Image design: Raquel Santamaria Germani, Carleton College
Question: What are the ecological and evolutionary feedbacks that shape the (re)emergence, transmission, and evolution of pathogens — and their genes? Goals: Identify and advance the understanding of how ecological and evolutionary feedbacks shape pathogen dynamics in complex communities. Understand how these eco-evo feedbacks can be leveraged to develop more sustainably manage pathogens and their genes.
Image design: Raquel Santamaria Germani, Carleton College
Antimicrobial resistance in Peri-agricultural systems
Antimicrobial resistance is now considered a critical environmental contaminants, akin to microplastics, ubiquitous, hidden in plain sight, and with unknown impacts on natural systems, prompting global initiatives to understand and mitigate its spread.
Wild polar bears, silverback gorillas, and songbirds in the far reaches of the globe harbor drug-resistant bacteria. These patterns often garner media attention, accompanied by dire predictions about the collapse of antibiotics, biomedicine’s most powerful tools. Should we be alarmed? Are these patterns early warning signals of a deeper ecological and public health crisis, or a benign byproduct of microbial evolution? Are environmental hot spots of antimicrobial resistance (AMR) sources or sinks for pathogens and drug-resistance genes? Despite decades of research, science still lacks the computational frameworks and data needed to answer these urgent questions.
Ultimately, these questions require moving beyond the lab where the vast majority of studies on AMR have and are conducted to fill in fundamental gaps in knowledge surrounding the evolution of microbes (pathogens) in complex ecological systems. However, the microbes themselves, are only part of the story. Through the wonders of horizontal gene transfer, drug resistance genes can transmit among bacterial species (e.g., E. coli to Salmonella) and hosts (e.g., cows to farmworkers). Hence, we also need to fill in gaps surrounding the selective pressures that promote co-selection among genes such as drug resistance genes and mobile genetic elements and pathogens.
Central Question: How does use of antimicrobials, local environmental conditions, and connectivity among environments shape the persistence and evolution of resistance?
We are addressing this question with field work and large-scale field experiments in multiple peri-agricultural systems and a suite of bioinformatic tools, statistical inference, and mathematical models. For example:
Aquaculture & wild fish: How does the use of antimicrobials in Salmon farms and the ‘spill-over’ of drug resistance impact wild fish populations (or is it the other way around - wild fish to Salmon farms)? How are these interactions shaped by land-use change and impacts on ecological interactions within and between hosts? To address these questions, this project combines field sampling, next-generation sequencing, geo-spatial, statistical, and climate modeling. This work is supported by the NSF and spans a gradient across Vancouver Island (one of my favorite places ever).
Berini, Fouilloux et al., in prep
Dairy systems, farmworkers, & agricultural crops. Wisconsin is the second largest producer of dairy in the US. While these efforts produce some of the best cheese in the world (yep, it’s true), they can also have pronounced impacts on surrounding environments and public health. In turn, the surrounding environment and public health effects can have major impact on production systems. Our goal is to use an ecological lens to help identify win-win solutions for farmers. Can we leverage soil management practices to reduce the spread of antimicrobial contaminants (from manure fertilizers) and biocides (from conventional farming practices) to reduce the emergence and spread of drug-resistant pathogens?
Related publications
Agers et al., Scientific Reports 2023
Nickodem et al., in review
Nickodem et al, in prep
Steinberger et al., in prep
Land USE CHange and pathogen transmission in COMPLEX LIFE CYCLE PARASITES
Spatio-temporal variation: some things, some places, all at different times (as opposed to everything, everywhere, all at once).
The uneven distribution of parasites across hosts and landscapes is a common but poorly understood pattern that poses a considerable barrier to accurately predicting and managing diseases. This is in part because transmission is shaped by a complex interplay of ecological, behavioral, and immunological factors and our understanding of how these factors interact and their relative impacts across scales remains fragmentary. These gaps in knowledge are particularly acute for parasites with complex life cycles. The goal of this project is to develop a general framework, informed by empirical data, for understanding and predicting how these different processes operate within multiple hosts and shape parasite transmission and distribution across space and time.
Thanks to recent funding from the NSF and collaborators, Amanda Hund, Dan Bolnick, and Sebastian Schreiber, John Berini, we are integrating lab and field data (across Vancouver Island) with mathematical models to explore multiple drivers of spatio-temporal variation in transmission dynamics in parasites with complex life cycles. We will use a model host-parasite system as a case study to gain mechanistic insight into helminth parasites more broadly.
Related Publications:
Dahmer et al., The Journal of Infectious Diseases 2023
Fouilloux et al., Molecular Ecology Resources 2024
Srinivas et al., in prep
