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Microbial Community Structure Dynamics in Ohio River Sediments During Reductive Dechlorination of Pcbs
University of Kentucky UKnowledge University of Kentucky Doctoral Dissertations Graduate School 2008 MICROBIAL COMMUNITY STRUCTURE DYNAMICS IN OHIO RIVER SEDIMENTS DURING REDUCTIVE DECHLORINATION OF PCBS Andres Enrique Nunez University of Kentucky Right click to open a feedback form in a new tab to let us know how this document benefits ou.y Recommended Citation Nunez, Andres Enrique, "MICROBIAL COMMUNITY STRUCTURE DYNAMICS IN OHIO RIVER SEDIMENTS DURING REDUCTIVE DECHLORINATION OF PCBS" (2008). University of Kentucky Doctoral Dissertations. 679. https://uknowledge.uky.edu/gradschool_diss/679 This Dissertation is brought to you for free and open access by the Graduate School at UKnowledge. It has been accepted for inclusion in University of Kentucky Doctoral Dissertations by an authorized administrator of UKnowledge. For more information, please contact [email protected]. ABSTRACT OF DISSERTATION Andres Enrique Nunez The Graduate School University of Kentucky 2008 MICROBIAL COMMUNITY STRUCTURE DYNAMICS IN OHIO RIVER SEDIMENTS DURING REDUCTIVE DECHLORINATION OF PCBS ABSTRACT OF DISSERTATION A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the College of Agriculture at the University of Kentucky By Andres Enrique Nunez Director: Dr. Elisa M. D’Angelo Lexington, KY 2008 Copyright © Andres Enrique Nunez 2008 ABSTRACT OF DISSERTATION MICROBIAL COMMUNITY STRUCTURE DYNAMICS IN OHIO RIVER SEDIMENTS DURING REDUCTIVE DECHLORINATION OF PCBS The entire stretch of the Ohio River is under fish consumption advisories due to contamination with polychlorinated biphenyls (PCBs). In this study, natural attenuation and biostimulation of PCBs and microbial communities responsible for PCB transformations were investigated in Ohio River sediments. Natural attenuation of PCBs was negligible in sediments, which was likely attributed to low temperature conditions during most of the year, as well as low amounts of available nitrogen, phosphorus, and organic carbon. -
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. -
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 -
Extensive Microbial Diversity Within the Chicken Gut Microbiome Revealed by Metagenomics and Culture
Extensive microbial diversity within the chicken gut microbiome revealed by metagenomics and culture Rachel Gilroy1, Anuradha Ravi1, Maria Getino2, Isabella Pursley2, Daniel L. Horton2, Nabil-Fareed Alikhan1, Dave Baker1, Karim Gharbi3, Neil Hall3,4, Mick Watson5, Evelien M. Adriaenssens1, Ebenezer Foster-Nyarko1, Sheikh Jarju6, Arss Secka7, Martin Antonio6, Aharon Oren8, Roy R. Chaudhuri9, Roberto La Ragione2, Falk Hildebrand1,3 and Mark J. Pallen1,2,4 1 Quadram Institute Bioscience, Norwich, UK 2 School of Veterinary Medicine, University of Surrey, Guildford, UK 3 Earlham Institute, Norwich Research Park, Norwich, UK 4 University of East Anglia, Norwich, UK 5 Roslin Institute, University of Edinburgh, Edinburgh, UK 6 Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Atlantic Boulevard, Banjul, The Gambia 7 West Africa Livestock Innovation Centre, Banjul, The Gambia 8 Department of Plant and Environmental Sciences, The Alexander Silberman Institute of Life Sciences, Edmond J. Safra Campus, Hebrew University of Jerusalem, Jerusalem, Israel 9 Department of Molecular Biology and Biotechnology, University of Sheffield, Sheffield, UK ABSTRACT Background: The chicken is the most abundant food animal in the world. However, despite its importance, the chicken gut microbiome remains largely undefined. Here, we exploit culture-independent and culture-dependent approaches to reveal extensive taxonomic diversity within this complex microbial community. Results: We performed metagenomic sequencing of fifty chicken faecal samples from Submitted 4 December 2020 two breeds and analysed these, alongside all (n = 582) relevant publicly available Accepted 22 January 2021 chicken metagenomes, to cluster over 20 million non-redundant genes and to Published 6 April 2021 construct over 5,500 metagenome-assembled bacterial genomes. -
Table S5. the Information of the Bacteria Annotated in the Soil Community at Species Level
Table S5. The information of the bacteria annotated in the soil community at species level No. Phylum Class Order Family Genus Species The number of contigs Abundance(%) 1 Firmicutes Bacilli Bacillales Bacillaceae Bacillus Bacillus cereus 1749 5.145782459 2 Bacteroidetes Cytophagia Cytophagales Hymenobacteraceae Hymenobacter Hymenobacter sedentarius 1538 4.52499338 3 Gemmatimonadetes Gemmatimonadetes Gemmatimonadales Gemmatimonadaceae Gemmatirosa Gemmatirosa kalamazoonesis 1020 3.000970902 4 Proteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas Sphingomonas indica 797 2.344876284 5 Firmicutes Bacilli Lactobacillales Streptococcaceae Lactococcus Lactococcus piscium 542 1.594633558 6 Actinobacteria Thermoleophilia Solirubrobacterales Conexibacteraceae Conexibacter Conexibacter woesei 471 1.385742446 7 Proteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas Sphingomonas taxi 430 1.265115184 8 Proteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas Sphingomonas wittichii 388 1.141545794 9 Proteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas Sphingomonas sp. FARSPH 298 0.876754244 10 Proteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas Sorangium cellulosum 260 0.764953367 11 Proteobacteria Deltaproteobacteria Myxococcales Polyangiaceae Sorangium Sphingomonas sp. Cra20 260 0.764953367 12 Proteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas Sphingomonas panacis 252 0.741416341 -
Role of Actinobacteria and Coriobacteriia in the Antidepressant Effects of Ketamine in an Inflammation Model of Depression
Pharmacology, Biochemistry and Behavior 176 (2019) 93–100 Contents lists available at ScienceDirect Pharmacology, Biochemistry and Behavior journal homepage: www.elsevier.com/locate/pharmbiochembeh Role of Actinobacteria and Coriobacteriia in the antidepressant effects of ketamine in an inflammation model of depression T Niannian Huanga,1, Dongyu Huaa,1, Gaofeng Zhana, Shan Lia, Bin Zhub, Riyue Jiangb, Ling Yangb, ⁎ ⁎ Jiangjiang Bia, Hui Xua, Kenji Hashimotoc, Ailin Luoa, , Chun Yanga, a Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China b Department of Internal Medicine, The Third Affiliated Hospital of Soochow University, Changzhou 213003, China c Division of Clinical Neuroscience, Chiba University Center for Forensic Mental Health, Chiba 260-8670, Japan ARTICLE INFO ABSTRACT Keywords: Ketamine, an N-methyl-D-aspartic acid receptor (NMDAR) antagonist, elicits rapid-acting and sustained anti- Ketamine depressant effects in treatment-resistant depressed patients. Accumulating evidence suggests that gut microbiota Depression via the gut-brain axis play a role in the pathogenesis of depression, thereby contributing to the antidepressant Lipopolysaccharide actions of certain compounds. Here we investigated the role of gut microbiota in the antidepressant effects of Gut microbiota ketamine in lipopolysaccharide (LPS)-induced inflammation model of depression. Ketamine (10 mg/kg) sig- nificantly attenuated the increased immobility time in forced swimming test (FST), which was associated with the improvements in α-diversity, consisting of Shannon, Simpson and Chao 1 indices. In addition to α-diversity, β-diversity, such as principal coordinates analysis (PCoA), and linear discriminant analysis (LDA) coupled with effect size measurements (LEfSe), showed a differential profile after ketamine treatment. -
Supplementary Data TMAO Microbiome R1
BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) Gut Content for Supplementary Data Tables Tables Page Annotation guide for taxonomic features. 1 Supplementary Data 1a. Microbial associations with TMAO, and intakes 7 of choline and red meat. Supplementary Data 1b. Microbial associations with TMAO in 8 15 sensitivity analysis models. Supplementary Data 2a. Associations of intakes of choline and red meat, 21 or other TMAO precursors with TMAO levels, stratified by TMAO- associated abundant species, in full models and additionally adjusted for other TMAO precursors or TMAO predicting species. Supplementary Data 2b. Associations of intakes of choline and red meat, 34 or other TMAO precursors with TMAO levels, stratified by TMAO- producer status, additionally adjusted for other TMAO precursors. Supplementary Data 2c. Associations of intakes of choline and red meat, 37 or other TMAO precursors with TMAO levels, stratified by TMAO- producer status, in 6 different sensitivity analysis models. Supplementary Data 2d. Associations of intakes of red meat with HDLC 39 and HBA1c levels, stratified by TMAO-producer status or TMAO- associated abundant species. Supplementary Data 3a. Association of DNA gene clusters within 40 TMAO-associated species with plasma TMAO levels, and intakes of choline and red meat. Supplementary Data 3b. Association of transcriptions of gene clusters 46 (RNA/DNA ratio) within TMAO-associated species with plasma TMAO levels, and intakes of choline and red meat. Supplementary Data 4a. Association of DNA enzyme within TMAO- 62 associated species with plasma TMAO levels, and intakes of choline and red meat. -
Diversity and Composition of the Skin, Blood and Gut Microbiome in Rosacea—A Systematic Review of the Literature
microorganisms Review Diversity and Composition of the Skin, Blood and Gut Microbiome in Rosacea—A Systematic Review of the Literature Klaudia Tutka, Magdalena Zychowska˙ and Adam Reich * Department of Dermatology, Institute of Medical Sciences, Medical College of Rzeszow University, 35-055 Rzeszow, Poland; [email protected] (K.T.); [email protected] (M.Z.)˙ * Correspondence: [email protected]; Tel.: +48-605076722 Received: 30 August 2020; Accepted: 6 November 2020; Published: 8 November 2020 Abstract: Rosacea is a chronic inflammatory skin disorder of a not fully understood pathophysiology. Microbial factors, although not precisely characterized, are speculated to contribute to the development of the condition. The aim of the current review was to summarize the rosacea-associated alterations in the skin, blood, and gut microbiome, investigated using culture-independent, metagenomic techniques. A systematic review of the PubMed, Web of Science, and Scopus databases was performed, according to PRISMA (preferred reporting items for systematic review and meta-analyses) guidelines. Nine out of 185 papers were eligible for analysis. Skin microbiome was investigated in six studies, and in a total number of 115 rosacea patients. Blood microbiome was the subject of one piece of research, conducted in 10 patients with rosacea, and gut microbiome was studied in two papers, and in a total of 23 rosacea subjects. Although all of the studies showed significant alterations in the composition of the skin, blood, or gut microbiome in rosacea, the results were highly inconsistent, or even, in some cases, contradictory. Major limitations included the low number of participants, and different study populations (mainly Asians). Further studies are needed in order to reliably analyze the composition of microbiota in rosacea, and the potential application of microbiome modifications for the treatment of this dermatosis. -
Neocallimastix Californiae G1 36,250,970 NA 29,649 95.52 85.2 SRX2598479 (3)
Supplementary material for: Horizontal gene transfer as an indispensable driver for Neocallimastigomycota evolution into a distinct gut-dwelling fungal lineage 1 1 1 2 Chelsea L. Murphy ¶, Noha H. Youssef ¶, Radwa A. Hanafy , MB Couger , Jason E. Stajich3, Y. Wang3, Kristina Baker1, Sumit S. Dagar4, Gareth W. Griffith5, Ibrahim F. Farag1, TM Callaghan6, and Mostafa S. Elshahed1* Table S1. Validation of HGT-identification pipeline using previously published datasets. The frequency of HGT occurrence in the genomes of a filamentous ascomycete and a microsporidian were determined using our pipeline. The results were compared to previously published results. Organism NCBI Assembly Reference Method used Value Value accession number to original in the original reported obtained study study in this study Colletotrichum GCA_000149035.1 (1) Blast and tree 11 11 graminicola building approaches Encephalitozoon GCA_000277815.3 (2) Blast against 12-22 4 hellem custom database, AI score calculation, and tree building Table S2. Results of transcriptomic sequencing. Accession number Genus Species Strain Number of Assembled Predicted peptides % genome Ref. reads transcriptsa (Longest Orfs)b completenessc coveraged (%) Anaeromyces contortus C3G 33,374,692 50,577 22,187 96.55 GGWR00000000 This study Anaeromyces contortus C3J 54,320,879 57,658 26,052 97.24 GGWO00000000 This study Anaeromyces contortus G3G 43,154,980 52,929 21,681 91.38 GGWP00000000 This study Anaeromyces contortus Na 42,857,287 47,378 19,386 93.45 GGWN00000000 This study Anaeromyces contortus O2 60,442,723 62,300 27,322 96.9 GGWQ00000000 This study Anaeromyces robustus S4 21,955,935 NA 17,127 92.41 88.7 SRX3329608 (3) Caecomyces sp. -
Associations Between Acute Gastrointestinal Gvhd and the Baseline Gut Microbiota of Allogeneic Hematopoietic Stem Cell Transplant Recipients and Donors
Bone Marrow Transplantation (2017) 52, 1643–1650 © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved 0268-3369/17 www.nature.com/bmt ORIGINAL ARTICLE Associations between acute gastrointestinal GvHD and the baseline gut microbiota of allogeneic hematopoietic stem cell transplant recipients and donors C Liu1, DN Frank2, M Horch3, S Chau2,DIr2, EA Horch3, K Tretina3, K van Besien3, CA Lozupone2,4 and VH Nguyen2,3,4 Growing evidence suggests that host-microbiota interactions influence GvHD risk following allogeneic hematopoietic stem cell transplant. However, little is known about the influence of the transplant recipient’s pre-conditioning microbiota nor the influence of the transplant donor’s microbiota. Our study examines associations between acute gastrointestinal GvHD (agGvHD) and 16S rRNA fecal bacterial profiles in a prospective cohort of N = 57 recipients before preparative conditioning, as well as N = 22 of their paired HLA-matched sibling donors. On average, recipients had lower fecal bacterial diversity (P = 0.0002) and different phylogenetic membership (UniFrac P = 0.001) than the healthy transplant donors. Recipients with lower phylogenetic diversity had higher overall mortality rates (hazard ratio = 0.37, P = 0.008), but no statistically significant difference in agGvHD risk. In contrast, high bacterial donor diversity was associated with decreased agGvHD risk (odds ratio = 0.12, P = 0.038). Further investigation is warranted as to whether selection of hematopoietic stem cell transplant donors with high gut microbiota diversity and/or other specific compositional attributes may reduce agGvHD incidence, and by what mechanisms. Bone Marrow Transplantation (2017) 52, 1643–1650; doi:10.1038/bmt.2017.200; published online 2 October 2017 INTRODUCTION reporting GvHD as the primary outcome. -
Anxiolytic Effects of a Galacto-Oligosaccharides Prebiotic in Healthy Female Volunteers 2 Are Associated with Reduced Negative Bias and the Gut Bacterial Composition
medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 1 Anxiolytic effects of a galacto-oligosaccharides prebiotic in healthy female volunteers 2 are associated with reduced negative bias and the gut bacterial composition. 3 4 Nicola Johnstone1, Chiara Milesi1 , Olivia Burn1 , Bartholomeus van den Bogert2,3, Arjen 5 Nauta4 Kathryn Hart5, Paul Sowden1,6, Philip WJ Burnet7 ,Kathrin Cohen Kadosh1 6 1School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, 7 Guildford, UK 8 2BaseClear, Leiden, The Netherlands 9 3MyMicroZoo, Leiden, The Netherlands 10 4FrieslandCampina, Amersfoort, The Netherlands 11 5Department of Nutritional Sciences, School of Biosciences and Medicine, Faculty of Health 12 and Medical Sciences, University of Surrey, Guildford, UK 13 6Department of Psychology, University of Winchester, Winchester, UK 14 7Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK 15 16 17 Corresponding authors 18 Phone: ++44(0) 1483 68 3968 19 Email: [email protected] 20 URL: kcohenkadosh.com 21 Email: [email protected] 22 23 Acknowledgements: 24 This research was supported by faculty research fund from the Faculty of Health and 25 Medical Sciences, University of Surrey, UK to KCK. FrieslandCampina provided the galacto- 26 oligosaccharides (GOS, prebiotics) used in this study. 27 Competing interests 28 AN is an employee of FrieslandCampina. -
Variations in the Two Last Steps of the Purine Biosynthetic Pathway in Prokaryotes
GBE Different Ways of Doing the Same: Variations in the Two Last Steps of the Purine Biosynthetic Pathway in Prokaryotes Dennifier Costa Brandao~ Cruz1, Lenon Lima Santana1, Alexandre Siqueira Guedes2, Jorge Teodoro de Souza3,*, and Phellippe Arthur Santos Marbach1,* 1CCAAB, Biological Sciences, Recoˆ ncavo da Bahia Federal University, Cruz das Almas, Bahia, Brazil 2Agronomy School, Federal University of Goias, Goiania,^ Goias, Brazil 3 Department of Phytopathology, Federal University of Lavras, Minas Gerais, Brazil Downloaded from https://academic.oup.com/gbe/article/11/4/1235/5345563 by guest on 27 September 2021 *Corresponding authors: E-mails: [email protected]fla.br; [email protected]. Accepted: February 16, 2019 Abstract The last two steps of the purine biosynthetic pathway may be catalyzed by different enzymes in prokaryotes. The genes that encode these enzymes include homologs of purH, purP, purO and those encoding the AICARFT and IMPCH domains of PurH, here named purV and purJ, respectively. In Bacteria, these reactions are mainly catalyzed by the domains AICARFT and IMPCH of PurH. In Archaea, these reactions may be carried out by PurH and also by PurP and PurO, both considered signatures of this domain and analogous to the AICARFT and IMPCH domains of PurH, respectively. These genes were searched for in 1,403 completely sequenced prokaryotic genomes publicly available. Our analyses revealed taxonomic patterns for the distribution of these genes and anticorrelations in their occurrence. The analyses of bacterial genomes revealed the existence of genes coding for PurV, PurJ, and PurO, which may no longer be considered signatures of the domain Archaea. Although highly divergent, the PurOs of Archaea and Bacteria show a high level of conservation in the amino acids of the active sites of the protein, allowing us to infer that these enzymes are analogs.