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Atasoy M, Scott WT, Regueira A, Mauricio-Iglesias M, Schaap PJ, Smidt H. Biobased short chain fatty acid production - Exploring microbial community dynamics and metabolic networks through kinetic and microbial modeling approaches. Biotechnol Adv 2024; 73:108363. [PMID: 38657743 DOI: 10.1016/j.biotechadv.2024.108363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 04/03/2024] [Accepted: 04/12/2024] [Indexed: 04/26/2024]
Abstract
In recent years, there has been growing interest in harnessing anaerobic digestion technology for resource recovery from waste streams. This approach has evolved beyond its traditional role in energy generation to encompass the production of valuable carboxylic acids, especially volatile fatty acids (VFAs) like acetic acid, propionic acid, and butyric acid. VFAs hold great potential for various industries and biobased applications due to their versatile properties. Despite increasing global demand, over 90% of VFAs are currently produced synthetically from petrochemicals. Realizing the potential of large-scale biobased VFA production from waste streams offers significant eco-friendly opportunities but comes with several key challenges. These include low VFA production yields, unstable acid compositions, complex and expensive purification methods, and post-processing needs. Among these, production yield and acid composition stand out as the most critical obstacles impacting economic viability and competitiveness. This paper seeks to offer a comprehensive view of combining complementary modeling approaches, including kinetic and microbial modeling, to understand the workings of microbial communities and metabolic pathways in VFA production, enhance production efficiency, and regulate acid profiles through the integration of omics and bioreactor data.
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Affiliation(s)
- Merve Atasoy
- UNLOCK, Wageningen University & Research and Delft University of Technology, Wageningen and Delft, the Netherlands; Department of Environmental Technology, Wageningen University & Research, Wageningen, the Netherlands; Laboratory of Microbiology, Wageningen University & Research, Wageningen, the Netherlands.
| | - William T Scott
- UNLOCK, Wageningen University & Research and Delft University of Technology, Wageningen and Delft, the Netherlands; Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, the Netherlands.
| | - Alberte Regueira
- CRETUS, Department of Chemical Engineering, Universidade de Santiago de Compostela, Santiago de Compostela, Spain; Center for Microbial Ecology and Technology (CMET), Ghent University, Ghent, Belgium; Center for Advanced Process Technology for Urban Resource Recovery (CAPTURE), Frieda Saeysstraat 1, Ghent, Belgium.
| | - Miguel Mauricio-Iglesias
- CRETUS, Department of Chemical Engineering, Universidade de Santiago de Compostela, Santiago de Compostela, Spain.
| | - Peter J Schaap
- UNLOCK, Wageningen University & Research and Delft University of Technology, Wageningen and Delft, the Netherlands; Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, the Netherlands.
| | - Hauke Smidt
- UNLOCK, Wageningen University & Research and Delft University of Technology, Wageningen and Delft, the Netherlands; Laboratory of Microbiology, Wageningen University & Research, Wageningen, the Netherlands.
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2
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Halle-Smith JM, Pearce H, Nicol S, Hall LA, Powell-Brett SF, Beggs AD, Iqbal T, Moss P, Roberts KJ. Involvement of the Gut Microbiome in the Local and Systemic Immune Response to Pancreatic Ductal Adenocarcinoma. Cancers (Basel) 2024; 16:996. [PMID: 38473357 DOI: 10.3390/cancers16050996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 02/19/2024] [Accepted: 02/24/2024] [Indexed: 03/14/2024] Open
Abstract
The systemic and local immunosuppression exhibited by pancreatic ductal adenocarcinoma (PDAC) contributes significantly to its aggressive nature. There is a need for a greater understanding of the mechanisms behind this profound immune evasion, which makes it one of the most challenging malignancies to treat and thus one of the leading causes of cancer death worldwide. The gut microbiome is now thought to be the largest immune organ in the body and has been shown to play an important role in multiple immune-mediated diseases. By summarizing the current literature, this review examines the mechanisms by which the gut microbiome may modulate the immune response to PDAC. Evidence suggests that the gut microbiome can alter immune cell populations both in the peripheral blood and within the tumour itself in PDAC patients. In addition, evidence suggests that the gut microbiome influences the composition of the PDAC tumour microbiome, which exerts a local effect on PDAC tumour immune infiltration. Put together, this promotes the gut microbiome as a promising route for future therapies to improve immune responses in PDAC patients.
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Affiliation(s)
- James M Halle-Smith
- Hepatobiliary and Pancreatic Surgery Unit, Queen Elizabeth Hospital Birmingham, Birmingham B15 2GW, UK
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham B15 2TT, UK
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham B15 2TT, UK
| | - Hayden Pearce
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham B15 2TT, UK
| | - Samantha Nicol
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham B15 2TT, UK
| | - Lewis A Hall
- Hepatobiliary and Pancreatic Surgery Unit, Queen Elizabeth Hospital Birmingham, Birmingham B15 2GW, UK
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham B15 2TT, UK
| | - Sarah F Powell-Brett
- Hepatobiliary and Pancreatic Surgery Unit, Queen Elizabeth Hospital Birmingham, Birmingham B15 2GW, UK
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham B15 2TT, UK
| | - Andrew D Beggs
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham B15 2TT, UK
| | - Tariq Iqbal
- Department of Gastroenterology, Queen Elizabeth Hospital Birmingham, Birmingham B15 2GW, UK
- Microbiome Treatment Centre, University of Birmingham, Birmingham B15 2TT, UK
- National Institute for Health Research Birmingham Biomedical Research Centre, Birmingham B15 2TT, UK
| | - Paul Moss
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham B15 2TT, UK
| | - Keith J Roberts
- Hepatobiliary and Pancreatic Surgery Unit, Queen Elizabeth Hospital Birmingham, Birmingham B15 2GW, UK
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham B15 2TT, UK
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3
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Halle-Smith JM, Hall LA, Powell-Brett SF, Merali N, Frampton AE, Beggs AD, Moss P, Roberts KJ. Pancreatic Exocrine Insufficiency and the Gut Microbiome in Pancreatic Cancer: A Target for Future Diagnostic Tests and Therapies? Cancers (Basel) 2023; 15:5140. [PMID: 37958314 PMCID: PMC10649877 DOI: 10.3390/cancers15215140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 10/18/2023] [Accepted: 10/20/2023] [Indexed: 11/15/2023] Open
Abstract
Pancreatic exocrine insufficiency (PEI) is common amongst pancreatic cancer patients and is associated with poorer treatment outcomes. Pancreatic enzyme replacement therapy (PERT) is known to improve outcomes in pancreatic cancer, but the mechanisms are not fully understood. The aim of this narrative literature review is to summarise the current evidence linking PEI with microbiome dysbiosis, assess how microbiome composition may be impacted by PERT treatment, and look towards possible future diagnostic and therapeutic targets in this area. Early evidence in the literature reveals that there are complex mechanisms by which pancreatic secretions modulate the gut microbiome, so when these are disturbed, as in PEI, gut microbiome dysbiosis occurs. PERT has been shown to return the gut microbiome towards normal, so called rebiosis, in animal studies. Gut microbiome dysbiosis has multiple downstream effects in pancreatic cancer such as modulation of the immune response and the response to chemotherapeutic agents. It therefore represents a possible future target for future therapies. In conclusion, it is likely that the gut microbiome of pancreatic cancer patients with PEI exhibits dysbiosis and that this may potentially be reversible with PERT. However, further human studies are required to determine if this is indeed the case.
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Affiliation(s)
- James M. Halle-Smith
- Hepatobiliary and Pancreatic Surgery Unit, Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham NHS Foundation Trust, Birmingham B15 2GW, UK (K.J.R.)
- Cancer and Genomic Sciences, University of Birmingham, Birmingham B15 2GW, UK;
| | - Lewis A. Hall
- Hepatobiliary and Pancreatic Surgery Unit, Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham NHS Foundation Trust, Birmingham B15 2GW, UK (K.J.R.)
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham B15 2TT, UK
| | - Sarah F. Powell-Brett
- Hepatobiliary and Pancreatic Surgery Unit, Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham NHS Foundation Trust, Birmingham B15 2GW, UK (K.J.R.)
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham B15 2TT, UK
| | - Nabeel Merali
- Section of Oncology, Department of Clinical & Experimental Medicine, University of Surrey, Guildford GU2 7WG, UK (A.E.F.); (P.M.)
- Minimal Access Therapy Training Unit (MATTU), Leggett Building, University of Surrey, Guildford GU2 7WG, UK
- Department of Hepato-Pancreato-Biliary (HPB) Surgery, Royal Surrey County Hospital, Egerton Road, Guildford GU2 7XX, UK
| | - Adam E. Frampton
- Section of Oncology, Department of Clinical & Experimental Medicine, University of Surrey, Guildford GU2 7WG, UK (A.E.F.); (P.M.)
- Minimal Access Therapy Training Unit (MATTU), Leggett Building, University of Surrey, Guildford GU2 7WG, UK
- Department of Hepato-Pancreato-Biliary (HPB) Surgery, Royal Surrey County Hospital, Egerton Road, Guildford GU2 7XX, UK
| | - Andrew D. Beggs
- Cancer and Genomic Sciences, University of Birmingham, Birmingham B15 2GW, UK;
- Colorectal Surgery Department, Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham NHS Foundation Trust, Birmingham B15 2GW, UK
| | - Paul Moss
- Section of Oncology, Department of Clinical & Experimental Medicine, University of Surrey, Guildford GU2 7WG, UK (A.E.F.); (P.M.)
| | - Keith J. Roberts
- Hepatobiliary and Pancreatic Surgery Unit, Queen Elizabeth Hospital Birmingham, University Hospitals Birmingham NHS Foundation Trust, Birmingham B15 2GW, UK (K.J.R.)
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham B15 2TT, UK
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4
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Seshadri R, Roux S, Huber KJ, Wu D, Yu S, Udwary D, Call L, Nayfach S, Hahnke RL, Pukall R, White JR, Varghese NJ, Webb C, Palaniappan K, Reimer LC, Sardà J, Bertsch J, Mukherjee S, Reddy T, Hajek PP, Huntemann M, Chen IMA, Spunde A, Clum A, Shapiro N, Wu ZY, Zhao Z, Zhou Y, Evtushenko L, Thijs S, Stevens V, Eloe-Fadrosh EA, Mouncey NJ, Yoshikuni Y, Whitman WB, Klenk HP, Woyke T, Göker M, Kyrpides NC, Ivanova NN. Expanding the genomic encyclopedia of Actinobacteria with 824 isolate reference genomes. CELL GENOMICS 2022; 2:100213. [PMID: 36778052 PMCID: PMC9903846 DOI: 10.1016/j.xgen.2022.100213] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 07/19/2022] [Accepted: 10/16/2022] [Indexed: 11/13/2022]
Abstract
The phylum Actinobacteria includes important human pathogens like Mycobacterium tuberculosis and Corynebacterium diphtheriae and renowned producers of secondary metabolites of commercial interest, yet only a small part of its diversity is represented by sequenced genomes. Here, we present 824 actinobacterial isolate genomes in the context of a phylum-wide analysis of 6,700 genomes including public isolates and metagenome-assembled genomes (MAGs). We estimate that only 30%-50% of projected actinobacterial phylogenetic diversity possesses genomic representation via isolates and MAGs. A comparison of gene functions reveals novel determinants of host-microbe interaction as well as environment-specific adaptations such as potential antimicrobial peptides. We identify plasmids and prophages across isolates and uncover extensive prophage diversity structured mainly by host taxonomy. Analysis of >80,000 biosynthetic gene clusters reveals that horizontal gene transfer and gene loss shape secondary metabolite repertoire across taxa. Our observations illustrate the essential role of and need for high-quality isolate genome sequences.
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Affiliation(s)
- Rekha Seshadri
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA,Corresponding author
| | - Simon Roux
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA
| | - Katharina J. Huber
- Leibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany
| | - Dongying Wu
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA
| | - Sora Yu
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Dan Udwary
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA,Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Lee Call
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA
| | - Stephen Nayfach
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA
| | - Richard L. Hahnke
- Leibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany
| | - Rüdiger Pukall
- Leibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany
| | | | - Neha J. Varghese
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA
| | - Cody Webb
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA
| | | | - Lorenz C. Reimer
- Leibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany
| | - Joaquim Sardà
- Leibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany
| | - Jonathon Bertsch
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA
| | | | - T.B.K. Reddy
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA
| | - Patrick P. Hajek
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA
| | - Marcel Huntemann
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA
| | - I-Min A. Chen
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA
| | - Alex Spunde
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA
| | - Alicia Clum
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA
| | - Nicole Shapiro
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA
| | - Zong-Yen Wu
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Zhiying Zhao
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA
| | - Yuguang Zhou
- China General Microbiological Culture Collection Center, Beijing, China
| | - Lyudmila Evtushenko
- Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences, All-Russian Collection of Microorganisms (VKM), Pushchino, Russia
| | - Sofie Thijs
- Center for Environmental Sciences, Environmental Biology, Hasselt University, Diepenbeek, Belgium
| | - Vincent Stevens
- Center for Environmental Sciences, Environmental Biology, Hasselt University, Diepenbeek, Belgium
| | - Emiley A. Eloe-Fadrosh
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA,Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Nigel J. Mouncey
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA,Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Yasuo Yoshikuni
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA,Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA,Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA,Center for Advanced Bioenergy and Bioproducts Innovation, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA,Global Institution for Collaborative Research and Education, Hokkaido University, Hokkaido 060-8589, Japan
| | | | - Hans-Peter Klenk
- School of Biology, Newcastle University, Newcastle upon Tyne, UK
| | - Tanja Woyke
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA,Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Markus Göker
- Leibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany,Corresponding author
| | - Nikos C. Kyrpides
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA,Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Natalia N. Ivanova
- US Department of Energy Joint Genome Institute, Berkeley, CA, USA,Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA,Corresponding author
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5
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Abstract
Shewanella baltica was the dominant culturable nitrate-reducing bacterium in the eutrophic and strongly stratified Baltic Sea in the 1980s, where it primarily inhabited the oxic-anoxic transition zone. The genomic structures of 46 of these isolates were investigated through comparative genomic hybridization (CGH), which revealed a gradient of genomic similarity, ranging from 65% to as high as 99%. The core genome of the S. baltica species was enriched in anaerobic respiration-associated genes. Auxiliary genes, most of which locate within a few genomic islands (GIs), were nonuniformly distributed among the isolates. Specifically, hypothetical and mobile genetic element (MGE)-associated genes dominated intraclade gene content differences, whereas gain/loss of functional genes drove gene content differences among less related strains. Among the major S. baltica clades, gene signatures related to specific redox-driven and spatial niches within the water column were identified. For instance, genes involved in anaerobic respiration of sulfur compounds may provide key adaptive advantages for clade A strains in anoxic waters where sulfur-containing electron acceptors are present. Genes involved in cell motility, in particular, a secondary flagellar biosynthesis system, may be associated with the free-living lifestyle by clade E strains. Collectively, this study revealed characteristics of genome variations present in the water column and active speciation of S. baltica strains, driven by niche partitioning and horizontal gene transfer (HGT).IMPORTANCE Speciation in nature is a fundamental process driving the formation of the vast microbial diversity on Earth. In the central Baltic Sea, the long-term stratification of water led to formation of a large-scale vertical redoxcline that provided a gradient of environmental niches with respect to the availability of electron acceptors and donors. The region was home to Shewanella baltica populations, which composed the dominant culturable nitrate-reducing bacteria, particularly in the oxic-anoxic transition zone. Using the collection of S. baltica isolates as a model system, genomic variations showed contrasting gene-sharing patterns within versus among S. baltica clades and revealed genomic signatures of S. baltica clades related to redox niche specialization as well as particle association. This study provides important insights into genomic mechanisms underlying bacterial speciation within this unique natural redoxcline.
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6
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Dey D. Space Microbiology: Modern Research and Advantages for Human Colonization on Mars. ACTA ACUST UNITED AC 2019. [DOI: 10.31033/ijrasb.6.4.2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
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7
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Griesemer M, Kimbrel JA, Zhou CE, Navid A, D'haeseleer P. Combining multiple functional annotation tools increases coverage of metabolic annotation. BMC Genomics 2018; 19:948. [PMID: 30567498 PMCID: PMC6299973 DOI: 10.1186/s12864-018-5221-9] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Accepted: 11/05/2018] [Indexed: 12/15/2022] Open
Abstract
Background Genome-scale metabolic modeling is a cornerstone of systems biology analysis of microbial organisms and communities, yet these genome-scale modeling efforts are invariably based on incomplete functional annotations. Annotated genomes typically contain 30–50% of genes without functional annotation, severely limiting our knowledge of the “parts lists” that the organisms have at their disposal. These incomplete annotations may be sufficient to derive a model of a core set of well-studied metabolic pathways that support growth in pure culture. However, pathways important for growth on unusual metabolites exchanged in complex microbial communities are often less understood, resulting in missing functional annotations in newly sequenced genomes. Results Here, we present results on a comprehensive reannotation of 27 bacterial reference genomes, focusing on enzymes with EC numbers annotated by KEGG, RAST, EFICAz, and the BRENDA enzyme database, and on membrane transport annotations by TransportDB, KEGG and RAST. Our analysis shows that annotation using multiple tools can result in a drastically larger metabolic network reconstruction, adding on average 40% more EC numbers, 3–8 times more substrate-specific transporters, and 37% more metabolic genes. These results are even more pronounced for bacterial species that are phylogenetically distant from well-studied model organisms such as E. coli. Conclusions Metabolic annotations are often incomplete and inconsistent. Combining multiple functional annotation tools can greatly improve genome coverage and metabolic network size, especially for non-model organisms and non-core pathways. Electronic supplementary material The online version of this article (10.1186/s12864-018-5221-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Marc Griesemer
- Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA, 94551, USA
| | - Jeffrey A Kimbrel
- Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA, 94551, USA
| | - Carol E Zhou
- Global Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, CA, 94551, USA
| | - Ali Navid
- Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA, 94551, USA
| | - Patrik D'haeseleer
- Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA, 94551, USA. .,Global Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, CA, 94551, USA.
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8
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Marks PC, Bigler M, Alsop EB, Vigneron A, Lomans BP, De Paula R, Geissler B, Tsesmetzis N. MetaHCR: a web-enabled metagenome data management system for hydrocarbon resources. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2018; 2018:1-10. [PMID: 30212909 PMCID: PMC6146120 DOI: 10.1093/database/bay087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/11/2018] [Accepted: 07/24/2018] [Indexed: 11/16/2022]
Abstract
The ever-increasing metagenomic data necessitate appropriate cataloguing in a way that facilitates the comparison and better contextualization of the underlying investigations. To this extent, information associated with the sequencing data as well as the original sample and the environment where it was obtained from is crucial. To date, there are not any publicly available repositories able to capture environmental metadata pertaining to hydrocarbon-rich environments. As such, contextualization and comparative analysis among sequencing datasets derived from these environments is to a certain degree hindered or cannot be fully evaluated. The metagenomics data management system for hydrocarbon resources (MetaHCRs) enables the capturing of marker gene and whole metagenome sequencing data as well as over 300 contextual attributes associated with samples, organisms, environments and geological properties, among others. Moreover, MetaHCR implements the Minimum Information about any Sequence–hydrocarbon resource specification from the Genomic Standards Consortium; it integrates a user-friendly web interface and relational database model, and it enables the generation of complex custom search. MetaHCR has been tested with 36 publicly available metagenomic studies, and its modular architecture can be easily customized for other types of environmental and metagenomics studies.
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Affiliation(s)
- Peter C Marks
- Shell International Exploration and Production Inc., Houston, USA
| | - Marc Bigler
- Ecole Supérieure de Biotechnologie Strasbourg, Illkirch-Graffenstaden, France
| | - Eric B Alsop
- Shell International Exploration and Production Inc., Houston, USA.,DOE Joint Genome Institute,Walnut Creek, California, USA
| | - Adrien Vigneron
- Shell International Exploration and Production Inc., Houston, USA.,School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Bart P Lomans
- Shell Global Solutions International B.V., HW Amsterdam, Netherlands
| | | | - Brett Geissler
- RD & E Microbiology Group, NALCO Champion, Sugar Land, USA
| | - Nicolas Tsesmetzis
- Shell International Exploration and Production Inc., Houston, USA.,School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, UK
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9
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Kyrpides NC, Eloe-Fadrosh EA, Ivanova NN. Microbiome Data Science: Understanding Our Microbial Planet. Trends Microbiol 2017; 24:425-427. [PMID: 27197692 DOI: 10.1016/j.tim.2016.02.011] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2016] [Revised: 02/09/2016] [Accepted: 02/19/2016] [Indexed: 10/21/2022]
Abstract
Microbiology is experiencing a revolution brought on by recent developments in sequencing technology. The unprecedented volume of microbiome data being generated poses significant challenges that are currently hindering progress in the field. Here, we outline the major bottlenecks and propose a vision to advance microbiome research as a data-driven science.
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Affiliation(s)
- Nikos C Kyrpides
- Prokaryotic Super Program, Department of Energy Joint Genome Institute, Walnut Creek, CA, USA.
| | - Emiley A Eloe-Fadrosh
- Prokaryotic Super Program, Department of Energy Joint Genome Institute, Walnut Creek, CA, USA
| | - Natalia N Ivanova
- Prokaryotic Super Program, Department of Energy Joint Genome Institute, Walnut Creek, CA, USA
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10
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1,003 reference genomes of bacterial and archaeal isolates expand coverage of the tree of life. Nat Biotechnol 2017; 35:676-683. [DOI: 10.1038/nbt.3886] [Citation(s) in RCA: 179] [Impact Index Per Article: 25.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Accepted: 04/21/2017] [Indexed: 12/16/2022]
Abstract
Abstract
We present 1,003 reference genomes that were sequenced as part of the Genomic Encyclopedia of Bacteria and Archaea (GEBA) initiative, selected to maximize sequence coverage of phylogenetic space. These genomes double the number of existing type strains and expand their overall phylogenetic diversity by 25%. Comparative analyses with previously available finished and draft genomes reveal a 10.5% increase in novel protein families as a function of phylogenetic diversity. The GEBA genomes recruit 25 million previously unassigned metagenomic proteins from 4,650 samples, improving their phylogenetic and functional interpretation. We identify numerous biosynthetic clusters and experimentally validate a divergent phenazine cluster with potential new chemical structure and antimicrobial activity. This Resource is the largest single release of reference genomes to date. Bacterial and archaeal isolate sequence space is still far from saturated, and future endeavors in this direction will continue to be a valuable resource for scientific discovery.
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11
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Speda J, Jonsson BH, Carlsson U, Karlsson M. Metaproteomics-guided selection of targeted enzymes for bioprospecting of mixed microbial communities. BIOTECHNOLOGY FOR BIOFUELS 2017; 10:128. [PMID: 28523076 PMCID: PMC5434538 DOI: 10.1186/s13068-017-0815-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2017] [Accepted: 05/08/2017] [Indexed: 05/25/2023]
Abstract
BACKGROUND Hitherto, the main goal of metaproteomic analyses has been to characterize the functional role of particular microorganisms in the microbial ecology of various microbial communities. Recently, it has been suggested that metaproteomics could be used for bioprospecting microbial communities to query for the most active enzymes to improve the selection process of industrially relevant enzymes. In the present study, to reduce the complexity of metaproteomic samples for targeted bioprospecting of novel enzymes, a microbial community capable of producing cellulases was maintained on a chemically defined medium in an enzyme suppressed metabolic steady state. From this state, it was possible to specifically and distinctively induce the desired cellulolytic activity. The extracellular fraction of the protein complement of the induced sample could thereby be purified and compared to a non-induced sample of the same community by differential gel electrophoresis to discriminate between constitutively expressed proteins and proteins upregulated in response to the inducing substance. RESULTS Using the applied approach, downstream analysis by mass spectrometry could be limited to only proteins recognized as upregulated in the cellulase-induced sample. Of 39 selected proteins, the majority were found to be linked to the need to degrade, take up, and metabolize cellulose. In addition, 28 (72%) of the proteins were non-cytosolic and 17 (44%) were annotated as carbohydrate-active enzymes. The results demonstrated both the applicability of the proposed approach for identifying extracellular proteins and guiding the selection of proteins toward those specifically upregulated and targeted by the enzyme inducing substance. Further, because identification of interesting proteins was based on the regulation of enzyme expression in response to a need to hydrolyze and utilize a specific substance, other unexpected enzyme activities were able to be identified. CONCLUSIONS The described approach created the conditions necessary to be able to select relevant extracellular enzymes that were extracted from the enzyme-induced microbial community. However, for the purpose of bioprospecting for enzymes to clone, produce, and characterize for practical applications, it was concluded that identification against public databases was not sufficient to identify the correct gene or protein sequence for cloning of the identified novel enzymes.
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Affiliation(s)
- Jutta Speda
- Molecular Biotechnology, Dept. of Physics, Chemistry and Biology, Linköping University, 581 83 Linköping, Sweden
| | - Bengt-Harald Jonsson
- Molecular Biotechnology, Dept. of Physics, Chemistry and Biology, Linköping University, 581 83 Linköping, Sweden
| | - Uno Carlsson
- Biochemistry, Dept. of Physics, Chemistry and Biology, Linköping University, 58183 Linköping, Sweden
| | - Martin Karlsson
- Molecular Biotechnology, Dept. of Physics, Chemistry and Biology, Linköping University, 581 83 Linköping, Sweden
- InZymes Biotech AB, Gjuterigatan 1B, 582 73 Linköping, Sweden
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Salter B, Salter C. Controlling new knowledge: Genomic science, governance and the politics of bioinformatics. SOCIAL STUDIES OF SCIENCE 2017; 47:263-287. [PMID: 28056721 PMCID: PMC5405805 DOI: 10.1177/0306312716681210] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
The rise of bioinformatics is a direct response to the political difficulties faced by genomics in its quest to be a new biomedical innovation, and the value of bioinformatics lies in its role as the bridge between the promise of genomics and its realization in the form of health benefits. Western scientific elites are able to use their close relationship with the state to control and facilitate the emergence of new domains compatible with the existing distribution of epistemic power - all within the embrace of public trust. The incorporation of bioinformatics as the saviour of genomics had to be integrated with the operation of two key aspects of governance in this field: the definition and ownership of the new knowledge. This was achieved mainly by the development of common standards and by the promotion of the values of communality, open access and the public ownership of data to legitimize and maintain the governance power of publicly funded genomic science. Opposition from industry advocating the private ownership of knowledge has been largely neutered through the institutions supporting the science-state concordat. However, in order for translation into health benefits to occur and public trust to be assured, genomic and clinical data have to be integrated and knowledge ownership agreed upon across the separate and distinct governance territories of scientist, clinical medicine and society. Tensions abound as science seeks ways of maintaining its control of knowledge production through the negotiation of new forms of governance with the institutions and values of clinicians and patients.
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Affiliation(s)
- Brian Salter
- Brian Salter, Department of Political Economy, King’s College London, Strand, London WC2R 2LS, UK.
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14
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Chen IMA, Markowitz VM, Palaniappan K, Szeto E, Chu K, Huang J, Ratner A, Pillay M, Hadjithomas M, Huntemann M, Mikhailova N, Ovchinnikova G, Ivanova NN, Kyrpides NC. Supporting community annotation and user collaboration in the integrated microbial genomes (IMG) system. BMC Genomics 2016; 17:307. [PMID: 27118214 PMCID: PMC4847265 DOI: 10.1186/s12864-016-2629-y] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Accepted: 04/16/2016] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND The exponential growth of genomic data from next generation technologies renders traditional manual expert curation effort unsustainable. Many genomic systems have included community annotation tools to address the problem. Most of these systems adopted a "Wiki-based" approach to take advantage of existing wiki technologies, but encountered obstacles in issues such as usability, authorship recognition, information reliability and incentive for community participation. RESULTS Here, we present a different approach, relying on tightly integrated method rather than "Wiki-based" method, to support community annotation and user collaboration in the Integrated Microbial Genomes (IMG) system. The IMG approach allows users to use existing IMG data warehouse and analysis tools to add gene, pathway and biosynthetic cluster annotations, to analyze/reorganize contigs, genes and functions using workspace datasets, and to share private user annotations and workspace datasets with collaborators. We show that the annotation effort using IMG can be part of the research process to overcome the user incentive and authorship recognition problems thus fostering collaboration among domain experts. The usability and reliability issues are addressed by the integration of curated information and analysis tools in IMG, together with DOE Joint Genome Institute (JGI) expert review. CONCLUSION By incorporating annotation operations into IMG, we provide an integrated environment for users to perform deeper and extended data analysis and annotation in a single system that can lead to publications and community knowledge sharing as shown in the case studies.
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Affiliation(s)
- I-Min A Chen
- Biosciences Computing, Computational Research Division, Lawrence Berkeley, National Laboratory, Berkeley, California, USA.
| | - Victor M Markowitz
- Biosciences Computing, Computational Research Division, Lawrence Berkeley, National Laboratory, Berkeley, California, USA
| | - Krishna Palaniappan
- Biosciences Computing, Computational Research Division, Lawrence Berkeley, National Laboratory, Berkeley, California, USA
| | - Ernest Szeto
- Biosciences Computing, Computational Research Division, Lawrence Berkeley, National Laboratory, Berkeley, California, USA
| | - Ken Chu
- Biosciences Computing, Computational Research Division, Lawrence Berkeley, National Laboratory, Berkeley, California, USA
| | - Jinghua Huang
- Biosciences Computing, Computational Research Division, Lawrence Berkeley, National Laboratory, Berkeley, California, USA
| | - Anna Ratner
- Biosciences Computing, Computational Research Division, Lawrence Berkeley, National Laboratory, Berkeley, California, USA
| | - Manoj Pillay
- Biosciences Computing, Computational Research Division, Lawrence Berkeley, National Laboratory, Berkeley, California, USA
| | - Michalis Hadjithomas
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, California, USA
| | - Marcel Huntemann
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, California, USA
| | - Natalia Mikhailova
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, California, USA
| | - Galina Ovchinnikova
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, California, USA
| | - Natalia N Ivanova
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, California, USA
| | - Nikos C Kyrpides
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, California, USA
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Liu S, Kulinich A, Cai ZP, Ma HY, Du YM, Lv YM, Liu L, Voglmeir J. The fucosidase-pool ofEmticicia oligotrophica: Biochemical characterization and transfucosylation potential. Glycobiology 2016; 26:871-879. [DOI: 10.1093/glycob/cww030] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2015] [Accepted: 02/29/2016] [Indexed: 11/14/2022] Open
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Abstract
Bacteria occur ubiquitously in nature and are broadly relevant throughout the food supply chain, with diverse and variable tolerance levels depending on their origin, biological role, and impact on the quality and safety of the product as well as on the health of the consumer. With increasing knowledge of and accessibility to the microbial composition of our environments, food supply, and host-associated microbiota, our understanding of and appreciation for the ratio of beneficial to undesirable bacteria are rapidly evolving. Therefore, there is a need for tools and technologies that allow definite, accurate, and high-resolution identification and typing of various groups of bacteria that include beneficial microbes such as starter cultures and probiotics, innocuous commensals, and undesirable pathogens and spoilage organisms. During the transition from the current molecular biology-based PFGE (pulsed-field gel electrophoresis) gold standard to the increasingly accessible omics-level whole-genome sequencing (WGS) N-gen standard, high-resolution technologies such as CRISPR-based genotyping constitute practical and powerful alternatives that provide valuable insights into genome microevolution and evolutionary trajectories. Indeed, several studies have shown potential for CRISPR-based typing of industrial starter cultures, health-promoting probiotic strains, animal commensal species, and problematic pathogens. Emerging CRISPR-based typing methods open new avenues for high-resolution typing of a broad range of bacteria and constitute a practical means for rapid tracking of a diversity of food-associated microbes.
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Affiliation(s)
- Rodolphe Barrangou
- Department of Food, Bioprocessing and Nutrition Sciences, North Carolina State University, Raleigh, North Carolina 27695; .,Department of Food Science, The Pennsylvania State University, University Park, Pennsylvania 16802;
| | - Edward G Dudley
- Department of Food Science, The Pennsylvania State University, University Park, Pennsylvania 16802;
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17
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Wang J, Wu G, Chen L, Zhang W. Integrated Analysis of Transcriptomic and Proteomic Datasets Reveals Information on Protein Expressivity and Factors Affecting Translational Efficiency. Methods Mol Biol 2016; 1375:123-136. [PMID: 25762301 DOI: 10.1007/7651_2015_242] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Integrated analysis of large-scale transcriptomic and proteomic data can provide important insights into the metabolic mechanisms underlying complex biological systems. In this chapter, we present methods to address two aspects of issues related to integrated transcriptomic and proteomic analysis. First, due to the fact that proteomic datasets are often incomplete, and integrated analysis of partial proteomic data may introduce significant bias. To address these issues, we describe a zero-inflated Poisson (ZIP)-based model to uncover the complicated relationships between protein abundances and mRNA expression levels, and then apply them to predict protein abundance for the proteins not experimentally detected. The ZIP model takes into consideration the undetected proteins by assuming that there is a probability mass at zero representing expressed proteins that were undetected owing to technical limitations. The model validity is demonstrated using biological information of operons, regulons, and pathways. Second, weak correlation between transcriptomic and proteomic datasets is often due to biological factors affecting translational processes. To quantify the effects of these factors, we describe a multiple regression-based statistical framework to quantitatively examine the effects of various translational efficiency-related sequence features on mRNA-protein correlation. Using the datasets from sulfate-reducing bacteria Desulfovibrio vulgaris, the analysis shows that translation-related sequence features can contribute up to 15.2-26.2% of the total variation of the correlation between transcriptomic and proteomic datasets, and also reveals the relative importance of various features in translation process.
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Affiliation(s)
- Jiangxin Wang
- Laboratory of Synthetic Microbiology, School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, People's Republic of China
- Key Laboratory of Systems Bioengineering, Ministry of Education of China, Tianjin, 300072, People's Republic of China
- Collaborative Innovation Center of Chemical Science and Engineering, Tianjin, People's Republic of China
| | - Gang Wu
- University of Maryland at Baltimore Country, Baltimore County, MD, USA
| | - Lei Chen
- Laboratory of Synthetic Microbiology, School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, People's Republic of China
- Key Laboratory of Systems Bioengineering, Ministry of Education of China, Tianjin, 300072, People's Republic of China
- Collaborative Innovation Center of Chemical Science and Engineering, Tianjin, People's Republic of China
| | - Weiwen Zhang
- Laboratory of Synthetic Microbiology, School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, People's Republic of China.
- Key Laboratory of Systems Bioengineering, Ministry of Education of China, Tianjin, 300072, People's Republic of China.
- Collaborative Innovation Center of Chemical Science and Engineering, Tianjin, People's Republic of China.
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18
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Tuorto SJ, Brown CM, Bidle KD, McGuinness LR, Kerkhof LJ. BioDry: An Inexpensive, Low-Power Method to Preserve Aquatic Microbial Biomass at Room Temperature. PLoS One 2015; 10:e0144686. [PMID: 26710122 PMCID: PMC4692454 DOI: 10.1371/journal.pone.0144686] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2014] [Accepted: 11/23/2015] [Indexed: 02/01/2023] Open
Abstract
This report describes BioDry (patent pending), a method for reliably preserving the biomolecules associated with aquatic microbial biomass samples, without the need of hazardous materials (e.g. liquid nitrogen, preservatives, etc.), freezing, or bulky storage/sampling equipment. Gel electrophoresis analysis of nucleic acid extracts from samples treated in the lab with the BioDry method indicated that molecular integrity was protected in samples stored at room temperature for up to 30 days. Analysis of 16S/18S rRNA genes for presence/absence and relative abundance of microorganisms using both 454-pyrosequencing and TRFLP profiling revealed statistically indistinguishable communities from control samples that were frozen in liquid nitrogen immediately after collection. Seawater and river water biomass samples collected with a portable BioDry “field unit", constructed from off-the-shelf materials and a battery-operated pumping system, also displayed high levels of community rRNA preservation, despite a slight decrease in nucleic acid recovery over the course of storage for 30 days. Functional mRNA and protein pools from the field samples were also effectively conserved with BioDry, as assessed by respective RT-PCR amplification and western blot of ribulose-1-5-bisphosphate carboxylase/oxygenase. Collectively, these results demonstrate that BioDry can adequately preserve a suite of biomolecules from aquatic biomass at ambient temperatures for up to a month, giving it great potential for high resolution sampling in remote locations or on autonomous platforms where space and power are limited.
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Affiliation(s)
- Steven J. Tuorto
- Department of Marine and Coastal Science, Rutgers University, New Brunswick, New Jersey, United States of America
| | - Chris M. Brown
- Environmental Proteomics N.B. Inc, Sackville, New Brunswick, Canada
| | - Kay D. Bidle
- Department of Marine and Coastal Science, Rutgers University, New Brunswick, New Jersey, United States of America
| | - Lora R. McGuinness
- Department of Marine and Coastal Science, Rutgers University, New Brunswick, New Jersey, United States of America
| | - Lee J. Kerkhof
- Department of Marine and Coastal Science, Rutgers University, New Brunswick, New Jersey, United States of America
- * E-mail:
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Markowitz VM, Chen IMA, Chu K, Pati A, Ivanova NN, Kyrpides NC. Ten Years of Maintaining and Expanding a Microbial Genome and Metagenome Analysis System. Trends Microbiol 2015; 23:730-741. [DOI: 10.1016/j.tim.2015.07.012] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2015] [Revised: 07/15/2015] [Accepted: 07/31/2015] [Indexed: 10/22/2022]
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20
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Punina NV, Makridakis NM, Remnev MA, Topunov AF. Whole-genome sequencing targets drug-resistant bacterial infections. Hum Genomics 2015; 9:19. [PMID: 26243131 PMCID: PMC4525730 DOI: 10.1186/s40246-015-0037-z] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2015] [Accepted: 07/03/2015] [Indexed: 01/07/2023] Open
Abstract
During the past two decades, the technological progress of whole-genome sequencing (WGS) had changed the fields of Environmental Microbiology and Biotechnology, and, currently, is changing the underlying principles, approaches, and fundamentals of Public Health, Epidemiology, Health Economics, and national productivity. Today’s WGS technologies are able to compete with conventional techniques in cost, speed, accuracy, and resolution for day-to-day control of infectious diseases and outbreaks in clinical laboratories and in long-term epidemiological investigations. WGS gives rise to an exciting future direction for personalized Genomic Epidemiology. One of the most vital and growing public health problems is the emerging and re-emerging of multidrug-resistant (MDR) bacterial infections in the communities and healthcare settings, reinforced by a decline in antimicrobial drug discovery. In recent years, retrospective analysis provided by WGS has had a great impact on the identification and tracking of MDR microorganisms in hospitals and communities. The obtained genomic data are also important for developing novel easy-to-use diagnostic assays for clinics, as well as for antibiotic and therapeutic development at both the personal and population levels. At present, this technology has been successfully applied as an addendum to the real-time diagnostic methods currently used in clinical laboratories. However, the significance of WGS for public health may increase if: (a) unified and user-friendly bioinformatics toolsets for easy data interpretation and management are established, and (b) standards for data validation and verification are developed. Herein, we review the current and future impact of this technology on diagnosis, prevention, treatment, and control of MDR infectious bacteria in clinics and on the global scale.
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Affiliation(s)
- N V Punina
- Bach Institute of Biochemistry, Russian Academy of Science, Moscow, 119071, Russia.
| | - N M Makridakis
- Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, 70112, USA
| | - M A Remnev
- The Federal State Unitary Enterprise All-Russia Research Institute of Automatics, Moscow, 127055, Russia
| | - A F Topunov
- Bach Institute of Biochemistry, Russian Academy of Science, Moscow, 119071, Russia
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21
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Tripp HJ, Sutton G, White O, Wortman J, Pati A, Mikhailova N, Ovchinnikova G, Payne SH, Kyrpides NC, Ivanova N. Toward a standard in structural genome annotation for prokaryotes. Stand Genomic Sci 2015; 10:45. [PMID: 26380633 PMCID: PMC4572445 DOI: 10.1186/s40793-015-0034-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2014] [Accepted: 07/01/2015] [Indexed: 11/17/2022] Open
Abstract
Background In an effort to identify the best practice for finding genes in prokaryotic genomes and propose it as a standard for automated annotation pipelines, 1,004,576 peptides were collected from various publicly available resources, and were used as a basis to evaluate various gene-calling methods. The peptides came from 45 bacterial replicons with an average GC content from 31 % to 74 %, biased toward higher GC content genomes. Automated, manual, and semi-manual methods were used to tally errors in three widely used gene calling methods, as evidenced by peptides mapped outside the boundaries of called genes. Results We found that the consensus set of identical genes predicted by the three methods constitutes only about 70 % of the genes predicted by each individual method (with start and stop required to coincide). Peptide data was useful for evaluating some of the differences between gene callers, but not reliable enough to make the results conclusive, due to limitations inherent in any proteogenomic study. Conclusions A single, unambiguous, unanimous best practice did not emerge from this analysis, since the available proteomics data were not adequate to provide an objective measurement of differences in the accuracy between these methods. However, as a result of this study, software, reference data, and procedures have been better matched among participants, representing a step toward a much-needed standard. In the absence of sufficient amount of exprimental data to achieve a universal standard, our recommendation is that any of these methods can be used by the community, as long as a single method is employed across all datasets to be compared. Electronic supplementary material The online version of this article (doi:10.1186/s40793-015-0034-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- H James Tripp
- DOE Joint Genome Institute, Walnut Creek, California USA
| | | | - Owen White
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD USA
| | | | - Amrita Pati
- DOE Joint Genome Institute, Walnut Creek, California USA
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22
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Varghese NJ, Mukherjee S, Ivanova N, Konstantinidis KT, Mavrommatis K, Kyrpides NC, Pati A. Microbial species delineation using whole genome sequences. Nucleic Acids Res 2015; 43:6761-71. [PMID: 26150420 PMCID: PMC4538840 DOI: 10.1093/nar/gkv657] [Citation(s) in RCA: 474] [Impact Index Per Article: 52.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2014] [Accepted: 06/12/2015] [Indexed: 01/25/2023] Open
Abstract
Increased sequencing of microbial genomes has revealed that prevailing prokaryotic species assignments can be inconsistent with whole genome information for a significant number of species. The long-standing need for a systematic and scalable species assignment technique can be met by the genome-wide Average Nucleotide Identity (gANI) metric, which is widely acknowledged as a robust measure of genomic relatedness. In this work, we demonstrate that the combination of gANI and the alignment fraction (AF) between two genomes accurately reflects their genomic relatedness. We introduce an efficient implementation of AF,gANI and discuss its successful application to 86.5M genome pairs between 13,151 prokaryotic genomes assigned to 3032 species. Subsequently, by comparing the genome clusters obtained from complete linkage clustering of these pairs to existing taxonomy, we observed that nearly 18% of all prokaryotic species suffer from anomalies in species definition. Our results can be used to explore central questions such as whether microorganisms form a continuum of genetic diversity or distinct species represented by distinct genetic signatures. We propose that this precise and objective AF,gANI-based species definition: the MiSI (Microbial Species Identifier) method, be used to address previous inconsistencies in species classification and as the primary guide for new taxonomic species assignment, supplemented by the traditional polyphasic approach, as required.
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Affiliation(s)
- Neha J Varghese
- Microbial and Metagenome Superprogram, DOE Joint Genomic Institute, Walnut Creek, CA 94598, USA
| | - Supratim Mukherjee
- Microbial and Metagenome Superprogram, DOE Joint Genomic Institute, Walnut Creek, CA 94598, USA
| | - Natalia Ivanova
- Microbial and Metagenome Superprogram, DOE Joint Genomic Institute, Walnut Creek, CA 94598, USA
| | | | | | - Nikos C Kyrpides
- Microbial and Metagenome Superprogram, DOE Joint Genomic Institute, Walnut Creek, CA 94598, USA
| | - Amrita Pati
- Microbial and Metagenome Superprogram, DOE Joint Genomic Institute, Walnut Creek, CA 94598, USA
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23
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Whitman WB, Woyke T, Klenk HP, Zhou Y, Lilburn TG, Beck BJ, De Vos P, Vandamme P, Eisen JA, Garrity G, Hugenholtz P, Kyrpides NC. Genomic Encyclopedia of Bacterial and Archaeal Type Strains, Phase III: the genomes of soil and plant-associated and newly described type strains. Stand Genomic Sci 2015; 10:26. [PMID: 26203337 PMCID: PMC4511459 DOI: 10.1186/s40793-015-0017-x] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2015] [Accepted: 04/29/2015] [Indexed: 11/18/2022] Open
Abstract
The Genomic Encyclopedia of Bacteria and Archaea (GEBA) project was launched by the JGI in 2007 as a pilot project to sequence about 250 bacterial and archaeal genomes of elevated phylogenetic diversity. Herein, we propose to extend this approach to type strains of prokaryotes associated with soil or plants and their close relatives as well as type strains from newly described species. Understanding the microbiology of soil and plants is critical to many DOE mission areas, such as biofuel production from biomass, biogeochemistry, and carbon cycling. We are also targeting type strains of novel species while they are being described. Since 2006, about 630 new species have been described per year, many of which are closely aligned to DOE areas of interest in soil, agriculture, degradation of pollutants, biofuel production, biogeochemical transformation, and biodiversity.
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Affiliation(s)
- William B Whitman
- Department of Microbiology, University of Georgia, Athens, GA, Greece
| | - Tanja Woyke
- DOE Joint Genome Institute, Walnut Creek, CA, USA
| | - Hans-Peter Klenk
- School of Biology, Newcastle University, Newcastle upon Tyne, UK
| | - Yuguang Zhou
- China General Microbiological Culture Collection Center (CGMCC), Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
| | - Timothy G Lilburn
- American Type Culture Collection, Manassas, VA, USA
- Current addresses: Novozymes North America Inc., Durham 27709, NC, USA
| | - Brian J Beck
- American Type Culture Collection, Manassas, VA, USA
- Current addresses: Microbiologics, St. Cloud, MN, USA
| | - Paul De Vos
- BCCM/LMG Bacteria Collection and Laboratory of Microbiology, Ghent University, Ghent, Belgium
| | - Peter Vandamme
- BCCM/LMG Bacteria Collection and Laboratory of Microbiology, Ghent University, Ghent, Belgium
| | | | - George Garrity
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA, and NamesforLife, LLC, East Lansing, MI, USA
| | - Philip Hugenholtz
- Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane 4072, QLD, Australia
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Yu JF, Guo J, Liu QB, Hou Y, Xiao K, Chen QL, Wang JH, Sun X. A hybrid strategy for comprehensive annotation of the protein coding genes in prokaryotic genome. Genes Genomics 2015. [DOI: 10.1007/s13258-014-0263-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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25
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Discovery and characterization of a novel extremely acidic bacterial N-glycanase with combined advantages of PNGase F and A. Biosci Rep 2014; 34:e00149. [PMID: 25294009 PMCID: PMC4231336 DOI: 10.1042/bsr20140148] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidases [PNGases (peptide N-glycosidases), N-glycanases, EC 3.5.1.52] are essential tools in the release of N-glycans from glycoproteins. We hereby report the discovery and characterization of a novel bacterial N-glycanase from Terriglobus roseus with an extremely low pH optimum of 2.6, and annotated it therefore as PNGase H+. The gene of PNGase H+ was cloned and the recombinant protein was successfully expressed in Escherichia coli. The recombinant PNGase H+ could liberate high mannose-, hybrid- and complex-type N-glycans including core α1,3-fucosylated oligosaccharides from both glycoproteins and glycopeptides. In addition, PNGase H+ exhibited better release efficiency over N-glycans without core α1,3-fucose compared with PNGase A. The facile expression, non-glycosylated nature, unusual pH optimum and broad substrate specificity of this novel type of N-glycanase makes recombinant PNGase H+ a versatile tool in N-glycan analysis. PNGase H+, from T. roseus was successfully cloned and expressed in E. coli. It shows activity in extremely acidic conditions and can release all types of N-glycans including core α1,3-fucosylated N-glycans from glycoproteins and glycopeptides in high efficiency.
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Reddy TBK, Thomas AD, Stamatis D, Bertsch J, Isbandi M, Jansson J, Mallajosyula J, Pagani I, Lobos EA, Kyrpides NC. The Genomes OnLine Database (GOLD) v.5: a metadata management system based on a four level (meta)genome project classification. Nucleic Acids Res 2014; 43:D1099-106. [PMID: 25348402 DOI: 10.1093/nar/gku950] [Citation(s) in RCA: 259] [Impact Index Per Article: 25.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The Genomes OnLine Database (GOLD; http://www.genomesonline.org) is a comprehensive online resource to catalog and monitor genetic studies worldwide. GOLD provides up-to-date status on complete and ongoing sequencing projects along with a broad array of curated metadata. Here we report version 5 (v.5) of the database. The newly designed database schema and web user interface supports several new features including the implementation of a four level (meta)genome project classification system and a simplified intuitive web interface to access reports and launch search tools. The database currently hosts information for about 19,200 studies, 56,000 Biosamples, 56,000 sequencing projects and 39,400 analysis projects. More than just a catalog of worldwide genome projects, GOLD is a manually curated, quality-controlled metadata warehouse. The problems encountered in integrating disparate and varying quality data into GOLD are briefly highlighted. GOLD fully supports and follows the Genomic Standards Consortium (GSC) Minimum Information standards.
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Affiliation(s)
- T B K Reddy
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, CA 94598, USA
| | - Alex D Thomas
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, CA 94598, USA
| | - Dimitri Stamatis
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, CA 94598, USA
| | - Jon Bertsch
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, CA 94598, USA
| | - Michelle Isbandi
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, CA 94598, USA
| | - Jakob Jansson
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, CA 94598, USA
| | - Jyothi Mallajosyula
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, CA 94598, USA
| | - Ioanna Pagani
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, CA 94598, USA
| | - Elizabeth A Lobos
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, CA 94598, USA
| | - Nikos C Kyrpides
- Prokaryotic Super Program, DOE Joint Genome Institute, Walnut Creek, CA 94598, USA Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
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Kyrpides NC, Hugenholtz P, Eisen JA, Woyke T, Göker M, Parker CT, Amann R, Beck BJ, Chain PSG, Chun J, Colwell RR, Danchin A, Dawyndt P, Dedeurwaerdere T, DeLong EF, Detter JC, De Vos P, Donohue TJ, Dong XZ, Ehrlich DS, Fraser C, Gibbs R, Gilbert J, Gilna P, Glöckner FO, Jansson JK, Keasling JD, Knight R, Labeda D, Lapidus A, Lee JS, Li WJ, MA J, Markowitz V, Moore ERB, Morrison M, Meyer F, Nelson KE, Ohkuma M, Ouzounis CA, Pace N, Parkhill J, Qin N, Rossello-Mora R, Sikorski J, Smith D, Sogin M, Stevens R, Stingl U, Suzuki KI, Taylor D, Tiedje JM, Tindall B, Wagner M, Weinstock G, Weissenbach J, White O, Wang J, Zhang L, Zhou YG, Field D, Whitman WB, Garrity GM, Klenk HP. Genomic encyclopedia of bacteria and archaea: sequencing a myriad of type strains. PLoS Biol 2014; 12:e1001920. [PMID: 25093819 PMCID: PMC4122341 DOI: 10.1371/journal.pbio.1001920] [Citation(s) in RCA: 138] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
This manuscript calls for an international effort to generate a comprehensive catalog from genome sequences of all the archaeal and bacterial type strains. Microbes hold the key to life. They hold the secrets to our past (as the descendants of the earliest forms of life) and the prospects for our future (as we mine their genes for solutions to some of the planet's most pressing problems, from global warming to antibiotic resistance). However, the piecemeal approach that has defined efforts to study microbial genetic diversity for over 20 years and in over 30,000 genome projects risks squandering that promise. These efforts have covered less than 20% of the diversity of the cultured archaeal and bacterial species, which represent just 15% of the overall known prokaryotic diversity. Here we call for the funding of a systematic effort to produce a comprehensive genomic catalog of all cultured Bacteria and Archaea by sequencing, where available, the type strain of each species with a validly published name (currently∼11,000). This effort will provide an unprecedented level of coverage of our planet's genetic diversity, allow for the large-scale discovery of novel genes and functions, and lead to an improved understanding of microbial evolution and function in the environment.
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Affiliation(s)
- Nikos C. Kyrpides
- DOE-Joint Genome Institute, Walnut Creek, California, United States of America
- Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
- * E-mail: (NCK); (HPK)
| | - Philip Hugenholtz
- Australian Centre for Ecogenomics Research, School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia
| | - Jonathan A. Eisen
- University of California, Davis, Davis, California, United States of America
| | - Tanja Woyke
- DOE-Joint Genome Institute, Walnut Creek, California, United States of America
| | - Markus Göker
- DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany
| | | | - Rudolf Amann
- Max Planck Institute for Marine Microbiology, Bremen, Germany
| | - Brian J. Beck
- American Type Culture Collection (ATCC), Manassas, Virginia, United States of America
| | - Patrick S. G. Chain
- Los Alamos National Laboratory, Bioscience Division, Los Alamos, New Mexico, United States of America
| | - Jongsik Chun
- School of Biological Sciences and Chunlab Inc., Seoul National University, Seoul, Korea
| | - Rita R. Colwell
- University of Maryland, College Park, College Park, Maryland, United States of America
- Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America
| | | | - Peter Dawyndt
- Ghent University, Department of Applied Mathematics and Computer Science, Ghent, Belgium
| | - Tom Dedeurwaerdere
- Centre for Philosophy of Law, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Edward F. DeLong
- Department of Civil and Environmental Engineering and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - John C. Detter
- Los Alamos National Laboratory, Bioscience Division, Los Alamos, New Mexico, United States of America
| | - Paul De Vos
- Ghent University, Department of Applied Mathematics and Computer Science, Ghent, Belgium
- Ghent University, BCCM/LMG Bacteria collection, Laboratory of Microbiology, Ghent, Belgium
| | - Timothy J. Donohue
- University of Wisconsin-Madison, Great Lakes Bioenergy Research Center, Madison, Wisconsin, United States of America
| | - Xiu-Zhu Dong
- Bioresource Center (BRC) of Institute of Microbiology, Chinese Academy of Sciences, P. R. China
| | - Dusko S. Ehrlich
- Institut National de la Recherche Agronomique, Jouy en Josas, France
| | - Claire Fraser
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Richard Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, United States of America
| | - Jack Gilbert
- Institute for Genomics and Systems Biology, Argonne National Laboratory, Argonne, Illinois, United States of America
| | - Paul Gilna
- BioEnergy Science Center (BESC), Oak Ridge National Laboratory, Knoxville, Tennessee, United States of America
| | - Frank Oliver Glöckner
- Max Planck Institute for Marine Microbiology, Bremen, Germany
- Jacobs University Bremen gGmbH, Bremen, Germany
| | - Janet K. Jansson
- Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
| | - Jay D. Keasling
- Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
- Joint BioEnergy Institute (JBEI), Berkeley, California, United States of America
| | - Rob Knight
- Howard Hughes Medical Institute and Department of Chemistry and Biochemistry, University of Colorado, Boulder, Colorado, United States of America
| | - David Labeda
- ARS, USDA, National Center for Agricultural Utilization Research, Peoria, Illinois, United States of America
| | - Alla Lapidus
- Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia
- Algorithmic Biology Lab, St. Petersburg Academic University, St. Petersburg, Russia
| | - Jung-Sook Lee
- Korean Collection for Type Cultures (KCTC), Korea Research Institute of Bioscience and Biotechnology (KRIBB), 111 Gwahangno, Yuseong-gu, Daejeon, Korea
| | - Wen-Jun Li
- The Key Laboratory for Microbial Resources of the Ministry of Education, Kunming, People's Republic of China
| | - Juncai MA
- China General Microbiological Culture Collection Center (CGMCC), Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China
| | - Victor Markowitz
- DOE-Joint Genome Institute, Walnut Creek, California, United States of America
- Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
| | - Edward R. B. Moore
- CCUG - Culture Collection University of Gothenburg, Sahlgrenska Academy of the University of Gothenburg, Gothenburg, Sweden
| | - Mark Morrison
- Diamantina Institute, The University of Queensland, St Lucia, Queensland, Australia
| | - Folker Meyer
- Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois, United States of America
| | - Karen E. Nelson
- The J. Craig Venter Institute, Rockville, Maryland, United States of America
| | - Moriya Ohkuma
- Riken Bioresource Center, Japan Collection of Microorganisms, Hirosawa, Wako, Saitama, Japan
| | - Christos A. Ouzounis
- Chemical Process & Energy Resources Institute, Centre for Research & Technology, Thessalonica, Greece
- Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario, Canada
| | - Norman Pace
- Department of Molecular, Cellular and Developmental Biology, University of Colorado, Boulder, Colorado, United States of America
| | - Julian Parkhill
- The Pathogen Genomics, The Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
| | - Nan Qin
- State Key Laboratory for Diagnosis and Treatment of Infectious Disease, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Ramon Rossello-Mora
- Institut Mediterrani d'Estudis Avançats (IMEDEA, CSIC-UIB), Esporles, Illes Balears, Spain
| | - Johannes Sikorski
- DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany
| | - David Smith
- CABI, Bakeham Lane, Egham, Surrey, United Kingdom
| | - Mitch Sogin
- Josephine Bay Paul Center for Comparative Evolution and Molecular Biology, MBL, Woods Hole, Massachusetts, United States of America
| | - Rick Stevens
- Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois, United States of America
| | - Uli Stingl
- Red Sea Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia
| | | | - Dorothea Taylor
- NamesforLife, LLC, East Lansing, Michigan, United States of America
| | - Jim M. Tiedje
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan, United States of America
| | - Brian Tindall
- DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany
| | - Michael Wagner
- Department of Microbial Ecology, University of Vienna, Vienna, Austria
| | - George Weinstock
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut
| | - Jean Weissenbach
- Commissariat à l'Energie Atomique (CEA), Genoscope, Evry, France
| | - Owen White
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Jun Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Disease, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Lixin Zhang
- Bioresource Center (BRC) of Institute of Microbiology, Chinese Academy of Sciences, P. R. China
- Chinese Academy of Sciences Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China
| | - Yu-Guang Zhou
- China General Microbiological Culture Collection Center (CGMCC), Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China
| | - Dawn Field
- U.K. Natural Environment Research Council (NERC), Environmental Bioinformatics Centre, Oxford, United Kingdom
| | - William B. Whitman
- Department of Microbiology, University of Georgia, Athens, Georgia, United States of America
| | - George M. Garrity
- NamesforLife, LLC, East Lansing, Michigan, United States of America
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan, United States of America
| | - Hans-Peter Klenk
- DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany
- * E-mail: (NCK); (HPK)
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Rastogi A, Gupta D. GFF-Ex: a genome feature extraction package. BMC Res Notes 2014; 7:315. [PMID: 24885931 PMCID: PMC4045924 DOI: 10.1186/1756-0500-7-315] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2013] [Accepted: 03/21/2014] [Indexed: 11/10/2022] Open
Abstract
Background Genomic features of whole genome sequences emerging from various sequencing and annotation projects are represented and stored in several formats. Amongst these formats, the GFF (Generic/General Feature Format) has emerged as a widely accepted, portable and successfully used flat file format for genome annotation storage. With an increasing interest in genome annotation projects and secondary and meta-analysis, there is a need for efficient tools to extract sequences of interests from GFF files. Findings We have developed GFF-Ex to automate feature-based extraction of sequences from a GFF file. In addition to automated sequence extraction of the features described within a feature file, GFF-Ex also assigns boundaries for the features (introns, intergenic, regions upstream to genes), which are not explicitly specified in the GFF format, and exports the corresponding primary sequence information into predefined feature specific output files. GFF-Ex package consists of several UNIX Shell and PERL scripts. Conclusions Compared to other available GFF parsers, GFF-Ex is a simpler tool, which permits sequence retrieval based on additional inferred features. GFF-Ex can also be integrated with any genome annotation or analysis pipeline. GFF-Ex is freely available at http://bioinfo.icgeb.res.in/gff.
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Affiliation(s)
| | - Dinesh Gupta
- Bioinformatics Laboratory, Structural and Computational Biology Group, International Center for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi 110067, India.
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Kyrpides NC, Woyke T, Eisen JA, Garrity G, Lilburn TG, Beck BJ, Whitman WB, Hugenholtz P, Klenk HP. Genomic Encyclopedia of Type Strains, Phase I: The one thousand microbial genomes (KMG-I) project. Stand Genomic Sci 2013; 9:1278-84. [PMID: 25197443 PMCID: PMC4148999 DOI: 10.4056/sigs.5068949] [Citation(s) in RCA: 75] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
The Genomic Encyclopedia of Bacteria and Archaea (GEBA) project was launched by the JGI in 2007 as a pilot project with the objective of sequencing 250 bacterial and archaeal genomes. The two major goals of that project were (a) to test the hypothesis that there are many benefits to the use the phylogenetic diversity of organisms in the tree of life as a primary criterion for generating their genome sequence and (b) to develop the necessary framework, technology and organization for large-scale sequencing of microbial isolate genomes. While the GEBA pilot project has not yet been entirely completed, both of the original goals have already been successfully accomplished, leading the way for the next phase of the project. Here we propose taking the GEBA project to the next level, by generating high quality draft genomes for 1,000 bacterial and archaeal strains. This represents a combined 16-fold increase in both scale and speed as compared to the GEBA pilot project (250 isolate genomes in 4+ years). We will follow a similar approach for organism selection and sequencing prioritization as was done for the GEBA pilot project (i.e. phylogenetic novelty, availability and growth of cultures of type strains and DNA extraction capability), focusing on type strains as this ensures reproducibility of our results and provides the strongest linkage between genome sequences and other knowledge about each strain. In turn, this project will constitute a pilot phase of a larger effort that will target the genome sequences of all available type strains of the Bacteria and Archaea.
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Affiliation(s)
| | - Tanja Woyke
- DOE Joint Genome Institute, Walnut Creek, CA
| | | | - George Garrity
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan, USA ; NamesforLife, LLC, East Lansing, MI, USA
| | | | | | | | - Phil Hugenholtz
- Australian Centre for Ecogenomics, The University of Queensland, Brisbane QLD 4072, Australia
| | - Hans-Peter Klenk
- Leibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany
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31
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Krishnakumar S, Durai DA, Wangikar PP, Viswanathan GA. SHARP: genome-scale identification of gene-protein-reaction associations in cyanobacteria. PHOTOSYNTHESIS RESEARCH 2013; 118:181-190. [PMID: 23975204 DOI: 10.1007/s11120-013-9910-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2013] [Accepted: 08/07/2013] [Indexed: 06/02/2023]
Abstract
Genome scale metabolic model provides an overview of an organism's metabolic capability. These genome-specific metabolic reconstructions are based on identification of gene to protein to reaction (GPR) associations and, in turn, on homology with annotated genes from other organisms. Cyanobacteria are photosynthetic prokaryotes which have diverged appreciably from their nonphotosynthetic counterparts. They also show significant evolutionary divergence from plants, which are well studied for their photosynthetic apparatus. We argue that context-specific sequence and domain similarity can add to the repertoire of the GPR associations and significantly expand our view of the metabolic capability of cyanobacteria. We took an approach that combines the results of context-specific sequence-to-sequence similarity search with those of sequence-to-profile searches. We employ PSI-BLAST for the former, and CDD, Pfam, and COG for the latter. An optimization algorithm was devised to arrive at a weighting scheme to combine the different evidences with KEGG-annotated GPRs as training data. We present the algorithm in the form of software "Systematic, Homology-based Automated Re-annotation for Prokaryotes (SHARP)." We predicted 3,781 new GPR associations for the 10 prokaryotes considered of which eight are cyanobacteria species. These new GPR associations fall in several metabolic pathways and were used to annotate 7,718 gaps in the metabolic network. These new annotations led to discovery of several pathways that may be active and thereby providing new directions for metabolic engineering of these species for production of useful products. Metabolic model developed on such a reconstructed network is likely to give better phenotypic predictions.
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Affiliation(s)
- S Krishnakumar
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, India
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32
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Microbial diversity in the era of omic technologies. BIOMED RESEARCH INTERNATIONAL 2013; 2013:958719. [PMID: 24260747 PMCID: PMC3821902 DOI: 10.1155/2013/958719] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2013] [Revised: 08/26/2013] [Accepted: 08/26/2013] [Indexed: 11/17/2022]
Abstract
Human life and activity depends on microorganisms, as they are responsible for providing basic elements of life. Although microbes have such a key role in sustaining basic functions for all living organisms, very little is known about their biology since only a small fraction (average 1%) can be cultured under laboratory conditions. This is even more evident when considering that >88% of all bacterial isolates belong to four bacterial phyla, the Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes. Advanced technologies, developed in the last years, promise to revolutionise the way that we characterize, identify, and study microbial communities. In this review, we present the most advanced tools that microbial ecologists can use for the study of microbial communities. Innovative microbial ecological DNA microarrays such as PhyloChip and GeoChip that have been developed for investigating the composition and function of microbial communities are presented, along with an overview of the next generation sequencing technologies. Finally, the Single Cell Genomics approach, which can be used for obtaining genomes from uncultured phyla, is outlined. This tool enables the amplification and sequencing of DNA from single cells obtained directly from environmental samples and is promising to revolutionise microbiology.
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Su L, Chang D, Liu C. The development of space microbiology in the future: the value and significance of space microbiology research. Future Microbiol 2013; 8:5-8. [PMID: 23252487 DOI: 10.2217/fmb.12.127] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
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Forde BM, O'Toole PW. Next-generation sequencing technologies and their impact on microbial genomics. Brief Funct Genomics 2013; 12:440-53. [PMID: 23314033 DOI: 10.1093/bfgp/els062] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Next-generation sequencing technologies have had a dramatic impact in the field of genomic research through the provision of a low cost, high-throughput alternative to traditional capillary sequencers. These new sequencing methods have surpassed their original scope and now provide a range of utility-based applications, which allow for a more comprehensive analysis of the structure and content of microbial genomes than was previously possible. With the commercialization of a third generation of sequencing technologies imminent, we discuss the applications of current next-generation sequencing methods and explore their impact on and contribution to microbial genome research.
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Affiliation(s)
- Brian M Forde
- Department of Microbiology, University College Cork, Cork, Ireland.
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Abstract
Microbial metabolomics constitutes an integrated component of systems biology. By studying the complete set of metabolites within a microorganism and monitoring the global outcome of interactions between its development processes and the environment, metabolomics can potentially provide a more accurate snap shot of the actual physiological state of the cell. Recent advancement of technologies and post-genomic developments enable the study and analysis of metabolome. This unique contribution resulted in many scientific disciplines incorporating metabolomics as one of their “omics” platforms. This review focuses on metabolomics in microorganisms and utilizes selected topics to illustrate its impact on the understanding of systems microbiology.
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Affiliation(s)
- Jane Tang
- Center for National Security and Intelligence, Noblis, Falls Church, Virginia, USA
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Abstract
High-throughput identification of proteins with the latest generation of hybrid high-resolution mass spectrometers is opening new perspectives in microbiology. I present, here, an overview of tandem mass spectrometry technology and bioinformatics for shotgun proteomics that make 2D-PAGE approaches obsolete. Non-labelling quantitative approaches have become more popular than labelling techniques on most proteomic platforms because they are easier to carry out while their quantitative outcome is rather robust. Parameters for recording mass spectrometry data, however, need to be chosen carefully and statistics to assess the confidence of the results should not be neglected. Interestingly, next-generation sequencing methodologies make any microbial model quickly amenable to proteomics, leading to the documentation of a wide range of organisms from diverse environments. Some recent discoveries made using microbial proteomics have challenged some biological dogma, such as: (i) initiation of the translation does not occur predominantly from ATG codons in some microorganisms, (ii) non-canonical initiation codons are used to regulate the production of specific but important proteins and (iii) a gene may code for multiple polypeptide species, heterogeneous in terms of sequences. Microbial diversity and microbial physiology can now be revisited by means of exhaustive comparative proteomic surveys where thousands of proteins are detected and quantified. Proteogenomics, consisting of better annotating of genomes with the help of proteomic evidence, is paving the way for integrated multi-omic approaches in microbiology. Finally, meta-proteomic tools and approaches are emerging for tackling the high complexity of the microbial world as a whole, opening new perspectives for assessing how microbial communities function.
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Affiliation(s)
- Jean Armengaud
- CEA, DSV, IBEB, Lab Biochim System Perturb, F-30207 Bagnols-sur-Cèze, France.
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37
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Sun Y, Zeng F, Zhang W, Qiao J. Structure-based phylogeny of polyene macrolide antibiotic glycosyltransferases. Gene 2012; 499:288-96. [DOI: 10.1016/j.gene.2012.02.050] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2011] [Revised: 02/23/2012] [Accepted: 02/27/2012] [Indexed: 11/28/2022]
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Abstract
The field of bioinformatics and computational biology has gone through a number of transformations during the past 15 years, establishing itself as a key component of new biology. This spectacular growth has been challenged by a number of disruptive changes in science and technology. Despite the apparent fatigue of the linguistic use of the term itself, bioinformatics has grown perhaps to a point beyond recognition. We explore both historical aspects and future trends and argue that as the field expands, key questions remain unanswered and acquire new meaning while at the same time the range of applications is widening to cover an ever increasing number of biological disciplines. These trends appear to be pointing to a redefinition of certain objectives, milestones, and possibly the field itself.
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Affiliation(s)
- Christos A Ouzounis
- Institute of Agrobiotechnology, Centre for Research & Technology Hellas-CERTH, Thessaloniki, Greece.
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Kimelman A, Levy A, Sberro H, Kidron S, Leavitt A, Amitai G, Yoder-Himes DR, Wurtzel O, Zhu Y, Rubin EM, Sorek R. A vast collection of microbial genes that are toxic to bacteria. Genome Res 2012; 22:802-9. [PMID: 22300632 PMCID: PMC3317161 DOI: 10.1101/gr.133850.111] [Citation(s) in RCA: 64] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2011] [Accepted: 01/25/2012] [Indexed: 11/25/2022]
Abstract
In the process of clone-based genome sequencing, initial assemblies frequently contain cloning gaps that can be resolved using cloning-independent methods, but the reason for their occurrence is largely unknown. By analyzing 9,328,693 sequencing clones from 393 microbial genomes, we systematically mapped more than 15,000 genes residing in cloning gaps and experimentally showed that their expression products are toxic to the Escherichia coli host. A subset of these toxic sequences was further evaluated through a series of functional assays exploring the mechanisms of their toxicity. Among these genes, our assays revealed novel toxins and restriction enzymes, and new classes of small, non-coding toxic RNAs that reproducibly inhibit E. coli growth. Further analyses also revealed abundant, short, toxic DNA fragments that were predicted to suppress E. coli growth by interacting with the replication initiator DnaA. Our results show that cloning gaps, once considered the result of technical problems, actually serve as a rich source for the discovery of biotechnologically valuable functions, and suggest new modes of antimicrobial interventions.
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MESH Headings
- Anti-Bacterial Agents/metabolism
- Anti-Bacterial Agents/pharmacology
- Bacterial Proteins/genetics
- Bacterial Proteins/metabolism
- Base Sequence
- Binding Sites/genetics
- Cloning, Molecular
- DNA, Bacterial/genetics
- DNA, Bacterial/metabolism
- DNA, Bacterial/pharmacology
- DNA-Binding Proteins/genetics
- DNA-Binding Proteins/metabolism
- Escherichia coli/genetics
- Escherichia coli/metabolism
- Gene Expression Regulation, Bacterial
- Genes, Bacterial/genetics
- Genome, Bacterial/genetics
- Microbial Viability/drug effects
- Microbial Viability/genetics
- Molecular Sequence Data
- Protein Binding
- RNA, Bacterial/genetics
- RNA, Bacterial/metabolism
- RNA, Bacterial/pharmacology
- RNA, Transfer/genetics
- RNA, Transfer/metabolism
- RNA, Transfer/pharmacology
- Sequence Homology, Nucleic Acid
- Transcription, Genetic
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Affiliation(s)
- Aya Kimelman
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Asaf Levy
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Hila Sberro
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Shahar Kidron
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Azita Leavitt
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Gil Amitai
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Deborah R. Yoder-Himes
- Department of Microbiology and Immunobiology, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Omri Wurtzel
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Yiwen Zhu
- DOE Joint Genome Institute, Walnut Creek, California 94598, USA
- Genome Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Edward M. Rubin
- DOE Joint Genome Institute, Walnut Creek, California 94598, USA
- Genome Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Rotem Sorek
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
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Leekitcharoenphon P, Lukjancenko O, Friis C, Aarestrup FM, Ussery DW. Genomic variation in Salmonella enterica core genes for epidemiological typing. BMC Genomics 2012; 13:88. [PMID: 22409488 PMCID: PMC3359268 DOI: 10.1186/1471-2164-13-88] [Citation(s) in RCA: 65] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2011] [Accepted: 03/12/2012] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Technological advances in high throughput genome sequencing are making whole genome sequencing (WGS) available as a routine tool for bacterial typing. Standardized procedures for identification of relevant genes and of variation are needed to enable comparison between studies and over time. The core genes--the genes that are conserved in all (or most) members of a genus or species--are potentially good candidates for investigating genomic variation in phylogeny and epidemiology. RESULTS We identify a set of 2,882 core genes clusters based on 73 publicly available Salmonella enterica genomes and evaluate their value as typing targets, comparing whole genome typing and traditional methods such as 16S and MLST. A consensus tree based on variation of core genes gives much better resolution than 16S and MLST; the pan-genome family tree is similar to the consensus tree, but with higher confidence. The core genes can be divided into two categories: a few highly variable genes and a larger set of conserved core genes, with low variance. For the most variable core genes, the variance in amino acid sequences is higher than for the corresponding nucleotide sequences, suggesting that there is a positive selection towards mutations leading to amino acid changes. CONCLUSIONS Genomic variation within the core genome is useful for investigating molecular evolution and providing candidate genes for bacterial genome typing. Identification of genes with different degrees of variation is important especially in trend analysis.
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Krumholz EW, Yang H, Weisenhorn P, Henry CS, Libourel IGL. Genome-wide metabolic network reconstruction of the picoalga Ostreococcus. JOURNAL OF EXPERIMENTAL BOTANY 2012; 63:2353-2362. [PMID: 22207618 DOI: 10.1093/jxb/err407] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
The green picoalga Ostreococcus is emerging as a simple plant model organism, and two species, O. lucimarinus and O. tauri, have now been sequenced and annotated manually. To evaluate the completeness of the metabolic annotation of both species, metabolic networks of O. lucimarinus and O. tauri were reconstructed from the KEGG database, thermodynamically constrained, elementally balanced, and functionally evaluated. The draft networks contained extensive gaps and, in the case of O. tauri, no biomass components could be produced due to an incomplete Calvin cycle. To find and remove gaps from the networks, an extensive reference biochemical reaction database was assembled using a stepwise approach that minimized the inclusion of microbial reactions. Gaps were then removed from both Ostreococcus networks using two existing gap-filling methodologies. In the first method, a bottom-up approach, a minimal list of reactions was added to each model to enable the production of all metabolites included in our biomass equation. In the second method, a top-down approach, all reactions in the reference database were added to the target networks and subsequently trimmed away based on the sequence alignment scores of identified orthologues. Because current gap-filling methods do not produce unique solutions, a quality metric that includes a weighting for phylogenetic distance and sequence similarity was developed to distinguish between gap-filling results automatically. The draft O. lucimarinus and O. tauri networks required the addition of 56 and 70 reactions, respectively, in order to produce the same biomass precursor metabolites that were produced by our plant reference database.
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Affiliation(s)
- Elias W Krumholz
- Department of Plant Biology, University of Minnesota, Saint Paul, MN 55108, USA
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42
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Christie-Oleza JA, Miotello G, Armengaud J. High-throughput proteogenomics of Ruegeria pomeroyi: seeding a better genomic annotation for the whole marine Roseobacter clade. BMC Genomics 2012; 13:73. [PMID: 22336032 PMCID: PMC3305630 DOI: 10.1186/1471-2164-13-73] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2011] [Accepted: 02/15/2012] [Indexed: 11/10/2022] Open
Abstract
Background The structural and functional annotation of genomes is now heavily based on data obtained using automated pipeline systems. The key for an accurate structural annotation consists of blending similarities between closely related genomes with biochemical evidence of the genome interpretation. In this work we applied high-throughput proteogenomics to Ruegeria pomeroyi, a member of the Roseobacter clade, an abundant group of marine bacteria, as a seed for the annotation of the whole clade. Results A large dataset of peptides from R. pomeroyi was obtained after searching over 1.1 million MS/MS spectra against a six-frame translated genome database. We identified 2006 polypeptides, of which thirty-four were encoded by open reading frames (ORFs) that had not previously been annotated. From the pool of 'one-hit-wonders', i.e. those ORFs specified by only one peptide detected by tandem mass spectrometry, we could confirm the probable existence of five additional new genes after proving that the corresponding RNAs were transcribed. We also identified the most-N-terminal peptide of 486 polypeptides, of which sixty-four had originally been wrongly annotated. Conclusions By extending these re-annotations to the other thirty-six Roseobacter isolates sequenced to date (twenty different genera), we propose the correction of the assigned start codons of 1082 homologous genes in the clade. In addition, we also report the presence of novel genes within operons encoding determinants of the important tricarboxylic acid cycle, a feature that seems to be characteristic of some Roseobacter genomes. The detection of their corresponding products in large amounts raises the question of their function. Their discoveries point to a possible theory for protein evolution that will rely on high expression of orphans in bacteria: their putative poor efficiency could be counterbalanced by a higher level of expression. Our proteogenomic analysis will increase the reliability of the future annotation of marine bacterial genomes.
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Johnston C, Ibrahim A, Magarvey N. Informatic strategies for the discovery of polyketides and nonribosomal peptides. MEDCHEMCOMM 2012. [DOI: 10.1039/c2md20120h] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
A modern challenge and opportunity exists for in the ability to link genomic and metabolomic data, using novel informatic methods to find new bioactive natural products.
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Affiliation(s)
- Chad Johnston
- Department of Biochemistry and Biomedical Sciences
- Department of Chemistry and Chemical Biology
- M. G. DeGroote Institute for Infectious Disease Research
- McMaster University
- Hamilton
| | - Ashraf Ibrahim
- Department of Biochemistry and Biomedical Sciences
- Department of Chemistry and Chemical Biology
- M. G. DeGroote Institute for Infectious Disease Research
- McMaster University
- Hamilton
| | - Nathan Magarvey
- Department of Biochemistry and Biomedical Sciences
- Department of Chemistry and Chemical Biology
- M. G. DeGroote Institute for Infectious Disease Research
- McMaster University
- Hamilton
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Pagani I, Liolios K, Jansson J, Chen IMA, Smirnova T, Nosrat B, Markowitz VM, Kyrpides NC. The Genomes OnLine Database (GOLD) v.4: status of genomic and metagenomic projects and their associated metadata. Nucleic Acids Res 2012; 40:D571-9. [PMID: 22135293 PMCID: PMC3245063 DOI: 10.1093/nar/gkr1100] [Citation(s) in RCA: 375] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2011] [Revised: 11/02/2011] [Accepted: 11/03/2011] [Indexed: 12/03/2022] Open
Abstract
The Genomes OnLine Database (GOLD, http://www.genomesonline.org/) is a comprehensive resource for centralized monitoring of genome and metagenome projects worldwide. Both complete and ongoing projects, along with their associated metadata, can be accessed in GOLD through precomputed tables and a search page. As of September 2011, GOLD, now on version 4.0, contains information for 11,472 sequencing projects, of which 2907 have been completed and their sequence data has been deposited in a public repository. Out of these complete projects, 1918 are finished and 989 are permanent drafts. Moreover, GOLD contains information for 340 metagenome studies associated with 1927 metagenome samples. GOLD continues to expand, moving toward the goal of providing the most comprehensive repository of metadata information related to the projects and their organisms/environments in accordance with the Minimum Information about any (x) Sequence specification and beyond.
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Affiliation(s)
- Ioanna Pagani
- Department of Energy Joint Genome Institute, Microbial Genomics and Metagenomics Program, 2800 Mitchell Drive, Walnut Creek, Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley and Department of Energy Joint Genome Institute, Genome Portals Group, 2800 Mitchell Drive, Walnut Creek, CA, USA
| | - Konstantinos Liolios
- Department of Energy Joint Genome Institute, Microbial Genomics and Metagenomics Program, 2800 Mitchell Drive, Walnut Creek, Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley and Department of Energy Joint Genome Institute, Genome Portals Group, 2800 Mitchell Drive, Walnut Creek, CA, USA
| | - Jakob Jansson
- Department of Energy Joint Genome Institute, Microbial Genomics and Metagenomics Program, 2800 Mitchell Drive, Walnut Creek, Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley and Department of Energy Joint Genome Institute, Genome Portals Group, 2800 Mitchell Drive, Walnut Creek, CA, USA
| | - I-Min A. Chen
- Department of Energy Joint Genome Institute, Microbial Genomics and Metagenomics Program, 2800 Mitchell Drive, Walnut Creek, Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley and Department of Energy Joint Genome Institute, Genome Portals Group, 2800 Mitchell Drive, Walnut Creek, CA, USA
| | - Tatyana Smirnova
- Department of Energy Joint Genome Institute, Microbial Genomics and Metagenomics Program, 2800 Mitchell Drive, Walnut Creek, Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley and Department of Energy Joint Genome Institute, Genome Portals Group, 2800 Mitchell Drive, Walnut Creek, CA, USA
| | - Bahador Nosrat
- Department of Energy Joint Genome Institute, Microbial Genomics and Metagenomics Program, 2800 Mitchell Drive, Walnut Creek, Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley and Department of Energy Joint Genome Institute, Genome Portals Group, 2800 Mitchell Drive, Walnut Creek, CA, USA
| | - Victor M. Markowitz
- Department of Energy Joint Genome Institute, Microbial Genomics and Metagenomics Program, 2800 Mitchell Drive, Walnut Creek, Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley and Department of Energy Joint Genome Institute, Genome Portals Group, 2800 Mitchell Drive, Walnut Creek, CA, USA
| | - Nikos C. Kyrpides
- Department of Energy Joint Genome Institute, Microbial Genomics and Metagenomics Program, 2800 Mitchell Drive, Walnut Creek, Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley and Department of Energy Joint Genome Institute, Genome Portals Group, 2800 Mitchell Drive, Walnut Creek, CA, USA
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Levy R, Borenstein E. Reverse Ecology: from systems to environments and back. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2012; 751:329-45. [PMID: 22821465 DOI: 10.1007/978-1-4614-3567-9_15] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The structure of complex biological systems reflects not only their function but also the environments in which they evolved and are adapted to. Reverse Ecology-an emerging new frontier in Evolutionary Systems Biology-aims to extract this information and to obtain novel insights into an organism's ecology. The Reverse Ecology framework facilitates the translation of high-throughput genomic data into large-scale ecological data, and has the potential to transform ecology into a high-throughput field. In this chapter, we describe some of the pioneering work in Reverse Ecology, demonstrating how system-level analysis of complex biological networks can be used to predict the natural habitats of poorly characterized microbial species, their interactions with other species, and universal patterns governing the adaptation of organisms to their environments. We further present several studies that applied Reverse Ecology to elucidate various aspects of microbial ecology, and lay out exciting future directions and potential future applications in biotechnology, biomedicine, and ecological engineering.
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Affiliation(s)
- Roie Levy
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
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Gilbert JA, Bailey M, Field D, Fierer N, Fuhrman JA, Hu B, Jansson J, Knight R, Kowalchuk GA, Kyrpides NC, Meyer F, Stevens R. The Earth Microbiome Project: The Meeting Report for the 1st International Earth Microbiome Project Conference, Shenzhen, China, June 13th-15th 2011. Stand Genomic Sci 2011. [PMCID: PMC3235519 DOI: 10.4056/sigs.2134923] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Affiliation(s)
| | - Mark Bailey
- 2Centre for Ecology & Hydrology, Natural Environment Research Council, Crowmarsh Gifford, Wallingford, Oxon, UK
| | - Dawn Field
- 2Centre for Ecology & Hydrology, Natural Environment Research Council, Crowmarsh Gifford, Wallingford, Oxon, UK
| | - Noah Fierer
- 3Dept. of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO USA
| | - Jed A. Fuhrman
- 4Dept. of Biological Sciences, University of Southern California, Los Angeles CA USA
| | - Bin Hu
- 5Beijing Genomics Institute at Shenzhen, Guangdong, China
| | - Janet Jansson
- 6Lawrence Berkeley National Laboratory, Earth Sciences Division Berkeley, CA USA
| | - Rob Knight
- 7Howard Hughes Medical Institute and Department of Chemistry & Biochemistry, University of Colorado at Boulder, Boulder, USA
| | - George A. Kowalchuk
- 8Department of Microbial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, The Netherlands
| | | | - Folker Meyer
- 10Computation Institute, University of Chicago, Chicago, IL USA
| | - Rick Stevens
- 10Computation Institute, University of Chicago, Chicago, IL USA
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Klimke W, O'Donovan C, White O, Brister JR, Clark K, Fedorov B, Mizrachi I, Pruitt KD, Tatusova T. Solving the Problem: Genome Annotation Standards before the Data Deluge. Stand Genomic Sci 2011; 5:168-93. [PMID: 22180819 PMCID: PMC3236044 DOI: 10.4056/sigs.2084864] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
The promise of genome sequencing was that the vast undiscovered country would be mapped out by comparison of the multitude of sequences available and would aid researchers in deciphering the role of each gene in every organism. Researchers recognize that there is a need for high quality data. However, different annotation procedures, numerous databases, and a diminishing percentage of experimentally determined gene functions have resulted in a spectrum of annotation quality. NCBI in collaboration with sequencing centers, archival databases, and researchers, has developed the first international annotation standards, a fundamental step in ensuring that high quality complete prokaryotic genomes are available as gold standard references. Highlights include the development of annotation assessment tools, community acceptance of protein naming standards, comparison of annotation resources to provide consistent annotation, and improved tracking of the evidence used to generate a particular annotation. The development of a set of minimal standards, including the requirement for annotated complete prokaryotic genomes to contain a full set of ribosomal RNAs, transfer RNAs, and proteins encoding core conserved functions, is an historic milestone. The use of these standards in existing genomes and future submissions will increase the quality of databases, enabling researchers to make accurate biological discoveries.
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Martin F, Cullen D, Hibbett D, Pisabarro A, Spatafora JW, Baker SE, Grigoriev IV. Sequencing the fungal tree of life. THE NEW PHYTOLOGIST 2011; 190:818-821. [PMID: 21401614 DOI: 10.1111/j.1469-8137.2011.03688.x] [Citation(s) in RCA: 64] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Affiliation(s)
- F Martin
- UMR INRA/UHP 1136, Interactions Arbres/Micro-Organismes, INRA-Nancy, 54280 Champenoux, France
- (Authors for correspondence: F. Martin tel +33 383 39 40 80; email ; I.V. Grigoriev email )
| | - D Cullen
- USDA, Forest Products Laboratory, Madison, WI, USA
| | - D Hibbett
- Clark University, Worcester, MA, USA
| | - A Pisabarro
- Department of Agrarian Production, Public University of Navarre, 31006 Pamplona, Spain
| | - J W Spatafora
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - S E Baker
- Chemical and Biological Process Development Group, Pacific Northwest National Laboratory, Richland, WA 99352, USA
- US DOE Joint Genome Institute, Walnut Creek, CA, USA
| | - I V Grigoriev
- US DOE Joint Genome Institute, Walnut Creek, CA, USA
- (Authors for correspondence: F. Martin tel +33 383 39 40 80; email ; I.V. Grigoriev email )
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Prediction and Characterization of Missing Proteomic Data in Desulfovibrio vulgaris. Comp Funct Genomics 2011; 2011:780973. [PMID: 21687592 PMCID: PMC3114432 DOI: 10.1155/2011/780973] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2010] [Revised: 12/17/2010] [Accepted: 03/01/2011] [Indexed: 11/17/2022] Open
Abstract
Proteomic datasets are often incomplete due to identification range and sensitivity issues. It becomes important to develop methodologies to estimate missing proteomic data, allowing better interpretation of proteomic datasets and metabolic mechanisms underlying complex biological systems. In this study, we applied an artificial neural network to approximate the relationships between cognate transcriptomic and proteomic datasets of Desulfovibrio vulgaris, and to predict protein abundance for the proteins not experimentally detected, based on several relevant predictors, such as mRNA abundance, cellular role and triple codon counts. The results showed that the coefficients of determination for the trained neural network models ranged from 0.47 to 0.68, providing better modeling than several previous regression models. The validity of the trained neural network model was evaluated using biological information (i.e. operons). To seek understanding of mechanisms causing missing proteomic data, we used a multivariate logistic regression analysis and the result suggested that some key factors, such as protein instability index, aliphatic index, mRNA abundance, effective number of codons (N(c)) and codon adaptation index (CAI) values may be ascribed to whether a given expressed protein can be detected. In addition, we demonstrated that biological interpretation can be improved by use of imputed proteomic datasets.
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50
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Do we need new antibiotics? The search for new targets and new compounds. J Ind Microbiol Biotechnol 2010; 37:1241-8. [PMID: 21086099 DOI: 10.1007/s10295-010-0849-8] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2010] [Accepted: 08/16/2010] [Indexed: 02/01/2023]
Abstract
Resistance to antibiotics and other antimicrobial compounds continues to increase. There are several possibilities for protection against pathogenic microorganisms, for instance, preparation of new vaccines against resistant bacterial strains, use of specific bacteriophages, and searching for new antibiotics. The antibiotic search includes: (1) looking for new antibiotics from nontraditional or less traditional sources, (2) sequencing microbial genomes with the aim of finding genes specifying biosynthesis of antibiotics, (3) analyzing DNA from the environment (metagenomics), (4) re-examining forgotten natural compounds and products of their transformations, and (5) investigating new antibiotic targets in pathogenic bacteria.
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