About Alex Washburne
I'm an ecologist and mathematician son of a microbiologist mother with additional interests in mathematical finance and cultural anthropology. One person's interdisciplinary archipelago is another person's island of expertise - I'm interested in everything that evolves, from microbes and mammals to memes and markets. Understanding evolving systems is necessary to manage everything from microbiomes to financial markets.
Recent Comments
Hi Colin!
Thanks for sharing your thoughts.
As a community ecologist, from the get-go I've laughed at the notion of "healthy" microbiomes from the beginning - what's a "healthy" community? Communities are difficult units of study, and the "microbiome" is a slice of a community defined only by a conserved amplicon being sequenced (though some disagreement on what I just said may depend on whether one hears "microbiome" as "small biome" or "the -ome of the microbi"; as an ecologist, I hear the former). In macroscopic systems, defining a "good" community is silly. Rather, one should look at multifaceted services a community can provide - carbon sequestration, water filtration, edible biomass production, etc. - and there's no a priori reason that one community will maximize all of these services. Hence, if our goal is to define "dysbiosis", then we're sure to fail not because of our technology but because of the simple error in our terminology.
Now, to the point of the broader direction of the field, I think there are rubies in the rubbish. I completely agree that we need to connect these big datasets with microbiological studies and an umpteenth PCoA plot does not tell us which microbes we should cultivate or which genomes we should interrogate. It was my discontent with this state of affairs that motivated me to develop phylofactorization (in PeerJ, and another more comprehensive treatise on the theory coming soon in Ecological Monographs). If we find groups of sequences sharing common ancestry having common associations (say with Crohn's disease, as Yoshiki Vasquez and I did in "Guiding longitudinal sampling of IBD cohorts"), then the connection to microbiology is clear: scan their genomes for traits which may determine microbe-immune system interactions and cultivate some representatives to see how they interface with various structural and immunological components of the ileum.
In other words, I don't think the problem is the abundance of rulers. Rather, it's the failure to use the right mathematical tools which can inform the microbiology you miss. PCoA plots tell us little - they can easily be driven by the noisiest microbes and not the "rare butterflies" which have the precise association we're testing. Compositionality of sequence-counts may seem like an impossible warping of the data, leaving some to put their heads in the sand or throw their arms in the air, but in fact it can be exploited with the right tools for even deeper inferences and theoretical gains: changes in population size must be measured relative to one-another, providing deep connections to special relativity in which we discovered there is no universal reference frame for measuring an object's motion.
I feel that the microbiome big-datasets are a treasure trove of insights for the wise thinker. A pile of Legos may seem like a Jackson Pollock painting to some, but to the engineer with an eye for mechanisms, it's an opportunity to construct something new. The microbiome can help us make new theories of community ecology, new methods for analyzing ecological data, and even new mathematics as surely as those tools Newton, Gauss and Feynman constructed for physical systems. We still need the rulers as surely as physicists still need telescopes, but we also need Pythagorean theorems, calculus, and relativity to help us make mechanistic sense of the things we're measuring.