Baptiste Quentin (doctorant) y a présenté un poster : Microbial dynamics and methanogenic activity during start up of twelve replicated anaerobic digesters
Anaerobic digestion is a promising solution for waste reduction and biogas production. This process is driven by complex microbial communities mainly composed of archaea and bacteria that collaborate to degrade organic matter into methane. However, the evolution of these ecosystems after their start-up is not fully understood in mesophilic conditions. Whether the microbial communities evolution follows a deterministic or a stochastic trajectory is unclear. Knowing it would be useful to better operate anaerobic digesters on the long run.
Twelve replicate semi-continuously fed stirred anaerobic digesters (5L) were set-up and operated in parallel. They were fed with biowaste, whose degradation was monitored by measuring biogas production and VFA concentrations. Metabolic pathway of methane production was determined using measurement of the carbon isotopic fractionation in biogas. Microbial dynamics were followed with sequencing of both DNA and RNA from 104 samples taken at different dates in the 12 digesters during 4 months. This way we got insight on both the present and active microorganisms. Data were analyzed with different multivariate approaches to assess whether microbial community evolution followed stochastic or deterministic trajectories.
A progressive evolution of microbial communities through time was observed in all the digesters. It was correlated between the twelve replicates, which suggests that the set parameters (such as organic loading rate) had a strong deterministic effect on the anaerobic digestion process. Comparison of 16 rRNA gene and rRNA metabarcoding showed that the most abundant microorganisms were not necessarily the most active: for instance, the Nanoarchaeota Woesarcheales was two to four times less abundant in 16rRNA metabarcoding than in 16rRNA gene metabarcoding after ten weeks of digesters monitoring.
Semi-continuously fed stirred anaerobic digestion start-up shows strong deterministic trajectory for its community performances and structures, suggesting that the set parameters are key to the process stability over time.
Ariane Bize (chercheuse) y a présenté un poster : Microbial community dynamics during co-digestion of manure and household waste organic fraction
Organic waste co-digestion is an attractive option for territories to valorize different types of locally-produced waste and to optimize biogas production in digestion plants. We studied dry batch co-digestion of reconstituted horse manure and of the organic fraction of residual household waste, in pilot reactors. We identified optimal proportions of co-substrates and evaluated the effects of the initial proportion on microbial community dynamics.
Reconstituted horse manure (MA) was composed of straw (84.3% in mass), wood chips (14.7%), and horse feces (1%). The second co-substrate was the organic fraction of residual household waste (HW). Batch pilots for dry anaerobic digestion (60 L each) were filled with HW:MA in various proportions (w:w): 0:100, 25:75, 50:50 and 75:25. The co-substrates were fully immersed in digested mixed urban waste water sludge serving both as inoculum and liquid input. The pilots were operated at 37°C during 5 weeks. Each condition was tested once. The conversion dynamics was characterized by measuring relevant physico-chemical parameters: biogas production and composition, pH; volatile fatty acids (VFA) and total alkalinity content. The composition of microbial communities was determined by 16S rDNA metabarcoding targeting the V4-V5 region with universal primers, using an Ion Torrent PGM sequencer. Principal component analysis was performed with R CRAN packages such as FactoMineR.
When co-digesting HW, a transient accumulation of volatile fatty acids (VFA) was observed. Maximal VFA concentrations were all the higher as the initial proportion of HW was important and reached up to ~17 g/L. Moreover, a partial inhibition of methane production occurred in presence of HW, mostly during the 8-15 first days of incubation, especially for proportions 50:50 and 75:25. Overall, the total cumulated production of methane after 35 days was similar for 0:100 or 25:75, whereas it was significantly lower for 50:50 or 75:25. The 16S metabarcoding profiles showed limited changes in 25:75 compared to 0:100. By contrast, major shifts occurred in 50:50 and 75:25, with two types of profiles. One corresponded to the highly inhibited status, in the early incubation phase. The other corresponded to the community adapted to higher levels of VFA production, in the late incubation phase. The archaeal population was especially affected in 50:50 and 75:25, both in abundance and composition.
The modification of the microbial population in relation with anaerobic digestion inhibition opens the perspective of identifying inhibition biomarkers. Further experiments will be carried out in this perspective.
Ariane a aussi fait une communication orale : Mining anaerobic digestion data with DeepOmics and Easy16S, user-friendly tools for environmental engineering meta-omics data
The recent breakthrough of meta-omics offers new perspectives to the field of anaerobic digestion (AD). It promises the deep understanding of microbial communities acting as catalysts and thereby the possibility to develop more cost-effective processes, through the design of operational biomarkers or through ecological engineering approaches. However, the variety of AD processes and operating conditions worldwide is very high. It is therefore difficult to extend the conclusions gained on one specific system. It highlights the need for data collection and organization at a large scale, to perform meta-analyses and to be able to identify robust trends. We present here two new software tools developed to favour data mining of meta-omics data from environmental biotechnologies.
DeepOmics is an n-tier web application: the user interface is a single page application built with the Angular framework. It accesses the data using a RESTful API. Data are stored in a PostgreSQL relational database as well as in an indexation and search engine (Elasticsearch, open-source version). Easy16S is an interactive R shiny interface based on two main R packages, shinydashboard and phyloseq. Easy16S is currently deployed on the INRAE-MIGALE server (https://migale.inrae.fr/).
DeepOmics offers the possibility to upload, request and export 16S metabarcoding data from several environmental biotechnologies together with many relevant associated metadata, especially regarding operating conditions and process design. It also enables the graphical monitoring of analytical data. Data collection is organized by research project: each project coordinator manages the rights associated to its project data (e.g. private, public). Many modules have been developed and are being tested by INRAE users and external partners. Our objective is to open a pilot version of DeepOmics to a wider community in the near future.
Easy16S is a user-friendly web server tool intended for practitioners eager to explore their data and create figures rapidly and interactively. It is specifically focused on the mapping of covariates of interest. Easy16S accepts as entry the classical file formats associated to 16S metabarcoding. The R code lines corresponding to each plot can be copy-pasted from the webpage. Updated on a regular basis, Easy16S is available online (https://genome.jouy.inra.fr/shiny/easy16S/).
To present these tools, we will rely on a practical example of AD inhibition data (Poirier and Chapleur, 2018).
These complementary user-friendly tools should foster data mining of meta-omics data from AD processes, helping to take full advantage of next generation sequencing data and to turn knowledge into operational outputs.