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Xu Q, Li L, Guo J, Guo H, Liu M, Guo S, Kuzyakov Y, Ling N, Shen Q. Active microbial population dynamics and life strategies drive the enhanced carbon use efficiency in high-organic matter soils. mBio 2024; 15:e0017724. [PMID: 38376207 PMCID: PMC10936188 DOI: 10.1128/mbio.00177-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 01/30/2024] [Indexed: 02/21/2024] Open
Abstract
Microbial carbon use efficiency (CUE) is a critical parameter that controls carbon storage in soil, but many uncertainties remain concerning adaptations of microbial communities to long-term fertilization that impact CUE. Based on H218O quantitative stable isotope probing coupled with metagenomic sequencing, we disentangled the roles of active microbial population dynamics and life strategies for CUE in soils after a long-term (35 years) mineral or organic fertilization. We found that the soils rich in organic matter supported high microbial CUE, indicating a more efficient microbial biomass formation and a greater carbon sequestration potential. Organic fertilizers supported active microbial communities characterized by high diversity and a relative increase in net growth rate, as well as an anabolic-biased carbon cycling, which likely explains the observed enhanced CUE. Overall, these results highlight the role of population dynamics and life strategies in understanding and predicting microbial CUE and sequestration in soil.IMPORTANCEMicrobial CUE is a major determinant of global soil organic carbon storage. Understanding the microbial processes underlying CUE can help to maintain soil sustainable productivity and mitigate climate change. Our findings indicated that active microbial communities, adapted to long-term organic fertilization, exhibited a relative increase in net growth rate and a preference for anabolic carbon cycling when compared to those subjected to chemical fertilization. These shifts in population dynamics and life strategies led the active microbes to allocate more carbon to biomass production rather than cellular respiration. Consequently, the more fertile soils may harbor a greater microbially mediated carbon sequestration potential. This finding is of great importance for manipulating microorganisms to increase soil C sequestration.
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Affiliation(s)
- Qicheng Xu
- Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Nanjing Agricultural University, Nanjing, China
- Centre for Grassland Microbiome, State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agricultural Science and Technology, Lanzhou University, Lanzhou, Gansu, China
| | - Ling Li
- Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Nanjing Agricultural University, Nanjing, China
| | - Junjie Guo
- Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Nanjing Agricultural University, Nanjing, China
| | - Hanyue Guo
- Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Nanjing Agricultural University, Nanjing, China
| | - Manqiang Liu
- Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Nanjing Agricultural University, Nanjing, China
- Centre for Grassland Microbiome, State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agricultural Science and Technology, Lanzhou University, Lanzhou, Gansu, China
| | - Shiwei Guo
- Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Nanjing Agricultural University, Nanjing, China
| | - Yakov Kuzyakov
- Department of Soil Science of Temperate Ecosystems, University of Gottingen, Göttingen, Germany
- Department of Agricultural Soil Science, University of Gottingen, Göttingen, Germany
- Peoples Friendship University of Russia (RUDN University), Moscow, Russia
| | - Ning Ling
- Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Nanjing Agricultural University, Nanjing, China
- Centre for Grassland Microbiome, State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agricultural Science and Technology, Lanzhou University, Lanzhou, Gansu, China
| | - Qirong Shen
- Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Nanjing Agricultural University, Nanjing, China
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2
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Marschmann GL, Tang J, Zhalnina K, Karaoz U, Cho H, Le B, Pett-Ridge J, Brodie EL. Predictions of rhizosphere microbiome dynamics with a genome-informed and trait-based energy budget model. Nat Microbiol 2024; 9:421-433. [PMID: 38316928 PMCID: PMC10847045 DOI: 10.1038/s41564-023-01582-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 12/08/2023] [Indexed: 02/07/2024]
Abstract
Soil microbiomes are highly diverse, and to improve their representation in biogeochemical models, microbial genome data can be leveraged to infer key functional traits. By integrating genome-inferred traits into a theory-based hierarchical framework, emergent behaviour arising from interactions of individual traits can be predicted. Here we combine theory-driven predictions of substrate uptake kinetics with a genome-informed trait-based dynamic energy budget model to predict emergent life-history traits and trade-offs in soil bacteria. When applied to a plant microbiome system, the model accurately predicted distinct substrate-acquisition strategies that aligned with observations, uncovering resource-dependent trade-offs between microbial growth rate and efficiency. For instance, inherently slower-growing microorganisms, favoured by organic acid exudation at later plant growth stages, exhibited enhanced carbon use efficiency (yield) without sacrificing growth rate (power). This insight has implications for retaining plant root-derived carbon in soils and highlights the power of data-driven, trait-based approaches for improving microbial representation in biogeochemical models.
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Affiliation(s)
- Gianna L Marschmann
- Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Jinyun Tang
- Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Kateryna Zhalnina
- Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Ulas Karaoz
- Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Heejung Cho
- Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA, USA
| | - Beatrice Le
- Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA, USA
| | - Jennifer Pett-Ridge
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, USA
- Life and Environmental Sciences Department, University of California Merced, Merced, CA, USA
| | - Eoin L Brodie
- Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
- Department of Environmental Science, Policy and Management, University of California Berkeley, Berkeley, CA, USA.
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3
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Lima J, Ingabire W, Roehe R, Dewhurst RJ. Estimating Microbial Protein Synthesis in the Rumen-Can 'Omics' Methods Provide New Insights into a Long-Standing Question? Vet Sci 2023; 10:679. [PMID: 38133230 PMCID: PMC10747152 DOI: 10.3390/vetsci10120679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 11/20/2023] [Accepted: 11/22/2023] [Indexed: 12/23/2023] Open
Abstract
Rumen microbial protein synthesis (MPS) provides at least half of the amino acids for the synthesis of milk and meat protein in ruminants. As such, it is fundamental to global food protein security. Estimating microbial protein is central to diet formulation, maximising nitrogen (N)-use efficiency and reducing N losses to the environment. Whilst factors influencing MPS are well established in vitro, techniques for in vivo estimates, including older techniques with cannulated animals and the more recent technique based on urinary purine derivative (UPD) excretion, are subject to large experimental errors. Consequently, models of MPS used in protein rationing are imprecise, resulting in wasted feed protein and unnecessary N losses to the environment. Newer 'omics' techniques are used to characterise microbial communities, their genes and resultant proteins and metabolites. An analysis of microbial communities and genes has recently been used successfully to model complex rumen-related traits, including feed conversion efficiency and methane emissions. Since microbial proteins are more directly related to microbial genes, we expect a strong relationship between rumen metataxonomics/metagenomics and MPS. The main aims of this review are to gauge the understanding of factors affecting MPS, including the use of the UPD technique, and explore whether omics-focused studies could improve the predictability of MPS, with a focus on beef cattle.
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Affiliation(s)
- Joana Lima
- SRUC Dairy Research and Innovation Centre, Barony Campus, Dumfries DG1 3NE, UK; (J.L.); (W.I.)
| | - Winfred Ingabire
- SRUC Dairy Research and Innovation Centre, Barony Campus, Dumfries DG1 3NE, UK; (J.L.); (W.I.)
| | | | - Richard James Dewhurst
- SRUC Dairy Research and Innovation Centre, Barony Campus, Dumfries DG1 3NE, UK; (J.L.); (W.I.)
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4
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Manzoni S, Chakrawal A, Ledder G. Decomposition rate as an emergent property of optimal microbial foraging. Front Ecol Evol 2023. [DOI: 10.3389/fevo.2023.1094269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Decomposition kinetics are fundamental for quantifying carbon and nutrient cycling in terrestrial and aquatic ecosystems. Several theories have been proposed to construct process-based kinetics laws, but most of these theories do not consider that microbial decomposers can adapt to environmental conditions, thereby modulating decomposition. Starting from the assumption that a homogeneous microbial community maximizes its growth rate over the period of decomposition, we formalize decomposition as an optimal control problem where the decomposition rate is a control variable. When maintenance respiration is negligible, we find that the optimal decomposition kinetics scale as the square root of the substrate concentration, resulting in growth kinetics following a Hill function with exponent 1/2 (rather than the Monod growth function). When maintenance respiration is important, optimal decomposition is a more complex function of substrate concentration, which does not decrease to zero as the substrate is depleted. With this optimality-based formulation, a trade-off emerges between microbial carbon-use efficiency (ratio of growth rate over substrate uptake rate) and decomposition rate at the beginning of decomposition. In environments where carbon substrates are easily lost due to abiotic or biotic factors, microbes with higher uptake capacity and lower efficiency are selected, compared to environments where substrates remain available. The proposed optimization framework provides an alternative to purely empirical or process-based formulations for decomposition, allowing exploration of the effects of microbial adaptation on element cycling.
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Fridman Y, Wang Z, Maslov S, Goyal A. Fine-scale diversity of microbial communities due to satellite niches in boom and bust environments. PLoS Comput Biol 2022; 18:e1010244. [PMID: 36574450 PMCID: PMC9829172 DOI: 10.1371/journal.pcbi.1010244] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 01/09/2023] [Accepted: 12/05/2022] [Indexed: 12/28/2022] Open
Abstract
Recent observations have revealed that closely related strains of the same microbial species can stably coexist in natural and laboratory settings subject to boom and bust dynamics and serial dilutions, respectively. However, the possible mechanisms enabling the coexistence of only a handful of strains, but not more, have thus far remained unknown. Here, using a consumer-resource model of microbial ecosystems, we propose that by differentiating along Monod parameters characterizing microbial growth rates in high and low nutrient conditions, strains can coexist in patterns similar to those observed. In our model, boom and bust environments create satellite niches due to resource concentrations varying in time. These satellite niches can be occupied by closely related strains, thereby enabling their coexistence. We demonstrate that this result is valid even in complex environments consisting of multiple resources and species. In these complex communities, each species partitions resources differently and creates separate sets of satellite niches for their own strains. While there is no theoretical limit to the number of coexisting strains, in our simulations, we always find between 1 and 3 strains coexisting, consistent with known experiments and observations.
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Affiliation(s)
- Yulia Fridman
- National Research Center “Kurchatov Institute”, Moscow, Russia
| | - Zihan Wang
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Sergei Maslov
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
- * E-mail: (SM); (AG)
| | - Akshit Goyal
- Physics of Living Systems, Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- * E-mail: (SM); (AG)
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6
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van den Berg NI, Machado D, Santos S, Rocha I, Chacón J, Harcombe W, Mitri S, Patil KR. Ecological modelling approaches for predicting emergent properties in microbial communities. Nat Ecol Evol 2022; 6:855-865. [PMID: 35577982 PMCID: PMC7613029 DOI: 10.1038/s41559-022-01746-7] [Citation(s) in RCA: 54] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 03/23/2022] [Indexed: 12/20/2022]
Abstract
Recent studies have brought forward the critical role of emergent properties in shaping microbial communities and the ecosystems of which they are a part. Emergent properties-patterns or functions that cannot be deduced linearly from the properties of the constituent parts-underlie important ecological characteristics such as resilience, niche expansion and spatial self-organization. While it is clear that emergent properties are a consequence of interactions within the community, their non-linear nature makes mathematical modelling imperative for establishing the quantitative link between community structure and function. As the need for conservation and rational modulation of microbial ecosystems is increasingly apparent, so is the consideration of the benefits and limitations of the approaches to model emergent properties. Here we review ecosystem modelling approaches from the viewpoint of emergent properties. We consider the scope, advantages and limitations of Lotka-Volterra, consumer-resource, trait-based, individual-based and genome-scale metabolic models. Future efforts in this research area would benefit from capitalizing on the complementarity between these approaches towards enabling rational modulation of complex microbial ecosystems.
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Affiliation(s)
| | - Daniel Machado
- Department of Biotechnology and Food Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Sophia Santos
- Centre of Biological Engineering, University of Minho, Braga, Portugal
| | - Isabel Rocha
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal
| | - Jeremy Chacón
- Ecology, Evolution and Behavior, University of Minnesota, Minneapolis, MN, USA
| | - William Harcombe
- Ecology, Evolution and Behavior, University of Minnesota, Minneapolis, MN, USA
| | - Sara Mitri
- Département de Microbiologie Fondamentale, University of Lausanne, Lausanne, Switzerland
| | - Kiran R Patil
- Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, UK.
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7
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Wang Y, Wilhelm RC, Swenson TL, Silver A, Andeer PF, Golini A, Kosina SM, Bowen BP, Buckley DH, Northen TR. Substrate Utilization and Competitive Interactions Among Soil Bacteria Vary With Life-History Strategies. Front Microbiol 2022; 13:914472. [PMID: 35756023 PMCID: PMC9225577 DOI: 10.3389/fmicb.2022.914472] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 05/12/2022] [Indexed: 11/13/2022] Open
Abstract
Microorganisms have evolved various life-history strategies to survive fluctuating resource conditions in soils. However, it remains elusive how the life-history strategies of microorganisms influence their processing of organic carbon, which may affect microbial interactions and carbon cycling in soils. Here, we characterized the genomic traits, exometabolite profiles, and interactions of soil bacteria representing copiotrophic and oligotrophic strategists. Isolates were selected based on differences in ribosomal RNA operon (rrn) copy number, as a proxy for life-history strategies, with pairs of “high” and “low” rrn copy number isolates represented within the Micrococcales, Corynebacteriales, and Bacillales. We found that high rrn isolates consumed a greater diversity and amount of substrates than low rrn isolates in a defined growth medium containing common soil metabolites. We estimated overlap in substrate utilization profiles to predict the potential for resource competition and found that high rrn isolates tended to have a greater potential for competitive interactions. The predicted interactions positively correlated with the measured interactions that were dominated by negative interactions as determined through sequential growth experiments. This suggests that resource competition was a major force governing interactions among isolates, while cross-feeding of metabolic secretion likely contributed to the relatively rare positive interactions observed. By connecting bacterial life-history strategies, genomic features, and metabolism, our study advances the understanding of the links between bacterial community composition and the transformation of carbon in soils.
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Affiliation(s)
- Ying Wang
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Roland C Wilhelm
- School of Integrative Plant Science, Cornell University, Ithaca, NY, United States
| | - Tami L Swenson
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Anita Silver
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Peter F Andeer
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Amber Golini
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Suzanne M Kosina
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Benjamin P Bowen
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States.,Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Daniel H Buckley
- School of Integrative Plant Science, Cornell University, Ithaca, NY, United States.,Department of Microbiology, Cornell University, Ithaca, NY, United States
| | - Trent R Northen
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States.,Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
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8
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Cherabier P, Ferrière R. Eco-evolutionary responses of the microbial loop to surface ocean warming and consequences for primary production. THE ISME JOURNAL 2022; 16:1130-1139. [PMID: 34864820 PMCID: PMC8940968 DOI: 10.1038/s41396-021-01166-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 11/19/2021] [Accepted: 11/26/2021] [Indexed: 11/09/2022]
Abstract
Predicting the response of ocean primary production to climate warming is a major challenge. One key control of primary production is the microbial loop driven by heterotrophic bacteria, yet how warming alters the microbial loop and its function is poorly understood. Here we develop an eco-evolutionary model to predict the physiological response and adaptation through selection of bacterial populations in the microbial loop and how this will impact ecosystem function such as primary production. We find that the ecophysiological response of primary production to warming is driven by a decrease in regenerated production which depends on nutrient availability. In nutrient-poor environments, the loss of regenerated production to warming is due to decreasing microbial loop activity. However, this ecophysiological response can be opposed or even reversed by bacterial adaptation through selection, especially in cold environments: heterotrophic bacteria with lower bacterial growth efficiency are selected, which strengthens the "link" behavior of the microbial loop, increasing both new and regenerated production. In cold and rich environments such as the Arctic Ocean, the effect of bacterial adaptation on primary production exceeds the ecophysiological response. Accounting for bacterial adaptation through selection is thus critically needed to improve models and projections of the ocean primary production in a warming world.
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Affiliation(s)
- Philippe Cherabier
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Université Paris Sciences et Lettres, CNRS, INSERM, Paris, 75005, France.
| | - Régis Ferrière
- grid.462036.5Institut de Biologie de l’Ecole Normale Supérieure (IBENS), Université Paris Sciences et Lettres, CNRS, INSERM, Paris, 75005 France ,grid.134563.60000 0001 2168 186XDepartment of Ecology & Evolutionary Biology, University of Arizona, Tucson, AZ 85721 USA ,grid.134563.60000 0001 2168 186XInternational Research Laboratory for Interdisciplinary Global Environmental Studies (iGLOBES), CNRS, ENS-PSL University, University of Arizona, Tucson, AZ 85721 USA
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9
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Abstract
Microbiomes play essential roles in the health and function of animal and plant hosts and drive nutrient cycling across ecosystems. Integrating novel trait-based approaches with ecological theory can facilitate the prediction of microbial functional traits important for ecosystem functioning and health. In particular, the yield-acquisition-stress (Y-A-S) framework considers dominant microbial life history strategies across gradients of resource availability and stress. However, microbiomes are dynamic, and spatial and temporal shifts in taxonomic and trait composition can affect ecosystem functions. We posit that extending the Y-A-S framework to microbiomes during succession and across biogeographic gradients can lead to generalizable rules for how microbiomes and their functions respond to resources and stress across space, time, and diverse ecosystems. We demonstrate the potential of this framework by applying it to the microbiomes hosted by the carnivorous pitcher plant Sarracenia purpurea, which have clear successional trajectories and are distributed across a broad climatic gradient.
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10
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Smith TP, Clegg T, Bell T, Pawar S. Systematic variation in the temperature dependence of bacterial carbon use efficiency. Ecol Lett 2021; 24:2123-2133. [PMID: 34240797 DOI: 10.1111/ele.13840] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 04/25/2021] [Accepted: 06/08/2021] [Indexed: 11/27/2022]
Abstract
Carbon use efficiency (CUE) is a key characteristic of microbial physiology and underlies community-level responses to changing environments. Yet, we currently lack general empirical insights into variation in microbial CUE at the level of individual taxa. Here, through experiments with 29 strains of environmentally isolated bacteria, we find that bacterial CUE typically responds either positively to temperature, or has no discernible response, within biologically meaningful temperature ranges. Using a global data synthesis, we show that these results are generalisable across most culturable groups of bacteria. This variation in the thermal responses of bacterial CUE is taxonomically structured, and stems from the fact that relative to respiration rates, bacterial population growth rates typically respond more strongly to temperature, and are also subject to weaker evolutionary constraints. Our results provide new insights into microbial physiology, and a basis for more accurately modelling the effects of thermal fluctuations on complex microbial communities.
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Affiliation(s)
- Thomas P Smith
- Department of Life Sciences, Imperial College London, Ascot, Berkshire, UK
| | - Tom Clegg
- Department of Life Sciences, Imperial College London, Ascot, Berkshire, UK
| | - Thomas Bell
- Department of Life Sciences, Imperial College London, Ascot, Berkshire, UK
| | - Samrāt Pawar
- Department of Life Sciences, Imperial College London, Ascot, Berkshire, UK
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