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There are so many interesting metabolites that the gut microbiome produces that modulate the immune system. My former startup (Interface Biosciences) was trying to develop a process for identifying and developing these as traditional pharmaceuticals (e.g. small molecule drugs).

One of the big problems with most of these metabolites is that they work better in preventing the emergence of disease pathology than they do in ameliorating it. In other words, they aren't super reverse causal for disease. You'll note that in this study, the design was pretreatment with the beneficial metabolite to prevent injury, rather than rescue once injury occurred ([0], [1]).

It's difficult to make a prophylactic pharmaceutical/intervention - the market is smaller, the therapeutic index must be larger, and the insurance reimbursement is harder to get. I hope that someone smarter can break this open at some point. Natural products are the source of over 50% of approved drugs (though weighted heavily towards antibiotics), and the gut microbiome has really not been explored enough for its natural products.

As a note on the probiotics - be very skeptical of probiotic claims. Even if the microbe actually engrafts in your GI tract (a very big if), the probability that it is producing a given 'good' metabolite is unclear. Microbes have thousands of genes and they are constantly changing metabolism (=the metabolites they excrete) as a function of an innumerable array of factors including: energetic (what food sources are in the GI at that moment?), competitive (what competitor species are they sensing?), immune (what is the host immune state?), and physical (do I sense a high diffusion environment?) factors.

[0] From the abstract: "Here, we report that oral administration of 10-HSA prevented AFB1-induced gut epithelial barrier disruption and preserved mucosal T cell populations.

[1] From the methods: "Mice were randomly assigned into three groups. One group (n = 6) was pretreated with 10-HSA (AstaTech A10837) at 100 mg/kg/day in vehicle for one week and then aflatoxin-β1 (Sigma-Aldrich A6636) dissolved in DMSO (final concentration in water was 0.1%) was added to their drinking water for 21 days at a concentration of 5 mg/L. Another group (n = 6) was pretreated with the vehicle control for 1 week and then aflatoxin-β1 was added to their drinking water for 21 days at a concentration of 5 mg/L. The third group (n = 4) served as the negative control group and received vehicle for 1 week prior to DMSO addition to drinking water for 21 days.

Just wanted to add some color to this good comment.

In the human context we are much closer to being able to culture anything we want. I would estimate that we are at 75% coverage now -- pick a species detected genomically in the human gut (or skin/vagina/nose, etc.) and we are likely to be able to culture it or a type strain of its species 75% of the time. For a long time we overestimated human microbial diversity because of bad genomic methods and error rates with the early 454 and then Illumina sequencers. This error rate, coupled with the fact that we can't easily replicate culture conditions for the vast majority of earth's bacterial biomass (i.e. the deep lithosphere or the oceans) led to this persistent if somewhat untrue description of the unculturability of human microbes.

[0] gives an estimate of 35-65% of human/mouse gut microbes having a culturable representative. This paper is from 2017, and there have been a lot of advancements since then.

[1] is a good non-review paper where they got 73% of the genomically defined species via just a single cultivation medium

There are others, but I finished my PhD in culturomics-related stuff in 2021, and haven't kept up as much as I should. Everything the OP cited about lithospheric, deep ocean, etc. still applies as far as I know. Those environments are just very hard to recreate with their pressure, temperature, and nutrient requirements.

[0] https://doi.org/10.1038/s41564-023-01426-7 [1] https://www.nature.com/articles/nature17645

Edit: typos

The comments on this article take for granted that agricultural use of antibiotics is a key driver of the emergence of antimicrobial resistance (AMR). This is an intuitive and popular explanation, but the magnitude of this effect is not well established.

As an example, [0] is of the best reviews available on the contribution of non-therapeutic antibiotic usage in animal feeds to AMR. Despite the large amount of evidence cited, the authors can't conclude that a ban on animal use of antibiotic class X would lead to Y more years before resistance to X emerges/spreads.

It seems well established that banning use of certain antibiotics as a feed additive would slow the emergence of resistance, but that magnitude of that effect seems totally unknown. There is perhaps a strong precautionary principle argument to be made for banning use of medically important antibiotics as feed additives, but we should be cautious in making any firm conclusions about how much that would impact the medically useful lifetime of existing or new antibiotics.

In a similar vein, the idea that commercial prospects for antibiotic development are limited because agricultural use would cause fast emergence is not supported from what I can find. A very good recent paper [1] discussing failures of antibiotic development in the US in the last 20 years highlights trial, regulatory, and commercial hurdles as key roadblocks to successful commercialization of antibiotics.

[0] https://journals.asm.org/doi/full/10.1128/cmr.00002-11 [1] https://www.nature.com/articles/s41599-024-03452-0

Very cool! This kind of material is potentially very interesting for biotech/lab automation tasks. Any info on surviving sterilization techniques (autoclave, ethylene oxide, clydox, etc)?

The direct role that university research plays in drug development is overstated. The majority of cost and difficulty in pharma is _drug development_ not _drug discovery_. Pharma can do the discovery and the development, academics can only do the development. Absent academia, we'd have less drugs. Absent pharma we'd have no drugs.

Academics focus on drug discovery because it's better aligned with academic incentives and timelines (see this commentary for a brief description [0]). Drug development costs (including clinical trials, extensive and repeated med chem, etc) are borne mostly by drug companies.

Fair data on this is hard to come by because the two main sources have clear conflicts of interest (academics and pharma industry publications). One study Derek covered before (data from 1995-2007) shows only 24% of drug scaffolds were first found at a university and transferred to a biotech or pharma for development [1]. You can break this down further to highlight any story you want to support ('university ID'd drugs more innovative' vs. 'pharma ID'd drugs help more people') but they key point is that combining all the US research leads to only 24% of drug scaffolds that make it to market.

I think everyone acknowledges that outside of finding the scaffolds and the basic biology, pharma is paying the vast majority of clinical trial costs. [2] gives a figure of total NIH funding of clinical trials at 10% of overall (e.g. pharma covers 90%).

I think an argument could be made that the NIH training grants (which pay grad students in the biomedical sciences) subsidize the work force substantially, and might have a higher impact than direct research grants. I couldn't find quantitative data on this with a quick search, but I think this is often overlooked in the discussion.

Finally, a less quantitative pieces make me think the impact of the NIH/government funding is overstated even given the above numbers. In my own field (microbiome), academic research has been almost inimical to the production of quality drugs. For every disease there exists a paper suggesting that a certain gut microbe changes the likelihood/severity/X about that disease. Academic labs have incentives to publish significant results fast, and in the microbiome this has led to a) abysmal signal to noise ratio with very high likelihood of failure to replicate, and b) an epistemic closure about what types of microbiome data matter and how they should be pursued as drugs that is totally divorced from the reality of how drugs are developed. Much of the knowledge base is polluted by low-quality research that has been done for the purpose of publishing. While the NIH spends ~40 billion a year on external research grants [3], I think you have to heavily discount this for the amount of just pure "grad student needs to graduate gotta publish" material that gets produced.

[0] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10812233/ [1] https://www.science.org/content/blog-post/where-drugs-come-n... [2] https://www.fiercebiotech.com/research/report-industry-not-n... [3] https://www.nih.gov/about-nih/what-we-do/budget

Inflammation is an extremely broad term which covers an extremely wide range of chemical responses in the body. You should be _extremely_ skeptical of anything that discusses "inflammation" as a single thing or even an easily understandable set of things. You should also be skeptical of people that link certain diets, nutrients, extracts, etc. to changes in "inflammation".

When people think inflammation they think "inflammation up = oxidative damage". This is the tiniest part of the story. Instead, you should think about the following several things.

1. Every individual component of an inflammatory cascade (=different protein signalling molecules released by cells) has a huge number of different effects. Some component that 'increases inflammation' might cause a certain set of neutrophils to increase oxidative activity in a particular area. That same component, however, might signal to nearby cells to turn on repair genes that close a wound or repair oxidative damage. It might also change the lining of the blood vessels to allow passage of different repair cells or more nutrients to the affected tissue. The bottom line is that if you understand only the "inflammation = oxidative damage" part of this story, you miss the much larger effects this inflammatory cascade is having on the body. In this case, the molecule I am talking about is IL-6; it causes 'inflammation' but it also is the canonical regulator of wound repair in your lungs, skin, and liver. It's a good 'pro-inflammatory' molecule in the right context.

2. Inflammation is not a static measure, it's not a state function. Staying on IL-6 as our example, correct timing of release is critical to cause wound repair in epithelial tissues. If you just see "high IL-6" you can't tell whether that's good or bad. You need to know the local tissue history and where you are in the cycle of damage --> repair.

3. Good neighbors make good fences. You are surrounded (both within and without) by hungry microbes that would love to access the energy your body greedily guards. Your body has two predominant modes of resolving this problem; a) it keeps the microbes out of privileged body spaces (e.g. blood, organs, etc.), b) when they reach those areas it responds to kill them with somewhat indiscriminate oxidative damage. The tradeoff is not "inflammation down --> live in harmony" the tradeoff is "inflammation down --> microbes access privileged body spaces --> inflammation incredibly high to prevent sepsis/bone infection/liver infection/etc". You want certain "inflammatory markers" to be high in the body because they keep nice tight barriers at places where microbes like to leak in (the gut).

4. Studies linking particular nutrients or conditions to "high inflammation" are often very low quality. Even when they are not low quality, it's hard to understand if they are correct in any meaningful sense. Nutrition and chemical exposure are extremely hard to study because you can't do very high quality experiments, you have extremely complex and subtle confounders, and you are operating at spatial scales from individual proteins all the way to the organism level. The chemistry, biology, and physics covered is over such a range that it's really hard to get meaningful mechanistic conclusions. Couple this with the fact that there is a high reward for fad diet/environmental toxicant research (e.g. lots of press, lots of commercial opportunities) and you get a low quality literature.

5. Certain types of chronic inflammation is probably bad, but what is inflammation and what is chronic? You are on solid ground if you stay specific and say something like: "chronic release of canonical 'pro-inflammatory' cytokines IL-4/IL-13 causes atopic dermatitis; contributes to SLE, AK, etc. and blockade of those cytokines with antibodies is an incredibly effective therapy". If you say "sugar causes inflammation and that's bad" it's just much harder to even evaluate what the truth value of that statement is.

This post analogizes between a specific theory of human intelligence and a badly caricatured theory of evolution. It feels like better versions of the arguments for Darwin Machines exist that would not: a) require an unsupportable neuron-centric view of evolution, and b) don't view evolution through the programmers lens.

Essentially, biology uses evolution because it is the best way to solve the problem of prediction (survival/reproduction) in a complex world.

1. This is anthropocentric in a way that meaningfully distorts the conclusion. The vast majority of life on earth, whether you count by raw number, number of species, weight, etc. do not have neurons. These organisms are of course, microbes (viruses and prokaryotes) and plants. Bacteria and viruses do not 'predict' in the way this post speaks of. Survival strategies that bacteria use (that we know about and understand) are hedging-based. For example, some portion of a population will stochastically switch certain survival genes on (e.g. sporulation, certain efflux pumps = antibiotic resistance genes) that have a cost benefit ratio that changes depending on the condition. This could be construed as a prediction in some sense: the genome that has enough plasticity to allow certain changes like this will, on average, produce copies in a large enough population that enable survival through a tremendous range of conditions. But that's a very different type of prediction than what the rest of the post talks about. In short, prediction is something neurons are good at, but it's not clear it's a 'favored' outcome in our biosphere.

It relies on the same insight that produced biology: That evolution is the best algorithm for predicting valid "solutions" within a near infinite problem space.

2. This gets the teleology reversed. Biology doesn't use anything, it's not trying to solve anything, and evolution isn't an algorithm because it doesn't have an end goal or a teleology (and it's not predicting anything). Evolution is what you observe over time in a population of organisms that reproduce without perfect fidelity copy mechanisms. All we need say is that things that reproduce are more likely to be observed. We don't have to anthropomorphize the evolutionary process to get an explanation of the distribution of reproducing entities that we observe or the fact that they solve challenges to reproduction.

Many people believe that, in biology, point mutations lead to the change necessary to drive novelty in evolution. This is rarely the case. Point mutations are usually disastrous and every organism I know of does everything in its power to minimize them. Think, for every one beneficial point mutation, there are thousands that don't have any effect, and hundreds that cause something awful like cancer. If you're building a skyscraper, having one in a hundred bricks be laid with some variation is not a good thing. Instead Biology relies on recombination. Swap one beneficial trait for another and there's a much smaller chance you'll end up with something harmful and a much higher chance you'll end up with something useful. Recombination is the key to the creativity of evolution, and Darwin Machines harness it.

3. An anthropocentric reading of evidence that distorts the conclusion. The fidelity (number of errors per cycle per base pair) of the polymerases varies by maybe 8 orders of magnitude across the tree of life. For a review, see figure 3 in ref [1]. I don't know about Darwin Machines, but the view that 'recombination' is the key to evolution is a conclusion you would draw if you examined only a part of the tree of life. We can quibble about viruses being alive or not, but they are certainly the most abundant reproducing thing on earth by orders of magnitude. Recombination doesn't seem as important for adaptation in them as it does in organisms with chromosomes.

4. There are arguments that seem interesting (and maybe not incompatible with some version of the post) that life should be abundant because it actually helps dissipate energy gradients. See the Quanta article on this [0].

[0] https://www.quantamagazine.org/a-new-thermodynamics-theory-o... [1] Sniegowski, P. D., Gerrish, P. J., Johnson, T., & Shaver, A. (2000). The evolution of mutation rates: separating causes from consequences. BioEssays, 22(12), 1057–1066. doi:10.1002/1521-1878(200012)22:12<1057::aid-bies3>3.0.co;2-w

I came here to post this - he was perfect for that role. He and Robert De Niro played off each other so well.

I think the author's mental model of what makes particulates dangerous is odd.

In part 1 of the post he mentions the molecular size of PFAs, and in part 2 he mentions benzene. I think "size" is not the relevant property - it's "does this molecule get imported into cells and alter some component of their activity". While molecular size is related to this, it's more about presence of transporters on the cells, hydrophobicity of the molecules, how the liver handles them (e.g. phase I/II metabolism) etc.

You can contrast this with asbestos, which is dangerous because it mechanically disrupts mucus clearance in the lungs without being imported into cells (also why asbestos + smoke is very dangerous, but asbestos alone probably not nearly as problematic).

Microplastics increase the surface area for degradation in the body, and thus might increase intestinal (and then blood) concentrations of plastic component chemicals or heavy metals they complex with. However, I think it's mainly a phenomenon of degradation in the intestine and then import into the blood stream. Contrast this with "microplastics get into the bloodstream intact". While there might be some of that going on (e.g. phagocytosis by macrophages, eosinophils, etc) I think it's the wrong mental model.

As a bit of reference, remember that your large intestine contains about 1E13 microbes/gram of digesta, and they are 0.2-2um in size. If the intestine let things of that size in at high rate we'd all have sepsis all the time

Microbiome researcher here. As usual, when a microbiome paper reaches HN, I emerge to urge caution.

You should be extremely skeptical of the larger conclusions drawn from this paper. The biology of Alzheimer's disease (AD) is poorly understood, and the contribution of dietary and microbiome factors are extremely unclear. I think you should treat the evidence from this paper (and shared in this thread) as more like "fails to converge" than "I will use this data to update my priors".

I want to note, first, that the researchers should be commended on clearly communicating their procedures, crafting a well written paper, and doing some nice experiments (in figure 4 particularly). The main criticisms I have relate to the conclusions drawn, and then echoed in this HN thread.

1. The behavioral analysis was not conducted in a blinded way - the researchers doing the behavioral analyses knew if the rats were AD or non-AD groups. From supplement "The experimenter was blinded to the FMT human donor but not to the rat group." The degree to which rodent behavior reflects human behavior is unclear (I would argue very little) but you should definitely be skeptical of measures with significant subjectivity done without blinding.

2. The paper has many materially important assertions not backed by the data.

However, at phylum level, Alzheimer’s patients had a higher abundance of Bacteroidetes (Fig. 1C) reported to comprise many pro-inflammatory species

A phylum is an extremely diverse group of microbes - the phylum Bacteroidetes contains microbes that likely diverged hundreds of millions of years ago (from their LCA). Claiming that an entire phylum is "pro-inflammatory" is not even wrong. The different Bacteroidetes found in humans can be "pro-inflammatory" or "anti-inflammatory" depending on a truly staggering number of factors (diet, what other microbes are there, host immune status, host epithelial integrity). To claim that it's clear that AD patients have more of a "bad phylum" exemplifies the strong claim X weak evidence of this paper.

...and a lower abundance of the phyla Firmicutes and Verruocomicrobiota, reported to produce beneficial metabolites.

Ahh yes, the beneficial metabolites of my favorite Firmicutes - Clostridium botulinum (most toxic metabolite known to man), Clostridium difficile (kills >20,000/year in the US), etc... Again, you can't paint with this broad a brush and have the conclusion mean anything.

Importantly, a positive correlation was observed between the abundance of the health-associated SCFA producer Coprococcus and the MMSE score, and inverse correlations were detected between the abundance of the disease-associated pathobionts Desulfovibrio, Dialister and the MMSE score, supporting a microbiome signature for cognitive performance in Alzheimer’s disease.

Desulfovirbio has evidence of potential linkage to AD (a quick google found correlational, but no causal evidence). On the other hand, a quick google showed that other groups disagree about Dialister - Vogt et al 2017 (PMID: 29051531) find that Dialister is reduced in AD patients and the less Dialister you have, the worse your symptoms! Again, claims stronger (and in this willfully ignoring) than evidence.

3. The main data from this paper is generated in a standard fecal transplant experiment. In short, feces from AD patients is given to some rats, and feces from healthy donors (HD) is given to other rats. Figure 2-4 rely on this setup. These are not independent verifications or tests of the hypothesis "Do AD bacteria --> AD?". Any systematic difference between the feces with the AD label and the HD label could be causal for the results the authors see. This is a major confounder in all microbiome work. Behavioral changes associated with AD are going to change food intake and bowel habit, which in turn will substantially change microbial characteristics of the gut. Other than the microbes, there are a huge number of human derived proteins, metabolites, signaling molecules, viruses, etc in the stool. The researchers don't eliminate these, and their data would be consistent with this as an explanation just as much as the microbes. Even the best studies cannot create a design that blocks every confounder, but FMT paradigm suffers from a really large number of them and the authors don't address this. There are some experiments you can do - for example, you could culture the individual microbes you believe to be responsible for the AD pathology, introduce them into rats, and show the _microbe alone_ is enough to cause the disease (this resolves the last confounder cited). The authors don't do this. There are many other considerations in designing FMT experiments that I could quibble with (like why not germ-free animals - that is the standard rather than the microbiota depletion they do), but the main point is: any systematic difference in AD vs HD feces could cause the differences in rat physiology they observe.

4. Figure 2 is an excellent example of a broader phenomenon in microbiome papers: statistically significant results with extremely small effect sizes. Consider 2D-I. The authors show (for instance) that the mean water content of stool differs significantly in their AD- vs. HD-colonized rats. The effect size is maybe ~12%. Everything in 2G-I is smaller than this. Do we think that losing 12% of the water from feces is a part of the physiological cascade that leads to AD? While this could be true (or this could be evidence of some other underlying change being caused by the AD microbes) the effects are extremely small. I think it's much more likely that some other systematic difference in the feces (as outlined in 3) is causal for these small-scale changes seen.

This is similar to the data in Figure 3. Consider 3B - the AD microbiota induces a (significant) ~0.23% change in the "discrimination index". What size is that effect? It might be large, but considering there is no comparison to differences in whatever the human equivalent of this index is (if it even exists) I am going to guess it's more on the 'too small to be meaningful' side.

These observations were further corroborated by correlating the clinical human donor profile to the Alzheimer’s behavioral readouts of the recipient rats. They test 50 different metadata correlations, don't correct for multiple hypotheses, and find one correlation at p<0.05 and one at p<0.08. This does not match the tone of that sentence.

5. Quoting from the paper: "Rats colonized with faecal material from Alzheimer’s donors exhibited no change in locomotor parameters in the Open Field Test (Supplementary Fig. 6A), no change in anxiety-related behaviours in the Elevated Plus Maze (EPM) (Supplementary Fig. 6B), or in antidepressant-like behaviour in the Forced Swim test (FST) (Supplementary Fig. 6C), indicating no specific effects of the Alzheimer’s human gut microbiota on comorbid features of Alzheimer’s disease in rats." So clearly whatever the effect of the microbiota is, it's not enough to trigger these measures of pathology. Does that suggest that the microbiota causes only some AD features? If you read their abstract "Our findings reveal for the first time, that Alzheimer’s symptoms can be transferred to a healthy young organism via the gut microbiota, confirming a causal role of gut microbiota in Alzheimer’s disease" they certainly don't qualify the result this way.

6. Figure 4 - there are some nice experiments here. They show differences in neuronal survival conditioned on AD or HD feces. There are microbial metabolites that affect neuronal survival that are certainly not linked to AD causally (e.g. the short chain fatty acids). Evaluate this in the context of point 3 above: the authors show differences in neuronal survival, but whether that is due to changes in AD patients microbiome that are _caused_ by the disease (e.g. they eat weird and get weird microbes that don't make short chain fatty acids) rather than _casual for_ the disease cannot be evaluated from this data.

7. Figure 5 has no evidence of microbial cause. The authors show that serum from AD patients injected into rats caused reduced neurogenesis. As outlined in point 3 above - this could be (and seems much more liekly to be) from any of the human-derived factors floating in the blood. They try to address this by saying "gut microbiota composition explains up to 58% of the variance of individual plasma metabolites" and citing a paper (PMID: 36151114) but this is a very misleading citation. First, the authors of the cited paper corrected that figure to 46%. Second, that figure is for a SINGLE metabolite, not the whole plasma metabolome. Quoting from the cited paper "We detected the largest variance explained (46%) for an uncharacterized common metabolite with the provisional identifier X-11850.". The gut microbiome makes a lot of chemicals, but your body makes many many more. The idea that gut-derived metabolites are the predominant thing in the bloodstream is...not correct. The authors similarly try to suggest with figure 6 that because the AD-transplanted rats show a different plasma metabolome, that means the serum injection experiment points to the microbes. This is not causal evidence, and it isn't a test of what they say it is.

I am a drug developer working on identifying novel therapeutics from human skin, oral, and intestinal bacteria.

I love the idea of Manifund - but I think this may not be the best project for it. This proposal needs some review by a biologist. In its current form, I think this is a much less impactful use of money than other things on Manifund.

I love the spirit of this grant but it has big "programmer knows better then pharma" vibes. At a first glance:

1) The original strain (BCS3-L1) is a clinically derived isolate with who knows what properties. Why not just take the well characterized ATCC/DSMZ strain and knock out the lactate dehydrogenase? I am sure the FDA would look more kindly on a better characterized strain - especially since you don't need whatever wild type mutations it has to keep it in the dental microbiome (the lantibiotic does that).

2) Who pays for this? Why? Finding the appropriate payer for a pharmaceutical intervention is difficult. Getting this through FDA trial costs (let's say) $200 million dollars. At the point of sale (PCP, dentist) the competitive product will be...toothpaste and a toothbrush. Getting a patient or insurance to purchase this under current models of care is going to be extremely difficult.

If you are looking for an in depth (pop-sci) dive into the mass extinctions in earth's history definitely check out "The Ends of the World" by Peter Brannen. It covers the five mass extinctions with a good mix of scientific detail and entertaining writing. IIRC it discusses the likelier explanations for Silurian extinctions including disruptions to the carbon-silicate cycle (volcanism -> fresh silicate rocks -> weathering removes CO2 from the atmosphere as ultimately insoluble CaCO3 -> global ice age), anoxia/CO2 drawdown caused by increased phosphorous and other nutrient availability, and others.

"The Ends of the World" stands out as a top disaster book along with Simon Winchester's "Krakatoa" and Sebastian Junger's "The Perfect Storm".

Somewhat self-interested plug here: consider working in metabolomics as well. Metabolomics is where sequencing was in ~2008. The physics and chemistry are pretty well worked out (though many improvements are surely coming in the same way that 454 gave way to Illumina, PacBio, Nanopore, etc.). The software and computational workflows are truly awful, like hard to describe bad. The company that figures out metaboloimcs well is going to command a much larger market than genomics - genomics tells you what's possible, metabolomics tells you actually what's happening.

Microbiome researcher here - I feel like this is the time I get to shine in HN threads.

The Segal and Elinav labs are powerhouses in computational and gnotobiotic microbiome study. They've published several highly cited papers around interactions between diet, the microbiome, and various host parameters. A couple highlights include this [1] 2015 Cell paper predicting host glycemic response from microbial and dietary information, and this [2] 2014 Nature paper identifying artificial sweeteners as a source of glucose intolerance (mediated through the microbiome).

In the current work, they show that two non-nutritive sweeteners (NNS, saccharin and sucralose) impair glucose tolerance, and that the microbiome of individuals most susceptible to NNS-induced glucose-intolerance can transmit some of the phenotype to mice. These data are generated with human cohorts of good size (n=20 per sweetener) over a reasonable time frame (2 weeks of daily NNS administration). Importantly, the levels of NNS that are administered are well below the acceptable daily intake (ADI). For example, sucralose is given at 102 mg/day, about 34% of the ADI of 5 mg/kg, and reasonably close to an estimate of 1.6 mg/kg as average daily consumption in humans (reference in [3]). The strongest data for the paper is with sucralose (and saccharin). The researchers show that consumption of sucralose causes a shift in glycemic response: participants consuming sucralose had higher glucose excursion in a glucose tolerance test (GTT) than those consuming either control diet (Fig 2A, E, F). In addition to GTT changes, sucralose-consuming participants had altered level of 9 identified metabolites (Fig 4B-D).

After establishing these baseline results, the researchers search for mechanism by stratifying the sucralose cohort in the top and bottom responders. These are, respectively, the individuals who show most change from baseline in GTT at the end of intervention (2 weeks) and those that show the least. There are differences in metabolites, as well as the biochemical pathways those metabolites come from (TCA cycle) in these two groups (Fig 4E, F). There are correlations between changes in the microbiome (both specific taxa and functional gene categories) and the changes in measured metabolite levels as well (Fig 5).

In figure 6, the researchers present their strongest data. The researchers inoculate groups of germ-free mice with fecal samples from the sucralose participants from either the baseline or end of intervention. 4 groups of mice receive the feces of the top 1-4 responders (most perturbed GTT), 3 groups receive feces from the bottom 1-3 responders, and each of these is compared to a group receiving baseline feces. The purpose of this test is to see if the microbiome, altered by sucralose administration, can cause impaired glucose tolerance in mice that have never been exposed to sucralose. The researchers show that indeed there is significant glucose-tolerance impairment in mice that receive post-sucralose feeding feces, though interetingly they show that both bottom- and top-responder feces causes this (Fig 6A, G). They show that baseline samples from bottom- and top-responders do not cause differences in glucose tolerance (Fig 8C), showing that something about the sucralose treatment changes microbial composition to promote glucose intolerance. The researchers attempt to find a mechanistic explanation for the differences by comparing groups of mice colonized with top- and bottom-responder (grouped by baseline or end of intervention) feces.

Ultimately, this is an extremely impressive paper representing a lot of work (and many storied I haven't recapped). Like many microbiome papers, I think it oversells the mechanistic and physiologically relevant aspects of the research.

1. The data is presented in ways that maximize statistical significance with very little reference to the scale of the actual change. a. Fig 4 B-D and Fig 5 B, D, F show significant metabolite differences but give no reference to actual changes in blood concentration (also Fig 5 metabolites not significant after FDR correction). Without isotope-dilution mass spectrometry (which this is not), it's hard to tell how large the changes are in the blood metabolites. The relationship between concentration of a metabolite and measured area on a mass spec is a power function (for different metabolites exponents can be less or greater than 1), and so this data may represent a lot of change in concentration or very little. In addition, the authors rely on GTT differences to tell the story, but what is the scale of these changes? It is not clear that there is physiological relevance to this scale of change. b. Many of the metrics used are hard to relate to physiologically relevant quantities and allow researcher degrees of freedom. As an example Fig 3 ordinates the participant samples using a principal components projection of the microbial gene annotations. The loadings determining the ordination - and selected for highlight are shown in Fig 3 G-J. The researchers group several of these loadings into super pathways (e.g. purine metabolism) but it's very hard to tell if this kind of difference reflects a functional capacity change in the microbiome (and certainly gives no data about the actual transcription of these genes). Any of these groupings could be highlighted, allowing a lot of flexibility in the storytelling with no penalization for multiple hypotheses. c. Fig 8J "Spearman correlation of sucrose degradation pathway fold change abundance (day 21/baseline) with fold difference in GTT-AUC of each of the conventionalized mouse groups." This is so far away from physiology it's hard to say what it means.

2. Both Eran Segal and Eran Elinav are co-founders of the company DayTwo - a personalized microbiome company that helps diabetics manage their symptoms with microbiome based analytics and treatments. The paper feels like it explores the 'personalization angle' and the expense of other mechanistic studies. For example, the importance of osmolarity on the microbiome and how phenotypes around osmostress might be contributing to the resulting host phenotypes.

[1] https://www.sciencedirect.com/science/article/pii/S009286741... [2] https://www.nature.com/articles/nature13793?tdc_uid=921043 [3] https://foodinsight.org/everything-you-need-to-know-about-su...

Very cool! Are you a wrapper for Metabolon - e.g. are they doing the untargeted work or do you all have your own LCMS farm? If you ever get interested in adding a microbial metabolites angle to this drop me a line.

Microbiome researcher here. Like many microbiome results - this paper has tantalizing evidence of a powerful and systemic effect, but extremely limited direct evidence. The primary experiment in the paper is the transfer of stool contents from old mice to young mice (and vice versa). The chemical complexity of stool is hard to overstate - it's one of the most chemically diverse environments known. While the microbes are ~75% of the weight of feces (and thus of the fecal transplant) there is a huge complement of other things including host-derived effector molecules, fungal, and viral components. Three things that I think are important to think about:

1) A critical experiment to determine that it is bacteria (or fungal/virus) per se and not a host effector would be the transfer of contents from aged germ-free control mice (mice without microbes of any type). The authors mention a transfer protocol that could be optimized for fungal commensals, but don't address the more important germ-free control.

2) It is hard to characterize individual immune metabolites/signals (e.g. IL-10, IL-6, etc.) as either good or bad. The context determines the effect and they show changes in at least 20 cytokines in Fig 3E. While they focus on IL-6 and TNF, it's not immediately clear those are necessarily a part of pathogenic inflammageing. LBP conversely, seems pretty hard to interpret as anything but evidence of barrier permeability and this result seems strong.

3) It's not clear how much of this effect would sustain over the long term. The amount of time between fecal transplant and mouse sacrifice/result generation was only 18 days. Experiments with such a short duration seem like they might capture an unrelated effect due to some other coincident factor.

Overall, a well done paper with a lot of interesting things, but also reasons to be very skeptical of the magnitude of this effect. As usual, I will end with: you can dramatically improve your microbiome health (whatever that term actually means) by eating a high fiber diet like most humans did for most of evolutionary time.

Interface Biosciences | Chemical biologist/microbiologist/computational drug discovery

Interface Biosciences is an early stage startup focused on identifying novel anti-inflammatory molecules produced by commensal gut and skin microbes. Natural products identified from microbes are still the best source of new drugs (over 50% of scaffold in the last 50 years are natural products) humanity has access to and yet no one has systematically mined the human microbiome for drug-like natural products. Join our Palo Alto based team working to mine the microbiome for the next generation of anti-inflammatory, antibiotic, and anti-cancer therapeutics.

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Edit: formatting.

This seems like a really interesting work in terms of synthesizing and systematizing the known reactions/fluxes in a minimal cell. However, the paper seems to be like many other modeling studies in the field of microbiology - there are either no, or very few testable predictions made. It's hard to think of the model of metabolism this paper presents as valid without at least some idea of it's predictive accuracy. The concordance with previously published results does not seem like very strong evidence.

Or coprolite - a killer with this set of letters.

I don't have much knowledge on supplements or even diet - beyond it's intersection with the microbiome. From the microbial perspective I think traditional dietary stuff is enough - eat fibrous plants and legumes and that's all you need to do.

Fascinating question - also not totally known.

We know that microbes colonize the gut in a somewhat predictable way as a function of age. As a newborn your gut is largely dominated by Bifidobacteria, and this slowly transitions to a more complex community over the next several years of life. Events like early childhood antibiotics, malnutrition, other disease, etc. can alter this trajectory. Interestingly this kind of ecological succession seems to be driven by an interplay of both immune maturation (as your immune system matures it starts being more selective about who it tries to let in) and by chemical processes. The gut becomes more anaerobic as the number of bacteria increase (and transition away from the Bifido dominated state) and that has a strong selective effect on the microbes that will grow well.

For specific commensal bacteria we know some of the mechanisms of colonization - there are particular genetic programs that bacteria turn on when they sense they are in the gut to enhance their ability to be retained and not washed out. These programs include physical attachment, motility, and chemical signalling to try to dampen the local immune response.

Pathogens are extremely good at getting in to the gut despite our best attempts at keeping them out. Salmonella typhimurium is notoriously adept at colonizing the host - the infectious dose you need is maybe 10 microbes taken orally in a susceptible host (compare that to 10 billion microbes/capsule in a probiotic).

For these specific bugs I don't know that much. I am excited to read more.

Absolutely - the chemicals that microbes make in the gut pass into your blood stream and from there access the entire body. There are mechanisms the body uses to ensure these chemicals are detoxified (phase I and phase II metabolism in the liver) and that they are excreted if they reach too high a concentration.

More locally, the enteroendocrine cells (https://en.wikipedia.org/wiki/Enteroendocrine_cell) that line the gut translate much of the internal nutrient state of the gut up to the brain to tell you things about if you should eat, etc.

There is a lot of research on how we could alter satiety by finding the right language that these cells use. There are approved drugs on the market that mimic the activity of these cells (incretin mimetics) to reduce appetite/weight control.

I think it's really hard - we don't know what a healthy state of the microbiome is. There is likely a lot of individuality, what is healthy for me is maybe not healthy for you. This probably has to do with early life immune system development and what we were exposed to as kids.

At a high level we know that diversity of microbial species in the gut (but for instance, not in the vagina) is linked to better overall health state. Is this because of the microbes? Probably not, it's probably that the microbes are a sensor/responding to an overall healthy diet/ecosystem.

In general, there are commercial services to track your microbiome and they are interesting from a data perspective, but I am not sure you will get much health information out of them.

We know the answer to a healthy diet - there are no microbial talismans - but it's just not sexy. Eat lots of plants, less sugar, and exercise. I wish it was as easy to follow this advice as it is to write haha.

Fascinating question - and not one whose answer is known.

Fiber is good for microbes merely by the virtue that humans lack the glycan-degrading enzymes that are necessary to break it down, so it reaches the colon intact where the microbes can eat it. Humans can digest starch (though it can be physically and chemically modified to be harder to digest) but not the hundreds of other types of fibers that are found in a traditional diet.

I think there is good research that shows that higher fiber diets are associated with lower risk of developing a range of metabolic and immune pathologies, but the particular mechanistic linkages are so subtle that it will require absolutely massive studies to identify them. In general, we know that humans used to eat a much higher fiber diet (e.g. the Hadza people eat 70-150 grams of fiber a day), and we believe that produces a much healthier microbial composition.

The paper you cited is really interesting! I haven't read it - but the overall idea that the mucus lining of the gut can be degraded by microbes who are sourcing carbon, energy, and nitrogen from it is well established.

I think there is consensus that some amount of gut barrier integrity is due to microbial signals. This occurs in two ways - 1) our epithelial cells sense microbial products (proteins, carbohydrates, etc.) and respond by tightening the junctions between them. The overall idea being that you want to keep the bacteria in the colon, but you must balance some level of nutrient flow. 2) The goblet cells which produce mucus in the gut, respond to microbial signals to increase or decrease their mucus production.

There is a lot of research going on trying to understand how certain diets cause defective mucus production and in turn how that can allow microbes to get to close to the epithelial lining (usually the mucus is ~100 microns thick) which results in inflammation.

Recent evidence of another function of microbial activity in the gut of hibernating animals. In short, it appears that they help the host supply enough nitrogen for maintaining muscle mass during hibernation: https://www.science.org/doi/10.1126/science.abh2950

I think you hit it on the head - the C. diff stuff is good and will meet FDA criteria soon (the phase III data from ECOSPOR was good: https://www.clinicaltrials.gov/ct2/show/NCT03183128).

In general we only have mouse or other animal data for other indications.

There are retrospective analyses of patient cohorts receiving anti-PD1 or anti-CTLA4 therapies which have identified certain microbiome states as supportive of those therapies. I believe that these are probably real effects, though I don't think the particular microbes matter - instead I think it's the metabolites they produce and how those influence resting immune state (https://www.science.org/doi/10.1126/science.abf3363 - but you can find many more).

A paper I really like shows that a specific protein from a common gut microbe (Akkermansia muciniphila) confers resistance to diet induced weight gain, insulin insensitivity, etc. (https://www.nature.com/articles/nm.4236).

In general, I think the majority of microbiome work has been associational and demonstrative of the kind of hypothesis-free science that is prone to all sorts of statistical artifacts and misaligend incentives between truth-finding and paper publishing (garden of forking paths, file-drawer effect, etc. etc.)

There are a variety of strategies being pursued to make pharmaceutical products out of microbiome research. Broadly those are: 1: "bugs as drugs" - genetically engineered microbes that perform some function. The idea here is that having the microbe in situ performing some function will be a much better way to administer a particular compound (or set of compounds), or remove a compound, than a traditional pharmaceutical. Large pharma companies have studied phenylketonuria as a metabolic disease for which the bugs as drugs approach would be great. Find a microbe that consumes phenlyalanine at a high rate and administer it at high levels (or get it to stably engraft in the host) and you have a treatment that would be vastly better than current dietary regimes. 2: "community engineering" - this takes many forms from fecal transplant, to trying to engraft a certain small cocktail of strains, to altering what the in situ community is doing by feeding a probiotic. The idea here is that there are tens of thousands of metabolites that microbes are producing in the gut, and by balancing or tailoring the set of metabolites that are made, you can improve health. Fecal transplants have good data for clearing recurrent C. diff in phase III clinical trials - this is the best developed of the microbial therapeutic strategies currently. Everything else is phase I or before. 3: "microbial natural products" - this is the world I work in (shameless self-promotion - if you want to come work at a very early stage microbiome startup email me at will@interface.bio). The idea here is to find the particular chemicals/metabolites that microbes make that have positive influences on our physiology. Most research here is focused on immune conditions, metabolic syndrome/dietary stuff, though there is increasing interest in depression and other conditions.

At a broad scale, I would say it will be 1-2 years before fecal transplants receive approval as a therapy for recurrent C. diff infection, at least 5 years before a bug-as-drug will be available, and at least 7 years before a microbe-derived natural product is on the market as a pharmaceutical. It takes an incredible amount of work to get from these associational studies to a pharma-grade product.

In the interim, I think there will continue to be a bunch of diagnostics and probiotics companies that (IMO) are bordering on absolute nonsense. There is very little predictive value to the tests supplied by most of these companies, and the data on probiotic efficacy is bad in humans. There is good evidence of probiotic and prebiotic effectiveness in animal husbandry (e.g. fish and livestock) but the data just aren't there in humans.

Gut microbiome researcher here - not involved in this study but happy to answer questions or dig in with anyone interested!

It seems like the manipulations were exceedingly silly. It seems like having the sophont start a nuclear war would be straightforward. It was hard for me to suspend disbelief in the sense that it had planet-sized computational power and the ability to manipulate some information on the subatomic level, but couldn't find a vulnerability in aging nuclear launch protocols? The history of near misses with human controlled nuclear weapons suggests a variety of vulnerabilities exist that wouldn't require e.g. directly hacking into command and control. Could it spoof images/data to a sub? Could it cause hallucinations in a large sensor array that feeds data to Norad or a Chinese/Russian equivalent?

Re MAD: I think a plan to destroy Earth would have been easily approved - much like it was in 1960-now, with ICBM and SSBN retaliatory strike capability. Obviously somewhat different in that those MAD-based nuclear wars would be extinctive but not deny the planet to the trisolarians, but the idea that human governments aren't ready to commit to that seems wrong given our history.

Totally agree with this, the effort to retard development could have been better spent with a myriad of ecosystem destroying actions or geopolitical manipulations. Also just send the indestructible probe to kill every human...

My bigger problem with this book was that the author seems to wholely confuse secrecy for strategy. The entire conceit behind the wallfacers seemed ridiculous to me. The best strategic plan need not be secret (eg MAD). Make it clear that humanity will destroy every planet in the solar system and you've got at least MAD in the centuries the trisolarians will take to arrive.