Coupling statistics and multi-omics to gain new insights in the determinants of anaerobic microbial bioprocess stability – STABILICS

The objective of STABILICS is to perform a series of longitudinal multi-omics experiments, with unprecedented sampling depth, in anaerobic digesters subjected to constant environmental parameters or different pattern disturbances created by the addition of NaCl.
For this, experiments in semi-continuous laboratory reactors will be set up and monitored over the long term (over a year). Two levels of analysis will be applied. 1) High frequency analysis of different descriptors of microbiome activity, using untargeted metabolomic analyzes to characterize degradation pathways and using RNA and DNA metabarcoding to target active and present microorganisms. 2) An in-depth analysis of the functioning of the microbiome with metagenomic approaches on selected samples and conditions.
These unprecedented datasets will be thoroughly analyzed and integrated using state-of-the-art statistical methods. For example, multivariate dimension reduction methods will be used to integrate omics data and select variables of interest. A specific analytical method will be developed to process longitudinal data.
These highly interdisciplinary approaches will allow 1) to evaluate at different omic levels the dynamics of the AD microbiome in repeated experiments and over the long term, 2) to describe the succession of events which, in the event of disturbance, leads to a imbalance of the microbiome and the digester 3) to propose an original analytical framework for longitudinal multi-omic studies taking into account temporality and 4) to provide generic knowledge allowing a better understanding of the determinants of AD stability.

coming soon

coming soon

coming soon

Anaerobic digestion (AD) is a microbiological process of degradation of the organic matter which produces biogas rich in methane that can be converted into valuable electrical and thermal energy. It is commonly used to manage different types of organic waste at industrial scale using anaerobic digesters. However, this bioprocess is not fully mastered and still has an important potential for improvement. One of the major limitations of AD is the important susceptibility of the microbial communities to changes in operational conditions of the digesters. It can lead to unstable methane formation. Controlling AD microbial community stability, though, is not a trivial task. Knowledge on the determinants of anaerobic microbial process stability (i.e. the conditions and the succession of microbial events that allow maintaining a balance after a disruption or, on the contrary, that generate a domino effect leading to total failure) over time is still missing. Emerging omics high-throughput approaches can now lead to unprecedented data to portray AD microbiome. Metagenomics, metatranscriptomics, metaproteomics and metabolomics enable to describe a community at different levels (genes, gene expression, and metabolites production). Appropriate and efficient analytical methods are required to analyse these big and complex data and unravel the intricate networks of functional processes of AD. Novel computational and statistical methods are progressively becoming available to fully harvest and integrate these complex datasets. In this context, the aim of STABILICS is to conduct the first sets of high-throughput multi-omics longitudinal experiments, with an unprecedented sampling depth, in anaerobic digesters under constant environmental parameters or subject to different model perturbations created by the addition of NaCl. Experiments in lab-scale semi-continuous reactors will be set-up and monitored in the long run (more than one year). Two levels of analysis will be applied. 1) A high frequency monitoring of different descriptors of microbiota activity, where non-targeted metabolomics and isotopic analyses will characterise the degradation pathways and metabarcoding of RNA and DNA will target both active and present microorganisms. 2) An in-depth monitoring of microbiota functioning with both metagenomics and metatranscriptomics on selected samples and conditions. These unprecedented sets of data will be thoroughly analysed and integrated using cutting-edge statistical methods. For example, multivariate dimension reduction methods will be used for data mining, omics integration and feature selection; specific analytical framework for longitudinal data will be developed. The objectives of this interdisciplinary project will be 1) to evaluate at different omics levels the dynamics of AD microbiome in long term and replicated time course experiments, 2) to describe the succession of events that, under stress, leads to microbiota equilibrium unbalance and digester disruption or on the contrary microbiota equilibrium preservation and maintenance of stability, 3) to propose an original analytical framework of multi-omics longitudinal studies accounting for temporality, and 4) to deliver generic knowledge to understand the determinants of perturbations.