Biology subjects

Bank, C.

Publications and source records attributed to Bank, C..

At least 19 recordsLinked to original sources

bioRxiv2026

The influence of incompatibilities and heterosis on hybrid population genetics

A long-standing question in evolutionary biology is: Under what circumstances can speciation occur despite hybridisation or because of hybridisation? Some models of hybrid incompatibilities predict that speciation can occur even in the presence of gene flow and strong selection against hybrids, an outcome also influenced by genetic contributions from parental species and genetic architecture. On the other hand, empirical work has shown that heterosis can counteract the effect of incompatibilities, hindering the speciation process. Theoretical models that simultaneously consider the positive and negative impacts of hybridisation on fitness remain scarce, raising questions about the effects of hybrid incompatibilities in the presence of heterosis. To address this question, we study how (Bateson)-Dobzhansky-Muller incompatibilities (BDMIs) interact with overdominant mutations in a two-locus population genetics model of an isolated hybrid population. We find that the strength of overdominance relative to incompatibilities determines the long-term genetic composition of the hybrid population. We show that high recombination exposes incompatibilities to selection and reduces the frequency of derived alleles in the hybrid population, limiting the strength of BDMIs that can be maintained by the balance with overdominance. We also show how neutral variation is affected by the strength of selection and the recombination rate between incompatible loci, generating patterns that include an increase in local variation resembling associative overdominance, or a reduction resembling background selection. Such variation of neutral variation, particularly at intermediate distances from BDMI loci, can generate peaks or troughs of diversity that are explained by the recombination rate between BDMI loci, and initial proportions of admixture between parental populations. Our work demonstrates how the genomic conflict caused by the interplay of overdominance and hybrid incompatibilities, recombination, and parental contributions, shape the genome of an isolated hybrid population.

evolutionary biology↗

bioRxiv2026

Constant and variable warming differentially shape bacterial coexistence through phage-mediated interactions

Frequency-dependent predation helps maintain bacterial diversity, but its stabilizing role may be compromised under climate warming. Whereas theory suggests that warming can weaken predator-prey interactions and destabilize prey coexistence, it remains unclear whether constant and variable warming regimes differentially disrupt predation and alter coexistence outcomes in bacterial communities. Here, we experimentally tested how constant and variable warming (both +4{degrees}C above ambient, but negligible versus high thermal variance) affect the coexistence of two Pseudomonas species in the presence of their lytic phage. Phage predation increased competitive symmetry between the two bacterial species and promoted bacterial coexistence. Under constant warming (negligible variance), this phage-mediated frequency dependence buffered competitive asymmetries and often promoted persistence of the otherwise inferior P. putida, thereby magnifying coexistence. In contrast, variable warming (high variance) weakened phage control, shifted the advantage to P. protegens, and increased competitive exclusion events. The erosion of top-down control under variable warming was consistent with strong thermal sensitivity of phage infection rates, revealed by thermal performance curves. Our findings demonstrate that phage reduction of competitive asymmetry between bacterial hosts is amplified under constant warming but undermined under variable warming, conditions that are becoming increasingly frequent under climate change.

ecology↗

bioRxiv2026

Repeatability of adaptation in interacting species

In many evolving systems, mutations have background-dependent fitness effects due to genetic interactions between loci within a genome (intragenomic epistasis). In coevolving species, genetic interactions can span across genomes, which has been described as intergenomic epistasis. It is known that intragenomic epistasis can make adaptation more repeatable by constraining accessible mutational paths from a specific starting genotype, generating path repeatability. Here, we investigate how endpoint repeatability, how often adaptation from different starting genotypes reaches the same states in the genotype and fitness space, is influenced by the interplay of intra- and intergenomic epistasis. To this end, we model a two-species community in which the fitness of each depends on the combination of genotypes in both species. We implement this system by constructing and simulating adaptation on coevolutionary fitness landscapes using an NKC(S) model, an extension of Kauffmans NK model of evolution that includes genetic interactions between loci across species. On these fitness landscapes, we simulate adaptive walks that alternate between mutation in a focal and a partner species. To quantify the repeatability of adaptation, we track the endpoints of adaptive walks and record the fitness of both species at the evolutionary endpoints. We find that intergenomic epistasis causes high endpoint repeatability within a given landscape but highly varying fitness outcomes across different coevolutionary landscapes. Thus, patterns of repeatability deviate from expectations based on single-species adaptation in the presence of intragenomic epistasis due to varying fitness trade-offs between species, which can lead to cycling and large coevolutionary fitness loads.

evolutionary biology↗

bioRxiv2025

Pervasive Intraspecific Genetic Local Adaptation Within the Natural Gut Microbiome

Gut microbial communities are shaped by the physicochemical gradients and compartmentalization along the gastrointestinal tract. Whether spatially variable selection is strong enough to promote lasting genetic divergence within microbial species subject to migration and clonal expansion remains unclear. We performed a metagenomic population-genetic analysis of roe deer microbiota across metabolically and structurally distinct gut compartments. Remarkably, 10 of 20 prevalent bacterial species exhibited clear signatures of genetic local adaptation, despite the homogenizing effects of frequent migration. Nutrient availability and environmental stability emerged as primary drivers of selection, with horizontal gene transfer as a key mechanism enabling local adaptation. Our findings demonstrate that a comprehensive understanding of ecological and evolutionary dynamics in the gut necessitates considering fine-scale genetic variation within species.

evolutionary biology↗

bioRxiv2025

Extended-spectrum beta-lactamase (ESBL)-producing E. coli in livestock and free-roaming wildlife: a combined phenotyping whole-genome sequencing One Health approach

Antimicrobial resistance (AMR) in Enterobacterales, particularly extended-spectrum beta-lactamase-producing Escherichia coli (ESBL-Ec), poses a significant public health concern. Widespread antimicrobial use exerts selection pressure, driving the persistence and spread of resistant bacteria in diverse environments. While ESBL-Ec is well-documented in clinical and agricultural settings, its presence in reservoirs remains poorly understood. This study assessed the prevalence, AMR profiles, and genetic diversity of ESBL-Ec in Swiss dairy cattle and wildlife. Between 2021 and 2023, 775 samples were analysed, including rectal swab samples from dairy cows (n=475), and fecal or cloacal swab samples and wildlife (n=300). ESBL-Ec was detected in 0.6% of dairy cattle and 3.7% of wildlife. Whole-genome sequencing of 54 ESBL-Ec isolates identified 28 sequence types with no overlap between livestock and wildlife, suggesting distinct evolutionary trajectories. Phenotypic testing revealed resistance beyond beta-lactams, notably against aminoglycosides, tetracyclines, and sulfonamides, whereas all isolates remained susceptible to tigecycline and meropenem. Multidrug resistance was prevalent (89%), with blaCTX-TEM1 (in dairy cattle), blaCTX-M55 and blaTEM-176 (in red foxes) widely distributed across Switzerland. Clonal plasmids (IncFIB, IncX1) were detected across hosts and some individuals harbored multiple ESBL-Ec strains. Despite their low prevalence, spatial clustering indicated local persistence in both livestock and wildlife, highlighting potential transmission. The observed presence of clinically relevant ESBL-Ec in wildlife highlights the need for a One Health approach to tackle the dangers of AMR. Our findings contribute to AMR surveillance by providing baseline data on ESBL-Ec reservoirs and informing the design of strategies to mitigate its environmental spread.

molecular biology↗

bioRxiv2025

Life history evolution facilitates trophic diversification

To what extent is biodiversity shaped by environmental conditions, and to what extent is it the result of self-organization? Both natural processes and structural features may contribute to promoting diversity. Here, we show that one such process, namely natural selection, and a structural feature, namely organismal life history, interact in a feedback mechanism that promotes the emergence of diversity. We illustrate how this mechanism operates using various models of ecological diversification driven by intraspecific resource competition, in which both a niche trait that determines resource use and a life history trait can evolve. We find that natural selection that acts on life history traits leads to increased competition, which, in the presence of ecological opportunity, facilitates niche diversification. As a consequence, the environmental conditions (e.g. productivity) for diversification are more restrictive in the absence of life history evolution than in its presence. Our findings indicate a strong influence of life history evolution on ecological processes that in turn shape the origin of biodiversity. Our results call for a better integration of life history evolution and ecological diversification in theoretical and empirical research.

evolutionary biology↗

bioRxiv2025

Antimicrobial Resistance in Wildlife across Switzerland and the Principality of Liechtenstein: Associations with Environmental Factors and Taxonomic Variation

Antimicrobial resistance (AMR) presents a significant challenge to global public health. Addressing this challenge requires a comprehensive One Health approach that integrates efforts in human, veterinary, and environmental domains. Whereas AMR research in medical and veterinary domains is extensive, AMR research in wildlife has received less attention. However, AMR prevalence in the environment, and specifically in wildlife, ultimately affects human life. In a large study conducted in Switzerland and the Principality of Liechtenstein, we collected 410 rectal swab samples from 37 different wildlife species to quantify the prevalence of Escherichia coli (E. coli) and its resistance to 16 antimicrobial drugs, determined through phenotypical antimicrobial susceptibility testing. The study yielded an 81.5% E. coli isolation rate with a considerable 10.8% of isolates resistant to one or more antimicrobial drugs. Notably, 4.5% of the isolates demonstrated multidrug resistance (MDR). Furthermore, we found that E. coli in omnivores exhibited the highest levels of AMR, significantly higher than in carnivores and herbivores. In addition to these dietary associations, we found that the percentage of forested areas surrounding the sampling locations was inversely related to AMR rates, suggesting that environmental conditions play a role in mitigating AMR. This study provides a large-scale quantification of AMR in a broad range of wildlife species and also identifies diverse patterns of AMR in E. coli, highlighting variations associated with both host species and environmental conditions. Our findings emphasize the role of wildlife as potential indicators of environmental contamination with antibiotics and as reservoirs of resistant bacteria.

microbiology↗

bioRxiv2024

Drivers of diversity within and between microbialcommunities during stochastic assembly

No two microbial communities share the same species richness and abundance. Experiments have shown that the assembly of new microbial communities from the same environmental pool is sufficient to generate diversity within and between communities. To identify the mechanisms behind these experimental results, we build a stochastic model that considers both the dispersal of microbes from a pool to communities and microbial division. By analyzing timescales, we identify distinct assembly regimes. Specifically, if dispersal is slower than division, microbial communities show low diversity within communities but high diversity between communities. Conversely, if dispersal is faster than division, microbial communities exhibit high diversity within communities but low diversity between them. We validate these predictions both numerically, using Gillespie simulations, and analytically, by deriving equations for species richness and abundance distributions. Our derivations pinpoint two key metrics, the bimodality coefficient and mean relative abundance, which identify the assembly regime and quantify trait differences. We apply these metrics to reanalyze an experimental data set, demonstrating their practical application. Overall, our study provides general predictions on how stochasticity, timescales, and traits impact diversity within and between communities during the assembly of new microbial communities, allowing for a better understanding of variation in microbiome formation.

ecology↗

bioRxiv2024

Adaptation of human cell populations to different levels of centriole amplification involves a two-step response

Centrioles are the main components of cilia and centrosomes, which play a central role in cell division and signalling. Their numbers are strictly regulated. Centriole amplification, or the presence of extra centrioles, often occurs in tumours and leads to aneuploidy and altered signalling and has been associated with cancer development and malignancy. Negative selection of cells with extra centrioles prevents numerical errors from expanding in the population, resulting in an overproduction-selection balance. However, how chronic perturbation of key centriolar regulators affects centriole number dynamics is poorly described. PLK4, a key regulator of centriole biogenesis, is often overexpressed in cancer. Here, we studied the long-term dynamics of cell populations exposed to different levels of PLK4 overexpression. We measured absolute and relative fitness in the evolving populations, quantified centriole numbers over time, as well as various aspects of the immediate response to centriole amplification. Our experiments indicated negative selection against cells with extra centrioles and outcompetition of PLK4-overexpressing cells by a cell line carrying a truncated form of PLK4, that does not amplify centrioles. In populations where cells carrying the truncated form of PLK4 were absent, cells overexpressing full-length PLK4 maintained the capacity to amplify centrioles over the course of experimental evolution and, strikingly, converge to the same degree of centriole amplification regardless of the level of PLK4 overexpression. Our results support a population-level response to centrosome amplification to control centriole amplification levels. Future work is necessary to further characterise this response and the mechanisms that allow cell populations to maintain centriole amplification.

cell biology↗

bioRxiv2023

Unpredictability of the fitness effects of antimicrobial resistance mutations across environments in Escherichia coli

The evolution of antimicrobial resistance (AMR) in bacteria is a major public health concern. When resistant bacteria are highly prevalent in microbial populations, antibiotic restriction protocols are often implemented to reduce their spread. These measures rely on the existence of deleterious fitness effects (i.e., costs) imposed by AMR mutations during growth in the absence of antibiotics. According to this assumption, resistant strains will be outcompeted by susceptible strains that do not pay the cost during the period of restriction. Hence, the success of a given intervention depends on the magnitude and direction of fitness effects of mutations, which can vary depending on the genetic and environmental context. However, the fitness effects of AMR mutations are generally studied in laboratory reference strains and estimated in a limited number of environments, usually a standard laboratory growth medium. In this study, we systematically measure how three sources of variation impact the fitness effects of AMR mutations: the type of resistance mutation, the genetic background of the host, and the growth environment. We demonstrate that while AMR mutations are generally costly in antibiotic-free environments, their fitness effects vary widely and depend on complex interactions between the AMR mutation, genetic background, and environment. We test the ability of the Rough Mount Fuji genotype-fitness model to reproduce the empirical data in simulation. We identify model parameters that reasonably capture the variation in fitness effects due to genetic variation. However, the model fails to accommodate variation when considering multiple growth environments. Overall, this study reveals a wealth of variation in the fitness effects of resistance mutations owing to genetic background and environmental conditions, that will ultimately impact their persistence in natural populations. Authors AbstractThe emergence and spread of antimicrobial resistance in bacterial populations poses a continuing threat to our ability to successfully treat bacterial infections. During exposure to antibiotics, resistant microbes outcompete susceptible ones, leading to increases in prevalence. This competitive advantage, however, can be reversed in antibiotic-free environments, due to deleterious fitness effects imposed by resistance determinants, a concept referred to as the cost of resistance. The extent of these fitness effects is an important factor governing the prevalence of resistance in natural populations. However, predicting the fitness effects of resistance mutations is challenging, since their magnitude can change depending on the genetic background in which the mutation arose and the environmental context. Comprehensive data on these sources of variation is lacking, and we address this gap by determining the fitness effects of resistance mutations introduced in a range of Escherichia coli clinical isolates, measured in different antibiotic-free environments. Our results reveal wide variation in the fitness effects, driven by irreducible interactions between resistance mutations, genetic backgrounds, and growth environments. We evaluate the performance of a fitness landscape model to reproduce the data in simulation, highlight its strengths and weaknesses, and call for improvements to accommodate these important sources of variation.

evolutionary biology↗

bioRxiv2023

Ecological tradeoffs lead to complex evolutionary trajectories and sustained diversity on dynamic fitness landscapes

The course and outcome of evolution are critically determined by the fitness landscape, which maps genotype to fitness. Most theory has considered static fitness landscapes or fitness landscapes that fluctuate according to abiotic environmental changes. In the presence of biotic interactions between coexisting genotypes, the fitness landscape becomes dynamic and frequency-dependent. Here, we introduce a fitness landscape model that incorporates ecological interactions between individuals in a population. In the model, fitness is determined by individuals competing for resources according to a set of traits they possess. An individuals genotype determines the trait values through a Rough Mount Fuji fitness landscape model, allowing for tunable epistasis (i.e., non-additive gene interaction) and trait correlations (i.e., whether there are tradeoffs or synergies in the ability to use resources). Focusing on the effects of epistasis and trait correlations, we quantify the resulting eco-evolutionary dynamics under simulated Wright-Fisher dynamics (i.e., including genetic drift, mutation, and selection under the assumption of a constant population size) on the dynamics fitness landscape in comparison with a similar, static, fitness landscape model without ecological interactions. Whereas the non-ecological model ultimately leads to the maintenance of one main geno-type in the population, evolution in the ecological model can lead to the long-term coexistence of several genotypes at intermediate frequencies across much of the parameter range. Including ecological interactions increases steady-state diversity whenever the trait correlations are not too strong. However, strong epistasis can hinder coexistence, and additive genotype-phenotype maps yield the highest haplotype diversity at the steady state. Interestingly, we frequently observe long-term coexistence also in the absence of induced trade-offs in the ability to consume resources. In summary, our simulation study presents a new dynamic fitness landscape model that highlights the complex eco-evolutionary consequences of a (finite) genotype-phenotype-fitness map in the presence of biotic interactions.

evolutionary biology↗

bioRxiv2023

STUN: forward-time Simulation on TUnable fitNess landscapes in recombining populations

Understanding the population genetics of complex polygenic traits during adaptation is challenging. Here, we implement a forward-in-time population-genetic simulator (STUN) based on Wright-Fisher dynamics. STUN is a flexible and user-friendly software package for simulating the polygenic adaptation of recombining haploid populations using either new mutations or standing genetic variation. STUN assumes that populations adapt to sudden environmental changes by undergoing selection on a new fitness landscape. With pre-implemented fitness landscape models like Rough Mount Fuji, NK, Block, additive, and House-of-Cards, users can explore the effect of different levels of epistasis (ruggedness of the fitness landscape). Custom fitness landscapes and recombination maps can also be defined. STUN empowers both experimentalists and advanced programmers to study the evolution of complex polygenic traits and to dissect the adaptation process. Availability and implementationSTUN is implemented in Rust. Its source code is available at https://github.com/banklab/STUN, which also includes a link to the softwares manual and binary files for Linux, macOS and Windows. Upon publication, the code will also be archived on Zenodo and a doi will be provided here.

evolutionary biology↗

bioRxiv2023

In search of the Goldilocks zone for hybrid speciation II: hard times for hybrid speciation.

Hybridization opens a unique window for observing speciation mechanisms and is a potential engine of speciation. One controversially discussed outcome of hybridization is homoploid hybrid speciation by reciprocal sorting, where a hybrid population maintains a mixed combination of the parental genetic incompatibilities, preventing further gene exchange between the newly formed population and the two parental sources. Previous work showed that, for specific linkage architectures (i.e., the genomic location and order of hybrid incompatibilities), reciprocal sorting could reliably result in hybrid speciation. Yet, the sorting of incompatibilities creates a risk of population extinction. To understand how demographic consequences of the purging of incompatibilities interact with the formation of a hybrid species, we model an isolated hybrid population resulting from a single admixture event. We study how population size, linkage architecture and the strength of the incompatibility affect survival of the hybrid population, resolution/purging of the genetic incompatibilities and the probability of observing hybrid speciation. We demonstrate that the extinction risk is highest for intermediately strong hybrid incompatibilities. In addition, the linkage architecture displaying the highest hybrid speciation probabilities changes drastically with population size. Overall, this indicates that population dynamics can strongly affect the outcome of hybridization and the hybrid speciation probability.

evolutionary biology↗

bioRxiv2022

Solving the stochastic dynamics of population growth

Population growth is a fundamental process in ecology, evolution, and epidemiology. The population size dynamics during growth are often described by deterministic equations derived from kinetic models. Here, we simulate several population growth models and compare the size averaged over many stochastic realizations with the deterministic predictions. We show that these deterministic equations are generically bad predictors of the average stochastic population dynamics. Specifically, deterministic predictions overestimate the simulated population sizes, especially those of populations starting with a small number of individuals. Describing population growth as a stochastic birth process, we prove that the discrepancy between deterministic predictions and simulated data is due to unclosed-moment dynamics. In other words, the deterministic approach does not take into account the variability of birth times, which is particularly important at small population sizes. We evaluate different moment-closure approximations and show that they do not satisfactorily reduce the error between analytical predictions and simulated data. We present two novel solutions to the stochastic growth dynamics, one of which applies to any population growth model. We show that our solution exactly quantifies the dynamics of a community composed of different strains and correctly predicts the fixation probability of a strain in a serial dilution experiment. Our work sets the foundations for a more faithful modeling of community dynamics. It provides tools for a more accurate analysis of experimental results, including the inference of important growth parameters.

ecology↗

bioRxiv2022

Short-term adaptation on tunable fitness landscapes from standing genetic variation in recombining populations

How does standing genetic variation affect polygenic adaptation in recombining populations? Despite a large body of work in quantitative genetics, epistatic and weak additive fitness effects among simultaneously segregating genetic variants are difficult to capture experimentally or to predict theoretically. In this study, we simulated adaptation on fitness landscapes with tunable ruggedness driven by standing genetic variation in recombining populations. We confirmed that recombination hinders the movement of a population through a rugged fitness landscape. When surveying the effect of epistasis on the fixation of alleles, we found that the combined effects of high ruggedness and high recombination probabilities lead to preferential fixation of alleles that had a high initial frequency. This indicates that positively epistatic alleles escape from being broken down by recombination when they start at high frequency. We further extract direct selection coefficients and pairwise epistasis along the adaptive path. When taking the final fixed genotype as the reference genetic background, we observe that, along the adaptive path, beneficial direct selection appears stronger and pairwise epistasis weaker than in the underlying fitness landscape. Quantitatively, the ratio of epistasis and direct selection is smaller along the adaptive path ({approx} 1) than expected. Thus, adaptation on a rugged fitness landscape may lead to spurious signals of direct selection generated through epistasis. Our study highlights how the interplay of epistasis and recombination constrains the adaptation of a diverse population to a new environment.

evolutionary biology↗

bioRxiv2022

Evolutionary rescue in a fluctuating environment

No environment is constant over time, and environmental fluctuations impact the outcome of evolutionary dynamics. Survival of a population not adapted to some environmental conditions is threatened unless a mutation rescues it, an eco-evolutionary process termed evolutionary rescue. We here investigate evolutionary rescue in an environment that fluctuates between a favorable state, in which the population grows, and a harsh state, in which the population declines. We develop a stochastic model that includes both population dynamics and genetics. We derive analytical predictions for the mean extinction time of a non-adapted population given that it is not rescued, the probability of rescue by a generalist mutation, and the mean appearance time of a rescue mutant, which we validate using numerical simulations. We find that evolutionary rescue is less (respectively more) likely if the environmental fluctuations are stochastic rather than deterministic and if the mean time between each environmental change is less (respectively more) than the mean survival time of the population in the harsh environment. We demonstrate that high equilibrium population sizes and per capita growth rates maximize the chances of evolutionary rescue. We show that an imperfectly harsh environment, which does not fully prevent births but makes the death rate to birth rate ratio much greater than unity, has almost the same rescue probability as a perfectly harsh environment, which fully prevents births. Finally, we put our results in the context of antimicrobial resistance and conservation biology.

evolutionary biology↗

bioRxiv2022

Epistasis decreases with increasing antibiotic pressure but not temperature

Predicting mutational effects is essential for the control of antibiotic resistance (ABR). Predictions are difficult when there are strong genotype-by-environment (GxE), gene-by-gene (GxG or epistatic), or gene- by-gene-by-environment (GxGxE) interactions. We quantified GxGxE effects in Escherichia coli across environmental gradients. We created intergenic fitness landscapes using gene knock-outs and single nucleotide ABR mutations previously identified to vary in the extent of GxE effects in our environments of interest. Then, we measured competitive fitness across a complete combinatorial set of temperature and antibiotic dosage gradients. In this way, we assessed the predictability of 15 fitness landscapes across 12 different but related environments. We found GxG interactions and rugged fitness landscapes in the absence of antibiotic, but as antibiotic concentration increased, the fitness effects of ABR genotypes quickly overshadowed those of gene knock-outs, and the landscapes became smoother. Our work reiterates that some single mutants, like those conferring resistance or susceptibility to antibiotics, have consistent effects across genetic backgrounds in stressful environments. Thus, although epistasis may reduce the predictability of evolution in benign environments, evolution may be more predictable in adverse environments.

evolutionary biology↗

bioRxiv2022

Metagenomics and metabarcoding experimental choices and their impact on microbial community characterization in freshwater recirculating aquaculture systems

Recirculating aquaculture systems (RAS) heavily depend on microbial communities to maintain water quality. These communities therefore influence the growth, development, and welfare of farmed fish. With the increasing socio-economic role of fish farming e.g. regarding food security, an in-depth understanding of aquaculture microbial communities is also relevant from a management perspective. However, the data situation regarding the composition of microbial communities within RAS is patchy. Since this is partly ascribed to method choices, there clearly is a need for accurate, standardized, and user-friendly methods to study microbial communities in aquaculture systems. Here, we compare the performance of 16S amplicon sequencing, Pac-Bio long-read amplicon sequencing, and amplification-free shotgun metagenomics in the characterization of microbial communities in two commercial-size RAS fish farms. We show that, even though primer choice affects read quality, diversity, and assigned taxa, distinct primer pairs uncover similar spatio-temporal patterns between sample types, farms, and time points. We find that long-read amplicons underperform regarding quantitative resolution of spatio-temporal patterns, but allow for species-level identification of functional services and pathogens. Finally, shotgun metagenomics data identified fungi, viruses, and bacteriophages, opening avenues for an exploration of natural approaches regarding antipathogenic treatments. Overall, the datasets agreed on major prokaryotic players. In conclusion, different sequencing approaches yield overlapping and highly complementary results, with each contributing data no other approach could. Such a tiered approach therefore constitutes a practical and cost-effective strategy for obtaining the maximum amount of information on aquaculture microbial communities. These data could lead to better farm management practices and at the same time inform basic research on community evolution dynamics.

microbiology↗