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

大多数单细胞多组学平台通常需要单细胞纯化。不需要的细胞，如死亡细胞、二倍体或残留的红细胞，将极大地减少有效数据。将固体组织制备成有活力的非红细胞包括三个主要步骤：组织分离、块/碎屑过滤和单细胞纯化。 对个别步骤进行了改进，以提高效率和缩短时间。虽然每一步都可以单独优化，以达到高完整性和高效率，但仍需要大量的移液和离心操作来连接大部分(如果不是全部)三个步骤。因此，多步骤、监控松散、注意力密集的过程在实践中通常需要更长的时间，整个过程中的材料损失可能相当高(从10^8到10^4-10^6或 99%-99.99%)。我们相信，使用丰富的TROVO技术，在消除中间步骤的同时将所有材料保留在一个地方是比提高单个步骤的效率更有效的策略。我们发现，消除中间步骤的关键是提高细胞分选过程的整体碎片容忍度，并将多个纯化目标结合到一个分离步骤中。利用图像导引的数字滤波器，可以将生存能力、奇异性、细胞大小等多种选择准则组合成一个复合滤波器，并直接应用于复杂的混合物 组织消化液。这一拟议项目的目的是将这种基于图像的技术进一步专业化，成为一种高吞吐量、应用程序就绪的产品。通过与耶鲁病理学公司最新建立的合作，Rich公司将能够使用多个临床样本来验证这一平台。

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.