What's Big about Small Proteins?

Something interesting has been happening in the world of microbiome research, and it’s all about small proteins.

What’s New?

There was a paper in my weekly roundup of microbiome publications which caught my eye:

Petruschke, H., Schori, C., Canzler, S. et al. Discovery of novel community-relevant small proteins in a simplified human intestinal microbiome. Microbiome 9, 55 (2021).

Reading through the abstract, the authors have “a particular focus on the discovery of novel small proteins with less than 100 amino acids.” While this may seem to be a relatively innocuous statement, I was very interested to see what they found because of some recent innovations in the computational approaches used to study the microbiome.

What’s the Context?

When people study the microbiome, they often only have access to the genome sequences of the bacteria which are present. This is very much the case for the type of metagenomic analysis which I focus on, as with any approach which takes advantage of the massive amounts of data which can be generated with genome sequencing instruments.

When analyzing bacterial genomes, we are able to predict what genes are contained in each genome using annotation tools designed for this purpose. The most commonly used tool for this task is Prokka, made by Torsten Seemann. Recently, researchers have started to realize that there are some bacterial proteins which were being missed by these types of approaches, since the experimental data used to build the predictive models did not include a whole collection of small proteins.

Then, in 2019 Dr. Ami Bhatt’s group at Stanford published a high-profile paper making the case that microbiome analyses were systematically omitting small bacterial proteins:

Sberro H, Fremin BJ, Zlitni S, Edfors F, Greenfield N, Snyder MP, Pavlopoulos GA, Kyrpides NC, Bhatt AS. Large-Scale Analyses of Human Microbiomes Reveal Thousands of Small, Novel Genes. Cell. 2019 Aug 22;178(5):1245-1259.e14. doi: 10.1016/j.cell.2019.07.016. Epub 2019 Aug 8. PMID: 31402174; PMCID: PMC6764417.

Around the same time, other groups were publishing studies which used other experimental approaches which supported the idea that bacteria encoded these small genes, which were also being transcribed and translated as bona fide proteins (a few quick examples).

What’s the Point?

The reason I think this story is worth mentioning is because it shines light on part the foundation of microbiome research. When we conduct a microbiome experiment, we can only make a limited number of measurements. We then do the best job we can to infer the biological features which are relevant to our experimental question. Part of the revolution of microbiome research from the last ten years has been the explosion of metagenomic data which is now available. This research is particularly interesting because it shows us how our analysis of that data may have been missing an entire class of genetic elements — genes which encode proteins less than 100 amino acids in length.

At the end of the day, the message is a positive one: with improved experimental techniques we can now generate more useful and accurate data from existing datasets. I am looking forward to seeing what we are able to find as the field continues to explore this new area of the microbiome!

What's the Matter with Recombination?

Required reading for anyone who uses taxonomy or phylogeny in their #bioinformatics to study the #microbiome (thread, and paper) https://t.co/ucs8r7gLH7

— Sam Minot (@sminot) January 9, 2021

Why would I be so bold as to assign required reading on a Saturday morning via Twitter? Because the ideas laid out in this paper have practical implications for many of the computational tools that we use to understand the microbiome. Taxonomy and phylogeny lies at the heart of k-mer based methods for metagenomics, as well as the core justification for measuring any marker gene (e.g. 16S) with amplicon sequencing.

Don’t get me wrong, I am a huge fan of both taxonomy and phylogeny as one of the best ways for humans to understand the microbial world, and I’m going to keep using both for the rest of my career. For that reason, I think it’s very important to understand the ways in which these methods can be confounded (i.e. the ways in which these methods can mislead us) by mechanisms like genomic recombination.

What Is Recombination?

Bacteria are amazingly complex creatures, and they do a lot more than just grow and divide. During the course of a bacterial cell’s life, it may end up doing something exciting like:

• Importing a piece of naked DNA from its environment and just pasting it into its genome;

• Using a small needle to inject a plasmid (small chromosome) into an adjacent cell; or

• Package up a small piece of its genome into a phage (protein capsule) which contains all of the machinery needed to travel a distance and then inject that DNA into another bacterium far away.

Not all bacteria do all of these things all of the time, but we know that they do happen. One common feature of these activities is that genetic material is exchanged between cells in a manner other than clonal reproduction (when a single cell splits into two). In other words, these are all forms of ‘recombination.’

How Do We Study the Microbiome?

Speaking for myself, I study the microbiome by analyzing data generated by genome sequencing instruments. We use those instruments to identify a small fraction of the genetic sequences contained in a microbiome sample, and then we draw inferences from those sequences. This may entail amplicon sequencing of the 16S gene, bulk WGS sequencing of a mixed population, or even single-cell sequencing of individual bacterial cells. Across all of these different technological approaches, we are collecting a small sample of the genomic sequences present in a much larger microbiome sample, and we are using that data to gain some understanding of the microbiome as a whole. In order to extrapolate from data to models, we rely on some key assumptions of how the world works, one of which being that bacteria do not frequently recombine.

What Does Recombination Mean to Me?

If you’ve read this far you are either a microbiome researcher or someone very interested in the topic, and so you should care about recombination. As an example, let’s walk through the logical progression of microbiome data analysis:

• I have observed microbial genomic sequence S in specimen X. This may be an OTU, ASV, or WGS k-mer.

• The same sequence S can also be observed in specimen Y, but not specimen Z. There may be some nuances of sequencing depth and the limit-of-detection, but I have satisfied myself that for this experiment marker S can be found in X and Y, but not Z.

• Because bacteria infrequently recombine, I can infer that marker S represents a larger genomic region G which is similarly present in X and Y, but not Z. For 16S that genomic region would be the species- or genus-level core genome, and for WGS it could also be some accessory genetic elements like plasmids, etc. In the simplest rendering, we may give a name to genomic region G which corresponds to the taxonomic label for those organisms which share marker S (e.g. Escherichia coli).

• When I compare a larger set of samples, I find that the marker S can be consistently found in samples obtained from individuals with disease D (like X and Y) but not in samples from healthy controls (like Z). Therefore I would propose the biological model that organisms containing the larger genomic region G are present at significantly higher relative abundance in the microbiome of individuals with disease D.

In this simplistic rendering I’ve tried to make it clear that the degree to which bacteria recombine will have a practical impact on how much confidence we can have in inferences which rely on the concepts of taxonomy or phylogeny.

The key idea here is that if you observe any marker S, we tend to assume that there is a monophyletic group of organisms which share that marker sequence. Monophyly is one of the most important concepts in microbiome analysis which also happens to be a lot of fun to say — it’s worth reading up on it.

How Much Recombination Is There?

Getting back to the paper that started it all, the authors did a nice job of carefully estimating the frequency of recombination across a handful of bacterial species for which a reasonable amount of data is available. The answer they found is that recombination rates vary, and this answer matches our mechanistic understanding of recombination. The documented mechanisms of recombination vary widely across different organisms, and there is undoubtedly a lot more out there we haven’t characterized yet.

At the end of the day, we have only studied a small fraction of the organisms which are found in the microbiome. As such, we should approach them with a healthy dose of skepticism for any key assumption, like a lack of recombination, which we know is not universal.

In conclusion, I am going to continue to use taxonomy and phylogeny every single day that I study the microbiome, but I’m also going to stay alert for how recombination may be misleading me. On a practical note, I am also going to try to use methods like gene-level analysis which keep a tight constraint on the size of regions G which are inferred from any marker S.

Quality and Insights – The Human Gut Virome in 2019

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.

3D structures of gut bacteria and the human immune system

When I talk to people about my work I sometimes get the question, “Do you really think that the microbiome has a direct effect on human health?” It’s a completely understandable question – the study-of-the-week which makes it into the news cycle tends to just confirm what we already know about the importance of diet and exercise. Then I come across these beautiful papers that show just how intimately connected we are with our gut bacteria. Here’s a good example, and it even comes with a video.

Ladinsky, M.S., et al. Endocytosis of commensal antigens by intestinal epithelial cells regulates mucosal T cell homeostasis. Science. 363(6431). DOI: 10.1126/science.aat4042.

There are some beautiful illustrations and graphics in this paper which I won’t reproduce here, but which I hope you can access from whichever side of the paywall you are on.

Background: Researchers are continuing to find evidence that the type of bacteria in your gut (if you are a mouse or a human) influences the type of your immune response. If you don’t study the immune system, just remember that the immune system responds in different ways to different kinds of pathogens – viruses are different from bacteria, which are different from parasites, etc. Mounting the correct type of response is essential, and it seems that which bacteria you have in your gut has some influence over the nature of those responses.

The Gist: This study focused on the how of the question, the specific molecular mechanism which would explain this observed relationship between bacteria and the immune system. They used one particular type of bacteria (segmented filamentous bacteria, or “SFB”) and showed that this bacteria gets so close to human cells that bacterial proteins are actually taken up and can be found inside the human cells. In addition, this movement of bacterial proteins inside human cells causes a shift in the type of response mounted by the immune system.

What Caught My Eye: This paper has a video showing a protrusion of a bacterial cell pushing deep into a human cell, complete with a 3D reconstruction of the physical structure using electron tomography. If you can follow the link above and make it to the video, I highly recommend taking a look.

The biggest story for me in the microbiome these days is that there are a number of great researchers who are starting to figure out some of the specific molecular mechanisms by which the microbiome may influence human health. This makes me more and more optimistic and excited that we will see a day where microbiome-based therapeutics make it into the clinic, which could have a profound impact on a broad range of diseases, from inflammatory bowel disease to colorectal cancer and auto-inflammatory disease. It is exciting to be a part of this effort and try to help as we bring that day closer.

Molecules Mediating Microbial Manipulation of Mouse (and Human) Maladies

Sometime in the last ten years I gave up on the idea of truly keeping up with the microbiome field. In graduate school it was more reasonable because I had the luxury of focusing on viruses in the microbiome, but since then my interests have broadened and the size of the field has continued to expand. These days I try to focus on the subset of papers which are telling the story of either gene-level metagenomics, or the specific metabolites which mediate the biological effect of the microbiome on human health. The other day I happened across a paper which did both, and so I thought it might be worth describing it quickly here.

Brown, EM, et al. Bacteroides-Derived Sphingolipids Are Critical for Maintaining Intestinal Homeostasis and Symbiosis. Cell Host & Microbe 2019 25(5) link

As a human, my interest is drawn by stories that confirm my general beliefs about the world, and do so with new specific evidence. Of course this is the fallacy of ascertainment bias, but it’s also an accurate description of why this paper caught my eye.

The larger narrative that I see this paper falling into is the one which says that microbes influence human health largely because they produce a set of specific molecules which interact with human cells. By extension, if you happen to have a set of microbes which cannot produce a certain molecule, then your health will be changed in some way. This narrative is attractive because it implies that if we understand which microbes are making which metabolites (molecules), and how those metabolites act on us, then we can design a therapeutic to improve human health.

Motivating This Study

Jumping into this paper, the authors describe a recently emerging literature (which I was unaware of) on how bacterially-produced sphingolipids have been predicted to influence intestinal inflammation like IBD. Very generally, sphingolipids are a diverse class of molecules that can be found in bacterial cell membranes, but which also can be produced by other organisms, and which also can have a signaling effect on human cells. The gist of the prior evidence going into this paper is that

• people with IBD have lower levels of different sphingolipids in their stool, and

• genomic analysis of the microbiome of people with IBD predicts that their bacteria are making less sphingolipids

Of course, those observations don’t go very far on their own, mostly because there are a ton of things that are different in the microbiome of people with IBD, and so it’s hard to point to any one bacteria or molecule from the bunch and say that it is having a causal role, and isn’t just a knock-on effect from some other cause.

The Big Deal Here

The hypothesis in this study is that one particular type of bacteria, Bacteroides are producing sphingolipids which reduce inflammation in the host. The experimental system they used were mice that were born completely germ-free, and which were subsequently colonized with strains of Bacteroides that either did or did not have the genes required to make some particular types of sphingolipids. The really cool thing here was that they were able to knock out the gene for sphingolipid production in one specific species of Bacteroides, and so they could see what the effect was of that particular set of genes, while keeping everything else constant. They found a pretty striking result, which is that inflammation was much lower in the mice which were colonized with the strain which was able to make the sphingolipid.

To me, narrowing down the biological effect in an experiment to the difference of a single gene is hugely motivating, and really makes me think that this could plausibly have a role in the overall phenomenon of microbiome-associated inflammation.

The authors rightly point out that sphingolipids might not actually be the molecular messenger having an impact on host physiology — there are a lot of other things different in the sphingolipid-deficient bacteria used here, including carbohydrate metabolism and membrane composition, but it’s certainly a good place to keep looking.

Of course the authors did a bunch of other work in this paper to demonstrate that the experimental system was doing what they said, and they also went on to re-analyze the metabolites from human stool and identify specific sphingolipids that may be produced by these Bacteroides species, but I hope that my short summary gives you an idea of what they are getting at.

All About Those Genes

I think it can be difficult for non-microbiologists to appreciate just how much genetic diversity there is among bacteria. Strains which seem quite similar can have vastly different sets of genes (encoding, for example, a giant harpoon used to kill neighboring cells), and strains which seem quite different may in fact be sharing genes through exotic forms of horizontal gene transfer. With all of this complexity, I find it very comforting when scientists are able to conduct experiments which identify specific molecules and specific genes within the microbiome which have an impact on human health. I think we are moving closer to a world where we are able to use our knowledge of the microbiome to improve human health, and I think studies like this are bringing us closer.

Massive unexplored genetic diversity of the human microbiome

When you analyze extremely large datasets, you tend to be guided by your intuition or predictions on how those datasets are composed, or how they will behave. Having studied the microbiome for a while, I would say that my primary rule of thumb for what to expect from any new sample is tons of novel diversity. This week saw the publication of another great paper showing just how true this is.

Extensive Unexplored Human Microbiome Diversity Revealed by Over 150,000 Genomes from Metagenomes Spanning Age, Geography, and Lifestyle Resource

The Approach

If you are new to the microbiome, you may be interested to know that there are basically two approaches to figuring out what microbes (bacteria, viruses, etc.) are in a given sample (e.g. stool). You can either (1) compare all of the DNA in that sample to a reference database of microbial genomes, or (2) try to reassemble the genomes in each sample directly from the DNA.

The thesis of this paper is one that I strongly support: reference databases contain very little of the total genomic content of microbes out there in the world. By extension, they predict that (1) would perform poorly, while (2) will generate a much better representation of what microbes are present.

Testing this idea, the authors analyzed an immense amount of microbiome data (almost 10,000 biological samples!), performing the relatively computationally intensive task of reconstructing genomes (so-called _de novo_ assembly).

The Results

The authors found a lot of things, but the big message is that they were able to reconstruct a *ton* of new genomes from these samples — organisms that had never been sequenced before, and many that don’t really resemble any phyla that we know of. In other words, they found a lot more novel genomic content than even I expected, and I was sure that they would find a lot.

There’s a lot more content here for microbial genome afficianados, so feel free to dig in on your own (yum yum).

Take Home

When you think about what microbes are present in the microbiome, remember that there are many new microbes that we’ve never seen before. Some of those are new strains of clearly recognizable species (e.g. E. coli with a dozen new genes), but some will be novel organisms that have never been cultured or sequenced by any lab.

If you’re a scientist, keep that in mind when you are working in this area. If you’re a human, take hope and be encouraged by the fact that there is still a massive undiscovered universe within us, full of potential and amazing new things waiting to be discovered.

Niche Theory and the Human Gut Microbiome

Without really having the time to write a full blog post, I want to mention two recent papers that have strongly influenced my understanding of the microbiome.

Niche Theory

The ecological concept of the “niche” is something that is discussed quite often in the field of the microbiome, namely that each bacterial species occupies a niche, and any incoming organism trying to use that same niche will be blocked from establishing itself. The mechanisms and physical factors that cause this “niche exclusion” is probably much more clearly described in the ecological study of plants and animals — in the case of the microbiome I have often wondered just what utility or value this concept really had.

That all changed a few weeks ago with a pair of papers from the Elinav group.

The Papers

Personalized Gut Mucosal Colonization Resistance to Empiric Probiotics Is Associated with Unique Host and Microbiome Features

Post-Antibiotic Gut Mucosal Microbiome Reconstitution Is Impaired by Probiotics and Improved by Autologous FMT

Quick, Quick Summary

At the risk of oversimplifying, I’ll try to summarize the two biggest points I took home from these papers.

1. Lowering the abundance and diversity of bacteria in the gut can increase the probability that a new strain of bacteria (from a probiotic) is able to grow and establish itself

2. The ability of a new bacteria (from a probiotic) to grow and persist in the gut varies widely on a person-by-person basis

Basically, the authors showed quite convincingly that the “niche exclusion” effect does indeed happen in the microbiome, and that the degree of niche exclusion is highly dependent on what microbes are present, as well as a host of other unknown factors.

So many more questions

Like any good study, this raises more questions than it answers. What genetic factors determine whether a new strain of bacteria can grow in the gut? Is it even possible to design a probiotic that can grow in the gut of any human? Are the rules for “niche exclusion” consistent across bacterial species or varied?

As an aside, these studies demonstrate the consistent observation that probiotics generally don’t stick around after you take them. If you have to take a probiotic every day in order to sustain its effect, it’s not a real probiotic.

I invite you to read over these papers and take what you can from them. If I manage to put together a more lengthy or interesting summary, I’ll make sure to post it at some point.

Microbiome Research: Hope over Hype

The story of microbiome research is one of hope and hype, both elevated to an extreme and fraught with controversy. You need look no further than popular blogs and high profile review articles to see this conflict play out. 

As a passionate microbiome researcher, I like to highlight the hope that I see -- the hope that humans will be able to understand and harness the microbiome to improve human health. 

The story of hope I have for you today is a story of the heart. The human heart. Well, heart disease. Reducing heart disease, really.

Setup

When I was in graduate school I saw the most fascinating lecture. It was from Stanley Hazen, a researcher at the Cleveland Clinic, and he was describing an experiment in which it appeared that bacteria in the gut were responsible for converting a normal part of our diet into a molecule that promoted atherosclerosis (heart disease). With a combination of (1) molecular analysis of the blood of humans with heart disease and (2) experiments in mice varying the diet and microbes present in the gut, they showed pretty convincingly that bacteria were converting phosphatidylcholine from food into TMAO, which then promoted heart disease (Wang, et al. 2011 Nature). 

Payoff

Fast forward 7 years, and the microbiome research field has advanced far enough to identify the exact bacterial genes involved in this process. Not only that, they are able to inhibit those specific bacterial enzymes and show in a mouse model that levels of harmful TMAO are pushed down as a result (Roberts, et al. 2018 Nature).

Fig. 5: A microbial choline TMA lyase inhibitor reverses diet-induced changes in cecal microbial community composition associated with plasma TMAO levels, platelet responsiveness, and in vivo thrombosis potential. Schematic of the relationship between human gut commensal choline TMA lyase activity, TMA and TMAO generation, and enhanced platelet responsiveness and thrombosis risk in the host

Bioinformatics Aside

One aspect of this story that I'll point out for the bioinformatics folks in the audience is that the biological mechanism involved in choline -> TMAO is not a phylogenetically conserved one. It is mediated by a set of genes that are distributed sporadically across the bacterial tree of life. For that reason and others, I am a strong supporter of microbiome analysis tools that enable gene-level comparison between large sets of samples in order to identify mechanisms like these in the future. 

Summary

My hope, my dream, is that the entire human microbiome field is able to eventually follow this path. We observe that the microbiome influences some aspect of human health, we identify the biological mechanism responsible for this effect, and then we demonstrate our knowledge and mastery of this biology to such an extent that we can intentionally manipulate this system and eventually improve human health. 

We have a long way to go, but I believe that this is the path that we can follow, the example we can aspire to. I hope that this story gives you hope, and helps cut through the hype. 

Hybrid Approach to Microbiome Research (to Culture, and Not to Culture)

I was rereading a great paper from the Huttenhower group (at Harvard) this week and I was struck by a common theme that it shared with another great paper from the Segre group (at NIH), which I think is a nice little window into how good scientists are approaching the microbiome these days. 

The paper I'm thinking about is Hall, et al. A novel Ruminococcus gnavus clade enriched in inflammatory bowel disease patients (2017) Genome Medicine. The paper is open access so you can feel free to go read it yourself, but my super short summary is: (1) they analyzed the gut microbiome from patients with (and without) IBD and found that a specific clade of Ruminococcus gnavus was enriched in IBD; and then (2) they took the extra step of growing up those bacteria in the lab and sequencing their genomes in order to figure out which specific genes were enriched in IBD. 

The basic result is fantastically interesting – they found enriched genes that were associated with oxidative stress, adhesion, iron acquisition, and mucus utilization, all of which make sense in terms of IBD – but I mostly want to talk about the way they figured this out. Namely, they took a combined approach of (1) analyzing the total DNA from stool samples with culture free genome sequencing, and then (2) they isolated and grew R. gnavus strains in culture from those same stool samples so that they could analyze their genomes.

Fig. 3: R. gnavus metagenomic strain phylogeny. 

Now, if you cast your mind back to the paper on pediatric atopic dermatitis from Drs. Segre and Kong (Byrd, et al. 2017 Science Translational Medicine) you will remember that they took a very similar approach. They did culture-free sequencing of skin samples, while growing Staph strains from those same skin samples in parallel. With the cultures in hand they were able to sequence the genomes of those strains as well as testing for virulence in a mouse model of dermatitis.

So, why do I think this is worth writing a post about? It helps tell the story of how microbiome research has been developing in recent years. At the start, all we could do was describe how different organisms were in higher and lower abundance in different body sites, disease states, etc. Now that the field has progressed, it is becoming clear that the strain-level differences within a given species may be very important to human health and disease. We know that although people may contain a similar set of common bacterial species, the exact strains in their gut (for example) are different between people and usually stick around for months and years. 

With this increased focus on strain-level diversity, we are coming up against the technological challenges of characterizing those differences between people, and how those differences track with health and disease. The two papers I've mentioned here are not the only ones to take this approach (it's also worth mentioning this great paper on urea metabolism in Crohn's disease from UPenn), which was to neatly interweave the complementary sets of information that can gleaned from culture-free whole-genome shotgun sequencing as well as culture-based strain isolation. Both of those techniques are difficult and they require extremely different sets of skills, so it's great to see collaborations come together to make these studies possible.

With such a short post, I've surely left out some important details from these papers, but I hope that the general reflection and point about the development of microbiome research has been of interest. It's certainly going to stay on my mind for the years to come.

Journal Club: Discovering new antibiotics with SLAY

This paper is a bit of a departure for me, but even though it's not a microbiome paper it's still one of the most surprising and wonderful papers that I've seen in the last year, so bear with me.

We're looking at Tucker, et al. "Discovery of Next-Generation Antimicrobials through Bacterial Self-Screening of Surface- Displayed Peptide Libraries" Cell 172:3, 2018. (http://www.cell.com/cell/fulltext/S0092-8674(17)31451-4).

When I first learned about this project, I said, "That's a fun idea, but it won't possibly work," to which the PI responded, "We've already done it." 

The extremely cool idea here was to rapidly discover new antibiotics by quickly screening an immense library of novel peptides. The diagram below lays it out: they created a library of peptides, expressed those peptides on the surface of E. coli, and then used genome sequencing to figure out which of those peptides were killing the bacteria. The overall method is called SLAY, which exceedingly clever.

While this idea seems simple, there are more than a few parts that I thought would be impossibly difficult. They include (a) building a sufficiently large library of peptides, (b) expressing those peptides on the surface of the bacteria and not inside the cell, and (c) making sure that the peptides were only killing the cells they were tethered to and not any neighbors. 

I won't go through the entire paper, but I will say that the authors ended up doing quite a bit of work to convince the readers that they actually discovered new antimicrobial peptides, and that they weren't observing some artifact. At the end of the day it seems pretty irrefutable to me that they were able to use this entirely novel approach in order to identify a few new antibiotic candidates, which typically takes hundreds of millions of dollars and decades of work. 

In short, it looks like smart people are doing good work, even outside of the microbiome field. I'll definitely be keeping an eye on these authors to see what they come up with next!