Glycoside Hydrolases across Environmental Microbial Communities.
Glycoside Hydrolases across Environmental Microbial Communities.
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DOI：
10.1371/journal.pcbi.1005300
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发表时间：
2016-12
影响因子：
4.3
通讯作者：
Martiny AC
中科院分区：
文献类型：
--
作者：
Berlemont R;Martiny AC
在许多环境中，微生物糖苷水解酶支持碳水化合物的酶促加工，这是许多生态系统中的关键功能。关于群落的微生物组成和碳水化合物加工的潜力如何相互关联，人们知之甚少。在这里，使用1，934个宏基因组数据集，我们将社区组成的变化与环境中碳水化合物加工潜力的变化联系起来。我们能够表明，每种生态系统类型显示出特定的碳水化合物利用潜力。这种潜力的大部分与77种细菌属有关。细菌属中的GH含量最好通过它们的分类从属关系来描述。在宏基因组中，微生物群落结构的波动和GH利用碳水化合物的潜力是相关的。我们的分析表明，确定性和随机过程都有助于组装复杂的微生物群落。复杂碳水化合物的解构（例如，纤维素、甲壳素），主要由微生物产生，向环境释放短的可代谢低聚糖。这有助于生态系统的运作，对全球碳循环至关重要。碳水化合物降解需要产生碳水化合物活性酶（CAZymes）。其中，GH是最丰富的酶，将多糖分解成更小的产物。然而，并非所有的微生物都具有所有糖苷水解酶（GH）的基因。此外，微生物群落是动态的组合，并显示出重要的时空变化。因此，两个主要问题是，哪些微生物与GH基因相关，哪些微生物参与了环境中的碳水化合物加工。因此，生物信息学的挑战是收集足够的宏基因组数据集，并根据GH基因重新分析微生物组。在这里，我们创建了一个定制的生物信息学管道，旨在识别来自13个广泛定义的生态系统的1，934个测序微生物组中的GH序列，包括陆地和海洋生态系统以及人类和动物相关的微生物组。我们将微生物群落组成的变化与环境中碳水化合物加工的功能潜力联系起来。我们的研究结果表明，相对少量的细菌属（即，潜在的降解物），GH基因数量增加，靶向其环境中预期的底物。这些降解剂在微生物组中显示出大部分保守的GH含量。然而，在每个生态系统中，潜在的退化者之间的功能冗余允许具有类似功能潜力的略有不同的社区。在全球范围内，将不同生态系统中微生物群落结构和功能的变化联系起来，可以深入了解微生物群落如何适应碳水化合物的供应。在未来，这将有助于预测微生物群落组成如何变化，以响应环境扰动（例如，全球变化），可以影响微生物群落的功能潜力。
Across many environments microbial glycoside hydrolases support the enzymatic processing of carbohydrates, a critical function in many ecosystems. Little is known about how the microbial composition of a community and the potential for carbohydrate processing relate to each other. Here, using 1,934 metagenomic datasets, we linked changes in community composition to variation of potential for carbohydrate processing across environments. We were able to show that each ecosystem-type displays a specific potential for carbohydrate utilization. Most of this potential was associated with just 77 bacterial genera. The GH content in bacterial genera is best described by their taxonomic affiliation. Across metagenomes, fluctuations of the microbial community structure and GH potential for carbohydrate utilization were correlated. Our analysis reveals that both deterministic and stochastic processes contribute to the assembly of complex microbial communities. The deconstruction of complex carbohydrates (e.g., cellulose, chitin), mostly by microbes, releases short metabolizable oligosaccharides to the environment. This contributes to the functioning of an ecosystem and is essential for global carbon cycling. Carbohydrate degradation requires the production of carbohydrate active enzymes (CAZymes). Among these, GH are the most abundant enzymes to break down polysaccharides into smaller products. However, not all the microbes have genes for all the glycoside hydrolases (GH). In addition, microbial communities are dynamic assemblages and display important spatio-temporal variations. Thus, two major questions are, which microbes are associated with GH genes and which are involved in carbohydrate processing across environments. The bioinformatic challenge is therefore to collect enough metagenomic datasets and to reanalyze microbiomes in the light of GH genes. Here, we created a custom bioinformatic pipeline aimed at identifying sequences for GH in 1,934 sequenced microbiomes derived from 13 broadly defined ecosystems, including terrestrial and marine ecosystems as well as human and animal associated microbiomes. We linked changes in microbial community composition and functional potential for carbohydrate processing across environments. Our results suggest that a relatively small number of bacterial genera (i.e., the potential degraders), with increased number of GH genes target the substrates expected in their environment. These degraders display mostly conserved GH content across microbiomes. In each ecosystem however, the functional redundancy among potential degraders allows for slightly distinct communities with similar functional potential. Globally, linking variations of microbial community structure and function, across ecosystems, provides insight into how microbial communities may adjust to the supply of carbohydrates. In the future, this will help predict how change in microbial community composition, in response to environmental perturbation (e.g., global change), can affect the functional potential of microbial communities.
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DOI：
10.1038/ismej.2011.159
发表时间：
2012-05
期刊：
The ISME journal
影响因子：
--
作者：
通讯作者：
--
影响因子：
11
作者：
Ferrenberg, Scott;O'Neill, Sean P.;Nemergut, Diana R.
通讯作者：
Nemergut, Diana R.
影响因子：
11
作者：
Delmont, Tom O.;Malandain, Cedric;Vogel, Timothy M.
通讯作者：
Vogel, Timothy M.
DOI：
10.1073/pnas.1203287109
发表时间：
2012-07-03
影响因子：
11.1
作者：
Fan, Lu;Reynolds, David;Thomas, Torsten
通讯作者：
Thomas, Torsten
影响因子：
4.4
作者：
Frank, Jeremy A.;Sorensen, Soren J.
通讯作者：
Sorensen, Soren J.