Fall 2021 Grant Awardees

The Bioremediation of Polyethylene, Polyurethane, Polypropylene and Polystyrene by Aspergillus Niger and Bacillus Subtilis

As the manufacturing and consumption of plastics has continued to increase over the years, plastic debris poses a huge threat to many ecosystems. The amount of plastic accumulating in the environment has been steadily increasing as a result of plastic durability and lightweight nature (1). An estimated 300 million tons of plastic are produced and used yearly (1). Plastics are man-made materials manufactured from polymers or long chains of repeating molecules derived from oil, natural gas, and plants such as corn and sugarcane. In addition to replacing steel in cars, and wood in furniture, plastics have replaced paper and other cellulose-based products for packaging. Biodegradation of these abundant plastics may be the key to controlling this problem (1). A more efficient technique of plastic degradation may be achieved, by understanding the mechanism of polymer degradation. This requires researchers become familiar with how compounds are metabolized by existing organisms, as well as identifying new organisms capable of biodegradation and characterizing their metabolic abilities (2). Biodegradation is a complex natural process to decompose substances and involves several steps: 1) fragmentation of materials into smaller functions (bio-deterioration); 2) secretion of free enzymes and free radical species to cleave oligomers, dimers and monomers (depolymerization), 3) recognitions and reorganization of select molecules (assimilation), and 4) oxidation of simple molecules, and salts from metabolites (mineralization) (3). While a number of bacteria have been found to be excellent at biodegradation relatively few fungi have been identified as capable of plastic decomposition. Polyethylene, polyurethane, and polystyrene are the predominant types of plastics used in industry and manufacturing, and all have shown susceptibility to biodegradation (2). Plastics are polymers generated by the condensation of polyisocyanate resulting in a carbon polymer composed of urethane linkages (2). Alterations in the spacing between urethane linkages, as well at the substitutions, can change the properties of the resulting polymer from linear and rigid to branched and flexible (2). Microorganisms in prolonged contact with plastic wastes have been found to adapt and maximize their degradation potential (4). These microorganisms are “reported to produce some special enzymes viz. intracellular and extracellular, which enable the microbes to disintegrate the polymer into several monomers and dimers, which are being used by the microbes as a carbon source” (7). In this study, special interest will be paid to Aspergillus niger, and Bacillus subtilis for their ability as known degraders. Baseline growth and bioremediation potential of these organisms both on their own and in consortia will be observed against a variety of plastic substrates (polyethylene, polyurethane, polypropylene, and polystyrene). Activity of the microorganisms against the plastic substrates will be observed in the laboratory setting. Understanding the detailed metabolism of the organisms which naturally degrade plastics may shed light on the challenges of removing plastic waste to preserve our environment. Growth Establishment A 6mL starter culture of Bacillus subtilis will be prepared using nutrient broth and placed in the shaking incubator for 24 hrs at 30 ℃ and 220 rpm. 100 μL of the starter culture will be spread on a nutrient agar plate and incubated for 24 hrs at 30 ℃. Two single colonies will then be picked from the plate and a separate glycerol stock will be made for each colony. Aspergillus niger will be rehydrated using 6 mL sterile distilled water and allowed to sit for 24hrs. 100μL of the starter culture will be spread on a Sabouraud Dextrose Agar (SDA) along with 100mg/mL ampicillin plate and incubated at 37 ℃ until growth is observed, 2 weeks, for fungi (2.3.5). Two single colonies will then be picked from the plate and a separate glycerol stock will be made for each colony. Bioremediation Tests Sheets of polyethylene and polyurethane, and shavings of polypropylene and polystyrene will be rinsed with sterile water, dried, weighed and sterilized with 70% Ethanol (4). Establishment of baseline bioremediation properties will be done with nutrient broth for Bacillus subtilis and Sabouraud Dextrose broth with ampicillin for Aspergillus niger. 1g of polyethylene, polyurethane, polypropylene or polystyrene will be added to the culture and growth will be carried out at 30 ℃ for Bacillus subtilis and 37 ℃ for Aspergillus niger for up to six weeks. The plastic sheet or shavings will be removed, cleaned with 70% ethanol and deionized water, dried in the oven for one hour, and weighted every 2 weeks. Once weighted the sheet or shavings will be added back to the culture. From there the degradation can be measured by the weight reduction of the dry samples. Three replicates will be done of polyethylene, polyurethane, polypropylene, and polystyrene with Aspergillus Niger, and Bacillus Subtilis. In addition to the negative control, which will contain only ampicillin in synthetic media, a positive control which contains each type of plastic with ampicillin in synthetic media will be prepared. The controls should show no fungal or bacterial growth and no weight reduction due to degradation. Bioremediation by fungi will be carried out in synthetic Czapek Dox broth (pH 6.8, 100 mg/mL ampicillin) (6). Bioremediation by bacteria will be carried out in Davis broth, a minimal ingredient medium (6). 1g of polyethylene, polyurethane, polypropylene or polystyrene will be added to the culture and growth will be carried out at 30 ℃ for Bacillus subtilis and 37 ℃ for Aspergillus niger for up to six weeks. The plastic sheet or shavings will be removed, cleaned with 70% ethanol and deionized water, dried in the oven for one hour, and weighted every 2 weeks. Once weighted the sheet or shavings will be added back to the culture. From there the degradation can be measured by the weight reduction of the dry samples. Three replicates will be done of polyethylene, polyurethane, polypropylene, and polystyrene with Aspergillus Niger, and Bacillus Subtilis. In addition to the negative control, which will contain only ampicillin in synthetic media, a positive control which contains each type of plastic with ampicillin in synthetic media will be prepared. The controls should show no fungal or bacterial growth and no weight reduction due to degradation.

Comparing Litter Decomposition Across a Gradient of Wetland Health

Background: Coastal wetlands are a vital part of the Great Lakes (Uzarki et al. 2019), by providing habitat, nutrients, fisheries and biodiversity to the ecosystem (Wetzel 1992, Brazner et al. 2000 and Wei et al. 2004). Many species rely on these wetlands for crucial nursery habitat, such as the yellow perch (Parker et al. 2012). In addition to benefiting the ecosystem, coastal wetlands have been estimated to produce 69 billion USD annually to the economy surrounding the Great Lakes (Krantzberg et al. 2008). In the past 100 years, human activities have caused a depletion of wetland habitat by over 50% (Krieger et al 1992) and these activities continue to threaten the remaining wetlands (Trebitz et al. 2007). For the past decade, the US EPA’s Great Lakes monitoring program has been assessing wetland health. The monitoring program has based its categories of wetland health largely on what species can or cannot be found there (Uzarki et al. 2019). This only accounts for the structure of the wetland and doesn’t represent the entire workings of its ecosystem. A functional indicator can aid in determining how it is working or how healthy it is based on its function (Sandin et al. 2009). One common way to test an ecosystem’s functional health, is to measure the rate of plant decomposition (Young et al. 2008, Udy et al. 2006 and Lamberti et al. 2017) because this function is affected by water quality and bacterial communities. Objective: The objective of my senior research is to assess whether current categories of wetland health correspond with the ecosystem’s functional health. This will be done using decomposition across a gradient of wetland health. As an alternative measurement, the number of bacteria feeding on the plant matter will be assessed. I hypothesize that the rate of litter decomposition will be quicker in higher quality wetlands compared to lower quality, and that microbial respiration will be higher in high quality wetlands compared to low quality. Overview of Methods: Litter decomposition will be measured in 12 wetlands during the summer, with 3 categories of health: high, medium and low across the St. Mary’s River, located in the Eastern Upper Peninsula of Michigan. Health categories will be determined using values assigned by the Great Lakes Coastal Wetland Monitoring program based on macroinvertebrates and fishes. Cattails will be used as the plant material as it is commonly found in the coastal wetlands. At least 156 mesh bags will be constructed from 1.27 mm mesh sheets: 20 x 20 cm (Benfield 1996), and each site will contain 13 bags. Ten grams of dried cattail will be weighed and placed in each mesh bag (Lamberti et al. 2017). Bags will be labelled with plastic tags, sealed with a vacuum sealer and tied onto rebar using braided fishing line. (Anderson et al. 2002). Six retrieval periods will take place every few weeks before the water freezes over. Three more retrieval periods will be completed after the ice melts next spring. Once mesh bags are retrieved, they will be dried, weighed, ashed, and re-weighed to determine loss of organic material (i.e., decomposition). The rate of mass loss over time will be used to calculate decomposition rate. On the 6th retrieval, the bacterial community on the plant material will be measured for each wetland. This will be done by measuring the rises and drops in oxygen during periods of light and dark incubation. During the light, photosynthesis will occur, and oxygen levels rise. During the dark, respiration will occur, and oxygen levels fall. Incubation will take place in Ashmun Bay to regulate temperature and sunlight the following morning of retrieval. Dark totes will be placed over light totes and then litter bags will be placed within the totes. This will allow the bags to be exposed to light and dark conditions without moving the bags. One of the tote sets will not contain any mesh bags and will serve as a control of microbial respiration without the litter. DO (dissolved oxygen) loggers will be placed in each shoe box tote to measure DO changes every 30 minutes. Changes in dissolved oxygen during the “dark” period and “light” period will be used to calculate respiration rates for each treatment. An ANCOVA test will be used to differentiate the loss of mass among wetland types over time. The mass loss would be the dependent variable, wetland type is the independent variable, and time is the covariate. The bacterial community gross primary production (GPP) will be calculated adding the oxygen change during the dark (R) by the oxygen change during the light (NPP). Respiration differences across wetland type and time will also be tested using an ANCOVA.

Macroalgae  in Saltwater Aquaponic Systems Reduce Nutrients in Effluent

Saltwater aquaponics is a relatively new area of study as a majority of systems are freshwater. However with growing concern over the lack of freshwater in many countries this setup is becoming the new way to farm in an effort to conserve drinking water and bring food to these areas. Aquaponics is known to conserve over 90% of water and be the sustainable way to raise two food sources that work together. However, effluent from these systems can cause eutrophication in watersheds as well as increase the salinity of the soil when not properly handled. Recent publications as of this year began to look at IMTAs or integrated multi-trophic aquaculture systems as a model in reducing the nutrient load of effluent. The idea of this system is to have three layers from a primary producer all the way to a primary consumer in an effort to reduce the solids into workable energy for macroalgae. IMTA systems have been studied in open ocean settings where they have found that the waste within the round-pens significantly decreased compared to pens without. They also found that the macroalgae grew much faster in this setting than it did on its own in similar growth pens without fish. Therefore, taking this multi-level system to land based shrimp farms could solve their excess nutrient effluent problem while in turn creating multiple avenues for business. To represent the aquaponic system set up each aquarium will have Salicornia europaea, a plant that will aid in nutrient testing as well. These species of plants do not like excess nutrients and have found to grow when there was not an abundance of phosphate or nitrogen in the water. Therefore, their growth rate will be another test outside of basic chemistry testing to see how much nutrients are in the water. This halophyte, or salt marsh plant, is just as much of a delicacy as nori seaweed is in the culinary world. Overall, finding that macroalgae can reduce nutrients in saltwater aquaponic systems there will be possibilities of expanding the field and reducing effluent waste.

Prevalence of Caspase -9 Mutations in the Lung Cancer Population of the Eastern Upper Peninsula

“Cancer is known for being the leading cause of deaths worldwide annually. While being the second most common diagnosed cancer, “lung cancer is the leading cause of deaths worldwide” (Mayo Clinic, 2021). Lung cancer is a type of abnormal cell growth that occurs in the lungs. To put into perspective, almost ten million cancer patients died in 2020, while nearly two million of those deaths were caused by lung cancer (Sung, H., et al., 2021). Therefore, identifying different causes to lung cancer should be prioritized. Today we know there are vast amounts of carcinogens in the world. Carcinogens are environmental factors that cause cancer. One example of this would be cigarettes. In fact, smoking is the best-known cause of lung cancer. On the other hand, lung cancer can also occur in patients’ who have never smoked. This leads to more background research such as; genetic history and other environmental factors to identify causes. Cancer is the development of tumors caused by rapid, uncontrolled proliferation of cells in the body. What causes these cells to rapidly proliferate? The development of cancer, is considered a multiple step process at the cellular level (Cooper, 1970). Mutations are the first step leading into any cancer development. These mutations affect cell division by altering how many proteins are present and their function of regulating how the cells grow, divide and how the protein repairs DNA (Gale, 2020). Once the mutation alters the DNA, continual replication of the altered DNA will occur. This can lead to mass cell division of the abnormal cells causing tumors. One type of mutation causes a proto-oncogene to convert to an oncogene. Proto-oncogenes promote cell growth and the differentiation of cells. This can be viewed as cell activity. When a proto-oncogene is mutated into an oncogene it can be over-active leading to excessive cell proliferation (Gale, 2020). Another type of mutation causes inactivation of tumor suppressor genes. The healthy tumor suppressor genes are part of the cellular balance that promotes apoptosis and inhibits cell division. Balancing the cells growth and death maintains a healthy body. The alteration of apoptosis caused by oncogenes and mutated tumor suppressor genes is the focus of this study. Apoptosis is programmed cell death, and the alterations to apoptosis are highly recognized in affects to human cancers (Olsson and Zhivotovsky, 2011). This form of cell death is controlled by caspases and other regulatory factors. There are a series of caspase genes, ordered by number and categorized into groups based off function. The focus of this study will be towards group II, since it is responsible for apoptosis. Group II is then split into two classes: “initiator (apical) caspases (caspase-2, -8, -9 and -10) and effector (executioner) caspases (caspase-3, -6 and 7)” (Olsson and Zhivotovsky, 2011). In short, the initiator caspase sends off an enzyme that signals the effector caspase to target specific proteins of the unhealthy cell to initiate apoptosis. To specify for this research, the focus will be on the initiator caspase, caspase-9, and polymorphisms or gene alterations that occur to it. There are several polymorphisms or mutations that occur in the caspase genes. Alterations of the caspase genes have been correlated to causing multiple types of cancer as well as lung cancer. Therefore, finding specific mutations linked to specific cancers is difficult. In studies specified to caspase-9 gene alterations, there is a lot of research on polymorphisms rs4645978 and rs4645981 and their link to lung cancer. A few studies have shown a possible correlation, more specifically of the rs4645981 polymorphism to lung cancer. For example, one study suggests a possible correlation to the development of lung cancer (Park, J., et al., 2006). In another study, three polymorphisms of different caspase genes were looked at, and were associated to with the risk of lung cancer (Lee, S.Y., et al., 2010). The possible link between the caspase-9 polymorphisms and lung cancer, could be steps toward finding the other causes of lung cancer. Therefore, the focus of this research will be on finding more data of polymorphisms on the caspase-9 gene in a population that could possibly be correlated to lung cancer. Methods: ​This study will be concentrated to the Eastern Upper Peninsula population, with participation of twenty lung cancer patients and twenty non-lung cancer patients as the control. Lung cancer patients will be identified by War Memorial Hospital Oncology department, and asked if they are interested in participating in the study. A waiver will be given to each participant, explaining the study and noting that identity of participants will not be traced from DNA sample. Each signed waiver will have a code number that matches with the number on a given swab, to keep identities anonymous. The participants will swab the inside of their cheek and place swab back into wrapping, for later testing. The swabs will then be taken to the LSSU lab where DNA extraction and amplification via PCR will take place. ​DNA amplification of the caspase-9 gene will be performed, using polymerase chain reaction (PCR). PCR using specific primers to make copies of targeted regions of the subject DNA. Each cycle doubles the amount of DNA copied. After 25-30 cycles there could be @ one billion copies. This can be repeated for several duplications of the same segment (National Human Genome Research Institute, 2020). Following previous studies, the PCR products will be sent out to Psomagen Inc. to sequence the DNA, to look at several mutations instead of just the two mentioned (Lee, S.Y., et al., 2010). Due to pricing, sending samples to be sequenced is considered the best option for analysis. ​After the DNA sequencing is completed, the base sequence can be analyzed. Each group will be analyzed through a paired T test. This will compare the prevalence of rs4645978 and rs4645981 that occurred in the control group to the prevalence in the lung cancer patients. Once the prevalence can be compared, the total mutation occurrence can be calculated for the population studied in the Eastern Upper Peninsula.

LSSU RobotX

The purpose of this research project is to design and develop an Unmanned Surface Vehicle (USV) mobile robot that is capable of completing the autonomous tasks specified by the 2022 Maritime RobotX Challenge. This competition is open to undergraduate and graduate student teams and will be held in Sydney, New South Wales, Australia. In order to complete these required tasks, the USV will need to be able to autonomously identify and localize different maritime objects, follow paths, hold positions, and communicate data to land stations and another mobile robot. The USV must also be able to correct itself in the presence of wind and waves. The RobotX competition directly advances the field of autonomous maritime operations since these task requirements are active research topics in fields such as ocean engineering and maritime mobile robotics. This is important since oceans and seas are highly dynamic environments that account for 71 percent of the Earth’s surface area. Advancing maritime autonomy will ultimately lead to better mapping of Earth’s oceans, improved data collection, and development of autonomous passenger and freight transportation. In order to complete this project, a Wave Adaptive Modular Vessel (WAM-V) has been granted to LSSU Robotics to serve as the base platform for the USV. The WAM-V is a 16-foot long, catamaran-style vessel with a payload capacity of 485 pounds. To meet the project requirements, the WAM-V will need propulsion, remote control, emergency stop, communication, power, vision, acoustic, and guidance, navigation, and control (GNC) systems. The propulsion system is used to move the vessel and will consist of motors and steering mechanisms. The remote control, emergency stop, and communication systems are used to manually control and shut down the vessel. The power system will consist of on-board batteries that will provide power to the other systems of the vessel. The vision and acoustic systems will use technology such as LiDAR, cameras, and hydrophones to provide information about the surrounding environment to the USV, allowing it to make decisions on how it should behave. The GNC system will consist of a computer that runs control software and a programmable circuit board that sends signals to the other systems of the USV. This research project is a School of Engineering and Technology Senior Design Project for Team AMORE (Autonomous Maritime Operations and Robotics Engineering). Team AMORE has six members.  The faculty advisor for the team is Dr. Edoardo Sarda. As a nontechnical requirement for the project, Team AMORE has created the LSSU RobotX Club. This project will give both team and club members the opportunity to be involved in a multidisciplinary mobile robotics project that involves marketing, working with industry professionals, collaborating with international university students, and competing in an international competition.

Competition Between Lactobacillus Acidophilus and Staphylococcus Aureus in Egg Salad at 27 Degrees C

Staphylococcus aureus is the bacteria responsible for 41% of food poisoning outbreaks (Hernàndez-Cortez et al. 2017). In the United States, there are approximately 241,000 cases of Staphylococcal food poisoning annually (Kadariya 2014). S. aureus is a concern as it is tolerant of high salt and sugar concentrations and produces heat resistant toxins (Kataoka et al. 2015, Hu et al. 2018). One to six hours after ingestion of the toxin causes symptoms including vomiting, diarrhea, fever, and cramping (Asao, 2002, Hu et al. 2007, Kim et al. 2011). Potlucks and picnic foods are at risk for S. aureus contamination as they are left at ambient temperature for hours, promoting the growth of bacteria. 30% of the human population carry S. aureus on their bodies and can spread the bacteria through physical contact and respiratory droplets (Argudín et al. 2010, Asao et al. 2003, Kim et al. 2011). Egg salad is a classic picnic food that is susceptible to S. aureus contamination. Competitive microbial growth between Lactobacillus acidophilus and Staphylococcus aureus may affect the growth of colonies. Lactobacillus produces hydrogen peroxide and lactic acid which has been shown to suppress the growth of S. aureus (Dahiya and Speck 1968, Sameshima et al. 1998). As L. acidophilus is commonly found in yogurts, it can be easily incorporated into the egg salad recipe. The objective is to determine the effect of Lactobacillus acidophilus on the growth of Staphylococcus aureus colonies in egg salad at 27°C. Tryptic Soy Broth, Nutrient Agar, Lactobacilli MRS broth, and Lactobacilli MRS agar will be prepared according to the manufacturer’s instructions. S. aureus ATCC 43300 will be obtained from LSSU frozen bacterial stock. The L. acidophilus from the probiotic capsule will be suspended in broth. Gram staining will be done to confirm the identity of the bacteria after streaking for isolated colonies. The egg salad will be prepared according to the recipe. The sample batch of egg salad will be inoculated with both S. aureus and L. acidophilus. The control batch of egg salad will only be inoculated with S. aureus. The two batches will be incubated at 27 °C for six hours to imitate a summer picnic in Sault Ste. Marie. Three sample replicates will be taken from both batches every hour and spread on an agar plate, then incubated for 24 hours. S. aureus colonies on each plate will be identified and counted. The mean and standard deviation will be taken for each of the three replicates. A scatterplot graph for “Average CFU S. aureus/g vs. time incubated (hrs)” will be made to compare the control to the sample (with L. acidophilus). Standard deviation error bars will be included on the graph for each time point. T-tests will be taken at each time point to determine if the difference in number of colonies of S. aureus per gram of egg salad is significant enough to say that L. acidophilus had an effect. Argudín, M.A., M.C. Mendoza and M.R. Rodicio. 2010. Food Poisoning and Staphylococcus aureus Enterotoxins. Toxins 2010(2): 1751-1773. Asao, T., Y. Kumeda, T. Kawai, T. Shibata, H. Oda, K. Haruki, H. Nakazawa and S. Kozaki. 2002. An extensive outbreak of staphylococcal food poisoning due to low-fat milk in Japan: estimation of enterotoxin A in the incriminated milk and powdered skim milk. Epidemiology and Infection 130(1): 33-40. Dahiya, R.S. and M.L. Speck. 1968. Hydrogen Peroxide Formation by Lactobacilli and Its Effect on Staphylococcus aureus. Journal of Dairy Science 51(10): 1568-1572. Hernàndez-Cortez, C. I. Galma-Martínez, L.U. Gonzalez-Avila, A. Guerror-Mandujano, R.C. Solís and G. Castro-Excarpulli. 2017. Food Poisoning Caused by Bacteria (Food Toxins). Pages 33-72 in Poisoning – From Specific Toxic Agents to Novel Rapid and Simplified Techniques for Analysis. N. Malangu (Editor). Intech Open. Hu., D.-L., G. Zhu, F. Mori, K. Omoe, M. Okada, K. Wakabayashi, S. Kaneko, K. Shinagawa and A. Nakane. 2007. Staphylococcal enterotoxin induces emesis through increasing serotonin release in intestine and it is downregulated by cannabinoid receptor 1. Cellular Microbiology 9(9): 2267-2277. Hu, J., L. Lin, M. Chen and W. Yan. 2018. Modeling for Predicting the Time to Detection of Staphylococcal Enterotoxin A in Cooked Chicken Product. Frontiers in Microbiology. 9 (1536): 1-11. Kadariya, J., T.C. Smith and D. Thapaliya. 2014. Staphylococcus aureus and Staphylococcal Food-Borne Disease: An Ongoing Challenge in Public Health. BioMed Research International 2014 (827965): 1-9. Kataoka, A., E. Enache, C. Napier, M. Hayman and L. Wedding. 2016. Effect of Storage Temperature on the Outgrowth and Toxin Production of Staphylococcus aureus in Freeze-Thawed Precooked Tuna Meat. Journal of Food Protection 79(4): 620-627. Kim, N.H., A.-R. Yun and M.S. Rhee. 2011. Prevalence and classification of toxigenic Staphylococcus aureus isolated from refrigerated ready-to-eat foods (sushi, kimbab and California rolls) in Korea. Journal of Applied Microbiology 111: 1456-1464. Sameshima, T., C. Magome, K. Takeshita, K. Arihara, M. Itoh, and Y. Kondo. 1998. Effect of intestinal Lactobacillus starter cultures on the behaviour of Staphylococcus aureus in fermented sausage. International Journal of Food Microbiology 41 (1998): 1-7.

Comparing the Effects of Traditional and E-Cigarette Vapor on Candida Albicans Growth and Virulence Factor Expression

Candida albicans is a prevalent and possibly pathogenic yeast found on most human bodies (Kendrick, 2017). While it typically acts as an interdependent fungus that causes the body no harm, an overgrowth of C. albicans may lead to infection and serious diseases known as candidiasis. As defined by the Center for Disease Control (CDC), candidiasis, also known as oral thrush, is an infection in the oral cavity caused by a Candida species. Symptoms include white patches on the inner cheeks, tongue, roof of the mouth and throat, redness or soreness, loss of taste, and pain while eating or swallowing (CDC, 2021). C. albicans and other Candida species are present in the oral cavity of up to 75% of the population (Ruhnke, 2002). Furthermore, a high incidence of C. albicans has been found in hospital settings. It was the most frequently isolated fungal pathogen (59.7%) in hospital environments (Beck-Sague and Jarvis, 1993). C. albicans has many different factors which increase the degree by which it can cause disease, making it more pathogenic that other Candida species. These factors include its attachment style, ability to change form, antifungal drug resistance, ability to congregate, and its secretion of aspartyl proteinase (Sap). This prevalence and widespread makes the study of C. albicans an important focus in the biomedical field. This research project aims to further explore the secretion of aspartyl proteinase (Sap) as an increased pathogenic factor in C. albicans. Sap is an extracellular enzyme that contributes to the nutrient acquisition, invasion, tissue damage, evasion of host response of C. albicans (Naglik, 2003). For example, the secreted proteinase from C. albicans decreases the antimicrobial defense efficacy of human saliva (Kaminishi, 1995), making C. albicans tough to kill in the oral cavity. Specifically, the SAP2 gene is one of the most commonly expressed genes in patients with oral candidiasis. The introduction of traditional cigarettes in the 1960’s fueled a rise in the smoking of tobacco. However, as time passed, more and more research offered evidence on the harmful long-term health effects of cigarette smoking. It has been linked to multiple neurological, cardiovascular, and pulmonary diseases, as well as health problems such as asthma due to second-hand smoke in children (Das, 2003). While there has been a downward trend in their use, in 2019 the CDC estimated 14.0% (34.1 million) of U.S. adults were current cigarette smokers. Recently, electronic cigarettes (e-cigarettes), also known as vapes, have increased in popularity. They are proposed as a safer alternative to smoking, leading to an e-cigarette acceptability increase by the public (Camenga and Tindle, 2018). Like cigarettes, e-cigarettes have turned into a huge market able to sustain many different product brands. When comparing traditional and e-cigarettes, the key differences is the use of tobacco. Traditional cigarettes contain tobacco while e-cigarettes typically do not. This is one of the primary reasons why they are considered “healthier”. Nonetheless, both products still contain nicotine. Nicotine is the primary addictive ingredient in e-cigarette solutions and tobacco products (Walley, 2019). Non-scientific claims are creating confusion in the public’s perception of the health of e-cigarettes. They are in fact hazardous to human health. Their use can cause multiple symptoms in the respiratory, nervous, gastro-intestinal system, etc. (Meo and Asiri, 2014). Yet, according to the U.S. Food and Drug Administration (FDA), 3.6 million youth still continue to use e-cigarettes today. Previous research has determined the effects that cigarette smoke vapor has on C. albicans. These findings are that cigarette smoke condensate promoted C. albicans growth and SAP2 enzymatic activity (Semlali, 2014). Because both methods of cigarette smoking are still widely used today, more research needs to be done to contribute to public health knowledge. The objective of this study is to compare the effects of traditional and e-cigarette smoke vapor on the growth rate and SAP2 gene expression of C. albicans. We hope to relate these findings to the risk of oral candidiasis with otherwise healthy smokers who contain C. albicans in their oral cavity. To perform this experiment, an in house “smoking device” (Baboni, 2009) will be used to collect cigarette smoke condensate (CSC) for a traditional cigarette group treatment. A 5% nicotine Juul pod liquid will be used for the e-cigarette group treatment. A Gas Chromatography Mass Spectrometry (GCMS) analysis will be performed to measure the amount of trace level nicotine in both treatment liquids to ensure equal amounts. A layer of the CSC and the Juul pod liquid will then be applied to 10 yeast peptone dextrose (YPD) agar plates each. A control group with no additive treatment will also be included. C. albicans will be suspended into a separate YPD broth to ensure ~200 colony forming units (CFU)/mL. 1 mL of this suspension will then be spread onto the surface of the plates and incubated at 37°C to maintain its yeast form. Two plates from each group will be tested at 12 hrs., 24 hrs., 36 hrs., 48 hrs., and 60 hrs. after inoculation. This test will include counting the number of colonies for a growth assessment and running a reverse transcriptase qualitative polymerase chain reaction (rt-qPCR) assessment. The mean number of colonies will be calculated for each group. The growth rates will then be calculated using the equation: Rate = change in number of colonies / time . These results will then be placed into a line graph for clarity. The procedure for the rt-qPCR will be imitated from a similar study performed by Humidah Alanazi, Abdelhabib Semlali, Witold Chmielewski, and Mahmoud Rouabhia in 2019. Firstly, RNA will be extracted and converted into single-stranded cDNA using a purchased High-Capacity cDNA Reverse transcription Kit. The reactions will be prepared by combining the sample RNA with the 2X RT master mix (provided by the kit) and then placing them into the thermo cycler where the cycle conditions include: 10 minutes at 25°C, followed by 120 minutes at 37°C, 5 minutes at 85°C, and then cooling to 4°C. Next, these cDNA samples will be combined with purchased synthetic nucleotide primers (Table 1: SAP2), and a purchased SYBR Green Master mix in order to run the rt-qPCR. The rt-qPCR cycle conditions include: 5 minutes at 95°C, followed by 30 cycles of 15 seconds at 95, 30 seconds at 60, and 30 seconds at 72°C. Finally, the comparative Ct Method of rt-qPCR will be implemented to analyze these results. This method compares the differences between the SAP2 gene Ct values of each sample against a reference gene (Table 1: ACT1) that expresses at a uniform level. The mean of these differences will then be calculated for each group and compared using a one-way ANOVA test. Table 1. Primer Sequences Gene Primer Sequence (3’-5’) Tm(°C) Amp Size (bp) SAP2 Forward: TCCTGATGTTAATGTTGATTGTCAAG Reverse: TGGATCATATGTCCCCTTTTGT 54 82 ACT1 Forward: GACAATTTCTCTTTCAGCACTAGTAGTGA Reverse: GCTGGTAGAGACTTGACCAACCA 57 87

A Correlation Study of ACEs, BCEs, and ASD

Epigenetic factors play a role in gene expression in the offspring of affected parents. At present, no single environmental condition or genetic link has been found to produce humans with a diagnosis of Autism Spectrum Disorder (ASD). Results of this research will help future study efforts in determining the exact cause of ASD worldwide. This study will examine environmental conditions of parents during their childhood to determine whether there is a correlation between benevolent and adverse parental conditions and a diagnosis of ASD in offspring. It is known that there are genetic factors that can play a role in the development of ASD. To eliminate the element of genetic heritability as the cause of ASD, one questionnaire will be supplied which requests information on social personality preferences which would then screen parents for broad autism phenotype, which would signal a possible genetic inheritance as the cause for their child’s development of Autism Additionally, participants will complete two more surveys which asks questions about negative experiences during childhood and positive experiences during childhood. This data will be coded and analyzed using statistical software SPSS to determine if there is an epigenetic link between parental childhood treatment and the production of atypically developing children. This epigenetic effect has already been studied and demonstrated using mouse models and fear conditioning.