22;

0,47628

GVT; day 23;

0,46666

GVT; day 24;

0,4668

GVT; day 26;

0,449265

GVT; day 33;

0,31201

GVT; day 36;

0,4668

GVT; day 40;

0,3318515

GVT; day 43;

0,274164

GVT; day 45;

0,2818475

M

M

G

GVT

37

G+T; 0,00; 4,18771E-

09

G+T; 13,00;

3,84693E-09

G+T; 14,00;

3,38323E-09

G+T; 15,01;

2,85383E-09

T; 0,00; 4,20721E-

09

T; 13,00; 4,1817E-

09

T; 14,00; 4,01142E-

09

T; 15,01; 3,83632E-

09

G+T CO2; 7,00;

1,91E-10

G+T CO2; 8,00;

1,78948E-10

G+T CO2; 13,01;

5,23923E-10

G+T CO2; 14,01;

1,89964E-10

G+T CO2; 15,00;

2,13128E-10

T CO2; 8,00;

1,84812E-10

T CO2; 13,01;

2,10981E-10

T CO2; 14,01;

2,18875E-10

T CO2; 15,00;

1,21E-10

G+T

T

G+T CO2

T CO2

38

Figure 21: GC-results: Toluene and CO2 values by Exophiala jeanselmei, 25.Carbon equivalence [mol] of the two molecules was plotted against runtime [days]. There are 4 different growth curves:

G+T: toluene of the positive control

G+T CO2: CO2 of the positive control

T: toluene of bottles with hexadecane and toluene as sole carbon source

T CO2: CO2 of bottles with hexadecane and toluene as sole carbon source Toluene values were decreasing slightly in both bottles. The speciality of this strain expressed itself in the stable value of CO2. It was not increasing in both bottles, not even in the positive control although having glucose as carbon source.

4 Discussion

We were able to successfully develop two screening methods to gain knowledge about the different strains and their degradation and growth abilities. The microtiter plate screening was newly developed and gave answers about the growth of the strains in presence of the hydrocarbons. 114 out of the 163 fungal strains showed growth in the microtiter plate screening on at least one of the hydrocarbon sources supplied. Finally, in the subsequent assimilation tests in liquid closed batches, we successfully selected two strains – Cladophialophora immunda and Exophiala mesophila- who were able to degrade toluene. Cladophialophora immunda comes from a hydrocarbon rich isolation source, a gasoline station. Therefore, we can state that it adapted to the environment and is able to degrade toluene. Exophiala mesophila, on the other hand, was isolated from a human, from a chronic sinusitis. This strain is able to degrade toluene although not having the hydrocarbon in his environment. This means that strains don’t need a hydrocarbon rich environment to have the features to degrade them although the isolate from the hydrocarbon rich source showed better degradation performance. The method of the microtiterplate screening provided a lot of data points by the Tecan reader. With data from the microtiter plate screening, growth curves were created with the help of Excel to demonstrate if the strains exhibited growth under certain conditions. In some cases growth of the positive control with vitamins and trace elements was slower or less but just in very few cases it inhibited growth. If there was inhibition by the vitamins and trace elements, the fungal strain could also not grow in presence of the hydrocarbon. The microtiter plate screening was a basic tool, to gain a general answer if the strains are able to grow in presence of the different hydrocarbons, not if the strain can degrade it. Therefore the number of positive strains was rather high. There are several reasons for a follow up screening in a second phase of investigation:

Graph interpretation Interpretation of the graphs was rather difficult as some showed a slight increase in the OD values compared to the positive control, while others were on the same level as the positive control. Therefore, the differentiation between + and was done in the result table (see Table 16).

Growth curve variations Curves varied a lot and did not always show a clear trend (see figures in chapter 3.3. and in the appendix). On one hand this occurred due to residual growth of fungi. Although being small, the wells of the microtiter plates have different options where the fungi can grow. Some of them preferred to grow on the surface, while others grew only on the walls or in some other region, where detection with the help of the Tecan reader was not possible. On the other hand desiccation of the wells and the need to refill wells with water affected growth of some fungi and as a consequence resulted in graph variations. The test method endured long and although sealing the plates with parafilm, the wells dried out after one week on the shaker. The growth differences in the wells are presented in Figure 22. Another reason for variations was the toxic effect of toluene to some strains. The chemical was poured in a beaker, which was then put in the desiccator. Therefore, in the desiccator the gaseous phase of the substance was saturated. For some fungal strains this was toxic, which could also be seen in the more detailed screening at IRTA. Due to this toxicity some strains were only able to grow slightly or stopped growth abruptly which resulted in graph variations. Also the concentration change of volatile toluene due to opening of the desiccator for measurements could have resulted in growth variations.

39

Figure 22: Two different microtiter plates with different fungal strains; Variations are seen between the 3rd and 4th, 7th and 8th and 11th and 12th well in each row although containing the same strain, growth was therefore different in the wells.

Homogenisation Homgenisation of the fungal strain from the agar plate in NaCl was a difficult task. While some fungal strains homogenised easily after a short time in the ribolyzer, some were hard to homogenise and therefore a difference appeared in the amount of cells in the inoculum between the different wells. As the screening was meant to generate a general yes or no answer to growth, this was seen as unproblematic.

Tecan Reader The results of the Tecan reader varied from day to day. A daily factor could have been introduced to correct the results. As data were corrected by a daily measured blank, the correction by a daily factor was considered as not necessary. The equipment delivered just little variation in the results, which was considered sufficient for the basic screening.

Oligotrophic strains Strains for the screening were mainly oligotrophic. Oligotrophic means growing and metabolizing slowly but steadily at low concentrations of energy sources, nutrients and water (Gostinčar et al., 2012). This is also exhibited in their potential to survive in extreme and stressful environments. This fact means that they can also survive using carbon sources other than hydrocarbons. For example they could metabolize ingredients of the microtiter plates or from any other sources. Although the plates were generally closed in general with lids, they were opened from time to time for refilling or other reasons. Hence, other nutrients could have entered. Some fungal strains sporulated and this optical density could still be measured with the Tecan reader.

In general, the microtiter plate screening provided the expected information. The results exhibited a general idea on the growth behaviour of the strains. Also a high throughput in a small time window was reached, as it is difficult to handle 163 strains in the same time and under same conditions. The data gave basic ideas of which strains could be good degrading candidates and therefore were used in the GC screening. In the GC screening the main research goal was to define if the fugal strain can use hydrocarbons as sole carbon source and therefore degrade those. For analytical detection, the GC-measurements were used. As equipment Teflon coated bottles were chosen due to the fact that hydrocarbons are not able to penetrate through. As mentioned in 3.3 the results were divided in three possible cases:

40

Negative results: no increase in CO2 and stable amount of toluene in the sample bottle, in glucose control increase in CO2 and decrease of toluene

Positive results: increase in CO2 and decrease of toluene, in glucose control increase in CO2 and decrease of toluene

Toxicity: neither in the sample nor in the glucose control increase of CO2 or decrease of toluene

Another case would have been the degradation of hexadecane. Therefore, the hexadecane concentration in the sample bottles would have decreased, while toluene concentration would have stayed stable and CO2 would have increased. This case didn’t appear in any of the bottles therefore it seems to be very difficult to degrade hexadecane for fungal strains. The PCB degradation abilities have not been tested in this screening and will be tested in further tests. The results of the GC screening and the microtiter plate screening results differed. The microtiter plate results were more often interpreted as positive for living in presence of hydrocarbons, while the GC screening showed that they were not able to degrade the hydrocarbon. This can be explained by sporulation and their being oligotrophic (see Figure 22). In all bottles, the graphs showed slight variations which happened due to equipment instability. There was a daily factor introduced for the correlation, but still there were slight variations. Additionally, toluene decreased slightly in bottles of non-degraders. The reason for this fact can be due to leakages in the bottles. The Teflon coated bottles were inherent stable for hydrocarbons but the connection to the injection valve and the valve itself can have minor leakages. Also while retrieving the injection volume, small amounts of toluene could have escaped. As the GC measurement is precise, it is not easy to find sample equipment in the same precise range which also fulfils all other requirements needed (i.e. sterility, volume, usage for microbes). Compared to the concentrations of the degrading strains it is a minor loss which does not disturb interpretation of the results. The glucose bottles exhibited that the fungal strains are able to degrade toluene in presence of glucose. Two candidates were found to degrade hydrocarbons: Cladophialophora immunda and Exophiala mesophila are two strains which were able to use toluene as sole carbon source. The negative controls were very important, as all of the strains were able to sporulate without any carbon source. Therefore, an optical comparison was possible to recognize the difference between sporulation and real growth. CO2 variations can be a result of a change in pH. The media were buffered and therefore no pH change should happen due to growth. However no measurement of pH was possible, as the sterility of the media was given more importance than the pH. Still this could have been a trigger for variations in CO2 levels. One big point in the results is the CO2 recovery. In the case of Cladophialophora immunda, 70% of toluene was recovered in CO2. For Exophiala mesophila around 40% of toluene was recovered. Taking the bioremediation goal in account, those percentages are very important as it is not known yet what happened to the rest of the toluene. Other unwanted toxic compounds could be produced in their degradation process or toluene degradation products could go into the biomass. This could be tested further through drying and weighing of the biomass. Especially for the bioremediation goal it is important to be sure that no toxic compounds are produced in the degrading process to make sure that not more dangers are introduced for environment and animals through applying the method. Another critical point for the Exophiala strain is that toluene is not degraded completely. Further tests would be necessary if with more inoculum all toluene can be degraded or if there will always remain some hydrocarbon.

41

Next to the toxicity of the intermediates the H2 level of the strains should not be forgotten. The strains can be human pathogenic and therefore the metabolic pathways of the fungal strains, their changes during the degradation and their pathogenic features have to be studied in detail. Cladophialophora immunda was isolated near a petrol station. Therefore it was already in hydrocarbon rich environment and adapted. A transcriptome study would be a good tool, to know in detail how this strain is able to survive in such an environment and how the strain can use toluene as a carbon source. Another interesting point is that although black fungi are known to survive high levels of stress, some of them were not able to survive low levels of toluene. They were toxic for them as seen for Exophiala jeanselmei (see 3.3.3). Therefore, not all abilities of black fungi are known and in some parts they are quite extraordinary while in other parts too high expectations are made regarding their stress tolerance.

42

5 Conclusion and Outlook

Both screening methods met the intended goals to define fungal strains with biodegradative abilities. The microtiter plate method was successfully developed and fulfilled the need of high throughput in a small time period in constant conditions was met. Although having some limitations caused by the inhomogeneous growth of fungi, the microtiter plate method turned out to be appropriate to answer the main questions. In the microtiter plate screening 114 fungal strains were found, which were able to grow in media with hydrocarbon as sole carbon source. Those were taken to the second screening, where the most promising candidates were screened for hydrocarbon degradation. In the second screening, two strains were proven to be able to degrade and assimilate toluene, while hexadecane was not degraded by any strain. PCB-126 still needs to be observed in the GC method. PCB-126 must be added into the Teflon bottles and afterwards measured in the GC-FID for degradation. The reasons for the differences between the results of the microtiter plate screening and the GC-screening can be seen in the preciseness of the methods and also on the two different targets. Further investigations for the knowledge were the rest of the degraded toluene goes (into biomass and/or into co-metabolites) and what kinds of co-metabolites are produced, are necessary before using them in bioremediation or on biofilters. It must be sure that no toxic or pathogenic compounds are produced during degradation. Moreover, the biochemical pathways should be studied on the basis of proteomic and trascriptomic (RNA sequence, gene expression) analysis before using the strain in field experiments or applications. The techniques also have to be developed from a lab scale to one which can be applied for large scale bioremediation. Being aware of possible risks and studying those before applying anything into nature is one of the major challenges of further studies. Anyhow, the strains found in the screening are useful candidates and are worth being tested further. Having a lot of pollutions around us, any possible approach for a solution should be tested. Additionally, the group of black yeast is not known completely and they have a lot of surprising attributes which could be used in a lot of approaches. For example the mechanisms which help them to survive in such extreme conditions are not fully understood. There are always new technologies invented and further developed, especially in the field of proteomics, metabolomics and genomics which could help us to understand all the processes better and use them in the field of biotechnology. Therefore research in this field is highly promising.

43

6 References

April, T.M., Abbott, S.P., Foght, J.M., Currah, R.S., 1998. Degradation of hydrocarbons in crude oil by the ascomycete Pseudallescheria boydii (Microascaceae). Can. J. Microbiol. 44, 270–278.

Ayotamuno, M.J., Okparanma, R.N., Nweneka, E.K., Ogaji, S.O.T., Probert, S.D., 2007. Bio-remediation of a sludge containing hydrocarbons. Appl. Energy 84, 936–943.

Badali, H., Carvalho, V.O., Vicente, V., Attili-Angelis, D., Kwiatkowski, I.B., Gerrits Van Den Ende, A.H.G., De Hoog, G.S., 2009. Cladophialophora saturnica sp. nov., a new opportunistic species of Chaetothyriales revealed using molecular data. Med. Mycol. 47, 51–62.

Badali, H., Prenafeta-Boldu, F.X., Guarro, J., Klaassen, C.H., Meis, J.F., de Hoog, G.S., 2011. Cladophialophora psammophila, a novel species of Chaetothyriales with a potential use in the bioremediation of volatile aromatic hydrocarbons. Fungal Biol. 115, 1019–29.

Caliman, F.A., Robu, B.M., Smaranda, C., Pavel, V.L., Gavrilescu, M., 2010. Soil and groundwater cleanup: benefits and limits of emerging technologies. Clean Technol. Environ. Policy 13, 241–268.

Claussen, M., Schmidt, S., 1998. Biodegradation of phenol and p-cresol by the hyphomycete Scedosporium apiospermum. Res. Microbiol. 149, 399–406.

Crawford, R., Hess, T., Paszezynski, A., 2004. Combined biological and abiological degradation of xenobiotic compounds, in: Singh, A., Ward, O. (Eds.), Soil Biology, Vol 2: Biodegradation and Bioremediation. Springer Verlag Berlin, pp. 254–278.

De Hoog, G.S., Grube M., 2008. Black fungal extremes. Stud Mycol. 61.

De Hoog, G.S., Vicente, V., Caligiorne, R.B., Kantarcioglu, S., Tintelnot, K., Gerrits van den Ende, A.H.G., Haase, G., 2003. Species diversity and polymorphism in the Exophiala spinifera clade containing opportunistic black yeast-like fungi. J. Clin. Microbiol. 41, 4767–78.

Dua, M., Singh, A., Sethunathan, N., Johri, A.K., 2002. Biotechnology and bioremediation: successes and limitations. Appl. Microbiol. Biotechnol. 59, 143–52.

EEA environmental statement 2007 — European Environment Agency (EEA) [WWW Document], 2007. URL http://www.eea.europa.eu/publications/corporate_document_2007_2 (accessed 1.29.14).

Engineering Forum, 2006. In Situ Treatment Technologies for Contaminated Soil [WWW Document]. URL http://nepis.epa.gov/Adobe/PDF/P1000STG.pdf (accessed 2.7.14).

Fiebig, R., Schulze, D., Erlemann, P., Slawinski, M., Dellweg, H., 1993. Microbial degradation of polychlorinated biphenyls in contaminated soil. Biotechnol. Lett. 15, 93–98.

Galagan, J.E., Henn, M.R., Ma, L.-J., Cuomo, C. a, Birren, B., 2005. Genomics of the fungal kingdom: insights into eukaryotic biology. Genome Res. 15, 1620–31.

Gavrilescu, M., 2005. Fate of Pesticides in the Environment and its Bioremediation. Eng. Life Sci. 5, 497–526.

Gorbushina, A.A., 2007. Life on the rocks. Environ. Microbiol. 9, 1613–31.

44

Gorbushina, A.A., Kotlova, E.R., Sherstneva, O.A., 2008. Cellular responses of microcolonial rock fungi to long-term desiccation and subsequent rehydration. Stud. Mycol. 61, 91–7.

Gostinčar, C., Muggia, L., Grube, M., 2012. Polyextremotolerant black fungi: oligotrophism, adaptive potential, and a link to lichen symbioses. Front. Microbiol. 3, 390.

Granzin, S., Valtl, M., 2013. Verdachtsflächenkataster und Altlastenatlas [WWW Document]. URL http://www.umweltbundesamt.at/umweltsituation/altlasten/statistik/ (accessed 2.7.14).

Hölker, U., Bend, J., Pracht, R., Tetsch, L., Müller, T., Höfer, M., de Hoog, G.S., 2004. Hortaea acidophila, a new acid-tolerant black yeast from lignite. Antonie Van Leeuwenhoek 86, 287–94.

Isola, D., Selbmann, L., de Hoog, G.S., Fenice, M., Onofri, S., Prenafeta-Boldú, F.X., Zucconi, L., 2013. Isolation and screening of black fungi as degraders of volatile aromatic hydrocarbons. Mycopathologia 175, 369–79.

Janda-Ulfig, K., Ulfig, K., Cano, J., Guarro, J., 2008. A study of the growth of Pseudallescheria boydii isolates from sewage sludge and clinical sources on tributyrin, rapeseed oil, biodiesel oil and diesel oil. Ann. Agric. Environ. Med. 15, 45–9.

Kao, C.M., Chen, C.Y., Chen, S.C., Chien, H.Y., Chen, Y.L., 2008. Application of in situ biosparging to remediate a petroleum-hydrocarbon spill site: field and microbial evaluation. Chemosphere 70, 1492–9.

Luykx, D.M.A.., Prenafeta-Boldú, F.X., de Bont, J.A.., 2003. Toluene monooxygenase from the fungus Cladosporium sphaerospermum. Biochem. Biophys. Res. Commun. 312, 373–379.

Medicine, U.S.N.L. of, 2002. Tox Town [WWW Document]. toluene. URL http://toxtown.nlm.nih.gov/text_version/chemicals.php?id=30 (accessed 1.27.14).

Mehlman, M.A., 1992. Dangerous and cancer-causing properties of products and chemicals in the oil refining and petrochemical industry. Environ. Res. 59, 238–249.

National Institutes of Health, 2012. HSDB “Toxnet” *WWW Document+. [Online]. URL http://toxnet.nlm.nih.gov/cgi-bin/sis/htmlgen?HSDB

Onodera, M., Sakai, H., Endo, Y., Ogasawara, N., 1990. Oxidation of Short-chain iso-Alkanes by Gaseous Hydrocarbon Assimilating Mold, Scedosporium sp. A-4(Microbiology & Fermentation Industry). Agric. Biol. Chem. 54, 2413–2416.

Prenafeta-Boldú, F.X., Ballerstedt, H., Gerritse, J., Grotenhuis, J.T.C., 2004. Bioremediation of BTEX hydrocarbons: effect of soil inoculation with the toluene-growing fungus Cladophialophora sp. strain T1. Biodegradation 15, 59–65.

Prenafeta-Boldú, F.X., Kuhn, A., Luykx, D.M.A.M., Anke, H., van Groenestijn, J.W., de Bont, J.A.M., 2001 a. Isolation and characterisation of fungi growing on volatile aromatic hydrocarbons as their sole carbon and energy source. Mycol. Res. 105, 477–484.

Prenafeta-Boldú, F.X., Luykx, D.M., Vervoort, J., de Bont, J.A., 2001 b. Fungal metabolism of toluene: monitoring of fluorinated analogs by (19)F nuclear magnetic resonance spectroscopy. Appl. Environ. Microbiol. 67, 1030–4.

45

Prenafeta-Boldú, F.X., Summerbell, R., Sybren de Hoog, G., 2006. Fungi growing on aromatic hydrocarbons: biotechnology’s unexpected encounter with biohazard? FEMS Microbiol. Rev. 30, 109–30.

Quensen, J.F., Boyd, S.A., Tiedje, J.M., 1990. Dechlorination of Four Commercial Polychlorinated Biphenyl Mixtures (Aroclors) by Anaerobic Microorganisms from Sediments. Appl. Environ. Microbiol. 56, 2360–2369.

Rojas-Avelizapa, N.G., odr guez- z uez, ., Enr uez- illanue a, F., Mart nez-Cruz, J., Poggi-Varaldo, H.M., 1999. Transformer oil degradation by an indigenous microflora isolated from a contaminated soil. Resour. Conserv. Recycl. 27, 15–26.

Royal Society of Chemistry, 2014. Chem Spider [WWW Document]. URL http://www.chemspider.com/

Ruiz-Aguilar, G.M.L., Fernández-S nchez, J.M., odr ́guez-Vázquez, R., Poggi-Varaldo, H., 2002. Degradation by white-rot fungi of high concentrations of PCB extracted from a contaminated soil. Adv. Environ. Res. 6, 559–568.

Rustler, S., Chmura, A., Sheldon, R.A., Stolz, A., 2008. Characterisation of the substrate specificity of the nitrile hydrolyzing system of the acidotolerant black yeast Exophiala oligosperma R1. Stud. Mycol. 61, 165–74.

Skala, C., Kanovsky, A., Ortmann, M., Schamann, M., Weish, S., Jobstmann, H., C. Kolesar, H., Längert-Mühlegger, Siller, R., Prokop, G., 2007. Altlastensanierung in Österreich Effekte und Ausblick. Bundesministerium für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft.

Sterflinger, K., 2005. Black Yeasts and Meristematic Fungi: Ecology, Diversity and Identification, in: Péter, D.G., Rosa, P.C. (Eds.), Biodiversity and Ecophysiology of Yeasts The Yeast Handbook. Springer-Verlag, pp. 501–514.

Sterflinger, K., Tesei, D., Zakharova, K., 2012. Fungi in hot and cold deserts with particular reference to microcolonial fungi. Fungal Ecol. 5, 453–462.

Strong-Gunderson, J.M., Palumbo, A. V., 1994. Alternative method for rapidly screening microbial isolates for their potential to degrade volatile contaminants. J. Ind. Microbiol. 13, 361–366.

Tsui, C.K.M., Woodhall, J., Chen, W., Lévesque, C.A., Lau, A., Schoen, C.D., Baschien, C., Najafzadeh, M.J., de Hoog, G.S., 2011. Molecular techniques for pathogen identification and fungus detection in the environment. IMA Fungus 2, 177–89.

Van Emon, J.M., Chuang, J.C., Bronshtein, A., Altstein, M., 2013. Determination of polychlorinated biphenyls in soil and sediment by selective pressurized liquid extraction with immunochemical detection. Sci. Total Environ. 463, 326–333.

Ward, O., Sing, A., 2004. Evaluation of current soil bioremediation technologies, in: Singh, A., Ward, O. (Eds.), Soil Biology, Vol 1: Applied Bioremediation and Phytoremediation. Springer Verlag Berlin, pp. 187–214.

Weber, F.J., Hage, K.C., de Bont, J.A., 1995. Growth of the fungus Cladosporium sphaerospermum with toluene as the sole carbon and energy source. Appl. Environ. Microbiol. 61, 3562–6.

46

Wrenn, B. a, Venosa, a D., 1996. Selective enumeration of aromatic and aliphatic hydrocarbon degrading bacteria by a most-probable-number procedure. Can. J. Microbiol. 42, 252–8.

Young, L.Y., Cerniglia, C.E., (Editors), 1995. Microbial transformation and degradation of toxic organic chemicals. Wiley-Liss Inc.

Zakharova, K., Tesei, D., Marzban, G., Dijksterhuis, J., Wyatt, T., Sterflinger, K., 2013. Microcolonial fungi on rocks: a life in constant drought? Mycopathologia 175, 537–47.

Zeng, J.S., Sutton, D.A., Fothergill, A.W., Rinaldi, M.G., Harrak, M.J., de Hoog, G.S., 2007. Spectrum of clinically relevant Exophiala species in the United States. J. Clin. Microbiol. 45, 3713–20.

Zhao, J., Zeng, J., de Hoog, G.S., Attili-Angelis, D., Prenafeta-Boldú, F.X., 2010. Isolation and identification of black yeasts by enrichment on atmospheres of monoaromatic hydrocarbons. Microb. Ecol. 60, 149–56.

47

7 Appendix:

7.1 Diagrams microtiter plate pre-tests

Test plates, different concentrations and equipment parameters were tested

-1

-0,5

0

0,5

TAG 0(18.04.13)

TAG 20 TAG 40 TAG 64

Average Hexadecane

Hexa

GlucVT

Gluc

-0,3

-0,2

-0,1

0

0,1

0,2

0,3

TAG

0

TAG

5

TAG

8

TAG

14

TAG

20

TAG

26

TAG

33

TAG

36

TAG

41

TAG

49

TAG

57

TAG

62

TAG

67

TAG

70

TAG

76

Average Tol

Tol

Tol2

GlucVT

Gluc

-0,2

-0,1

0

0,1

0,2

TAG

0

TAG

5

TAG

9

TAG

16

TAG

21

TAG

27A

bs

n Hexadecan Average

Hex1

Hex2

GlucVT

Gluc

-0,4

-0,3

-0,2

-0,1

0

0,1

TAG0

TAG5

TAG9

TAG16

TAG21

TAG27

Average Toluol

Tol

Tol2

GlucVT

Gluc

0

0,1

0,2

0,3

0,4

0,5

day0

day9

day17

day29

day39

day46

day53

Average Hexadecan

Hex 1

Hex 2

GlucVT

Gluc0

0,1

0,2

0,3

0,4

0,5

1 4 7 10 13 16 19 22

Average Hex with TTC Hex 1

Hex 2

GlucVT

Gluc

48

0

0,05

0,1

0,15

day0

day9

day17

day29

day39

day46

day53

Tol average

Tol 1

tol 2

GlucVT

Gluc0

0,1

0,2

0,3

1 4 7 10 13 16 19 22

Tol average with TTC Tol 1

tol 2

GlucVT

Gluc

-0,1

0

0,1

0,2

0,3

0,4

0,5

day0

day9

day17

day29

day39

day46

day53

PCB Average

pcb 1

pcb 2

GlucVT

Gluc 0

0,2

0,4

0,6

day0

day6

day15

day26

day30

day36

day43

Average PCB

pcb 1

pcb 2

GlucVT

Gluc

49

7.2 Diagrams microtiter plate screening

Runtime in days against absorbtion M = medium plus hydrocarbon G = medium plus glucose GVT = medium plus glucose, vitamins and trace elements

7.2.1 PCB 126

-2

0

2

day

0

day

4

day

6

day…

day…

day…

day…

day…

day…

day…

10 Selenophoma mahoniae / Average

PCB

M

M

G-2

-1

0

1

day

0

day

4

day

6

day

12

day

16

day

22

day

24

day

33

day

40

day

45

13 Scedosporium apiospermum / Average

PCB

M

M

G

GVT

-2

0

2

day 0day 3day 4day 5day 6day 7day 12day 15day 16day 19day 22day 23day 24day 26day 33day 36day 40day 43day 45

12 Exophiala alcalophila / Average

PCB

M

M

G-2

0

2

day 0day 3day 4day 5day 6day 7day 12day 15day 16day 19day 22day 23day 24day 26day 33day 36day 40day 43day 45

11 Exophiala oligosperma / Average PCB

M

M

G

-1

0

1

2

day

0

day

4

day

6

day

12

day

16

day

22

day

24

day

33

day

40

day

45

7 Exophiala castellanii / Average PCB

M

M

G

GVT-2

0

2

day 0day 3day 4day 5day 6day 7day 12day 15day 16day 19day 22day 23day 24day 26day 33day 36day 40day 43day 45

9 Exophiala exophialae / Average

PCB

M

M

G

50

-2

0

2

day

0

day

4

day

6

day…

day…

day…

day…

day…

day…

day…

2 Exohiala xenobiotica / Average

PCB

M

M

G -1

0

1

2

day

0

day

4

day

6

day

12

day

16

day

22

day

24

day

33

day

40

day

45

4 Exophiala sideris / Average PCB

M

M

G

GVT

-1

0

1

2

day

0

day

4

day

6

day

12

day

16

day

22

day

24

day

33

day

40

day

45

1 Exophiala dermatitidis / Average

PCB

M

M

G

GVT-0,5

0

0,5

1

1,5

day

0

day

5

day

12

day

19

day

24

day

36

day

45

24 Cladophialophora minourae / Average PCB

M

M

G

GVT

-2

-1

0

1

day

0

day

4

day

6

day

12

day

16

day

22

day

24

day

33

day

40

day

45

28 Aureobasidium pullulans var. pullulans / Average PCB

M

M

G

GVT

-2

0

2

day

0

day

4

day

6

day

12

day

16

day

22

day

24

day

33

day

40

day

45

19 graphium eumorphum / Average

PCB

M

M

G

GVT

-1,5

-1

-0,5

0

0,5

1

day

0

day

5

day

12

day

19

day

24

day

36

day

45

35 Pseudallescheria minutispora / Average PCB

M

M

G

GVT -1

0

1

2

day

0

day

4

day

6

day

12

day

16

day

22

day

24

day

33

day

40

day

45

36 Cladophialophora australiensis / Average

PCB

M

M

G

GVT

51

-2

-1

0

1

2

day

0

day

4

day

6

day

12

day

16

day

22

day

24

day

33

day

40

day

45

33 Exophiala spinifera / Average PCB

M

M

G

GVT-2

0

2

day 0day 3day 4day 5day 6day 7day 12day 15day 16day 19day 22day 23day 24day 26day 33day 36day 40day 43day 45

34 Exophiala heteromorpha /

Average PCB

M

M

G

-2

-1

0

1

day

0

day

4

day

6

day

12

day

16

day

22

day

24

day

33

day

40

day

45

32 Rhinocladiella similis / Average PCB

M

M

G

GVT-1

0

1

day

0

day

4

day

6

day

12

day

16

day

22

day

24

day

33

day

40

day

45

31 Exophiala spinifera / Average PCB

M

M

G

GVT

-2

-1

0

1

day

0

day

4

day

6

day

12

day

16

day

22

day

24

day

33

day

40

day

45

29 Cladophialophora subtilis / Average PCB

M

M

G

GVT -1

0

1

2

day

3

day

5

day

7

day

15

day

19

day

23

day

26

day

36

day

43

30 Phialophora americana / Average

PCB

M

M

G

GVT

-1

0

1

2

3

day

0

day

2

day

11

day

17

day

22

day

29

day

33

day

38

day

43

37 Cladophialophora emmonsii/ Average PCB

M

-2

0

2

day

0

day

2

day

11

day

17

day

22

day

29

day

33

day

38

day

43

66 Pseudallescheria boydii/ Average PCB

52

-2

0

2

day

0

day

2

day…

day…

day…

day…

day…

day…

day…

26 Pseudallescheria fusoidea/ Average

PCB

-1

0

1

2

day

0

day

2

day

11

day

17

day

22

day

29

day

33

day

38

day

43

20 Exophiala bergeri/ Average PCB

-2

0

2

day

0

day

2

day…

day…

day…

day…

day…

day…

day…

78 Aureobasidium pullulans/ Average

PCB M

-2

0

2

4d

ay 0

day

2

day…

day…

day…

day…

day…

day…

day…

5 Cladophialophora carrionii/ Average

PCB M

-1

0

1

2

day

0

day

2

day

11

day

17

day

22

day

29

day

33

day

38

day

43

21 Exophiala lecanii-corni/ Average PCB

-2

-1

0

1

2

day

0

day

2

day

11

day

17

day

22

day

29

day

33

day

38

day

43

27 Cladophialophora boppii/ Average PCB

M

-2

0

2

day

0

day

2

day…

day…

day…

day…

day…

day…

day…

14 Pseudallescheria ellipsoidea / Average

PCB

0

1

2

3

day0

day2

day11

day17

day22

day29

day33

17 Cladophialophora immunda/ Average PCB

M

53

-2

0

2

day

0

day

2

day…

day…

day…

day…

day…

day…

day…

63 Exophiala dermatitidis/ Average

PCB M

-2

0

2

day0

day2

day11

day20,

day24

day31

day36

day40

46 Aureobasidium pullulans/ Average

PCB M

-2

-1

0

1

2

day0

day2

day11

day17

day22

day31

day36

day40

3 Pseudallescheria agusta/ Average PCB

M

-1

0

1

2

day0

day2

day11

day17

day22

day31

day36

day40

16 Cladophialophora arxii / Average PCB

M

0

2

day 0day 2day 11day 17day 22day 31day 36day 40

53 Exophiala mesophila/ Average

PCB M

-5

0

5

day 0day 2day 14day 20,day 24day 31day 36day 40

70 Exophiala mesophila/ Average

PCB M

-1

0

1

2

3

day0

day2

day11

day17

day22

day31

day36

day40

74 Rhinocladiella similis/ Average PCB

-2

0

2

day0

day2

day11

day17

day22

day31

day36

day40

51 Exophiala xenobiotica/ Average

PCB

54

-5

0

5

day 0day 2day 11day 17day 22day 31day 36day 40

39 Cladophialophora mycetomatis/ Average PCB

-2

0

2

day0

day2

day11

day17

day22

day31

day36

day40

65 Exohiala heteromorpha/

Average PCB M

-5

0

5

day 0day 2day 11day 17day 22day 31day 36day 40

22 Cladophialophroa yegresii / Average

PCB M

0

2

day 0day 10day 17day 21day 26day 30day 35day 40

40 Exophiala alcalophila/ Average

PCB

M

M

G

0

1

2

day 7day 14day 19day 23day 28day 33day 37

68 Exophiala sideris /

Average PCB

M

M

G

GVT-1

0

1

2

3

day 0day 10day 17day 21day 26day 30day 35day 40

49 Cladophialophora carrionii/ Average PCB

M

0

0,5

1

1,5

2

day 0day 10day 17day 21day 26day 30day 35day 40

59 Cladophialophora yegresii/ Average PCB

M

0

1

2

3

day 0day 10day 17day 21day 26day 30day 35day 40

41 Exophiala sideris/ Average PCB

M

M

G

GVT

55

-0,5

0

0,5

1

1,5

day 0day 10day 17day 21day 26day 30day 35day 40

42 Pseudallescheria ellipsoidea/ Average PCB

M

-1

0

1

2

day 0day 10day 17day 21day 26day 30day 35day 40

47 Exophiala dermatitidis/ Average

PCB

M

M

G

-1

0

1

2

day 0day 10day 17day 21day 26day 30day 35day 40

45 Exophiala spinifera / Average PCB

M

-2

0

2

4

day 0day 10day 17day 21day 26day 30day 35day 40

8 Phialophora verrucosa/ Average

PCB M

0

2

4

day 0day 10day 17day 21day 26day 30day 35day 40

43 Exophiala oligosperma/ Average

PCB

M

M

G-0,5

0

0,5

1

1,5

day 0day 10day 17day 21day 26day 30day 35day 40

73 Exophiala castellanii/ Average PCB

M

-1

0

1

2

day 0day 10day 17day 21day 26day 30day 35day 40

72 Pseudallescheria angusta/ Average PCB

M

M

G

GVT-2

0

2

4

day 0day 10day 17day 21day 26day 30day 35day 40

60 Exophiala oligosperma/ Average

PCB M

56

-1

0

1

2

day 0day 10day 17day 21day 26day 30day 35day 40

61 Pseudallescheria boydii/ Average PCB

M

-2

0

2

4

day 0day 10day 17day 21day 26day 30day 35day 40

48 Phialophora verrucosa/ Average

PCB

M

M

G

-5

0

5

day 0day 10day 17day 21day 26day 30day 35day 40

67 Cladophialophora minourae/ Average

PCB

M

M

G-1

0

1

2

day 0day 10day 17day 21day 26day 30day 35day 40

23 Cladophialophora samoёnsis/ Average PCB

M

M

G

GVT

-2

0

2

4

day 0day 10day 17day 21day 26day 30day 35day 40

6 Cladophialophora saturnica / Average PCB

-0,5

0

0,5

1

1,5

day 0day 10day 17day 21day 26day 30day 35day 40

59 Cladophialophora yegresii / Average PCB

M

M

G

GVT

-1

0

1

2

3

day 0day 10day 17day 21day 26day 30day 35day 40

62 Cladophialophora arxii / Average PCB

M

-0,5

0

0,5

1

day 0day 10day 17day 21day 26day 30day 35day 40

71 Pseudallescheria boydii/ / Average PCB

M

M

G

GVT

57

0

0,5

1

1,5

2

day0

day4

day9

day14

day18

day23

day28

day32

day37

57 Cladophialophora boppii / Average PCB

0

0,5

1

1,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

104 Exophiala spinifera / Average PCB

-1

0

1

2

3

4

day0

day4

day9

day14

day18

day23

day28

day32

day37

76 Cladophialophora immunda / Average PCB

-0,5

0

0,5

1

1,5

2

day0

day4

day9

day14

day18

day23

day28

day32

day37

52 Exophiala bergeri / Average PCB

0

1

2

3

4

day 0day 4day 9day 14day 18day 23day 28day 32day 37

75 Pseudallescheria boydii / Average PCB

-1

0

1

2

3

day0

day4

day9

day14

day18

day23

day28

day32

day37

58 Cladophialophora immunda / Plate 2 PCB

-1

0

1

2

3

day0

day4

day9

day14

day18

day23

day28

day32

day37

55 Cladophialophora immunda / Average PCB

-1

0

1

2

3

day0

day4

day9

day14

day18

day23

day28

day32

day37

56 Exophiala lecanii-corni / Average PCB

58

-0,5

0

0,5

1

1,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

105 Pseudallescheria boydii / Average PCB

-0,5

0

0,5

1

1,5

2

day0

day4

day9

day14

day18

day23

day28

day32

day37

102 Pseudallescheria boydii / Average PCB

-2

0

2

4

day0

day4

day9

day14

day18

day23

day28

day32

day37

108 Exophiala xenobiotica / Average

PCB

-1

0

1

2

3

4

day0

day4

day9

day14

day18

day23

day28

day32

day37

91 Cladophialophora immunda / Average PCB

0

0,5

1

1,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

103 Exophiala dermatitidis / Average

PCB

0

0,5

1

1,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

101 Exophiala sideris / Average PCB

0

0,5

1

1,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

93 Aureobasidium pullulans / Average PCB

0

0,5

1

1,5

2

day0

day4

day9

day14

day18

day23

day28

day32

day37

95 Exophiala sideris / Average PCB

59

0

0,5

1

day0

day4

day9

day14

day18

day23

day28

day32

day37

80 Pseudallescheria boydii / Average PCB

0

0,5

1

1,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

113 Exophiala bergeri / Average PCB

0

1

2

3

day0

day4

day9

day14

day18

day23

day28

day32

day39

115 Exophiala spinifera / Average PCB

0

0,5

1

1,5

2

day0

day4

day9

day14

day18

day23

day28

day32

day37

106 Cladophialophora carrionii / Average PCB

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

117 Cladophialophora potulentorum / Average

PCB

-2

0

2

4

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

118 Cladophialophora chaetospira / Average

PCB

0

0,5

1

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

110 Pseudallescheria boydii / Average PCB

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

111 Exophiala mesophila / Average

PCB

60

0

0,5

1

1,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

109 Pseudallescheria boydii / Average PCB

0

0,5

1

1,5

2

2,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

84 Cladophialophora immunda / Average PCB

0

0,5

1

1,5

2

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

83 Exophiala jeanselmei / Average PCB

-2

0

2

4

day 0day 6 day13

day20

day27

day34

day42

97 Exophiala oligosperma / Average PCB

0

1

2

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

124 Cladophialophorum potulentora / Average

PCB

-1

0

1

2

3

4

day 0day 6 day13

day20

day27

day34

day42

123 Exophiala moniliae / Average PCB

0

0,5

1

1,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

107 Pseudallescheria boydii / Average PCB

0

0,5

1

1,5

2

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

92 Pseudallescheria boydii / Average PCB

61

-0,5

0

0,5

1

1,5

day 0day 6 day13

day20

day27

day34

day42

120 Pseudallescheria boydii / Average PCB

-0,5

0

0,5

1

day 0day 6 day13

day20

day27

day34

day42

119 Exophiala castellanii / Average PCB

0

0,5

1

day 0day 6 day13

day20

day27

day34

day42

121 Aureobasidium pullulans / Average PCB

-0,5

0

0,5

1

1,5

day 0day 6 day13

day20

day27

day34

day42

122 Pseudallescheria desertorum / Average

PCB

0

1

2

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

94 Pseudallescheria ellipsoidea / Average

PCB

-2

0

2

4

day 0day 6 day13

day20

day27

day34

day42

96 Exophiala heteromorpha / Average

PCB

-0,5

0

0,5

1

1,5

2

2,5

day 0day 6 day13

day20

day27

day34

day42

98 Cladophialophora carrionii / Average PCB

-0,2

0

0,2

0,4

0,6

0,8

1

day 0day 6 day13

day20

day27

day34

day42

90 Pseudallescheria boydii / Average PCB

62

-0,5

0

0,5

1

day 0day 6 day13

day20

day27

day34

day42

100 Aureobasidium pullulans var. pullulans /

Average PCB

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

125 Cladophialophora potulentorum / Average

PCB

-1

0

1

2

3

day 0day 6 day13

day20

day27

day34

day42

116 Cladophialophora chaetospira / Average

PCB

-0,5

0

0,5

1

1,5

2

2,5

day 0day 6 day13

day20

day27

day34

day42

85 Exophiala jeanselmei / Average PCB

0

0,5

1

1,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

88 Pseudallescheria boydii /Average PCB

-1

0

1

2

3

day 0day 6 day13

day20

day27

day34

day42

87 Exophiala oligosperma / Average

PCB

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

79 Exophiala xenobiotica / Plate 2

PCB

-0,5

0

0,5

1

1,5

day 0day 6 day13

day20

day27

day34

day42

82 Pseudallescheria boydii / Average PCB

63

-0,5

0

0,5

1

1,5

day 0day 6 day13

day20

day27

day34

day42

81 Pseudallescheria boydii / Average PCB

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

149 Exophiala xenobiotica / Average

PCB

0

1

2

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

154 Exophiala dermatitidis / Average

PCB

0

0,5

1

1,5

2

2,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

136 Exophiala sideris / Average PCB

0

0,2

0,4

0,6

0,8

1

day 0day 6 day13

day20

day27

day34

day42

139 Pseudallescheria boydii / Average PCB

0

0,5

1

1,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

141 Exophiala dermatitidis / Average

PCB

0

1

2

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

129 Exophiala alcalophila / Average

PCB

-0,5

0

0,5

1

day 0day 6 day13

day20

day27

day34

day42

159 Pseudallescheria boydii / Average PCB

64

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

161 Exophiala dermatitidis / Average

PCB

0

1

2

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

162 Exophiala heteromorpha / Average

PCB

0

2

4

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

163 Wangiella / Average PCB

-2

0

2

4

day 0day 6 day13

day20

day27

day34

day42

89 Exophiala dermatitidis / Average

PCB

-0,5

0

0,5

1

1,5

day 0day 6 day13

day20

day27

day34

day42

86 Pseudallescheria boydii / Average PCB

-2

0

2

4

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

148 Exophiala jeanselmei / Average

PCB

0

1

2

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

144 Exophiala mesophila / Average

PCB

0

1

2

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

130 Exophiala alcalophila / Average

PCB

65

0

0,5

1

1,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

132 Pseudallescheria boydii / Average PCB

-0,5

0

0,5

1

1,5

2

2,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

146 Fonsecaea / Average PCB

0

0,2

0,4

0,6

0,8

1

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

143 Pseudallescheria boydii / Average PCB

-0,5

0

0,5

1

1,5

2

2,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

150 Cladophialophora sp. / Average PCB

0

0,5

1

1,5

2

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

153 Exophiala spinifera / Average PCB

-0,5

0

0,5

1

1,5

day 0day 7 day14

day21

day28

day35

day42

151 Pseudallescheria boydii / Average PCB

0

0,2

0,4

0,6

0,8

1

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

128 Pseudallescheria boydii / Average PCB

-0,5

0

0,5

1

1,5

2

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

126 Exophiala lecanii-corni / Average PCB

66

0

0,5

1

1,5

2

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

160 Exophiala sideris / Average PCB

-0,5

0

0,5

1

1,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

158 Pseudallescheria boydii / Average PCB

-1

0

1

2

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

134 Exophiala bergeri / Average PCB

0

0,5

1

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

133 Pseudallescheria boydii / Average PCB

0

1

2

3

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

142 Exophiala bergeri / Average PCB

-0,5

0

0,5

1

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

157 Pseudallescheria boydii / Average PCB

0

2

4

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

156 Exophiala mesophila / Average

PCB

-0,5

0

0,5

1

1,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

155 Pseudallescheria boydii / Average PCB

67

-2

0

2

4

day 0day 7 day14

day21

day28

day35

day42

152 Exophiala jeanselmei / Average

PCB

-0,5

0

0,5

1

1,5

2

day 0day 2day 5day 7day 9day 12day 14day 16day 19day 21day 23day 26day 28day 30day 33day 35day 37day 41day 42day 44day 47

137 Pseudallescheria boydii / Average PCB

0

0,2

0,4

0,6

0,8

day 0 day 2 day 5 day 7 day 9 day12

day14

135 Pseudallescheria boydii / Average PCB

-0,5

0

0,5

1

day0

day2

day5

day7

day9

day12

day14

145 Pseudallescheria ellipsoidea / Average

PCB

0

1

2

3

4

day 0 day 2 day 5 day 7 day 9 day12

day14

18 Pseudallescheria boydii / Average PCB

-0,5

0

0,5

1

1,5

day 0day 2day 5day 7day 9 day12

day14

138 Cladophialophora mycetomatis / Average

PCB

-0,5

0

0,5

1

1,5

day0

day2

day5

day7

day9

day12

day14

140 Pseudallescheria boydii / Average PCB

-0,5

0

0,5

1

1,5

2

day 0day 2day 5day 7day 9 day12

day14

127 Fonsecaea / Plate 2 PCB

68

7.2.2 Toluene

-0,2

0

0,2

0,4

0,6

day0

day2

day5

day7

day9

day12

day14

131 Pseudallescheria boydii / Average PCB

0

0,5

1

1,5

day 0day 2day 5day 7day 9 day12

day14

147 Pseudallescheria boydii / Average PCB

-0,1

0

0,1

0,2

0,3

day

0

day

05

day

12

day

19

day

24

day

36

day

45

24 Cladophialophora minourae/ Average Tol

M

M

G

GVT -0,2

0

0,2

0,4

0,6

day

0

day

05

day

12

day

19

day

24

day

36

day

45

28 Aureobasidium pullulans var. pullulans/ Average Tol

M

M

G

GVT

-0,5

0

0,5

1

day0

day05

day12

day19

day24

day36

day45

19 Graphium eumorphum /

Average Tol

M

M

G -0,5

0

0,5

1

day

0

day

05

day

12

day

19

day

24

day

36

day

45

Ach

sen

tite

l

35 Pseudallescheria minutispora/ Average

Tol

M

M

G

GVT

-0,5

0

0,5

day

0

day

05

day

12

day

19

day

24

day

36

day

45

Ach

sen

tite

l

36 Cladophialophora australiensis / Plate 2

Tol

M

M

G

GVT -0,5

0

0,5

1

day0

day05

day12

day19

day24

day36

day45

33 Exophiala spinifera/ Average Tol

M

M

G

GVT

69

-0,5

0

0,5

1

day0

day05

day12

day19

day24

day36

day45

34 Exophiala heteromorpha / Average

Tol M

M

G

GVT

0

1

2

3

day

0

day

4

day

06

day

12

day

16

day

22

day

24

day

33

day

40

day

45

32 Rhinocladiella similis/ Average Tol

M

M

G

GVT

-0,5

0

0,5

1

day0

day05

day12

day19

day24

day36

day45

31 Exophiala spinifera/ Average Tol

M

M

G

GVT -0,2

0

0,2

0,4

0,6

day0

day05

day12

day19

day24

day36

day45

29 Cladophialophora subtilis/ Average Tol

M

M

G

GVT

-0,5

0

0,5

1

day0

day05

day12

day19

day24

day36

day45

30 Phialophora americana / AverageTol

M

M

G

00,5

1

day0

day05

day12

day19

day24

day36

day45

10 Selenophoma mahoniae / AverageTol

M

M

G

-0,5

0

0,5

1

day0

day05

day12

day19

day24

day36

day45

13 Scedosporium apiospermium/ Average

Tol

M

M

G

GVT

00,5

1

day0

day05

day12

day19

day24

day36

day45

12 Exophiala alcalophila / Average

Tol

M

M

G

70

0

1

2

day

0

day

4

day…

day…

day…

day…

day…

day…

day…

day…

11 Exophiala oligosperma /

Average Tol

M

M

G -0,5

0

0,5

1

1,5

day0

day05

day12

day19

day24

day36

day45

7 Exophiala castellanii / Average Tol

M

M

G

GVT

00,5

1

day0

day05

day12

day19

day24

day36

day45

9 Exophiala exophialae / Average

Tol

M

M

G -0,5

0

0,5

1

day0

day05

day12

day19

day24

day36

day45

2 Exophiala xenobiotica /

AverageTol

M

M

G

0

0,5

1

day0

day05

day12

day19

day24

day36

day45

4 Exophiala sideris / Average Tol

M

M

G

GVT

0

1

2

day

0

day

4

day…

day…

day…

day…

day…

day…

day…

day…

1 Exophiala dermatitidis /

AverageTol

M

M

G

0

0,5

1

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

27 Cladiophialophora boppii/ Average Tol

M

M

G

GVT -0,5

0

0,5

1

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

26 Pseudallescheria fusoidea/ Average Tol

M

71

-0,1

-0,05

0

0,05

0,1

0,15

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

22 Cladophialophora yegresii/ Average Tol

M

M

G

GVT-0,5

0

0,5

1

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

3 Pseudallescheria agusta/ Average Tol

M

0

0,5

1

1,5

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

74 Rhinocladiella similis/ Average Tol

M

M

G

GVT-0,2

0

0,2

0,4

0,6

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

14 Pseudallescheria ellipsoidea/ AverageTol

M

-0,2

-0,1

0

0,1

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

5 Cladophialophora carrionii/ Average Tol

M

00,10,20,30,4

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

16 Cladophialophora arxii / Average Tol

M

00,20,40,60,8

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

78 Aureobasidium pullans/ Average Tol

M

-0,2

-0,1

0

0,1

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

21 Exophiala lecanii-corni/ Average Tol

72

0

0,1

0,2

0,3

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

17 Cladophialophora immunda/ Average Tol

M

00,5

1

day

0

day

2 day…

day…

day…

day…

day…

day…

day…

70 Exophiala mesophila/ Average

Tol

M

M

G

0

0,2

0,4

0,6

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

46 Aureobasidium pullulans/ AverageTol

-0,050

0,050,1

0,150,2

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

37 Cladophialophora emmonsii/Average Tol

M

-0,4

-0,2

0

0,2

0,4

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

39 Cladophialophora mycetomatis/ Average Tol

M

-0,1

0

0,1

0,2

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

20 Exophiala bergeri/ Average Tol

M

0

1

2

day

0

day

2 day…

day…

day…

day…

day…

day…

day…

65 Exophiala heteromorpha/

AverageTol M

-0,5

0

0,5

1

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

66 Pseudallescheria boydii/ Plate 2 Tol

73

-0,5

0

0,5

day

0

day

2 day…

day…

day…

day…

day…

day…

day…

63 Exophiala dermatitidis/ Average

Tol

00,5

1

day

0

day

2 day…

day…

day…

day…

day…

day…

day…

51 Exophiala xenobiotica/ Average

Tol M

00,5

1

day

0

day

2 day…

day…

day…

day…

day…

day…

day…

53 Exophiala mesophila/ Average

Tol

0

1

2

day 0day 10day 17day 21day 26day 30day 35day 40

40 Exophiala alcalophila/ Average

Tol

0

0,5

1

day 7day 14day 19day 23day 28day 33day 37

68 Exophiala sideris /

Average Tol

-0,1

0

0,1

day 0day 10day 17day 21day 26day 30day 35day 40

49 Cladophialophora

carrionii/ Average Tol

0

0,5

1

day 0day 10day 17day 21day 26day 30day 35day 40

59 Cladophialophora yegresii/Average Tol

0

1

2

day 0day 10day 17day 21day 26day 30day 35day 40

41 Exophiala sideris/ Average Tol

74

-0,5

0

0,5

1

day 0day 10day 17day 21day 26day 30day 35day 40

42 Pseudallescheria ellipsoidea/ Average Tol

0

0,5

day 0day 10day 17day 21day 26day 30day 35day 40

47 Exophiala dermatitidis/ Average

Tol

-0,5

0

0,5

1

day 0day 10day 17day 21day 26day 30day 35day 40

45 Exophiala spinifera / Average Tol

-0,5

0

0,5

1

day 0day 10day 17day 21day 26day 30day 35day 40

8 Phialophora verrucosa/ Average

Tol

0

1

2

day 0day 10day 17day 21day 26day 30day 35day 40

43 Exophiala oligosperma/ Average

Tol

0

0,5

1

day 0day 10day 17day 21day 26day 30day 35day 40

73 Exophiala castellanii/

Average Tol

-0,5

0

0,5

1

day0

day10

day17

day21

day26

day30

day35

day40

Ach

sen

tite

l

72 Pseudallescheria angusta/ Average Tol

-0,5

0

0,5

day0

day10

day17

day21

day26

day30

day35

day40

60 Exophiala oligosperma/ Average

Tol

75

-0,5

0

0,5

1

day 0day 10day 17day 21day 26day 30day 35day 40

61 Pseudallescheria boydii/ Average Tol

-1

0

1

2

day 7day 14day 19day 23day 28day 33day 37

48 Phialophora verrucosa/ Average

Tol

-0,1

0

0,1

0,2

day 0day 10day 17day 21day 26day 30day 35day 40

67 Cladophialophora minourae/ Average Tol

-0,2

0

0,2

0,4

0,6

day 0day 10day 17day 21day 26day 30day 35day 40

23 Cladophialophora samoёnsis/ Average Tol

-0,05

0

0,05

0,1

day

0

day

10

day

17

day

21

day

26

day

30

day

35

day

40

6 Cladophialophora saturnica / Average Tol

-0,5

0

0,5

1

day 0day 10day 17day 21day 26day 30day 35day 40

59 Cladophialophora yegresii / Average Tol

-0,1

-0,05

0

0,05

0,1

day0

day10

day17

day21

day26

day30

day35

day40

62 Cladophialophora arxii / Average Tol

-0,2

0

0,2

0,4

0,6

day 0day 10day 17day 21day 26day 30day 35day 40

71 Pseudallescheria boydii/ / Average Tol

76

0

0,05

0,1

0,15

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

57 Cladophialophora boppii / Average Tol

0

0,1

0,2

0,3

0,4

0,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

104 Exophiala spinifera / Average Tol

-0,2

0

0,2

0,4

0,6

0,8

1

day 0day 7 day14

day21

day28

day35

day43

76 Cladophialophora immunda / Average Tol

-0,04

-0,02

0

0,02

0,04

day 0day 7 day14

day21

day28

day35

day43

52 Exophiala bergeri / Average Tol

-0,5

0

0,5

1

1,5

2

day 0day 7 day14

day21

day28

day35

day43

75 Pseudallescheria boydii / Average Tol

0

0,05

0,1

0,15

0,2

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

58 Cladophialophora immunda / Average Tol

-0,2

0

0,2

0,4

0,6

0,8

day 0day 7 day14

day21

day28

day35

day43

55 Cladophialophora immunda / Average Tol

0

0,5

1

1,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

56 Exophiala lecanii-corni / Average Tol

77

-0,2

0

0,2

0,4

0,6

0,8

day 0day 7 day14

day21

day28

day35

day43

105 Pseudallescheria boydii / Average Tol

-0,2

0

0,2

0,4

0,6

0,8

1

day 0day 7 day14

day21

day28

day35

day43

102 Pseudallescheria boydii / Average Tol

-0,5

0

0,5

1

day 0day 7 day14

day21

day28

day35

day43

108 Exophiala xenobiotica / Average

Tol

-0,05

0

0,05

0,1

0,15

day 0day 7 day14

day21

day28

day35

day43

91 Cladophialophora immunda / Average Tol

0

1

2

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

103 Exophiala dermatitidis / Average

Tol

0

0,5

1

1,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

101 Exophiala sideris / Average Tol

0

0,5

1

1,5

day 0day 7 day14

day21

day28

day35

day43

93 Aureobasidium pullulans / Average Tol

0

0,5

1

1,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

95 Exophiala sideris / Average Tol

78

0

0,2

0,4

0,6

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

80 Pseudallescheria boydii / Average Tol

0

1

2

3

day 0day 7 day14

day21

day28

day35

day43

113 Exophiala bergeri / Average Tol

0

0,5

1

1,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

115 Exophiala spinifera / Average Tol

0

0,2

0,4

0,6

0,8

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

106 Cladophialophora carrionii / Average Tol

0

0,5

1

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

117 Cladophialophora potulentorum / Average

Tol

-0,05

0

0,05

0,1

day 0day 6 day13

day20

day27

day34

day42

118 Cladophialophora chaetospira / Average

Tol

0

0,5

1

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

110 Pseudallescheria boydii / Average Tol

0

0,5

1

1,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

111 Exophiala mesophila / Average Tol

79

0

0,2

0,4

0,6

0,8

1

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

109 Pseudalleschria boydii / Average Tol

0

0,2

0,4

0,6

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

84 Cladophialophora immunda / Plate 2 Tol

0

0,5

1

1,5

2

2,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

83 Exophiala jeanselmei / Average Tol

-0,5

0

0,5

1

1,5

day 0day 6 day13

day20

day27

day34

day42

97 Exophiala oligosperma / Average

Tol

0

0,1

0,2

0,3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

124 Cladophialophorum potulentora / Average

Tol

0

0,02

0,04

0,06

0,08

0,1

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

123 Exophiala moniliae / Average Tol

0

0,2

0,4

0,6

0,8

1

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

107 Pseudallescheria boydii / Average Tol

0

0,5

1

1,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

92 Pseudallescheria boydii / Average Tol

80

-0,2

0

0,2

0,4

0,6

0,8

day 0day 6 day13

day20

day27

day34

day42

120 Pseudallescheria boydii / Average Tol

-0,2

0

0,2

0,4

0,6

day 0day 6 day13

day20

day27

day34

day42

119 Exophiala castellanii / Average Tol

0

0,5

1

day 0day 6 day13

day20

day27

day34

day42

121 Aurepbasidium pullulans / Average Tol

0

0,5

1

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

122 Pseudallescheria desertorum / Average

Tol

0

0,2

0,4

0,6

0,8

1

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

94 Pseudallescheria ellipsoidea / Average Tol

-0,1

0

0,1

0,2

day 0day 6 day13

day20

day27

day34

day42

96 Exophiala heteromorpha / Average

Tol

-0,02

0

0,02

0,04

0,06

0,08

0,1

day0

day6

day13

day20

day27

day34

day42

98 Cladophialophora carrionii / Average Tol

-0,5

0

0,5

1

1,5

day 0day 6 day13

day20

day27

day34

day42

90 Pseudallescheria boydii / Average Tol

81

-0,05

0

0,05

0,1

0,15

day0

day6

day13

day20

day27

day34

day42

100 Aureobasidium pullulans var. pullulans/

Average Tol

0

0,5

1

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

125 Cladophialophora potulentronum /

Average Tol

0

1

2

day1

day6

day10

day15

day20

day24

day29

day34

day38

day43

116 Cladiophialophora

chaetospira / …

0

1

2

3

day0

day6

day13

day20

day27

day34

day42

85 Exophiala jeanselmei / Average Tol

0

0,5

1

day0

day6

day13

day20

day27

day34

day42

88 Pseudallescheria boydii / Plate 1 Tol

-1

0

1

2

day0

day6

day13

day20

day27

day34

day42

87 Exophiala oligosperma /

Average Tol

0

0,5

1

1,5

day0

day6

day13

day20

day27

day34

day42

79 Exophiala xenobiotica / Plate 2 Tol

-0,5

0

0,5

1

1,5

day0

day6

day13

day20

day27

day34

day42

82 Pseudallescheria boydii / Average Tol

82

-0,5

0

0,5

1

day0

day6

day13

day20

day27

day34

day42

81 Pseudallescheria boydii / Average Tol

0

1

2

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

149 Exophiala xenobiotica / Average

Tol

0

0,5

1

1,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

154 Exophiala dermatitidis / Average

Tol

0

0,2

0,4

0,6

0,8

day0

day6

day13

day20

day27

day34

day42

136 Exophiala sideris / Average Tol

0

0,5

1

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

139 Pseudallescheria boydii / Average Tol

0

1

2

day0

day6

day13

day20

day27

day34

day42

141 Exophiala dermatitidis / Average

Tol

012

day0

day6

day13

day20

day27

day34

day42

129 Exohiala alcalophila / Average

Tol

-1

0

1

2

day1

day6

day10

day15

day20

day24

day29

day34

day38

day43

159 Pseudallescheria boydii / Average Tol

83

0

2

4

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

161 Exophiala dermatitidis /

Average Tol

0

1

2

day0

day6

day13

day20

day27

day34

day42

162 Exophiala heteromorpha / Average

Tol

0

1

2

day0

day6

day13

day20

day27

day34

day42

163 Wangiella / Average Tol

0

1

2

day0

day6

day13

day20

day27

day34

day42

89 Exophiala dermatitidis / Average

Tol

-0,5

0

0,5

1

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

86 Pseudallescheria boydii / Average Tol

-1

0

1

2

day0

day7

day14

day21

day28

day35

day42

148 Exophiala jeanselmei / Average

Tol

0

1

2

day

2

day

7

day…

day…

day…

day…

day…

day…

day…

day…

144 Exophiala mesophila / Average

Tol

0

0,5

1

1,5

day0

day7

day14

day21

day28

day35

day42

130 Exophiala alcalophila / Average Tol

84

0

0,5

1

day0

day7

day14

day21

day28

day35

day42

132 Pseudallescheria boydii /Average Tol

-0,5

0

0,5

1

1,5

day0

day7

day14

day21

day28

day35

day42

146 Fonsecaea / Average Tol

0

0,2

0,4

0,6

0,8

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

143 Pseudallescheria boydii / Average Tol

-0,5

0

0,5

1

1,5

day0

day7

day14

day21

day28

day35

day42

150 Cladophialophora / Average Tol

012

day0

day7

day14

day21

day28

day35

day42

153 Exophiala spinifera / Average

Tol

-0,5

0

0,5

1

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

151 Pseudallescheria boydii / Average Tol

0

0,5

1

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

128 Pseudallescheria boydii / Average Tol

-0,5

0

0,5

1

day0

day7

day14

day21

day28

day35

day42

126 Exophiala lecanii-corni / Average Tol

85

0

0,5

1

1,5

day0

day7

day14

day21

day28

day35

day42

160 Exophiala sideris / Average Tol

0

0,2

0,4

0,6

day0

day7

day14

day21

day28

day35

day42

158 Pseudallescheria boydii / Average Tol

-0,1

0

0,1

0,2

day0

day7

day14

day21

day28

day35

day42

134 Exophiala bergeri / Average Tol

0

0,5

1

day2

day7

day12

day16

day21

day26

day30

day35

day41

day44

133 Pseudallescheria boydii / Average Tol

0

1

2

day0

day7

day14

day21

day28

day35

day42

142 Exophiala bergeri / Average Tol

0

0,5

1

day0

day7

day14

day21

day28

day35

day42

157 Pseudallescheria boydii / Average Tol

0

1

2

day0

day7

day14

day21

day28

day35

day42

156 Exophiala mesophila / Average Tol

-0,2

0

0,2

0,4

0,6

0,8

day0

day7

day14

day21

day28

day35

day42

155 Pseudallescheria boydii / Average Tol

86

-0,05

0

0,05

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

152 Exophiala jeanselmei / Average

Tol

-0,05

0

0,05

0,1

1 2 3 4 5 6 7 8 9101112131415161718192021

137 Pseudallescheria boydii / Average Tol

0

0,5

1

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

135 Pseudallescheria boydii/ Average Tol

0

0,5

1

day2

day7

day12

day16

day21

day26

day30

day35

day41

145 Pseudallescheria ellipsoidea / Average

Tol

0

0,1

0,2

0,3

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

18 Pseudallescheria boydii/ Average Tol

-0,05

0

0,05

0,1

day0

day7

day14

day21

day28

day35

day42

138 Cladophialophora mycetomatis /Average

Tol

0

0,5

1

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

140 Pseudallescheria boydii / Average Tol

-0,5

0

0,5

1

1,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

127 Fonsecaea / Average Tol

87

7.2.3 Hexadecane

-0,5

0

0,5

1

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

131 Pseudallescheria boydii / Average Tol

0

0,5

1

1,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

147 Pseudallescheria boydii / Average Tol

0

2

4

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

24 Cladophialophora minourae/

Average Hex

M

M

G

GVT-0,5

00,5

11,5

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

28 Aureobasidium pullulans var. pullulans/ Average Hex

M

M

G

GVT

0

1

2

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

19 Gaphium eumorphum/ Average

Hex

M

M

G

GVT-0,5

0

0,5

1

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

35 Exophiala jeanselmei/ Average

Hex

M

M

G

GVT

0

2

4

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

36 Cladophialophora australiensis / Average

Hex

M

M

G

GVT

0

1

2

day

0

day…

day…

day…

day…

day…

day…

day…

day…

33 Exophiala spinifera/ Average

Hex

M

M

G

88

0

2

4

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

34 Exophiala heteromorpha/ Average

Hex

M

M

G

GVT

0

1

2

3

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

32 Rhinocladiella similis / Average Hex

M

M

G

GVT

0

1

2

3

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

31 Exophiala spinifera / Average Hex

M

M

G

GVT

0

0,5

1

1,5

2

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

29 Cladophialophora subtilis / Average Hex

M

M

G

GVT

0

0,5

1

1,5

2

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

30 Phialophora americana/ Average Hex

M

M

G

GVT

0

0,5

1

1,5

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

10 Selenohoma mahoniae/ average Hex

M

M

G

GVT

0

0,5

1

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

13 Scedosporium apiosermum/ Aveage hex

M

M

G

GVT

0

0,5

1

1,5

2

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

12 Exophiala alcalohila/ Average Hex

M

M

G

GVT

89

0

1

2

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

11 Exophiala oligosperma / Average

Hex

M

M

G

GVT

0

0,5

1

1,5

2

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

7 Exophiala castellanii/ Average Hex

M

M

G

GVT

0

1

2

3

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

9 Exophiala exophialae/ Average Hex

M

M

G

GVT

0

1

2

3

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

2 Exophiala xenobiotica / Average Hex

M

M

G

GVT

0

0,5

1

1,5

2

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

4 Exophiala sideris/ Average Hex

M

M

G

GVT

0

0,5

1

1,5

2

day

0

day

04

day

06

day

15

day

19

day

23

day

26

day

36

day

43

1 Exophiala dermatitidis/ Average Hex

M

M

G

GVT

0

1

2

3

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

27 Cladiophialophora boppii/ Average Hex

M

M

G

GVT

0

0,5

1

1,5

2

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

22 Cladophialophora yegressii/ Average Hex

M

M

G

GVT

90

-0,5

0

0,5

1

1,5

2

day0

day2

day10

day14

day18

day21

day31

day37

day41

3 Pseudallescheria agusta/Average Hex

M

M

G

GVT

0

1

2

3

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

74 Rhinocladiella similis/ Average Hex

M

M

G

GVT

-1

0

1

2

3

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

14 Pseudallescheria ellipsoidea/ Plate 2 Hex

M

M

G

GVT -0,5

0

0,5

1

1,5

2

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

5 Cladophialophora carrionii/ Average Hex

M

M

G

GVT

0

1

2

3

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

16 Cladophialophora arxii/ Average Hex

M

M

G

GVT

0

0,2

0,4

0,6

0,8

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

78 Aureobasidium pullans/ Average Hex

M

M

G

GVT

-1

0

1

2

3

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

21 Exophiala lecanii-corni/ Average Hex

M

M

G

GVT0

1

2

3

day0

day7

day14

day19

day31

day39

Ach

sen

tite

l

70 Exophiala mesophila / Average Hex

M

M

G

GVT

91

0

0,5

1

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

46 Aureobasidium / Average Hex

M

M

G

GVT -0,5

0

0,5

1

1,5

2

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

37 Cladophilalophora emmonsii/ Average Hex

M

M

G

GVT

0

1

2

3

day 1day 7day 11day 17day 19day 28day 34day 39

39 Cladophialophora mycetomatis / Average Hex

M

M

G

GVT

0

1

2

3

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

20 Exophiala bergeri/ Average Hex

M

M

G

GVT

0

1

2

3

4

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

65 Exophiala heteromorpha / Average Hex

M

M

G

GVT-0,5

0

0,5

1

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

66 Pseudallescheria boydii/ Average Hex

00,5

11,5

2

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

63 Exohiala dermatitidis/ Average Hex

M

M

G

GVT

0

1

2

3

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

51 Exohiala xenobiotica/ Average Hex

M

M

G

GVT

92

0

1

2

3

day

0

day

2

day

10

day

14

day

18

day

21

day

31

day

37

day

41

53 Exophiala mesophila/ Average Hex

M

M

G

GVT0

0,5

1

1,5

2

day0

day10

day17

day21

day26

day30

day35

day40

40 Exophiala alcalophila/ Average Hex

0

1

2

3

day0

day10

day17

day21

day26

day30

day35

day40

68 Exophiala sideris /

Average Hex

-1

0

1

2

3

day0

day10

day17

day21

day26

day30

day35

day40

49 Cladophialophora carrionii/ Average Hex

M

0

1

2

3

day 0day 10day 17day 21day 26day 30day 35day 40

59 Cladophialophora yegresii/Average Hex

0

1

2

3

day0

day10

day17

day21

day26

day30

day35

day40

41 Exophiala sideris/ Average Hex

M

0

0,5

1

1,5

day 0day 10day 17day 21day 26day 30day 35day 40

42 Pseudallescheria ellipsoidea/ Plate 2 Hex

M

M

G

GVT

0

0,5

1

1,5

2

day0

day10

day17

day21

day26

day30

day35

day40

47 Exophiala dermatitidis/

Average Hex

M

M

G

GVT

93

0

0,5

1

1,5

2

day0

day10

day17

day21

day26

day30

day35

day40

45 Exophiala spinifera / Average Hex

M

M

G

GVT -1

0

1

2

3

4

day0

day10

day17

day21

day26

day30

day35

day40

8 Phialophora verrucosa/ / Average Hex

M

0

1

2

3

day0

day10

day17

day21

day26

day30

day35

day40

43 Exophiala oligosperma/ Average Hex

M

0

0,5

1

1,5

day0

day10

day17

day21

day26

day30

day35

day40

73 Exophiala castellanii/ Average Hex

M

0

0,5

1

1,5

day0

day10

day17

day21

day26

day30

day35

day40

72 Pseudallescheria angusta/ Average Hex

M

0

1

2

3

day0

day10

day17

day21

day26

day30

day35

day40

60 Exophiala oligosperma/ Average Hex

M

-0,5

0

0,5

1

1,5

day0

day10

day17

day21

day26

day30

day35

day40

61 Pseudallescheria boydii/ Average Hex

M

-1

0

1

2

3

4

day7

day14

day19

day23

day28

day33

day37

48 Phialophora verrucosa/ Average Hex

M

94

-1

0

1

2

3

day0

day10

day17

day21

day26

day30

day35

day40

67 Cladophialophora minourae/ Average Hex

M

-1

0

1

2

3

day0

day10

day17

day21

day26

day30

day35

day40

23 Cladophialophora samoёnsis/ Average Hex

-1

0

1

2

3

day0

day10

day17

day21

day26

day30

day35

day40

6 Cladophialophora saturnica / Average Hex

-0,5

0

0,5

1

1,5

day0

day10

day17

day21

day26

day30

day35

day40

59 Cladophialophora yegresii / Average Hex

M

M

G

GVT

-1

0

1

2

3

4

day0

day10

day17

day21

day26

day30

day35

day40

62 Cladophialophora arxii / Average Hex

M

0

0,5

1

1,5

day0

day10

day17

day21

day26

day30

day35

day40

71 Pseudallescheria boydii/Average Hex

M

M

G

GVT

0

0,5

1

1,5

2

2,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

57 Cladophialophora boppii / Average Hex

0

0,2

0,4

0,6

day 0day 7 day14

day21

day28

day35

day43

104 Exophiala spinifera / Average Hex

95

-1

0

1

2

3

day 0day 7 day14

day21

day28

day35

day43

76 Cladophialophora immunda / Average Hex

-0,5

0

0,5

1

1,5

2

day 0day 7 day14

day21

day28

day35

day43

52 Exophiala bergeri / Average Hex

-1

0

1

2

3

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

75 Pseudallescheria boydii / Average Hex

0

0,5

1

1,5

2

2,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

58 Cladophialophora immunda / Average Hex

-1

0

1

2

3

4

day 0day 7 day14

day21

day28

day35

day43

55 Cladophialophora immunda / Average Hex

0

1

2

3

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

56 Exophiala lecanii-corni / Average Hex

-0,5

0

0,5

1

1,5

day 0day 7 day14

day21

day28

day35

day43

105 Pseudallescheria boydii / Average Hex

-0,5

0

0,5

1

1,5

day 0day 7 day14

day21

day28

day35

day43

102 Pseudallescheria boydii / Average Hex

96

-1

0

1

2

3

day 0day 7 day14

day21

day28

day35

day43

108 Exophiala xenobiotica / Average

Hex

-1

0

1

2

3

4

day0

day7

day14

day21

day28

day35

day43

91 Cladophialophora immunda / Average Hex

0

1

2

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

103 Exophiala dermatitidis / Average

Hex

0

1

2

3

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

101 Exophiala sideris / Average Hex

0

1

2

day 0day 7 day14

day21

day28

day35

day43

93 Aureobasidium pullulans / Average Hex

0

0,5

1

1,5

2

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

95 Exophiala sideris / Average Hex

0

0,5

1

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

80 Pseudallescheria boydii / Average Hex

0

1

2

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

113 Exophiala bergeri / Average Hex

97

0

0,5

1

1,5

2

2,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

115 Exophiala spinifera / Average Hex

0

0,5

1

1,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

114 Pseudallescheria boydii / Average Hex

0

0,5

1

1,5

2

2,5

day0

day4

day9

day14

day18

day23

day28

day32

day37

day43

day46

106 Cladophialophora carrionii / Average Hex

0

1

2

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

117 Cladophialophora potulentorum / Average

Hex

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

118 Cladophialophora chaetospira / Average

Hex

0

0,5

1

1,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

110 Pseudallescheria boydii / Average Hex

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

111 Exophiala mesophila / Average

Hex

0

0,5

1

1,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

109 Pseudallescheria boydii / Average Hex

98

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

84 Cladophialophora immunda / Average Hex

0

0,5

1

1,5

2

2,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

83 Exophiala jeanselmei / Average Hex

-2

0

2

4

day 0day 6 day13

day20

day27

day34

day42

97 Exophiala oligosperma / Average

Hex

0

1

2

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

124 Cladophialophora potulentorum/ Average

Hex

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

123 Exophiala moniliae / Average Hex

0

0,5

1

1,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

107 Pseudallescheria boydii / Average Hex

0

0,5

1

1,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

92 Pseudallescheria boydii / Average Hex

-0,5

0

0,5

1

1,5

day 0day 6 day13

day20

day27

day34

day42

120 Pseudallescheria boydii / Average Hex

99

-0,5

0

0,5

1

1,5

day 0day 6 day13

day20

day27

day34

day42

119 Exophiala castellanii / Average Hex

0

0,5

1

day 0day 6 day13

day20

day27

day34

day42

121 Aurepbasidium pullulans / Average Hex

0

0,5

1

1,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

122 Pseudallescheria desertorum / Average

Hex

0

1

2

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

94 Pseudallescheria ellipsoidea / Average

Hex

-2

0

2

4

day 0day 6 day13

day20

day27

day34

day42

96 Exophiala heteromorpha / Average

Hex

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

98 Cladophialophora carrionii / Average Hex

-0,5

0

0,5

1

1,5

day 0day 6 day13

day20

day27

day34

day42

90 Pseudallescheria boydii / Average Hex

-0,5

0

0,5

1

day 0day 6 day13

day20

day27

day34

day42

100 Aureobasidium pullulans var. Pullulans /

Average Hex

100

0

2

4

day 0day 1day 3day 6day 8day 10day 13day 15day 17day 20day 22day 24day 27day 29day 31day 34day 36day 38day 42day 43day 45

125 Cladophialophora potulentorum /

Average Hex

0

1

2

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

116 Cladophialophora chaetospira / Average

Hex

0

0,5

1

1,5

2

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

85 Exophiala jeanselmei / Average Hex

0

0,5

1

1,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

88 Pseudallescheria boydii / Average Hex

-2

0

2

4

day 0day 6 day13

day20

day27

day34

day42

87 Exophiala oligosperma / Average

Hex

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

79 Exophiala xenobiotica / Plate 2 Hex

-0,5

0

0,5

1

1,5

day 0day 6 day13

day20

day27

day34

day42

82 Pseudallescheria boydii / Average Hex

-0,5

0

0,5

1

1,5

day 0day 6 day13

day20

day27

day34

day42

81 Pseudallescheria boydii / Average Hex

101

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

149 Exophiala xenobiotica / Average

Hex

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

154 Exophiala dermatitidis / Average

Hex

0

0,5

1

1,5

2

2,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

136 Exophiala sideris / Average Hex

0

0,5

1

1,5

day 0day 6 day13

day20

day27

day34

day42

139 Pseudallescheria boydii / Average Hex

0

0,5

1

1,5

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

141 Exophiala dermatitidis / Average

Hex

0

1

2

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

129 Exophiala alcalophila / Average

Hex

-0,5

0

0,5

1

day 0day 6 day13

day20

day27

day34

day42

159 Pseudallescheria boydii / Average Hex

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

161 Exophiala dermatitidis / Average

Hex

102

0

1

2

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

162 Exophiala heteromorpha / Average

Hex

0

2

4

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

163 Wangiella / Average Hex

0

1

2

3

day0

day3

day8

day13

day17

day22

day27

day31

day36

day42

day45

89 Exophiala dermatitidis / Average

Hex

-0,5

0

0,5

1

1,5

day 0day 6 day13

day20

day27

day34

day42

86 Pseudallescheria boydii / Average Hex

-2

0

2

4

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

148 Exophiala jeanselmei / Average

Hex

0

1

2

3

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

144 Exophiala mesophila / Average

Hex

0

1

2

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

130 Exophiala alcalophila / Average

Hex

0

0,5

1

1,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

132 Pseudallescheria boydii /Average Hex

103

0

0,5

1

1,5

2

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

146 Fonsecaea / Average Hex

0

0,5

1

1,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

143 Pseudallescheria boydii / Average Hex

-0,5

0

0,5

1

1,5

2

2,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

150 Cladophialophora sp. / Average Hex

0

0,5

1

1,5

2

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

153 Exophiala spinifera / Average Hex

-0,5

0

0,5

1

1,5

day 0day 7 day14

day21

day28

day35

day42

151 Pseudallescheria boydii / Average Hex

0

0,5

1

1,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

128 Pseudallescheria boydii / Average Hex

-0,5

0

0,5

1

1,5

2

2,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

126 Exophiala lecanii-corni / Average Hex

0

0,5

1

1,5

2

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

160 Exophiala sideris / Average Hex

104

0

0,5

1

1,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

158 Pseudallescheria boydii / Average Hex

-1

0

1

2

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

134 Exophiala bergeri / Average Hex

0

0,5

1

1,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

133 Pseudallescheria boydii / Average Hex

0

0,5

1

1,5

2

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

142 Exophiala bergeri / Average Hex

0

0,5

1

1,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

157 Pseudallescheria boydii / Average Hex

0

2

4

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

156 Exophiala mesophila / Average

Hex

0

0,5

1

1,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

155 Pseudallescheria boydii / Average Hex

-2

0

2

4

day 0day 7 day14

day21

day28

day35

day42

152 Exophiala jeanselmei / Average

Hex

105

0

1

2

day 0day 2day 5day 7day 9day 12day 14day 16day 19day 21day 23day 26day 28day 30day 33day 35day 37day 41day 42day 44day 47

137 Pseudallescheria boydii / Average Hex

-0,2

0

0,2

0,4

0,6

0,8

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

135 Pseudallescheria boydii / Average Hex

0

0,5

1

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

145 Pseudallescheria ellipsoidea / Average

Hex

0

1

2

3

4

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

18 Pseudallescheria boydii / Average Hex

0

1

2

3

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

138 Cladophialophora mycetomatis /Average

Hex

0

0,5

1

1,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

140 Pseudallescheria boydii / Average Hex

-0,5

0

0,5

1

1,5

2

2,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

127 Fonsecaea / Average Hex

0

0,2

0,4

0,6

0,8

1

day 0day 7 day14

day21

day28

day35

day42

131 Pseudallescheria boydii / Average Hex

106

7.3 Diagrams GC screening

Carbon equivalence [mol] of the Toluene and CO2 was plotted against runtime [days]. different curves:

G+T: toluene of the positive control

G+T CO2: CO2 of the positive control

T: toluene of bottles with hexadecane and toluene as sole carbon source

T CO2: CO2 of bottles with hexadecane and toluene as sole carbon source

0

0,5

1

1,5

day0

day5

day9

day14

day19

day23

day28

day33

day37

day42

day47

147 Pseudallescheria boydii / Average Hex

-5E-09

0

5E-09

1E-08

0,00 10,00 20,00

C e

q

Runtime

26 Pseudallescheria fusoidea

G+T

T

G+T CO2

T CO2

0

5E-09

0,00 10,00 20,00

C e

q

Runtime

14 Pseudallescheria ellipsoidea

G+T

T

G+T CO2

T CO2

0

2E-09

4E-09

6E-09

8E-09

0,00 10,00 20,00

C e

q

Runtime

31 Exophiala spinifera

G+T

T

G+T CO2

T CO2

0

2E-09

4E-09

0,00 10,00 20,00

C e

q

Runtime

19 Graphium emorphum

G+T

T

G+T

T

107

0

5E-09

0,00 10,00 20,00

C e

q

Runtime

71 Pseudallescheria boydii

G+T

T

G+T CO2

T CO2

0

5E-09

1E-08

0,00 10,00 20,00

C e

q

Runtime

32 Rhinocladiella similis

G+T

T

G+T CO2

T CO2

0

5E-09

1E-08

0,00 10,00 20,00

C e

q

Runtime

27 Cladiophialophora boppii

G+T

T

G+T CO2

T CO2

0

5E-09

0,00 10,00 20,00

C e

q

Runtime

110 Pseudallescheria boydii

T

T CO2

0

5E-09

0,00 5,00 10,0015,00

C e

q

Runtime

158 Pseudallescheria boydii

T

T CO20

5E-09

0,00 2,00 4,00 6,00

C e

q

Runtime

94 Pseudallescheria ellipsoidea

T

T CO2

0

5E-09

0,00 2,00 4,00 6,00

C e

q

Runtime

139 Pseudallescheria boydii

T

T CO20

2E-09

4E-09

0,00 5,00 10,0015,00

C e

q

Runtime

75 Pseudallescheria boydii

T

T CO2

108

0

5E-09

0,00 2,00 4,00 6,00

C e

q

Runtime

159 Pseudallescheria boydii

T

T CO20

5E-09

0,00 2,00 4,00 6,00

C e

q

Runtime

143 Pseudallescheria boydii

T

T CO2

0

5E-09

0,00 5,00 10,0015,00

C e

q

Runtime

97 Exophiala oligosperma

T

T CO20

5E-09

0,00 5,00 10,0015,00

C e

q

Runtime

90 Pseudallescheria boydii

T

T CO2

0

5E-09

0,00 5,00 10,0015,00

C e

q

Runtime

105 Pseudallescheria boydii

T

T CO20

5E-09

0,00 5,00 10,0015,00

C e

q

Runtime

107 Pseudallescheria boydii

T

T CO2

0

5E-09

0,00 2,00 4,00 6,00

C e

q

Runtime

86 Pseudallescheria boydii

T

T CO20

5E-09

0,00 2,00 4,00 6,00

C e

q

Runtime

92 Pseudallescheria boydii

T

T CO2

109

0

5E-09

0,00 2,00 4,00 6,00

C e

q

Runtime

81 Pseudallescheria boydii

T

T CO2

110

STATUTORY DECLARATION I declare that I have authored this thesis independently, that I have not used other than the declared sources/resources, and that I have explicitly marked all material which has been quoted either literally or by content from the used sources.

Vienna, April 2014

Caroline Poyntner

EIDESSTATTLICHE ERKLÄRUNG Ich erkläre an Eides statt, dass ich die vorliegende Arbeit selbstständig verfasst, andere als die angegebenen Quellen/Hilfsmittel nicht benutzt, und die den benutzten Quellen wörtlich und inhaltlich entnommene Stellen als solche kenntlich gemacht habe.

Wien, April 2014 Caroline Poyntner

111