David Fenyö

Sequence and Structural Convergence of Broad and Potent HIV Antibodies That Mimic CD4 Binding

Anti-HIV broadly neutralizing antibodies with similar specificities and modes of binding were found in multiple HIV-infected individuals. Passive transfer of broadly neutralizing HIV antibodies can prevent infection, which suggests that vaccines that elicit such antibodies would be protective. Thus far, however, few broadly neutralizing HIV antibodies that occur naturally have been characterized. To determine whether these antibodies are part of a larger group of related molecules, we cloned 576 new HIV antibodies from four unrelated individuals. All four individuals produced expanded clones of potent broadly neutralizing CD4-binding-site antibodies that mimic binding to CD4. Despite extensive hypermutation, the new antibodies shared a consensus sequence of 68 immunoglobulin H (IgH) chain amino acids and arise independently from two related IgH genes. Comparison of the crystal structure of one of the antibodies to the broadly neutralizing antibody VRC01 revealed conservation of the contacts to the HIV spike.

Proteogenomic characterization of human colon and rectal cancer

Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA ‘microsatellite instability/CpG island methylation phenotype’ transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology.

Proteogenomics connects somatic mutations to signalling in breast cancer

Summary Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. We describe quantitative mass spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers of which 77 provided high-quality data. Integrated analyses allowed insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. The 5q trans effects were interrogated against the Library of Integrated Network-based Cellular Signatures, thereby connecting CETN3 and SKP1 loss to elevated expression of EGFR, and SKP1 loss also to increased SRC. Global proteomic data confirmed a stromal-enriched group in addition to basal and luminal clusters and pathway analysis of the phosphoproteome identified a G Protein-coupled receptor cluster that was not readily identified at the mRNA level. Besides ERBB2, other amplicon-associated, highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

Four histone variants mark the boundaries of polycistronic transcription units in Trypanosoma brucei

Unusually for a eukaryote, genes transcribed by RNA polymerase II (pol II) in Trypanosoma brucei are arranged in polycistronic transcription units. With one exception, no pol II promoter motifs have been identified, and how transcription is initiated remains an enigma. T. brucei has four histone variants: H2AZ, H2BV, H3V, and H4V. Using chromatin immunoprecipitation (ChIP) and sequencing (ChIP-seq) to examine the genome-wide distribution of chromatin components, we show that histones H4K10ac, H2AZ, H2BV, and the bromodomain factor BDF3 are enriched up to 300-fold at probable pol II transcription start sites (TSSs). We also show that nucleosomes containing H2AZ and H2BV are less stable than canonical nucleosomes. Our analysis also identifies >60 unexpected TSS candidates and reveals the presence of long guanine runs at probable TSSs. Apparently unique to trypanosomes, additional histone variants H3V and H4V are enriched at probable pol II transcription termination sites. Our findings suggest that histone modifications and histone variants play crucial roles in transcription initiation and termination in trypanosomes and that destabilization of nucleosomes by histone variants is an evolutionarily ancient and general mechanism of transcription initiation, demonstrated in an organism in which general pol II transcription factors have been elusive.

RADARS, a bioinformatics solution that automates proteome mass spectral analysis, optimises protein identification, and archives data in a relational database

RADARS, a rapid, automated, data archiving and retrieval software system for high‐throughput proteomic mass spectral data processing and storage, is described. The majority of mass spectrometer data files are compatible with RADARS, for consistent processing. The system automatically takes unprocessed data files, identifies proteins via in silico database searching, then stores the processed data and search results in a relational database suitable for customized reporting. The system is robust, used in 24/7 operation, accessible to multiple users of an intranet through a web browser, may be monitored by Virtual Private Network, and is secure. RADARS is scalable for use on one or many computers, and is suited to multiple processor systems. It can incorporate any local database in FASTA format, and can search protein and DNA databases online. A key feature is a suite of visualisation tools (many available gratis), allowing facile manipulation of spectra, by hand annotation, reanalysis, and access to all procedures. We also described the use of Sonar MS/MS, a novel, rapid search engine requiring 40 MB RAM per process for searches against a genomic or EST database translated in all six reading frames. RADARS reduces the cost of analysis by its efficient algorithms: Sonar MS/MS can identifiy proteins without accurate knowledge of the parent ion mass and without protein tags. Statistical scoring methods provide close‐to‐expert accuracy and brings robust data analysis to the non‐expert user.

Integrated proteogenomic characterization of human high-grade serous ovarian cancer

To provide a detailed analysis of the molecular components and underlying mechanisms associated with ovarian cancer, we performed a comprehensive mass-spectrometry-based proteomic characterization of 174 ovarian tumors previously analyzed by The Cancer Genome Atlas (TCGA), of which 169 were high-grade serous carcinomas (HGSCs). Integrating our proteomic measurements with the genomic data yielded a number of insights into disease, such as how different copy-number alternations influence the proteome, the proteins associated with chromosomal instability, the sets of signaling pathways that diverse genome rearrangements converge on, and the ones most associated with short overall survival. Specific protein acetylations associated with homologous recombination deficiency suggest a potential means for stratifying patients for therapy. In addition to providing a valuable resource, these findings provide a view of how the somatic genome drives the cancer proteome and associations between protein and post-translational modification levels and clinical outcomes in HGSC. VIDEO ABSTRACT.

Ischemia in tumors induces early and sustained phosphorylation changes in stress kinase pathways but does not affect global protein levels

Protein abundance and phosphorylation convey important information about pathway activity and molecular pathophysiology in diseases including cancer, providing biological insight, informing drug and diagnostic development, and guiding therapeutic intervention. Analyzed tissues are usually collected without tight regulation or documentation of ischemic time. To evaluate the impact of ischemia, we collected human ovarian tumor and breast cancer xenograft tissue without vascular interruption and performed quantitative proteomics and phosphoproteomics after defined ischemic intervals. Although the global expressed proteome and most of the >25,000 quantified phosphosites were unchanged after 60 min, rapid phosphorylation changes were observed in up to 24% of the phosphoproteome, representing activation of critical cancer pathways related to stress response, transcriptional regulation, and cell death. Both pan-tumor and tissue-specific changes were observed. The demonstrated impact of pre-analytical tissue ischemia on tumor biology mandates caution in interpreting stress-pathway activation in such samples and motivates reexamination of collection protocols for phosphoprotein analysis.

Interlaboratory Study Characterizing a Yeast Performance Standard for Benchmarking LC-MS Platform Performance

Optimal performance of LC-MS/MS platforms is critical to generating high quality proteomics data. Although individual laboratories have developed quality control samples, there is no widely available performance standard of biological complexity (and associated reference data sets) for benchmarking of platform performance for analysis of complex biological proteomes across different laboratories in the community. Individual preparations of the yeast Saccharomyces cerevisiae proteome have been used extensively by laboratories in the proteomics community to characterize LC-MS platform performance. The yeast proteome is uniquely attractive as a performance standard because it is the most extensively characterized complex biological proteome and the only one associated with several large scale studies estimating the abundance of all detectable proteins. In this study, we describe a standard operating protocol for large scale production of the yeast performance standard and offer aliquots to the community through the National Institute of Standards and Technology where the yeast proteome is under development as a certified reference material to meet the long term needs of the community. Using a series of metrics that characterize LC-MS performance, we provide a reference data set demonstrating typical performance of commonly used ion trap instrument platforms in expert laboratories; the results provide a basis for laboratories to benchmark their own performance, to improve upon current methods, and to evaluate new technologies. Additionally, we demonstrate how the yeast reference, spiked with human proteins, can be used to benchmark the power of proteomics platforms for detection of differentially expressed proteins at different levels of concentration in a complex matrix, thereby providing a metric to evaluate and minimize preanalytical and analytical variation in comparative proteomics experiments.

Phosphotyrosine Signaling Networks in Epidermal Growth Factor Receptor Overexpressing Squamous Carcinoma Cells

Overexpression and enhanced activation of the epidermal growth factor (EGF) receptor are frequent events in human cancers that correlate with poor prognosis. Anti-phosphotyrosine and anti-EGFr affinity chromatography, isotope-coded μLC-MS/MS, and immunoblot methods were combined to describe and measure signaling networks associated with EGF receptor activation and pharmacological inhibition. The squamous carcinoma cell line HN5, which overexpresses EGF receptor and displays sustained receptor kinase activation, was used as a model system, where pharmacological inhibition of EGF receptor kinase by erlotinib markedly reduced auto and substrate phosphorylation, Src family phosphorylation at EGFR Y845, while increasing total EGF receptor protein. Diverse sets of known and poorly described functional protein classes were unequivocally identified by affinity selection, comprising either proteins tyrosine phosphorylated or complexed therewith, predominantly through EGF receptor and Src family kinases, principally 1) immediate EGF receptor signaling complexes (18%); 2) complexes involved in adhesion and cell-cell contacts (34%); and 3) receptor internalization and degradation signals. Novel and known phosphorylation sites could be located despite the complexity of the peptide mixtures. In addition to interactions with multiple signaling adaptors Grb2, SHC, SCK, and NSP2, EGF receptors in HN5 cells were shown to form direct or indirect physical interactions with additional kinases including ACK1, focal adhesion kinase (FAK), Pyk2, Yes, EphA2, and EphB4. Pharmacological inhibition of EGF receptor kinase activity by erlotinib resulted in reduced phosphorylation of downstream signaling, for example through Cbl/Cbl-B, phospholipase Cγ (PLCγ), Erk1/2, PI-3 kinase, and STAT3/5. Focal adhesion proteins, FAK, Pyk2, paxillin, ARF/GIT1, and plakophillin were down-regulated by transient EGF stimulation suggesting a complex balance between growth factor induced kinase and phosphatase activities in the control of cell adhesion complexes. The functional interactions between IGF-1 receptor, lysophosphatidic acid (LPA) signaling, and EGF receptor were observed, both direct and/or indirectly on phospho-Akt, phospho-Erk1/2, and phospho-ribosomal S6.

Identifying the proteome: software tools

The interest in proteomics has recently increased dramatically and proteomic methods are now applied to many problems in cell biology. The method of choice in proteomics for identifying and characterizing proteins is mass spectrometry combined with database searching. Software tools have been improved to increase the sensitivity of protein identification and methods for evaluating the search results have been incorporated