Hasil untuk "Microbial ecology"

A. Gomes, F. Malcata

Teddy Lazebnik

Socks are produced and replaced at a massive scale, yet their paired use makes them unusually vulnerable to waste, as the loss of a single sock can strand usable wear-capacity and trigger premature replacement. In this study, we quantify the economic and ecological value of pairing non-matching \say{orphan} socks, and the social cost that discourages this behaviour. We formalize sock ownership as a sequential decision problem under uncertainty in which socks wear out and disappear stochastically during laundering, while public exposure induces a person-specific mismatch penalty. We conducted an in-person study to estimate mismatch sensitivity and diversity preference, linking behavioural heterogeneity to optimal mixing strategies. Using these results and a computer simulation-based evaluation of interpretable pairing policies, we show that strict matching can appear resource-frugal largely because it generates many sockless days, whereas controlled tolerance for mismatch sustains service and reduces stranded capacity across loss regimes. This study establishes the feasibility of matching non-matching socks while outlining its limitations and challenges.

J. Sanford, R. Gallo

Shuaiying Wang, Yuguang Yang, Aming Li

Understanding the stability of complex communities is a central focus in ecology, many important theoretical advancements have been made to identify drivers of ecological stability. However, previous results often rely on the continuous-time dynamics, assuming that species have overlapping generations. In contrast, numerous real-world communities consist of species with non-overlapping generations, whose quantitative behavior can only be precisely represented by discrete-time dynamics rather than continuous ones. Here, we develop a theoretical framework and propose a metric to quantify the stability of complex communities characterized by non-overlapping generations and diverse interaction types. In stark contrast to existing results for overlapping generations, we find that increasing self-regulation strength first stabilizes and then destabilizes complex communities. This pattern is further confirmed in both exploitative (E. aerogenes, P. aurantiaca, P. chlororaphis, P. citronellolis) and competitive (P. putida, P. veroni, S. marcescens) soil microbial communities. Moreover, we show that communities with diverse interaction types become the most stable, which is corroborated by empirical mouse microbial networks. Furthermore, we reveal that the prevalence of weak interactions can stabilize communities, which is consistent with findings from existing microbial experiments. Our analyses of complex communities with non-overlapping generations provide a more comprehensive understanding of ecological stability and informs practical strategies for ecological restoration and control.

Alexandru Hening, Siddharth Sabharwal

We study how environmental stochasticity influences the long-term population size in certain one- and two-species models. The difficulty is that even when one can prove that there is persistence, it is usually impossible to say anything about the invariant probability measure which describes the persistent species. We are able to circumvent this problem for some important ecological models by noticing that the per-capita growth rates at stationarity are zero, something which can sometimes yield information about the invariant probability measure. For more complicated models we use a recent result by Cuello to explore how small noise influences the population size. We are able to show that environmental fluctuations can decrease, increase, or leave unchanged the expected population size. The results change according to the dynamical model and, within a fixed model, also according to which parameters (growth rate, carrying capacity, etc) are affected by environmental fluctuations. Moreover, we show that not only do things change if we introduce noise differently in a model, but it also matters what one takes as the deterministic `no-noise' baseline for comparison.

Hao-Neng Luo, Zhi-Xi Wu, Jian-Yue Guan

Bacteriophage-bacteria interactions are central to microbial ecology, influencing evolution, biogeochemical cycles, and pathogen behavior. Most theoretical models assume static environments and passive bacterial hosts, neglecting the joint effects of bacterial traits and environmental fluctuations on coexistence dynamics. This limitation hinders the prediction of microbial persistence in dynamic ecosystems such as soils and oceans.Using a minimal ordinary differential equation framework, we show that the bacterial growth rate and the phage adsorption rate collectively determine three possible ecological outcomes: phage extinction, stable coexistence, or oscillation-induced extinction. Specifically, we demonstrate that environmental fluctuations can suppress destructive oscillations through resonance, promoting coexistence where static models otherwise predict collapse. Counterintuitively, we find that lower bacterial growth rates are helpful in enhancing survival under high infection pressure, elucidating the observed post-infection growth reduction.Our studies reframe bacterial hosts as active builders of ecological dynamics and environmental variation as a potential stabilizing force. Our findings thus bridge a key theory-experiment gap and provide a foundational framework for predicting microbial responses to environmental stress, which might have potential implications for phage therapy, microbiome management, and climate-impacted community resilience.

Sylvain Billiard, Virgile Brodu, Nicolas Champagnat et al.

We design a stochastic individual-based model structured in energy, for single species consuming an external resource, where populations are characterized by a typical energy at birth in $\mathbb{R}^{*}_{+}$. The resource is maintained at a fixed amount, so we benefit from a branching property at the population level. Thus, we focus on individual trajectories, constructed as Piecewise Deterministic Markov Processes, with random jumps modelling births and deaths in the population; and a continuous and deterministic evolution of energy between jumps. We are mainly interested in the case where metabolic (i.e. energy loss for maintenance), growth, birth and death rates depend on the individual energy over time, and follow allometric scalings (i.e. power laws). Our goal is to determine in a bottom-up approach what are the possible allometric coefficients (i.e. exponents of these power laws) under elementary -- and ecologically relevant -- constraints, for our model to be valid for the whole spectrum of possible body sizes. We show in particular that assuming an allometric coefficient $α$ related to metabolism strongly constrains the range of possible values for the allometric coefficients $β$, $δ$, $γ$, respectively related to birth, death and growth rates. We further identify and discuss the precise and minimal ecological mechanisms that are involved in these strong constraints on allometric scalings.

Xinkang Zhang, Guanchao Mao, Zhipeng Pei et al.

Sulfur mustard (SM) causes multi-organ toxicity, yet its impact on intestinal tissue and the associated gut microbiota remains poorly characterized. This study demonstrates that in a mouse model of SM exposure, gut microbial ecological collapse occurs, characterized by depletion of protective taxa (Bifidobacteriales, <i>Gordonibacter</i>, and Lachnospiraceae UCG010) while promoting a 302-fold expansion of inflammation-associated <i>Escherichia/Shigella</i>. Mendelian randomization analysis established causal relationships between these SM-perturbed taxa and human inflammatory bowel disease. Fecal microbiota transplantation effectively restored microbial diversity (Simpson index: 0.85 to 0.95), suppressed <i>Escherichia/Shigella</i> by 97.4%, and ameliorated intestinal pathology. Longitudinal tracking revealed persistent vulnerability of Bifidobacteriales compared to other depleted taxa. Our findings establish the gut microbiota as a key mediator in SM intestinal toxicity and provide new insights for microbiota-targeted interventions against chemical injuries.

Huiduo Guo, Yalei Wang, Yu Guo et al.

Metabolic syndrome is a global health crisis. However, there are no effective therapeutic strategies for metabolic syndrome. Therefore, this study was conducted to find out a novel silkworm-based metabolic syndrome model that bridges microbial ecology and metabolic dysregulation by integrating hemolymph lipids and midgut microbiota. Our results showed that the levels of HDL-C in the hemolymph of the lean silkworm strain were significantly higher than that in the obese silkworm strain. Furthermore, correlation analysis revealed that <i>Lactococcus</i> and <i>Oceanobacillus</i> were positively related to HDL-C levels, while <i>SM1A02</i> and <i>Pseudonocardia</i> were negatively associated with HDL-C levels. These relationships between the identified bacteria in the midgut and HDL-C, known as the “good” lipid, in the hemolymph could help guide the development of new treatments for obesity and metabolic problems like high cholesterol in humans. Overall, our results not only established a framework for understanding microbiota-driven lipid dysregulation in silkworms but also offered potential probiotic targets and a bacterial biomarker for obesity and metabolic dysfunction intervention in humans.

Yi-Ze Wang, Hai-Ming Zhao, Xian-Pei Huang et al.

Abstract Background Accumulation of antibiotics in crops threatens human health. However, the mechanisms and effects of microorganisms on the uptake and accumulation of antibiotics in crops remain poorly understood. This study aimed to investigate the impact and underlying mechanisms of seed-borne microbiota in root on ciprofloxacin (CIP) accumulation in two choy sum varieties through amplicon sequencing, multiple statistical analyses, and subsequent validation of key bacteria via isolation and co-culturing with plants. Results Bacillaceae (mainly Bacillus) was enriched specifically in the roots of CIP high-antibiotic-accumulating variety (HAV) via seed-based vertical transmission activated by the root exudate-derived maleic acid. The relative abundance of Bacillaceae was 9.2 to 27.7 times higher in roots of HAV relative to the low-antibiotic-accumulating variety (LAV). The enrichment of Bacillaceae facilitated a cooperative and beneficial bacterial community formed by the deterministic process. The community in HAV could not only stimulate antioxidase activities and decrease membrane lipid peroxidation via secreting indoleacetic acid and siderophore but also promote its biomass, especially the root length and biomass of HAV, thus greatly improving its tolerance to and absorption of CIP. The variety-specific plant-microbial interactions caused 1.6- to 3.2-fold higher CIP accumulation in shoots of HAV relative to LAV shoots. Conclusions The findings highlight the crucial roles of the seed-borne microbiota in regulating the uptake and accumulation of antibiotics in crops, giving new understanding on the accumulation of organic pollutants in plants, with an emphasis on plant-microbial interactions Video Abstract

Maojin Tian, Hamed Soleimani Samarkhazan, Seyed Shahabedin Alemohammad et al.

Abstract AML often relapses due to chemotherapy resistance, increasingly linked to gut microbiome dysbiosis. Microbial drug modification, immune modulation, and metabolite-driven survival/epigenetic changes (e.g., SCFAs, kynurenine) promote resistance. Clinical data associate reduced diversity, loss of Faecalibacterium, and Enterococcus overgrowth with poorer outcomes. Microbiome interventions (FMT, probiotics, diet) show promise; priorities are standardizing methods and defining microbe–metabolite mechanisms to guide trials.

Jennifer R. Brum, M. Sullivan

Xiyang Dong, C. Greening, J. Rattray et al.

The lack of microbial genomes and isolates from the deep seabed means that very little is known about the ecology of this vast habitat. Here, we investigate energy and carbon acquisition strategies of microbial communities from three deep seabed petroleum seeps (3 km water depth) in the Eastern Gulf of Mexico. Shotgun metagenomic analysis reveals that each sediment harbors diverse communities of chemoheterotrophs and chemolithotrophs. We recovered 82 metagenome-assembled genomes affiliated with 21 different archaeal and bacterial phyla. Multiple genomes encode enzymes for anaerobic oxidation of aliphatic and aromatic compounds, including those of candidate phyla Aerophobetes, Aminicenantes, TA06 and Bathyarchaeota. Microbial interactions are predicted to be driven by acetate and molecular hydrogen. These findings are supported by sediment geochemistry, metabolomics, and thermodynamic modelling. Overall, we infer that deep-sea sediments experiencing thermogenic hydrocarbon inputs harbor phylogenetically and functionally diverse communities potentially sustained through anaerobic hydrocarbon, acetate and hydrogen metabolism. Little is known about the microbial ecology of the deep seabed. Here, Dong et al. predict metabolic capabilities and microbial interactions in deep seabed petroleum seeps using shotgun metagenomics, sediment geochemistry, metabolomics, and thermodynamic modelling.

Chiao-Jung Han, Chih-Hsin Cheng, Ting-Feng Yeh et al.

Melissah Rowe, Liisa Veerus, P. Trosvik et al.

All multicellular organisms host microbial communities in and on their bodies, and these microbiomes can have major influences on host biology. Most research has focussed on the oral, skin, and gut microbiomes, whereas relatively little is known about the reproductive microbiome. Here, we review empirical evidence to show that reproductive microbiomes can have significant effects on the reproductive function and performance of males and females. We then discuss the likely repercussions of these effects for evolutionary processes related to sexual selection and sexual conflict, as well as mating systems and reproductive isolation. We argue that knowledge of the reproductive microbiome is fundamental to our understanding of the evolutionary ecology of reproductive strategies and sexual dynamics of host organisms.

Ekaterina Smirnova, P. Puri, M. Muthiah et al.

The role of the intestinal microbiome in alcoholic hepatitis is not established. The aims of this study were to (1) characterize the fecal microbial ecology associated with alcoholic hepatitis, (2) relate microbiome changes to disease severity, and (3) infer the functional relevance of shifts in microbial ecology.

N. Fromin, Jérôme Hamelin, S. Tarnawski et al.

Srijan Chattopadhyay, Swapnaneel Bhattacharyya

Similarity index is an important scientific tool frequently used to determine whether different pairs of entities are similar with respect to some prefixed characteristics. Some standard measures of similarity index include Jaccard index, Sørensen-Dice index, and Simpson's index. Recently, a better index ($\hatα$) for the co-occurrence and/or similarity has been developed, and this measure really outperforms and gives theoretically supported reasonable predictions. However, the measure $\hatα$ is not data dependent. In this article we propose a new measure of similarity which depends strongly on the data before introducing randomness in prevalence. Then, we propose a new method of randomization which changes the whole pattern of results. Before randomization our measure is similar to the Jaccard index, while after randomization it is close to $\hatα$. We consider the popular ecological dataset from the Tuscan Archipelago, Italy; and compare the performance of the proposed index to other measures. Since our proposed index is data dependent, it has some interesting properties which we illustrate in this article through numerical studies.

Lucas K. Johnson, Michael J. Mahoney, Madeleine L. Desrochers et al.

Understanding historical forest dynamics, specifically changes in forest biomass and carbon stocks, has become critical for assessing current forest climate benefits and projecting future benefits under various policy, regulatory, and stewardship scenarios. Carbon accounting frameworks based exclusively on national forest inventories are limited to broad-scale estimates, but model-based approaches that combine these inventories with remotely sensed data can yield contiguous fine-resolution maps of forest biomass and carbon stocks across landscapes over time. Here we describe a fundamental step in building a map-based stock-change framework: mapping historical forest biomass at fine temporal and spatial resolution (annual, 30m) across all of New York State (USA) from 1990 to 2019, using freely available data and open-source tools. Using Landsat imagery, US Forest Service Forest Inventory and Analysis (FIA) data, and off-the-shelf LiDAR collections we developed three modeling approaches for mapping historical forest aboveground biomass (AGB): training on FIA plot-level AGB estimates (direct), training on LiDAR-derived AGB maps (indirect), and an ensemble averaging predictions from the direct and indirect models. Model prediction surfaces (maps) were tested against FIA estimates at multiple scales. All three approaches produced viable outputs, yet tradeoffs were evident in terms of model complexity, map accuracy, saturation, and fine-scale pattern representation. The resulting map products can help identify where, when, and how forest carbon stocks are changing as a result of both anthropogenic and natural drivers alike. These products can thus serve as inputs to a wide range of applications including stock-change assessments, monitoring reporting and verification frameworks, and prioritizing parcels for protection or enrollment in improved management programs.

F. Russo, A. Tenore, M. R. Mattei et al.

A multiscale mathematical model describing the genesis and ecology of algal-bacterial photogranules and the metals biosorption on their solid matrix within a sequencing batch reactor (SBR) is presented. The granular biofilm is modelled as a spherical free boundary domain with radial symmetry and a vanishing initial value. The free boundary evolution is governed by an ODE accounting for microbial growth, attachment and detachment phenomena. The model is based on systems of PDEs derived from mass conservation principles. Specifically, two systems of nonlinear hyperbolic PDEs model the growth of attached species and the dynamics of free adsorption sites; and two systems of quasi-linear parabolic PDEs govern the diffusive transport and conversion of nutrients and metals. The model is completed with systems of impulsive ordinary differential equations (IDEs) describing the evolution of dissolved substrates, metals, and planktonic and detached biomasses within the granular-based SBR. All main phenomena involved in the process are considered in the mathematical model. Moreover, the dual effect of metal presence on the formation process of photogranules is accounted: metal stimulates the production of EPS by sessile species and negatively affects the metabolic activities of microbial species. To describe the effects related to metal presence, a stimulation term for EPS production and an inhibition term for metal are included in all microbial kinetics. The model is used to examine the role of the microbial species and EPS in the adsorption process, and the effect of metal concentration and adsorption proprieties of biofilm components on the metal removal. Numerical results show that the model accurately describes the photogranules evolution and ecology and confirm the applicability of algal-bacterial photogranules systems for metal-rich wastewater treatment.