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Drop-on-demand single cell isolation and total RNA analysis.

ABSTRACT: Technologies that rapidly isolate viable single cells from heterogeneous solutions have significantly contributed to the field of medical genomics. Challenges remain both to enable efficient extraction, isolation and patterning of single cells from heterogeneous solutions as well as to keep them alive during the process due to a limited degree of control over single cell manipulation. Here, we present a microdroplet based method to isolate and pattern single cells from heterogeneous cell suspensions (10% target cell mixture), preserve viability of the extracted cells (97.0±0.8%), and obtain genomic information from isolated cells compared to the non-patterned controls. The cell encapsulation process is both experimentally and theoretically analyzed. Using the isolated cells, we identified 11 stem cell markers among 1000 genes and compare to the controls. This automated platform enabling high-throughput cell manipulation for subsequent genomic analysis employs fewer handling steps compared to existing methods.

SUBMITTER: Moon S

PROVIDER: S-EPMC3055874 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature

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Drop-on-demand single cell isolation and total RNA analysis.

Moon Sangjun S Kim Yun-Gon YG Dong Lingsheng L Lombardi Michael M Haeggstrom Edward E Jensen Roderick V RV Hsiao Li-Li LL Demirci Utkan U

PloS one 20110311 3

Technologies that rapidly isolate viable single cells from heterogeneous solutions have significantly contributed to the field of medical genomics. Challenges remain both to enable efficient extraction, isolation and patterning of single cells from heterogeneous solutions as well as to keep them alive during the process due to a limited degree of control over single cell manipulation. Here, we present a microdroplet based method to isolate and pattern single cells from heterogeneous cell suspens ...[more]

PMID: 21412416

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Project description:The advent of single-cell RNA sequencing (scRNA-Seq) has brought with it the ability to gain greater insights into the cellular composition of tissues and heterogeneity in gene expression within specific cell types. For tissue-engineered blood vessels, this is particularly impactful to better understand how neotissue forms and remodels into tissue resembling a native vessel. A notable challenge, however, is the ability to separate cells from synthetic biomaterials to generate high-quality single-cell suspensions to interrogate the cellular composition of our tissue-engineered vascular grafts (TEVGs) during active remodeling in situ. We present here a simple, commercially available approach to separate cells within our TEVG from the residual scaffold for downstream use in a scRNA-Seq workflow. Utilizing this method, we identified the cell populations comprising explanted TEVGs and compared these with results from immunohistochemical analysis. The process began with explanted TEVGs undergoing traditional mechanical and enzymatic dissociation to separate cells from scaffold and extracellular matrix proteins. Magnetically labeled antibodies targeting murine origin cells were incubated with enzymatic digests of TEVGs containing cells and scaffold debris in suspension allowing for separation by utilizing a magnetic separator column. Single-cell suspensions were processed through 10 × Genomics and data were analyzed utilizing R to generate cell clusters. Expression data provided new insights into a diverse composition of phenotypically unique subclusters within the fibroblast, macrophage, smooth muscle cell, and endothelial cell populations contributing to the early neotissue remodeling stages of TEVGs. These populations were correlated qualitatively and quantitatively with immunohistochemistry highlighting for the first time the potential of scRNA-Seq to provide exquisite detail into the host cellular response to an implanted TEVG. These results additionally demonstrate magnetic cell isolation is an effective method for generating high-quality cell suspensions for scRNA-Seq. While this method was utilized for our group's TEVGs, it has broader applications to other implantable materials that use biodegradable synthetic materials as part of scaffold composition. Impact statement Single-cell RNA sequencing is an evolving technology with the ability to provide detailed information on the cellular composition of remodeling biomaterials in vivo. This present work details an effective approach for separating nondegraded biomaterials from cells for downstream RNA-sequencing analysis. We applied this method to implanted tissue-engineered vascular grafts and for the first time describe the cellular composition of the remodeling graft at a single-cell gene expression level. While this method was effective in our scaffold, it has broad applicability to other implanted biomaterials that necessitate separation of cell from residual scaffold materials for single-cell RNA sequencing.

Dataset Information

Drop-on-demand single cell isolation and total RNA analysis.

Publications

Drop-on-demand single cell isolation and total RNA analysis.

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