Drop-on-Demand Single Cell Isolation and Total RNA Analysis
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 ali...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | en_US |
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Public Library of Science
2011
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| Online Access: | http://hdl.handle.net/1721.1/65377 |
| _version_ | 1826209137164288000 |
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| author | Moon, Sangjun Kim, Yun-Gon Dong, Lingsheng Lombardi, Michael Haeggstrom, Edward Jensen, Roderick V. Hsiao, Li-Li Demirci, Utkan |
| author2 | Harvard University--MIT Division of Health Sciences and Technology |
| author_facet | Harvard University--MIT Division of Health Sciences and Technology Moon, Sangjun Kim, Yun-Gon Dong, Lingsheng Lombardi, Michael Haeggstrom, Edward Jensen, Roderick V. Hsiao, Li-Li Demirci, Utkan |
| author_sort | Moon, Sangjun |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T14:17:50Z |
| format | Article |
| id | mit-1721.1/65377 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T14:17:50Z |
| publishDate | 2011 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | mit-1721.1/653772022-09-28T19:50:39Z Drop-on-Demand Single Cell Isolation and Total RNA Analysis Moon, Sangjun Kim, Yun-Gon Dong, Lingsheng Lombardi, Michael Haeggstrom, Edward Jensen, Roderick V. Hsiao, Li-Li Demirci, Utkan Harvard University--MIT Division of Health Sciences and Technology Demirci, Utkan Demirci, Utkan 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. National Institutes of Health (U.S.) (NIH R21 EB007707) Wallace H. Coulter Foundation (Young Investigation Award) Center for Integration of Medicine and Innovative Technology (U.S. Army Medical Research Acquisition Activity Cooperative Agreement) United States. Army Medical Research and Materiel Command (RO1 A1081534) United States. Army Medical Research and Materiel Command (R21 AI087107) United States. Army. Telemedicine & Advanced Technology Research Center 2011-08-25T20:44:10Z 2011-08-25T20:44:10Z 2011-03 2010-09 Article http://purl.org/eprint/type/JournalArticle 1932-6203 http://hdl.handle.net/1721.1/65377 Moon, Sangjun et al. “Drop-on-Demand Single Cell Isolation and Total RNA Analysis.” Ed. Dimas Covas. PLoS ONE 6.3 (2011) : e17455. en_US http://dx.doi.org/10.1371/journal.pone.0017455 PLoS ONE Creative Commons Attribution http://creativecommons.org/licenses/by/2.5/ application/pdf Public Library of Science PLoS |
| spellingShingle | Moon, Sangjun Kim, Yun-Gon Dong, Lingsheng Lombardi, Michael Haeggstrom, Edward Jensen, Roderick V. Hsiao, Li-Li Demirci, Utkan Drop-on-Demand Single Cell Isolation and Total RNA Analysis |
| title | Drop-on-Demand Single Cell Isolation and Total RNA Analysis |
| title_full | Drop-on-Demand Single Cell Isolation and Total RNA Analysis |
| title_fullStr | Drop-on-Demand Single Cell Isolation and Total RNA Analysis |
| title_full_unstemmed | Drop-on-Demand Single Cell Isolation and Total RNA Analysis |
| title_short | Drop-on-Demand Single Cell Isolation and Total RNA Analysis |
| title_sort | drop on demand single cell isolation and total rna analysis |
| url | http://hdl.handle.net/1721.1/65377 |
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