scholarly journals A survey of single nucleotide polymorphisms identified from whole-genome sequencing and their functional effect in the porcine genome,

2017 ◽  
Vol 48 (4) ◽  
pp. 404-411 ◽  
Author(s):  
B. N. Keel ◽  
D. J. Nonneman ◽  
G. A. Rohrer
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Nucleotide Polymorphisms ◽  
Porcine Genome ◽  
Functional Effect ◽  
Single Nucleotide

scholarly journals Mycobacterium chimaera genomics with regard to epidemiological and clinical investigations conducted for the open-chest post-surgical Mycobacterium chimaera infections outbreak

2021 ◽  
Author(s):  
Emmanuel Lecorche ◽  
Côme Daniau ◽  
Kevin La ◽  
Faiza Mougari ◽  
Hanaa Benmansour ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Clinical Isolates ◽  
Whole Genome ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Healthcare Facilities ◽  
Open Chest

Abstract Background Post-surgical infections due to Mycobacterium chimaera appeared as a novel nosocomial threat in 2015, with a worldwide outbreak due to contaminated heater-cooler units used in open chest surgery. We report the results of investigations conducted in France including whole genome sequencing comparison of patient and HCU isolates. Methods We sought M. chimaera infection cases from 2010 onwards through national epidemiological investigations in healthcare facilities performing cardiopulmonary bypass together with a survey on good practices and systematic heater-cooler unit microbial analyses. Clinical and HCU isolates were subjected to whole genome sequencing analyzed with regards to the reference outbreak strain Zuerich-1. Results Only two clinical cases were shown to be related to the outbreak, although 23% (41/175) heater-cooler units were declared positive for M. avium complex. Specific measures to prevent infection were applied in 89% (50/56) healthcare facilities although only 14% (8/56) of them followed the manufacturer maintenance recommendations. Whole genome sequencing comparison showed that the clinical isolates and 72% (26/36) of heater-cooler unit isolates belonged to the epidemic cluster. Within clinical isolates, 5 to 9 non-synonymous single nucleotide polymorphisms were observed, among which an in vivo mutation in a putative efflux pump gene observed in a clinical isolate obtained for one patient under antimicrobial treatment. Conclusions Cases of post-surgical M. chimaera infections were declared to be rare in France, although heater-cooler units were contaminated as in other countries. Genomic analyses confirmed the connection to the outbreak and identified specific single nucleotide polymorphisms, including one suggesting fitness evolution in vivo.

scholarly journals In-Depth Study of a Nosocomial Outbreak Caused by Extensively Drug-Resistant Pseudomonas aeruginosa Using Whole Genome Sequencing Coupled With a Polymerase Chain Reaction Targeting Strain-Specific Single Nucleotide Polymorphisms

2020 ◽  
Vol 189 (8) ◽  
pp. 841-849
Author(s):  
Fermín Acosta ◽  
Ana Fernández-Cruz ◽  
Sandra R Maus ◽  
Pedro J Sola-Campoy ◽  
Mercedes Marín ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Nucleotide Polymorphisms ◽  
Outbreak Strain ◽  
Single Nucleotide ◽  
Specific Pcr ◽  
Extensively Drug Resistant ◽  
Polymerase Chain

Abstract In 2013–2014, an outbreak involving 14 patients infected by an extensively drug-resistant strain of Pseudomonas aeruginosa was detected in a hospital in Madrid, Spain. Our objective was to evaluate an alternative strategy for investigating the outbreak in depth by means of molecular and genomic approaches. Pulsed-field gel electrophoresis (PFGE) was applied as a first-line approach, followed by a more refined whole genome sequencing analysis. Single nucleotide polymorphisms identified by whole genome sequencing were used to design a specific polymerase chain reaction (PCR) for screening unsuspected cases infected by the outbreak strain. Whole genome sequencing alerted us to the existence of greater genetic diversity than was initially assumed, splitting the PFGE-associated outbreak isolates into 4 groups, 2 of which represented coincidental transmission unrelated to the outbreak. A multiplex allele-specific PCR targeting outbreak-specific single nucleotide polymorphisms was applied to 290 isolates, which allowed us to identify 25 additional cases related to the outbreak during 2011–2017. Whole genome sequencing coupled with an outbreak-strain-specific PCR enabled us to markedly redefine the initial picture of the outbreak by 1) ruling out initially suspected cases, 2) defining likely independent coincidental transmission events, 3) predating the starting point of the outbreak, 4) capturing new unsuspected cases, and 5) revealing that the outbreak was still active.

scholarly journals In silico detection of phylogenetic informative Y-chromosomal single nucleotide polymorphisms from whole genome sequencing data

2014 ◽  
Vol 35 (21-22) ◽  
pp. 3102-3110 ◽  
Author(s):  
Anneleen Van Geystelen ◽  
Tom Wenseleers ◽  
Ronny Decorte ◽  
Maarten J. L. Caspers ◽  
Maarten H. D. Larmuseau
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
In Silico ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Nucleotide Polymorphisms ◽  
Sequencing Data ◽  
Single Nucleotide

scholarly journals Single nucleotide polymorphism in the rpoB gene Mycobacterium tuberculosis from Papua-Indonesia and its impact on rifampicin resistance: A whole genome sequencing analysis

2021 ◽  
Vol 15 (2) ◽  
pp. 1
Author(s):  
Yustinus Maladan ◽  
Tri Wahyuni ◽  
Hana Krismawati
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Mycobacterium Tuberculosis ◽  
Single Nucleotide Polymorphisms ◽  
Rna Polymerase ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Nucleotide Polymorphisms ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide

In the antibiotic era, Tuberculosis (TB) drugs resistance especially Rifampicin (RIF) is highly reported around the world. Resistance of RIF is caused by the mutation of genes that associated with RIF receptor. The aims of this study are detecting the Single Nucleotide Polymorphism of Rifampicin resistant genes using Whole Genome Sequencing (WGS) and analysing the profile of protein changing caused by SNP. Twenty Mycobacterium tuberculosis culture samples were passed on WGS procedure and 19 samples were adequate to further bioinformatics analysis. Single Nucleotide Polymorphisms Analysis was done using TBprofiler. Based on TBProfiler, seventeen samples were resistant to rifampicin. The mutations that cause the resistance are S450L, D435Y, H445Y, 430P, Q432K. Other Single Nucleotide Polymorphisms H835R, V534M and R224C were also found. The H835R mutants are present together with the S450L, V534M with S450L mutants, and R224C with Q432K mutants. Native protein for RNA Polymerase Subunit β used was the result of separation from the crystal structure of Mycobacterium tuberculosis H37Rv RNA polymerase (PDB: 5UHB). Binding affinity RIF to RNA Polymerase Subunit β calculated using AutoDock vina. Construction of mutant 3D structures using FoldX5. From the analysis, it was found that seventeen samples were resistant to rifampicin and two samples did not contain SNP which could cause resistance to rifampicin.

scholarly journals 869. Outbreak of Vancomycin Resistant Enterococcus faecium (VREfm) in a Hematology Unit Identified Through Whole Genome Sequencing

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S472-S474
Author(s):  
Gayathri Krishnan ◽  
Zulema Udaondo ◽  
Se-Ran Jun ◽  
Atul Kothari
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Central Venous Access ◽  
The United States ◽  
Tree Of Life ◽  
Whole Genome ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Time Period

Abstract Background VREfm is a major cause of Hospital Acquired Infection in the United States. We analyzed all the VREfm infections that occurred in our institution between 2018 and 2019 using Whole Genome Sequencing (WGS) to understand epidemiological relationship between previously unidentified clusters. In this study we describe a cluster in our hematology oncology unit. Methods A total of 109 discrete VREfm isolates from 66 patients were analyzed. VREfm isolates used in this study were identified from positive blood and urine cultures. Genomic deoxyribonucleic acid (DNA) was extracted from pure cultures. The purity and integrity of extracted DNA were determined using appropriate assays. Library construction and sequencing were conducted and Multi Locust Sequence Typing (MLST) obtained (image 1). Phylogenomic tree was plotted using the Interactive Tree of Life (image 2). Image 1 - methods Image 2 - Tree of Life Results Total of 7 clusters were identified. Here we describe one cluster (image 3) with the highest genetic similarity which showed maximum difference of 5 Single Nucleotide Polymorphisms (zero between patient 1 and 2, image 4). The cluster is composed of 24 clinical strains of VREfm from 6 patients, over a 9 month time period (Image 5). All patients had hematologic malignancies; 4/6 patients had received recent chemotherapy and 5/6 patients were neutropenic. 4 patients were admitted in a single unit (labelled E7), 1 patient was on a sister unit (labelled F7); and 1 patient was in the cancer infusion center. All patients had central venous access placed by radiology at the time of diagnosis of infection and had visited our outpatient infusion center multiple times during this time frame. Image 3 - Close look at cluster 1 Image 4 - Dendrogram of 106 isolates performed with coreSNP(Single Nucleotide Polymorphisms) pairwise distances. • Dendogram shows different patients (same color for isolates that belong to the same patient) and the patient numbers. • Besides the patient number, the number of largest number SNPS that separate those isolates is shown. • Branches represent the number of coreSNPs that differ strains from that branch. As you see isolates from cluster 1 differ in a maximum of 5 SNPs but isolates of patient 1 and patient 2 differ in 0 SNPs between them. Cluster 1 is represented by a green square. Image 5 - Time period of infections Conclusion The prolonged period in our cluster argues in favor of an environmental niche in the hospital unit. We are unable to elucidate pattern of transmission in a cluster of infections without knowing patient colonization of VREfm; because we are likely looking at the tip of the iceberg when analyzing infected cases. It is difficult to ascribe causality to any one of these exposures without concomitant surveillance cultures of environment and personnel. Retrospective WGS is of limited value in infection control. We now have third generation sequencing with the MinION device to do real time sequencing with which we also validated some of our samples. Disclosures Atul Kothari, MD, Ansun Biopharma (Consultant)

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