Below is a transcript of our conversation with Chris Haupt:
David Nicholas:
I'm David Nicholas and this is Central Focus, a weekly look at research activity and innovative work from Central Michigan University students and faculty. Everything ends up in the wastewater. So, during the early stages of the COVID-19 pandemic, it proved to be a valuable resource to try to figure out what COVID was and what it wasn't. Chris Haupt is from Gladwin, Michigan. He is a CMU graduate student in biochemistry and molecular biology. He was one of those who thought that answers could come from that wastewater. And he joined me to tell me more. Were any of the questions that you're asking now being studied then? Was there any thought that there was some connection of tie in between wastewater and numbers related to COVID?
Chris Haupt:
As soon as COVID started, a lot of people had the the (the) mindset that we were going to be studying this for years to come. So luckily, people started collecting wastewater samples, which is a really great thing to study when you're looking at especially global pandemics, because everything ends up in wastewater. So, we can look at the amount of people that have COVID, we can look at COVID numbers by looking at certain indicators in the wastewater, and then also obviously a lot of people ended up in the hospital during this time. So, we see a steep rise in the amount of people being treated for secondary conditions, which they were prescribed antibiotics or being misdiagnosed. And being prescribed antibiotics, which also will end up in the wastewater. So yes, people…
DN:
Misdiagnosed then when we didn't…The full understanding, and so it might have been COVID might have been something else, and we weren't sure?
CH:
Yep, and. And everybody's heard that you can't treat viruses with antibiotics, but still some people don't understand that fully and will get antibiotics when they have viruses and use them. And then that ends up in the wastewater and…
DN:
What do we go into the wastewater expecting to find and was when we were looking at cases of COVID, was that the same? More different from maybe what we knew.
CH:
Before wastewater has all these genes floating around that can convey resistance to antibiotics, and when we prescribe those antibiotics, people go to the bathroom and they'll those antibiotics end up in the. Wastewater they select for resistant strains of bacteria, and then those bacteria, if they find a way to get out of the wastewater not being destroyed, then they can start sicknesses that aren't easily treated. When we have what we had with COVID, where tons of people are going to be treated in hospitals or treating themselves or just, basically adding to the (the) supply of resistance genes. Then we…
DN:
The number of sick people overall just…
CH:
Right. The whole basis of my research is that we expect there to be a positive correlation between the amount of the, the prevalence of COVID and of antibiotic resistance gene. So, if they both increase at a certain a peak time like we're seeing a lot of peak cases right after winter break in those years that we looked at because you know a lot of people are coming back to campus. And they were sick. And they were all here. So, all of that ended up in the wastewater treatment plant that we looked at, which is the Mount Pleasant wastewater treatment plant. So, we would expect there to be a rise in both COVID detection and antibiotic resistance genes. Couple weeks later, a decrease. And then if one peaks, we want to see a peak in the resistance genes. So. We're just looking for a correlation.
DN:
Does the age group did that have any impact one way or the other? I mean disproportionate number of the age group of our campus community. So did that give any signal or or hint of a particular impact if we were looking at a particular age group?
CH:
Luckily, we have data from on campus cases versus off campus cases where we can put the data that we can. Like did as far as the resistance genes against the COVID cases, we need to further look at getting records from hospitalizations and see if we can see any of that information like age or whatever you need. But the (the) biggest indicator and I think (the) probably the most interesting thing is looking at the difference between on campus cases versus off campus cases at any given time.
DN:
Is there another question then that that came out of this or series of questions? Options that would prompt another study.
CH:
Once we finish and we, we see if we have that correlation, then we kind of open a lot of doors and if we do see a positive correlation that they increase and decrease together, then we can look at different areas and see if that holds true to these different areas. And then even further we can go to the hospitals and see about getting actual hospitalization records and track back the source of where these resistance genes are coming from. So yeah, there there's a lot of doors that can be opened based on.
DN:
Our findings, some questions answered and many others with answers coming. Thanks to the work. That you're doing, Chris Hoff. Thanks very much for taking the time to talk with us. We appreciate it.
CH:
Yeah. Thank you.
