npj Biofilms and Microbiomes volume 9, Número do artigo: 27 (2023) Citar este artigo
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Os porcos tibetanos (TPs) podem se adaptar aos ambientes extremos no planalto tibetano implicados por seus sinais de autogenoma, mas pouco se sabe sobre os papéis da microbiota intestinal na adaptação do hospedeiro. Aqui, reconstruímos 8.210 genomas montados por metagenoma de TPs (n = 65) vivendo em porcos cativos de alta e baixa altitude (87 da China—CPs e 200 da Europa—EPs) que foram agrupados em 1.050 conjuntos de genomas em nível de espécie (SGBs) no limite de 95% de identidade nucleotídica média. 73,47% dos SGBs representaram espécies novas. A análise da estrutura da comunidade microbiana intestinal com base em 1.048 SGBs mostrou que TPs era significativamente diferente dos porcos cativos de baixa altitude. SGBs associados a TP permitem digerir múltiplos polissacarídeos complexos, incluindo celulose, hemicelulose, quitina e pectina. Especialmente, descobrimos que os TPs mostraram o enriquecimento mais comum dos filos Fibrobacterota e Elusimicrobia, que estavam envolvidos na produção de ácidos graxos de cadeia curta e média (ácido acético, butanoato e propanoato; ácidos octanômico, decanóico e dodecanóico), bem como na biossíntese de lactato, 20 aminoácidos essenciais, múltiplas vitaminas B (B1, B2, B3, B5, B7 e B9) e cofatores. Inesperadamente, Fibrobacterota mostrou apenas uma poderosa capacidade metabólica, incluindo a síntese de ácido acético, alanina, histidina, arginina, triptofano, serina, treonina, valina, B2, B5, B9, heme e tetrahidrofolato. Esses metabólitos podem contribuir para a adaptação do hospedeiro a grandes altitudes, como captação de energia e resistência contra hipóxia e radiação ultravioleta. Este estudo fornece informações sobre a compreensão do papel do microbioma intestinal desempenhado na adaptação de mamíferos de alta altitude e descobre alguns micróbios potenciais como probióticos para melhorar a saúde animal.
O porco tibetano (Sus scrofa domesticus) é uma raça indígena nativa do planalto Qinghai-Tibet que pode sobreviver em ambientes hostis de alta altitude a longo prazo, como hipóxia, frio intenso, radiação ultravioleta intensa (UVR) e escassez de alimentos1, 2,3. Portanto, entender o mecanismo de adaptação de alta altitude do porco tibetano é muito importante para a descoberta de novos componentes genéticos envolvidos na resistência ao estresse. A análise genômica descobriu 268 genes sob seleção positiva em javalis tibetanos que estão relacionados a adaptações à alta altitude, como manutenção da estabilidade genômica contra UVR e adaptação molecular sob hipóxia4. Mais especificamente, este estudo identificou três genes de ligação à vitamina B6 (ALB, SPTLC2 e GLDC) que auxiliam na síntese de hemoglobina e aumentam a ligação ao oxigênio e quatro genes relacionados à hipóxia (ALB, ECE1, GNG2 e PIK3C2G). Estudo posterior encontrou mutações genéticas nos genes PLA2G12A e EPAS1 relacionadas à variação fenotípica do tônus vascular pulmonar e da concentração de hemoglobina5. Recentemente, estudos adicionais também prestaram atenção às assinaturas do microbioma intestinal da adaptação a grandes altitudes no porco tibetano, devido ao papel essencial que a microbiota intestinal desempenha no metabolismo nutricional6,7, regulação energética8,9 e desenvolvimento do sistema imunológico para manter a saúde do hospedeiro10,11. Por exemplo, uma meta-análise ribossômica 16 S revelou as três bactérias intestinais mais abundantes Acinetobacter, Pseudomonas e Sphingobacterium em porcos tibetanos em comparação com porcos de baixa altitude12. A análise metabolômica de 12 amostras fecais de porco tibetano de alta altitude demonstrou que as produções de ácido propanóico e ácido octadecanóico foram significativamente melhoradas e os genes relacionados a esses dois metabólitos também foram regulados positivamente12. Em suma, essas descobertas indicaram que ambientes de alta altitude moldaram o microbioma intestinal único e a diversidade funcional do porco tibetano. No entanto, ainda não está claro sobre a diversidade e a paisagem funcional da microbiota intestinal do porco tibetano e sua assinatura para adaptação de alta altitude do hospedeiro, devido às limitações do pequeno tamanho da amostra e baixa profundidade de sequenciamento metagenômico nos estudos anteriores.
75% and contamination <10%22,23 (see "Methods"; Fig. 1A). In total, 3807 of these MAGs were high-quality genomes with >90% completeness with <5% contamination (Fig. 1B). After de-replication at an average nucleotide identity (ANI) threshold of 95%24, 1050 SGBs were identified for further analysis (see "Methods"). We used at least 40% genome coverage to determine the presence of SGBs in each sample, and 1048 representative SGBs were finally obtained, of which 623 SGBs (59.45%) were high-quality genomes (>90% completeness and <5% contamination) (Supplementary Table 2). Each SGB was supported by an average of 7.8 MAGs and 57.25% of SGBs contained at least two MAGs (Supplementary Table 2). We used the genome taxonomy database toolkit (GTDB-Tk)25 to perform taxonomic assignment of the SGBs (see "Methods)". The results showed they were classified into 20 bacterial phyla and one archaea phylum, 90.74% of SGBs were assigned to known genera, and 73.47% of SGBs were unclassified species (named uSGBs) (Fig. 1C). Besides, 45.04% of 1048 SGBs were assigned into Firmicutes A, 25.86% to Bacteroidetes, 6.97% to Firmicutes, and 5.63% to Proteobacteria (Supplementary Table 3). The prevalence and classification of SGBs in TPs, EPs and CPs were shown in Fig. 1D, indicating the differences of microbial community at phylum-level between three groups. Additionally, functional gene profiles of 1048 SGBs were predicted using MetaGeneMark (v.3.38)26 (see "Methods"). All gene annotations were performed by using the Carbohydrate-active enzymes (CAZymes)27 and Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology (KO)28 databases (see "Methods")./p>50% completeness and <5% contamination) and 2673 SGBs (ANI ≥ 95%) from gut microbiome dataset from 500 Chinese pigs. To explore the uniqueness of our identified SGBs, we integrated our 8210 MAGs with Chen's dataset and kept the MAGs with >75% completeness and <5% contamination for the identification of SGBs at the threshold of ANI ≥ 95%. A total of 2266 SGBs were finally obtained. 1248 (55.08%) of them were unique to Chen's study, 519 (22.90%) to this study and 499 (22.02%) were overlapped (Supplementary Fig. 1). This finding indicates that ongoing efforts are needed for understanding the pig gut microbial diversity./p> 0.05), and the colors indicate enriched groups./p> 90% completeness and < 5% contamination (Supplementary Table 2). Hence, we performed KO annotation and enrichment analysis of KEGG pathways to decipher their functional potential. The results showed that there were 38 KEGG pathways significantly enriched in the SGBs of Fibrobacterota and 39 pathways in the SGBs of Elusimicrobia, respectively (Supplementary Table 6, Fisher's test, p < 0.05, FDR corrected). Overall, the two phyla bacteria exhibited different metabolic characteristics, even though the most enriched ten pathways in them both included translation, replication and repair, signal transduction and energy metabolism (Fig. 4, Fisher's test, p < 0.001). Fibrobacterota was particularly involved in the metabolism of cofactors and vitamins, as well as amino acid metabolism, and Elusimicrobia mostly participated in glycan biosynthesis and metabolism, as well as carbohydrate metabolism. Additionally, enriched pathways involved in amino acid metabolism were distinct between Fibrobacterota and Elusimicrobia (Fig. 4 and Supplementary Table 6, Fisher's test, p < 0.05, FDR corrected). For example, Fibrobacterota was significantly enriched in the pathways of valine, leucine and isoleucine biosynthesis (Fisher's test, p = 0.002), alanine, aspartate and glutamate metabolism (Fisher's test, p = 0.010), arginine biosynthesis (Fisher's test, p = 0.014), phenylalanine, tyrosine and tryptophan biosynthesis (Fisher's test, p = 0.023), lysine biosynthesis (Fisher's test, p = 0.025), histidine metabolism (Fisher's test, p = 0.025), cysteine and methionine metabolism (Fisher's test, p = 0.032). Elusimicrobia preferred to lysine biosynthesis (Fisher's test, p = 0.0174), and glycine, serine and threonine metabolism (Fisher's test, p = 0.0277)./p> 500 bp were aligned to reads using BWA(v.0.7.12)57. The coverage and depth of contigs were then computed by using Samtools (v.1.9)58 and Bedtools (v.2.27.1)59. We performed MetaBAT260 to bin the assembled contigs into putative genomes (MAGs) within each sample based on tetranucleotide frequency and abundance(or average depth) of contigs. Subsequently, CheckM (v.1.0.7)61 was used to estimate the completeness and contamination of MAGs by lineage-specific markers genes and default parameters. Generally, recovered MAGs with completeness >50% and contamination < 10% were considered medium or high-quality62,63,64, but we set up a more strict threshold for medium quality as completeness > 75% and contamination < 10%22,23. The MAGs with completeness > 75% and contamination < 10% were retained for further refinement and validation. We used RefineM (v.0.0.14)22 to filter the bins with divergent genomic properties, with incongruent taxonomic classification and with incongruent 16 S rRNA genes using default parameters. CheckM (v.1.0.7) was re-run to assess the genome quality of the retained MAGs. 8210 high-medium quality MAGs (completeness 75% and contamination 10%) were obtained. Then, those MAGs were clustered into species-level genomes using dRep (v.2.6.2)65 with default parameters of Mash66 and ANIs67 (at the threshold of 95%). The genomes with maximum genome quality score (completeness-5X contamination + 0.5logN50) in each cluster were selected as representative SGBs. SGBs with coverage greater than 40% in a sample were determined to be present in this sample. So a total of 1048 representative SGBs in pig gut were finally reconstructed in this study (Supplementary Table 2)./p>
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