Hasil untuk "Microbial ecology"

S. Compant, A. Samad, H. Faist et al.

Graphical abstract

A. Akkermans, J. D. Elsas, F. J. Bruijn

E. Elinav, T. Strowig, A. Kau et al.

G. Muyzer, K. Smalla

Ethan T. Hillman, Hang Lu, Tianming Yao et al.

The ecosystem of the human gastrointestinal (GI) tract traverses a number of environmental, chemical, and physical conditions because it runs from the oral cavity to the anus. These differences in conditions along with food or other ingested substrates affect the composition and density of the microbiota as well as their functional roles by selecting those that are the most suitable for that environment. Previous studies have mostly focused on Bacteria, with the number of studies conducted on Archaea, Eukarya, and Viruses being limited despite their important roles in this ecosystem. Furthermore, due to the challenges associated with collecting samples directly from the inside of humans, many studies are still exploratory, with a primary focus on the composition of microbiomes. Thus, mechanistic studies to investigate functions are conducted using animal models. However, differences in physiology and microbiomes need to be clarified in order to aid in the translation of animal model findings into the context of humans. This review will highlight Bacteria, Archaea, Fungi, and Viruses, discuss differences along the GI tract of healthy humans, and perform comparisons with three common animal models: rats, mice, and pigs.

Changchao Li, Lifei Wang, Shuping Ji et al.

O. Paliy, Vijay Shankar

Kenneth Wasmund, M. Mussmann, A. Loy

Summary Almost the entire seafloor is covered with sediments that can be more than 10 000 m thick and represent a vast microbial ecosystem that is a major component of Earth's element and energy cycles. Notably, a significant proportion of microbial life in marine sediments can exploit energy conserved during transformations of sulfur compounds among different redox states. Sulfur cycling, which is primarily driven by sulfate reduction, is tightly interwoven with other important element cycles (carbon, nitrogen, iron, manganese) and therefore has profound implications for both cellular‐ and ecosystem‐level processes. Sulfur‐transforming microorganisms have evolved diverse genetic, metabolic, and in some cases, peculiar phenotypic features to fill an array of ecological niches in marine sediments. Here, we review recent and selected findings on the microbial guilds that are involved in the transformation of different sulfur compounds in marine sediments and emphasise how these are interlinked and have a major influence on ecology and biogeochemistry in the seafloor. Extraordinary discoveries have increased our knowledge on microbial sulfur cycling, mainly in sulfate‐rich surface sediments, yet many questions remain regarding how sulfur redox processes may sustain the deep‐subsurface biosphere and the impact of organic sulfur compounds on the marine sulfur cycle.

Dongmei Qiu, Liwei Suo, Tao Wei et al.

<b>Background</b>: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a globally prevalent condition with a complex pathogenesis. While both m6A RNA methylation regulators and gut microbiota have been independently implicated in MASLD, their potential causal interplay remains unexplored. This study aimed to investigate the causal relationships among m6A regulatory genes, gut microbiota, and MASLD, and to assess the mediating role of gut microbiota. <b>Methods</b>: We performed a two-sample Mendelian randomization (MR) analysis using publicly available genome-wide association study (GWAS) data. Genetic instruments for m6A regulators were derived from blood expression quantitative trait loci (eQTL) data. Gut microbiota and MASLD data were obtained from large-scale metagenomic and disease GWAS, respectively. The inverse-variance weighted method was the primary analysis, supplemented by sensitivity and mediation analyses to evaluate potential mediating pathways. <b>Results</b>: Genetically predicted levels of four m6A regulators showed significant causal associations with MASLD risk: ALKBH3 increased risk (OR = 1.17), whereas ALKBH5 (OR = 0.89), CBLL1 (OR = 0.76), and RBM15B (OR = 0.83) were protective. Nineteen gut microbial taxa were causally linked to MASLD. Among these, seven taxa were influenced by the four identified m6A genes. Although no mediation effects reached strict statistical significance, the pathway from ALKBH5 to MASLD via Parabacteroides abundance showed a suggestive indirect effect accounting for 21.9% of the total effect (<i>p</i> = 0.068). Given the limited statistical power of mediation analyses in MR settings, this observation should be interpreted with caution and requires validation in larger, well-powered studies. <b>Conclusions</b>: This MR study provides genetic evidence supporting causal roles of specific m6A regulators in MASLD and suggests that gut microbiota may partially mediate these relationships. The findings highlight a potential “m6A–gut microbiota–liver” axis in MASLD pathogenesis.

Jehane Fadlallah, Hela El Kafsi, D. Sterlin et al.

Damien Richard, Nils Poulicard

As sequencing technologies become more affordable and genomic databases expand continuously, the reuse of publicly available sequencing data emerges as a powerful strategy for studying microbial pathogens. Indeed, raw sequencing reads generated for the study of a given organism often contain reads originating from the associated microbiota. This review explores how such off-target reads can be detected and used for the study of microbial pathogens. We present genomic data mining as a method to identify relevant sequencing runs from petabase-scale databases, highlighting recent methodological advances that allow efficient database querying. We then briefly outline methods designed to retrieve relevant data and associated metadata, and provide an overview of common downstream analysis pipelines. We discuss how such approaches have (i) expanded the known genetic diversity of microbial pathogens, (ii) enriched our understanding of their spatiotemporal distribution, and (iii) highlighted previously unrecognized ecological interactions involving microbial pathogens. However, these analyses often rely on the completeness and accuracy of accompanying metadata, which remain highly variable. We detail common pitfalls, including data contamination and metadata misannotations, and suggest strategies for result interpretation. Ultimately, while data mining cannot replace dedicated studies, it constitutes an essential and complementary tool for microbial pathogen research. Broader utility will depend on improved data standardization and systematic genomic monitoring across ecosystems.

José Edson Fontes Figueiredo, Gisele de Fátima Dias Diniz, Mikaely Sousa Marins et al.

IntroductionBacillus velezensis is a ubiquitous bacterium with potent antifungal activity and a plant growth promoter. This study investigated the potential of B. velezensis CNPMS-22 as a biocontrol agent against phytopathogenic fungi under diverse experimental conditions and its potential as a plant growth promoter. Genome sequencing and analysis revealed putative genes involved in these traits.MethodsThis research performed in vitro experiments to evaluate the CNPMS-22 antagonistic activity against 10 phytopathogenic fungi using dual culture in plate (DCP) and inverted sealed plate assay (ISP). Greenhouse and field tests evaluated the ability of CNPMS-22 to control Fusarium verticillioides in maize plants in vivo. The CNPMS-22 genome was sequenced using the Illumina HiSeq 4,000 platform, and genomic analysis also included manual procedures to identify genes of interest accurately.ResultsCNPMS-22 showed antifungal activity in vitro against all fungi tested, with notable reductions in mycelial growth in both DCP and ISP experiments. In the ISP, volatile organic compounds (VOCs) produced by CNPMS-22 also altered the mycelium coloration of some fungi. Scanning electron microscopy revealed morphological alterations in the hyphae of F. verticillioides in contact with CNPMS-22, including twisted, wrinkled, and ruptured hyphae. Eight cluster candidates for synthesizing non-ribosomal lipopeptides and ribosomal genes for extracellular lytic enzymes, biofilm, VOCs, and other secondary metabolites with antifungal activity and plant growth promoters were identified by genomic analysis. The greenhouse and field experiments showed that seed treatment with CNPMS-22 reduced Fusarium symptoms in plants and increased maize productivity.ConclusionOur findings highlight the CNPMS-22’s potential as bioinoculant for fungal disease control and plant growth with valuable implications for a sustainable crop productivity.

Elise Schnabel, César Augusto Diniz Xavier, Anna E. Whitfield et al.

Numerous viruses infect blackberry, and they are associated with virus disease complexes with complicated etiologies. Blackberry virus diseases limit the lifespan of blackberry production in the Southeastern United States. Although some previous research has been conducted to understand which viruses are prevalent in South Carolina, a comprehensive study on the virome of blackberry has not been done in this region. Additionally, the role of wild Rubus as a virus inoculum source is likely underappreciated and represents a potential opportunity for disease management. We took a comprehensive approach to characterize viral genome sequences from known and novel viruses using metatranscriptomic sequencing of blackberry and wild Rubus spp. leaf samples collected in 2021 from eight sites across South Carolina. We detected 17 known and 6 novel plant viruses and describe relevant genome sequence information. Although the etiologies of these novel viruses are yet to be elucidated, they should be considered part of the blackberry/wild Rubus virome and further studied. We describe instances of potential connectivity of virus populations between cultivated blackberry and wild Rubus for several viruses at several sites. In addition to plant viruses, we describe numerous viruses likely associated with foliar fungi, referred to as Rubus leaf-associated viruses. This study revealed a diverse landscape of both known and novel viruses in blackberry and wild Rubus in South Carolina and has stimulated topics for future research, such as temporal analyses of virus spread at the landscape scale and investigating potential vectors and the biological relevance of novel viruses. [Figure: see text] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Wanxin Lai, Antton Alberdi, Andy Leu et al.

ABSTRACT The rumen microbiome plays a critical role in determining feed conversion and methane emissions in cattle, with significant implications for both agricultural productivity and environmental sustainability. In this study, we applied a hierarchical joint species distribution model to predict directional associations between biotic factors and abundances of microbial populations determined via metagenome-assembled genomes (MAGs). Our analysis revealed distinct microbial differences, including 191 MAGs significantly more abundant in animals with a higher methane yield (above 24 g/kg dry matter intake [DMI]; high-emission cattle), and 220 MAGs more abundant in low-emission cattle. Interestingly, the microbiome community of the low-methane-emission rumen exhibited higher metabolic capacity but with lower functional redundancy compared to that of high-methane-emission cattle. Our findings also suggest that microbiomes associated with low methane yields are prevalent in specific functionalities such as active fiber hydrolysis and succinate production, which may enhance their contributions to feed conversion in the host animal. This study provides an alternate genome-centric means to investigate the microbial ecology of the rumen and identify microbial and metabolic intervention targets that aim to reduce greenhouse gas emissions in livestock production systems.IMPORTANCERuminant livestock are major contributors to global methane emissions, largely through microbial fermentation in the rumen. Understanding how microbial communities vary between high- and low-methane-emitting animals is critical for identifying mitigation strategies. This study leverages a genome-centric approach to link microbial metabolic traits to methane output in cattle. By reconstructing and functionally characterizing hundreds of microbial genomes, we observe that a low-methane-emission rumen harbors well-balanced, “streamlined” microbial communities characterized by high metabolic capacity and minimal metabolic overlap across populations (low functional redundancy). Our results demonstrate the utility of genome-level functional profiling in uncovering microbial community traits tied to climate-relevant phenotypes.

Hui Chen, Siyao Li, Chengheng Fan et al.

Biological nitrogen (N) fixation is an ecological method used to provide nutrition for crops and reduce fertilizer application in terrestrial ecosystems. Silver nanoparticles (AgNPs) are becoming environmental contaminants, and, thus, could negatively affect the activity and diversity of soil diazotrophs. To test this, a greenhouse pot experiment for growing maize was performed under different concentrations of AgNPs (0, 1, 5, 10, 20 mg kg⁻¹). We measured the N₂-fixation activity and abundance of <i>nifH</i> gene encoding the nitrogenase reductase subunit and analyzed the diversity, composition and co-occurrence networks of diazotrophic communities in maize rhizospheric soil. Results showed that a lower dose of AgNPs did not show significant influence on soil diazotrophs, while a higher dose of AgNPs decreased both soil N₂-fixation activity and <i>nifH</i> gene abundance, though diazotrophic diversity remained unchanged. AgNPs at 10 mg kg⁻¹ and 20 mg kg⁻¹ strongly shifted the community composition of diazotrophs, increasing the proportions of <i>Bradyrhizobium</i> and <i>Paenibacillus,</i> while decreasing <i>Azospirillum</i> and <i>Rhizobium.</i> Network analysis revealed weakened negative associations among species under AgNPs, with keystone taxa shifting from <i>Bradyrhizobium</i>, <i>Geobacter</i>, <i>Azospirillum</i> and <i>Burkholderia</i> to <i>Bradyrhizobium</i>, <i>Paenibacillus</i> and <i>Skermanella</i> under AgNPs. Soil-soluble Ag, dissolved organic carbon and soil pH were identified as the factors most closely driving the diazotrophic community composition. In conclusion, higher doses of AgNPs could inhibit N₂-fixation activity and shape the diazotrophic communities. These findings provide empirical evidence of AgNPs’ ecological impacts on soil microbial functions.

Flavien Ferreira, Paul Oliver, Fred Kraus et al.

Species are fundamental units in biology; however, information on species diversity and distribution remain scarce for most taxonomic groups, especially in tropical rainforests. Such knowledge gaps are particularly acute in amphibians, the most threatened group of vertebrates, in which new species continue to be described at a high rate. Herein, using molecular-based approaches, we provide estimates for species diversity of frogs (Anura) in New Guinea and nearby islands, one of the biologically most diverse regions of the world. We first characterised taxonomic and geographic sampling for all available mitochondrial DNA sequences from native frog species. This led us to identify important molecular sampling gaps in the western half of New Guinea that we partially filled by adding 534 new sequences (16S rRNA). Large territories remain uncharted, particularly in the westernmost part of the central cordillera of New Guinea. Using our 16S rRNA dataset, we then delimited Molecular Operational Taxonomic Units (MOTUs), a subset of which was bioacoustically analysed. From a total of 369 delimited MOTUs, we found that 190 could not be assigned to any taxon. Amongst these, 123 are represented by specimens collected in the western half of New Guinea and 19 were supported as distinct by bioacoustics, confirming that this portion of the island is home to many unrecognised species. Based on the estimated level of undescribed diversity in taxa and areas for which data are available, we extrapolate that New Guinea and neighbouring islands could host 800–1,200 frog species, with only 560 species described to date. Highlights We assembled the most comprehensive molecular dataset to date (16S rRNA) for frogs from New Guinea and neighbouring islands. We delimited 190 candidate species, of which 19 are supported by available bioacoustic data. We estimated the actual number of frog species on New Guinea and neighbouring islands to be between 800 and 1,200. Parts of New Guinea exhibit species-diversity levels comparable to similarly sized regions in Amazonia and Madagascar. Most unrecognised frog taxa in the region are likely confined to restricted geographical areas and, thus, likely sensitive to both land use and climate change.

Lu Lin

Lignocellulose is the most abundant organic carbon polymer on the earth. Its decomposition and conversion greatly impact the global carbon cycle. Furthermore, it provides feedstock for sustainable fuel and other value-added products. However, it continues to be underutilized, due to its highly recalcitrant and heterogeneric structure. Microorganisms, which have evolved versatile pathways to convert lignocellulose, undoubtedly are at the heart of lignocellulose conversion. Numerous studies that have reported successful metabolic engineering of individual strains to improve biological lignin valorization. Meanwhile, the bottleneck of single strain modification is becoming increasingly urgent in the conversion of complex substrates. Alternatively, increased attention has been paid to microbial consortia, as they show advantages over pure cultures, e.g., high efficiency and robustness. Here, we first review recent developments in microbial communities for lignocellulose bioconversion. Furthermore, the emerging area of synthetic ecology, which is an integration of synthetic biology, ecology, and computational biology, provides an opportunity for the bottom-up construction of microbial consortia. Then, we review different modes of microbial interaction and their molecular mechanisms, and discuss considerations of how to employ these interactions to construct synthetic consortia via synthetic ecology, as well as highlight emerging trends in engineering microbial communities for lignocellulose bioconversion.

Tejasv Bedi, Bencong Zhu, Michael L. Neugent et al.

The human body consists of microbiomes associated with the development and prevention of several diseases. These microbial organisms form several complex interactions that are informative to the scientific community for explaining disease progression and prevention. Contrary to the traditional view of the microbiome as a singular, assortative network, we introduce a novel statistical approach using a weighted stochastic infinite block model to analyze the complex community structures within microbial co-occurrence microbial interaction networks. Our model defines connections between microbial taxa using a novel semi-parametric rank-based correlation method on their transformed relative abundances within a fully connected network framework. Employing a Bayesian nonparametric approach, the proposed model effectively clusters taxa into distinct communities while estimating the number of communities. The posterior summary of the taxa community membership is obtained based on the posterior probability matrix, which could naturally solve the label switching problem. Through simulation studies and real-world application to microbiome data from postmenopausal patients with recurrent urinary tract infections, we demonstrate that our method has superior clustering accuracy over alternative approaches. This advancement provides a more nuanced understanding of microbiome organization, with significant implications for disease research.

Angela Monti, Fasma Diele, Deborah Lacitignola et al.

Models of soil organic carbon (SOC) frequently overlook the effects of spatial dimensions and microbiological activities. In this paper, we focus on two reaction-diffusion chemotaxis models for SOC dynamics, both supporting chemotaxis-driven instability and exhibiting a variety of spatial patterns as stripes, spots and hexagons when the microbial chemotactic sensitivity is above a critical threshold. We use symplectic techniques to numerically approximate chemotaxis-driven spatial patterns and explore the effectiveness of the piecewice dynamic mode decomposition (pDMD) to reconstruct them. Our findings show that pDMD is effective at precisely recreating chemotaxis-driven spatial patterns, therefore broadening the range of application of the method to classes of solutions different than Turing patterns. By validating its efficacy across a wider range of models, this research lays the groundwork for applying pDMD to experimental spatiotemporal data, advancing predictions crucial for soil microbial ecology and agricultural sustainability.

Giulia Ceriotti, Alice Bosco-Santos, Sergey M. Borisov et al.

Iron (Fe) reduction is one of Earth's most ancient microbial metabolisms, but after atmosphere-ocean oxygenation, this anaerobic process was relegated to niche anoxic environments below the water and soil surface. However, new technologies to monitor redox processes at the microscale relevant to microbial cells have recently revealed that the oxygen (O2) concentrations controlling the distribution of aerobic and anaerobic metabolisms are more heterogeneous than previously believed. To explore how O2 levels regulate microbial Fe reduction, we cultivated a facultative Fe-reducing bacterium using a cutting-edge microfluidic reactor integrated with transparent planar O2 sensors. Contrary to expectations, microbial growth induced Fe(III)-oxide (ferrihydrite) reduction under fully oxygenated conditions without forming O2-depleted microsites. Batch incubations highlighted the importance of the process at a larger scale, fundamentally changing our understanding of Fe cycling from the conceptualization of metal and nutrient mobility in the subsurface to our interpretation of Fe mineralogy in the rock record.