Evidence map›Paper›PMID 38722174›Full record

ArticlemSystems2024

Genomic fingerprints of the world's soil ecosystems.

Emily B Graham, Vanessa A Garayburu-Caruso, Ruonan Wu, Jianqiu Zheng, Ryan McClure, Gerrad D Jones

Abstract read
In one paragraph

Article in mSystems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Emily B GrahamEarth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington, USA.ORCID 0000-0002-4623-7076
Vanessa A Garayburu-CarusoEarth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington, USA.ORCID 0000-0003-3383-6237
Ruonan WuEarth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington, USA.ORCID 0000-0001-9466-4462
Jianqiu ZhengEarth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington, USA.ORCID 0000-0002-1609-9004
Ryan McClureEarth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington, USA.ORCID 0000-0003-0573-6917
Gerrad D JonesDepartment of Biological and Ecological Engineering, Oregon State University, Corvallis, Oregon, USA.ORCID 0000-0002-1529-9506

Funding

DOE | SC | Pacific Northwest National Laboratory (PNNL)
6 · The paper itself

Abstract

Despite the explosion of soil metagenomic data, we lack a synthesized understanding of patterns in the distribution and functions of soil microorganisms. These patterns are critical to predictions of soil microbiome responses to climate change and resulting feedbacks that regulate greenhouse gas release from soils. To address this gap, we assay 1,512 manually curated soil metagenomes using complementary annotation databases, read-based taxonomy, and machine learning to extract multidimensional genomic fingerprints of global soil microbiomes. Our objective is to uncover novel biogeographical patterns of soil microbiomes across environmental factors and ecological biomes with high molecular resolution. We reveal shifts in the potential for (i) microbial nutrient acquisition across pH gradients; (ii) stress-, transport-, and redox-based processes across changes in soil bulk density; and (iii) greenhouse gas emissions across biomes. We also use an unsupervised approach to reveal a collection of soils with distinct genomic signatures, characterized by coordinated changes in soil organic carbon, nitrogen, and cation exchange capacity and in bulk density and clay content that may ultimately reflect soil environments with high microbial activity. Genomic fingerprints for these soils highlight the importance of resource scavenging, plant-microbe interactions, fungi, and heterotrophic metabolisms. Across all analyses, we observed phylogenetic coherence in soil microbiomes-more closely related microorganisms tended to move congruently in response to soil factors. Collectively, the genomic fingerprints uncovered here present a basis for global patterns in the microbial mechanisms underlying soil biogeochemistry and help beget tractable microbial reaction networks for incorporation into process-based models of soil carbon and nutrient cycling.IMPORTANCEWe address a critical gap in our understanding of soil microorganisms and their functions, which have a profound impact on our environment. We analyzed 1,512 global soils with advanced analytics to create detailed genetic profiles (fingerprints) of soil microbiomes. Our work reveals novel patterns in how microorganisms are distributed across different soil environments. For instance, we discovered shifts in microbial potential to acquire nutrients in relation to soil acidity, as well as changes in stress responses and potential greenhouse gas emissions linked to soil structure. We also identified soils with putative high activity that had unique genomic characteristics surrounding resource acquisition, plant-microbe interactions, and fungal activity. Finally, we observed that closely related microorganisms tend to respond in similar ways to changes in their surroundings. Our work is a significant step toward comprehending the intricate world of soil microorganisms and its role in the global climate.

Indexed as

MetagenomeMicrobiotaSoil MicrobiologyBacteriaEcosystemFungiMetagenomicsPhylogenySoilSoilbiogeochemistrybiogeographycarbon cyclingfunctional potentialmachine learningmetaanalysismetagenomicsnitrogen cyclingsoil microbiologysoil microbiome

Identifiers

PMID38722174
PMCPMC11237643

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.