METABOLIC MODELING AND OMICS-INTEGRATIVE ANALYSIS OF SINGLE AND MULTI-ORGANISM SYSTEMS: DISCOVERY AND REDESIGN

Computations and modeling have emerged as indispensable tools that drive the process of understanding, discovery, and redesign of biological systems. With the accelerating pace of genome sequencing and annotation information generation, the development of computational pipelines for the rapid reconstruction of high-quality genome-scale metabolic networks has received significant attention. These models provide a rich tapestry for computational tools to quantitatively assess the metabolic phenotypes for various systems-level studies and to develop engineering interventions at the DNA, RNA, or enzymatic level by careful tuning in the biophysical modeling frameworks. in silico genome-scale metabolic modeling algorithms based on the concept of optimization, along with the incorporation of multi-level omics information, provides a diverse array of toolboxes for new discovery in the metabolism of living organisms (which includes single-cell microbes, plants, animals, and microbial ecosystems) and allows for the reprogramming of metabolism for desired output(s). Throughout my doctoral research, I used genome-scale metabolic models and omics-integrative analysis tools to study how microbes, plants, animal, and microbial ecosystems respond or adapt to diverse environmental cues, and how to leverage the knowledge gleaned from that to answer important biological questions. Each chapter in this dissertation will provide a detailed description of the methodology, results, and conclusions from one specific research project. The research works presented in this dissertation represent important foundational advance in Systems Biology and are crucial for sustainable development in food, pharmaceuticals and bioproduction of the future. Advisor: Rajib Sah

Reference genome and comparative genome analysis for the WHO reference strain for Mycobacterium bovis BCG Danish, the present tuberculosis vaccine

Background: Mycobacterium bovis bacillus Calmette-Guerin (M. bovis BCG) is the only vaccine available against tuberculosis (TB). In an effort to standardize the vaccine production, three substrains, i.e. BCG Danish 1331, Tokyo 172-1 and Russia BCG-1 were established as the WHO reference strains. Both for BCG Tokyo 172-1 as Russia BCG-1, reference genomes exist, not for BCG Danish. In this study, we set out to determine the completely assembled genome sequence for BCG Danish and to establish a workflow for genome characterization of engineering-derived vaccine candidate strains.ResultsBy combining second (Illumina) and third (PacBio) generation sequencing in an integrated genome analysis workflow for BCG, we could construct the completely assembled genome sequence of BCG Danish 1331 (07/270) (and an engineered derivative that is studied as an improved vaccine candidate, a SapM KO), including the resolution of the analytically challenging long duplication regions. We report the presence of a DU1-like duplication in BCG Danish 1331, while this tandem duplication was previously thought to be exclusively restricted to BCG Pasteur. Furthermore, comparative genome analyses of publicly available data for BCG substrains showed the absence of a DU1 in certain BCG Pasteur substrains and the presence of a DU1-like duplication in some BCG China substrains. By integrating publicly available data, we provide an update to the genome features of the commonly used BCG strains. Conclusions: We demonstrate how this analysis workflow enables the resolution of genome duplications and of the genome of engineered derivatives of the BCG Danish vaccine strain. The BCG Danish WHO reference genome will serve as a reference for future engineered strains and the established workflow can be used to enhance BCG vaccine standardization

Improving interoperability between microbial information and sequence databases

BACKGROUND: Biological resources are essential tools for biomedical research. Their availability is promoted through on-line catalogues. Common Access to Biological Resources and Information (CABRI) is a service for distribution of biological resources and related data collected by 28 European culture collections. Linking this information to bioinformatics databanks can make the collections' holdings more visible after a search in molecular biology databanks and vice-versa. Identification of links to sequence databases can be useful, but annotation and indexing problems, together with compilation errors, immediately arise. In this paper, we present our efforts for the identification of cross-references between CABRI catalogues and the EMBL Data Library and related results. RESULTS: An SRS site with both EMBL and CABRI catalogues has been set up. Ad-hoc changes in indexing scripts allowed to achieve homogeneous index keys and SRS link features have been used to identify links between databases. After manual checking and comparison with an alternative procedure, about 67,500 valid cross-references were identified, added to the EMBL Data Library and are now distributed with it. HTML links can be established from EMBL to CABRI network service. Procedures can be executed whenever needed. CONCLUSION: Links between EMBL and CABRI catalogues constitute an improved access to micro-organisms of certified quality and can produce positive effects on biomedical research. Further links between CABRI catalogues and other bioinformatics databases can now easily be defined by using these cross-references. Linking genetic information onto natural resources information may stand model for the integration of other databases containing empirical data on these materials

Updates in metabolomics tools and resources: 2014-2015

Data processing and interpretation represent the most challenging and time-consuming steps in high-throughput metabolomic experiments, regardless of the analytical platforms (MS or NMR spectroscopy based) used for data acquisition. Improved machinery in metabolomics generates increasingly complex datasets that create the need for more and better processing and analysis software and in silico approaches to understand the resulting data. However, a comprehensive source of information describing the utility of the most recently developed and released metabolomics resources—in the form of tools, software, and databases—is currently lacking. Thus, here we provide an overview of freely-available, and open-source, tools, algorithms, and frameworks to make both upcoming and established metabolomics researchers aware of the recent developments in an attempt to advance and facilitate data processing workflows in their metabolomics research. The major topics include tools and researches for data processing, data annotation, and data visualization in MS and NMR-based metabolomics. Most in this review described tools are dedicated to untargeted metabolomics workflows; however, some more specialist tools are described as well. All tools and resources described including their analytical and computational platform dependencies are summarized in an overview Table

Data shopping in an open marketplace: Introducing the Ontogrator web application for marking up data using ontologies and browsing using facets

In the future, we hope to see an open and thriving data market in which users can find and select data from a wide range of data providers. In such an open access market, data are products that must be packaged accordingly. Increasingly, eCommerce sellers present heterogeneous product lines to buyers using faceted browsing. Using this approach we have developed the Ontogrator platform, which allows for rapid retrieval of data in a way that would be familiar to any online shopper. Using Knowledge Organization Systems (KOS), especially ontologies, Ontogrator uses text mining to mark up data and faceted browsing to help users navigate, query and retrieve data. Ontogrator offers the potential to impact scientific research in two major ways: 1) by significantly improving the retrieval of relevant information; and 2) by significantly reducing the time required to compose standard database queries and assemble information for further research. Here we present a pilot implementation developed in collaboration with the Genomic Standards Consortium (GSC) that includes content from the StrainInfo, GOLD, CAMERA, Silva and Pubmed databases. This implementation demonstrates the power of ontogration and highlights that the usefulness of this approach is fully dependent on both the quality of data and the KOS (ontologies) used. Ideally, the use and further expansion of this collaborative system will help to surface issues associated with the underlying quality of annotation and could lead to a systematic means for accessing integrated data resources

Data shopping in an open marketplace: introducing the Ontogrator web application for marking up data using ontologies and browsing using facets

In the future, we hope to see an open and thriving data market in which users can find and select data from a wide range of data providers. In such an open access market, data are products that must be packaged accordingly. Increasingly, eCommerce sellers present heterogeneous product lines to buyers using faceted browsing. Using this approach we have developed the Ontogrator platform, which allows for rapid retrieval of data in a way that would be familiar to any online shopper. Using Knowledge Organization Systems (KOS), especially ontologies, Ontogrator uses text mining to mark up data and faceted browsing to help users navigate, query and retrieve data. Ontogrator offers the potential to impact scientific research in two major ways: 1) by significantly improving the retrieval of relevant information; and 2) by significantly reducing the time required to compose standard database queries and assemble information for further research. Here we present a pilot implementation developed in collaboration with the Genomic Standards Consortium (GSC) that includes content from the StrainInfo, GOLD, CAMERA, Silva and Pubmed databases. This implementation demonstrates the power of ontogration and highlights that the usefulness of this approach is fully dependent on both the quality of data and the KOS (ontologies) used. Ideally, the use and further expansion of this collaborative system will help to surface issues associated with the underlying quality of annotation and could lead to a systematic means for accessing integrated data resources

Proceedings of the international workshop on Ribosomal RNA technology, April 7–9, 2008, Bremen, Germany

Author Posting. © The Author(s), 2008. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Systematic and Applied Microbiology 31 (2008): 258-268, doi:10.1016/j.syapm.2008.08.004.Thirty years have passed since Carl Woese proposed three primary domains of life based on the phylogenetic analysis of ribosomal RNA genes. Adopted by researchers worldwide, ribosomal RNA has become the “gold-standard” for molecular taxonomy, biodiversity analysis and the identification of microorganisms. The more than 700,000 rRNA sequences in public databases constitute an unprecedented hallmark of the richness of microbial biodiversity on earth. The International Workshop on Ribosomal RNA Technology convened on April 7-9, 2008 in Bremen, Germany (http://www.arb-silva.de/rrna-workshop) to summarize the current status of the field and strategize on the best ways of proceeding on both biological and technological fronts. In five sessions, 26 leading international speakers and ~120 participants representing diverse disciplines discussed new technological approaches to address three basic ecological questions: “Who is out there?” “How many are there?” and “What are they doing?”The workshop was a joint collaborative effort of the Max Planck Institute in Bremen and the Ribocon GmbH Bremen, the Technical University Munich, the International Census of Marine Microbes (ICoMM) and the European Census of Marine Life (EuroCoML). The workshop was further sponsored by the Operon and BioCat biotechnology companies

Recent trends in molecular diagnostics of yeast infections : from PCR to NGS

The incidence of opportunistic yeast infections in humans has been increasing over recent years. These infections are difficult to treat and diagnose, in part due to the large number and broad diversity of species that can underlie the infection. In addition, resistance to one or several antifungal drugs in infecting strains is increasingly being reported, severely limiting therapeutic options and showcasing the need for rapid detection of the infecting agent and its drug susceptibility profile. Current methods for species and resistance identification lack satisfactory sensitivity and specificity, and often require prior culturing of the infecting agent, which delays diagnosis. Recently developed high-throughput technologies such as next generation sequencing or proteomics are opening completely new avenues for more sensitive, accurate and fast diagnosis of yeast pathogens. These approaches are the focus of intensive research, but translation into the clinics requires overcoming important challenges. In this review, we provide an overview of existing and recently emerged approaches that can be used in the identification of yeast pathogens and their drug resistance profiles. Throughout the text we highlight the advantages and disadvantages of each methodology and discuss the most promising developments in their path from bench to bedside