Kiefer, Sarah (MU-Student)

By Sarah Kiefer

Could there be a better way to detect colon cancer than a colonoscopy? A less invasive test might depend on its association with microbes in the gut.

University of Missouri researchers looked at the overall microbiome in a rat model of human colon cancer  to discern how differences in the bacteria affect adenomas, benign tumor growth that frequently is precursor to colorectal cancer. Those changes translated into a measurable difference that doctors could one day use to get a jump on this second leading cause of cancer death.

James Amos-Landgraf, an associate professor of veterinary pathobiology, worked with Lloyd W. Sumner, a professor of biochemistry and Bond Life Sciences Center researcher, on a multi-omics approach to analyze the molecules created by cell processes. By measuring large numbers of metabolites — small molecules that act as building blocks or energy sources for an organism — the team found when a unique combination of bacteria and metabolites are present, they correlate with higher susceptibility to colon cancer before any observable symptoms exist.

“In the rat model studies we could classify the severity of the cancer and tumor loads based upon earlier metabolic profiles,” Sumner said. “If you could achieve the same in people, the metabolic profiles could be used as a prognostic tool which would allow better alignment of treatments with the predictive severity. For example, you might want to be more aggressive with treatments in more severe cancer patients.”

Colorectal cancer is the second leading cause of cancer death and, currently, the only way to definitively diagnose it is to get a colonoscopy. If the adenomas are found and dealt with early, the survival rate is high.

This gut microbiome research is one of the projects Amos-Landgraf has been working on for the past 10 years, and the multi-omics approach sets it apart from the microbiome research of peers. Most experiments pick apart one or two bacteria samples and place them into an otherwise germ-free animal to see what happens, but the team wanted to analyze the entire stew of microbes present. Bacterium do not live alone, so what happens when the other bacteria recognize the new guy in the room?

“We know bacteria live in a community just like we do, and not everybody does the same job,” Amos-Landgraf said. “Just like we wouldn’t have the same lifestyle we have without someone providing our electricity, gas, or other utilities, the bacteria have requirements of their own.”

Amos-Landgraf and Sumner looked at this bigger picture, something they first partnered on in 2016. Sumner used his metabolomics expertise to profile and draw conclusions from the rat fecal samples.

“While this paper might not be foundational because other papers have noted several specific metabolites associated with cancers, it is a progressive step in the right direction towards better understanding of the metabolic relationship between the gut microbiome and forms of cancer,” Sumner said.

The analyses helped researchers find similarities and differences in small molecules present in rats with tumors in their colon versus those without.

“I think we have a scientific platform to really study these differences in more detail in a controlled system,” said Amos-Landgraf. “While we can now see a visible difference, this still leaves a lot of challenges to overcome and to answer.”

By looking in tandem at the transcriptome — the full range of messenger RNA that tells cells how to make proteins — they also saw what genes were turned on and off and correlated that with tumor presence. With tumors, they saw increases in biological processes to create bile for fat absorption, fatty acid breakdown and mucin that lubricates the gut. The team found certain species of bacteria in the gut microbiome gave way to specific metabolites and influenced genetic changes that turned off a gene that would normally suppress a tumor.

This sort of analysis is possible because of the advanced tools in MU’s Metabolomics Center.

Previously the way to study gut microbiome within the body was to look at the evidence and build a hypothesis from there in a sequential manner, which takes time and money. Now, the team can perform discovery based metabolic profiling on a larger scale with high resolution instruments that organize and categorize metabolites without having to test and re-test a hypothesis until they find a perfect fit.

“I’m an analytical chemist by training and I like instrumentation, but instruments cost money and they must solve problems,” said Sumner, who is also the director of MU’s Metabolomics Center and professor of agriculture biochemistry at the University of Missouri. “This is a project that utilizes problem solving and new knowledge, making it a measurable outcome. We just need one hundred more like it.”

Metabolic profiling is achieved through a series of a few experiments where the team uses gas and liquid chromatography to separate complex mixtures of metabolites.  For example, gas chromatography uses a small, hollow tube coated on the inside that appears to be a piece of fishing wire to the naked eye. Samples are  injected into the column and they move through this column to ultimately separate in a series based upon chemical interactions specific to each small molecule.

The chromatography system is coupled to a mass spectrometer that serves as a detector and weighs the molecules as they elute or are removed by washing with a solvent.  The molecular weight helps to identify the metabolites.  These methods provide an overview of some 1000 to 1500 metabolites that may change over time.

“A lot of my research is focused on building tools to help with the identification process of these molecules,” Sumner said. “Mass spectrometer will give us an accurate mass and molecular formula, but it doesn’t always tell us how those atoms and molecules are connected together.”

In these situations, they use nuclear magnetic resonance spectroscopy (NMR) which identifies molecules by irradiating and listening to responding radio frequency levels and matching them to a structure.

In 2022, a partnership with Stanford University led to placing a humanized microbiome into a mouse, creating a better model for studying our gut bacteria. Amos-Landgraf wants to do the same thing with their genetically modified animals to see how it affects those susceptible to development of cancer.

The next step for the team is to identify whether this metabolite correlation truly means a direct genetic relationship between these bacterial species, tumors and colon cancer.

The project could lead to more diagnostic tests in order to identify cancers early on in a patient’s history or it could be as simple as prevention through the taking of supplements or probiotics. Getting to the guts of this issue is what the project is all about, so they must take this information and dissect it to draw accurate conclusions.

“Science doesn’t happen in a vacuum and one of the reasons that people stay in science is because they want to solve a piece of the puzzle and step back to study how and why it comes together,” Amos- Landgraf said.

The paper titled, “Integrated multi-omic analyses provide insight into colon adenoma susceptibility modulation by the gut microbiota” by Susheel Bhanu Busi, Zhentian Lei, Lloyd Sumner, and James Amos-Landgraf was first published in the American Society for Microbiology journal mSystems on July 17, 2023.

By Sarah Kiefer

The LED lights danced as the OPEN leaf system powered up. Quickly, the robot zips down the track to its preplanned destination, hovering above each plant sitting atop a 3D-printed mechanism, then the camera snaps a shot as it conducts this same routine every 30 minutes. 

This open source, data driven tool is one way scientists like David Mendoza-Cózatl lab at Bond LSC and work to simplify the tedious data collection required in plant research.  

 The OPEN leaf system — described in The Plant Journal in September 2023 — uses modern technology to do its job better and gather results faster than other machines of the same kind. But this National Science Foundation funded project is more than just a robot taking a picture of a plant.

“Phenotypes are a change in a plant that you can visualize. Our goal is to characterize phenotypes through time,” said Mendoza-Cózatl, a Bond LSC researcher, director of graduate studies and associate professor of Plant Science and Technology at the University of Missouri. “In my mind, time is one of the black boxes that we have not been able to solve because it is variable.”

Color plays a big role in measuring change in a plant. Using color quantization techniques that simplify colors into numbers, researchers can identify four basic colors to analyze. The machine captures RGB (red, green, blue) images using a camera and converts it into a LAB color space to do the heavy lifting. L stands for lightness, whereas A and B represent the green to magenta and blue to yellow color spectrums detected in something like a leaf of the plant. 

 “Color is a subjective thing to a lot of people and it’s a lot easier to look at a number and say this number is more than this number, but saying this color is more yellow than this one is a harder thing to recognize,” said Landon Swartz, the Mizzou computer science graduate research assistant who engineered the system. “Our process correlates the human perception of color which is actually very different from the way a computer sees color.”

When the colors are quantified, then the real work begins — plotting the points.

This procedure morphs a primarily visual measurement into a mathematical one. Just like with numerical data, Swartz can take colors and observe how they change over time by using coordinates from his simplified combinations.

“It’s a really dynamic process and something that’s not thought about a lot, but because no one’s ever done it before, it’s very hard to convince people it’s accurate and try to visualize or explain the process to others,” said. 

Mendoza-Cózatl  said this way of quantifying and recording takes the system to the next level. 

“We thought this idea of describing color through time was solved a long time ago. Turns out, it was not,” Mendoza-Cózatl said. “Extracting the color of a plant has been done, but representing the color to viewers over time is something that has not been done.” 

The team differentiated their system from others by considering a hybrid work environment to allow many collaborators through the Slack communication app. The app can be used to chat directly with the robot itself. 

“We are trying to advance the field of phenotyping as a group,” Mendoza- Cózatl said. “It’s not just my machine, it can be your machine or anyone’s machine.”

Slack was first suggested by Drew Dahlquist, a former undergraduate in the Mendoza-Cózatl  lab, during the COVID-19 pandemic when research labs needed to cut out the middleman on projects that require collaborators from afar. 

“Let’s say I’m sitting in my basement, the experiment is running and I want to know how it’s going. I can message the machine ‘hey, can you send me the last couple of pictures that you took’ and the machine will send them,” Mendoza-Cózatl said. “The element that sets this system apart is you can then share it with colleagues, students, or anyone.”

Swartz and his collaborators worked to incorporate the details of the plant, not just the entire rosette — the circular arrangement of leaves on the plant. Their system recognizes each individual leaf without bias. 

But how can observation of a leaf be biased in the first place?

Traditionally, these systems prompt the user to draw a line around each leaf for it to be recognized, which is a subjective observation based on how each person draws their boundaries. 

The OPEN leaf system’s computer algorithm automatically recognizes each leaf to be analyzed separately. 

“To me it’s really exciting because I was trained as a biochemist then I decided to work with plants. I never thought I would be publishing papers about computer vision and phenotyping,” Mendoza-Cozatl said. “It gives a fantastic example that science is really open. We saw a need, so we tackled the problem and came up with a solution that is very rewarding.”  

Their new machine also makes the database more accessible and cheaper than other similar machines. Costing less than $3,000 to build, the blueprints and instructions to build the OPEN leaf system are accessible to anyone who wants to put it together. 

“This type of project shows that you can do a lot with a little because you don’t need to pay thousands of dollars to get the same amount of insight into your research,” Swartz said. “This project has become a tool that we are going to use for papers to come, and we are hoping that other people will start to use it for their papers as well.” 

 The collaboration between engineers and biologists helped them address the evolving nature and nuanced challenges of the project. 

“The most interesting part about this project is that there is a novelty to working in an interdisciplinary manner like this,” Swartz said. “Usually, how it works is someone comes to you with a problem and you present a solution. But here we are coming up with solutions to find the problems, which I think is a very fruitful approach.”  

Swartz is already working on his next big project — an OPEN root system. This machine will accomplish similar goals but apply to the root system of the plants instead of the leaves. 

The paper titled, “OPEN leaf: an open-source cloud-based phenotyping system for tracking dynamic changes at leaf-specific resolution in Arabidopsis” by Landon Swartz, Suxing Liu, Drew Dahlquist, Skyler T. Kramer, Emily S. Walter, Samuel A. McInturf, Alexander Bucksch, and David G. Mendoza-Cózatl was first published in The Plant Journal on September 21, 2023. 

By Sarah Kiefer | Bond LSC

Marc Libault only ended up one floor up from his old stomping ground in his recent move.

Libault — the most recent MizzouForward hire at Bond Life Sciences Center — returned this fall to bring his expertise in plant single cell biology to MU.

“What is exciting about this research is its innovation to generate a new knowledge in crop science; we’re the first group in the world to develop a very broad application of single cell biology in plants,” said Libault, Bond LSC principal investigator and professor of plant science and technology in the College of Agriculture, Food and Natural Resources. “I was excited to come back here to continue to work on solutions at the single cell level notably by working in collaboration with experts in proteomics, metabolomics, and phenomics at MU.”

Single cell biology is exactly what it sounds like: singling out individual cells in a plant in order to reveal their unique molecular features and mechanisms. This field can help scientists better understand the functions of different genes and proteins.

“If you want to engineer a complex machine such as a car, to enhance its performance you need to first understand the nature and the contribution of each part and how they work together,” Libault said. “In plants, you need to understand how each gene contributes to the biology of the cell and how each cell plays a part in the entire plant before creating meaningful genetic strategies to enhance crop biology. Having this more accurate picture allows us to enhance our current knowledge in plant and cell biology.”

While cutting and chopping are more common descriptors in cooking, researchers in Libault’s lab chop a plant sample in order to isolate the nucleus of the cells to study gene activity. His lab also focuses on spatial transcriptomics, a process that looks at how cells use their genes within the organs they inhabit. If they can understand the contribution of each cell in the plant and how they are interacting with one another, they can grasp how they work together to respond to environmental stressors.

“In society, each individual has unique competences and expertise. They  work together to accomplish one goal. That’s similar to cells with unique functions working together in an organs to support its function,” he said.

By pooling this information together, they hope to identify important regulators that control how other genes are expressed then manipulate those molecular chains to see how the plant improves.

Libault is not exactly a newcomer at Mizzou.

Back in 2005, Libault came to MU from Paris, where he grew up. He worked as a postdoc in the Gary Stacey lab until 2011 when he became an assistant professor at the University of Oklahoma. He stayed there until 2017 when he moved into an associate professor position at the University of Nebraska. He got his bachelor’s degree from Denis Diderot University in molecular and cellular plant physiology and his master’s degree from Pierre et Marie Curie University in cellular biology and physiology. He went on to earn his Ph.D. in molecular and cellular plant physiology from Paris-Saclay University.

But, Libault’s last 20 years of research have been focused on understanding the mechanisms controlling gene activity including the role of epigenetics — the study of how environment and behavior change the way your genes work — helping him tackle questions like “how does the expression or repression of genes change from cell to cell?” This gives him a unique perspective as he learns to recognize the systems behind gene activity and apply that to his work on a single cell level.

The interaction between roots and bacteria is one of the areas of exploration of the Libault lab at the single cell level. In legumes like soybeans, bumps called nodules grow on the plant roots to facilitate the relationship between plant and bacteria. This nodulation gives the bacteria a place to live while it converts atmospheric nitrogen into food for itself and the plant.

“The bacteria capture the atmospheric nitrogen and convert it into a source of nitrogen supply for the plant,” Libault said. “In return, the plant will give sugar to the bacteria, which is why the two help each other.”

Outside of the lab, Libault enjoys watching Formula 1 racing or movies from the ‘70s and ‘80s in his free time. He is also interested in keeping up with French and European news. Although his balance between work and home life can become challenging at times, when things get hectic Libault prioritizes family time with his wife and three teenage boys as they continue to settle into Columbia after a few years apart.

Libault has been able to hit the ground running in his lab because much of his team made the trek south with him from Nebraska in September.

Libault’s work necessitates collaboration to bring all the pieces together, and that’s what drew him back to MU.

“I know how collaborative the university and the researchers working here are, so that was a strong motivation for me to come back here and continue that kind of collective work,” Libault said. “What we have developed has been highly successful and that’s fun, but what’s next? What more can we learn? This is just the beginning of my next 25 years of research.”

MizzouForward is a transformative, $1.5 billion long-term investment strategy in the continued research excellence of the University of Missouri. Over 10 years, MizzouForward will use existing and new resources to recruit up to 150 new tenure and tenure-track faculty to address some of society’s greatest challenges. Investments also will enhance staff to support the research mission, build and upgrade research facilities and instruments, augment support for student academic success, and retain faculty and staff through additional salary support.