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Conacher CG, Watson BW, Bauer FF. Gradient boosted regression as a tool to reveal key drivers of temporal dynamics in a synthetic yeast community. FEMS Microbiol Ecol 2024; 100:fiae080. [PMID: 38777744 PMCID: PMC11212668 DOI: 10.1093/femsec/fiae080] [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: 01/23/2024] [Revised: 05/14/2024] [Accepted: 05/21/2024] [Indexed: 05/25/2024] Open
Abstract
Microbial communities are vital to our lives, yet their ecological functioning and dynamics remain poorly understood. This understanding is crucial for assessing threats to these systems and leveraging their biotechnological applications. Given that temporal dynamics are linked to community functioning, this study investigated the drivers of community succession in the wine yeast community. We experimentally generated population dynamics data and used it to create an interpretable model with a gradient boosted regression tree approach. The model was trained on temporal data of viable species populations in various combinations, including pairs, triplets, and quadruplets, and was evaluated for predictive accuracy and input feature importance. Key findings revealed that the inoculation dosage of non-Saccharomyces species significantly influences their performance in mixed cultures, while Saccharomyces cerevisiae consistently dominates regardless of initial abundance. Additionally, we observed multispecies interactions where the dynamics of Wickerhamomyces anomalus were influenced by Torulaspora delbrueckii in pairwise cultures, but this interaction was altered by the inclusion of S. cerevisiae. This study provides insights into yeast community succession and offers valuable machine learning-based analysis techniques applicable to other microbial communities, opening new avenues for harnessing microbial communities.
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Affiliation(s)
- Cleo Gertrud Conacher
- Department of Viticulture and Oenology, South African Grape and Wine Research Institute, Private Bag X1, Stellenbosch University, Stellenbosch 7600, South Africa
- Centre for Artificial Intelligence Research (CAIR), School for Data-Science & Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Bruce William Watson
- Centre for Artificial Intelligence Research (CAIR), School for Data-Science & Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Florian Franz Bauer
- Department of Viticulture and Oenology, South African Grape and Wine Research Institute, Private Bag X1, Stellenbosch University, Stellenbosch 7600, South Africa
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2
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Muramatsu MK, Winter SE. Nutrient acquisition strategies by gut microbes. Cell Host Microbe 2024; 32:863-874. [PMID: 38870902 PMCID: PMC11178278 DOI: 10.1016/j.chom.2024.05.011] [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: 03/25/2024] [Revised: 05/08/2024] [Accepted: 05/14/2024] [Indexed: 06/15/2024]
Abstract
The composition and function of the gut microbiota are intimately tied to nutrient acquisition strategies and metabolism, with significant implications for host health. Both dietary and host-intrinsic factors influence community structure and the basic modes of bacterial energy metabolism. The intestinal tract is rich in carbon and nitrogen sources; however, limited access to oxygen restricts energy-generating reactions to fermentation. By contrast, increased availability of electron acceptors during episodes of intestinal inflammation results in phylum-level changes in gut microbiota composition, suggesting that bacterial energy metabolism is a key driver of gut microbiota function. In this review article, we will illustrate diverse examples of microbial nutrient acquisition strategies in the context of habitat filters and anatomical location and the central role of energy metabolism in shaping metabolic strategies to support bacterial growth in the mammalian gut.
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Affiliation(s)
- Matthew K Muramatsu
- Department of Internal Medicine, Division of Infectious Diseases, UC Davis, Davis, CA 95616, USA
| | - Sebastian E Winter
- Department of Internal Medicine, Division of Infectious Diseases, UC Davis, Davis, CA 95616, USA.
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3
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Singh K, Gupta S, Singh AP. Review: Nutrient-nutrient interactions governing underground plant adaptation strategies in a heterogeneous environment. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2024; 342:112024. [PMID: 38325661 DOI: 10.1016/j.plantsci.2024.112024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 12/20/2023] [Accepted: 02/01/2024] [Indexed: 02/09/2024]
Abstract
Plant growth relies on the mineral nutrients present in the rhizosphere. The distribution of nutrients in soils varies depending on their mobility and capacity to bind with soil particles. Consequently, plants often encounter either low or high levels of nutrients in the rhizosphere. Plant roots are the essential organs that sense changes in soil mineral content, leading to the activation of signaling pathways associated with the adjustment of plant architecture and metabolic responses. During differential availability of minerals in the rhizosphere, plants trigger adaptation strategies such as cellular remobilization of minerals, secretion of organic molecules, and the attenuation or enhancement of root growth to balance nutrient uptake. The interdependency, availability, and uptake of minerals, such as phosphorus (P), iron (Fe), zinc (Zn), potassium (K), nitrogen (N) forms, nitrate (NO3-), and ammonium (NH4+), modulate the root architecture and metabolic functioning of plants. Here, we summarized the interactions of major nutrients (N, P, K, Fe, Zn) in shaping root architecture, physiological responses, genetic components involved, and address the current challenges associated with nutrient-nutrient interactions. Furthermore, we discuss the major gaps and opportunities in the field for developing plants with improved nutrient uptake and use efficiency for sustainable agriculture.
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Affiliation(s)
- Kratika Singh
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, India
| | - Shreya Gupta
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, India
| | - Amar Pal Singh
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, India.
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4
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Giacomini JJ, Torres-Morales J, Tang J, Dewhirst FE, Borisy GG, Mark Welch JL. Spatial ecology of Haemophilus and Aggregatibacter in the human oral cavity. Microbiol Spectr 2024; 12:e0401723. [PMID: 38488280 PMCID: PMC10986600 DOI: 10.1128/spectrum.04017-23] [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: 11/23/2023] [Accepted: 01/26/2024] [Indexed: 04/06/2024] Open
Abstract
Haemophilus and Aggregatibacter are two of the most common bacterial genera in the human oral cavity, encompassing both commensals and pathogens of substantial ecological and medical significance. In this study, we conducted a metapangenomic analysis of oral Haemophilus and Aggregatibacter species to uncover genomic diversity, phylogenetic relationships, and habitat specialization within the human oral cavity. Using three metrics-pangenomic gene content, phylogenomics, and average nucleotide identity (ANI)-we first identified distinct species and sub-species groups among these genera. Mapping of metagenomic reads then revealed clear patterns of habitat specialization, such as Aggregatibacter species predominantly in dental plaque, a distinctive Haemophilus parainfluenzae sub-species group on the tongue dorsum, and H. sp. HMT-036 predominantly in keratinized gingiva and buccal mucosa. In addition, we found that supragingival plaque samples contained predominantly only one out of the three taxa, H. parainfluenzae, Aggregatibacter aphrophilus, and A. sp. HMT-458, suggesting independent niches or a competitive relationship. Functional analyses revealed the presence of key metabolic genes, such as oxaloacetate decarboxylase, correlated with habitat specialization, suggesting metabolic versatility as a driving force. Additionally, heme synthesis distinguishes H. sp. HMT-036 from closely related Haemophilus haemolyticus, suggesting that the availability of micronutrients, particularly iron, was important in the evolutionary ecology of these species. Overall, our study exemplifies the power of metapangenomics to identify factors that may affect ecological interactions within microbial communities, including genomic diversity, habitat specialization, and metabolic versatility. IMPORTANCE Understanding the microbial ecology of the mouth is essential for comprehending human physiology. This study employs metapangenomics to reveal that various Haemophilus and Aggregatibacter species exhibit distinct ecological preferences within the oral cavity of healthy individuals, thereby supporting the site-specialist hypothesis. Additionally, it was observed that the gene pool of different Haemophilus species correlates with their ecological niches. These findings shed light on the significance of key metabolic functions in shaping microbial distribution patterns and interspecies interactions in the oral ecosystem.
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Affiliation(s)
| | | | - Jonathan Tang
- The Forsyth Institute, Cambridge, Massachusetts, USA
| | - Floyd E. Dewhirst
- The Forsyth Institute, Cambridge, Massachusetts, USA
- Harvard School of Dental Medicine, Boston, Massachusetts, USA
| | | | - Jessica L. Mark Welch
- The Forsyth Institute, Cambridge, Massachusetts, USA
- Marine Biological Laboratory, Woods Hole, Massachusetts, USA
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Dai Z, Guo X, Lin J, Wang X, He D, Zeng R, Meng J, Luo J, Delgado-Baquerizo M, Moreno-Jiménez E, Brookes PC, Xu J. Metallic micronutrients are associated with the structure and function of the soil microbiome. Nat Commun 2023; 14:8456. [PMID: 38114499 PMCID: PMC10730613 DOI: 10.1038/s41467-023-44182-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 12/04/2023] [Indexed: 12/21/2023] Open
Abstract
The relationship between metallic micronutrients and soil microorganisms, and thereby soil functioning, has been little explored. Here, we investigate the relationship between metallic micronutrients (Fe, Mn, Cu, Zn, Mo and Ni) and the abundance, diversity and function of soil microbiomes. In a survey across 180 sites in China, covering a wide range of soil conditions the structure and function of the soil microbiome are highly correlated with metallic micronutrients, especially Fe, followed by Mn, Cu and Zn. These results are robust to controlling for soil pH, which is often reported as the most important predictor of the soil microbiome. An incubation experiment with Fe and Zn additions for five different soil types also shows that increased micronutrient concentration affects microbial community composition and functional genes. In addition, structural equation models indicate that micronutrients positively contribute to the ecosystem productivity, both directly (micronutrient availability to plants) and, to a lesser extent, indirectly (via affecting the microbiome). Our findings highlight the importance of micronutrients in explaining soil microbiome structure and ecosystem functioning.
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Affiliation(s)
- Zhongmin Dai
- Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
- Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
- The Rural Development Academy at Zhejiang University, Zhejiang University, Hangzhou, 310058, China
| | - Xu Guo
- Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
- Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
| | - Jiahui Lin
- Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
- Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
| | - Xiu Wang
- Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
- Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
| | - Dan He
- Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
- Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
| | - Rujiong Zeng
- Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
- Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
| | - Jun Meng
- Zhejiang Province Key Laboratory of Recycling and Ecological Treatment of Waste Biomass, School of Environmental and Natural Resources, Zhejiang University of Science and Technology, Hangzhou, 310023, China
| | - Jipeng Luo
- Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Manuel Delgado-Baquerizo
- Laboratorio de Biodiversidad y Funcionamiento Ecosistémico. Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS), CSIC, Av. Reina Mercedes 10, E-41012, Sevilla, Spain
| | - Eduardo Moreno-Jiménez
- Department of Agricultural and Food Chemistry, Faculty of Sciences, Universidad Autónoma de Madrid, 28049, Madrid, Spain
- Institute for Advanced Research in Chemical Sciences, Faculty of Sciences, Universidad Autónoma de Madrid, 28049, Madrid, Spain
| | - Philip C Brookes
- Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
- Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
| | - Jianming Xu
- Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China.
- Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China.
- The Rural Development Academy at Zhejiang University, Zhejiang University, Hangzhou, 310058, China.
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Zhang G, Shi L, Liu C, Mao R, Xia B, Huang Z, Wei X, Wu L, Zheng Y, Wei G, Xu J, Gao S, Chen S, Dong L. Modules in robust but low-efficiency phyllosphere fungal networks drive saponin accumulation in leaves of different Panax species. ENVIRONMENTAL MICROBIOME 2023; 18:57. [PMID: 37438802 DOI: 10.1186/s40793-023-00516-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Accepted: 07/07/2023] [Indexed: 07/14/2023]
Abstract
BACKGROUND The phyllosphere mycobiome plays a crucial role in plant fitness and ecosystem functions. The complex microbial ecological networks (MEN) formed by these fungi remain poorly understood, particularly with regard to their organization strategy and their contributions to plant secondary metabolites such as saponin. RESULTS In this study, we constructed six MENs from leaf epiphytic and endophytic mycobiomes of three Panax species distributed in the northeast and southwest ends of mainland China. Hub nodes were absent in these MENs, which were significantly more complex, robust, and less efficient compared to random graphs (P < 0.05), indicating a hub-independent high-robustness strategy to maintain structural homeostasis. The important roles of specific MEN modules in shaping leaf saponin profiles of each Panax species were proved by multiple machine learning algorithms. Positive regulation modules (PRMs) of total saponin content were further identified, which exhibited more deterministic ecological assembly and comprised of highly connected nodes as well as higher proportion of plant-associated fungal guilds compared to other network members, indicating their tight links with host plant. The significant and direct effects (P < 0.05) of PRMs on total saponin accumulation were validated by well-fitted structural equation models (χ2 < 0.3, P > 0.5). Taxonomic analysis revealed that Pleosporales and Chaetothyriales were significantly overrepresented by positive regulation taxa (PRT) of total saponin content (FDR < 0.05). Across PRT identified in three Panax species, Epicoccum and Coniothyrium were conservatively present, while species-specific taxa such as Agaricales were also found, indicating the conservatism and specificity of plant-fungi interactions associated with leaf saponin accumulation in Panax genus. CONCLUSIONS These findings provide a foundation for understanding mechanisms maintaining the steady state of phyllosphere mycobiome in healthy plant, and offer clues for engineering phyllosphere mycobiome to improve the accumulation of bioactive secondary metabolites on the basis of network modules.
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Affiliation(s)
- Guozhuang Zhang
- Key Laboratory of Beijing for Identification and Safety Evaluation of Chinese Medicine, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Liping Shi
- Key Laboratory of Beijing for Identification and Safety Evaluation of Chinese Medicine, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Congsheng Liu
- Zhangzhou Pien Tze Huang Pharmaceutical Co., Ltd., Fujian, 363000, China
| | - Renjun Mao
- School of Life Sciences, Yan' an University, Yan' an, 716000, China
| | - Bing Xia
- Key Laboratory of Beijing for Identification and Safety Evaluation of Chinese Medicine, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Zhixin Huang
- Zhangzhou Pien Tze Huang Pharmaceutical Co., Ltd., Fujian, 363000, China
| | - Xiuye Wei
- Key Laboratory of Beijing for Identification and Safety Evaluation of Chinese Medicine, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Lixuan Wu
- Zhangzhou Pien Tze Huang Pharmaceutical Co., Ltd., Fujian, 363000, China
| | - Yuqing Zheng
- Zhangzhou Pien Tze Huang Pharmaceutical Co., Ltd., Fujian, 363000, China
| | - Guangfei Wei
- Key Laboratory of Beijing for Identification and Safety Evaluation of Chinese Medicine, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Jia Xu
- Key Laboratory of Beijing for Identification and Safety Evaluation of Chinese Medicine, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Shuangrong Gao
- Key Laboratory of Beijing for Identification and Safety Evaluation of Chinese Medicine, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Shilin Chen
- Key Laboratory of Beijing for Identification and Safety Evaluation of Chinese Medicine, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China
- Institute of Herbgenomics, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Linlin Dong
- Key Laboratory of Beijing for Identification and Safety Evaluation of Chinese Medicine, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China.
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