背景:全球对不可再生化石燃料的过度依赖导致了温室气体的排放,创造一个关键的全球环境挑战。迫切需要替代解决方案,如生物燃料。先进的生物燃料是由木质纤维素植物材料产生的可再生可持续能源,这可以大大有助于减少二氧化碳的排放。微生物碳水化合物活性酶(CAZymes)是产生可持续生物燃料能源的最关键酶。本研究设计了shot弹枪宏基因组学方法来组装,预测,并注释,旨在深入了解分类多样性,注释CAZymes,并首次从Menageshasuba森林土壤中的微生物组中鉴定出碳水化合物水解CAZymes。
结果:基于小亚基(SSU)rRNA分析的微生物多样性揭示了细菌结构域在研究样品中占81.82%和92.31%的优势。此外,门组成结果表明门变形杆菌占优势(23.08%,27.27%),放线菌(11.36%,20.51%),和酸杆菌(10.26%,15.91%)。该研究还鉴定了未分配的细菌,这些细菌可能具有独特的生物聚合物水解潜力。宏基因组研究显示,从两个不同的样本中预测了100,244和65,356个基因。共鉴定出1806个CAZyme基因,在注释的CAZymes中,758具有分配给CAZymes的已知酶。糖苷水解酶(GHs)CAZyme家族包含大多数具有已知酶的CAZyme基因,例如β-葡萄糖苷酶,内切β-1,4-甘露聚糖酶,exo-β-1,4-葡聚糖酶,α-L-阿拉伯呋喃糖苷酶和低聚木糖葡聚糖还原末端特异性纤维二糖水解酶。另一方面,1048个已鉴定的CAZyme基因是具有未知酶活性的推定CAZyme基因,其中大多数属于GHs家族。
结论:一般来说,确定的推定CAZymes基因为发现负责水解用于生物燃料能源生成的生物聚合物的新酶开辟了机会。这一发现被用作第一手证据,作为进一步全面研究的基准,以揭示新类别的生物经济价值基因及其编码产物。
BACKGROUND: The global over-reliance on non-renewable fossil fuels has led to the emission of greenhouse gases, creating a critical global environmental challenge. There is an urgent need for alternative solutions like biofuels. Advanced biofuel is a renewable sustainable energy generated from lignocellulosic plant materials, which can significantly contribute to mitigating CO2 emissions. Microbial Carbohydrate Active Enzymes (CAZymes) are the most crucial enzymes for the generation of sustainable biofuel energy. The present study designed shotgun metagenomics approaches to assemble, predict, and annotate, aiming to gain an insight into the taxonomic diversity, annotate CAZymes, and identify carbohydrate hydrolyzing CAZymes from microbiomes in Menagesha suba forest soil for the first time.
RESULTS: The microbial diversity based on small subunit (SSU) rRNA analysis revealed the dominance of the bacterial domain representing 81.82% and 92.31% in the studied samples. Furthermore, the phylum composition result indicated the dominance of the phyla Proteobacteria (23.08%, 27.27%), Actinobacteria (11.36%, 20.51%), and Acidobacteria (10.26%, 15.91%). The study also identified unassigned bacteria which might have a unique potential for biopolymer hydrolysis. The metagenomic study revealed that 100,244 and 65,356 genes were predicted from the two distinct samples. A total number of 1806 CAZyme genes were identified, among annotated CAZymes, 758 had a known enzyme assigned to CAZymes. Glycoside hydrolases (GHs) CAZyme family contained most of the CAZyme genes with known enzymes such as β-glucosidase, endo-β-1,4-mannanase, exo-β-1,4-glucanase, α-L-arabinofuranosidase and oligoxyloglucan reducing end-specific cellobiohydrolase. On the other hand, 1048 of the identified CAZyme genes were putative CAZyme genes with unknown enzymatical activity and the majority of which belong to the GHs family.
CONCLUSIONS: In general, the identified putative CAZymes genes open up an opportunity for the discovery of new enzymes responsible for hydrolyzing biopolymers utilized for biofuel energy generation. This finding is used as a first-hand piece of evidence to serve as a benchmark for further and comprehensive studies to unveil novel classes of bio-economically valuable genes and their encoded products.