Major
Biology
Research Abstract
The novel coronavirus 2019 (COVID-19) pandemic is a stark reminder that we should continue to prioritize ensuring that every one of us maintains the highest quality of health. The biodiversity hypothesis states that living in natural environments is beneficial for the human immune system and nourishes the human microbiome, thereby promoting good health. When people are exposed to diverse microbes from the environment, they develop immunoregulatory markers which promote appropriate responses to pathogenic and non-pathogenic microbes. However, extensive land-use changes to accommodate population spurts in urban cities, are decreasing the area of urban green spaces where people directly interact with nature. Furthermore, due to varying levels of air pollution, urban cities usually record a wide range of air quality between different neighborhoods. The air quality variations in urban cities likely affect the microbial diversity of urban green spaces. My aim is to understand how the aerial microbial diversity of urban green spaces changes with air quality. I will be doing this through a 2-part research project utilizing both secondary and primary research data analysis methods. In the first part of my research, I will explore the current practices in vegetation analysis of urban green spaces and the technologies in tracking air quality for urban cities. In the second part of my research, I will carry out a series of experimental procedures to understand how vegetation and land cover, influence outdoor aerial microbial diversity outdoors under different levels of air quality. I hypothesize that when we have dry weather conditions with wind speeds above 1m/s, the microbial taxa diversity of outdoor air pockets downwind of vegetation in areas of low air quality will be lower, compared to that downwind of vegetation in areas of relatively higher air quality. I plan to collect air samples from selected urban green spaces in San Francisco, extract DNA from the samples, and sequence them to find the microbial taxa present. Using various packages in R and bioinformatics pipelines, I will analyze and visualize the data to understand the relation between urban green space microbial diversity and air quality. To find the microbial abundance, I will use qPCR. I expect that the results from the sampling will show that aerial microbial diversity of urban green spaces varies with air quality, possibly observing higher diversity when the air quality is higher. Well-planned green infrastructure is a population-wide intervention, through which people’s health can be improved. When we know more about how different species of vegetation or types of land cover influence the microbial composition of outdoor air, we can convert allergen-rich environments into human-microbiome-enriching ecosystems everyone can enjoy. This approach helps us reduce the pressure on hospital resources, and prevents sick-days which can negatively impact people’s earning potential, and consequently the economy.
Faculty Mentor/Advisor
Naupaka Zimmerman
Included in
Effect of Air Quality on Outdoor Aerial Microbial Diversity in Urban Green Spaces
The novel coronavirus 2019 (COVID-19) pandemic is a stark reminder that we should continue to prioritize ensuring that every one of us maintains the highest quality of health. The biodiversity hypothesis states that living in natural environments is beneficial for the human immune system and nourishes the human microbiome, thereby promoting good health. When people are exposed to diverse microbes from the environment, they develop immunoregulatory markers which promote appropriate responses to pathogenic and non-pathogenic microbes. However, extensive land-use changes to accommodate population spurts in urban cities, are decreasing the area of urban green spaces where people directly interact with nature. Furthermore, due to varying levels of air pollution, urban cities usually record a wide range of air quality between different neighborhoods. The air quality variations in urban cities likely affect the microbial diversity of urban green spaces. My aim is to understand how the aerial microbial diversity of urban green spaces changes with air quality. I will be doing this through a 2-part research project utilizing both secondary and primary research data analysis methods. In the first part of my research, I will explore the current practices in vegetation analysis of urban green spaces and the technologies in tracking air quality for urban cities. In the second part of my research, I will carry out a series of experimental procedures to understand how vegetation and land cover, influence outdoor aerial microbial diversity outdoors under different levels of air quality. I hypothesize that when we have dry weather conditions with wind speeds above 1m/s, the microbial taxa diversity of outdoor air pockets downwind of vegetation in areas of low air quality will be lower, compared to that downwind of vegetation in areas of relatively higher air quality. I plan to collect air samples from selected urban green spaces in San Francisco, extract DNA from the samples, and sequence them to find the microbial taxa present. Using various packages in R and bioinformatics pipelines, I will analyze and visualize the data to understand the relation between urban green space microbial diversity and air quality. To find the microbial abundance, I will use qPCR. I expect that the results from the sampling will show that aerial microbial diversity of urban green spaces varies with air quality, possibly observing higher diversity when the air quality is higher. Well-planned green infrastructure is a population-wide intervention, through which people’s health can be improved. When we know more about how different species of vegetation or types of land cover influence the microbial composition of outdoor air, we can convert allergen-rich environments into human-microbiome-enriching ecosystems everyone can enjoy. This approach helps us reduce the pressure on hospital resources, and prevents sick-days which can negatively impact people’s earning potential, and consequently the economy.
