Investigating Fluorescence Lifetime Spectroscopy & Imaging. David Birch Department of Physics University of Strathclyde Glasgow G4 0NG Scotland

Transcription

1 Investigating Fluorescence Lifetime Spectroscopy & Imaging David Birch Department of Physics University of Strathclyde Glasgow G4 0NG Scotland

2 Content Fluorescence lifetime and its measurement Use in spectroscopy and microscopy Applications 1. Glucose sensing 2. β-amyloid fibrils 3. Nanoparticle metrology» Focus on aromatic fluorophores

3 Fluorescence is the emission of light following absorption of light has a multidimensional signature λ Fluorescence = f ( I,, λ, p, r, t) exc em I = intensity λexc = excitation wavelength λem = emission wavelength p = polarisation r = position t = time Fluorescence colours give contrast/specificity - imaging, microscopy

4 Fluorescence measurands λ Fluorescence = f ( I,, λ, p, r, t) exc em I = intensity λexc = excitation wavelength λem = emission wavelength p = polarisation r = position t = time Quantum yield Absorption spectrum Fluorescence spectrum Fluorescence anisotropy Fluorescence microscopy Fluorescence lifetime decay Some can be combined

5 Absorption spectrum Fluorescence spectrum I 0 (λ) I(λ ) I exc (λ) I fluor (λ) Excited State (Heat) Vibrational levels Electronic level PPO NATA HSA Abs Fluor Intensity Ground State Non-radiative Relaxation (Heat) Abs Fluor Wavelength/nm Fluorescence 1. Isotropic 2. Emission at longer wavelength than excitation (Stokes shift) 3. Emission spectrum does not vary with excitation wavelength 4. Emission spectrum often a mirror image of the excitation spectrum

6 Fluorescence rate parameters From steady state excitation Fluorescence quantum yield Φ From time-resolved excitation Fluorescence lifetime τ Φ = rate of fluorescence rate of absorption (total decay rate) = k r / (k r +k nr ) k r radiative rate K nr non-radiative rate Φ a difficult, inaccurate & relative measurement Range 0-1 τ = average time in exc. state τ = 1 / total decay rate = 1 / (k r +k nr ) τ = Φ / k r τ an easier, accurate & absolute measurement Typically 10-9 s (ns)

7 In dilute solution most fl. molecules show a monoexponential fluorescence lifetime after fn excitation i( t) t = exp τ i(τ)=1/e=0.37 fn exc. 37% t = 0 intensity at t =τ τ = 2 ns τ = 2ns

8 Real photon counting data has known noise statistics - Poisson 1 std. dev. at each datum = N i Where N i is the number of counts at channel/time i

9 Fitting to data fn exc. Fl. decay Fitted fn. Weighted residuals

10 That is the basics now some refinements. A. The decay can be complex B. We usually don t have fn exc. Answer: use a sum of n exponentials or other function n I(t) = Σα i exp( t/τ i ) i=1 Answer: 1. Treat the excitation pulse as a series of fns 2. The fluor. decay as a series of exponentials from each fn 3. Fit the measured data to a reconstituted decay fn using statistical criteria to assess goodness of fit >> gives best fit parameters τ,α... Above is reconvolution

11 Typical reconvolution fit to data Exc. fn Decay = Σ fn responses Residuals Exc. pulse = Σ fns Fitted fn.

12 A poor fit model is incorrect 2 exp. fit to 5 exp. data High chi-sq Fit & data differ Systematic not random trend

13 Time- correlated single-photon counting Photomultiplier Detector COMPUTER DECAY Pulsed source (e.g. LED) Em. filter S statistical single photon events ANALYSIS PHOTON COUNTS Cumulative histogram TIME, CHANNELS t periodic pulses Time digitizer stop/start 2% avoids data pile-up

14 Instruments Integrated or modular?

15 Advantages of Fluorescence Lifetimes Easy, accurate & absolute measurement Digital not analogue technique - single-photon sensitivity & known statistics Gives kinetic rates & dynamic information Concentration independent overcomes photo-bleaching Extra specificity can discriminate against background fluorescence, scattered excitation etc Includes fluorescence virtues - Stokes red shift, single-molecule detection, compatible with optoelectronics ( nm) Probe of nano-environment ph, polarity, quenching, energy transfer, analyte specific interactions, etc

16 1st application in-vivo glucose sensing The Problem of Diabetes Mellitus - A condition characterized by a chronically raised blood glucose concentration due to a relative or absolute lack of insulin (Type I) 250 million people have diabetes worldwide (~ 7.5 x HIV/AIDS) 3.8 million people die from diabetes every year 10% of healthcare spending in many countries Maintaining normal glucose levels minimises complications blindness, kidney disease, arteriosclerosis, poor circulation Grand challenge - No non-invasive and continuous glucose sensor exists Glucose metabolic range ~ 5 30 mm

17 Present-day blood glucose monitoring based on finger-prick sampling & electrochemical monitoring Impaired signal responses and drift in serum and tissue due to other metabolite interference Requires frequent calibration and impairs accuracy Not continuous problem when sleeping, driving Poor patient compliance We need a new technology Fluorescence sensing?

18 Problems! Many important metabolites don t absorb or fluoresce at all in the visible & melanin absorption & scatter increases towards the UV - glucose is one of them unfortunately!

19 One possibility - Multi-photon excitation 2 x 800 nm 1 x 400 nm 5 x 800 nm 1 x 160 nm Excited State Vibrational levels Electronic level Abs Fluor Ground State Non-radiative Relaxation (Heat) Photon energies add

20 Multi-photon excitation 2 x 800 nm 1 x 400 nm, 5 x 800 nm 1 x 160 nm Excited State Vibrational levels Electronic level Abs Fluor Ground State Non-radiative Relaxation (Heat) time / ns # of carbons Photon energies add Linear alkane fluor. decay at 220 nm A Volmer, K Wynne and D Birch, Chem.Phys.Letts. 299, 395,1999

21 But multi-photon excitation needs femtosecond laser exc. - Expensive, complex and impractical for a miniaturized sensor Also UV fluorescence will be filtered out by melanin Answer use an extrinsic fluorescent probe & an indirect assay

22 Two approaches to fluorescence-based glucose sensors Fibre-optic glucose sensor in the subcutaneous tissue Excitation Fluorescence Smart tattoo concept of implanted glucose micro- or nanosensors for non-invasive monitoring

23 Fluorescence indirect assays Glucose Receptor Change in fluorescence Lectin (Con A) Enzyme (glucose oxidase, hexokinase) Boronic acid derivative Cell Bacterial glucose-binding protein

24 Promising approach - Glucose sensing with glucose binding protein(gbp) Engineer mutant of GBP with cysteine near glucose binding site Attach environmentally sensitive fluorophore (badan) to the cysteine C terminus Hinge protein closes around glucose on binding to protein & decreases polarity around dye as water is extruded Φ & τ of badan increases Badan attached at Cysteine 152 Glucose N terminus Reversible Khan F, Gnudi L, Pickup JC. Biochem Biophys Res Comm. 2008; 365:

25 Badan fluorescence spectra - polarity sensitive 1) toluene 2) chloroform 3) acetonitrile Φ 4) ethanol, 5) methanol 6) water. Badan - 6-bromoacetyl-2-dimethylaminonaphthalene

26 Fluorescence lifetime of badan Fluorescence decay in organic solvent Fluorescence decay in water In Water

27 Glucose increases encapsulated GBP-Badan fluorescence by ~ 300% λex = 400 nm λem = 550 nm 5µm GBP-Badan capsules without glucose Encapsulation - GBP-Badan GBP-Badan capsules with 100 µm glucose poly-lysine and polyglutamic acid layers CaCO 3 CaCO 3 CaCO 3 GBP-B Template dissolution with EDTA

28 GBP-badan fluorescence lifetime increases on addition of glucose Bi-exponential decay Glucose changes % of : Short lifetime component ~0.8 ns Long-lifetime component ~3.1 ns 310 µm glucose Zero glucose Closed form GBP On glucose binding Open form GBP-badan

29 Test responses of GBP-badan Capsules (tattoo) Agarose beads (fibre optic tip) Fluorescence K d ~ 12 mm PBS Serum K d ~ 14 mm τ % τ PBS Serum In glucose solution [glucose] mm Glucose / mm Glucose / mm T Saxl et al Biosens. Bioelectron. 2009; 24: T Saxl, F Khan, M Ferla, D Birch, J Pickup The Analyst (In press)

30 Fluorescence Lifetime Imaging Microscopy (FLIM) Scanning microscope Pulsed source Single detector Single-photon timing ContrastEach pixel gives lifetime & intensity

31 Optimising Agarose beads with FLIM of bound GBP-Badan in PBS. excitation 400 nm, fluorescence 550 nm fl. intensity image Zero glucose saturated (100 mm glucose) Fluorescence lifetime images of beads (1 exp fit)

32 Glucose sensing summary Reliable and accurate glucose monitoring is a major problem in diabetes awaiting a solution Fluorophore-labelled glucose-binding protein encapsulated in nanoengineered capsules or immobilised on a fibre optic probe has potential for in-vivo glucose sensing System can be miniaturized on an ASIC using pulsed or phase techniques with LED excitation, photodiode detection, average decay time determination, fibre optic coupling Recent review Nanomedicine and its potential in diabetes research and practice J C Pickup, Z-L Zhi, F Khan, T Saxl and D J S Birch Diabetes/Metabolism Res. and Rev. 24, , 2008.

33 2 nd application - β-amyloid (Aβ) fibrils Uses amino acid intrinsic fluorescence to monitor early stages of β-amyloid aggregation

34 Why study fibrils? Amyloid fibrils play a key role in neurology e.g. Alzheimer s, Parkinson s, Huntington s diseases, CJD form β - sheets of amyloid plaques in the brain Alzheimer s - Afflicts 5% men and 6% women over 60 > 20 m afflicted, expected to be >100 m by 2050 no clinical diagnosis, no cure Also in type II diabetes, cataracts The growth mechanisms of fibrils are poorly understood Understanding fibril growth may lead to new materials (as good as some old ones!)

35 The 3 fluorescent amino acids Pulsed LEDs are now the appropriate sources for these wavelengths See Peak absorption Meas. Sci. Technol. 15, L19-22, nm Appl. Phys. Letts. 86, , nm Appl. Phys. Letts 89, 63901, nm

36 The 3 fluorescent amino acids Pulsed LEDs are now the appropriate sources for these wavelengths See Peak absorption Meas. Sci. Technol. 15, L19-22, nm Appl. Phys. Letts. 86, , nm Appl. Phys. Letts 89, 63901, nm

37 β-amyloid - a protein fragment The peptide One tyrosine (in position 10) No tryptophan no energy transfer Forms fibrils amino acids ~ 10-8 M concentration in biological fluids (role unknown) Amphipathic nature - aggregation & plaques in the brain Early oligomers not β -sheets/plaques are thought to be the most cytotoxic Plaques symptom not cause

38 β-amyloid s single tyrosine - absorption & fluorescence spectra FluorescenceIntensity /a.u λ /nm Fluorescence Intensity /a.u Tyr emission spectra in beta-amyloid λ/nm Wavelenght /nm Ex@279n Absorption/excitation spectra of Tyr in Aβ. Fluorescence spectra of Tyr in Aβ

39 Thyoflavin T (ThT) extrinsic probe traditionally used to detect β-amyloid aggregation Fluorescence Intensity / a.u t / h: Increasingly planar configuration during β-amyloid aggregation increases fluorescence λ (nm) Evolution of emission spectra of ThT in time

40 Thyoflavin T (ThT) extrinsic probe traditionally used to detect β-amyloid aggregation 800 Peak Intensity / a.u No measurable change Problems Early stage aggregates are most neurotoxic, but not detected by ThT ThT needs β-sheets to be formed first ThT t / h Extrinsic probes can disturb native structure Evolution of emission intensity of ThT in time at peak intensity (482nm)

41 β-amyloid s tyrosine fluorescence decay - 3 exponential decay components - τ 1, τ 2, τ 3 correspond to tyrosine rotamers i(t) = Σ α i e t /τ i i=3 8 τ constant in early stages φ constant τ / ns component contributions to the fluorescence f i track decay amplitudes & rotamer populations p i f i = α i τ i /Σ i=3 α i τ I f i ~ φ i x p i τ 1 τ 2 τ t / h

42 β-amyloid tyrosine decay parameters. Populations p 1, p 2, p 3 derived from decay amplitudes α 1, α 2,α R C H N CH α O C N H R 0.5 p 2 O H H C β 0.4 O H p i p 1 p t / h Rotamers at 180,60, -60 Interpreted as aggregation affecting tyrosine rotamer distributions

43 Comparison between tyrosine and ThT Ratio between amplitudes p 1 and p 2 from Tyr and between F t and F 0 from ThT (ph 7, 30 µm Aβ, 22C) Tyr ~ 30% change 3 Tyr p 1 / p F t / F o ThT ThT Negligible change t / h For further details see O Rolinski, M Amaro & D Birch Biosens. & Bioelec. 25, 2249, 2010

44 β-amyloid fibrils summary Tyrosine fluorescence lifetime reports on early oligomer aggregation - Offers a new approach for research into drug intervention therapeutics

45 3 rd application - nanoparticle metrology Concerns over possible nanoparticle toxicology and risk to the environment Fear of the unknown the next asbestos? Risks unknown Correlation of effect with size unknown Size often unknown

46 3 rd application - nanoparticle metrology Concerns over possible nanoparticle toxicology Fear of the unknown the next asbestos? Risks unknown Toxicology correlation with size unknown Size often unknown 1-10 nm particles of particular concern pass through cell membranes & are the hardest to measure

47 Conventional Techniques for Np metrology x-ray, neutron scattering techniques -works over limited Np concentration range -difficult to use for on-line measurements -complex Light scattering - Inadequate resolution < 10 nm Electron micrographs & AFM -a direct visualisation, but only on dry samples, not in-situ Nitrogen isotherms and mercury porosimetry -only on dry samples, slow and expensive Fluorescence lifetime metrology ideal for 1-10 nm

48 Metrology? How can fluorescence lifetimes measure distance? Polarised fluorescence anisotropy decay time τ r gives radius r via Stokes- Einstein eq. τ = rrot 4πη r 3k T B 3 Non-radiative Fluorescence resonance energy transfer (FRET) rate k(r) between donor D and acceptor A quenches decay time - Requires D-A spectral overlap ( ) k r 1 R0 = τ r 0 I(t) = αexp-(t/τ 0 +k(r)) 6 δ(0) D I(t) k(r) r A

49 Fluorescence anisotropy Measurement geometry z Random molecule orientation Exc. Polariser I v (t) I h (t) x Fl. y

50 z Abs. probability ~ cos 2 θ I v (t) I h (t) x y Anisotropy introduced

51 z Anisotropy destroyed in ns by Brownian rotation I v (t) I h (t) x y I h (t) I v (t) ( ) r t = v ( ) h ( ) ( ) + 2 ( ) I t I t v I t I t h ( ) = 0 r t t r e τ 4πη r τ rot = 3k T B 3 rot

52 Application to silica nanoparticles - the idea is straight forward Dye electrostatically (or covalently) attached to silica particles R = 6 nm Free dye τ r ~ 200 ps - Gives microviscosity η Dye bound to SiO 2 nanoparticle τ r ~ 200 ns - Gives particle size Stable colloidal silica Dupont s Ludox AM30, ph 8.9

53 Colloidal silica (Ludox AM30) + fluorophore A negatively charged fluorophore added to SiO 2 with a negative surface charge - -Ve Before silica added ~ 200 ps After silica added ~ 300 ps Fluorescein τ ~ 4 ns No binding

54 Colloidal silica (Ludox AM30) + fluorophore A positively charged fluorophore added to SiO 2 with a negative surface charge -Ve + Rhodamine 6G τ ~ 4 ns Before silica added ~ 300 ps After silica added ~ inf Strong binding. But τ << τ r Hence no dynamic range

55 Colloidal silica (Ludox AM30) + fluorophore A positively charged fluorophore added to SiO 2 with a negative surface charge + -Ve Before silica added ~ 40 ps After silica added 6-Methoxyquinolinium τ ~ 25 ns ~ τ r / 10 τ r1 ~ 17 ns τ r2 ~ 273 ns τ r3 ~ infinity r Strong interaction. and dynamic range!

56 6-MQ attached to different Ludox -stable silica colloids Particle rotational diffusion Ludox τ r2 / ns r fl /nm r (SEM) SM30 65 ± ± nm AM ± ± nm AS ± ± nm Good agreement

57 Silica nanoparticle growth in a sol-gel Na 2 O.SiO 2.H 2 O + H 2 SO 4 Si(OH) 4 + Na 2 SO 4 Si(OH) 4 + Si(OH) 4 2(SiO 2 ) + 4(H 2 O) siloxane bonds formed Sub nm resolution ph 10, 2% SiO 2, t g 250 hr

58 Nanoparticle summary Fluorescence anisotropy decay reliably measures nanoparticle size In situ At comparatively low cost With ease of use And high resolution See K Apperson, J Karolin, R W Martin and D J S Birch Meas. Sci. Technol. 20, 25310, 2009

59 To Conclude. Fluorescence Lifetimes Routine to measure Provide more information than steady-state fluorimetry e.g. kinetics processes Versatile probe of nano-environment Combine with spectroscopy, microscopy & sensors Providing new approaches in helping to solve global healthcare problems

60 Acknowledgements Strathclyde University: Olaf Rolinski - FRET & Aβ Jan Karolin nanoparticles Mariana Amaro - Aβ KCL School of Medicine: John Pickup - Glucose & co-workers Horiba Jobin Yvon IBH Ltd: David McLoskey - UV LEDs Kulwinder Sagoo- UV LEDs Sponsors: EPSRC Scottish Funding Council Wellcome Trust & thank you for attending this Webinar