• 2018-07
  • 2018-10
  • 2018-11
  • 2019-04
  • 2019-05
  • 2019-06
  • 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2019-11
  • 2019-12
  • 2020-01
  • 2020-02
  • 2020-03
  • 2020-04
  • 2020-05
  • 2020-06
  • 2020-07
  • 2020-08
  • Multiple technologies exist for analyzing the


    Multiple technologies exist for analyzing the contents of single cells, including single-cell DNA sequencing, RNA expression analysis, and protein level and activity measurements (Hu et al., 2018; Narrandes & Xu, 2018; Ortega et al., 2017; Wang & Navin, 2015). Single-cell DNA sequencing is generally accomplished by next-generation sequencing after whole genome amplification (Zeng et al., 2018; Zhu, Qiu, Shao, & Hou, 2018). Though this method can provide detailed genetic information, challenges in these techniques arise due to the low amount of DNA in a single cell (2 copies of each gene), necessitating amplification prior to sequencing. This can lead to non-uniform coverage of the genome and bias in the results as early technical errors are amplified, yielding overestimation of certain 98 5 coupled with complete loss of others (Mincarelli et al., 2018). Single-cell RNA sequencing provides transcriptome information, yet also relies on amplification of the starting material and falls prey to some of the same sampling biases that can occur in DNA sequencing (Zeng et al., 2018). Further bias occurs when higher abundance mRNA (~100,000 copy numbers) are more likely to be amplified than lower abundance mRNA (~10 copy numbers), skewing interpretation of true variability in the cells (Mincarelli et al., 2018; Wagner, Regev, & Yosef, 2016). Protein amount can be measured at the single-cell level via antibody-based techniques including FACS (fluorescence activated cell sorting), phosphoflow cytometry, microscopic imaging, and single-cell Western blotting; but these are limited by antibody specificity and purity, a non-trivial issue (Baker, 2015; Bougen-Zhukov, Loh, Lee, & Loo, 2017; Su, Shi, & Wei, 2017). Protein activity in single cells can be measured with energy transfer probes or fluorescent substrates, yet face the challenge of loading probes into viable cells (Goryashchenko, Khrenova, & 98 5 Savitsky, 2018; Kovarik & Allbritton, 2011; Rowland, Brown, Medintz, & Delehanty, 2015). Proximity ligation assays have also been used to assess enzyme activity, but this method relies on genetic transformation of cells, a difficulty when utilizing primary samples obtained directly from a patient (Li et al., 2017). In summary, while several methods have been described for analyzing single cells, multiple challenges exist: antibody reliance can limit practical application; the small size of cells makes sampling requirements and detection challenging; and clinically obtained samples often contain a small number of cells (hundreds to thousands) of mixed origin (including fibroblasts, stroma, etc., in addition to the diseased cells of interest), compounding existing challenges with low sample sizes (Keating et al., 2018). Methods to overcome these difficulties would be of high utility for single-cell analysis. Chemical cytometry utilizes sensitive analytical techniques such as microelectrophoresis or mass spectrometry to analyze and characterize the contents of single cells (Dovichi, 2010; Dovichi & Hu, 2003). Microelectrophoretic chemical cytometry is well-suited to address many of the challenges of single-cell analysis by virtue of its low sample volume requirements (pL to nL), superb resolving power (hundreds of analytes), and extremely low detection limits (10mol), enabling separation of a large number of analytes from single cells with sub-pM detection limits (Vickerman, Anttila, Petersen, Allbritton, & Lawrence, 2018). These attributes, in combination with the absence of the need for cell genetic engineering, make this technique ideal for analyzing single cells from small mixed populations such as that from a primary clinical sample. Furthermore, chemical cytometry can provide a direct readout of enzyme activity, irrespective of the DNA, RNA, or protein levels in the cells, yielding valuable information about active cellular processes that cannot be obtained from genetic or expression information alone. However, a key challenge of this technique is design of a suitable probe that meets the strict requirements for reporting enzyme activity in single cells. These requirements include a probe or substrate with sufficient specificity to reliably report the activity of an enzyme or group of enzymes, the ability to load the probe into single cells without perturbing signaling pathways, and an intracellular lifetime sufficiently long to measure the desired process. Herein, we focus on the design of a reporter for chemical cytometry, specifically on the selection, optimization, and validation of intracellular reporters (typically short peptides) for protein kinase activity measurements by chemical cytometry.