The goal of this research is to develop distributed manufacturing strategies for robust mRNA-containing biomaterials. Our approach is to use yeast such as S. cerevisiae to produce large volumes of mRNA and oligo DNA sequences with unprecedented accuracy and scalability. The DNA strands will form the custom-designed nanocage via self-assembly which will encapsulate mRNA. The DNA architectures will be programmed for on-demand mRNA release and 3D printed into a hydrogel formulation for stable storage and administration. This specific project will focus on the printing of DNA origami ladened hydrogels and study the impact of printing parameters on the resulting geometry and functionality of the overall material system.

Biological Characterization and Imaging, Material Processing and Characterization, Other

• Mechanical Engineering
• Biomedical Engineering
• Mechatronics Engineering

Fluid mechanics System dynamics and control Familiarity with Labview

Mechanical Engineering

George Chiu

Angiosarcomas are aggressive cancers with a poor prognosis for patients. We utilize genetically engineered cell lines and in vivo models to study the molecular drivers of angiosarcoma. In recent work, we found that DICER1 and microRNAs may function as critical tumor suppressors. We have gone on to generate additional tumor models investigating other genes known to be altered in patients. In this project we will study a novel oncogene to determine its role in angiosarcoma and potential as a therapeutic target.

Biological Characterization and Imaging, Cellular Biology, Genetics

• No Major Restriction

Biological Sciences

Jason Hanna

Novel natural products from Streptomyces are challenging to discover, often because they are not produced under standard laboratory conditions. We are exploring methods of activating production of novel natural products using antibiotics.

Biological Characterization and Imaging, Cellular Biology

• No Major Restriction

Chemistry

Elizabeth Parkinson

HIV/AIDS effects millions of people all over the world. The antiretroviral therapy used to treat HIV is effective, but HIV first must be diagnosed and then monitored to measure the treatment effectiveness to eliminate transmission to others and increase a patient’s quality of life. The Linnes Lab uses state of the art microfluidic technologies to prevent, detect, and understand the pathogenesis of diseases, such as HIV. This undergraduate summer research project will focus on developing new technology for HIV diagnostics that will also aid in diagnostics research of other bloodborne illnesses. The student will learn about biological sample preparation, nucleic acid amplification methods, microfluidic device design, fabrication, and testing, and rapid prototyping tools such as 3D printing and laser cutting. The researcher will develop a new tool for sample preparation of the blood that minimizes the number of user steps to integrate into an easy-to-use point-of-care diagnostic tool for people living with HIV to monitor their viral load within the convenience and privacy of their homes. The new tool design specifications include that it must be compatible with the smartphone imaging platform, microfluidic chip, and the HIV assay to diagnose the disease with high sensitivity and specificity.

Biological Characterization and Imaging, Fabrication and Robotics, Human Factors, Medical Science and Technology, Nanotechnology

• Biomedical Engineering
• Biochemistry
• Biological Engineering - multiple concentrations
• Microbiology

3d printing and prototyping, medical technology

Weldon School of Biomedical Engineering

Jacqueline Linnes

We seek to modify the deformation characteristics of bone through a pharmacological treatment. This project would demonstrate such a concept using animal bone. Treated and untreated bone will be made available for the interrogation of bone by x-rays. Students will be engaged in the data interpretation of x-ray scattering experiments on bone, not subjected to mechanical loads or subjected to mechanical loads.

Biological Characterization and Imaging, Biological Simulation and Technology, Material Modeling and Simulation, Material Processing and Characterization, Other

• Materials Engineering
• Mechanical Engineering
• Biomedical Engineering

Materials Characterization, X-ray techniques; Experience in lab work

School of Mechanical Engineering

Thomas Siegmund

This SURF research project seems to engage a student in the study of fracture of bone. In particular we seek to change the strength and toughness of bone through a pharmacological treatment. A project participant would use pig or cow bone, modifiy such bone with the pharmacological treatment and conduct mechanical property measurements on said bone.

Biological Characterization and Imaging, Material Modeling and Simulation, Other

• Mechanical Engineering
• Biomedical Engineering
• Materials Engineering

Knowledge in strength of materials desired; Some experience with lab work

School of Mechanical Engineering

Thomas Siegmund

The student will join a multi-disciplinary team investigating epigenetic processes, chromatin structure and gene regulation. This project will involve learning and applying biochemical, genetic and molecular biology strategies to build and characterize customized budding yeast (Saccharomyces cerevisiae) strains or mammalian cell lines for the investigation of evolutionarily conserved protein-protein interactions and post-translational modifications using state-of-the-art detection and quantification strategies. Biological targets may include histone modifying enzymes, histone modifications, histone variants and chromatin assembly and DNA replication factors.

Biological Characterization and Imaging, Cellular Biology, Genetics

• No Major Restriction

General Chemistry required, introduction to molecular biology, biochemistry, genetics preferred.

Biochemistry

Ann Kirchmaier

Breast cancer is the number one diagnosed cancer among women and affects over a quarter of a million people annually. The five-year survival rate is exceptional if the disease remains local, however, once breast cancer has metastasized, patient survival rates drop precipitously. There is a critical need to better understand the events required for breast cancer metastasis and how these events culminate in systemic tumor growth. During breast cancer metastasis, the composition and structure of the extracellular matrix (ECM) in the metastatic niche are dramatically altered before the arrival of colonizing cells. As such, the ECM is emerging as a potential therapeutic target for disrupting the metastatic process. Our goal is to determine how changes in the ECM are permissive to metastasis and to manipulate these events in order to inhibit metastatic disease. Our recent studies have demonstrated that Fibronectin (FN) is upregulated in the lungs before the arrival of metastatic cancer cells, and clinical evidence has shown that increased FN is predictive of decreased patient survival. Despite these findings, there remain fundamental gaps in determining how matrix remodeling events that occur during metastasis can dictate the cancer cell fate. In particular, the architecture of the FN matrix can induce phenotypic changes of invading cancer cells that can make the cells less sensitive to drug treatment. Additionally, changes in the local tissue architecture can direct a cell to enter a growth cycle or a dormant phenotype, which can diminish the clinical efficacy of ECM-targeted therapeutics.
Our group has recently observed that tumor-derived metastatic cancer cells express elevated levels of FN, but unlike fibroblasts and other stromal cells, the tumor cells do not deposit FN as a fibrillar matrix. Instead, tumor cells secrete FN in a soluble form which must be converted into insoluble fibrils through a cell-mediated event, exposing cryptic binding domains and transitioning the protein into a bioactive state. Our studies suggest that the assembly of fibrillar FN is dependent on a functional relationship between tumor cells and fibroblasts. Interestingly, we have demonstrated that the FN matrix produced and assembled by resident lung fibroblasts during pre-metastatic niche formation results in a highly aligned and organized FN matrix. However, the matrix formed by fibroblasts utilizing FN produced by tumor cells is less organized and more dispersed, which can significantly alter how forces are transmitted to local cells. To study the impact of FN architecture on the metastatic process independent of the confounding influence of other cell populations, our group has developed an advanced 3D cell culture platform that allows us to create a bioactive fibrillar FN network without the need for cell-mediated assembly. Utilizing this platform, we can tune the alignment of the resultant 3D fibrillar FN network to interrogate the role of the matrix on cell fate decisions. Based on our strong preliminary results, we hypothesize that dynamic changes in the FN network architecture will alter both biochemical and mechanical signaling within the niche, influencing the cell phenotype and dormancy and ultimately altering the cell sensitivity to drugs.

Through this project, we seek to evaluate the effect of FN architecture on dormancy. We will use genetic depletion strategies along with a rigorous panel of markers to determine the effect of matrix architecture on the entrance to or exit from dormancy.

Biological Characterization and Imaging, Cellular Biology, Medical Science and Technology

• No Major Restriction

BME

Luis Solorio

Autism spectrum disorder (ASD) is estimated to affect 1 in 54 children and is often diagnosed in early childhood. More than 200 genes have been implicated in ASD, and recent studies have shed light on particular proteins ASD in adult brains. In contrast, little is known about the ASD-related changes in the protein composition in the critical early stages of brain development.

In the proposed research, we will use our recently developed protein labeling techniques and protein enrichment techniques together with tandem mass spectrometry analysis to identify proteomic changes that occur during early brain development in the Syngap1+/- mouse model of ASD.

Work on this project will include a variety of biochemical methods as well as animal handling and tissue collection. The specific techniques and training will be taught on site, but a familiarity with basic biochemistry and laboratory work as well as an interest in neuroscience is desired.

Biological Characterization and Imaging

• Biochemistry (Biology)
• Biomedical Engineering
• Biology
• Cell Molecular and Developmental Biology
• Neurobiology and Physiology

A basic understanding and interest in biochemistry is desired

Biomedical Engineering

Tamara Kinzer-Ursem

Neurons convert biochemical information (through binding of a neurotransmitter) to electrical signal (via action potential) and back to biochemical signal (through the release of neurotransmitters). These distinct and separable processes can be reconstituted in a synthetic neuron by using natural and engineered proteins, and a synthetic neuron platform can be used to understand the rules governing the emergence of the present morphology of a neuron and the architecture of the neuronal system. This project thus aims to construct a synthetic neuron with a modular design and a programmable synthetic neuronal network capable of recapitulating basic functions of a natural neuronal system (e.g., action potential, synaptic communication, and basic computation) and with a long-term vision of incorporating more advanced computation and potentiation.

Biological Characterization and Imaging, Biological Simulation and Technology, Cellular Biology

• Chemical Engineering
• Biological Engineering - multiple concentrations
• Biomedical Engineering
• Neurobiology and Physiology

Chemical Engineering

Chongli Yuan

Our project is funded by the U.S. Environmental Protection Agency (EPA) and involves an interdisciplinary collaboration between engineers, chemists, and psychologists at Purdue University and New York University (NYU). We will elucidate determinants of indoor dust ingestion in 6- to 24-month-old infants (age range for major postural and locomotor milestones). Specific objectives are to test: (1) whether the frequency and characteristics of indoor dust and non-dust mouthing events change with age and motor development stage for different micro-environments; (2) how home characteristics and demographic factors affect indoor dust mass loading and dust toxicant concentration; (3) how dust transfer between surfaces is influenced by dust properties, surface features, and contact dynamics; and (4) contributions of developmental, behavioral, and socio-environmental factors to dust and toxicant-resolved dust ingestion rates. In addition, the project will (5) create a shared corpus of video, dust, toxicant, and ingestion rate data to increase scientific transparency and speed progress through data reuse by the broader exposure science community.

Our transdisciplinary work will involve: (1) parent report questionnaires and detailed video coding of home observations of infant mouthing and hand-to-floor/object behaviors; (2) physical and chemical analyses of indoor dust collected through home visits and a citizen-science campaign; (3) surface-to-surface dust transfer experiments with a robotic platform; (4) dust mass balance modeling to determine distributions in and determinants of dust and toxicant-resolved dust ingestion rates; and (5) open sharing of curated research videos and processed data in the Databrary digital library and a public website with geographic and behavioral information for participating families.

The project will provide improved estimates of indoor dust ingestion rates in pre-sitting to independently walking infants and characterize inter-individual variability based on infant age, developmental stage, home environment, and parent behaviors. Dust transport experiments and modeling will provide new mechanistic insights into the factors that affect the migration of dust from the floor to mouthed objects to an infant’s mouth. The shared corpus will enable data reuse to inform future research on how dust ingestion contributes to infants’ total exposure to environmental toxicants.

U.S. EPA project overview: https://cfpub.epa.gov/ncer_abstracts/index.cfm/fuseaction/display.abstractDetail/abstract_id/11194

Biological Characterization and Imaging, Ecology and Sustainability, Energy and Environment, Engineering the Built Environment, Environmental Characterization, Human Factors

• No Major Restriction

We are seeking students passionate about studying environmental contaminants and infant exposure to chemicals in the indoor environment. Preferred skills: experience with MATLAB, Python, or R. Coursework: environmental science and chemistry, microbiology, physics, thermodynamics, heat/mass transfer, fluid mechanics, developmental psychology.

Lyles School of Civil Engineering

Brandon Boor

Spinal cord injury is a significant human health problem affecting about 300,000 people in the US. Better treatment options are needed to overcome the limited regeneration potential of the human spinal cord. Zebrafish larvae are an emerging model system for drug screening for several reasons including large number of embryos per breeding, genetics, and availability of behavioral assays for drug testing. Our lab is conducting a large scale drug screen with an FDA-approved library to identify novel compounds that enhance functional recovery following injury as assessed by a swimming assay. The student will be involved with fish breeding, spinal cord injury, drug treatment, and behavioral assay. We hope that this work will identify new compounds with translational potential.

Biological Characterization and Imaging, Biological Simulation and Technology, Cellular Biology, Medical Science and Technology

• Biology
• Cell Molecular and Developmental Biology
• Biochemistry
• Neurobiology and Physiology
• Genetics
• Microbiology

Cell Biology, Neurobiology, fine motor skills, working with zebrafish

Biological Sciences

Daniel Suter

EMBRIO

Biological Characterization and Imaging, Biological Simulation and Technology

• No Major Restriction

BIOL

Janice Evans

This project is NSF REU project that aims to develop a high-speed 3D microscopy imaging system for robotics, biological applications. Undergraduate will work with a graduate student to develop novel image processing algorithms , data analytics methods, and instrumentation.

Big Data/Machine Learning, Biological Characterization and Imaging, Fabrication and Robotics

• No Major Restriction

Prior programming experiences.

Mechanical Engineering

Song Zhang

From leopards to fish, many animals sport patterns (like stripes or spots) on their bodies. My group takes a mathematical approach to understand how patterns form in the skin of zebrafish, which are small striped with important biomedical applications. Zebrafish development takes months, but simulating pattern formation takes minutes. In this project, I will mentor a student in building image-processing software to make simulated zebrafish patterns look more like real fish.

Big Data/Machine Learning, Biological Characterization and Imaging, Biological Simulation and Technology, Cellular Biology

• Mathematics
• Computer Science
• Biomedical Engineering
• Biological Engineering - multiple concentrations
• Engineering (First Year)
• Agricultural Engineering

Good team members who are excited about interdisciplinary research, have taken a course in linear algebra, and have strong programming skills.

Mathematics

Alexandria Volkening

This project will be a nexus of the design, imaging, and manufacturing science and engineering of tissue matrix by cellular engineering. The project will engage students in high-resolution imaging, building a 2D and 3D digital design construct of the cellular matrix, and application of AR/VR for the human-matrix interface. Students will learn convergence of imaging, design, tissue engineering, and visualization. This project will be conducted in the College of Engineering and the College of Agriculture.

Biological Characterization and Imaging, Cellular Biology, Other

• Agricultural & Biological Engineering

Junior and Senior students are preferred. Student's personality expectations- Self-motivated, able to "figure out" solutions, persistent, and trustworthy to complete assigned projects.

School of Mechanical Engineering

Ajay Malshe

We are using mass spectrometry to study the localization of lipids, drugs, and proteins in biological tissues and to prepare novel functional interfaces using well-defined polyatomic ions. The student will work with a graduate student mentor to either perform nanocluster synthesis and characterization using mass spectrometry and electrochemical measurements or to develop new analytical approaches for quantitative analysis of biomolecules in biological samples. In both projects, the student will be trained to operate state-of-the-art mass spectrometers and perform independent data acquisition and analysis. The student will also work with the scientific literature to obtain a broader understanding of the field.

Biological Characterization and Imaging, Material Processing and Characterization, Nanotechnology

• chemistry, biochemistry, computer science, engineering

general chemistry, calculus, analytical or physical chemistry

Chemistry

Julia Laskin

As illustrated with the COVID vaccines, storage and stability of medications can limit widespread availability. We are developing innovative chemical imaging tools with ultrafast pulsed lasers capable of mapping transformations within medical formulations to model and inform stability and bioavailability. Depending on the interests of the students, project scope can range from: i) bench-science in sample preparation and characterization, ii) instrument design and optical path alignment, iii) data acquisition and image analysis algorithm development, iv) partnership with collaborators in the pharmaceutical industry. We have a vibrant and diverse cohort of current researchers dedicated to fostering a supportive and collaborative research environment for all.

Big Data/Machine Learning, Biological Characterization and Imaging, Material Processing and Characterization, Medical Science and Technology

• No Major Restriction

Chemistry

Garth Simpson

The increasing worldwide demand for vaccines along with the intensifying economic pressure on health care systems underlines the need for further improvement of vaccine manufacturing. In addition, regulatory authorities are encouraging investment in continuous manufacturing process to ensure robust production, avoid shortages, and ultimately lower the cost of medications for patients. The limitations of in-line process analytical tools are a serious drawback of the efforts taken in place. In line analysis of viral particles are very limited, due to the large time required for the current techniques for detection, qualitative and quantitative analysis. Therefore, there is a need for new process analytical technology. This project has both experimental and computation components and two students will be recruited for perform different tasks. The student focusing on experiments will fabricate devices and test them. The student focusing on computations will focus on developing machine learning codes.

Big Data/Machine Learning, Biological Characterization and Imaging, Biological Simulation and Technology, Biotechnology Data Insights, Cellular Biology, Computer Architecture, Deep Learning

• No Major Restriction

For the experimental portion of the project: fabrication, cell culture, microfluidics, microscopy For the computational portion of the project: Coding, Python

Mechanical Engineering

Arezoo Ardekani

Cancer is a major threat for humans worldwide, with over 18 million new cases and 9.6 million cancer-related deaths in 2019. Although most common cancer treatments include surgery, chemotherapy, and radiotherapy, unsatisfactory cure rates require new therapeutic approaches. Recently, adoptive cellular immunotherapies with chimeric antigen receptor (CAR) engineered T and natural killer (NK) cells have shown impressive clinical responses in patients with various blood and solid cancers. However, current clinical practices are limited by the need of large numbers of healthy immune cells, resistance to gene editing, lack of in vivo persistence, and a burdensome manufacturing strategy that requires donor cell extraction, modulation, expansion, and re-introduction per each patient. The ability to generate universally histocompatible and
genetically-enhanced immune cells from continuously renewable human pluripotent stem cell (hPSC) lines offers the potential to develop a true off-the-shelf cellular immunotherapy. While functional CAR-T and NK cells have been successfully derived from hPSCs, a significant gap remains in the scalability, time-consuming (5 or more weeks), purity and robustness of the differentiation methods due to the cumbersome use of serum, and/or feeder cells, which will incur potential risk for contamination and may cause batch-dependency in the treatment. This project thus aims to develop a novel, chemically-defined platform for robust production of CAR-T and CAR-NK cells from hPSCs.

Biological Characterization and Imaging, Biological Simulation and Technology, Cellular Biology, Genetics, Medical Science and Technology

• No Major Restriction
• Chemical Engineering
• Biological Engineering - multiple concentrations
• Biochemistry
• any related major

Previous experience with cell culture and molecular biology is a bonus, but NOT required.

Davidson School of Chemical Engineering

Xiaoping Bao

Two projects are available. One involves the investigation of enhancing optical imaging resolution using single photon counting techniques. Conventional optical imaging has a hard limit on its spatial resolution, to about one half of the wavelength, and many situations can benefit from higher resolution. In addition, it is challenging to image through scattering media. By way of example, being able to sense with light deeper in the brain would be of enormous benefit in neuroscience. The statistics of photons emitted by or transmitted through an object contain valuable information about the object which could be used to enhance image resolution and possibly see through substantial background scatter. Experiments will be conducted using laser light and with a set of single photon avalanche detectors (SPADs) to measure photon correlations in time, over wavevector (direction), and between detectors in various imaging configurations. Results from these experiments will be used to assess the effectiveness of various techniques for enhancing spatial resolution in imaging applications. This work has a diverse set of potential applications including biological imaging, sensing defects in semiconductors, and imaging through fog. The other project relates to optical forces on structured membranes induced by a laser. The modeling of the mechanical motion of a thin membrane deflected by laser light will be used to determine the membrane properties from experimental and simulated data. This will allow extraction of the mechanical material properties and more generally the validation of a theory for optomechanics that can then be used in design. The nascent field of optomechanics offers enormous impact scope, including remote actuation and propulsion, of importance in fields as diverse and molecular biology, communication, and transport. This project relates to attaining the underpinnings to move along such paths in engineering, as well as the basic physics of optical forces in material at small length scales.

Biological Characterization and Imaging, Biological Simulation and Technology, Deep Learning, Material Modeling and Simulation, Nanotechnology, Other

• Electrical Engineering
• Physics

Students with an interest in experimental work and a strong background in electromagnetics would be a good fit for this project. The undergraduate student will work with graduate students to perform experiments in an optics laboratory, perform modeling and data analysis using MATLAB or python, and review relevant literature to develop a working understanding of single photon measurement techniques and their applications to super-resolution imaging. This project would be suitable for students majoring in electrical engineering, physics, or a related discipline.

Electrical and Computer Engineering

Kevin Webb

Clean drinking water is a universal right, but on the global scale, we still struggle to provide water free of contaminants to everyone. By developing more efficient systems to purify water, we can expand the availability of clean drinking water and reduce the environmental impact of treatment operations. This project will explore the operation of reverse osmosis membranes as a means of efficiently purifying water.

Reverse osmosis membranes are traditionally an expensive and energy intensive drinking water treatment method, and the membranes can suffer from biofouling that reduce the life of the membrane. Operating reverse osmosis membranes intermittently has profound implications for energy savings, and is still an effective form of water treatment. It is unclear if these systems will also be subject to biofouling, or growth of organisms on and after the filter. In this project, the student will utilize real-time microbiology tools and community sequencing to measure and characterize the microbes able to survive fluctuating salinity levels. It is hypothesized that the fluctuations in salinity will prevent significant growth of any microorganisms, thus extending the life and optimizing the operation of reverse osmosis membranes.

Biological Characterization and Imaging, Ecology and Sustainability, Energy and Environment, Engineering the Built Environment

• No Major Restriction

Biology or engineering background. Lab skills in drinking water characterization, microbiology (e.g. culture plating), or mechanical engineering are desired but not required.

Environmental and Ecological Engineering

Caitlin Proctor