Check here your local time and date
Add the ATLANTIC event to your calendar
Check here your local time and date
Add the PACIFIC event to your calendar
Keynote talk
The Microbe's Master Plan to Control Sperm and Shape Generations
by Prof. Seth Bordenstein
Half of all animal species harbor bacteria and phages in the reproductive tissues, yet the extent to which these microbes influence host biology is often overlooked relative to the microbiomes of guts and roots, for instance. In this talk, I will illuminate (i) the most widespread bacterial symbiosis in the animal kingdom (Wolbachia reproductive symbionts and their phage WO) and (ii) the central dogma underpinnings by which they determine the fate of Drosophila sperm biology to create a symbiosis that is fundamental to host evolution and vector control.
MicroTalks
Rapid species-level metagenome profiling and containment estimation with sylph
Profiling metagenomes against databases allows for the detection and quantification of microbes, even at low abundances where assembly is not possible. We introduce sylph (https://github.com/bluenote-1577/sylph), a metagenome profiler that estimates metagenome-genome average nucleotide identity (ANI) through zero-inflated Poisson k-mer statistics, enabling ANI-based taxa detection. Sylph is the most accurate method on the CAMI2 marine dataset, and compared to Kraken2 for multi-sample profiling, sylph takes 10× less CPU time and uses 30× less memory. Sylph’s ANI estimates provide an orthogonal signal to abundance, enabling an ANI-based metagenome-wide association study for Parkinson’s disease against 289,323 genomes, confirming known butyrate-PD associations at the strain level. Sylph takes < 1 minute and 16 GB of RAM to profile against 85,205 prokaryotic and 2,917,521 viral genomes, detecting 30× more viral sequences in the human gut compared to RefSeq. Sylph offers precise, efficient profiling with accurate ANI estimation for even low-coverage genomes.
Jim Shaw, University of Toronto, Canada; Dana-Farber Cancer Institute, and Harvard Medical School, USA
Link to OA paper: https://doi.org/10.1038/s41587-024-02412-y
Unravelling the microbiome of wild flowering plants: a comparative study of leaves and flowers in alpine ecosystems
Background: While substantial research has explored rhizosphere and phyllosphere microbiomes, knowledge on flower microbiome, particularly in wild plants remains limited. This study explores into the diversity, abundance, and composition of bacterial and fungal communities on leaves and flowers of wild flowering plants in their natural alpine habitat, considering the influence of environmental factors.
Methods: We investigated 50 wild flowering plants representing 22 families across seven locations in Austria. Sampling sites encompassed varied soil types (carbonate/silicate) and altitudes (450–2760 m). Amplicon sequencing to characterize bacterial and fungal communities and quantitative PCR to assess microbial abundance was applied, and the influence of biotic and abiotic factors assessed.
Results: Our study revealed distinct bacterial and fungal communities on leaves and flowers, with higher diversity and richness on leaves (228 fungal and 91 bacterial ASVs) than on flowers (163 fungal and 55 bacterial ASVs). In addition, Gammaproteobacteria on flowers and Alphaproteobacteria on leaves suggests niche specialization for plant compartments. Location significantly shaped both community composition and fungal diversity on both plant parts. Notably, soil type influenced community composition but not diversity. Altitude was associated with increased fungal species diversity on leaves and flowers. Furthermore, significant effects of plant family identity emerged within a subset of seven families, impacting bacterial and fungal abundance, fungal Shannon diversity, and bacterial species richness, particularly on flowers.
Conclusion: This study provides novel insights into the specific microbiome of wild flowering plants, highlighting adaptations to local environments and plant–microbe coevolution. The observed specificity indicates a potential role in plant health and resilience, which is crucial for predicting how microbiomes respond to changing environments, ultimately aiding in the conservation of natural ecosystems facing climate change pressures.
Dinesh Ramakrishnan, Leibniz Institute for Agricultural Engineering and Bioeconomy, Germany
Link to OA paper: https://doi.org/10.1186/s12866-024-03574-0
Selected Talks
Nanopore PCR-free sequencing of eDNA samples leads to detection of Batrachochytrium dendrobatidis in La Mandria Regional Park near Turin, Italy
Health surveillance of wildlife is crucial for the early detection of emerging pathogens. The One Health Integrated Wildlife Monitoring approach combines information from the biotic compo-nents of the ecosystem, disease surveillance on animals (domestic and wild) and data on wild-life population (i.e. abundance or diversity). Environmental detection of pathogens through en-vironmental Nucleic Acids (eNA) methods is a promising component of such programs. In this study, we analysed eight eDNA samples from eigh sampling sites derived from water filtered at eight different irrigation channels inside and outside the La Mandria Regional Park’s fenced-off area near Turin, Italy. We sequenced these samples with Nanopore’s PCR-free native sequenc-ing kit to identify taxonomies that can be informative of candidate species of importance for wildlife populations. Besides F. magna whose presence was detected previously in the same samples, Batrachochytrium dendrobatidis and other candidate pathogens and possible host species have been detected. The latter was confirmed by ddPCR months before its first case being reported in animals.
Amir reza Varzandi, University of Turin, Italy
Link to OA paper: https://doi.org/10.1016/j.scitotenv.2024.170338
Evolution and Functional Potential of Gut Microbiota in Honeybees: A Comparative Metagenomic Approach
Studying gut microbiota evolution across animals is crucial for understanding microbiome ecology and evolution. However, this is hampered by the lack of high-resolution genomic data, especially from natural systems. Honeybees, with their specialized gut microbiota and well-known host ecology and evolutionary history, offer an ideal system for studying this evolution. Using shotgun metagenomics on 200 honeybee workers from five species, we recovered thousands of metagenome-assembled genomes, identifying several novel bacterial species.
Our analysis revealed that microbial communities were mainly host-specific. Yet, we found specialist and generalist bacteria, even among bacterial species within the same genera, with notable variation between host species. Intriguingly, some generalists exhibited host-specificity only at the strain level, suggesting recent host-switch events. Contrary to expectations, we found no evidence of co-diversification between honeybee species and their gut microbiota. Instead, the gut microbiota displayed dynamic patterns of gains, losses, and replacements that could influence key functional traits, such as the degradation of pollen-derived pectin—an important process for honeybee nutrition and health.
These findings advance our understanding of host specificity in gut microbiota-host associations and show that ancient interactions can be maintained in the absence of co-diversification. We also highlight the importance of other factors, such as host distribution and ecology, in driving microbiome diversity. Beyond offering new insights into gut microbiota evolution, our study uncovers the functional potential of the gut microbiota of Asian honeybees, which remained underexplored despite the crucial role of these pollinators in their native ecosystem.
Aiswarya Prasad, University of Lausanne, Switzerland
Link to OA paper: https://doi.org/10.1101/2024.09.11.612390
Differences in metagenome coverage may confound abundance-based and diversity conclusions
Although the importance of rarefying 16S rRNA gene data to the same coverage for reliable comparisons of diversity between samples has been well appreciated, the impact of (shotgun) metagenome coverage (i.e., what fraction of diversity was sequenced) on biological conclusions is commonly overlooked. We demonstrate that uneven coverage can lead to misleading conclusions about which features (e.g., genes, genomes) may differentiate two metagenomes or their diversity comparisons. We outline an approach to minimize this impact.
Borja Aldeguer Riquelme, Georgia Institute of Technology, USA
Link to OA paper: https://doi.org/10.1101/2024.10.10.617679