Microbial genome collection of aerobic granular sludge cultivated in sequencing batch reactors using different carbon source mixtures.

Aerobic granular sludge (AGS) consists of a microbial consortium that has an important role in wastewater treatment. This study investigates AGS microorganisms cultivated in a laboratory-scale sequencing batch reactor. Metagenomic sequencing was conducted using PacBio and Illumina, resulting in 759 metagenome-assembled genomes, 331 of which remained after dereplication.

Environment rather than breed or body site shapes the skin bacterial community of healthy sheep as revealed by metabarcoding.

BACKGROUND: The skin is inhabited by a variety of micro-organisms, with bacteria representing the predominant taxon of the skin microbiome. In sheep, the skin bacterial community of healthy animals has been addressed in few studies, only with culture-based methods or sequencing of cloned amplicons. OBJECTIVES: The objectives of this study were to determine the sheep skin bacterial community composition by using metabarcoding for a detailed characterisation and to determine the effect of body part, breed and environment. MATERIALS AND METHODS: Overall, 267 samples were taken from 89 adult female sheep, belonging to three different breeds and kept on nine different farms in Switzerland. From every individual, one sample each was taken from belly, left ear and left leg and metabarcoding of the 16S rRNA V3-V4 hypervariable region was performed. RESULTS: The main phyla identified were Actinobacteriota, Firmicutes, Proteobacteria and Bacteriodota. The alpha diversity as determined by Shannon's diversity index was significantly different between sheep from different farms. Beta diversity analysis by principal coordinate analysis (PCoA) showed clustering of the samples by farm and body site, while breed had only a marginal influence. A sparse partial least squares discriminant analysis (sPLS-DA) revealed seven main groups of operational taxonomic units (OTUs) of which groups of OTUs were specific for some farms. CONCLUSIONS AND CLINICAL RELEVANCE: These findings indicate that environment has a larger influence on skin microbial variability than breed, although the sampled breeds, the most abundant ones in Switzerland, are phenotypically similar. Future studies on the sheep skin microbiome may lead to novel insights in skin diseases and prevention.

Deterministic processes drive the microbial assembly during the recovery of an anaerobic digester after a severe ammonia shock.

Anaerobic digestion allows to produce sustainable energy but the microbial community involved in this process is highly sensitive to perturbations. In this study, a longitudinal experiment was performed in two sets of triplicate bioreactors to evaluate the influence of ammonia addition on AD microbiome and its recovery. Zeolite was added in three reactors to mitigate the inhibition. Microbial dynamics were monitored with 16S rRNA sequencing at 15 time points. Dominant methanogenic pathways were determined with gas isotopic signature analysis. Zeolite addition did not enable to reduce ammonia inhibition or improve the process under the conditions tested. In all the bioreactors, ammonia inhibition sharply decreased the methane production but the process could restart thanks to the increase of hydrogenotrophic archaea and syntrophic bacteria. Interestingly, similar behaviour was observed in the six reactors. Neutral modelling and null model were used and showed that a deterministic process governed the recovery of AD microbiome after failure.

Zeolite favours propionate syntrophic degradation during anaerobic digestion of food waste under low ammonia stress.

Zeolite addition has been widely suggested for its ability to overcome ammonia stress occurring during anaerobic digestion. However little is known regarding the underlying mechanisms of mitigation and especially how zeolite influences the microbial structuration. The aim of this study was to bring new contributions on the effect of zeolite on the microbial community arrangement under a low ammonia stress. Replicated batch experiments were conducted. The microbial population was characterised with 16S sequencing. Methanogenic pathways were identified with methane isotopic fractionation. In presence of ammonia, zeolite mitigated the decrease of biogas production rate. Zeolite induced the development of Izimaplasmatales order and preserved Peptococcaceae family members, known as propionate degraders. Moreover methane isotopic fractionation showed that hydrogenotrophic methanogenesis was maintained in presence of zeolite under ammonia low stress. Our results put forward the benefit of zeolite to improve the bacteria-archaea syntrophy needed for propionate degradation and methane production under a low ammonia stress.

Integrative Analyses to Investigate the Link between Microbial Activity and Metabolite Degradation during Anaerobic Digestion.

Anaerobic digestion (AD) is a promising biological process that converts waste into sustainable energy. To fully exploit AD's capability, we need to deepen our knowledge of the microbiota involved in this complex bioprocess. High-throughput methodologies open new perspectives to investigate the AD process at the molecular level, supported by recent data integration methodologies to extract relevant information. In this study, we investigated the link between microbial activity and substrate degradation in a lab-scale anaerobic codigestion experiment, where digesters were fed with nine different mixtures of three cosubstrates (fish waste, sewage sludge, and grass). Samples were profiled using 16S rRNA sequencing and untargeted metabolomics. In this article, we propose a suite of multivariate tools to statistically integrate these data and identify coordinated patterns between groups of microbial and metabolic profiles specific of each cosubstrate. Five main groups of features were successfully evidenced, including cadaverine degradation found to be associated with the activity of microorganisms from the order Clostridiales and the genus Methanosarcina. This study highlights the potential of data integration toward a comprehensive understanding of AD microbiota.

Assessment of the microbial interplay during anaerobic co-digestion of wastewater sludge using common components analysis.

Anaerobic digestion (AD) is used to minimize solid waste while producing biogas by the action of microorganisms. To give an insight into the underlying microbial dynamics in anaerobic digesters, we investigated two different AD systems (wastewater sludge mixed with either fish or grass waste). The microbial activity was characterized by 16S RNA sequencing. 16S data is sparse and dispersed, and existent data analysis methods do not take into account this complexity nor the potential microbial interactions. In this line, we proposed a data pre-processing pipeline addressing these issues while not restricting only to the most abundant microorganisms. The data were analyzed by Common Components Analysis (CCA) to decipher the effect of substrate composition on the microorganisms. CCA results hinted the relationships between the microorganisms responding similarly to the AD physicochemical parameters. Thus, in overall, CCA allowed a better understanding of the inter-species interactions within microbial communities.

Assessment of substrate biodegradability improvement in anaerobic Co-digestion using a chemometrics-based metabolomic approach.

Anaerobic co-digestion (AcoD) can increase methane production of anaerobic digesters in plants treating wastewater sludge by improving the nutrient balance needed for the microorganisms to grow in the digesters, resulting in a faster process stabilization. Substrate mixture proportions are usually optimized in terms of biogas production, while the metabolic biodegradability of the whole mixture is neglected in this optimisation. In this aim, we developed a strategy to assess AcoD using metabolomics data. This strategy was explored in two different systems. Specifically, we investigated the co-digestion of wastewater sludge with different proportions of either grass or fish waste using untargeted High Performance Liquid Chromatography coupled to Mass Spectrometry (HPLC-MS) metabolomics and chemometrics methods. The analysis of these data revealed that adding grass waste did not improve the metabolic biodegradability of wastewater sludge. Conversely, a synergistic effect in the metabolic biodegradability was observed when fish waste was used, this effect being the highest for 25% of fish waste. In conclusion, metabolomics can be regarded as a promising tool both for characterizing the biochemical processes occurring during anaerobic digestion, and for providing a better understanding of the anaerobic digestion processes.

Co-digestion of wastewater sludge: Choosing the optimal blend.

Anaerobic co-digestion (AcoD) is a promising strategy to increase the methane production of anaerobic digestion plants treating wastewater sludge (WAS). In this work the degradability of six different mixtures of WAS with fish waste (FW) or garden-grass (GG) was evaluated and compared to the three mono-digestions. Degradation performances and methanogenic pathways, determined with the isotopic signatures of biogas, were compared across time. Fish and grass mono-digestion provided a higher final methane production than WAS mono-digestion. In co-digestion the addition of 25% of fish was enough to increase the final methane production from WAS while 50% of grass was necessary. To determine the optimal blend of WAS co-digestion two indicators were specifically designed, representing the maximum potential production (ODI) and the expected production in mono-digestion conditions (MDI). The comparison between these indicators and the experimental results showed that the most productive blend was composed of 75% of co-substrate, fish or grass, with WAS. Indeed, the final methane production was increased by 1.9 times with fish and by 1.7 times with grass associated to an increase of the methane production rate by 1.5 times. Even if the same succession of methanogenic pathways across time was observed for the different mixtures, their relative proportions were different. Sewage sludge degradation was mostly achieved through hydrogenotrophic pathway while acetoclastic pathway was dominant for fish and grass degradation. These results were confirmed by the identification of Archaea with 16S sequencing.

Shotgun metaproteomic profiling of biomimetic anaerobic digestion processes treating sewage sludge.

Two parallel anaerobic digestion lines were designed to match a "bovid-like" digestive structure. Each of the lines consisted of two continuous stirred tank reactors placed in series and separated by an acidic treatment step. The first line was inoculated with industrial inocula whereas the second was seeded with cow digestive tract contents. After 3 months of continuous sewage sludge feeding, samples were recovered for shotgun metaproteomic and DNA-based analysis. Strikingly, protein-inferred and 16S ribosomal DNA tags based taxonomic community profiles were not consistent. PCA however revealed a similar clustering pattern of the samples, suggesting that reproducible methodological and/or biological factors underlie this observation. The performances of the two digestion lines did not differ significantly and the cow-derived inocula did not establish in the reactors. A low throughput metagenomic dataset (3.4 × 10(6) reads, 1.1 Gb) was also generated for one of the samples. It allowed a substantial increase of the analysis depth (11 vs. 4% of spectral identification rate for the combined samples). Surprisingly, a high proportion of proteins from members of the "Candidatus Competibacter" group, a key microbial player usually found in activated sludge plants, was retrieved in our anaerobic digester samples. Data are available via ProteomeXchange with identifier PXD002420 (http://proteomecentral.proteomexchange.org/dataset/PXD002420).