DOCSLIB.ORG

Characterization of an Adapted Microbial Population to the Bioconversion of Carbon Monoxide Into Butanol Using Next-Generation Sequencing Technology

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Characterization of an Adapted Microbial Population to the Bioconversion of Carbon Monoxide Into Butanol Using Next-Generation Sequencing Technology Characterization of an adapted microbial population to the bioconversion of carbon monoxide into butanol using next-generation sequencing technology Guillaume Bruant Research officer, Bioengineering group Energy, Mining, Environment - National Research Council Canada Pacific Rim Summit on Industrial Biotechnology and Bioenergy December 8 -11, 2013 Butanol from residue (dry): syngas route biomass → gasification → syngas → catalysis → synfuels (CO, H2, CO2, CH4) (alcohols…) Biocatalysis vs Chemical catalysis potential for higher product specificity may be less problematic when impurities present less energy intensive (low pressure and temperature) Anaerobic undefined mixed culture vs bacterial pure culture mesophilic anaerobic sludge treating agricultural wastes (Lassonde Inc, Rougemont, QC, Canada) PRS 2013 - 2 Experimental design CO Alcohols Serum bottles incubated at Next Generation RDP Pyrosequencing mesophilic temperature Sequencing (NGS) pipeline 35°C for 2 months Ion PGMTM sequencer http://pyro.cme.msu.edu/ sequences filtered CO continuously supplied Monitoring of bacterial and to the gas phase archaeal populations RDP classifier atmosphere of 100% CO, http://rdp.cme.msu.edu/ 1 atm 16S rRNA genes Ion 314TM chip classifier VFAs & alcohol production bootstrap confidence cutoff low level of butanol of 50 % Samples taken after 1 and 2 months total genomic DNA extracted, purified, concentrated PRS 2013 - 3 NGS: bacterial results Bacterial population - Phylum level 100% 80% Other Chloroflexi 60% Synergistetes % of total Firmicutes sequences Proteobacteria 40% Bacteroidetes Spirochaetes 20% Actinobacteria unclassified Bacteria 0% 1 month 2 months Initial sludge Other (<0.5%): TM7, Cyanobacteria/Chloroplast, Thermotogae, Chlorobi, Acidobacteria, Verrucomicrobia, Planctomycetes, OP11, Elusimicrobia, Thermodesulfobacteria, Lentisphaerae and SR1 Phylum of interest: Firmicutes (8.0% to 82.5%) PRS 2013 - 4 NGS: bacterial results Bacterial population - class level 100% Other Anaerolineae (Ch) 80% Synergistia (Sy) Negativicutes (F) Clostridia (F) 60% % of total Gammaproteobacteria (P) identified classes Alphaproteobacteria (P) 40% Betaproteobacteria (P) Deltaproteobacteria (P) 20% Epsilonproteobacteria (P) Flavobacteria (B) Sphingobacteria (B) 0% Bacteroidia (B) Spirochaetes (S) 1 month 2 months Actinobacteria (A) Initial sludge Other (<0.5%): Bacteroidetes incertae sedis (B), Bacilli (C), Erysipelotrichia (C) and Dehalococcoidetes (Ch) A: Actinobacteria, S: Spirochaetes, B: Bacteroidetes, P: Proteobacteria, F: Firmicutes, Sy: Synergistetes and Ch: Chloroflexi Class of interest: Clostridia (6.5% to 82.4%) PRS 2013 - 5 NGS: bacterial results Bacterial population - order level Other Anaerolineales (Ch) Synergistales (Sy) 100% Selenomonadales (F) 90% Clostridiales (F) Methylococcales (P) 80% Rhodospirillales (P) 70% Caulobacterales (P) 60% Rhizobiales (P) % of total 50% Hydrogenophilales (P) identified orders Burkholderiales (P) 40% Desulfuromonadales (P) 30% Desulfovibrionales (P) 20% Syntrophobacterales (P) 10% Campylobacterales (P) 0% Flavobacteriales (B) Sphingobacteriales (B) Bacteroidales (B) 1 month 2 months Spirochaetales (S) Initial sludge Actinomycetales (A) Other: 20 orders < 0.5% A: Actinobacteria, S: Spirochaetes, B: Bacteroidetes, P: Proteobacteria, F: Firmicutes, Sy: Synergistetes and Ch: Chloroflexi Order of interest: Clostridiales (6.4% to 82.3%) PRS 2013 - 6 NGS: bacterial results Order Clostridiales - family level 100% Gracilibacteraceae Peptostreptococcaceae 80% Eubacteriaceae Clostridiales Incertae Sedis III 60% Ruminococcaceae % of total Syntrophomonadaceae identified families Clostridiales Incertae Sedis XI 40% Lachnospiraceae Clostridiaceae 1 20% Peptococcaceae 2 Peptococcaceae 1 0% Clostridiales Incertae Sedis XIII Clostridiales Incertae Sedis XII unclassified Clostridiales 1 month 2 months Initial sludge genera of interest: Clostridium (~0% to 9.0%), Oscillibacter (~0% to 9.9%), Acetobacterium (~0% to 49.8%) PRS 2013 - 7 NGS: bacterial main results Significant decrease of the 3 principal components of the initial bacterial population Bacteroidetes (30.3% to 4.3%) Actinobacteria (23.7% to 9.3%) Proteobacteria (20.9% to 1.4%) Significant increase of the Firmicutes became ultra-dominant (82.5%) 1 class (Clostridia, 82.4%), 1 order (Clostridiales, 82.3%) Emergence of 3 families Clostridiaceae (Clostridium, known solvent producers) Ruminococcaceae (Oscillibacter, valeric acid producer) Eubacteriaceae (Acetobacterium, known acetate producers) PRS 2013 - 8 NGS: archaeal main results Limited impact of CO on archaeal population Archaeal population - class level 100% 2 phyla 90% Euryarchaeota 80% (98.1% to 99.2%) 70% 60% Crenarchaeota % of total 50% Thermoprotei (C) identitfied classes No impact on 40% Methanomicrobia (E) Methanobacteria (E) 30% diversity 20% 2 phyla 10% 3 classes 0% e th s g n th 5 orders d o n lu o s m l 1 m ia 2 it In Methanobacteria increased (13.9% to 45.9%) specifically Methanobacterium (44.6%), hydrogenotrophic methanogen Methanomicrobia decreased (82.8% to 52.7%) emergence of Methanosarcina, methanogen metabolically diverse and nonmethanogenically CO user PRS 2013 - 9 Conclusions and perspectives Ion Torrent Next Generation Sequencing platform powerful technique for microbial population monitoring Impact of CO on microbial population insights on microbial species adapted to bioconversion of CO into butanol importance of Clostridiales (Clostridium and Oscillibacter) Next: bio-augmentation strategies microorganisms identified through NGS optimize and stabilize the process (improve butanol production) PRS 2013 - 10 Acknowledgments Serge Guiot Marie-Josée Lévesque Alain Corriveau Questions? PRS 2013 - 11 .
Load more

Recommended publications
  • Genomics 98 (2011) 370–375
    Genomics 98 (2011) 370–375 Contents lists available at ScienceDirect Genomics journal homepage: www.elsevier.com/locate/ygeno Whole-genome comparison clarifies close phylogenetic relationships between the phyla Dictyoglomi and Thermotogae Hiromi Nishida a,⁎, Teruhiko Beppu b, Kenji Ueda b a Agricultural Bioinformatics Research Unit, Graduate School of Agricultural and Life Sciences, University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan b Life Science Research Center, College of Bioresource Sciences, Nihon University, Fujisawa, Japan article info abstract Article history: The anaerobic thermophilic bacterial genus Dictyoglomus is characterized by the ability to produce useful Received 2 June 2011 enzymes such as amylase, mannanase, and xylanase. Despite the significance, the phylogenetic position of Accepted 1 August 2011 Dictyoglomus has not yet been clarified, since it exhibits ambiguous phylogenetic positions in a single gene Available online 7 August 2011 sequence comparison-based analysis. The number of substitutions at the diverging point of Dictyoglomus is insufficient to show the relationships in a single gene comparison-based analysis. Hence, we studied its Keywords: evolutionary trait based on whole-genome comparison. Both gene content and orthologous protein sequence Whole-genome comparison Dictyoglomus comparisons indicated that Dictyoglomus is most closely related to the phylum Thermotogae and it forms a Bacterial systematics monophyletic group with Coprothermobacter proteolyticus (a constituent of the phylum Firmicutes) and Coprothermobacter proteolyticus Thermotogae. Our findings indicate that C. proteolyticus does not belong to the phylum Firmicutes and that the Thermotogae phylum Dictyoglomi is not closely related to either the phylum Firmicutes or Synergistetes but to the phylum Thermotogae. © 2011 Elsevier Inc.
    [Show full text]
  • Alternative Hydrogen Uptake Pathways Suppress Methane Production In
    bioRxiv preprint doi: https://doi.org/10.1101/486894; this version posted December 4, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 December 4, 2018 2 Alternative hydrogen uptake pathways 3 suppress methane production in ruminants 4 Chris Greening1 * #, Renae Geier2 #, Cecilia Wang3, Laura C. Woods1, Sergio E. 5 Morales3, Michael J. McDonald1, Rowena Rushton-Green3, Xochitl C. Morgan3, 6 Satoshi Koike4, Sinead C. Leahy5, William J. Kelly6, Isaac Cann2, Graeme T. 7 Attwood5, Gregory M. Cook3, Roderick I. Mackie2 * 8 9 1 Monash University, School of Biological Sciences, Clayton, VIC 3800, Australia 10 2 University of Illinois at Urbana-Champaign, Department of Animal Sciences and 11 Institute for Genomic Biology, Urbana, IL 61801, USA 12 3 University of Otago, Department of Microbiology and Immunology, Dunedin 9016, 13 New Zealand 14 4 Hokkaido University, Research Faculty of Agriculture, Sapporo, Japan 15 5 AgResearch Ltd., Grasslands Research Centre, Palmerston North 4410, New 16 Zealand. 17 6 Donvis Ltd., Palmerston North 4410, New Zealand. 18 19 # These authors contributed equally to this work. 20 21 * Correspondence can be addressed to: 22 23 Dr Chris Greening ([email protected]), School of Biological Sciences, 24 Monash University, Clayton, VIC 3800, Australia 25 Prof Roderick Mackie ([email protected]), Department of Animal Sciences, 26 Urbana, IL 61801, USA 27 bioRxiv preprint doi: https://doi.org/10.1101/486894; this version posted December 4, 2018.
    [Show full text]
  • Acetogen Communities in the Gut of Herbivores and Their Potential Role in Syngas Fermentation
    fermentation Article Acetogen Communities in the Gut of Herbivores and Their Potential Role in Syngas Fermentation Chunlei Yang Institute of Dairy Science, MoE Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China; [email protected] Received: 2 May 2018; Accepted: 4 June 2018; Published: 7 June 2018 Abstract: To better understand the effects of host selection on gut acetogens and their potential role in syngas fermentation, the composition and hydrogenotrophic features of acetogen populations in cow and sheep rumens, rabbit ceca, and horse feces were studied. The acetogens detected in horses and rabbits were more phylogenetically diverse than those in cows and sheep, suggesting that the host species plays an important role in shaping gut acetogen populations. Acetogen enrichments from these animals presented good capacities to use hydrogen, with acetate as the major end product. Minor propionate, butyrate, and isovalerate were also produced. During 48 h of incubation, acetogen enrichments from horse consumed 4.75 moles of H2 to every 1 mole of acetate—significantly lower than rabbits, cows, and sheep (5.17, 5.53, and 5.23 moles, respectively) (p < 0.05)—and produced significantly more butyrate (p < 0.05). Enrichments from cows and sheep produced significantly higher amounts of propionate when compared to rabbits or horses (p < 0.05); enrichments from sheep produced the highest amounts of isovalerate (p < 0.05). These short chain fatty acids are important precursors for the synthesis of biofuel products, suggesting that gut contents of herbivores may be promising sources for harvesting functional acetogens for biofuel production.
    [Show full text]
  • Global Metagenomic Survey Reveals a New Bacterial Candidate Phylum in Geothermal Springs
    ARTICLE Received 13 Aug 2015 | Accepted 7 Dec 2015 | Published 27 Jan 2016 DOI: 10.1038/ncomms10476 OPEN Global metagenomic survey reveals a new bacterial candidate phylum in geothermal springs Emiley A. Eloe-Fadrosh1, David Paez-Espino1, Jessica Jarett1, Peter F. Dunfield2, Brian P. Hedlund3, Anne E. Dekas4, Stephen E. Grasby5, Allyson L. Brady6, Hailiang Dong7, Brandon R. Briggs8, Wen-Jun Li9, Danielle Goudeau1, Rex Malmstrom1, Amrita Pati1, Jennifer Pett-Ridge4, Edward M. Rubin1,10, Tanja Woyke1, Nikos C. Kyrpides1 & Natalia N. Ivanova1 Analysis of the increasing wealth of metagenomic data collected from diverse environments can lead to the discovery of novel branches on the tree of life. Here we analyse 5.2 Tb of metagenomic data collected globally to discover a novel bacterial phylum (‘Candidatus Kryptonia’) found exclusively in high-temperature pH-neutral geothermal springs. This lineage had remained hidden as a taxonomic ‘blind spot’ because of mismatches in the primers commonly used for ribosomal gene surveys. Genome reconstruction from metagenomic data combined with single-cell genomics results in several high-quality genomes representing four genera from the new phylum. Metabolic reconstruction indicates a heterotrophic lifestyle with conspicuous nutritional deficiencies, suggesting the need for metabolic complementarity with other microbes. Co-occurrence patterns identifies a number of putative partners, including an uncultured Armatimonadetes lineage. The discovery of Kryptonia within previously studied geothermal springs underscores the importance of globally sampled metagenomic data in detection of microbial novelty, and highlights the extraordinary diversity of microbial life still awaiting discovery. 1 Department of Energy Joint Genome Institute, Walnut Creek, California 94598, USA. 2 Department of Biological Sciences, University of Calgary, Calgary, Alberta T2N 1N4, Canada.
    [Show full text]
  • Recruitment of Reverse Transcriptase-Cas1 Fusion Proteins by Type VI-A CRISPR-Cas Systems
    fmicb-10-02160 September 12, 2019 Time: 16:22 # 1 ORIGINAL RESEARCH published: 13 September 2019 doi: 10.3389/fmicb.2019.02160 Recruitment of Reverse Transcriptase-Cas1 Fusion Proteins by Type VI-A CRISPR-Cas Systems Nicolás Toro*, Mario Rodríguez Mestre, Francisco Martínez-Abarca and Alejandro González-Delgado Structure, Dynamics and Function of Rhizobacterial Genomes, Department of Soil Microbiology and Symbiotic Systems, Estación Experimental del Zaidín, Consejo Superior de Investigaciones Científicas, Granada, Spain Type VI CRISPR–Cas systems contain a single effector nuclease (Cas13) that exclusively targets single-stranded RNA. It remains unknown how these systems acquire spacers. It has been suggested that type VI systems with adaptation modules can acquire spacers from RNA bacteriophages, but sequence similarities suggest that spacers may provide Edited by: Kira Makarova, immunity to DNA phages. We searched databases for Cas13 proteins with linked RTs. National Center for Biotechnology We identified two different type VI-A systems with adaptation modules including an Information (NLM), United States RT-Cas1 fusion and Cas2 proteins. Phylogenetic reconstruction analyses revealed that Reviewed by: these adaptation modules were recruited by different effector Cas13a proteins, possibly Yuri Wolf, National Center for Biotechnology from RT-associated type III-D systems within the bacterial classes Alphaproteobacteria Information (NLM), United States and Clostridia. These type VI-A systems are predicted to acquire spacers from RNA Omar
    [Show full text]
  • Genomic Analysis of Family UBA6911 (Group 18 Acidobacteria)
    bioRxiv preprint doi: https://doi.org/10.1101/2021.04.09.439258; this version posted April 10, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 2 Genomic analysis of family UBA6911 (Group 18 3 Acidobacteria) expands the metabolic capacities of the 4 phylum and highlights adaptations to terrestrial habitats. 5 6 Archana Yadav1, Jenna C. Borrelli1, Mostafa S. Elshahed1, and Noha H. Youssef1* 7 8 1Department of Microbiology and Molecular Genetics, Oklahoma State University, Stillwater, 9 OK 10 *Correspondence: Noha H. Youssef: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2021.04.09.439258; this version posted April 10, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 11 Abstract 12 Approaches for recovering and analyzing genomes belonging to novel, hitherto unexplored 13 bacterial lineages have provided invaluable insights into the metabolic capabilities and 14 ecological roles of yet-uncultured taxa. The phylum Acidobacteria is one of the most prevalent 15 and ecologically successful lineages on earth yet, currently, multiple lineages within this phylum 16 remain unexplored. Here, we utilize genomes recovered from Zodletone spring, an anaerobic 17 sulfide and sulfur-rich spring in southwestern Oklahoma, as well as from multiple disparate soil 18 and non-soil habitats, to examine the metabolic capabilities and ecological role of members of 19 the family UBA6911 (group18) Acidobacteria.
    [Show full text]
  • Development of the Equine Hindgut Microbiome in Semi-Feral and Domestic Conventionally-Managed Foals Meredith K
    Tavenner et al. Animal Microbiome (2020) 2:43 Animal Microbiome https://doi.org/10.1186/s42523-020-00060-6 RESEARCH ARTICLE Open Access Development of the equine hindgut microbiome in semi-feral and domestic conventionally-managed foals Meredith K. Tavenner1, Sue M. McDonnell2 and Amy S. Biddle1* Abstract Background: Early development of the gut microbiome is an essential part of neonate health in animals. It is unclear whether the acquisition of gut microbes is different between domesticated animals and their wild counterparts. In this study, fecal samples from ten domestic conventionally managed (DCM) Standardbred and ten semi-feral managed (SFM) Shetland-type pony foals and dams were compared using 16S rRNA sequencing to identify differences in the development of the foal hindgut microbiome related to time and management. Results: Gut microbiome diversity of dams was lower than foals overall and within groups, and foals from both groups at Week 1 had less diverse gut microbiomes than subsequent weeks. The core microbiomes of SFM dams and foals had more taxa overall, and greater numbers of taxa within species groups when compared to DCM dams and foals. The gut microbiomes of SFM foals demonstrated enhanced diversity of key groups: Verrucomicrobia (RFP12), Ruminococcaceae, Fusobacterium spp., and Bacteroides spp., based on age and management. Lactic acid bacteria Lactobacillus spp. and other Lactobacillaceae genera were enriched only in DCM foals, specifically during their second and third week of life. Predicted microbiome functions estimated computationally suggested that SFM foals had higher mean sequence counts for taxa contributing to the digestion of lipids, simple and complex carbohydrates, and protein.
    [Show full text]
  • Evolution Génomique Chez Les Bactéries Du Super Phylum Planctomycetes-Verrucomicrobiae-Chlamydia
    AIX-MARSEILLE UNIVERSITE FACULTE DE MEDECINE DE MARSEILLE ECOLE DOCTORALE : SCIENCE DE LA VIE ET DE LA SANTE THESE Présentée et publiquement soutenue devant LA FACULTE DE MEDECINE DE MARSEILLE Le 15 janvier 2016 Par Mme Sandrine PINOS Née à Saint-Gaudens le 09 octobre 1989 TITRE DE LA THESE: Evolution génomique chez les bactéries du super phylum Planctomycetes-Verrucomicrobiae-Chlamydia Pour obtenir le grade de DOCTORAT d'AIX-MARSEILLE UNIVERSITE Spécialité : Génomique et Bioinformatique Membres du jury de la Thèse: Pr Didier RAOULT .................................................................................Directeur de thèse Dr Pierre PONTAROTTI ....................................................................Co-directeur de thèse Pr Gilbert GREUB .............................................................................................Rapporteur Dr Pascal SIMONET............................................................................................Rapporteur Laboratoires d’accueil Unité de Recherche sur les Maladies Infectieuses et Tropicales Emergentes – UMR CNRS 6236, IRD 198 I2M - UMR CNRS 7373 - EBM 1 Avant propos Le format de présentation de cette thèse correspond à une recommandation de la spécialité Maladies Infectieuses et Microbiologie, à l’intérieur du Master de Sciences de la Vie et de la Santé qui dépend de l’Ecole Doctorale des Sciences de la Vie de Marseille. Le candidat est amené à respecter des règles qui lui sont imposées et qui comportent un format de thèse utilisé dans le Nord de l’Europe permettant un meilleur rangement que les thèses traditionnelles. Par ailleurs, la partie introduction et bibliographie est remplacée par une revue envoyée dans un journal afin de permettre une évaluation extérieure de la qualité de la revue et de permettre à l’étudiant de le commencer le plus tôt possible une bibliographie exhaustive sur le domaine de cette thèse. Par ailleurs, la thèse est présentée sur article publié, accepté ou soumis associé d’un bref commentaire donnant le sens général du travail.
    [Show full text]
  • WO 2018/064165 A2 (.Pdf)
    (12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date WO 2018/064165 A2 05 April 2018 (05.04.2018) W !P O PCT (51) International Patent Classification: Published: A61K 35/74 (20 15.0 1) C12N 1/21 (2006 .01) — without international search report and to be republished (21) International Application Number: upon receipt of that report (Rule 48.2(g)) PCT/US2017/053717 — with sequence listing part of description (Rule 5.2(a)) (22) International Filing Date: 27 September 2017 (27.09.2017) (25) Filing Language: English (26) Publication Langi English (30) Priority Data: 62/400,372 27 September 2016 (27.09.2016) US 62/508,885 19 May 2017 (19.05.2017) US 62/557,566 12 September 2017 (12.09.2017) US (71) Applicant: BOARD OF REGENTS, THE UNIVERSI¬ TY OF TEXAS SYSTEM [US/US]; 210 West 7th St., Austin, TX 78701 (US). (72) Inventors: WARGO, Jennifer; 1814 Bissonnet St., Hous ton, TX 77005 (US). GOPALAKRISHNAN, Vanch- eswaran; 7900 Cambridge, Apt. 10-lb, Houston, TX 77054 (US). (74) Agent: BYRD, Marshall, P.; Parker Highlander PLLC, 1120 S. Capital Of Texas Highway, Bldg. One, Suite 200, Austin, TX 78746 (US). (81) Designated States (unless otherwise indicated, for every kind of national protection available): AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW.
    [Show full text]
  • Table S4. Phylogenetic Distribution of Bacterial and Archaea Genomes in Groups A, B, C, D, and X
    Table S4. Phylogenetic distribution of bacterial and archaea genomes in groups A, B, C, D, and X. Group A a: Total number of genomes in the taxon b: Number of group A genomes in the taxon c: Percentage of group A genomes in the taxon a b c cellular organisms 5007 2974 59.4 |__ Bacteria 4769 2935 61.5 | |__ Proteobacteria 1854 1570 84.7 | | |__ Gammaproteobacteria 711 631 88.7 | | | |__ Enterobacterales 112 97 86.6 | | | | |__ Enterobacteriaceae 41 32 78.0 | | | | | |__ unclassified Enterobacteriaceae 13 7 53.8 | | | | |__ Erwiniaceae 30 28 93.3 | | | | | |__ Erwinia 10 10 100.0 | | | | | |__ Buchnera 8 8 100.0 | | | | | | |__ Buchnera aphidicola 8 8 100.0 | | | | | |__ Pantoea 8 8 100.0 | | | | |__ Yersiniaceae 14 14 100.0 | | | | | |__ Serratia 8 8 100.0 | | | | |__ Morganellaceae 13 10 76.9 | | | | |__ Pectobacteriaceae 8 8 100.0 | | | |__ Alteromonadales 94 94 100.0 | | | | |__ Alteromonadaceae 34 34 100.0 | | | | | |__ Marinobacter 12 12 100.0 | | | | |__ Shewanellaceae 17 17 100.0 | | | | | |__ Shewanella 17 17 100.0 | | | | |__ Pseudoalteromonadaceae 16 16 100.0 | | | | | |__ Pseudoalteromonas 15 15 100.0 | | | | |__ Idiomarinaceae 9 9 100.0 | | | | | |__ Idiomarina 9 9 100.0 | | | | |__ Colwelliaceae 6 6 100.0 | | | |__ Pseudomonadales 81 81 100.0 | | | | |__ Moraxellaceae 41 41 100.0 | | | | | |__ Acinetobacter 25 25 100.0 | | | | | |__ Psychrobacter 8 8 100.0 | | | | | |__ Moraxella 6 6 100.0 | | | | |__ Pseudomonadaceae 40 40 100.0 | | | | | |__ Pseudomonas 38 38 100.0 | | | |__ Oceanospirillales 73 72 98.6 | | | | |__ Oceanospirillaceae
    [Show full text]
  • Supplemental Material S1.Pdf
    Phylogeny of Selenophosphate synthetases (SPS) Supplementary Material S1 ! SelD in prokaryotes! ! ! SelD gene finding in sequenced prokaryotes! We downloaded a total of 8263 prokaryotic genomes from NCBI (see Supplementary Material S7). We scanned them with the program selenoprofiles (Mariotti 2010, http:// big.crg.cat/services/selenoprofiles) using two SPS-family profiles, one prokaryotic (seld) and one mixed eukaryotic-prokaryotic (SPS). Selenoprofiles removes overlapping predictions from different profiles, keeping only the prediction from the profile that seems closer to the candidate sequence. As expected, the great majority of output predictions in prokaryotic genomes were from the seld profile. We will refer to the prokaryotic SPS/SelD !genes as SelD, following the most common nomenclature in literature.! To be able to inspect results by hand, and also to focus on good-quality genomes, we considered a reduced set of species. We took the prok_reference_genomes.txt list from ftp://ftp.ncbi.nlm.nih.gov/genomes/GENOME_REPORTS/, which NCBI claims to be a "small curated subset of really good and scientifically important prokaryotic genomes". We named this the prokaryotic reference set (223 species - see Supplementary Material S8). We manually curated most of the analysis in this set, while we kept automatized the !analysis on the full set.! We detected SelD proteins in 58 genomes (26.0%) in the prokaryotic reference set (figure 1 in main paper), which become 2805 (33.9%) when considering the prokaryotic full set (figure SM1.1). The difference in proportion between the two sets is due largely to the presence of genomes of very close strains in the full set, which we consider redundant.
    [Show full text]
  • Yu-Chen Ling and John W. Moreau
    Microbial Distribution and Activity in a Coastal Acid Sulfate Soil System Introduction: Bioremediation in Yu-Chen Ling and John W. Moreau coastal acid sulfate soil systems Method A Coastal acid sulfate soil (CASS) systems were School of Earth Sciences, University of Melbourne, Melbourne, VIC 3010, Australia formed when people drained the coastal area Microbial distribution controlled by environmental parameters Microbial activity showed two patterns exposing the soil to the air. Drainage makes iron Microbial structures can be grouped into three zones based on the highest similarity between samples (Fig. 4). Abundant populations, such as Deltaproteobacteria, kept constant activity across tidal cycling, whereas rare sulfides oxidize and release acidity to the These three zones were consistent with their geological background (Fig. 5). Zone 1: Organic horizon, had the populations changed activity response to environmental variations. Activity = cDNA/DNA environment, low pH pore water further dissolved lowest pH value. Zone 2: surface tidal zone, was influenced the most by tidal activity. Zone 3: Sulfuric zone, Abundant populations: the heavy metals. The acidity and toxic metals then Method A Deltaproteobacteria Deltaproteobacteria this area got neutralized the most. contaminate coastal and nearby ecosystems and Method B 1.5 cause environmental problems, such as fish kills, 1.5 decreased rice yields, release of greenhouse gases, Chloroflexi and construction damage. In Australia, there is Gammaproteobacteria Gammaproteobacteria about a $10 billion “legacy” from acid sulfate soils, Chloroflexi even though Australia is only occupied by around 1.0 1.0 Cyanobacteria,@ Acidobacteria Acidobacteria Alphaproteobacteria 18% of the global acid sulfate soils. Chloroplast Zetaproteobacteria Rare populations: Alphaproteobacteria Method A log(RNA(%)+1) Zetaproteobacteria log(RNA(%)+1) Method C Method B 0.5 0.5 Cyanobacteria,@ Bacteroidetes Chloroplast Firmicutes Firmicutes Bacteroidetes Planctomycetes Planctomycetes Ac8nobacteria Fig.
    [Show full text]