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Held NA, Manhart M. Are microbes colimited by multiple resources? Curr Opin Microbiol 2024; 80:102509. [PMID: 38991468 DOI: 10.1016/j.mib.2024.102509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 05/03/2024] [Accepted: 06/20/2024] [Indexed: 07/13/2024]
Abstract
Resource colimitation - the dependence of growth on multiple resources simultaneously - has become an important topic in microbiology due both to the development of systems approaches to cell physiology and ecology and to the relevance of colimitation to environmental science, biotechnology, and human health. Empirical tests of colimitation in microbes suggest that it may be common in nature. However, recent theoretical and empirical work has demonstrated the need for systematic measurements across resource conditions, in contrast to the factorial supplementation experiments used in most previous studies. The mechanistic causes of colimitation remain unclear in most cases and are an important challenge for future work, but we identify the alignment of resource consumption with the environment, interactions between resources, and biological and environmental heterogeneity as major factors. On the other hand, the consequences of colimitation are widespread for microbial physiology and ecology, especially the prediction and control of microbial growth, motivating continued consideration of this state in microbiology.
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Affiliation(s)
- Noelle A Held
- Department of Biological Sciences, Marine and Enviornmental Biology Section, University of Southern California, Los Angeles, CA, USA.
| | - Michael Manhart
- Center for Advanced Biotechnology and Medicine and Department of Biochemistry and Molecular Biology, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA.
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Yamagishi JF, Kaneko K. Universal Transitions between Growth and Dormancy via Intermediate Complex Formation. PHYSICAL REVIEW LETTERS 2024; 132:118401. [PMID: 38563921 DOI: 10.1103/physrevlett.132.118401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 01/30/2024] [Indexed: 04/04/2024]
Abstract
A simple cell model consisting of a catalytic reaction network with intermediate complex formation is numerically studied. As nutrients are depleted, the transition from the exponential growth phase to the growth-arrested dormant phase occurs along with hysteresis and a lag time for growth recovery. This transition is caused by the accumulation of intermediate complexes, leading to the jamming of reactions and the diversification of components. These properties are generic in random reaction networks, as supported by dynamical systems analyses of corresponding mean-field models.
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Affiliation(s)
- Jumpei F Yamagishi
- Department of Basic Science, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
| | - Kunihiko Kaneko
- Center for Complex Systems Biology, Universal Biology Institute, University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-0041, Japan
- Niels Bohr Institute, University of Copenhagen, Blegdamsvej 17, 2100 Copenhagen, Denmark
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Kimotho RN, Maina S. Unraveling plant-microbe interactions: can integrated omics approaches offer concrete answers? JOURNAL OF EXPERIMENTAL BOTANY 2024; 75:1289-1313. [PMID: 37950741 PMCID: PMC10901211 DOI: 10.1093/jxb/erad448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 11/08/2023] [Indexed: 11/13/2023]
Abstract
Advances in high throughput omics techniques provide avenues to decipher plant microbiomes. However, there is limited information on how integrated informatics can help provide deeper insights into plant-microbe interactions in a concerted way. Integrating multi-omics datasets can transform our understanding of the plant microbiome from unspecified genetic influences on interacting species to specific gene-by-gene interactions. Here, we highlight recent progress and emerging strategies in crop microbiome omics research and review key aspects of how the integration of host and microbial omics-based datasets can be used to provide a comprehensive outline of complex crop-microbe interactions. We describe how these technological advances have helped unravel crucial plant and microbial genes and pathways that control beneficial, pathogenic, and commensal plant-microbe interactions. We identify crucial knowledge gaps and synthesize current limitations in our understanding of crop microbiome omics approaches. We highlight recent studies in which multi-omics-based approaches have led to improved models of crop microbial community structure and function. Finally, we recommend holistic approaches in integrating host and microbial omics datasets to achieve precision and efficiency in data analysis, which is crucial for biotic and abiotic stress control and in understanding the contribution of the microbiota in shaping plant fitness.
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Affiliation(s)
- Roy Njoroge Kimotho
- Hebei Key Laboratory of Soil Ecology, Key Laboratory of Agricultural Water Resources, Centre for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Solomon Maina
- Elizabeth Macarthur Agricultural Institute, NSW Department of Primary Industries, Menangle, New South Wales 2568, Australia
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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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Narla AV, Hwa T, Murugan A. Dynamic coexistence driven by physiological transitions in microbial communities. ARXIV 2024:arXiv:2401.02556v1. [PMID: 38259349 PMCID: PMC10802671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Microbial ecosystems are commonly modeled by fixed interactions between species in steady exponential growth states. However, microbes often modify their environments so strongly that they are forced out of the exponential state into stressed or non-growing states. Such dynamics are typical of ecological succession in nature and serial-dilution cycles in the laboratory. Here, we introduce a phenomenological model, the Community State model, to gain insight into the dynamic coexistence of microbes due to changes in their physiological states. Our model bypasses specific interactions (e.g., nutrient starvation, stress, aggregation) that lead to different combinations of physiological states, referred to collectively as "community states", and modeled by specifying the growth preference of each species along a global ecological coordinate, taken here to be the total community biomass density. We identify three key features of such dynamical communities that contrast starkly with steady-state communities: increased tolerance of community diversity to fast growth rates of species dominating different community states, enhanced community stability through staggered dominance of different species in different community states, and increased requirement on growth dominance for the inclusion of late-growing species. These features, derived explicitly for simplified models, are proposed here to be principles aiding the understanding of complex dynamical communities. Our model shifts the focus of ecosystem dynamics from bottom-up studies based on idealized inter-species interaction to top-down studies based on accessible macroscopic observables such as growth rates and total biomass density, enabling quantitative examination of community-wide characteristics.
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Affiliation(s)
| | - Terence Hwa
- Department of Physics, University of California, San Diego
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