scholarly journals Whole-genome sequence comparison as a method for improving bacterial species definition

2014 ◽  
Vol 60 (2) ◽  
pp. 75-78 ◽  
Author(s):  
Wen Zhang ◽  
Pengcheng Du ◽  
Han Zheng ◽  
Weiwen Yu ◽  
Li Wan ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Sequence Comparison ◽  
Bacterial Species ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Species Definition ◽  
Genome Sequence Comparison

scholarly journals Whole genome sequence comparison of avian pathogenic Escherichia coli from acute and chronic salpingitis of egg laying hens

2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Louise Ladefoged Poulsen ◽  
Egle Kudirkiene ◽  
Steffen Lynge Jørgensen ◽  
Steven Philip Djordjevic ◽  
Max Laurence Cummins ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Genome Sequence ◽  
Sequence Comparison ◽  
Laying Hens ◽  
Egg Laying ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Avian Pathogenic Escherichia Coli ◽  
Genome Sequence Comparison ◽  
Pathogenic Escherichia Coli

scholarly journals Rapid High Resolution Genotyping of Francisella tularensis by Whole Genome Sequence Comparison of Annotated Genes (“MLST+”)

PLoS ONE ◽  
2015 ◽  
Vol 10 (4) ◽  
pp. e0123298 ◽  
Author(s):  
Markus H. Antwerpen ◽  
Karola Prior ◽  
Alexander Mellmann ◽  
Sebastian Höppner ◽  
Wolf D. Splettstoesser ◽  
...  
Keyword(s):  
High Resolution ◽  
Francisella Tularensis ◽  
Genome Sequence ◽  
Sequence Comparison ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Comparison

scholarly journals Whole genome sequence comparison of vtx2-converting phages from Enteroaggregative Haemorrhagic Escherichia coli strains

BMC Genomics ◽  
2014 ◽  
Vol 15 (1) ◽  
pp. 574 ◽  
Author(s):  
Laura Grande ◽  
Valeria Michelacci ◽  
Rosangela Tozzoli ◽  
Paola Ranieri ◽  
Antonella Maugliani ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Genome Sequence ◽  
Sequence Comparison ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Comparison

scholarly journals Whole genome sequence comparison of ten diagnostic brucellaphages propagated on two Brucella abortus hosts

2015 ◽  
Vol 12 (1) ◽  
Author(s):  
Ekaterine Tevdoradze ◽  
Jason Farlow ◽  
Adam Kotorashvili ◽  
Natia Skhirtladze ◽  
Irina Antadze ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Brucella Abortus ◽  
Sequence Comparison ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Comparison

scholarly journals Antimicrobial resistance genetic factor identification from whole-genome sequence data using deep feature selection

2019 ◽  
Vol 20 (S15) ◽  
Author(s):  
Jinhong Shi ◽  
Yan Yan ◽  
Matthew G. Links ◽  
Longhai Li ◽  
Jo-Anne R. Dillon ◽  
...  
Keyword(s):  
Feature Selection ◽  
Antimicrobial Resistance ◽  
Genome Sequence ◽  
Sequence Data ◽  
Bacterial Species ◽  
Clinical Diagnostics ◽  
New Drugs ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Data

Abstract Background Antimicrobial resistance (AMR) is a major threat to global public health because it makes standard treatments ineffective and contributes to the spread of infections. It is important to understand AMR’s biological mechanisms for the development of new drugs and more rapid and accurate clinical diagnostics. The increasing availability of whole-genome SNP (single nucleotide polymorphism) information, obtained from whole-genome sequence data, along with AMR profiles provides an opportunity to use feature selection in machine learning to find AMR-associated mutations. This work describes the use of a supervised feature selection approach using deep neural networks to detect AMR-associated genetic factors from whole-genome SNP data. Results The proposed method, DNP-AAP (deep neural pursuit – average activation potential), was tested on a Neisseria gonorrhoeae dataset with paired whole-genome sequence data and resistance profiles to five commonly used antibiotics including penicillin, tetracycline, azithromycin, ciprofloxacin, and cefixime. The results show that DNP-AAP can effectively identify known AMR-associated genes in N. gonorrhoeae, and also provide a list of candidate genomic features (SNPs) that might lead to the discovery of novel AMR determinants. Logistic regression classifiers were built with the identified SNPs and the prediction AUCs (area under the curve) for penicillin, tetracycline, azithromycin, ciprofloxacin, and cefixime were 0.974, 0.969, 0.949, 0.994, and 0.976, respectively. Conclusions DNP-AAP can effectively identify known AMR-associated genes in N. gonorrhoeae. It also provides a list of candidate genes and intergenic regions that might lead to novel AMR factor discovery. More generally, DNP-AAP can be applied to AMR analysis of any bacterial species with genomic variants and phenotype data. It can serve as a useful screening tool for microbiologists to generate genetic candidates for further lab experiments.

scholarly journals Whole-Genome Sequence of Chlamydia gallinacea Type Strain 08-1274/3

2016 ◽  
Vol 4 (4) ◽  
Author(s):  
Martin Hölzer ◽  
Karine Laroucau ◽  
Heather Huot Creasy ◽  
Sandra Ott ◽  
Fabien Vorimore ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Type Strain ◽  
Bacterial Species ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Protein Coding ◽  
Coding Sequences ◽  
Domestic Poultry ◽  
Avian Pathogen

The recently introduced bacterial species Chlamydia gallinacea is known to occur in domestic poultry and other birds. Its potential as an avian pathogen and zoonotic agent is under investigation. The whole-genome sequence of its type strain, 08-1274/3, consists of a 1,059,583-bp chromosome with 914 protein-coding sequences (CDSs) and a plasmid (p1274) comprising 7,619 bp with 9 CDSs.

scholarly journals Draft genome sequence of the strain 16-537536, isolated from a patient with bronchiectasis and its relationship to the Pseudomonas koreensis group of the Pseudomonas fluorescens complex

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Ad. C. Fluit ◽  
Malbert R. C. Rogers ◽  
María Díez-Aguilar ◽  
Rafael Cantón ◽  
Barry J. Benaissa-Trouw ◽  
...  
Keyword(s):  
Pseudomonas Fluorescens ◽  
Genome Sequence ◽  
Sequence Data ◽  
Bacterial Species ◽  
Antibiotic Resistance Gene ◽  
Draft Genome ◽  
Draft Genome Sequence ◽  
Whole Genome Sequence ◽  
Correct Identification ◽  
Whole Genome

Abstract Objective The Pseudomonas koreensis group bacteria are usually found in soil and are associated with plants. Currently they are poorly described. Here we report on the whole genome sequence of a bacterial isolate from a patient with bronchiectasis that was first identified as P. koreensis, and on its position in the P. koreensis group. Results Strain 16-537536 was isolated from a patient with bronchiectasis from Spain and initially identified by MALDI-TOF as P. koreensis, a member of the Pseudomonas fluorescens complex. However, the average nucleotide identity analysis (ANIb) and whole genome alignments of the draft genome sequence of this strain showed it to be a member of the P. koreensis group of the P. fluorescens complex, but belonging to an undescribed species. In addition, based on ANIb analysis, the P. koreensis group contains several other unnamed species. Several genes for putative virulence factors were identified. The only antibiotic resistance gene present in strain 16-537536 was a class C β-lactamase. The correct identification of bacterial species from patients is of utmost importance in order to understand their pathogenesis and to track the potential spread of pathogens between patients. Whole genome sequence data should be included for the description of new species.

scholarly journals Whole-Genome Sequence of French Clinical Peptoniphilus catoniae Strain P8546

2019 ◽  
Vol 8 (45) ◽  
Author(s):  
Hussein Anani ◽  
Issam Hasni ◽  
Rita Zgheib ◽  
Amael Fadlane ◽  
Didier Raoult ◽  
...  
Keyword(s):  
Kidney Cancer ◽  
Genome Sequence ◽  
Bacterial Species ◽  
Whole Genome Sequence ◽  
Clinical Strain ◽  
Whole Genome ◽  
Content Type ◽  
French Patient

In 2016, Peptoniphilus catoniae was reported as a bacterial species isolated from a healthy Peruvian male. In 2018, a clinical strain from the same species was isolated from the stool of a French patient with kidney cancer. The genome of this strain, P8546, was 1,725,465 bp long, with 33.4% G+C content.

scholarly journals Genome sequence-based criteria for demarcation and definition of species in the genus Rickettsia

2020 ◽  
Vol 70 (3) ◽  
pp. 1738-1750 ◽  
Author(s):  
Awa Diop ◽  
Khalid El Karkouri ◽  
Didier Raoult ◽  
Pierre-Edouard Fournier
Keyword(s):  
Genome Sequence ◽  
Bacterial Species ◽  
Whole Genome Sequence ◽  
Current Standard ◽  
Phenotypic Properties ◽  
Species Definition ◽  
Content Type ◽  
Link Type ◽  
Reliable Classification

Over recent years, genomic information has increasingly been used for prokaryotic species definition and classification. Genome sequence-based alternatives to the gold standard DNA–DNA hybridization (DDH) relatedness have been developed, notably average nucleotide identity (ANI), which is one of the most useful measurements for species delineation in the genomic era. However, the strictly intracellar lifestyle, the few measurable phenotypic properties and the low level of genetic heterogeneity made the current standard genomic criteria for bacterial species definition inapplicable to Rickettsia species. We evaluated a range of whole genome sequence (WGS)-based taxonomic parameters to develop guidelines for the classification of Rickettsia isolates at genus and species levels. By comparing the degree of similarity of 74 WGSs from 31 Rickettsia species and 61 WGSs from members of three closely related genera also belonging to the order Rickettsiales ( Orientia , 11 genomes; Ehrlichia , 22 genomes; and Anaplasma , 28 genomes) using digital DDH (dDDh) and ANI by orthology (OrthoANI) parameters, we demonstrated that WGS-based taxonomic information, which is easy to obtain and use, can serve for reliable classification of isolates within the Rickettsia genus and species. To be classified as a member of the genus Rickettsia , a bacterial isolate should exhibit OrthoANI values with any Rickettsia species with a validly published name of ≥83.63 %. To be classified as a new Rickettsia species, an isolate should not exhibit more than any of the following degrees of genomic relatedness levels with the most closely related species: >92.30 and >99.19 % for the dDDH and OrthoANI values, respectively. When applied to four rickettsial isolates of uncertain status, the above-described thresholds enabled their classification as new species in one case. Thus, we propose WGS-based guidelines to efficiently delineate Rickettsia species, with OrthoANI and dDDH being the most accurate for classification at the genus and species levels, respectively.

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