Gut Instinct: Human Microbiome May Reveal COVID-19 Mysteries


Days before a national lockdown in the U.S., Daniel McDonald realized his life’s work had put a unique tool in his hands to fight COVID-19.
The assay kits his team was about to have made by the tens of thousands could be repurposed to help understand the novel coronavirus that causes the disease.
McDonald is scientific director of the American Gut Project and the Microsetta Initiative , part of an emerging field that studies microbiomes, the collections of single-cell creatures that make up much if not most of life in and around us. The assay kits were the first to be able to safely take and ship samples from human feces preserved at room temperature.
The kits originally targeted broad research in microbiology. But McDonald and his colleagues knew they needed to pivot into the pandemic.
With careful screening, samples might reveal patterns of how the mutating coronavirus was spreading. That information would be gold for public health experts trying to slow the growth of new infections.
The team also hopes to gather just enough data from participants to let researchers explore another mystery: Why does the virus make some people very sick while others show no symptoms at all?
“Everybody here is absolutely excited about doing something that could help save lives,” said McDonald, part of the 50-person team in Rob Knight’s lab at the University of California, San Diego.
“We are lucky to work close and collaborate with experts in RNA and other areas applicable for studying this virus,” he added.
Hitting the Accelerator at the Right Time
As the kits were taking shape, the group had another stroke of good fortune.
Igor Sfiligoi, lead scientific software developer at the San Diego Supercomputer Center , ported to NVIDIA GPUs the latest version of the team’s performance-hungry UniFrac software, which is used to analyze microbiomes. The results were stunning.
A genetic analysis of 113,000 samples that would have required 1,300 CPU core-hours on a cluster of servers (or about 900 hours on a single CPU) finished in less than two hours on a single NVIDIA V100 Tensor Core GPU – a 500x speedup. A cluster of eight V100 GPUs would cut that to less than 15 minutes.
The port also enabled individual researchers to run the analysis in nine hours on a workstation equipped with an NVIDIA GeForce RTX 2080 Ti . And a smaller dataset that takes 13 hours on a server CPU now runs in just over one hour on a laptop with an NVIDIA GTX 1050 GPU .
“That’s game changing for people who don’t have access to high-performance computers,” said McDonald. For example, individual researchers may be able to use UniFrac as a kind of search tool for ad hoc queries, he said.
With the lab’s cluster of six V100 GPUs, it also can begin to tackle analysis of its expanding datasets.
Sfiligoi’s work on 113,000 samples “arguably represents the largest...

Top