Innovations in Flow Cytometry & Extracellular Vesicles 2024 Agenda

Session Title: Single Cell Analysis and EV Research via Flow Cytometry
Michael Graner, Professor, Dept of Neurosurgery, University of Colorado Anschutz School of Medicine, United States of America

High-Resolution Analysis of Single Extracellular Vesicles and Particles with Digital Flow Cytometry
Daniel Chiu, A. Bruce Montgomery Professor of Chemistry, University of Washington, United States of America

We have developed a multi-parametric high-throughput flow-based method for the analysis of individual extracellular vesicles and particles (EVPs), and a super-resolution method for sizing individual EVPs in a high-throughput fashion. EVPs are highly heterogeneous and comprise a diverse set of surface protein markers as well as intra-vesicular cargoes. Yet, current approaches to the study of EVPs lack the necessary sensitivity and precision to fully characterize and understand the make-up and the distribution of various EV subpopulations that may be present. Digital flow cytometry (dFC) provides single-fluorophore sensitivity and enables multiparameter characterization of EVPs, including sin­gle-EVP phenotyping, the absolute quantitation of EVP concentrations, and biomarker copy numbers. dFC has a broad range of applications, from analysis of single EVPs such as exosomes or RNA-binding proteins to characterization of therapeutic lipid nano­particles, viruses, and proteins. dFC also provides absolute quantita­tion of non-EVP samples such as dyes, beads, and Ab-dye conjugates.

AI Enabled 2D and 3D Image-Guided Cell Analyzers and Sorters
Yu-Hwa Lo, Professor, University of California San Diego, United States of America

Single cell analysis is playing an important role in biological and medical research.  Flow cytometers and fluorescence-activated cell sorters (FACS) are workhorse for single cell analysis, offering high throughput and the ability of isolating cells of high interest, especially those rare cells or new cell types.  On the other hand, microscopy, especially 3D microscopy, can produce high information contents, revealing important insight in cell phenotypes and high spatial information although cell isolation in a microscope platform with techniques such as laser microdissection is cumbersome and subject to cell damage. We present results of image-guided cell sorters that possess the merits of high throughput and high content imaging in a single system.  The image-guided FACS system uses a microfluidic cartridge with an on-chip piezoelectric actuator to sort cells of interest into tubes or 384-well plates.  The cell sorting criteria is based on the 2D images of cells, defined by either operator specified gating criteria or AI with or without human instructions. Going beyond the systems with 2D images, we further demonstrate flow cytometers that produce 3D fluorescent, scattering, and transmission images of each single cell at a throughput of 1000 cells/s, which is 1000-10,000 times faster than a fluorescent confocal microscope. The cell tomography offers far more information than 2D images and is more adaptive to AI and machine learning. Both the 2D and 3D image-guided cell analyzers and sorters are powered by artificial intelligence with convolutional neural networks.  With AI capabilities based on semi-supervised learning, both systems have shown exceptional capabilities for classification and cell type discovery.  Results from several experiments, including the diagnosis of leukemia and NASH diseases, DNA damage assessment, protein translocations under drug treatments, cell cycle detection, and cell fate prediction (the so-called Day Zero experiment) will be discussed in the presentation.

A Microfluidic Serial Cytometer to Estimate Per-Cell Uncertainty and Single Object Kinetic Measurements
Gregory Cooksey, Project Leader, National Institute of Standards and Technology (NIST), United States of America

NIST has developed a serial microfluidic cytometer that repeats the interrogation of objects at multiple points along a flow path, which enables direct assessment of uncertainty in cytometry measurements (DiSalvo et al., Lab Chip 2022). We have achieved per-particle measurement variation below 2 % at throughputs above 100 s^-1 and detection limits and dynamic range comparable to conventional cytometers. This presentation will introduce various measurement capabilities novel to our serial cytometry, including 1) uncertainty quantification, 2) signals analysis that permit estimation of velocity, size, and shape of samples, including elastically deformable particles and mitotic cells, and 3) tracking dynamics of individual objects over time. Utilizing microdroplets, we demonstrated temporal tracking of an enzymatic reaction on a per-droplet basis in real time.  An upstream fluidic mixing system is also used to create known concentrations and dilutions of fluorophores in droplets, which permits direct calibration of measured fluorescence intensity to fluorophores in solution.

Title to be Confirmed.
Leyla Esfandiari, Associate Professor of Biomedical Engineering, University of Cincinnati, United States of America

Title to be Confirmed.
Terry Morgan, Professor of Pathology and Laboratory Medicine, Oregon Health and Science University, United States of America

Title to be Confirmed.
John Nolan, CEO, Cellarcus Biosciences, Inc., United States of America

Title to be Confirmed.
Lynn Pulliam, Professor of Laboratory Medicine and Medicine, University of California San Francisco, United States of America

Diagnosing neurocognitive disorders has been challenging and doing so without invasive and expensive procedures even more difficult. My lab has been interested in diagnosing chronic cognitive impairment in HIV infection and more recently longCOVID using neuronal-derived exosomes. The goal is to identify liquid biomarkers associated with cognitive impairment and follow these during and after treatment. In addition, studies may identify common and distinct processes in neurodegeneration that may help in drug interventions. Alternatively, exosomes can be used as therapeutic delivery vehicles. Implementing these strategies in the clinical laboratory is the goal and still a challenge.