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Battistuzzi2009chap07.Pdf
Eubacteria Fabia U. Battistuzzia,b,* and S. Blair Hedgesa shown increasing support for lower-level phylogenetic Department of Biology, 208 Mueller Laboratory, The Pennsylvania clusters (e.g., classes and below), they have also shown the State University, University Park, PA 16802-5301, USA; bCurrent susceptibility of eubacterial phylogeny to biases such as address: Center for Evolutionary Functional Genomics, The Biodesign horizontal gene transfer (HGT) (20, 21). Institute, Arizona State University, Tempe, AZ 85287-5301, USA In recent years, three major approaches have been used *To whom correspondence should be addressed (Fabia.Battistuzzi@ asu.edu) for studying prokaryote phylogeny with data from com- plete genomes: (i) combining gene sequences in a single analysis of multiple genes (e.g., 7, 9, 10), (ii) combining Abstract trees from individual gene analyses into a single “super- tree” (e.g., 22, 23), and (iii) using the presence or absence The ~9400 recognized species of prokaryotes in the of genes (“gene content”) as the raw data to investigate Superkingdom Eubacteria are placed in 25 phyla. Their relationships (e.g., 17, 18). While the results of these dif- relationships have been diffi cult to establish, although ferent approaches have not agreed on many details of some major groups are emerging from genome analyses. relationships, there have been some points of agreement, A molecular timetree, estimated here, indicates that most such as support for the monophyly of all major classes (85%) of the phyla and classes arose in the Archean Eon and some phyla (e.g., Proteobacteria and Firmicutes). (4000−2500 million years ago, Ma) whereas most (95%) of 7 ese A ndings, although criticized by some (e.g., 24, 25), the families arose in the Proterozoic Eon (2500−542 Ma). -
Fatty Acid Diets: Regulation of Gut Microbiota Composition and Obesity and Its Related Metabolic Dysbiosis
International Journal of Molecular Sciences Review Fatty Acid Diets: Regulation of Gut Microbiota Composition and Obesity and Its Related Metabolic Dysbiosis David Johane Machate 1, Priscila Silva Figueiredo 2 , Gabriela Marcelino 2 , Rita de Cássia Avellaneda Guimarães 2,*, Priscila Aiko Hiane 2 , Danielle Bogo 2, Verônica Assalin Zorgetto Pinheiro 2, Lincoln Carlos Silva de Oliveira 3 and Arnildo Pott 1 1 Graduate Program in Biotechnology and Biodiversity in the Central-West Region of Brazil, Federal University of Mato Grosso do Sul, Campo Grande 79079-900, Brazil; [email protected] (D.J.M.); [email protected] (A.P.) 2 Graduate Program in Health and Development in the Central-West Region of Brazil, Federal University of Mato Grosso do Sul, Campo Grande 79079-900, Brazil; pri.fi[email protected] (P.S.F.); [email protected] (G.M.); [email protected] (P.A.H.); [email protected] (D.B.); [email protected] (V.A.Z.P.) 3 Chemistry Institute, Federal University of Mato Grosso do Sul, Campo Grande 79079-900, Brazil; [email protected] * Correspondence: [email protected]; Tel.: +55-67-3345-7416 Received: 9 March 2020; Accepted: 27 March 2020; Published: 8 June 2020 Abstract: Long-term high-fat dietary intake plays a crucial role in the composition of gut microbiota in animal models and human subjects, which affect directly short-chain fatty acid (SCFA) production and host health. This review aims to highlight the interplay of fatty acid (FA) intake and gut microbiota composition and its interaction with hosts in health promotion and obesity prevention and its related metabolic dysbiosis. -
World Journal of Clinical Cases
World Journal of W J C C Clinical Cases Submit a Manuscript: http://www.f6publishing.com World J Clin Cases 2018 April 16; 6(4): 54-63 DOI: 10.12998/wjcc.v6.i4.54 ISSN 2307-8960 (online) ORIGINAL ARTICLE Observational Study Correlations between microbial communities in stool and clinical indicators in patients with metabolic syndrome Lang Lin, Zai-Bo Wen, Dong-Jiao Lin, Jiang-Ting Dong, Jie Jin, Fei Meng Lang Lin, Zai-Bo Wen, Dong-Jiao Lin, Jiang-Ting Dong, the use is non-commercial. See: http://creativecommons.org/ Department of Gastroenterology, Cangnan People’s Hospital, licenses/by-nc/4.0/ Cangnan 325800, Zhejiang Province, China Manuscript source: Unsolicited manuscript Jie Jin, Fei Meng, Department of Research Service, Zhiyuan Medical Inspection Institute CO., LTD, Hangzhou 310030, Correspondence to: Lang Lin, MSc, Chief Doctor, Department Zhejiang Province, China of Gastroenterology, Cangnan People’s Hospital, Lingxi Town, Yucang Road No.195, Cangnan 325800, Zhejiang Province, ORCID number: Lang Lin (0000-0001-5879-7487); Zai-Bo Wen China. [email protected] (0000-0003-1290-0404); Dong-Jiao Lin (0000-0001-5186-8182); Jiang- Telephone: +86-577-64767351 Ting Dong (0000-0002-6433-0143); Jie Jin (0000-0003-1481-5107); Fei Fax: +86-577-64767351 Meng (0000-0003-1233-4270). Received: January 2, 2018 Author contributions: Lin L formulated the problem; Wen ZB, Peer-review started: January 2, 2018 Lin DJ and Dong JT collected samples; Meng F performed 16S First decision: January 18, 2018 rDNA sequencing; Jin J analyzed the data; Lin L and Jin J wrote Revised: February 2, 2018 the paper. -
Taqman® Cronobacter Sakazakii Detection
Applied Biosystems Food Pathogen Detection System TaqMan ® Cronobacter sakazakii Detection Kit Simple, reliable, and rapid detection TaqMan® Pathogen Detection Kits • Cronobacter sakazakii • Salmonella enterica • Campylobacter jejuni • E. coli O157:H7 • Listeria monocytogenes • Pseudomonas aeruginosa • Staphylococcus aureus An Infant Formula Contaminant Real-Time PCR Delivers Detect E. sakazakii Faster Cronobacter sakazakii is a pathogen The TaqMan Cronobacter sakazakii A number of tests are currently mostly associated with powdered Detection Kit uses proven real-time available that identify Cronobacter infant formula, causing seizures, brain PCR technology designed to provide: sakazakii based on phenotypic and abscesses, developmental delay, and biochemical methods. However, • Highly selective identification of even death in infants with premature because of isolates that may escape Cronobacter sakazakii in a wide variety infants and newborns at greatest risk. identification with these methods, faster, of food and finished product samples It is therefore extremely important more reliable methods are needed. that infant formula be tested prior to • Verified performance The TaqMan® Cronobacter sakazakii release to the marketplace. It is currently Detection Kit offers such an alternative. • Ready-to-use convenience unknown how many organisms will cause infection, thus a highly specific • Reduced risk of contamination product testing method is necessary to determine the presence of Cronobacter sakazakii. Rely on Applied Biosystems Use a Complete -
Serine Proteases with Altered Sensitivity to Activity-Modulating
(19) & (11) EP 2 045 321 A2 (12) EUROPEAN PATENT APPLICATION (43) Date of publication: (51) Int Cl.: 08.04.2009 Bulletin 2009/15 C12N 9/00 (2006.01) C12N 15/00 (2006.01) C12Q 1/37 (2006.01) (21) Application number: 09150549.5 (22) Date of filing: 26.05.2006 (84) Designated Contracting States: • Haupts, Ulrich AT BE BG CH CY CZ DE DK EE ES FI FR GB GR 51519 Odenthal (DE) HU IE IS IT LI LT LU LV MC NL PL PT RO SE SI • Coco, Wayne SK TR 50737 Köln (DE) •Tebbe, Jan (30) Priority: 27.05.2005 EP 05104543 50733 Köln (DE) • Votsmeier, Christian (62) Document number(s) of the earlier application(s) in 50259 Pulheim (DE) accordance with Art. 76 EPC: • Scheidig, Andreas 06763303.2 / 1 883 696 50823 Köln (DE) (71) Applicant: Direvo Biotech AG (74) Representative: von Kreisler Selting Werner 50829 Köln (DE) Patentanwälte P.O. Box 10 22 41 (72) Inventors: 50462 Köln (DE) • Koltermann, André 82057 Icking (DE) Remarks: • Kettling, Ulrich This application was filed on 14-01-2009 as a 81477 München (DE) divisional application to the application mentioned under INID code 62. (54) Serine proteases with altered sensitivity to activity-modulating substances (57) The present invention provides variants of ser- screening of the library in the presence of one or several ine proteases of the S1 class with altered sensitivity to activity-modulating substances, selection of variants with one or more activity-modulating substances. A method altered sensitivity to one or several activity-modulating for the generation of such proteases is disclosed, com- substances and isolation of those polynucleotide se- prising the provision of a protease library encoding poly- quences that encode for the selected variants. -
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 -
A Genomic Timescale of Prokaryote Evolution: Insights Into the Origin of Methanogenesis, Phototrophy, and the Colonization of Land
BMC Evolutionary Biology BioMed Central Research article Open Access A genomic timescale of prokaryote evolution: insights into the origin of methanogenesis, phototrophy, and the colonization of land Fabia U Battistuzzi1, Andreia Feijao2 and S Blair Hedges*1 Address: 1NASA Astrobiology Institute and Department of Biology, 208 Mueller Laboratory, The Pennsylvania State University, University Park, PA 16802, USA and 2European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany Email: Fabia U Battistuzzi - [email protected]; Andreia Feijao - [email protected]; S Blair Hedges* - [email protected] * Corresponding author Published: 09 November 2004 Received: 07 August 2004 Accepted: 09 November 2004 BMC Evolutionary Biology 2004, 4:44 doi:10.1186/1471-2148-4-44 This article is available from: http://www.biomedcentral.com/1471-2148/4/44 © 2004 Battistuzzi et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: The timescale of prokaryote evolution has been difficult to reconstruct because of a limited fossil record and complexities associated with molecular clocks and deep divergences. However, the relatively large number of genome sequences currently available has provided a better opportunity to control for potential biases such as horizontal gene transfer and rate differences among lineages. We assembled a data set of sequences from 32 proteins (~7600 amino acids) common to 72 species and estimated phylogenetic relationships and divergence times with a local clock method. Results: Our phylogenetic results support most of the currently recognized higher-level groupings of prokaryotes. -
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TECHNISCHE UNIVERSITÄT MÜNCHEN Lehrstuhl für Biofunktionalität der Lebensmittel Mechanistic impact of Enterococcus faecalis metalloprotease on bacterial virulence in the context of chronic intestinal inflammation Natalie Marie Annabel Steck Vollständiger Abdruck der von der Fakultät Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt der Technischen Universität München zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften genehmigten Dissertation. Vorsitzender: Univ.-Prof. Dr. M. Schemann Prüfer der Dissertation: 1. Univ.-Prof. Dr. D. Haller 2. Univ.-Prof. Dr. R.F. Vogel Die Dissertation wurde am 17.11.2011 bei der Technischen Universität München eingereicht und durch die Fakultät Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt am 06.02.2012 angenommen. Für meine Familie und Freunde PUBLICATIONS AND PRESENTATIONS PUBLICATIONS AND PRESENTATIONS Peer-reviewed original manuscripts and reviews Steck N*, Mueller K*, Schemann M and Haller D. Bacterial proteases in IBD and IBS. Gut, 2011 (*authors equally contributed to the manuscript) Steck N , Hoffmann M, Sava IG, Kim SC, Hahne H, Tonkonogy SL, Mair K, Krueger D, Pruteanu M, Shanahan F, Vogelmann R, Schemann M, Kuster B, Sartor RB and Haller D. Enterococcus faecalis Metalloprotease Compromises Epithelial Barrier and Contributes to Intestinal Inflammation. Gastroenterology, 2011 Sep;141(3):959-71. Published abstracts Steck N , Hoffmann M, Hew Ferstl CM, Kim SC, Tonkonogy SL, Vogel RF, Sartor RB, Haller D. E. faecalis Gelatinase contributes to the development of intestinal inflammation by impairing epithelial barrier function: Role for bacteria-derived proteases in the pathology of IBD. Journal of Crohn's and Colitis Supplements - April 2010, Vol. 4, Issue 1, Pages 22-23 Steck N , Hoffmann M, Hew Ferstl CM, Kim SC, Liu B, Vogel RF, Sartor RB, Haller D. -
Infant and New Mother
Infant and New Mother Product Category: Infant and New Mother EleCare® Similac Expert Care® 24 Cal With Iron EleCare® (for Infants) Similac Expert Care® Alimentum® Similac Expert Care® for Diarrhea Similac Expert Care® NeoSure® Metabolic Similac For Spit-Up® Calcilo XD® Similac Go & Grow® Milk-Based Formula Cyclinex®-1 Similac Go & Grow® Soy-Based Formula Glutarex®-1 Similac Sensitive® Hominex®-1 Similac Total Comfort™ I-Valex®-1 Similac® 10-pct Glucose Water Ketonex®-1 Similac® 5-pct Glucose Water Phenex™-1 Similac® Advance® Pro-Phree® Similac® Advance® Organic Propimex®-1 Similac® For Supplementation ProViMin® Similac® Human Milk Fortifier RCF® Similac® Human Milk Fortifier Concentrated Liquid Tyrex®-1 Similac® Nipples Similac® PM 60/40 Pedialyte® Similac® Prenatal & Breastfeeding Dietary Supplement Pedialyte AdvancedCare™ Pedialyte® Liters Similac® Simply Smart™ Similac® Soy Isomil® Similac® Similac® Sterilized Water Similac® Volu-Feed® Bottles & Caps Liquid Protein Fortifier For more information, contact your Abbott Nutrition Representative or visit www.abbottnutrition.com Abbott Nutrition Abbott Laboratories © 2013 Abbott Laboratories Inc. Columbus, OH 43219-3034 Updated 11/18/2013 1-800-227-5767 EleCare® Product Category: EleCare® EleCare® (for Infants) For more information, contact your Abbott Nutrition Representative or visit www.abbottnutrition.com Abbott Nutrition Abbott Laboratories © 2013 Abbott Laboratories Inc. Columbus, OH 43219-3034 Updated 11/18/2013 1-800-227-5767 EleCare® (for Infants) Nutritionally Complete Amino Acid-Based Infant Formula with Iron Product Information: EleCare® (for Infants) For more information, contact your Abbott Nutrition Representative or visit www.abbottnutrition.com Abbott Nutrition Abbott Laboratories © 2013 Abbott Laboratories Inc. Columbus, OH 43219-3034 Updated 1/1/0001 1-800-227-5767 1 of 5 EleCare® (for Infants) Nutritionally Complete Amino Acid-Based Infant Formula with Iron l EleCare is a nutritionally complete amino-acid based formula for infants who cannot tolerate intact or hydrolyzed protein. -
Genes Preferring Non-AUG Start Codons in Bacteria Abstract
Genes Preferring Non-AUG Start Codons in Bacteria 1,2 2,3,4 Anne Gvozdjak and Manoj P. Samanta 1. Bellevue High School, 10416 SE Wolverine Way, Bellevue, WA 98004 2. Coding for Life Science, Redmond, WA 98053 3. Systemix Institute, Redmond, WA 98053 4. [email protected] Abstract Here we investigate translational regulation in bacteria by analyzing the distribution of start codons in fully assembled genomes. We report 36 genes (infC, rpoC, rnpA, etc.) showing a preference for non-AUG start codons in evolutionarily diverse phyla (“non-AUG genes”). Most of the non-AUG genes are functionally associated with translation, transcription or replication. In E. coli, the percentage of essential genes among these 36 is significantly higher than among all genes. Furthermore, the functional distribution of these genes suggests that non-AUG start codons may be used to reduce gene expression during starvation conditions, possibly through translational autoregulation or IF3-mediated regulation. Introduction Understanding the regulation of gene expression at the transcriptional and translational levels is a key step in deciphering the information contained by genomes. Whereas inexpensive, high-throughput technologies (ChIP-seq, RNAseq) are helping in extensive experimental investigation of transcriptional regulation [1,2], the measurement of translational regulation using high-throughput mass spectroscopy [3] is less widely adopted. Bioinformatics provides another avenue to leverage the rapidly falling cost of DNA sequencing to explore translational regulation. Prior to 2000, computational researchers identified a number of relevant patterns through the comparative analysis of gene sequences [4,5] . With the availability of ~250,000 prokaryotic genomes, thousands of eukaryotic genomes, and additional metagenomic sequences, those patterns can now be studied at a significantly larger scale, and new patterns may also be identified. -
International Journal of Systematic and Evolutionary Microbiology (2016), 66, 5575–5599 DOI 10.1099/Ijsem.0.001485
International Journal of Systematic and Evolutionary Microbiology (2016), 66, 5575–5599 DOI 10.1099/ijsem.0.001485 Genome-based phylogeny and taxonomy of the ‘Enterobacteriales’: proposal for Enterobacterales ord. nov. divided into the families Enterobacteriaceae, Erwiniaceae fam. nov., Pectobacteriaceae fam. nov., Yersiniaceae fam. nov., Hafniaceae fam. nov., Morganellaceae fam. nov., and Budviciaceae fam. nov. Mobolaji Adeolu,† Seema Alnajar,† Sohail Naushad and Radhey S. Gupta Correspondence Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, Ontario, Radhey S. Gupta L8N 3Z5, Canada [email protected] Understanding of the phylogeny and interrelationships of the genera within the order ‘Enterobacteriales’ has proven difficult using the 16S rRNA gene and other single-gene or limited multi-gene approaches. In this work, we have completed comprehensive comparative genomic analyses of the members of the order ‘Enterobacteriales’ which includes phylogenetic reconstructions based on 1548 core proteins, 53 ribosomal proteins and four multilocus sequence analysis proteins, as well as examining the overall genome similarity amongst the members of this order. The results of these analyses all support the existence of seven distinct monophyletic groups of genera within the order ‘Enterobacteriales’. In parallel, our analyses of protein sequences from the ‘Enterobacteriales’ genomes have identified numerous molecular characteristics in the forms of conserved signature insertions/deletions, which are specifically shared by the members of the identified clades and independently support their monophyly and distinctness. Many of these groupings, either in part or in whole, have been recognized in previous evolutionary studies, but have not been consistently resolved as monophyletic entities in 16S rRNA gene trees. The work presented here represents the first comprehensive, genome- scale taxonomic analysis of the entirety of the order ‘Enterobacteriales’. -
Handbook of Proteolytic Enzymes Second Edition Volume 1 Aspartic and Metallo Peptidases
Handbook of Proteolytic Enzymes Second Edition Volume 1 Aspartic and Metallo Peptidases Alan J. Barrett Neil D. Rawlings J. Fred Woessner Editor biographies xxi Contributors xxiii Preface xxxi Introduction ' Abbreviations xxxvii ASPARTIC PEPTIDASES Introduction 1 Aspartic peptidases and their clans 3 2 Catalytic pathway of aspartic peptidases 12 Clan AA Family Al 3 Pepsin A 19 4 Pepsin B 28 5 Chymosin 29 6 Cathepsin E 33 7 Gastricsin 38 8 Cathepsin D 43 9 Napsin A 52 10 Renin 54 11 Mouse submandibular renin 62 12 Memapsin 1 64 13 Memapsin 2 66 14 Plasmepsins 70 15 Plasmepsin II 73 16 Tick heme-binding aspartic proteinase 76 17 Phytepsin 77 18 Nepenthesin 85 19 Saccharopepsin 87 20 Neurosporapepsin 90 21 Acrocylindropepsin 9 1 22 Aspergillopepsin I 92 23 Penicillopepsin 99 24 Endothiapepsin 104 25 Rhizopuspepsin 108 26 Mucorpepsin 11 1 27 Polyporopepsin 113 28 Candidapepsin 115 29 Candiparapsin 120 30 Canditropsin 123 31 Syncephapepsin 125 32 Barrierpepsin 126 33 Yapsin 1 128 34 Yapsin 2 132 35 Yapsin A 133 36 Pregnancy-associated glycoproteins 135 37 Pepsin F 137 38 Rhodotorulapepsin 139 39 Cladosporopepsin 140 40 Pycnoporopepsin 141 Family A2 and others 41 Human immunodeficiency virus 1 retropepsin 144 42 Human immunodeficiency virus 2 retropepsin 154 43 Simian immunodeficiency virus retropepsin 158 44 Equine infectious anemia virus retropepsin 160 45 Rous sarcoma virus retropepsin and avian myeloblastosis virus retropepsin 163 46 Human T-cell leukemia virus type I (HTLV-I) retropepsin 166 47 Bovine leukemia virus retropepsin 169 48