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 fecal 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; 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 trade-off between the quantity and quality of recovered genomes.IMPORTANCEMice are an important model organism for understanding the gut microbiome. When studying these gut microbiomes using DNA techniques, researchers can choose from technologies that use short or long DNA reads. In this study, we perform an extensive benchmark between short- and long-read DNA sequencing for studying mice gut microbiomes. We find that no one approach was best for all metrics and provide information that can help guide researchers in planning their experiments.

A pangenome graph reference of 30 chicken genomes allows genotyping of large and complex structural variants.

BACKGROUND: The red junglefowl, the wild outgroup of domestic chickens, has historically served as a reference for genomic studies of domestic chickens. These studies have provided insight into the etiology of traits of commercial importance. However, the use of a single reference genome does not capture diversity present among modern breeds, many of which have accumulated molecular changes due to drift and selection. While reference-based resequencing is well-suited to cataloging simple variants such as single-nucleotide changes and short insertions and deletions, it is mostly inadequate to discover more complex structural variation in the genome. METHODS: We present a pangenome for the domestic chicken consisting of thirty assemblies of chickens from different breeds and research lines. RESULTS: We demonstrate how this pangenome can be used to catalog structural variants present in modern breeds and untangle complex nested variation. We show that alignment of short reads from 100 diverse wild and domestic chickens to this pangenome reduces reference bias by 38%, which affects downstream genotyping results. This approach also allows for the accurate genotyping of a large and complex pair of structural variants at the K feathering locus using short reads, which would not be possible using a linear reference. CONCLUSIONS: We expect that this new paradigm of genomic reference will allow better pinpointing of exact mutations responsible for specific phenotypes, which will in turn be necessary for breeding chickens that meet new sustainability criteria and are resilient to quickly evolving pathogen threats.

Field and laboratory guidelines for reliable bioinformatic and statistical analysis of bacterial shotgun metagenomic data.

Shotgun metagenomics is an increasingly cost-effective approach for profiling environmental and host-associated microbial communities. However, due to the complexity of both microbiomes and the molecular techniques required to analyze them, the reliability and representativeness of the results are contingent upon the field, laboratory, and bioinformatic procedures employed. Here, we consider 15 field and laboratory issues that critically impact downstream bioinformatic and statistical data processing, as well as result interpretation, in bacterial shotgun metagenomic studies. The issues we consider encompass intrinsic properties of samples, study design, and laboratory-processing strategies. We identify the links of field and laboratory steps with downstream analytical procedures, explain the means for detecting potential pitfalls, and propose mitigation measures to overcome or minimize their impact in metagenomic studies. We anticipate that our guidelines will assist data scientists in appropriately processing and interpreting their data, while aiding field and laboratory researchers to implement strategies for improving the quality of the generated results.

Mammals show distinct functional gut microbiome dynamics to identical series of environmental stressors.

IMPORTANCE: In our manuscript, we report the first interspecific comparative study about the plasticity of the gut microbiota. We conducted a captivity experiment that exposed wild-captured mammals to a series of environmental challenges over 45 days. We characterized their gut microbial communities using genome-resolved metagenomics and modeled how the taxonomic, phylogenetic, and functional microbial dynamics varied across a series of disturbances in both species. Our results indicate that the intrinsic properties (e.g., diversity and functional redundancy) of microbial communities coupled with physiological attributes (e.g., thermal plasticity) of hosts shape the taxonomic, phylogenetic, and functional response of gut microbiomes to environmental stressors, which might influence their contribution to the acclimation and adaptation capacity of animal hosts.

DNA metabarcoding reveals seasonal changes in diet composition across four arthropod-eating lizard species (Phrynosomatidae: Sceloporus).

Diet composition and its ecological drivers are rarely investigated in coexisting closely related species. We used a molecular approach to characterize the seasonal variation in diet composition in four spiny lizard species inhabiting a mountainous ecosystem. DNA metabarcoding revealed that the lizards Sceloporus aeneus, S. bicanthalis, S. grammicus, and S. spinosus mostly consumed arthropods of the orders Hemiptera, Araneae, Hymenoptera, and Coleoptera. The terrestrial lizards S. aeneus and S. bicanthalis mostly predated ants and spiders, whereas the arboreal-saxicolous S. grammicus and saxicolous S. spinosus largely consumed grasshoppers and leafhoppers. The taxonomic and phylogenetic diversity of the prey was higher during the dry season than the rainy season, likely because reduced prey availability in the dry season forced lizards to diversify their diets to meet their nutritional demands. Dietary and phylogenetic composition varied seasonally depending on the species, but only dietary composition varied with altitude. Seasonal dietary turnover was greater in S. spinosus than in S. bicanthalis, suggesting site-specific seasonal variability in prey availability; no other differences among species were observed. S. bicanthalis, which lives at the highest altitude in our study site, displayed interseasonal variation in diet breadth. Dietary differences were correlated with the species' feeding strategies and elevational distribution, which likely contributed to the coexistence of these lizard species in the studied geographic area and beyond.

A species-level trait dataset of bats in Europe and beyond.

Knowledge of species' functional traits is essential for understanding biodiversity patterns, predicting the impacts of global environmental changes, and assessing the efficiency of conservation measures. Bats are major components of mammalian diversity and occupy a variety of ecological niches and geographic distributions. However, an extensive compilation of their functional traits and ecological attributes is still missing. Here we present EuroBaTrait 1.0, the most comprehensive and up-to-date trait dataset covering 47 European bat species. The dataset includes data on 118 traits including genetic composition, physiology, morphology, acoustic signature, climatic associations, foraging habitat, roost type, diet, spatial behaviour, life history, pathogens, phenology, and distribution. We compiled the bat trait data obtained from three main sources: (i) a systematic literature and dataset search, (ii) unpublished data from European bat experts, and (iii) observations from large-scale monitoring programs. EuroBaTrait is designed to provide an important data source for comparative and trait-based analyses at the species or community level. The dataset also exposes knowledge gaps in species, geographic and trait coverage, highlighting priorities for future data collection.

Unravelling animal-microbiota evolution on a chip.

Whether and how microorganisms have shaped the evolution of their animal hosts is a major question in biology. Although many animal evolutionary processes appear to correlate with changes in their associated microbial communities, the mechanistic processes leading to these patterns and their causal relationships are still far from being resolved. Gut-on-a-chip models provide an innovative approach that expands beyond the potential of conventional microbiome profiling to study how different animals sense and react to microbes by comparing responses of animal intestinal tissue models to different microbial stimuli. This complementary knowledge can contribute to our understanding of how host genetic features facilitate or prevent different microbiomes from being assembled, and in doing so elucidate the role of host-microbiota interactions in animal evolution.

Impact of microbial genome completeness on metagenomic functional inference.

Inferring the functional capabilities of bacteria from metagenome-assembled genomes (MAGs) is becoming a central process in microbiology. Here we show that the completeness of genomes has a significant impact on the recovered functional signal, spanning all domains of metabolic functions. We identify factors that affect this relationship between genome completeness and function fullness, and provide baseline knowledge to guide efforts to correct for this overlooked bias in metagenomic functional inference.

Bacterial topography of the upper and lower respiratory tract in pigs.

BACKGROUND: Understanding the complex structures and interactions of the bacterial communities inhabiting the upper (URT) and lower (LRT) respiratory tract of pigs is at an early stage. The objective of this study was to characterize the bacterial topography of three URT (nostrils, choana, and tonsils) and LRT (proximal trachea, left caudal lobe and secondary bronchi) sites in pigs. Thirty-six post-mortem samples from six pigs were analysed by 16S rRNA gene quantification and sequencing, and the microbiota in nostrils and trachea was additionally profiled by shotgun sequencing. RESULTS: The bacterial composition obtained by the two methods was congruent, although metagenomics recovered only a fraction of the diversity (32 metagenome-assembled genomes) due to the high proportion (85-98%) of host DNA. The highest abundance of 16S rRNA copies was observed in nostrils, followed by tonsils, trachea, bronchi, choana and lung. Bacterial richness and diversity were lower in the LRT compared to the URT. Overall, Firmicutes and Proteobacteria were identified as predominant taxa in all sample types. Glasserella (15.7%), Streptococcus (14.6%) and Clostridium (10.1%) were the most abundant genera but differences in microbiota composition were observed between the two tracts as well as between sampling sites within the same tract. Clear-cut differences were observed between nasal and tonsillar microbiomes (R-values 0.85-0.93), whereas bacterial communities inhabiting trachea and lung were similar (R-values 0.10-0.17). Moraxella and Streptococcus were more common in bronchial mucosal scraping than in lavage, probably because of mucosal adherence. The bacterial microbiota of the choana was less diverse than that of the nostrils and similar to the tracheal microbiota (R-value 0.24), suggesting that the posterior nasal cavity serves as the primary source of bacteria for the LRT. CONCLUSION: We provide new knowledge on microbiota composition and species abundance in distinct ecological niches of the pig respiratory tract. Our results shed light on the distribution of opportunistic bacterial pathogens across the respiratory tract and support the hypothesis that bacteria present in the lungs originate from the posterior nasal cavity. Due to the high abundance of host DNA, high-resolution profiling of the pig respiratory microbiota by shotgun sequencing requires methods for host DNA depletion.

A simplified protocol for DNA extraction from FTA cards for faecal microbiome studies.

As metagenomic studies continue to increase in size and complexity, they are often required to incorporate data from geographically isolated locations or longitudinal time samples. This represents a technical challenge, given that many of the commonly used methods used for sample collection, storage, and DNA extraction are sensitive to differences related to the time, storage and chemistry involved. FTA cards have been previously proposed as a simple, reliable and cost-efficient method for the preservation of animal faecal microbiomes. In this study, we report a simplified extraction methodology for recovering microbiome DNA from faeces stored on FTA cards and compare its performance to a common alternative means of characterising such microbiomes; namely, immediate freezing of the faeces followed by DNA extraction using the Qiagen PowerSoil DNA isolation kit. Our results show that overall the application of our simplified DNA extraction methodology yields microbial community results that have higher diversity and an expanded core microbiome than that found using the PowerSoil methodology. This suggests that the FTA card extraction method presented here is a viable alternative for metagenomic studies using faecal material when traditional freeze-based storage methods are not feasible.

Enriching captivity conditions with natural elements does not prevent the loss of wild-like gut microbiota but shapes its compositional variation in two small mammals.

As continued growth in gut microbiota studies in captive and model animals elucidates the importance of their role in host biology, further pursuit of how to retain a wild-like microbial community is becoming increasingly important to obtain representative results from captive animals. In this study, we assessed how the gut microbiota of two wild-caught small mammals, namely Crocidura russula (Eulipotyphla, insectivore) and Apodemus sylvaticus (Rodentia, omnivore), changed when bringing them into captivity. We analyzed fecal samples of 15 A. sylvaticus and 21 C. russula, immediately after bringing them into captivity and 5 weeks later, spread over two housing treatments: a "natural" setup enriched with elements freshly collected from nature and a "laboratory" setup with sterile artificial elements. Through sequencing of the V3-V4 region of the 16S recombinant RNA gene, we found that the initial microbial diversity dropped during captivity in both species, regardless of treatment. Community composition underwent a change of similar magnitude in both species and under both treatments. However, we did observe that the temporal development of the gut microbiome took different trajectories (i.e., changed in different directions) under different treatments, particularly in C. russula, suggesting that C. russula may be more susceptible to environmental change. The results of this experiment do not support the use of microbially enriched environments to retain wild-like microbial diversities and compositions, yet show that specific housing conditions can significantly affect the drift of microbial communities under captivity.

Novel strategies to improve chicken performance and welfare by unveiling host-microbiota interactions through hologenomics.

Fast optimisation of farming practices is essential to meet environmental sustainability challenges. Hologenomics, the joint study of the genomic features of animals and the microbial communities associated with them, opens new avenues to obtain in-depth knowledge on how host-microbiota interactions affect animal performance and welfare, and in doing so, improve the quality and sustainability of animal production. Here, we introduce the animal trials conducted with broiler chickens in the H2020 project HoloFood, and our strategy to implement hologenomic analyses in light of the initial results, which despite yielding negligible effects of tested feed additives, provide relevant information to understand how host genomic features, microbiota development dynamics and host-microbiota interactions shape animal welfare and performance. We report the most relevant results, propose hypotheses to explain the observed patterns, and outline how these questions will be addressed through the generation and analysis of animal-microbiota multi-omic data during the HoloFood project.

Gut microbiota differences between paired intestinal wall and digesta samples in three small species of fish.

The microbial gut communities of fish are receiving increased attention for their relevance, among others, in a growing aquaculture industry. The members of these communities are often split into resident (long-term colonisers specialised to grow in and adhere to the mucus lining of the gut) and transient (short-term colonisers originated from food items and the surrounding water) microorganisms. Separating these two communities in small fish are impeded by the small size and fragility of the gastrointestinal tract. With the aim of testing whether it is possible to recover two distinct communities in small species of fish using a simple sampling technique, we used 16S amplicon sequencing of paired intestinal wall and digesta samples from three small Cyprinodontiformes fish. We examined the diversity and compositional variation of the two recovered communities, and we used joint species distribution modelling to identify microbes that are most likely to be a part of the resident community. For all three species we found that the diversity of intestinal wall samples was significantly lower compared to digesta samples and that the community composition between sample types was significantly different. Across the three species we found seven unique families of bacteria to be significantly enriched in samples from the intestinal wall, encompassing most of the 89 ASVs enriched in intestinal wall samples. We conclude that it is possible to characterise two different microbial communities and identify potentially resident microbes through separately analysing samples from the intestinal wall and digesta from small species of fish. We encourage researchers to be aware that different sampling procedures for gut microbiome characterization will capture different parts of the microbiome and that this should be taken into consideration when reporting results from such studies on small species of fish.

Disentangling host-microbiota complexity through hologenomics.

Research on animal-microbiota interactions has become a central topic in biological sciences because of its relevance to basic eco-evolutionary processes and applied questions in agriculture and health. However, animal hosts and their associated microbial communities are still seldom studied in a systemic fashion. Hologenomics, the integrated study of the genetic features of a eukaryotic host alongside that of its associated microbes, is becoming a feasible - yet still underexploited - approach that overcomes this limitation. Acknowledging the biological and genetic properties of both hosts and microbes, along with the advantages and disadvantages of implemented techniques, is essential for designing optimal studies that enable some of the major questions in biology to be addressed.

Recovering High-Quality Host Genomes from Gut Metagenomic Data through Genotype Imputation.

Metagenomic datasets 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, genotype imputation can be employed to reconstruct host genotypes if a reference panel is available. Here, the performance of a two-step strategy is tested to impute genotypes from four types of reference panels built using different strategies to low-depth host genome data (≈2× coverage) recovered from intestinal samples of two chicken genetic lines. First, imputation accuracy is evaluated in 12 samples for which both low- and high-depth sequencing data are available, obtaining high imputation accuracies for all tested panels (>0.90). Second, the impact of reference panel choice in population genetics statistics on 100 chickens is assessed, all four panels yielding comparable results. In light of the observations, the feasibility and application of the applied imputation strategy are discussed for different species with regard to the host DNA proportion, genomic diversity, and availability of a reference panel. This method enables leveraging insofar discarded host DNA to get insights into the genetic structure of host populations, and in doing so, facilitates the implementation of hologenomic approaches that jointly analyze host and microbial genomic data.

Diversity and compositional changes in the gut microbiota of wild and captive vertebrates: a meta-analysis.

The gut microbiota is recognised as an essential asset for the normal functioning of animal biology. When wild animals are moved into captivity, the modified environmental pressures are expected to rewire the gut microbiota, yet whether this transition follows similar patterns across vertebrates is still unresolved due to the absence of systematic multi-species analyses. We performed a meta-analysis of gut microbiota profiles of 322 captive and 322 wild specimens from 24 vertebrate species. Our analyses yielded no overall pattern of diversity and compositional variation between wild and captive vertebrates, but a heterogeneous landscape of responses, which differed depending on the components of diversity considered. Captive populations showed enrichment patterns of human-associated microorganisms, and the minimal host phylogenetic signal suggests that changes between wild and captive populations are mainly driven by case-specific captivity conditions. Finally, we show that microbiota differences between wild and captive populations can impact evolutionary and ecological inferences that rely on hierarchical clustering-based comparative analyses of gut microbial communities across species.

The role of the gut microbiota in the dietary niche expansion of fishing bats.

BACKGROUND: Due to its central role in animal nutrition, the gut microbiota is likely a relevant factor shaping dietary niche shifts. We analysed both the impact and contribution of the gut microbiota to the dietary niche expansion of the only four bat species that have incorporated fish into their primarily arthropodophage diet. RESULTS: We first compared the taxonomic and functional features of the gut microbiota of the four piscivorous bats to that of 11 strictly arthropodophagous species using 16S rRNA targeted amplicon sequencing. Second, we increased the resolution of our analyses for one of the piscivorous bat species, namely Myotis capaccinii, and analysed multiple populations combining targeted approaches with shotgun sequencing. To better understand the origin of gut microorganisms, we also analysed the gut microbiota of their fish prey (Gambusia holbrooki). Our analyses showed that piscivorous bats carry a characteristic gut microbiota that differs from that of their strict arthropodophagous counterparts, in which the most relevant bacteria have been directly acquired from their fish prey. This characteristic microbiota exhibits enrichment of genes involved in vitamin biosynthesis, as well as complex carbohydrate and lipid metabolism, likely providing their hosts with an enhanced capacity to metabolise the glycosphingolipids and long-chain fatty acids that are particularly abundant in fish. CONCLUSIONS: Our results depict the gut microbiota as a relevant element in facilitating the dietary transition from arthropodophagy to piscivory.

The gut microbiome buffers dietary adaptation in Bronze Age domesticated dogs.

In an attempt to explore the role of the gut microbiome during recent canine evolutionary history, we sequenced the metagenome of 13 canine coprolites dated ca. 3,600-3,450 years ago from the Bronze Age archaeological site of Solarolo (Italy), which housed a complex farming community. The microbiome structure of Solarolo dogs revealed continuity with that of modern dogs, but it also shared some features with the wild wolf microbiome, as a kind of transitional state between them. The dietary niche, as also inferred from the microbiome composition, was omnivorous, with evidence of consumption of starchy agricultural foods. Of interest, the Solarolo dog microbiome was particularly enriched in sequences encoding alpha-amylases and complemented a low copy number of the host amylase gene. These findings suggest that Neolithic dogs could have responded to the transition to a starch-rich diet by expanding microbial functionalities devoted to starch catabolism, thus compensating for delayed host response.

Holo-Omics: Integrated Host-Microbiota Multi-omics for Basic and Applied Biological Research.

From ontogenesis to homeostasis, the phenotypes of complex organisms are shaped by the bidirectional interactions between the host organisms and their associated microbiota. Current technology can reveal many such interactions by combining multi-omic data from both hosts and microbes. However, exploring the full extent of these interactions requires careful consideration of study design for the efficient generation and optimal integration of data derived from (meta)genomics, (meta)transcriptomics, (meta)proteomics, and (meta)metabolomics. In this perspective, we introduce the holo-omic approach that incorporates multi-omic data from both host and microbiota domains to untangle the interplay between the two. We revisit the recent literature on biomolecular host-microbe interactions and discuss the implementation and current limitations of the holo-omic approach. We anticipate that the application of this approach can contribute to opening new research avenues and discoveries in biomedicine, biotechnology, agricultural and aquacultural sciences, nature conservation, as well as basic ecological and evolutionary research.

Comparative Microbiome Analysis Reveals the Ecological Relationships Between Rumen Methanogens, Acetogens, and Their Hosts.

Ruminant methane, which is generated by methanogens through the consumption of hydrogen and supports the normal function of the rumen ecosystem, is a major source of greenhouse gases. Reductive acetogenesis by acetogens is a possible alternative sink that can dispose of hydrogen for acetate production. However, the distribution of rumen methanogens and acetogens along with the relationships among methanogens, acetogens, and their host are poorly understood. Therefore, we investigated the rumen methanogen and acetogen communities of 97 individual animals representing 14 ruminant species within three ruminant families Cervidae (deer), Bovidae (bovid), and Moschidae (musk deer). The results showed that the Methanobrevibacter spp. and acetogens associated with Eubacteriaceae were the most widespread methanogens and acetogens, respectively. However, other methanogens and acetogens exhibited host specificity in the rumen of reindeer and Chinese muntjac deer. Acetogen and methanogen communities were not correlated in these species, and the phylosymbiosis signature between host phylogeny and the composition of both communities was lacking. The abundance of Methanobrevibacter gottschalkii was negatively correlated with the degree of papillation of the rumen wall. Finally, co-occurrence analysis showed that the variation of the predicted methane yields was characterized by the interactive patterns between methanogens, acetogens, and concentrations of rumen metabolites. Our results show that rumen methanogen and acetogen communities have low compositional interdependence and do not exhibit parallel host evolution, which suggests that the strategies for mitigating methane production should be based on a species-specific rumen microbiota analysis.