Development of a Cellular Isolation System for Real-Time Single Cell Oxygen Consumption Monitoring

1. Development of a Cellular Isolation System for Real-Time Single Cell Oxygen Consumption Monitoring Joe Dragavon March 21, 2007

2. Microscale Life Sciences Center (MLSC)Comprehensive Understanding ofComplex Cellular Processes • Measure multiple parameters in individual living cells in real-time to correlate cellular events with genomic information. • Develop modular, affordable microsystems for analyzing complex cellular processes. • Application: To monitor and increase the understanding of programmed cell death, apoptosis (ap-a-tow’-sis) • This is done by determining the cellular oxygen consumption rate before and after a stress is applied (LPS) • Too much apoptosis = cell-loss disorders • Too little apoptosis = uncontrolled cell growth (cancer) Highly interdisciplinary undertaking!! Major Contributors www.nst.co.il/frontiers/apoptosis.htm

3. My Objective • To develop a Cell Isolation System (CIS) with which we can monitor oxygen consumption rates at the single cell level • Must be user friendly • Must be adaptable for performing stimulus response experiments • Cells must be kept viable and in a “low-stress” environment • Hopefully inexpensive (relatively)

4. Why Oxygen • History of O2 sensors at the UW • Professor Callis: pressure sensitive paints • Direct indicator of cell viability and metabolic activity • Difficult analyte to exclusively monitor • If we can do this, we should be able to do other analytes in a similar manner

5. Why Single Cell • Heterogeneous subpopulations • Cell death due to inflammatory pathology (pyroptosis) • Malignancy due to unregulated cell growth • Susceptibility and resistance to cell death leading to clones with aberrant survival

6. Porphyrin O2 Sensor 0% 20% Clark Electrode microspheres McGraw, C. M., Callis, J. B. Experiments in Fluids2006, 40, 2, 203-211. Dy, E. S.; Kasai, H. e-Journal of Surface Science and Nanotechnology 2005, 3, 473-475. Strovas, T.; Dragavon, J.; et al. Appl. Environ. Microbiol. 2006, 72 (2), 1692-1695.

7. 2-Photon photo polymerization Camera Dichroic mirror Laser Shutter 63x 1.4 NA objective Nano- cube Substrate Sensor Deposition • Good for individual sensor deposition • Low throughput • Porphyrin embedded into polymer 100µm Young Dragavon Young, A. C., Dragavon, J. et al. Two-Photon Lithography of Platinum-Porphyrin Oxygen Sensors. IEEE Sensors. Accepted

8. Big Idea: Integrated Parallel Cell Fluorescence System Jen Young

9. 1 2 3 4 5 6 7 8 9 Microwell Array • All microwells seeded simultaneously (random seeding) • Can sequentially perform oxygen consumption measurements on multiple locations • High throughput • Approaching the requirements for commercial implementation • Decent uniformity

10. Model 1) 2) 3) Phase Modulation Data Processing • System calibrated using a PMT, MLE, and the OOFD • Improved fit by going to higher order polynomial • Multiple phosphorescent lifetimes being detected (non-linear Stern-Volmer) Dragavon Molter

11. System acts as a manual linear actuator Load cell allows for accurate monitoring of the exerted force Rigid structure allows for a significant amount of force to be applied V-groove system ensures proper piston alignment ActuatorSystem Holl Dragavon Molter

12. Plunger (stainless steel) PDMS Glass Living Cell Array • Increased support • Aluminum plate • 1/8” quartz window • One macrowell format • ~5mL volume • Reusable seal! • VERY IMPORTANT!! • The glass lid is also made of borosilicate, just like the chips • The thickness of the PDMS layer is ≈ the same as the lid • Adhesive not optimized

13. Temperature Control Heat Source Pressure Control Lid Actuator Laser Scanning Module 405nm Excitation

14. QA/QC cleaned sealed (visual confirmation!) unsealed dense array seal and other flaws PDMS delamination bad seal

15. delta O2 (ppm/min) Sequential Drawdowns • 2 Locations (3X3) • 1 chip (81 wells) • 4 sequential repetitions • Mouse macrophage • very fragile! • 10x objective Cell Drawdown Histogram Single Cell Drawdown • General linearity • Not centered around 0 • Superimposed biological and system variance Frequency D O2 (ppm/min) paper in progress Δ O2 (ppm/min) # of cells

16. intensity Fourier coefficient frequency Final Work:New Data Collection For a Single Oxygen Determination Φ = tan-1(I/R) * Camera Limited Dragavon Young Burgess

17. My Objective • To develop a Cell Isolation System (CIS) with which we can monitor oxygen consumption rates at the single cell level • Must be user friendly • Must be adaptable for performing stimulus response experiments • Cells must be kept viable and in a “low-stress” environment • Hopefully inexpensive (relatively) (working on this still)

18. HIBISCUS • Hybrid Integraged BIophotonic Sensors Created by Ultrafast laser Systems • 7 universities and companies • 6 different countries • Aiming to develop a single production machine for biophotonic chips • Use a high-power femtosecond laser to write waveguides and etch the channels

19. Proposed Synthesis • Gramicidin S, a cyclic pentapeptide antibiotic

20. Representative reaction to be used to test various analytical methods • Experimental parameters already determined by current Watts group members +

21. Optical Techniques Costin, c. D., Synovec, R. E. Anal. Chem.2002, 74, 4558 – 4565

22. Multi-Channel Chip • Promotes phase separation • Diffusion properties can be used to improve analysis Ben Wahab, Watts group

23. Multiple channels will promote the separation/isolation of desired compounds Increases the effectiveness of the optical analysis Good for: µMS SPR Fluorescence Phase Separation

24. University of Washington MLSC-NIH CPAC Cody Young, Tim Molter, Sarah McQuaide Drs. Jen, Lidstrom, Meldrum, Holl, Chao, Lutz, Marquardt, Strovas Lloyd Burgess, Gordon Mitchell University of Hull HIBISCUS Paul Watts and Watts group members Acknowledgements

25. External Trigger Degree Shift Step -180° Laser 1 -90° 2 Camera 0° 3 Intensifier 4 90° 100μsec 5 180° Phase Modulated Determination(OOFD) Delay of the intensifier is established using the camera software Laser period = Intensifier period The period is variable Shonat, R., Kight, A. Annals of Biomedical Engineering, Vol. 31, pp. 1084–1096, 2003

26. OXYGEN SENSOR CALIBRATION AND REPRODUCIBILITY average ppm average ppm average ppm average ppm Thermoelectric Cooler Effect Accumulation Comparison well # well # N = 30 Gain Comparison Focus Comparison well # well #

27. OXYGEN SENSOR CALIBRATION AND REPRODUCIBILITY Long-term Stability 17,000 x 50msec exposures ( >150 O2 determinations) average ppm average ppm Shot Comparison 1800 x 50µsec exposures Bin Comparison average integrated intensity well # well # N = 30 Microwell Location Comparison average ppm well # well #

28. Δ O2 (11 min, 10 Kinetic Series) Δ O2 (15 min, 42 Kinetic Series) well # well #

29. Integrated intensity at a fixed phase shift Table 1. Integrated Intensities of One Microwell Over Multiple Kinetic Series * will return to this camera issue Coefficient of Variance = CV = (StDev/Average)*100

30. Benzylamine Pentafluorophenol http://www.aist.go.jp/RIODB/SDBS/cgi-bin/direct_frame_top.cgi?lang=eng

31. Ongoing Work:External Stimulus • External Stimulus Response • LPS Application • Monitor O2 consumption prior to and after application • Monitor O2 over time • This would add the metabolic rate of the cell as another dimension to the data set

32. Ongoing Work: SLM used to generate dynamic optical tweezers Size exclusion optical trapping High-throughput cell deposition 5m bead 1920 x 1200 pixels Burgess Young Jesacher et. al., 23 August 2004 / Vol. 12, No. 17 / OPTICS EXPRESS 4129

33. Ongoing Work:Sample Cassette Technology from the current CIS is the foundation for the cassette Holl

34. Ongoing Work: Multispectral Analysis Holl Burgess Powell Karlsgodt Cheaper than the current set-up!

35. Bulk O2 Consumption and Biological Compatibility Clark Electrode microspheres Dragavon Strovas Strovas, T.; Dragavon, J.; et al. “Measurement of Respiration Rates of Methylobacterium extorquens AM1 Cultures by Use of a Phosphorescence-Based Sensor”, Appl. Environ. Microbiol. 2006, 72 (2), 1692-1695.