DOCSLIB.ORG

Mental Figure 1 Color Key a -2 0 2 B Z-Score 100%

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Mental Figure 1 Color Key a -2 0 2 B Z-Score 100% Supplemental Figure 1 Color Key A -2 0 2 B z-score 100% 75% 50% 25% 0% KC pan 1 WT pan 3 WT KC pan 3 WT pan 2 WT pan 1 WT KC pan 2 C Color Key D a: Brevibacterium f: Chlamydiales b: Brevibacteriaceae g: Chlamydiia -3 0 3 z-score c: Sphingobacteriaceae h: Chlamydiae d: Sphingobacteriales i: Mogibacterium e: Sphingobacteriia j: Oscillospira k: Methylobacteriaceae NML Control Microb.-entrained MΦ PDA PDA Patient Population Control Microb.-entrained MΦ + Myd88i E F Ctrl Abx 350 * 300 250 200 150 40X 100 Tumor weight (mg) 50 0 x Ctrl Ab Supplemental Figure 2 A KC WT B ** * Actinobacteria * ** Bacteroidetes Cyanobacteria Deferribacteres * Firmicutes Proteobacteria % Relative abundance TM7 Others Time(wks) 3 9 13 16 20 24 28 32 36 3 9 13 16 20 24 28 32 36 Alpha Diversity Measure C E 60 KC WT 40 20 B. pseudolongum B. animalis 60 5 KC WT 0 B. adolescentis 40% Rel. abundance 3 9 13 16 20 24 28 32 36 3 9 13 16 20 24 28 32 36 20 Age (weeks) B. pseudolongum B. animalis 5 0 B. adolescentis % Rel. abundance 3 9 13 16 20 24 28 32 36 3 9 13 16 20 24 28 32 36 F Age (weeks) Week 3 Week 9 Week 13 p=0.678 p=0.02 p=0.385 Time(wks) 3 9 24 20 13 16 D 28 32 36 Week 13 KC WT Firmicutes; Ruminococcus Firmicutes; Dehalobacterium Alpha Diversity Measure Firmicutes; Oscillospira Bacteroidates; Odoribacter Axis.2 [12.7%] Actinobacteria; Bifidobacterium Axis.2 [23.8%] Axis.2 [24.7%] Week 16 Bacteroidetes; Bacteroidales Axis.1 [80.8%] Axis.1 [65.4%] Axis.1 [49.6%] Actinobacteria; Bifidobacterium Week 16 Week 20 Week 24 Week 20 p=0.339 p=0.036 p=0.021 Firmicutes; Dehalobacterium Firmicutes; Mogibacteriaceae Bacteroidetes; Bacteroidales Actinobacteria; Bifidobacterium Week 24 Firmicutes Unclass Lachnospiraceae Actinobacteria; Bifidobacterium Axis.2 [17.9%] Axis.2 [44.3%] Axis.2 [23.5%] Week 28 Firmicutes; Candidatus Arthromitus Axis.1 [73.3%] Axis.1 [48.6%] Axis.1 [66.6%] Deferribacteres; Mucispirillum Proteobacteria; G Desulfovibrionaceae Week 28 Week 32 p=0.014 p=0.002p=0.002 Firmicutes; Turicibacter Firmicutes; Coprococcus Actinobacteria; Cortobacteriaceae Actinobacteria; Bifidobacterium Week 36 Alpha Diversity Measure Firmicutes; Turicibacter Bacteroidetes; Bacteroides Axis.2 [23.6%] Bacteroidetes; Rikenellaceae Axis.2 [27.8%] Actinobacteria; Bifidobacterium -6.0 -4.8 -3.6 -2.4 -1.2 0 1.2 2.4 3.6 4.8 6.0 LDA Score (log 10) Axis.1 [59.0%] Axis.1 [63.5%] Supplemental Figure 3 A B C D Chao1 Observed Shannon PD whole tree * * * * * * * * Alpha Diversity Measure 60 KC WT 40 20 B. pseudolongum E B. animalis F 5 Chao1 Observed 0 B. adolescentis % Rel. abundance 3 9 13 16 20 24 28 32 36 3 9 13 16 20 24 28 32 36 * * * * * * Age (weeks) Alpha Diversity Measure G H Shannon PD whole tree * * * * * * Alpha Diversity Measure Supplemental Figure 4 A *** * % Relative abundance *** B Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient 9 Gut 2% 27% 7% 18% 13% 22% 1% 1% 4% 56% 45% 54% 57% 72% 18% 56% 52% 46% PDA Acidobacteria Tenericutes Firmicutes Bacteroidetes TM7 Synergistetes Deferribacteres Verrucomicrobia OD1 Fusobacteria Cyanobacteria Unassigned Lentisphaerae Actinobacteria Thermi Proteobacteria Gemmatimonadetes C D PDA Gut Veillonella Enterobacteriaceae a: Brachybacterium Alcaligenaceae b: Dermabacteraceae Enterococcus c: Prevotella Streptococcus d: Streptophyta Lachnospiraceae-Uncl. e: Enterococcus Lachnospiraceae f: Lactobacillus Clostridiales g: Coprococcus Prevotella h: Lachnospiraceae Bacteroides i: Butyricicoccus Blautia j: Fusobacterium Dialister k: Fusobacteriaceae Ruminococcaceae l: Acorus Ruminococcus m: Escherichia Faecalibacterium n: Treponema Methylobacterium o: Spirochaetaceae Delftia p: Spirochaetales q: Mycoplasma Elizabethkingia Duodenum Caulobacteraceae r: Mycoplasmataceae Pseudomonas Pancreas s: Mycoplasmatales 1 Pt. 2 3 8 9 1 7 5 4 6 7 9 6 5 4 2 8 3 Supplemental Figure 5 A Firmicutes; Megamonas NML Firmicutes; Dorea PDA Bacteroidetes; Prevotella Firmicutes; Gallicola Firmicutes; Christensenella Firmicutes; Anaerotruncus Firmicutes; Mogibacterium Proteobacteria; Escherichia TM7; TM7 3 Proteobacteria; Unclass. Enterobac. Actinobacteria; Rothia Proteobacteria; Proteus Synergistetes; Pyramidobacter Firmicutes; Unclassified Veillonellacea Bacteroidetes; Paraprevotella Firmicutes; Oribacterium Proteobacteria; Erwinia Fusobacteria; Leptotrichia Synergistetes; Synergistaceae Proteobacteria; Oxalobacter Firmicutes; Unclass. Aerococcaceae TM7; TM7 3CW040 Unassigned Firmicutes; Christensenellaceae Firmicutes; Veillonellaceae Proteobacteria; Cardiobacterium Proteobacteria; Klebsiella Firmicutes; Veillonella Bacterioidetes; Parabacteroides Proteobacteria; Enterbacteriaceae -4 -2 0 2 4 4% LDA Score (log 10) 46% B ACE Chao1 Observed Shannon Simpson PD 1.00 p=0.06 * ** ** ** *** a: Brachybacterium b: Dermabacteraceae c: Prevotella d: Streptophyta e: Enterococcus f: Lactobacillus g: Coprococcus h: Lachnospiraceae Alpha Diversity Measure i: Butyricicoccus j: Fusobacterium NML PDA NML PDA NML PDA NML PDA NML PDA NML PDA Supplemental Figure 6 A Abx Repop. Analysis B Repop. Analysis Cre G12D 8 14 16 22 Germ free 6 14 p48 ;Kras Cre G12D Weeks of life p48 ;Kras Weeks of life C Control Abx 6% 17% 20 D **** 39% 81% 53% + 15 SSA SSC 10 %CD3 5 CD3 Viability SSC-W CD45 0 * Ctrl Abx 40 E Control Abx 3 40 14 16 30 180 **** **** 20 150 Ctrl 10 % MDSCs Abx CD11b 120 ns 49 8 64 6 0 90 Gr1 Ctrl Abx * * Control (pg/ml) 60 F 60 Control Abx + * Abx *** ns 25 40 30 40 20 0 CD8 % of CD3 a b a 1 5 S 8 67 18 42 E 0 + + P-1 IP-3 Cxcl Cxcl CD4 CD8 MIP-1 MI M CD4 RANT G H Control Abx Control Abx 80 ** + 60 * Ctrl 40 6% 26% SSC 40% 74% SSC Abx CD8 CD8 % CD38 20 0 IFN-γ CD38 CD4+ CD8+ Control Abx I *** J Control Abx 50 * Control Abx 15 ns + + 4 40 D 30 10 C f 9% 9% o 20 SSC 14% 47% 5 CD4 %FoxP3 SSC % 10 0 0 + + ICOS ICOS LFA-1 FoxP3 Ctrl Abx K L M N ns O ns P ns * ** ** 75 20 65 70 * * 20 *** * 80 * ** + + 60 + Ctl a 15 52 56 15 60 45 39 42 Abx 10 10 40 30 T cells 26 28 Abx + KPC Feces % % T cells % CD44 5 5 % CD44 20 % TNF- 15 13 % MDSCs 14 0 0 0 0 0 0 Ctrl Abx Ctrl Abx Ctrl Abx Ctrl Abx Ctrl Abx Ctrl Abx KPC Repop KPC repop KPC Repop Supplemental Figure 7 A B *** Control Abx Abx + **** Control αPD-1 Abx αPD-1 * Ccl24 Ccl24 50 ns *** * Control Masp2 Masp2 + 40 Hmgn1 aPD-1 Hmgn1 30 Csf1 Csf1 11% 12% 26% 33% T Cells) SSC + 20 Abx C8b C8b C4a C4a % CD44 10 Abx + aPD-1 Retnla Retnla CD44 (CD4 0 Mapk3 Mapk3 *** **** Defa-rs1 Defa-rs1 C Abx + p=0.06 Gnas Gnas Control αPD-1 Abx αPD-1 ns ** * Control Il22 Il22 25 Hc Hc + 20 aPD-1 15 Ifna1 Ifna1 7% 7% 15% 20% T Cells) SSC Stat1 Stat1 + 10 Abx H2-Eb1 H2-Eb1 % CD44 5 Abx + aPD-1 Itgb2 Itgb2 CD44 (CD8 0 Ly96 Ly96 l o *** x Irf7 Irf7 D Abx + tr n PD-1 Ab* PD-1 Control αPD-1 Abx αPD-1 a ns a * Mknk1 Control Mknk1 Co ns 60 6 * x +*** Control Map3k1 Map3k1 + + Abx * Tnf Tnf Ab aPD-1 40 4 Mapkapk5 Mapkapk5 1% 3% 1% 7% T Cells) SSC + Abx Nfkb1 20 Nfkb1 2 Ifit2 Ifit2 % CXCR3 Abx + aPD-1 % of CD3 0 Cxcr4 Cxcr4 CXCR3 (CD4 0 + + l Cfd Cfd o x CD4 CD8 tr * Pik3c2g Pik3c2g n PD-1 Ab * PD-1 Abx + a a Gnaq Gnaq E Co ns Control αPD-1 Abx αPD-1 x + ns ns * Control 80 **Iigp1 Iigp1 40 Ab Il5 + + Il5 30 aPD-1 60 * Gnb1 Ctrl Gnb1 13% 19% 17% 38% T Cells) Mapkapk2 SSC 20 40 Mapkapk2 + Abx Ccl11 Abx Ccl11 10 % LFA-1 % CD38 20 Abx + aPD-1 Ccl19 Ccl19 LFA-1 (CD8 0 0 Il15 Il15 + + l Ctrl CD4 CD8Rock2 o x Rock2 tr n PD-1αPD-1Ab PD-1 Irf1 Irf1 a a Co Abx Birc2 Birc2 Abx, xαPD-1 + Raf1 Raf1 -1.7 Ab Ccl2 Ccl2 -1.2 Tgfb3 Tgfb3 -0.8 Cd55 Cd55 -0.4 0 Tyrobp Tyrobp 0.4 Mafk Mafk 0.8 Map2k6 Map2k6 1.2 Cd40lg Cd40lg 0 1.7 Supplemental Figure 8 Color Key A B ea-KPC adv-KPC -2 0 2 z-score Bacteroides Akkermansia Parabacteroides Blautia Rikenella Oscillospira Desulfovibrio H&E; 5x Ruminococcus Coprobacillus Odoribacter Rikenellaceae AF12 Flexispira Mucispirillum Bifidobacterium Sutterella C Candidatus Arthromitus Prevotella WT ea-KPC Lactobacillus Allobaculum Bacteroidetes; Prevotella Deferribacteres; Mucispirillum Paraprevotella Unassigned Bacteroidetes; Paraprevotella Firmicutes; Erysipelotrichaceae WT 5 WT 6 WT 4 WT 1 WT 3 WT 2 Proteobacteria; Helicobacteraceae ea-KPC 7 ea-KPC 6 ea-KPC 3 ea-KPC 8 ea-KPC 2 ea-KPC 4 ea-KPC 5 ea-KPC 1 Bacteroidetes; Bacteroidales adv-KPC 4 adv-KPC 3 adv-KPC 2 Adv-KPC 1 Firmicutes; Allobaculum Firmicutes; Coprobacillus Alpha Bacteroidetes; Prevotellaceae Proteobacteria; Flexispira Diversity Firmicutes; Anaerotruncus F G Measure Actinobacteria; Bifidobacterium Firmicutes; Unclass. Lachnospiraceae p=0.009 PD Firmicutes; Lachnospiraceae * * * -4 -2 0 2 4 LDA Score (log 10) D WT adv-KPC Bacteroidetes; Prevotella Firmicutes; Allobaculum Unassigned Firmicutes; Coprobacillus Axis.2 [13.4%] Firmicutes; Erysipelotrichaceae Bacteroidetes; Paraprevotella Actinobacteria; Bifidobacterium adv-KPC Firmicutes; Anaerotruncus ea-KPC Firmicutes; Unclass. Lactobacillales WT Firmicutes; Coprococcus Firmicutes; Unclass. Lachnospiraceae Firmicutes; Lachnospiraceae Axis.1 [57%] -4 -2 0 2 4 LDA Score (log 10) E H ea-KPC adv-KPC Stage I/II Stage IV Proteobacteria; Helicobacteraceae Firmicutes; Phascolarctobacterium Bacteroidetes; Bacteroidales Bacteroidetes; Paraprevotellaceae Firmicutes; Mogibacteriaceae Proteobacteria; Alcaligenaceae Bacteroidetes; Elizabethkingia Synergistetes;Unclassified;Synergistaceae Tenericutes; Mycoplasmataceae Firmicutes; Veillonella Proteobacteria; Enterobacteriaceae Firmicutes; Streptococcus -4 -2 0 2 4 -5 -4 -3 -2 -1 0 1 2 3 4 LDA Score (log 10) LDA Score (log 10).
Load more

Recommended publications
  • Bacterial Communities of the Upper Respiratory Tract of Turkeys
    www.nature.com/scientificreports OPEN Bacterial communities of the upper respiratory tract of turkeys Olimpia Kursa1*, Grzegorz Tomczyk1, Anna Sawicka‑Durkalec1, Aleksandra Giza2 & Magdalena Słomiany‑Szwarc2 The respiratory tracts of turkeys play important roles in the overall health and performance of the birds. Understanding the bacterial communities present in the respiratory tracts of turkeys can be helpful to better understand the interactions between commensal or symbiotic microorganisms and other pathogenic bacteria or viral infections. The aim of this study was the characterization of the bacterial communities of upper respiratory tracks in commercial turkeys using NGS sequencing by the amplifcation of 16S rRNA gene with primers designed for hypervariable regions V3 and V4 (MiSeq, Illumina). From 10 phyla identifed in upper respiratory tract in turkeys, the most dominated phyla were Firmicutes and Proteobacteria. Diferences in composition of bacterial diversity were found at the family and genus level. At the genus level, the turkey sequences present in respiratory tract represent 144 established bacteria. Several respiratory pathogens that contribute to the development of infections in the respiratory system of birds were identifed, including the presence of Ornithobacterium and Mycoplasma OTUs. These results obtained in this study supply information about bacterial composition and diversity of the turkey upper respiratory tract. Knowledge about bacteria present in the respiratory tract and the roles they can play in infections can be useful in controlling, diagnosing and treating commercial turkey focks. Next-generation sequencing has resulted in a marked increase in culture-independent studies characterizing the microbiome of humans and animals1–6. Much of these works have been focused on the gut microbiome of humans and other production animals 7–11.
    [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]
  • The Mysterious Orphans of Mycoplasmataceae
    The mysterious orphans of Mycoplasmataceae Tatiana V. Tatarinova1,2*, Inna Lysnyansky3, Yuri V. Nikolsky4,5,6, and Alexander Bolshoy7* 1 Children’s Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, 90027, California, USA 2 Spatial Science Institute, University of Southern California, Los Angeles, 90089, California, USA 3 Mycoplasma Unit, Division of Avian and Aquatic Diseases, Kimron Veterinary Institute, POB 12, Beit Dagan, 50250, Israel 4 School of Systems Biology, George Mason University, 10900 University Blvd, MSN 5B3, Manassas, VA 20110, USA 5 Biomedical Cluster, Skolkovo Foundation, 4 Lugovaya str., Skolkovo Innovation Centre, Mozhajskij region, Moscow, 143026, Russian Federation 6 Vavilov Institute of General Genetics, Moscow, Russian Federation 7 Department of Evolutionary and Environmental Biology and Institute of Evolution, University of Haifa, Israel 1,2 [email protected] 3 [email protected] 4-6 [email protected] 7 [email protected] 1 Abstract Background: The length of a protein sequence is largely determined by its function, i.e. each functional group is associated with an optimal size. However, comparative genomics revealed that proteins’ length may be affected by additional factors. In 2002 it was shown that in bacterium Escherichia coli and the archaeon Archaeoglobus fulgidus, protein sequences with no homologs are, on average, shorter than those with homologs [1]. Most experts now agree that the length distributions are distinctly different between protein sequences with and without homologs in bacterial and archaeal genomes. In this study, we examine this postulate by a comprehensive analysis of all annotated prokaryotic genomes and focusing on certain exceptions.
    [Show full text]
  • MIB–MIP Is a Mycoplasma System That Captures and Cleaves Immunoglobulin G
    MIB–MIP is a mycoplasma system that captures and cleaves immunoglobulin G Yonathan Arfia,b,1, Laetitia Minderc,d, Carmelo Di Primoe,f,g, Aline Le Royh,i,j, Christine Ebelh,i,j, Laurent Coquetk, Stephane Claveroll, Sanjay Vasheem, Joerg Joresn,o, Alain Blancharda,b, and Pascal Sirand-Pugneta,b aINRA (Institut National de la Recherche Agronomique), UMR 1332 Biologie du Fruit et Pathologie, F-33882 Villenave d’Ornon, France; bUniversity of Bordeaux, UMR 1332 Biologie du Fruit et Pathologie, F-33882 Villenave d’Ornon, France; cInstitut Européen de Chimie et Biologie, UMS 3033, University of Bordeaux, 33607 Pessac, France; dInstitut Bergonié, SIRIC BRIO, 33076 Bordeaux, France; eINSERM U1212, ARN Regulation Naturelle et Artificielle, 33607 Pessac, France; fCNRS UMR 5320, ARN Regulation Naturelle et Artificielle, 33607 Pessac, France; gInstitut Européen de Chimie et Biologie, University of Bordeaux, 33607 Pessac, France; hInstitut de Biologie Structurale, University of Grenoble Alpes, F-38044 Grenoble, France; iCNRS, Institut de Biologie Structurale, F-38044 Grenoble, France; jCEA, Institut de Biologie Structurale, F-38044 Grenoble, France; kCNRS UMR 6270, Plateforme PISSARO, Institute for Research and Innovation in Biomedicine - Normandie Rouen, Normandie Université, F-76821 Mont-Saint-Aignan, France; lProteome Platform, Functional Genomic Center of Bordeaux, University of Bordeaux, F-33076 Bordeaux Cedex, France; mJ. Craig Venter Institute, Rockville, MD 20850; nInternational Livestock Research Institute, 00100 Nairobi, Kenya; and oInstitute of Veterinary Bacteriology, University of Bern, CH-3001 Bern, Switzerland Edited by Roy Curtiss III, University of Florida, Gainesville, FL, and approved March 30, 2016 (received for review January 12, 2016) Mycoplasmas are “minimal” bacteria able to infect humans, wildlife, introduced into naive herds (8).
    [Show full text]
  • Supplementary Information for Microbial Electrochemical Systems Outperform Fixed-Bed Biofilters for Cleaning-Up Urban Wastewater
    Electronic Supplementary Material (ESI) for Environmental Science: Water Research & Technology. This journal is © The Royal Society of Chemistry 2016 Supplementary information for Microbial Electrochemical Systems outperform fixed-bed biofilters for cleaning-up urban wastewater AUTHORS: Arantxa Aguirre-Sierraa, Tristano Bacchetti De Gregorisb, Antonio Berná, Juan José Salasc, Carlos Aragónc, Abraham Esteve-Núñezab* Fig.1S Total nitrogen (A), ammonia (B) and nitrate (C) influent and effluent average values of the coke and the gravel biofilters. Error bars represent 95% confidence interval. Fig. 2S Influent and effluent COD (A) and BOD5 (B) average values of the hybrid biofilter and the hybrid polarized biofilter. Error bars represent 95% confidence interval. Fig. 3S Redox potential measured in the coke and the gravel biofilters Fig. 4S Rarefaction curves calculated for each sample based on the OTU computations. Fig. 5S Correspondence analysis biplot of classes’ distribution from pyrosequencing analysis. Fig. 6S. Relative abundance of classes of the category ‘other’ at class level. Table 1S Influent pre-treated wastewater and effluents characteristics. Averages ± SD HRT (d) 4.0 3.4 1.7 0.8 0.5 Influent COD (mg L-1) 246 ± 114 330 ± 107 457 ± 92 318 ± 143 393 ± 101 -1 BOD5 (mg L ) 136 ± 86 235 ± 36 268 ± 81 176 ± 127 213 ± 112 TN (mg L-1) 45.0 ± 17.4 60.6 ± 7.5 57.7 ± 3.9 43.7 ± 16.5 54.8 ± 10.1 -1 NH4-N (mg L ) 32.7 ± 18.7 51.6 ± 6.5 49.0 ± 2.3 36.6 ± 15.9 47.0 ± 8.8 -1 NO3-N (mg L ) 2.3 ± 3.6 1.0 ± 1.6 0.8 ± 0.6 1.5 ± 2.0 0.9 ± 0.6 TP (mg
    [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 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
    [Show full text]
  • Exploring the Diversity and Antimicrobial Potential of Marine Actinobacteria from the Comau Fjord in Northern Patagonia, Chile
    ORIGINAL RESEARCH published: 19 July 2016 doi: 10.3389/fmicb.2016.01135 Exploring the Diversity and Antimicrobial Potential of Marine Actinobacteria from the Comau Fjord in Northern Patagonia, Chile Agustina Undabarrena 1, Fabrizio Beltrametti 2, Fernanda P. Claverías 1, Myriam González 1, Edward R. B. Moore 3, 4, Michael Seeger 1 and Beatriz Cámara 1* 1 Laboratorio de Microbiología Molecular y Biotecnología Ambiental, Departamento de Química & Centro de Biotecnología Daniel Alkalay Lowitt, Universidad Técnica Federico Santa María, Valparaíso, Chile, 2 Actygea S.r.l., Gerenzano, Italy, 3 Culture Collection University of Gothenburg (CCUG), Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, 4 Department of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden Edited by: Bioprospecting natural products in marine bacteria from fjord environments are attractive Learn-Han Lee, due to their unique geographical features. Although, Actinobacteria are well known Monash University Malaysia Campus, Malaysia for producing a myriad of bioactive compounds, investigations regarding fjord-derived Reviewed by: marine Actinobacteria are scarce. In this study, the diversity and biotechnological Atte Von Wright, potential of Actinobacteria isolated from marine sediments within the Comau University of Eastern Finland, Finland fjord, in Northern Chilean Patagonia, were assessed by culture-based approaches. Polpass Arul Jose, Central Salt and Marine Chemicals The 16S rRNA gene sequences revealed that members phylogenetically related Research Institute, India to the Micrococcaceae, Dermabacteraceae, Brevibacteriaceae, Corynebacteriaceae, *Correspondence: Microbacteriaceae, Dietziaceae, Nocardiaceae, and Streptomycetaceae families were Beatriz Cámara [email protected] present at the Comau fjord. A high diversity of cultivable Actinobacteria (10 genera) was retrieved by using only five different isolation media.
    [Show full text]
  • Correlation Between the Oral Microbiome and Brain Resting State Connectivity in Smokers
    bioRxiv preprint doi: https://doi.org/10.1101/444612; this version posted October 16, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Correlation between the oral microbiome and brain resting state connectivity in smokers Dongdong Lin1, Kent Hutchison2, Salvador Portillo3, Victor Vegara1, Jarod Ellingson2, Jingyu Liu1,3, Amanda Carroll-Portillo3,* ,Vince D. Calhoun1,3,* 1The Mind Research Network, Albuquerque, New Mexico, 87106 2University of Colorado Boulder, Boulder, CO 3University of New Mexico, Department of Electrical and Computer Engineering, Albuquerque, New Mexico, 87106 * authors contributed equally to the work. Abstract Recent studies have shown a critical role for the gastrointestinal microbiome in brain and behavior via a complex gut–microbiome–brain axis, however, the influence of the oral microbiome in neurological processes is much less studied, especially in response to the stimuli in the oral microenvironment such as smoking. Additionally, given the complex structural and functional networks in brain system, our knowledge about the relationship between microbiome and brain functions on specific brain circuits is still very limited. In this pilot work, we leverage next generation microbial sequencing with functional MRI techniques to enable the delineation of microbiome-brain network links as well as their relations to cigarette smoking. Thirty smokers and 30 age- and sex- matched non-smokers were recruited for measuring both microbial community and brain functional networks. Statistical analyses were performed to demonstrate the influence of smoking on: the taxonomy and abundance of the constituents within the oral microbial community, brain functional network connectivity, and associations between microbial shifts and the brain signaling network.
    [Show full text]
  • Mapping the Bacterial Ecology on the Phyllosphere Of
    bioRxiv preprint doi: https://doi.org/10.1101/494799; this version posted December 12, 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 4.0 International license. 1 Mapping the bacterial ecology on the phyllosphere of grass hay and the 2 potential hazards of soaking fodder for horse gut health 3 Meriel JS Moore-Colyer1, Annette Longland2, Patricia Harris3, Susan Crosthwaite4 4 1 Royal Agricultural University, Cirencester Gloucestershire, UK GL7 6JS. 5 2Equine and Livestock Nutrition Services, Pantafallen Fach, Tregaron, Ceredigion, Wales. SY25 6NF 6 3Mars Horsecare UK LTD; Equine Studies Group, Waltham Centre for Pet Nutrition, Waltham-on-the Wolds, 7 Leicestershire, UK. LE14 4RT 8 4 Faculty of Biology, Medicine and Health, University of Manchester, UK M13 9PT. 9 10 Corresponding author: *[email protected] ORCID 0000-0002-9172-9862 11 12 Short title: The bacterial ecology on the phyllosphere of dry and post-soaked grass hay for 13 horses 14 bioRxiv preprint doi: https://doi.org/10.1101/494799; this version posted December 12, 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 4.0 International license. 15 Abstract 16 Globally hay is the preferred forage for stabled horses. Variable nutritional and hygienic quality stimulates pre- 17 feeding soaking to reduce dust and nutrients to reduce respiratory and metabolic disorders in horses.
    [Show full text]
  • Data Sheet on Spiroplasma Citri
    Prepared by CABI and EPPO for the EU under Contract 90/399003 Data Sheets on Quarantine Pests Spiroplasma citri The vectors of Spiroplasma citri are individually included in EU Directive 77/93. Since their importance only arises in relation to S. citri, they are covered in this data sheet. IDENTITY • Spiroplasma citri Name: Spiroplasma citri Saglio et al. Taxonomic position: Bacteria: Tenericutes: Mollicutes Common names: Stubborn, little leaf (English) Stubborn (French) Bayer computer code: SPIRCI EU Annex designation: II/A2 • Circulifer tenellus Name: Circulifer tenellus (Baker) Synonyms: Neoaliturus tenellus (Baker) Eutettix tenellus Baker Taxonomic position: Insecta: Hemiptera: Homoptera: Cicadellidae Common names: Beet leafhopper (English) Cicadelle de la betterave (French) Saltahojas de la remolacha (Spanish) Notes on taxonomy and nomenclature: Oman (1970) argues for the retention of Circulifer and Neoaliturus as separate genera; in his concept both tenellus and haematoceps are placed in Circulifer. Nast (1972) treats the two genera as Neoaliturus notwithstanding Oman's (1970) arguments for the retention of the two genera. He includes 17 species in the Palaearctic region of which 14 are recorded from the Mediterranean Basin. The two species, tenellus and haematoceps, are both included in Circulifer by della Giustina (1989), who reports that tenellus is confirmed in Corsica. Bayer computer code: CIRCTE EU Annex designation: II/A2 • Neoaliturus haematoceps Name: Neoaliturus haematoceps (Mulsant & Rey) Synonyms: Circulifer haematoceps (Mulsant & Rey) Jassus haematoceps Mulsant & Rey Taxonomic position: Insecta: Hemiptera: Homoptera: Cicadellidae Bayer computer code: NEOAHA EU Annex designation: II/A2 (under the name Circulifer haematoceps) HOSTS • Spiroplasma citri The principal economic hosts of S. citri are susceptible Citrus spp.
    [Show full text]
  • Downloaded from Genome Website
    bioRxiv preprint doi: https://doi.org/10.1101/2020.11.18.388454; this version posted November 19, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Characterization of the first cultured free-living representative of 2 Candidatus Izimaplasma uncovers its unique biology 3 Rikuan Zheng1,2,3,4, Rui Liu1,2,4, Yeqi Shan1,2,3,4, Ruining Cai1,2,3,4, Ge Liu1,2,4, Chaomin Sun1,2,4* 1 4 CAS Key Laboratory of Experimental Marine Biology & Center of Deep Sea 5 Research, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China 2 6 Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory 7 for Marine Science and Technology, Qingdao, China 3 8 College of Earth Science, University of Chinese Academy of Sciences, Beijing, 9 China 10 4Center of Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, China 11 12 * Corresponding author 13 Chaomin Sun Tel.: +86 532 82898857; fax: +86 532 82898857. 14 E-mail address: [email protected] 15 16 17 Key words: Candidatus Izimaplasma, uncultivation, biogeochemical cycling, 18 extracellular DNA, in situ, deep sea 19 Running title: Characterization of the first cultured Izimaplasma 20 21 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.11.18.388454; this version posted November 19, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 22 Abstract 23 Candidatus Izimaplasma, an intermediate in the reductive evolution from Firmicutes 24 to Mollicutes, was proposed to represent a novel class of free-living wall-less bacteria 25 within the phylum Tenericutes found in deep-sea methane seeps.
    [Show full text]