Evidence map›Paper›PMID 29651035›Full record

ArticleScientific reports2018

Impact of sequencing depth on the characterization of the microbiome and resistome.

Rahat Zaheer, Noelle Noyes, Rodrigo Ortega Polo, Shaun R Cook, Eric Marinier, Gary Van Domselaar, Keith E Belk, Paul S Morley, Tim A McAllister

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 120 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
120citing papers in PubMed, 1 pooled it
–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

120 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  11. Computational Microbial and Viral Ecology Analysis.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  12. Frontiers in microbiology · 2026
    Article
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60 more citing papers are in PubMed but not listed here.

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

9 authors.

Rahat ZaheerLethbridge Research and Development Centre, 5403 1 Ave South, Lethbridge, AB, T1J 4P4, Canada.ORCID 0000-0003-3307-4666
Noelle NoyesDepartment of Clinical Sciences, Colorado State University, Fort Collins, CO, 80523, USA.
Rodrigo Ortega PoloLethbridge Research and Development Centre, 5403 1 Ave South, Lethbridge, AB, T1J 4P4, Canada.
Shaun R CookLethbridge Research and Development Centre, 5403 1 Ave South, Lethbridge, AB, T1J 4P4, Canada.
Eric MarinierNational Microbiology Laboratory, Public Health Agency of Canada, 1015 Arlington Street, Winnipeg, MB, R3E 3R2, Canada.
Gary Van DomselaarNational Microbiology Laboratory, Public Health Agency of Canada, 1015 Arlington Street, Winnipeg, MB, R3E 3R2, Canada.
Keith E BelkDepartment of Clinical Sciences, Colorado State University, Fort Collins, CO, 80523, USA.
Paul S MorleyDepartment of Clinical Sciences, Colorado State University, Fort Collins, CO, 80523, USA.
Tim A McAllisterLethbridge Research and Development Centre, 5403 1 Ave South, Lethbridge, AB, T1J 4P4, Canada. tim.mcallister@agr.gc.ca.

Funding

Veterinary Pre-Doctoral Research Scholars ProgramT32OD012201 · OD · COLORADO STATE UNIVERSITY · PI VANDEWOUDE, SUE · 2013 to 2019
$795k
NIH HHS T32 OD012201
6 · The paper itself

Abstract

Developments in high-throughput next generation sequencing (NGS) technology have rapidly advanced the understanding of overall microbial ecology as well as occurrence and diversity of specific genes within diverse environments. In the present study, we compared the ability of varying sequencing depths to generate meaningful information about the taxonomic structure and prevalence of antimicrobial resistance genes (ARGs) in the bovine fecal microbial community. Metagenomic sequencing was conducted on eight composite fecal samples originating from four beef cattle feedlots. Metagenomic DNA was sequenced to various depths, D1, D0.5 and D0.25, with average sample read counts of 117, 59 and 26 million, respectively. A comparative analysis of the relative abundance of reads aligning to different phyla and antimicrobial classes indicated that the relative proportions of read assignments remained fairly constant regardless of depth. However, the number of reads being assigned to ARGs as well as to microbial taxa increased significantly with increasing depth. We found a depth of D0.5 was suitable to describe the microbiome and resistome of cattle fecal samples. This study helps define a balance between cost and required sequencing depth to acquire meaningful results.

Indexed as

AnimalsAnti-Bacterial AgentsArchaeaArchaeal ProteinsBacteriaBacterial ProteinsCattleDrug ResistanceFecesFungal ProteinsFungiGastrointestinal MicrobiomeGene ExpressionHigh-Throughput Nucleotide SequencingMetagenomicsPhylogenyAnti-Bacterial AgentsArchaeal ProteinsBacterial ProteinsFungal ProteinsViral Proteins

Identifiers

PMID29651035
PMCPMC5897366

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.