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Search Results: 1 - 10 of 3589 matches for " Folker Meyer "
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Metagenomics - a guide from sampling to data analysis
Torsten Thomas, Jack Gilbert, Folker Meyer
Microbial Informatics and Experimentation , 2012, DOI: 10.1186/2042-5783-2-3
Abstract: Arguably, one of the most remarkable events in the field of microbial ecology in the past decade has been the advent and development of metagenomics. Metagenomics is defined as the direct genetic analysis of genomes contained with an environmental sample. The field initially started with the cloning of environmental DNA, followed by functional expression screening [1], and was then quickly complemented by direct random shotgun sequencing of environmental DNA [2,3]. These initial projects not only showed proof of principle of the metagenomic approach, but also uncovered an enormous functional gene diversity in the microbial world around us [4].Metagenomics provides access to the functional gene composition of microbial communities and thus gives a much broader description than phylogenetic surveys, which are often based only on the diversity of one gene, for instance the 16S rRNA gene. On its own, metagenomics gives genetic information on potentially novel biocatalysts or enzymes, genomic linkages between function and phylogeny for uncultured organisms, and evolutionary profiles of community function and structure. It can also be complemented with metatranscriptomic or metaproteomic approaches to describe expressed activities [5,6]. Metagenomics is also a powerful tool for generating novel hypotheses of microbial function; the remarkable discoveries of proteorhodopsin-based photoheterotrophy or ammonia-oxidizing Archaea attest to this fact [7,8].The rapid and substantial cost reduction in next-generation sequencing has dramatically accelerated the development of sequence-based metagenomics. In fact, the number of metagenome shotgun sequence datasets has exploded in the past few years. In the future, metagenomics will be used in the same manner as 16S rRNA gene fingerprinting methods to describe microbial community profiles. It will therefore become a standard tool for many laboratories and scientists working in the field of microbial ecology.This review gives an over
Metagenomic Profiling of a Microbial Assemblage Associated with the California Mussel: A Node in Networks of Carbon and Nitrogen Cycling
Catherine A. Pfister,Folker Meyer,Dionysios A. Antonopoulos
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0010518
Abstract: Mussels are conspicuous and often abundant members of rocky shores and may constitute an important site for the nitrogen cycle due to their feeding and excretion activities. We used shotgun metagenomics of the microbial community associated with the surface of mussels (Mytilus californianus) on Tatoosh Island in Washington state to test whether there is a nitrogen-based microbial assemblage associated with mussels. Analyses of both tidepool mussels and those on emergent benches revealed a diverse community of Bacteria and Archaea with approximately 31 million bp from 6 mussels in each habitat. Using MG-RAST, between 22.5–25.6% were identifiable using the SEED non-redundant database for proteins. Of those fragments that were identifiable through MG-RAST, the composition was dominated by Cyanobacteria and Alpha- and Gamma-proteobacteria. Microbial composition was highly similar between the tidepool and emergent bench mussels, suggesting similar functions across these different microhabitats. One percent of the proteins identified in each sample were related to nitrogen cycling. When normalized to protein discovery rate, the high diversity and abundance of enzymes related to the nitrogen cycle in mussel-associated microbes is as great or greater than that described for other marine metagenomes. In some instances, the nitrogen-utilizing profile of this assemblage was more concordant with soil metagenomes in the Midwestern U.S. than for open ocean system. Carbon fixation and Calvin cycle enzymes further represented 0.65 and 1.26% of all proteins and their abundance was comparable to a number of open ocean marine metagenomes. In sum, the diversity and abundance of nitrogen and carbon cycle related enzymes in the microbes occupying the shells of Mytilus californianus suggest these mussels provide a node for microbial populations and thus biogeochemical processes.
BMP signaling components in embryonic transcriptomes of the hover fly Episyrphus balteatus (Syrphidae)
Steffen Lemke, Dionysios A Antonopoulos, Folker Meyer, Marc H Domanus, Urs Schmidt-Ott
BMC Genomics , 2011, DOI: 10.1186/1471-2164-12-278
Abstract: To search for BMP signaling components in E. balteatus, we generated and analyzed transcriptomes of freshly laid eggs (0-30 minutes) and late blastoderm to early germband extension stages (3-6 hours) using Roche/454 sequencing. We identified putative E. balteatus orthologues of 43% of all annotated D. melanogaster genes, including the genes of all BMP ligands and other BMP signaling components.The diversification of several BMP signaling components in the dipteran linage of D. melanogaster preceded the origin of the amnioserosa.[Transcriptome sequence data from this study have been deposited at the NCBI Sequence Read Archive (SRP005289); individually assembled sequences have been deposited at GenBank (JN006969-JN006986).]Across animals, the Bone Morphogenetic Protein (BMP) signaling pathway plays a major role in specifying the dorsoventral (DV) axis [1,2]. However, the components of the BMP pathway have been repeatedly modified through lineage specific gene duplications and gene losses [3,4]. Whether some of these genetic changes correlate with the origin of species-specific morphological traits that develop under the control of the BMP pathway is unknown. Flies (Diptera) provide an excellent opportunity to address this question firstly because the BMP signaling pathway of Drosophila melanogaster has been studied in great detail [5,6], and secondly because tissue specification presumably under the control of BMP signaling along the DV axis of dipterans has undergone significant change [7]. In D. melanogaster, dorsal blastoderm differentiates into a single extraembryonic epithelium, called amnioserosa, which closes the developing embryo dorsally [8]. This tissue is found in higher cyclorrhaphan flies (Schizophora), but in other dipterans, dorsal blastoderm gives rise to distinct serosal and amniotic epithelia [9-11]. Serosa and amnion develop from an amnioserosal fold at the margins of the gastrulating embryo. The outer cell layer of this fold becomes the serosa, whi
A Platform-Independent Method for Detecting Errors in Metagenomic Sequencing Data: DRISEE
Kevin P. Keegan ,William L. Trimble,Jared Wilkening,Andreas Wilke,Travis Harrison,Mark D'Souza,Folker Meyer
PLOS Computational Biology , 2012, DOI: 10.1371/journal.pcbi.1002541
Abstract: We provide a novel method, DRISEE (duplicate read inferred sequencing error estimation), to assess sequencing quality (alternatively referred to as “noise” or “error”) within and/or between sequencing samples. DRISEE provides positional error estimates that can be used to inform read trimming within a sample. It also provides global (whole sample) error estimates that can be used to identify samples with high or varying levels of sequencing error that may confound downstream analyses, particularly in the case of studies that utilize data from multiple sequencing samples. For shotgun metagenomic data, we believe that DRISEE provides estimates of sequencing error that are more accurate and less constrained by technical limitations than existing methods that rely on reference genomes or the use of scores (e.g. Phred). Here, DRISEE is applied to (non amplicon) data sets from both the 454 and Illumina platforms. The DRISEE error estimate is obtained by analyzing sets of artifactual duplicate reads (ADRs), a known by-product of both sequencing platforms. We present DRISEE as an open-source, platform-independent method to assess sequencing error in shotgun metagenomic data, and utilize it to discover previously uncharacterized error in de novo sequence data from the 454 and Illumina sequencing platforms.
The M5nr: a novel non-redundant database containing protein sequences and annotations from multiple sources and associated tools
Andreas Wilke, Travis Harrison, Jared Wilkening, Dawn Field, Elizabeth M Glass, Nikos Kyrpides, Konstantinos Mavrommatis, Folker Meyer
BMC Bioinformatics , 2012, DOI: 10.1186/1471-2105-13-141
Abstract: We introduce a mechanism for automatically maintaining a comprehensive, non-redundant protein database and for creating a quarterly release of this resource. In addition, we present tools for translating similarity searches into many annotation namespaces, e.g. KEGG or NCBI's GenBank.The data and tools we present allow the creation of multiple result sets using a single computation, permitting computational results to be shared between groups for large sequence data sets.
Intestinal Tissues Induce an SNP Mutation in Pseudomonas aeruginosa That Enhances Its Virulence: Possible Role in Anastomotic Leak
Andrea D. Olivas, Benjamin D. Shogan, Vesta Valuckaite, Alexander Zaborin, Natalya Belogortseva, Mark Musch, Folker Meyer, William L.Trimble, Gary An, Jack Gilbert, Olga Zaborina, John C. Alverdy
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0044326
Abstract: The most feared complication following intestinal resection is anastomotic leakage. In high risk areas (esophagus/rectum) where neoadjuvant chemoradiation is used, the incidence of anastomotic leaks remains unacceptably high (~10%) even when performed by specialist surgeons in high volume centers. The aims of this study were to test the hypothesis that anastomotic leakage develops when pathogens colonizing anastomotic sites become in vivo transformed to express a tissue destroying phenotype. We developed a novel model of anastomotic leak in which rats were exposed to pre-operative radiation as in cancer surgery, underwent distal colon resection and then were intestinally inoculated with Pseudomonas aeruginosa, a common colonizer of the radiated intestine. Results demonstrated that intestinal tissues exposed to preoperative radiation developed a significant incidence of anastomotic leak (>60%; p<0.01) when colonized by P. aeruginosa compared to radiated tissues alone (0%). Phenotype analysis comparing the original inoculating strain (MPAO1- termed P1) and the strain retrieved from leaking anastomotic tissues (termed P2) demonstrated that P2 was altered in pyocyanin production and displayed enhanced collagenase activity, high swarming motility, and a destructive phenotype against cultured intestinal epithelial cells (i.e. apoptosis, barrier function, cytolysis). Comparative genotype analysis between P1 and P2 revealed a single nucleotide polymorphism (SNP) mutation in the mexT gene that led to a stop codon resulting in a non-functional truncated protein. Replacement of the mutated mexT gene in P2 with mexT from the original parental strain P1 led to reversion of P2 to the P1 phenotype. No spontaneous transformation was detected during 20 passages in TSB media. Use of a novel virulence suppressing compound PEG/Pi prevented P. aeruginosa transformation to the tissue destructive phenotype and prevented anastomotic leak in rats. This work demonstrates that in vivo transformation of microbial pathogens to a tissue destroying phenotype may have important implications in the pathogenesis of anastomotic leak.
The Biological Observation Matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome
Daniel McDonald, Jose C Clemente, Justin Kuczynski, Jai Rideout, Jesse Stombaugh, Doug Wendel, Andreas Wilke, Susan Huse, John Hufnagle, Folker Meyer, Rob Knight, J Caporaso
GigaScience , 2012, DOI: 10.1186/2047-217x-1-7
Abstract: The BIOM file format is supported by an independent open-source software project (the biom-format project), which initially contains Python objects that support the use and manipulation of BIOM data in Python programs, and is intended to be an open development effort where developers can submit implementations of these objects in other programming languages.The BIOM file format and the biom-format project are steps toward reducing the “bioinformatics bottleneck” that is currently being experienced in diverse areas of biological sciences, and will help us move toward the next phase of comparative omics where basic science is translated into clinical and environmental applications. The BIOM file format is currently recognized as an Earth Microbiome Project Standard, and as a Candidate Standard by the Genomic Standards Consortium.Advances in DNA sequencing have led to exponential increases in the quantity of data available for “comparative omics” analyses, including metagenomics (e.g., [1,2]), comparative genomics (e.g., [3]), metatranscriptomics (e.g., [4,5]), and marker-gene-based community surveys (e.g., [6,7]). With the introduction of a new generation of "benchtop sequencers" [8], accessible to small research, clinical, and educational laboratories, sequence-based comparative omic studies will continue to increase in scale. The rate-limiting step in many areas of comparative omics is no longer obtaining data, but analyzing that data (the “bioinformatics bottleneck”) [9,10]. One mechanism that will help reduce this “bioinformatics bottleneck” is standardization of common file formats to facilitate sharing and archiving of data [11].As with the increasing prevalence of high-throughput technologies in the biological sciences, the categories of comparative omics data, which we collectively term the “ome-ome”, are rapidly increasing in number (Figure 1). Researchers are relying on more types of omics data to investigate biological systems, and the coming years will bri
Predicted Relative Metabolomic Turnover (PRMT): determining metabolic turnover from a coastal marine metagenomic dataset
Peter E Larsen, Frank R Collart, Dawn Field, Folker Meyer, Kevin P Keegan, Christopher S Henry, John McGrath, John Quinn, Jack A Gilbert
Microbial Informatics and Experimentation , 2011, DOI: 10.1186/2042-5783-1-4
Abstract: We propose a methodology, Predicted Relative Metabolic Turnover (PRMT) that defines and enables exploration of metabolite-space inferred from the metagenome. Our analysis of metagenomic data from a time-series study in the Western English Channel demonstrated considerable correlations between predicted relative metabolic turnover and seasonal changes in abundance of measured environmental parameters as well as with observed seasonal changes in bacterial population structure.The PRMT method was successfully applied to metagenomic data to explore the Western English Channel microbial metabalome to generate specific, biologically testable hypotheses. Generated hypotheses linked organic phosphate utilization to Gammaproteobactaria, Plantcomycetes, and Betaproteobacteria, chitin degradation to Actinomycetes, and potential small molecule biosynthesis pathways for Lentisphaerae, Chlamydiae, and Crenarchaeota. The PRMT method can be applied as a general tool for the analysis of additional metagenomic or transcriptomic datasets.Marine biomes dominate the planet's surface and single-celled microorganisms are responsible for up to 98% of the ocean's primary productivity [1]; understanding the nutrient and carbon cycles of the world's oceans has key applications for understanding global ecology. The extremely diverse marine microbial communities mediate the largest active pool of near-surface carbon on the planet [2] and are a dominant force in the planet's biogeochemical cycles [3]. The L4 Station of the Western Channel Observatory (WCO), an oceanographic time-series and marine biodiversity reference site in the Western English Channel http://www.westernchannelobservatory.org.uk webcite, provides a unique opportunity to study a coastal marine microbial ecosystem. Environmental parameter data from the WCO have been continuously monitored for over a century. More recently, microbial metagenomic data collected from this site have shown that the abundance and relative composition
The United States of America and Scientific Research
Gregory J. Hather,Winston Haynes,Roger Higdon,Natali Kolker,Elizabeth A. Stewart,Peter Arzberger,Patrick Chain,Dawn Field,B. Robert Franza,Biaoyang Lin,Folker Meyer,Vural Ozdemir,Charles V. Smith,Gerald van Belle,John Wooley,Eugene Kolker
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0012203
Abstract: To gauge the current commitment to scientific research in the United States of America (US), we compared federal research funding (FRF) with the US gross domestic product (GDP) and industry research spending during the past six decades. In order to address the recent globalization of scientific research, we also focused on four key indicators of research activities: research and development (R&D) funding, total science and engineering doctoral degrees, patents, and scientific publications. We compared these indicators across three major population and economic regions: the US, the European Union (EU) and the People's Republic of China (China) over the past decade. We discovered a number of interesting trends with direct relevance for science policy. The level of US FRF has varied between 0.2% and 0.6% of the GDP during the last six decades. Since the 1960s, the US FRF contribution has fallen from twice that of industrial research funding to roughly equal. Also, in the last two decades, the portion of the US government R&D spending devoted to research has increased. Although well below the US and the EU in overall funding, the current growth rate for R&D funding in China greatly exceeds that of both. Finally, the EU currently produces more science and engineering doctoral graduates and scientific publications than the US in absolute terms, but not per capita. This study's aim is to facilitate a serious discussion of key questions by the research community and federal policy makers. In particular, our results raise two questions with respect to: a) the increasing globalization of science: “What role is the US playing now, and what role will it play in the future of international science?”; and b) the ability to produce beneficial innovations for society: “How will the US continue to foster its strengths?”
Role of primary surgery in advanced ovarian cancer
Karsten Münstedt, Folker E Franke
World Journal of Surgical Oncology , 2004, DOI: 10.1186/1477-7819-2-32
Abstract: We reviewed published reports on primary surgical treatment, surgical expertise, inadequate primary surgery/quality assurance, neoadjuvant chemotherapy, interval debulking, and surgical prognostic factors in advanced ovarian cancer to help resolve outstanding issues.The aim of primary surgery is a well-planned and complete intervention with optimal staging and surgery. Surgical debulking is worthwhile as there are further effective treatments available to control unresectable residual disease. Patients of gynecologic oncology specialist surgeons have better survival rates. This may reflect a working 'culture' rather than better technical skills. One major problem though, is that despite pleas to restrict surgery to experienced surgeons, specialist centers are often left to cope with the results of inadequate primary surgical resections. Patients with primary chemotherapy or those who have had suboptimal debulking may benefit from interval debulking. A proposal for a better classification of residual tumor is given.Optimal surgical interventions have definite role to play in advanced ovarian cancers. Improvements in surgical treatment in the general population will probably improve patients' survival when coupled with improvements in current chemotherapeutic approaches.The Fédération Internationale de Gynécologie et d'Obstétrigue (FIGO) classifies ovarian carcinoma in stage I to IV [1,2]. Stage I has been defined as growth limited to the ovaries; stage II as growth involving one or both ovaries with pelvic extension; stage III as tumor involving one or both ovaries with peritoneal implants, and outside the pelvis and/or positive retroperitoneal or inguinal nodes and stage IV as having distant metastasis [1,2].Tumors in stages I and II are generally considered to represent early disease, while stages III and IV evince late or advanced disease [3,4]. The strong prognostic value of the FIGO classification system has been proved in number of studies [5].Unfortunately, mo
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