Project description:Prokaryotes, due to their moderate complexity, are particularly amenable to the comprehensive identification of the protein repertoire expressed under different conditions. We applied a generic strategy to identify a complete expressed prokaryotic proteome, which is based on the analysis of RNA and proteins extracted from matched samples. Saturated transcriptome profiling by RNA-seq provided an endpoint estimate of the protein-coding genes expressed under two conditions which mimic the interaction of Bartonella henselae with its mammalian host. Directed shotgun proteomics experiments were carried out on four subcellular fractions. By specifically targeting proteins which are short, basic, low abundant, and membrane localized, we could eliminate their initial underrepresentation compared to the estimated endpoint. A total of 1250 proteins were identified with an estimated false discovery rate below 1%. This represents 85% of all distinct annotated proteins and ?90% of the expressed protein-coding genes. Genes that were detected at the transcript but not protein level, were found to be highly enriched in several genomic islands. Furthermore, genes that lacked an ortholog and a functional annotation were not detected at the protein level; these may represent examples of overprediction in genome annotations. A dramatic membrane proteome reorganization was observed, including differential regulation of autotransporters, adhesins, and hemin binding proteins. Particularly noteworthy was the complete membrane proteome coverage, which included expression of all members of the VirB/D4 type IV secretion system, a key virulence factor.
Project description:Prokaryotes are, due to their moderate complexity, particularly amenable to the comprehensive identification of the protein repertoire expressed under different conditions. We applied a generic strategy to identify a complete expressed prokaryotic proteome, which is based on the analysis of RNA and proteins extracted from matched samples. Saturated transcriptome profiling by RNA-seq provided an endpoint estimate of the protein-coding genes expressed under two conditions which mimic the interaction of Bartonella henselae with its mammalian host. Directed shotgun proteomics experiments were carried out on four subcellular fractions. By specifically targeting proteins which are short, basic, low abundant and membrane localized, we could eliminate their initial under-representation compared to the estimated endpoint. A total of 1,250 proteins were identified with an estimated false discovery rate below 1%. This represents 85% of all distinct annotated proteins and around 90% of the expressed protein-coding genes. Genes, whose transcripts were detected, but not their corresponding protein products, were found highly enriched in several genomic islands. Additionally, genes that lacked an ortholog and a functional annotation were not detected at the protein level, and possibly include over-predicted genes in genome annotations. Furthermore, a dramatic membrane proteome re-organization was observed including differential regulation of autotransporters, adhesins and hemin binding proteins. Particularly noteworthy was the complete membrane proteome coverage which included expression of all members of the VirB/D4 type IV secretion system, a key virulence factor. Transcriptome and proteome analysis of B.henselae in two conditions and duplicates: uninduced and induced for host invasion.
Project description:Bacteria utilize a general stress response system to combat stresses from their surrounding environments. In alpha-proteobacteria, the general stress response uses an alternate sigma factor as the main regulator and incorporates it with a two-component system into a unique regulatory circuit. This system has been described in several alpha-proteobacterial species, including the pathogens Bartonella quintana and Brucella abortus. Most of the studies have focused on characterizing the PhyR anti-anti-sigma factor, the NepR anti-sigma factor, and the alternate sigma factor. However, not enough attention is directed toward studying the role of histidine kinases in the general stress response. Our study identifies the general stress response system in Bartonella henselae, where the gene synteny is conserved and both the PhyR and alternate sigma factor have similar sequence and domain structures with other alpha-proteobacteria. Our data showed that the general stress response genes are up-regulated under conditions that mimic the cat flea vector. Furthermore, we showed that both RpoE and PhyR positively regulate this system and that RpoE also affects transcription of genes encoding heme-binding proteins and the gene encoding the BadA adhesin. Finally, we identified a histidine kinase, annotated as BH13820 that can potentially phosphorylate PhyR.
Project description:Using a discovery proteomics approach, the expressed proteome of Bartonella henselae, a Gram-negative prokaryotic model organism was exhaustively studied under two conditions that mimic those encountered in different hosts. Using the analysis-driven experimentation (ADE) feedback-loop strategy, we were able to virtually eliminate the biases of commonly under-represented short, basic, and particularly lower abundant and membrane protein classes, all of which are experimentally tractable. Based on a very stringent FDR at the PSM level, we identified 85% of all distinct, annotated proteins and above 90% compared to the expressed protein-coding genes in the two conditions. Several lines of evidence indicated that this is very close to all proteins that can be identified by a discovery proteomics approach with current technology Our experimental strategy relied on four elements: First, we used a combination of sub-cellular fractionation (Cyt, TM, IM, OM) with additional biochemical fractionation regimens (gelfiltration, OGEpep, OGEprot, ProteoMiner) to reduce the overall sample complexity. Second, an exclusion list approach was applied, where each sample is measured twice in a mass spectrometer. Third, we relied on the ADE strategy to target typically under-represented areas of the proteome. Finally, we also used chymotrypsin as enzyme in addition to trypsin for all membrane-derived fractions. For computational analysis, we combined results from two database search engines (Mascot and MS-GF+).Mass spectra were searched against a protein sequence database containing 1488 NCBI RefSeq annotated B. henselae proteins (NC_005956.1), 3336 sheep proteins, a positive control (myc-gfp), as well as protein sequences of 256 common contaminants. Spectra were searched against this database using the target/decoy option either with Mascot (version 2.3.0, Matrix Science) or with MS-GF+ (MS-GFDB v7747, kindly provided by Dr. Sangtae Kim, UCSD, USA) using the following parameters: Carbamidomethylation was set as a fixed modification on all Cysteines, oxidation of Methionines, deamidation of Asparagines and Glutamines, as well as cyclization of N-terminal Glutamines were considered as optional modifications. Spectra were searched for a match to fully-tryptic and semi-tryptic peptides with up to two missed cleavage sites. Precursor ion mass tolerance was set to 5 ppm, fragment ion mass tolerance was set to 0.8 Da, and the automatic decoy search option was enabled. For Mascot, data were further post-processed with Percolator (Brosch et al. 2009). Additional RNA-seq data are at GEO under the accession: GSE44564.
Project description:Fructose bisphosphate aldolase (FBPA) enzymes have been found in a broad range of eukaryotic and prokaryotic organisms. FBPA catalyses the cleavage of fructose 1,6-bisphosphate into glyceraldehyde 3-phosphate and dihydroxyacetone phosphate. The SSGCID has reported several FBPA structures from pathogenic sources, including the bacterium Brucella melitensis and the protozoan Babesia bovis. Bioinformatic analysis of the Bartonella henselae genome revealed an FBPA homolog. The B. henselae FBPA enzyme was recombinantly expressed and purified for X-ray crystallographic studies. The purified enzyme crystallized in the apo form but failed to diffract; however, well diffracting crystals could be obtained by cocrystallization in the presence of the native substrate fructose 1,6-bisphosphate. A data set to 2.35 Å resolution was collected from a single crystal at 100 K. The crystal belonged to the orthorhombic space group P2(1)2(1)2(1), with unit-cell parameters a=72.39, b=127.71, c=157.63 Å. The structure was refined to a final free R factor of 22.2%. The structure shares the typical barrel tertiary structure and tetrameric quaternary structure reported for previous FBPA structures and exhibits the same Schiff base in the active site.
Project description:Systemic Bartonella spp. infections are being increasingly reported in association with complex medical presentations. Individuals with frequent arthropod exposures or animal contact appear to be at risk for acquiring long standing infections with Bartonella spp.This case report describes infections with Bartonella koehlerae and Bartonella henselae in a female veterinarian whose symptoms were predominantly rheumatologic in nature. Infection was confirmed by serology, polymerase chain reaction (PCR), enrichment blood culture, and DNA sequencing of amplified B koehlerae and B henselae DNA. Long-term medical management with antibiotics was required to achieve elimination of these infections and was accompanied by resolution of the patient's symptoms. Interestingly, the patient experienced substantial improvement in the acquired joint hypermobility mimicking Ehlers-Danlos Syndrome (EDS) type III.To facilitate early and directed medical interventions, systemic bartonellosis should potentially be considered as a differential diagnosis in patients with incalcitrant rheumatological symptoms and frequent arthropod exposures or extensive animal contact.
Project description:The rapid development of mass spectrometry (MS) technologies has solidified shotgun proteomics as the most powerful analytical platform for large-scale proteome interrogation. The ability to map and determine differential expression profiles of the entire proteome is the ultimate goal of shotgun proteomics. Label-free quantitation has proven to be a valid approach for discovery shotgun proteomics, especially when sample is limited. Label-free spectral count quantitation is an approach analogous to RNA sequencing whereby count data is used to determine differential expression. Here we show that statistical approaches developed to evaluate differential expression in RNA sequencing experiments can be applied to detect differential protein expression in label-free discovery proteomics. This approach, termed MultiSpec, utilizes open-source statistical platforms; namely edgeR, DESeq and baySeq, to statistically select protein candidates for further investigation. Furthermore, to remove bias associated with a single statistical approach a single ranked list of differentially expressed proteins is assembled by comparing edgeR and DESeq q-values directly with the false discovery rate (FDR) calculated by baySeq. This statistical approach is then extended when applied to spectral count data derived from multiple proteomic pipelines. The individual statistical results from multiple proteomic pipelines are integrated and cross-validated by means of collapsing protein groups.Spectral count data from shotgun proteomics experiments is semi-quantitative and semi-random, yet a robust way to estimate protein concentration. Tag-count approaches are routinely used to analyze RNA sequencing data sets. This approach, termed MultiSpec, utilizes multiple tag-count based statistical tests to determine differential protein expression from spectral counts. The statistical results from these tag-count approaches are combined in order to reach a final MultiSpec q-value to re-rank protein candidates. This re-ranking procedure is completed to remove bias associated with a single approach in order to better understand the true proteomic differences driving the biology in question. The MultiSpec approach can be extended to multiple proteomic pipelines. In such an instance, MultiSpec statistical results are integrated by collapsing protein groups across proteomic pipelines to provide a single ranked list of differentially expressed proteins. This integration mechanism is seamlessly integrated with the statistical analysis and provides the means to cross-validate protein inferences from multiple proteomic pipelines.
Project description:Ideally, shotgun proteomics would facilitate the identification of an entire proteome with 100% protein sequence coverage. In reality, the large dynamic range and complexity of cellular proteomes results in oversampling of abundant proteins, while peptides from low abundance proteins are undersampled or remain undetected. We tested the proteome equalization technology, ProteoMiner, in conjunction with Multidimensional Protein Identification Technology (MudPIT) to determine how the equalization of protein dynamic range could improve shotgun proteomics methods for the analysis of cellular proteomes. Our results suggest low abundance protein identifications were improved by two mechanisms: (1) depletion of high abundance proteins freed ion trap sampling space usually occupied by high abundance peptides and (2) enrichment of low abundance proteins increased the probability of sampling their corresponding more abundant peptides. Both mechanisms also contributed to dramatic increases in the quantity of peptides identified and the quality of MS/MS spectra acquired due to increases in precursor intensity of peptides from low abundance proteins. From our large data set of identified proteins, we categorized the dominant physicochemical factors that facilitate proteome equalization with a hexapeptide library. These results illustrate that equalization of the dynamic range of the cellular proteome is a promising methodology to improve low abundance protein identification confidence, reproducibility, and sequence coverage in shotgun proteomics experiments, opening a new avenue of research for improving proteome coverage.
Project description:The in-depth analysis of complex proteome samples requires fractionation of the sample into subsamples prior to LC-MS/MS in shotgun proteomics experiments. We have established a 3D workflow for shotgun proteomics that relies on protein separation by 1D PAGE, gel fractionation, trypsin digestion, and peptide separation by in-gel IEF, prior to RP-HPLC-MS/MS. Our results show that applying peptide IEF can significantly increase the number of proteins identified from PAGE subfractionation. This method delivers deeper proteome coverage and provides a large degree of flexibility in experimentally approaching highly complex mixtures by still relying on protein separation according to molecular weight in the first dimension.
Project description:Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Owing to the incorporation of risk-adapted therapy and the arrival of new directed agents, the cure rate and survival of patients with ALL have improved dramatically, get near to 90%. In Latin American countries, the mortality rates of ALL are high, for example in Colombia, during the last decade, ALL has been the most prevalent cancer among children between 0-14 years of age. In the face of this public health problem and coupled with the fact that the knowledge of the proteome of the child population is little, our investigation proposes the study of the plasma proteome of Colombian children diagnosed with B-cell ALL (B-ALL) to determine potential disease markers that could reflect processes altered by the presence of the disease or in response to it. A proteomic study by LC-MS/MS and quantification by label-free methods were performed in search of proteins differentially expressed between healthy children and those diagnosed with B-ALL. We quantified a total of 472 proteins in depleted blood plasma, and 25 of these proteins were differentially expressed (fold change >2, Bonferroni-adjusted P-values <0.05). Plasma Aggrecan core protein, alpha-2-HS-glycoprotein, coagulation factor XIII A chain and gelsolin protein were examined by ELISA assay and compared to shotgun proteomics results. Our data provide new information on the plasma proteome of Colombian children. Additionally, these proteins may also have certain potential as illness markers or as therapeutic targets in subsequent investigations.