SBIR TOPIC 439 - ADVANCED SAMPLE PROCESSING PLATFORMS FOR DOWNSTREAM SINGLE-CELL MULTI-OMIC ANALYSIS

NIH RePORTER · NIH · N43 · $399,674 · view on reporter.nih.gov ↗

Abstract

Single cell purifications are usually needed for most single cell multiomics platforms. Unwanted cells such as dead cells, doublet, or residual red blood cells will greatly reduce the effective data. Sample preparation of solid tissues into viable, non-red blood cells consists of three major steps: tissue dissociation, clump/debris filtration and single cells purification. Improvements been made to individual steps to enhance efficiency and reduce time. Though each step can be individually optimized to high completeness and efficiency, extensive pipetting and centrifugation operations are still required to bridge most, if not all, three steps. Therefore, the multistep, loosely monitored, attention-intensive process normally takes much longer in practice, and the material loss during the whole process can be rather high (from 10^8 to 10^4 -10^6 or 99%- 99.99%). Using Enrich TroVo technology, we believe eliminating intermediate steps while keeping all material in one place is a more effective strategy than improving the efficiency of individual steps. And we found the key of eliminating intermediate steps is to enhance the overall debris tolerance of the cell sorting process and to combine multiple purification goals into one single isolation step. Using image guided digital filter, multiple selection criteria such as viability, singularity, cell size, can be combined into one composite filter and directly applied to a complicated mixture of tissue digests. The purpose of this proposed project is to further specialize such image-based technology into a highthroughput, application ready product. With the newly forged collaboration with Yale pathology, Enrich will be able to validate this platform using multiple clinical samples.

Key facts

NIH application ID
10723179
Project number
75N91022C00062-0-9999-1
Recipient
INSO BIOSCIENCES INC
Principal Investigator
ADAM BISOGNI
Activity code
N43
Funding institute
NIH
Fiscal year
2022
Award amount
$399,674
Award type
Project period
2022-09-19 → 2023-09-18