Legume–microbiome interactions unlock mineral nutrients in regrowing tropical forests

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Significance

Symbiotic dinitrogen (N ₂)-fixing trees fulfill a critical function in tropical forests by bringing in new nitrogen, yet it remains unclear how they overcome constraints by highly weathered, nutrient-poor tropical soils. We advance forest biogeochemistry and microbial ecology with the discovery from field trials in Panama that fast-growing N ₂-fixing trees in tropical forests exhibit accelerated mineral weathering and distinctive soil metagenomes that improve their access to inorganic nutrients in nutrient-poor soils. Furthermore, we show that N ₂-fixing trees exert similar effects on non-N ₂–fixing trees nearby thus having previously overlooked community-wide effects on tropical forest nutrient cycling. These results offer insights into the role of N ₂-fixing trees and their associated microbiomes in safeguarding the function of tropical forests within the global biosphere.

Abstract

Legume trees form an abundant and functionally important component of tropical forests worldwide with N ₂-fixing symbioses linked to enhanced growth and recruitment in early secondary succession. However, it remains unclear how N ₂-fixers meet the high demands for inorganic nutrients imposed by rapid biomass accumulation on nutrient-poor tropical soils. Here, we show that N ₂-fixing trees in secondary Neotropical forests triggered twofold higher in situ weathering of fresh primary silicates compared to non-N ₂–fixing trees and induced locally enhanced nutrient cycling by the soil microbiome community. Shotgun metagenomic data from weathered minerals support the role of enhanced nitrogen and carbon cycling in increasing acidity and weathering. Metagenomic and marker gene analyses further revealed increased microbial potential beneath N ₂-fixers for anaerobic iron reduction, a process regulating the pool of phosphorus bound to iron-bearing soil minerals. We find that the Fe(III)-reducing gene pool in soil is dominated by acidophilic Acidobacteria, including a highly abundant genus of previously undescribed bacteria, Candidatus Acidoferrum, genus novus. The resulting dependence of the Fe-cycling gene pool to pH determines the high iron-reducing potential encoded in the metagenome of the more acidic soils of N ₂-fixers and their nonfixing neighbors. We infer that by promoting the activities of a specialized local microbiome through changes in soil pH and C:N ratios, N ₂-fixing trees can influence the wider biogeochemical functioning of tropical forest ecosystems in a manner that enhances their ability to assimilate and store atmospheric carbon.

Related collections

Most cited references 62

Record: found
Abstract: found
Article: found

Is Open Access

CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes

Donovan Parks, Michael Imelfort, Connor Skennerton … (2015)

Large-scale recovery of genomes from isolates, single cells, and metagenomic data has been made possible by advances in computational methods and substantial reductions in sequencing costs. Although this increasing breadth of draft genomes is providing key information regarding the evolutionary and functional diversity of microbial life, it has become impractical to finish all available reference genomes. Making robust biological inferences from draft genomes requires accurate estimates of their completeness and contamination. Current methods for assessing genome quality are ad hoc and generally make use of a limited number of “marker” genes conserved across all bacterial or archaeal genomes. Here we introduce CheckM, an automated method for assessing the quality of a genome using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes. We demonstrate the effectiveness of CheckM using synthetic data and a wide range of isolate-, single-cell-, and metagenome-derived genomes. CheckM is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches. Using CheckM, we identify a diverse range of errors currently impacting publicly available isolate genomes and demonstrate that genomes obtained from single cells and metagenomic data vary substantially in quality. In order to facilitate the use of draft genomes, we propose an objective measure of genome quality that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities.

0 comments Cited 2843 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph.

Dinghua Li, Chi-Man Liu, Ruibang Luo … (2015)

MEGAHIT is a NGS de novo assembler for assembling large and complex metagenomics data in a time- and cost-efficient manner. It finished assembling a soil metagenomics dataset with 252 Gbps in 44.1 and 99.6 h on a single computing node with and without a graphics processing unit, respectively. MEGAHIT assembles the data as a whole, i.e. no pre-processing like partitioning and normalization was needed. When compared with previous methods on assembling the soil data, MEGAHIT generated a three-time larger assembly, with longer contig N50 and average contig length; furthermore, 55.8% of the reads were aligned to the assembly, giving a fourfold improvement. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

0 comments Cited 1945 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

Morgan G. I. Langille, Jesse R. R. Zaneveld, J. Gregory Caporaso … (2013)

Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community’s functional capabilities. Here we describe PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this ‘predictive metagenomic’ approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available.

0 comments Cited 1922 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Journal ID (nlm-ta): Proc Natl Acad Sci U S A

Journal ID (iso-abbrev): Proc Natl Acad Sci U S A

Journal ID (hwp): pnas

Journal ID (pmc): pnas

Journal ID (publisher-id): PNAS

Title: Proceedings of the National Academy of Sciences of the United States of America

Publisher: National Academy of Sciences

ISSN (Print): 0027-8424

ISSN (Electronic): 1091-6490

Publication date (Print): 16 March 2021

Publication date (Electronic): 10 March 2021

Publication date PMC-release: 10 March 2021

Volume: 118

Issue: 11

Electronic Location Identifier: e2022241118

Affiliations

[1] ^aDepartment of Animal and Plant Sciences, University of Sheffield , S10 2TN Sheffield, United Kingdom;

[2] ^bLeverhulme Centre for Climate Change Mitigation, University of Sheffield , S10 2TN Sheffield, United Kingdom;

[3] ^cSmithsonian Tropical Research Institute , 0843 Ancón, Panamá, Panama;

[4] ^dSchool of Geography and Priestley International Centre for Climate, University of Leeds , LS2 9JT Leeds, United Kingdom;

[5] ^eCary Institute of Ecosystem Studies , Millbrook, NY 12545;

[6] ^fDepartment of Ecology and Evolutionary Biology, Princeton University , Princeton, NJ 08544;

[7] ^gForest Global Earth Observatory, Smithsonian Tropical Research Institute , 0843 Ancón, Panamá, Panama;

[8] ^hYale-NUS College , Singapore 138527;

[9] ⁱDepartment of Biological Sciences, National University of Singapore , Singapore 119077

Author notes

¹To whom correspondence may be addressed. Email: d.z.epihov@ 123456sheffield.ac.uk .

Edited by James M. Tiedje, Michigan State University, East Lansing, MI, and approved January 25, 2021 (received for review October 30, 2020)

Author contributions: D.Z.E., J.R.L., and D.J.B. designed research; D.Z.E. and K.S. performed research; D.Z.E. and K.S. contributed new reagents/analytic tools; D.Z.E. analyzed data; and D.Z.E., K.S., S.A.B., L.O.H., J.S.H., M.v.B., J.R.L., and D.J.B. wrote the paper.