scholarly journals SARS-CoV-2 R.1 lineage variants prevailed in Tokyo in March 2021

2021 ◽  
Author(s):  
Katsutoshi Nagano ◽  
Chihiro Tani-Sassa ◽  
Yumi Iwasaki ◽  
Yuna Takatsuki ◽  
Sonoka Yuasa ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Disease Severity ◽  
Genome Sequencing ◽  
Melting Curve ◽  
Melting Curve Analysis ◽  
Nasopharyngeal Swab ◽  
Whole Genome ◽  
Crucial Issue ◽  
Chain Reaction ◽  
Polymerase Chain

Background: The spread of SARS-CoV-2 variants, such as B.1.1.7 and B.1.351, has become a crucial issue worldwide. Therefore, we began testing all patients with COVID-19 for the N501Y and E484K mutations associated with SARS-CoV-2. Study design: Nasopharyngeal swab samples from 108 patients who visited our hospital between February and April 2021 were analyzed. The samples were analyzed using reverse transcription-polymerase chain reaction with melting curve analysis to detect the N501Y and E484K mutations. A part of the samples were also subjected to whole genome sequencing. Clinical parameters such as mortality and admission to the intensive care unit were analyzed to examine the association between increased disease severity and the E484K mutation. Results: The ratio of cases showing the 501N+484K mutation rapidly increased from 8% in February to 46% in March. Whole genome sequencing revealed that the viruses with 501N+484K mutation are R.1 lineage variants. Evidence of increased disease severity related to the R.1 variants were not found. Conclusions: We found that the R.1 lineage variants rapidly prevailed in Tokyo in March 2021.

scholarly journals Prognostic Utility of Whole-Genome Sequencing and Polymerase Chain Reaction Tests of Ocular Fluids in Postprocedural Endophthalmitis

2020 ◽  
Vol 217 ◽  
pp. 325-334 ◽  
Author(s):  
Cecilia S. Lee ◽  
Bryan Hong ◽  
Sundeep K. Kasi ◽  
Christopher Aderman ◽  
Katherine E. Talcott ◽  
...  
Keyword(s):  
Polymerase Chain Reaction ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Chain Reaction ◽  
Ocular Fluids ◽  
Prognostic Utility ◽  
Polymerase Chain

scholarly journals Serotyping of sub-Saharan Africa Salmonella strains isolated from poultry feces using multiplex PCR and whole genome sequencing

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Assèta Kagambèga ◽  
Lari M. Hiott ◽  
David S. Boyle ◽  
Elizabeth A. McMillan ◽  
Poonam Sharma ◽  
...  
Keyword(s):  
Burkina Faso ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
The United States ◽  
Sub Saharan Africa ◽  
Whole Genome ◽  
Chain Reaction ◽  
Food Borne ◽  
Polymerase Chain ◽  
Sub Saharan

Abstract Background Salmonella enterica remains a leading cause of food-borne diseases worldwide. Serotype information is important in food safety and public health activities to reduce the burden of salmonellosis. In the current study, two methods were used to determine serotypes of 111 strains of Salmonella isolated from poultry feces in Burkina Faso. First, Salmonella Multiplex Assay for Rapid Typing (SMART) Polymerase Chain Reaction (PCR) was used to determine the serovars of the S. enterica isolates. Second, serovar prediction based on whole genome sequencing (WGS) data was performed using SeqSero 2.0. Results Among the 111 Salmonella isolates, serotypes for 17 (15.31%) isolates were identified based on comparison to a panel of representative SMART codes previously determined for the 50 most common serovars in the United States. Forty-four (44) new SMART codes were developed for common and uncommon serotypes. A total of 105 (94.59%) isolates were serotyped using SeqSero 2.0 for serovar prediction based on WGS data. Conclusion We determined that SeqSero 2.0 was more comprehensive for identifying Salmonella serotypes from Burkina Faso than SMART PCR.

Homogenous measurement during a circulation-water-based ultrahigh-speed polymerase chain reaction and melting curve analysis device

2014 ◽  
Vol 53 (6S) ◽  
pp. 06JM08 ◽  
Author(s):  
Hideyuki Terazono ◽  
Kenji Matsuura ◽  
Hyonchol Kim ◽  
Hiroyuki Takei ◽  
Akihiro Hattori ◽  
...  
Keyword(s):  
Polymerase Chain Reaction ◽  
Melting Curve ◽  
Curve Analysis ◽  
Melting Curve Analysis ◽  
Chain Reaction ◽  
Water Based ◽  
Polymerase Chain

scholarly journals Genotyping of Benzimidazole-Resistant and Dicarboximide-Resistant Mutations in Botrytis cinerea Using Real-Time Polymerase Chain Reaction Assays

2008 ◽  
Vol 98 (4) ◽  
pp. 397-404 ◽  
Author(s):  
Shinpei Banno ◽  
Fumiyasu Fukumori ◽  
Akihiko Ichiishi ◽  
Kiyotsugu Okada ◽  
Hidetoshi Uekusa ◽  
...  
Keyword(s):  
Polymerase Chain Reaction ◽  
Real Time ◽  
Botrytis Cinerea ◽  
Melting Curve ◽  
Resonance Energy Transfer ◽  
Resonance Energy ◽  
Cross Resistance ◽  
Melting Curve Analysis ◽  
Chain Reaction ◽  
Polymerase Chain

Botrytis cinerea, an economically important gray mold pathogen, frequently exhibits multiple fungicide resistance. A fluorescence resonance energy transfer-based real-time polymerase chain reaction assay has been developed to detect benzimidazole- and dicarboximide-resistant mutations. Three benzimidazole-resistant mutations—198Glu to Ala (E198A), F200Y, and E198K—in β-tubulin BenA were detected using a single set of fluorescence-labeled sensor and anchor probes by melting curve analysis. Similarly, three dicarboximide-resistant mutations—I365S, V368F plus Q369H, and Q369P—in the histidine kinase BcOS1 were successfully distinguished. Unassigned melting profiles in BenA genotyping assay resulted in the identification of a new benzimidazole-resistant BenA E198V mutation. This mutation conferred resistance to carbendazim as do E198A and E198K mutations. The isolates with BenA E198V mutation showed a negative cross-resistance to diethofencarb, but to a lesser extent than the E198A mutants. A survey of 210 B. cinerea field isolates revealed that most of benzimidazole-resistant isolates possessed the E198V or E198A mutation in the BenA gene, and the I365S mutation in the BcOS1 gene was also frequently observed in Japanese isolates. However, benzimidazole-resistant isolates with BenA F200Y or E198K mutations, which confer the diethofencarb-insensitive phenotype, were rare. Our BenA and BcOS1 genotyping is a rapid and reliable method that is suitable for monitoring the fungicide-resistant field population.

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.

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