Linköping University Medical Dissertations No. 1128

Antibiotic Resistance in Wastewater Methicillin-resistant Staphylococcus aureus (MRSA)

and antibiotic resistance genes

Stefan Börjesson

Division of Medical Microbiology Department of Clinical and Experimental Medicine

Faculty of Health Sciences Linköping University

SE-581 85 Linköping Sweden

Linköping 2009

Antibiotic Resistance in Wastewater - Methicillin-resistant Staphylococcus aureus (MRSA) and antibiotic resistance genes ISBN: 978-91-7393-629-3 ISSN: 0345-0082 © Stefan Börjesson All previously published papers, figures, and tables are reprinted with the permission from the respective publisher Cover art: Trickling filters at Ryaverket, Göteborg, Sweden. Photo by: Stefan Börjesson. The work in this thesis was financed by: The Swedish Research Council for Environment, Agriculture Science and Spatial Planning, The Medical Research Council of South Eastern Sweden (FORSS) and County Council of Östergötland, Sweden. Printed by LiU-Tryck, Linköping, Sweden, 2009

“Don't make fun of graduate students. They just made a

terrible life choice”

- Marge Simpson (The Simpsons)

Till Far och Mor

Modified from the Cartoon by Nick D Kim

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Abstract

A large part of the antibiotics consumed ends up in wastewater, and in the wastewater the

antibiotics may exert selective pressure for or maintain resistance among microorganisms.

Antibiotic resistant bacteria and genes encoding antibiotic resistance are commonly detected

in wastewater, often at higher rates and concentrations compared to surface water.

Wastewater can also provide favourable conditions for the growth of a diverse bacterial

community, which constitutes a basis for the selection and spread of antibiotic resistance.

Therefore, wastewater treatment plants have been suggested to play a role in the

dissemination and development of antibiotic resistant bacteria. Methicillin-resistant

Staphylococcus aureus (MRSA) is a large problem worldwide as a nosocomial pathogen, but

knowledge is limited about occurrence in non-clinical environments, such as wastewater, and

what role wastewater plays in dissemination and development of MRSA.

In this thesis we investigated the occurrence of MRSA in a full-scale wastewater treatment

plant (WWTP). We also investigated the concentration of genes encoding resistance to

aminoglycosides (aac(6’)-Ie+aph(2’’)), β-lactam antibiotics (mecA) and tetracyclines (tetA

and tetB) in three wastewater-associated environments: (1) soil from an overland flow area

treating landfill leachates, (2) biofilm from a municipal wastewater treatment plant, and (3)

sludge from a hospital wastewater pipeline. In addition, concentrations of mecA, tetA and

tetB were investigated over the treatment process in the WWTP. These investigations were

performed to determine how the prevalence and concentration of MRSA and the antibiotic

resistence genes are affected in wastewater and wastewater treatment processes over time.

The occurrence of MRSA was investigated by cultivation and a commercially available real-

time PCR assay. In order to determine concentrations of the genes aac(6’)-Ie+aph(2’’), mecA,

tetA and tetB in wastewater we developed a LUXTM real-time PCR assay for each gene.

Using cultivation and real-time PCR we could for the first time describe the occurrence of

MRSA in wastewater and show that it had a stable occurrence over time in a WWTP. MRSA

could mainly be detected in the early treatment steps in the WWTP, and the wastewater

treatment process reduced the number and diversity of cultivated MRSA. However, our

results also indicate that the treatment process selects for strains with more extensive

resistance and possibly higher virulence. The isolated wastewater MRSA strains were shown

to have a close genetic relationship to clinical isolates, and no specific wastewater lineages

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could be detected, indicating that they are a reflection of carriage in the community. Taken

together, these data indicate that wastewater may be a potential reservoir for MRSA and that

MRSA are more prevalent in wastewater than was previously thought.

The real-time PCR assays, for aac(6’)-Ie+aph(2’’), mecA, tetA, and tetB that we developed,

were shown to be sensitive, fast, and reproducible methods for detection and quantification of

these genes in wastewater environments. The highest concentrations of all genes were

observed in the hospital pipeline, and the lowest in the overland flow system, with tetA and

aac(6´)-Ie+aph(2´´) detected in all three environments. In the full-scale WWTP, we

continuously detected mecA, tetA and tetB over the treatment process and over time. In

addition, it was shown that the treatment process reduces concentrations of all three genes.

The data presented in this thesis also indicate that the reduction for all three genes may be

connected to the removal of biomass, and in the reduction of tetA and tetB, sedimentation and

precipitation appear to play an important role.

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Populärvetenskaplig sammanfattning Resistenta gula stafylokocker (MRSA) och antibiotikaresistensgener förekommer i

svenskt kommunalt avloppsvatten

Methicillinresistenta Staphylococcus aureus (MRSA), även kända som resistenta gula

stafylokocker, är en bakterieart som utvecklat resistens mot alla penicilliner och

penicillinliknande antibiotika (β-laktam antibiotika). Detta innebär stora problem inom

sjukvården eftersom β-laktamerna är den vanligast använda antibiotikaklassen. S. aureus

ingår ofta i normalfloran hos en stor del av befolkningen men är också en opportunistisk

patogen som kan orsaka en rad olika sjukdomar. Bland annat är S. aureus den främsta orsaken

till variga sårinfektioner men den kan också orsaka allvarligare sjukdomar som t ex

blodförgiftning, lung- och hjärnhinneinflammation. De vårdrelaterade sjukdomarna (populärt

kallad sjukdomssjukan) utgörs till stor del av S. aureus infektioner. I stora delar av världen

dominerar nu MRSA över de methicillinkänsliga S. aureus vid infektioner inom sjukvården,

vilket leder till längre sjukhusvistelser, högre dödlighet och högre kostnader för samhället.

MRSA i Sverige är fortfarande ganska ovanligt men trenden är här som i övriga världen en

ökning i antalet MRSA infektioner. Hur spridning och utveckling av MRSA sker i sjukvården

är utförligt studerat, men vilken roll andra miljöer har för spridning och utveckling av MRSA

är mindre känt.

I denna avhandling har vi försökt öka kunskapen om förekomst av MRSA i

ickekliniska miljöer. Syftet var att undersöka om MRSA kan förekomma i avloppsvatten och

hur MRSA och förekomsten av genen mecA (som ger methicillinresistensen hos

stafylokocker) påverkas av reningsprocesserna i ett kommunalt avloppsvattenreningsverk.

Dessutom ville vi bestämma släktskap mellan MRSA i avloppsvattnet och MRSA inom

sjukvården. För att kunna utföra projektet samlades vattenprover in från ett kommunalt

avloppsvattenreningsverk. I verket togs vattenprover från flera provpunkter som var utvalda

för att täcka upp de olika stegen i reningsprocessen. MRSA i avloppsvattnet identifierades

dels genom odling från vattnet men också genom identifiering av MRSA-DNA med hjälp av

en känslig molekylärbiologisk metodik, en så kallad realtids-PCR. För att identifiera och

koncentrationsbestämma mecA genen i avloppsvatten utvecklade vi en helt ny realtids-PCR.

Med hjälp av de utvalda metoderna kunde vi för första gången observera MRSA i

avloppsvatten. Våra resultat visar att MRSA främst förekommer under ett tidigt skede i

reningsprocessen och att det sker en minskning av MRSA i både antal och variationsrikedom.

Det finns en antydan till att det under reningsprocessen också sker ett urval mot MRSA med

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utvidgad antibiotikaresistens och möjligen högre virulens. När MRSA stammarna från

avloppsvattnet jämfördes med de 20 vanligaste inom sjukvården isolerade MRSA stammar i

Sverige 2007 – 2008 visade resultaten att samma MRSA stammar förekom i avloppsvattnet

eller att stammarna var närbesläktade med sjukvårdsstammarna. Våra resultat tyder därför på

att MRSA som hittats i avloppsvattnet är en spegling av bärandet i samhället. Resultatet av

projektet visar också att mecA koncentrationen varierar över året men att någon klar trend ej

kan ses. Vid en jämförelse mellan obehandlat och behandlat avloppsvatten kunde vi i de flesta

proverna observera en sänkning av mecA koncentrationen, sänkningen varierade mellan 3 och

300 ggr.

Utöver undersökning av MRSA och mecA genen utvecklades i doktorandprojektet

realtids-PCR för att identifiera och kvantifiera gener som ger resistens mot aminoglykosider

och tetracykliner, vilka är två vanligt använda antibiotikaklasser. Målet var att använda

realtids-PCR för att undersöka förekomsten och koncentrationen av generna i olika miljöer

kopplade till avloppsvatten. Generna som undersöktes var aac(6’)-Ie+aph(2’’) som ger

bakterier resistens mot aminoglykosidantibiotika, samt generna tetA och tetB som ger

gramnegativa bakterier resistens mot tetracyklinantibiotika. Tillsammans med den utvecklade

metoden för kvantifiering av genen mecA, användes dessa fyra metoder på tre olika

avloppsvattenmiljöer: jordprov från en översilningsvåtmark behandlad med lakvatten,

biofilmprov från ett kommunalt reningsverk samt slamprov från ett sjukhusavlopp. De

utvecklade metoderna visade en hög tillförlitlighet för identifiering och kvantifiering av de

aktuella generna i avloppsvattenmiljöerna. De högsta koncentrationerna av alla gener kunde

detekteras i sjukhusavloppet och de lägsta koncentrationerna i översilningsvåtmarken.

Förekomst och koncentration av generna tetA och tetB undersöktes också i det kommunala

avloppsvattenreningsverket och hur koncentrationerna av generna påverkas av

reningsprocessen. Våra mätningar visade att koncentrationen av de båda generna varierade

över året men utan tydlig trend. Precis som för genen mecA kunde en minskning av tetA och

tetB påvisas över reningsprocessen. När obehandlat och behandlat avloppsvatten jämfördes

varierade reduktionen av tetA mellan 4 och 300 ggr och för tetB mellan 3 och 40 ggr.

Minskningen av tetA och tetB koncentrationerna verkar delvis bero på utfällnings- och

sedimentationsprocesserna som utförs vid reningen av avloppsvattnet. Koncentrationerna av

de båda generna påverkas också starkt av mängd biomassa och borttagandet av biomassa i

reningsverket.

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List of Papers This doctoral thesis is based on the following papers. They are referred to in the text by their Roman numerals I. Börjesson S., Dienus O., Jarnheimer PA., Olsen B., Matussek A. and Lindgren PE. (2009) Quantification of genes encoding resistance to aminoglycosides, ß-lactams and tetracyclines in wastewater environments by real-time PCR. International Journal of Environmental Health Research DOI: 10.1080/09603120802449593 II. Börjesson S., Melin S., Matussek A. and Lindgren PE. (2009) A seasonal study of the mecA gene and Staphylococcus aureus including methicillin-resistant S. aureus in a municipal wastewater treatment plant. Water Research 43:4 925-932 III. Börjesson S., Matussek A., Melin S., Löfgren S. and Lindgren PE. Methicillin-resistant Staphylococcus aureus (MRSA) in municipal wastewater: An uncharted threat? Manuscript IV. Börjesson S., Mattsson A., and Lindgren PE. Genes encoding tetracycline

resistance in a full-scale municipal wastewater treatment plant investigated during one year. Manuscript

Papers are reprinted with permission from the respective publisher

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Table of Contents 1. Antibiotic resistance 01 2. Antibiotic resistance as an environmental problem 02 3. Wastewater treatment in Sweden 04

3.1. The wastewater treatment plant Ryaverket, Gothenburg, Sweden 04 3.2. Bacterial communities and pathogens in municipal wastewater treatment plants 06

4. Staphylococcus aureus 08 4.1. Typing of S. aureus 10 4.1.1 Pulse field gel electrophoresis 11 4.1.2 Multilocus sequence typing 11 4.1.3 spa typing 12 4.2. S. aureus in wastewater and the environment 13

5. Methicillin resistant S. aureus (MRSA) 14 5.1. β-lactam antibiotics and resistance to β-lactams 15 5.2. The mecA gene and the staphylococcal cassette chromosome mec (SCCmec) 17 5.3. Hospital- and community-associated MRSA 19 5.4. MRSA in animals 20 5.5. β-lactam antibiotics in wastewater 21 5.6. Methicillin resistant staphylococci and other β-lactam resistance in wastewater

and other environments 21 6. Aminoglycoside antibiotics 22

6.1. Aminoglycosides in wastewater 23 6.2. Resistance to aminoglycosides 23 6.3. Aminoglycoside resistance in wastewater and other environments 24

7. Tetracycline antibiotics 25 7.1. Tetracyclines in wastewater 26 7.2. Resistance to tetracyclines 26 7.3. Tetracycline resistance in wastewater and other environments 28

8. Polymerase chain reaction (PCR) and real-time PCR 30 8.1 LUXTM real-time PCR 34 9. Aims of the thesis 35 10. Sampling sites 36 11. Design and evaluation of LUXTM real-time PCR assays for the mecA, tetA, tetB and aac(6’)-Ie+aph(2’’) genes 37 12. Detection of the mecA gene, Staphylococcus aureus and MRSA in a full-scale

wastewater treatment plant 40 13. Cultivation and characterisation of MRSA from municipal wastewater 41 14. The effect of wastewater treatment on concentrations of mecA, tetA and tetB 45 15. Conclusions 48 16. Future work 48 17. Acknowledgements 50 18. References 52

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Abbreviations BURP The algorithm based upon repeat patterns BURST The algorithm based upon related sequence types CC Clonal complex CoNS Coagulase-negative staphylococci LUX Light upon extension MRSA Methicillin resistant Staphylococcus aureus CA-MRSA Community associated MRSA HA-MRSA Hospital associated MRSA MLST Multilocus sequence typing MSSA Methicillin sensitive Staphylococcus aureus otr-genes Oxytetracycline resistance gene PBP Penicillin-binding protein PCR Polymerase chain reaction PFGE Pulse field gel electrophoresis PVL Panton Valentine leukocidin RPP Ribosomal protection proteins SCCmec Staphylococcal cassette chromosome mec ST Sequence type tet-genes Tetracycline genes VRE Vancomycin resistant enterococci WWTP Wastewater treatment plant

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1. Antibiotic resistance

Ever since the introduction of penicillin during the Second World War antibiotics have been

viewed as miracle drugs. After the introduction of penicillin, isolation of new antibiotics

proceeded quickly and most of the major classes were isolated during the 1940s to 1960s

(169). As a result of these “miracle drugs” an accelerated decline in deaths caused by

infections was seen. For example after the introduction of sulphadiazine, deaths from childbed

fever caused by Streptococcus pyogenes decreased by 50 % in England and Wales (28).

However, today the miracle may be over due to increasing antibiotic resistance in bacteria,

including multi-resistant bacteria, which threatens the earlier effective treatment of bacterial

infections. Antibiotic resistance has been given a lot of attention during the last two decades

both within the scientific community and in public media. However, the risk of development

of resistance was put forward already in the childhood of antibiotics, or to quote Sir

Alexander Fleming, the discoverer of penicillin, from his Noble lecture in 1945 (6):

“It is not difficult to make microbes resistant to penicillin in the laboratory by exposing them

to concentrations not sufficient to kill them, and the same thing has occasionally happened in

the body.”

Just a few years later more than 50 % of the Staphylococcus aureus isolates were resistant to

penicillin (8). The trend has not been stopped, and today more than 95 % of S. aureus are

resistant to penicillin (119). The fact is that there are almost daily reports of bacteria that have

developed resistance to common antibiotics, which they were previously susceptible to.

Furthermore, to all the different antibiotic classes available, there exists at least one

mechanism of resistance, and in most cases more than one (96). The biggest problem is the

emergence of multi-resistant bacteria, which make treatment especially difficult, costly, and

in the end maybe even impossible (170). The major reason for the increasing trend is the

ongoing overuse and misuse of antibiotics worldwide. Although resistance is mainly

considered to be a clinical problem the antibiotic use is not restricted to clinical settings. At

least half of all antibiotics are consumed in the farming and agriculture setting (178). This use

has certainly contributed to the spread and increase of antibiotic resistance.

2

2. Antibiotic resistance as an environmental problem

The use of antibiotics and spread of antibiotic resistance in clinical settings is a well-

recognised problem, but antibiotics and antibiotic resistance as environmental problems and

pollutants have largely been overlooked. This is probably due to the fact that antibiotics in

non-clinical settings are generally found in concentrations well below those used

therapeutically (77;81;140). However, even low levels can sustain and/or favour development

and spread of antibiotic resistance in microbial communities. It is also important to realise that

antibiotics and antibiotic resistance are naturally occurring and play a vital role as regulatory

factors in all microbial ecosystems. In addition, several of the antibiotic resistance

determinants have primary physiological roles other than giving resistance. This means that

even introduction of a low concentration of antibiotics in an environment can have significant

effects on the stability of the ecosystem and select for antibiotic resistance. During the last

decade there has been an increasing number of reports both of antibiotic and antibiotic

resistance genes in different environmental settings. It has also been described that transfer of

antibiotic resistance genes can occur between bacterial strains that are unrelated evolutionary

and ecologically, even in the absence of antibiotics (88). The view of the role of introduced

antibiotics, antibiotic resistant bacteria and genes encoding antibiotic resistance in nature is

changing. Among others, the United Nations states in their System-wide Earthwatch that

research into how dispersal of antibiotics affects the natural bacterial community in non-

clinical settings is essential and urgent (3). The reason is that these settings can be a potential

source for spread and development of antibiotic resistance, which may find its way back into

the human population.

Antibiotics are mainly introduced into the environment through two routes, human or animal

treatment. However, it is important to realise that the same or similar antibiotics can be used

in both human and animal treatment. Figure 1 shows anticipated routes of antibiotics and

antibiotic resistance genes to the environment and potential routes back to the populations.

The antibiotics are dispersed in two ways, (1) urine and faeces, or (2) direct disposal. A

substantial part of all antibiotics consumed are not absorbed or metabolised by the body, but

excreted in their active form in the urine and faeces. The urine and faeces are transported to

wastewater treatment plants or can be used directly as manure. Direct disposal includes

addition of food additives directly to the water in fish farms or treatment of crops. One large

source is probably the disposal of outdated or remainders of antibiotics in household and farm

3

Figure 1. Potential routes for introduction of antibiotics and genes encoding antibiotics in the

environment drains. In Germany it has been estimated that 20 - 40 % of all administered antibiotics are

disposed of in this way (90). In most industrialised countries a majority of households are

connected to municipal sewers; in Sweden around 85 % and in The United States about 75 %

(2;5). Wastewater treatment plants (WWTP) are therefore probably primary routes of entry

for antibiotics into the environment. Several studies have also described the occurrence of

different antibiotics in both untreated and treated water (81). The majority of the studies

describe lower concentrations in treated water, suggesting a partial removal in WWTPs.

However, it has been indicated that biodegradation does not occur for all antibiotics in the

WWTPs (90). Thus, a main removal mechanism is probably through sorption to sludge (140).

In most modern wastewater treatment facilities, the sludge is processed to biosolids or applied

directly as fertilisers. In both treated and untreated wastewaters there are higher numbers of

resistant bacteria and genes encoding antibiotic resistance compared to surface water (81).

The occurrence of multiresistant bacteria, e.g. vancomycin resistant enterococci (VRE), has

also been described in WWTPs (73;111). One study performed on Swedish sewage showed

relatively high prevalence of VRE, which was unexpected due to the low prevalence of VRE

in the human and animal population in Sweden (73). Several studies have pointed out that

WWTPs can have favourable environmental conditions that increase the likelihood of

4

antibiotic resistance gene transfer. The potential spread of specific genes encoding antibiotic

resistance in wastewater by horisontal gene transfer has also been shown (54;122;139). It is

therefore essential to perform more extensive studies concerning the occurrence of antibiotic

resistance and how it is affected over time and by different treatment steps in WWTPs.

3. Wastewater treatment in Sweden

Sweden was early in implementing wastewater treatment, and there was a large production

boom during the 1960 - 1970s because wastewater emission into freshwaters was causing

eutrophication, mainly due to the large amount of phosphorous. Today there are over 2000

publicly owned WWTPs in Sweden. During the 1990s it was realised that nitrogen in

wastewater also was an environmental problem causing eutrophication in coastal areas.

Therefore, during the last few years’ nitrogen removal in the Swedish WWTPs has been

developed drastically. Three different treatment techniques, in different combinations, are

implemented in most WWTPs today; (1) Mechanical treatment; large and heavy particles

and fats are removed through coarse bar screens, sand traps and pre-sedimentation, (2)

Chemical treatment; removal of phosphorus through precipitation by addition of chemical

compounds, e.g. iron and aluminium, (3) Biological treatment; microorganisms, foremost

bacteria, utilised for removal of the remainders of organic compounds and nitrogen. In all

steps, sludge is collected and it is estimated that the WWTPs in Sweden annually produce

230,000 tons of sludge. The sludge is rich in nutrients, but may contain biological and

chemical pollutants. Although faecal indicator bacteria, such as Escherichia coli, coliform

bacteria and Enterococci spp., are measured for indication of bacterial content, there is no

direct treatment step focusing on removal and disinfection of bacteria and possible pathogens

today. (154;177)

3.1 The WWTP Ryaverket, Gothenburg, Sweden

The municipal WWTP Ryaverket in Gothenburg city is one of the largest in Northern Europe,

receiving wastewater from nearly 830,000 person equivalents, with an average daily flow of

350,000 m3. It was taken into operation in 1972 and was rebuilt for biological nitrogen

removal during 1995 – 1997. The wastewater is collected from five municipalities; Ale,

Gothenburg, Härryda, Kungälv, Mölndal and Partille, and around 10 % of the total

wastewater are from industry, health-care and public administration.

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Like all other treatment plants in Sweden, Ryaverket utilises mechanical treatment, but also

implements both chemical and biological treatment. In addition to removal of phosphorus, the

plant is designed for biological nitrogen removal, utilising pre-denitrification in a non-

nitrifying activated sludge system, and post-nitrification in a trickling filter. An overview of

the complete treatment process at Ryaverket can be viewed in Figure 2. After mechanical

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treatment the wastewater at Ryaverket is transferred to the activated sludge basins. In the

activated sludge, bacteria is utilised for oxidation of organic particles. The first part (40 - 60

%) of the basins is anoxic which forces the bacterial community to use NO3 for respiration

resulting in NO3 being converted to N2, which is released directly to the atmosphere. The

second part of the basins is aerobic, resulting in organic particles being oxidised through

aerobic respiration. After passing the activated sludge basins, the water is pumped into

sedimentation basins, where phosphorus aggregates and sludge are allowed to settle.

Phosphorus is precipitated with iron sulphate, which is added prior to the activated sludge.

The collected sludge is pumped back to primary settling in the mechanical treatment, while

the water is separated, with about 50 % released at the Rya nabbe in the estuary of Göta

River. The remaining water is mixed with ammonium rich reject water from dewatered

sludge, collected mainly from primary settling, and recirculated in the system through

nitrifying trickling filters (NH4++ 2 O2 → NO3

- + 2H+ + H2O). The trickling filter is filled

with a plastic crossflow material that provides a large surface for bacterial biofilm growth.

After the trickling filters, the water is pumped back into the anoxic phase of activated sludge.

In 2004, Ryaverket received on average Ptot of 4.4 mg l-1 and Ntot of 27.1 mg l-1 and released

Ptot 0.4 mg l-1 and N2 10 mg l-1. The system has a hydraulic retention time of ~8 h and the

activated sludge system has a solid retention time of 2-4 days. (4;138)

3.2 Bacterial communities and pathogens in municipal WWTPs

Bacterial communities play a vital role in wastewater treatment, since they are the ones

responsible for most of the carbon and nutrient removal in WWTPs (167). In activated sludge,

bacteria are used for oxidation of organic particles and the transformation of nitrate and nitrite

to nitrogen (nitrification and denitrification). The bacteria in biofilms are commonly used to

transfer ammonium to nitrate (nitrification).

There is no such thing as a universal bacterial flora for all WWTPs, instead studies have

shown a great difference in population structure between WWTPs (20;167). The structure of

the bacterial community is probably affected to a high degree by operational parameters and

quality/composition of the wastewater. In Ryaverket it has been shown that the ammonium

content largely affected the nature of the bacterial biofilm in the trickling filters in terms of

thickness, structure, biomass content and community structure (105). However, within a

WWTP the bacterial structure is often stable, at least over a 6-month period (20). Molecular

typing has shown that the community has a high diversity, with high numbers of cells and

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different bacterial species (20;168). A total of 13 bacterial phyla out of the 36 described have

been detected in WWTPs. The Proteobacteria is the most abundant phylum, constituting for

up to 50 % of the population in WWTPs (168), and in the aeration basins in activated sludge

they can account for up to 70 % (166). It is foremost α- β- and γ- Proteobacteria that are

detected, with the β-Proteobacteria being the most frequent. Furthermore, in activated sludge,

it has been shown that the β-Proteobacteria has high diversity (168). Cultivation experiments

have shown that Enterobacteriaceae, Aeromonas spp. and Acinetobacter spp. can be

commonly isolated (166). Besides Proteobacteria, other common phyla are Actinobacteria,

Bacteroidetes, Chloroflexi and Planctomycetes.

The nitrifying and denitrifying bacteria in WWTPs have been paid a lot of attention due to

their importance for reducing nitrogen levels. However, the bacteria responsible for

denitrification in WWTPs are still largely unknown, but a majority probably belong to β-

Proteobacteria (167;168). Alcaligenes spp., Pseudomonas spp., Methylobacterium spp.,

Bacillus spp., Paracoccus spp. and Hypohomicrobium spp. have all been isolated through

their denitrifying ability, but it is not clear if they are representative for the in-situ flora. On

the other hand the bacteria responsible for the nitrification process are better described.

Nitrosomonas europea and Nitrobacter spp. are commonly identified in WWTPs all over the

world as the main ammonium and nitrite oxidisers, but Nitrosomonas eutropha, Nitrosomonas

marina, Nitrococcus mobilis, and phylogentic lineages of uncultured representatives are also

common. In Ryaverket it was shown that the most common ammonium oxidising bacterium

was Nitrosomonas oligotropha (104).

Besides the “normal” flora in WWTPs, a large diversity of different pathogens has been

described (Table 1) (57;79;93;125;141;144;175), but the levels of pathogens are lower than

those of the non-pathogenic bacteria (93). Studies showed that pathogens were detected to a

higher extent in incoming water compared to outgoing, and that the treatment processes

reduced their concentrations. E. coli, coliforms and Enterococcus spp. are often used as

indicators for bacterial concentration and studies have shown that total coliforms was reduced

by up to 6 log10 units, E. coli, 1-4 log10 units, while Enterococcus spp. was reduced 0.5-3

log10 units (47;48;79). One study focusing on Clostridium perfringens showed a reduction by

1-2.5 log10 units, and the authors proposed that pathogenic bacteria might survive better than

the indicator bacteria (175). Studies have also shown that the treatment process reduced the

8

number of human viruses; astroviruses, 2-3 log10 units and norovirus, 0-2.5 log10 units

(92;121). However, most of the pathogens were never completely removed (Table 1).

Table 1. Detected pathogens in wastewater Untreated Aeromonas hydrophilia Bacillus cereus

Campylobacter coli Campylobacter jejuni Clostridium perfringens Enterococcus faecalis

Enterotoxigenic Escherichia coli Klebsiella pneumoniae Escherichia coli O157 Pseudomonas aeruginosa Listeria monocytogenes Salmonella spp.

Shigella flexneri adenoviruses astroviruses enteroviruses Noroviruses Helminth ova* Giardia cysts** Cryptosporidium spp.**

Treated Aeromonas hydrophilia Campylobacter coli

Campylobacter jejuni, Clostridium perfringens Enterococcus faecalis Klebsiella pneumoniae Listeria monocytogenes Salmonella spp.

Shigella flexneri adenoviruses astroviruses noroviruses Giardia cysts**

*Parasitic worm, **Protozoa

4. Staphylococcus aureus

The genus staphylococcus was first described in 1880 (123) and is gram-positive cocci of 0.8-

1.0 μm in diameter. Under the microscope the staphylococci have a characteristic grape-like

appearance, due to division in several plains (107). Today, more than 40 different

staphylococcal species have been described (1), and several of them are pathogenic to humans

and/or animals (71). Staphylococcus aureus is by far the staphylococci species that is most

pathogenic to humans and is also the best studied. It can be easily separated from most other

staphylococci through its ability to coagulate plasma, thanks to production of coagulase. The

other staphylococci are therefore often referred to as coagulase-negative staphylococci

(CoNS). The reason for the higher virulence of S. aureus is probably due to the wide variety

9

of cell-wall associated proteins and secreted toxins it possesses (22;103). This also gives S.

aureus its capability of causing a large diversity of both benign and lethal infections in

humans and animals (Table 2). (136;176) In many parts of the world S. aureus is the most

Table 2. Diseases caused by S. aureus Skin and Invasive infections Others soft tissue infections Botryomycosis Endocarditis Gastroenteritis Carbuncles Osteomyelitis Toxic shock syndrom Cellulitis/erysipelas Pneumonia Folliculitis Sepsis Fruncles Septic arthritis Impetigo Sinusitis Pyomyositis Urinary tract infection Scalded skin syndrome Stye

frequent cause of hospital-acquired infections. In the USA 19 % of over 3 million bacterial

isolates from inpatients were determined to be S. aureus, making it the most prevalent species

(152). Besides being a common hospital pathogen, S. aureus causes infections in the

community; in the USA it was the second most prevalent species from outpatient specimens.

The community-acquired infections are generally minor skin infections, but there are cases of

severe skin-infections and lethal haemolytic pneumonia (101). Furthermore, the total number

of infections caused by S. aureus, both in the community and clinical settings, has increased

steadily over the past decades (103).

The duality of S. aureus is that it is also a human commensal and has been described to be

carried by ~30 % up to 70 % of the population (126). Longitudinal studies have distinguished

three different carriage patterns; persistent, intermittent and non-carriage. However, some

researchers make a further distinction; occasional and intermittent. Studies have shown that

12 - 30 % of the population are persistent carriers, 16 - 70 % occasional/intermittent carriers

and 16 – 69 % are non-carriers. The large variation in percentages is due to differences in the

studies, e.g. culture techniques, the population (carriage is connected to age, sex and

ethnicity) and interpretation guidelines. The persistent carriers are colonised by a single strain,

while intermittent carriers can carry different strains over time. A fit between host and the

carried S. aureus is essential, because persistent carriers are resistant to colonisation with new

strains (126;176). The genetic diversity of carriage strains of S. aureus is high, but no clear

association of genotypes and different host attributes, such as sex, age or medical history, is

10

evident (143). However, some genotypes of S. aureus are more prevalent among carriers. The

most frequent carriage site is the anterior nose, but the exact position is still unclear. Cross-

sectional surveys performed on healthy adults have reported nasal carriage rates of ~27 %.

Besides nasal carriage, S. aureus can often be isolated from the skin, perineum and pharynx.

(126;176) The risk of acquiring a S. aureus infection increases if you are a carrier. Studies

have shown that for nasal carriers the relative risk for a surgical infection increases with 1.3 -

7.0 and 80% of those with community acquired skin lesions were nasal carriers (162;176).

However, among non-carriers that have acquired exogenous S. aureus bacteraemia the

mortality is fourfold higher compared to nasal carriers (176).

4.1 Typing of S. aureus

Because of S. aureus status as one of the most common causes of bacterial infections, and as a

commensal, it is important to understand its occurrence and distribution. It is also significant

to identify if there are specific isolates or major clusters responsible for infections and

colonisation (161). If there are one or a few strains, this indicates that these have genotypic

and/or phenotypic factors that give a selective advantage. On the other hand, if major clusters

are responsible, there should be factors that are common in the population. Accurate typing

methods are therefore necessary for S. aureus, to identify different strains and elucidate their

relationship. An optimal typing method should have high stability, reproducibility, typeability

and discriminating power. Furthermore, it would be advantageous if it is user friendly, rapid

and has a low cost. Several different techniques for typing, both phenotypic and genotypic,

have therefore been developed for S. aureus over the past four decades (36). In the beginning,

isolates were distinguished based on phenotypic properties. Common typing methods were

antibiotic resistance typing, phage typing (resistance to a standard set of phages), serological

typing (differences in antigenicity), biotyping (metabolic capabilities), bacteriocin typing and

resisto-typing (resistance to various chemicals). These methods have in common that they are

all limited in reproducibility, typeability and/or discriminatory power. The reason is that the

expression of genes, giving rise to the resulting phenotypes, is often dependent on

environmental factors, which means that unrelated strains can share phenotypic traits. The

methods are also inadequate for evolutionary studies, since the genes responsible for

phenotypic traits tend to evolve quickly or may be subjected to horisontal gene transfer.

(36;39) All the disadvantages of phenotypic typing methods have led to the development of

genotypic methods, such as plasmid analysis, southern hybridisation analysis, e.g. ribo typing

(RT) and binary typing (BT); PCR-based techniques, e.g. random amplified polymorphic

11

DNA (RAPD), repetitive element sequence based-PCR (rep-PCR), amplified fragment length

polymorphism (AFLP); pulse field gel electrophoresis (PFGE), and sequence typing, such as

spa typing and multilocus sequence typing (MLST) (36). Based on the literature, the most

used methods today are PFGE, MLST and spa typing (32).

4.1.1 Pulse field gel electrophoresis

PFGE is the most frequently used typing method, and many have embraced it as the golden

standard for studying outbreaks and hospital transmissions. The reason is that PFGE is the

most discriminative of the genotypic methods, due to the fact that it reflects genetic events

that occur during a short period of time. PFGE is based on the fragmentation of the whole

bacterial chromosomal DNA using restriction enzymes, often SmaI. The fragmented DNA is

then separated on an agarose gel using an alternating voltage field. This result in a unique

band pattern, which is analysed with specially designed computer software, often using the

Dice coefficient and unweighted pair grouping. However, for long-term surveillance and

evolutionary studies, PFGE may be inadequate, due to the instability of the restriction sites

over a prolonged period of time, and that minor genetic alterations can lead to major changes

in the band pattern. The comparison of results between laboratories is also difficult or even

impossible due to poorly harmonised protocols, the lack of a standardised nomenclature and

the fact that the analyses of patterns are subjective. Furthermore, the PFGE is both time and

cost consuming. (33;36;39)

4.1.2 Multilocus sequence typing

MLST is used for typing of almost all major human bacterial pathogens including S. aureus,

and more protocols are in the pipeline (159). It is based on sequencing of several

housekeeping genes; for S. aureus typing sequences of approximately 500 bp are determined

for seven genes; arc, aroE, glpF, gmk, pta, tpi, and ygiL. The sequences are compared for

each gene and different sequences are assigned distinct alleles. The alleles for all seven genes

are then used to create an allelic profile and every specific profile is designated as a sequence

type (ST). An S. aureus isolate assigned to ST8 has an allelic profile that looks like 3-3-1-1-4-

4-3, while an isolate designated ST5 has the profile 1-4-2-4-12-1-10. Using the Based Upon

Related Sequence Types (BURST) algorithm, related STs can then be joined together in

clonal complexes (CC). An ST is grouped within the same CC when at least five out of seven

genes have identical gene sequences/alleles. MLST has been shown to be an excellent method

12

with high reproducibility and is suitable for population and evolutionary studies. However, it

is also expensive and laborious. (32;33)

4.1.3 spa typing

spa typing, introduced in 1996 by Frenay et al. (44) has a discriminating power that lies

between MLST and PFGE, and in contrast to these methods, has been described to be suitable

for studying both evolutionary events and hospital outbreaks. This fact has probably

contributed to its increasing popularity over the last couple of years. Its simplicity, time

efficiency and lower cost relatively to PFGE and MLST, have probably also contributed to the

popularity. These advantages are due to that spa typing is a single locus sequence typing

method, using only the polymorphic region X of the protein A gene, found exclusively in S.

aureus. The typing is based on that the region X constitutes a number of repeats of 24 bp in

length. The diversity of the region is due to the deletion and duplication of the repeats, but

also in some cases point mutations. S. aureus strains are divided into spa types based on the

number and arrangement of these repeats and on which repeats that are identified. As an

example of spa types, one can compare t008 and t064 that have the same number of repeats,

but differs in the sequence of the fourth repeat (table 3). It should be pointed out that because

Table 3. Examples of spa types and arrangement of repeats spa type Repeat succession Sequence of mismatching repeats t008 11-19-12-21-17-34-24-34-33-25 r21 =AAAGAAGACAACAACAAGCCTGGC t064 11-19-12-05-17-34-24-34-33-25 r05 =AAAGAAGACAACAAAAAGCCTGGC

spa typing is more discriminating than MLST several different spa types can correspond to a

single ST, but remain within an assigned CC. Furthermore, using the typing software Ridom

StaphType it is possible to perform cluster analysis using the algorithm based upon repeat

patterns (BURP). (32;33)

A problem with spa typing is that studies have shown that spa types on occasion violate

MLST STs. This violation can occur in two ways, either that different STs, belonging to the

same CC, have the same spa type, or that closely related spa types are found in distant CC

(59). The reason for this problem is probably intergenomic recombination events of the spa

gene. However, these events take place only rarely, and the spa gene has been shown to have

both long-term in vitro and in vivo stability (86). A further disadvantage is that two parallel

nomenclatures exist today, based on the works of Harmsen et al. (63), as exemplified in table

13

3, and Koreen et al. (86), making it difficult to compare studies. Generally, the Harmsen

system is more commonly used in Europe, while Koreen is more accepted in the U.S.A. One

large advantage of using spa typing is that a spa server, http://spaserver.ridom.de exists, and

this is probably the world largest typing database for S. aureus. At the time of writing this

thesis, the database lists more than 4700 spa types combined from over 270 different repeats

based on over 78 000 strains from 61 countries. Furthermore, this spa server is freely

accessibly through the Internet and all spa types and repeat sequences can be downloaded.

Submission of new repeats and spa types is possible for everyone, and the server is

synchronised with the typing software Ridom StaphType (Ridom GmbH, Würzburg,

Germany).

4.2 S. aureus in wastewater and the environment

The occurrence of S. aureus in the environment is scarcely studied, although failed attempts

to cultivate S. aureus from municipal wastewater, drinking water and river surface water have

been made (145;164). However, it was possible to isolate S. aureus from hospital wastewater

(145). There have also been attempts to detect S. aureus using molecular methods in samples

collected from municipal WWTPs, both from treated and untreated wastewater, but S. aureus

was not detected (93;144;146). Taken together, these results indicate that S. aureus has low

prevalence in wastewater. However, there are indications that S. aureus can be viable in

wastewater and is more resilient than earlier believed. Cultivation experiments have shown

that S. aureus can be sustained on culture plates supplemented with wastewater for up to 80

days, but they were not able to grow (45). Furthermore, one study made observations

indicating that S. aureus can enter a viable but un-cultivatable state in wastewater (122). This

study also described that S. aureus in vitro has the capability of transferring plasmids,

harbouring the aminoglycoside resistance genes aac(6´)-Ie+aph(2´´) in wastewater. In

addition, other groups have been able to cultivate S. aureus from bioaerosols in WWTPs, at

least during the winter period (43). Studies have also indicated that S. aureus can survive the

treatment process in a WWTP, because an increase in prevalence of S. aureus infections has

been reported among residents living in proximity to areas fertilised with sewage sludge (97).

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5. Methicillin resistant S. aureus (MRSA)

MRSA, which is resistant to all clinically used β-lactam antibiotics, is the reason for

increasing numbers of S. aureus infections in hospitals and in the community. Besides higher

infection rates MRSA is also responsible for higher cost and mortality in the society.

Methicillin, a semi-synthetic penicillin, originally named celbenin, is no longer in use, but the

definition MRSA remains. Methicillin was introduced in 1959 as a way to battle the

increasing number of β-lactamase producing S. aureus strains. However, just two years after

the introduction the first case of “celbenin” resistant S. aureus was reported (75), and in 1967

the first reports of multi-resistant MRSA came, in Australia, Denmark, England, France, India

and Switzerland (51). During the 60s and 70s a swift dissemination of a specific multi-

resistant clone, the phage type 83A, occurred in Europe. In Denmark 15 % and in Zürich,

Switzerland, 20 % of all clones belonged to this phage type, but in the late 70s and early 80s

the occurrence decreased to 2 % in Denmark and 3 % in Zürich. The reason for the decrease is

unknown, but it was probably influenced by changes in antibiotic prescriptions and control

policies. In the 1980s, when rapid increases in gentamycin resistant MRSA was reported in

USA, United Kingdom and Ireland, the concern for MRSA was renewed (51). Today, MRSA

has risen to one of the most frequent causes of hospital infections worldwide. In the USA ~34

% of all S. aureus were described as MRSA in 1998 – 2002; Central Europe 9 %, in 1995;

Europe 26 % and Latin America 35 %, in 1997-1999; South Africa 40 %, Japan 67 % and

Australia 22 % in 1998-1999. However, in Europe there are big geographical differences (Fig

3) with less than 3 % in Scandinavia, Iceland and Netherlands compared to over 30 % in

Figure 3. The prevalence of MRSA among blood

isolates of S. aureus in Europe 2006 (7)

15

southern Europe, UK and Ireland. One study compared over 3000 MRSA isolates from Asia,

Europe, Latin America and North America using different typing techniques (36). It was

found that six clones of MRSA were spreading worldwide suggesting that only a few

epidemic clones exist. However, there were also clones, with high diversity, dominating in a

single area or hospital and from only one or a few patients. In contrast to the 70s and 80s the

increasing trend is not due to a specific clone, and it appears not to secede any time soon.

Furthermore, the increase in MRSA includes the low prevalence areas, Scandinavia, Iceland

and Holland, e.g. in Sweden there were 1128 cases of MRSA blood isolates in 2007 compared

to 327 cases in 2000 (155).

5.1 β-lactams and resistance mechanisms to β-lactams

The β-lactam antibiotics are extensively used clinically, and in Sweden they constitute ~50 %

of the antibiotics administered in the community and hospital care (155). They are broad-

spectrum bactericidal agents and have low toxicity to eukaryotes (49). Furthermore, it is the

largest class of antibiotics and most of them are semi-synthetic compounds. The class is

defined by the β-lactam ring in their chemical structure (Fig 4) and is roughly divided into

four groups: penicillins (narrow to extended spectrum), cephalosporins (1st - 4th generation),

carbapenems and monobactams. The exact mechanism by which the β-lactams kill the

bacteria is not completely understood, but they affect the cell wall biosynthesis (62;171). The

rigidity of the bacterial cell wall comes from peptidoglycan, a complex of covalently cross-

linked peptide and glycan strands (Fig 5A). The cell wall synthesis includes ~30 enzymes and

is performed in three stages. β-lactams inhibit the third and final stage, the completion of the

cross-link, performed by transpeptidases. The inhibition is due to that β-lactams act as

pseudosubstrates and acylate the active site of the transpeptidases (Fig 5B), which in the end

leads to cell-lysis. The transpeptidases are therefore also termed penicillin-binding proteins

(PBPs). The PBPs are found in all bacteria and in addition to the transpeptidases, there are

other related PBPs.

Figure 4. The β-lactam ring

16

Figure 5. The inhibition of cell-wall synthesis by β-lactams A. Covalent Cross-linking of

peptidoglycan chains B. Binding of penicillin to transpeptidases (penicillin-binding protein). Modified from Walsh (171).

Bacteria have evolved three major ways in which they avoid the bactericidal effect of β-

lactam antibiotics: (1) Production of β-lactamases, which are enzymes that hydrolyse the β-

lactam ring, rendering the antibiotic inactive, (2) Altered PBPs with low affinity for β-

lactams, (3) Lowered or lack of expression, due to mutations, of outer membrane proteins in

gram-negative bacteria, which leads to difficulty for the β-lactams to access the PBPs (12).

The first described resistance to β-lactams was the production of penicillinase by E. coli, and

penicillinase was also the first resistance mechanism described for S. aureus. To date, over

530 β-lactamases have been reported and the genes encoding them (bla genes) are located on

either the bacterial chromosome, plasmids, transposons or integrons (12;180). There are ways

to overcome the β-lactamases; (1) finding inhibitors/inactivators, and (2) to develop or find

new β-lactam antibiotics that are not hydrolysed or hydrolysed poorly by the β-lactamases.

The gram-positive bacteria have remained susceptible to inhibitors (16), but the introduction

of semi-synthetic β-lactams, such as methicillin, cephalosporins and carbapenems, led to the

evolution of PBPs with low or no affinity for β-lactams. For gram-positive bacteria, altered

17

PBPs are the most important resistance mechanism for β-lactams, while the gram-negative

rely more on β-lactamases (12;16). The mecA gene, responsible for β-lactam antibiotic

resistance in MRSA, is the most described and studied example of alternative PBP.

5.2 The mecA gene and the staphylococcal cassette chromosome mec (SCCmec)

The resistance to β-lactams in MRSA is the result of the 2.1 kb mecA gene that encodes a 78

kDA PBP dubbed PBP2a (alternatively PBP2’) with low affinity for binding the β-lactams

(17;32). Compared to the four native PBPs, the PBP2a appears to be a relatively poor

transpeptidase, taking over only after the others have been saturated, and it also requires a

native transglycosylase to function. The mecA gene is regulated by the neighbouring genes

mecI and mecRI/ΔmecRI. The mecI gene codes for the repressor and mecRI/ΔmecRI codes for

a trans-membrane β-lactam sensing signal transducer (32). Besides mecI and mecRI, other

genes can influence the expression of mecA, for example blaRI and blaI, which are analogous

to mecI and mecRI, or the factors essential for methicillin resistance (fem) genes, femA-F,

femR and femX, that encode peptidoglycan modifying enzymes (17). Furthermore, genes that

are part of the native genome and partake in cell-wall biosynthesis and turnover, most likely

also play a role for β-lactam resistance (109).

The only vector identified for the mecA gene is the staphylococcal cassette chromosome mec

(SCCmec), which has not been identified in any other bacteria except staphylococci (61). The

SCCmec appears to be a well-developed vessel for genetic exchange, believed to occur

through horisontal transfer, but the exact mechanism is unclear. The fact that it is transferred

frequently is supported by species independent conservations (61). The distribution of

SCCmec among S. aureus strains is not even, instead they are found more frequently in five

out of eleven identified MLST CC (40). The reason for the uneven distribution is not known,

but it may be due to that these strains are more virulent and selection pressure from antibiotic

treatment may have forced them to retain SCCmec. Compared to other genes in the S. aureus

genome the SCCmec appear to have been acquired relatively recent (69).

The SCCmec is introduced in the S. aureus genome at a specific site (attBSCC) at the 3’ end of

an open reading frame with unidentified function (orfX) (33;34;61). The specific integration,

and excision, of SCCmec into the genome is executed by the cassette chromosome

recombinases (ccr), of the invertase/resolvase class, which is found in all SCCmec. In MRSA

three genes have been identified that code for the ccr, ccrA and ccrB with four allotypes, and

18

ccrC. The mecA gene itself is located on a structure termed the mec complex. Besides mecA,

the genes responsible for regulation of transcription, mecI and mecRI/ΔmecRI, as well as

insertions sequences, IS431 and IS1272, are found in this complex. Five different classes (A –

E) of the complex have, to date, been defined based on the combination of mecI, mecRI,

ΔmecRI and insertion sequences (Table 4). Of these the classes, A - C are the most common.

Table 4. The classes of the mec complex Class Structure A mecI-mecRI-mecA-IS431 B IS1272-ΔmecRI-mecA-IS431 C IS431-ΔmecRI-mecA-IS431 D ΔmecRI-mecA-IS431 E ΔmecRI-mecA-IS431

In addition, to the two essential components, the ccr- genes and the mec-complex, SCCmec

contain junkyard (J) regions. These J-regions are made up of non-essential components, but

additional resistance genes can be found here. There are three J-regions; (1) J1, between the

genome right junction and the ccr genes, (2) J2, between the ccr and the mec complex, and

(3) J3, from the mec complex to the orfX. Based on the composition of the ccr genes and the

mec complex, the SCCmec is divided into seven types, ranging in size from 20.9 to 66.9 kb

(Fig 6) (32), and based on variations in the J-regions these types can be further divided into

subtypes. The SCCmec types have been named using roman numerals, I-VII, based on the

Figure 6. Comparison of the SCCmec types I-VII described in MRSA Deurenberg and

Stobberingh (32). order in which they were described. Among MRSA isolates worldwide, the SCCmec IV

dominates and is at least twice as common as any other type. The SCCmec IV also dominates

19

in Swedish MRSA strains (18). Carrying SCCmec is thought to impose an energetic cost for

the staphylococci, but the type IV does not to impose a cost in terms of growth rate, cell yield

or number of cells produced per mole ATP consumed (94). This can explain why type IV is

more common than the other types. The type IV is also the most variable with eight subtypes,

IVa-IVh, and these variations are largely believed to be a result of higher mobility of type IV

compared to the other types (32). The SCCmec I, IV, V and VII do not generally carry any

other resistance genes except the mecA, but the types II and III on the other hand cause multi-

resistance, due to integration of plasmids. Besides carrying resistance genes in the SCCmec

MRSA can harbour resistance genes in other sites of the genome and on plasmids. (32;61).

The origin of mecA and SCCmec is not known, but there are data indicating that they

originated from CoNS (51;61). The leading theory is that SCCmec elements have been

introduced several times in S. aureus, due to the genetic difference of MRSA strains and that

the same strains harbour different SCCmec (137). The suggested number of times that

SCCmec has been introduced in S. aureus is at least 20, while the same number for S.

epidermidis is around 50 times (34).

5.3 Hospital- and community-associated MRSA

MRSA was traditionally considered just as nosocomial pathogens, but this changed when a

novel MRSA was isolated in 1993 among aborigines in Western Australia, not previously

exposed to western healthcare (51). After this first report came several more about

community-associated MRSA (CA-MRSA), mainly occurring in groups with high physical

contact. Today, CA-MRSA is described worldwide in all type of settings, and is primarily

associated with skin and soft tissue infections. Furthermore, the trend is that CA-MRSA

strains are replacing the more traditional hospital-associated MRSA (HA-MRSA) strains (32).

In the USA, >75 % of the MRSA cases are defined to have CA background and in

Scandinavia the CA-MRSA is more prevalent then the HA-MRSA (32;148). No universal

definition of what a CA-MRSA really is exist, but they are generally considered to be strains

isolated in outpatient settings or from a patient within 48 hours of hospital admission, with no

history of previous MRSA infection/colonisation or contact with healthcare settings the

previous year (32;37). In addition, the patients should have no permanent catheters or medical

devices piercing the skin. CA-MRSA is more genetically diverse compared to HA-MRSA,

and appear generally to carry SCCmec IV. HA-MRSA generally harbours SCCmec I, II and

III and is more resistant compared to the CA-MRSA, which mainly shows β-lactam

20

resistance. However, the CA-MRSA is more virulent, probably due to the presence of

additional virulence factors. One such factor can be the genes lukS-PV and lukF-PV, which

encode the subunits of Panton Valentine leukocidin (PVL). PVL is a cytotoxin that causes

necrosis and leukocyte destruction through pore formation (21). It is also the most consistent,

of the transferable toxins, in CA-MRSA. Among CA-MRSA harbouring SCCmec IV, PVL

has been found in 40-90 % of the isolates, while the corresponding number among SCCmec I

and II is <5 %. However, there is evidence suggesting that PVL is not a major virulence factor

(110;165).

HA-MRSA mainly appears to constitute a handful of highly epidemic clones that share a

genetic background with epidemic Methicillin-sensitive Staphylococcus aureus (MSSA)

(32;34), suggesting that their successful proliferation lays in their genetics rather than that

they are MRSA. Originally, it was believed that CA-MRSA was spread from the hospital to

the community, but when applying PFGE and MLST it was shown that the CA-MRSA were

genetically distinct from the main HA-MRSA (113;137). It was also shown that CA-MRSA

had a genetically distinct background in distinct geographic areas, or that they can originate

from many different backgrounds in the same area. However, CA-MRSA clones that are more

frequent than others, have been identified and they are rapidly spreading worldwide (34;60).

They belong mainly to the MLST ST8, ST30 and ST80, which are the same STs that are

found most frequently in MSSA isolated from the community. Although the CA-MRSA are

increasing they do not dominate in the community, as the HA-MRSA do in hospitals in some

parts of the world, e.g. Japan, U.S.A and U.K. (34;80).

5.4 MRSA in animals

Besides being a problem in human medicine, MRSA is an increasing problem in veterinary

settings (132). MRSA was first isolated in 1972 from cows with inflammation of the udder,

and has since then been identified in a variety of domestic animals (95). The MRSA from

household pets is generally identical to the human HA-MRSA, indicating that the animals

have been colonised through human contact. However, MRSA isolated from equines and pigs

have been described to be distinct from the human MRSA (32;95). In the Netherlands, it was

found that 39 % of the pigs carried MRSA, and it has been shown that persons living or

working on farms (particularly pig farms) have an increased risk of being colonised with

MRSA (98). Therefore, it is possible that animals and animal farms can be significant

reservoirs for known and new MRSA clones.

21

5.5 β-lactams in wastewaters

β-lactam antibiotics, foremost penicillins and cephalosporins, have been described to occur in

untreated and treated sewage from WWTPs (25;56;173;174), but concentrations were

generally low, measured in ng - μg per litre. One study focusing on WWTPs in Sweden,

showed that penicillins and cephalosporins could not be detected in a majority of samples

(100). Furthermore, the β-lactams were reduced in the treatment process at WWTPs by up to

100 % and detected with far lower frequency in treated sewage (56;173;174). However, the

removal varies and the cephalosporin Cefalexin varied in reduction between 9 and 89 %

between different WWTPs (56). In addition, the cephalosporins were generally found in

higher concentrations compared to the other groups, and appeared to be more resilient to the

wastewater treatment, i.e. found in higher degree and concentration in outlet (56;173;174).

The penicillins on the other hand were only occasionally detected, and in very low

concentrations (23;56;100;173;174). In surface waters, β-lactams were rarely detected and

when they occurred it was at concentrations well below those in wastewater (23;25;174). The

reason why β-lactams are not persistent in aquatic environments is hydrolysis of the

chemically unstable β-lactam ring (25).

5.6 Methicillin-resistant staphylococci and other ß-lactam resistance in wastewater

and other environments

MRSA has not been isolated from wastewater, but methicillin-resistant CoNS has been

isolated from hospital wastewater (145;164). In addition, the mecA gene has been molecularly

detected in hospital wastewater, but not in municipal wastewater, surface water or agriculture

soil (including soil fertilised with wastewater) (108;145;164). However, other ß-lactam

resistant bacteria and genes encoding ß-lactam resistance occur frequently in wastewater.

Bacteria resistant to penicillins, amoxicillin and/or ampicillin have been isolated from both

treated and untreated wastewater in several studies (30;41;46;52;53;131;147;181). These

studies generally focused on isolation of Acinetobacter spp., Enterobacteriaceae,

Enterococcus spp. and/or Pseudomonas spp., and described 10 % up to 100 % of the isolates

as penicillin, amoxicillin and/or ampicillin resistant. In addition, many of the isolates were

described to be resistant to cephalosporin and/or resistant to more than one class of antibiotic.

It has also been shown that ESBL-producing E. coli and Klebsiella spp. frequently occur in

wastewater (114;130). The question of whether WWTPs selects for a higher prevalence of

antibiotic resistance or not is still unanswered. Some studies have shown more extensive and

higher frequency of antibiotic resistance in treated wastewater (41;46;147), while others have

22

described the opposite (53;131;181). One study focusing on quantification of the ß-lactamase

gene blaTEM group showed that the concentration of the gene group were higher in WWTPs

compared to natural environments, but that the wastewater treatment reduced blaTEM

concentration, both related to water volume and total-DNA, by ~0.5 log10 unit (91). However,

if related to total number of 16S rRNA genes an increase, by ~1 log10 unit, was observed in

treated compared to untreated wastewater.

Besides wastewater ß-lactam, including cephalosporin, resistant bacteria have been isolated

from surface water, soil and wetland sediment (10;38;58;172), and in a polluted estuary, ß-

lactamases genes were frequently detected (66). It has also been shown that anthropogenic

influence leads to an increased prevalence of ß-lactam resistance (24;38;91;172).

6. Aminoglycoside antibiotics

The aminoglycosides are rapid broad-spectrum bactericidal antibiotics, which are naturally

produced by Streptomyces spp. or Micromonospora spp. (74;87). Examples of commonly

used aminoglycosides are gentamicin, tobramycin and streptomycin. They are primarily used

to treat infections caused by aerobic gram-negative bacteria, but are also active against

Staphylococcus spp., Enterococcus spp. and some Mycobacteria spp.. However, their

usefulness is limited by their serious toxicity, e.g. nephrotoxicity and ototoxicity. The class is

characterised by a backbone structure consisting of an aminocyclitol ring, which in most

clinically used aminoglycosides are streptamine or 2-deoxystreptamine (Fig 8). The exception

Figure 8. The backbone structure of aminoglycosides. Jana and Deb (74)

is streptomycin, which has a streptidine molecule. The ring in all aminoglycosides is saturated

with amine and hydroxyl substitutions, and connected to amino sugars (aminoglycosides)

through glycosidic linkages. The bactericidal effect of aminoglycosides is primarily due to

23

binding to the 30S ribosomal subunit rendering the ribosome unavailable for translation,

which results in halting protein synthesis. In addition to their direct effect on protein

synthesis, they cause membrane damage through changed membrane composition and

permeability, altered cellular ionic concentrations and disturbance of the DNA and RNA

synthesis.

6.1 Aminoglycosides in wastewater

Occurrence of aminoglycosides in wastewater and other environments is scarcely studied, due

to the fact that the antibiotics are not persistent in the environment (72). Compared to many of

the other antibiotic classes, they are more readily degraded in the environment. Furthermore,

aminoglycosides are generally positively charged under acidic conditions, which can facilitate

adsorption to negatively charged soil and clay particles, thus further decreasing the

concentration. However, one study was able to measure the occurrence of aminoglycosides in

hospital wastewater, showing concentrations from 0.4 to 7.6 μg per litre (106).

6.2 Resistance to aminoglycosides

Resistance to aminoglycosides by bacteria is mediated by three mechanisms: (1) reduction of

aminoglycoside concentrations via either dedicated or general efflux pumps, (2) alteration of

target for the agent and (3) enzymatic inactivation of the aminoglycoside (74;87). It should be

pointed out that the same bacterial strain often utilises more than one mechanism. Reduction

of aminoglycoside concentration is mainly seen in non-fermenting gram-negative bacilli, such

as Pseudomonas spp., and among others the nodulation cell division transporters superfamily

play an important role in intrinsic or acquired resistance. Alteration of target sites mainly

occurs through two ways; the acquisition of genes encoding rRNA methylases, which are

capable of modifying 16sRNA at positions critical for binding, and secondly, point mutations

of the ribosomal target. However, out of the three resistance mechanisms enzymatic

inactivation is by far the most common and widespread, with >50 enzymes already described

(42;74). Most of the enzymes, and the genes encoding them, are detected in gram-negative

bacteria and the genes are generally located on transferable elements, i.e. plasmids,

transposons and integrons. Three types of modifications have been described and the enzymes

are classified based on these mechanisms: acetyltransferases (AAC); adenylyltransferases

/nucleotidyltransferases (ANT); and phosphotransferases (APH) (Figure 9A), but all three

mechanisms have the same end result, reduced affinity for the aminoglycosides to the

ribosomal target. The enzymes have different positions on the substrate for modification,

24

which in the classification is denoted by a number, with or without a primer or double primer

(Figure 9B). A further subclassification can be done based on which aminoglycoside that is

Figure 9A. Modification of aminoglycoside by acetyltransferases (AAC);

adenylyltransferases/nucleotidyltransferases (ANT); and phosphotransferases (APH) B. The modifying enzymes and their substrates: A amikacin, Dbk dibekacin, G gentamicin, GmB

geneticin, I isepamicin, K kanamycin, N netilmicin, S Sisomicin and T tobramycin. Modified from Dessen et al (35) and Jana and Deb (74).

modified. The genes encoding the transferases follow the same nomenclature, but can be

further subclassified when different genes encode transferases with the same substrate profile.

A bifunctional enzyme ACC(6’)+APH(2’’) exists that can simultaneously acetylate and

phosphorylate, resulting in resistance to most clinically used aminoglycosides. The gene

encoding ACC(6’)+APH(2’’) is widely distributed among pathogenic bacteria and is common

and highly conserved in gram-positive bacteria such as staphylococci, enterococci and

streptococci.

6.3 Aminoglycoside resistance in wastewaters and other environments

The prevalence of bacteria resistant to aminoglycosides in wastewater varies greatly between

location and occasion. Studies focusing on Enterococcus spp. have described 0 % up to 20 %

of the isolates as aminoglycoside resistant (30;46;116). Aminoglycoside resistance among

Acinetobacter spp., E. coli and Pseudomonas spp. isolates vary from generally no resistance,

up to 15 % (30;46;53;131;172). However, when aminoglycoside resistant bacteria were

isolated, they were often multi-resistant, and most isolates carried more than one gene

encoding aminoglycoside resistance (30;163). Studies have also described that genes

encoding enzymatic inactivation, from all three classes, can be detected in wastewater

(67;157;163). In addition, conjugative plasmids carrying the genes have been isolated, mainly

from activated sludge in WWTPs, and have been shown to be transferred to aminoglycoside-

25

sensitive strains in vitro. It has also been indicated that the number of aminoglycoside

resistant isolates increases over the treatment process in WWTPs (53;42;147), but also the

contrary has been described (181).

Aminoglycoside resistant bacteria and genes encoding the resistance have been detected in

soil, farm-soil, coastal and estuarine water, seawater, creek/river and lake water

(13;67;84;150;156;163), and conjugative plasmids have been isolated from most of these

environments. It has also been described that soil harbours several not previously

characterised AAC-, APH- and ANT-genes (133).

7. Tetracycline antibiotics

The tetracyclines are the second most clinically used antibiotic class in Sweden and are

extensively used worldwide in human and animal therapy (27;155). They are also extensively

used in farming, agriculture, and aquaculture. Tetracyclines exhibit activity against a wide

range of gram-positive and -negative bacteria, but also against protozoan parasites and filarial

nematodes. In addition, they have non-bacterial effects such as anti-inflammation,

immunosuppression, inhibition of lipase and collagenase activity, enhancement of gingival

fibroblast cell attachment and wound healing (134). Tetracycline is also the cheapest class of

antibiotics, and has no major side effects in humans. Examples of commonly prescribed

tetracyclines for human treatment are minocycline and doxycycline.

The tetracycline molecules all contain a linear fused tetracycline core (Fig 10) and an

Figure 10. Structure of the tetracycline molecule Rn = the functional groups. Modified from Chopra and Roberts, 2001 (27)

assortment of functional groups is attached to the core (27). They are only bacteriostatic and

affect the bacteria through binding to the 30S subunit of the ribosome, resulting in halted

26

protein synthesis. However, the binding is reversible and diluting the antibiotic can reverse

the effect. Besides their effect on bacteria, they also bind to 70S ribosomes in mitochondria

and weakly to the 80S ribosome in eukaryotic cells.

7.1 Tetracyclines in wastewater

Tetracyclines have been detected in both treated and untreated wastewater from WWTPs,

including Swedish ones, with concentrations generally in the range 10 to 1000 ng per litre

(14;15;56;78;100;174). However, other studies have described no or limited occurrence in

wastewater (23;70;173). Concentrations were generally reduced, by 70 to 100 %, by the

wastewater treatment process at WWTPs, but studies have also shown limited, below 30 %, to

no reduction (15;56;100;174). The rate of reduction is probably influenced by removal of

solids in the treatment facilities, because there are indications of strong adsorption of

tetracyclines to soil, sludge, clay and sediment. (15;72). However, tetracyclines appear not to

be biodegraded, but photodegradation on the other hand plays an essential role in removal

(72). In rivers receiving WWTP discharge, tetracycline concentrations can be as high as 400

μg per litre in the sediment (128), compared to concentrations generally below 100 ng per

litre in discharge or in receiving surface water (14;100;158;174).

7.2 Resistance to tetracycline

Resistance to tetracycline exists in all bacterial genera, but the rate of resistant bacteria varies

greatly between genus, species and geographical location. Most tetracycline resistant bacteria

also harbour more than one resistance gene (27;134). In total, 35 tetracycline resistance genes

(tet-genes) and 3 oxytetracycline resistance gene (otr-genes) have been described (135).

However, no innate difference between the tet-genes and otr-genes exists, instead the

nomenclature reflects the bacterium first described to carry the gene.

Of the 38 genes, 23 encode resistance through efflux pumps, most belonging to the major

facilitator superfamily (MFS) (Fig 11) (134;135). The tetracycline MFS are membrane-

associated proteins, commonly residing in the lipid bilayer, that export tetracycline out of the

cell against the concentration gradient by exchange of one proton. This reduces tetracycline

concentration and thus protects the intracellular ribosomes. Most pumps confer resistance

only to tetracycline and doxycycline, but not minocycline and tigecycline. Only four genes

encoding efflux pumps, tetK, tetL, tet33 and tet38, have been detected in gram-positive

27

Figure 11. Example of structure of the tetracycline major-facilitator superfamily.

EmrA: periplasmic accessory protein and ErmB: cytoplasmic accessory. Modified from Mckeegan et al. (112).

bacteria. The tetB gene has the widest host range among gram-negatives and it confers

resistance to minocycline.

Eleven of the genes encode ribosomal protection proteins (RPP), of which tetO and tetM are

the best studied. However, it is generally assumed that the other nine genes have similar

mechanisms (29;135). The RPPs are soluble cytoplasmic proteins conferring a wider

spectrum of resistance than efflux pumps. They have high sequence similarity to the bacterial

ribosomal elongation factors EF-G and EF-Tu and display, like these factors, guanosine

triphosphatase (GTPase) activity. However, they cannot substitute the EF-G and EF-Tu, but

may have evolved from them. Instead the RPPs confer resistance by binding to the

tetracycline inhibited ribosome at the base of the h34 protein, causing an allosteric disruption

and thereby releasing the tetracycline. Exactly by which mechanism the RPPs distinguish the

tetracycline inhibited ribosome is not completely understood, nor whether they actively

prevent the antibiotic from rebinding. RPPs have been detected in gram-positive bacteria,

anaerobes and non-enteric gram-negative bacteria, and tetM is the most commonly detected

tet-gene in gram-positive pathogens.

In addition to the efflux pumps and RPPs, three genes (tetX, tet34 and tet37) have been

described to confer resistance through enzymatic modification, but they are not common

(135). The tetX has only been described in anaerobic Bacteroides spp. and tet34 only in

Vibrio spp. isolates from marine fish, while no specific bacteria have been identified carrying

28

the tet37. Another gene, the tetU, exists, which confers low-level resistance with unknown

functions.

The tet-genes are mainly found on highly mobile elements, i.e. plasmids, transposons,

conjugative transposons and integrons, and with a few exceptions pathogens acquire their

resistance by acquisition of these elements. In addition, horizontal gene transfer has been

described both between different species and genera (134). The gram-positive RPPs genes are

generally harboured on small plasmids, while the gram-negative efflux pump genes are found

on transposons or integrons inserted in a high diversity of plasmids.

7.3 Tetracycline resistance in wastewater and other environments

Tetracycline resistant bacteria are commonly isolated from a wide range of environments such

as ground water, seawater, freshwater, aquaculture, soil, feedlot, and from wastewater

(11;26;115;120;124). Most studies dealing with tetracycline resistance in WWTPs has

focused on isolation of Coliform bacteria, Escherichia spp., Klebsiella spp., Citrobacter spp.,

Pseudomonas spp., Enterobacter spp., Salmonella spp., Enterococcus spp., and Acinetobacter

spp. (30;41;52;131;147;183). In untreated wastewater, the rate of resistance among the

isolates ranged from 6-60 % and in treated wastewaters from 16-75 %, with most of the

studies describing an increase of resistance. However, there are examples describing limited

or no occurrence of tetracycline resistant isolates (46). Rates of tetracycline resistant bacteria

varied greatly between different types of wastewater, for example if the WWTP receives

hospital or pharmaceutical wastewater, the level of resistant bacteria reported is generally

higher compared to municipal wastewater (52;55;131). High rates of tetracycline resistance

have also been shown in slaughterhouse WWTPs e.g. 86 % of Enterococcus spp. being

tetracycline resistant (30). It has been shown that the percentage of tetracycline resistant

bacteria increases with increasing influent tetracycline concentration in a WWTP (83). The

biomass also influences the rate, at least in activated sludge, where higher rates of tetracycline

resistant bacteria correlated with higher biomass (82). There is conflicting evidence if

effluent from WWTPs increases the rate of tetracycline resistance in receiving water with

studies showing an increase (52;172) and others describing no difference between WWTPs

effluent, receiving water and non-receiving water (19;131).

Using a microarray targeting, 23 genes encoding tetracycline resistances, it was shown that

only the genes encoding efflux pumps could be detected in farm and garden soil (124). The

29

tetA gene was detected in all soils investigated, with other common genes being tetC and

tetD. In animal faeces, the RPP genes were more abundant with no single efflux gene

frequently detected. In WWTPs, genes encoding efflux pumps and RPP could both be

continuously detected over the treatment process, with tetA detected in all samples (11). In

addition, tetA was the only gene detected in lake water. Concentration of genes tetG,

encoding an efflux pump, and tetQ, encoding a RPP, were also determined during the

wastewater treatment process. It was shown that tetG was reduced by 1-2 log10 units and tetQ

by 2-3 log10 units, related to wastewater volume. If gene copies instead were related to total-

DNA, the reduction was lower or did not occur. When tetA-E were investigated in urban and

hospital wastewater tetA, but none of the other genes, was detected in all samples (55). From

seawater samples collected in close proximity to outflow of WWTPs, the genes tetA, tetC,

tetE, tetK and tetM could be detected (120). In sediment samples, collected from rivers

receiving wastewater from WWTPs and agriculture, concentrations of tetW and tetO were

generally higher compared to a river with low anthropogenic affect (128).

Tetracycline resistant bacteria and genes encoding the resistance are common in wastewater

lagoons connected to animal confinement facilities and/or feedlots, with a 100% detection

frequency in all studies (26;85;127;149;151). Both genes encoding RPP and efflux pumps

were detected and quantified in the lagoons, but concentrations of RPPs were two to seven

times higher (85;151). Genes commonly detected and/or had high abundance in the lagoons

were tetM, tetA and tetB. It has been shown that the concentration of both gene types

increased with higher usage of tetracycline in the feedlots (127;149), but that the RPP genes

increased more drastically (127). However, only weak correlation of gene concentrations to

measured tetracycline concentrations in the lagoons were detected. Tetracycline resistant

bacteria and the genes encoding resistance were also frequently detected in groundwater wells

and surface water in close vicinity to the animal settings (26;85;151). However, the

concentration of the genes was much lower, and genes encoding efflux pumps had higher

concentrations than the genes encoding RPPs (85). The rates of resistant bacteria were also

lower e.g. 79 % of the Enterococci being tetracycline resistant in the lagoons as compared to

15 % in the surface waters (151).

Another environment where tetracycline resistance is commonly detected is fresh and marine

aquacultures (64;115;120;139). In these studies the genes tetA and tetB were commonly

30

detected both in total DNA extracted and in tetracycline resistant bacterial isolates. Some of

the isolates were also able to transfer tetA and tetB in vitro through plasmid conjugation.

8. Polymerase chain reaction (PCR) and Real-time PCR

The use of molecularly based methods for detection and assessment of microorganisms are an

integral part in microbiology laboratories today. An abundance of different nucleic acid based

systems exists for detection and assessment of antimicrobial resistance and mechanisms,

extensively reviewed by Fluit et al. (42) and Sundsfjord et al. (153), with PCR, first

introduced in 1988 by Mullis and co-workers (142), as the golden standard. Compared to

cultivation-based methods, PCR offers a rapid, sensitive and easy way for detection of

resistance genes and is especially useful for slow-growing and uncultivable microorganisms.

This is important for evaluating microorganisms in non-clinical settings, such as wastewater

and soil, as it has been estimated that >99 % of the bacteria are uncultivable (9). However, the

PCR approach contains some limitations, e.g. it is only possible to screen for what you

already know, silent and pseudogenes giving false positives exists, and you cannot directly

detect resistance caused by point mutations. Furthermore, PCR detects nucleic acids rather

than living cells so there is a risk of “free” nucleic acids or nucleic acids from dead cells

giving false-positives (179).

The basis for PCR is the detection and synthesis of a specific DNA/RNA template (129). The

template is identified with two short synthetic and sequence-specific oligonucleotides, a.k.a.

primers, and the primers also acts as the initiation points for the synthesis, which is carried out

by polymerases. The first and most used polymerase is Taq DNA polymerase, isolated from

Thermus aquaticus, but another commonly used is the high fidelity Pfu DNA polymerase,

isolated from Pyrococcus furiosus. In addition, to polymerase and primers,

deoxyribonucleotide triphosphates (dNTP), which are building blocks of the synthesised

DNA strands, are needed. The PCR is carried out by temperature cycling (Fig 12), starting

with high temperature for separation/melting of the double stranded helical DNA molecule

(denaturing), after which the temperature is lowered to let primers bind (annealing) and then

increased, usually to around 72 ºC, to allow the polymerase to extend the primers from the

3´end using the dNTPs (extension). This procedure is usually repeated through 25 - 45 cycles,

which will allow for an exponential increase in the amount of DNA produced, with each

31

Figure 12. The PCR temperature cycle

newly formed product acting as a template during the remaining cycles. PCR is a sensitive

method where the stability and efficiency of the reaction are affected by many parameters;

DNA/RNA concentration/quality, primer concentration/quality, dNTP concentration, type and

concentration of polymerase, buffer type, cycling parameters, type of tubes/wells and PCR

instrument. Furthermore, after completion it requires a separation of the formed PCR-product,

usually by agarose gel electrophoresis with ethidium bromide staining, to confirm that the

template has been amplified and that it is of expected size.

The basis for PCR has not changed significantly since its introduction over twenty years ago,

but the method has been modified and improved through the years. The most significant

advancement is the introduction of real-time PCR in 1993 (68) and its development into a

commercially available real-time quantitative PCR in 1996 (65). The biggest problem with

conventional PCR is that it is only possible to study the end product of the reaction. In theory

the PCR reaction generates copies in an exponential fashion with a doubling in each cycle, but

this is only true if the PCR function with 100 % efficiency. During the later cycles, the PCR

will not generate products in an exponential fashion. It will instead enter a plateau phase due

to limitations in the polymerase, primer concentrations and dNTP concentrations. Real-time

PCR circumvents this problem by using fluorescent dyes that bind to the amplified DNA in

each cycle (50;89;160). The fluorescent signal is measured in each cycle and is directly

proportional to the amplified DNA, making it possible to follow the PCR in “real time”. This

makes it possible to study the amount of PCR product during the exponential phase and to

extrapolate back to determine the original amount of template. One must be aware that during

the initial cycles the signal will be weak and cannot be distinguished from the background,

but as the template is amplified the signal exponentially increase (Fig 13). The time the signal

32

is amplified over the background depends on the initial amount of template, with higher

concentrations reaching the threshold earlier (Fig 13). In order to compare different runs, the

background fluorescence is subtracted from each separate run; a baseline is set (Fig 13).

Figure 13. A hypothetical real-time PCR amplification plot.

Amplification plot = the fluorescence signal vs. the PCR cycle number. Furthermore, separate runs are only comparable in the exponential phase, so a threshold must

be set for the runs where all are above the baseline, in their exponential phase and parallel in

growth. The number of PCR cycles that are required to reach this threshold is called the Ct

value. Using a serial dilution of pure DNA with known concentrations the efficiency of the

PCR reaction can be estimated from a standard curve (Fig 14). The Ct values of the diluted

standards will be plotted against the logarithm of the standards concentration, dilution factor

or number of template copies. The efficiency of the PCR corresponds to the slope of the

curve, with a –3.33 slope corresponding to 100 % efficiency. Using the standard curve it is

Figure 14. Real-time PCR standard curve. Showing the fluorescence amplification plots in

logarithmic scale for six standard samples and the interpolated standard curve using determined Ct values and known template numbers.

also possible to determine the concentration in unknown samples, by using the determined

equation of the curve and a Ct value for an unknown sample. This approach is often referred

to as absolute quantification or standard-curve quantification. An alternative is relative

33

quantification, where, simply put, the determined Ct for the template of interest is compared

to the Ct of a reference run simultaneously with the template. The reference must not vary in

concentration or expression, with the efficiency of both reactions as equal as possible and

preferably above 90 % (50;89;160). In addition, to offer the possibility to follow the PCR in

real-time and to quantify DNA/RNA, real-time PCR also eliminates the need for post-PCR

processing, which reduces the time to obtain results and minimise the risks for carryover

contamination.

Today a wide range of different fluorescence chemistries offered by different manufacturers

exists (50;89;160). The chemistries can be broadly categorised as, (1) Non-specific DNA

binding dyes/fluorophores, e.g. SYBR® green and Ethidium bromide, (2) Specific

hybridisation probes, a probe is a extra oligonucleotide designed to anneal in a position

“between” the primers, e.g. TaqManTM and Molecular beacons, (3) Labelled primers, e.g.

LUXTM and AmplifluorTM. In some of the chemistries, the dye/fluorophore is incorporated

into the final PCR product, e.g. SYBR® green or LUXTM. This binding can be utilised for

characterisation of the product. After the end of the PCR cycling, the temperature is increased

slowly and the fluorescence continuously measured. What happens is that the PCR product

starts to “melt”, resulting in the fluorescence decreasing gradually until it reaches a

temperature where the double stranded DNA completely separates, resulting in an abrupt drop

in fluorescence. This temperature is referred to as the melting temperature and is determined

by the length and sequence of the amplified product (Fig 15). The melting temperature can be

Figure 15. Melting curve analysis. Fluorescence drops rapidly when the PCR products melt. The melting temperature is the inflection point that is easily determined as the maximum of

the negative first derivate of the measured melting curve.

used to discriminate between primer-dimers, non-specific products, specific products and

differences in sequences of a product (50;89;160).

34

In this thesis, PCR and real-time PCR are by far the most important methods. Real-time PCR

is used for detection and quantification of genes encoding antibiotic resistance in wastewater

environments. Several studies have earlier demonstrated real-time PCR as a fast, reliable and

sensitive method for this purpose (11;85;91;127;145;149;151;164). Both PCR and real-time

PCR are also applied to detect and characterise MRSA.

8.1 LUXTM real-time PCR

In this thesis we mainly worked with LUX (Light Upon eXtension) TM, which is a relatively

recent technique that only use one fluorophore that is attached to the 3’ end of either the

forward or reverse primer (102). The labelled primer is constructed to form a hairpin-loop

thus giving it fluorescence-quenching capability. The hairpin is achieved by designing a non-

sequence specific tail at the 5’-end complementary to the 3’ end. To get high quenching

capability the fluorophore should be incorporated within 3 nucleotides of a guanosine base

(31;117). Furthermore, it is preferable to have a blunt-ended guanosine-cytosine base pairing.

When the primer is incorporated into double stranded DNA the fluorophore is dequenched

resulting in an increase in fluorescence (Fig 17). This technique simplifies the PCR kinetics

and the 5’-tail prevents primer-dimer formation and mispriming (118). A further advantage is

that the fluorophore is incorporated into the amplified DNA, making it possible to perform

Figure 17. The Light Upon eXtension (LUX TM) effect.

melting curve analysis. Assays are also easy to design and it is a cost-effective technique,

since it does not use probes or various fluorophores. In addition, it can be used on most real-

time PCR platforms.

35

9. Aims

The knowledge about occurrence and survival of MRSA in non-clinical environments and

what roles these might play in dissemination and development are very limited. The primary

aim of this thesis was to establish whether MRSA and the mecA gene occur in wastewater and

how they might be affected by the wastewater treatment in a full-scale WWTP. The secondary

aim was to generate knowledge about the occurrence and concentration of genes encoding

aminoglycoside and tetracycline resistance in wastewater environments. It is well described

that wastewater harbours aminoglycoside and tetracycline resistant bacteria and genes

encoding these resistances, as described in the introduction of this thesis. However, it is

scarcely studied how the gene concentrations are affected over time and by wastewater

treatment. In this thesis the focus was on the genes aac(6’)-Ie+aph(2’’), mecA, tetA and tetB.

The specific aims for each individual paper were:

I. Develop quantitative real-time PCR assays, based on the LUXTM primer system, for

the genes, aac(6’)-Ie+aph(2’’), mecA, tetA and tetB, to be used for analysing

wastewater samples. The occurrence and concentration of these four genes were then

investigated in three different types of wastewater environments.

II. Determine if the mecA gene, S. aureus and MRSA can be detected using real-time

PCR in a full-scale municipal WWTP. Furthermore, to investigate the effects of the

wastewater treatment process on mecA concentration and the prevalence of S. aureus

and MRSA.

III. Characterise the MRSA flora in a municipal wastewater treatment plant by cultivation,

how the treatment processes affects the clonal-distribution and to establish

possible genetic relations to clinical isolates.

IV. Investigate how the treatment process in a full-scale municipal WWTP affects the

concentrations of tetA and tetB, and determine if physiochemical parameters, bacterial

and biomass load, influence the gene concentrations.

36

10. Sampling sites

For paper I, samples were collected from three sites representing widely different

wastewater-associated environments:

(1) Korslöt overland flow area located in Vagnhärad in the southeast central Sweden

and operated by Torsabygdens Teknik AB. It was constructed in year 2000 on a

previous farmland. The area is covered with Phalaris arundinacea and reed Pragmites

australis and operated all year around. From 2000 - 2003 it was flooded with

wastewater from the Korslöt WWTP, and from 2003 it has been applied with

landfill leachates from Korslöt recycling site. From the area, triplicate soil samples

were collected at 0 – 10 cm depth, every third month from August 2004 to August

2005.

(2) Ryaverket WWTP, Göteborg, described in section 3.3, samples were collected from

the plastic biofilm carriers in the nitrifying trickling filters. The biofilm was brushed

off and suspended in 1 ml phosphate buffered saline (PBS). The samples were

collected with approximately two-week intervals from December 2004 to February

2005.

(3) County Hospital in Kalmar, on the coast in Southeast Sweden, sludge was collected

from a sewage pipeline, as grab samples, with two-week intervals from April 2003 to

July 2003. The pipeline received sewage from a building containing 127 beds (72

general and urology surgery, 33 gynaecology and 22 paediatric).

Papers II - IV were carried out using wastewater samples collected at Ryaverket WWTP

from key locations chosen to reflect the treatment processes at the plant (Fig 16). In paper II

and IV, one 500 ml water sample was collected as a grab sample, every month from March

2006 to February 2007 at eight locations in the plant; inlet, after primary settling, activated

sludge, after secondary settling, outlet, before and after trickling filter and reject water from

the centrifuges. For paper II, two additional grab-samples were collected from Inlet in

November 2007 with a two-week interval. All wastewater samples were collected in new and

clean polyethylene high-density bottles. For paper III, water samples were collected from

37

four locations: inlet, activated sludge, outlet and after trickling filters (Fig 16). From each

location, one 1-litre sample was collected in autoclaved Pyrex glass bottles every second

Figure 16. Schematic drawing of the wastewater treatment process at Ryaverket, with

sampling locations indicated with numbers. 1. Inlet 2. After primary settling 3. Activated sludge 4. After secondary settling 5. Outlet 6. Before trickling filters 7. After trickling filters

and 8. Water from rejects pumps. (Paper II)

week from May 5th 2008 to July 1st 2008. Inlet and Outlet samples were collected from

wastewater, pooled over 24 h, while unpooled samples from activated sludge and after

trickling filters were collected on site in the treatment process.

11. Design and evaluation of LUXTM real-time PCR assays for the mecA, tetA, tetB and aac(6’)-Ie+aph(2’’) genes

The main objective of paper I was to develop quantitative real-time PCR assays based on the

LUXTM technique for detection and quantification of the genes mecA, tetA, tetB and aac(6’)-

Ie+aph(2’’), to be applied on samples collected from wastewater environments. At the start of

this project, no well-established quantitative method was available for these genes.

Quantitative methods are needed to be able to monitor prevalence of the genes in wastewater

in order to study differences over time, between different environments or if concentrations

are increasing due to anthropogenic effects.

Using nucleotide sequences of mecA, tetA, tetB and aac(6’)-Ie+aph(2’’) collected from

GenBank (www.ncbi.nlm.nih.gov), primer-pairs suitable for LUXTM real-time PCR were

designed for each gene, using the LUXTM designer (Invitrogen Corp., Paisley, UK) and the

Lasergen 6.0 (DNASTAR Inc., Madison, WI, USA) (Table 5). The primer pairs were

evaluated using conventional PCR on reference strains and DNA extracted from wastewater

38

TABLE 5. PCR primers, targeting genes coding for antibiotic resistance, designed for LUX™ real-time PCR assay. Lower-case letters at the 5´-end of primers denote the part of the primer added to give the hairpin structure. The lower-case letter t in the 3´-end of primers denotes the putative location of the dye (L in the primer name). F = forward, R = reverse (Paper I) Primer Target gene Sequence (5´ - 3´)

(Amplicon size, bp) aac(6´)-F1 aac(6´)-Ie CATTATACAGAGCCTTGGGAAGA aac(6´)-R1-L +aph(2´´) (364) gaacatgGCCCTCGTGTAATTCATGtTC mecA-F5 mecA (108) TGCTCAATATAAAATTAAAACAAACTACG mecA-R5-L gaagtATGACGCTATGATCCCAATCTAACTtC tetA-F2-L tetA (96) cagccTCAATTTCCTGACGGGCTG tetA-R2 GAAGCGAGCGGGTTGAGAG tetB-F1-L tetB (101) cagcaAGTGCGCTTTGGATGCtG tetB-R1 TGAGGTGGTATCGGCAATGA

samples. The specificity of the primer-pairs were verified through agarose gel electrophoresis

and by nucleotide sequencing. Using the designed primers, assay conditions for the real-time

PCR were optimised for annealing temperature, Mg2+-concentration and primer concentration.

The efficiencies and detection limits were then determined for each assay using serial

dilutions of reference strains. Slopes (= PCR efficiencies) of the standard curves generated

from the serial dilutions were as follow for each primer pair (given as mean, n ≥ 3): aac(6´)-

F1+ aac(6´)-R1-L, -4.17; mecA-F5+mecA-R5-L, -3.52; tetA-F2-L+tetA-R2, -3.52 and tetB-

F1-L+tetB-R1; -3.31. The detection limits were determined to aac(6’)-Ie+aph(2’’), 15 gene

copies; mecA, 10 gene copies; tetA, 10 gene copies, and tetB, 5 gene copies, all per PCR

reaction.

To evaluate if the developed LUXTM real-time PCR assays were suitable for quantification of

mecA, tetA, tetB and aac(6’)-Ie+aph(2’’) in wastewater, they were applied on the samples

collected from an overland flow area, a municipal WWTP and a hospital sewage pipeline. We

were able to detect and/or quantify all genes in the three investigated environments. The

results are summarised in table 6. To verify that the PCR efficiency was not compromised,

due to co-extraction of inhibitory substances, serial dilutions were performed on the samples,

on which the assays then were applied. It was shown that no inhibition of the PCR occurred in

samples diluted more than 10-1. The specificity of the assays was verified in all collected

samples using melting curve analysis.

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Table 6. Summary of the results of detection and quantification of the genes mecA, tetA, tetB and aac(6’)-Ie+aph(2’’) in three wastewater environments. BD = Below detection limit, D = Detected but not reliable quantified, Q = Quantified. Gene Overland flow Ryaverket Hospital Sewage area, 5 samples WWTP, 5 samples pipeline, 8 samples

(genes per μg DNA) (genes per μg DNA) (genes per μg DNA) aac(6’)-Ie D: 5/5 D: 2/5 Q: 8/8 (4.0x102 -1.4x105) +aph(2’’) Q: 3/5 (1.4x103-6.3x103) …………………………………………………………………………………………………... mecA BD: 5/5 D: 4/5 BD: 7/8 BD: 1/5 Q: 1/8 (4.5 x 103) …………………………………………………………………………………………………... tetA D: 5/5 Q: 5/5 (1.7x104-8.0x104) Q: 8/8 (2.8x105-6.5x105) ....................................................................................................................................................... tetB D: 4/5 BD: 5/5 Q: 8/8 (1.1x103-5.7x103) Q: 1/5 (4.2x102)

The only environment where all four genes could be detected was the hospital sewage

pipeline (Paper I). In addition, this was the environment with the highest concentration of all

genes (Table 6). This might indicate that there is a higher selection for antibiotic resistance in

this environment. The hospital pipeline probably has relatively high concentration of

antibiotics compared to the other environments, which may help to sustain or select for

resistance. Earlier studies have also described relatively high amounts of antibiotics in the

wastewater at Kalmar County Hospital (76;99). The number of resistant bacteria that are

transported to the hospital sewage pipeline is also probably higher compared to the two other

environments. It was shown that the concentrations varied over time in the hospital pipeline,

but no clear trend could be detected. The overland flow area is the environment with generally

the lowest gene concentrations. This was expected because it treats landfill leachates and

therefore probably has the lowest antibiotic pressure. Tetracycline resistance appears do be

commonly detected in the environment, as described in section 8.3. So it could be expected

that the genes encoding tetracycline would be detected in all environments and have the

highest concentrations. The tetA gene had the clearest trend, lowest concentrations in the

overland flow area and highest in the hospital pipeline, when comparing concentrations

between the three environments. It should be pointed out that tetA appears to be a common

gene in anthropogenic-affected environments, and compared to tetB, its more frequently

detected (11;55;124). According to the literature mecA has previously only been detected in

hospital wastewater. However, in this study it was shown that besides occurring in hospital

wastewater mecA has a stable occurrence in municipal wastewater, since it was detected in

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four out of five biofilm samples collected from the trickling filter in a WWTP. To our

knowledge, this is also the first study to detect aac(6’)-Ie+aph(2’’) in municipal wastewater,

but it has previously been detected in manure and soil (67).

12. Detection of the mecA gene, S. aureus and MRSA in a full-scale wastewater treatment plant

The fact that mecA was detected for the first time in municipal wastewater (paper I) raised

questions whether it would be possible to detect S. aureus and MRSA in wastewater (paper II)

and how the prevalence of mecA and possibly S. aureus and MRSA are affected over the

treatment process and time in a full-scale WWTP. To investigate this we used the

experimental set-up shown in Figure 18.

Figure 18. Overview of the experimental procedure for molecular detection of mecA, the S.

aureus specific nuc gene and MRSA. It was shown that mecA could be detected continuously over the year at all sampling sites,

except in water from the rejects pumps (Table 7). S. aureus could also be detected every

month in inlet, after primary settling and activated sludge. In all other sampling sites S. aureus

occurred in most months, with the exception of water from reject pumps. MRSA was detected

during most months in inlet, after primary settling and in activated sludge. In all other

sampling sites MRSA was only occasionally detected, with the exception of after secondary

settling and before trickling filter, where MRSA could not be detected.

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Table 7. Molecular detection of mecA, nuc/S. aureus and MRSA, in wastewater samples collected from eight sites in a full-scale WWTP March 2006 to February 2007

To our knowledge this is the first report that shows occurrence of both S. aureus and MRSA

in municipal wastewater. The results indicate that both S. aureus and MRSA are more

resilient than previously believed and that wastewater may be a potential reservoir for MRSA.

However, the treatment process appears to reduce MRSA as evidenced by that it is mainly

detected in the early treatment steps. The mesophilic digestion of sludge collected from

primary settling is likely to have a highly reducing effect on MRSA, as well as on S. aureus

and mecA, because all three could only be occasionally detected in the water from the reject

pumps. That the mecA gene is detected in all locations indicates that it mainly originates from

CoNS, since CoNS often carry mecA, at least in the clinical setting (61), and since

methicillin-resistant S. epidermidis have been isolated from wastewater (145). Because both

mecA and S. aureus simultaneously occur in the same environment, there may be a potential

for new MRSA to develop due to horizontal gene transfer. The potential for S. aureus to

transfer genes encoding antibiotic resistance in wastewater has earlier been described (122).

13. Cultivation and characterisation of MRSA from municipal wastewater

In paper II it was shown that MRSA occurs in municipal wastewater and could be molecularly

detected in the early treatment steps in a full-scale WWTP. However, we did not show

whether MRSA is viable or how MRSA is affected over the treatment process. In addition,

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the study raised some further questions: is there only one or a few strains present and are these

specific for the WWTP? In order to answer these questions cultivation of MRSA was

performed from four sampling sites in the WWTP (paper III), using the experimental set-up in

figure 19. The clonal relationship of MRSA isolates from wastewater to the 20 most common

clinical MRSA spa types in Sweden 2007 and 2008 were also determined using BURP

analysis.

Figure 19. Overview of the experimental procedure for cultivation of MRSA from a full-scale

wastewater treatment plant

In total, 189 MRSA were isolated from wastewater, corresponding to 29 different spa types

including six novel spa types t3950, t4013, t4100, t4102, t4203 and t4140 (Paper III). Most of

the isolates, 65 %, 12 spa types, were resistant only to β-lactam antibiotics, but 21 %, 9 spa

types, were defined as multi-resistant (resistant to at least two classes of antibiotics in addition

to β-lactams). MRSA was isolated from inlet and activated sludge, but not from outlet or after

trickling filters. Most of the isolates, 66 %, were cultivated from inlet and 19 spa types were

identified in inlet compared to 15 spa types in activated sludge (Figure 20). The majority of

the spa types were detected at one sampling site and one sampling occasion, but spa types

t018, t127, t172 and t186 occurred in more than one sampling. In the activated sludge 40 % of

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spa types were defined as multi-resistant, while in inlet only 21 % were multi-resistant. PVL

positive isolates, spa types t008, t019, t127 and t852, were only detected in activated sludge.

The isolates were shown to harbour either SCCmec type I or IV, with 63 % carrying type IV.

Figure 20. The number of MRSA isolates and their spa types in Inlet (I) and Activated sludge

(A). The t127/t127* spa type with two different antibiograms. (paper III)

Based on that Sweden is a low prevalence area for MRSA and earlier studies have indicated

low or no occurrence of S. aureus in wastewater, it was surprising that we were able to isolate

such a great variety of spa types. However, the treatment process appears to have a negative

impact on the MRSA as they can only be isolated early in the WWTP, confirming the results

in paper II. Although the treatment process reduced MRSA, there are indications that it selects

for more extensive antibiotic resistance and possibly more virulent strains. These indications

are a higher rate of the spa types being multi-resistant in the activated sludge, and PVL

positive isolates only being detected at this stage.

The results show that it is not one specific lineage of MRSA that survives in the wastewater

(Paper III). Eight of the spa types, t002, t008, t015, t018, t019, t127, t186 and t790, detected

in the wastewater are among the 20 most commonly reported MRSA spa types in Sweden and

nine of them, t002, t008, t015, t018, t019, t067, t127, t172 and t790 are among the 30 most

reported spa types in the Ridom SpaServer. The remaining spa types isolated from

wastewater clustered in the same BURP-CC as the top 20 MRSA in Sweden (Fig 21). In

addition, several of the wastewater isolates showed a genetic relationship, sharing spa type

and SCCmec with worldwide-distributed MRSA clones (32). Together these data indicate that

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the wastewater MRSA is most likely a reflection of the carriage in the community. This

assumption is further supported by the fact that a large and diverse MRSA flora, changing

from each sampling occasion, can be detected in the wastewater under such a short time

period.

Figure 21. Dendogram based on BURP analyses of MRSA spa types isolated from municipal

wastewater, and the 20 most common clinical MRSA spa types 2007 to 2008. Framed spa types = wastewater MRSA isolates (Paper III)

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14. The effect of wastewater treatment on concentrations of mecA, tetA and tetB

Using the LUXTM real-time PCR assays developed in paper I, we investigated how the

wastewater treatment process in a full-scale WWTP affected concentrations of mecA, tetA

and tetB (paper II and IV). Furthermore, it was determined how the gene concentration

correlated to faecal bacteria, e.g. E. coli and Coliform bacteria, physiochemical parameters,

and biomass, using the experimental set-up in Figure 22.

Figure 22. Overview of the experimental procedure for detection and quantification of mecA,

tetA and tetB It was shown that mecA, tetA and tetB could be continuously detected throughout the year at

all sampling sites and that gene concentrations varied over the year (Fig 23), but no trend

could be observed for the genes. When comparing the median of the gene concentrations,

related to wastewater volume over the year at each sample site, it was observed that they

decreased during the wastewater treatment. However, the three genes showed higher

concentrations in the activated sludge compared to the other sampling sites. Higher

concentration for tetA was also observed at reject water compared to at inlet. If related to

biomass, i.e. total-DNA, the median over the year for mecA and tetA concentrations still

decreased, but the difference between median values is smaller than those of comparison of

genes and water volume. The median for mecA in inlet and after primary settling and for tetB

in inlet, after primary and secondary settling and outlet were on similar levels. The median

concentrations of tetA and tetB were lower in the three locations affected by biological

treatment compared to the other sampled locations.

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Figure 23. Concentration of the genes. Sampling sites; 1. Inlet, 2. after primary settling, 3.

activated sludge, 4. after secondary settling, 5. outlet, 6. before trickling filter, 7. after trickling filter, and 8. water from reject pumps. ●denotes the gene concentration for each

month. The horizontal line = the median of concentrations over the year. Months when the genes were detected, but not quantified, are marked as 10 genes, corresponding to the

detection limit of each respective gene at the different sampling site.

It was shown that the treatment process in a full-scale WWTP reduced concentrations of

genes encoding antibiotic resistance, both related to wastewater volume and total-DNA

(papers II and IV). Comparing inlet and outlet, a reduction in concentration related to volume

was observed in eleven months for tetA and tetB, on average by 1.2 and 0.9 log10 units,

respectively, and for mecA in 8 months by 1.4 log10 units. If gene concentrations were related

to total-DNA the reductions were on average 0.3 log10 units in 9 months for tetA, 0.2 log10

units in 7 months for tetB and 0.5 log10 units in 8 months for mecA. These results are

supported by earlier studies showing reduction of genes encoding tetracycline resistance and

genes encoding ß-lactamases in WWTPs (11;91). In the activated sludge, the gene copies

related to water volume, exhibited higher concentrations compared to inlet in all months, on

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average by 0.8 log10 for tetA, 0.9 log10 for tetB and 1.1 log10 units for mecA. However, when

related to total-DNA the gene levels are lower in all months for tetA and tetB, on average by

0.7 log10 units and 0.5 log10 units respectively, and in 8 months, by 0.5 log10 unit for mecA,

indicating that the genes have a selective disadvantage here. That gene concentrations related

to volume are higher at sampling sites with a high biomass, suggests that biomass load

influence the number of antibiotic resistance genes. This assumption is further supported by

that tetA concentration correlates to total-DNA concentration at most sampling sites, and that

reduction of the genes when related to total-DNA is smaller compared to related to water

volume. The smaller or lack of differences may also indicate that the reduction of gene copies

are partly due to removal of biomass rather than direct removal of the genes. Especially for

tetA and tetB, the reduction of biomass appears to play an essential role, since tetA and tetB

reductions correlates to biomass reduction. However, there is still a reduction in gene

concentration when comparing inlet and outlet, indicating additional mechanisms behind the

reduction. Over the trickling filter, concentrations of tetA and tetB related to total-DNA are

reduced, on average by 0.4 and 0.4 log10 units (paper IV), respectively, but the mecA

concentration show an increase in 10 months by 0.4 log10 units (paper II). These data suggest

a selective advantage for mecA in the trickling filter, but not for tetA or tetB.

Reduction of tetA and tetB concentrations, but not mecA, correlates to reduction of biomass,

COD and Ptot (Paper IV). This indicates that the removal of tetA and tetB may partly be

explained by precipitation and sedimentation, as Ptot is removed by precipitation and

sedimentation and COD and biomass are partly reduced by sedimentation. The notion that

sedimentation is important for removal of tetA and tetB is further supported by that the

reductions correlated to reduction of E. coli and coliform bacteria. Sedimentation has been

described to have an essential role in removal of bacteria (48;182).

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15. Conclusions

• Methicillin-resistant S. aureus (MRSA) was for the first time shown to occur in

wastewater, using both cultivation and molecular detection. The treatment

processes in a full-scale municipal WWTP were also shown to reduce both number

and diversity of MRSA. However, there are indications that the treatment process

selects for strains with more extensive antibiotic resistance and possibly higher

virulence.

• LUX™ Real-time PCR assays targeting the genes aac(6´)-Ie+aph(2´´), mecA,

tetA, and tetB were developed and verified to be fast, sensitive and specific

methods for detection and quantification of the respective resistance genes in

wastewater environments. The results show that real-time PCR can be a useful tool

in monitoring concentration of genes encoding antibiotic resistance, between

different environments and over time, to be used for assessment of anthropogenic

impact.

• By applying the developed real-time PCR assays targeting the genes mecA, tetA,

and tetB, it was shown that the wastewater treatment in a full-scale municipal

wastewater treatment plant reduced concentrations of the genes encoding antibiotic

resistance. Furthermore, biomass loads appear to influence the total number of

genes, and the reduction may partly be explained by removal of biomass. In

addition, the reduction of tetA and tetB concentrations can partly be explained

through precipitation and sedimentation in the plant.

16. Future work

In this thesis it was described that MRSA survives in municipal wastewater, and wastewater

may therefore be a potential reservoir and source for MRSA. In the future it should be

addressed whether new strains of MRSA can evolve in wastewater and investigated whether

transfer of SCCmec can occur. However, this might be difficult to study because it has not

been established what the transfer mechanisms of SCCmec are or what triggers the gene

transfer. A way to get an indication whether transfer has recently occurred is to determine if

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the isolated MRSA-strains can perform spontaneous excision of the SCCmec, i.e. if the

recombinases are active. The excision of SCCmec is an essential step in a possible transfer.

The SCCmec from the isolated MRSA strains should also be further subtyped to establish if

they possibly are new subtypes. It should be investigated whether MRSA has the capability to

collect “new” resistance genes and virulence factors in wastewater that is not carried by the

SCCmec. Furthermore, the CoNS flora in wastewaters should be paid attention to, as well as

the question if they carry SCCmec, which SCCmec type they harbour and whether they can

transfer SCCmec.

Although it was shown that the wastewater treatment reduced the concentration of genes

encoding antibiotic resistance, the concentrations in the outlet are probably higher than in the

receiving environment. It should therefore be investigated what potential impact this input has

on the surrounding environments. In addition, it was shown that mecA concentrations

increased over the trickling filter in the WWTP. A more extensive study should therefore be

considered for the trickling filters, for example to establish which bacteria carry mecA, if

transfer of mecA occur and if there is an increase in bacteria carrying the mecA. The

sedimentation, precipitation and removal of biomass were shown to play an essential role in

the decrease of gene concentration. It is therefore important to establish the ratio of resistant

bacteria and genes encoding the resistance in the collected sludge and how concentrations are

affected by the treatment of the sludge. We have also described that concentrations vary over

the year in the WWTP, but since no trend could be shown it would be interesting to measure

concentrations of antibiotics in the wastewater and establish if concentrations of the genes can

be correlated to incoming antibiotic concentrations.

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17. Acknowledgements During the five years I’ve spent trying to be a researcher I have had the benefit of meeting a lot of interesting people, making new friends and getting help and input (sometimes much, sometimes little) from different persons. In this section I will therefore try to thank and acknowledge the people that has contributed or helped me both with the project and/or on a personal level. This will also include people I met outside the research and knew before my time as a PhD-student. If you’re not mentioned here I’m sorry, but sometimes you just forget people temporarily or completely. Jan-Ove Johansson and Elisabeth Börjesson, my dad and mom, for their love, support, encouragement and convincing me after high school that it was not in my best interest to study to be a welder. You have always supported and cheered me on through my studies despite the fact you haven’t understand half of what I’ve been doing or talking about. (Far och mor, för er kärlek, support, uppmuntran och för ni övertygade mig att det inte var i mitt intresse att läsa svetsareutbildningen efter gymnasiet. Ni har alltid stött och hejat fram mig genom mina år på universitet fast ni en stor del av tiden inte förstått vad jag har arbetat med och pratat om.) Martina Börjesson, my sister for your love, support and just being the best sister in the world. She is also acknowledged for taking the time to read and comment on the popular science summary in this thesis making sure that a layman would understand it. Stefan Johansson my brother-in-law, for his support and for actually being a brother. My main-supervisor Per-Eric Lindgren for giving me the opportunity to become a PhD-student and for your support. Thanks to Åke Hagström at the University of Kalmar for introducing me to the world of microbiology and giving me the first taste of the researchers life. So this is the guy you can blame for my decision to become a PhD-student and my extra years spent at the University. Andreas Matussek my hockey stick wielding and bicycle crazy co-supervisor for getting involved in my project when he was needed the most. Thank you for your support and especially your time, which I know you have a lack off. Thanks to Lennart Nilsson and Björn Olsen for being my co-supervisors although you were not involved 100 percent of the time you had always time over for me, my questions and signing the papers. Special thanks to Lennart who took the time to comment and give suggestions on this thesis. Thanks to the “posse” Johan “Charmören” Nordgren, Peter “Boxholmaren” Wilhelmsson, “Snäll-” Pontus Lindblom, Björn “Macho-Man” Berglund and the hang-around Fredrik “Dansken a.k.a Hissförstöraren” Nyström for their contributions to my work, friendship and the many funny hours consuming beer and other beverages. Hopefully this is not the end, but we will always have Girona. Magalí Martí our Catalonian flower for inviting the gang to Girona and being a good friend. A special thanks to Pontus and Johan for the many hours spent on the squash court, it was fun despite the fact that I almost always seem to lose. Pontus should also be recognised for his meticulous review of my thesis. In addition, Björn deserves a special thank because as my office-mate he became the guinea pig for a lot of sentences and formulations used and not used in this thesis, and for commenting on the thesis. Thanks to

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Carina Sundberg for being my “lab mom” when I started and being a good friend. Other people that should be thanked are Elisabeth Hollén and Charlotte Strandgren and also all the other people that been or is part of Per-Eric’s group and out-groups. All the other people, past and present, at the Division of Medical Microbiology for five funny and pleasant years and being the best coworkers a guy could have. You are not mentioned by name but you are all remembered. A special acknowledgment should go to the lady-mob, the ones that possess the true power at the division. Amanda Welin also deserves a special thank as she provided linguistic revision on this thesis and for being a good friend. Thanks to Sara Melin, Sture Löfgren and Olaf Dienus for their help and contribution to my work. Thanks also to all the other people at the Division of Laboratory Medicine, County Hospital Ryhov for support and making my stay at Ryhov a pleasant one. To all my other “real-life” friends old and new for your love, support and just being my friends, hopefully I will now have more time over for you. I would also like to thank Wala och Folke Danielssons Stiftelse, Svenska Försäkringsföreningen Hans Dalbergs stiftelse för miljö och hälsa, Stiftelsen Längmanska Kulturfonden and Knut och Alice Wallenbergs Stiftelse for giving me the opportunities to visit Lyon (BAGECO-8), Vienna (ISME-11), Tokyo (WaterMicro-14) and Cairns/Sydney/Melbourne (ISSSI-13). Finally remember the words of the immortal Homer Simpson:

"Phfft! Facts. You can use them to prove anything”

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