Deciphering individual bacterial strains in the gut is important to understanding the microbiome

Phylogenetic trees go beyond just genus and species, but also to strains.

When scientists determine the bacterial population of one’s microbiome using genetic sequencing they are forced to make determinations of the populations’ phylogeny.  Some scientists will determine the abundance of each genus, like all the bacteria that belong to the Clostridium genus, while others will narrow their scope to specific species, like all the bacteria that belong to the Clostridium difficile versus Clostridium scindens species.  These distinctions can be immensely important.  For example, C difficile can cause colitis, but C. scindens can prevent colitis, so measuring the amount of Clostridium in the gut does not paint as clear a picture as measuring the amount of C. difficile (potentially harmful) and C. scindens (potentially helpful).  There is, however, a deeper level of differentiation within species: the strain (e.g. C. difficile A90 vs. C. difficile AA1).  These strains are very similar genetically, especially in the genomic regions most important to determining phylogeny, there are however, potentially important genetic differences. 

Scientists have long realized and understood that by characterizing the species population of the microbiome they were neglecting possible important strain-specific effects.  There have even been specific examples within the microbiome that differences in strains are important, like strains within the Staphylococcus aureus that differ in their antibiotic resistance (e.g. MRSA).  Just how important these strain-specific differences are is unknown, but there is mounting evidence they need to be taken into account.  Last week in the journal Cell, researchers from the University of Washington published results that showed strain-specific differences can be vast and immense, and that this is even more so true in the microbiome where genetic mutations and genetic transfers happen at a high rate.

The researchers used metagenomics data from patients with IBD from a previously published data set.  They took this data, compared it with previously published species’ genomes, and did a lot of fancy bioinformatics to measure strain-specific genetic differences within species.  I don’t mean to neglect the bioinformatics aspect of the paper, which is critically important their results, but the details of their ‘pipeline’ are beyond the scope of this short blog.  In any event, they learned that there were many examples of different strains that coded for as much as 20% more copies of specific genes.  As it turns out, these differences were prevalent in genes that coded for important functions, like transport, signaling, biosynthesis, motility, secretion, and virulence.  These are important processes in the gut environment, and each may have important impacts on the host.

Before this paper, the level of genomic resolution and bioinformatics needed to make strain specific determinations was difficult, and beyond the expertise of most labs.  Now that these researchers have published their methods, this type of strain analysis can be incorporated into many more experiments.  It does have its drawbacks, as full genomes are needed for each species that is analyzed, and inserted/deleted genes are not analyzed, but overall it is a very important paper.  As we move forward in microbiome research, this type of analysis that incorporates specific strains will become critical in associating diseases and phenotypes with the microbiome.

Quality control is critical to microbiome research

We just got back from two days in Rockville, MD for a meeting of the Microbiome Quality Control Project (MBQC).  The MBQC is a project that seeks to understand variability in microbiome data from sampling to analysis and make recommendations as to best practices.  Its steering committee includes some of the leading scientists in the microbiome field, Rob Knight, Curtis Huttenhower, and Owen White (all members of the AMI Scientific Advisory Board), along with epidemiologists from the National Cancer Institute Rashmi Sinha and Christian Abnet.  

Labs from around North America signed up to participate in two different aspects of the study, microbiome handling and bioinformatic data analysis. The labs that were involved in the handling aspect of the study received anonymized samples from a central repository and were tasked with extracting DNA from the samples and sequencing them.  They then made their data available (still anonymized) for the groups who signed up for the bioinformatics phase of the projects to analyze the data. Because all of the groups were handling and sequencing the same samples, differences in results meant that the variability was being caused by some aspect of the handling process or differences in the analysis.

At the meeting the steering committee presented the results of the study followed by a day and a half of discussion of the results and what steps could be taken to develop more standardized results, protocols, and reference materials for future microbiome studies. The results were exciting to see but even forgetting the results, the overall initiative was a huge success. This was a project that took place for over a year and all of the project's participants volunteered an enormous amount of time and conducted their research studies without receiving any funding.  It was wonderful to see a group of the world's leading scientists to come together like this with the sole goal of bettering future microbiome research.  

The AMI supports the MBQC and looks forward to being involved in the future phases of this work. As we learned at the meeting, there is so much left to be done to improve microbiome quality control and this was just the beginning.  More information about the results of the study and the meeting will be published in the coming months.