Hasil untuk "Microbial ecology"

Tatsuo Hashimoto, Thomas Perlot, A. Rehman et al.

Malnutrition affects up to one billion people in the world and is a major cause of mortality. In many cases, malnutrition is associated with diarrhoea and intestinal inflammation, further contributing to morbidity and death. The mechanisms by which unbalanced dietary nutrients affect intestinal homeostasis are largely unknown. Here we report that deficiency in murine angiotensin I converting enzyme (peptidyl-dipeptidase A) 2 (Ace2), which encodes a key regulatory enzyme of the renin-angiotensin system (RAS), results in highly increased susceptibility to intestinal inflammation induced by epithelial damage. The RAS is known to be involved in acute lung failure, cardiovascular functions and SARS infections. Mechanistically, ACE2 has a RAS-independent function, regulating intestinal amino acid homeostasis, expression of antimicrobial peptides, and the ecology of the gut microbiome. Transplantation of the altered microbiota from Ace2 mutant mice into germ-free wild-type hosts was able to transmit the increased propensity to develop severe colitis. ACE2-dependent changes in epithelial immunity and the gut microbiota can be directly regulated by the dietary amino acid tryptophan. Our results identify ACE2 as a key regulator of dietary amino acid homeostasis, innate immunity, gut microbial ecology, and transmissible susceptibility to colitis. These results provide a molecular explanation for how amino acid malnutrition can cause intestinal inflammation and diarrhoea.

Melanie Ghoul, Sara Mitri

G. Kowalchuk, J. Stephen

S. Giovannoni, J. C. Thrash, Ben Temperton

Zhichao Zhou, Patricia Q. Tran, Adam M. Breister et al.

Advances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent; however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and microbial contributions to biogeochemical cycling. We present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry studies using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the microbiome, potential microbial metabolic handoffs and metabolite exchange, reconstruction of functional networks, and determination of microbial contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, community-scale microbial functional networks using a newly defined metric “MW-score” (metabolic weight score), and metabolic Sankey diagrams. METABOLIC takes ~ 3 h with 40 CPU threads to process ~ 100 genomes and corresponding metagenomic reads within which the most compute-demanding part of hmmsearch takes ~ 45 min, while it takes ~ 5 h to complete hmmsearch for ~ 3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut. METABOLIC enables the consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available under GPLv3 at https://github.com/AnantharamanLab/METABOLIC. 8JzsRQQL6mihmS_qxcrFZs Video abstract Video abstract

Huijie Lu, K. Chandran, D. Stensel

Elizabeth J. Culp, A. Goodman

Microbial communities are shaped by positive and negative interactions ranging from competition to mutualism. In the context of the mammalian gut and its microbial inhabitants, the integrated output of the community has important impacts on host health. Cross-feeding, the sharing of metabolites between different microbes, has emergent roles in establishing communities of gut commensals that are stable, resistant to invasion, and resilient to external perturbation. In this review, we first explore the ecological and evolutionary implications of cross-feeding as a cooperative interaction. We then survey mechanisms of cross-feeding across trophic levels, from primary fermenters to H2 consumers that scavenge the final metabolic outputs of the trophic network. We extend this analysis to also include amino acid, vitamin, and cofactor cross-feeding. Throughout, we highlight evidence for the impact of these interactions on each species' fitness as well as host health. Understanding cross-feeding illuminates an important aspect of microbe-microbe and host-microbe interactions that establishes and shapes our gut communities.

K. M. Kennedy, M. D. de Goffau, M. Perez-Muñoz et al.

Christian Kost, K. R. Patil, Jonathan Friedman et al.

A. Boetius, A. Anesio, J. Deming et al.

J. Jansson, N. Taş

PEI Xiangli, XU Zhenghe, LIU Miao et al.

【Background and Objective】Soil salinization is a major constraint to sustainable agricultural production, and amending such soils with salt-tolerant microorganisms has been found to be effective in improving soil quality and enhancing crop tolerance to water and salinity stress. This paper analyzes international research in this area.【Method】Bibliometric analysis was conducted using VOSviewer and CiteSpace to systematically examine publications from 2004 to 2024 on saline-alkali soil microbiology retrieved from the China National Knowledge Infrastructure (CNKI, 652 articles) and the Web of Science Core Collection (WOS, 982 articles).【Result】Annual publications in saline–alkali soil microbiology showed a substantial increase during this period, with publications in English journals consistently and markedly overshadowing those in Chinese journals. China led the world, publishing 1 103 papers and collaborating with 26 countries, including Canada and the United Kingdom. Keyword clustering analysis showed that research hotspots in this field were: ①microbial community structure and its environmental drivers; ②mechanisms underlying plant-microbe interactions and their ecological functions; and ③ screening of salt-tolerant and growth-promoting microorganisms, as well as the mechanisms underlying biological remediation of saline-alkali soils. From 2004 to 2024, research on microbiology in saline-alkali soil can be divided into three stages: an early stage (2004—2015) emphasizing species identification and soil improvement; a middle stage (2016—2020) focusing on microbial community ecology and functional characterization; and the most recent stage (2021—2024) characterized by increased attention to the regulation of the microbe-soil-plant system.【Conclusion】Future research in saline-alkali soil microbiology will depend on international collaboration and interdisciplinary cooperation. Advances in multi-omics approaches, big data and artificial intelligence will enable systematic elucidation of microbial community assembly and functional regulation mechanisms, which will promote precision microbial management, functional strain development, and microbiome restoration. These advances will provide environmentally friendly solutions for remediating saline-alkali soils and sustaining agricultural production to meet the growing demand for food.

Valentin Slepukhin, Víctor Peris Yagüe, Christian Westendorf et al.

Bacteria frequently colonize natural microcavities such as gut crypts, plant apoplasts, and soil pores. Recent studies have shown that the physical structure of these spaces plays a crucial role in shaping the stability and resilience of microbial populations (Karita et al., PNAS 2022, Postek et al. PNAS 2024). Here, we demonstrate that protected microhabitats can emerge dynamically, even in the absence of physical barriers. Interactions with surface features -- such as roughness or friction -- lead microbial populations to self-organize into effectively segregated subpopulations. Our numerical and analytical models reveal that this self-organization persists even when strains have different growth rates, allowing slower-growing strains to avoid competitive exclusion. These findings suggest that emergent spatial structuring can serve as a fundamental mechanism for maintaining microbial diversity, despite selection pressures, competition, and genetic drift.

Zhijie Feng, Emmy Blumenthal, Pankaj Mehta et al.

Predicting the outcomes of species invasions is a central goal of ecology, a task made especially challenging due to ecological feedbacks. To address this, we develop a general theory of ecological invasions applicable to a wide variety of ecological models: including Lotka-Volterra models, consumer resource models, and models with cross feeding. Importantly, our framework remains valid even when invading evolved (non-random) communities and accounts for invasion-driven species extinctions. We derive analytical expressions relating invasion fitness to invader abundance, shifts in the community, and extinction probabilities. These results can be understood through a new quantity we term ``dressed invasion fitness'', which augments the traditional notion of invasion fitness by incorporating ecological feedbacks. We apply our theory to analyze short-term evolutionary dynamics through a series of invasions by mutants whose traits are correlated with an existing parent. We demonstrate that, generically, mutants and parents can coexist, often by driving the extinction of low-abundance species. We validate theoretical predictions against experimental datasets spanning ecosystems from plants to microbial protists. Our work highlights the central role of ecological feedbacks in shaping community responses to invasions and mutations, suggesting that parent-mutant coexistence is widespread in eco-evolutionary dynamics.

Ellen Piercy, Xinyang Sun, Peter R Ellis et al.

Anaerobic digestion (AD) offers a sustainable biotechnology to recover resources from carbon-rich wastewater, such as food-processing wastewater. Despite crude wastewater characterisation, the impact of detailed chemical fingerprinting on AD remains underexplored. This study investigated the influence of fermentation-wastewater composition and operational parameters on AD over time to identify critical factors influencing reactor biodiversity and performance. Eighteen reactors were operated under various operational conditions using mycoprotein fermentation wastewater. Detailed chemical analysis fingerprinted the molecules in the fermentation wastewater throughout AD including sugars, sugar alcohols and volatile fatty acids (VFAs). Sequencing revealed distinct microbiome profiles linked to temperature and reactor configuration, with mesophilic conditions supporting a more diverse and densely connected microbiome. Significant elevations in Methanomassiliicoccus were correlated to high butyric acid concentrations and decreased biogas production, further elucidating the role of this newly discovered methanogen. Dissimilarity analysis demonstrated the importance of individual molecules on microbiome diversity, highlighting the need for detailed chemical fingerprinting in AD studies of microbial trends. Machine learning (ML) models predicting reactor performance achieved high accuracy based on operational parameters and microbial taxonomy. Operational parameters had the most substantial influence on chemical oxygen demand removal, whilst Oscillibacter and two Clostridium sp. were highlighted as key factors in biogas production. By integrating detailed chemical and biological fingerprinting with ML models this research presents a novel approach to advance our understanding of AD microbial ecology, offering insights for industrial applications of sustainable waste-to-energy systems.

Mattia Mattei, David Soriano Paños, Mahantesh Halappanavar et al.

Bacteria possess diverse mechanisms to regulate their motility in response to environmental and physiological signals, enabling them to navigate complex habitats and adapt their behavior. Among these mechanisms, interspecies recognition enables cells to modulate their movement based on the ecological identity of neighboring species. Here, we introduce a model in which we assume bacterial species recognizes each other and interact via local signals that either enhance or suppress the motility of neighboring cells. Through large-scale simulations and a coarse-grained stochastic model, we demonstrate the emergence of a sharp transition driven by nucleation processes: increasing the density of motility-suppressing interactions drives the system from a fully mixed, motile phase to a state characterized by large, stationary bacterial clusters. Remarkably, in systems with a large number of interacting species, this transition can be triggered solely by altering the structure of the motility-regulation interaction matrix while maintaining species and interaction densities constant. In particular, we find that heterogeneous and modular interactions promote the transition more readily than homogeneous random ones. These results contribute to the ongoing effort to understand microbial interactions, suggesting that structured, non-random ones may be key to reproducing commonly observed spatial patterns in microbial communities.

Mario Castro, Rafael Vida, Javier Galeano et al.

Metagenomic data has significantly advanced microbiome research by employing ecological models, particularly in personalised medicine. The generalised Lotka-Volterra (gLV) model is commonly used to understand microbial interactions and predict ecosystem dynamics. However, gLV models often fail to capture complex interactions, especially when data is limited or noisy. This study critically assesses the effectiveness of gLV and similar models using Bayesian inference and a model reduction method based on information theory. We found that ecological data often leads to non-interpretability and overfitting due to limited information, noisy data, and parameter sloppiness. Our results highlight the need for simpler models that align with the available data and propose a distribution-based approach to better capture ecosystem diversity, stability, and competition. These findings challenge current bottom-up ecological modelling practices and aim to shift the focus toward a Statistical Mechanics view of ecology based on distributions of parameters.

Yaa Abu, Sabita Roy

The maternal microbiome is increasingly being recognized as a key determinant in various neonatal health outcomes, including offspring immunity, metabolism, brain function, and behavior. While the oral, vaginal, skin, and gut microbiota are significant contributors to the offspring’s postnatal gut microbial seeding, the composition and diversity of the maternal gut microbiome during pregnancy seems to be critical in shaping neonatal health outcomes, even prior to birth. Growing evidence suggests that the balance among the microbial groups in the gut and their interactions with the host are crucial for health. Dysbiotic communities in pregnancy and early in life may lead to disease processes in offspring, though the specific processes by which maternal gut microbes affect offspring gut microbial development are unknown. Here, we summarize research examining gut microbial shifts during pregnancy, and their effects on the diversity and composition of the infant microbiome and on early health outcomes. We also discuss current theories for how the maternal gastrointestinal (GI) tract influences neonatal seeding, and how probiotics during the perinatal period may affect offspring health outcomes.

Dana Ment, Sapna Mishra

The Black Soldier fly (BSF), Hermetia illucens, exhibits versatile bioconversion abilities and effectively transforms various waste materials into a nutritious biomass suitable for consumption. The degradation ability of BSF larvae has been attributed to their gut microbiota. Therefore, this review explores the role of the BSF microbiota throughout the BSF life stages in the bioconversion, focusing on the BSF larvae and its microbiota. We reflect on the microbiota’s contribution to life cycle aspects, growth, reproduction, immune response, and waste breakdown. The key points discussed include the gut microbiota in organic waste bioconversion by BSF larvae, the role of microbiota in BSF oviposition and growth throughout its life history, and microbiota’s role in immunity with a specific focus on antimicrobial peptides. Where knowledge gaps were identified for BSF, we provide examples of closely related dipteran insects or insects with well-studied microbiota functioning. The significant role of the BSF gut microbiota is enabling its versatile waste degradation while conferring protection against pathogens and xenobiotic compounds. As such, we discuss the future perspectives that microbiome engineering may offer for BSF.

Shuzhen Song, Kaiming Ren, Wei Zhang et al.

Biochar and microorganisms are widely used soil amendments, but the effects of their combined application on crops and soils have not been thoroughly evaluated. We conducted a meta-analysis of 103 studies to examine the effects of biochar-microbe combined (BCM) application on crop physiology ecology and soil function. Together, they significantly improved crop growth and soil properties, with shoot dry weight increasing by 51.79 % and soil organic carbon increasing by 49.38 % compared with the control. BCM application can activate the antioxidant defense system in crops, reduce malondialdehyde levels by 18.24 %, and enhance soil bacterial abundance by 71.9 %. Their effect on soil pH was negatively correlated with the initial soil pH. The effects of BCM application vary with the properties of different biochar sources, pyrolysis temperatures, microbial species, and experiment types. Integrating microbes with low-temperature (≤ 500°C) wood-based biochar showed even better effects, not only enhancing crop growth performance and chlorophyll content, but also producing significant improvements in soil physicochemical properties. The combined application of different functional microorganisms and biochar resulted in varying effects on crop biomass accumulation, growth, and soil quality. In the study, BCM was evaluated for its ecological consequences on crops and soils, and we recommend prioritizing low-temperature biochar in combination with microorganisms to maximize crop and soil improvement.