Genome-resolved metagenome and metatranscriptome analyses of thermophilic composting reveal key bacterial players and their metabolic interactions.

BACKGROUND: Composting is an important technique for environment-friendly degradation of organic material, and is a microbe-driven process. Previous metagenomic studies of composting have presented a general description of the taxonomic and functional diversity of its microbial populations, but they have lacked more specific information on the key organisms that are active during the process. RESULTS: Here we present and analyze 60 mostly high-quality metagenome-assembled genomes (MAGs) recovered from time-series samples of two thermophilic composting cells, of which 47 are potentially new bacterial species; 24 of those did not have any hits in two public MAG datasets at the 95% average nucleotide identity level. Analyses of gene content and expressed functions based on metatranscriptome data for one of the cells grouped the MAGs in three clusters along the 99-day composting process. By applying metabolic modeling methods, we were able to predict metabolic dependencies between MAGs. These models indicate the importance of coadjuvant bacteria that do not carry out lignocellulose degradation but may contribute to the management of reactive oxygen species and with enzymes that increase bioenergetic efficiency in composting, such as hydrogenases and N2O reductase. Strong metabolic dependencies predicted between MAGs revealed key interactions relying on exchange of H+, NH3, O2 and CO2, as well as glucose, glutamate, succinate, fumarate and others, highlighting the importance of functional stratification and syntrophic interactions during biomass conversion. Our model includes 22 out of 49 MAGs recovered from one composting cell data. Based on this model we highlight that Rhodothermus marinus, Thermobispora bispora and a novel Gammaproteobacterium are dominant players in chemolithotrophic metabolism and cross-feeding interactions. CONCLUSIONS: The results obtained expand our knowledge of the taxonomic and functional diversity of composting bacteria and provide a model of their dynamic metabolic interactions.

Genome-resolved metagenome and metatranscriptome analyses of thermophilic composting reveal key bacterial players and their metabolic interactions

Background Composting is an important technique for environment-friendly degradation of organic material, and is a microbe-driven process. Previous metagenomic studies of composting have presented a general description of the taxonomic and functional diversity of its microbial populations, but they have lacked more specific information on the key organisms that are active during the process. Results Here we present and analyze 60 mostly high-quality metagenome-assembled genomes (MAGs) recovered from time-series samples of two thermophilic composting cells, of which 47 are potentially new bacterial species; 24 of those did not have any hits in two public MAG datasets at the 95% average nucleotide identity level. Analyses of gene content and expressed functions based on metatranscriptome data for one of the cells grouped the MAGs in three clusters along the 99-day composting process. By applying metabolic modeling methods, we were able to predict metabolic dependencies between MAGs. These models indicate the importance of coadjuvant bacteria that do not carry out lignocellulose degradation but may contribute to the management of reactive oxygen species and with enzymes that increase bioenergetic efficiency in composting, such as hydrogenases and N2O reductase. Strong metabolic dependencies predicted between MAGs revealed key interactions relying on exchange of H+, NH3, O2 and CO2, as well as glucose, glutamate, succinate, fumarate and others, highlighting the importance of functional stratification and syntrophic interactions during biomass conversion. Our model includes 22 out of 49 MAGs recovered from one composting cell data. Based on this model we highlight that Rhodothermus marinus, Thermobispora bispora and a novel Gammaproteobacterium are dominant players in chemolithotrophic metabolism and cross-feeding interactions. Conclusions The results obtained expand our knowledge of the taxonomic and functional diversity of composting bacteria and provide a model of their dynamic metabolic interactions.

Extraction of Glucuronoarabinoxylan from Quinoa Stalks (Chenopodium quinoa Willd.) and Evaluation of Xylooligosaccharides Produced by GH10 and GH11 Xylanases.

Byproducts from quinoa are not yet well explored sources of hemicellulose or products thereof. In this work, xylan from milled quinoa stalks was retrieved to 66% recovery by akaline extraction using 0.5 M NaOH at 80 °C, followed by ethanol precipitation. The isolated polymer eluted as a single peak in size-exclusion chromatography with a molecular weight of >700 kDa. Analysis by Fourier transform infrared spectroscopy and nuclear magnetic resonance (NMR) combined with acid hydrolysis to monomers showed that the polymer was built of a backbone of ß(1 → 4)-linked xylose residues that were substituted by 4-O-methylglucuronic acids, arabinose, and galactose in an approximate molar ratio of 114:23:5:1. NMR analysis also indicated the presence of α(1 → 5)-linked arabinose substituents in dimeric or oligomeric forms. The main xylooligosaccharides (XOs) produced after hydrolysis of the extracted glucuronoarabinoxylan polymer by thermostable glycoside hydrolases (GHs) from families 10 and 11 were xylobiose and xylotriose, followed by peaks of putative substituted XOs. Quantification of the unsubstituted XOs using standards showed that the highest yield from the soluble glucuronoarabinoxylan fraction was 1.26 g/100 g of xylan fraction, only slightly higher than the yield (1.00 g/100 g of xylan fraction) from the insoluble fraction (p < 0.05). No difference in yield was found between reactions in buffer or water (p > 0.05). This study shows that quinoa stalks represent a novel source of glucuronoarabinoxylan, with a substituent structure that allowed for limited production of XOs by GH10 or GH11 enzymes.