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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.

Um MAG (metagenome-assembled genome) é um genoma recuperado de dados metagenômicos e neste trabalho referem-se sempre a genomas de organismos procariotos. Após a obtenção de um MAG, diversas análises podem ser feitas para identificar similaridades e diferenças com os genomas já publicados da mesma espécie (quando a espécie é conhecida). Apresentamos MAGset, um software para comparar genomas e identificar especificidades em MAGs de espécies conhecidas. Essas especificidades podem ser regiões genômicas que existem somente no MAG e não existem nos genomas de referência, ou regiões que existem em um ou mais genomas de referência e não existem no MAG. Neste último caso, o módulo acessório MAGcheck permite verificar se as regiões não encontradas no MAG estão disponíveis nas amostras (reads) utilizadas na montagem do MAG, indicando um possível erro na montagem. Feita a comparação entre os genomas de interesse de forma automática pelo software, os seguintes resultados são apresentados ao usuário por meio de uma interface gráfica amigável: Matriz ANI comparando todos os genomas, pangenoma, anotações dos genes codificadores de proteína com os bancos CAZy e COG, regiões genômicas de interesse e resultado da validação do MAGcheck contra as amostras. Utilizando MAGset e MAGcheck, apresentamos os resultados de análises de 36 MAGs obtidos de diversas fontes. Os resultados obtidos com MAGcheck (obtivemos resultados em 34 MAGs) foram utilizados para realizar a remontagem dos MAGs originais, gerando melhorias na completude (24 dos 34 MAGs remontados) e no tamanho final (todos os MAGs remontados tiveram seu tamanho aumentado). A metagenome-assembled genome (MAG) is a genome reconstructed from metagenomic data, and in this work, MAGs refers to genomes of prokaryotic organisms. After obtaining a MAG, several analyses can be performed to identify similarities and differences with already published genomes from the same species (when the species is known). MAGset is a software to compare genomes and identify specificities in MAGs of known species. These specificities can be genomic regions that exist only in the MAG but not in reference genomes, or regions that exist in one or more reference genomes but do not exist in the MAG. In the latter case, the MAGcheck accessory module verifies whether the regions not found in the MAG are available in the samples (reads) used in the MAG assembly, indicating data missed by the assembler or binning program. Once the software has automatically compared the genomes of interest, the following results are presented to the user via a user-friendly graphical interface: ANI matrix comparing all genomes, pangenome information, annotations of protein-coding genes with CAZy and COG databases, genomic regions of interest, and the results of the MAGcheck validation against the samples. Using MAGset and MAGcheck, we present the results of analyses of 36 MAGs obtained from a variety of sources. The results obtained with MAGcheck (we obtained results for 34 MAGs) were used to perform the reassembly of the original MAGs, generating improvements in completeness (24 of the 34 MAGs reassembled) and in the final size (all reassembled MAGs increased in size).

Background: Thermophilic composting is a semi-engineered process carried out by diverse microbial communities. Composting is an environment friendly way of degrading biomass; its study may help uncover important biomass-degrading organisms and key enzymes. DNA sequence-based previous studies have presented a general description of the microbial-molecular features of composting, but they have lacked more specific information on the key organisms that are active during the process and their genomes. Methods: We present an analysis of metagenome-assembled genomes (MAGs) obtained from time-series samples of a thermophilic composting process in the São Paulo Zoological Park (Brazil). Our results are based on a careful analysis of MAG gene content and on metabolic modeling of their interactions. Results: We recovered 60 MAGs from sequencing datasets from two separate composting cells. Phylogenetic analysis shows that 47 of these MAGs represent novel taxa at the genus or higher levels. We have analyzed the gene repertoire of these MAGs in terms of lignocellulose degradation, secondary metabolite production, antibiotic resistance genes, denitrification genes, sulfur metabolism, hydrogen metabolism, and oxygen metabolism. For one of the composting cells we also had metatranscriptome data, which allowed a deeper analysis of 49 MAGs. This analysis showed the presence of three distinct clusters of MAGs with varying activity during the 99-day composting process. The interaction model pointed to Sphaerobacter thermophilus and Thermobispora bispora as key players in the process, as well as other bacteria that are novel. Our results also show the importance of coadjuvant bacteria and of microbial functions related to efficient bioenergetic processes during biomass conversion, such as N2O reduction and hydrogenases. A novel acidobacteria MAG encodes N2O reductase hallmark genes (nosZD). Strong metabolic dependencies predicted between MAGs revealed that cross-feeding in composting can be determined by complementary functions found in the genomes of producers and consumers, supporting the Black Queen hypothesis for co-evolutionary interactions. Conclusions: This study reveals for the first time the key bacterial players in thermophilic composting and provides a model of their dynamic metabolic interactions. These findings pave the way for more rational composting procedures and provide information that could help the development of novel biomass-degrading technologies.