Mining co-regulated gene profiles for the detection of functional associations in gene expression data

Motivation: Association pattern discovery (APD) methods have been successfully applied to gene expression data. They find groups of co-regulated genes in which the genes are either up- or down-regulated throughout the identified conditions. These methods, however, fail to identify similarly expressed genes whose expressions change between up- and down-regulation from one condition to another. In order to discover these hidden patterns, we propose the concept of mining co-regulated gene profiles. Co-regulated gene profiles contain two gene sets such that genes within the same set behave identically (up or down) while genes from different sets display contrary behavior. To reduce and group the large number of similar resulting patterns, we propose a new similarity measure that can be applied together with hierarchical clustering methods. Results: We tested our proposed method on two well-known yeast microarray data sets. Our implementation mined the data effectively and discovered patterns of co-regulated genes that are hidden to traditional APD methods. The high content of biologically relevant information in these patterns is demonstrated by the significant enrichment of co-regulated genes with similar functions. Our experimental results show that the Mining Attribute Profile (MAP) method is an efficient tool for the analysis of gene expression data and competitive with bi-clustering techniques. Contact: [email protected] Supplementary information: Supplementary data and an executable demo program of the MAP implementation are freely available at http://www.fgcz.ch/publications/ma

Sorbitol dehydrogenase overexpression and other aspects of dysregulated protein expression in human precancerous colorectal neoplasms: a quantitative proteomics study

Colorectal adenomas are cancer precursor lesions of the large bowel. A multitude of genomic and epigenomic changes have been documented in these preinvasive lesions, but their impact on the protein effectors of biological function has not been comprehensively explored. Using shotgun quantitative MS, we exhaustively investigated the proteome of 30 colorectal adenomas and paired samples of normal mucosa. Total protein extracts were prepared from these tissues (prospectively collected during colonoscopy) and from normal (HCEC) and cancerous (SW480, SW620, Caco2, HT29, CX1) colon epithelial cell lines. Peptides were labeled with isobaric tags (iTRAQ 8-plex), separated via OFFGEL electrophoresis, and analyzed by means of LC-MS/MS. Nonredundant protein families (4325 in tissues, 2017 in cell lines) were identified and quantified. Principal component analysis of the results clearly distinguished adenomas from normal mucosal samples and cancer cell lines from HCEC cells. Two hundred and twelve proteins displayed significant adenoma-related expression changes (q-value < 0.02, mean fold change versus normal mucosa ±1.4), which correlated (r = 0.74) with similar changes previously identified by our group at the transcriptome level. Fifty-one (∼25%) proteins displayed directionally similar expression changes in colorectal cancer cells (versus HCEC cells) and were therefore attributed to the epithelial component of adenomas. Although benign, adenomas already exhibited cancer-associated proteomic changes: 69 (91%) of the 76 protein up-regulations identified in these lesions have already been reported in cancers. One of the most striking changes involved sorbitol dehydrogenase, a key enzyme in the polyol pathway. Validation studies revealed dramatically increased sorbitol dehydrogenase concentrations and activity in adenomas and cancer cell lines, along with important changes in the expression of other enzymes in the same (AKR1B1) and related (KHK) pathways. Dysregulated polyol metabolism might represent a novel facet of metabolome remodeling associated with tumorigenesis

Pathogens and host immunity in the ancient human oral cavity.

Calcified dental plaque (dental calculus) preserves for millennia and entraps biomolecules from all domains of life and viruses. We report the first, to our knowledge, high-resolution taxonomic and protein functional characterization of the ancient oral microbiome and demonstrate that the oral cavity has long served as a reservoir for bacteria implicated in both local and systemic disease. We characterize (i) the ancient oral microbiome in a diseased state, (ii) 40 opportunistic pathogens, (iii) ancient human-associated putative antibiotic resistance genes, (iv) a genome reconstruction of the periodontal pathogen Tannerella forsythia, (v) 239 bacterial and 43 human proteins, allowing confirmation of a long-term association between host immune factors, 'red complex' pathogens and periodontal disease, and (vi) DNA sequences matching dietary sources. Directly datable and nearly ubiquitous, dental calculus permits the simultaneous investigation of pathogen activity, host immunity and diet, thereby extending direct investigation of common diseases into the human evolutionary past

FCC – An automated rule-based processing tool for life science data

BACKGROUND: Data processing in the bioinformatics field often involves the handling of diverse software programs in one workflow. The field is lacking a set of standards for file formats so that files have to be processed in different ways in order to make them compatible to different analysis programs. The problem is that mass spectrometry vendors at most provide only closed-sourceWindows libraries to programmatically access their proprietary binary formats. This prohibits the creation of an efficient and unified tool that fits all processing needs of the users. Therefore, researchers are spending a significant amount of time using GUI-based conversion and processing programs. Besides the time needed for manual usage, such programs also can show long running times for processing, because most of them make use of only a single CPU. In particular, algorithms to enhance data quality, e.g. peak picking or deconvolution of spectra, add waiting time for the users. RESULTS: To automate these processing tasks and let them run continuously without user interaction, we developed the FGCZ Converter Control (FCC) at the Functional Genomics Center Zurich (FGCZ) core facility. The FCC is a rule-based system for automated file processing that reduces the operation of diverse programs to a single configuration task. Using filtering rules for raw data files, the parameters for all tasks can be custom-tailored to the needs of every single researcher and processing can run automatically and efficiently on any number of servers in parallel using all available CPU resources. CONCLUSIONS: FCC has been used intensively at FGCZ for processing more than hundred thousand mass spectrometry raw files so far. Since we know that many other research facilities have similar problems, we would like to report on our tool and the accompanying ideas for an efficient set-up for potential reuse

The extracellular proteome of two Bifidobacterium species reveals different adaptation strategies to low iron conditions

Background: Bifidobacteria are among the first anaerobic bacteria colonizing the gut. Bifidobacteria require iron for growth and their iron-sequestration mechanisms are important for their fitness and possibly inhibit enteropathogens. Here we used combined genomic and proteomic analyses to characterize adaptations to low iron conditions of B. kashiwanohense PV20-2 and B. pseudolongum PV8-2, 2 strains isolated from the feces of iron-deficient African infants and selected for their high iron-sequestering ability. Results: Analyses of the genome contents revealed evolutionary adaptation to low iron conditions. A ferric and a ferrous iron operon encoding binding proteins and transporters were found in both strains. Remarkably, the ferric iron operon of B. pseudolongum PV8-2 is not found in other B. pseudolongum strains and likely acquired via horizontal gene transfer. The genome B. kashiwanohense PV20-2 harbors a unique region encoding genes putatively involved in siderophore production. Additionally, the secretomes of the two strains grown under low-iron conditions were analyzed using a combined genomic-proteomic approach. A ferric iron transporter was found in the secretome of B. pseudolongum PV8-2, while ferrous binding proteins were detected in the secretome of B. kashiwanohense PV20-2, suggesting different strategies to take up iron in the strains. In addition, proteins such as elongation factors, a glyceraldehyde-3-phosphate dehydrogenase, and the stress proteins GroEL and DnaK were identified in both secretomes. These proteins have been previously associated with adhesion of lactobacilli to epithelial cells. Conclusion: Analyses of the genome and secretome of B. kashiwanohense PV20-2 and B. pseudolongum PV8-2 revealed different adaptations to low iron conditions and identified extracellular proteins for iron transport. The identified extracellular proteins might be involved in competition for iron in the gastrointestinal tract

Optimization of LTQ-Orbitrap mass spectrometer parameters for the identification of ADP-ribosylation sites

ADP-ribosylation of proteins alters their function or provides a scaffold for the recruitment of other proteins, thereby regulating several important cellular processes. Mono- or poly-ADP-ribosylation is catalyzed by different ADP-ribosyltransferases (ARTs) that have different subcellular localizations and modify different amino acid acceptor sites. However, our knowledge of ADP-ribosylated proteins and their acceptor amino acids is still limited due to the lack of suitable mass spectrometry (MS) tools. Here, we describe an MS approach for the detection of ADP-ribosylated peptides and identification of the ADP-ribose acceptor sites, combining higher-energy collisional dissociation (HCD) and electron-transfer dissociation (ETD) on an LTQ-Orbitrap mass spectrometer. The presence of diagnostic ions of ADP-ribose in the HCD spectra allowed us to detect putative ADP-ribosylated peptides to target in a second LC-MS/MS analysis. The combination of HCD with ETD fragmentation gave a more comprehensive coverage of ADP-ribosylation sites than that with HCD alone. We successfully identified different ADP-ribose acceptor sites on several in vitro modified proteins. The combination of optimized HCD and ETD methods may be applied to complex samples, allowing comprehensive identification of ADP-ribosylation acceptor sites

Mining co-regulated gene profiles for the detection of functional associations in gene expression data

ISSN:1367-4803ISSN:1460-205

The extracellular proteome of two Bifidobacterium species reveals different adaptation strategies to low iron conditions

Abstract Background Bifidobacteria are among the first anaerobic bacteria colonizing the gut. Bifidobacteria require iron for growth and their iron-sequestration mechanisms are important for their fitness and possibly inhibit enteropathogens. Here we used combined genomic and proteomic analyses to characterize adaptations to low iron conditions of B. kashiwanohense PV20-2 and B. pseudolongum PV8-2, 2 strains isolated from the feces of iron-deficient African infants and selected for their high iron-sequestering ability. Results Analyses of the genome contents revealed evolutionary adaptation to low iron conditions. A ferric and a ferrous iron operon encoding binding proteins and transporters were found in both strains. Remarkably, the ferric iron operon of B. pseudolongum PV8-2 is not found in other B. pseudolongum strains and likely acquired via horizontal gene transfer. The genome B. kashiwanohense PV20-2 harbors a unique region encoding genes putatively involved in siderophore production. Additionally, the secretomes of the two strains grown under low-iron conditions were analyzed using a combined genomic-proteomic approach. A ferric iron transporter was found in the secretome of B. pseudolongum PV8-2, while ferrous binding proteins were detected in the secretome of B. kashiwanohense PV20-2, suggesting different strategies to take up iron in the strains. In addition, proteins such as elongation factors, a glyceraldehyde-3-phosphate dehydrogenase, and the stress proteins GroEL and DnaK were identified in both secretomes. These proteins have been previously associated with adhesion of lactobacilli to epithelial cells. Conclusion Analyses of the genome and secretome of B. kashiwanohense PV20-2 and B. pseudolongum PV8-2 revealed different adaptations to low iron conditions and identified extracellular proteins for iron transport. The identified extracellular proteins might be involved in competition for iron in the gastrointestinal tract