2025 Research Projects

Mentor: Professor Ian Schneider

During development, wound healing and cancer progression, cells must migrate to particular targets. They do this by sensing aligned fibers of insoluble extracellular matrix (ECM) proteins such as collagen and gradients in ECM stiffness, directing migration through processes of contact guidance and durotaxis, respectively. While both processes have been studied in isolation, how cells integrate this information and make migration decisions is unknown. The goal of this project is to control collagen fiber alignment through self-assembly and stiffness through photopolymerizable hydrogels to create multi-cue environments. These tools will be used in conjunction with fluorescent biosensors and live-cell light microscopy techniques that allow for the visualization of cell migration. Understanding how cells respond to precisely defined structural and mechanical properties will uncover fundamental mechanisms of cancer invasion and metastasis as well as guide the design of tissue engineered constructs for wound healing.

Example REU Project: Dermal fibroblasts will be seeded on aligned collagen fibers transferred to hydrogels with gradients in stiffness. Collagen orientation, local stiffness and cell migration will be assessed in these multi-cue environments. The REU student will learn how to align collagen fibers and make stiffness gradients in hydrogels. The migratory behavior of cells and traction forces exerted by cells will be assessed using microscopy and intracellular proteins will be targeted using RNA interference or gene editing. This project will expose the REU student to collagen alignment techniques, mechanical and structural property measurements, cell biology and quantitative light microscopy.

Mentor: Professor Thomas Mansell

The probiotic E. coli strain Nissle 1917 is a gut isolate from a WWI soldier resilient to Shigellosis (dysentery). Now sold in Canada and Europe as Mutaflor for protection against traveler’s diarrhea, it is a good gut colonizer that is non-pathogenic: a perfect model probiotic. The Mansell lab is interested in understanding the mechanisms of Nissle’s probiotic effects as well as its demonstrated resilience to many biofuel and short chain fatty acid challenges. We have been performing various genome engineering experiments with Nissle which have led to the production of useful probiotic small molecules such as antimicrobial peptides. Additionally, we are beginning to test Nissle’s probiotic effects in mouse and other gut microbiome models.

Example REU Project: The REU student will use genome and genetic engineering techniques (e.g., CRISPR-Cas9) to explore Nissle’s probiotic nature, adding and deleting metabolic pathways to determine which traits are most useful in Nissle. The project may also involve production of therapeutic molecules (e.g., immunomodulating cytokines, small molecules, antimicrobial peptides, or therapeutic proteins).

Mentor:  Professor Molly Kozminsky

Cancer is the second leading cause of death in the United States, and yet every individual’s disease is different. This is in part due to the selective pressures of metastasis, the multi-step process by which cancer spreads that is responsible for 90% of cancer deaths. The different events in metastasis—from the intravasation of the tumor cell into the blood stream to shear stress and immune response experienced while circulating to extravasating and forming colonies in distant sites—present obstacles that can lead to different outcomes. Our lab uses a DNA-directed patterning technique to build models of these microenvironments that we can study in the lab. DNA-directed patterning allows high-resolution, high-spatial complexity immobilization of cells, ligands, antibodies over a wide range of length scales, from nanometers to millimeters. This platform combines the numerous highly advantageous features necessary to probe the tumor heterogeneity that is at the root of cancer progression and variable response to treatment.

Example REU Project: The REU student will investigate the contribution of specific immune cell populations to cancer cell behavior in the tumor microenvironment. The REU student will gain experience in cell culture, immunofluorescence staining, and immunofluorescence microscopy. The student will additionally have the opportunity to work in the Keck Microfabrication facility to learn the fundamentals of photolithography used in the DNA-directed patterning technique. Combining these skill sets, the student will perform cell patterning and learn image processing techniques required for data analysis.

Mentor: Professor Jing Wang

In metastasis, tumor cells travel from the primary site to distant organs through the blood or lymph system.  We are interested in a three-dimensional (3D) spatial analysis to decipher how far tumor cells can penetrate the lung tissues (the most common metastasis site for multiple cancers) from the blood vessels. This study cannot be performed directly with lung tissues because the abundance of tumor cells in the lungs at the early or middle stage of cancer is extremely low, which is < 100 tumor cells per mouse lung. To address this issue, we have designed a subcutaneous model with a 3D scaffold implant, which can develop vasculature and recruit lung-tropic tumor cells from the blood in a mouse model bearing a metastatic tumor. This lung-mimicking subcutaneous model can enrich circulating tumor cells. A scaffold that has a size ten times smaller than a mouse lung can collect > 3000 tumor cells at the early stage of cancer. We will analyze the distance of each tumor cell from the adjacent blood vessel in this lung-mimicking subcutaneous model to advance our understanding of lung metastasis.

Example REU project: The student will work with a graduate student to prepare multiple nanoparticle-delivered anti-cancer peptide drugs using recombinant technology and compare their therapeutic efficacy in cancer cell lines to identify the drug with the highest tumor-killing activity. The student can expect to receive training is using bacteria to produce protein conjugates, operating multiple advanced machines to prepare and characterize nanoparticles, and learning how to grow mammalian cells.

Mentor: Professor Balaji Narasimhn

We have designed novel biodegradable amphiphilic polyanhydrides that have the ability to enhance the immune response and stabilize protein antigens. These capabilities have important implications for the design of single dose vaccines for diseases ranging from cancer and HIV to anthrax and plague to tetanus and diphtheria. We have fabricated nanoparticles based on sebacic acid (SA), 1,6-bis(p-carboxyphenoxy)hexane (CPH), and 1,8-bis(p-carboxyphenoxy)3,6-dioxaoctane (CPTEG) and demonstrated the stability and immunogenicity of antigens released from these nanoparticles. Our overall goal is to understand the cellular and molecular mechanisms by which these polymeric nano-adjuvants enhance and activate host immune responses. This work will be in collaboration with Professors Wannemuehler and Bellaire from the Veterinary Microbiology and Preventive Medicine department at ISU.

Example REU Project: Two REU students will learn to fabricate antigen-loaded nanoparticles (200-800 nm) using CPH:SA and CPTEG:CPH copolymers. The antigens of interest include ovalbumin, F1-V (plague antigen), influenza hemagglutinins, and rPA (recombinant protective antigen against anthrax). The students will learn to characterize these nanoparticles using electron microscopy and a Zetasizer (for size distribution). One REU student will study how the blank nanoparticles (i.e., no antigen) are uptaken by antigen presenting cells of the immune system using confocal laser scanning microscopy. The second REU student will immunize mice with these antigen-loaded nanoparticles with the appropriate controls. The immune response in these animals will be characterized using both antigen-specific antibody responses and T and/or B cell proliferative responses. Together, all these studies will provide molecular and cellular information about how polymer chemistry enhances and activates host immune responses. This project will expose the students to nanotechnology, materials science, biochemistry, animal studies, and applied immunology.

Mentor: Surya Mallapragada

The Mallapragada group has designed and synthesized smart bioinspired multi-block copolymers that exhibit pH and temperature sensitivity. These polymers are ionic and undergo thermoreversible gelation at body temperatures. She has developed novel combination therapies for pancreatic cancer through delivery of microRNAs and chemotherapeutic agents to treat pancreatic cancer. She has also developed combination nanovaccines for respiratory infections through the delivery of pathogen-associated proteins using these nano carriers and modulating and enhancing immune responses through polymer chemistry. Through this experience, the student will learn 1) cell culture and sterile technique 2) biomaterials synthesis 3) working in an interdisciplinary environment integrating engineering and biological approaches.

Mentor: Professor Qun Wang

An organoid is a self-organized 3D tissue typically derived from stem cells (pluripotent, fetal or adult), miming an organ’s key functional, structural and biological complexity. Organoids can be dissected and interrogated for fundamental mechanistic studies on genetics and development. They can also be used in diagnostics, personalized medicine, disease modeling, and drug discovery. Organoids are ideally suited for drug discovery and development because they are straightforward to establish, tractable, and highly similar to the organ of origin. To advance the alternative methods and reduce animal use at the FDA, organoid-based MPSs are critical tools under the umbrella of alternative models, which could describe the absorption, disposition, and toxicity of drug substances in the body quantitatively and mechanistically. Computational modeling, such as artificial intelligence and machine learning (AI/ML) technologies, could also be used to build biomimetic organoid-based MPSs for absorption, distribution, metabolism, and excretion (ADME) assessment and prediction.

Example REU Project: In this project, we will build gut, liver, and brain organoid-based MPS models to systematically study drugs’ absorption, toxicity, and disposition for ADME evaluations.

Mentor: Professor Jean-Philippe Tessonnier

The production of adipic acid (AA) is a major contributor to global greenhouse gas emissions, releasing over 10 million metric tons of CO₂ equivalents annually. Our lab is developing a sustainable alternative to conventional AA production by integrating biomanufacturing and electrocatalysis. This innovative pathway combines the production of cis,cis-muconic acid (ccMA) from sugars and lignin monomers using fermentation, and the electrocatalytic hydrogenation of ccMA to AA using water-derived (instead of fossil-derived) hydrogen and renewable electricity. The electrocatalytic hydrogenation step occurs on metal surfaces and is highly sensitive to the chemical composition and crystallographic structure of the metal catalyst. The goal of this REU project is to synthesize metal alloy catalysts through electrodeposition, establish structure-activity correlations, and generate data that will advance our fundamental understanding of this reaction. Students involved in this project will gain hands-on experience in catalyst synthesis and characterization, electrocatalysis in flow reactors, reaction monitoring using online nuclear magnetic resonance, and reaction kinetics.

Mentor: Professor Eric Cochran

We seek to eliminate “plastic guilt” with projects that create new technologies from cradle to grave in the plastics life cycle, new bio-based materials with advanced performance to game-changing chemical recycling technologies.

Mentor: Professor Laura Jarboe

Microbial cell factories, such as yeast, convert the carbon in substrate molecules to the desired product. This project aims develop yeast strains that can use low-value lipid-rich materials to produce valuable biomolecules. Metabolic activity requires that cells be provided with nitrogen so that they can form the enzymes that perform biochemical reactions. This project will explore methods to improve yeast utilization of complex mixtures of lipids while using sustainable sources of nitrogen.

Example REU Project: The REU student will characterize utilization of various non-conventional lipid substrates and nitrogen sources by yeast and relate this data to the relevant physical and chemical properties of the molecules. The student will have the opportunity to work with several yeast species and learn multiple characterization techniques for soft materials. Finally, the REU student will characterize changes in yeast physiology or composition associated with utilization of these carbon and energy sources.

Mentor: Professor Zengyi Shao

Genomes serve as scaffolds for transmitting information through both genetic and epigenetic means. Eukaryotes face an information packaging challenge because DNA molecules of each chromosome need to be folded within a tiny space in the nuclei. Accumulating evidence demonstrates that the spatial arrangement of the genomes in eukaryotes is far from random. We are interested in studying the influence offered by different genome contexts on heterologous pathway performance, which is directly correlated to the productivity when the host is engineered as a microbial factory to produce high-value chemicals (e.g., biofuels, biopolymer precursors and other compounds used as nutraceuticals and pharmaceuticals).

Example REU Project: The REU student will be exposed to frontier research topics such as high throughput DNA assembly and CRISPR-based genome editing technology, and also learn the techniques to generate recombinant DNAs, perform flow cytometry, and gene knock-in/knock-out.

Mentor: Professor Monica Lamm

Emerging and reemerging viral diseases are a serious public health issue with potentially profound impacts on human health, economic health, and political stability. Low-cost, high reliability monitoring is crucial to track the spread of a virus, and such testing must be conducted rapidly and on a much broader scale than is currently feasible. Central to developing robust yet low-cost testing systems are high-fidelity molecular recognition elements. Single stranded DNA oligonucleotides, known as aptamers, are promising candidates for use in such diagnostic test kits.

Example REU Project: This aim of this project is to model and identify the fundamental mechanisms that allow aptamers to bind protein targets with high affinity and specificity. Our approach is to use the computational methods of molecular docking and molecular dynamics simulations to investigate aptamer-protein complexes, with an emphasis on understanding how aptamers bind and interact with protein targets. The outcome of this project will be insight that enables the rational design of aptamer-based sensors.

Mentor: Professor Ratul Chowdhury

Enzymes are key for making better medicines, alternative fuel, and household detergents, flavoring agents, and cleansers. Being able to design new and effective enzymes need us to be able to estimate how good an enzyme is even before investing experimental dollars on it. To this end, we make AI/ML and optimization tools that delve in protein structural biology to gauge and estimate accurately how effective an enzyme is likely to be for a given task. The student will work in a collaborative team of PhDs, postdocs, across three institutes in the USA.

Example REU Project: This work will be led by us at Iowa State The student will learn to make datasets for machine learning, write new machine learning algorithms, do testing of these algorithms on new data, and contribute to research presentations, and papers that come out of this.

Mentor: Professor Nigel Reuel

Proteins are the biological machines powering life. These biological molecules carry out essential functions in your body and in nature, such as recognizing pathogens, giving your cells structural support, and producing the nutrients that your body needs to survive. Because of these properties, proteins are widely used in both industry and medicine to treat disease, develop new materials, and produce high value commodities like fragrances. To meet societal demands for new medicines and industrial products, efficient protein engineering workflows are required. Machine learning has been pitched as a way to more efficiently guide protein engineering through the unfathomably large design space (20¹⁰⁰ for a 100 amino acid protein). However, current workflows suffer from tedious cell-based expression strategies which slow down the engineering process. The purpose of this research is to develop workflows integrating cell-free expression, a streamlined protein synthesis method, and the machine learning technique Bayesian optimization to quicken protein development cycles.