Forecasting the dynamics of a complex microbial community using integrated meta-omics.

peer reviewedPredicting the behaviour of complex microbial communities is challenging. However, this is essential for complex biotechnological processes such as those in biological wastewater treatment plants (BWWTPs), which require sustainable operation. Here we summarize 14 months of longitudinal meta-omics data from a BWWTP anaerobic tank into 17 temporal signals, explaining 91.1% of the temporal variance, and link those signals to ecological events within the community. We forecast the signals over the subsequent five years and use 21 extra samples collected at defined time intervals for testing and validation. Our forecasts are correct for six signals and hint on phenomena such as predation cycles. Using all the 17 forecasts and the environmental variables, we predict gene abundance and expression, with a coefficient of determination ≥0.87 for the subsequent three years. Our study demonstrates the ability to forecast the dynamics of open microbial ecosystems using interactions between community cycles and environmental parameters.R-AGR-0369 - ATTRACT A09/03 Sysbionama (01/02/2010 - 31/01/2015) - WILMES Pau

ASaiM-MT: A validated and optimized ASaiM workflow for metatranscriptomics analysis within Galaxy framework

The Earth Microbiome Project (EMP) aided in understanding the role of microbial communities and the influence of collective genetic material (the 'microbiome') and microbial diversity patterns across the habitats of our planet. With the evolution of new sequencing technologies, researchers can now investigate the microbiome and map its influence on the environment and human health. Advances in bioinformatics methods for next-generation sequencing (NGS) data analysis have helped researchers to gain an in-depth knowledge about the taxonomic and genetic composition of microbial communities. Metagenomic-based methods have been the most commonly used approaches for microbiome analysis; however, it primarily extracts information about taxonomic composition and genetic potential of the microbiome under study, lacking quantification of the gene products (RNA and proteins). On the other hand, metatranscriptomics, the study of a microbial community's RNA expression, can reveal the dynamic gene expression of individual microbial populations and the community as a whole, ultimately providing information about the active pathways in the microbiome. In order to address the analysis of NGS data, the ASaiM analysis framework was previously developed and made available via the Galaxy platform. Although developed for both metagenomics and metatranscriptomics, the original publication demonstrated the use of ASaiM only for metagenomics, while thorough testing for metatranscriptomics data was lacking. In the current study, we have focused on validating and optimizing the tools within ASaiM for metatranscriptomics data. As a result, we deliver a robust workflow that will enable researchers to understand dynamic functional response of the microbiome in a wide variety of metatranscriptomics studies. This improved and optimized ASaiM-metatranscriptomics (ASaiM-MT) workflow is publicly available via the ASaiM framework, documented and supported with training material so that users can interrogate and characterize metatranscriptomic data, as part of larger meta-omic studies of microbiomes

Embryonic and induced pluripotent stem cells: understanding, creating, and exploiting the nano-niche for regenerative medicine.

Embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) have the capacity to differentiate into any specialized cell type of the human body, and therefore, ESC/iPSC-derived cell types offer great potential for regenerative medicine. However, key to realizing this potential requires a strong understanding of stem cell biology, techniques to maintain stem cells, and strategies to manipulate cells to efficiently direct cell differentiation toward a desired cell type. As nanoscale science and engineering continues to produce novel nanotechnology platforms, which inform, infiltrate, and impinge on many aspects of everyday life, it is no surprise that stem cell research is turning toward developments in nanotechnology to answer research questions and to overcome obstacles in regenerative medicine. Here we discuss recent advances in ESC and iPSC manipulation using nanomaterials and highlight future challenges within this area of research

Roles of bacteriophages, plasmids and CRISPR immunity in microbial community dynamics revealed using time-series integrated meta-omics

Viruses and plasmids (invasive mobile genetic elements (iMGEs)) have important roles in shaping microbial communities, but their dynamic interactions with CRISPR-based immunity remain unresolved. We analysed generation-resolved iMGE-host dynamics spanning one and a half years in a microbial consortium from a biological wastewater treatment plant using integrated meta-omics. We identified 31 bacterial metagenome-assembled genomes encoding complete CRISPR-Cas systems and their corresponding iMGEs. CRISPR-targeted plasmids outnumbered their bacteriophage counterparts by at least fivefold, highlighting the importance of CRISPR-mediated defence against plasmids. Linear modelling of our time-series data revealed that the variation in plasmid abundance over time explained more of the observed community dynamics than phages. Community-scale CRISPR-based plasmid-host and phage-host interaction networks revealed an increase in CRISPR-mediated interactions coinciding with a decrease in the dominant 'Candidatus Microthrix parvicella' population. Protospacers were enriched in sequences targeting genes involved in the transmission of iMGEs. Understanding the factors shaping the fitness of specific populations is necessary to devise control strategies for undesirable species and to predict or explain community-wide phenotypes.status: publishe

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

Van Den Bossche T, Kunath BJ, Schallert K, et al. Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows. Nature Communications. 2021;12(1): 7305.**Abstract** Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments