Metagenomic sequencing of complete microbial communities has greatly enhanced our understanding of the taxonomic composition of microbiotas. This has led to breakthrough developments in bioinformatic disciplines such as assembly, gene clustering, metagenomic binning of species genomes and the discovery of an incredible, so far undiscovered, taxonomic diversity. However, functional annotations and estimating metabolic processes from single species – or communities – is still challenging. Earlier approaches relied mostly on inferring the presence of key enzymes for metabolic pathways in the whole metagenome, ignoring the genomic context of such enzymes, resulting in the ‘bag-of-genes’ approach to estimate functional capacities of microbiotas.

Here, we review recent developments in metagenomic bioinformatics, with a special focus on emerging technologies to simulate and estimate metabolic information, that can be derived from metagenomic assembled genomes. Genome-scale metabolic models can be used to model the emergent properties of microbial consortia and whole communities, and the progress in this area is reviewed. While this subfield of metagenomics is still in its infancy, it is becoming evident that there is a dire need for further bioinformatic tools to address the complex combinatorial problems in modelling the metabolism of large communities as a ‘bag-of-genomes’.

完整微生物群落的宏基因组测序极大地增强了我们对微生物群分类组成的理解。这导致了生物信息学学科的突破性发展，例如组装、基因聚类、物种基因组的宏基因组分类，以及令人难以置信的、迄今为止尚未发现的分类多样性的发现。然而，功能注释和估计单个物种或群落的代谢过程仍然具有挑战性。早期的方法主要依赖于推断整个宏基因组中代谢途径关键酶的存在，忽略了这些酶的基因组背景，从而导致了估计微生物群功能能力的“基因袋”方法。

在这里，我们回顾了宏基因组生物信息学的最新发展，特别关注模拟和估计代谢信息的新兴技术，这些信息可以从宏基因组组装的基因组中获得。基因组规模的代谢模型可用于模拟微生物群落和整个群落的新兴特性，并回顾了该领域的进展。虽然宏基因组学的这一子领域仍处于起步阶段，但越来越明显的是，迫切需要进一步的生物信息学工具来解决将大型群落的新陈代谢建模为“基因组袋”时的复杂组合问题。