Biology subjects

Alberdi, A.

Publications and source records attributed to Alberdi, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Interspecific faecal microbiota transplantation tests microbial contributions to thermal physiology in lizards

While the influence of microorganisms in the thermal physiology of animals is increasingly recognised, the role of the gut microbiome in enhancing phenotypic plasticity remains underexplored, particularly in ectotherms. Here, we tested the effect of gut microbiomes in modulating the physiological response of lizards to sudden temperature fluctuations. In captivity, we conducted an experiment with wild-caught Podarcis lizards: Mediterranean Podarcis liolepis (n=9) adapted to warm and dry environments, and Atlantic P. muralis (n=18) adapted to cooler and wetter conditions. Animals were assigned to three groups (intervention, control-cold and control-warm) and subjected to microbiota manipulations using antibiotics and faecal microbiota transplants (FMT). In the intervention group, cold-adapted P. muralis received faecal suspension from warm-adapted P. liolepis, while control-cold and control-warm groups received intraspecific transplants. Microbiome variation was analysed through genome-resolved metagenomics of 162 faecal samples, yielding 313 MAGs across 15 phyla, containing almost 1M annotated genes. One week after transplantation, microbiomes of control animals differed from their original state, whereas those of the intervention group (P. muralis), transitioned to a state resembling P. liolepis. After two weeks, both control groups showed trends of reversing their microbiomes to their original states. However, the intervention group displayed a distinct trajectory, resembling the microbial donors'. Although potentially relevant trends were observed, these microbiome alterations did not translate into detectable significant differences in their thermal physiology. Nevertheless, our results provide proof of concept for microbial transplants in lizards, and opportunities to further explore the link between gut microbes and host physiological responses in ectotherms.

zoology↗

bioRxiv2026

Histomonas meleagridis infection and vaccination protection in chickens -- a metabolomics study

Histomonosis, caused by Histomonas meleagridis, is a severe disease in poultry with main pathological lesions in ceca and liver, leading to significant animal suffering and economic losses, with no licensed treatments available. While cecal pathology and microbiota disruption have been documented, the metabolic consequences of infection and vaccination remain poorly understood. Here, we used untargeted LC-MS metabolomics to profile cecal tissue and luminal digesta in a controlled vaccination-challenge chicken trial (n=100, 25 birds/group), including uninfected and unvaccinated but challenged controls, together with birds vaccinated either cloacally, or orally via an edible gel following challenge, across five post-challenge timepoints. Results showed that H. meleagridis infection caused extensive, time-dependent disruption of the cecal metabolome, especially at 7-14 days post-infection (DPI). At DPI 14, 325 tissue and 359 digesta metabolites were significantly altered in unvaccinated challenged birds. Infection was associated with depletion of microbiota-related metabolites, including dicarboxylic acids, tryptophan indoles, phytochemical derivatives, bilirubin catabolites, phenolics, vitamins, and secondary bile acids, alongside accumulation of microbial substrates and fermentation products. Changes in the host-associated metabolites indicated mucosal inflammation, epithelial injury, mitochondrial and amino acid metabolic disturbance, oxidative stress, and membrane lipid remodeling. Cloacal vaccination provided greater metabolic protection than oral vaccination, with 78.3% of disrupted metabolites preserved at DPI 14, compared with 60.7% vaccination by oral gel delivery, pointing towards the importance of vaccine take. By DPI 21, cloacally vaccinated birds showed nearly complete metabolic recovery across most pathway groups, whereas gel-vaccinated birds retained broader metabolic disturbance. These findings reveal histomonosis as a disruption of the cecal host-microbiota metabolic interface and provide a metabolite-level framework for future studies of pathogenesis, vaccine development, and prevention strategies.

pharmacology and toxicology↗

bioRxiv2026

Impact of sequencing approach on ecological inference from highly variable bat gut microbiomes

Understanding the functional potential of animal gut microbiomes requires analytical approaches that can accurately capture both taxonomic and functional diversity, particularly in hosts with samples with low and variable microbial DNA fractions, such as bats. Here, we compared 16S amplicon sequencing and genome-resolved metagenomics for characterising the gut microbiomes of three sympatric insectivorous bats (Pipistrellus kuhlii, Hypsugo ariel, and Cnephaeus bottae). Amplicon sequencing recovered 3,536 amplicon sequence variants (ASVs) spanning 29 microbial phyla, including five archaeal groups, while metagenomics yielded 135 metagenome-assembled genomes (MAGs) across 15 bacterial phyla. Alpha and beta diversity patterns differed significantly between approaches. Applying prevalence- and abundance-based filtering to amplicon data improved alpha diversity congruence with metagenomic profiles, indicating that low-abundance and rare ASVs inflate diversity estimates, while the low microbial DNA fractions in bat faeces challenge genome reconstruction of such taxa. Functional reconstructions diverged notably, with metagenomics-based functional profiles yielding consistently lower metabolic capacities than those indirectly inferred from 16S amplicon sequencing, both before and after prevalence- and abundance-based filtering, due to incompleteness of many reconstructed genomes. However, metagenome-assembled genomes harboured metabolic capacities missed by the indirect functional inference of metabarcoding, which largely rely on genomes of strains characterised in model organisms. Together, these findings highlight the influence of chosen methodology, host species, and data filtering on microbiome profiling in taxa with low microbial biomass. We propose practical guidelines to improve analytical consistency and reliability when studying gut microbiomes of bats and other hosts with similarly variable microbial communities.

microbiology↗

bioRxiv2025

Beyond the core: endemic microbiota drive functional and microdiversity differences across salamander populations

Population-specific variation in animal microbiomes is well documented, yet the functional consequences and underlying mechanisms remain poorly understood. To address this, we conducted genome-resolved metagenomic analyses on gut and skin microbiomes from four populations of Pyrenean brook salamanders (Calotriton asper) inhabiting two distinct environments (Pyrenean subalpine brooks and Atlantic montane streams). From paired faecal and skin swab samples, we reconstructed 539 and 43 metagenome-assembled genomes (MAGs), respectively, and examined taxonomic composition, metabolic capacity, and microdiversity across environments. While alpha diversity remained consistent, both gut and skin microbiomes exhibited significant differences in community composition and functional potential between environments. Partitioning the gut microbiome into core, endemic, and marginal fractions revealed a dominant core community--shared across environments and accounting for over 85% of reads--that did not drive functional divergence. Instead, functional differences were primarily shaped by low-abundance, population-specific endemic bacteria. Atlantic salamanders hosted endemic taxa with significantly greater metabolic potential and higher strain-level microdiversity than those at the Pyrenees. These patterns were not explained by dietary differences and may reflect environmental influences such as temperature and nutrient availability. Our findings highlight the relevance of rare, endemic bacteria in driving microbiome function and underscore the power of genome-resolved metagenomics to uncover functional and evolutionary dynamics in wild host-microbe systems.

microbiology↗

bioRxiv2025

Integrative holo-omic data analysis predicts interactions across the host-microbiome axis

Understanding the interplay between host organisms and their microbiomes is central to the development of sustainable food systems. However, high dimensionality and spurious associations remain major obstacles to extracting meaningful biological insight from multi-omic host-associated microbiome data; a challenge further exacerbated when "holo-omic" analyses across the host-microbiome boundary is considered. Here, we show that a computational method designed for multi-omic analysis in eukaryotes can be leveraged to integrate and analyse five layers of holo-omic data from porcine hosts and their gut microbiomes. We collected caecal tissue and digesta samples during a feeding trial that tested the impact of microbiota-directed fibres (acetylated galactoglucomannan) at critical developmental stages. From 800,000 features including microbial and host genes, metagenome-assembled genomes, and metabolites from caecal tissue and digesta, we used multiset correlation and factor analysis to select the most relevant features for capturing coordinated patterns across omic layers. From these features, we predicted over 2,000 putative host-microbiome interactions based on co-occurrence. Some of them reflected previously known relationships between animal and microbiome features, such as microbial genes for carbohydrate metabolism being linked to glycoside abundances in host tissue. Other predicted co-occurrences included features that were not detected in single-omic analysis and offer new hypotheses of host-microbiome interactions that warrant future investigation. Hence, we showcase an application of holo-omic analysis that avoids common pitfalls in high-dimensional data analysis; identifies known interactions as a form of validation; and most importantly, predicts new leads for understanding host-microbiome symbiosis. ImportanceWhile study systems involving mammalian hosts and their microbiomes are inherently complex, multi- and holo-omic analyses promise to provide interpretable results with translational value for the animal production industry. Unfortunately, computational methods capable of this kind of integration are currently scarce, as most existing multi-omics approaches have been developed for analysis of data layers within a single multicellular organism. We propose to adapt existing multi-omic methods for holo-omics by combining feature selection and interaction inference. This two-step analysis approach addresses common challenges in data-driven studies and can be implemented with a variety of tools for feature selection and interaction modelling. Through this holistic approach, we show that both known and novel relationships across the holobiont axis can be identified in a data-driven manner, offering new targets for the continued study of host-microbiome interactions and the effect of dietary interventions on production animals.

bioinformatics↗

bioRxiv2025

Micro-scale spatial metagenomics: revealing high-resolution spatial biogeography of gut microbiomes

Spatial organisation is a fundamental yet poorly resolved aspect of gut microbial ecology. Conventional shotgun metagenomics provides rich functional information but relies on homogenised, macro-scale samples that obscure the micron-scale distributions critical for understanding microbial community dynamics. Here, we introduce Micro-Scale Spatial Metagenomics (MSSM), a new methodological framework that couples laser micro-dissection of tissue sections, ultra-low-input library preparation, and genome-resolved bioinformatics to reconstruct microbial communities from intestinal microsamples measuring as little as [~]500 {micro}m{superscript 2} ({approx}100 bacterial cells). We describe a fully optimised laboratory and computational pipeline that enables quantitative, strain-resolved, and functionally informed spatial profiling directly from intact gut tissue. Using chicken intestinal samples, we validated MSSM through combinatorial single-cell fluorescence in situ hybridisation (FISH) imaging and comparisons with macro-scale metagenomics, demonstrating its robustness and accuracy. MSSM captured fine-scale heterogeneity in taxonomic and functional composition across intestinal cryosections, hinting at spatially structured assemblages and segregation of metabolic capacities. Strain-level analyses uncovered coexisting Lawsonibacter lineages exhibiting distinct spatial distributions and host-specific occurrence patterns, while SNP-level microdiversity analyses showed that genetically coherent clonal populations cluster at spatial scales below [~]200 {micro}m. By enabling shotgun metagenomics at micron resolution, MSSM closes a longstanding methodological gap and provides a scalable platform for studying microbial ecosystems in situ. This approach unlocks a previously inaccessible view of microbial biogeography, offering new opportunities to investigate host-microbe and microbe-microbe interactions, and the spatial principles governing gut ecosystems. Significance statementUnderstanding how microbial communities are organised in space is essential to explaining their ecological and functional roles, yet microbiome research still relies overwhelmingly on bulk, spatially averaged measurements. We introduce micro-scale spatial metagenomics (MSSM), the first method that brings shotgun metagenomics to the microscale, enabling direct measurement of functional and taxonomic variation across regions containing as few as [~]100 cells. Unlike existing spatial approaches, MSSM reconstructs complete genomes and resolves strain-level diversity within intact tissue, allowing researchers to map metabolic potential, microdiversity, and community structure in situ. By coupling high-resolution sequencing with spatial context, MSSM reveals a previously inaccessible layer of microbial organisation, transforming how host-associated ecosystems can be studied.

microbiology↗

bioRxiv2025

Predicting DNA origami stability in physiological media by machine learning

DNA origami nanostructures offer substantial potential as programmable, biocompatible platforms for drug delivery and diagnostics. However, their structural stability under physiological conditions remains a major barrier to practical applications. Stability assessment of DNA origami nanostructures has traditionally relied on image-based and empirical approaches, which are time-consuming and difficult to generalize across conditions. To address these limitations, we developed a machine learning approach for DNA origami stability prediction, based on measurable physicochemical parameters. Using dynamic light scattering (DLS) to quantify diffusion coefficients as a proxy for structural integrity, we characterized over 1400 DNA origami samples under varying physiologically relevant variables: temperature, incubation time, MgCl2 concentration, pH, and DNase I concentrations. The predictive performance of the model was confirmed using an independent set of samples under previously untested conditions. This data-driven approach offers a scalable and generalizable framework to guide the design of robust DNA nanostructures for biomedical applications.

bioengineering↗

bioRxiv2025

Characterization and description of Clostridium filamentum ETTB, a novel gut bacterium with TLR5 modulating properties

The Clostridium genus is highly heterogeneous, encompassing numerous species and strains, many of which remain to be isolated and characterized to better understand their relationship to host physiology. This study aimed to isolate and characterize novel bacterial species within the Clostridium genus and explore their potential links to host health. Under microaerophilic conditions, we isolated and characterized three bacterial isolates belonging to a new anaerobic Clostridium species, designating Clostridium sp. DSM 115107 (Clostridium filamentum ETTB3) as the type strain. C. filamentum ETTB isolates are rod- to filament-shaped, Gram-positive bacteria and exhibit poor growth when cultured on rich media such as LYBHI. Genome sequencing and phylogenetic analysis revealed that C. filamentum ETTB belongs to the Clostridium genus and clusters closely with Clostridium saudiense JCC. Interestingly, C. filamentum ETTB has a significantly smaller genome compared to C. saudiense JCC containing a reduced repertoire of genes involved in carbohydrate degradation and amino acid synthesis and a larger number of genes related to cell motility, including an additional copy of the fliC gene. Unlike C. saudiense, C. filamentum ETTB adopted a filamentous morphology when in contact with Caco-2 cells and stimulate the TLR5 pathway in Caco-2 cells. Metagenomics analysis revealed that C. filamentum ETTB is present in both industrialized and non-industrialized populations, although the relative abundance varying considerably between and within individuals. Our study identifies a novel bacterial strain adapted for the human gut that has the potential to influence host immune response by activating TLR5 pathway.

microbiology↗

bioRxiv2024

Dietary intervention in captive-bred hares fails to enrich gut microbiomes with wild-like functions

Reintroducing captive-bred animals into the wild often faces limited success, with the underlying causes frequently unclear. One emerging hypothesis is that maladapted gut microbiota may play a significant role in these challenges. To investigate this possibility, we employed genome-resolved metagenomics to analyse the taxonomic and functional differences in the gut microbiota of wild and captive European hares (Lepus europaeus), as well as to assess the impact of a dietary switch to grass aimed at pre-adapting captive hares to wild conditions. Our analyses recovered 860 metagenome-assembled genomes, with 87% of them representing novel species. We found significant taxonomic and functional differences between the gut microbiota of wild and captive hares, notably the absence of Spirochaetota in captive animals and differences in amino acid and sugar degradation capacities. While the dietary switch to grass induced some minor changes in the gut microbiota, it did not result in a shift towards a more wild-like microbial community. The increased capacity for degrading amino acids and specific sugars observed in wild hares suggest that, instead of bulk grass, dietary interventions tailored to their specific dietary preferences might be necessary for pre-adapting hare gut microbiota to wild conditions. ImportanceThis study sheds light on the critical role of gut microbiota in the success of reintroducing captive-bred animals into the wild. By comparing the gut microbiota of wild and captive European hares, we identified significant taxonomic and functional differences, including the absence of key microbial groups in captive hares. Dietary interventions, such as switching to grass, showed limited success in restoring a wild-like microbiota, highlighting the need for tailored approaches to mimic natural diets. With 87% of recovered microbial genomes representing novel species, this research also enriches our understanding of microbial diversity in wildlife. These findings emphasise that maladapted gut microbiota may hinder the survival and adaptation of reintroduced animals, suggesting that microbiome-targeted strategies could improve conservation efforts and the success of animal rewilding programs.

ecology↗

bioRxiv2024

Functional insights into the effect of feralisation on the gut microbiota of cats worldwide

Feralisation, the process by which domesticated organisms revert to a wild state, is a widespread phenomenon across various species. Successfully adapting to a new environment with different access to food, shelter, and other resources requires rapid physiological and behavioural changes, which could potentially be facilitated by gut microbiota plasticity. To investigate whether alterations in gut microbiota support this transition to a feral lifestyle, we analysed the gut microbiomes of domestic and feral cats from six geographically diverse locations using genome-resolved metagenomics. By reconstructing 229 draft genomes from 92 cats, we identified a typical carnivore microbiome structure, with notable diversity and taxonomic differences across regions. While overall diversity metrics did not differ significantly between domestic and feral cats, hierarchical modelling of species communities, accounting for geographic and sex covariates, revealed distinct taxonomic and functional profiles between the two groups. While taxonomic enrichment was balanced, microbial functional capacities were significantly enriched in feral cats. These functional enhancements, particularly in amino acid and lipid degradation, correspond to feral cats dietary reliance on crude protein and fat. Additionally, functional differences were consistent with behavioural contrasts, such as the more aggressive and elusive behaviour measured in feral cats compared to the docile behaviour of domestic cats. Finally, the observed enrichment in short-chain fatty acid, neurotransmitter, and vitamin B12 production in feral cats aligns with improved cognitive function and potentially contributes to their heightened aggression and elusiveness. Our findings suggest that microbiome shifts may play a significant role in the development of physiological and behavioural traits advantageous for a feral lifestyle, supporting the adaptive success of feral cats in the wild.

evolutionary biology↗

bioRxiv2024

Mechanism of neurodegeneration mediated by clonal inflammatory microglia

Langerhans cell Histiocytosis (LCH) and Erdheim-Chester disease (ECD) are clonal myeloid disorders, associated with MAP-Kinase activating mutations and an increased risk of neurodegeneration. Surprisingly, we found pervasive PU.1+ microglia mutant clones across the brain of LCH and ECD patients with and without neurological symptoms, associated with microgliosis, reactive astrocytosis, and neuronal loss. The disease predominated in the grey nuclei of the rhombencephalon, a topography attributable to a local proliferative advantage of mutant microglia. Presence of clinical symptoms was associated with a longer evolution of the disease and a larger size of PU.1+ clones (p= 0.0003). Genetic lineage tracing of PU.1+ clones suggest a resident macrophage lineage or a bone marrow precursor origin depending on patients. Finally, a CSF1R-inhibitor depleted mutant microglia and limited neuronal loss in mice suggesting an alternative to MAPK inhibitors. These studies characterize a progressive neurodegenerative disease, caused by clonal proliferation of inflammatory microglia (CPIM), with a decade(s)-long preclinical stage of incipient disease that represent a therapeutic window for prevention of neuronal death.

immunology↗

bioRxiv2024

Quantifying microbial DNA in metagenomes improves microbial trait estimation

Shotgun metagenomics is a powerful tool for studying the genomic traits of microbial community members, such as genome size, gene content, etc. While such traits can be used to better understand the ecology and evolution of microbial communities, the accuracy of their estimations can be critically influenced by both known and unknown factors. One factor that can bias trait estimations is the proportion of eukaryotic DNA in a metagenome, as some bioinformatic tools assume that all DNA reads in a metagenome are non-eukaryotic. Here, we help resolve a recent debate about the influence of eukaryotic DNA in the estimation of average genome size from a global soil sample dataset using a new bioinformatic tool. Contrary to what was assumed, our reanalysis of this dataset revealed that soil samples can contain a substantial proportion of eukaryotic DNA ([~]38.8%), which severely inflated average genome size estimates. We report that correcting for this bias significantly improves the statistical support for the negative relationship between average bacterial genome size and soil pH. These results highlight that metagenomes can contain large quantities of eukaryotic DNA, and that new methods that correct for this can improve microbial trait estimation.

microbiology↗

bioRxiv2024

Large-scale estimation of bacterial and archaeal DNA prevalence in metagenomes reveals biome-specific patterns

Metagenomes often contain many reads derived from eukaryotes. However, there is usually no reliable method for estimating the prevalence of non-microbial reads in a metagenome, forcing many analysis techniques to make the often-faulty assumption that all reads are microbial. For instance, the success of metagenome-assembled genome (MAG) recovery efforts is assessed by the number of reads mapped to recovered MAGs, a procedure which will underestimate the true fidelity if eukaryotic reads are present. Here we present "SingleM microbial_fraction" (SMF), a scalable algorithm that robustly estimates the number of bacterial and archaeal reads in a metagenome, and the average microbial genome size. SMF does not use eukaryotic reference genome data and can be applied to any Illumina metagenome. Based on SMF, we propose the "Domain-Adjusted Mapping Rate" (DAMR) as an improved metric to assess microbial genome recovery from metagenomes. We benchmark SMF on simulated and real data, and demonstrate how DAMRs can guide genome recovery. Applying SMF to 136,284 publicly available metagenomes, we report substantial variation in microbial fractions and biome-specific patterns of microbial abundance, providing insights into how microorganisms and eukaryotes are distributed across Earth. Finally, we show that substantial amounts of human host DNA sequence data have been deposited in public metagenome repositories, possibly counter to ethical directives that mandate screening of these reads prior to release. As the adoption of metagenomic sequencing continues to grow, we foresee SMF being a valuable tool for the appraisal of genome recovery efforts, and the recovery of global patterns of microorganism distribution.

bioinformatics↗

bioRxiv2024

A microglia clonal inflammatory disorder in Alzheimer's Disease

Somatic genetic heterogeneity resulting from post-zygotic DNA mutations is widespread in human tissues and can cause diseases, however few studies have investigated its role in neurodegenerative processes such as Alzheimers Disease (AD). Here we report the selective enrichment of microglia clones carrying pathogenic variants, that are not present in neuronal, glia/stromal cells, or blood, from patients with AD in comparison to age-matched controls. Notably, microglia-specific AD-associated variants preferentially target the MAPK pathway, including recurrent CBL ring-domain mutations. These variants activate ERK and drive a microglia transcriptional program characterized by a strong neuro-inflammatory response, both in vitro and in patients. Although the natural history of AD-associated microglial clones is difficult to establish in human, microglial expression of a MAPK pathway activating variant was previously shown to cause neurodegeneration in mice, suggesting that AD-associated neuroinflammatory microglial clones may contribute to the neurodegenerative process in patients. One-Sentence SummaryA subset of Alzheimer Disease patients carry mutant microglia somatic clones which promote neuro-inflammation.

neuroscience↗

bioRxiv2023

A comparison of short-read, HiFi long-read, and hybrid strategies for genome-resolved metagenomics

Shotgun metagenomics enables the reconstruction of complex microbial communities at a high level of detail. Such an approach can be conducted using both short-read and long-read sequencing data, as well as a combination of both. To assess the pros and cons of these different approaches, we used 22 faecal DNA extracts collected weekly for 11 weeks from two respective lab mice to study seven performance metrics over four combinations of sequencing depth and technology: i) 20 Gbp of Illumina short-read data, ii) 40 Gbp of short-read data, iii) 20 Gbp of PacBio HiFi long-read data, and iv) 40 Gbp of hybrid (20 Gbp of short-read + 20 Gbp of long-read) data. No strategy was best for all metrics, but instead, each one excelled across different metrics. The long-read approach yielded the best assembly statistics, with the highest N50 and lowest number of contigs. The 40 Gbp short-read approach yielded the highest number of refined bins. Finally, the hybrid approach yielded the longest assemblies, and the highest mapping rate to the bacterial genomes. Our results suggest that while long-read sequencing significantly improves the quality of reconstructed bacterial genomes, it is more expensive and requires deeper sequencing than short-read approaches to recover a comparable amount of reconstructed genomes. The most optimal strategy is study-specific, and depends on how researchers assess the tradeoff between the quantity and quality of recovered genomes. ImportanceOur understanding of microbial communities is limited by the technologies we employ. Here, we test several different DNA sequencing techniques to better understand the pros and cons of each. Long read DNA sequencing allowed for the reconstruction of higher quality and even complete microbial genomes, however, the cost was greater than commonly used short-read DNA sequencing. We suggest researchers consider the trade-offs between each method and decide based on the goals of their research question/s.

microbiology↗

bioRxiv2021

Recovering high-quality host genomes from gut metagenomic data through genotype imputation

Metagenomic data sets of host-associated microbial communities often contain host DNA that is usually discarded because the amount of data is too low for accurate host genetic analyses. However, if a reference panel is available, genotype imputation can be employed to reconstruct host genotypes and maximise the use of such a priori useless data. We tested the performance of a two-step strategy to input genotypes from four types of reference panels, comprised of deeply sequenced chickens to low-depth host genome (~2x coverage) data recovered from metagenomic samples of chicken intestines. The target chicken population was formed by two broiler breeds and the four reference panels employed were (i) an internal panel formed by population-specific individuals, (ii) an external panel created from a public database, (iii) a combined panel of the previous two, and (iv) a diverse panel including more distant populations. Imputation accuracy was high for all tested panels (concordance >0.90), although samples with coverage under 0.28x consistently showed the lowest accuracies. The best imputation performance was achieved by the combined panel due to the high number of imputed variants, including low-frequency ones. However, common population genetics parameters measured to characterise the chicken populations, including observed heterozygosity, nucleotide diversity, pairwise distances and kinship, were only minimally affected by panel choice, with all four panels yielding suitable results for host population characterization and comparison. Likewise, genome scans between the two studied broiler breeds using imputed data with each panel consistently identified the same sweep regions. In conclusion, we show that the applied imputation strategy enables leveraging insofar discarded host DNA to get insights into the genetic structure of host populations, and in doing so, facilitate the implementation of hologenomic approaches that jointly analyse host genomic and microbial metagenomic data. Author summaryWe introduce and assess a methodological approach that enables recovering animal genomes from complex mixtures of metagenomic data, and thus expand the portfolio of analyses that can be conducted from samples such as faeces and gut contents. Metagenomic data sets of host-associated microbial communities often contain DNA of the host organism. The principal drawback to use this data for host genomic characterisation is the low percentage and quality of the host DNA. In order to leverage this data, we propose a two-step imputation method, to recover high-density of variants. We tested the pipeline in a chicken metagenomic dataset, validated imputation accuracy statistics, and studied common population genetics parameters to assess how these are affected by genotype imputation and choice of reference panel. Being able to analyse both domains from the same data set could considerably reduce sampling and laboratory efforts and resources, thereby yielding more sustainable practices for future studies that embrace a hologenomic approach that jointly analyses animal genomic and microbial metagenomic features.

genomics↗

bioRxiv2019

Diet diversification shapes broad-scale distribution patterns in European bats

Large-scale species distributions have been traditionally attributed to physiological traits related to abiotic factors, while behavioural features linked to biotic interactions have received little attention. We tested the relationship between trophic and spatial niche breadths through combining species distribution modelling with dietary DNA metabarcoding of over 400 bats sampled across Europe belonging to seven species. Our results point to a causality cascade between hunting plasticity, trophic niche breadth and spatial niche breadth, and thus indicate that behavioral plasticity and dietary diversification can contribute to shaping broad-scale species distributions.

ecology↗

bioRxiv2019

hilldiv: an R package for the integral analysis of diversity based on Hill numbers

O_LIHill numbers provide a powerful framework for measuring, estimating, comparing and partitioning the diversity of biological systems as characterised using high throughput DNA sequencing approaches. However, the implementation of Hill numbers in this context remains limited. C_LIO_LIIn order to facilitate the implementation of Hill numbers into such analyses, whether focussing on diet reconstruction, microbial community profiling or more general ecosystem characterisation analyses, we present a new R package. Hilldiv provides a set of functions to assist analysis of diversity based on Hill numbers, using OTU tables and associated phylogenetic trees as inputs. C_LIO_LIMultiple functionalities of the library are introduced, including (phylo)diversity measurement, (phylo)diversity profile plotting, (phylo)diversity comparison between samples and groups, (phylo)diversity partitioning and (dis)similarity measurement. All of these are grounded in abundance-based and incidence-based Hill numbers. C_LIO_LIWe provide a supplement that demonstrates the packages main functions using an OTU table representing the diet of eight bat species. The package can be directly installed from github (https://github.com/anttonalberdi/hilldiv). C_LI

ecology↗