Hasil untuk "Microbial ecology"

Anjali Purathekandy, Deepak N. Subramani

We introduce an online learning algorithm for computing adaptive resource allocation policies against strategic ecological adversaries with unknown behavioral models and partial observability. Our setting addresses a fundamental limitation of security games: when adversary behavior cannot be modeled a priori, classical equilibrium-based approaches fail. We formulate the problem as regret minimization in a combinatorial action space with semi-bandit feedback, where payoffs are non-stationary and interdependent across targets. Our algorithm, named HERDS (Human-Elephant conflict mitigation through Resource Deployment for Strategic guarding), extends Follow-the-Perturbed-Leader (FPL) with three innovations: (1) simultaneous exploration-exploitation through dynamic budget partitioning driven by observed losses, (2) adaptive payoff estimation under confounded observations where attack entry points are unidentifiable, and (3) model-agnostic learning that provides regret guarantees without behavioral assumptions. We demonstrate our framework on Human-Elephant Conflict mitigation, a domain where intelligent ecological adversaries exhibit strategic behavior (optimal foraging, spatial memory, adaptive evasion) yet lack tractable behavioral models. Experiments using an Agent-Based Model calibrated with elephant movement data demonstrate 15--45% regret reduction versus Follow-the-Perturbed-Leader with Uniform-Exploration (FPL-UE), 40--50% crop damage reduction against adaptive adversaries, and convergence in 40--50 rounds versus 60--80 for baselines.

Jiaxue Peng, Xinyue Liu, Jieni Wang et al.

Abstract Background Quorum sensing is a fundamental chemical communication mechanism that enables microorganisms to coordinate behavior and adapt to environmental conditions. However, its contribution in deep-sea cold seep ecosystems, where diverse microbial communities and frequent communication occur, remains poorly understood. In this study, we aimed to elucidate the occurrence and potential ecological roles of quorum sensing in cold seeps. Results We analyzed 170 metagenomes and 33 metatranscriptomes from 17 global cold seep sites, identifying 299,355 quorum sensing genes from the cold seep non-redundant gene catalog. These genes represent 34 types across six quorum sensing systems, with distribution patterns influenced by sediment depth and seep type. A total of 32,500 quorum sensing genes were identified in 3576 metagenome-assembled genomes from 12 archaeal and 108 bacterial phyla, revealing a complex network of intraspecies and interspecies communication. Microbial groups involved in key metabolic processes, such as sulfate-reducing bacteria, anaerobic methanotrophic archaea, diazotrophs, and organohalide reducers, were extensively regulated by quorum sensing, influencing biogeochemical cycles in cold seeps. Phylogenetic analysis and protein domain identification highlighted the involvement of key quorum sensing-related proteins (e.g., PDE, RpfC/G, CahR, and LuxR) in modulating microbial behaviors, such as motility and chemotaxis. Heterologous expression further confirmed the activity of representative LuxI-R pairs, and metabolomic profiling suggested the presence of putative quorum sensing inhibitors in cold seep sediments. Conclusions Overall, these findings highlight the complexity and significance of quorum sensing in microbial interactions, ecological adaptation, and biogeochemical cycling within cold seep ecosystems, advancing our understanding of microbial communication in the deep biosphere. Video Abstract

Zunwen Zheng, Deqian Xie, Yongzheng Han et al.

Given that the sterility of urine and the urinary tract has been questioned by research, urinary microbiome dysbiosis has been recognized as one of the potential cancer-promoting factors. The composition of the urinary microbial community in healthy individuals has a relatively high similarity at the phylum level, with factors like age and gender influencing the expression and distribution. In contrast, the urinary microbiome of patients with urologic cancers shows significant variability and diversity depending on the type of cancer. Most of the early studies focused on the distribution, aggregation, and expression of microbiota in urologic cancers, warranting advanced studies on the causal relationship between microbes and urologic cancers. Bladder and prostate cancer tumorigenesis and progression can be influenced by microbes through chronic inflammatory or immunomodulatory pathways making them cancer models strongly associated with the urinary microbiome. Here, we summarize the expression characteristics of the microbiomes associated with these cancers and analyze the pathophysiological mechanisms and signaling pathways of the microbiome in the tumor promotion or suppression. By examining the role played by the urinary microbiome in the pathogenesis of urologic cancers, we assess the potential of specific microbial groups as biomarkers for diagnosis and surveillance. Additionally, involving the microbiome or using adjunctive participation in tumor therapy is becoming an emerging cancer treatment option. Improving urinary microbial homeostasis in urinary cancers by direct treatment with microbial products, microbial co-immunotherapy, probiotic-assisted therapy, and fecal microbial transplantation may broaden the scope of therapy and enhance the efficacy of conventional medicines.

Alexis Bailey, Alexis Bailey, Kerstin K. Leuther et al.

The human microbiome plays a critical role in shaping physiological processes, immune system function, metabolism, and disease development. Recent research has highlighted the microbiome’s profound cancer impact, particularly on lung cancer. This review explores how microbial communities in lung and gut influence tumor progression, immune responses, and treatment outcomes as well as describing the interactions between the microbiome and the host immune system in modulating the efficacy of cancer therapies. Emerging evidence from preclinical and clinical studies investigating the role of the lung and gut microbiome in lung cancer focus on alterations in the microbiota that influence the tumor microenvironment, modulate immune responses, and potentially enhance/hinder treatment effectiveness such as chemotherapy, targeted therapies, and immunotherapy. Microbial diversity plays a significant role in immune regulation, and specific microbial species may activate/suppress immune cells such as T-cells, dendritic cells, and macrophages. Furthermore, this review examines the therapeutic implications of microbiome modulation, including the use of probiotics, antibiotics, and fecal microbiota transplantation in enhancing cancer therapies. Alterations in the lung and gut microbiome and their interaction in the recently described gut-lung axis with its bidirectional communication significantly influence the tumor microenvironment and systemic immune responses. These findings suggest that microbial diversity can regulate immune functions, with specific species capable of activating or suppressing immune cell activity. Furthermore, microbiome-targeted interventions show potential in improving the effectiveness of treatments including chemotherapy, targeted therapies, and immunotherapy, underscoring the importance of the microbiome as a key factor in lung cancer pathogenesis and treatment.

Ahmed M. Aboseif, Nasser S. Flefil, Mostafa K.S. Taha et al.

The field of high-effective functional foods has emerged from advancements in biological pharmaceutical research, bridging pharmacology and food science. Microorganisms have been used in food production for ages. In this study, two lactobacilli were used for Azolla fermentation to be used as an economic aquafeed ingredient to identify the most suitable condition in tilapia rearing systems. The study explored the impact of using fermented Azolla and Chlorella vulgaris as a fish feed component in aquaculture systems, emphasizing their nutritional and environmental benefits. The fermentation process, involving Lactobacillus plantarum KU985433 and L. rhamnosus KU985437, enhances Azolla’s protein, phenolic, and antioxidant content while reducing carbohydrates and lipids. Comparative trials in biofloc and green water systems showed that fish fed with fermented Azolla exhibited improved growth, feed utilization, and immune response, demonstrating the potential of fermented plant-based feed as a sustainable alternative to conventional soybean meal. In silico analyses using PCA, heat maps, and network analysis identified that the optimal feed conditions were achieved using 50 % soy bean substitution with Azolla fermented with L. plantarum in both systems, highlighting the efficacy of incorporating fermented Azolla in aquaculture.

Marco Menale, Carmelo Filippo Munafò, Francesco Oliveri

Kinetic theory frameworks are widely used for modeling stochastic interacting systems, where the evolution primarily depends on binary interactions. Recently, in this framework the action of the external force field has been introduction in order to gain a more realistic picture of some phenomena. In this paper, we introduce nonconservative kinetic equations where a particular shape external force field acts on the overall system. Then, this framework is used in an ecological context for modeling the evolution of a system composed of two species interacting with a prey-predator mechanism. The linear stability analysis concerned with the coexistence equilibrium point is provided, and a case where a Hopf bifurcations occurs is discussed. Finally, some relevant scenarios are numerically simulated.

Mark Jones, Jannik Schestag

For a phylogenetic tree, the phylogenetic diversity of a set A of taxa is the total weight of edges on paths to A. Finding small sets of maximal diversity is crucial for conservation planning, as it indicates where limited resources can be invested most efficiently. In recent years, efficient algorithms have been developed to find sets of taxa that maximize phylogenetic diversity either in a phylogenetic network or in a phylogenetic tree subject to ecological constraints, such as a food web. However, these aspects have mostly been studied independently. Since both factors are biologically important, it seems natural to consider them together. In this paper, we introduce decision problems where, given a phylogenetic network, a food web, and integers k, and D, the task is to find a set of k taxa with phylogenetic diversity of at least D under the maximize all paths measure, while also satisfying viability conditions within the food web. Here, we consider different definitions of viability, which all demand that a "sufficient" number of prey species survive to support surviving predators. We investigate the parameterized complexity of these problems and present several fixed-parameter tractable (FPT) algorithms. Specifically, we provide a complete complexity dichotomy characterizing which combinations of parameters - out of the size constraint k, the acceptable diversity loss D, the scanwidth of the food web, the maximum in-degree in the network, and the network height h - lead to W[1]-hardness and which admit FPT algorithms. Our primary methodological contribution is a novel algorithmic framework for solving phylogenetic diversity problems in networks where dependencies (such as those from a food web) impose an order, using a color coding approach.

Samuel Munalula Munjita, Benjamin Mubemba, John Tembo et al.

Ticks are widespread arthropods that transmit microorganisms of veterinary and medical significance to vertebrates, including humans. Rhipicephalus simus, an ixodid tick frequently infesting and feeding on humans, may play a crucial role in transmitting infectious agents across species. Despite the known association of many Rhipicephalus ticks with phleboviruses, information on R. simus is lacking. During a study in a riverine area in Lusaka Zambia, ten R. simus ticks were incidentally collected from the grass and bushes and subjected to metagenomic next generation sequencing (mNGS) in 2 pools of 5. Analysis detected a diverse microbial profile, including bacteria 82% (32/39), fungi 15.4% (6/39), and viruses 2.6% (1/39). Notably, viral sequence LSK-ZM-102022 exhibited similarity to tick phleboviruses, sharing 74.92% nucleotide identity in the RdRp gene and 72% in the NP gene with tick-borne phlebovirus (TBPV) from Greece and Romania, respectively. Its RNA-dependent RNA polymerase (RdRp) encoding region carried conserved RdRp and endonuclease domains characteristic of phenuiviridae viruses. Phylogenetic analysis positioned LSK-ZM-102022 in a distinct but lone lineage within tick phleboviruses basal to known species like brown dog tick phlebovirus and phlebovirus Antigone. Pair-wise genetic distance analysis revealed similar findings. This study emphasizes the urgency of further research on the ecology, transmission dynamics, and pathogenic potential of LSK-ZM-102022 and related TBPVs, crucial for local and global preparedness against emerging tick-borne diseases.

Jiayin Feng, Linlin Wang, Changchun Zhai et al.

Abstract Global change has the potential to alter soil carbon (C) inputs from above- and below-ground sources, with subsequent influences on soil microbial communities and ecological functions. Using data from a 13-year field experiment in a semi-arid grassland, we investigated the effects of litter manipulations and plant removal on soil microbiomes and ecosystem multifunctionality (EMF). Litter addition did not affect soil microbial α-diversity whereas litter removal reduced bacterial and fungal α-diversity due to decreased C substrate supply and soil moisture. By contrast, plant removal led to larger declines in bacterial and fungal α-diversity, lower microbial network stability and complexity. EMF was enhanced by litter addition but largely reduced by plant removal, primarily attributed to the loss of fungal diversity. Our findings underscore the importance of C inputs in shaping soil microbiomes and highlight the dominant role of plant root-derived C inputs in maintaining ecological functions under global change scenarios.

T. McGenity, Benjamin D. Folwell, B. McKew et al.

The marine environment is highly susceptible to pollution by petroleum, and so it is important to understand how microorganisms degrade hydrocarbons, and thereby mitigate ecosystem damage. Our understanding about the ecology, physiology, biochemistry and genetics of oil-degrading bacteria and fungi has increased greatly in recent decades; however, individual populations of microbes do not function alone in nature. The diverse array of hydrocarbons present in crude oil requires resource partitioning by microbial populations, and microbial modification of oil components and the surrounding environment will lead to temporal succession. But even when just one type of hydrocarbon is present, a network of direct and indirect interactions within and between species is observed. In this review we consider competition for resources, but focus on some of the key cooperative interactions: consumption of metabolites, biosurfactant production, provision of oxygen and fixed nitrogen. The emphasis is largely on aerobic processes, and especially interactions between bacteria, fungi and microalgae. The self-construction of a functioning community is central to microbial success, and learning how such “microbial modules” interact will be pivotal to enhancing biotechnological processes, including the bioremediation of hydrocarbons.

D. Peterson, D. Frank, N. Pace et al.

James L. Alexander, Joram M. Posma, Alasdair Scott et al.

Abstract Background and aims The gut microbiota is implicated in the pathogenesis of colorectal cancer (CRC). We aimed to map the CRC mucosal microbiota and metabolome and define the influence of the tumoral microbiota on oncological outcomes. Methods A multicentre, prospective observational study was conducted of CRC patients undergoing primary surgical resection in the UK (n = 74) and Czech Republic (n = 61). Analysis was performed using metataxonomics, ultra-performance liquid chromatography-mass spectrometry (UPLC-MS), targeted bacterial qPCR and tumour exome sequencing. Hierarchical clustering accounting for clinical and oncological covariates was performed to identify clusters of bacteria and metabolites linked to CRC. Cox proportional hazards regression was used to ascertain clusters associated with disease-free survival over median follow-up of 50 months. Results Thirteen mucosal microbiota clusters were identified, of which five were significantly different between tumour and paired normal mucosa. Cluster 7, containing the pathobionts Fusobacterium nucleatum and Granulicatella adiacens, was strongly associated with CRC (P FDR = 0.0002). Additionally, tumoral dominance of cluster 7 independently predicted favourable disease-free survival (adjusted p = 0.031). Cluster 1, containing Faecalibacterium prausnitzii and Ruminococcus gnavus, was negatively associated with cancer (P FDR = 0.0009), and abundance was independently predictive of worse disease-free survival (adjusted p = 0.0009). UPLC-MS analysis revealed two major metabolic (Met) clusters. Met 1, composed of medium chain (MCFA), long-chain (LCFA) and very long-chain (VLCFA) fatty acid species, ceramides and lysophospholipids, was negatively associated with CRC (P FDR = 2.61 × 10−11); Met 2, composed of phosphatidylcholine species, nucleosides and amino acids, was strongly associated with CRC (P FDR = 1.30 × 10−12), but metabolite clusters were not associated with disease-free survival (p = 0.358). An association was identified between Met 1 and DNA mismatch-repair deficiency (p = 0.005). FBXW7 mutations were only found in cancers predominant in microbiota cluster 7. Conclusions Networks of pathobionts in the tumour mucosal niche are associated with tumour mutation and metabolic subtypes and predict favourable outcome following CRC resection. Video Abstract

Shuang Liu, Isaac V. Greenhut, E. Patrick Heist et al.

ABSTRACT The popularity and production of whiskey have grown dramatically in recent years. During whiskey fermentation, lactic acid bacteria (LAB) are a major concern since they can outcompete yeast and spoil the fermentation. However, some bacteria present in the fermentation could potentially counter this effect and promote fermentation efficiency. To better understand the possible roles bacteria play in yeast-based whiskey fermentations, we examined bacterial community dynamics across fermentation stages and investigated how variation in the mash recipe affects bacterial community composition and fermentation efficiency. To this end, we collected 193 samples from three distilleries at the beginning (Cook/set), middle (Fermentation), and end (Drop) of whiskey fermentation, with six mash recipes sampled from one distillery. We used high-performance liquid chromatography (HPLC) to quantify the contents of sugars, organic acids, and ethanol, which revealed distinct differences between distilleries and mash recipes. High-throughput Illumina Miseq sequencing of the 16S rRNA gene V4 region revealed that bacterial communities shifted toward Firmicutes during the fermentative conversion of sugar to ethanol, especially Lactobacillales. Mash recipes also influenced sugar composition, fermentation efficiency, and microbial dynamics. Recipe-specific operational taxonomic unit (OTU) biomarkers in Drop samples included Leuconostoc for corn, Lactococcus for wheat, and Lactobacillaceae_unclassified for rye, while Escherichia/Shigella was associated with sorghum, suggesting potential suppression of LAB. IMPORTANCE Production of ethanol from sugars and yeast is an ancient, ostensibly simple process. The source of sugars varies depending on the desired product and can include fruits, vegetables, molasses, honey, or grains, among other things. The source of yeast can be natural in the case of spontaneous ferments, but dry yeast addition is typical for large-scale fermentations. While the polymicrobial nature of some alcoholic fermentations is appreciated (e.g., for wine), most grain-based ethanol producers view microbes, apart from the added yeast, as “contaminants” meant to be controlled in order to maximize efficiency of ethanol production per unit of sugar. Nonetheless, despite rigorous cleaning-in-place measures and cooking the mash, bacteria are routinely cultured from these fermentations. We now know that bacteria can contribute to fermentation efficiency on an industrial scale, yet nothing is known about the makeup and stability of microbial communities in distilled spirit fermentations. The work here establishes the roles of mash recipes and distillery practices in microbial community assembly and dynamics over the course of fermentation. This represents an important first step in appreciating the myriad roles of bacteria in the production of distilled spirits.

Jeffrey W. Doser, Andrew O. Finley, Marc Kéry et al.

Numerous modeling techniques exist to estimate abundance of plant and wildlife species. These methods seek to estimate abundance while accounting for multiple complexities found in ecological data, such as observational biases, spatial autocorrelation, and species correlations. There is, however, a lack of user-friendly and computationally efficient software to implement the various models, particularly for large data sets. We developed the spAbundance R package for fitting spatially-explicit Bayesian single-species and multi-species hierarchical distance sampling models, N-mixture models, and generalized linear mixed models. The models within the package can account for spatial autocorrelation using Nearest Neighbor Gaussian Processes and accommodate species correlations in multi-species models using a latent factor approach, which enables model fitting for data sets with large numbers of sites and/or species. We provide three vignettes and three case studies that highlight spAbundance functionality. We used spatially-explicit multi-species distance sampling models to estimate density of 16 bird species in Florida, USA, an N-mixture model to estimate Black-throated Blue Warbler (Setophaga caerulescens) abundance in New Hampshire, USA, and a spatial linear mixed model to estimate forest aboveground biomass across the continental USA. spAbundance provides a user-friendly, formula-based interface to fit a variety of univariate and multivariate spatially-explicit abundance models. The package serves as a useful tool for ecologists and conservation practitioners to generate improved inference and predictions on the spatial drivers of populations and communities.

Stuart Semple, Ramon Ferrer-i-Cancho, Morgan L. Gustison

Linguistic laws, the common statistical patterns of human language, have been investigated by quantitative linguists for nearly a century. Recently, biologists from a range of disciplines have started to explore the prevalence of these laws beyond language, finding patterns consistent with linguistic laws across multiple levels of biological organisation, from molecular (genomes, genes, and proteins) to organismal (animal behaviour) to ecological (populations and ecosystems). We propose a new conceptual framework for the study of linguistic laws in biology, comprising and integrating distinct levels of analysis, from description to prediction to theory building. Adopting this framework will provide critical new insights into the fundamental rules of organisation underpinning natural systems, unifying linguistic laws and core theory in biology.

Hao Huang, Katherine R. Davis, H. Vincent Poor

The long-term resilient property of ecosystems has been quantified as ecological robustness (RECO) in terms of the energy transfer over food webs. The RECO of resilient ecosystems favors a balance of food webs' network efficiency and redundancy. By integrating RECO with power system constraints, the authors are able to optimize power systems' inherent resilience as ecosystems through network design and system operation. A previous model used on real power flows and aggregated redundant components for a rigorous mapping between ecosystems and power systems. However, the reactive power flows also determine power systems resilience; and the power components' redundancy is part of the global network redundancy. These characteristics should be considered for RECO-oriented evaluation and optimization for power systems. Thus, this paper extends the model for quantifying RECO in power systems using real, reactive, and apparent power flows with the consideration of redundant placement of generators. Recalling the performance of RECO-oriented optimal power flows under N-x contingencies, the analyses suggest reactive power flows and redundant components should be included for RECO to capture power systems' inherent resilience.

Matthias Orlikowski, Paul Röttger, Philipp Cimiano et al.

Many NLP tasks exhibit human label variation, where different annotators give different labels to the same texts. This variation is known to depend, at least in part, on the sociodemographics of annotators. Recent research aims to model individual annotator behaviour rather than predicting aggregated labels, and we would expect that sociodemographic information is useful for these models. On the other hand, the ecological fallacy states that aggregate group behaviour, such as the behaviour of the average female annotator, does not necessarily explain individual behaviour. To account for sociodemographics in models of individual annotator behaviour, we introduce group-specific layers to multi-annotator models. In a series of experiments for toxic content detection, we find that explicitly accounting for sociodemographic attributes in this way does not significantly improve model performance. This result shows that individual annotation behaviour depends on much more than just sociodemographics.

Sarah Moraïs, I. Mizrahi

ABSTRACT The herbivore rumen ecosystem constitutes an extremely efficient degradation machinery for the intricate chemical structure of fiber biomass, thus, enabling the hosting animal to digest its feed. The challenging task of deconstructing and metabolizing fiber is performed by microorganisms inhabiting the rumen. Since most of the ingested feed is comprised of plant fiber, these fiber-degrading microorganisms are of cardinal importance to the ecology of the rumen microbial community and to the hosting animal, and have a great impact on our environment and food sustainability. We summarize herein the enzymological fundamentals of fiber degradation, how the genes encoding these enzymes are spread across fiber-degrading microbes, and these microbes' interactions with other members of the rumen microbial community and potential effect on community structure. An understanding of these concepts has applied value for agriculture and our environment, and will also contribute to a better understanding of microbial ecology and evolution in anaerobic ecosystems.

K. Clements, Esther R. Angert, W. Montgomery et al.

Lauren Russell, Lauren Russell, Paul Whyte et al.

This study investigated the survival of Salmonella Senftenberg, Escherichia coli O157:H7, Listeria monocytogenes, Enterococcus faecalis and Clostridium sporogenes in sandy and clay loam textured soils when applied in bovine slurry or unpasteurised digestate, using laboratory based inoculation studies. The run-off rate for a test bacterium, Listeria innocua, when applied to grass in slurry and digestate, was also examined using field studies. Bovine slurry and digestate were inoculated with the target bacteria to a final concentration of 106 log10 cfu/g or spores/g, thoroughly mixed into soil samples and incubated at 4°C or 14°C. Samples were removed periodically and the surviving cells enumerated using AOAC or equivalent methods. The loss of viability/culturability phase followed first order kinetics and T90 values ranged from 11.9 to 166.7 d at 4°C and from 6.0 to 156 d at 14°C. With the exception of E. coli O157:H7 and E. faecalis in sandy loam textured soil at 14°C (T90 values were significantly (P < 0.05) higher in slurry) the type of soil texture or application material (slurry or digestate) did not affect survival rates. In the field study, 12 grass covered micro-plots were prepared. L. innocua was applied in digestate and bovine slurry and rainfall was simulated at a target rate of ~11 mm per plot per h−1. Rainfall simulation (30 min) took place after 24, 48 h, 14 d and 30 d. Run-off samples were tested for the L. innocua strain using Brilliance Listeria agar supplemented with streptomycin sulphate (1,000 μg/ml) at 37°C for 48 h, as were soil samples after 30, 58, 86 and 112 d. Significantly (P < 0.05) lower counts were obtained in the run-off from digestate after 1, 2 and 30 d as compared to slurry. It was concluded that the type of organic fertiliser does not affect the bacterial survival rates in sandy and clay soils, with the exception of E. coli O157:H7 and E. faecalis in sandy loam textured soil at 14°C. Furthermore, bacteria may be retained better in the soil-digestate matrices during rainfall although additional research is required to further validate and provide the scientific basis for this observation.