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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.
Precision immunoprofiling to reveal diagnostic signatures for latent tuberculosis infection and reactivation risk stratification
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.
Silicon Photonic Microring Resonator Arrays for Mass Concentration Detection of Polymers in Isocratic Separations
Molecular weight distribution (MWD) is often the most informative analytical parameter in polymer analysis with gel permeation chromatography (GPC) being the most common approach for determining the MWD for polymer samples. Many industrially relevant polymers lack chromogenic or fluorogenic signatures, precluding use of spectroscopy-based detection. Universal detectors, such as evaporative light scattering and charged aerosol detectors, are nonlinear, limiting quantitative polymer analysis. Differential refractive index (dRI) detectors show linear mass concentration sensitivity but are limited for some analyses given that they are incompatible with gradient-based separations, have limited dynamic range, and require extended thermal equilibration times. In this study, we investigated the utility of silicon photonic microring resonator arrays as a quantitative mass concentration detector for industrial polymer analysis. Microring resonators have optical properties that are sensitive to changes in refractive index, offer an extended dynamic range, broad solvent compatibility, and linear mass concentration detection for a range of molecular weights. Linear mass concentration detection for microrings was demonstrated through a series of isocratic GPC separations using narrow MWD polystyrene (PS) standards. This detection technology was then utilized in conjunction with GPC to analyze a series of broad MWD PS standards, with results in good agreement with dRI and UV. These results demonstrate the potential of the microring resonator platform as a detector for industrial polymer analysis.
Dr. Yi Xu recently successfully defended her thesis titled “Towards Automated Epigenetics: Sample Processing with Droplet Microfluidics."
She will be heading to Zymo Research to continue her successful career. Congratulations Yi!
Recently, various members of the Bailey lab showed off their hard work. At the University's Karle Symposium, Colleen picked up an award for her oral presentation, "Microfluidic Platform for Rapidly Incorporating Total Membrane Protein Content from Whole Cell Lysate into Nanodisc Libraries Enables Activity-Based Profiling." Cole also talked his poster about "Cytokine Profiling for the Diagnosis of Chorioamnionitis Using Silicon Photonic Microring Resonator Arrays" up for an award.
Heather also just got back from the AACC Annual Scientific Meeting & Clinical Lab Expo where she presented her work, "A Machine Learning Approach to Inflammatory Cytokine Profiling Reveals Diagnostic Signatures for Latent Tuberculosis Infection and Reactivation Risk Stratification," and earned the AACC Student Poster Contest, Second Place and Personalized Medicine Division Outstanding Abstract Award!
Way to go, everyone!
Droplet Microfluidics in Thermoplastics: Device Fabrication, Droplet Generation, and Content Manipulation using Integrated Electric and Magnetic Fields
We have developed droplet microfluidic devices in thermoplastics and demonstrated the integration of key functional components that not only facilitate droplet generation, but also include electric field-assisted reagent injection, droplet splitting, and magnetic field-assisted bead extraction. We manufactured devices in poly(methyl methacrylate) and cyclic olefin polymer using a hot-embossing procedure employing silicon masters fabricated via photolithography and deep reactive ion etching techniques. Device characterization showed robust fabrication with uniform feature transfer and good embossing yield. Channel modification with heptadecafluoro-1,1,2,2-tetrahydrodecyltrichlorosilane increased device hydrophobicity, allowing stable generation of 330-pL aqueous droplets using T-junction configuration. Picoinjector and K-channel motifs were also both successfully integrated into the thermoplastic devices, allowing for robust control over electric field-assisted reagent injection, as well as droplet splitting with the K-channel. A magnetic field was also introduced to the K-channel geometry to allow for selective concentration of magnetic beads while decanting waste volume through droplet splitting. To show the ability to link multiple, modular features in a single thermoplastic device, we integrated droplet generation, reagent injection, and magnetic field-assisted droplet splitting on a single device, realizing a magnetic bead washing scheme to selectively exchange the fluid composition around the magnetic particles, analogous to the washing steps in many common biochemical assays. Finally, integrated devices were used to perform a proof-of-concept in-droplet β-galactosidase enzymatic assay combining enzyme-magnetic bead containing droplet generation, resorufin-β-D-galactopyranoside substrate injection, enzyme-substrate reaction, and enzyme-magnetic bead washing. By integrating multiple droplet operations and actuation forces we have demonstrated the potential of thermoplastic droplet microfluidic devices for complex (bio)chemical analysis, and we envision a path toward mass fabrication of droplet microfluidic devices for a range of (bio)chemical applications.
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A droplet microfluidic platform for efficient enzymatic chromatin digestion enables robust determination of nucleosome positioning
The first step in chromatin-based epigenetic assays involves the fragmentation of chromatin to facilitate precise genomic localization of the associated DNA. Here, we report the development of a droplet microfluidic device that can rapidly and efficiently digest chromatin into single nucleosomes starting from whole-cell input material offering simplified and automated processing compared to conventional manual preparation. We demonstrate the digestion of chromatin from 2500–125 000 Jurkat cells using micrococcal nuclease for enzymatic processing. We show that the yield of mononucleosomal DNA can be optimized by controlling enzyme concentration and incubation time, with resulting mononucleosome yields exceeding 80%. Bioinformatic analysis of sequenced mononucleosomal DNA (MNase-seq) indicated a high degree of reproducibility and concordance (97–99%) compared with conventionally processed preparations. Our results demonstrate the feasibility of robust and automated nucleosome preparation using a droplet microfluidic platform for nucleosome positioning and downstream epigenomic assays.
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