scholarly journals Next-Generation Sequencing as a Tool to Detect Vaginal Microbiota Disturbances during Pregnancy

2020 ◽  
Vol 8 (11) ◽  
pp. 1813 ◽  
Author(s):  
Agnieszka Sroka-Oleksiak ◽  
Tomasz Gosiewski ◽  
Wojciech Pabian ◽  
Artur Gurgul ◽  
Przemysław Kapusta ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Streptococcus Agalactiae ◽  
Vaginal Microbiota ◽  
Quantitative Composition ◽  
Next Generation ◽  
Lactobacillus Jensenii ◽  
Sequencing Method ◽  
Genus Lactobacillus ◽  
Caucasian Women ◽  
Generation Sequencing

The physiological microbiota of the vagina is responsible for providing a protective barrier, but Some factors can disturb the balance in its composition. At that time, the amounts of the genus Lactobacillus decrease, which may lead to the development of infection and severe complications during pregnancy. The aim of the study was the analysis of the bacterial composition of the vagina in 32 Caucasian women at each trimester of pregnancy using the next-generation sequencing method and primers targeting V3-V4 regions. In the studied group, the dominant species were Lactobacillus iners, Lactobacillus gasseri, and Lactobacillusplantarum. Statistically significant differences in the quantitative composition between trimesters were observed in relation to Lactobacillus jensenii,Streptococcus agalactiae, Lactobacillus iners, Gardnerella spp. Out of the 32 patients, 20 demonstrated fluctuations within the genus Lactobacillus, and 9 of them, at different stages of pregnancy, exhibited the presence of potentially pathogenic microbiota, among others: Streptococcus agalactiae, Gardnerella spp., Atopobium vaginae, and Enterococcus faecalis. The composition of the vaginal microbiota during pregnancy was subject to partial changes over trimesters. Although in one-third of the studied patients, both the qualitative and quantitative composition of microbiota was relatively constant, in the remaining patients, physiological and potentially pathogenic fluctuations were distinguished.

scholarly journals Development of a Next-Generation Sequencing Method for BRCA Mutation Screening

2012 ◽  
Vol 14 (6) ◽  
pp. 602-612 ◽  
Author(s):  
Maurice Chan ◽  
Shen Mo Ji ◽  
Zhen Xuan Yeo ◽  
Linda Gan ◽  
Eric Yap ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Brca Mutation ◽  
Mutation Screening ◽  
Next Generation ◽  
Sequencing Method ◽  
Generation Sequencing ◽  
Next Generation Sequencing Method

scholarly journals Subacute Thyroiditis is Associated with HLA-B*18:01, -DRB1*01 and -C*04:01—The Significance of the New Molecular Background

2020 ◽  
Vol 9 (2) ◽  
pp. 534
Author(s):  
Magdalena Stasiak ◽  
Bogusław Tymoniuk ◽  
Renata Michalak ◽  
Bartłomiej Stasiak ◽  
Marek L. Kowalski ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Human Leukocyte ◽  
Subacute Thyroiditis ◽  
Control Group ◽  
Next Generation ◽  
Sequencing Method ◽  
Triggering Factor ◽  
Almost All ◽  
Generation Sequencing ◽  
Next Generation Sequencing Method

Subacute thyroiditis (SAT) is a thyroid inflammatory disease whose pathogenesis is still not completely defined. Previous viral infection is considered to be a triggering factor in genetically predisposed individuals. In about 70% of patients, susceptibility to SAT is associated with the HLA-B*35 allele. The correlation between SAT and other human leukocyte antigens (HLA) has not yet been unequivocally demonstrated and the genetic background is still unknown in about 30% of patients. The purpose of our study was to perform HLA genotyping using a next-generation sequencing method, to find out whether alleles other than HLA-B*35 are correlated with SAT morbidity. HLA-A, -B, -C, -DQB1, -DRB1 were genotyped using a next-generation sequencing method in 1083 subjects, including 60 SAT patients and 1023 healthy controls. Among 60 patients diagnosed with SAT, 81.7% of subjects were identified as having allele HLA-B*35, 23.3% had HLA-B*18:01, 28.3% had HLA-DRB1*01 and 75.5% had HLA-C*04:01. These alleles occurred in the control group at frequencies of 10.2%, 7.2%, 12.9% and 12.5%, respectively. The differences were statistically significant, with p < 0.05. In addition to its previously described relationship with HLA-B*35, genetic susceptibility to SAT was associated with the presence of HLA-B*18:01, DRB1*01 and C*04:01. The alleles HLA-B*18:01 and DRB1*01 were independent SAT risk factors. The assessment of these four alleles allows the confirmation of genetic predisposition in almost all patients with SAT.

A Streamlined and High-Throughput Error-Corrected Next-Generation Sequencing Method for Low Variant Allele Frequency Quantitation

2019 ◽  
Author(s):  
Page B McKinzie ◽  
Michelle E Bishop
Keyword(s):  
Next Generation Sequencing ◽  
Suppressor Gene ◽  
Tumor Formation ◽  
Read Length ◽  
Next Generation ◽  
Sequencing Method ◽  
Proportional Increase ◽  
Duplex Sequencing ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

Abstract Quantifying mutant or variable allele frequencies (VAFs) of ≤10−3 using next-generation sequencing (NGS) has utility in both clinical and nonclinical settings. Two common approaches for quantifying VAFs using NGS are tagged single-strand sequencing and duplex sequencing. While duplex sequencing is reported to have sensitivity up to 10−8 VAF, it is not a quick, easy, or inexpensive method. We report a method for quantifying VAFs that are ≥10−4 that is as easy and quick for processing samples as standard sequencing kits, yet less expensive than the kits. The method was developed using PCR fragment-based VAFs of Kras codon 12 in log10 increments from 10−5 to 10−1, then applied and tested on native genomic DNA. For both sources of DNA, there is a proportional increase in the observed VAF to input VAF from 10−4 to 100% mutant samples. Variability of quantitation was evaluated within experimental replicates and shown to be consistent across sample preparations. The error at each successive base read was evaluated to determine if there is a limit of read length for quantitation of ≥10−4, and it was determined that read lengths up to 70 bases are reliable for quantitation. The method described here is adaptable to various oncogene or tumor suppressor gene targets, with the potential to implement multiplexing at the initial tagging step. While easy to perform manually, it is also suited for robotic handling and batch processing of samples, facilitating detection and quantitation of genetic carcinogenic biomarkers before tumor formation or in normal-appearing tissue.

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