| Title: |
A genomic view of environmental and life history controls on microbial nitrogen acquisition strategies |
| Authors: |
Reji, Linta; Darnajoux, Romain; Zhang, Xinning |
| Contributors: |
Simons Foundation |
| Source: |
Environmental Microbiology Reports ; volume 16, issue 1 ; ISSN 1758-2229 1758-2229 |
| Publisher Information: |
Wiley |
| Publication Year: |
2023 |
| Collection: |
Wiley Online Library (Open Access Articles via Crossref) |
| Description: |
Microorganisms have evolved diverse strategies to acquire the vital element nitrogen (N) from the environment. Ecological and physiological controls on the distribution of these strategies among microbes remain unclear. In this study, we examine the distribution of 10 major N acquisition strategies in taxonomically and metabolically diverse microbial genomes, including those from the Genomic Catalogue of Earth's Microbiomes dataset. We utilize a marker gene‐based approach to assess relationships between N acquisition strategy prevalence and microbial life history strategies. Our results underscore energetic costs of assimilation as a broad control on strategy distribution. The most prevalent strategies are the uptake of ammonium and simple amino acids, which have relatively low energetic costs, while energy‐intensive biological nitrogen fixation is the least common. Deviations from the energy‐based framework include the higher‐than‐expected prevalence of the assimilatory pathway for chitin, a large organic polymer. Energy availability is also important, with aerobic chemoorganotrophs and oxygenic phototrophs notably possessing ~2‐fold higher numbers of total strategies compared to anaerobic microbes. Environmental controls are evidenced by the enrichment of inorganic N assimilation strategies among free‐living taxa compared to host‐associated taxa. Physiological constraints such as pathway incompatibility add complexity to N acquisition strategy distributions. Finally, we discuss the necessity for microbially‐relevant spatiotemporal environmental metadata for improving mechanistic and prediction‐oriented analyses of genomic data. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| DOI: |
10.1111/1758-2229.13220 |
| Availability: |
https://doi.org/10.1111/1758-2229.13220; https://sfamjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/1758-2229.13220 |
| Rights: |
http://creativecommons.org/licenses/by/4.0/ |
| Accession Number: |
edsbas.97A1B6B8 |
| Database: |
BASE |