Mastering the Microbiome: 9/18/23
The Microbiome as a Metabolic Machine
Introduction
Thanks for tuning in to Mastering the Microbiome! In writing this newsletter, our goal is to uncover all the different ways that researchers studying the microbiome are driving research forward.
For researchers, the idea of this newsletter is to show what successful, publishable work in the field looks like right now. At the same time, it also aims to encourage new kinds of research projects that push the field in new directions, towards new translational goals. For non-researchers, the idea is to pull back the curtain to show what research work actually looks like, and why it matters for society at large.
We’re trying out a new, narrative-driven format this month. Check it out below!
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The Microbiome as a Metabolic Machine
Just as an automobile impacts the environment by emitting particles into the air, the microbiome can affect its human host by producing molecules called metabolites. These molecules can affect how host cell’s function – in the gut, in the immune system, or in other organsA.
Each individual member of the microbiome has its own set of metabolic enzymes, encoded by its DNA. These enzymes can digest chemicals and transform them into different metabolitesB. The raw material for microbial metabolite production often comes from the host – nutrients from food, for example, can be transformed by the microbiome into metabolites that are good or bad for human health. Drug compounds, too, can be transformed by the microbiome. Sometimes the microbiome will render drug compounds inactive.
It has become a key goal for researchers who study the microbiome to predict what metabolites a microbiome will produce based on it’s the DNA content of the microbiome. Researchers use microbiome sequencing techniques like ‘16S sequencing’ or ‘shotgun metagenomics’ to visualize the microbial landscape. They can tell researchers what microbes are present and what genetic functions they possess (i.e., the capacity to produce certain metabolites)C,D.
In addition to these sequencing procedures, there are also experimental techniques that identify the actual metabolites produced by the microbiome (as opposed to identifying the genetic elements responsible for producing these metabolites). However, these procedures can be far more technically demanding and expensive. For a given sample, a metagenomic sequencing experiment will likely be cheaper than a metabolite identification (metabolomic) experimentE.
Given these technical challenges, it remains very useful to predict metabolite production from metagenomic sequencing data. And it will likely maintain the focus of researchers for a long time. For if you can effectively predict based on an individual’s microbiome profile (i.e., metagenomic data) how they will respond to a specific drug or diet by producing metabolites, you can make more personalized dietary or treatment suggestions.
This edition begins a series where we will share ongoing efforts to predict the metabolic activity of the microbiome – the digestion of drugs, dietary components, and other factors that influence human health.
We will also describe other ways that researchers are exploring the microbiome and unraveling its impact on human health – each with its own series of editions.
These future editions will be formatted in two parts: a short story that explores one or several recent research papers, and a ‘broader trends’ section that comments on related developments in the field – like a podcast where the presenter both describes an article or event and then adds their own commentary. It will look like the section below
Broader Trends
(A) The broader goal of this research area is to achieve more personalized medicine. If you can effectively predict the metabolic capacity of a microbiome sample from one individual, you can do it for other individuals too, and observe differences between individuals. As an example, one individual might have a microbiome that can effectively handle a certain diet, producing metabolites that are beneficial to the host. Another individual may have a microbiome that is better suited for a different kind of diet. Ultimately, you can use this data to provide personalized dietary recommendations (or recommendations for drug use, exercise, and other modifiable health parameters).
(B) Perhaps as important as the metabolic enzymes that convert chemicals into different forms are the so-called transporter proteins that shuttle the chemicals into the bacterial cell to begin with. These transports are like tunnels that grant chemicals passage through the cell membrane. Without these transporters, many chemicals could not be transformed by bacterial cells (the exception being cases where the chemical is small and soluble enough to diffuse through the cell membrane without a transporter protein to carry it).
(C) 16S sequencing and shotgun metagenomics offer different levels of resolution. The former can only tell you what bacteria are present (and often not even the exact species present, but rather which groups of related bacteria are in a sample). Shotgun metagenomics experiments, in contrast, will tell you what microbial genes are present in a sample. Genes encode various kinds of proteins, including metabolic enzymes. By identifying the genes present, you can also learn what species are present (because a gene encoding a particular protein has distinguishable sequences in different bacteria).
(D) How is it that researchers can map back the genetic sequences observed in shotgun metagenomics experiments to specific bacterial species? After subjecting a microbiome sample to sequencing, you get a bunch of different genetic sequences (You have sequence A, B, C, D, E, and many more). Some of these sequences will be more prevalent than others. Each sequence comes from some specific bacterial species – the challenge is figuring out what species sequence A belongs to, what species sequence B belongs to, C, D, and so on. Sometimes this is more challenging because a sequence could belong to multiple possible species. The researchers who develop sequencing processing pipelines have found ways to address this issue. New algorithms are constantly being developed to improve sequence processing.
Once you map the sequences in a sample to specific microbes, you can determine which microbes are most abundant in a sample by looking at how many times their associated sequences were counted.
Large databases exist that contain the genetic sequences of specific bacteria. These databases make sequence-species mapping possible. Researchers are still actively expanding these databases to include new bacterial species so that the species present in microbiome samples can be more accurately identified.
(E) So-called ‘metabolomics’ techniques that can identify the metabolic products produced by the microbiome or by human cells/tissues or some other kind of biological sample are constantly improving in terms of sensitivity and cost. This is a very active area of research. The paper linked here is a good review of current metabolomic techniques, the sorts of studies they support, and the challenges that remain to be addressed.
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