The workflow of single-cell expression profiling using quantitative real-time PCR

Abstract

Biological material is heterogeneous and when exposed to stimuli the various cells present respond differently. Much of the complexity can be eliminated by disintegrating the sample, studying the cells one by one. Single-cell profiling reveals responses that go unnoticed when classical samples are studied. New cell types and cell subtypes may be found and relevant pathways and expression networks can be identified. The most powerful technique for single-cell expression profiling is currently quantitative reverse transcription real-time PCR (RT-qPCR). A robust RT-qPCR workflow for highly sensitive and specific measurements in high-throughput and a reasonable degree of multiplexing has been developed for targeting mRNAs, but also microRNAs, non-coding RNAs and most recently also proteins. We review the current state of the art of single-cell expression profiling and present also the improvements and developments expected in the next 5 years.

Keywords::

• gene expression profiling
• preamplification
• RT-qPCR
• single-cell analysis
• single-cell biology
• single-cell workflow

Financial & competing interests disclosure

A Ståhlberg is supported by grants from Assar Gabrielssons Research Foundation, BioCARE National Strategic Research Program at University of Gothenburg, LUA/ALF Västra Götaland, Johan Jansson Foundation for Cancer Research, Swedish Cancer Society, Swedish Society for Medical Research, Swedish Research Council (521-2011-2367), Wilhelm and Martina Lundgren Foundation for Scientific Research. A Ståhlberg is a shareholder in TATAA Biocenter. M Kubista is supported by grants No.GA13-02154S, Grant Agency of the Czech Republic, and BIOCEV CZ.1.05/1.1.00/02.0109, ERDF. M Kubista is a shareholder in TATAA Biocenter and MultiD Analyses. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

No writing assistance was utilized in the production of this manuscript.

Key issues

• Tissues are heterogeneous, and even cells of the same type respond differently to stimuli. This is resolved with single-cell profiling.

• Single-cell collection often requires advanced sample preprocessing that may affect the measured expression profile, highlighting the need for controls.

• Sampling ambiguity introduced by the handling of few molecules (<25) is given by the Poisson distribution and is an issue in single-cell analysis.

• To minimize sampling ambiguity, the number of molecules processed should be maximized in all steps of the protocol including cell lysis, reverse transcription, preamplification and quantitative PCR.

• Profiles should be compared as measured per cell; normalization to house-keeping genes or other tentative reference genes introduces uncontrolled errors.

• Emerging technologies allow multianalyte (DNA, RNA and protein) analysis in the same cell.

• Single-cell expression profiling opens up new avenues in molecular biology and diagnostics including improved tools to define cell types, explore expression pathways and characterize expression networks

• Single-cell profiling makes it possible to characterize rare cells.

Notes