Ultrahigh-throughput single-cell genetic analysis and sorting with PACS
利用 PACS 进行超高通量单细胞遗传分析和分选
基本信息
- 批准号:8713869
- 负责人:
- 金额:$ 22.29万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2014
- 资助国家:美国
- 起止时间:2014-08-04 至 2015-04-09
- 项目状态:已结题
- 来源:
- 关键词:AntibodiesAreaAutoimmune DiseasesBehaviorBiologicalBiological AssayBiological MarkersBiological ProcessBiological SciencesBloodBreast Cancer CellCell CountCell SeparationCell Surface ProteinsCell physiologyCellsClonal EvolutionComplexDNADetectionDevelopmentDiseaseDropsFingerprintFunctional RNAGene ExpressionGene Expression ProfileGene MutationGeneticGenotypeGoalsHIVHealthHeterogeneityHourHumanImmune responseImmunologyIndividualInfectionInvestigationMalignant NeoplasmsMeasurementMessenger RNAMethodsMicrofluidicsMutationNeoplasm Circulating CellsOilsOncogenesOther GeneticsPhasePlayPopulationPopulation HeterogeneityPropertyPublicationsRNARNA SplicingReactionRelianceResearchResearch PersonnelResidual TumorsRoleSamplingSolutionsSorting - Cell MovementStem Cell ResearchSystemTechnologyTranscriptVariantVisionWorkanticancer researchaqueousbasecancer cellcommercializationcomplex biological systemscostgenetic analysisgenome analysishigh throughput analysisimprovedinstrumentinstrumentationprototypepublic health relevanceresearch studyscreeningstemstem cell biologysuccesstooltumoruser-friendly
项目摘要
DESCRIPTION (provided by applicant): The goal of Torrent Bio, Inc. is to commercialize a technology capable of ultrahigh-throughput screening of single-cells using PCR. The system is in many ways analogous to Fluorescent Activated Cell Sorting (FACS), except that rather than sorting intact cells, it isolates individual cells into individual aqueous picoliter-volume drops suspended in oil and performs PCR reactions on their lysates. Using multiplexed TaqMan PCR assays, the system is able to interrogate each cell for the expression of specific combinations of genes, mutations or non-coding RNAs. Moreover, similar to FACS, this system can sort the cell lysate into different containers, allowing the lysates of the cells with a unique transcriptional fingerprint to be recovered for additional analysis using microarrays, Next Gen Sequencing, or other methods. The principal advantage of this system is that it combines the high-throughput single-cell screening and sorting capacity of FACS with the sensitivity of PCR. In this proposal, we aim to further improve the single-cell throughput of a working lab prototype and demonstrate the complete PACS workflow using a multiplexed TaqMan assay to target and sort breast cancer cells from a mixed cell population. The intellectual merits of the PACS approach stem from its ability to deliver a rapid and low-cost solution for massively parallel single-cell geneti and transcriptional analysis on large heterogeneous populations of cells. Cellular heterogeneity and its impact on biological function and disease is crucially important to questions in human immunology, stem cell biology and cancer research. By analyzing individual cells within a population, it is possible to identify rare cell populations or transient cell states, critical to uman health and development, that are otherwise unobservable by ensemble measurements. Commercialization of the PACS system will enable a more detailed and comprehensive analysis of the genomes and transcriptomes of these rare cells than ever before.
描述(由申请人提供):Torrent Bio,Inc.是将能够使用PCR超高通量筛选单细胞的技术商业化。该系统在许多方面类似于荧光激活细胞分选(FACS),除了不是分选完整的细胞,而是将单个细胞分离成悬浮在油中的单个皮升体积的水性液滴,并对其裂解物进行PCR反应。使用多重TaqMan PCR分析,该系统能够询问每个细胞的基因、突变或非编码RNA的特定组合的表达。此外,类似于FACS,该系统可以将细胞裂解物分选到不同的容器中,允许回收具有独特转录指纹的细胞的裂解物,用于使用微阵列、下一代测序或其他方法进行额外分析。该系统的主要优点是,它结合了高通量单细胞筛选和分选能力的流式细胞仪与PCR的灵敏度。在这项提案中,我们的目标是进一步提高工作实验室原型的单细胞吞吐量,并使用多重TaqMan检测来从混合细胞群中靶向和分选乳腺癌细胞,从而展示完整的PACS工作流程。 PACS方法的智力优势源于其能够为大规模并行单细胞遗传学和大规模异质细胞群体的转录分析提供快速和低成本的解决方案。细胞异质性及其对生物功能和疾病的影响对人类免疫学、干细胞生物学和癌症研究中的问题至关重要。通过分析群体中的单个细胞,可以识别对人类健康和发育至关重要的稀有细胞群体或瞬时细胞状态,否则这些细胞状态无法通过整体测量观察到。PACS系统的商业化将使这些罕见细胞的基因组和转录组的分析比以往任何时候都更加详细和全面。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
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Dennis J Eastburn其他文献
Dennis J Eastburn的其他文献
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{{ truncateString('Dennis J Eastburn', 18)}}的其他基金
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$ 22.29万 - 项目类别:
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