FIDA for Rapid Detection of Protein Based Biomarkers

Transcription

1 FIDA for Rapid Detection of Protein Based Biomarkers Guisheng Zhuang 1, Nicklas N. Poulsen 1, Nina Z. Andersen 1, Jesper Østergaard 1,2, Jørgen Schøller 2 and Henrik Jensen 1,2 1 Department of Pharmacy, Faculty of Health and Medical Sciences, University of Copenhagen 2 FIDA-Tech Aps Dias 1

2 FIDA: Flow Induced Dispersion Analysis, is a new flow based methodology for rapid quantification of biomarkers Analytes passing through a capillary are dispersed due to flow and diffusion A A + B Dispersion analysis in microfluidics may therefore give information on binding and Analyte (B) concentration Dias 2

3 Determination of stability constants D + βcd = D-βCD AU [βcd] = 0 and 12.1 mm Free analyte Time / min Complex 7.2 t R / σ α-naphthol naproxen binding isotherm 6 8 [βcd] (mm) Compound K a (M -1 ) D Ab (cm 2 s -1 ) D ALc (cm 2 s -1 ) α-naphthol 2400 (± 240) e Naproxen 1050 (± 185) g Henrik Jensen and Jesper Østergaard; Flow Induced Dispersion Analysis Quantifies Noncovalent Interactions in Nanoliter Samples J. Am. Chem. Soc., 2010, 132, Dias 3

4 Analyte Quantification by FIDA: Instant ELISA All we need is a hydrodynamic flow! 1.2x σ 2 / t R x10-3 σ 2 / t R α-naphtol K = 650 L/mol [β-cd] / mm log [β-cd] With proper calibration and system setup, measurement of σ 2 provides ligand concentration. In this example the concentration of β-cd is determined. Fast one-step method! Can this approach be used for more interesting analytes: Proteins (biomarkers), Toxins, DNA, vira or bacteria? Dias 4

5 Analyte Quantification by FIDA: Instant ELISA Traditional ELISA procedure Total time of analysis: 2-4 hours long analysis time is due to slow mass transport and heterogeneous kinetics, multiple washing procedures, and signal transduction (typically relying on an enzymatic reaction) Complications due to non-specific Adsorption Many possibilities for pipetting errors. Difficult to automate. Dias 5

6 But is FIDA really well-suited for POC applications? Can we handle complex biomolecules such as proteins? Can we analyse biological samples such as plasma, urine or blood? Can we down-size the currently used instrumentation? Are we able to accurately characterize FIDA (for development and quantification purposes)? Dias 6

7 Analyte Quantification by FIDA: Instant ELISA Bromocresol green Human serum albumin (HSA). Fast assay for determination of HSA in urine UV detection (small-large) Addition of HSA Conditions: Pressure: 20 mbar [Bromocresolgreen] = 50 x 10-6 mol /L Artificial urine: NaCl, KCl, sodium phosphate buffer, Creatinine. Conditions: As example on the Left, but with 1.5 g/l HSA Dias 7 σ 2 1 σ [HSA] / g L [HSA] / g L Conditions: Pressure: 20 mbar [Bromocresolgreen] = 50 x 10-6 mol /L Artificial urine: NaCl, KCl, sodium phosphate buffer, Creatinine.

8 Analyte Quantification by FIDA: Instant ELISA The BSA-FC and antibsa system: Interaction of two large molecules Standard curve for quantification of antibsa 6 BSAfc + IgG = BSAfc-IgG 0.24 UV / AU 4 2 σ Time / Min [IgG] / 10-7 M Flow induced dispersion of BSAfc in a 50 mm ID silica capillary with (red) and without (blue) IgG, respectively. Unpublished results Peak variances, σ 2, versus IgG concentration. Unpublished results. Conditions: Pressure: 20 mbar, [BSA-FC] = 10 x 10-6 mol /L,66 mm phosphate buffer Dias 8

9 Analyte Quantification by FIDA: Instant ELISA Detection of Human Serum Albumin in Plasma Samples t R (min) nm fluorescein 80 µm humant serumalbumin Intensitet (a.u.) t R (min) Dispersion of unbound fluorescein and fluorescein bound to human serum albumin. The variance of the peak for unbound fluorescein is 0,012 min 2 and for fluorescein bound to albumin it is 0,043 min 2. Fluorescence detection was employed to detect the indicator molecule fluorescein. A membrane filtration was applied to the samples. Dias 9

10 Analyte Quantification by FIDA: Instant ELISA Detection of Human Serum Albumin in Plasma Samples 9x10-3 σ 2 (min 2 ) Standard curve. The variance of 7 nl 50 nm fluorescein was analysed with increasing concentrations of human serum albumin present in the run buffer. The time for each experiment was approximately 2.5 minutes. Each data point shows the average of three injections plus/minus the standard deviation [HSA] (M) 150x10-6 Plasma sample FIDA HSA (g/l)(average ± rstd) BCP Relative standard deviation between the two assays 1 36,5 (±0,4 %) 32,7 (±0,2 %) 6,2 % 2 33,9 (±6,8 %) 27,6 (±0,5 %) 12,2 % 3 37,8 (±7,8 %) 32,9 (±0,2 %) 9,3 % Comparison of human serum albumin concentration in plasma samples determined with FIDA and a Bromocresol Purple assay. Three samples were analysed with both assays the relative standard deviation between the two assays is shown. Dias 10

11 Are we able to accurately characterize FIDA? What determines analysis speed and sensitivity? FIDA succesfully modeled employing FEM simulations (see poster) Requirements to flow, geometry and diffusivity for optimal performance What determines sensitivity? 1) Ability to detect the ligand (indicator molecule) in a low concentration. 2) The affinity constant between ligand (indicator molecule) and analyte. BSA-FC 10 Log(RFU) time (min) vs ~1E-7M time (min) vs ~1E-8M time (min) vs ~1E-9M time (min) vs ~1E-10M time (min) vs ~1E-11M time (min) vs ~1E-12M Using our current detection system, detection limits may be extended to the pico molar range or possibly lower. (1pM = mol = 6000 molecules of IgG) time (min) Dias 11

12 Outline of simple device (may be based on integrated microfluidic system) Integrated microfluidics, sample pretreatment, detection and data analysis First experiments: Lab-based instrumentation Lab-rack prototype for development (see poster) Dias 12

13 IPR Status Analyte quantification using flow induced dispersion analysis PCT/EP2011/ International report on patentability: Main claims accepted in terms of novelty, inventive steps and industrial applicability. IP licenced to FIDA-tech Aps (1/9-2012) Possible IP related to sample pre-treatment, optimisation of dispersion using novel flow geometries and future prototype designs Dias 13

14 FIDA is well-suited for POC applications! Can we handle complex biomolecules such as proteins? Can we analyse biological samples such as plasma, urine or blood? Can we down-size the currently used instrumentation? Are we able to accurately characterize FIDA? Future applications will focus on autoimmune diseases (antibodies) and (type 2) diabetes (glycosylated albumin). Dias 14

15 Acknowledgements: University of Copenhagen (initial IP cost) MVTU: Proof-of Concept 0.75MKr, MVTU: FTP 5.4 MKr Nicklas N. Poulsen 1, Guisheng Zhuang 1, Nina Z. Andersen 1, Jesper Østergaard 1,2, Jørgen Schøller 2 and Henrik Jensen 1,2 1 Department of Pharmacy, Faculty of Health and Medical Sciences, University of Copenhagen 2 FIDA-Tech Aps Dias 15