SEARCH · bioRxiv Science

Results for “ecology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 667 records · Page 37Linked to original sources

bioRxiv2018

Using molecular ecological network analysis to explore the effects of chemotherapy on intestinal microbial communities of colorectal cancer patients

Intestinal microbiota is now widely known to be key roles in the nutrition uptake, metabolism, and the regulation of human immune responses. However, we do not know how changes the intestinal microbiota in response to the chemotherapy. In this study, we used network-based analytical approaches to explore the effects of five stages of chemotherapy on the intestinal microbiota of colorectal cancer patients. The results showed that chemotherapy greatly reduced the alpha diversity and changed the specie-specie interaction networks of intestinal microbiota, proved by the network size, network connectivity and modularity. The OTU167 and OTU8 from the genus Fusobacterium and Bacteroides were identified as keystone taxa by molecular ecological networks in the first two stages of chemotherapy, and were significantly correlated with tumor makers (P < 0.05). Five stages of chemotherapy did not make the intestinal micro-ecosystem regain a steady state, because of the lower alpha diversity and more complicated ecological networks compared to the healthy individuals. Furthermore, combing the changes of ecological networks with the tumor markers, the intestinal microbiota was closely linked with clinical chemotherapeutic effects.\n\nImportanceA deeply understanding of the role of intestinal microbiota contributes to help us find path forward for improving the prognosis of colorectal cancer patients. In addition, diet or probiotics interventions will be a possible attempt to improve the clinical chemotherapeutic effects for colorectal cancer patients.

microbiology↗

bioRxiv2018

Distinct Microbes, Metabolites, and Ecologies Define the Microbiome in Deficient and Proficient Mismatch Repair Colorectal Cancers

Background\n\nThe link between colorectal cancer (CRC) and the gut microbiome has been established, but the specific microbial species and their role in carcinogenesis remain controversial. Our understanding would be enhanced by better accounting for tumor subtype, microbial community interactions, metabolism, and ecology.\n\nMethods\n\nWe collected paired colon tumor and normal-adjacent tissue and mucosa samples from 83 individuals who underwent partial or total colectomies for CRC. Mismatch repair (MMR) status was determined in each tumor sample and classified as either deficient MMR (dMMR) or proficient MMR (pMMR) tumor subtypes. Samples underwent 16S rRNA gene sequencing and a subset of samples from 50 individuals were submitted for targeted metabolomic analysis to quantify amino acids and short-chain fatty acids. A PERMANOVA was used to identify the biological variables that explained variance within the microbial communities. dMMR and pMMR microbial communities were then analyzed separately using a generalized linear mixed effects model that accounted for MMR status, sample location, intra-subject sample correlation, and read depth. Genome-scale metabolic models were then used to generate microbial interaction networks for dMMR and pMMR microbial communities. We assessed global network properties as well as the metabolic influence of each microbe within the dMMR and pMMR networks.\n\nResults\n\nWe demonstrate distinct roles for microbes in dMMR and pMMR CRC. Sulfidogenic Fusobacterium nucleatum and hydrogen sulfide production were significantly enriched in dMMR CRC, but not pMMR CRC. We also surveyed the butyrate-producing microbial species, but did not find a significant difference in predicted or actual butyrate production between dMMR and pMMR microbial communities. Finally, we observed that dMMR microbial communities were predicted to be less stable than pMMR microbial communities. Community stability may play an important role in CRC development, progression, or immune activation within the respective MMR subtypes.\n\nConclusions\n\nIntegrating tumor biology and microbial ecology highlighted distinct microbial, metabolic, and ecological properties unique to dMMR and pMMR CRC. This approach could critically improve our ability to define, predict, prevent, and treat colorectal cancers.

cancer biology↗

bioRxiv2018

The ecological cocktail party: Measuring brain activity during an auditory oddball task with background noise

Most experiments using EEG recordings take place in highly isolated and restricted environments, limiting their applicability to real-life scenarios. New technologies for mobile EEG are changing this by allowing EEG recording to take place outside of the laboratory. However, before results from experiments performed outside the laboratory can be fully understood, the effects of ecological stimuli on brain activity during cognitive tasks must be examined. In this experiment, participants performed an auditory oddball task while also listening to concurrent background noises of silence, white noise and outdoor ecological sounds, as well as a condition in which the tones themselves were at a low volume. We found a significantly increased N1 and decreased P2 when participants performed the task with outdoor sounds and white noise in the background, with the largest differences in the outdoor sound condition. This modulation in the N1 and P2 replicates what we have previously found outside while people ride bicycles (Scanlon et al., 2017). No behavioural differences were found in response to the target tones. We interpret these modulations in early ERPs as indicative of sensory filtering of background sounds, and that ecologically valid sounds require more filtering than synthetic sounds. Our results reveal that much of what we understand about the brain will need to be updated as we step outside the lab.

neuroscience↗

bioRxiv2018

Molecular noise shapes bacteria-phage ecologies

Mathematical models have been used successfully at diverse scales of biological organization, ranging from ecology and population dynamics to stochastic reaction events occurring between individual molecules in single cells. Generally, many biological processes unfold across multiple scales, with mutations being the best studied example of how stochasticity at the molecular scale can influence outcomes at the population scale. In many other contexts, however, an analogous link between micro- and macro-scale remains elusive, primarily due to the challenges involved in setting up and analyzing multi-scale models. Here, we employ such a model to investigate how stochasticity propagates from individual biochemical reaction events in the bacterial innate immune system to the ecology of bacteria and bacterial viruses. We show analytically how the dynamics of bacterial populations are shaped by the activities of immunity-conferring enzymes in single cells and how the ecological consequences imply optimal bacterial defense strategies against viruses. Our results suggest that bacterial populations in the presence of viruses can either optimize their initial growth rate or their steady state population size, with the first strategy favoring simple and the second strategy favoring complex bacterial innate immunity.

biophysics↗

bioRxiv2018

Emergence of social inequality in a spatial-ecological public goods game

Spatial ecological public goods, such as forests, grasslands, and fish stocks risk being overexploited by selfish consumers, a phenomenon called \"the tragedy of commons\". The spatial and ecological dimensions introduce new features absent in non spatio-ecological contexts, such as consumer mobility, incomplete information availability, and rapid evolution by social learning. It is unclear how these different processes interact to influence the harvesting and dispersal strategies of consumers. To answer these questions, we develop and analyze an individual-based, spatially-structured evolutionary model with explicit resource dynamics. We find that, 1) When harvesting efficiency is low, consumers evolve a sedentary harvesting strategy, with which resources are harvested sustainably, but harvesting rates remain far below their maximum sustainable value. 2) As harvesting efficiency increases, consumers adopt a mobile consume-and-disperse strategy, which is sustainable, equitable, and allows for maximum sustainable yield. 3) Further increase in harvesting efficiency leads to large-scale overexploitation. 4) If costs of dispersal are significant, increased harvesting efficiency also leads to social inequality between frugal sedentary consumers and overexploitative mobile consumers. Whereas overexploitation can occur without social inequality, social inequality always leads to overexploitation. Thus, we identify four conditions, which are characteristic (and as such positive) features of modern societies resulting from technological progress, but also risk promoting social inequality and unsustainable resource use: high harvesting efficiency, moderately low costs of dispersal, high consumer density, and consumers tendency to rapidly adopt new strategies. We also show that access to global information, which is also a feature of modern societies, may help mitigate these risks.

evolutionary biology↗

bioRxiv2018

The ecology of sexual conflict: behaviorally plastic responses to temperature variation in the social environment can drastically modulate male harm to females.

Sexual conflict is a fundamental driver of male/female adaptations, an engine of biodiversity, and a crucial determinant of population viability. For example, sexual conflict frequently leads to behavioural adaptations that allow males to displace their rivals, but in doing so harm those same females they are competing to access. Sexual conflict via male harm hence not only deviates females from their fitness optimum, but can decrease population viability and facilitate extinction. Despite this prominent role, we are far from understanding what factors modulate the intensity of sexual conflict, and particularly the role of ecology in mediating underlying behavioural adaptations. In this study we show that, in Drosophila melanogaster, variations in environmental temperature of {+/-}4[Formula]C (within the natural range in the wild) decrease male harm impact on female fitness by between 45-73%. Rate-sensitive fitness estimates indicate that such modulation results in an average rescue of population productivity of 7% at colder temperatures and 23% at hotter temperatures. Our results: a) show that the thermal ecology of social interactions can drastically modulate male harm via behaviourally plasticity, b) identify a potentially crucial ecological factor to understand how sexual conflict operates in nature, and c) suggest that behaviourally plastic responses can lessen the negative effect of sexual conflict on population viability in the face of rapid environmental temperature changes.

evolutionary biology↗

bioRxiv2018

Loci, genes, and gene networks associated with life history variation in a model ecological organism, Daphnia pulex (complex)

BackgroundIdentifying the molecular basis of heritable variation provides insight into the underlying mechanisms generating phenotypic variation and the evolutionary history of organismal traits. Life history trait variation is of central importance to ecological and evolutionary dynamics, and contemporary genomic tools permit studies of the basis of this variation in non-genetic model organisms. We used high density genotyping, RNA-Seq gene expression assays, and detailed phenotyping of fourteen ecologically important life history traits in a wild-caught panel of 32 Daphnia pulex clones to explore the molecular basis of trait variation in a model ecological species.\n\nResultsWe found extensive phenotypic and a range of heritable genetic variation (~0 < H2 < 0.44) in the panel, and accordingly identify 75-261 genes--organized in 3-6 coexpression modules--associated with genetic variation in each trait. The trait-related coexpression modules possess well-supported promoter motifs, and in conjunction with marker variation at trans- loci, suggest a relatively small number of important expression regulators. We further identify a candidate genetic network with SNPs in eight known transcriptional regulators, and dozens of differentially expressed genes, associated with life history variation. The gene-trait associations include numerous un-annotated genes, but also support several a priori hypotheses, including an ecdysone-induced protein and several Gene Ontology pathways.\n\nConclusionThe genetic and gene expression architecture of Daphnia life history traits is complex, and our results provide numerous candidate loci, genes, and coexpression modules to be tested as the molecular mechanisms that underlie Daphnia eco-evolutionary dynamics.

genomics↗

bioRxiv2018

Parent-offspring conflict, ecology, and life history diversification of livebearing fishes

Shifts in life history evolution can potentiate sexual selection and speciation. However, we rarely understand the causative links between correlated patterns of diversification or the tipping points that initiate changes with cascading effects. We investigated livebearing fishes with repeated transitions from pre- (lecithotrophy) to post-fertilization maternal provisioning (matrotrophy) to identify the potential ecological drivers of evolutionary transitions in life history. Phylogenetic comparative analyses across 94 species revealed that bi-directional evolution along the lecithotrophy-matrotrophy continuum is correlated with ecology, supporting adaptive hypotheses of life history diversification. Consistent with theory, matrotrophy was associated with high resource availability and low competition. Our results suggest that ecological sources of selection contribute to the diversification of female provisioning strategies in livebearing fishes, which have been associated with macroevolutionary patterns of sexual selection and speciation.

evolutionary biology↗

bioRxiv2019

Ecological specificity of the metagenome in a set of lower termite species supports contribution of the microbiome to adaptation of the host

BackgroundElucidating the interplay between hosts and their microbiomes in ecological adaptation has become a central theme in evolutionary biology. A textbook example of microbiome-mediated adaptation is the adaptation of lower termites to a wood-based diet, as they depend on their gut microbiome to digest wood. Lower termites have further adapted to different life types. Termites of the wood-dwelling life type never leave their nests and feed on a uniform diet. Termites of the foraging life type forage for food outside the nest and have access to other nutrients. Here we sought to investigate whether the microbiome that is involved in food substrate breakdown and nutrient acquisition might contribute to adaptation to these ecological differences. We reasoned that this should leave ecological imprints on the microbiome.\n\nResultsWe investigated the protist and bacterial microbiomes of a total of 29 replicate colonies from five termite species, covering both life types, using metagenomic shotgun sequencing. The microbiome of wood-dwelling species with a uniform wood diet was enriched for genes involved in lignocellulose degradation. Furthermore, metagenomic patterns suggest that the microbiome of wood-dwelling species relied primarily on direct fixation of atmospheric nitrogen, while the microbiome of foraging species entailed the necessary pathways to utilize nitrogen in the form of nitrate for example from soil.\n\nConclusionOur findings are consistent with the notion that the microbiome of wood-dwelling species bears an imprint of its specialization on degrading a uniform wood diet, while the microbiome of the foraging species might reflect its adaption to access growth limiting nutrients from more diverse sources. This supports the idea that specific subsets of functions encoded by the microbiome can contribute to host adaptation.

evolutionary biology↗

bioRxiv2019

Assessment and representation of variability in ecological niche model predictions

Ecological niche models are popular tools used in fields such as ecology, biogeography, conservation biology, and epidemiology. These models are used commonly to produce representations of species potential distributions, which are then used to answer other research questions; for instance, where species richness is highest, where potential impacts of climate change can be anticipated, or where to expect spread of invasive species or disease vectors. Although these representations of potential distributions are variable which contributes to uncertainty in these predictions, model variability is neglected when presenting results of ecological niche model analyses. Here, we present examples of how to quantify and represent variability in models, particularly when models are transferred in space and time. To facilitate implementations of analyses of variability, we developed R functions and made them freely available. We demonstrate means of understanding how much variation exists and where this variation is manifested in geographic space. Representing model variability in geographic space gives a reference of the uncertainty in predictions, so analyzing this aspect of model outcomes must be a priority when policy is to be set or decisions taken based on these models. Our open access tools also facilitate post modeling process that otherwise could take days of manual work.

bioinformatics↗

bioRxiv2019

Inferring the ecological drivers of arboviral outbreaks

The emergence and wide-spread circulation of mosquito-transmitted viral diseases, such as dengue, Zika and Chikungunya, is a global public health concern. In the absence of effective vaccines, current control measures are mostly targeted against the mosquito vector and have so far only shown limited success. The reliance on mosquitoes for transmission also imposes strong ecological constraints that can introduce significant spatial and temporal variations in disease incidence. However, the way that epidemiological and ecological factors interact and determine population-level disease dynamics is only partially understood. Here we fit a spatially-explicit individual based model defined within a Bayesian framework to Zika incidence data from Feira de Santana, allowing us to more precisely quantify the relationships between socio-ecological factors and arboviral outbreaks. Our results further demonstrated that the virus was likely introduced into multiple spatially segregated locations at the start of the outbreak, highlighting the benefits that spatio-temporal incidence data would bring in making modelling approaches more realistic for public health planning.

epidemiology↗

bioRxiv2019

Geostatistical visualization of ecological interactions in tumors

Recent advances in our understanding sof cancer progression have highlighted the important role played by proteomic heterogeneity and the tumor microenvironment. Single-cell measurement technologies have enabled deep investigation of tumor heterogeneity. However, tools to visualize and interpret single-cell data have lagged behind experimental methods; currently, dimensionality reduction and clustering techniques, such as t-sne and SPADE, are the most prevalent visualization techniques. However, such techniques do not enable the visualization of the super-cellular structures that arise either via microenvironmental forces (e.g. hypoxia) or through cell-cell interactions. They additionally do not allow the visualization of ecological niches that are critical to understanding tumor behavior. The advent of novel experimental hyperplex immunostaining platforms, capable of measuring the in situ protein expression of dozens of proteins simultaneously, necessitates novel computational tools to quantify and visualize spatial patterns in the tumor microenvironment. Here, we introduce an approach to visualize tumor heterogeneity that integrates multiple geostatistics to capture both global and local spatial patterns. We assess the utility of this approach using an agent-based model of tumor growth under four ecological contexts; predation, mutualism, commensalism, and parasitism. Spatial patterns are visualized in real time as the models progress. This application introduces both an ecological framework for characterizing cellular interactions in cancer and novel way of quantifying and visualizing spatial patterns in cancer.

bioinformatics↗

bioRxiv2019

The ecology of cancer differentiation therapy I: non-spatial models

A promising, yet still under development approach to cancer treatment is based on the idea of differentiation therapy (DTH). Most tumours are characterized by poorly differentiated cell populations exhibiting a marked loss of traits associated to communication and tissue homeostasis. DTH has been suggested as an alternative (or complement) to cytotoxic-based approaches, and has proven successful in some specific types of cancer such as acute promyelocytic leukemia (APL). While novel drugs favouring the activation of differentiation therapies are being tested, several open problems emerge in relation to its effectiveness on solid tumors. Here we present a mathematical framework to DTH based on a well-known ecological model used to describe habitat loss. The models presented here account for some of the observed clinical and in vitro outcomes of DTH, providing relevant insight into potential therapy design. Furthermore, the same ecological approach is tested in a hierarchical model that accounts for cancer stem cells, highlighting the role of niche specificity in CSC therapy resistance. We show that the lessons learnt from metapopulation ecology can help guide future developments and potential difficulties of DTH.

cancer biology↗

bioRxiv2019

Developing political-ecological theory: The need for Many-Task Computing

Models of political-ecological systems can inform policies for managing ecosystems that contain endangered species. One way to increase the credibility of these models is to subject them to a rigorous suite of data-based statistical assessments. Doing so involves statistically estimating the models parameters, computing confidence intervals for these parameters, determining the models prediction error rate, and assessing its sensitivity to parameter misspecification. Here, these statistical algorithms along with a method for constructing politically feasible policies from a statistically fitted model, are coded as JavaSpaces programs that run as compute jobs on either supercomputers or a collection of in-house workstations. Several new algorithms for implementing such jobs in distributed computing environments are described. This downloadable code is used to compute each jobs output for the management challenge of conserving the East African cheetah (Acinonyx jubatus). This case study shows that the proposed suite of statistical tools can be run on a supercomputer to establish the credibility of a managerially-relevant model of a political-ecological system that contains one or more endangered species. This demonstration means that the new standard of credibility that any political-ecological model needs to meet before being used to inform ecosystem management decisions, is the one given herein.

scientific communication and education↗

bioRxiv2025

A panel of near-isogenic lines derived from locally adapted populations of a wild plant: A powerful tool for dissecting additive and non-additive effects on ecologically important traits

Identifying and estimating the effects of loci contributing to natural variation in ecologically important traits can be hampered by quantitative inheritance, dominance, epistasis, and environmentally dependent trait expression. Here we announce the availability of germplasm and sequence data for a reciprocal panel of near-isogenic lines (NILs) derived from locally adapted natural populations of Arabidopsis thaliana, for investigating the genetic basis of ecologically important traits. We created a panel of 54 NILs and performed whole genome sequencing to precisely locate introgression segments(s) in each NIL. Deep sequencing largely confirmed prior knowledge of NIL genotypes but also identified multiple novel small introgressions and regions of residual heterozygosity. To illustrate the utility of this panel, we identified genomic regions underlying ecotypic differences in flowering time in a laboratory common garden experiment. We detected strong additive effects on flowering time in multiple NILs with segments at the top of chromosome 5 implicating the floral regulator FLC, as expected based on previous quantitative trait locus studies. We also detected novel and complex contributions to ecotypic differences in flowering time, only visible in the NILs, suggesting the possibility of epistasis. Our results highlight the utility of this panel for dissecting the genetic architecture of ecologically important traits, including the future potential for fine mapping of additive effects and testing for epistasis and linkage using NILs derived from the panel. This panel can be used by any member of the research community to investigate any of a broad suite of traits for which the parents differ.

evolutionary biology↗

bioRxiv2025

Ecological and Genetic Determinants of Essential Oil Diversity in Mediterranean Thymus

The Mediterranean Basin is a hotspot of plant diversity, with many species producing aromatic essential oils (EOs) that mediate ecological interactions and stress responses. Within Lamiaceae, the genus Thymus shows remarkable chemical variability, yet high intraspecific EO variation often limits its taxonomic resolution. We investigated EO composition, genetic structure, and environmental influences across 39 populations of Thymus sect. Mastichina in the Iberian Peninsula, using GC-MS alongside soil and climatic data to assess drivers of chemical variation and refine taxonomic characterization. We identified 14 major EO compounds, dominated by oxygenated monoterpenes. Most populations exhibited 1,8-cineole-rich chemotypes, yet seven populations showed linalool dominance, and multiple chemotypes often co-occurred within the same populations, revealing high intrapopulation chemical diversity. Minor compounds, including camphor, borneol, and camphene, varied among genetic clusters and were significantly correlated with temperature and precipitation gradients. Differences in EO composition were also detected between ploidy levels and genetic groups, although the major compounds (1,8-cineole and linalool) remained relatively consistent, indicating both conserved and locally adaptive chemical traits. These findings suggest that EO diversity in Thymus sect. Mastichina arises from a complex interplay of environmental conditions, genetic background, and ploidy. Integrating chemical, genetic, and ecological data provides a robust framework for understanding the evolutionary and ecological drivers of EO variation in Mediterranean aromatic plants, with implications for taxonomy, conservation, and the study of adaptive chemical traits.

evolutionary biology↗

bioRxiv2025

Pangenome structure and ecological adaptation in the Klebsiella pneumoniae species complex: insights from a geographically and time limited multi-habitat study

Klebsiella pneumoniae species complex (KpSC) members inhabit distinct ecological habitats, yet the diversity and adaptation of environmental KpSC populations remain underexplored. We investigated KpSC transmission, pangenome structure and diversity, and functional gene enrichment across four distinct habitats in Burgundy, France over one year. In total, 664 environmental samples were collected from an organic vegetable farm (n=329), an organic cattle farm (n=304) and wastewater treatment plants (WWTP; n=31), alongside 47 clinical isolates. KpSC was detected in 22.4% of environmental samples, most commonly in WWTP (83.9%), followed by vegetable farm (27.1%) and cattle farm (11.2%). A total of 336 isolates were collected and whole-genome sequenced. K. pneumoniae sensu stricto (phylogroup Kp1) was predominant (76%), followed by K. variicola subsp. variicola (phylogroup Kp3) (21%). Genomic analyses revealed substantial novel diversity, especially in environmental habitats (67 novel STs), with limited cross transmission but clear local persistence. Over 90% of environmental isolates lacked acquired antimicrobial resistance genes, whereas half of the clinical isolates exhibited a multi-drug resistance profile. Comparative pangenome analyses showed Kp1 possessed a larger and more diverse pangenome than Kp3. Human-associated populations (clinical and WWTP) shared similar pangenome structures, although clinical isolates exhibited an expanded accessory genome. Cattle farm isolates had the most restricted and distinct pangenome while vegetable farm isolates displayed the largest total genomic repertoire. Functional enrichment analysis highlighted Kp3s environmental adaptation via conserved functions linked to the phylogroup genetic background, such as metabolic and regulatory pathways, including nitrogen fixation genes. Contrarily, human-associated populations, especially Kp1 members, were enriched in acquired functions linked to the ecological context, including antimicrobial and metal resistance determinants and mobile genetic elements. These findings emphasize phylogroup- and ecological niche-driven pangenome contrasts in KpSC, contributing to explain the successful adaptation of Kp1 to multiple habitats, including human-related settings.

genomics↗

bioRxiv2026

Ecological context structures duplication and mobilization of antibiotic and metal resistance genes in bacteria

Antibiotic resistance is a global challenge driven by the persistence and spread of resistance genes across ecological contexts. While mobile genetic elements (MGEs) facilitate horizontal gene transfer, gene duplication represents an additional mechanism through which resistance genes can be amplified, diversified, and maintained under selection. How these processes interact across environments remains poorly understood. Here, we examined genome-level patterns of resistance gene abundance, duplication, and mobilization across clinical, agricultural, and wastewater settings, focusing on both antibiotic resistance genes (ARGs) and metal resistance genes (MRGs). Resistance gene profiles were strongly structured by environment, with distinct duplication patterns emerging across sources. Duplicate genes were frequently associated with MGEs, although the strength of this relationship varied by resistance type and ecological context. Despite frequent co-occurrence of ARGs and MRGs, their duplication and mobilization dynamics were not uniformly coupled at the genome level. Together, these findings highlight gene duplication as a context-dependent contributor to resistance evolution and underscore the importance of ecological setting in shaping how resistance genes persist and spread across microbial communities.

bioinformatics↗