There were a couple of good virome papers I read this week, and I thought it was worth commenting on the juxtaposition.
Virome — The collection of viruses which are found in a complex microbial community, such as the human microbiome. NB: Most viruses found in any environment are bacteriophages — the viruses which infect bacteria, and do not infect humans.
Measuring Quality, Measuring Viruses
https://www.nature.com/articles/s41587-019-0334-5
I was excited to see two of my favorite labs collaborating on a virome data quality project: the Bushman lab at the University of Pennsylvania (where I trained) and the Segata lab at the University of Trento (who originally made MetPhlAn, the first breakthrough software tool for microbial metagenomics). The goal of this work was to measure the quality of virome research projects.
Virome research projects over the last decade have relied on a technological approach in which viral particles are physically isolated from a complex sample and then loaded onto a genome sequencer. There are a variety of experimental approaches which you can use to isolate viruses, including size filtration and density gradient centrifugation, which rely on the fact that viruses are physically quite different from bacterial cells.
The question asked by the researchers in this study was, “How well are these physical isolation methods actually working?” It’s such a good question that I’m surprised (in retrospect) that nobody had asked it before. As someone who has worked a bit in this area, I’m also surprised that I never thought to ask this question before.
Their approach was nice and straightforward — they looked in these datasets for sequences that should not be found very often, those belonging to the bacterial ribosome, whose absence is almost required in order to be considered a virus.
They found that the quality of these virome datasets varied extremely widely. You can read the paper for more details, and I am hesitant to post the figures on a public blog, but I really did not expect to see that there were published virome datasets with proportions of ribosomal sequences ranging from 0.001% all the way up to 1%.
Take Home: When you use a laboratory method to study your organism of interest, you need to use some straightforward approach for proving to yourself and others that it is actually working as you expect. For something as challenging and complex as the human virome, this new QC tool might help the field maintain a high standard of quality and avoid misleading or erroneous results.
Viral Dark Matter in IBD
https://www.sciencedirect.com/science/article/pii/S1931312819305335
One of the best talks I saw at ASM Microbe 2019 was from Colin Hill (APC Microbiome Ireland) and so I was happy to see a new paper from that group analyzing the gut virome in the context of Inflammatory Bowel Disease. I was even more gratified to read the abstract and see some really plausible and defensible claims being made in an area which is particularly vulnerable to over-hype.
No Change in Richness in IBD: Microbiome researchers talk a lot about “richness,” which refers to the total number of distinct organisms in a community. This metric can be particularly hard to nail down with viruses because they are incredibly diverse and we have a hard time counting how many “types” there are (or even what being a “type” means). In this paper they used the very careful approach of re-assembling all viral genomes from scratch, rather than comparing against an existing database, and found that there was no difference in the richness of the virome in IBD vs. non-IBD samples. When others have analyzed the same data with methods that relied on reference databases, they found a significant difference in richness, which suggests that the database was confounding the results for those prior studies.
Changes in Viruses Reflect Bacteria: The authors state that “the changes in virome composition reflected alterations in bacterial composition,” which resonated with me so strongly that I think it merits mentioning again here. Viruses tend to be extremely specific and only infect a subset of strains within a species of bacteria. They are also so diverse that it is hard to even figure out which virus is infecting which bacteria. Therefore, with our current level of understanding and technology, viruses in the human gut are really best approached as a marker of what bacterial strains are present. It’s hard to get anything more concrete than that from sequencing-based approaches, except with some specific examples of well-understood viruses. With that limitation of our knowledge in mind, it is entirely expected that changes in bacteria would be reflected in changes in their viruses. Moreover, in this type of observational study we don’t have any way to figure out which direction the arrow of directionality is pointing. I think the authors did a great job of keeping their claims to the limits of our knowledge without over-hyping the results.
There is a lot more to this paper, so I encourage you to read it in more depth and I won’t claim to make a full summary here.
In Summary: This is a fascinating field, with some really great groups doing careful and important work. We know a lot about how little we know, which means that there are even more exciting discoveries on the horizon.