Expansion of the BioCyc collection of pathway/genome databases to 160 genomes

The BioCyc database collection is a set of 160 pathway/genome databases (PGDBs) for most eukaryotic and prokaryotic species whose genomes have been completely sequenced to date. Each PGDB in the BioCyc collection describes the genome and predicted metabolic network of a single organism, inferred from the MetaCyc database, which is a reference source on metabolic pathways from multiple organisms. In addition, each bacterial PGDB includes predicted operons for the corresponding species. The BioCyc collection provides a unique resource for computational systems biology, namely global and comparative analyses of genomes and metabolic networks, and a supplement to the BioCyc resource of curated PGDBs. The Omics viewer available through the BioCyc website allows scientists to visualize combinations of gene expression, proteomics and metabolomics data on the metabolic maps of these organisms. This paper discusses the computational methodology by which the BioCyc collection has been expanded, and presents an aggregate analysis of the collection that includes the range of number of pathways present in these organisms, and the most frequently observed pathways. We seek scientists to adopt and curate individual PGDBs within the BioCyc collection. Only by harnessing the expertise of many scientists we can hope to produce biological databases, which accurately reflect the depth and breadth of knowledge that the biomedical research community is producing

The Vaginal Microbiome: Disease, Genetics and the Environment

The vagina is an interactive interface between the host and the environment. Its surface is covered by a protective epithelium colonized by bacteria and other microorganisms. The ectocervix is nonsterile, whereas the endocervix and the upper genital tract are assumed to be sterile in healthy women. Therefore, the cervix serves a pivotal role as a gatekeeper to protect the upper genital tract from microbial invasion and subsequent reproductive pathology. Microorganisms that cross this barrier can cause preterm labor, pelvic inflammatory disease, and other gynecologic and reproductive disorders. Homeostasis of the microbiome in the vagina and ectocervix plays a paramount role in reproductive health. Depending on its composition, the microbiome may protect the vagina from infectious or non-infectious diseases, or it may enhance its susceptibility to them. Because of the nature of this organ, and the fact that it is continuously colonized by bacteria from birth to death, it is virtually certain that this rich environment evolved in concert with its microbial flora. Specific interactions dictated by the genetics of both the host and microbes are likely responsible for maintaining both the environment and the microbiome. However, the genetic basis of these interactions in both the host and the bacterial colonizers is currently unknown. _Lactobacillus_ species are associated with vaginal health, but the role of these species in the maintenance of health is not yet well defined. Similarly, other species, including those representing minor components of the overall flora, undoubtedly influence the ability of potential pathogens to thrive and cause disease. Gross alterations in the vaginal microbiome are frequently observed in women with bacterial vaginosis, but the exact etiology of this disorder is still unknown. There are also implications for vaginal flora in non-infectious conditions such as pregnancy, pre-term labor and birth, and possibly fertility and other aspects of women’s health. Conversely, the role of environmental factors in the maintenance of a healthy vaginal microbiome is largely unknown. To explore these issues, we have proposed to address the following questions:

*1.	Do the genes of the host contribute to the composition of the vaginal microbiome?* We hypothesize that genes of both host and bacteria have important impacts on the vaginal microbiome. We are addressing this question by examining the vaginal microbiomes of mono- and dizygotic twin pairs selected from the over 170,000 twin pairs in the Mid-Atlantic Twin Registry (MATR). Subsequent studies, beyond the scope of the current project, may investigate which host genes impact the microbial flora and how they do so.
*2.	What changes in the microbiome are associated with common non-infectious pathological states of the host?* We hypothesize that altered physiological (e.g., pregnancy) and pathologic (e.g., immune suppression) conditions, or environmental exposures (e.g., antibiotics) predictably alter the vaginal microbiome. Conversely, certain vaginal microbiome characteristics are thought to contribute to a woman’s risk for outcomes such as preterm delivery. We are addressing this question by recruiting study participants from the ~40,000 annual clinical visits to women’s clinics of the VCU Health System.
*3.	What changes in the vaginal microbiome are associated with relevant infectious diseases and conditions?* We hypothesize that susceptibility to infectious disease (e.g. HPV, _Chlamydia_ infection, vaginitis, vaginosis, etc.) is impacted by the vaginal microbiome. In turn, these infectious conditions clearly can affect the ability of other bacteria to colonize and cause pathology. Again, we are exploring these issues by recruiting participants from visitors to women’s clinics in the VCU Health System.

Three kinds of sequence data are generated in this project: i) rDNA sequences from vaginal microbes; ii) whole metagenome shotgun sequences from vaginal samples; and iii) whole genome shotgun sequences of bacterial clones selected from vaginal samples. The study includes samples from three vaginal sites: mid-vaginal, cervical, and introital. The data sets also include buccal and perianal samples from all twin participants. Samples from these additional sites are used to test the hypothesis of a per continuum spread of bacteria in relation to vaginal health. An extended set of clinical metadata associated with these sequences are deposited with dbGAP. We have currently collected over 4,400 samples from ~100 twins and over 450 clinical participants. We have analyzed and deposited data for 480 rDNA samples, eight whole metagenome shotgun samples, and over 50 complete bacterial genomes. These data are available to accredited investigators according to NIH and Human Microbiome Project (HMP) guidelines. The bacterial clones are deposited in the Biodefense and Emerging Infections Research Resources Repository ("http://www.beiresources.org/":http://www.beiresources.org/). 

In addition to the extensive sequence data obtained in this study, we are collecting metadata associated with each of the study participants. Thus, participants are asked to complete an extensive health history questionnaire at the time samples are collected. Selected clinical data associated with the visit are also obtained, and relevant information is collected from the medical records when available. This data is maintained securely in a HIPAA-compliant data system as required by VCU’s Institutional Review Board (IRB). The preponderance of these data (i.e., that judged appropriate by NIH staff and VCU’s IRB are deposited at dbGAP ("http://www.ncbi.nlm.nih.gov/gap":http://www.ncbi.nlm.nih.gov/gap). Selected fields of this data have been identified by NIH staff as ‘too sensitive’ and are not available in dbGAP. Individuals requiring access to these data fields are asked to contact the PI of this project or NIH Program Staff. 
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MACiE: a database of enzyme reaction mechanisms.

SUMMARY: MACiE (mechanism, annotation and classification in enzymes) is a publicly available web-based database, held in CMLReact (an XML application), that aims to help our understanding of the evolution of enzyme catalytic mechanisms and also to create a classification system which reflects the actual chemical mechanism (catalytic steps) of an enzyme reaction, not only the overall reaction. AVAILABILITY: http://www-mitchell.ch.cam.ac.uk/macie/.EPSRC (G.L.H. and J.B.O.M.), the BBSRC (G.J.B. and J.M.T.—CASE studentship in association with Roche Products Ltd; N.M.O.B. and J.B.O.M.—grant BB/C51320X/1), the Chilean Government’s Ministerio de Planificacio´n y Cooperacio´n and Cambridge Overseas Trust (D.E.A.) for funding and Unilever for supporting the Centre for Molecular Science Informatics.application note restricted to 2 printed pages web site: http://www-mitchell.ch.cam.ac.uk/macie

Spectral analysis of gene expression profiles using gene networks

Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) and their biological significance is often difficult. Currently, the standard approach is to map a posteriori the results onto gene networks to elucidate the functions perturbed at the level of pathways. However, integrating a priori knowledge of the gene networks could help in the statistical analysis of gene expression data and in their biological interpretation. Here we propose a method to integrate a priori the knowledge of a gene network in the analysis of gene expression data. The approach is based on the spectral decomposition of gene expression profiles with respect to the eigenfunctions of the graph, resulting in an attenuation of the high-frequency components of the expression profiles with respect to the topology of the graph. We show how to derive unsupervised and supervised classification algorithms of expression profiles, resulting in classifiers with biological relevance. We applied the method to the analysis of a set of expression profiles from irradiated and non-irradiated yeast strains. It performed at least as well as the usual classification but provides much more biologically relevant results and allows a direct biological interpretation

Algebraic and Topological Indices of Molecular Pathway Networks in Human Cancers

Protein-protein interaction networks associated with diseases have gained prominence as an area of research. We investigate algebraic and topological indices for protein-protein interaction networks of 11 human cancers derived from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. We find a strong correlation between relative automorphism group sizes and topological network complexities on the one hand and five year survival probabilities on the other hand. Moreover, we identify several protein families (e.g. PIK, ITG, AKT families) that are repeated motifs in many of the cancer pathways. Interestingly, these sources of symmetry are often central rather than peripheral. Our results can aide in identification of promising targets for anti-cancer drugs. Beyond that, we provide a unifying framework to study protein-protein interaction networks of families of related diseases (e.g. neurodegenerative diseases, viral diseases, substance abuse disorders).Comment: 15 pages, 4 figure

Post-transcriptional knowledge in pathway analysis increases the accuracy of phenotypes classification

Motivation: Prediction of phenotypes from high-dimensional data is a crucial task in precision biology and medicine. Many technologies employ genomic biomarkers to characterize phenotypes. However, such elements are not sufficient to explain the underlying biology. To improve this, pathway analysis techniques have been proposed. Nevertheless, such methods have shown lack of accuracy in phenotypes classification. Results: Here we propose a novel methodology called MITHrIL (Mirna enrIched paTHway Impact anaLysis) for the analysis of signaling pathways, which has built on top of the work of Tarca et al., 2009. MITHrIL extends pathways by adding missing regulatory elements, such as microRNAs, and their interactions with genes. The method takes as input the expression values of genes and/or microRNAs and returns a list of pathways sorted according to their deregulation degree, together with the corresponding statistical significance (p-values). Our analysis shows that MITHrIL outperforms its competitors even in the worst case. In addition, our method is able to correctly classify sets of tumor samples drawn from TCGA. Availability: MITHrIL is freely available at the following URL: http://alpha.dmi.unict.it/mithril

Genome sequences of 14 Firmicutes strains isolated from the human vagina

Research on vaginal infections is currently limited by a lack of available fully sequenced bacterial reference strains. Here, we present strains (now available through BEI Resources) and genome sequences for a set of 14 vaginal isolates from the phylum Firmicutes. These genome sequences provide a valuable resource for future research in understanding the role of Gram-positive bacteria in vaginal health and disease