Small extracellular vesicles (sEVs, < 200nm) have been found in bodily fluids such as plasma, saliva, and urine, and hold immense potential as a diagnostic marker for cancer. By analyzing the molecular composition of sEVs, researchers can detect the presence of cancer and monitor its progression. This innovative diagnostic technique has the potential to transform cancer diagnosis by enabling the development of non-invasive or minimally invasive methods for detection, prognosis, and monitoring of cancer patients. To this end, we propose the development of a plasmofluidic chip capable of directly isolating sEVs from plasma, followed by the use of an integrated surface plasmon resonance-based sensor to detect cancer.

Building a cell from scratch has been a study hot point for decades. Microfluidics offers a potential way to build cell-like structures with specific functions. This could help people efficiently understand what happened in a cell. In this project, the student will play with the vesicle to build the artificial cell in steps. Different chip structures will be designed depending on applied physic fields. Simulation and experiment will be combined to get a deep understanding of building artificial cells.

To join this project, you should at least equipped with basic simulation skill, like Comsol. Also, basic chemistry and biology knowledge is required for this project. It would be better if you also have a strong background working on protein or lipids.

Microrobots manipulation by different physic fields have been widely studied by researchers in last decades, and it is still a hot point. The ability microrobots can be precisely controlled at microscopic scale has been demonstrated. However, how to scale up the fabrication of the microrobots and bring them close to the real application is still a problem. Microfluidics could be a solution, since it is born with the virtue to product tiny scale particles in high throughput. Here, we aim to combine magnetic microrobots with microfluidic fabrication to make them be able to be used for some applications. In this project, the student will learn how to fabricate this microrobot and develop the potential functions of them.

To join this project, you should know or have work experience on cells, basic simulations (molecular dynamics or magnetic field simulation). An strong ability in simulation or biology (protein/lipids) would be more helpful to this project.

What? Digital diagnostics are a relatively new technology where tens of thousands of independent tests are done in tiny constrained areas and read as either a true or false and then interpreted together using Poisson statistics to infer disease markers like viral load. They are ultra-sensitive and have lower limits of detection than other technologies.

Why? Diagnosis is a key step in the treatment process, and improving diagnostic technology has shown outsized positive effects in personal health and population health (a lesson underscored by the COVID-19 pandemic). However, recent gains require robust infrastructure and thus have disproportionately benefited developed countries.

How? This project maximizes impact by focusing on the translation of digital diagnostic techniques to paper-based microfluidic substrates for use in resource-constrained locations. Specifically, the focus is on the protein micropatterning to make the individual “compartments” which are key to the digital analysis. The student will extend work which was already done with streptavidin patterning to other proteins, testing both the pattern stamping parameters as well as the capacity of the deposited proteins to be functionalized for the biological assay.

More details see here

Human cells communicate within tissue and more generally within the organism using diffusible factors to adapt and synchronize biological processes. Many proteins secreted by cells, such as hormones, cytokines, and growth factors, have already been involved in these processes.

Interestingly, cells also communicate by secreting "information packets" in the form of extracellular vesicles (EV) containing proteins and nucleic acids cargos. However, characterizing the nature and function of these vesicles remains challenging because of their size (40-1000nm), and our current lack of knowledge about the processes ruling their secretion. Hence, dissecting the fundamental mechanisms associated with their biogenesis could teach us a lot about cellular communication and the biology of certain viruses that are known to exploit similar mechanisms. We can also use this knowledge to develop innovative diagnostic or therapeutic tools based on the encapsulation of bioactive molecules in these vesicles.

This project aims to combine advanced chemistry and biology approaches to develop novel assays allowing monitoring of EV secretion at the single-cell level. To achieve this goal, we are currently creating hydrogel materials that become fluorescent in the presence of EVs. By encapsulating cells into these "smart" hydrogels using microfluidics approaches, we can then study single-cell EV production over time using microscopy and flow cytometry. Our long-term objectives are to exploit these new tools to study the dynamics of extracellular vesicle secretions and perform CRISPR genetic screens to identify which proteins are involved in these processes.

In this work, we propose using a microfluidic probe (MFP) to quantify heterogeneity in tissue sections by periodic sampling and spatial mapping of the tissue section.

Tumors, as all biological organisms, provide a wide range of variability in their structure and expression. This variability manifests itself in the macro scale – the morphology itself, and also in the micro-scale – the difference in molecular expression. These molecular variations are expressed as inter-tumor and intra-tumor heterogeneities. Traditional gold standard technique of tumor analysis – immunohistochemistry (IHC) provided an elegant staining method but is limited by being an end-point assay and is used to provide one data point for the whole tissue. Averaging out all heterogeneity information in the entire tissue section leads to loss of important diagnostic information. A recently developed workflow, called GeneScape (Voithenberg et. al., Small, 2021), allows localized analysis while preserving spatial information.

We propose to extend the workflow to parallelize sample collection and subsequent analysis. Adapting sample collection techniques to existing workflows will further allow easy acceptance and adoption of the proposed technique in general practice. The application of spatial information in tumor heterogeneity will be in basic research and clinical use to adapt tumor therapy based on molecular heterogeneity.

CRISPR, and specifically Cas9, is truly an exceptional genome engineering tool and winner of the Nobel prize in Chemistry 2020. It is easy to use, functional in most species, and has many applications in research and clinical studies. The focus of this project is to develop a new CRISPR tool based on Cas13 enzyme, which has the ability to bind target RNA instead of DNA, enabling transcriptome manipulation without direct and permanent genome modification. The cherry on the top of this new tool will be to combine CRISPR/Cas13 with the endogenous RNA silencing machinery in order to control the cell transcriptome in a context-dependent manner, allowing modifications only in specific cell types and/or stages. Aspects of the project will be:

• Molecular cloning (generation of guide RNA constructs with different conformations)

• Cell culture (cell lines generation, tool optimization)

• Flow cytometry and data analysis

Three-dimensional (3D) imaging of cells can reflect important morphological information, which is crucial for understanding complex biological processes. However, current 3D cell imaging techniques typically suffer from inherently low throughput (few cells per second) which is not suitable for the vast majority of biological applications. To this end, we will develop a high-throughput microfluidic platform for multiparametric 3D cell imaging. We envision our platform can be a powerful tool for high content cell analyses.

Rare cells sorting is important for single cell analysis and disease diagnosis. However, these cells, like circulating tumor cells (CTCs), usually present at very low levels (around 1~10 CTCs per milliliter), which challenges the current benchtop fluorescence-activated cell sorting systems. For this project, a high throughput microfluidic flow cytometer for CTCs enrichment will be developed, the goal of which is to provide a pre-sorting strategy which can enrich the CTCs concentration to a large extent in quite a short time with high accuracy before downstream analysis.

Extracellular vesicles (EVs), including apoptotic bodies, microvesicles and exosomes, is a kind of lipid-based vector which contains nucleic acids and proteins for intracellular communication, demonstrating great potential for early disease detection and therapeutic drug delivery systems. Traditional separation methods, e.g. differential centrifugation and ultrafiltration, are time-consuming and labor-intensive, and suffer from low sample purity or low sample yield. Towards this end, a novel and simple microfluidic system for isolation of EVs based on their size will be developed. Downstream analysis, e.g. western blot and sequencing, will be employed, hopefully providing an easy-operating way for early detection of cancer.