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microfluidics & miniaturization for clinical diagnostics

microfluidics & miniaturization for clinical diagnostics

... talk given at EMBL, Heidelberg. Microfluidics 2012, July 25-27, 2012.

andreas manz

July 25, 2012
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  1. Andreas Manz, Jörg Ingo Baumbach, Pavel Neužil KIST Europe, Saarbrücken

    Germany Saarland University, Physics & Mechatronics, Germany microfluidics & miniaturization for clinical diagnostics
  2. fluorescence [arb. units] time [s] 0 40 80 120 160

    1 2 3 4 5 6 cycle # 7 8 t 7 s synchr. fluorescence [arb. units] time [s] 0 40 80 120 160 1 2 3 4 5 6 cycle # 7 8 t 7 s synchr. fluorescence [arb. units] time [s] 0 40 80 120 160 1 2 3 4 5 6 cycle # 7 8 t 7 s synchr. electrophoresis FITC labeled amino acids 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)
  3. publications per month citing Agilent 2100 bioanalyzer Courtesy of Agilent

    Waldbronn introduced 1999 more than 8500 instruments sold worldwide Gold-Standard for the analysis of RNA
  4. what did I learn from all this? 100x speed 100x

    parallel market collapses companies will do everything to block it
  5. KIST Europe Korea Institute for Science and Technology Saarbrücken Germany

    technology, instrumentation & biotech to help prevent pandemics
  6. KIST Europe Korea Institute for Science and Technology Saarbrücken Germany

    technology, instrumentation & biotech to help prevent pandemics
  7. 18 H7 H5 H9* 1980 1997 Recorded new avian influenzas

    1996 2002 1999 2003 1955 1965 1975 1985 1995 2005 H1N1 H2N2 1889 Russian influenza H2N2 H2N2 1957 Asian influenza H2N2 H3N2 1968 Hong Kong influenza H3N2 H3N8 1900 Old Hong Kong influenza H3N8 1918 Spanish influenza H1N1 1915 1925 1955 1965 1975 1985 1995 2005 1895 1905 2010 2015 2009 Pandemic influenza H1N1 recorded human pandemic influenza (early sub-types inferred) Reproduced and adapted (2009) with permission of Dr Masato Tashiro, Director, Center for Influenza Virus Research, National Institute of Infectious Diseases (NIID), Japan. H1N1 Pandemic H1N1
  8. possible European scenario In reality, the initiation phase can be

    prolonged, especially in the summer months. What cannot be determined is when acceleration takes place. 0% 5% 10% 15% 20% 25% Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Month Proportion of total cases, consultations, hospitalisations or deaths Initiation Acceleration Peak Declining Animated slide: Press key Apr
  9. 1918/1919 pandemic: A(H1N1) influenza deaths, England and Wales 1918/19: ‘Influenza

    deaths’, England and Wales. The pandemic affected young adults, the very young and older age groups. 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 27 29 31 33 35 37 39 41 43 45 47 49 51 2 4 6 8 10 12 14 16 18 1918 1919 Week no. and year Deaths in England and Wales Ro = 2-3 (US) Mills, Robins, Lipsitch (Nature 2004) Ro = 1.5-2 (UK) Gani et al (EID 2005) Ro = 1.5-1.8 (UK) Hall et al (Epidemiol. Infect. 2006) Ro = 1.5-3.7 (Geneva) Chowell et al (Vaccine 2006) Courtesy of the Health Protection Agency, UK Transmissibility: estimated Basic Reproductive Number (Ro )
  10. estimated additional deaths in Europe if a 1918/19 pandemic occurred

    now – a published worst case scenario Austria 13,000 Latvia 13,800 Netherlands 23,100 Belgium 14,900 Lithuania 18,800 Poland 155,200 Bulgaria 47,100 Germany 116,400 Portugal 25,100 Czech Rep 34,100 Greece 27,400 Romania 149,900 Cyprus 1, 900 Hungary 37,700 Slovenia 5,000 Denmark 7,300 Ireland 6,700 Slovakia 20,600 Estonia 6,100 Italy 95,200 Spain 87,100 Finland 8,100 Luxembourg 500 Sweden 13,300 France 89,600 Malta 1,100 UK 93,000 Iceland 420 Norway 5,800 EU total: 1.1 million (computer simulation) Murray CJL, Lopez AD, Chin B, Feehan D, Hill KH. Estimation of potential global pandemic influenza mortality on the basis of vital registry data from the 1918–20 pandemic: a quantitative analysis. Lancet. 2006;368: 2211-2218.
  11. main reason for worse situation today: increased population increased population

    density in large cities increased mobility (commute, tourism) closed air circulation (e.g. offices, airplanes) insufficient filtering, insufficient hygiene
  12. to discuss time to activate and use measurements time to

    getting technology & biotech ready false negatives acceptance in public (non invasive would be best)
  13. Peak position qualitative information Peak area quantitative information Ion mobility

    spectrum of positive ions of acetone in air information
  14. 0 25 50 75 100 125 0 5 10 15

    20 25 Tetrachloroethene Toluene Pyridine Trichloroethene Butanol Ethylmethylketone Propanol Pentane MCC-UV-IMS Tetrachloroethene Toluene Pyridine Trichloroethene Butanol Ethylmethylketone Pentane Propanol Drift Time / ms Retention Time / s MCC/IMS
  15. Pseudomonas signals in breath 0.0 0.2 0.4 0.6 0.8 1.0

    0.000 0.005 0.010 0.015 0.020 Pseudomonas Control Analyte PS0 Analyte P_1 Cooperation with the Ruhrlandklinik Essen chronic? infectious ?
  16. breath analysis – lung cancer Pilot Study: • 36 patients

    suffering with lung cancer • 54 healthy persons in a control group. A reduction from more than one million data points per IMS-chromatogram to 25 variables enabled a classification and differentiation of these two groups with an error of < 1.3 %. S. Bader, J.I. Baumbach et al. Science Price 2006 of the ´Deutsche Gesellschaft für Pneumologie´ obtained at the 47. Annual Conference in Nürnberg, March 29 - April 1, 2006: Ionenbeweglichkeitsspektrometrie bei Bronchialkarzinom und Atemwegsinfektion Discriminator -10 -5 0 5 10 Smoking status Non-smoker Smoker No information available Non-smoker Smoker Lung Cancer Control Carcinoma in situ
  17. introduction and assessment of anesthesia target controlled infusions (TCI) calculated

    based on - patient height - patient weight - patient age bispectral index (BIS) monitor depth of anesthesia - Indicates brain activity most of the values are not optimal for particular patient
  18. breath analysis – anaesthesia 0,0 0,5 1,0 1,5 2,0 2,5

    3,0 3,5 4,0 4,5 cPP [µg/mL] 4 6 8 10 12 14 16 18 cAP [ppb] Breath Blood Cooperation with the University Göttingen propofol
  19. breath analysis - anesthetic propofol 0 10 20 30 40

    0.00 0.01 0.02 Peak intensity (V) Time (min) MCC/IMS breath analysis from anesthetized patient over time 0 10 20 30 40 50 0 1 2 3 4 Plasma concentration (µg/mL) Time (min) calculated plasma value target 4 µg/ml target 2 µg/ml propofol in breath
  20. MCC/IMS breath analysis from anesthetized patient over time BIS 19

    BIS 33 BIS 62 Propofol in breath corresponds to the BIS value breath analysis - anesthetic propofol
  21. Online monitoring of anesthesia Result: Plasma conc. Vs. End tidal

    conc. (peak intensity) end tidal concentration (a.u.) dosage: propofol TCI plasma (µg/ml) 0,0 5,0 10,0 15,0 20,0 25,0 30,0 0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5 4,0 4,5 C B A D E F G H „theranostics“- anesthetic propofol wake up go sleep maintain
  22. virtual reaction chamber key properties – water-based sample encapsulated by

    oil – (RT) PCR conducted on a glass cover slip – micromachined heater/sensor are separated from the sample – cover slip is disposable – small sample volume makes system very fast PCR Sample Oi l B mirror reflection
  23. VRC details key properties – VRC with glass placed on

    a micromachined silicon – heater integrated with temperature sensor – heating rate: thermal mass, available power with PID control – cooling rate: t (thermal time constant) LENGTH HEATER LINK SENSOR T G P G H    ; t
  24. how fast can the heater be? B A 200 nL

    sample covered with 600 nL of oil. The heater is not well thermally isolated making cooling of the VRC faster. T G P G H    ; t
  25. avian influenza virus detection by RT-PCR key properties • SYBR-green

    real-time RT-PCR • melting curve analysis • 8 minutes for RNA detection 0 2 4 6 8 10 12 14 0.0 0.2 0.4 0.6 0.8 1.0 -3 -2 -1 0 1 2 Fluorescence (V) Time (min) 105 copies in 10 L MC Virus Detected Hot Start RT Temperature (V) PCR 0 10 20 30 40 0 50 100 150 10-4 10-3 10-2 Fluorescence (mV) Cycle Number Differential Fluorescence (V/cycle) Critical Threshold 22.3 0 2 4 6 8 10 12 0.0 0.3 0.6 -5 -4 -3 -2 -1 0 1 2 Fluorescence (V) Time (min) Virus Detected Hot Start RT Temperature (V) PCR
  26. current development • cost below 200 USD per unit •

    four samples a time, i.e. positive and negative control plus two samples • USB enabled • simple display • powered by 12V battery
  27. 1) disruption of spores by superheating for fast DNA extraction

    2) protein and peptide decomposition by superheating 58 sample preparation
  28. superheating solvent is at a temperature higher than boiling point

    without boiling! experiment no boiling of aqueous solutions at 240 °C for more than 30 min!!! limited by thermal decomposition of surrounding oil temperature x exposure time = applied energy 59 PCR Sample Oi l B mirror reflection
  29. Bacillus spore disruption by superheating spores of bacteria are highly

    resistance against: - dryness - toxic substances - other aggressive substances - aging - heat: dry: 150 °C ca. 1 h boiling: ca. 5 h 60 electron microscope cross-section of a spore of Bacillus subtilis, showing the cortex and coat layers surrounding the core (dark central area). spore is 1.2 µm across. (Picture: S. Pankratz, Berkeley University of California)
  30. B. subtilis sporulation microscope image of Bacillus subtilis cells and

    spores after contrast staining (spores: blue, cells: green) 61 Zeiss Axiotron 2, 1500 magnification
  31. B. subtilis purified spores microscope image of Bacillus subtilis spores

    after contrast staining (spores: blue) 62 Zeiss Axiotron 2, 1500 magnification
  32. B. subtilis purified spores after SUPERHEATING microscope image of Bacillus

    subtilis spores after contrast staining (spores: blue) 63 Zeiss Axiotron 2, 1500 magnification
  33. spore disruption destruction of spores by superheating 64 0 5

    10 15 20 25 30 35 40 10-2 10-1 100 101 Fluorescence intensity Cycle Number positive control negative control spore solution spores after pretreatment spores after superheating
  34. mass spectrometric protein identification: state-of-art up to now: MS-grade trypsin

    digestion (Promega): expensive and time consuming  about 100 € per 100 µg! up to 5 € per experiment! 66
  35. 699.0 1361.8 2024.6 2687.4 3350.2 4013.0 Mass (m/z) 3246.7 0

    10 20 30 40 50 60 70 80 90 100 % Intensity 1230.6394 1100.5487 2515.1196 1369.7378 852.4741 790.3886 2711.2883 1665.9083 2451.0972 1886.8596 2151.0325 918.5013 2040.9810 1089.5344 1960.0337 1558.7766 953.4868 1038.5365 2060.9817 2636.2397 2840.3665 1199.6136 1689.8890 1918.8551 1103.5511 1519.7914 2212.9788 842.5106 1302.6404 2456.1160 1794.8060 1849.9048 1356.6586 2133.0422 1723.8525 2529.1252 712.3416 2971.3765 804.3983 3112.5217 2725.2981 2167.0552 1234.6450 1623.8132 1419.7062 1974.0247 2045.9821 883.4579 2388.1460 2287.0447 1555.7543 3015.3503 2653.2954 956.4841 1020.5149 1760.8679 2083.0049 759.4001 3348.6680 921.5129 1186.6179 1145.5305 2253.1111 2908.2954 MALDI example spectrum •each peak is a compound •each protein gives a different peptide pattern 69
  36. • adrenocorticotropic hormone (fragment 1-24) • molecular weight 2933.44 Da

    • ACTH is a biomarker for cellular stress, infections, cancer (metastases!), activates G proteins… 70 start with “easy” samples: ACTH
  37. 71 49.0 640.8 1232.6 1824.4 2416.2 3008.0 Mass (m/z) 2628.2

    10 20 30 40 50 60 70 80 90 100 % Intensity 2932.645 1467.313 49.0 640.8 1232.6 1824.4 2416.2 3008.0 Mass (m/z) 5354.2 10 20 30 40 50 60 70 80 90 100 % Intensity 2932.6687 1467.3292 360.343 2724.5750 1475.3208 978.5501 213.122 2885.6414 1635.0529 49.0 640.8 1232.6 1824.4 2416.2 3008.0 Mass (m/z) 2.0E+4 10 20 30 40 50 60 70 80 90 100 % Intensity 2932.6814 1467.3354 2915.7068 2724.5742 1635.0637 379.0871 71.3642 2835.6299 978.8941 2884.6804 2682.5625 1363.2769 1539.3729 1498.2889 1691.1270 No heating Superheating to 130 °C for 10 s Superheating to 130 °C for 20 s peptide decomposition by superheating
  38. RNA extraction chip Electrophoresis electrodes Lysis electrode Gel Cell sample

    RNA P.Vulto, et al., Lab Chip, 11, 1596-1602 (2011)
  39. Phaseguides principle Capillary pressure bariers for liquid guidance Top-view P.

    Vulto, et al., J. Micromech. Microeng., 16, 2006 x y
  40. Precise gel patterning Nutrient & gas perfusion No physical barrier

    Co-culturing Gradients & stimuli Organotypic cell cultures for drug efficacy and toxicity screening Cells in matrix Perfusion Perfusion
  41. Microtiter plate format Superior imaging Controlled gas flux Cheap and

    disposable Compatible with standard robots & readout stations 384 pitch
  42. „the human document project“ workshop, Stanford, September 12-13, 2012 (chair:

    Steve Quake, www.humandocument.org) to preserve one document about mankind for one million years
  43. acknowledgement Matthias Altmeyer, PhD Mark Tarn, PhD Sasidhar Maddula, PhD

    Kathrin Rupp Anne-Cristin Hauschild Adam Pribylka Per Arvid Lothman Vanessa Almeida Zeynep Meric Sung Eun Choi Dong Sik Han Younggeun Jo Jukyung Park Juergen Pipper, IBN Singapore Lukas Novak, CTU, Prague Julien Reboud, IME Singapore Paul Vulto, IMTEK Freiburg Susann Podszun, IMTEK Philipp Meyer, IMTEK Carsten Hermann, IMTEK Gerald Urban, Prof. IMTEK