“Plasmo2D”: An Ancillary Proteomic Tool to Aid Identification of

Proteins from Plasmodium falciparum

Amit Khachane, Ranjit Kumar, Sanyam Jain, Samta Jain, Gowrishankar Banumathy,Varsha Singh, Saurabh Nagpal, and Utpal Tatu*

Department of Biochemistry, Indian Institute of Science, Bangalore 560012, India

Received August 30, 2005

Abstract: Bioinformatics tools to aid gene and proteinsequence analysis have become an integral part of biol-ogy in the post-genomic era. Release of the Plasmodiumfalciparum genome sequence has allowed biologists todefine the gene and the predicted protein content as wellas their sequences in the parasite. Using pI and molecularweight as characteristics unique to each protein, we havedeveloped a bioinformatics tool to aid identification ofproteins from Plasmodium falciparum. The tool makesuse of a Virtual 2-DE generated by plotting all of theproteins from the Plasmodium database on a pI versusmolecular weight scale. Proteins are identified by com-paring the position of migration of desired protein spotsfrom an experimental 2-DE and that on a virtual 2-DE. Theprocedure has been automated in the form of user-friendly software called “Plasmo2D”. The tool can bedownloaded from http://144.16.89.25/Plasmo2D.zip.

Keywords: Plasmo2D • bioinformatics • proteomics • malaria •heat shock proteins

Introduction

Release of the Plasmodium falciparum genome sequencetwo years ago has made it possible to identify previouslyunknown genes and pathways in the malarial parasite.1 Thecomplex task of understanding the biology of the parasite hasreceived a definite framework, which is to examine the expres-sion and functions of 5331 genes present in the parasitegenome. Plasmodium gene arrays, developed using the genomedata, have facilitated expression profiling of parasite genesduring different stages of its life cycle.2-4 Proteomic approachesusing mass spectrometric analysis have also been initiated forprotein identification and examination of their temporalexpressions in the parasite.5,6 Efficient use of genomic andproteomic technologies however depends on the supportingbioinformatics tools.7-13

Using Plasmodium falciparum genome data, we have de-veloped a bioinformatics tool that will facilitate analysis ofprotein expression and identification in the parasite. Bycomparing the isoelectric point (pI) and molecular weight (MW)of protein of interest with those reported in the Plasmodium

database, the tool allows tentative but rapid identification ofproteins. Out of a total of 5331 genes reported in the Plasmo-dium falciparum genome, the tool allows you to narrow downthe identity of protein of interest to a list of a few candidates.In addition to providing a rapid identification of unknownprotein spots, the tool can serve as an important accessory toaid final, mass spectrometric identification of proteins. Ad-ditionally, the tool can be used in an average biochemistrylaboratory on a routine basis. The uniqueness of this tool isthat it aids in the identification of proteins from the scannedexperimental 2-DE gel image by utilizing genome informationof the parasite. Inclusion of the genome information adds anew dimension in the proteome analysis from 2-DE. Conven-tional manual hunt for the required pI and MW proteins intoa protein database is indeed time-consuming and laborious.

The approach consists of the following three steps: (1)examination of migration of protein of interest on two-dimensional gel electrophoresis (2-DE), (2) superimposition ofthe experimental gel to a virtual 2-DE generated by plottingall the proteins of P. falciparum from www.plasmodb.org on apI versus MW scale and (3) matching the position of migrationof the protein from the experimental 2-DE with the theoretical2-DE to make protein identification. The approach allows youto make tentative identification of proteins of interest by 2-DE.14

We have incorporated steps 2 and 3 of this approach in theform of user-friendly software called “Plasmo2D” that performsgel alignment and protein identification computationally.

We examined the validity of “Plasmo2D” by using anexperimental 2-DE on which parasite lysate were subjected towestern blotting using antibodies specific of 3 abundantparasite proteins. Using Western blotting and MALDI-TOF massspectrometry, we were able to identify spots corresponding toPfHsp70 (70 kDa Heat shock protein of Plasmodium falci-parum), PfHsp90 (90 kDa Heat shock protein of Plasmodiumfalciparum), PfBiP (72 kDa Binding protein of Plasmodiumfalciparum), Pftubulin, PfPDI (Protein disulfide isomeraseof Plasmodium falciparum) among other proteins, by“Plasmo2D”.15,16 The results confirmed the validity and use of“Plasmo2D” for identification of unknown proteins from themalarial parasite. A similar approach can be implemented foranalysis of proteomes of other sequenced genomes.

Experimental Section

Development of the Tool. Plasmo2D was developed usingVisual Basic version 6.0 (Microsoft Inc.). Differing pI andmolecular weight markers were subjected to 2-DE on a 10%

* To whom correspondence should be addressed. Phone: 080 22932823.Fax: 080 23600814. E-mail: tatu@biochem.iisc.ernet.in.

10.1021/pr050289p CCC: $30.25 2005 American Chemical Society Journal of Proteome Research 2005, 4, 2369-2374 2369Published on Web 10/18/2005

resolving gel. The migration distances along pI and MW werenoted [Supporting Information Table 1]. pI is plotted on X-axisand MW on Y-axis. The above-derived values were consideredas training set to generate mathematical equations usingCURVEEXPERT 1.37 software (D. Hyams, Starkville, MS). Themathematical equations derived are as follows:

Molecular weight equation:

“MW” is Molecular weightpI equation:

The standard error of estimation (SE) for pI equation was0.19 cm, and for the molecular weight equation, the SE is ∼0.21cm. Theoretical pI and molecular weight of all the proteinsencoded by the parasite genome were predicted using thealgorithm as described.17 Using the above-generated math-ematical equations, the parasite proteome was theoreticallyplotted (which formed the Virtual 2-D).

Once the desired protein spot on a scanned experimentalgel image is clicked using the mouse cursor, the correspondingX and Y coordinates of the spot are matched to the spotscorresponding to that in the Virtual 2-D dataset. To take intoaccount the SE while calculating migration distance and tocompensate for the shift due to post-translational modification,a circular radius of 0.4 cm around the protein spot in the gel isincorporated, thus making sure that the protein of interest isnot missed. All the proteins, which fall within the 0.4 cm radiusof the clicked spot, are considered a match. The 0.4 cm radiuscorresponds to a maximum of 0.3 units pI shift.

Preparation of Parasite Lysate. P. falciparum infectederythrocytes were metabolically labeled with [35S]-cysteine-and methionine, washed twice with PBS and lysed in 10volumes of NETT buffer (300 mM NaCl, 1 mM EDTA, 10 mMTris pH 7.5, and 1% Triton X-100) supplemented with proteaseinhibitors. The lysate was separated from the pellet by cen-trifugation at 20 000 × g for 20 min at 4 °C and the clarifiedlysate was solubilized in 2D lysis buffer containing 9.5 M urea,4% CHAPS, 2% pharmalytes of pI range 3-10 and 65mM DTT.18

A fraction of the total lysate was subjected to 2-DE andphosphorimager analysis. For Western blotting19 and MALDI-TOF analysis, the infected cells were lysed using 0.15% saponinand the parasite pellet was lysed directly in 2D lysis buffer.

2-DE, In-Gel Proteolytic Digestion and Peptide MassFingerprint Analysis by MALDI-TOF. The sample solubilizedin 2D lysis buffer was loaded onto 7 cm IPG (Immobilized pHGradient) strip by active rehydration at 50 V for 10 h. Followingthis, the rehydrated IPG strips were subjected to IEF on EttanIPGPhore. After the run was over, the tube gels were incubatedin 10 mL of equilibration buffer (6 M Urea, 125 mM Tris, 65mM DTT, 30% glycerol, and 2% SDS, pH 8.8) for 15 min. Thefocused IPG strips were then laid horizontally on top of 10%SDS-polyacrylamide gels and sealed with 1% agarose in SDS-PAGE running buffer (50 mM Tris, 380 mM glycine, and 0.1%SDS). SDS-PAGE was carried out at 110 V for 2 h and 10minutes. The proteins from 2DE were transferred onto nitro-cellulose membrane and probed with specific antibodies.Alternatively, Coomassie-stained protein spots of interest werecut into 1 mm3 pieces from 2-DE gels, and processed for in-gel proteolytic digestion as described.20 In-gel digestion was

carried out using trypsin 20 ng/mL at 37 °C for 12 h. Peptidedigests were mixed with equal volume of matrix (R-cyano4-hydroxy cinnamic acid) and peptide mass spectra wererecorded using ‘Ettan MALDI-TOF Pro’ (Amersham Bioscienc-es, Sweden). Protein Identification of peptide fragments wasperformed by using in built ‘Ettan MALDI Software’ with‘proteo Matrics LLC’ search engine. The criterion given forsearch was oxidation at methionine residues, carbamidom-ethylation at cysteine residues, up to 1 missed cleavage wasallowed and the protein was searched against the nonredun-dant database.

Results

“Plasmo2D” analyzes P. falciparum proteome based on theirpI and molecular weight. By plotting all the 5331 proteinspresent in the P. falciparum database as a function of their pIand molecular weight, we generated a virtual 2D for the parasiteproteome. The scale on the X-axis was established based onmigration of proteins with known pI values after isoelectricfocusing and the scale on the Y-axis was established based ondistance of migration of molecular weight standards on SDS-PAGE (see methods). Figure 1, shows a virtual 2-D where weplotted all the proteins from the Plasmodium database withcoordinate on the X-axis being the theoretically calculated pIvalue and Y-axis corresponding to distance of migration basedon their molecular weights. The parasite proteome showedbimodal distribution in the basic range (between pI of 8 to 10)and in the acidic range (between pI 4 to 7). Proteins withrelatively basic pI were somewhat more abundant than thosewith acidic pI values. There were very few proteins with pIvalues below 4.5 and also very few proteins with pI values above10. Interestingly, the pI range around pH 7 was also verysparsely populated as shown in Figure 1 (Table).

Description of the Tool. “Plasmo2D” is a semiautomaticuser-friendly tool that aids in the identification of proteins inthe P. falciparum 3D7 proteome from the 2-DE gel image. Thetool works on windows operating system. On executing theprogram, the user has to provide as input the complete pathof the 2D image file in .gif or.jpeg format. Subsequently, theimage is loaded. The window on which image is being loadedhas pI and MW markers marked on it, based on the migrationdistance data. To minimize gel/image distortion, the user canoverlap the markers of the gel image on the marker providedby the software using the image resizes buttons in the software.Now user can click on the desired protein spot to retrieve theinformation about it.

Background Dataset (Virtual 2D) Correlation. The coordi-nates of the clicked spot are compared with the coordinates ofall the proteins in the dataset. All proteins present within 0.4cm radius are considered a match. The stringency of searchcan however be adjusted by varying the radius size.

The Output. The output window of Plasmo2D displays thelist of potential candidate proteins corresponding to the spotof interest. The list provides (a) PlasmoDB protein ID (b) Nameof the protein (c) pI (d) Molecular weight (e) Score. The scorereflects the confidence level in prediction of the right protein.The scoring system is taken from the data available from theanalysis of protein expression for the malarial parasite.21 Here,the expression level of individual parasite proteins, derivedfrom the spectral count of their peptides has been taken intoaccount. The scoring system thereby provides greater score toprotein that are expressed at high levels. In addition a facility

migration dist. (Y-axis) ) ((9.4814173 * MW 1.1576522) -

375.104)/(33.710706 + MW 1.1576522)

migration dist. (X-axis) ) (1.1319 * pI) - 3.9028

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Figure 1. Screenshot of the different interfaces of“Plasmo2D”. The input frame displays the 2-DE gel image. On clicking the spot onthe image using the mouse cursor, the virtual 2D dataset is queried at the background and the likely set of proteins are displayed ina different output frame. Theoretical pI and molecular weight of all the annotated P. falciparum protein sequences were plotted (Virtual2D proteome profile) with pI along X-axis and molecular weight along Y-axis corresponding to their migration distances.

technical notes Khachane et al.

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is provided to classify the listed proteins according to theirintracellular localization and their proposed function. Theclassification is based on the information available on Plas-moDB (www.plasmodb.org) web site. A screenshot of differentinterfaces of Plasmo2D is shown in Figure 1(Input and Output).

Validity of Plasmo2D: The Tool Identifies Proteins ofVaried Size and pI in the Parasite Proteome. We used“Plasmo2D” to analyze proteins from Plasmodium falciparumresolved on a 2-DE. We selected three among the abundant

protein spots (labeled as Spots 1, 2, and 3) for analyses using“Plasmo2D”. Cell lysate was prepared saponin-freed parasites(see methods) by lysing the parasites in 2D lysis buffer andexamined by 2-DE and western blotting using anti-PfHsp90,anti-PfHsp70 and anti-PfBiP. The immunoblots were subjectedto Plasmo2D analysis. As shown in Figure 2A, several proteinspots were visible on the 2-DE of metabolically labeled totalparasite lysate. Figure 2B shows the location of spots inimmunoblots probed with anti-PfHsp90 (spot 1), anti-PfHsp70

Figure 2. Validation of ‘Plasmo2D’ by western blotting and MALDI/TOF mass spectrometry. Plasmodium falciparum-infected erythrocyteswere metabolically labeled and lysed in NETT buffer. Panel A shows the labeled protein profile of P. falciparum cell lysate resolved ona 2-DE. Panel B indicates the location of spots in immunoblots probed with anti-PfHsp90 (spot 1), anti-PfHsp70 (spot 2) and anti-PfBiP(spot 3). Panel C shows the lists of proteins identified by ‘Plasmo2D’ corresponding to spots 1, 2, 3, 4, and 5 marked in panel A. It alsoshows MALDI-TOF spectra and peptide mass fingerprint analysis of the above-mentioned spots. All the mass spectrometry proteinidentification search results are significant with E-value < 0.5 and Rank 1, where ‘Rank’ is the probability that the candidate protein isthe sample protein and ‘E-value’ is the statistical expectation value with a value of representing 1% statistical probability that theprotein is a random hit.

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(spot 2) and anti-PfBiP (spot 3). Figure 2C shows the lists ofproteins identified by the program for these spots. Indeed theseproteins were included in the list derived by “Plasmo2D”. Weconfirmed the identities of 3 of these spots also by MALDI-TOF. Tryptic digestion of the protein spots was performed asdescribed under methods. It also shows peptide mass finger-prints of these proteins. Analysis of these peptide massfingerprints using search engines revealed the identity of theseproteins to be PfHsp90 for spot no. 1, PfHsp70 for spot no. 2,and PfBiP for spot no. 3. The results confirmed the validity of‘Plasmo2D’ approach. We also examined the efficiency of theprogram for 2 unknown proteins from 2-DE. The MALDI-TOFanalysis was done for spots 4 and 5 (labeled in Figure 2A). Theidentities of spots 4 and 5 were Pftubulin and PfPDI, respec-tively. These proteins were also included in the list derived by“Plasmo2D”. In all of the above cases the correct protein IDwas given the highest score by plasmo 2D. The analysisconfirmed that “Plasmo2D” is able to provide tentative iden-tifications of proteins from their 2-DE profiles.

Discussion

Developing efficient tools to organize, analyze, and harnessthe information content in the genome sequences has becomean important priority in the post genomic era. Release ofPlasmodium falciparum genome sequence two years ago hastriggered a burst of activity among bioinformaticians interestedin parasite biology. In addition to purely bioinformatics toolsfor sequence analysis, alignments, search for homologues,modeling, and prediction of functions, other tools that interfacetheoretical and experimental approaches have also beendeveloped to aid genomic and proteomic approaches. Identi-fication of low abundance proteins expressed during differentstages of the parasite, from protein complexes and fromsubcellular fractions is an important part of proteomic studies.Mass spectrometric analysis of peptide mass fingerprints iscurrently the method of choice for protein identification.22

Several bioinformatics tools have been developed to supportanalysis of peptide mass fingerprints for identification ofprotein being analyzed. There are several commercial toolsavailable for gel to gel comparisons and analysis of 2-DE(Melanie, Progenesis, 2Dquest, Decode, Gel-Pro analyzer, Gelcompart, Protplot, Flicker etc). These tools are more useful ingel warping and spot Quantitation. None of these tools,however, allow identification of protein from a spot on a 2Dgel. In this paper, we have described a tool to aid tentativeidentification of parasite proteins using an approach of 2-DE.This is the first effort to use a synthetic 2-D for proteinidentification and is particularly relevant to experimentallychallenging systems such as Plasmodium falciparum.

2-DE resolves proteins based on unique molecular weightand pI of each protein. We have exploited the same principleto facilitate identification of proteins elaborated on a 2-DE. Bytheoretically deducing the pI and molecular weight for eachprotein reported in the Plasmodium database, we have gener-ated a theoretical 2-DE encompassing the entire Plasmodiumfalciparum proteome. We developed a software called“Plasmo2D”, which allows one to superimpose and link anexperimental 2-DE with the theoretical 2-DE. By a click of thecursor on the spot of interest on a 2-DE, “Plasmo2D” analysisprovides a list of proteins, which the spot is likely to correspondto. The approach allows one to quickly narrow down theidentity of a particular spot on a 2-DE gel to a few proteins.From the knowledge of the sample used for the experimental

2-DE one can eliminate out certain proteins from the listobtained. Thus, starting with an image of a 2-DE showing spotscorresponding to different parasite proteins, the tool allows oneto get a tentative ID for any spot of interest on the gel. Theanalysis of total lysates from Plasmodium falciparum bywestern blotting and MALDI-TOF mass spectrometry presentedhere validates and confirms the value of “Plasmo2D” inproteomic analysis.

The sensitivity of “Plasmo2D” analysis is adjusted in therange of 0.3 pI units Thereby, all proteins within a range of 0.3pI units from the spot of interest will be included in the list.While this result in an increase in the number of predictedidentities for a given protein spot, it also allows the tool to coverpI shifts due to post-translational modifications that a proteinmight undergo. For example, if the pI of a protein of interesthas shifted to an acidic value due to phosphorylation, themodified protein spot will still be included in the list of proteinsidentified. Indeed, acidic shifts in pI due to phosphorylationare commonly observed on 2-DE gels.23

“Plasmo2D” analysis is not suitable for absolute identifica-tion of protein spots of interest from an experimental 2-DE butis designed to be an ancillary tool. Further confirmation ofprotein identification becomes easier with approaches such aspeptide mass fingerprinting using MALDI-TOF. The mainadvantage of this tool lies in its ability to provide quick analysisand easy adaptability. The current tool is designed to analyzea 10% gel run on a standard Ettan IPGPhore (AmershamBiosciences) of 7 cm length; the system has the flexibility tobe adapted to other experimental 2-DE systems. The approachcan also be expanded for analysis of other organisms whosegenome sequences are available. “Plasmo2D” will serve as animportant aid in rapid characterization of protein complexes,pathways, and compartments in the malarial parasite.

Conclusions

Plasmo2D aims to facilitate analysis of parasite proteomesby providing rapid identification of parasite proteins from astandard 2-DE platform. The main advantage of this tool liesin its ability to provide tentative protein identifications evenfrom a radio labeled protein spot on a 2-DE. Some approacheswhere Plasmo2D is likely to be of particular value are identi-fication of low abundance protein components in (a) proteincomplexes, e.g., in a co-immunoprecipitation experiment (b)subcellular organellar fractions of the parasite and in (c)analyzing their stage specific expressions.

Abbreviations. PfHsp70, 70 kDa heat shock protein ofPlasmodium falciparum; PfHsp90, 90 kDa heat shock proteinof Plasmodium falciparum; PfBiP, 72 kDa binding protein ofPlasmodium falciparum; MW, Molecular weight.

Acknowledgment. The authors thank Indo-FrenchCenter for the Promotion of Advanced Scientific Research(IFCPAR), Department of Biotechnology (DBT), and NMITLIprogram of Council for Scientific and Industrial Research(CSIR), New Delhi for their financial support.

Supporting Information Available: Supporting In-formation Table 1. Training set data with migration distanceis provided. Panel A lists the proteins, their molecular weights(in kDa) and migration distance (in cm) used for molecularweight training data set. Panel B lists the proteins, their pI andmigration distance (in cm) used for pI training data set. This

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material is available free of charge via the Internet at http://pubs.acs.org.

References

(1) Gardner, M. J.; Hall, N.; Fung, E.; White, O.; Berriman, M.; Hyman,R. W.; Carlton, J. M.; Pain, A.; Nelson, K. E.; Bowman S.; et al.Nature 2002, 419, 498-511.

(2) Ben Mamoun, C.; Gluzman, I. Y.; Hott, C.; MacMillan, S. K.;Amarakone, A. S.; Anderson, D. L.; Carlton, J. M.; Dame, J. B.;Chakrabarti, D.; Martin, R. K.; Brownstein, B. H. Mol. Microbiol.2001, 39, 26-36.

(3) Bozdech, Z.; Zhu, J.; Joachimiak, M. P.; Cohen, F. E.; Pulliam, B.and DeRisi, J. L. Genome Bio. 2003, 4, R9.

(4) Bozdech, Z.; Llinas, M.; Pulliam, B. L.; Wong, E. D.; Zhu, J. andDeRisi, J. L. PLoS Biol. 2003, 1, E5.

(5) Lasonder, E.; Ishihama, Y.; Andersen, J. S.; Vermunt, A. M.; Pain,A.; Sauerwein, R. W.; Eling, W. M.; Hall, N.; Waters, A. P.;Stunnenberg, H. G.; et al. Nature 2002, 419, 537-542.

(6) Florens, L.; Washburn, M. P.; Raine, J. D.; Anthony, R. M.;Grainger, M.; Haynes, J. D.; Moch, J. K.; Muster, N.; Sacci, J. B.;Tabb, D. L.; et al. Nature 2002, 419, 520-526.

(7) Raman, B.; Cheung, A.; Marten, M. R. Electrophoresis 2002, 23,2194-2202.

(8) Appel, R. D.; Vargas, J. R.; Palagi, P. M.; Walther, D.; Hochstrasser,D. F. Electrophoresis 1997, 18, 2735-2748.

(9) Cutler, P.; Heald, G.; White, I. R.; Ruan, J. Proteomics 2003, 3,392-401.

(10) Efrat, A.; Hoffmann, F.; Kriegel, K.; Schultz, C.; Wenk, C. J.Comput. Biol. 2002, 9, 299-315.

(11) Gevaert, K.; Vandekerckhove, J. Electrophoresis 2000, 21, 1145-1154.

(12) Hiller, K.; Schobert, M.; Hundertmark, C.; Jahn, D.; Munch, R.Nucleic Acids Res. 2003, 31, 3862-3865.

(13) Halligan1, B. D.; Ruotti1, V.; Jin1, W.; Laffoon3, S.; Twigger1, S.N.; Dratz, E. A. Nucleic Acids Res. 2004, 32, 638-344.

(14) O’Farrell, P. H. J Biol. Chem. 1975, 250, 4007-4021.(15) Kumar, N.; Koski, G.; Harada, M.; Aikawa, M.; Zheng, H. Mol.

Biochem. Parasitol. 1991, 48, 47-58.(16) Bonnefoy, S.; Attal, G.; Langsley, G.; Tekaia, F.; Puijalon, O. M.

Mol. Biochem. Parasitol. 1994, 67, 157-170.(17) Patrickios, C. S; Yamasaki, E. N. Anal. Biochem. 1995, 231 (1),

82-91.(18) Celis, J. E. Cell Biology 1998, A Laboratory Manual, 2nd ed.;

Academic Press: California, USA, Vol. 4, 398-404.(19) Banumathy, G.; Singh, V.; Tatu, U. J. Biol. Chem. 2002, 277, 3902-

3912.(20) Kumar, Y.; Uppuluri, N. R. V.; Babu, K.; Phadke, K.; Kumar, P. P.;

Ballal, S.; Tatu, U. Curr. Sci. 2002, 82, 655-663.(21) Le Roch, K. G.; Johnson, J. R.; Florens, L.; Zhou, Y.; Santrosyan,

A.; Grainger, M.; Yan, S. F.; Williamson, K. C.; Holder, A. A.;Carucci, D. J.; Yates, J. R. Genome Res. 2004, 14, 2308-2318.

(22) Kumar, Y.; Tatu, U. Proteomics 2003, 3, 513-526.(23) Khachane, A.; Kumar, Y.; Belwal, M.; Das, S.; Somsundaram, K.;

Tatu, U. Proteomics 2004, 4, 1672-1683.

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