It is well known that microorganisms can have positive or negative interactions with each other in the natural environment. Our research area is about the relationship between microorganisms with the environment. Specifically, we investigated how Antarctic microorganisms living in ice-covered lakes are affected by nutrient limitation. We used the enrichment cultures collected from an ice-covered, […]
B32-P: MBI475: High Salinity Stress on Antarctic Microorganisms
The goal of this research was to study the impact of high salinity stress on enrichment cultures containing algae and heterotrophic bacteria from a lake located in the McMurdo Dry Valleys, Antarctica. The research question – Does high salinity stress affect the phylogenetic diversity of microbial communities in a dry valley lake? – tested the […]
B29-P: MBI 475: An Adventure with Antarctic Enrichment Cultures in Extreme Shade
Lake Fryxell is a perennially ice-covered lake located in the McMurdo Dry Valley, Antarctica. Due to harsh conditions such as low temperature and light, its food web is composed entirely of microbes. In this project, the goal was to investigate the composition of Lake Fryxell’s microbial communities when placed under extreme shade as the abiotic […]
B33-P: The Effects of Heat Stress on an Antarctic Microbial Community
Our research involved enrichment culture samples collected from Lake Bonney in Antarctica. From these sample cultures our research group conducted two separate experiments: how does heat treatment affect the growth, physiology, and diversity of the microbial communities?, and are the isolated bacteria from these samples psychrophilic or psychrotolerant? For the first research project, OD600, countess, […]
B34-P: Chlamydomonas sp. ICE -MDV growth and photosynthetic ability under various stress conditions
Our field of research primarily includes Microbial Ecology, understanding microbial community structure and metabolic diversity in ecosystems based on the nutrients and environmental conditions that primarily drive the ecosystem functions. Antarctic lakes are a perfect resource for studying microorganisms, since the food web in the lake ecosystems consists of microorganisms that have acclimatized to extreme […]
B31-P: Comparing Microbial Parasitic Protists and Predators in Antarctic and Temperate Lakes
Parasitic protists are microbes that invade species and derive substances from them; this can be a positive, negative or neutral relationship (Baron 1996). Microbial predators kill other microbes to use for energy and a carbon source (Perez et. al. 2015). They are vital parts of the Antarctic and temperate lake food webs. It is important […]
B24-P: Twitching for Psilocybin: Evidence for an Entourage Effect in Psilocybin Containing Mushrooms
Preliminary research with psilocybin has shown its potential therapeutic efficacy as a treatment for depression, anxiety, PTSD, and substance use disorders. However, we do not know much about the drug’s pharmacological mechanisms and if related tryptamines, like norbaeocystin, could have similar efficacy or better when administered alone. We also were curious as to if norbaeocystin […]
B26-P: A Novel Optical Method for Quantifying Neural Activity
Assessment of neural activity in awake and behaving animals is notoriously complex, and often challenging for undergraduate students to implement in their research. In the last two years, a new technology has emerged that has dramatically simplified the assessment of neural activity in awake behaving animals, called Fiber Photometry, making it potentially useful in an […]
B25-P: A Novel Circuit Controlling Motivation
To maximize rewards, one must learn what specifically causes those rewards. This learning process is disrupted in numerous psychological disorders, including depression and substance use. Understanding the systems responsible for these processes is key to developing future treatments for psychological diseases. The serotonin and dopamine systems play critical roles in learning and motivation. While these […]
B27-P: Building Dynamic Time Warping in R and Applying It to Time Series Data
Dynamic time warping is an algorithm for comparing two different time series by minimizing the distance between time series. This project explores how dynamic time warping can be applied to the number of Covid-19 cases in 2021 in Ohio and Illinois. The functions associated with dynamic time warping were created and tested in R using […]
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