Ph.D. Student in Microbiology
Schmidt Lab - Aquatic Microbiology
Cornell University
Integrating environmental, genetic, and biochemical data
Microbes are the foundation of healthy freshwater ecosystems and their potential to remediate environmental damage drives my interest in microbial ecology. I use fieldwork, molecular biology, and bioinformatics to study the bacteria that live in freshwater ecosystems, including the Great Lakes (via the EPA CSMI cruises), the Lake Superior National Estuarine Research Reserve (through a NOAA Davidson Fellowship), and at Cornell's own experimental ponds. I study how physical processes (like stratification and circulation) affect the ecological processes of selection, dispersal, and drift in microbial populations and communities. I'm also an R and Julia programmer and teach coding through the Software Carpentries. On this page you can access my publications and some of my personal projects as a bioinformatician. You can also view my CV here. Always happy to chat about bacteria, coding, or freshwater, so please feel free to reach out via BlueSky or email.
I've been lucky to work in diverse research areas, whether studying organisms from the deep ocean to pathogenic virulence. Feel free to peruse my published work on my Google Scholar page
As a current Ph.D. student in the Schmidt Lab, I study the formation, structure, and function of freshwater microbial communities in New York. Current projects include characterizating microbial communities in the Great Lakes and disturbance experiments in Cornell's experimental ponds. Our most recent preprint decsribes on hydrodynamic circulation structures microbial communities across Lake Ontario.
Staphylococcus aureus can be a harmless commensal or a devastating pathogen. That switch from nice to nasty is regulated by a complex mix of two-component systems and nutritional sensors. First, we showed branched-chain fatty acids are required for Staph to become virulent via the two-component system SaeRS. Then we discovered an alternative route to branched chain fatty acids in this manuscript
Ireland is still debating the slippery question of how to regulate seaweed harvesting. Coastal communities have a long history of sustainably managing their seaweed harvest, but new laws increasingly centralize regulatory decisions. In this work, we talked to seaweed harvesters to get their perspective on how their industry should be regulated. I hope it “kelps” you to learn more about seaweed!
When you picture coral, you might imagine sun-drenched reefs populated by sassy little clownfish. But there's a whole world of coral most of us will never get to see. Balanophyllia is a solitary cup coral that looks like a cursed ice-cream cone and flourishes in some of the darkest, coldest waters on Earth. In this work, we characterized the reproduction of this deep-sea coral using histology and SEM.
I'll admit this is a random mix. Maybe you're looking for chemoproteomic profiling of gut bile salt hydrolases using click chemistry?. Or an in-depth look at flavin use by S. oneidensis? Or maybe that one summer where I studied whale pathogens? I hope you enjoy the randomness as much as I did!
One of my favorite ways to spend time is with a cup of tea, my dog in my lap, and a coding project on my computer. Below are a combination of coding projects I've developed in both my work and personal time.
As my first dissertation project, I generated what is currently the most comprehensive survey of bacterial diversity across Lake Ontario, by 16S sequencing microbial samples from two seasons, 15 stations, and multiple depths. You can explore these data using MicrobeMapper, an interactive web app I built to visualize the spatial and seasonal distribution of bacterial taxa across the lake. You can also view downstream data, such as biodiversity estimates, functional predictions, and the associated chemical metadata from the EPA.
I wanted to learn Julia, and what better way to pick up a language than writing a package? CUBScout makes working with codons easy in Julia. You can calculate codon frequency, multiple codon usage bias measures (e.g. B, MILC, and SCUO), and multiple expressivity predictions (e.g. E, MELP, and GCB). For a quick intro, read this demonstration where I explored codon bias in B. subitilis. For a deeper dive, look into thedocumentation
At Cornell, I've worked to develop an inclusive coding community within my department. Working with my PI and numerous volunteer instructors, I've helped organize and teach two-day workshops focused on reproducible data analysis, using the command line, git, and R. You can view the custom curriculum I've developed here. To maintain learner's momentum, I also host weekly Hacky Hours, where students gather for short coding tutorials, data discussions, and coworking sessions. The best part? All Hacky Hour Tutorials are publicly available!
These are smaller projects which I still had a blast creating. My first R package, doublr, allows you to interactively calculate doubling times from growth curve data. This website is probably the dumbest thing I've ever made and I'm so proud of it. I expanded my skills in machine learning and shiny applications to create a website that walks you through imaginary data science projects with my cats.
Thanks again for stopping by! I grew up fishing and camping in Wisconsin, received my B.S. in Microbiology from the University of Minnesota and then traveled to Ireland to complete my M.Sc. in Geography in Galway as a Fulbright Scholar. After spending two years in Washington, D.C. as a research assistant at Georgetown University, I have begun my Ph.D. in Microbiology at Cornell University. Outside the lab, you can find me running/hiking/skiing with my husband, taking care of our animals (2 dogs, 2 cats, and 5 chickens), and absolutely flocking it up in Wingspan.
Feel free to reach out via email at arp277@cornell.edu or on BlueSky at @augustuspendle1.bsky.social