Add Erik Wright Story

2022-12-14-CHTC-Facilitation.md

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2023-11-16-the-pelican-project.md

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 canonical_url: "https://morgridge.org/story/the-pelican-project/"
 
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   path: "https://raw.githubusercontent.com/CHTC/Articles/main/images/researchcomp-pelican.jpg"

2024-11-01-mining-genomes.md

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+---
+title: Mining millions of genomes for the next powerful antibiotic
+
+author: Morgridge Communications
+
+publish_on:
+  - htcondor
+  - path
+  - chtc
+  - osg
+
+type: user
+
+canonical_url: https://chtc.cs.wisc.edu/mining-genomes.html
+
+tag:
+- chtc_featured_article
+
+image:
+  path: "https://raw.githubusercontent.com/CHTC/Articles/main/images/erik-wright.png"
+  alt: Image of Erik Wright
+
+excerpt: Interview of Erik Wright, assistant professor of biomedical informatics at the University of Pittsburgh and his use of the OSPool.
+
+---
+
+Erik Wright, assistant professor of
+biomedical informatics at the University of
+Pittsburgh, spoke to Fearless Science Magazine
+about how his quest to discover new antibiotics
+to counter resistance — and how that pursuit
+has made him biology’s No. 1 user of the Open
+Science Pool for advanced computing.
+
+#### How did an electrical engineer end up as a microbiologist?
+
+After a few years working at Apple as an electrical
+engineer, I decided to go back to grad school and
+switched to environmental engineering. Studying
+water and wastewater treatment introduced me to
+microbes and bacteria and I just fell in love with it. I
+shifted to microbiology for my Ph.D. at UW–Madison,
+and the prerequisite classes felt like I was being
+fed gold nuggets of information. There’s this whole
+invisible universe out there of microorganisms that I
+was completely oblivious to. I found a little niche for
+myself doing biology tied to computing. And now I
+run what I call soggy lab, which is a hybrid wet and
+dry lab together.
+
+#### Why did you decide to make antibiotic resistance the focus of your research work?
+
+The bugs evolve resistance to our drugs. It’s a really
+hard thing to counter, and it’s especially hard to
+reverse. I like that it’s so difficult, that’s probably
+the main draw. I live and breathe the idea that
+resistance is something that can be stopped and
+reversed. I began to study the natural antibiotic producers, the
+microorganisms that we get about 70% of our antibiotics from.
+These organisms have been naturally producing antibiotics for
+about half a billion years at least, and because they’re mostly
+bacteria, they’ve also figured out how to resist them.
+
+#### What are the areas of focus for your lab?
+
+We’re one of the few labs that studies what strategies bacteria
+use to avoid resistance. Then we want to understand how to
+use to avoid resistance. Then we want to understand how to
+bring that strategy to the clinic and scale it up.
+We are studying durability, to understand why some antibiotics
+have been able to avoid resistance. And we are exploring how we
+can prescribe them in a multidrug cocktail such as for HIV and
+tuberculosis. The vast majority of the antibiotics we give are pure
+compounds in a high dose, but that’s only one hurdle for the bug
+to jump over, we want to present them with many hurdles.
+We’re trying to figure out how to work with the existing available
+pool of drugs to do something that’s better than what we
+currently do. And we think that by changing the way we treat
+patients — mimicking the biology that currently exists — then
+maybe we can figure out a more sustainable solution.
+
+#### You are the number one biology user of high throughput computing with the Open Science Pool. How do you integrate computational approaches to tackle antibiotic resistance?
+
+I had the extreme advantage of being part of the Wisconsin
+Institute for Discovery at UW–Madison, so I was an early adopter
+and that has completely changed my career. I’ve been using the
+Open Science Pool for 12 years and we simply could not reach
+the kind of computing capacity we need without it. Because it’s
+open, we don’t have to write grant proposals, which allows us to
+do a lot of exploratory work. I can’t overstate how much that is
+worth to me. It is also set up in a way amenable to my research.
+Instead of shared memory computing, the OS Pool is set up
+with a distributed memory. We like to split up our work into tiny
+compartments that each last an hour, so we hit something like 17
+million jobs last year.
+
+#### Why is your lab so computationally intensive?
+
+The main thing my lab’s doing is comparing genomes by
+processing huge data sets in millions of separate computing
+jobs on the grid. We have access to about 2 million bacterial
+genomes, and we have developed software that can draw on
+thousands of computers to quickly compare new genomes to
+those that already exist. Then other computers store the data,
+and thousands more process and analyze the results — all
+through this gigantic set of grid jobs that is always running.
+We end up having groups of genes that are the same gene
+across different organisms, and then we build software that tells
+us which genes work together. From that we can do things like
+find which groups make natural products like antibiotics.
+We aim to build an ecosystem that will live on the grid, which
+is a little bit of a wild idea, but it will continuously update and
+compute new genomes and add them into a giant comparison
+of all genomes versus all genomes. What we’re ultimately
+going to do is take those groups of genes that work together,
+transplant them into a host organism, and then turn them on and
+see what product they make.
+
+#### What would a dream outcome look like from the research that you’re doing now?
+
+I would like to discover new small molecules that no one has
+known about. And to find totally new drugs if I could. We’ve
+developed ways of finding genes that work together, that
+nobody’s seen before. But we have no idea what antibiotic or
+other compound that makes. It’s on the order of millions of
+different possible compounds and it’s a dream to bring some of
+those to reality. We have developed ways of handling hundreds
+of thousands of genomes, approaching millions, so this is very
+much possible.