Combined analysis of microbial metagenomic and metatranscriptomic sequencing data to assess in situ physiological conditions in the premature infant gut
Abstract
Microbes alter their transcriptomic profiles in response to the environment. The physiological conditions experienced by a microbial community can thus be inferred using meta-transcriptomic sequencing by comparing transcription levels of specifically chosen genes. However, this analysis requires accurate reference genomes to identify the specific genes from which RNA reads originate. In addition, such an analysis should avoid biases in transcript counts related to differences in organism abundance. In this study we describe an approach to address these difficulties. Sample-specific meta-genomic assembled genomes (MAGs) were used as reference genomes to accurately identify the origin of RNA reads, and transcript ratios of genes with opposite transcription responses were compared to eliminate biases related to differences in organismal abundance, an approach hereafter named the “diametric ratio” method. We used this approach to probe the environmental conditions experienced by Escherichia spp. in the gut of 4 premature infants, 2 of whom developed necrotizing enterocolitis (NEC), a severe inflammatory intestinal disease. We analyzed twenty fecal samples taken from four premature infants (4–6 time points from each infant), and found significantly higher diametric ratios of genes associated with low oxygen levels in samples of infants later diagnosed with NEC than in samples without NEC. We alsomore »
- Authors:
-
[1];
- Univ. of California, Berkeley, CA (United States)
- Enview, Inc., San Francisco, CA (United States)
- Univ. of Pittsburgh, PA (United States). School of Medicine
- Magee-Womens Hospital of UPMC, Pittsburgh, PA (United States)
- Univ. of Pittsburgh, PA (United States). School of Medicine; Magee-Womens Hospital of UPMC, Pittsburgh, PA (United States)
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC); National Institutes of Health (NIH); March of Dimes Foundation; USDA
- OSTI Identifier:
- 1631619
- Grant/Contract Number:
- AC02-05CH11231; 5-FY10-103; 2016-67012-24717
- Resource Type:
- Accepted Manuscript
- Journal Name:
- PLoS ONE
- Additional Journal Information:
- Journal Volume: 15; Journal Issue: 3; Journal ID: ISSN 1932-6203
- Publisher:
- Public Library of Science
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES
Citation Formats
Sher, Yonatan, Olm, Matthew R., Raveh-Sadka, Tali, Brown, Christopher T., Sher, Ruth, Firek, Brian, Baker, Robyn, Morowitz, Michael J., and Banfield, Jillian F. Combined analysis of microbial metagenomic and metatranscriptomic sequencing data to assess in situ physiological conditions in the premature infant gut. United States: N. p., 2020.
Web. doi:10.1371/journal.pone.0229537.
Sher, Yonatan, Olm, Matthew R., Raveh-Sadka, Tali, Brown, Christopher T., Sher, Ruth, Firek, Brian, Baker, Robyn, Morowitz, Michael J., & Banfield, Jillian F. Combined analysis of microbial metagenomic and metatranscriptomic sequencing data to assess in situ physiological conditions in the premature infant gut. United States. https://doi.org/10.1371/journal.pone.0229537
Sher, Yonatan, Olm, Matthew R., Raveh-Sadka, Tali, Brown, Christopher T., Sher, Ruth, Firek, Brian, Baker, Robyn, Morowitz, Michael J., and Banfield, Jillian F. Wed .
"Combined analysis of microbial metagenomic and metatranscriptomic sequencing data to assess in situ physiological conditions in the premature infant gut". United States. https://doi.org/10.1371/journal.pone.0229537. https://www.osti.gov/servlets/purl/1631619.
@article{osti_1631619,
title = {Combined analysis of microbial metagenomic and metatranscriptomic sequencing data to assess in situ physiological conditions in the premature infant gut},
author = {Sher, Yonatan and Olm, Matthew R. and Raveh-Sadka, Tali and Brown, Christopher T. and Sher, Ruth and Firek, Brian and Baker, Robyn and Morowitz, Michael J. and Banfield, Jillian F.},
abstractNote = {Microbes alter their transcriptomic profiles in response to the environment. The physiological conditions experienced by a microbial community can thus be inferred using meta-transcriptomic sequencing by comparing transcription levels of specifically chosen genes. However, this analysis requires accurate reference genomes to identify the specific genes from which RNA reads originate. In addition, such an analysis should avoid biases in transcript counts related to differences in organism abundance. In this study we describe an approach to address these difficulties. Sample-specific meta-genomic assembled genomes (MAGs) were used as reference genomes to accurately identify the origin of RNA reads, and transcript ratios of genes with opposite transcription responses were compared to eliminate biases related to differences in organismal abundance, an approach hereafter named the “diametric ratio” method. We used this approach to probe the environmental conditions experienced by Escherichia spp. in the gut of 4 premature infants, 2 of whom developed necrotizing enterocolitis (NEC), a severe inflammatory intestinal disease. We analyzed twenty fecal samples taken from four premature infants (4–6 time points from each infant), and found significantly higher diametric ratios of genes associated with low oxygen levels in samples of infants later diagnosed with NEC than in samples without NEC. We also show this method can be used for examining other physiological conditions, such as exposure to nitric oxide and osmotic pressure. These study results should be treated with caution, due to the presence of confounding factors that might also distinguish between NEC and control infants. Nevertheless, together with benchmarking analyses, we show here that the diametric ratio approach can be applied for evaluating the physiological conditions experienced by microbes in situ. Results from similar studies can be further applied for designing diagnostic methods to detect NEC in its early developmental stages.},
doi = {10.1371/journal.pone.0229537},
journal = {PLoS ONE},
number = 3,
volume = 15,
place = {United States},
year = {Wed Mar 04 00:00:00 EST 2020},
month = {Wed Mar 04 00:00:00 EST 2020}
}
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