Colin Campbell. Improved surface technology. for protein arrays

Transcription

1 Colin Campbell Improved surface technology for protein arrays

2 Introduction Rationale Background Surface choice for protein microarray Detection and discrimination of diverse surface antigens Label-free detection Analysis tools

3 Common ABO blood types A 1 B A 1 B O A 2 The basic unit of the ABO system is the O antigen: fucose-terminated pentasaccharide The A and B antigens are derivatives In the case of A the sugar is N-acetyl galactose In the case of B it is galactose.

4 Current methods of blood typing Olympus plate reader Diamed chromatography card

5 Protein array surface chemistry Define surface chemistry: Glass slides have been prepared and coated with 1. Polyion 2. Functional silane layer 3. Functional hyrogel layer H

6 Comparison of array surfaces 2 gold 15 Hydrogel I 1 Epoxy Silane S/N 5 Hydrogel II BRAD3 JLDM3 LA2 LB2 Poly-l-lysine

7 Surface enhanced fluorescence Effect of metallic surface: Fluorophore quenching -5 nm Increased radiative decay rate/quantum yield 5-2 nm

8 B S/N A1 A B 1 BRAD3 DAM1 ES15A(B) JLDM3 LA2 DIL 1/8 LB2 DIL 1/2 BRAD3 DAM1 ES15A(B) JLDM3 LA2 DIL 1/8 LB2 DIL 1/2 A2 A 2 O BRAD3 DAM1 ES15A(B) JLDM3 LA2 DIL 1/8 LB2 DIL 1/2 S/N S/N ABO detection Anti-RhD Anti-A Anti-A(B) -ve cont Anti-A Anti-B Anti-RhD Anti-A Anti-A/B -ve cont Anti-A Anti-B a b BRAD3 DAM1 ES15A(B) JLDM3 LA2 DIL 1/8 LB2 DIL 1/2 Anti-RhD Anti-A Anti-A(B) -ve cont Anti-A Anti-B Anti-RhD Anti-A Anti-A(B) -ve cont Anti-A Anti-B c d S/N

9 A1B+ A2B+ A 1 BRhD A 2 BRhD BRAD3 DAM1 ES15A(B) JLDM3 LA2 DIL 1/8 LB2 DIL 1/2 A1+ BRhD B+ A 1 RhD BRAD3 DAM1 ES15A(B) JLDM3 LA2 DIL 1/8 LB2 DIL 1/2 S/N S/N Ax+ A X RhD S/N BRAD3 DAM1 ES15A(B) JLDM3 LA2 DIL 1/8 Anti-RhD Anti-A Anti-A(B) -ve cont Anti-A Anti-B Anti-RhD Anti-A Anti-A(B) -ve cont Anti-A Anti-B a b LB2 DIL 1/2 BRAD3 DAM1 ES15A(B) JLDM3 LA2 DIL 1/8 LB2 DIL 1/2 O+ BRAD3 DAM1 ES15A(B) JLDM3 LA2 DIL 1/8 LB2 DIL 1/2 BRAD3 DAM1 ES15A(B) JLDM3 LA2 DIL 1/8 LB2 DIL 1/2 S/N S/N S/N Anti-RhD Anti-A Anti-A(B) -ve cont Anti-A Anti-B Anti-RhD Anti-A Anti-A(B) -ve cont Anti-A Anti-B c d ORhD Anti-RhD Anti-A Anti-A(B) -ve cont Anti-A Anti-B Anti-RhD Anti-A Anti-A(B) -ve cont Anti-A Anti-B e f

10 Rhesus antigen Most common Rhesus antigens are D, C or c and E or e Encoded on two structurally homologous genes on the Rh locus. Both are 417 aa multi-pass integral membrane proteins with 6 exposed peptide loops on erythrocyte surface presenting discrete antigenic epitopes. Two proteins differ by 36 amino acids and the antigenic regions differ by as little as one amino acid between RhD and RhCE

11 Rhesus discrimination log (S/N) LHM76/58 LHM76/59 LHM5/2B ESD1 LHM76/55 LHM77/64 LHM7/45 LHM59/19 LHM169/8 BRAD3 LDM1 LDM77/64 ESD1M H48 DEM1 Antibodies R 1 R 1 blood has D antigen but neither c nor E r r has c and E but not D

12 Label-free blood typing Motivation Remove variability and time by removing process steps like Purification Labelling Came about from efforts to label the whole blood proteome

13 Choice of scanner settings 1.5 Red Cells nm 488/1 543/1 543/2 543/3 488/1 Repeat DAM1 ES15 LA2 LB2 Anti-A Anti-A(B) Anti-A Anti-B S/N Absorbance Case 488/1 Case 543/1 Case 543/2 Case 543/3 Excitation wavelength (nm) Detection wavelength (nm)

14 1 Group B Labelled Red Cells Whole Blood - Neat Whole Blood 1/5 Dilution Whole Blood 1/1 Dilution log S/N Ratio Choice of sample pre-treatment 1 DAM1 Neat ES15 Neat LA2 Neat LB2 1:4 Anti-A Anti-A(B) Anti-A Anti-B.1 Type O Group A1 1 Labelled Red Cells Whole Blood - Neat Whole Blood 1/5 Dilution Whole Blood 1/1 Dilution Labelled Red Cells Whole Blood - Neat Whole Blood 1/5 Dilution Whole Blood 1/1 Dilution 3 DAM1 ES15 LA2 LB2 2 1 DAM1 Neat ES15 Neat LA2 Neat LB2 1:2 Anti-A Anti-A(B) Anti-A Anti-B log S/N Ratio log S/N Ratio Anti-A Anti-A(B) Anti-A Anti-B Shows label-free ABO discrimination

15 Conclusion Array based method can discriminate common erythrocytes Autofluorescence can be used as a readout modality

16 Evaluation of a Protein Microchip Method for Typing Whole Blood Stew Lab Talk 2 th November 26

17 Aim Take 67 blood samples and evaluate the array method of ABO phenotyping. Arrays were printed with multiple spotted replicates of antibodies specific for either A (LA2) or B (LB2) blood type antigens, along with PBS and IgG only spots as negative controls In total 32 separate sub-arrays were printed per slide, with each sub-array containing 5 replicates of LA2 antibody, 7 replicates of LB2, 2 replicates of IgG and 7 replicates of PBS Therefore each array contained the following numbers of replicate spots: LA2 (n = 16), LB2 (n = 224), IgG (n = 64) and PBS (n = 224)

18 Expected Results Three blood types were analysed: A, B and O Two antibodies were used to detect these different blood types: LA2 = anti-a blood type antigen LB2 = anti-b blood type antigen Type A blood should react with the LA2 antibody Type B blood should react with the LB2 antibody Type O blood should not react with either antibody (negative response)

19 ROC Curves ROC curves were initially developed in the 194s in order to make sense of radio signals contaminated by noise ROC s are a graphical plot of sensitivity vs (1-specificity) or true positives vs false positives The optimum predictive outcome is therefore a curve in the upper left corner of the graph i.e % sensitivity (all true positives found) and % specificity (no false positives found) In contrast a completely random predictor would give a straight line at 45 degrees from the horizontal, from bottom left to top right

20 Use of ROCs to set thresholds An Index Score was obtained for each array where the median signal-background value for the LA2 antibody was divided by the median for the LB2, giving a ratio value for the two antibody responses ROC curves (sensitivity vs. (1-specificity)) were then plotted to obtain threshold values within which it could be confidently said that a given sample was of a particular blood type

21 Defining a threshold ROC curves were constructed to obtain threshold values for each of the blood types, the ROC curve for the A blood type is shown below The ROC curve is a graphical plot of sensitivity vs. (1-specificity). For the ROC analysis the A blood type sample index scores were used to represent the true positive samples, whilst the index scores of the B blood type samples were used as the false positives Area under curve =.995

22 Defining a threshold The ROC curve demonstrated a good ability to separate the A and B blood types as the area under the curve (.995) was close to the maximum area of 1, indicating a total separation of the sample sets. This indicates that for the chosen threshold cut-off value of 2.71 for the A blood type values, a sensitivity of % and a specificity of 96.2 % was obtained Threshold values for the other blood types were obtained and are presented below, again the ROC curves demonstrated a good ability to separate both the A and O, and the B and O blood types Blood Type Threshold Value Selected of Index Score from ROC Curve % Sensitivity at Threshold % Specificity at Threshold A B O (at.929) 92.3 (at 2.7) (at.929) 97 (at 2.7)

23 Assigning blood types based on the selected thresholds Carried out a hold-out validation by using 9% of the samples as training set and 1% as a test set Classification A B O Total Samples Total Samples Correctly Predicted Incorrectly Predicted % Samples Correctly Predicted

24 Conclusions Shown that we can use antibody array technology to accurately phenotype RBCs by detecting complex mixtures of antigens on the cell surface The system is label free and can detect blood type antigens in whole blood samples thus acting to significantly simplifying the blood typing procedure The use of ROC curves allows the definition of clear thresholds within which an unknown sample can be successfully assigned a particular blood type

25 Acknowledgements DPM Peter Ghazal, John Beattie, Alan Ross, Stewart Burgess, Thorsten Forster SNBTS Nick O looney, Janine Robb, Marisa Chong- Kwan, Juraj Petrik Scottish Enterprise