You probably already know that skim milk and buttermilk are byproducts of cheese-making. But did you know that whey is another major byproduct of the cheese-making process? Maybe you did. Well, did you know that for each 1 kg of cheese obtained, there are about 9 kg of whey produced as a byproduct?! What in the world is done with all of that whey? And what even is whey? In this week’s episode, Food Science Master’s student Alyssa Thibodeau tells us all about it!
Alyssa making cheese!
Whey is the liquid that remains after milk has been curdled and strained to produce cheese (both soft and hard cheeses) and yoghurt. Whey is mainly water but it also has lots of proteins and fats, as well as some vitamins, minerals, and a little bit of lactose. There are two types of whey: acid-whey (byproduct of yoghurt and soft cheese production) and sweet-whey (byproduct of hard cheese production). Most people are probably familiar with whey protein, which is isolated from whey. The whey protein isolates are only a small component of the liquid though and unfortunately the process of isolating the proteins is very energy inefficient. So, it is not the most efficient or effective way of using the huge quantities of whey produced. This is where Alyssa comes in. Alyssa’s research at OSU is focused on trying to develop a whey-beverage. Because of the small amounts of lactose that are in whey, yeast can be used to ferment the lactose, creating ethanol. This ethanol can then be converted by bacteria to acetic acid. Does this process sound a little familiar? It is! A similar process is involved when making kombucha and the end-product in Alyssa’s mind isn’t too far off of kombucha. She envisions creating an organic, acid-based or vinegar-type beverage from whey.
Morphology of yeast species Brettanomyces anomalus which Alyssa is planning on using for her whey-beverage.
How does one get into creating the potentially next-level kombucha? Alyssa’s route to graduate school has been backwards, one that most students don’t get to experience. While the majority of students get a degree, get a job and then start a family, Alyssa started a family, got a job, and then went to graduate school. On top of being a single mother in graduate school, she is also a first-gen student and Hispanic. To quote Alyssa: “It makes me proud every day that I am able to go back to school as a single mom. In the past, this would have maybe been too hard to do or wouldn’t have been possible for older generations but our generations are progressing and people are making decisions for themselves.”.
Intrigued by Alyssa’s research and personal journey? You can hear all about it on Sunday, January 29th at 7 pm on https://kbvrfm.orangemedianetwork.com/. Missed the live show? You can listen to the recorded episode on your preferred podcast platform!
Tree rings famously reflect the age of the tree, but they can also encode information about the environmental conditions throughout the organism’s life. A similar principle motivates the study of ice cores – traces of the ancient atmosphere are preserved in the massive ice caps covering Earth’s polar regions.
This Sunday’s guest is Olivia Williams, a graduate student here at Oregon State who is helping to uncover the wealth of climate information harbored by polar ice cores. Olivia is a member of the College of Earth, Ocean and Atmospheric Sciences (CEOAS), where she is advised by Christo Buizert. Their lab uses ice cores to study paleoclimatology and heads the Center for Oldest Ice Exploration (COLDEX), a multi-institution NSF collaboration.
Drilling an ice core in the Arctic or Antarctic is an expensive and labor-intensive process. As a result, once they have been studied by project leads, most American ice core samples are centrally managed by the National Ice Core Lab in Denver, CO and carefully allocated to labs throughout the country. Researchers analyze cross-sections of the larger ice core sample for many geochemical features, including dust records, stable isotopes, and evidence of volcanic eruptions. Determining the historical levels of carbon dioxide, methane, and other greenhouse gases is one application of ice core analysis that yields important insights into climate change.
Olivia’s project focuses on “melt layers”, which are formed by a large-scale melting and refreezing event. The frequency and intensity of melt layers help characterize polar summer temperatures, and specifically the number of days above freezing. Typically, researchers use visual examination or optical instruments to locate layers with relatively smooth and bubble-free ice. However, such methods can fail further down in ice cores, where clathrate ice formed by increased pressure excludes all bubbles. In response, the lab of Jeffrey Severinghaus at the Scripps Institution of Oceanography developed a chemical method to serve as a supplement. This technique extracts noble gases from the core and compares the ratio of the heavier (xenon and krypton) to argon, the lightest noble gas. Since the heavier noble gases are more water-soluble, spikes in the relative concentration of krypton and xenon suggest that a melting event occurred.
During a typical day in the lab, Williams takes samples from the ice core stored at -20 C in a large walk-in freezer and handles the samples in chilled ethanol baths. She particularly focuses on ice cores from Greenland and time periods such as the last interglacial period ~120 thousand years ago and the early Holocene ~12 thousand years ago. Since the OSU lab’s noble gas methodology is novel, Olivia’s work involves a lot of design and troubleshooting the extraction line, which extracts the trapped gases. One time, she even had to commission a scientific glassblower for custom cold traps in the extraction line.
Olivia presenting at the International Partnerships in Ice Core Science conference Handling ice quarter core samples in the Wilkinson freezer
Williams’ interest in geology was impressed upon her at an early age, in part by the influence of her grandfather, a longtime science writer for the Seattle Times. Her grandfather’s love for the geology of the Pacific Northwest inspired her to follow in his footsteps as a scientific journalist. At Boston University, Olivia initially planned to major in communications, until she took a seminar on interdisciplinary science communication offered by BU Antarctic Research Lab, together with education and earth sciences majors. This experience helped solidify her interest in geology, and she switcher her major to earth sciences. Her senior research project related to nutrient cycling in salt marshes, but she knew that she eventually wanted to work in polar science and paleoclimatology. Besides her research at OSU, Olivia has stayed active in science communication, serving as the outreach chair for the CEOS graduate student association. She has helped organize education tables at the Corvallis Farmer’s Market. In the future, Olivia hopes to pursue an academic career and continue research and teaching in the field she loves but is open to the full range of earth science career paths.
For more on Olivia’s exciting research and to hear what it is like to drill ice from a lava formation, tune in this Sunday, January 22nd at 7PM on KBVR 88.7 FM or look out for the podcast upload on Spotify!
Correlation does not equal causation. This phrase gets mentioned a lot in science. In part, because many scientists can fall into the trap of assuming that correlation equals causation. Proof that this phrase is true can be found in ice cream and sharks. Monthly ice cream sales and shark attacks are highly correlated in the United States each year. Does that mean eating lots of ice cream causes sharks to attack more people? No. The likely reason for this correlation is that more people eat ice cream and get in the ocean during the summer months when it’s warmer outside, which explain why the two are correlated. But, one does not cause the other. Correlation does not equal causation.
To date, much of the research that has been conducted on LGBTQ+ health has been correlational. Our guest this week, Kalina Fahey, hopes that her dissertation project will play a part in changing this paradigm as she is trying to get more at causation. Kalina is a 5th year PhD candidate in the School of Psychological Science working with her advisors Drs. Anita Cservenka and Sarah Dermody. Her research broadly investigates LGBTQ+ health disparities and how stress impacts health in LGBTQ+ groups. She is also interested in understanding ways in which spiritual and/or religious identities can influence stress, and thereby, health. To do this, Kalina is employing a number of methods, including undertaking a systematic review to synthesize the existing research on substance use in transgender youth, analyzing large-scale publicly available datasets to look at how religious and spiritual identity relates to health outcomes, and finally developing a safe experiment to look at how specific forms of stress impact substance use-related behaviors in real time.
Most of Kalina’s time at the moment is being spent on the experimental portion of her research as part of her dissertation. For this study, Kalina is adapting the personalized guided induction stress paradigm, with the aim of safely eliciting minor stress responses in a laboratory setting. The experiment involves one virtual study visit and two in-person sessions. During the first visit, participants are asked to describe a minority-induced stressful event that occurred recently, as well as a description of a moment or situation that is soothing or calming. After this session, Kalina and her team develop two meditative scripts – one each to recreate the two events or moments described by the participant. When the participant comes back for their in-person sessions, they listen to one of two different meditative scripts and are asked a series of questions regarding their stress levels. Kalina and her team also are collecting saliva and heart rate readings to look at physiological stress levels. This project is still looking for participants. If you are a sexual-minority woman who drinks alcohol, consider checking out the following website to learn more about the study: https://oregonstate.qualtrics.com/jfe/form/SV_8e443Lq10lgyX66?fbclid=IwAR3XOdECIOvCbx1xn3QA5rrCtHfSezZrR5Ppkpnd9sx1SsicZRQnfYHAqb8. Kalina hopes to continue experiment-based research on LGBTQ+ health disparities in the future as she sees the lack of experimental studies to be a major gap in better understanding, and thereby supporting, the LGBTQ+ community.
Interested in learning more about Kalina’s research, the results, and her background? Listen live on Sunday, January 15, 2023 at 7 PM on 88.7 KBVR FM. Missed the live show? You can download the episode on our Podcast Pages! Also, check out her other work here or finder her on Twitter @faheypsych
We eat food to keep ourselves happy and healthy. While the foods we eat are degraded in our gut, it’s actually little microbes that do most of the work to break down our food. Many many microbes. It is well known that our diet controls our health. But until recently, we have not appreciated the intermediate step that relies on microbes in our gut, and their influence on our health. What if our gut microbes are just as important for human health as the food we eat? The so-called gut microbiome, the unique community of microbes living in our digestive tract that influences how we break down food, is the quickly evolving research area that our guest is interested in. Michael Sieler is a 3rd year Ph.D. student in the Microbiology Department and is interested in better understanding how environmental factors, like rising temperatures and pathogens to name just a few, influence our gut microbiome and thus our health.
Michael Sieler is a 3rd year PhD student in the department of Microbiology at Oregon State University
There are hundreds of different microbial species living in human guts. These microbes work together to support human health by helping us digest our food and fight off pathogenic microbes. Because humans eat a multitude of diets, it can be tricky to figure out how human health is influenced by our gut microbes if the things we eat are not consistent. Instead of forcing humans to undergo rigorous eating and environmental trials – that may even be unethical given how much we’d need to control a human life – researchers like Michael use different organisms that are similar to humans to help understand some of the fundamental drivers of health. While you may be thinking of mice trials to see how toxic a substance is, or if we’ve successfully created a non-hallucinogenic version of psilocybin for therapeutic purposes, mice still have plenty of limitations.
Instead of using mice to run experiments, researchers are increasingly using zebrafish because they’re well studied, easy to grow and maintain, fast to reproduce, and 70% of their genes overlap with human genes so we can generally use these little fish as models of larger humans. For example, we’ve interviewed previous guests like Grace Deitzler researching how the gut microbiome can influence anxiety disorders and the connections to autism spectrum disorder. We’ve also interviewed Sarah Alto who researched how different levels of oxygen and carbon dioxide are connected to stress responses. Finally, Delia Shelton is actively researching how cadmium, a toxic heavy metal, is influencing behavioral patterns. You can imagine these studies would be tricky to perform on humans, that’s why all of these researchers use zebrafish as their model organism.
Michael’s research uses the zebrafish model organism to answer questions about how the gut microbiome influences the health of its host.
Michael’s work focuses on how environmental factors impact our gut microbiome to influence our health. For example, exposure to antibiotics or pathogens can dramatically affect the microbes living in our guts, but so can our diet. Surprisingly, unlike other model organisms such as mice, zebrafish are not fed a consistent diet across research studies and facilities. Given the importance of the gut microbiome to digest food and support our health, inconsistent use of diets in zebrafish microbiome studies could lead to inconsistency in study results. It’s like trying to compare race times for a five-mile race, except some people get to use cars and bikes and unicycles. Without a standard way to compare people, how comparable are the race results? Michael’s current work seeks to address this conundrum by feeding zebrafish one of three commonly used research diets and comparing their microbiomes. He finds that type of diet has an overwhelming effect on their gut microbiome, and these effects may overwhelm the effects of other environmental factors, like pathogen exposure.
What does this mean for the mountain of research built on zebrafish? We’ll answer that, and so much more with our guest Michael Sieler. We’ll also discuss his non-traditional route to graduate school, his love of travel, a side project using a tamagotchi-style video game to teach students about fish health, and how a year in the Guatemalan countryside helped him rethink his relationship to food and how he could have a greater impact in our world. Tune in live on Sunday at 7pm PT on 88.7FM, or check out the podcast if you missed the interview.
In the summer of 2012, the seeds for Michael’s interest in science were planted while working alongside Guatemalan community members and agronomists
Puffy snout syndrome: though it has a cute-sounding name, this debilitating condition causes masses on the face of Scombridae fish (a group of fish that includes mackerel and tuna.) Fish afflicted with puffy snout syndrome (PSS) develop excessive collagenous tumor-like growths around the eyes, snout, and mouth. This ultimately leads to visual impairment, difficulty feeding, and eventual death. PSS is surprisingly confined to just fish raised in captivity – those in aquaculture farms or aquariums, for example. Unfortunately, when PSS is identified in aquaculture, the only option is to cull the entire tank — no treatments or cures currently exist.
Left: a mackerel with puffy snout syndrome. Collagenous growths cover the snout and eye. Right: a healthy mackerel. Photos Emily Miller
PSS was first identified in the 1950s, in a fish research center in Honolulu, Hawaii. Since then, there have only been 9 publications in the scientific literature documenting the condition and possible causes, although the fish community has come to the conclusion that PSS is likely a transmittable condition with an infectious agent as the cause. But despite this conclusion, there’s been no success so far in identifying such a cause – tests for parasites, bacterial growth, and viruses have come up empty-handed. That was until a 2021 paper, using high-resolution electron microscopy, found evidence of viral particles in facial tissues taken from Pacific mackerel. Suddenly, there was a lead: could PSS be caused by a virus that we just don’t have a test for yet?
Electron microscopy images showing viral-like particles (red arrows) in facial tissue from Pacific mackerel (Miller et al 2022).
Putting Together the Pieces
To investigate this hypothesis, this week’s guest Savanah Leidholt (a co-author of the 2021 microscopy study) is using an approach for viral detection known as metatranscriptomics. Leidholt, a fourth year PhD candidate in the Microbiology department, sees this complex approach as a sort of puzzle: “Your sample of RNA has, say, 10 giant jigsaw puzzles in it. But the individual puzzles might not be complete, and the pieces might fit into multiple places, so your job is to reassemble the pieces into the puzzles in a way that gives you a better picture of your story.”
Savanah Leidholt, PhD candidate in Rebecca Vega-Thurber’s lab, is looking for evidence of viruses in the tissues of fish with puffy snout syndrome.
RNA, or ribonucleic acid, is a nucleic acid similar to DNA found in all living organisms, But where DNA is like a blueprint – providing the code that makes you, you; RNA is more like the assembly manual. When a gene is expressed (meaning the corresponding protein is manufactured), the double-stranded DNA is unwound and the information is transcribed into a molecule called messenger RNA. This single-stranded mRNA is now a copy of the gene that can be translated into protein. The process of writing an mRNA copy of the DNA blueprint is called transcription, and these mRNA molecules are the target of this metatranscriptomics approach, with the prefix “meta” meaning all of the RNA in a sample (both the fish RNA and the potential viral RNA, in this case) and the suffix “omics” just referring to the fact that this approach happens on a large scale (ALL of the RNA, not just a single gene, is sequenced here!) When mRNA is sequenced in this manner, the researchers can then conclude that the gene it corresponds to was being expressed in the fish at the time the sample was collected.
The process of transcription: making messenger RNA from DNA. Image from Nature Education.
So far, Leidholt has identified some specific genes in fish that tend to be much more abundant in fish from captive settings versus those found in the wild. Could these genes be related to why PSS is only seen in fish in captivity? It’s likely – the genes identified are immune markers, and the upregulation of immune markers is well-known to be associated with chronic stress. Think about a college student during finals week – stress is high after a long semester, maybe they’ve been studying until late in the night and not eating or sleeping well, consuming more alcohol than is recommended. And then suddenly, on the day of the test, they’re stuck in bed with the flu or a cold. The same thing can happen to fish (well, maybe not the part where they take a test!,) especially in captivity – Pacific mackerel, tuna, and other scombrid species susceptible to PSS are fairly large, sometimes swimming hundreds of miles in a single day in the ocean. But in captivity, they are often in very small tanks, constantly swimming in constrained circles. They’re not exposed to the same diversity of other fish, plankton, prey, and landscape as they would be in the wild. “Captivity is a great place to be if you’re a pathogen, but not great if you’re a fish”, says Leidholt.
The results of Leidholt’s study are an exciting step forward in the field of PSS research, as one of the biggest challenges currently facing aquaculture farms and aquariums is that there is no way to screen for PSS in healthy fish before symptoms begin to show. Finding these marker genes that appear in fish that could later on develop PSS means that in the future a test could be developed. If vulnerable fish could be identified and removed from the population before they begin to show symptoms and spread the condition, then it would mean fish farmers no longer have to cull the entire tank when PSS is noticed.
The elusive virus
One of the challenges that remains is going beyond the identification of genes in the fish and beginning to identify viruses in the samples. Viruses, which are small entities made up of a DNA or RNA core and a protective protein coating, are thought to be the most abundant biological entities on the planet Earth – and the smallest in terms of size. They usually get a bit of a bad reputation due to their association with diseases in humans and other animals, but there are also viruses that play important positive roles in their ecosystems – bacteriophages, for example, are viruses that infect bacteria. In humans, bacteriophages can attack and invade pathogenic or antibiotic-resistance bacteria like E. coli or S. aureus (for more information on phages and how they are actually studied as a potential therapy for infections, check out this November 2021 interview with Miriam Lipton!) Across the entire planet there are estimated to be between 10^7 to 10^9 distinct viral species – that’s between 10 million and 10 billion different species. And fish are thought to host more viruses than any other vertebrate species. Because of technological advancements, these viral species have only really been identified very recently, and identification still poses a significant challenge.
As a group, viruses are very diverse, so one of the challenges is finding a reliable way to identify them in a given sample. For bacteria, researchers can use a marker gene called the 16S rRNA gene – this gene is found in every single bacterial cell, making it universal, but it also has a region of variability. This region of variability allows for identification of different strains of bacteria. “Nothing like 16S exists for viruses,” Leidholt says. “Intense sequencing methods have to be used to capture them in a given sample.” The metatranscriptomic methods that Leidholt is using should allow her to capture elusive viruses by taking a scorched earth approach – targeting and sequencing any little bit of RNA in the sample at all, and trying to match up that RNA to a virus.
To learn more about Savanah’s research on puffy snout syndrome, her journey to Oregon State, and the amazing outreach she’s doing with high school students in the Microbiology Department, tune in to Inspiration Dissemination on Sunday, November 20th at 7 PM Pacific!
Machines take me by surprise with great frequency. – Alan Turing
This week we have a PhD student from the College of Engineering and advised by Dr. Maude David in Microbiology, Nima Azbijari, to discuss how he uses machine learning to better understand biology. Before we dig in to the research, let’s dig into what exactly machine learning is, and how it differs from artificial intelligence (AI). Both AI and machine learning learn patterns from data they are fed, but the difference is that AI is typically developed to be interacted with and make decisions in real time. If you’ve ever lost a game of chess to a computer, that was AI playing against you. But don’t worry, even the world’s champion at an even more complex game, Go, was beaten by AI. AI utilizes machine learning, but not all machine learning is AI. Kind of like how a square is a rectangle, but not all rectangles are squares. The goal of machine learning is to use data to improve at tasks using data it is fed.
So how exactly does a machine, one of the least biological things on this planet, help us understand biology?
Ten years ago it was big news that a computer was able to recognize images of cats, but now photo recognition is quite common. Similarly, Nima uses machine learning with large sets of genomic (genes/DNA), proteomic (proteins), and even gut microbiomic data (symbiotic microbes in the digestive track) to then see if the computer can predict varying patient outcomes. By using computational power, larger data sets and the relationships between the varying kinds of data can be analyzed more quickly. This is great for both understanding the biological world in which we live, and also for the potential future of patient care.
How exactly do you teach an old machine a new trick?
First, it’s important to note that he’s using a machine, not magic, and it can be massively time consuming (even for a computer) to do any kind of analysis on every element of a massive set. Potentially millions of computations, or even more. So to isolate only the data that matters, Nima uses graph neural networks to extrapolate the important pieces. Imagine if you had a data set about your home, and you counted both the number of windows and the number of blinds and found that they were the same. Then you might conclude that you only need to count windows, and that counting blinds doesn’t tell you anything new. The same idea works with reducing data into only the components that add meaning.
The phrase ‘neural network’ can invoke imagery of a massive computer-brain made of wires, but what does this neural network look like, exactly? The 1999 movie The Matrix borrowed its name from a mathematical object which contains columns and rows of data, much like the iconic green columns of data from the movie posters. These matrices are useful for storing and computing data sets since they can be arranged much like an excel sheet, with columns for each patient and rows for each type of recorded data. He (or the computer?) can then work with that matrix to develop this neural network graph. Then, the neural network determines which data is relevant and can also illustrate connections between the different pieces of data. Much like how you might be connected to friends, coworkers, and family on a social network, except in this case, each profile is a compound or molecule and the connections can be any kind of relationship, such as a common reaction between the pair. However, unlike a social network, no one cares how many degrees from Kevin Bacon they are. The goal here isn’t to connect one molecule to another but to instead identify unknown relationships. Perhaps that makes it more like 23 and Me than Facebook.
TLDR
Nima is using machine learning to discover previously unknown relationships between various kinds of human biological data such as genes and the gut microbiome. Now, that’s a machine you don’t need to rage against.
Excited to learn more about machine learning? Us too. Be sure to listen live on Sunday November 13th at 7PM on 88.7FM, or download the podcast if you missed it. And if you want to stay up to date on Nima’s research, you can follow them on Twitter.
A team of researchers makes its way across the beach on this dark night, lighting their way only with starlight and moonlight. It’s high tide on this small island off the coast of Brazil, and the kind of night when green sea turtles love to come ashore to nest. The turtles fall into a trance-like state after wandering around for hours and finally building their nests, and this is when the team approaches. They take a skin sample, place a temperature logger to measure the nest temperature, and tag the turtle with a nail polish marking for future identification. One member of the team is Vic Quennessen (she/they), the subject of our next episode. Vic is a PhD student in the Department of Fisheries, Wildlife, and Conservation Sciences. Quennessen is a computational researcher on the project but helping out on nights like these is part of the job. Vic’s team collaborates with Projeto TAMAR, a Brazilian nonprofit organization that works to preserve and conserve these endangered animals throughout Brazil since the 1980s.
Vic Quennessen releases their first hatchling!
Sea turtles have no sex chromosomes, and their sex is instead determined by the environmental temperature during incubation. Eggs subjected to higher temperatures are more likely to produce female hatchlings. The point at which the sex ratio of eggs approaches 50/50 is around 29 degrees Celsius, but at just one degree higher, some clutches of eggs produce as high as 90% female hatchlings. As temperatures rise due to climate change, this has resulted in a worrying oversupply of female hatchlings.
Sea turtles are difficult to study due to their long and mysterious life cycles. It is believed that they reach reproductive maturity after around twenty-five years, but only females are readily observed because they return to land to build their nests and lay eggs. In contrast, the males stay out at sea for their entire lives. This complicates any effort to ascertain the true population structure. Sea turtles also live a long time, so there is a lag between changes in the hatchling population and the overall population. Finally, hatchlings lack external reproductive organs or other visible sexual characteristics, so the sex ratios must be estimated using temperature as a surrogate.
Vic has always loved the ocean, and they came to OSU looking to help conserve resources that are threatened, such as fish stocks or sea turtles. While attending UMass Dartmouth for their undergraduate degree, they double majored in computational mathematics and marine biology. Initially these felt like separate interests, until a professor suggested that she apply to a NOAA workshop on marine resources and population dynamics. Here she learned that mathematical methods could be a part of rigorous modeling efforts in population biology. After a gap year dedicated to science education, Vic made her way to Oregon State for a Masters in Fisheries Science. Her advisor, Prof. Will White, persuaded her to stay on for a PhD with an opportunity to study her beloved sea turtles.
Sea turtles visit the beaches of more than eighty countries, but Vic’s fieldwork focuses on a population that nests on a small Brazilian island.
Quennessen’s research seeks to predict how the green sea turtle population will be affected by their looming sex imbalance. Vic uses data collected from over 3000 hatchlings per season, including nest temperature readings as well as the numbers of nesting females, hatchlings, and captured males. They build a mathematical model to explore possible scenarios for the “mating function”, the unknown relationship between the sex ratio and reproductive success. On the one hand it is easy to imagine that such a mismatch could reduce the number of mating pairs and lead to a rapid population decline. On the other, it is not well understood how many breeding males are required to sustain the population, and adaptations in mating behavior could slow the decline in population long enough for the more optimistic climate mitigation scenarios to take effect. In any case, it will take a lot of international cooperation to conserve these ancient marine creatures – green sea turtles nest on the shores of over 80 countries. Vic’s hope is that a mathematical exploration of this question could help reveal the chances of survival for the green sea turtles and possibly inform these conservation efforts.
To learn more about Vic’s research and their other interests, including science education and working with CGE, the graduate student union at OSU, tune in Sunday, Nov 6th at 7pm PST on KBVR 88.7 FM or online!
Missed the show? Don’t worry, you can download this episode via your podcast player of choice here.
Happy Halloween from the ID team! This week we’re chatting about a popular halloweekend beverage: Beer and a “creepy” phenomenon seen in a west coast favorite, IPAs. Hop creep may not mean that there are creepy crawlies in your beer, but it may lead to exploding cans or a beer that’s all trick and no treat. To find out more, we are talking with Cade Jobe on his work on hops maturity and its impact on understanding this spooky problem facing the beer industry.
Cade Jobe, a 1st year masters student in FST
Cade is a 1st year masters student in the Department of Food Science and Technology at OSU, where he works under the advisement of Dr. Tom Shellhammer. In the “Beer”, or “Hops”, lab there are a wide variety of projects on the various components of beer, in addition to offering resources to the brewing industry by running standard analytical measurements on hops. Cade moved to Oregon in pursuit of joining the Hop Lab, after falling in love with home-brewing and embarking upon a career shift from law to food science. While his master’s work is going to be more focused on the impact of wildfire-smoke on hops, his post-baccalaureate work focused on hop maturity, in particular the Citra hop variety.
How does one study the impact of hop maturity? Cade worked with a hop grower in Yakima, Washington to harvest hops from 3 fields at 7 different time points during the hop picking season. These dried samples were then sent back to Corvallis where they underwent standard hop chemical analysis, sensory analysis, and enzymatic analysis.
Cade and team harvesting hops
Cade pelletizing hops
This is all great, but how does it help me drink beer? From the chemical analysis, there are standard components that are measured to give an overall hop quality measure to know if it is going to produce the desired result. From sensory analysis, they can see what aromas are associated with the different maturity levels of the hops and what aromas they would impart in beer. Spoiler: late season hops might identify if you are a vampire! And finally, going back to the exploding beer cans, the enzymatic analysis shows the potential of hop creep occurring so that brewers can mitigate the problem.
Want to learn more about the science behind beer and more on Cade’s research into hops? Tune in Sunday, October 30th, 2022 at 7 PM on KBVR 88.7FM (https://kbvrfm.orangemedianetwork.com) or wherever you get your podcasts!
Also, if you’re interested in learning more about the wide-world of brewing, check out Cade on the “BruLab” podcast.
This blog post was written by Jenna Fryer and posted by Lisa Hildebrand.
Coral reef ecosystems offer a multitude of benefits, ranging from coastline protection from storms and erosion to a source of food through fishing or harvest. In fact, it is estimated that over half a billion people depend on reefs for food, income, and/or protection. However, coral reefs face many threats in our rapidly changing world. Climate change and nutrient input due to run-off from land are two stressors that can affect coral health. How exactly do these stressors impact corals? This week’s guest Alex Vompe is trying to figure that out!
Alex is a 4th year PhD candidate in the Department of Microbiology at OSU, where he is co-advised by Dr. Becky Vega-Thurber and Dr. Tom Sharpton. The goal of Alex’s research is to understand how coral microbe communities change over time and across various sources of stress. While the microbial communities of different coral species can differ, typically under normal, non-stressed conditions, they look quite similar. However, once exposed to a stressor, changes start to arise in the microbial community between different coral species, which can have different outcomes for the coral host. This pattern has been coined the ‘Anna Karenina principle’ whereby all happy corals are alike, however as soon as things start to go wrong, corals suffer differently.
Alex is testing how this Anna Karenina principle plays out for three different coral species (Acropora retusa, Pocillopora verrucosa [also known as cauliflower coral], Porites lobata [also known as lobe coral]) in the tropical Pacific Ocean. The stressors that Alex is investigating are reduction in herbivory and introduction of fertilizer. A big source of stress for reefs is when fish populations are low, which results in a lack of grazing by fish on macroalgae. In extreme situations, macroalgae can overgrow a coral reef completely and outcompete it for light and resources. Fertilizers contain a whole host of nutrients with the intent of increasing plant growth and production on land. However, these fertilizers run-off from land into aquatic ecosystems which can often be problematic for aquatic flora and fauna.
How is Alex testing the effects of these stressors on the corals? He is achieving this both in-situ and in the lab. Alex and his lab conduct field work on coral reefs off the island of Moorea in French Polynesia. Here, they have set up experimental apparatus in the ocean on coral reefs (via scuba diving!) to simulate the effects of reduced herbivory and fertilizer introduction. This field work is conducted three times a year. When not under the water surface, Alex sets up aquaria experiments on land in Moorea using coral fragments, which he has been able to grow in order to investigate the microbial communities more closely. These samples then get processed in the lab at OSU for genomic analysis and Alex uses bioinformatics to investigate the coral microbiome dynamics.
Alex underwater in Moorea
Curious to know more about Alex’s research? Listen live on Sunday, October 23, 2022 at 7 PM on KBVR 88.7FM. Missed the live show? You can download the episode on our Podcast Pages! Also, feel free to follow Alex on Twitter (@AVompe) and Instagram (@vompedomp) to learn more about him and his research.
Around 80,000 years ago, the Earth was in the middle of the late Pleistocene era, and much of Canada and the northern part of the United States was blanketed in ice. The massive Laurentide Ice Sheet covered millions of square miles, and in some places, up to 2 miles thick. Over vast timescales this ice sheet advanced its way across the continent slowly, gouging out what we now know as the Great Lakes, carving the valleys, depositing glacial tills, and transforming the surface geology of much of the southern part of Canada and northern US. Further west, the Cordilleran ice sheet stretched across what is now Alaska, British Columbia, and the northern parts of the Western US, compressing the ground under its massive weight. As these ice sheets depressed the land beneath them, the Earth’s crust bulged outwards, and as the planet warmed and the ice sheets began to melt, the pressure was released, returning the crust underneath to its previous shape. As this happened, ocean water flowed away, resulting in lower sea levels locally, but higher levels across the other side of the planet.
The effects of massive bodies of ice forming, moving, and melting are far from negligible in their impact on the overall geology of the region, the sea level throughout history, and the patterns of a changing climate. Though there are only two ice sheets on the planet today, deducing the ancient patterns and dynamics of ice sheets can help researchers fill the geological record and even make predictions about what the planet might look like in the future. Our guest on Inspiration Dissemination this week is PhD candidate and researcher Schmitty Thompson, of the Department of Geology in CEOAS. Thompson is ultimately trying to answer questions about ice distribution, sea levels, and other unknown parameters that the geologic record is missing during two different ice age warming periods. Their research is very interdisciplinary – Thompson has degrees in both math and geology, and also uses a lot of data science, computer science, and physics in their work. They are using computer modeling to figure out just what the shorelines looked like during this time period around 80,000 years ago.
Schmitty Thompson, fourth year PhD candidate with Jessica Creveling in the Geology Department.
“I use models because the geologic record is pretty incomplete – the further back you go, the less complete it is. So by matching my models to the existing data, we can then infer more information about what the shoreline was like,” they explain. To do this accurately, Thompson feeds the model what the ice sheets looked like over the course of around 250,000 years. They also need to incorporate other inputs to the model to get an accurate picture – variables such as the composition of the interior of the Earth, the physics of Earth’s interior, and even the ice sheets’ own gravitational pull (ice sheets are so massive they exert a gravitational pull on the water around them!)
Using math to learn about ice
The first equation to describe global changes in sea level was published in 1976, with refining throughout the 90s and early 2000s. Thompson’s model builds on these equations in two versions: one which can run in about 10 minutes on their laptop, and another which can take multiple weeks and must run on a supercomputer. The quicker version uses spherical harmonics as the basis function for the pseudospectral formulation, which is basically a complex function that does math and incorporates coefficient representations of the earth’s radius, meridional wave numbers, variation across north/south and east/west, and a few other variables. The short of it is that it can perform these calculations across a 250k time span relatively quickly, but it makes assumptions about the homogeneity of the earth’s crust and mantle viscosity. Think of it like a gumball: a giant, magma-filled gumball with a smooth outer surface and even layers. So while this method is fast, the assumptions that it makes means the output data is limited in its usefulness. When Thompson needs a more accurate picture, they turn to collaborators who are able to run the models on a supercomputer, and then they work with the model’s outputs.
While the model is useful for filling in gaps in the historical record, Thompson also points out that it has uses in predicting what the future will look like in the context of a changing climate. After testing out these models and seeing how sensitive they are, they could be used by researchers looking at much smaller time scales and more sensitive constraints for current and future predictions. “There are still lots of open questions – if we warm the planet by a few degrees, are we going to collapse a big part of Antarctica or a small part? How much ice will melt?”
To learn more about ice sheets, sea levels, and using computer models to figure out how the shoreline looked thousands of years ago, tune in to Schmitty Thompson’s episode on Inspiration Dissemination this upcoming Sunday evening at 7 PM PST. Catch the show live by streaming on https://kbvrfm.orangemedianetwork.com/, or check out the show later wherever you get your podcasts!
Thompson was also recently featured on Alie Ward’s popular podcast Ologies. You can catch up with all things geology by checking out their episode here.
