Evidence map›Paper›PMID 21572460›Full record

ReviewNature reviews. Microbiology2011

How sulphate-reducing microorganisms cope with stress: lessons from systems biology.

Jizhong Zhou, Qiang He, Christopher L Hemme, Aindrila Mukhopadhyay, Kristina Hillesland, Aifen Zhou, Zhili He, Joy D Van Nostrand, Terry C Hazen, David A Stahl and 2 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Microbiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.

0numbers the graph read from it
0cells of the map it votes in
68citing 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

68 citing papers in PubMed.

  1. Article
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  9. Review
  10. Deep-seamBio · 2024
    Article
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  17. Generation of zero-valent sulfur from dissimilatory sulfate reduction in sulfate-reducing microorganisms.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  18. Article
  19. Article
  20. Article

8 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

12 authors.

Jizhong ZhouStephenson Research & Technology Center, 101 David L. Boren Blvd., Institut for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman, Oklahoma 73019, USA. jzhou@ou.edu
Qiang He
Christopher L Hemme
Aindrila Mukhopadhyay
Kristina Hillesland
Aifen Zhou
Zhili He
Joy D Van Nostrand
Terry C Hazen
David A Stahl
Judy D Wall
Adam P Arkin

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sulphate-reducing microorganisms (SRMs) are a phylogenetically diverse group of anaerobes encompassing distinct physiologies with a broad ecological distribution. As SRMs have important roles in the biogeochemical cycling of carbon, nitrogen, sulphur and various metals, an understanding of how these organisms respond to environmental stresses is of fundamental and practical importance. In this Review, we highlight recent applications of systems biology tools in studying the stress responses of SRMs, particularly Desulfovibrio spp., at the cell, population, community and ecosystem levels. The syntrophic lifestyle of SRMs is also discussed, with a focus on system-level analyses of adaptive mechanisms. Such information is important for understanding the microbiology of the global sulphur cycle and for developing biotechnological applications of SRMs for environmental remediation, energy production, biocorrosion control, wastewater treatment and mineral recovery.

Indexed as

Bacteria, AnaerobicBiodegradation, EnvironmentalDesulfovibrio vulgarisPhylogenyStress, PhysiologicalSulfatesSystems BiologySulfates

Identifiers

PMID21572460

What OpenQuestion holds

Textmetadata
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.