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A Metagenomics Pipeline to Characterize Self-Collected Vaginal Microbiome Samples.

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Title: A Metagenomics Pipeline to Characterize Self-Collected Vaginal Microbiome Samples.
Authors: Thomas-White, Krystal, Hilt, Evann E., Olmschenk, Genevieve, Gong, Maryann, Phillips, Caleb D., Jarvis, Courtney, Sanford, Nicholas, White, Jennifer, Navarro, Pita
Source: Diagnostics (2075-4418); Sep2024, Vol. 14 Issue 18, p2039, 10p
Subject Terms: BACTERIAL vaginitis, CHILDBEARING age, SHOTGUN sequencing, VAGINITIS, ANAEROBIC bacteria
Abstract: Vaginitis is a widespread issue for women worldwide, yet current diagnostic tools are lacking. Bacterial vaginosis (BV) is the most prevalent type of vaginitis, found in 10–50% of reproductive-aged women. Current diagnostic methods for BV rely on clinical criteria, microscopy, or the detection of a few microbes by qPCR. However, many vaginal infections lack a single etiological agent and are characterized by changes in the vaginal microbiome community structure (e.g., BV is defined as a loss of protective lactobacilli resulting in an overgrowth of anaerobic bacteria). Shotgun metagenomic sequencing provides a comprehensive view of all the organisms present in the vaginal microbiome (VMB), allowing for a better understanding of all potential etiologies. Here, we describe a robust VMB metagenomics sequencing test with a sensitivity of 93.1%, a specificity of 90%, a negative predictive value of 93.4%, and a positive predictive value of 89.6% certified by Clinical Laboratory Improvement Amendments (CLIA), the College of American Pathologist (CAP), and the Clinical Laboratory Evaluation Program (CLEP). We sequenced over 7000 human vaginal samples with this pipeline and described general findings and comparisons to US census data. [ABSTRACT FROM AUTHOR]
Copyright of Diagnostics (2075-4418) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
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  Data: A Metagenomics Pipeline to Characterize Self-Collected Vaginal Microbiome Samples.
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  Data: <searchLink fieldCode="AR" term="%22Thomas-White%2C+Krystal%22">Thomas-White, Krystal</searchLink><br /><searchLink fieldCode="AR" term="%22Hilt%2C+Evann+E%2E%22">Hilt, Evann E.</searchLink><br /><searchLink fieldCode="AR" term="%22Olmschenk%2C+Genevieve%22">Olmschenk, Genevieve</searchLink><br /><searchLink fieldCode="AR" term="%22Gong%2C+Maryann%22">Gong, Maryann</searchLink><br /><searchLink fieldCode="AR" term="%22Phillips%2C+Caleb+D%2E%22">Phillips, Caleb D.</searchLink><br /><searchLink fieldCode="AR" term="%22Jarvis%2C+Courtney%22">Jarvis, Courtney</searchLink><br /><searchLink fieldCode="AR" term="%22Sanford%2C+Nicholas%22">Sanford, Nicholas</searchLink><br /><searchLink fieldCode="AR" term="%22White%2C+Jennifer%22">White, Jennifer</searchLink><br /><searchLink fieldCode="AR" term="%22Navarro%2C+Pita%22">Navarro, Pita</searchLink>
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  Data: Diagnostics (2075-4418); Sep2024, Vol. 14 Issue 18, p2039, 10p
– Name: Subject
  Label: Subject Terms
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  Data: <searchLink fieldCode="DE" term="%22BACTERIAL+vaginitis%22">BACTERIAL vaginitis</searchLink><br /><searchLink fieldCode="DE" term="%22CHILDBEARING+age%22">CHILDBEARING age</searchLink><br /><searchLink fieldCode="DE" term="%22SHOTGUN+sequencing%22">SHOTGUN sequencing</searchLink><br /><searchLink fieldCode="DE" term="%22VAGINITIS%22">VAGINITIS</searchLink><br /><searchLink fieldCode="DE" term="%22ANAEROBIC+bacteria%22">ANAEROBIC bacteria</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Vaginitis is a widespread issue for women worldwide, yet current diagnostic tools are lacking. Bacterial vaginosis (BV) is the most prevalent type of vaginitis, found in 10–50% of reproductive-aged women. Current diagnostic methods for BV rely on clinical criteria, microscopy, or the detection of a few microbes by qPCR. However, many vaginal infections lack a single etiological agent and are characterized by changes in the vaginal microbiome community structure (e.g., BV is defined as a loss of protective lactobacilli resulting in an overgrowth of anaerobic bacteria). Shotgun metagenomic sequencing provides a comprehensive view of all the organisms present in the vaginal microbiome (VMB), allowing for a better understanding of all potential etiologies. Here, we describe a robust VMB metagenomics sequencing test with a sensitivity of 93.1%, a specificity of 90%, a negative predictive value of 93.4%, and a positive predictive value of 89.6% certified by Clinical Laboratory Improvement Amendments (CLIA), the College of American Pathologist (CAP), and the Clinical Laboratory Evaluation Program (CLEP). We sequenced over 7000 human vaginal samples with this pipeline and described general findings and comparisons to US census data. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Diagnostics (2075-4418) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3390/diagnostics14182039
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      – Code: eng
        Text: English
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        StartPage: 2039
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      – SubjectFull: BACTERIAL vaginitis
        Type: general
      – SubjectFull: CHILDBEARING age
        Type: general
      – SubjectFull: SHOTGUN sequencing
        Type: general
      – SubjectFull: VAGINITIS
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      – SubjectFull: ANAEROBIC bacteria
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              M: 09
              Text: Sep2024
              Type: published
              Y: 2024
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