Independent Recruitment of Different Types of Phospholipases A2 to the Venoms of Caenophidian Snakes: The Rise of PLA2-IIE within Pseudoboini (Dipsadidae).

Snake venoms harbor a wide and diverse array of enzymatic and nonenzymatic toxic components, allowing them to exert myriad effects on their prey. However, they appear to trend toward a few optimal compositional scaffolds, dominated by four major toxin classes: SVMPs, SVSPs, 3FTxs, and PLA2s. Nevertheless, the latter appears to be restricted to vipers and elapids, as it has never been reported as a major venom component in rear-fanged species. Here, by investigating the original transcriptomes from 19 species distributed in eight genera from the Pseudoboini tribe (Dipsadidae: Xenodontinae) and screening among seven additional tribes of Dipsadidae and three additional families of advanced snakes, we discovered that a novel type of venom PLA2, resembling a PLA2-IIE, has been recruited to the venom of some species of the Pseudoboini tribe, where it is a major component. Proteomic and functional analyses of these venoms further indicate that these PLA2s play a relevant role in the venoms from this tribe. Moreover, we reconstructed the phylogeny of PLA2s across different snake groups and show that different types of these toxins have been recruited in at least five independent events in caenophidian snakes. Additionally, we present the first compositional profiling of Pseudoboini venoms. Our results demonstrate how relevant phenotypic traits are convergently recruited by different means and from homologous and nonhomologous genes in phylogenetically and ecologically divergent snake groups, possibly optimizing venom composition to overcome diverse adaptative landscapes.

SARS-CoV-2 Proteins Bind to Hemoglobin and Its Metabolites.

(1) Background: coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been linked to hematological dysfunctions, but there are little experimental data that explain this. Spike (S) and Nucleoprotein (N) proteins have been putatively associated with these dysfunctions. In this work, we analyzed the recruitment of hemoglobin (Hb) and other metabolites (hemin and protoporphyrin IX-PpIX) by SARS-Cov2 proteins using different approaches. (2) Methods: shotgun proteomics (LC-MS/MS) after affinity column adsorption identified hemin-binding SARS-CoV-2 proteins. The parallel synthesis of the peptides technique was used to study the interaction of the receptor bind domain (RBD) and N-terminal domain (NTD) of the S protein with Hb and in silico analysis to identify the binding motifs of the N protein. The plaque assay was used to investigate the inhibitory effect of Hb and the metabolites hemin and PpIX on virus adsorption and replication in Vero cells. (3) Results: the proteomic analysis by LC-MS/MS identified the S, N, M, Nsp3, and Nsp7 as putative hemin-binding proteins. Six short sequences in the RBD and 11 in the NTD of the spike were identified by microarray of peptides to interact with Hb and tree motifs in the N protein by in silico analysis to bind with heme. An inhibitory effect in vitro of Hb, hemin, and PpIX at different levels was observed. Strikingly, free Hb at 1mM suppressed viral replication (99%), and its interaction with SARS-CoV-2 was localized into the RBD region of the spike protein. (4) Conclusions: in this study, we identified that (at least) five proteins (S, N, M, Nsp3, and Nsp7) of SARS-CoV-2 recruit Hb/metabolites. The motifs of the RDB of SARS-CoV-2 spike, which binds Hb, and the sites of the heme bind-N protein were disclosed. In addition, these compounds and PpIX block the virus's adsorption and replication. Furthermore, we also identified heme-binding motifs and interaction with hemin in N protein and other structural (S and M) and non-structural (Nsp3 and Nsp7) proteins.

PepExplorer: a similarity-driven tool for analyzing de novo sequencing results.

Peptide spectrum matching is the current gold standard for protein identification via mass-spectrometry-based proteomics. Peptide spectrum matching compares experimental mass spectra against theoretical spectra generated from a protein sequence database to perform identification, but protein sequences not present in a database cannot be identified unless their sequences are in part conserved. The alternative approach, de novo sequencing, can make it possible to infer a peptide sequence directly from a mass spectrum, but interpreting long lists of peptide sequences resulting from large-scale experiments is not trivial. With this as motivation, PepExplorer was developed to use rigorous pattern recognition to assemble a list of homologue proteins using de novo sequencing data coupled to sequence alignment to allow biological interpretation of the data. PepExplorer can read the output of various widely adopted de novo sequencing tools and converge to a list of proteins with a global false-discovery rate. To this end, it employs a radial basis function neural network that considers precursor charge states, de novo sequencing scores, peptide lengths, and alignment scores to select similar protein candidates, from a target-decoy database, usually obtained from phylogenetically related species. Alignments are performed using a modified Smith-Waterman algorithm tailored for the task at hand. We verified the effectiveness of our approach using a reference set of identifications generated by ProLuCID when searching for Pyrococcus furiosus mass spectra on the corresponding NCBI RefSeq database. We then modified the sequence database by swapping amino acids until ProLuCID was no longer capable of identifying any proteins. By searching the mass spectra using PepExplorer on the modified database, we were able to recover most of the identifications at a 1% false-discovery rate. Finally, we employed PepExplorer to disclose a comprehensive proteomic assessment of the Bothrops jararaca plasma, a known biological source of natural inhibitors of snake toxins. PepExplorer is integrated into the PatternLab for Proteomics environment, which makes available various tools for downstream data analysis, including resources for quantitative and differential proteomics.

A snapshot of Bothrops jararaca snake venom gland subcellular proteome.

Snake venom protein synthesis undergoes finely regulated processes in the specialized secretory epithelium within the venom gland. Such processes occur within a defined period in the cell and at specific cellular locations. Thus, the determination of subcellular proteomes allows the characterization of protein groups for which the site may be relevant to their biological roles, thereby allowing the deconvolution of complex biological circuits into functional information. In this regard, we performed subcellular fractionation of proteins from B. jararaca venom gland, focusing on nuclear proteins since this cellular compartment comprises key effectors that shape gene expression. Our results provided a snapshot of B. jararaca's subcellular venom gland proteome and pointed to a 'conserved' proteome core among different life stages (newborn and adult) and between sexes (adult male and female). Overall, the top 15 highly abundant proteins identified in B. jararaca venom glands mirrored the panel of highly expressed genes in human salivary glands. Therefore, the expression profile observed for such a protein set could be considered a conserved core signature of salivary gland secretory epithelium. Moreover, the newborn venom gland displayed a unique expression signature of transcription factors involved in regulating transcription and biosynthetic processes and may mirror biological constraints of the ontogenetic development of B. jararaca, contributing to venom proteome diversity.

DiagnoMass: A proteomics hub for pinpointing discriminative spectral clusters.

MOTIVATION: There are several well-established paradigms for identifying and pinpointing discriminative peptides/proteins using shotgun proteomic data; examples are peptide-spectrum matching, de novo sequencing, open searches, and even hybrid approaches. Such an arsenal of complementary paradigms can provide deep data coverage, albeit some unidentified discriminative peptides remain. RESULTS: We present DiagnoMass, software tool that groups similar spectra into spectral clusters and then shortlists those clusters that are discriminative for biological conditions. DiagnoMass then communicates with proteomic tools to attempt the identification of such clusters. We demonstrate the effectiveness of DiagnoMass by analyzing proteomic data from Escherichia coli, Salmonella, and Shigella, listing many high-quality discriminative spectral clusters that had thus far remained unidentified by widely adopted proteomic tools. DiagnoMass can also classify proteomic profiles. We anticipate the use of DiagnoMass as a vital tool for pinpointing biomarkers. AVAILABILITY: DiagnoMass and related documentation, including a usage protocol, are available at http://www.diagnomass.com.

Search engine processor: Filtering and organizing peptide spectrum matches.

The search engine processor (SEPro) is a tool for filtering, organizing, sharing, and displaying peptide spectrum matches. It employs a novel three-tier Bayesian approach that uses layers of spectrum, peptide, and protein logic to lead the data to converge to a single list of reliable protein identifications. SEPro is integrated into the PatternLab for proteomics environment, where an arsenal of tools for analyzing shotgun proteomic data is provided. By using the semi-labeled decoy approach for benchmarking, we show that SEPro significantly outperforms a commercially available competitor.

Platelet proteome reveals features of cell death, antiviral response and viral replication in covid-19.

Coronavirus disease 2019 (COVID-19) has affected over 400 million people worldwide, leading to 6 million deaths. Among the complex symptomatology of COVID-19, hypercoagulation and thrombosis have been described to directly contribute to lethality, pointing out platelets as an important SARS-CoV-2 target. In this work, we explored the platelet proteome of COVID-19 patients through a label-free shotgun proteomics approach to identify platelet responses to infection, as well as validation experiments in a larger patient cohort. Exclusively detected proteins (EPs) and differentially expressed proteins (DEPs) were identified in the proteomic dataset and thus classified into biological processes to map pathways correlated with pathogenesis. Significant changes in the expression of proteins related to platelet activation, cell death, and antiviral response through interferon type-I were found in all patients. Since the outcome of COVID-19 varies highly among individuals, we also performed a cross-comparison of proteins found in survivors and nonsurvivors. Proteins belonging to the translation pathway were strongly highlighted in the nonsurvivor group. Moreover, the SARS-CoV-2 genome was fully sequenced in platelets from five patients, indicating viral internalization and preprocessing, with CD147 as a potential entry route. In summary, platelets play a significant role in COVID-19 pathogenesis via platelet activation, antiviral response, and disease severity.

Simple, efficient and thorough shotgun proteomic analysis with PatternLab V.

Shotgun proteomics aims to identify and quantify the thousands of proteins in complex mixtures such as cell and tissue lysates and biological fluids. This approach uses liquid chromatography coupled with tandem mass spectrometry and typically generates hundreds of thousands of mass spectra that require specialized computational environments for data analysis. PatternLab for proteomics is a unified computational environment for analyzing shotgun proteomic data. PatternLab V (PLV) is the most comprehensive and crucial update so far, the result of intensive interaction with the proteomics community over several years. All PLV modules have been optimized and its graphical user interface has been completely updated for improved user experience. Major improvements were made to all aspects of the software, ranging from boosting the number of protein identifications to faster extraction of ion chromatograms. PLV provides modules for preparing sequence databases, protein identification, statistical filtering and in-depth result browsing for both labeled and label-free quantitation. The PepExplorer module can even pinpoint de novo sequenced peptides not already present in the database. PLV is of broad applicability and therefore suitable for challenging experimental setups, such as time-course experiments and data handling from unsequenced organisms. PLV interfaces with widely adopted software and community initiatives, e.g., Comet, Skyline, PEAKS and PRIDE. It is freely available at http://www.patternlabforproteomics.org .

Can the false-discovery rate be misleading?

The decoy-database approach is currently the gold standard for assessing the confidence of identifications in shotgun proteomic experiments. Here, we demonstrate that what might appear to be a good result under the decoy-database approach for a given false-discovery rate could be, in fact, the product of overfitting. This problem has been overlooked until now and could lead to obtaining boosted identification numbers whose reliability does not correspond to the expected false-discovery rate. To overcome this, we are introducing a modified version of the method, termed a semi-labeled decoy approach, which enables the statistical determination of an overfitted result.

Diversity of metalloproteinases in Bothrops neuwiedi snake venom transcripts: evidences for recombination between different classes of SVMPs.

BACKGROUND: Snake venom metalloproteinases (SVMPs) are widely distributed in snake venoms and are versatile toxins, targeting many important elements involved in hemostasis, such as basement membrane proteins, clotting proteins, platelets, endothelial and inflammatory cells. The functional diversity of SVMPs is in part due to the structural organization of different combinations of catalytic, disintegrin, disintegrin-like and cysteine-rich domains, which categorizes SVMPs in 3 classes of precursor molecules (PI, PII and PIII) further divided in 11 subclasses, 6 of them belonging to PII group. This heterogeneity is currently correlated to genetic accelerated evolution and post-translational modifications. RESULTS: Thirty-one SVMP cDNAs were full length cloned from a single specimen of Bothrops neuwiedi snake, sequenced and grouped in eleven distinct sequences and further analyzed by cladistic analysis. Class P-I and class P-III sequences presented the expected tree topology for fibrinolytic and hemorrhagic SVMPs, respectively. In opposition, three distinct segregations were observed for class P-II sequences. P-IIb showed the typical segregation of class P-II SVMPs. However, P-IIa grouped with class P-I cDNAs presenting a 100% identity in the 365 bp at their 5' ends, suggesting post-transcription events for interclass recombination. In addition, catalytic domain of P-IIx sequences segregated with non-hemorrhagic class P-III SVMPs while their disintegrin domain grouped with other class P-II disintegrin domains suggesting independent evolution of catalytic and disintegrin domains. Complementary regions within cDNA sequences were noted and may participate in recombination either at DNA or RNA levels. Proteins predicted by these cDNAs show the main features of the correspondent classes of SVMP, but P-IIb and P-IIx included two additional cysteines cysteines at the C-termini of the disintegrin domains in positions not yet described. CONCLUSIONS: In B. neuwiedi venom gland, class P-II SVMPs were represented by three different types of transcripts that may have arisen by interclass recombination with P-I and P-III sequences after the divergence of the different classes of SVMPs. Our observations indicate that exon shuffling or post-transcriptional mechanisms may be driving these recombinations generating new functional possibilities for this complex group of snake toxins.

Molecular Architecture of the Antiophidic Protein DM64 and its Binding Specificity to Myotoxin II From Bothrops asper Venom.

DM64 is a toxin-neutralizing serum glycoprotein isolated from Didelphis aurita, an ophiophagous marsupial naturally resistant to snake envenomation. This 64 kDa antitoxin targets myotoxic phospholipases A2, which account for most local tissue damage of viperid snakebites. We investigated the noncovalent complex formed between native DM64 and myotoxin II, a myotoxic phospholipase-like protein from Bothrops asper venom. Analytical ultracentrifugation (AUC) and size exclusion chromatography indicated that DM64 is monomeric in solution and binds equimolar amounts of the toxin. Attempts to crystallize native DM64 for X-ray diffraction were unsuccessful. Obtaining recombinant protein to pursue structural studies was also challenging. Classical molecular modeling techniques were impaired by the lack of templates with more than 25% sequence identity with DM64. An integrative structural biology approach was then applied to generate a three-dimensional model of the inhibitor bound to myotoxin II. I-TASSER individually modeled the five immunoglobulin-like domains of DM64. Distance constraints generated by cross-linking mass spectrometry of the complex guided the docking of DM64 domains to the crystal structure of myotoxin II, using Rosetta. AUC, small-angle X-ray scattering (SAXS), molecular modeling, and molecular dynamics simulations indicated that the DM64-myotoxin II complex is structured, shows flexibility, and has an anisotropic shape. Inter-protein cross-links and limited hydrolysis analyses shed light on the inhibitor's regions involved with toxin interaction, revealing the critical participation of the first, third, and fifth domains of DM64. Our data showed that the fifth domain of DM64 binds to myotoxin II amino-terminal and beta-wing regions. The third domain of the inhibitor acts in a complementary way to the fifth domain. Their binding to these toxin regions presumably precludes dimerization, thus interfering with toxicity, which is related to the quaternary structure of the toxin. The first domain of DM64 interacts with the functional site of the toxin putatively associated with membrane anchorage. We propose that both mechanisms concur to inhibit myotoxin II toxicity by DM64 binding. The present topological characterization of this toxin-antitoxin complex constitutes an essential step toward the rational design of novel peptide-based antivenom therapies targeting snake venom myotoxins.

Conformational plasticity of DM43, a metalloproteinase inhibitor from Didelphis marsupialis: chemical and pressure-induced equilibrium (un)folding studies.

We have investigated the folding of DM43, a homodimeric metalloproteinase inhibitor isolated from the serum of the South American opossum Didelphis marsupialis. Denaturation of the protein induced by GdnHCl (guanidine hydrochloride) was monitored by extrinsic and intrinsic fluorescence spectroscopy. While the equilibrium (un)folding of DM43 followed by tryptophan fluorescence was well described by a cooperative two-state transition, bis-ANS (4,4'-dianilino-1,1'-binaphthyl-5,5'-disulfonic acid) fluorescence measurements revealed an intensity maximum at the midpoint of the unfolding transition (2 M GdnHCl), indicating a partially folded intermediate state. We further investigated the DM43 intermediate stabilized at 2 M GdnHCl using size exclusion chromatography. This analysis revealed that the folding intermediate can be best described as partially folded DM43 monomers. Thermodynamic analysis of the GdnHCl-induced denaturation of DM43 revealed Gibbs free-energy changes of 13.57 kcal/mol for dimer dissociation and 1.86 kcal/mol for monomer unfolding, pointing to a critical role of dimerization as a determinant of the structure and stability of this protein. In addition, by using hydrostatic pressure (up to 3.5 kbar) we were able to stabilize partially folded states different from those stabilized in the presence of GdnHCl. Taken together, these results indicate that the conformational plasticity of DM43 could provide this protein with the ability to adapt its conformation to a variety of different environments and biological partners during its biological lifetime.

The interaction between the natural metalloendopeptidase inhibitor BJ46a and its target toxin jararhagin analyzed by structural mass spectrometry and molecular modeling.

Snakebite envenoming affects millions of people worldwide, being officially considered a neglected tropical disease by the World Health Organization. The antivenom is effective in neutralizing the systemic effects of envenomation, but local effects are poorly neutralized, often leading to permanent disability. The natural resistance of the South American pit viper Bothrops jararaca to its venom is partly attributed to BJ46a, a natural snake venom metalloendopeptidase inhibitor. Upon complex formation, BJ46a binds non-covalently to the metalloendopeptidase, rendering it unable to exert its proteolytic activity. However, the structural features that govern this interaction are largely unknown. In this work, we applied structural mass spectrometry techniques (cross-linking-MS and hydrogen-deuterium exchange MS) and in silico analyses (molecular modeling, docking, and dynamics simulations) to understand the interaction between BJ46a and jararhagin, a metalloendopeptidase from B. jararaca venom. We explored the distance restraints generated from XL-MS experiments to guide the modeling of BJ46a and jararhagin, as well as the protein-protein docking simulations. HDX-MS data pinpointed regions of protection/deprotection at the interface of the BJ46a-jararhagin complex which, in addition to the molecular dynamics simulation data, reinforced our proposed interaction model. Ultimately, the structural understanding of snake venom metalloendopeptidases inhibition by BJ46a could lead to the rational design of drugs to improve anti-snake venom therapeutics, alleviating the high morbidity rates currently observed.

Mixed-Data Acquisition: Next-Generation Quantitative Proteomics Data Acquisition.

We present the Mixed-Data Acquisition (MDA) strategy for mass spectrometry data acquisition. MDA combines Data-Dependent Acquisition (DDA) and Data-Independent Acquisition (DIA) in the same run, thus doing away with the requirements for separate DDA spectral libraries. MDA is a natural result from advances in mass spectrometry, such as high scan rates and multiple analyzers, and is tailored toward exploiting these features. We demonstrate MDA's effectiveness on a yeast proteome analysis by overcoming a common bottleneck for XIC-based label-free quantitation; namely, the coelution of precursors when m/z values cannot be distinguished. We anticipate that MDA will become the next mainstream data generation approach for proteomics. MDA can also serve as an orthogonal validation approach for DDA experiments. Specialized software for MDA data analysis is made available on the project's website.

Analysis of the subproteomes of proteinases and heparin-binding toxins of eight Bothrops venoms.

Viperid snakes show the most complex snake-venom proteomes and offer an intriguing challenge in terms of understanding the nature of their components and the pathological outcomes of envenomation characterized by local and systemic effects. In this work, the venom complexity of eight Bothrops species was analyzed by 2-DE, and their subproteomes of proteinases were explored by 2-D immunostaining and 2-D gelatin zymography, demonstrating the diversity of their profiles. Heparin, a highly sulfated glycosaminoglycan released from mast cells, is involved in anti-coagulant and anti-inflammatory processes. Here, we explored the hypothesis that heparin released upon envenomation could interact with toxins and interfere with venom pathogenesis. We first identified the Bothrops venom subproteome of toxins that bind with high-affinity for heparin as composed of mainly serine proteinases and C-type lectins. Next, we explored the Bothrops jararaca toxins that bind to heparin under physiological conditions and identified a relationship between the subproteomes of proteinases, and that of heparin-binding toxins. Only the non-bound fraction, composed mainly of metalloproteinases, showed lethal and hemorrhagic activities, whereas the heparin-bound fraction contained mainly serine proteinases associated with coagulant and fibrinogenolytic activities. These data suggest that heparin binding to B. jararaca venom components in vivo has a minor protective effect to venom toxicity.

Molecular effects of Microcystin-LA in tilapia (Oreochromis niloticus).

Nile tilapia (Oreochromis niloticus) is a freshwater phytoplanktivorous fish species reported to accumulate and tolerate large amounts of cyanotoxins such as microcystins (MCs). The present study aimed to investigate molecular responses to the acute exposure of Nile tilapia to the Microcystin-LA analogue (MC-LA). Thus, the specimens were sublethally exposed to 1000 µg kg-1 of MC-LA for 12, 24, 48, and 96 h. Gene expression of PP1, PP2A, GST, GPX and actin was analyzed by quantitative PCR. The protein abundance profile of PP2A was determined by immunoblotting, while the integrity of its biological function was assessed by a phosphatase enzymatic assay. PP2A activity was significantly and strongly reduced by MC-LA. A resulting feedback mechanism significantly increased PP2A gene expression and protein abundance in all assessed times. However, a recovery of that phosphatase activity was not observed. In this study, the observed increase in GPX gene expression was the only response that could be directly related to the unknown factors associated to the fish survival to such high dose exposure.

Data on antigen recognition hindrance by antibodies covalently immobilized to Protein G magnetic beads by dimethyl pimelimidate (DMP) cross-linking.

The data presented herein is related to the article entitled "Trypanosoma cruzi immunoproteome: calpain-like CAP5.5 differentially detected throughout distinct stages of human Chagas disease cardiomyopathy" [1]. Electrophoretic analyses under denaturing and reducing conditions indicate that covalent immobilization of human IgG to Protein G magnetic beads by cross-linking with 50 mM dimethyl pimelimidate hinders the recognition of T. cruzi antigens in immunoprecipitation assays.

Trypanosoma cruzi immunoproteome: Calpain-like CAP5.5 differentially detected throughout distinct stages of human Chagas disease cardiomyopathy.

Chagas disease, caused by the protozoan Trypanosoma cruzi, affects millions of people worldwide, especially in Latin America. Approximately 30% of the cases evolve to the chronic symptomatic stage due to cardiac and/or digestive damage, generally accompanied by nervous system impairment. Given the higher frequency and severity of clinical manifestations related to cardiac tissue lesion, the goal of this study was the identification of proteins associated with the disease progression towards its cardiac form. Thus, T. cruzi bloodstream trypomastigotes proteins were submitted to immunoprecipitation using antibodies from patients with the asymptomatic or cardiac (stages B1 and C) forms of the disease and from healthy donors as control. Immunoreactive proteins were identified and quantified based on mass spectrometry analysis and shifts in the recognition profile were further evaluated. Compared to asymptomatic samples, IgG from stage C patients predominantly detected the I/6 autoantigen, whereas IgG from B1 patients resulted in higher yield of dihydrolipoamide acetyltransferase precursor, calpain cysteine peptidase, and two variants of CAP5.5. In this work, CAP5.5 recognition by serum immunoglobulin from patients with early cardiomyopathy generated a 23-fold abundance variation when compared to samples from asymptomatic patients, highlighting the participation of this protein in cardiac form progression of the disease. SIGNIFICANCE: While T. cruzi has become the major cause of infectious cardiomyopathy in Latin America, research groups have been struggling to find alternative treatment, vaccine candidates, and improved diagnostic tests. In addition, the absence of adequate biomarkers to assess cure and progression of disease is a major setback for clinical trials and patients monitoring. Therefore, our findings may contribute to a better understanding of T. cruzi pathogenesis and evaluation of suitable candidates for vaccine and diagnostic tests, besides the clinical applicability of the potential biomarkers for patient follow-up and prognosis. Finally, the identification of T. cruzi proteins recognized by IgG from healthy donors may contribute for the understanding and discovery of epitope conservation among a broad range of pathogens.

Quantitative Proteomic Map of the Trypanosomatid Strigomonas culicis: The Biological Contribution of its Endosymbiotic Bacterium.

Strigomonas culicis is a kinetoplastid parasite of insects that maintains a mutualistic association with an intracellular symbiotic bacterium, which is highly integrated into the protist metabolism: it furnishes essential compounds and divides in synchrony with the eukaryotic nucleus. The protist, conversely, can be cured of the endosymbiont, producing an aposymbiotic cell line, which presents a diminished ability to colonize the insect host. This obligatory association can represent an intermediate step of the evolution towards the formation of an organelle, therefore representing an interesting model to understand the symbiogenesis theory. Here, we used shotgun proteomics to compare the S. culicis endosymbiont-containing and aposymbiotic strains, revealing a total of 11,305 peptides, and up to 2,213 proteins (2,029 and 1,452 for wild type and aposymbiotic, respectively). Gene ontology associated to comparative analysis between both strains revealed that the biological processes most affected by the elimination of the symbiont were the amino acid synthesis, as well as protein synthesis and folding. This large-scale comparison of the protein expression in S. culicis marks a step forward in the comprehension of the role of endosymbiotic bacteria in monoxenous trypanosomatid biology, particularly because trypanosomatids expression is mostly post-transcriptionally regulated.

Deciphering the proteomic profile of Mycobacterium leprae cell envelope.

The complete sequence of the Mycobacterium leprae genome, an obligate intracellular pathogen, shows a dramatic reduction of functional genes, with a coding capacity of less than 50%. Despite this massive gene decay, the leprosy bacillus has managed to preserve a minimal gene set, most of it shared with Mycobacterium tuberculosis, allowing its survival in the host with ensuing pathological manifestations. Thus, the identification of proteins that are actually expressed in vivo by M. leprae is of high significance in understanding obligate, intracellular mycobacterial pathogenesis. In this study, a high-throughput proteomic approach was undertaken resulting in the identification of 218 new M. leprae proteins. Of these, 60 were in the soluble/cytosol fraction, 98 in the membrane and 104 in the cell wall. Although several proteins were identified in more than one subcellular fraction, the majority were unique to one. As expected, a high percentage of these included enzymes responsible for lipid biosynthesis and degradation, biosynthesis of the major components of the mycobacterial cell envelope, proteins involved in transportation across lipid barriers, and lipoproteins and transmembrane proteins with unknown functions. The data presented in this study contribute to our understanding of the in vivo composition and physiology of the mycobacterial cell envelope, a compartment known to play a major role in bacterial pathogenesis.