An introduction to micromachined biochemical sensors

An introduction to micromachined biochemical sensors
P. Grutter Physics Department, McGill University, Montréal, Canada

Outline Introduction What is a sensor?
Issues in sensors: what are the problems? Cantilever based sensors Alkanethiol self-assembled monolayers on gold from the vapor phase Surface stress at the solid-liquid Interface Conclusions: Connections to molecular electronics

Why sensors?

Why sensors? Intellectually challenging, intersection between fundamental science and applications, excellent training for graduate students, complex, fun, cross fertilization between different research fields, fundable

Why sensors? Intellectually challenging, intersection between fundamental science and applications, excellent training for graduate students, complex, fun, cross fertilization between different research fields, fundable e.g. nanowire FET - sensor – tunable catalyst electronic nose – cooperative hunting strategy in wolves

Research and applications!
Why sensors? Research and applications!

Why sensors? Research and applications! sensors as tools (e.g. force transducer in AFM)

Why sensors? Research and applications! sensors as tools (e.g. force transducer in AFM) AFM image of PTCDA on KBr Grutter Group

Why sensors? Research and applications! sensors as research tool (how big is the human genome ?) sensors as diagnostic platforms (‘personalized medicine’)

Introduction to sensors
what is a sensor? terminology of detection overview of sensor classes with some examples

from Stephen Creager (Clemson University):

Distinctions between probes, reporters, and sensors...
Probes provide feedback about a physical state (T, force, etc.) Reporters provide feedback by the nature of their distribution in heterogeneous media (dyes, tagged lipids, etc.) Sensors report the presence of a chemical species in the presence of many others.

direct measurement in crude sample
Detector vs. Sensor blood sample centrifuge acid treatment ion chromatography (separation) detector (flame ionization) direct measurement in crude sample

Sensors examples pH (litmus paper; pH electrode-potentiometry)
Breathalyzer (alcohol dehydrogenase, colorimetric detection of NADH produced) pregnancy tests (antibody linked to color change) carbon monoxide (canary; metal oxide resistance change)

Sensitivity, selectivity & dynamic range
What concentration of target is measurable? Does signal need to be integrated over time or is “instant read” possible? Selectivity : Are common interferents going to effect response? Do they enhance signals? Reduce them? Matrix effects : Is response dependent upon capture of target by sensor? Does matrix viscosity affect signal?

Reproducibility Repetitive use or single use?
Internally calibrated or per-use calibrated? Tolerance limits of (ir)reproducibility? 0.1%? 5%? 30%? Shelf life?

Limitations of Chemosensors
tend to be powerful for ions, metals, some low MW molecules very limited for organic molecules of interest (sugars, drugs/metabolites, peptides/proteins, antibodies, DNA/RNA)

Biosensors Use a biorecognition event to initiate detection process
Extent of binding, kinetics of binding, fate of bound species are all crucial Substrate Active site Enzyme

Biosensors : 2 types Affinity sensor : Catalytic sensor : + + +
Measure this

Affinity Biosensors HCG sensing (pregnancy test) + + HCG 250 kD
Ab 250 kD 425 g/mol Human chorionic gonadotropin (hCG) is a glycoprotein hormone produced in pregnancy that is made by the developing embryo soon after conception (Human chorionic gonadotropin (hCG) is a glycoprotein hormone produced in pregnancy that is made by the developing embryo soon after conception.)

Affinity sensor: DNA Biosensor
Technique: Hybridization fluorescent tag Complementary strands of ssDNA form dsDNA. GeneChip technology: Specific DNA sequences used as probe to detect fluorescent tags in complementary target ssDNA.

GeneChip System DNA sensor 65,000 genes Hybridization Process (48˚C )
For 16 hours Washing and cleaning process of hybridized DNA (GeneChip). To remove wrong hybridization condition.

GeneChip System Issues & Problems: PCR amplification const?
fluorescence intensity (e.g focus, bleaching,.. ) -> limits quantitative analysis Sensitivity limit: 16pM Mismatch binding (false positives) Chip not reusable (depends on perspective)

Bio-catalytic Sensors
Glucose sensing Diabetes (Type I, Type II) creates about 15% of our total healthcare costs Glucose management is the only route to minimization/delay of vision and circulation problems $2.7 billion market (2002) and growing

Sensing via Redox-Active Enzymes
Glucose 2 electrons per reaction gluconolactone H2O2 τ ≈ 2 yrs O2 glucose

glucose oxidase-reduced
(GOD·H2) gluconolactone O2 τ ≈ 10 ms glucose oxidase (GOD) H2O2 glucose Sensing with redox enzyme is an exercise in electronics

Clark Electrode (1962) GOD·H2 O2 e- glucose GOD H2O2 membrane Pt electrode Still the “gold standard”; cumbersome, expensive

LifeScan® Glucose Sensor
Blue molecule GOD·H2 O2 glucose Colorless molecule GOD H2O2 membrane Handheld reflectometer measures amount of “blue” produced in 30s,60s,90s and interpolates to a calibration curve Prone to variations in O2, interferents in blood including Vit. C

In-vivo: wired vs. ‘wireless’ sensors
in situ use of molecules, complexes, and materials which undergo a well understood change in optical or physical properties Dyes (incl. genetic constructs such as GFP), quantum dots, metal nanoparticles A. L. Lucido F. Suarez, P. Thostrup, et al (Coleman & Grutter group) Journal of Neuroscience (2009)

What properties would the dream nanoparticle sensor have?
targeted localization within cellular environment single-particle detection (and change thereof) single–species selectivity non-perturbing incident/exiting radiation

A functionalized Qdot nanocrystal
Schematic of the overall structure of a Qdot nanocrystal conjugate. The layers represent the distinct structural elements, and are drawn roughly to scale. Qdot nanocrystals are roughly protein-sized clusters of semiconductor material.

Chemical issues with QDs
Ligand coating is difficult to design and keep Hole-electron pair can do chemistry (Nadeau, Nat. Mat. 2006) Early availability of commercial products that do not have certificates of analysis

Sensors: what are the problems?

a sensor needs to be: selective transduce signal timely

a sensor needs to be: selective transduce signal (*) timely
(*) smallest detectable signal (s/n), dynamic range (DR), quantitative or ‘yes-no’, stability/shelf life, cost… all very relevant issues. Note: optimizing them an interesting challenge!

So – what are the ultimate limits?
a sensor needs to be: selective transduce signal time constraints So – what are the ultimate limits?

Sensitivity, sensor size and time
sensitivity, selectivity sensor size detection time

Sensitivity, sensor size and time
sensitivity, selectivity sensor size detection time what are the scaling laws???

Understanding the details necessary to determine relationships
Lavrick et al, Rev. Sci. Instrum. 75, 2229 (2004)

Step 1: How does the reagent get to the sensor?

Diffusion!

Diffusion ?

Reality check……..number of molecules in your sample

Detection time So – if we need to measure at a concentration of pM or better, how fast can we get the molecules to the sensor/transducer part?

Detection time So – if we need to measure at a concentration of pM or better, how fast can we get the molecules to the sensor/transducer part? In the case of ‘doing nothing’ – diffusion!

Lets look at diffusion Diffusion constant D = 10-8 cm2 /s in H2O
= 1 mm2 /s Probed volume V = D3/2 t (dimensional analysis) for 1 molecule to probe 1 mm3 wait 1 s for 1 molecule to probe 1 ml wait 109 s 1 mol in 1 mu m in 1 sec – Brownian motion

Reality check! How long and far does pollen ‘jump’ on water (Brownian motion)

Reality check! How long and far does pollen ‘jump’ on water (Brownian motion) How long do you wait for milk in your coffee (with a volume substantially larger than 1 ml ) to diffuse?

Reality check! How long and far does pollen ‘jump’ on water (Brownian motion) How long do you wait for milk in your coffee (with a volume substantially larger than 1 ml ) to diffuse?  Activated diffusion is the key!  thermal, electrochemical, magnetic, mechanical, convection, turbulence, flow, … scaling???

So – what about kinetics?
A + B AB

For 10% reaction yield: You will wait 10 minutes at 10 nM
You will wait 100 x 1000 minutes = 70 days at 1 pM ASSUMING a (low) reaction rate constant of 107 M -1 (typical reaction rate for RNA hybridization)

The Tyranny of Langmuir Adsorption Isotherms (Robert Corn, UC Irvine)
You will wait 10 minutes at 10 nM for 10% reaction You will wait 100 minutes for 10% reaction at 1 nM You will wait 100 x 1000 minutes = 70 days for 10% reaction at 1 pM ASSUMING a reaction rate constant of 10exp(+7) per M (typical reaction rate for RNA hybridization)

Conclusion You better speed up things by:
applying a strong driving force (e.g. electrochemical, magnetic driving forces, turbulence…) or/and

Conclusion You better speed up things by:
applying a strong driving force (e.g. electrochemical, magnetic driving forces, turbulence…) or/and concentrating analyte (e.g. evaporation, magnetic beads, PCR, …) (even if your sensor/transducer is VERY sensitive)

Nano to the rescue! Small  short distances  fast
Small/nano  sensitive  small concentration and small number of analytes work!

Nano to the rescue? Small  short distances  fast
Small & nano  sensitive  small concentration and small number of analytes work! But not all things scale well: 1. really hard to get turbulence/mixing in a microfluidics device; 2. s/n might be better, but DR reduced, etc.

Understanding the details is important
Transport times and reaction kinetics will determine how big system can be which determines How many parallel sensors can be operated How complex a reaction one can monitor

Transduction mechanism of sensor
Needs to be understood in order to Optimize s/n, DR Understand calibration Control reproducibility Determines ultimate sensitivity …understand if it is a viable business proposition

Understand system noise (=output noise)
small numbers  sqrt(n) fluctuations ! [or very different operation mode: counting of individual molecules (discrete output)] Intrinsic noise sources of transducer: cantilever sensor: external vibrations, bimetallic bending, thermal vibrations optical sensor: shot noise, scattering depth, … resistor: shot noise, 1/f noise, …

Matching system components to optimize signal
What is the rate limiting step? Output noise is a function of averaging time Needs to be matched to transduction time scale (e.g. diffusion time into sensing polymer) System size and concentration of analyte determines ‘analyte time scale’, as molecules need to interact with sensors.

Maximizing signal Understand where it comes from!
(i.e. what is the transduction mechanism ?)

For ultimate sensitivity do single molecule counting!

But hard to do…

So – single molecule biophysics research could have an impact on ultimate sensing! e.g. quantum dots!

So – single molecule biophysics research could have an impact on ultimate sensing! e.g. quantum dots! but, they blink…

So – single molecule biophysics research could have an impact on ultimate sensing! e.g. quantum dots! but, they blink… and might kill cells…

Sensitivity, sensor size, time, integration, and $: a systems approach necessary, touching on many disciplines sensitivity sensor size detection time

Nanosensors: some useful reviews
Nanotechnology: what are the prospects for sensors? Robert W. Bogue, Sensor Review 24 · 253–260 (2004) Cross-Reactive Chemical Sensor Arrays Keith J. Albert, Nathan S. Lewis, Caroline L. Schauer, Gregory Sotzing, Shannon E. Stitzel, Thomas P. Vaid, and David R. Walt Chem. Rev. 100, (2000) Cantilever transducers as a platform for chemical and biological sensors, Lavrik, Sepaniak, and Datskos Rev. Sci. Instrum., 75, 2229 (2004) On scaling laws of biosensors: a stochastic approach Das, Vikalo and Hassibi J. Appl. Phys. 105, (2009)

Cantilever-based Sensors
Solid-liquid Interface Phase Transitions of metal clusters, alkanes (picoliters) Landmine detection Thermometer/ Calorimeter 10-5 K / 1 pJ Sensitivities Alkanethiol SAM Polypyrrole Actuators Single E. Coli bacterium (665 fg) Single vaccinia virus - Smallpox (9.5 fg) Mass Balance 10-18 g sensitivity Surface Stress Sensor Specific Target Molecules DNA Proteins Antigen-Antibody pH sensing … Lang et al. Nanotechnology 13, R29-R36 (2002)

Concept of DNA Sensor McKendry et al., PNAS 99, 9783 (2002) Fritz et al. Science 288, 316 (2000)

Systems Integration Lang et al., Materials Today, April 2005

Towards Understanding Stress Associated with the Self Assembly of Alkane Thiols on Au(111)
J. Delantes, V. Tabard-Cossa, M. Godin, T. Monga, Y. Nagai, H. Bourque, R. Sladek, R.B. Lennox Physics, Chemistry & Genomics Department, McGill University, Montréal, Canada

Outline Motivation: Cantilever based biochemical sensors
Question: origin of signal? Model gas phase system: alkanethiol SAM on Au(111) thin film Electrochemical system: extra control button! Dramatic improvement of DNA sensing signal

Model system Alkanethiol Self-Assembled Monolayers (SAM) Applications
HS-(CH2)n-CH [Head – Chain – Endgroup] Model for a variety of self-assembled systems Stable - Covalent binding to gold surface Simple - Simple chemical composition Versatile - Various functionalizations Applications Surface passivation Surface functionalization (sensing) Molecular electronics defined contacts straightforward assembly

Differential Sensor Second cantilever acts as a reference, eliminating effects of temperature noise non-specific binding etc. Differential signal purely due to chemical interaction of interest M. Godin et al. Rev. Sci. Instrum.74, 4902 (2003)

Experimental Procedure
Animation by M. Godin

Calibration Optical beam deflection technique
For small deflections, the microcantilever deflection (Dz) is linearly proportional to the acquired PSD signal (DS). Ccal = (3.42 ±0.07) 10-6 m/V The surface stress (Ds) is in turn directly proportional to the microcantilever deflection (Dz) through : M. Godin et al. Appl. Phys. Lett. 79, 551 (2001) L. Y. Beaulieu et al. Appl. Phys. Lett. 88, (2006)

Previous Studies Big variability in the surface stress – puzzling…
Berger et al. Science 276, 2021 (1997) n = 12 Berger et al. first to measure surface stress induced during the formation of alkanethiol SAM from the vapor phase Reproduced: ~0.5 N/m (dodecanethiol – C12) Berger et al. previously investigated the surface stress during the formation of alkanethiol SAM from the vapor phase… We were somewhat successful in reproducing these results, despite the slightly larger value. However, we obtained very different surface stress responses using a different cell and depending on who the samples were prepared by. Decided to control the parameters which could influence SAM formation. Big variability in the surface stress – puzzling… Must control SAM formation conditions

Gold Substrate Morphology
3 µm × 3 µm – Small-Grained Gold 3 µm × 3 µm – Large-Grained Gold C12 C10 STM Tip Bias 600 mV; I = 100 pA 100 nm Au, 10 nm Ti (adhesion) Grainsize: 90 ± 50 nm 100 nm Au, T = 200oC - 260oC Grainsize: 600 ± 400 nm Godin et al. Langmuir 20, 7090 (2004) Godin et al. submitted for publication

Alkanethiol SAM Formation
Lying-Down Striped Phases Structure with increasing coverage Standing-up Phase G.E. Poirier, Langmuir 15, 1167 (1999)

Complementary info: STM
24.5 × 24.5 nm 44.7 × 44.7 nm Tip Bias: 600mV ; I = 25 pA C12 SAM on Small-Grained Gold Predominantly Stacked lying-down Phase “Kinetics Trap” C12 SAM on Large-Grained Gold All Standing-up Phase c(4×2) of (√3×√3)R30o

Kinetics Trap Seems consistent with literature:
G. E. Poirier; Langmuir 15, 1167 (1999) and H. Kondoh et al.; J. Chem. Phys. 111, 1175 (1999) Nucleation of the standing-up phase occurs at the domain boundaries of the lying-down phase Small-Grain size  Few domains  Few domain boundaries  restricted transition into the standing-up phase (i.e. kinetics trap) Y. Yourdshahyan et al. J. Chem. Phys. 117, 825 (2002)

Kinetics of SAM formation
A: Initial adsorption B: Lying down phase C: Standing up phase Long time scales:

Rate of change of vapor concentration

‘Aging’ of substrate

Chain-length Dependence
Au(111) grain size = 500 ± 400 nm Surface stress is independent of chain-length ! Berger et al. Science 276, 2021 (1997)

Some Conclusions… Substrate morphology & analyte introduction conditions (concentration) strongly influences kinetics and SAM structure Factors critical to SAM growth; explains reproducibility problems (Schwartz, Annu. Rev. Phys. Chem. 52, 107 (2001)) 6 N/m is a lower bound in surface stress. ( ~ 10 N/m) I have shown you how the substrate morphology plays a huge role on the cantilever sensor’s response, by strongly influencing the final SAM structure, in either stacked lying-down or standing up phase. In addition, we have identified that the analyte introduction conditions, the thiol concentration at the early stage of exposure, affects the SAM structure as well. This is illustrated by the overshoot previously seen, indicative of an unstacked lying-down phase. Finally, from the surface stress curves we can also distinguish the different time constant associated with the different phase of SAM formation. This study helped us understand the parameters influencing the cantilever sensor’s response, but also to highlight factors critical to SAM growth which can be useful in other field such as molecular electronics, to help explain the reproducibility issues from lab to lab. More on this can be found in this Langmuir article. The 6 N/m found is only a lower bound and expect the surface stress to be of tens of N/m. We will now turn to modeling to understand the physical origin of the measured surface stress. Godin et al. Langmuir 20, 7090 (2004)

Modeling Origins of Surface Stress
1. Chain-Chain Interactions Lennard-Jones (van der Waals) Steric Repulsion 2. Electrostatic repulsion [Berger et al. Science 276, 2021 (1997)] Between Au+S- bonds 3. Changes in electronic structure of Au surface atoms Surface reconstruction of Au(111) d

Origin of Surface Stress
compressive tensile Variation in electron density at the surface which alters the inter-atomic bonds’ strength between surface atoms, while the strength of the interaction of charged adsorbates with the surface is mostly responsible for the details of the structure of the surface stress curve (through the interfacial capacity). In essence, as in the gas-phase experiments, the induced surface stress at the solid-liquid interface is due to changes in the electronic structure of the underlying gold surface upon ionic adsorption.

Modeling: conclusions
Relevance of various contributions to the surface stress: Lennard-Jones – 0.01 N/m steric hindrance Electrostatic 0.1 – 1 N/m dipole interactions Surface charge redistribution 1 – 10 N/m charge transfer

Surface charge redistribution important!
Nanotechnology 21, 5501 (2010) Surface charge redistribution important! Grutter group, Nanotechnology 21, 5501 (2010)

Ibach’s backbond model
Electron-donating adsorbates make bonds stronger, increasing tensile stress, while electron-withdrawing adatoms produce the opposite effect. BUT: Data reveal O and H adsorption on Pt(111) produces a compressive change in surface stress. Unfilled bands of Pt are antibonding, not bonding; adding electrons into the unfilled states should weaken not strengthen the bonds. Correlation with work function ? O increases the work function and H drops it on Pt(111) Cl/Cu(111) increase the work function whereas Li/Cu(111) lowers it. P. J. Feibelman, Physical Review B, 56, (1997) A. Zangwill, Physics at Surfaces, Cambridge University Press (1988) \

Why an Electrochemistry Set-up?
Electrochemistry: a knob to gain extra control over the interface Well-defined, clean surfaces kinetics measurements and in a reversible fashion. Measurements of thermodynamic parameters surface stress and surface energy surface charge density (via Coulomb chronometry) Gain a deeper understanding of the physical origins of surface stress through testing of theoretical modeling of the cantilever-electrolyte interface.

Combined stress and electrochemistry measurements
V. Tabard-Cossa et al. Analyt.Chem. 79, 8136 (2007) V. Tabard-Cossa et al. Sensors and Actuators B 107, (2005)

Thermodynamics at the Solid-Liquid Interface
surface energy Lippmann Equation charge density surface stress potential Shuttleworth Equation Electrocapillary curve surface energy Simplest model of electrical double layer assumes constant capacity, C Derivative of surface energy with surface strain surface stress Lipkowski et al. J. Electroanal. Chem. 452 (1998)

Solid-Liquid Interface
PZC Double layer region : Adsorption of ClO4- takes place to compensate for the build up of positive charge on the cantilever surface, analogous to the charging of a capacitor

Surface Energy Cantilever results same as electrochem. on single crystal!

Morphology independence in electrolytes
Image size 500nm x 500 nm evaporated gold film on a Ti adhesion layer sputtered gold film at 300 °C grown on a Nb adhesion layer sputtered gold film at 400 °C grown on a Nb adhesion layer The inset of the graph represents data from surface A, B and C normalized by a constant factor. V. Tabard-Cossa et al., Anal. Chem, 79, 8136 (2007)

Origin of Surface Stress
PZC PZC Simple Model of a parallel-plate capacitor [1] to model electrostatic repulsive interaction between charges at the interface: Possible to produce the magnitude and the right sign BUT Not a quadratic function of q No maximum at the PZC Not symmetric about the PZC deff = Rion = 0.24 nm, Y. MARCUS, Chem. Rev [1] Ibach et al. PRL vol. 77, (1996)

Major Conclusions Surface energy  surface stress
Potential-induced surface stress is dominated by the differential capacitance. Capacity V. Tabard-Cossa, M. Godin, I. J. Burgess, T. Monga, R.B. Lennox, and P. Grutter Anal. Chem, 79, 8136 (2007)

Modeling Surface Stress in Liquids: Challenging!!!
tensile compressive Reminder: In solution: Competing effects due to charge density redistribution on cantilever Au surface through: Battery (or open circuit) Ion adsorption (with possible charge transfer, depending on nature of interaction)

Dirty (‘aged’) Au(111) Surface stress generated on a dirty gold-coated cantilever has a parabolic shape and therefore a constant capacity

Thiol-modified gold surfaces
C12 SAM on gold-coated cantilevers Surface Energy change measured by Tensiometry 50 mM NaCl Parabolic Shape Surface Stress Change of 10 mN/m From fit C= ~3mF cm-2 Capacity C12= 1.1 mFcm-2 A system where the capacity is more define is the case of a thiol-modified surface. The thiol molecule block the gold surface, reduce greatly the capacity of the surface. Because the medium in between the two plates of the capacitor is not water but thiol molecules. The surface now varies with a parabolic shape which closely resembles surface energy change. In the literature people have measured the surface tension of thiol modified gold electrodes. Sondag-Huethorst & Fokkink, J. Electroanal. Chem. 367 (1994)

Stress as a function of defect density
Defect density (surface coverage) % C12 SAM on Au(111) in Cl-, measured by ferrocene replacement reaction, quantified electrochemically

Surface stress in 100 mM solution
Change in the surface stress as a function of electrode potential in 100 mM NaCl of (a) a SAM modified Au-coated cantilever, (b) defective SAM, (c) bare Au in 100 mM HClO4 and (d) bare Au in 100 mM NaCl. The change in surface stress values were set to zero at the most negative potential. The shaded regions indicate the respective position of the PZC for the bare Au surfaces. The inset shows the change in surface stress (from +200 to +700 mV) as function of charge density determined from the simultaneous cyclic voltammetry data. The red dash line is a linear fit to the data

Defect Engineering is crucial!
probe + target ~ 50nm for dsDNA Probe: ssDNA persistence length ~1nm

Defect Engineering Changes in persistence length ~1nm for ss-DNA, 50 nm for DS-DNA Sequence dependent melting temperature Charge transfer reactions Competitive binding: bonds are dynamic many other possibilities….

Outlook: large signals for DNA
Au Cantilever ~160 m N/m 25 bp ssDNA ~145 m N/m 25 bp dsDNA perfect match ~110 m N/m Periodic Square Potential Wave TRIS-HCl 10 mM NaCl 50 mM buffer, pH = Patent pending TRIS-HCl 10 mM NaCl 50 mM buffer, pH =

Some concluding remarks
If specific interactions involve charge transfer to a metallic layer, this can lead to large changes in cantilever stress  Connection to molecular electronics, in particular the role of contacts. For NEMS, this is an issue and an opportunity: mass change as well as charge transfer can lead to changes in resonance frequency. Cantilever sensors very sensitive. BUT how to make the few analyte molecules find the detector? Use electrochemistry to drive them onto the receptor surface (well defined, cleaned) ! Beware of or use defects in sensing layer! Can dominate response!

Sensitivity, sensor size and time: a systems approach necessary, touching on many disciplines
detection time

Beware of cartoons! Inspirational, drive new fields
Reality often more transpirational, as real systems can be much more complicated (and exciting) ! Ask yourself critically ‘do we really know?’

Acknowledgements McGill group members: Group Leaders: Collaborators:
Jorge Dulanto Vincent Tabard-Cosa* Michel Godin* Tanya Monga Brian Seivewright Dr. Helène Bourque Dr. Luc Beaulieu*** Dr. Ian Burgess Dr. Yoichi Miyahara * Assist. Prof, U. Ottawa *** Assit. Prof, Memorial University, NF Fundin Group Leaders: Prof. B. Lennox (Chemistry McGill) Prof. P. Grütter (Physics McGill) Collaborators: Current: Prof. R. Sladek (Genomics McGill) Dr. Y. Nagai (Genome Québec) Prof. J. White (Physiology, McGill) Past: Prof. A. Badia (Chem., U Montréal) Prof. P. Williams (Acadia U.)

Identified Bio-markers for Disease
Acetone => diabetes Ammonium => kidney failure Heavy hydrocarbons => prostate, bladder cancer Pentane => acute myocardial infraction, arthritis, multiple sclerosis Ethane => deficiency in vitamin E methylethylketone n-propanol => lung cancer tolualdehyde oxepanone Breath testing can also measure impairment of specific metabolic pathways Slide from Cristina E. Davis M. Philips, “Ion-trap detection of volatile organic compounds in alveolar breath” Clinical Chemistry, Vol 38, No. 1, pp , 1992

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