Comparative Analysis of the Endogenous Peptidomes Displayed by HLA-B*27 and Mamu-B*08: Two MHC Class I Alleles Associated with Elite Control of HIV/SIV Infection

Indian rhesus macaques are arguably the most reliable animal models in AIDS research. In this species the MHC class I allele Mamu-B*08, among others, is associated with elite control of SIV replication. A similar scenario is observed in humans where the expression of HLA-B*27 or HLA-B*57 has been linked to slow or no progression to AIDS after HIV infection. Despite having large differences in their primary structure, it has been reported that HLA-B*27 and Mamu-B*08 display peptides with sequence similarity. To fine-map the Mamu-B*08 binding motif and assess its similarities with that of HLA-B*27, we affinity purified the peptidomes bound to these MHC class I molecules and analyzed them by LC-MS, identifying several thousands of endogenous ligands. Sequence analysis of both sets of peptides revealed a degree of similarity in their binding motifs, especially at peptide position 2 (P2), where arginine was present in the vast majority of ligands of both allotypes. In addition, several differences emerged from this analysis: (i) ligands displayed by Mamu-B*08 tended to be shorter and to have lower molecular weight, (ii) Mamu-B*08 showed a higher preference for glutamine at P2 as a suboptimal binding motif, and (iii) the second major anchor position, found at PΩ, was much more restrictive in Mamu-B*08. In this regard, HLA-B*27 bound efficiently peptides with aliphatic, aromatic (including tyrosine), and basic C-terminal residues while Mamu-B*08 preferred peptides with leucine and phenylalanine in this position. Finally, in silico estimations of binding efficiency and competitive binding assays to Mamu-B*08 of several selected peptides revealed a good correlation between the characterized anchor motif and binding affinity. These results deepen our understanding of the molecular basis of the presentation of peptides by Mamu-B*08 and can contribute to the detection of novel SIV epitopes restricted by this allotype

New Copper Resistance Determinants in the Extremophile <i>Acidithiobacillus ferrooxidans</i>: A Quantitative Proteomic Analysis

<i>Acidithiobacillus ferrooxidans</i> is an extremophilic bacterium used in biomining processes to recover metals. The presence in <i>A. ferrooxidans</i> ATCC 23270 of canonical copper resistance determinants does not entirely explain the extremely high copper concentrations this microorganism is able to stand, suggesting the existence of other efficient copper resistance mechanisms. New possible copper resistance determinants were searched by using 2D-PAGE, real time PCR (qRT-PCR) and quantitative proteomics with isotope-coded protein labeling (ICPL). A total of 594 proteins were identified of which 120 had altered levels in cells grown in the presence of copper. Of this group of proteins, 76 were up-regulated and 44 down-regulated. The up-regulation of RND-type Cus systems and different RND-type efflux pumps was observed in response to copper, suggesting that these proteins may be involved in copper resistance. An overexpression of most of the genes involved in histidine synthesis and several of those annotated as encoding for cysteine production was observed in the presence of copper, suggesting a possible direct role for these metal-binding amino acids in detoxification. Furthermore, the up-regulation of putative periplasmic disulfide isomerases was also seen in the presence of copper, suggesting that they restore copper-damaged disulfide bonds to allow cell survival. Finally, the down-regulation of the major outer membrane porin and some ionic transporters was seen in <i>A</i>. <i>ferrooxidans</i> grown in the presence of copper, indicating a general decrease in the influx of the metal and other cations into the cell. Thus, <i>A</i>. <i>ferrooxidans</i> most likely uses additional copper resistance strategies in which cell envelope proteins are key components. This knowledge will not only help to understand the mechanism of copper resistance in this extreme acidophile but may help also to select the best fit members of the biomining community to attain more efficient industrial metal leaching processes

Proteogenomics Dashboard for the Human Proteome Project

<i>dasHPPboard</i> is a novel proteomics-based dashboard that collects and reports the experiments produced by the Spanish Human Proteome Project consortium (SpHPP) and aims to help HPP to map the entire human proteome. We have followed the strategy of analog genomics projects like the Encyclopedia of DNA Elements (ENCODE), which provides a vast amount of data on human cell lines experiments. The dashboard includes results of shotgun and selected reaction monitoring proteomics experiments, post-translational modifications information, as well as proteogenomics studies. We have also processed the transcriptomics data from the ENCODE and Human Body Map (HBM) projects for the identification of specific gene expression patterns in different cell lines and tissues, taking special interest in those genes having little proteomic evidence available (missing proteins). Peptide databases have been built using single nucleotide variants and novel junctions derived from RNA-Seq data that can be used in search engines for sample-specific protein identifications on the same cell lines or tissues. The <i>dasHPPboard</i> has been designed as a tool that can be used to share and visualize a combination of proteomic and transcriptomic data, providing at the same time easy access to resources for proteogenomics analyses. The <i>dasHPPboard</i> can be freely accessed at: http://sphppdashboard.cnb.csic.es

PACOM: A Versatile Tool for Integrating, Filtering, Visualizing, and Comparing Multiple Large Mass Spectrometry Proteomics Data Sets

Mass-spectrometry-based proteomics has evolved into a high-throughput technology in which numerous large-scale data sets are generated from diverse analytical platforms. Furthermore, several scientific journals and funding agencies have emphasized the storage of proteomics data in public repositories to facilitate its evaluation, inspection, and reanalysis. As a consequence, public proteomics data repositories are growing rapidly. However, tools are needed to integrate multiple proteomics data sets to compare different experimental features or to perform quality control analysis. Here, we present a new Java stand-alone tool, Proteomics Assay COMparator (PACOM), that is able to import, combine, and simultaneously compare numerous proteomics experiments to check the integrity of the proteomic data as well as verify data quality. With PACOM, the user can detect source of errors that may have been introduced in any step of a proteomics workflow and that influence the final results. Data sets can be easily compared and integrated, and data quality and reproducibility can be visually assessed through a rich set of graphical representations of proteomics data features as well as a wide variety of data filters. Its flexibility and easy-to-use interface make PACOM a unique tool for daily use in a proteomics laboratory. PACOM is available at https://github.com/smdb21/pacom

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study