Evidence map›Paper›PMID 29146960›Full record

ArticleNature communications2017

Assessing species biomass contributions in microbial communities via metaproteomics.

Manuel Kleiner, Erin Thorson, Christine E Sharp, Xiaoli Dong, Dan Liu, Carmen Li, Marc Strous

Abstract read
In one paragraph

Article in Nature communications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 157 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
157citing 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

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

  1. Pooled it
  2. Trial
  3. Review
  4. Review
  5. Establishment of anmSystems · 2026
    Article
  6. Microbial pairing alters metabolic wiring.Nature ecology & evolution · 2026
    Article
  7. Observational
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Metaproteomics for Water Biotechnology: Considerations and Study Cases.Advances in experimental medicine and biology · 2026
    Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

97 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

7 authors.

Manuel KleinerDepartment of Geoscience, University of Calgary, Calgary, AB, Canada, T2N 1N4. manuel_kleiner@ncsu.edu.ORCID http://orcid.org/0000-0001-6904-0287
Erin ThorsonDepartment of Geoscience, University of Calgary, Calgary, AB, Canada, T2N 1N4.ORCID http://orcid.org/0000-0001-9648-0093
Christine E SharpDepartment of Geoscience, University of Calgary, Calgary, AB, Canada, T2N 1N4.
Xiaoli DongDepartment of Geoscience, University of Calgary, Calgary, AB, Canada, T2N 1N4.
Dan LiuDepartment of Geoscience, University of Calgary, Calgary, AB, Canada, T2N 1N4.
Carmen LiDepartment of Biological Sciences, University of Calgary, Calgary, AB, Canada, T2N 1N4.
Marc StrousDepartment of Geoscience, University of Calgary, Calgary, AB, Canada, T2N 1N4.ORCID http://orcid.org/0000-0001-9600-3828

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbial community structure can be analyzed by quantifying cell numbers or by quantifying biomass for individual populations. Methods for quantifying cell numbers are already available (e.g., fluorescence in situ hybridization, 16-S rRNA gene amplicon sequencing), yet high-throughput methods for assessing community structure in terms of biomass are lacking. Here we present metaproteomics-based methods for assessing microbial community structure using protein abundance as a measure for biomass contributions of individual populations. We optimize the accuracy and sensitivity of the method using artificially assembled microbial communities and show that it is less prone to some of the biases found in sequencing-based methods. We apply the method to communities from two different environments, microbial mats from two alkaline soda lakes, and saliva from multiple individuals. We show that assessment of species biomass contributions adds an important dimension to the analysis of microbial community structure.

Indexed as

BiomassArchaeaBacteriaBacteriophagesGenomicsHumansLakesMicrobiotaProteomeProteomicsRNA, Ribosomal, 16SSalivaProteomeRNA, Ribosomal, 16S

Identifiers

PMID29146960
PMCPMC5691128

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.