Project description:Bio-augmentation could be a promising strategy to improve processes for treatment and resource recovery from wastewater. In this study, the Gram-positive bacterium Bacillus subtilis was co-cultured with the microbial communities present in wastewater samples with high concentrations of nitrate or ammonium. Glucose supplementation (1%) was used to boost biomass growth in all wastewater samples. In anaerobic conditions, the indigenous microbial community bio-augmented with B. subtilis was able to rapidly remove nitrate from wastewater. In these conditions, B. subtilis overexpressed nitrogen assimilatory and respiratory genes including NasD, NasE, NarG, NarH, and NarI, which arguably accounted for the observed boost in denitrification. Next, we attempted to use the the ammonium- and nitrate-enriched wastewater samples bio-augmented with B. subtilis in the cathodic compartment of bioelectrochemical systems (BES) operated in anaerobic condition. B. subtilis only had low relative abundance in the microbial community, but bio-augmentation promoted the growth of Clostridium butyricum and C. beijerinckii, which became the dominant species. Both bio-augmentation with B. subtilis and electrical current from the cathode in the BES promoted butyrate production during fermentation of glucose. A concentration of 3.4 g/L butyrate was reached with a combination of cathodic current and bio-augmentation in ammonium-enriched wastewater. With nitrate-enriched wastewater, the BES effectively removed nitrate reaching 3.2 mg/L after 48 h. In addition, 3.9 g/L butyrate was produced. We propose that bio-augmentation of wastewater with B. subtilis in combination with bioelectrochemical processes could both boost denitrification in nitrate-containing wastewater and enable commercial production of butyrate from carbohydrate- containing wastewater, e.g. dairy industry discharges. These results suggest that B. subtilis bio-augmentation in our BES promotes simultaneous wastewater treatment and butyrate production.
Project description:Nucleic acids in wastewater provide a rich source of data for detection and surveillance of microbes. We have longitudinally collected 116 RNA samples from a wastewater treatment plant in Berlin/Germany, from March 2021 to July 2022, and 24 DNA samples from May to July 2022. We tracked human astroviruses, enteroviruses, noroviruses and adenoviruses over time to the level of strains or even individual nucleotide variations, showing how detailed human pathogens can be observed using wastewater. For respiratory pathogens, a broad enrichment panel enabled us to detect waves of RSV, influenza, or common cold coronaviruses in high agreement with clinical data. By applying a profile Hidden Markov Model-based search for novel viruses, we identified more than 100 thousand novel transcript assemblies likely not belonging to known virus species, thus substantially expanding our knowledge of virus diversity. Phylogenetic analysis is shown for bunyaviruses and parvoviruses. Finally, we identify Hundreds of novel protein sequences for CRISPR-associated proteins such as Transposase B, a class of small RNA-guided DNA editing enzymes. Taken together, we present a longitudinal and deep investigation into wastewater-derived genomic sequencing data that underlines the value of sewage surveillance for public health, planetary virome research, and biotechnological potential.
Project description:Wastewater-based epidemiology has been revealed as a powerful approach for the survey of the population's health and lifestyle. In this context, proteins have been proposed as potential biomarkers that complement the information provided by those used up to now (small exogenous molecules, metabolites, and genomic material). However, few is known about the range of molecular species and dynamics of proteins in wastewater and the information hidden in these protein profiles is still to be uncovered. In previous research, we have described for the first time the proteome of wastewater using polymer probes immersed in wastewater at the entrance of a wastewater treatment plant (WWTP). Here, we studied the protein composition of wastewater from municipalities with diverse population and industrial activities. For this purpose, we collected water samples at the inlet of 10 different WWTPs in Catalonia at three different times of the year and the soluble fraction of this material was then analyzed by Liquid Chromatography High-resolution Tandem Mass Spectrometry using a shotgun proteomics approach. The complete proteomic profiles, the distribution among different organisms, and the semiquantitative analysis of the main constituents are described. Excreta (urine and feces) from humans, and blood and other residues from livestock were identified as the two main protein sources. Significant differences between the proteomes in the soluble phase and the particulate material, respectively dominated by eukaryote and bacterial proteins, were observed. Our findings provide new insights into the characterization of wastewater proteomics that allow proposing specific bioindicators for wastewater-based environmental monitoring, including human and animal population monitoring, most notably, for rodent pest control (immunoglobulins, amylases), and livestock processing industry monitoring (albumins).
Project description:Characterization of microbial communities at the genomic, transcriptomic, proteomic and metabolomic levels, with a special interest on lipid accumulating bacterial populations, which are naturally enriched in biological wastewater treatment systems and may be harnessed for the conversion of mixed lipid substrates (wastewater) into biodiesel. The project aims to elucidate the genetic blueprints and the functional relevance of specific populations within the community. It focuses on within-population genetic and functional heterogeneity, trying to understand how fine-scale variations contribute to differing lipid accumulating phenotypes. Insights from this project will contribute to the understanding the functioning of microbial ecosystems, and improve optimization and modeling strategies for current and future biological wastewater treatment processes. This project contains datasets derived from the same biological wastewater treatment plant. The data includes metagenomes, metatranscriptomes, metaproteomes and organisms isolated in pure cultures. Characterization of microbial communities at the genomic, transcriptomic, proteomic and metabolomic levels, with a special interest on lipid accumulating bacterial populations, which are naturally enriched in biological wastewater treatment systems and may be harnessed for the conversion of mixed lipid substrates (wastewater) into biodiesel. The project aims to elucidate the genetic blueprints and the functional relevance of specific populations within the community. It focuses on within-population genetic and functional heterogeneity, trying to understand how fine-scale variations contribute to differing lipid accumulating phenotypes. Insights from this project will contribute to the understanding the functioning of microbial ecosystems, and improve optimization and modeling strategies for current and future biological wastewater treatment processes. This project contains datasets derived from the same biological wastewater treatment plant. The data includes metagenomes, metatranscriptomes, metaproteomes and organisms isolated in pure cultures.
Project description:Phosphorus (P) limitation will play a key role in the productivity of agriculture in the coming decades. Struvite is an ammonium magnesium phosphate mineral that can be recovered from wastewater-treatment plants and can be considered as an alternative source of P. However, the impact of struvite on the plant yield and, particularly, on the soil microbial community is barely known. Here, we tested the impacts of struvite, sewage sludge, and their combination on the barley yield, soil macro and micronutrients, and biochemical and microbiological soil properties. Amendment with struvite alone and its combination with sludge increased the availability of P in soil, the plant uptake of P and Mg, and the barley yield. The analysis of phospholipid fatty acids (PLFAs) and metaproteomics approaches revealed significant effects of struvite on the biomass of Gram-positive bacteria and, particularly, on actinobacterial populations in soil.
Project description:Advances in DNA sequencing technologies has drastically changed our perception of the structure and complexity of the plant microbiome. By comparison, our ability to accurately identify the metabolically active fraction of soil microbiota and its specific functional role in augmenting plant health is relatively limited. Here, we combined our recently developed protein extraction method and an iterative bioinformatics pipeline to enable the capture and identification of extracellular proteins (metaexoproteomics) synthesised in the rhizosphere of Brassica spp. We first validated our method in the laboratory by successfully identifying proteins related to a host plant (Brassica rapa) and its bacterial inoculant, Pseudomonas putida BIRD-1. This identified numerous rhizosphere specific proteins linked to the acquisition of plant-derived nutrients in P. putida. Next, we analysed natural field-soil microbial communities associated with Brassica napus L. (oilseed rape). By combining metagenomics with metaexoproteomics, 1882 proteins were identified across bulk and rhizosphere samples. Meta-exoproteomics identified a clear shift (p<0.001) in the metabolically active fraction of the soil microbiota responding to the presence of B. napus roots that was not apparent in the composition of the total microbial community (metagenome). This metabolic shift was associated with the stimulation of rhizosphere-specialised bacteria, such as Gammaproteobacteria, Betaproteobacteria and Flavobacteriia and the upregulation of plant beneficial functions related to phosphorus and nitrogen mineralisation. Together, our metaproteomic assessment of the ‘active’ plant microbiome at the field-scale demonstrates the importance of moving past a genomic assessment of the plant microbiome in order to determine ecologically important plant-microbe interactions underpinning plant health.