Deeper understanding starts with a single cell

Afif M. Abdel Nour 1,*, Georges Nemer2, Lara Hanna Wakim1, Esam Azhar3,4
1Faculty of Agricultural and Food Sciences, Holy Spirit University of Kaslik, Jounieh, Lebanon
2 Department of Biochemistry and Molecular Genetics, American University of Beirut-Medical Center, Beirut, Lebanon
3 Special Infectious Agents Unit-Biosafety Level 3, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia; 
4Medical Laboratory Technology Department, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia

Abstract
In the past few years Single cell research had tremendous inter- est from public and private researchers and as a result many institutions were striving in publishing single cell related papers. Over the course of the last 10 years the growth rate of published papers was not far from double digits. Although, most of the pro- tocols are based on qPCR, we are presenting today our “one stop full solution” for needs in single cell analysis this including the qPCR as well as the ddPCR. This workflow includes rapid, ultra- sensitive analysis of 2-10 genes in as low as single cell. We have developed a cost effective and streamlined gene expression pro- filing workflow that enables monitoring of hESC/iPSC culture for quality control, reprogramming, and lineage determination with minimal sample consumption. The 4-step integrated workflow couples column-free total RNA isolation (gDNA-free) with lysate- compatible reverse transcription and target specific (up to 100) tandem pre-amplification followed by SYBR-based qPCR analysis. The entire workflow can be completed from sample to quantita- tion of up to 100 targets in less than 1 day. The STDEV from three independent pre-amplifications reactions is only 0.09, and 97% of expressed targets show less than 0.75 deviation from predicted values. Other tools are also presented including single cell sequenc- ing. The reductionist approach to study organisms using single cell analysis proved to be efficient specially in oncology.
http://dx.doi.org/10.1016/j.bdq.2017.02.088


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