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Journal articles on the topic 'Microbial genomics - Data processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Dieckmann, Marius Alfred, Sebastian Beyvers, Rudel Christian Nkouamedjo-Fankep, et al. "EDGAR3.0: comparative genomics and phylogenomics on a scalable infrastructure." Nucleic Acids Research 49, W1 (2021): W185—W192. http://dx.doi.org/10.1093/nar/gkab341.

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Abstract The EDGAR platform, a web server providing databases of precomputed orthology data for thousands of microbial genomes, is one of the most established tools in the field of comparative genomics and phylogenomics. Based on precomputed gene alignments, EDGAR allows quick identification of the differential gene content, i.e. the pan genome, the core genome, or singleton genes. Furthermore, EDGAR features a wide range of analyses and visualizations like Venn diagrams, synteny plots, phylogenetic trees, as well as Amino Acid Identity (AAI) and Average Nucleotide Identity (ANI) matrices. Dur

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Shen-Gunther, Jane, Qingqing Xia, Hong Cai, and Yufeng Wang. "HPV DeepSeq: An Ultra-Fast Method of NGS Data Analysis and Visualization Using Automated Workflows and a Customized Papillomavirus Database in CLC Genomics Workbench." Pathogens 10, no. 8 (2021): 1026. http://dx.doi.org/10.3390/pathogens10081026.

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Next-generation sequencing (NGS) has actualized the human papillomavirus (HPV) virome profiling for in-depth investigation of viral evolution and pathogenesis. However, viral computational analysis remains a bottleneck due to semantic discrepancies between computational tools and curated reference genomes. To address this, we developed and tested automated workflows for HPV taxonomic profiling and visualization using a customized papillomavirus database in the CLC Microbial Genomics Module. HPV genomes from Papilloma Virus Episteme were customized and incorporated into CLC “ready-to-use” workf

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Murovec, Boštjan, Leon Deutsch, and Blaz Stres. "Computational Framework for High-Quality Production and Large-Scale Evolutionary Analysis of Metagenome Assembled Genomes." Molecular Biology and Evolution 37, no. 2 (2019): 593–98. http://dx.doi.org/10.1093/molbev/msz237.

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Abstract Microbial species play important roles in different environments and the production of high-quality genomes from metagenome data sets represents a major obstacle to understanding their ecological and evolutionary dynamics. Metagenome-Assembled Genomes Orchestra (MAGO) is a computational framework that integrates and simplifies metagenome assembly, binning, bin improvement, bin quality (completeness and contamination), bin annotation, and evolutionary placement of bins via detailed maximum-likelihood phylogeny based on multiple marker genes using different amino acid substitution model

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Rau, Martin H., and Ahmad A. Zeidan. "Constraint-based modeling in microbial food biotechnology." Biochemical Society Transactions 46, no. 2 (2018): 249–60. http://dx.doi.org/10.1042/bst20170268.

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Genome-scale metabolic network reconstruction offers a means to leverage the value of the exponentially growing genomics data and integrate it with other biological knowledge in a structured format. Constraint-based modeling (CBM) enables both the qualitative and quantitative analyses of the reconstructed networks. The rapid advancements in these areas can benefit both the industrial production of microbial food cultures and their application in food processing. CBM provides several avenues for improving our mechanistic understanding of physiology and genotype–phenotype relationships. This is

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Smolikova, Galina, Daria Gorbach, Elena Lukasheva, et al. "Bringing New Methods to the Seed Proteomics Platform: Challenges and Perspectives." International Journal of Molecular Sciences 21, no. 23 (2020): 9162. http://dx.doi.org/10.3390/ijms21239162.

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For centuries, crop plants have represented the basis of the daily human diet. Among them, cereals and legumes, accumulating oils, proteins, and carbohydrates in their seeds, distinctly dominate modern agriculture, thus play an essential role in food industry and fuel production. Therefore, seeds of crop plants are intensively studied by food chemists, biologists, biochemists, and nutritional physiologists. Accordingly, seed development and germination as well as age- and stress-related alterations in seed vigor, longevity, nutritional value, and safety can be addressed by a broad panel of ana

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van Belkum, Alex, Marc Struelens, Arjan de Visser, Henri Verbrugh, and Michel Tibayrenc. "Role of Genomic Typing in Taxonomy, Evolutionary Genetics, and Microbial Epidemiology." Clinical Microbiology Reviews 14, no. 3 (2001): 547–60. http://dx.doi.org/10.1128/cmr.14.3.547-560.2001.

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SUMMARY Currently, genetic typing of microorganisms is widely used in several major fields of microbiological research. Taxonomy, research aimed at elucidation of evolutionary dynamics or phylogenetic relationships, population genetics of microorganisms, and microbial epidemiology all rely on genetic typing data for discrimination between genotypes. Apart from being an essential component of these fundamental sciences, microbial typing clearly affects several areas of applied microbiogical research. The epidemiological investigation of outbreaks of infectious diseases and the measurement of ge

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Gangadoo, Sheeana, Piumie Rajapaksha Pathirannahalage, Samuel Cheeseman, et al. "The Multiomics Analyses of Fecal Matrix and Its Significance to Coeliac Disease Gut Profiling." International Journal of Molecular Sciences 22, no. 4 (2021): 1965. http://dx.doi.org/10.3390/ijms22041965.

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Gastrointestinal (GIT) diseases have risen globally in recent years, and early detection of the host’s gut microbiota, typically through fecal material, has become a crucial component for rapid diagnosis of such diseases. Human fecal material is a complex substance composed of undigested macromolecules and particles, and the processing of such matter is a challenge due to the unstable nature of its products and the complexity of the matrix. The identification of these products can be used as an indication for present and future diseases; however, many researchers focus on one variable or marke

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Shah, Carisa M., Rohan Bareja, and Olivier Elemento. "Pathogen identification in prostate cancer biopsies using transcriptome sequencing." Journal of Clinical Oncology 35, no. 15_suppl (2017): e16545-e16545. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.e16545.

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e16545 Background: Tumor biopsies may frequently be associated with microbial species due to proximity with microbial communities or due to contamination during tissue processing. We examined sequencing data from tumor biopsies to explore the tumor-associated microbiome in prostate cancer. Methods: Patients were enrolled in a prospective Precision Medicine study to evaluate genomic alterations based on freshly obtained tissue biopsies. Total RNA was prepared for RNA sequencing using the standard Illumina mRNA sample preparation protocol. Paired-end RNA-sequencing at read lengths of 50 or 51 bp

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Magnitov, Mikhail D., Veronika S. Kuznetsova, Sergey V. Ulianov, Sergey V. Razin, and Alexander V. Tyakht. "Benchmark of software tools for prokaryotic chromosomal interaction domain identification." Bioinformatics 36, no. 17 (2020): 4560–67. http://dx.doi.org/10.1093/bioinformatics/btaa555.

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Abstract Motivation The application of genome-wide chromosome conformation capture (3C) methods to prokaryotes provided insights into the spatial organization of their genomes and identified patterns conserved across the tree of life, such as chromatin compartments and contact domains. Prokaryotic genomes vary in GC content and the density of restriction sites along the chromosome, suggesting that these properties should be considered when planning experiments and choosing appropriate software for data processing. Diverse algorithms are available for the analysis of eukaryotic chromatin contac

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Ilyina, L. A., V. A. Filippova, E. A. Yildirim, et al. "APPLICATION OF NGS FOR EVALUATING THE SYMBIOTIC MICROFLORA OF THE REINDEER RUMEN IN THE RUSSIAN ARCTIC." International bulletin of Veterinary Medicine 2 (2020): 127–31. http://dx.doi.org/10.17238/issn2072-2419.2020.2.127.

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The method of next generation sequencing (NGS) allows deeply analyze the composi-tion of the microorganisms of the rumen of ruminants. Sampling of the contents of the rumen was carried out in the winter-spring period during the slaughter of reindeer in the territory of the Murmansk region - in the agricultural complex “Tundra” of the Lovozero district. 12 samples of rumen con-tent were taken. Samples of rumen contents intended for molecular genetic studies were frozen immediately after selection at -20 ° C and then placed for long-term storage in a freezer. Total DNA was extracted from the sam

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Li, Qianqian, Rebecca E. Cooper, Carl-Eric Wegner, and Kirsten Küsel. "Molecular Mechanisms Underpinning Aggregation in Acidiphilium sp. C61 Isolated from Iron-Rich Pelagic Aggregates." Microorganisms 8, no. 3 (2020): 314. http://dx.doi.org/10.3390/microorganisms8030314.

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Iron-rich pelagic aggregates (iron snow) are hot spots for microbial interactions. Using iron snow isolates, we previously demonstrated that the iron-oxidizer Acidithrix sp. C25 triggers Acidiphilium sp. C61 aggregation by producing the infochemical 2-phenethylamine (PEA). Here, we showed slightly enhanced aggregate formation in the presence of PEA on different Acidiphilium spp. but not other iron-snow microorganisms, including Acidocella sp. C78 and Ferrovum sp. PN-J47. Next, we sequenced the Acidiphilium sp. C61 genome to reconstruct its metabolic potential. Pangenome analyses of Acidiphiliu

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L Hazell, Stuart. "Genomics and drug discovery." Microbiology Australia 23, no. 5 (2002): 17. http://dx.doi.org/10.1071/ma02517.

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Genomics represents a new tool in drug discovery. Microbial genomics have been at the forefront of a new era of whole cell molecular biology because genomic data provides a quantum leap in available genetic data. But while the tool is valuable and important, it is not the complete answer.

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Konwar, Chaini, Giulia Del Gobbo, Victor Yuan, and Wendy P. Robinson. "Considerations when processing and interpreting genomics data of the placenta." Placenta 84 (September 2019): 57–62. http://dx.doi.org/10.1016/j.placenta.2019.01.006.

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Marçais, Guillaume, Brad Solomon, Rob Patro, and Carl Kingsford. "Sketching and Sublinear Data Structures in Genomics." Annual Review of Biomedical Data Science 2, no. 1 (2019): 93–118. http://dx.doi.org/10.1146/annurev-biodatasci-072018-021156.

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Large-scale genomics demands computational methods that scale sublinearly with the growth of data. We review several data structures and sketching techniques that have been used in genomic analysis methods. Specifically, we focus on four key ideas that take different approaches to achieve sublinear space usage and processing time: compressed full-text indices, approximate membership query data structures, locality-sensitive hashing, and minimizers schemes. We describe these techniques at a high level and give several representative applications of each.

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Karabayev, Daniyar, Askhat Molkenov, Kaiyrgali Yerulanuly, et al. "re-Searcher: GUI-based bioinformatics tool for simplified genomics data mining of VCF files." PeerJ 9 (May 3, 2021): e11333. http://dx.doi.org/10.7717/peerj.11333.

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Background High-throughput sequencing platforms generate a massive amount of high-dimensional genomic datasets that are available for analysis. Modern and user-friendly bioinformatics tools for analysis and interpretation of genomics data becomes essential during the analysis of sequencing data. Different standard data types and file formats have been developed to store and analyze sequence and genomics data. Variant Call Format (VCF) is the most widespread genomics file type and standard format containing genomic information and variants of sequenced samples. Results Existing tools for proces

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van der Hooft, Justin J. J., Hosein Mohimani, Anelize Bauermeister, Pieter C. Dorrestein, Katherine R. Duncan, and Marnix H. Medema. "Linking genomics and metabolomics to chart specialized metabolic diversity." Chemical Society Reviews 49, no. 11 (2020): 3297–314. http://dx.doi.org/10.1039/d0cs00162g.

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Microbial and plant specialized metabolites play key roles in mediating ecological interactions between organisms. Analysis and integration of genomics and metabolomics data facilitates charting their immense chemical diversity.

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H. Mohamad, Ummul, Mohamad T. Ijab, and Rabiah A. Kadir. "Genomics big data hybrid depositories architecture to unlock precision medicine: a conceptual framework." International Journal of Engineering & Technology 7, no. 4 (2018): 2585. http://dx.doi.org/10.14419/ijet.v7i4.16893.

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As the genome sequencing cost becomes more affordable, genomics studies are extensively carried out to empower the ultimate healthcare goal which is the precision medicine. By tailoring each individual medical treatment through precision medicine, it will potentially lead to nearly zero occurrence of the drugs side effects and treatment complications. Unfortunately, the complexity of the genomics data has been one of the bottlenecks that deter the advances of healthcare practices towards precision medicine. Therefore, based on the extensive literature review on the data driven genomics challen

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Heidelberg, Karla B., and John F. Heidelberg. "Marine Environmental Genomics: New Secrets from a Mysterious Ocean." Marine Technology Society Journal 39, no. 3 (2005): 94–98. http://dx.doi.org/10.4031/002533205787442549.

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Ocean microbes play critical roles in ecosystem dynamics and biogeochemical cycles. For a number of reasons, these organisms have been hard to study; among other characteristics, they are difficult or maybe impossible to culture. The recent application of cultivation-independent genomic techniques to study bacterial communities has begun to fundamentally change our views of microbial ecology and function. These approaches are providing more comprehensive insights into the structure and function of natural assemblages of microbial populations. Genomics-based technologies are revealing previousl

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Chun, Jongsik, and Fred A. Rainey. "Integrating genomics into the taxonomy and systematics of the Bacteria and Archaea." International Journal of Systematic and Evolutionary Microbiology 64, Pt_2 (2014): 316–24. http://dx.doi.org/10.1099/ijs.0.054171-0.

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The polyphasic approach used today in the taxonomy and systematics of the Bacteria and Archaea includes the use of phenotypic, chemotaxonomic and genotypic data. The use of 16S rRNA gene sequence data has revolutionized our understanding of the microbial world and led to a rapid increase in the number of descriptions of novel taxa, especially at the species level. It has allowed in many cases for the demarcation of taxa into distinct species, but its limitations in a number of groups have resulted in the continued use of DNA–DNA hybridization. As technology has improved, next-generation sequen

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Jarlier, Frédéric, Nicolas Joly, Nicolas Fedy, et al. "QUARTIC: QUick pArallel algoRithms for high-Throughput sequencIng data proCessing." F1000Research 9 (April 6, 2020): 240. http://dx.doi.org/10.12688/f1000research.22954.1.

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Life science has entered the so-called ’big data era’ where biologists, clinicians and bioinformaticians are overwhelmed with unprecedented amount of data. High-throughput sequencing has revolutionized genomics and offers new insights to decipher the genome structure. However, using these data for daily clinical practice care and diagnosis purposes is challenging as the data are bigger and bigger. Therefore, we implemented software using Message Passing Interface such that the alignment and sorting of sequencing reads can easily scale on high-performance computing architecture. Our implementat

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Avram, Oren, Dana Rapoport, Shir Portugez, and Tal Pupko. "M1CR0B1AL1Z3R—a user-friendly web server for the analysis of large-scale microbial genomics data." Nucleic Acids Research 47, W1 (2019): W88—W92. http://dx.doi.org/10.1093/nar/gkz423.

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Abstract Large-scale mining and analysis of bacterial datasets contribute to the comprehensive characterization of complex microbial dynamics within a microbiome and among different bacterial strains, e.g., during disease outbreaks. The study of large-scale bacterial evolutionary dynamics poses many challenges. These include data-mining steps, such as gene annotation, ortholog detection, sequence alignment and phylogeny reconstruction. These steps require the use of multiple bioinformatics tools and ad-hoc programming scripts, making the entire process cumbersome, tedious and error-prone due t

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Tabassum Khan, Nida. "The Emerging Role of Bioinformatics in Biotechnology." Journal of Biotechnology and Biomedical Science 1, no. 3 (2018): 13–24. http://dx.doi.org/10.14302/issn.2576-6694.jbbs-18-2173.

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Bioinformatic tools is widely used to manage the enormous genomic and proteomic data involving DNA/protein sequences management, drug designing, homology modelling, motif/domain prediction ,docking, annotation and dynamic simulation etc. Bioinformatics offers a wide range of applications in numerous disciplines such as genomics. Proteomics, comparative genomics, nutrigenomics, microbial genome, biodefense, forensics etc. Thus it offers promising future to accelerate scientific research in biotechnology

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Feltus, Frank A., Joseph R. Breen, Juan Deng, et al. "The Widening Gulf between Genomics Data Generation and Consumption: A Practical Guide to Big Data Transfer Technology." Bioinformatics and Biology Insights 9s1 (January 2015): BBI.S28988. http://dx.doi.org/10.4137/bbi.s28988.

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In the last decade, high-throughput DNA sequencing has become a disruptive technology and pushed the life sciences into a distributed ecosystem of sequence data producers and consumers. Given the power of genomics and declining sequencing costs, biology is an emerging “Big Data” discipline that will soon enter the exabyte data range when all subdisciplines are combined. These datasets must be transferred across commercial and research networks in creative ways since sending data without thought can have serious consequences on data processing time frames. Thus, it is imperative that biologists

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Kuang, Ellen, Matthew Marney, Daniel Cuevas, Robert A. Edwards, and Erica M. Forsberg. "Towards Predicting Gut Microbial Metabolism: Integration of Flux Balance Analysis and Untargeted Metabolomics." Metabolites 10, no. 4 (2020): 156. http://dx.doi.org/10.3390/metabo10040156.

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Genomics-based metabolic models of microorganisms currently have no easy way of corroborating predicted biomass with the actual metabolites being produced. This study uses untargeted mass spectrometry-based metabolomics data to generate a list of accurate metabolite masses produced from the human commensal bacteria Citrobacter sedlakii grown in the presence of a simple glucose carbon source. A genomics-based flux balance metabolic model of this bacterium was previously generated using the bioinformatics tool PyFBA and phenotypic growth curve data. The high-resolution mass spectrometry data obt

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Blum, Matthias, Pierre-Etienne Cholley, Valeriya Malysheva, et al. "A comprehensive resource for retrieving, visualizing, and integrating functional genomics data." Life Science Alliance 3, no. 1 (2019): e201900546. http://dx.doi.org/10.26508/lsa.201900546.

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The enormous amount of freely accessible functional genomics data is an invaluable resource for interrogating the biological function of multiple DNA-interacting players and chromatin modifications by large-scale comparative analyses. However, in practice, interrogating large collections of public data requires major efforts for (i) reprocessing available raw reads, (ii) incorporating quality assessments to exclude artefactual and low-quality data, and (iii) processing data by using high-performance computation. Here, we present qcGenomics, a user-friendly online resource for ultrafast retriev

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Robinson, Tony, Jim Harkin, and Priyank Shukla. "Hardware acceleration of genomics data analysis: challenges and opportunities." Bioinformatics 37, no. 13 (2021): 1785–95. http://dx.doi.org/10.1093/bioinformatics/btab017.

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Summary The significant decline in the cost of genome sequencing has dramatically changed the typical bioinformatics pipeline for analysing sequencing data. Where traditionally, the computational challenge of sequencing is now secondary to genomic data analysis. Short read alignment (SRA) is a ubiquitous process within every modern bioinformatics pipeline in the field of genomics and is often regarded as the principal computational bottleneck. Many hardware and software approaches have been provided to solve the challenge of acceleration. However, previous attempts to increase throughput using

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Zanina, Irina, Eugenia Kostromina, Natalia Stuzhenko, and Yuri Chertov. "Processing of poultry farm waste by microbial conversion." E3S Web of Conferences 175 (2020): 04004. http://dx.doi.org/10.1051/e3sconf/202017504004.

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The article presents the results of an analysis of modern research in the field of organic waste processing. To solve the problem, anaerobic bioconversion method was chosen. The data of experimental laboratory experiments on the selection of a consortium of microorganisms’ methanizing waste from poultry farms with maximum efficiency are presented.

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Jolley, Keith A., James E. Bray, and Martin C. J. Maiden. "Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications." Wellcome Open Research 3 (September 24, 2018): 124. http://dx.doi.org/10.12688/wellcomeopenres.14826.1.

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The PubMLST.org website hosts a collection of open-access, curated databases that integrate population sequence data with provenance and phenotype information for over 100 different microbial species and genera. Although the PubMLST website was conceived as part of the development of the first multi-locus sequence typing (MLST) scheme in 1998 the software it uses, the Bacterial Isolate Genome Sequence database (BIGSdb, published in 2010), enables PubMLST to include all levels of sequence data, from single gene sequences up to and including complete, finished genomes. Here we describe developme

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Gu, Ji-Dong. "More than simply microbial growth curves." Applied Environmental Biotechnology 1, no. 2 (2016): 63. http://dx.doi.org/10.18063/aeb.2016.02.007.

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Bacterial growth is a very important piece of information in a wide range of investigation and, in most of the time the data are simply shown directly without any further processing. In a single factor investigation without comparative information to be extracted, this simple approach can be used together with other data to form a comprehensive set of results. When comparison is involved, such direct showing of bacterial growth curves without processing cannot warrant a meaningful comparison thoroughly and further processing of data is necessary. In addition, there is little, if any, quantitat

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Keeling, Patrick J. "Combining morphology, behaviour and genomics to understand the evolution and ecology of microbial eukaryotes." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1786 (2019): 20190085. http://dx.doi.org/10.1098/rstb.2019.0085.

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Microbial eukaryotes (protists) are structurally, developmentally and behaviourally more complex than their prokaryotic cousins. This complexity makes it more difficult to translate genomic and metagenomic data into accurate functional inferences about systems ranging all the way from molecular and cellular levels to global ecological networks. This problem can be traced back to the advent of the cytoskeleton and endomembrane systems at the origin of eukaryotes, which endowed them with a range of complex structures and behaviours that still largely dominate how they evolve and interact within

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Karczewski, Konrad J., Guy Haskin Fernald, Alicia R. Martin, Michael Snyder, Nicholas P. Tatonetti, and Joel T. Dudley. "STORMSeq: An Open-Source, User-Friendly Pipeline for Processing Personal Genomics Data in the Cloud." PLoS ONE 9, no. 1 (2014): e84860. http://dx.doi.org/10.1371/journal.pone.0084860.

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Wu, M. Y., K. Suryanarayanan, W. J. van Ooij, and D. B. Oerther. "Using microbial genomics to evaluate the effectiveness of silver to prevent biofilm formation." Water Science and Technology 55, no. 8-9 (2007): 413–19. http://dx.doi.org/10.2166/wst.2007.285.

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Increasingly, monovalent silver cations are being considered as an alternative biocide in water distribution systems. The objective of this study was to understand how bacteria respond when challenged with silver. The approach used included cultivation of Escherichia coli in planktonic and sessile phases, exposing biomass to a solution of silver nitrate and evaluating genetic responses using commercial Affymetrix microarrays. Experimental results showed that lower pH enhanced silver toxicity in a dose-dependent manner. Sessile biomass demonstrated resistance to silver, and the microarray resul

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Ostrowski, Martin, Sasha Tetu, Karl Hassan, et al. "From omics to systems biology: Exploring the mystery box of microbial life." Microbiology Australia 32, no. 4 (2011): 147. http://dx.doi.org/10.1071/ma11147.

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Microbial molecular biology has traditionally used very reductionist approaches; for example, find a gene of interest, clone it or knock it out and see if you can detect a phenotype. The genomics era has opened up the possibility of analysing microbes and communities at a systems level by combining high-throughput experimental data from genomic, transcriptomic, proteomic and phenomic techniques. This parallels earlier reductionist approaches by going from DNA to RNA to protein to phenotype, albeit on a global rather than individual gene scale.

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SASAKI, YUTAKA, JOHN MCNAUGHT, and SOPHIA ANANIADOU. "THE VALUE OF AN IN-DOMAIN LEXICON IN GENOMICS QA." Journal of Bioinformatics and Computational Biology 08, no. 01 (2010): 147–61. http://dx.doi.org/10.1142/s0219720010004513.

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This paper demonstrates that a large-scale lexicon tailored for the biology domain is effective in improving question analysis for genomics Question Answering (QA). We use the TREC Genomics Track data to evaluate the performance of different question analysis methods. It is hard to process textual information in biology, especially in molecular biology, due to a huge number of technical terms which rarely appear in general English documents and dictionaries. To support biological Text Mining, we have developed a domain-specific resource, the BioLexicon. Started in 2006 from scratch, this lexic

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Crisan, Anamaria, Geoffrey McKee, Tamara Munzner, and Jennifer L. Gardy. "Evidence-based design and evaluation of a whole genome sequencing clinical report for the reference microbiology laboratory." PeerJ 6 (January 10, 2018): e4218. http://dx.doi.org/10.7717/peerj.4218.

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Background Microbial genome sequencing is now being routinely used in many clinical and public health laboratories. Understanding how to report complex genomic test results to stakeholders who may have varying familiarity with genomics—including clinicians, laboratorians, epidemiologists, and researchers—is critical to the successful and sustainable implementation of this new technology; however, there are no evidence-based guidelines for designing such a report in the pathogen genomics domain. Here, we describe an iterative, human-centered approach to creating a report template for communicat

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Gouripeddi, Ram, Andrew Miller, Karen Eilbeck, Katherine Sward, and Julio C. Facelli. "3399 Systematically Integrating Microbiomes and Exposomes for Translational Research." Journal of Clinical and Translational Science 3, s1 (2019): 29–30. http://dx.doi.org/10.1017/cts.2019.71.

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OBJECTIVES/SPECIFIC AIMS: Characterize microbiome metadata describing specimens collected, genomic pipelines and microbiome results, and incorporate them into a data integration platform for enabling harmonization, integration and assimilation of microbial genomics with exposures as spatiotemporal events. METHODS/STUDY POPULATION: We followed similar methods utilized in previous efforts in charactering and developing metadata models for describing microbiome metadata. Due to the heterogeneity in microbiome and exposome data, we aligned them along a conceptual representation of different data u

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Dvinge, Heidi, Rhonda E. Ries, Janine O. Ilagan, Derek L. Stirewalt, Soheil Meshinchi, and Robert K. Bradley. "Sample Processing Obscures Cancer-Specific Alterations in Leukemic Transcriptomes." Blood 124, no. 21 (2014): 2201. http://dx.doi.org/10.1182/blood.v124.21.2201.2201.

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Abstract Substantial effort is currently devoted to identifying cancer-associated alterations using genomics technologies. While the genome is inherently stable over short time frames, the transcriptome is dynamic and potentially susceptible to alteration as samples move from the patient to the lab bench. Here, we show that standard blood collection procedures rapidly change the transcriptional and post-transcriptional landscapes of hematopoietic cells, resulting in biased activation of specific biological pathways, up-regulation of pseudogenes, antisense RNAs, and unannotated coding isoforms,

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Percudani, Riccardo. "A Microbial Metagenome (Leucobacter sp.) in Caenorhabditis Whole Genome Sequences." Bioinformatics and Biology Insights 7 (January 2013): BBI.S11064. http://dx.doi.org/10.4137/bbi.s11064.

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DNA of apparently recent bacterial origin is found in the genomic sequences of Caenorhabditis angaria and Caenorhabditis remanei. Here we present evidence that the DNA belongs to a single species of the genus Leucobacter (high-GC Gram+Actinobacteria). Metagenomic tools enabled the assembly of the contaminating sequences in a draft genome of 3.2 Mb harboring 2,826 genes. This information provides insight into a microbial organism intimately associated with Caenorhabditis as well as a solid basis for the reassignment of 3,373 metazoan entries of the public database to a novel bacterial species (

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Kinnunen, Päivi, Hanna Miettinen, and Malin Bomberg. "Review of Potential Microbial Effects on Flotation." Minerals 10, no. 6 (2020): 533. http://dx.doi.org/10.3390/min10060533.

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Microorganisms enter the flotation process mainly from intake water and ore material. The diversity and number of microorganisms can vary significantly from mine to mine. In flotation, the conditions including oxygen levels, temperature, and nutrients from ore, intake water, and reagents are often favorable for the microbial growth. The mining industry aims to close the water loops, which is expected to result in the accumulation of microorganisms in the process waters with potential effects on flotation performance. Bioflotation, bioleaching, and bio-oxidation have been studied for decades as

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Ghoneimy, Samy, and Samir Abou El-Seoud. "A MapReduce Framework for DNA Sequencing Data Processing." International Journal of Recent Contributions from Engineering, Science & IT (iJES) 4, no. 4 (2016): 11. http://dx.doi.org/10.3991/ijes.v4i4.6537.

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<p class="Els-1storder-head">Genomics and Next Generation Sequencers (NGS) like Illumina Hiseq produce data in the order of ‎‎200 billion base pairs in a single one-week run for a 60x human genome coverage, which ‎requires modern high-throughput experimental technologies that can ‎only be tackled with high performance computing (HPC) and specialized software algorithms called ‎‎“short read aligners”. This paper focuses on the implementation of the DNA sequencing as a set of MapReduce programs that will accept a DNA data set as a FASTQ file and finally generate a VCF (variant call format)

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Tolonen, Andrew C., Trevor R. Zuroff, Mohandass Ramya, Magali Boutard, Tristan Cerisy, and Wayne R. Curtis. "Physiology, Genomics, and Pathway Engineering of an Ethanol-Tolerant Strain of Clostridium phytofermentans." Applied and Environmental Microbiology 81, no. 16 (2015): 5440–48. http://dx.doi.org/10.1128/aem.00619-15.

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ABSTRACTNovel processing strategies for hydrolysis and fermentation of lignocellulosic biomass in a single reactor offer large potential cost savings for production of biocommodities and biofuels. One critical challenge is retaining high enzyme production in the presence of elevated product titers. Toward this goal, the cellulolytic, ethanol-producing bacteriumClostridium phytofermentanswas adapted to increased ethanol concentrations. The resulting ethanol-tolerant (ET) strain has nearly doubled ethanol tolerance relative to the wild-type level but also reduced ethanol yield and growth at low

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Mazandu, Gaston K., and Nicola J. Mulder. "Generation and Analysis of Large-Scale Data-Driven Mycobacterium tuberculosis Functional Networks for Drug Target Identification." Advances in Bioinformatics 2011 (November 29, 2011): 1–14. http://dx.doi.org/10.1155/2011/801478.

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Technological developments in large-scale biological experiments, coupled with bioinformatics tools, have opened the doors to computational approaches for the global analysis of whole genomes. This has provided the opportunity to look at genes within their context in the cell. The integration of vast amounts of data generated by these technologies provides a strategy for identifying potential drug targets within microbial pathogens, the causative agents of infectious diseases. As proteins are druggable targets, functional interaction networks between proteins are used to identify proteins esse

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Men, Hong, Jian Ping Sun, Jing Zhang, Yu Ming Guo, and Zhi Ming Xu. "The Compare of Microbial Electronic Tongue Data Based on Direct and Two-Stage Processing." Applied Mechanics and Materials 20-23 (January 2010): 331–36. http://dx.doi.org/10.4028/www.scientific.net/amm.20-23.331.

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In this paper, we used three working electrodes of platinum, gold, glassy carbon which constituted the microbial electronic tongue to identify microorganisms. The main purpose of this article is to classify sulfate-reducing bacteria and iron bacteria with the reference of broth culture. The accuracy of classification was compared based on directly processing (raw data processed by Back- Propagation Neural Network (BPNN), raw data processed by Partial LeastSquares (PLS) and raw data processed by Principal Components Analysis (PCA)) and two-stage processing (Principal Components Analysis (PCA) o

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Kromer, Jens O. "Quantification of microbial phenotypes using 13C-Fluxomics." Microbiology Australia 32, no. 4 (2011): 163. http://dx.doi.org/10.1071/ma11163.

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Systems biology is an emerging tool in microbiology that helps us to understand cellular processes and to optimise microbes for production purposes1. It strongly relies on the use of large datasets created using omics tools followed by data mining and modelling in order to gain new insights into biology. The creation of the datasets is usually comprised of genomics defining the overall capacity of a microbe, transcriptomics and proteomics as a measure of the active set of reactions within the overall capacity and more recently metabolomics as a measure of the available building blocks and (if

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Tanisawa, Kumpei, Guan Wang, Jane Seto, et al. "Sport and exercise genomics: the FIMS 2019 consensus statement update." British Journal of Sports Medicine 54, no. 16 (2020): 969–75. http://dx.doi.org/10.1136/bjsports-2019-101532.

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Rapid advances in technologies in the field of genomics such as high throughput DNA sequencing, big data processing by machine learning algorithms and gene-editing techniques are expected to make precision medicine and gene-therapy a greater reality. However, this development will raise many important new issues, including ethical, moral, social and privacy issues. The field of exercise genomics has also advanced by incorporating these innovative technologies. There is therefore an urgent need for guiding references for sport and exercise genomics to allow the necessary advancements in this fi

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He, Kejun, Sharon M. Donovan, Ivan V. Ivanov, Jennifer S. Goldsby, Laurie A. Davidson, and Robert S. Chapkin. "Assessing the Multivariate Relationship between the Human Infant Intestinal Exfoliated Cell Transcriptome (Exfoliome) and Microbiome in Response to Diet." Microorganisms 8, no. 12 (2020): 2032. http://dx.doi.org/10.3390/microorganisms8122032.

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Gut microbiota and the host exist in a mutualistic relationship, with the functional composition of the microbiota strongly influencing the health and well-being of the host. In addition to the standard differential expression analysis of host genes to assess the complex cross-talk between environment (diet), microbiome, and host intestinal physiology, data-driven integrative approaches are needed to identify potential biomarkers of both host genes and microbial communities that characterize these interactions. Our findings demonstrate that the complementary application of univariate different

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Kuramae, Eiko E., Stan Derksen, Thiago R. Schlemper, Maurício R. Dimitrov, Ohana Y. A. Costa, and Adriana P. D. da Silveira. "Sorghum Growth Promotion by Paraburkholderia tropica and Herbaspirillum frisingense: Putative Mechanisms Revealed by Genomics and Metagenomics." Microorganisms 8, no. 5 (2020): 725. http://dx.doi.org/10.3390/microorganisms8050725.

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Bacteria from the genera Paraburkholderia and Herbaspirillum can promote the growth of Sorghum bicolor, but the underlying mechanisms are not yet known. In a pot experiment, sorghum plants grown on sterilized substrate were inoculated with Paraburkholderia tropica strain IAC/BECa 135 and Herbaspirillum frisingense strain IAC/BECa 152 under phosphate-deficient conditions. These strains significantly increased Sorghum bicolor cultivar SRN-39 root and shoot biomass. Shotgun metagenomic analysis of the rhizosphere revealed successful colonization by both strains; however, the incidence of coloniza

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Bertelli, Claire, Keith E. Tilley, and Fiona S. L. Brinkman. "Microbial genomic island discovery, visualization and analysis." Briefings in Bioinformatics 20, no. 5 (2018): 1685–98. http://dx.doi.org/10.1093/bib/bby042.

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Abstract Horizontal gene transfer (also called lateral gene transfer) is a major mechanism for microbial genome evolution, enabling rapid adaptation and survival in specific niches. Genomic islands (GIs), commonly defined as clusters of bacterial or archaeal genes of probable horizontal origin, are of particular medical, environmental and/or industrial interest, as they disproportionately encode virulence factors and some antimicrobial resistance genes and may harbor entire metabolic pathways that confer a specific adaptation (solvent resistance, symbiosis properties, etc). As large-scale anal

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Wilkins, Michael J., David W. Kennedy, Cindy J. Castelle, et al. "Single-cell genomics reveals metabolic strategies for microbial growth and survival in an oligotrophic aquifer." Microbiology 160, no. 2 (2014): 362–72. http://dx.doi.org/10.1099/mic.0.073965-0.

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Bacteria from the genus Pedobacter are a major component of microbial assemblages at Hanford Site (a largely decommissioned nuclear production complex) in eastern Washington state, USA, and have been shown to change significantly in abundance in response to the subsurface intrusion of Columbia River water. Here we employed single-cell genomics techniques to shed light on the physiological niche of these micro-organisms. Analysis of four Pedobacter single amplified genomes (SAGs) from Hanford Site sediments revealed a chemoheterotrophic lifestyle, with the potential to exist under both aerobic

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Elsliger, Marc-André, Ashley Deacon, Adam Godzik, et al. "JCSG – Adapting Structural Genomics to Eukaryotic Complexes." Acta Crystallographica Section A Foundations and Advances 70, a1 (2014): C1148. http://dx.doi.org/10.1107/s2053273314088512.

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For over a decade, the Joint Center for Structural Genomics (JCSG.org) has been at the forefront of developing tools and methodologies that enable the application of high-throughput structural biology (HTBSB) approaches to a broad range of challenging biological and biomedical problems. In PSI:Biology (2010-2015) to meet the challenges and embrace the opportunities that arise from our Partnerships projects, we have leveraged our gene-to-structure pipeline to explore challenging projects focused on structural characterization of interaction networks involved in stem cell regulation, T-cell acti

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