Evidence map›Paper›PMID 34589188›Full record

ArticleComputational and structural biotechnology journal2021

Recovery of microbial community profile information hidden in chimeric sequence reads.

Mengfei Ho, Damee Moon, Melissa Pires-Alves, Patrick D Thornton, Barbara L McFarlin, Brenda A Wilson

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Insights into the prey ofFrontiers in insect science · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Mengfei HoDepartment of Microbiology, School of Molecular and Cellular Biology, University of Illinois at Urbana-Champaign, United States.
Damee MoonDepartment of Microbiology, School of Molecular and Cellular Biology, University of Illinois at Urbana-Champaign, United States.
Melissa Pires-AlvesDepartment of Microbiology, School of Molecular and Cellular Biology, University of Illinois at Urbana-Champaign, United States.
Patrick D ThorntonDepartment of Human Development Nursing Science, College of Nursing, University of Illinois at Chicago, United States.
Barbara L McFarlinDepartment of Human Development Nursing Science, College of Nursing, University of Illinois at Chicago, United States.
Brenda A WilsonDepartment of Microbiology, School of Molecular and Cellular Biology, University of Illinois at Urbana-Champaign, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The next frontier in the field of microbiome studies is identification of all microbes present in the microbiome and accurate determination of their abundance such that microbiome profiles can serve as reliable assessments of health or disease status. PCR-based 16S rRNA gene sequencing and metagenome shotgun sequencing technologies are the prevailing approaches used in microbiome analyses. Each poses a number of technical challenges associated with PCR amplification, sample availability, and cost of processing and analysis. In general, results from these two approaches rarely agree completely with each other. Here, we compare these methods utilizing a set of vaginal swab and lavage specimens from a cohort of 42 pregnant women collected for a pilot study exploring the effect of the vaginal microbiome on preterm birth. We generated the microbial community profiles from the sequencing reads of the V3V4 and V4V5 regions of the 16S rRNA gene in the vaginal swab and lavage samples. For a subset of the vaginal samples from 12 subjects, we also performed metagenomic shotgun sequencing analysis and compared the results obtained from the PCR-based sequencing methods. Our findings suggest that sample composition and complexity, particularly at the species level, are major factors that must be considered when analyzing and interpreting microbiome data. Our approach to sequence analysis includes consideration of chimeric reads, by using our chimera-counting BlastBin program, and enables recovery of microbial content information generated during PCR-based sequencing methods, such that the microbial profiles more closely resemble those obtained from metagenomic read-based approaches.

Indexed as

16S rRNABlastnchimerasmetagenomic sequencingmicrobial community profilesMorisita-Horn similaritynext-generation sequencingQIIME2Shannon diversityvaginal microbiome

Identifiers

PMID34589188
PMCPMC8453192

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.