The Bailey Lab Wins Awards at Karle Symposium

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This year, members of the Bailey Lab presented their work at the Karle Symposium and won awards for their hard work. Emily Mordan received second place among graduate student presenters for her talk, “Linear Gradient Compatible Refractive Index Based Detector for Polymer Composition Characterization.” Colleen, Cole, and Shannon all earned awards for their poster presentations, too!

Way to go, everyone! You can stay posted on future publications by following us here!

Colleen and Steve Earn Awards at MBSTP Symposium!

Members of the Bailey group just wrapped up presenting at UM’s Microfluidics in Biomedical Sciences Training Program Symposium. Among all of the thought-provoking presentations, Colleen Riordan was able to take home a best poster award for her presentation on a "Microfluidic Platform for Optimizing the Formation of Nanodisc Libraries from Whole Cell Lysate“. Steve Doonan walked away with an award for his talk titled “Development of the Droplet CAR-Wash Platform for Picoliter-Scale Epigenetic Analysis“.

The Bailey lab greatly appreciates the opportunity to share their work and learn from campus colleagues. For those interested in learning about microfluidics and seeing what MBSTP has to offer, you can follow this link http://umich.edu/~ufluids/ to find out more. See you next year!

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Don't Spin Your Wheels: New publication from Steve!

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Droplet CAR-Wash:Continuous Picoliter-Scale Immunocapture and Washing

ABSTRACT

To address current limitations in adapting solid phase sample capture and washing techniques to continuously flowing droplet microfluidics, we have developed the “Coalesce-Attract-Resegment Wash” (CAR-Wash) approach. This module provides efficient, high-throughput magnetic washing by electrocoalescing magnetic bead-laden input droplets with a washing buffer flow and magnetophoretically transporting beads through the buffer into a secondary droplet formation streamline. In this work, we first characterized the technology in terms of throughput, sample retention, and flow-based exclusion of waste volume, demonstrating >500 Hz droplet processing with >98% bead retention and >100-fold dilution in final droplets. Next, we showed that the technique can be adapted to alternative commercially available magnetic beads with lower magnetite content per particle. Then, we demonstrated the CAR-Wash module’s effectiveness in washing away a small molecule competitive inhibitor to restore the activity of magnetic bead-immobilized β-galactosidase. Finally, we applied the system to immunomagnetically enrich a Green Fluorescent Protein-Histone H2B fusion protein from cell lysate while washing away mCherry and other lysate components. We believe this approach will bridge the gap between powerful biochemical and bioanalytical techniques and current droplet microfluidic capabilities, and we envision future application in droplet-based immunoassays, solid phase extraction, and other complex, multi-step operations.


Click here to read the manuscript!

C&EN Highlights the Lab's Work on LTBI Diagnostics

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Here’s a snippet from the article:

Nearly a quarter of the world’s population has latent tuberculosis infection (LTBI). These people don’t have symptoms of the infection because the TB bacteria living inside them are dormant. In about 10% of those people, the bacteria will wake up, but diagnosing latent TB and predicting who is at risk for reactivating is hard.

A team led by Ryan C. Bailey of the University of Michigan and Patricio Escalante of Mayo Clinic reports an assay that reveals diagnostic signatures that doctors could use to both diagnose latent TB and evaluate a patient’s reactivation risk.

You can read the full text here!

Congrats to Heather on her latest publication in Integrated Biology!

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Precision immunoprofiling to reveal diagnostic signatures for latent tuberculosis infection and reactivation risk stratification

ABSTRACT

Latent tuberculosis infection (LTBI) is estimated in nearly one quarter of the world’s population, and of those immunocompetent and infected ~10% will proceed to active tuberculosis (TB). Current diagnostics cannot definitively identify LTBI and provide no insight into reactivation risk, thereby defining an unmet diagnostic challenge of incredible global significance. We introduce a new machine-learning-driven approach to LTBI diagnostics that leverages a high throughput, multiplexed cytokine detection technology and powerful bioinformatics to reveal multi-marker signatures for LTBI diagnosis and risk stratification. This approach is enabled through an individualized normalization procedure that allows disease-relevant biomarker signatures to be revealed despite heterogeneity in basal immune response. Specifically, cytokines secreted from antigen-challenged peripheral blood mononuclear cells were detected using silicon photonic sensor arrays and multidimensional data correlation of individually-normalized immune responses revealed signatures important for LTBI status. These results demonstrate a powerful combination of multiplexed biomarker detection technologies, precision immune normalization, and feature selection algorithms that revealed positively correlated multi-biomarker signatures for LTBI status and reactivation risk stratification from a relatively simple blood-based assay.


Click here to read the manuscript!