chip-based microfluidic methods for analytical chemistry

3014362bc816c0e34f9bb270d226e31c?s=47 andreas manz
September 25, 2008

chip-based microfluidic methods for analytical chemistry

... talk given at Bologna, September 2008.

3014362bc816c0e34f9bb270d226e31c?s=128

andreas manz

September 25, 2008
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  1. Chip based microfluidic methods Chip-based microfluidic methods for analytical chemistry

    y y Andreas Manz U K U.K.
  2. microfabrication, 1979

  3. None
  4. glass glass device, 1747

  5. 747 y 17 logy hnol tech not na

  6. micro- micro- fluidics, , 1747

  7. many things start off with sophisticated many things start off

    with sophisticated manual methods d l i t f l f l develop into fool-proof general methods methods finally, crude power dominates the field
  8. algorithm to calculate square root of a algorithm to calculate

    square root of a number
  9. l ith i t bl lid l logarithmic tables, slide

    rules
  10. algorithm to calculate square root of a algorithm to calculate

    square root of a number l ith i t bl lid l logarithmic tables, slide rules PC
  11. information content vision content „...ome“ complex mixture mixture 1 d

    ti l mixture time 1 times 1 location 1 compound continuously 1/s 1/min 1d 2d 3d space 3d
  12. information content content proteomics glucose sensor most analytical methods time

    methods NMR tomography space
  13. information content content vision time space

  14. “l b hi ” “lab on a chip” microfabrication microfabrication

    microfluidics μTAS miniaturized total analysis systems
  15. s ip” cs pers a chi uidic 0 pap on

    a roflu 0,000 “lab micr a. 10 “ ca
  16. microfluidics / scaling laws t i k trick: every existing

    chemistry will work the every existing chemistry will work the same on small as on large scale g
  17. scaling laws for microwell plate scaling laws for microwell plate

    volume of 1µL 1nL 1pL (1mm)3 (100µm)3 (10µm)3 is a cube of 600,000,000 600,000 600 # molecules (1nM solution) 25 / cm2 2500 / cm2 250 ,000/ cm2 # volumes In array 17 min 10s 100ms diffusion time 1.5 /min / cm2 250 /s / cm2 2,500,000 /s / cm2 # reactions (diffusion controlled) (diffusion controlled)
  18. None
  19. detection in small volumes is an issue detection in small

    volumes is an issue going nano is getting worse g g g g
  20. microfluidics / scaling laws microfluidics / scaling laws trick works

    for: h i l ti chemical reaction separation separation dilution series etc
  21. for more information on the topic for more information on

    the topic micro TAS conference S Di USA 2008 San Diego, USA 2008 Cheju, Korea 2009 impact factor 5.8 1,000 attendees annually p f Reviews on Micro total analysis systems in Anal.Chem. 2002, 2004, 2006 and 2008 cited over 1,900 times
  22. 1 part 1 p

  23. electrophoresis p

  24. scaling laws g

  25. 10 fold miniaturization 100 x faster separation p 1000 x

    smaller volume 10 x lower reagent consumption
  26. electrophoresis FITC l b l d i id FITC labeled

    amino acids c e [ a r b . u n i t s ] 1 2 3 4 c y c l e # t 7 s s y n c h r . c e [ a r b . u n i t s ] 1 2 3 4 c y c l e # t 7 s s y n c h r . c e [ a r b . u n i t s ] 1 2 3 4 c y c l e # t 7 s s y n c h r . f l u o r e s c e n 0 4 0 8 0 1 2 0 1 6 0 5 6 7 8 f l u o r e s c e n 0 4 0 8 0 1 2 0 1 6 0 5 6 7 8 f l u o r e s c e n 0 4 0 8 0 1 2 0 1 6 0 5 6 7 8 D J H i K Fl K S il Z F C S Eff h A M S i 261 895 897 D.J.Harrison, K.Flury, K.Seiler, Z.Fan, C.S.Effenhauser, A.Manz, Science 261, 895-897 (1993) C.S.Effenhauser, A.Manz, H.M.Widmer, Anal. Chem. 65, 2637-2642 (1993)
  27. publications per month publications per month citing 2100 bioanalyzer 200

    220 C 140 160 180 Courtesy 80 100 120 y of Agi 40 60 80 ilent W 0 20 -00 -00 -01 -01 -02 -02 -03 -03 -04 -04 -05 -05 -06 -06 Waldbro Jan Jul Jan Jul Jan Jul Jan Jul Jan Jul Jan Jul Jan Jul nn
  28. 2 part 2 p

  29. serial to parallel converter SERIAL 1 2 3 4 CONVERTER

    ? PARALEL 1 2 PARALEL 2 3 4
  30. SERIAL 1 1 CONVERTER 1 PARALEL 2 3 3 4

  31. 17 SEPARATION CHANNELS INJECTION CHANNEL INJECTION CHANNEL

  32. None
  33. None
  34. None
  35. double stranded DNA separation

  36. reaction with intercalating dye

  37. None
  38. x x x x x x x x x x

    x x x x x x x double stranded DNA SYBR green complex [fluorescing] ration DNA is slowing down at moving front of SYBR green SYBR green is slowing down at moving front of DNA concentr length of plug orescence fluo length of plug
  39. 3 part 3 p

  40. no scaling laws for cell biology hi on chip

  41. size similarity of cells and microchannels ll h t “f

    l h ” cells have to “feel happy”
  42. timescale 1-2 weeks

  43. Start Position & Current Situation in Stem Cell Research H

    i Brain Blood vessels Ear Tooth 1. Take stem cells from any origin Hair Lung Heart Pancraes Liver Kidney Kidney Cartilage 2. Induce differentiation by: Soluble Immobi- lised C ge Bone factors lised factors Muscle 3. Count and find model cell type to test the device 43 Cell Programming by Nanoscaled Devices
  44. Problem 1: The Difficulty in Comparing Results St ll (SC)

    Inner cell group In vitro ESC Stem cell (SC) sources tial of ntiation higher embryonic adult Single ESC In vitro ESC (no. of passage?) In vitro adult SC (passage?) Potent differen lower adult on low Morphology only Specific marker (images only) Statistics ifferentiati Specific markers (quantitatively) Proteome- charac- Quality of d Functionality Functionality and cell interaction Complete epigenetic h t i ti terisation Q high characterisation Long-term stable implantation 44 Cell Programming by Nanoscaled Devices
  45. Problem 2: Statistical Significance of Differentiation 90 100% 1. Spontaneous

    differentiation depends on many factors. Not constant! 2 No 100% no 0% differentiation ] 70 80 90 Embryonic SC Adult SC 2. No 100%, no 0% differentiation. 3. Suppressing any differentiation in the case of ESC only. ells in [% 50 60 70 differentiation fferentiation 4. Frequently many factors are changed simultaneously. ntiated ce n tion 30 40 pontaneous d Induced di 5. Isotrope versus cluster differentiation. of differe differentiation ed differentiat 10 20 Sp erentiation Amount o Spontaneous Induce ? 0 ppressed diffe S ? 45 Cell Programming by Nanoscaled Devices Sup
  46. Problem 3: Differentiation is not in vivo Differentiation I it

    lt f t ll In vitro-culture of stem cells A li i f Application of factors SPARC Variant 1: X Variant 2: Variant n: SPARC + X Variant 3: X + Y SPARC X SPARC + X + Y X + Y … … … Actual single factor induction of cell differentiation! Application of different media! pp Unphysiological high concentration of factors! In addition undefined substances (e.g. FCS, Trypsin …)! 46 Cell Programming by Nanoscaled Devices
  47. SC lines installed and investigated in CellPROM in vivo Embryogenese:

    highest accuracy in cell highest accuracy in cell location and differentiation in space and time! 47 Cell Programming by Nanoscaled Devices
  48. Hundreds of Nanoscapes & Extra Equipment 48 Cell Programming by

    Nanoscaled Devices
  49. MagnaLab: Long-term Cell Cultivation & Differentiation Device 49 Cell Programming

    by Nanoscaled Devices
  50. MagnaLab - Cell Cultivation on Carriers over Weeks Highly parallel

    NANOSCAPES Variable s rface mediated and NANOSCAPES Variable surface-mediated and soluble factor application 50 Cell Programming by Nanoscaled Devices
  51. Results of CellPROM P i i l f M L

    b Principle of MagnaLab Bild MagnaLab 20 Carrier 120 Microcarriers in one cultivation unit 20 Carrier 20 Carrier unit 20 Carrier 20 Carrier 20 Carrier Cultivation for more than 20 days! ! Inlet and outlet tubes removed ! 51 Cell Programming by Nanoscaled Devices Cultivation for more than 20 days!
  52. R lt f C llPROM Results of CellPROM Cultivation for

    more than 20 days! 52 Cell Programming by Nanoscaled Devices Cultivation for more than 20 days!
  53. Principle of Microcarrier-Multichannel Cultivation Nanoscape immobilised factor Spontaneous differentiation Soluble

    factor Spontaneous differentiation BSA BSA Suppressed differentiation Suppressed differentiation LIF Induced differentiation LIF Induced differentiation Induced differentiation SPARC SPARC 53 Cell Programming by Nanoscaled Devices
  54. Beating Cardiomyocyte Clusters Stem Cell Colonies X = Number of

    beating (synchronised) clusters/cm2 Y = Number of stem cell clusters/cm2 50 up to 100 synchronized 54 Cell Programming by Nanoscaled Devices 50 up to 100 synchronized cardiomyocytes
  55. work in progress …work in progress mm scale device handling

    m scale channels m scale channels nm scale surface chemistry nm scale surface chemistry 5-15 days time scale
  56. part 4 part 4 panic

  57. • soft matter for microfluidics ? biocompatible biocompatible self assembly

    potentially low cost
  58. None
  59. vesicle production PDMS p PDMS Si PDMS Si PDMS

  60. vesicle production p PDMS Si PDMS 100 µm 2 µm

  61. vesicle production p flow direction 100 µm 100 µm side

    view side view fluorescence image
  62. Formation of vesicles 100 µm 100 µm 100 µm 1

    0 0 1 2 0 1 4 0 4 0 6 0 8 0 # 100 µm 2 4 6 8 1 0 1 2 0 2 0 d ia m e te r (µ m ) (µ ) Lipid: DLPC (16:0 Phosphocholine) dye: DiI-C18
  63. formation of vesicles P.S.Dittrich, M.Heule, P.Renaud, A.Manz Lab Chip 6

    488-493 (2006) formation of vesicles Lab Chip 6, 488 493 (2006) i fl increase flow increase backside pressure pressure
  64. formation of vesicle tubes

  65. formation of vesicle tubes

  66. formation of vesicle tubes

  67. Stopping the flow P.S.Dittrich, M.Heule, P.Renaud, A.Manz Lab Chip 6,

    488-493 (2006)
  68. Formation of helices 50 µm 50 µm P.S.Dittrich, M.Heule, P.Renaud,

    A.Manz Lab Chip 6, 488-493 (2006)
  69. i panic

  70. None
  71. None
  72. None
  73. Part 5 fun panic

  74. hottest issues: 1 ll bi l t 1.cell biology support

    2 widening gap between academic 2.widening gap between academic research and industry needs y 3.expiry of microfluidic patents in coming few years
  75. acknowledgements g Dr Petra Dittrich Dr.Petra Dittrich Dr.Jonathan West Li

    Ch Prof.Günter Fuhr, St. Ingbert Lin Chen Helke Reinhardt g Dr.Daniel Schmidt, St.Ingbert Prof Claude Leclerq Paris Kaoru Tachikawa Claus Schumann Prof.Claude Leclerq, Paris Dr.Richard Loman, Paris Prof Philippe Renaud Lausanne Dr.Joachim Franzke Prof Philip Day Prof.Philippe Renaud, Lausanne Dr.Martin Heule, Lausanne i i Prof.Philip Day Ying Cai P f K i hi Oh Dr.Luc Bousse, Mountain View Prof.Ken-ichi Ohno
  76. h d the end