Gustavo A. de Souza

Definition of novel cell envelope associated proteins in Triton X-114 extracts of Mycobacterium tuberculosis H37Rv

BackgroundMembrane- and membrane-associated proteins are important for the pathogenicity of bacteria. We have analysed the content of these proteins in virulent Mycobacterium tuberculosis H37Rv using Triton X-114 detergent-phase separation for extraction of lipophilic proteins, followed by their identification with high resolution mass spectrometry.ResultsIn total, 1417 different proteins were identified. In silico analysis of the identified proteins revealed that 248 proteins had at least one predicted trans-membrane region. Also, 64 of the identified proteins were predicted lipoproteins, and 54 proteins were predicted as outer membrane proteins. Three-hundred-and-ninety-five of the observed proteins, including 91 integral membrane proteins were described for the first time. Comparison of abundance levels of the identified proteins was performed using the exponentially modified protein abundance index (emPAI) which takes into account the number of the observable peptides to the number of experimentally observed peptide ions for a given protein. The outcome showed that among the membrane-and membrane-associated proteins several proteins are present with high relative abundance. Further, a close examination of the lipoprotein LpqG (Rv3623) which is only detected in the membrane fractions of M. tuberculosis but not in M. bovis, revealed that the homologous gene in M. bovis lack the signal peptide and lipobox motif, suggesting impaired export to the membrane.ConclusionsAltogether, we have identified a substantial proportion of membrane- and membrane-associated proteins of M. tuberculosis H37Rv, compared the relative abundance of the identified proteins and also revealed subtle differences between the different members of the M. tuberculosis complex.

Bacterial proteins with cleaved or uncleaved signal peptides of the general secretory pathway

Correct protein compartmentalization is a key step for molecular function and cell viability, and this is especially true for membrane and externalized proteins of bacteria. Recent proteomic reports of Bacillus subtilis have shown that many proteins with Sec-like signal peptides and absence of a transmembrane helix domain are still observed in membrane-enriched fractions, but further evidence about signal peptide cleavage or soluble protein contamination is still needed. Here we report a proteomic screening of identified peptides in culture filtrate, membrane fraction and whole cell lysate of Mycobacterium tuberculosis. We were able to detect peptide sequencing evidence that shows that the predicted signal peptide was kept uncleaved for several types of proteins such as mammalian cell entry (Mce) proteins and PE or PE-PGRS proteins. Label-free quantitation of all proteins identified in each fraction showed that the majority of these proteins with uncleaved signal peptides are, indeed, enriched in the Triton X-114 lipid phase. Some of these proteins are likely to be located in the inner membrane while others may be outer membrane proteins.

High accuracy mass spectrometry analysis as a tool to verify and improve gene annotation using Mycobacterium tuberculosis as an example

BackgroundWhile the genomic annotations of diverse lineages of the Mycobacterium tuberculosis complex are available, divergences between gene prediction methods are still a challenge for unbiased protein dataset generation. M. tuberculosis gene annotation is an example, where the most used datasets from two independent institutions (Sanger Institute and Institute of Genomic Research-TIGR) differ up to 12% in the number of annotated open reading frames, and 46% of the genes contained in both annotations have different start codons. Such differences emphasize the importance of the identification of the sequence of protein products to validate each gene annotation including its sequence coding area.ResultsWith this objective, we submitted a culture filtrate sample from M. tuberculosis to a high-accuracy LTQ-Orbitrap mass spectrometer analysis and applied refined N-terminal prediction to perform comparison of two gene annotations. From a total of 449 proteins identified from the MS data, we validated 35 tryptic peptides that were specific to one of the two datasets, representing 24 different proteins. From those, 5 proteins were only annotated in the Sanger database. In the remaining proteins, the observed differences were due to differences in annotation of transcriptional start sites.ConclusionOur results indicate that, even in a less complex sample likely to represent only 10% of the bacterial proteome, we were still able to detect major differences between different gene annotation approaches. This gives hope that high-throughput proteomics techniques can be used to improve and validate gene annotations, and in particular for verification of high-throughput, automatic gene annotations.

Comparison of membrane proteins of Mycobacterium tuberculosis H37Rv and H37Ra strains

BackgroundThe potential causes for variation in virulence between distinct M. tuberculosis strains are still not fully known. However, differences in protein expression are probably an important factor. In this study we used a label-free quantitative proteomic approach to estimate differences in protein abundance between two closely related M. tuberculosis strains; the virulent H37Rv strain and its attenuated counterpart H37Ra.ResultsWe were able to identify more than 1700 proteins from both strains. As expected, the majority of the identified proteins had similar relative abundance in the two strains. However, 29 membrane-associated proteins were observed with a 5 or more fold difference in their relative abundance in one strain compared to the other. Of note, 19 membrane- and lipo-proteins had higher abundance in H37Rv, while another 10 proteins had a higher abundance in H37Ra. Interestingly, the possible protein-export membrane protein SecF (Rv2586c), and three ABC-transporter proteins (Rv0933, Rv1273c and Rv1819c) were among the more abundant proteins in M. tuberculosis H37Rv.ConclusionOur data suggests that the bacterial secretion system and the transmembrane transport system may be important determinants of the ability of distinct M. tuberculosis strains to cause disease.

Using a Label-free Proteomics Method to Identify Differentially Abundant Proteins in Closely Related Hypo- and Hypervirulent Clinical Mycobacterium tuberculosis Beijing Isolates

Although the genome of the Mycobacterium tuberculosis H37Rv laboratory strain has been available for over 10 years, it is only recently that genomic information from clinical isolates has been used to generate the hypothesis of virulence differences between different strains. In addition, the relationship between strains displaying differing virulence in an epidemiological setting and their behavior in animal models has received little attention. The potential causes for variation in virulence between strains, as determined by differential protein expression, have similarly been a neglected area of investigation. In this study, we used a label-free quantitative proteomics approach to estimate differences in protein abundance between two closely related Beijing genotypes that have been shown to be hyper- and hypovirulent on the basis of both epidemiological and mouse model studies. We were able to identify a total of 1668 proteins from both samples, and protein abundance calculations revealed that 48 proteins were over-represented in the hypovirulent isolate, whereas 53 were over-represented in the hypervirulent. Functional classification of these results shows that molecules of cell wall organization and DNA transcription regulatory proteins may have a critical influence in defining the level of virulence. The reduction in the presence of ESAT-6, other Esx-like proteins, and FbpD (MPT51) in the hypervirulent strain indicates that changes in the repertoire of highly immunogenic proteins can be a defensive process undertaken by the virulent cell. In addition, most of the previously well characterized gene targets related to virulence were found to be similarly expressed in our model. Our data support the use of proteomics as a complementary tool for genomic comparisons to understand the biology of M. tuberculosis virulence.

Membrane and membrane-associated proteins in Triton X-114 extracts of Mycobacterium bovis BCG identified using a combination of gel-based and gel-free fractionation strategies

Tuberculosis is an ancient disease that remains a significant global health problem. Because many membrane and membrane‐associated proteins of this pathogen represent potential targets for drugs, diagnostic probes or vaccine components, we have analysed Mycobacterium bovis, bacillus Calmette–Guérin (BCG) substrain Moreau, using Triton X‐114 for extraction of lipophilic proteins, followed by identification with LC coupled MS/MS. We identified 351 different proteins in total, and 103 (29%) were predicted as integral membrane proteins with at least one predicted transmembrane region and another 84 (23.9%) proteins had a positive grand average of hydropathicity (GRAVY) value, indicating increased probability for membrane association. Altogether 43 predicted lipoproteins (Lpps) were identified which is close to 50% of the total number of Lpps in the genome. Fifty‐four proteins, including twenty‐four predicted integral membrane proteins and seven predicted Lpps are described for the first time. The proportion of hydrophobic membrane and membrane‐associated proteins shows that Triton X‐114 is a highly efficient method for extraction of membrane proteins from bacteria, without the need for preisolation of membranes. ATP synthase, NAD(P) transhydrogenase, ubiquinone oxidoreductase and ubiquinol–cytochrome C reductase appear to represent major enzyme complexes in the membrane of Mycobacterium tuberculosis complex organisms.

Proteogenomic Analysis of Polymorphisms and Gene Annotation Divergences in Prokaryotes using a Clustered Mass Spectrometry-Friendly Database

Precise annotation of genes or open reading frames is still a difficult task that results in divergence even for data generated from the same genomic sequence. This has an impact in further proteomic studies, and also compromises the characterization of clinical isolates with many specific genetic variations that may not be represented in the selected database. We recently developed software called multistrain mass spectrometry prokaryotic database builder (MSMSpdbb) that can merge protein databases from several sources and be applied on any prokaryotic organism, in a proteomic-friendly approach. We generated a database for the Mycobacterium tuberculosis complex (using three strains of Mycobacterium bovis and five of M. tuberculosis), and analyzed data collected from two laboratory strains and two clinical isolates of M. tuberculosis. We identified 2561 proteins, of which 24 were present in M. tuberculosis H37Rv samples, but not annotated in the M. tuberculosis H37Rv genome. We were also able to identify 280 nonsynonymous single amino acid polymorphisms and confirm 367 translational start sites. As a proof of concept we applied the database to whole-genome DNA sequencing data of one of the clinical isolates, which allowed the validation of 116 predicted single amino acid polymorphisms and the annotation of 131 N-terminal start sites. Moreover we identified regions not present in the original M. tuberculosis H37Rv sequence, indicating strain divergence or errors in the reference sequence. In conclusion, we demonstrated the potential of using a merged database to better characterize laboratory or clinical bacterial strains.

Phosphoproteomics analysis of a clinical Mycobacterium tuberculosis Beijing isolate: expanding the mycobacterial phosphoproteome catalog

Reversible protein phosphorylation, regulated by protein kinases and phosphatases, mediates a switch between protein activity and cellular pathways that contribute to a large number of cellular processes. The Mycobacterium tuberculosis genome encodes 11 Serine/Threonine kinases (STPKs) which show close homology to eukaryotic kinases. This study aimed to elucidate the phosphoproteomic landscape of a clinical isolate of M. tuberculosis. We performed a high throughput mass spectrometric analysis of proteins extracted from an early-logarithmic phase culture. Whole cell lysate proteins were processed using the filter-aided sample preparation method, followed by phosphopeptide enrichment of tryptic peptides by strong cation exchange (SCX) and Titanium dioxide (TiO2) chromatography. The MaxQuant quantitative proteomics software package was used for protein identification. Our analysis identified 414 serine/threonine/tyrosine phosphorylated sites, with a distribution of S/T/Y sites; 38% on serine, 59% on threonine and 3% on tyrosine; present on 303 unique peptides mapping to 214 M. tuberculosis proteins. Only 45 of the S/T/Y phosphorylated proteins identified in our study had been previously described in the laboratory strain H37Rv, confirming previous reports. The remaining 169 phosphorylated proteins were newly identified in this clinical M. tuberculosis Beijing strain. We identified 5 novel tyrosine phosphorylated proteins. These findings not only expand upon our current understanding of the protein phosphorylation network in clinical M. tuberculosis but the data set also further extends and complements previous knowledge regarding phosphorylated peptides and phosphorylation sites in M. tuberculosis.

Evaluation of signal peptide prediction algorithms for identification of mycobacterial signal peptides using sequence data from proteomic methods.

Secreted proteins play an important part in the pathogenicity of Mycobacterium tuberculosis, and are the primary source of vaccine and diagnostic candidates. A majority of these proteins are exported via the signal peptidase I-dependent pathway, and have a signal peptide that is cleaved off during the secretion process. Sequence similarities within signal peptides have spurred the development of several algorithms for predicting their presence as well as the respective cleavage sites. For proteins exported via this pathway, algorithms exist for eukaryotes, and for Gram-negative and Gram-positive bacteria. However, the unique structure of the mycobacterial membrane raises the question of whether the existing algorithms are suitable for predicting signal peptides within mycobacterial proteins. In this work, we have evaluated the performance of nine signal peptide prediction algorithms on a positive validation set, consisting of 57 proteins with a verified signal peptide and cleavage site, and a negative set, consisting of 61 proteins that have an N-terminal sequence that confirms the annotated translational start site. We found the hidden Markov model of SignalP v3.0 to be the best-performing algorithm for predicting the presence of a signal peptide in mycobacterial proteins. It predicted no false positives or false negatives, and predicted a correct cleavage site for 45 of the 57 proteins in the positive set. Based on these results, we used the hidden Markov model of SignalP v3.0 to analyse the 10 available annotated proteomes of mycobacterial species, including annotations of M. tuberculosis H37Rv from the Wellcome Trust Sanger Institute and the J. Craig Venter Institute (JCVI). When excluding proteins with transmembrane regions among the proteins predicted to harbour a signal peptide, we found between 7.8 and 10.5 % of the proteins in the proteomes to be putative secreted proteins. Interestingly, we observed a consistent difference in the percentage of predicted proteins between the Sanger Institute and JCVI. We have determined the most valuable algorithm for predicting signal peptidase I-processed proteins of M. tuberculosis, and used this algorithm to estimate the number of mycobacterial proteins with the potential to be exported via this pathway.

Validating divergent ORF annotation of the Mycobacterium leprae genome through a full translation data set and peptide identification by tandem mass spectrometry

Mycobacterium leprae has undergone extensive degenerative evolution, with a large number of pseudogenes. It is also the organism with the greatest divergence between gene annotations from independent institutes. Therefore, M. leprae is a good model to verify the currently predicted coding sequence regions between different annotations, to identify new ones and to investigate the expression of pseudogenes. We submitted a total extract of the bacteria isolated from Armadillo to Gel‐LC‐MS/MS using a linear quadrupole ion trap‐Orbitrap mass spectrometer. Spectra were analyzed using the Leproma (1614 genes and 1133 pseudogenes) and TIGR (5446 genes) databases and a database containing the full genome translation. We identified a total of 1046 proteins, including five proteins encoded by previously predicted pseudogenes, which upon closer inspection appeared to be proper genes. Only 11 of the additional annotations by TIGR were verified. We also identified six tryptic peptides from five proteins from regions not considered to be coding sequences, in addition to peptides from two unannotated gene candidates that overlap with other genes. Our data show that the Leproma annotation of M. leprae is quite accurate, and there were no peptide observations corresponding to true pseudogenes, except for a new gene candidate, overlapping with an essential enolase on the complementary strand.