The chemical conversation of the human microbiome

The microbial community populating the human body plays an important role in health and disease, but with few exceptions, how individual microbial species affect health and disease states remains poorly understood.

The identity and balance of bacterial species on human skin and mucosal surfaces influences a variety of disease conditions, ranging from digestive ailments to halitosis, bacterial vaginosis and eczema. The microbiome also aids immune development and the fight against pathogens. However, the human microbiome is incredibly diverse; the communities of bacteria, viruses, fungi and other tiny organisms differ according to the tissue where they live, and across human populations and individuals. It's unclear what constitutes a normal, healthy microbiome, much less how one might go about bringing a sick one back into balance.

A common approach to solving this problem is to culture an individual microbe in the lab and explore how it contributes to health or disease states. Unfortunately, it can be difficult to identify and isolate very rare species, or find the conditions necessary to support their growth outside their natural niche. To do this with every species would be a daunting task. Alternatively, scientists can examine the microbiome in situ, with the aim of describing its individual components and how they interact.

One way microbes communicate -- and do battle -- with each other and with human cells is through biologically active small molecules.

The researchers developed computer algorithms that can detect BGCs by analyzing and interpreting metagenomic sequencing data. Metagenomic sequencing data are composed of genetic sequences obtained from the tissues or excretions of hundreds of human subjects. Some metagenomic data sets are drawn from clinical samples taken from diverse populations, including persons in different states of health or disease, or people in different geographical locales. Intensive analysis is needed to make sense of the rich but often fragmentary information contained in these data sets.

The approach employed began by identifying genes essential for the synthesis of a particular molecule or chemical of interest, then using computational algorithms to sort through metagenomic data for similar (homologous) genetic sequences, and grouping these sequence fragments together. They then assessed the prevalence of each group in the human population, and used the grouped sequences to piece together full-length BGCs. Importantly, this approach allowed identification of novel BGCs even if they are extremely rare.

To validate this approach, the researchers investigated whether they could detect BGCs involved in the synthesis of type II polyketides. This class of chemicals, which includes the anti-cancer drug doxorubicin and several antibiotic drugs, was previously found in soil bacteria but had never before been found in bacteria of the human microbiome.

With this technology, it is now possible to mine our own microbiomes for drug discovery or novel biological interactions. What other treasures might this type of analysis reveal? 

Reference:

Yuki Sugimoto, Francine R. Camacho, Shuo Wang, Pranatchareeya Chankhamjon, Arman Odabas, Abhishek Biswas, Philip D. Jeffrey, Mohamed S. Donia. A metagenomic strategy for harnessing the chemical repertoire of the human microbiome. Science, 2019; eaax9176 DOI: 10.1126/science.aax9176

Posted by Dr. Tim Sandle, Pharmaceutical Microbiology Resources (http://www.pharmamicroresources.com/)