Molecular Analysis of Ftsz-Ring Assembly in <I>E. Coli</I> Cytokinesis
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Abstract Betaproteobacteria Alphaproteobacteria
Abstract N-210 Contact Information The majority of the soil’s biosphere containins biodiveristy that remains yet to be discovered. The occurrence of novel bacterial phyla in soil, as well as the phylogenetic diversity within bacterial phyla with few cultured representatives (e.g. Acidobacteria, Anne Spain Dr. Mostafa S.Elshahed Verrucomicrobia, and Gemmatimonadetes) have been previously well documented. However, few studies have focused on the Composition, Diversity, and Novelty within Soil Proteobacteria Department of Botany and Microbiology Department of Microbiology and Molecular Genetics novel phylogenetic diversity within phyla containing numerous cultured representatives. Here, we present a detailed University of Oklahoma Oklahoma State University phylogenetic analysis of the Proteobacteria-affiliated clones identified in a 13,001 nearly full-length 16S rRNA gene clones 770 Van Vleet Oval 307 LSE derived from Oklahoma tall grass prairie soil. Proteobacteria was the most abundant phylum in the community, and comprised Norman, OK 73019 Stillwater, OK 74078 25% of total clones. The most abundant and diverse class within the Proteobacteria was Alphaproteobacteria, which comprised 405 325 5255 405 744 6790 39% of Proteobacteria clones, followed by the Deltaproteobacteria, Betaproteobacteria, and Gammaproteobacteria, which made Anne M. Spain (1), Lee R. Krumholz (1), Mostafa S. Elshahed (2) up 37, 16, and 8% of Proteobacteria clones, respectively. Members of the Epsilonproteobacteria were not detected in the dataset. [email protected] [email protected] Detailed phylogenetic analysis indicated that 14% of the Proteobacteria clones belonged to 15 novel orders and 50% belonged (1) Dept. of Botany and Microbiology, University of Oklahoma, Norman, OK to orders with no described cultivated representatives or were unclassified. -
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 -
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 -
Which Organisms Are Used for Anti-Biofouling Studies
Table S1. Semi-systematic review raw data answering: Which organisms are used for anti-biofouling studies? Antifoulant Method Organism(s) Model Bacteria Type of Biofilm Source (Y if mentioned) Detection Method composite membranes E. coli ATCC25922 Y LIVE/DEAD baclight [1] stain S. aureus ATCC255923 composite membranes E. coli ATCC25922 Y colony counting [2] S. aureus RSKK 1009 graphene oxide Saccharomycetes colony counting [3] methyl p-hydroxybenzoate L. monocytogenes [4] potassium sorbate P. putida Y. enterocolitica A. hydrophila composite membranes E. coli Y FESEM [5] (unspecified/unique sample type) S. aureus (unspecified/unique sample type) K. pneumonia ATCC13883 P. aeruginosa BAA-1744 composite membranes E. coli Y SEM [6] (unspecified/unique sample type) S. aureus (unspecified/unique sample type) graphene oxide E. coli ATCC25922 Y colony counting [7] S. aureus ATCC9144 P. aeruginosa ATCCPAO1 composite membranes E. coli Y measuring flux [8] (unspecified/unique sample type) graphene oxide E. coli Y colony counting [9] (unspecified/unique SEM sample type) LIVE/DEAD baclight S. aureus stain (unspecified/unique sample type) modified membrane P. aeruginosa P60 Y DAPI [10] Bacillus sp. G-84 LIVE/DEAD baclight stain bacteriophages E. coli (K12) Y measuring flux [11] ATCC11303-B4 quorum quenching P. aeruginosa KCTC LIVE/DEAD baclight [12] 2513 stain modified membrane E. coli colony counting [13] (unspecified/unique colony counting sample type) measuring flux S. aureus (unspecified/unique sample type) modified membrane E. coli BW26437 Y measuring flux [14] graphene oxide Klebsiella colony counting [15] (unspecified/unique sample type) P. aeruginosa (unspecified/unique sample type) graphene oxide P. aeruginosa measuring flux [16] (unspecified/unique sample type) composite membranes E. -
Taxonomy JN869023
Species that differentiate periods of high vs. low species richness in unattached communities Species Taxonomy JN869023 Bacteria; Actinobacteria; Actinobacteria; Actinomycetales; ACK-M1 JN674641 Bacteria; Bacteroidetes; [Saprospirae]; [Saprospirales]; Chitinophagaceae; Sediminibacterium JN869030 Bacteria; Actinobacteria; Actinobacteria; Actinomycetales; ACK-M1 U51104 Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Comamonadaceae; Limnohabitans JN868812 Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Comamonadaceae JN391888 Bacteria; Planctomycetes; Planctomycetia; Planctomycetales; Planctomycetaceae; Planctomyces HM856408 Bacteria; Planctomycetes; Phycisphaerae; Phycisphaerales GQ347385 Bacteria; Verrucomicrobia; [Methylacidiphilae]; Methylacidiphilales; LD19 GU305856 Bacteria; Proteobacteria; Alphaproteobacteria; Rickettsiales; Pelagibacteraceae GQ340302 Bacteria; Actinobacteria; Actinobacteria; Actinomycetales JN869125 Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Comamonadaceae New.ReferenceOTU470 Bacteria; Cyanobacteria; ML635J-21 JN679119 Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Comamonadaceae HM141858 Bacteria; Acidobacteria; Holophagae; Holophagales; Holophagaceae; Geothrix FQ659340 Bacteria; Verrucomicrobia; [Pedosphaerae]; [Pedosphaerales]; auto67_4W AY133074 Bacteria; Elusimicrobia; Elusimicrobia; Elusimicrobiales FJ800541 Bacteria; Verrucomicrobia; [Pedosphaerae]; [Pedosphaerales]; R4-41B JQ346769 Bacteria; Acidobacteria; [Chloracidobacteria]; RB41; Ellin6075 -
Parst Is a Widespread Toxin–Antitoxin Module That Targets Nucleotide Metabolism
ParST is a widespread toxin–antitoxin module that targets nucleotide metabolism Frank J. Piscottaa, Philip D. Jeffreyb, and A. James Linka,b,c,1 aDepartment of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544; bDepartment of Molecular Biology, Princeton University, Princeton, NJ 08544; and cDepartment of Chemistry, Princeton University, Princeton, NJ 08544 Edited by Marlene Belfort, University at Albany, Albany, NY, and approved December 4, 2018 (received for review August 27, 2018) Toxin–antitoxin (TA) systems interfere with essential cellular pro- I toxins are typified by an RNA-level TA interaction, where an cesses and are implicated in bacterial lifestyle adaptations such as antisense RNA binds toxin mRNA to inhibit its translation. Type persistence and the biofilm formation. Here, we present structural, II TA systems function via protein–protein interactions, where biochemical, and functional data on an uncharacterized TA system, binding of the antitoxin to the toxin inhibits its activity (10). Of the COG5654–COG5642 pair. Bioinformatic analysis showed that the two earliest known TA systems mentioned above, hok/sok is this TA pair is found in 2,942 of the 16,286 distinct bacterial species an example of a type I system, while ccdAB is type II (11, 12). in the RefSeq database. We solved a structure of the toxin bound Upon translation, type I toxins are small, hydrophobic peptides to a fragment of the antitoxin to 1.50 Å. This structure suggested that lead to cell lysis through disruption of the plasma mem- that the toxin is a mono-ADP-ribosyltransferase (mART). The toxin brane. Type II toxins, however, function through a variety of specifically modifies phosphoribosyl pyrophosphate synthetase mechanisms. -
Host-Adaptation in Legionellales Is 2.4 Ga, Coincident with Eukaryogenesis
bioRxiv preprint doi: https://doi.org/10.1101/852004; this version posted February 27, 2020. 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 4.0 International license. 1 Host-adaptation in Legionellales is 2.4 Ga, 2 coincident with eukaryogenesis 3 4 5 Eric Hugoson1,2, Tea Ammunét1 †, and Lionel Guy1* 6 7 1 Department of Medical Biochemistry and Microbiology, Science for Life Laboratories, 8 Uppsala University, Box 582, 75123 Uppsala, Sweden 9 2 Department of Microbial Population Biology, Max Planck Institute for Evolutionary 10 Biology, D-24306 Plön, Germany 11 † current address: Medical Bioinformatics Centre, Turku Bioscience, University of Turku, 12 Tykistökatu 6A, 20520 Turku, Finland 13 * corresponding author 14 1 bioRxiv preprint doi: https://doi.org/10.1101/852004; this version posted February 27, 2020. 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 4.0 International license. 15 Abstract 16 Bacteria adapting to living in a host cell caused the most salient events in the evolution of 17 eukaryotes, namely the seminal fusion with an archaeon 1, and the emergence of both the 18 mitochondrion and the chloroplast 2. A bacterial clade that may hold the key to understanding 19 these events is the deep-branching gammaproteobacterial order Legionellales – containing 20 among others Coxiella and Legionella – of which all known members grow inside eukaryotic 21 cells 3. -
Exploring Bacteria Diversity in Commercialized Table Olive Biofilms
www.nature.com/scientificreports OPEN Exploring bacteria diversity in commercialized table olive bioflms by metataxonomic and compositional data analysis Antonio Benítez‑Cabello1, Verónica Romero‑Gil2, Eduardo Medina‑Pradas1, Antonio Garrido‑Fernández1 & Francisco Noé Arroyo‑López1* In this work, a total of 72 samples of non-thermally treated commercial table olives were obtained from diferent markets of the world. Then, prokaryotic diversity in olive bioflms was investigated by metataxonomic analysis. A total of 660 diferent OTUs were obtained, belonging to Archaea (2.12%) and Bacteria domains (97.88%). From these, 41 OTUs with a proportion of sequences ≥ 0.01% were studied by compositional data analysis. Only two genera were found in all samples, Lactobacillus, which was the predominant bacteria in the bioflm consortium (median 54.99%), and Pediococcus (26.09%). Celerinatantimonas, Leuconostoc, Alkalibacterium, Pseudomonas, Marinilactibacillus, Weissella, and the family Enterobacteriaceae were also present in at least 80% of samples. Regarding foodborne pathogens, only Enterobacteriaceae, Vibrio, and Staphylococcus were detected in at least 91.66%, 75.00%, and 54.10% of samples, respectively, but their median values were always below 0.15%. Compositional data analysis allowed discriminating between lye treated and natural olive samples, as well as between olives packaged in glass, PET and plastic bags. Leuconostoc, Celerinatantimonas, and Alkalibacterium were the bacteria genera with a higher discriminant power among samples. These results expand our knowledge of the bacteria diversity in olive bioflms, providing information about the sanitary and hygienic status of this ready‑to‑eat fermented vegetable. Te world’s olive grove consists of more than 10 million hectares, of which over 1 million are destined to table olives, which constitute the most important fermented vegetable in the Mediterranean countries, with also noticeable productions in South America, USA and Australia. -
Wedding Higher Taxonomic Ranks with Metabolic Signatures Coded in Prokaryotic Genomes
Wedding higher taxonomic ranks with metabolic signatures coded in prokaryotic genomes Gregorio Iraola*, Hugo Naya* Corresponding authors: E-mail: [email protected], [email protected] This PDF file includes: Supplementary Table 1 Supplementary Figures 1 to 4 Supplementary Methods SUPPLEMENTARY TABLES Supplementary Tab. 1 Supplementary Tab. 1. Full prediction for the set of 108 external genomes used as test. genome domain phylum class order family genus prediction alphaproteobacterium_LFTY0 Bacteria Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Unknown candidatus_nasuia_deltocephalinicola_PUNC_CP013211 Bacteria Proteobacteria Gammaproteobacteria Unknown Unknown Unknown candidatus_sulcia_muelleri_PUNC_CP013212 Bacteria Bacteroidetes Flavobacteriia Flavobacteriales NA Candidatus Sulcia deinococcus_grandis_ATCC43672_BCMS0 Bacteria Deinococcus-Thermus Deinococci Deinococcales Deinococcaceae Deinococcus devosia_sp_H5989_CP011300 Bacteria Proteobacteria Unknown Unknown Unknown Unknown micromonospora_RV43_LEKG0 Bacteria Actinobacteria Actinobacteria Micromonosporales Micromonosporaceae Micromonospora nitrosomonas_communis_Nm2_CP011451 Bacteria Proteobacteria Betaproteobacteria Nitrosomonadales Nitrosomonadaceae Unknown nocardia_seriolae_U1_BBYQ0 Bacteria Actinobacteria Actinobacteria Corynebacteriales Nocardiaceae Nocardia nocardiopsis_RV163_LEKI01 Bacteria Actinobacteria Actinobacteria Streptosporangiales Nocardiopsaceae Nocardiopsis oscillatoriales_cyanobacterium_MTP1_LNAA0 Bacteria Cyanobacteria NA Oscillatoriales -
Oral Microbiome Shifts from Caries-Free to Caries-Affected Status in 3-Year-Old Chinese Children: a Longitudinal Study
fmicb-09-02009 August 27, 2018 Time: 17:19 # 1 ORIGINAL RESEARCH published: 28 August 2018 doi: 10.3389/fmicb.2018.02009 Oral Microbiome Shifts From Caries-Free to Caries-Affected Status in 3-Year-Old Chinese Children: A Longitudinal Study He Xu1†, Jing Tian1†, Wenjing Hao1, Qian Zhang2, Qiong Zhou1, Weihua Shi1, Man Qin1*, Xuesong He3* and Feng Chen2* 1 Department of Pediatric Dentistry, Peking University School and Hospital of Stomatology, Beijing, China, 2 Central Laboratory, Peking University School and Hospital of Stomatology, Beijing, China, 3 The Forsyth Institute, Cambridge, MA, United States As one of the most prevalent human infectious diseases, dental caries results from dysbiosis of the oral microbiota driven by multiple factors. However, most of caries studies were cross-sectional and mainly focused on the differences in the oral microbiota Edited by: Giovanna Batoni, between caries-free (CF) and caries-affected (CA) populations, while little is known Università degli Studi di Pisa, Italy about the dynamic shift in microbial composition, and particularly the change in species Reviewed by: association pattern during disease transition. Here, we reported a longitudinal study Rainer Haak, of a 12-month follow-up of a cohort of 3-year-old children. Oral examinations and Leipzig University, Germany Xuedong Zhou, supragingival plaque collections were carried out at the beginning and every subsequent Sichuan University, China 6 months, for a total of three time points. All the children were CF at enrollment. Children *Correspondence: who developed caries at 6-month follow-up but had not received any dental treatment Man Qin [email protected]; until the end of the study were incorporated into the CA group. -
IDTAXA, for Taxonomic
Improving the accuracy of taxonomic classification for identifying taxa in microbiome samples Adithya Murali1, Aniruddha Bhargava2, & Erik S. Wright3 1Department of Computer Sciences, University of Wisconsin–Madison 2Robotics, Amazon, Inc. 3Department of Biomedical Informatics, University of Pittsburgh Contact info: [email protected] WrightLabScience.com 1. Classifying marker gene (e.g., 16S) sequences into a taxonomy Introduction a. Given a reference taxonomy b. The goal is to predict the taxon It has become increasingly clear with sequence representatives of a microbiome sequence that the microbiome is an essential Root new marker gene sequence (e.g., 16S rRNA): component of human and Archaea Bacteria ecosystem health. Microbiome ... AGCGGCAGCACAGAGGAACTTGTTCCTTGG... ... studies frequently involve Phylum: Actinobacteria Bacteroidetes Proteobacteria assign to a taxon sequencing a taxonomic marker, Class: ⍺ β ! " ε ... such as the 16S rRNA or ITS, to ... Order: Aeromonadales Enterobacteriales Legionellales confidences at identify the microorganisms that Root (97.8%); each rank level are present in a sample of interest. Family: Enterobacteriaceae Bacteria (97.8%); ... Proteobacteria (97.8%); We have developed a new method, ... Genus: Citrobacter Erwinia Escherichia Salmonella Gammaproteobacteria (97.8%); named IDTAXA, for taxonomic ... Taxonomic Enterobacteriales (97.8%); classification of marker gene Species: assignment: Enterobacteriaceae (97.8%); Escherichia (95%); sequences that exhibits a E. coli E. coli (82%) substantially lower error -
The Microbiome of the Footrot Lesion in Merino Sheep Is Characterized by a Persistent Bacterial Dysbiosis T ⁎ Andrew S
Veterinary Microbiology 236 (2019) 108378 Contents lists available at ScienceDirect Veterinary Microbiology journal homepage: www.elsevier.com/locate/vetmic The microbiome of the footrot lesion in Merino sheep is characterized by a persistent bacterial dysbiosis T ⁎ Andrew S. McPherson, Om P. Dhungyel, Richard J. Whittington Farm Animal Health, Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, 425 Werombi Rd, Camden, New South Wales, 2570, Australia ARTICLE INFO ABSTRACT Keywords: Footrot is prevalent in most sheep-producing countries; the disease compromises sheep health and welfare and Footrot has a considerable economic impact. The disease is the result of interactions between the essential causative Merino agent, Dichelobacter nodosus, and the bacterial community of the foot, with the pasture environment and host Sheep resistance influencing disease expression. The Merino, which is the main wool sheep breed in Australia, is Microbiome particularly susceptible to footrot. We characterised the bacterial communities on the feet of healthy and footrot- Dichelobacter nodosus affected Merino sheep across a 10-month period via sequencing and analysis of the V3-V4 regions of the bacterial 16S ribosomal RNA gene. Distinct bacterial communities were associated with the feet of healthy and footrot- affected sheep. Infection with D. nodosus appeared to trigger a shift in the composition of the bacterial com- munity from predominantly Gram-positive, aerobic taxa to predominantly Gram-negative, anaerobic taxa. A total of 15 bacterial genera were preferentially abundant on the feet of footrot-affected sheep, several of which have previously been implicated in footrot and other mixed bacterial diseases of the epidermis of ruminants.