Abstract

Although there are well established methodologies to measure and model the relationship between mRNA and protein content in bulk, new techniques are necessary to measure the fundamental expression of these compounds at the single-cell level with single-molecule sensitivity. Examining the heterogeneity of mRNA and protein expression at the single-cell level can lead to fundamental information about the cellular response to external stimuli, including the sensitivity, timing, and regulatory interactions of these genes. Our initial results demonstrate the ability to simultaneously quantify up to five genes of interest in single cells using conventional wide-field imaging and labeling methods. Single-molecule mRNA content is measured by single-molecule fluorescence in-situ hybridization (smFISH) while protein content is quantified though the use of antibody probes. Full system automation of the 3D microscope scan and custom image analysis routines allows hundreds of individual cells to be automatically segmented and the mRNA-protein content to be digitally counted. To mimic immune response to bacterial infection, THP-1 cells are stimulated with lipopolysaccharide (LPS) and up to five genes of interest (e.g. IL1β, TNF-α, TLR2) are simultaneously monitored to examine the distribution of single-cell response to this pathogenic stimulus. Despite these initial successes, it is highly desirable to increase the number of genes simultaneously monitored. To this end we are designing a new microfluidic platform to precisely trap and lyse single cells within an analysis chamber for high-dimensional gene analysis. Within this diffusion limited chamber, the mRNA and protein probes are spatially printed (using ink jet and dip-pen technology) to create specific capture and fluorescent detection regions. Spatially arraying the detection regions, combined with super-resolution fluorescent read-out, should enable multi-parameter analysis beyond the ∼5 color fluorescent limit, allowing tens-to-hundreds of genes to be simultaneously analyzed in each single cell.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call