Hasil untuk "Microbial ecology"

C. Field, J. Randerson, C. Malmstrom

Terrestrial net primary production (NPP) is sensitive to a number of controls, including aspects of climate, topography, soils, plant and microbial characteristics, disturbance, and anthropogenic impacts. Yet, at least at the global scale, models based on very different types and numbers of parameters yield similar results. Part of the reason for this is that the major NPP controls influence each other, resulting, under current conditions, in broad correlations among controls. NPP models that include richer suites of controlling parameters should be more sensitive to conditions that disrupt the broad correlations, but the current paucity of global data limits the power of complex models. Improved data sets will facilitate applications of complex models, but many of the critical data are very difficult to produce, especially for applications dealing with the past or future. It may be possible to overcome some of the challenges of data availability through increased understanding and modeling of ecological processes that adjust plant physiology and architecture in relation to resources. The CASA (Carnegie, Stanford, Ames Approach) model introduced by Potter et al. (1993) and expanded here uses a combination of ecological principles, satellite data, and surface data to predict terrestrial NPP on a monthly time step. CASA calculates NPP as a product of absorbed photosynthetically active radiation, APAR, and an efficiency of radiation use, ϵ. The underlying postulate is that some of the limitations on NPP appear in each. CASA estimates annual terrestrial NPP to be 48 Pg and the maximum efficiency of PAR utilization (ϵ∗) to be 0.39 g C MJ−1 PAR. Spatial and temporal variation in APAR is more than fivefold greater than variation in ϵ.

S. Krause, X. Le Roux, P. Niklaus et al.

In ecology, biodiversity-ecosystem functioning (BEF) research has seen a shift in perspective from taxonomy to function in the last two decades, with successful application of trait-based approaches. This shift offers opportunities for a deeper mechanistic understanding of the role of biodiversity in maintaining multiple ecosystem processes and services. In this paper, we highlight studies that have focused on BEF of microbial communities with an emphasis on integrating trait-based approaches to microbial ecology. In doing so, we explore some of the inherent challenges and opportunities of understanding BEF using microbial systems. For example, microbial biologists characterize communities using gene phylogenies that are often unable to resolve functional traits. Additionally, experimental designs of existing microbial BEF studies are often inadequate to unravel BEF relationships. We argue that combining eco-physiological studies with contemporary molecular tools in a trait-based framework can reinforce our ability to link microbial diversity to ecosystem processes. We conclude that such trait-based approaches are a promising framework to increase the understanding of microbial BEF relationships and thus generating systematic principles in microbial ecology and more generally ecology.

Huaiyu Ye, Xiaoying Yang, Mingxuan Zheng et al.

Abstract Background Second-generation antipsychotics (SGAs) are increasingly being utilized in children and adolescents. Risperidone, one of the most commonly prescribed SGAs in this population, has been found to adversely affect cognitive function; however, limited knowledge exists regarding the impact of risperidone on the gut microbiome-brain axis. We hypothesized that the cognitive impairment induced by risperidone is mediated by alterations in the gut microbiome and its metabolites. Results In this study, we found that early-life risperidone exposure impaired cognition in mice, including deficits in behavior tests and hippocampal dendritic architecture. The risperidone-exposed mice also exhibited gut microbiota dysbiosis along with damage to the intestinal barrier. Fecal microbiota transplantation (FMT) from treated donors to recipients demonstrated the causal role of the gut microbiome in risperidone-induced cognitive deficits. Of note, risperidone increased the abundance of species Escherichia coli, Eggerthella lenta, Ruminococcus gnavus, Clostridium perfringens, Clostridium difficile, and Blautia hydrogenotrophica. These altered species are identified to encode 7α-HSDH, 3β/α-HSDH, TyrB, and porA, the key enzymes in secondary bile acid metabolism and tyrosine metabolism. Furthermore, a significant reduction in tauroursodeoxycholic acid (TUDCA, the metabolite of bile acid metabolism) and accumulation of p-cresol (the metabolite of tyrosine metabolism) were observed in the brains of mice exposed to risperidone. Mechanically, TUDCA prevented cognitive impairment and endoplasmic reticulum (ER) stress in the hippocampus induced by risperidone, while p-cresol induced neuronal ER stress. Knockout of protein tyrosine phosphatase 1B (PTP1B, ER stress-associated protein) in neurons ameliorated cognitive impairment and neurological damage induced by risperidone. Conclusions This study, for the first time, reveals that early risperidone exposure induces gut microbiome dysbiosis and disturbs the bile acids/tyrosine-PTP1B axis to impair cognitive function. These findings alert the risk of gut and neurological side effects of SGAs treatment and highlight that it is crucial to maintain gut homeostasis during the brain developmental phases of children and adolescents with SGAs exposure. Video Abstract

A. Brune, Carsten Dietrich

Y. Nancharaiah, Piet N.L. Lens

Jurga Jankauskienė, Kornelija Janušaitienė, Jūratė Karosienė et al.

The agricultural sector plays one of the pivotal roles in fulfilling the objectives set forth by the EU Green Deal. However, the extensive use of synthetic fertilizers has contributed to nutrient over-enrichment in aquatic ecosystems, promoting eutrophication due to excess nitrogen inputs from fertilizers. This phenomenon is a key driver of rapid and excessive algal blooms in rivers, lakes, and seas. In this study, three globally cultivated crop species—oilseed rape (<i>Brassica napus</i> L.), common wheat (<i>Triticum aestivum</i> L.), and pea (<i>Pisum sativum</i> L.)—were selected for experimental analysis, including the assessment of biochemical parameters such as proline content, lipid peroxidation levels, hydrogen peroxide production, total phenol content, and antioxidant activity, which were evaluated to determine the potential of phytoplankton biomass as a substitute for synthetic fertilizers. Various quantities of lyophilized phytoplankton biomass, collected from the Curonian Lagoon, a biologically productive and ecologically sensitive brackish water body in the southeastern Baltic region, were incorporated into the growth substrates of the studied plants. The findings indicate that utilizing excess phytoplankton biomass can serve not only as a plant growth biostimulant but also as a sustainable alternative to synthetic fertilizers, thereby contributing to improved water quality and more environmentally responsible agricultural practices.

Jinyuan Liu, Qixian Zou, Diyan Li et al.

IntroductionFrançois’ langur (Trachypithecus francoisi), an endangered primate endemic to limestone forests in Vietnam and China, relies on gut microbiota to maintain gastrointestinal stability and adapt to dietary shifts. While gut microbial communities are dynamic and sensitive to seasonal and resource variations, their specific responses in François’ langurs remain poorly characterized. This study investigates seasonal variations in the composition and diversity of gut bacterial and fungal communities in this species to enhance understanding of its ecological adaptations.MethodsFresh fecal samples from 22 François’ langurs in Mayanghe National Nature Reserve, China, were collected across four seasons. Bacterial and fungal communities were analyzed using high-throughput sequencing to assess taxonomic composition and α-diversity. Statistical comparisons were conducted to evaluate seasonal differences at phylum and genus levels.ResultsSignificant seasonal shifts occurred in both bacterial and fungal communities. Bacterial α-diversity peaked in warmer seasons, whereas fungal diversity was higher in colder months. At the genus level, Akkermansia (1.3% relative abundance in summer), a mucin-degrading bacterium linked to gut health, dominated warmer seasons. In contrast, the fungal genus Cercophora, associated with plant biomass degradation, was enriched during colder seasons. Seasonal factors strongly influenced microbial structure, with distinct community assemblages observed across all seasons.DiscussionThe inverse diversity patterns of bacterial and fungal communities suggest complementary roles in nutrient extraction under seasonal dietary constraints. Akkermansia’s summer prevalence may reflect enhanced mucin utilization during fruit-rich periods, while Cercophora’s cold-season dominance likely aids cellulose breakdown in leaf-heavy diets. These dynamics highlight the microbiota’s role in optimizing energy harvest from seasonally variable diets. By elucidating microbial seasonal plasticity, this study provides critical insights for developing conservation strategies tailored to the nutritional ecology of François’ langurs.

Mei Yang, Qian Xie, Jing Wang et al.

Abstract Background Gut microbiota has been extensively demonstrated to modulate host lipid metabolism. Higher intramuscular fat (IMF) accumulation in Chinese indigenous breed pigs is associated with their special gut microbiota structure. However, the specific microbes and metabolic pathways responsible for lipid deposition are still poorly understood. Results In the present study, a comparative analysis of the gut microbiota and metabolome in obese Ningxiang (NX) pigs and lean Duroc × Landrace × Yorkshire (DLY) pigs was conducted. The results revealed a higher abundance of gut lactobacilli and a correlation of branched-chain amino acid (BCAA) metabolism pathway in NX pigs. We proceeded to verify the roles of various lactobacilli strains originating from NX pigs in BCAA metabolism and lipids deposition in SD rats. We demonstrated that L. reuteri is a fundamental species responsible for modulating lipid deposition in NX pigs and that increased circulating levels of BCAA are positively linked to greater lipid deposition. Additionally, it has been verified that L. reuteri originating from NX pigs has the ability to improve BCAA synthesis in the gut and enhance IMF content in lean DLY pigs. The expression of genes related to lipid synthesis was also significantly upregulated. Conclusions Taken together, our results imply that NX pig-derived L. reuteri regulates BCAA metabolism and plays a potential role in improving the meat quality of lean pig breeds through modulation of host intramuscular lipid deposition. The results provide a new strategy for improving the meat quality of commercial pigs by influencing host metabolism through supplementing dietary additives. Video Abstract

Yulong Zha, Linrui Fan, Tao Shen et al.

Abstract Acute lung injury (ALI) associated with pulmonary edema is a severe clinical condition characterized by acute inflammation, disrupted lung barrier function, and high mortality. Current therapeutic strategies remain limited, highlighting the need for exploring novel agents and their underlying mechanisms. Triptolide (TP), an active component derived from Tripterygium wilfordii, has shown anti-inflammatory and tissue-protective properties1,2, but its specific role in alleviating ALI and the involvement of the lung-gut axis in metabolic regulation remain poorly understood. This study aims to investigate the therapeutic effects of TP on LPS-induced ALI, focusing on its impact on pulmonary edema and inflammatory injury. By analyzing the lung-gut axis using multi-omics approaches, we seek to clarify the metabolic network regulatory mechanisms through which TP exerts its effects. LPS-induced ALI model was established in Balb/c mice, with TP administered as the therapeutic intervention. Histopathological examination of lung tissues and detection of pro-inflammatory cytokines were performed to assess lung injury. Untargeted metabolomics via LC-MS/MS was used to identify differential metabolites in lung tissues and serum, while metagenomic sequencing analyzed changes in gut microbiota composition. Integrated multi-omics analysis was applied to explore associations between gut microbiota alterations, serum metabolites, and pulmonary bile acid levels. TP administration significantly reduced histopathological damage in lung tissues of ALI mice and decreased pro-inflammatory cytokine levels. Metabolomics profiling revealed distinct changes in key metabolites, including bile acids, amino acid derivatives, and energy metabolism intermediates, in both lung tissues and serum after TP treatment. Metagenomic analysis showed that TP restructured gut microbiota composition, with functional enrichment in glycolysis and thiamine metabolism pathways. Integrated analysis confirmed strong correlations between dynamic microbiota changes, serum metabolite profiles, and pulmonary bile acid levels, indicating a regulatory role of the lung-gut axis. This study demonstrates that TP alleviates pulmonary edema and inflammatory injury in ALI by modulating gut microbial ecology and function, which drives bile acid metabolic reprogramming and regulates metabolite interactions within the lung-gut axis. These findings provide novel insights into TP’s therapeutic mechanism and support its potential application in ALI treatment.

Alice Beau, Jane Natividad, Berengère Benoit et al.

Chronic kidney disease (CKD) is characterized by accumulation of uremic toxins (UTs), such as p-cresyl sulfate and indoxyl sulfate, generated through the transformation of tyrosine and tryptophan by the gut microbiota. Using an ex vivo Simulator of the Human Intestinal Microbial Ecosystem (SHIME) colonized with fecal samples from eight CKD patients or nine healthy volunteers, a higher bacterial generation of p-cresol and indoles post-amino acid enrichment, as well lower basal butyrate levels, in the feces of CKD patients were found. Through in silico data mining, we selected a probiotic strain lacking the capacity to produce UT, i.e. without genes for tryptophanase, tyrosinase and urease. In vitro, we confirmed the potential of cellobiose as a prebiotic supporting the growth of this strain. We further designed a novel specific multi-biotic for CKD (SynCKD) [containing a probiotic Lactobacillus johnsonii NCC533, a prebiotic (1% cellobiose), and a postbiotic (1% short and medium chain triglycerides C4-C8, a source of butyrate)]. SynCKD effectively curtailed UT precursor generation ex vivo. The in vivo efficacy of SynCKD (and the synergic effect) was established in two uremic rodent models, demonstrating lower plasma levels of UTs and enhancing kidney function after 6–8 weeks of treatment. These effects were linked to better gut microbial ecology. Metagenomic analysis revealed reduced microbial genes for tryptophan/tyrosine degradation. This study lays the foundation for SynCKD as a potential therapy to mitigate CKD progression.

Xin Kou, Xiong Cao, Yushuai Wang et al.

Ecological water replenishment (EWR) has been an essential strategy to alleviate water scarcity and restore ecological functions in degraded rivers. However, the ecological consequences of multi-source replenishment, particularly how diverse water inputs jointly reshape microbial communities, assembly processes and network stability, remain largely underexplored. Here, we investigated the Yongding River Basin, a representative water-scarce river system in northern China that receives inflows including natural surface runoff, inter-basin transfers from Yellow River and South-to-North Water Diversion Project (SNWD), and reclaimed municipal wastewater. Through integrated analysis of bacterioplankton and bacteriobenthos communities, we found a progressive decline in alpha diversity and significant shifts in beta diversity from upstream to downstream sections with increasing engineered inputs. Stochastic processes dominated the assembly of both bacterioplankton and bacteriobenthos, although their relative importance varied with replenishment source. Compared with natural runoff, the proportions of dispersal limitation and homogeneous selection for bacterioplankton decreased under Yellow River and mixed replenishment, whereas bacteriobenthos assembly exhibited little overall change. Network analysis further revealed that EWR reduced the resilience of bacterioplankton network but enhanced that of bacteriobenthos. Across the entire aquatic ecosystem, microbial network complexity was strongly and positively associated with ecological stability. More, community assembly process affected network stability not only directly but also indirectly through their regulation of microbial diversity. These findings advance the mechanistic understanding of how large-scale, multi-source EWR reshapes microbial ecology and network structure, providing valuable insights for optimizing water input allocation, enhancing the functional recovery of aquatic microbial ecosystems, and supporting the sustainable management of water resources.

Annalisa Caligiuri, Emile Emery, Leonardo Ferreira et al.

Ecological communities are composed of species interactions that respond to environmental fluctuations. Despite increasing evidence of temporal variation in these interactions, most theoretical frameworks remain rooted in static assumptions. Here, we develop and apply a time-varying network model to five long-term ecological datasets spanning diverse taxa and environments. Using a generalized Lotka-Volterra framework with environmental covariates, we quantify temporal rewiring of interspecific interactions, asymmetry patterns, and structural stability. Our results reveal contrasting dynamics across ecosystems: in datasets with rich temporal resolution, interaction networks exhibit marked rewiring and shifts in cooperation-competition ratios that correlate with environmental stress, consistent, though not always linearly, with the stress-gradient hypothesis. Conversely, in datasets with coarser temporal sampling, networks retain constant interaction sign structure and remain in cooperation-dominated regimes. These findings highlight the importance of temporal resolution and environmental context in shaping ecological coexistence.

Alex Hoi Hang Chan, Otto Brookes, Urs Waldmann et al.

Computer vision methods have demonstrated considerable potential to streamline ecological and biological workflows, with a growing number of datasets and models becoming available to the research community. However, these resources focus predominantly on evaluation using machine learning metrics, with relatively little emphasis on how their application impacts downstream analysis. We argue that models should be evaluated using application-specific metrics that directly represent model performance in the context of its final use case. To support this argument, we present two disparate case studies: (1) estimating chimpanzee abundance and density with camera trap distance sampling when using a video-based behaviour classifier and (2) estimating head rotation in pigeons using a 3D posture estimator. We show that even models with strong machine learning performance (e.g., 87% mAP) can yield data that leads to discrepancies in abundance estimates compared to expert-derived data. Similarly, the highest-performing models for posture estimation do not produce the most accurate inferences of gaze direction in pigeons. Motivated by these findings, we call for researchers to integrate application-specific metrics in ecological/biological datasets, allowing for models to be benchmarked in the context of their downstream application and to facilitate better integration of models into application workflows.

Eric D. Kelsic, Jeffrey Zhao, Kalin H. Vetsigian et al.

A major challenge in theoretical ecology is understanding how natural microbial communities support species diversity, and in particular how antibiotic-producing, -sensitive and -resistant species coexist. While cyclic ‘rock–paper–scissors’ interactions can stabilize communities in spatial environments, coexistence in unstructured environments remains unexplained. Here, using simulations and analytical models, we show that the opposing actions of antibiotic production and degradation enable coexistence even in well-mixed environments. Coexistence depends on three-way interactions in which an antibiotic-degrading species attenuates the inhibitory interactions between two other species. These interactions enable coexistence that is robust to substantial differences in inherent species growth rates and to invasion by ‘cheating’ species that cease to produce or degrade antibiotics. At least two antibiotics are required for stability, with greater numbers of antibiotics enabling more complex communities and diverse dynamic behaviours ranging from stable fixed points to limit cycles and chaos. Together, these results show how multi-species antibiotic interactions can generate ecological stability in both spatially structured and mixed microbial communities, suggesting strategies for engineering synthetic ecosystems and highlighting the importance of toxin production and degradation for microbial biodiversity.

Pamela C. Köster, Ana M. Figueiredo, Jenny G. Maloney et al.

Abstract The ongoing increase in wild boar populations across Europe has fostered human–wildlife conflicts, including the transmission of emerging pathogens with zoonotic importance. Blastocystis is a ubiquitous, faecal-oral transmitted protist that can cause gastrointestinal illnesses and is observed in humans and animals worldwide. The role of wildlife in the epidemiology of Blastocystis is insufficiently understood. Thus, we investigated the occurrence and subtype diversity of Blastocystis in free-ranging wild boars from the Iberian Peninsula using conventional PCR and next-generation amplicon sequencing of a fragment of the ssu RNA gene. A total of 459 wild boar faecal samples were collected across Spain (n = 360) and Portugal (n = 99) between 2014 and 2021. Blastocystis was present in 15.3% (70/459; 95% CI 12.1–18.9) of the wild boars analysed, and its occurrence was significantly higher in Portugal (34.3%, 34/99; 95% CI 25.1–44.6) than in Spain (10.0%, 36/360; 95% CI 7.1–13.6). Seven Blastocystis subtypes (ST5, ST10b, ST13–ST15, ST24b, and ST43) were detected among the surveyed wild boar populations, with greater variability detected in Portuguese samples. ST5 was identified in all the Blastocystis-positive animals, whereas 14.3% of them harboured ST mixed colonisations. Our results demonstrate that Blastocystis ST5 is particularly adapted to infect wild boars. The additional identification of zoonotic STs reinforces the role of wild boars as spreaders of zoonotic infections with public health significance.

Shibabrata Pattanayak

The use of biocide chemicals is crucial for the elimination of microbial species required to prevent the spread of infectious diseases and ensure the safeguarding of animal and human health. Like antimicrobial drug resistance (AMR), anti-biocide resistance (ABR) may be a serious threat to healthcare, agriculture, animal husbandry, pisciculture as well as pharmaceutical and many other industries. Pathways of functioning of the antimicrobial drugs and biocides are alike in many cases, and among the patterns of resistance development in the microbes, such similarities are also found. Reaching such multidrug and multi-biocide resistant microbes in the water bodies and other sectors of the environment may also cause serious effects on ecology, the environment, and the entire biosphere. Framing of strict legislative measures is required for the rational use of biocides by considering their spectrum of activity, effective concentration in different conditions, residue calculation, and after-use destruction. This review aims to explore the use, detection, and regulation of biocidal agents across different contexts, highlighting their application that can contribute to the concurrent development of biocidal resistance and overall antimicrobial resistance among microorganisms.

J. Seiffarth, L. Blöbaum, R. D. Paul et al.

Tracking the development of living cells in live-cell time-lapses reveals crucial insights into single-cell behavior and presents tremendous potential for biomedical and biotechnological applications. In microbial live-cell imaging (MLCI), a few to thousands of cells have to be detected and tracked within dozens of growing cell colonies. The challenge of tracking cells is heavily influenced by the experiment parameters, namely the imaging interval and maximal cell number. For now, tracking benchmarks are not widely available in MLCI and the effect of these parameters on the tracking performance are not yet known. Therefore, we present the largest publicly available and annotated dataset for MLCI, containing more than 1.4 million cell instances, 29k cell tracks, and 14k cell divisions. With this dataset at hand, we generalize existing tracking metrics to incorporate relevant imaging and experiment parameters into experiment-aware metrics. These metrics reveal that current cell tracking methods crucially depend on the choice of the experiment parameters, where their performance deteriorates at high imaging intervals and large cell colonies. Thus, our new benchmark quantifies the influence of experiment parameters on the tracking quality, and gives the opportunity to develop new data-driven methods that generalize across imaging and experiment parameters. The benchmark dataset is publicly available at https://zenodo.org/doi/10.5281/zenodo.7260136.

Guillaume Franchi, Lionel Truquet

We introduce a general class of autoregressive models for studying the dynamic of multivariate binary time series with stationary exogenous covariates. Using a high-level set of assumptions, we show that existence of a stationary path for such models is almost automatic and does not require parameter restrictions when the noise term is not compactly supported. We then study in details statistical inference in a dynamic version of a multivariate probit type model, as a particular case of our general construction. To avoid a complex likelihood optimization, we combine pseudo-likelihood and pairwise likelihood methods for which asymptotic results are obtained for a single path analysis and also for panel data, using ergodic theorems for multi-indexed partial sums. The latter scenario is particularly important for analyzing absence-presence of species in Ecology, a field where data are often collected from surveys at various locations. Our results also give a theoretical background for such models which are often used by the practitioners but without a probabilistic framework.

Anqi Dong, Can Chen

Complex ecological networks are often characterized by intricate interactions that extend beyond pairwise relationships. Understanding the stability of higher-order ecological networks is salient for species coexistence, biodiversity, and community persistence. In this article, we present complexity analyses for determining the linear stability of higher-order ecological networks through tensor decompositions. We are interested in the higher-order generalized Lotka-Volterra model, which captures high-order interactions using tensors of varying orders. To efficiently compute Jacobian matrices and thus determine stability in large ecological networks, we exploit various tensor decompositions, including higher-order singular value decomposition, Canonical Polyadic decomposition, and tensor train decomposition, accompanied by in-depth computational and memory complexity analyses. We demonstrate the effectiveness of our framework with numerical examples.

Xiaozhou Qi, Yong Zhang, Yilin Zhang et al.

Abstract Background Pathogen infections seriously affect host health, and the use of antibiotics increases the risk of the emergence of drug-resistant bacteria and also increases environmental and health safety risks. Probiotics have received much attention for their excellent ability to prevent pathogen infections. Particularly, explaining mechanism of action of probiotics against pathogen infections is important for more efficient and rational use of probiotics and the maintenance of host health. Results Here, we describe the impacts of probiotic on host resistance to pathogen infections. Our findings revealed that (I) the protective effect of oral supplementation with B. velezensis against Aeromonas hydrophila infection was dependent on gut microbiota, specially the anaerobic indigenous gut microbe Cetobacterium; (II) Cetobacterium was a sensor of health, especially for fish infected with pathogenic bacteria; (III) the genome resolved the ability of Cetobacterium somerae CS2105-BJ to synthesize vitamin B12 de novo, while in vivo and in vitro metabolism assays also showed the ability of Cetobacterium somerae CS2105-BJ to produce vitamin B12; (IV) the addition of vitamin B12 significantly altered the gut redox status and the gut microbiome structure and function, and then improved the stability of the gut microbial ecological network, and enhanced the gut barrier tight junctions to prevent the pathogen infection. Conclusion Collectively, this study found that the effect of probiotics in enhancing host resistance to pathogen infections depended on function of B12 produced by an anaerobic indigenous gut microbe, Cetobacterium. Furthermore, as a gut microbial regulator, B12 exhibited the ability to strengthen the interactions within gut microbiota and gut barrier tight junctions, thereby improving host resistance against pathogen infection. Video Abstract