Biology Department, Brookhaven National Laboratory, Upton, New York 11973, USA.
Biotechnol Biofuels. 2009 May 18;2:10. doi: 10.1186/1754-6834-2-10.
Throughout immeasurable time, microorganisms evolved and accumulated remarkable physiological and functional heterogeneity, and now constitute the major reserve for genetic diversity on earth. Using metagenomics, namely genetic material recovered directly from environmental samples, this biogenetic diversification can be accessed without the need to cultivate cells. Accordingly, microbial communities and their metagenomes, isolated from biotopes with high turnover rates of recalcitrant biomass, such as lignocellulosic plant cell walls, have become a major resource for bioprospecting; furthermore, this material is a major asset in the search for new biocatalytics (enzymes) for various industrial processes, including the production of biofuels from plant feedstocks. However, despite the contributions from metagenomics technologies consequent upon the discovery of novel enzymes, this relatively new enterprise requires major improvements. In this review, we compare function-based metagenome screening and sequence-based metagenome data mining, discussing the advantages and limitations of both methods. We also describe the unusual enzymes discovered via metagenomics approaches, and discuss the future prospects for metagenome technologies.
在无法估量的时间里，微生物进化并积累了显著的生理和功能异质性，现在构成了地球上遗传多样性的主要储备。通过宏基因组学，即直接从环境样本中回收的遗传物质，无需培养细胞即可获得这种生物遗传多样化。因此，从木质纤维素植物细胞壁等难生物降解生物质周转率高的生境中分离出的微生物群落及其宏基因组已成为生物勘探的主要资源；此外，这种材料还是寻找各种工业过程（包括从植物原料生产生物燃料）新型生物催化剂（酶）的主要资产。然而，尽管发现了新型酶，宏基因组学技术做出了贡献，但这个相对较新的领域仍需要重大改进。在这篇综述中，我们比较了基于功能的宏基因组筛选和基于序列的宏基因组数据分析，讨论了这两种方法的优缺点。我们还描述了通过宏基因组方法发现的不寻常酶，并讨论了宏基因组技术的未来前景。
