1. Single cell analysis
2019

2. Why? Limited, hard to get cell samples
Heterogeneity with in sample population: think biopsy, small organisms etc.
Cell to cell variability due to genetic differences leads to differential activities, responsiveness, effect on environment
Developmental biology
Localization of cellular activities while they occur
We already know about the heterogeneity of cancer cell population
Identify clonal expansion
Tumor development history

3. Semin Cell Dev Biol (2016),

5. Challenges Isolating a single cell w/o changing its characteristics
Signal enhancement (fluorescent, molecular structure= DNA, quantifying+ RNA/ protein)
Screening noise (technical, leakiness)
Unbiased detection
Localization per cell / time
computation

6. Isolating a single cell(s)
Reduce the sampling- few cells/ volume.
Can be a “must” or a choice
Disperse cells (disconnect, re-plate..)
Immunoafinity on unique markers (FACS)
Magnetic trapping
Allow cells to “move” through separating matrix like soundwaves, ultrasound, traping into nano-wells

7. Lab on a chip- microfluidic separation
Proc Natl Acad Sci U S A Apr 21;112(16): doi: /pnas

8. Technology Micro-electronics Especially designed platforms
Micro-fluidics parameters
Where to put the cellular assay?
Application: CTC, Inflammation, Field diagnosis, Research

9. Molecular analysis
Common approach= Sequencing DNA, RNA and protein detection
Problems: identification on single molecules in a complex background, Signal, quantification
Linking expression profile to genomics, Epigenomics etc.
Transcriptome +/- direct genomics
Barcoding the specific amplification/cell (see below) and article
Linking Existing proteins to transcriptome/ Genome
Use very specific Ab linked to strong “trapping” Split cells
Cool trick: Ab connected to primers/ each protein- get qPCR from proximity
In-House Validation, Repeating by others, Cost

12. Liquid Biopsy, CTC
ECC
Stem cells
Micro- niche

14. Inserting constructs or engineering cells/ animals with appropriate sequences
Level of endogenous expression
Budget/ equipment / specificity

15. The Rac-FRET Mouse Reveals Tight Spatiotemporal Control of Rac Activity in Primary Cells and Tissues
(Cell reports 2014)

16. Back to research How much data can we achieve/cell?
Is one cell enough?
How reliable is SCA, could SCA be carried out on tissue level?
What is the relevance of strength in number?
Microdots as a fluorescent vehicle.

17. QD (especially with cadmium selenide (CdSe) core and a zinc sulfide (ZnS) shell )
Bright fluorescence (x10)
10-40 nm
Colour spectrum
Non-bleaching (yet blinking)
Surface functionalization/ non reactiveness
FRET friendly/ single molecule tracking
Size and chemistry are usually obstacles for crowded membrane pass cellular environments
Non-reversal binding

18. QD-labeled Myosin V molecules in the cytoplasm of a HeLa cell observed by fluorescence microscopy A persistence filter was applied to highlight the trajectories of Myosin V driven quantum dots moving along the actin filaments (white arrows)
Trajectory of a Myosin V-driven quantum dot moving along an actin filament (scale bar 1μm).
And Quantum dot randomly diffusing through the cytoplasm