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Background Several investigations on the microbial diversity and functional properties of the International Space Station (ISS) environment were carried out to understand the influence of spaceflight conditions on the microbial population. However, metagenome-assembled genomes (MAGs) of ISS samples are yet to be generated and subjected to various genomic analyses, including phylogenetic affiliation, predicted functional pathways, antimicrobial resistance, and virulence characteristics. Results In total, 46 MAGs were assembled from 21 ISS environmental metagenomes, in which metaSPAdes yielded 20 MAGs and metaWRAP generated 26 MAGs. Among 46 MAGs retrieved, 18 bacterial species were identified, including one novel genus/species combination (Kalamiella piersonii) and one novel bacterial species (Methylobacterium ajmalii). In addition, four bins exhibited fungal genomes; this is the first-time fungal genomes were assembled from ISS metagenomes. Variations in the antimicrobial resistant (AMR) and virulence genes of the selected 20 MAGs were characterized to predict the ecology and evolution of biosafety level (BSL) 2 microorganisms in space. Since microbial virulence increases in microgravity, AMR gene sequences of MAGs were compared with genomes of respective ISS isolates and corresponding type strains. Among these 20 MAGs characterized, AMR genes were more prevalent in theEnterobacter bugandensisMAG, which has been predominantly isolated from clinical samples. MAGs were further used to analyze if genes involved in AMR and biofilm formation of viable microbes in ISS have variation due to generational evolution in microgravity and radiation pressure. Conclusions Comparative analyses of MAGs and whole genome sequences of related ISS isolates and their type strains were characterized to understand the variation related to the microbial evolution under microgravity. ThePantoea/Kalamiellastrains have the maximum single nucleotide polymorphisms found within the ISS strains examined. This may suggest thatPantoea/Kalamiellastrains are much more subjective to microgravity changes. The reconstructed genomes will enable researchers to study the evolution of genomes under microgravity and low dose irradiation compared to the evolution of microbes here on Earth.

On a daily based, there is a huge amount of biological data being generated that brings deeper insight into our world. This exponential growth of information has brought many challenges, especially when dealing with metagenomic data. Thousands of metagenomic-assembled genomes (MAG) are recovered annually, and many methods try to achieve the best output possible through assembly and binning approaches. But the question that every time is more frequent is: Are these MAGs reliable? The importance of having good quality data is undeniable. Retrieving reliable and complete, or nearly-complete MAGs, provides important data for further analysis and research purposes. Within this scenario, we\'d like to know if it is possible to improve the MAGs metrics quality when compared to the state-of-the art in time series data. In addition, we\'d like to develop a tool capable of locating and fixing assembly errors, thereby assisting in genomic curation. Here, we describe an approach of MAGs recovery from time-serial data called the \"screening method\", drastically reducing the recovery from potentially unreliable MAGs. In addition, we present FixAME, a tool capable of helping curate assembled sequences of metagenome, single genome, a set of bins, phages, archaea, or any organism that contains single double-stranded DNA. Diariamente, há uma grande quantidade de dados biológicos sendo gerados que trazem uma visão mais profunda do nosso mundo. Esse crescimento exponencial de informações trouxe muitos desafios, principalmente quando se trata de dados metagenômicos. Milhares de genomas montados a partir de dados metagenômicos (MAG) são recuperados anualmente, e muitos métodos tentam alcançar o melhor resultado possível por meio de abordagens de montagem e binning. Mas a pergunta que cada vez é mais frequente é: esses MAGS são confiáveis? A importância de ter dados de boa qualidade é inegável. A recuperação de MAGs confiáveis e completos, ou quase completos, fornece dados importantes para análises futuras e propósitos de pesquisa. Dentro desse cenário, gostaríamos de saber se é possível melhorar a qualidade das métricas dos MAGs quando comparadas ao estado da arte em dados seriados no tempo. Além disso, gostaríamos de desenvolver uma ferramenta capaz de localizar e corrigir erros de montagem, dessa forma auxiliando na curadoria genômica. Aqui, nós descrevemos uma abordagem de MAGs recuperados de dados seriados no tempo chamado \"método de triagem\", reduzindo drasticamente a recuperação de MAGs potencialmente não confiáveis. Além disso, apresentamos FixAME, uma ferramenta capaz de auxiliar na curadoria de sequências montadas de metagenoma, genoma único, conjunto de bins, fagos, arqueias ou qualquer organismo que contenha DNA de fita simples.

Rare diseases affect up to 13.2 million individuals in Brazil. The Brazilian Rare Genomes Project is envisioned to further the implementation of genomic medicine into the Brazilian public healthcare system. Here we report the validation results of a whole genome sequencing (WGS) procedure for implementation in clinical laboratories. In addition, we report data quality for the first 1,200 real-world patients sequenced. We sequenced a well-characterized group of 76 samples, including seven gold standard genomes, using a PCR-free WGS protocol on Illumina Novaseq 6,000 equipment. We compared the observed variant calls with their expected calls, observing good concordance for single nucleotide variants (SNVs; mean F-measure = 99.82%) and indels (mean F-measure = 99.57%). Copy number variants and structural variants events detection performances were as expected (F-measures 96.6% and 90.3%, respectively). Our WGS protocol presented excellent intra-assay reproducibility (coefficients of variation ranging between 0.03% and 0.20%) and inter-assay reproducibility (coefficients of variation ranging between 0.02% and 0.09%). Limitations of the WGS protocol include the inability to confidently detect variants such as uniparental disomy, balanced translocations, repeat expansion variants, and low-level mosaicism. In summary, the observed performance of the WGS protocol was in accordance with that seen in the best centers worldwide. The Rare Genomes Project is an important initiative to bring pivotal improvements to the quality of life of the affected individuals.

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.

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.

Thanks in large part to newer, better, and cheaper DNA sequencing technologies, an enormous number of metagenomic sequence datasets have been and continue to be generated, covering a huge variety of environmental niches, including several different human body sites. Comparing these metagenomes and identifying their commonalities and differences is a challenging task, due not only to the large amounts of data, but also because there are several methodological considerations that need to be taken into account to ensure an appropriate and sound comparison between datasets. In this chapter, we describe current techniques aimed at comparing metagenomes generated by 16S ribosomal RNA and shotgun DNA sequencing, emphasizing methodological issues that arise in these comparative studies. We provide a detailed case study to illustrate some of these techniques using data from the Human Microbiome Project comparing the microbial communities from ten buccal mucosa samples with ten tongue dorsum samples in terms of alpha diversity, beta diversity, and their taxonomic and functional profiles.

Microbial consortia selected from complex lignocellulolytic microbial communities are promising alternatives to deconstruct plant waste, since synergistic action of different enzymes is required for full degradation of plant biomass in biorefining applications. Culture enrichment also facilitates the study of interactions among consortium members, and can be a good source of novel microbial species. Here, we used a sample from a plant waste composting operation in the Sao Paulo Zoo (Brazil) as inoculum to obtain a thermophilic aerobic consortium enriched through multiple passages at 60°C in carboxymethylcellulose as sole carbon source. The microbial community composition of this consortium was investigated by shotgun metagenomics and genome-centric analysis. Six near-complete (over 90%) genomes were reconstructed. Similarity and phylogenetic analyses show that four of these six genomes are novel, with the following hypothesized identifications: a new Thermobacillus species; the first Bacillus thermozeamaize genome (for which currently only 16S sequences are available) or else the first representative of a new family in the Bacillales order; the first representative of a new genus in the Paenibacillaceae family; and the first representative of a new deep-branching family in the Clostridia class. The reconstructed genomes from known species were identified as Geobacillus thermoglucosidasius and Caldibacillus debilis. The metabolic potential of these recovered genomes based on COG and CAZy analyses show that these genomes encode several glycoside hydrolases (GHs) as well as other genes related to lignocellulose breakdown. The new Thermobacillus species stands out for being the richest in diversity and abundance of GHs, possessing the greatest potential for biomass degradation among the six recovered genomes. We also investigated the presence and activity of the organisms corresponding to these genomes in the composting operation from which the consortium was built, using compost metagenome and metatranscriptome datasets generated in a previous study. We obtained strong evidence that five of the six recovered genomes are indeed present and active in that composting process. We have thus discovered three (perhaps four) new thermophillic bacterial species that add to the increasing repertoire of known lignocellulose degraders, whose biotechnological potential can now be investigated in further studies.

Composting is a promising source of new organisms and thermostable enzymes that may be helpful in environmental management and industrial processes. Here we present results of metagenomic- and metatranscriptomic-based analyses of a large composting operation in the São Paulo Zoo Park. This composting exhibits a sustained thermophilic profile (50 °C to 75 °C), which seems to preclude fungal activity. The main novelty of our study is the combination of time-series sampling with shotgun DNA, 16S rRNA gene amplicon, and metatranscriptome high-throughput sequencing, enabling an unprecedented detailed view of microbial community structure, dynamics, and function in this ecosystem. The time-series data showed that the turning procedure has a strong impact on the compost microbiota, restoring to a certain extent the population profile seen at the beginning of the process; and that lignocellulosic biomass deconstruction occurs synergistically and sequentially, with hemicellulose being degraded preferentially to cellulose and lignin. Moreover, our sequencing data allowed near-complete genome reconstruction of five bacterial species previously found in biomass-degrading environments and of a novel biodegrading bacterial species, likely a new genus in the order Bacillales. The data and analyses provided are a rich source for additional investigations of thermophilic composting microbiology.

Apesar de altamente estável, o DNA sofre milhares de alterações em sua estrutura diariamente, sejam essas espontâneas ou pela exposição a agentes mutagênicos. A maior parte dessas alterações é prontamente removida por um conjunto de eventos de reparo de DNA. A via de reparo por excisão de nucleotídeos (NER) é a mais versátil e flexível lidando com uma variedade de lesões que podem gerar distorções das hélices do DNA. Esses danos resultam em alterações características que, caso não reparadas, podem gerar mutações ou morte celular e, consequentemente, câncer e envelhecimento. Algumas síndromes, nas quais os pacientes são sensíveis à luz solar, estão relacionadas à deficiência no processo de NER, como a Xeroderma Pigmentosum (XP), síndrome de Cockayne (CS) e Tricotiodistrofia (TTD). Indivíduos brasileiros, incluindo pacientes com diagnóstico clínico de XP e membros das famílias, passaram por um processo in silico para a identificação variantes em genes relacionados aos processos de reparo do DNA após o sequenciamento do DNA por plataformas de nova geração (NGS: plataforma ABI 5500XL SOLiD e MiSeq Illumina) e análises de Bioinformática. Para cada paciente, foram selecionados os melhores valores de parâmetros para se realizar a busca por variantes considerando a qualidade de alinhamento e a taxa de cobertura das bases alvo. SNPs já depositados no banco de dados do projeto 1000genomes foram removidos de nossos dados. O restante das variantes foi analisado para encontrar potenciais candidatos que poderiam explicar o diagnóstico clínico do paciente. Em muitas amostras foi possível determinar pelo menos uma variante (mutação) com uma elevada possibilidade de ser responsável pelos sintomas XP. Para alguns pacientes, a má qualidade do sequenciamento ou eventos não esclarecidos durante este, dificultou a identificação de candidatos à mutação patogênica. Potenciais mutações não sinônimas foram analisadas com os programas SIFT e PROVEAN, que identificaram a potencial capacidade deletéria da alteração de aminoácido na proteína. Finalmente, foi desenvolvida uma interface de domínio público amigável, a Human Variantes do Finder Interface (http://www.varfinderhg.com.br), que visa facilitar a identificação de variantes em dados gerados por NGS. Although highly stable, DNA molecule undergoes thousands of damage in its structure every day, due to spontaneous lesions or exposure to various mutagens. Most of these lesions are readily removed by a number of cellular DNA repair processes. The process of nucleotide excision repair (NER) is the most versatile and flexible dealing with a variety of lesions that can lead to distortions of the DNA strands. Ultraviolet irradiation induced DNA damage are the main substrates for NER. These DNA damage, if not repaired, can generate mutations or cell death causing several diseases, including cancer and aging. Some syndromes, sensitive to sunlight, are related to deficiencies in the NER process, such as Xeroderma Pigmentosum (XP), Cockayne syndrome (CS) and Trichothiodystrophy (TTD). Brazilian individuals, including patients with clinical diagnosis of XP and family members, went through in silico process for the identification of variants in genes related to DNA repair processes after DNA sequencing by next generation sequencing (NGS in the platforms ABI 5500XL SOLiD and MiSeq Illumina) and dedicated Bioinformatics pipelines. For each patient the best search pattern of variant calling was used considering the alignment quality and coverage rate of bases in target. SNPs already deposited at the 1000genomes project database were removed from the data. The remaining variants were analyzed to find potential candidates that could explain the clinical diagnosis. In many samples, it was possible to determine at least one variant (mutation) with a high possibility of being responsible for the clinical XP. For some patients, the poor quality of the sequencing or unclear events during sequencing hampered the identification of clear mutation candidates. Potential nonsynonymous mutations were analyzed with SIFT and PROVEAN softwares, which identified the potential deleterious capacity of the amino acid change in the protein. Finally, we developed a user-friendly public domain interface, the Human Variants Finder Interface (http://www.varfinderhg.com.br), which, we expect, will facilitate the identification of variants in data generated by NGS.