Nature offered mankind the first golden era of discovery of novel antimicrobials based on the ability of eukaryotes or micro-organisms to produce such compounds. The microbial world proved to be a huge reservoir of such antimicrobial compounds which play important functional roles in every environment. However, most of those organisms are still uncultivable in a classical way, and therefore, the use of extended culture or DNA based methods (metagenomics) to discover novel compounds promises usefulness. In the past decades, the advances in next-generation sequencing and bioinformatics revealed the enormous diversity of the microbial worlds and the functional repertoire available for studies. Thus, data-mining becomes of particular interest in the context of the increased need for new antibiotics due to antimicrobial resistance and the rush in antimicrobial discovery. In this review, an overview of principles will be presented to discover new natural compounds from the microbiome. We describe culture-based and culture-independent (metagenomic) approaches that have been developed to identify new antimicrobials and the input of those methods in the field as well as their limitations.

大自然为人类提供了基于真核生物或微生物产生此类化合物的能力而发现新型抗菌剂的第一个黄金时代。事实证明，微生物世界是这类抗菌化合物的巨大储存库，它们在每种环境中都起着重要的功能作用。然而，大多数这些生物仍无法以经典方式进行培养，因此，使用扩展培养或基于DNA的方法（基因组学）来发现新​​型化合物有望带来帮助。在过去的几十年中，下一代测序和生物信息学的进步揭示了微生物世界的巨大多样性以及可供研究的功能库。从而，由于抗菌素耐药性和对抗菌素发现的热衷，在对新抗生素的需求增加的背景下，数据挖掘变得尤为重要。在这篇综述中，将概述原理以从微生物组中发现新的天然化合物。我们描述了基于文化和与文化无关的（元基因组）方法，这些方法已被开发出来，用于识别新的抗菌剂以及这些方法在该领域的输入及其局限性。