Filho Jaire A Ferreira, Rosolen Rafaela R, Almeida Deborah A, de Azevedo Paulo Henrique C, Motta Maria Lorenza L, Aono Alexandre H, Dos Santos Clelton A, Horta Maria Augusta C, de Souza Anete P
Center for Molecular Biology and Genetic Engineering (CBMEG), University of Campinas (UNICAMP), Campinas, SP Brazil.
Brazilian Biorenewables National Laboratory (LNBR), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, SP Brazil.
3 Biotech. 2021 Nov;11(11):475. doi: 10.1007/s13205-021-03032-y. Epub 2021 Oct 26.
Fungi are key players in biotechnological applications. Although several studies focusing on fungal diversity and genetics have been performed, many details of fungal biology remain unknown, including how cellulolytic enzymes are modulated within these organisms to allow changes in main plant cell wall compounds, cellulose and hemicellulose, and subsequent biomass conversion. With the advent and consolidation of DNA/RNA sequencing technology, different types of information can be generated at the genomic, structural and functional levels, including the gene expression profiles and regulatory mechanisms of these organisms, during degradation-induced conditions. This increase in data generation made rapid computational development necessary to deal with the large amounts of data generated. In this context, the origination of bioinformatics, a hybrid science integrating biological data with various techniques for information storage, distribution and analysis, was a fundamental step toward the current state-of-the-art in the postgenomic era. The possibility of integrating biological big data has facilitated exciting discoveries, including identifying novel mechanisms and more efficient enzymes, increasing yields, reducing costs and expanding opportunities in the bioprocess field. In this review, we summarize the current status and trends of the integration of different types of biological data through bioinformatics approaches for biological data analysis and enzyme selection.
真菌是生物技术应用中的关键角色。尽管已经开展了多项聚焦于真菌多样性和遗传学的研究，但真菌生物学的许多细节仍不为人知，包括这些生物体中纤维素分解酶是如何被调控，从而使主要植物细胞壁成分、纤维素和半纤维素发生变化，以及随后的生物质转化过程。随着DNA/RNA测序技术的出现与巩固，在降解诱导条件下，可以在基因组、结构和功能水平上生成不同类型的信息，包括这些生物体的基因表达谱和调控机制。数据生成的增加使得快速的计算发展成为处理大量生成数据的必要条件。在此背景下，生物信息学的起源——一门将生物数据与信息存储、分发和分析的各种技术相结合的交叉科学，是迈向当前后基因组时代先进水平的重要一步。整合生物大数据的可能性促成了令人兴奋的发现，包括识别新机制和更高效的酶、提高产量、降低成本以及扩大生物工艺领域的机会。在本综述中，我们总结了通过生物信息学方法整合不同类型生物数据以进行生物数据分析和酶选择的现状与趋势。
