Proteomics in Malaria Jeffrey R. Johnson, Laurence Florens,† Daniel J. Carucci,‡ and John R. Yates III* Department of Cell Biology, The Scripps Research Institute, La Jolla, California 92037 Received September 29, 2003
The recent completion of human, Anopheles gambiae, and Plasmodium falciparum genomes relevant to the study of human malaria allows the application of modern proteomic technologies to complement previously implemented conventional approaches. Proteomic analysis has been employed to elucidate global protein expression profiles, subcellular localization of gene products, and host-pathogen interactions that are central to disease pathogenesis and treatment. The high-throughput nature of these techniques is in accord with the pace of drug and vaccine development that have the potential to directly reduce the morbidity and mortality of disease. Keywords: malaria • Plasmodium falciparum • proteomics • mass spectrometry
Introduction One of the oldest infectious diseases on the planet, malaria still casts a formidable shadow on many parts of the world, causing hundreds of millions of new infections and millions of deaths each year.1 The characterization of genes in the Plasmodium genus of apicomplexan parasites, the causative agents of malaria, has been hindered by the lack of efficient methods for transient and stable transfection commonly used to probe gene functions that have proven successful only a handful of times.2-5 Yet the outlook is bright due to sequencing efforts that have yielded complete genome sequences of human,6 mouse,7 mosquito,8 and most recently, two Plasmodium species, P. falciparum,9 and P. y. yoelii.10 Researchers are now beginning to use these datasets to complement conventional approaches with sensitive and high-throughput methods to characterize gene and protein expression, protein-protein interactions, and protein localization. These methods aim to fulfill the pressing need to characterize the function of P. falciparum genes, a required step to develop a malaria vaccine as well as new drugs replacing those that have succumbed to resistance. DNA microarrays have been implemented to observe patterns of gene expression in the parasite, even prior to the completion of the parasite genome sequences using expressed sequence tag and gene sequence tag datasets.11,12 More recently, the released genome sequence of P. falciparum has allowed two independent studies of mRNA expression across the entire parasite life cycle13 and across short time intervals within the intraerythrocytic developmental cycle (IDC).14 The first study described methods for functional annotation of the >60% of genes lacking annotated functions by way of gene expression clustering followed by correlating temporal patterns of expres* To whom correspondence should be addressed. E-mail: jyates@ scripps.edu. Fax: (858) 784-8883. † Present address: The Stowers Institute for Medical Research, Kansas City, MO 64110. ‡ Naval Medical Research Center, Malaria Program (IDD), Silver Spring, MD 20910.
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sion with similar functions or cellular processes.13 The second revealed a dramatic cascade of gene expression where over 75% of genes are activated only once during the IDC, with their activation correlated to time-specific biological processes.14 Both studies provide valuable information about the vast number of hypothetical proteins for which data was previously absent, however these studies are limited to observations at the level of transcription, whereas information regarding protein expression, modification, and localization cannot be inferred. This is a significant limitation when attempting to resolve those proteins that effectively generate an immune response, for example, considering that this small fraction of proteins are likely to be secreted or membrane proteins expressed at the cell surface. To identify these proteins, their subcellular localization is of prime importance and genetic expression profiles cannot give the answer. In combination with proteomic datasets, however, data-mining approaches utilizing the union of quantitative genetic and protein expression profiles look to be a promising tool for gathering information regarding the post-transcriptional regulation of expressed genes.15-17 To study the dynamic nature of the P. falciparum parasite, efforts to characterize gene expression directly at the proteomic level have been successful at gathering previously unavailable information, especially with respect to the more inaccessible mosquito stages of the parasite that cannot be easily cultivated in vitro. Global proteomic profiles that delineate protein expression according to the distinct parasite life cycle stages have been obtained and may provide drug developers with new targets specific for certain stages. With relevance to vaccine development, host-pathogen interactions elucidated at the proteomic level will be valuable tools to identify antigens that elicit a powerful immune response to combat an infection. Host-drug and pathogen-drug interactions are valuable as well in dissecting the mechanisms of drug action and resistance, and minimizing debilitating side effects. In addition, information about the post-translational modifications and subcellular localization of proteins will aid in understanding disease 10.1021/pr0340781 CCC: $27.50
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Figure 1. Life cycle of Plasmodium falciparum. Parasite-infected mosquitoes inject the sporozoite form upon bloodmeal consumption. Sporozoites travel to the liver where they mature to merozoites, which invade red blood cells and cycle through the ring, trophozoite, and schizont stages, eventually producing new merozoites. A subset of merozoites develop into gametocytes that are taken up by mosquitoes and develop into gametes that fertilize to form a zygote in the mosquito midgut. Zygotes mature into ookinetes that cross the endothelial lining of the midgut to form a sporozoite-containing oocyste. Upon oocyste lysis, sporozoites migrate to the mosquito salivary glands to infect another human host.
processes and provide researchers with detailed databases containing information regarding protein structure and function.18 Through the combined results of these proteomics applications, primary genomic sequence information will aid in tackling the disease mechanisms of malaria that have eluded scientists for centuries. Protein Expression Profiling. Several advances in highthroughput proteomics technologies have created the foundation for the global analysis of proteins from cellular extracts. Considered by many to be the classical proteomics experiment, the goals of protein expression profiling are to maximize the identification and quantification of components contributing or unique to a particular disease state, tissue type, or in the case of malaria, life-cycle stage. The incredibly complex life cycle of Plasmodium consists of markedly different morphological stages (Figure 1), each with distinct patterns of protein expression that coordinate survival and reproduction within Anopheles and human hosts. A glimpse into these patterns of protein expression can aid vaccine and drug design to target stage-specific factors and can also help determine protein function by correlating protein expression with life cycle stages that perform stage-specific processes. Two general strategies have emerged for profiling protein expression. The more conventional approach involves twodimensional polyacrylamide gel electrophoresis (2D-PAGE) of a cellular lysate followed by gel excision of silver-stained protein
spots, digestion, and subsequent protein identification by either peptide mass fingerprinting using MALDI-TOF or direct peptide sequencing by tandem mass spectrometry. Advances in electrospray ionization and streamlining liquid chromatography with mass spectrometry (LC-MS/MS) have led to a second approach that directly couples peptide separation with mass analysis.19 A particular implementation of LC-MS/MS, often referred to as “shotgun” proteomics, applies proteolytic digestion to a whole cellular lysate en masse followed by separation of the peptides by an online 2D-liquid chromatography system that is coupled with a mass spectrometer for peptide identification.20 Application of multidimensional protein identification technology (MudPIT) led to the largest analysis of the yeast proteome to date.21 2D-LC-MS/MS and 2D-PAGE approaches have been shown to complement each other when combined to increase protein identification, as has been demonstrated by the analysis of the rice proteome.22 2D-PAGE. While gel-based approaches are more common, they are also limited to the representation of a fraction of protein content due to an inherently limited pH and molecular weight range. Most 2D-PAGE studies are also insufficient for the analysis of membrane proteins, but new techniques and reagents improving membrane protein analysis by 2D-PAGE have been recently developed to meet this demand.23,24 One study applied these techniques for the improved solubilization and 2D-PAGE analysis of membrane proteins to Journal of Proteome Research • Vol. 3, No. 2, 2004 297
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erythrocytes.25
Plasmodium falciparum-infected During the erythrocytic life stages, the parasite expresses secreted proteins that are relocated to the cell surface and are thought to affect the adherence of infected erythrocytes to the endothelium of internal organ capillaries26 and possibly participate in the uptake of nutrients for the parasite (reviewed in ref 27).27 Parasite-derived proteins are also responsible for creating Maurer’s clefts and knob-like structures on the erythrocytic membrane. These membranous structures play a role in the lysis of the host cell and the release of parasites that continue on to infect other red blood cells.28 To characterize these proteins, the extraction and separation of proteins located in the membrane of infected red blood cells was optimized utilizing a variety of chaotropic mixtures with detergents of defined length and structural features. A red blood cell protein with twelve putative transmembrane domains called band III, the cleavage of which by a parasite-derived protease appears to be essential for parasite entry,29 was used to evaluate membrane protein solubilization. Band III was successfully solubilized and detected on 2D gels where it was previously undetected, but it was detected at equal to higher levels in 2D gels of infected compared with uninfected red blood cells, disagreeing with its predicted cleavage necessary for parasite entry. Comparing the 2D gels of noninfected and infected preparations, several protein spots were identified that were abundant only in infected preparations compared with uninfected and were only weakly detected in a free parasite preparation. Unfortunately, these proteins remain unidentified due to the status of the public database at the time, but hopefully the most recent database release9 will make it possible to determine the role of these proteins in erythrocyte structural remodeling during infection. Another recent 2D-PAGE study investigated sex-specific and blood meal induced proteins in the midgut of Anopheles gambiae, the mosquito vector responsible for P. falciparum transmission.30 Sporogonic development of parasites takes place in the lumen and epithelium of the mosquito midgut, thus gametes must first escape the peritrophic matrix surrounding the parasite-containing blood meal to gain access to the midgut and continue development.31,32 To distinguish those proteins involved in parasite escape from the peritrophic matrix, 2D-PAGE profiles of male mosquitoes (which never ingest blood) and female mosquitoes fed with either sugar or blood were compared. Ten protein spots were detected uniquely on 2D gels of female mosquitoes after feeding on a blood meal, but similar to the previous study, these proteins were not identified due to an incomplete sequence database. These proteins may be involved in blood digestion or formation of the peritrophic matrix and their functions may be affected by an infection, thus their identification and the elucidation of their function in uninfected mosquitoes could lend valuable insight regarding the parasite’s escape mechanism from the peritrophic matrix. The recent completion of the Anopheles gambiae genome sequence8 should permit the identification of these proteins. LC-MS/MS. While 2D-PAGE proteomics have been applied extensively to study proteins correlated with disease states, nongel based approaches have several advantages over these methods, including increased sensitivity, throughput, and the ability to analyze proteins with a wide range of properties within highly complex mixtures. In particular, the high amount of starting material required for 2D-PAGE analysis renders this method of proteomic analysis insufficient for poorly accessible 298
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stages of the Plasmodium life cycle, such as the sporozoite stage, whereas LC/MS approaches are able to characterize a large number of proteins.33 Illustrating the versatility of LC/ MS-based proteomics, two proteomic analyses of P. falciparum were performed side-by-side with the completion of its genome resulting in a snapshot of stage-specific protein expression as well as information that aids genome annotation. The first of these studies was a large scale analysis using MudPIT of both mosquito and vertebrate stages, analyzing protein expression patterns from the following: (1) sporozoites, the stage injected from mosquitoes into human hosts, (2) merozoites, the stage actively invading red blood cells, (3) trophozoites, the asexually reproducing stage within red blood cells, and (4) gametocytes, the sexual gamete precursors in the blood that mature to gametes within the mosquito midgut following bloodmeal consumption (Figure 1).34 Malaria parasites present a particular challenge to whole proteomic analysis in that they cannot be grown as a homogeneous cell culture, but must be purified from host cell material (mosquito or animal). Two levels of control were implemented to differentiate host proteins from parasites. First, noninfected erythrocytes and Plasmodium-free mosquitoes were used as controls for blood stage parasites and sporozoites, respectively. From all four stages analyzed, 12 258 unique peptides were assigned to parasite proteins. Table 1 of ref 34 indicates the distribution of identified proteins by the different stages in which they were detected. Only 86 (0.7%) of those peptides were also found in noninfected controls. Most of those peptides belonged to proteins with sequences conserved across genomes, such as ribosomal and heat shock proteins, tubulins, and actins. Because those peptides could not be unambiguously assigned, they were removed from the final parasite peptide list. Only seven parasite proteins, most of which were single peptide hits, were discarded because of these ambiguous peptides. We concluded that the local sequence similarity between Plasmodium proteins and those of the hosts was sufficiently low, enabling us to identify parasite-specific proteins. Second, MS/MS datasets were searched against combined databases, parasite/human or parasite/mosquito, to account for spectra resulting from contaminating host peptides. At the time of the analysis, the Anopheles genome was not available, thus the mosquito stage samples were searched against diptera sequences, which included Anopheles, Aedes, and Drosophila proteins. Incidentally, using Drosophila protein sequences proved an efficient way to identify mosquito proteins. A comparative genomic analysis of two diptera35 showed that an average of 65.4% local sequence identity was observed for the most similar exons. With 1173 Drosophila proteins identified from mosquito peptides, our analysis suggested a high local sequence identity at the proteome level as well. On average, 52% of the proteins identified from blood stage samples were host erythrocyte proteins (Figure 2). A high level of contamination (68%) by host proteins was observed for sporozoite samples purified by Percoll gradient methods (Figure 2). When sporozoites were purified further using monoclonal antibodies against the circumsporozoite protein (one of the major sporozoite surface proteins) coupled to magnetic beads, the contamination by host proteins was reduced by 30%. Figure 1 clearly illustrates why the shotgun approach was the preferred method for such a heavily contaminated type of sample. Running such a sample on a 2D-PAGE gel would entail a 50% chance of selecting a contaminating host protein, whereas in
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purification method
sporozoite
manual dissection of A. stephansi mosquito salivary glands 14-days post-infection; parasites purified from host using a Renograffin-60 density gradient109 extraction from highly synchronizedb schizont-stage erythrocytes using Saponin; passage through size-selective membrane filters to purify merozoite stage parasites from larger schizonts110 trophozoite-stage erythrocytes purified from highly synchronizedb cultures on 70% Percoll-alanine111; extracted from erythrocytes with Saponin cultures synchronized using a temperature-cycling incubator112 were maintained unti very few asexual parasites remained; gametocyte-infected erythrocytes form the 52.5%/45% and 45%/30% interfaces of a Percoll gradient113
merozoite
trophozoite gametocyte
host proteins identified
P. falciparum proteins identified
1275
1039
911
839
1251
1036
1159
1147
a P. falciparum strain 3D7 (Oxford) was used for all experiments. b Synchronization of these stages was achieved through treatment with Sorbitol that lyses erythrocytes infected with late-stage parasites (trophozoites and schizonts) but leaves erythrocytes infected with early-stage parasites unharmed.
Figure 2. Computer-generated two-dimensional plot of proteomic results. Parasite- and human-derived proteins detected by proteomic analysis34 are plotted for four P. falciparum stages: sporozoites, trophozoites, merozoites, and gametocytes. Many proteins detected represent extremes in pI and molecular weight that would likely not be detected by 2D-PAGE analysis.
the shotgun approach, all the peptides are analyzed together, the wheat being separated from the chaff in silico. By using combined databases and noninfected controls, 2417 parasite proteins were confidently identified out of thousands of host proteins, i.e., ∼46% of the 5283 genes encoded in the genome were detected in just four stages of the malaria life cycle. Sporozoite, merozoite, trophozoite, and gametocyte analyses contributed 1039, 839, 1036, and 1147 proteins to the final tally, respectively. The methodology described here should serve as a model for proteomic analyses of interspecies heterogeneous samples, such as from tissue samples containing pathogenic organisms or neoplastic cells. The published results indicated unexpected stage expression for many Plasmodium proteins, including the detection in the sporozoite stage of several PfEMP1 and rifin polymorphic surface proteins, which are part of large, multigene families.27,36 The sporozoites, which do not replicate until they reach the
host liver and develop into merozoites, may display an array of these genes to evade immune detection, whereas asexual stages of the parasite replicate frequently allowing for antigenic switching of their expressed antigens and do not require the expression of these genes for survival in the host. Although controversial when first published, these results are now confirmed by the observed mRNA expression for 22 of 23 var genes in a large-scale microarray analysis of the parasite.13 Also confirmed by the transcriptomic analysis was the observation that coexpressed genes tended to cluster along the chromosomes, indicating a high order of genome organization. In addition, a large number of proteins predicted to have at least one transmembrane segment and/or a signal peptide sequence were identified (439 and 304, respectively), of which more than half were annotated as hypothetical proteins. These proteins with no sequence similarity within other species may indeed be Plasmodium-specific factors that, by virtue of being transJournal of Proteome Research • Vol. 3, No. 2, 2004 299
reviews membrane or secreted proteins, could be vulnerable to immune discretion. Proteomic profiling analyses of several other P. falciparum stages (rings, schizonts, and gametes), as well as mosquito stages from P. gallinaceum (ookinetes and zygotes), P. berghei, and P. yoelii are underway. The second study37 analyzed proteins from a mixture of late asexual blood stages (trophozoites and schizonts), gametes, and gametocytes extracted from P. falciparum. This approach combined a separation step on 1D-PAGE followed by systematic cutting of the gel in one cm increments and analysis of the digested slices by LC-MS/MS. Several stage-specific proteins were putatively assigned on the basis of not only their detection within particular samples but also the quantitative comparison of integrated ion currents for the peptides identifying these proteins between samples. This method of approximate quantitation should be used with caution, as it is only reliable using highly reproducible preparations. Vastly different peptide elution times will lead to inconsistent buffer conditions and may differentially affect peptide ionization efficiency, therefore comparison of ion intensities may incorrectly quantify the relative amount of peptide present if the elution times are not tightly coordinated. To address this concern, the authors only compared the integrated ion current of peptides that eluted within 3 min of each other in separate analyses. This paper also addressed the ability of proteomics to assist in database annotation. The completion of the P. falciparum genome marks the first sequencing project of an (A+T)-rich (80%) genome.38 This unique property of the parasite genome has not only created difficulties in genome sequencing efforts, but it also creates a quandary with respect to gene prediction by algorithms that have been trained using organisms with drastically different genomic properties. Thus, techniques indicating expressed gene products in a highthroughput fashion and creating large subsets of data can aid in the training of useful modeling algorithms for this organism. Datasets obtained in this study were searched directly against the P. falciparum raw genomic database in addition to the annotated database resulting in a large number of “orphan” peptides that were detected uniquely from the genomic database.37 These peptides may arise from incorrect intron/ exon or start site predictions, and some may be peptides from regions of the genome incorrectly assigned as noncoding. A similar strategy was applied to aid the annotation of the P. y. yoelii genome, which was sequenced using a shotgun approach at low coverage, by providing proteomic information highlighting expressed products.10 In this case, the proteome analysis and genome annotation efforts progressed side-by-side with the proteomic analysis identifying 83 expressed regions of the genome that were not assigned by the initial P. y. yoelii gene model. Several of these regions occurred near a gene-modeled region, indicating areas of improvement in gene model prediction. Single peptide hits comprise a large portion of proteins identified from both studies, and recent claims have questioned the validity of these identifications.39 The fractions of proteins identified by single peptides were not drastically different: 44% and 32% for the Florens et al. and Lasonder et al. papers, respectively. For increased confidence regarding these matches, Florens and co-workers manually evaluated the spectra of low coverage loci for baseline noise intensity, b/y ion continuity, and fragmentation patterns. All of the over 2400 proteins submitted were identified from peptides which met certain criteria upon matching to predicted spectra, including stringent 300
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cross-correlation values (Xcorrs) calculated by Sequest,40 and a significant difference between Xcorrs of the best and secondbest matches. The presence of a Lys or Arg residue was only required at either end of the peptides, mostly to account for the fact that about half of the dataset had been generated from insoluble fractions, in which case the proteins were first chemically cleaved by cyanogen bromide in formic acid. In addition, it has been widely demonstrated that proteolytic digestion with trypsin often generates nontryptic peptides due to chymotrypsin impurities, chymotryptic activity of pseudotrypsin (generated by trypsin self-cleavage), or fragmentation within the mass spectrometer.41-43 Indeed, 34% of all peptides identified were half-tryptic, indicating that this is a common occurrence. Comparison from results of global mRNA expression profiling confirmed the expression of all but 72 of over 1000 genes for which proteins were detected in the merozoites or trophozoite stages of proteomic analysis.13 Lasonder and coworkers used probability-based scoring provided by the Mascot algorithm44 to match observed fragment ion masses obtained using high accuracy MS (reported mass deviation of 0.03 Da) to calculated fragment ions of tryptic peptides from both human and P. falciparum proteins databases. Similar constraints were applied to filter these data as above, and spectra receiving low Mascot scores were manually evaluated, however half-tryptic peptides were discarded, and over 200 identified peptides had lengths much shorter than 7 amino acids that are rarely long enough to be unique in either host or pathogen genomes. Subcellular Localization. Perhaps the clearest illustration of the need for functional characterization of Plasmodium genes is the presence of over 60% of proteins in the annotated P. falciparum database listed as hypothetical proteins.9 One approach to resolve this issue makes use of large-scale proteomics studies to produce subcellular localization data that infer protein function based on location. The complex anatomy of the Plasmodium parasite compartmentalizes proteins within function-specific organelles. Apical organelles are the secretory vesicles of the parasite: proteins localized within the micronemes aid in initial selection of host cells and in gliding motility, rhoptries appear to contain proteins involved in the formation of the parasitophorous vacuole, and dense granules are thought to contain proteins that modify the host cell following invasion.45 Also of significance is the digestive vacuole that contains the site of hemoglobin digestion and heme detoxification.46 This organelle is of particular interest since chloroquine, the most historically effective drug to fight malaria, is thought to exert its effects by blocking the heme detoxification process.47,48 Widespread chloroquine resistance has intensified the study of processes within the digestive vacuole in order to understand mechanisms of drug resistance.49-51 As opposed to the global protein profiling methods described above, which analyze the protein complement of whole cell lysates across various life cycle stages, subcellular localization data are obtained by analyzing subset proteomes gathered by the selective purification of cellular components or the isolation of specific organelles. Antigens expressed on the surface of malaria-infected erythrocytes are promising targets for vaccine development due to their accessibility to the immune system, however most surface antigens that have been previously characterized are polymorphic and have evolved mechanisms for immune evasion.52 A new method described by Florens and co-workers to enrich surface proteins and subsequently apply LC-MS/MS proteomic
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analysis has led to the identification of two novel surface proteins encoded by highly conserved single copy genes.53 Two nonpermeable biotins, Sulfo-NHS-LC-Biotin and PEO maelimide activated Biotin, were used to label late erythrocytic parasite stages (late trophozoites and schizonts), followed by cell lysis and Streptavidin-affinity chromatography to retain labeled proteins. Eluates were analyzed by MudPIT54 because of its ability to analyze complex membrane protein mixtures that are difficult to resolve by 2D-PAGE methods. Thirty-six candidate proteins were identified that were novel, uncharacterized gene products and had a predicted signal peptide and/ or predicted transmembrane domain(s). Two of these candidates were further characterized by raising antibodies against them. Immunofluorescence labeling of infected erythrocytes confirmed localization at the erythrocyte surface. These proteins were also labeled in P. falciparum strains lacking the protruding knob structures at the erythrocyte surface and in rosetting-negative strains, indicating that the novel surface proteins are not knob-associated and are not involved in the rosetting process. Sequence analysis revealed that one of the proteins belongs to a cluster of adjacent, coexpressed genes that also includes Pfsbp1, the skeleton binding protein 1. The proteins expressed in this cluster, including the identified surface antigen, are likely to form a complex that has been previously suggested to translocate parasite proteins to the erythrocyte surface.55 A vaccine targeting this surface antigen is alluring since the protein is not polymorphic, and its potential involvement in a multiprotein complex indicates that antibody inhibition of this protein could disrupt the translocation of other variant proteins to the erythrocyte surface. The extent of post-analysis validation performed for these studies illustrates an often overlooked process. With the increased complexity associated with whole-organism genomic databases comes an increased chance of obtaining spurious peptide matches that may lead to false biological conclusions, causing some researchers to be weary of drawing a direct biological explanation from proteomic data. Experimental biochemical techniques such as immunofluorescence microscopy, Western blot analysis, and RT-PCR are often employed to ensure that proteins detected by proteomic analysis are indeed present, and as illustrated in these studies, these followup procedures often reveal even more interesting results than simple validation. Host-Pathogen Interactions. The high-throughput detection of interactions between parasite and host factors is essential in advancing Plasmodium research toward the identification of effective immune targets for vaccination and immune protection. The demonstration that protective immunity could be induced in rodent models,56,57 monkeys,58 and humans59,60 by exposure to irradiated sporozoites showed the feasibility of constructing a malaria vaccine that could be administered to inhibit parasite development. The malaria vaccine challenge is significant, however, presenting several confounding obstacles that require a creative design to curtail the parasite’s exquisite immune evasion tactics. The stagespecific variation of protein expression complicates vaccine development such that an effective vaccine target present in the infectious sporozoite stages may not be expressed in the blood stages. In addition, polymorphic proteins such as the PfEMP1 surface antigen are present in as many as 50 different copies per parasite clone and are able to undergo variant antigen switching between waves of parasitemia, rendering antibodies against antigens expressed in preceding waves
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ineffective. Also indicative of the need for a vaccine incorporating multiple epitopes is the remarkable diversity of immune responses to candidate antigens in humans,62 due in part to differences in haplotypes and the genetically restricted nature of the T-cell response. These obstacles present vaccine developers with the daunting task of identifying numerous antigens for an effective multi-epitope vaccine, and reveal the tremendous value of high-throughput techniques able to identify new antigens. To elucidate the minimal CD8+ and CD4+ T cell epitopes that elicit a protective immune response, various approaches have been proposed for antigen identification, including expression cloning,63 reverse immunogenetics,64,65 and peptide elution from MHC class I and II complexes and subsequent mass spectrometric sequencing.66-69 However, the dynamic range of antigens detected by these approaches is limited; dominant epitopes are often repeatedly detected while less abundant epitopes remain unidentified. These approaches are also limited to the HLA types of the individuals from which complexes are isolated, yielding little information about antigen binding capacity of other haplotypes. A novel approach integrating bioinformatic predictions with in vitro HLA-peptide binding assays70 has been applied to identify immunogenic antigens from P. falciparum.71 By predicting antigen-binding affinities in silico for several HLA class I and II types from antigens prioritized by genomic and proteomic data, potentially immunogenic antigens can be detected regardless of antigen abundance by in vitro testing of candidate antigens with MHC class I and II complexes isolated from volunteers immunized with radiation-attenuated P. falciparum sporozoites. A panel of protein sequences identified by a P. falciparum proteomic analysis with a diverse range of expression levels, stage specificity, membrane association, and sequence coverage was selected for scanning by an HLA supertype antigen-binding algorithm to identify putatively immunogenic peptides. A subset of these peptides were synthesized and tested in vitro to reveal 16 antigenic proteins recognized by immunized volunteers, but not by mock injected controls, some of which were more immunogenic than previously characterized P. falciparum antigens. It is interesting to note that of the 16 proteins showing a positive response, four were detected by a unique peptide in the whole sporozoite proteomic analyses, demonstrating that not only are single peptide hits valid, they are also valuable. The number of putative sporozoite-specific proteins is much larger than the subset screened in this study, and the dramatic response to these relatively randomly chosen proteins suggests that a very complex and multifaceted immune response occurs upon immunization with irradiated sporozoites instead of a strong immune response targeted toward relatively few immunodominant antigens. Protein-Drug Interactions. Separate yet complementary to host-pathogen interactions are studies aimed at identifying the protein components interacting with drugs that are routinely used to treat malaria but lack clear mechanisms of action. Chloroquine, a member of the quinoline family of drugs, was once the most successful anti-malarial drug in history; however, its success was also its pitfall; it has been rendered essentially ineffective in many parts of the world by increasingly widespread resistance resulting from heavy use over decades of treatment.72 Like most areas of malaria research, mechanisms of chloroquine action are hotly debated; a popular theory proposes that quinoline drugs interfere with the heme detoxification process that, when inhibited, creates an oxidative Journal of Proteome Research • Vol. 3, No. 2, 2004 301
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Figure 3. Proteome Mining strategy to identify and validate targets of quinoline drugs. Cell lysates were first passed over ATP-Sepharose, washed, and eluted with quinoline compounds. Lysates were also passed over hydroxychloroquine (HCQ) and primaquine (PQ) columns and eluted with quinoline compounds. Eluates were separated by 1D-PAGE and protein bands sequenced and identified by MALDI TOF MS fingerprinting. Quinoline-binding proteins identified from steps 1 and 2 were assayed for enzyme activity in the presence of quinoline compounds. Adapted from.77
environment in which P. falciparum cannot survive.73 However, quinoline compounds are also used to treat diseases unrelated to malaria, such as lupus erythematosus,74 arthritis,75 and HIV,76 suggesting that there must be some amount of cross-reactivity with the human host. To identify both human- and parasitederived protein targets of quinoline compounds, Graves and co-workers applied a displacement affinity chromatography strategy to screen the purine binding proteome for protein targets of quinoline drugs followed by enzymatic assays to validate the significance of their results.77 Using a technique termed “Proteome Mining” (Figure 3), the purine binding proteome of P. falciparum-infected red blood cells was captured by binding to γ-phosphate-linked ATPSepharose. Over 400 proteins were captured from a whole mouse extract and eluted with purine nucleotides as indicated by 2D-PAGE. 72 gel spots were identified by Edman sequencing or mass spectrometry and all shown to be known purine binding proteins. P. falciparum-infected and noninfected human red blood cell extracts were charged and eluted from the ATP-Sepharose column with three quinoline compounds (chloroquine, mefloquine, and primaquine), releasing only two human proteins: aldehyde dehydrogenase 1 (ALDH1) and quinine reductase 2 (QR2). Primaquine and hydroxychloroquine were immobilized to Sepharose and charged with red blood cell and P. falciparum lysates. Elution of the red blood cell charged column with primaquine or hydroxychloroquine released three human proteins: ALDH1, ALDH2, and QR2. No proteins were detected in the P. falciparum eluates, however, given that P. falciparum is cultivated in a heterogonous culture with human red blood cells, it cannot be expected that a silverstained 1D-PAGE gel will resolve parasite-derived proteins of low abundance in the presence of highly abundant human proteins. Enzyme activity assays revealed that chloroquine 302
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strongly inhibited QR2 activity, did not inhibit QR1 activity, and only weakly inhibited ALDH1. The observation that quinoline compounds bind very selectively to QR2 is an intriguing result pointing to an alternate hypothesis on the anti-malarial action of quinoline compounds. Quinones naturally present in all respiring plant and animal cells, if not reduced to the hydroquinone form by QR1 or QR2, can create an oxidative environment by redox cycling generating reactive oxygen species.78 P. falciparum has been shown to be very sensitive to oxidative stress,79 and mutations in malaria-endemic areas that confer partial protection against malaria have been observed in glucose-6-phosphate dehydrogenase, a mutation resulting in increased oxidative stress within red blood cells.80 It is proposed that, at least partially, quinoline compounds exert their anti-malarial activity by inhibiting quinone detoxification and thus poisoning the parasite. Inhibitors of QR2 showed IC50 concentrations several orders of magnitude above quinoline compounds, which the authors attribute to decreased permeability of the inhibitors compared with quinoline compounds, but the result could also indicate that QR2 inhibition may not completely represent the scope of quinoline action.
Outlook Two powerful proteomic applications that will further advance malaria research are the ability to elucidate posttranslational modifications and to precisely quantitate relative protein abundance between samples. Some potential applications and strategies are discussed below. Post-translational Modifications. The ability of parasites to shuffle their surface proteins to avoid immune recognition has frustrated protein-based vaccine design, leading researchers to investigate alternative molecules as vaccine targets. Complex sugars make an attractive target, given that parasite carbohydrates are often distinct from those of the host, and sugars linked to protein have the potential to induce a strongly immunogenic response.81 Success has been demonstrated with the carbohydrate-based vaccines for Streptococcus pneumoniae and Haemophilus influenzae (reviewed in ref 82), and although these bacterial organisms are far from the sophisticated evasion tactics observed by Plasmodium, parasite glycoproteins have been reported to be crucial to parasite maturation83 and their inhibition via vaccination could significantly reduce the morbidity of disease. Mass spectrometry-based methods have the unique ability to characterize post-translationally modified states from very small amounts of starting material, and combined with improved methods for carbohydrate synthesis,84 the study of glycosylation in Plasmodium could be more feasible than previously thought. Comprehensive approaches to specifically identify N-linked glycoproteins have recently been described by two different strategies.85,86 In one approach,85 glycoproteins were covalently attached to a solid support via hydrazide chemistry, proteolytically digested, labeled with isotopically enriched succinic anhydride (if relative protein quantification is desired), and released by peptide-N-glycosidase F (PNGase F) after washing away nonglycosylated peptides. The glycosylated peptides released were subsequently analyzed by µLC-ESI-MS/MS and analyzed by SEQUEST. The strategy was applied for a set of standard proteins, human serum, and LNCaP prostate cancer epithelial cells.87 Glycosylated proteins identified in LNCaP cells were predicted transmembrane (70%), extracellular (11%), and lysosomal proteins (14%), subcellular locations that often
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enrichment.88
observe glycoprotein Alternatively, an isotopecoded glycosylation-site-specific tagging (IGOT) strategy86 integrates lectin-affinity chromatography with enzymatic glycopeptide release in the presence of H218O in order to incorporate an isotope tag at the site of glycosylation. This approach was employed to study N-linked high-mannose glycoproteins from C. elegans extracts, leading to the identifications of 250 glycoproteins and 400 unique N-glycosylation sites. While both of these studies focused on N-glycosylation, methods could be tailored for O-glycosylation, however the lack of a comparable PNGase F-like enzyme for O-linked sugars presents a significant barrier. Since O-glycosidase only removes a core disaccharide, O-glycosylated peptides would first need to be stripped to the Galβ1,3GalNAc core using diverse exoglycosidase treatments or β-elimination before enymatic release from a lectin or hydrazide-linked support. The presence and significance of glycosylated protein residues in the intraerythrocytic stages of Plasmodium is quite controversial. It has been reported that P. falciparum contains no N-glycosylation machinery,89 yet the existence of N-linked glycans has been reported.83 In addition, while it has been suggested that O-linked glycans comprise the majority of carbohydrates in the erythrocytic stages,89,90 others report that O-linked glycosylation on proteins in these stages is extremely low or absent.91 Nonetheless, many proteins from P. falciparum erythrocytic stages are known to be glycosylated,92-96 all of which were characterized prior to the release of the P. falciparum genome,9 giving hope that other novel glycosylated proteins are yet to be discovered. Glycosylation information for the mosquito stages of Plasmodium is extremely limited, likely due to the lack of sufficient sample quantities that can be extracted from mosquito salivary glands and midguts. Recent studies detailing the effects of calmodulin-dependent kinase inhibitors on P. gallinaceum indicate that protein phosphorylation may also be a significant modification, particularly within the sexual stages of the parasite.97 Similar to the methods described above, several strategies have been outlined to specifically isolate and analyze the phosphorylated protein content of complex organisms.98-100 Generally, these procedures involve proteolytic digestion of a cellular extract, chemically altering phosphorylated sites to ligands amenable to purification, and affinity purifying the modified peptides followed by their mass spectrometric identification and localization of modified residues. As the sexual stages of development appear to be most relevant to the study of these modifications, demonstrated methods for reproducible in vitro development of the mosquito stages of the parasite101 are at the heart of extending high-thoughput techniques toward analysis of the less accessible stages of the parasite by providing a system able to generate sample quantities compatible with the detection of low abundance post-translational modifications. Quantitative Proteomic Profiling. As trends in proteomics favor methods able to quantify relative protein expression between samples, applications for quantitative protein profiling in malaria are abundant. The comparison of relative protein expression between drug-treated and nontreated samples can elucidate the target or mechanism of a particular drug. Also, the comparison of protein expression for drug-resistant and sensitive strains could reveal potentially altered protein expression related to the genetic factors that confer resistance. Quantitative mass spectrometry-based proteomic methods rely on stable-isotope dilution methods that simultaneously
analyze chemically identical species (i.e., identical peptides from different sample preparations) that differ only in their isotopic composition. Isotope differences separate identical peptides from different preparations within the same mass spectrum such that the ratio of their signal intensities precisely represents the relative amount of each peptide present in the combined sample. A variety of methods have been developed to incorporate stable isotopes into peptides sequences, including metabolic labeling using isotope-enriched media or amino acids,102 the enzymatic transfer of 18O from water,103,104 and chemical labeling of peptides with isotope-coded affinity tags.15,98 Metabolic labeling strategies have the potential to label all peptides but depend on an organism’s in vivo ability to incorporate supplemented amino acids or salts into newly synthesized proteins, whereas chemical labeling strategies can be performed in vitro following proteolytic digestion but typically depend on the presence of label-specific amino acids within peptides for incorporation of a particular isotope tag. As an alternative to stable-isotope dilution, difference gel electrophoresis (DIGE) can quantify relative protein expression by labeling sample derived from different sample preparations with spectrally resolvable dyes (generally Cy3 and Cy5).105 Differentially labeled proteins are evaluated by a single 2DPAGE separation to generate precisely overlaid 2D-PAGE images. Fluorescence labeling permits the detection of low abundance proteins, however DIGE suffers from the same limitations that apply to 2D-PAGE analysis: a limited range of pH and molecular weight, and the assumption that individual gel spots do not consist of multiple proteins. P. falciparum utilizes hemoglobin within human red blood cells as a major source of amino acids, however intraerythrocytic growth of the parasite requires exogenously supplied isoleucine, methionine, cysteine, glutamate, and glutamine.106,107 Radiolabeled amino acids supplied exogenously and derived from labeled hemoglobin can be incorporated into P. iophurae proteins,108 but the extent of incorporation required for the stable isotope dilution experiments described above, likely at least 80% incorporation, has not been demonstrated. Most radiolabeling studies were performed long before the era of quantitative proteomics, and their reinvestigation could present promising tools for relative protein expression analysis. Meanwhile, no significant obstacles prevent the use of isotope-coded chemical labels for studying relative protein expression.
Acknowledgment. We are grateful to Karine Le Roch and Parinaz Aliahmad for critical reading of the manuscript. The authors wish to acknowledge the support of the Office of Naval Research, the US Army Medical Research and Material Command, and the National Institutes of Health (to J.R.Y.). J.R.J. wishes to acknowledge the Burroughs-Wellcome Fund and the LJIS interdisciplinary training program for fellowship support. The opinions expressed are those of the authors and do not reflect the official policy of the Department of the Navy, Department of Defense, or the US government. References (1) Breman, J. G.; Egan, A.; Keusch, G. T. Am. J. Trop. Med. Hyg. 2001, 64, iv-vii. (2) Wu, Y.; Sifri, C. D.; Lei, H. H.; Su, X. Z.; Wellems, T. E. Proc. Natl. Acad. Sci. USA 1995, 92, 973-977. (3) van Dijk, M. R.; Waters, A. P.; Janse, C. J. Science 1995, 268, 13581362. (4) Crabb, B. S.; Cowman, A. F. Proc. Natl. Acad. Sci. USA 1996, 93, 7289-7294.
Journal of Proteome Research • Vol. 3, No. 2, 2004 303
reviews (5) Fidock, D. A.; Wellems, T. E. Proc. Natl. Acad. Sci. USA 1997, 94, 10 931-10 936. (6) Venter, J. C.; Adams, M. D.; Myers, E. W.; Li, P. W.; Mural, R. J.; Sutton, G. G.; Smith, H. O.; Yandell, M.; Evans, C. A.; Holt, R. A.; Gocayne, J. D.; Amanatides, P.; Ballew, R. M.; Huson, D. H.; Wortman, J. R.; Zhang, Q.; Kodira, C. D.; Zheng, X. H.; Chen, L.; Skupski, M.; Subramanian, G.; Thomas, P. D.; Zhang, J.; Gabor Miklos, G. L.; Nelson, C.; Broder, S.; Clark, A. G.; Nadeau, J.; McKusick, V. A.; Zinder, N.; Levine, A. J.; Roberts, R. J.; Simon, M.; Slayman, C.; Hunkapiller, M.; Bolanos, R.; Delcher, A.; Dew, I.; Fasulo, D.; Flanigan, M.; Florea, L.; Halpern, A.; Hannenhalli, S.; Kravitz, S.; Levy, S.; Mobarry, C.; Reinert, K.; Remington, K.; Abu-Threideh, J.; Beasley, E.; Biddick, K.; Bonazzi, V.; Brandon, R.; Cargill, M.; Chandramouliswaran, I.; Charlab, R.; Chaturvedi, K.; Deng, Z.; Di Francesco, V.; Dunn, P.; Eilbeck, K.; Evangelista, C.; Gabrielian, A. E.; Gan, W.; Ge, W.; Gong, F.; Gu, Z.; Guan, P.; Heiman, T. J.; Higgins, M. E.; Ji, R. R.; Ke, Z.; Ketchum, K. A.; Lai, Z.; Lei, Y.; Li, Z.; Li, J.; Liang, Y.; Lin, X.; Lu, F.; Merkulov, G. V.; Milshina, N.; Moore, H. M.; Naik, A. K.; Narayan, V. A.; Neelam, B.; Nusskern, D.; Rusch, D. B.; Salzberg, S.; Shao, W.; Shue, B.; Sun, J.; Wang, Z.; Wang, A.; Wang, X.; Wang, J.; Wei, M.; Wides, R.; Xiao, C.; Yan, C.; Yao, A.; Ye, J.; Zhan, M.; Zhang, W.; Zhang, H.; Zhao, Q.; Zheng, L.; Zhong, F.; Zhong, W.; Zhu, S.; Zhao, S.; Gilbert, D.; Baumhueter, S.; Spier, G.; Carter, C.; Cravchik, A.; Woodage, T.; Ali, F.; An, H.; Awe, A.; Baldwin, D.; Baden, H.; Barnstead, M.; Barrow, I.; Beeson, K.; Busam, D.; Carver, A.; Center, A.; Cheng, M. L.; Curry, L.; Danaher, S.; Davenport, L.; Desilets, R.; Dietz, S.; Dodson, K.; Doup, L.; Ferriera, S.; Garg, N.; Gluecksmann, A.; Hart, B.; Haynes, J.; Haynes, C.; Heiner, C.; Hladun, S.; Hostin, D.; Houck, J.; Howland, T.; Ibegwam, C.; Johnson, J.; Kalush, F.; Kline, L.; Koduru, S.; Love, A.; Mann, F.; May, D.; McCawley, S.; McIntosh, T.; McMullen, I.; Moy, M.; Moy, L.; Murphy, B.; Nelson, K.; Pfannkoch, C.; Pratts, E.; Puri, V.; Qureshi, H.; Reardon, M.; Rodriguez, R.; Rogers, Y. H.; Romblad, D.; Ruhfel, B.; Scott, R.; Sitter, C.; Smallwood, M.; Stewart, E.; Strong, R.; Suh, E.; Thomas, R.; Tint, N. N.; Tse, S.; Vech, C.; Wang, G.; Wetter, J.; Williams, S.; Williams, M.; Windsor, S.; Winn-Deen, E.; Wolfe, K.; Zaveri, J.; Zaveri, K.; Abril, J. F.; Guigo, R.; Campbell, M. J.; Sjolander, K. V.; Karlak, B.; Kejariwal, A.; Mi, H.; Lazareva, B.; Hatton, T.; Narechania, A.; Diemer, K.; Muruganujan, A.; Guo, N.; Sato, S.; Bafna, V.; Istrail, S.; Lippert, R.; Schwartz, R.; Walenz, B.; Yooseph, S.; Allen, D.; Basu, A.; Baxendale, J.; Blick, L.; Caminha, M.; Carnes-Stine, J.; Caulk, P.; Chiang, Y. H.; Coyne, M.; Dahlke, C.; Mays, A.; Dombroski, M.; Donnelly, M.; Ely, D.; Esparham, S.; Fosler, C.; Gire, H.; Glanowski, S.; Glasser, K.; Glodek, A.; Gorokhov, M.; Graham, K.; Gropman, B.; Harris, M.; Heil, J.; Henderson, S.; Hoover, J.; Jennings, D.; Jordan, C.; Jordan, J.; Kasha, J.; Kagan, L.; Kraft, C.; Levitsky, A.; Lewis, M.; Liu, X.; Lopez, J.; Ma, D.; Majoros, W.; McDaniel, J.; Murphy, S.; Newman, M.; Nguyen, T.; Nguyen, N.; Nodell, M.; Pan, S.; Peck, J.; Peterson, M.; Rowe, W.; Sanders, R.; Scott, J.; Simpson, M.; Smith, T.; Sprague, A.; Stockwell, T.; Turner, R.; Venter, E.; Wang, M.; Wen, M.; Wu, D.; Wu, M.; Xia, A.; Zandieh, A.; Zhu, X. Science 2001, 291, 1304-1351. (7) Waterston, R. H.; Lindblad-Toh, K.; Birney, E.; Rogers, J.; Abril, J. F.; Agarwal, P.; Agarwala, R.; Ainscough, R.; Alexandersson, M.; An, P.; Antonarakis, S. E.; Attwood, J.; Baertsch, R.; Bailey, J.; Barlow, K.; Beck, S.; Berry, E.; Birren, B.; Bloom, T.; Bork, P.; Botcherby, M.; Bray, N.; Brent, M. R.; Brown, D. G.; Brown, S. D.; Bult, C.; Burton, J.; Butler, J.; Campbell, R. D.; Carninci, P.; Cawley, S.; Chiaromonte, F.; Chinwalla, A. T.; Church, D. M.; Clamp, M.; Clee, C.; Collins, F. S.; Cook, L. L.; Copley, R. R.; Coulson, A.; Couronne, O.; Cuff, J.; Curwen, V.; Cutts, T.; Daly, M.; David, R.; Davies, J.; Delehaunty, K. D.; Deri, J.; Dermitzakis, E. T.; Dewey, C.; Dickens, N. J.; Diekhans, M.; Dodge, S.; Dubchak, I.; Dunn, D. M.; Eddy, S. R.; Elnitski, L.; Emes, R. D.; Eswara, P.; Eyras, E.; Felsenfeld, A.; Fewell, G. A.; Flicek, P.; Foley, K.; Frankel, W. N.; Fulton, L. A.; Fulton, R. S.; Furey, T. S.; Gage, D.; Gibbs, R. A.; Glusman, G.; Gnerre, S.; Goldman, N.; Goodstadt, L.; Grafham, D.; Graves, T. A.; Green, E. D.; Gregory, S.; Guigo, R.; Guyer, M.; Hardison, R. C.; Haussler, D.; Hayashizaki, Y.; Hillier, L. W.; Hinrichs, A.; Hlavina, W.; Holzer, T.; Hsu, F.; Hua, A.; Hubbard, T.; Hunt, A.; Jackson, I.; Jaffe, D. B.; Johnson, L. S.; Jones, M.; Jones, T. A.; Joy, A.; Kamal, M.; Karlsson, E. K.; Karolchik, D.; Kasprzyk, A.; Kawai, J.; Keibler, E.; Kells, C.; Kent, W. J.; Kirby, A.; Kolbe, D. L.; Korf, I.; Kucherlapati, R. S.; Kulbokas, E. J.; Kulp, D.; Landers, T.; Leger, J. P.; Leonard, S.; Letunic, I.; Levine, R.; Li, J.; Li, M.; Lloyd, C.; Lucas, S.; Ma, B.; Maglott, D. R.; Mardis, E. R.; Matthews, L.; Mauceli, E.; Mayer, J. H.; McCarthy, M.; McCombie, W. R.; McLaren, S.; McLay, K.; McPherson, J. D.; Meldrim, J.; Meredith, B.; Mesirov, J. P.; Miller, W.; Miner, T. L.; Mongin, E.;
304
Journal of Proteome Research • Vol. 3, No. 2, 2004
Johnson et al.
(8)
(9)
(10)
(11) (12)
(13) (14) (15) (16)
Montgomery, K. T.; Morgan, M.; Mott, R.; Mullikin, J. C.; Muzny, D. M.; Nash, W. E.; Nelson, J. O.; Nhan, M. N.; Nicol, R.; Ning, Z.; Nusbaum, C.; O’Connor, M. J.; Okazaki, Y.; Oliver, K.; OvertonLarty, E.; Pachter, L.; Parra, G.; Pepin, K. H.; Peterson, J.; Pevzner, P.; Plumb, R.; Pohl, C. S.; Poliakov, A.; Ponce, T. C.; Ponting, C. P.; Potter, S.; Quail, M.; Reymond, A.; Roe, B. A.; Roskin, K. M.; Rubin, E. M.; Rust, A. G.; Santos, R.; Sapojnikov, V.; Schultz, B.; Schultz, J.; Schwartz, M. S.; Schwartz, S.; Scott, C.; Seaman, S.; Searle, S.; Sharpe, T.; Sheridan, A.; Shownkeen, R.; Sims, S.; Singer, J. B.; Slater, G.; Smit, A.; Smith, D. R.; Spencer, B.; Stabenau, A.; Stange-Thomann, N.; Sugnet, C.; Suyama, M.; Tesler, G.; Thompson, J.; Torrents, D.; Trevaskis, E.; Tromp, J.; Ucla, C.; Ureta-Vidal, A.; Vinson, J. P.; Von Niederhausern, A. C.; Wade, C. M.; Wall, M.; Weber, R. J.; Weiss, R. B.; Wendl, M. C.; West, A. P.; Wetterstrand, K.; Wheeler, R.; Whelan, S.; Wierzbowski, J.; Willey, D.; Williams, S.; Wilson, R. K.; Winter, E.; Worley, K. C.; Wyman, D.; Yang, S.; Yang, S. P.; Zdobnov, E. M.; Zody, M. C.; Lander, E. S. Nature 2002, 420, 520-562. Holt, R. A.; Subramanian, G. M.; Halpern, A.; Sutton, G. G.; Charlab, R.; Nusskern, D. R.; Wincker, P.; Clark, A. G.; Ribeiro, J. M.; Wides, R.; Salzberg, S. L.; Loftus, B.; Yandell, M.; Majoros, W. H.; Rusch, D. B.; Lai, Z.; Kraft, C. L.; Abril, J. F.; Anthouard, V.; Arensburger, P.; Atkinson, P. W.; Baden, H.; de Berardinis, V.; Baldwin, D.; Benes, V.; Biedler, J.; Blass, C.; Bolanos, R.; Boscus, D.; Barnstead, M.; Cai, S.; Center, A.; Chatuverdi, K.; Christophides, G. K.; Chrystal, M. A.; Clamp, M.; Cravchik, A.; Curwen, V.; Dana, A.; Delcher, A.; Dew, I.; Evans, C. A.; Flanigan, M.; Grundschober-Freimoser, A.; Friedli, L.; Gu, Z.; Guan, P.; Guigo, R.; Hillenmeyer, M. E.; Hladun, S. L.; Hogan, J. R.; Hong, Y. S.; Hoover, J.; Jaillon, O.; Ke, Z.; Kodira, C.; Kokoza, E.; Koutsos, A.; Letunic, I.; Levitsky, A.; Liang, Y.; Lin, J. J.; Lobo, N. F.; Lopez, J. R.; Malek, J. A.; McIntosh, T. C.; Meister, S.; Miller, J.; Mobarry, C.; Mongin, E.; Murphy, S. D.; O’Brochta, D. A.; Pfannkoch, C.; Qi, R.; Regier, M. A.; Remington, K.; Shao, H.; Sharakhova, M. V.; Sitter, C. D.; Shetty, J.; Smith, T. J.; Strong, R.; Sun, J.; Thomasova, D.; Ton, L. Q.; Topalis, P.; Tu, Z.; Unger, M. F.; Walenz, B.; Wang, A.; Wang, J.; Wang, M.; Wang, X.; Woodford, K. J.; Wortman, J. R.; Wu, M.; Yao, A.; Zdobnov, E. M.; Zhang, H.; Zhao, Q.; Zhao, S.; Zhu, S. C.; Zhimulev, I.; Coluzzi, M.; della Torre, A.; Roth, C. W.; Louis, C.; Kalush, F.; Mural, R. J.; Myers, E. W.; Adams, M. D.; Smith, H. O.; Broder, S.; Gardner, M. J.; Fraser, C. M.; Birney, E.; Bork, P.; Brey, P. T.; Venter, J. C.; Weissenbach, J.; Kafatos, F. C.; Collins, F. H.; Hoffman, S. L. Science 2002, 298, 129-149. Gardner, M. J.; Hall, N.; Fung, E.; White, O.; Berriman, M.; Hyman, R. W.; Carlton, J. M.; Pain, A.; Nelson, K. E.; Bowman, S.; Paulsen, I. T.; James, K.; Eisen, J. A.; Rutherford, K.; Salzberg, S. L.; Craig, A.; Kyes, S.; Chan, M. S.; Nene, V.; Shallom, S. J.; Suh, B.; Peterson, J.; Angiuoli, S.; Pertea, M.; Allen, J.; Selengut, J.; Haft, D.; Mather, M. W.; Vaidya, A. B.; Martin, D. M.; Fairlamb, A. H.; Fraunholz, M. J.; Roos, D. S.; Ralph, S. A.; McFadden, G. I.; Cummings, L. M.; Subramanian, G. M.; Mungall, C.; Venter, J. C.; Carucci, D. J.; Hoffman, S. L.; Newbold, C.; Davis, R. W.; Fraser, C. M.; Barrell, B. Nature 2002, 419, 498-511. Carlton, J. M.; Angiuoli, S. V.; Suh, B. B.; Kooij, T. W.; Pertea, M.; Silva, J. C.; Ermolaeva, M. D.; Allen, J. E.; Selengut, J. D.; Koo, H. L.; Peterson, J. D.; Pop, M.; Kosack, D. S.; Shumway, M. F.; Bidwell, S. L.; Shallom, S. J.; van Aken, S. E.; Riedmuller, S. B.; Feldblyum, T. V.; Cho, J. K.; Quackenbush, J.; Sedegah, M.; Shoaibi, A.; Cummings, L. M.; Florens, L.; Yates, J. R.; Raine, J. D.; Sinden, R. E.; Harris, M. A.; Cunningham, D. A.; Preiser, P. R.; Bergman, L. W.; Vaidya, A. B.; van Lin, L. H.; Janse, C. J.; Waters, A. P.; Smith, H. O.; White, O. R.; Salzberg, S. L.; Venter, J. C.; Fraser, C. M.; Hoffman, S. L.; Gardner, M. J.; Carucci, D. J. Nature 2002, 419, 512-519. Hayward, R. E.; Derisi, J. L.; Alfadhli, S.; Kaslow, D. C.; Brown, P. O.; Rathod, P. K. Mol. Microbiol. 2000, 35, 6-14. 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.; Goldberg, D. E. Mol. Microbiol. 2001, 39, 26-36. Le Roch, K. G.; Zhou, Y.; Blair, P. L.; Grainger, M.; Moch, J. K.; Haynes, J. D.; De La Vega, P.; Holder, A. A.; Batalov, S.; Carucci, D. J.; Winzeler, E. A. Science 2003, 301, 1503-1508. Bozdech, Z.; Zhu, J.; Joachimiak, M. P.; Cohen, F. E.; Pulliam, B.; DeRisi, J. L. Genome Biol. 2003, 4, R9. Gygi, S. P.; Rist, B.; Gerber, S. A.; Turecek, F.; Gelb, M. H.; Aebersold, R. Nat. Biotechnol. 1999, 17, 994-999. Griffin, T. J.; Gygi, S. P.; Rist, B.; Aebersold, R.; Loboda, A.; Jilkine, A.; Ens, W.; Standing, K. G. Anal. Chem. 2001, 73, 978986.
reviews
Proteomics in Malaria (17) Washburn, M. P.; Koller, A.; Oshiro, G.; Ulaszek, R. R.; Plouffe, D.; Deciu, C.; Winzeler, E.; Yates, J. R., 3rd Proc. Natl. Acad. Sci. USA 2003, 100, 3107-3112. (18) Bahl, A.; Brunk, B.; Coppel, R. L.; Crabtree, J.; Diskin, S. J.; Fraunholz, M. J.; Grant, G. R.; Gupta, D.; Huestis, R. L.; Kissinger, J. C.; Labo, P.; Li, L.; McWeeney, S. K.; Milgram, A. J.; Roos, D. S.; Schug, J.; Stoeckert, C. J., Jr. Nucleic Acids Res. 2002, 30, 87-90. (19) Link, A. J.; Eng, J.; Schieltz, D. M.; Carmack, E.; Mize, G. J.; Morris, D. R.; Garvik, B. M.; Yates, J. R., 3rd Nat. Biotechnol. 1999, 17, 676-682. (20) Wolters, D. A.; Washburn, M. P.; Yates, J. R., 3rd Anal. Chem. 2001, 73, 5683-5690. (21) Washburn, M. P.; Wolters, D.; Yates, J. R., 3rd Nat. Biotechnol. 2001, 19, 242-247. (22) Koller, A.; Washburn, M. P.; Lange, B. M.; Andon, N. L.; Deciu, C.; Haynes, P. A.; Hays, L.; Schieltz, D.; Ulaszek, R.; Wei, J.; Wolters, D.; Yates, J. R., 3rd Proc. Natl. Acad. Sci. USA 2002, 99, 11 969-11 974. (23) Rabilloud, T.; Adessi, C.; Giraudel, A.; Lunardi, J. Electrophoresis 1997, 18, 307-316. (24) Chevallet, M.; Santoni, V.; Poinas, A.; Rouquie, D.; Fuchs, A.; Kieffer, S.; Rossignol, M.; Lunardi, J.; Garin, J.; Rabilloud, T. Electrophoresis 1998, 19, 1901-1909. (25) Rabilloud, T.; Blisnick, T.; Heller, M.; Luche, S.; Aebersold, R.; Lunardi, J.; Braun-Breton, C. Electrophoresis 1999, 20, 36033610. (26) Udeinya, I. J.; Schmidt, J. A.; Aikawa, M.; Miller, L. H.; Green, I. Science 1981, 213, 555-557. (27) Deitsch, K. W.; Wellems, T. E. Mol. Biochem. Parasitol. 1996, 76, 1-10. (28) Martinez, S. L.; Clavijo, C. A.; Winograd, E. Mol. Biochem. Parasitol. 1998, 91, 273-280. (29) Roggwiller, E.; Betoulle, M. E.; Blisnick, T.; Braun Breton, C. Mol. Biochem. Parasitol. 1996, 82, 13-24. (30) Prevot, G.; Laurent-Winter, C.; Rodhain, F.; Bourgouin, C. Malar. J. 2003, 2, 1. (31) Shahabuddin, M.; Kaslow, D. C. Exp. Parasitol. 1994, 79, 85-88. (32) Shahabuddin, M.; Lemos, F. J.; Kaslow, D. C.; Jacobs-Lorena, M. Infect. Immun. 1996, 64, 739-743. (33) Carucci, D. J. Philos. Trans. R Soc. Lond. B. Biol. Sci. 2002, 357, 13-16. (34) 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.; Witney, A. A.; Wolters, D.; Wu, Y.; Gardner, M. J.; Holder, A. A.; Sinden, R. E.; Yates, J. R.; Carucci, D. J. Nature 2002, 419, 520-526. (35) Bolshakov, V. N.; Topalis, P.; Blass, C.; Kokoza, E.; della Torre, A.; Kafatos, F. C.; Louis, C. Genome Res. 2002, 12, 57-66. (36) Kyes, S. A.; Rowe, J. A.; Kriek, N.; Newbold, C. I. Proc. Natl. Acad. Sci. USA 1999, 96, 9333-9338. (37) 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.; Mann, M. Nature 2002, 419, 537-542. (38) Gardner, M. J.; Shallom, S. J.; Carlton, J. M.; Salzberg, S. L.; Nene, V.; Shoaibi, A.; Ciecko, A.; Lynn, J.; Rizzo, M.; Weaver, B.; Jarrahi, B.; Brenner, M.; Parvizi, B.; Tallon, L.; Moazzez, A.; Granger, D.; Fujii, C.; Hansen, C.; Pederson, J.; Feldblyum, T.; Peterson, J.; Suh, B.; Angiuoli, S.; Pertea, M.; Allen, J.; Selengut, J.; White, O.; Cummings, L. M.; Smith, H. O.; Adams, M. D.; Venter, J. C.; Carucci, D. J.; Hoffman, S. L.; Fraser, C. M. Nature 2002, 419, 531-534. (39) Aebersold, R.; Mann, M. Nature 2003, 422, 198-207. (40) Eng, J. K.; McCormack, A. L.; Yates, J. R., 3rd J. Am. Soc. Mass. Spectrom. 1994, 5, 976-989. (41) Smith, R. L.; Shaw, E. J. Biol. Chem. 1969, 244, 4704-4712. (42) Karty, J. A.; Ireland, M. M. E.; Brun, Y. V.; Reilly, J. P. J. Chrom. B 2002, 782, 363-383. (43) McDonald, W. H.; Ryoma, O.; D. T., M.; Mitchison, T. J.; Yates, J. R. Int. J. Mass Spectrom. 2002, 219, 245-251. (44) Perkins, D. N.; Pappin, D. J.; Creasy, D. M.; Cottrell, J. S. Electrophoresis 1999, 20, 3551-3567. (45) Blackman, M. J.; Bannister, L. H. Mol. Biochem. Parasitol. 2001, 117, 11-25. (46) Zhang, J.; Krugliak, M.; Ginsburg, H. Mol. Biochem. Parasitol. 1999, 99, 129-141. (47) Chou, A. C.; Chevli, R.; Fitch, C. D. Biochemistry 1980, 19, 15431549. (48) Dorn, A.; Vippagunta, S. R.; Matile, H.; Jaquet, C.; Vennerstrom, J. L.; Ridley, R. G. Biochem. Pharmacol. 1998, 55, 727-736. (49) Trape, J. F.; Pison, G.; Preziosi, M. P. C. R. Acad. Sci. III 1998, 321, 689-697.
(50) (51) (52) (53) (54) (55) (56) (57) (58) (59) (60) (61) (62)
(63) (64) (65) (66) (67) (68) (69) (70)
(71)
(72) (73) (74) (75) (76) (77) (78) (79) (80)
(81) (82) (83) (84) (85) (86)
Payne, D. Parastol. Today 1987, 3, 241-246. Cowman, A. F.; Foote, S. J. Int. J. Parasitol. 1990, 20, 503-513. Craig, A.; Scherf, A. Mol. Biochem. Parasitol. 2001, 115, 129-143. Florens, L.; Liu, X.; Wang, Y.; Yang, S.; Schwartz, O.; Peglar, M.; Carucci, D. J.; Yates, J. R.; Wu, Y. 2003, in press. Wolters, D. A.; Washburn, M. P.; Yates, J. R., 3rd Anal. Chem 2001, 73, 5683-5690. Blisnick, T.; Morales Betoulle, M. E.; Barale, J. C.; Uzureau, P.; Berry, L.; Desroses, S.; Fujioka, H.; Mattei, D.; Braun Breton, C. Mol. Biochem. Parasitol. 2000, 111, 107-121. Romero, P.; Maryanski, J. L.; Corradin, G.; Nussenzweig, R. S.; Nussenzweig, V.; Zavala, F. Nature 1989, 341, 323-326. Rodrigues, M. M.; Cordey, A. S.; Arreaza, G.; Corradin, G.; Romero, P.; Maryanski, J. L.; Nussenzweig, R. S.; Zavala, F. Int. Immunol. 1991, 3, 579-585. Collins, W. E.; Contacos, P. G. Nat. New. Biol. 1972, 236, 176177. Egan, J. E.; Hoffman, S. L.; Haynes, J. D.; Sadoff, J. C.; Schneider, I.; Grau, G. E.; Hollingdale, M. R.; Ballou, W. R.; Gordon, D. M. Am. J. Trop. Med. Hyg. 1993, 49, 166-173. Rieckmann, K. H.; Beaudoin, R. L.; Cassells, J. S.; Sell, K. W. Bull. World Health Organ. 1979, 57 Suppl. 1, 261-265. Saul, A. Parasitol. Today 1999, 15, 455-457. Saul, A.; Lawrence, G.; Smillie, A.; Rzepczyk, C. M.; Reed, C.; Taylor, D.; Anderson, K.; Stowers, A.; Kemp, R.; Allworth, A.; Anders, R. F.; Brown, G. V.; Pye, D.; Schoofs, P.; Irving, D. O.; Dyer, S. L.; Woodrow, G. C.; Briggs, W. R.; Reber, R.; Sturchler, D. Vaccine 1999, 17, 3145-3159. Kawakami, Y.; Rosenberg, S. A. Int. Rev. Immunol. 1997, 14, 173192. Davenport, M. P.; Hill, A. V. Mol. Med. Today 1996, 2, 38-45. Aidoo, M.; Lalvani, A.; Allsopp, C. E.; Plebanski, M.; Meisner, S. J.; Krausa, P.; Browning, M.; Morris-Jones, S.; Gotch, F.; Fidock, D. A.; et al. Lancet 1995, 345, 1003-1007. Rotzschke, O.; Falk, K.; Deres, K.; Schild, H.; Norda, M.; Metzger, J.; Jung, G.; Rammensee, H. G. Nature 1990, 348, 252-254. Van Bleek, G. M.; Nathenson, S. G. Nature 1990, 348, 213-216. Hunt, D. F.; Henderson, R. A.; Shabanowitz, J.; Sakaguchi, K.; Michel, H.; Sevilir, N.; Cox, A. L.; Appella, E.; Engelhard, V. H. Science 1992, 255, 1261-1263. Cox, A. L.; Skipper, J.; Chen, Y.; Henderson, R. A.; Darrow, T. L.; Shabanowitz, J.; Engelhard, V. H.; Hunt, D. F.; Slingluff, C. L., Jr. Science 1994, 264, 716-719. Sidney, J.; Southwood, S.; Oseroff, C.; Del Guercio, M. F.; Appella, E.; Hoffman, S.; Kubo, R. T.; Chesnut, R.; Grey, H. M.; Sette, A. In Current Protocols in Immunology; Wiley: New York, 1998, 18.13.11-18.13.19. Doolan, D. L.; Southwood, S.; Freilich, D. A.; Sidney, J.; Graber, N. L.; Shatney, L.; Bebris, L.; Florens, L.; Dobano, C.; Witney, A. A.; Appella, E.; Hoffman, S. L.; Yates, J. R., 3rd; Carucci, D. J.; Sette, A. Proc. Natl. Acad. Sci. USA 2003, 100, 9952-9957. Foley, M.; Tilley, L. Pharmacol. Ther. 1998, 79, 55-87. Foley, M.; Tilley, L. Int. J. Parasitol. 1997, 27, 231-240. Van Beek, M. J.; Piette, W. W. Dermatol. Clin. 2001, 19, 147-160, ix. Fox, R. I. Semin. Arthritis Rheum. 1993, 23, 82-91. Savarino, A.; Gennero, L.; Chen, H. C.; Serrano, D.; Malavasi, F.; Boelaert, J. R.; Sperber, K. Aids 2001, 15, 2221-2229. Graves, P. R.; Kwiek, J. J.; Fadden, P.; Ray, R.; Hardeman, K.; Coley, A. M.; Foley, M.; Haystead, T. A. Mol. Pharmacol. 2002, 62, 13641372. O’Brien, P. J. Chem. Biol. Interact. 1991, 80, 1-41. Postma, N. S.; Mommers, E. C.; Eling, W. M.; Zuidema, J. Pharm. World Sci. 1996, 18, 121-129. Tishkoff, S. A.; Varkonyi, R.; Cahinhinan, N.; Abbes, S.; Argyropoulos, G.; Destro-Bisol, G.; Drousiotou, A.; Dangerfield, B.; Lefranc, G.; Loiselet, J.; Piro, A.; Stoneking, M.; Tagarelli, A.; Tagarelli, G.; Touma, E. H.; Williams, S. M.; Clark, A. G. Science 2001, 293, 455-462. Dennis, C. Nature 2003, 423, 580-582. Ada, G.; Isaacs, D. Clin. Microbiol. Infect. 2003, 9, 79-85. Kimura, E. A.; Couto, A. S.; Peres, V. J.; Casal, O. L.; Katzin, A. M. J. Biol. Chem. 1996, 271, 14 452-14 461. Plante, O. J.; Seeberger, P. H. Curr. Opin. Drug Discov. Devel. 2003, 6, 521-525. Zhang, H.; Li, X. J.; Martin, D. B.; Aebersold, R. Nat. Biotechnol. 2003, 21, 660-666. Kaji, H.; Saito, H.; Yamauchi, Y.; Shinkawa, T.; Taoka, M.; Hirabayashi, J.; Kasai, K.; Takahashi, N.; Isobe, T. Nat. Biotechnol. 2003, 21, 667-672.
Journal of Proteome Research • Vol. 3, No. 2, 2004 305
reviews (87) Horoszewicz, J. S.; Leong, S. S.; Chu, T. M.; Wajsman, Z. L.; Friedman, M.; Papsidero, L.; Kim, U.; Chai, L. S.; Kakati, S.; Arya, S. K.; Sandberg, A. A. Prog. Clin. Biol. Res. 1980, 37, 115-132. (88) Roth, J. Chem. Rev. 2002, 102, 285-303. (89) Dieckmann-Schuppert, A.; Bender, S.; Odenthal-Schnittler, M.; Bause, E.; Schwarz, R. T. Eur. J. Biochem. 1992, 205, 815825. (90) Dayal-Drager, R.; Hoessli, D. C.; Decrind, C.; Del Guidice, G.; Lambert, P. H.; Nasir ud, D. Carbohydr. Res. 1991, 209, c5-8. (91) Gowda, D. C.; Gupta, P.; Davidson, E. A. J. Biol. Chem. 1997, 272, 6428-6439. (92) Heidrich, H. G.; Strych, W.; Mrema, J. E. Z. Parasitenkd. 1983, 69, 715-725. (93) Fenton, B.; Clark, J. T.; Wilson, C. F.; McBride, J. S.; Walliker, D. Mol. Biochem. Parasitol. 1989, 34, 79-86. (94) Vermeulen, A. N.; van Deursen, J.; Brakenhoff, R. H.; Lensen, T. H.; Ponnudurai, T.; Meuwissen, J. H. Mol. Biochem. Parasitol. 1986, 20, 155-163. (95) Ramasamy, R. Immunol. Cell. Biol. 1987, 65 (Pt 2), 147-152. (96) Jakobsen, P. H.; Theander, T. G.; Jensen, J. B.; Molbak, K.; Jepsen, S. J. Clin. Microbiol. 1987, 25, 2075-2079. (97) Silva-Neto, M. A.; Atella, G. C.; Shahabuddin, M. J. Biol. Chem. 2002, 277, 14085-14091. (98) Zhou, H.; Ranish, J. A.; Watts, J. D.; Aebersold, R. Nat. Biotechnol. 2002, 20, 512-515. (99) Ficarro, S. B.; McCleland, M. L.; Stukenberg, P. T.; Burke, D. J.; Ross, M. M.; Shabanowitz, J.; Hunt, D. F.; White, F. M. Nat. Biotechnol. 2002, 20, 301-305. (100) McLachlin, D. T.; Chait, B. T. Anal. Chem. 2003, 75, 6826-6836.
306
Journal of Proteome Research • Vol. 3, No. 2, 2004
Johnson et al. (101) Al-Olayan, E. M.; Beetsma, A. L.; Butcher, G. A.; Sinden, R. E.; Hurd, H. Science 2002, 295, 677-679. (102) Ong, S. E.; Blagoev, B.; Kratchmarova, I.; Kristensen, D. B.; Steen, H.; Pandey, A.; Mann, M. Mol. Cell. Proteomics. 2002, 1, 376386. (103) Mirgorodskaya, O. A.; Kozmin, Y. P.; Titov, M. I.; Korner, R.; Sonksen, C. P.; Roepstorff, P. Rapid Commun. Mass. Spectrom. 2000, 14, 1226-1232. (104) Yao, X.; Freas, A.; Ramirez, J.; Demirev, P. A.; Fenselau, C. Anal. Chem 2001, 73, 2836-2842. (105) Tonge, R.; Shaw, J.; Middleton, B.; Rowlinson, R.; Rayner, S.; Young, J.; Pognan, F.; Hawkins, E.; Currie, I.; Davison, M. Proteomics 2001, 1, 377-396. (106) Divo, A. A.; Geary, T. G.; Davis, N. L.; Jensen, J. B. J. Protozool. 1985, 32, 59-64. (107) Francis, S. E.; Gluzman, I. Y.; Oksman, A.; Knickerbocker, A.; Mueller, R.; Bryant, M. L.; Sherman, D. R.; Russell, D. G.; Goldberg, D. E. Embo. J. 1994, 13, 306-317. (108) Sherman, I. W.; Ruble, J. A.; Tanigoshi, L. Mil. Med. 1969, 134, 954-961. (109) Pacheco, N. D.; Strome, C. P.; Mitchell, F.; Bawden, M. P.; Beaudoin, R. L. J. Parasitol. 1979, 65, 414-417. (110) Blackman, M. J. Methods Cell. Biol. 1994, 45, 213-220. (111) Kanaani, J.; Ginsburg, H. J. Biol. Chem. 1989, 264, 3194-3199. (112) Haynes, J. D.; Moch, J. K. Methods Mol. Med. 2002, 72, 489-497. (113) Carter, R.; Ranford-Cartwright, L.; Alano, P. Methods Mol. Biol. 1993, 21, 67-88.
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