Proteomics, Genomics and Metabolomics in Kidney Disease. Principles, Potential Pitfalls and Promises

Transcription

1 Proteomics, Genomics and Metabolomics in Kidney Disease Principles, Potential Pitfalls and Promises (Transplantation a Model System) Peter Nickerson Krescent Meeting (Montreal 29)

2 Objectives 1. To overview omics technologies 2. To discuss advantages disadvantages of each method 3. To review the importance of study design 4. To discuss key attributes of a useful biomarker

3 Systems Biology Approach to Complexity Strategies to Profile all Components of a Sample gdna mrna Protein Metabolism 3, 5, Genes > 1, mrnas > 1,, Proteins Low MW Compounds (<5kD) acgtacca aggtaacg cggtttttcgt gtatctccctt cdna Microarrays 2-D Gels + 1 H Magnetic Resonance Tandem Mass Spectroscopy Spectroscopy

4 From Reductionist to Embracing Complexity Promise Define the Biological Mechanisms Clinical Phenotypes Elucidating the underlying integrated molecular processes responsible for the variability in clinical behaviour and outcome Hypothesis generation without learning bias a priori from past single-pathway experiments. Goals: Mechanistic Understanding Identification of Therapeutic Targets Surrogate Biomarkers

5 Omic Technologies Transcriptomics (mrna) interogate simultaneously cell s/tissues transcriptional activity of known genes Commercial Microarrays (1 s of oligonucleotide targets) Proteomics (Proteins) unbiased approach to identify differentially expressed proteins in health and disease two-dimensional gel electropheresis (2-DE) two-dimensional difference gel electrophoresis (2D DIGE) surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF) electrospray ionization (ESI) matrix-assisted laser desorption/ionization (MALDI) liquid chromatography coupled with mass spectrometry (LC-MS) Metabolomics (Metabolites) examines a panel of metabolites (<2 Da) relative to specific disease states Mass spectrometry (MS) Nuclear magnetic resonance spectroscopy (MR Spectra)

6 Array Technologies Limitations Sarwal, Curr Opin Organ Transplant (29) 14:544

7 HPLC MS/MS: Good, the Bad and the Ugly Advantages vs. Genomics not affected by microrna s not biased to known proteins relatively stable in biologic fluids easy to quantify once target protein identified enzyme activity can be measured Disadvantages vs. Genomics not able to amplify not easy to quantify in an array #proteins detectable are limited in a complex mixture Similar problems as Genomics Run to run variation Data analysis (bioinformatics) complex Defining appropriate controls for comparison

8 A small number of proteins make up the top 99% of serum by mass 9% 1 proteins 9-99% 12 proteins Fig. adopted from Anderson, N.L. and Anderson, N.G., Molecular and Cellular Proteomics, 1.11, (22)

9 Enhancing Sensitivity: Complexity Reduction 3ml Urine Depletion (1h at room temperature) Concentration (3ml to 4µl) ~1h at 4º C Reduction, Alkylation, Digestion (overnight at 37ºC) 6 antibodies: αhsa, Protein A, α Apolipoprotein, α β-2-m, α Haptoglobin, GtxHuIgG Centrifugal Filter Device, Millipore, 5kDa MWCO 5µl out of 4µl Clean on C18 Column Fractionation on SCX 2 fractions Mass spec (MS/MS) : 3 hour run

10 URINE LABELING WITH O- METHYLISOUREA 3ml Urine Depletion (1h at room temperature) Concentration (3ml to 4µl) ~1h at 4º C 6 antibodies: αhsa, Protein A, α Apolipoprotein, α β-2-m, α Haptoglobin, GtxHuIgG Centrifugal Filter Device, Millipore, 5kDa MWCO 3ml Urine Depletion (1h at room temperature) Concentration (3ml to 4µl) ~1h at 4º C Reduction, Alkylation, Digestion (overnight at 37ºC) 5µl out of 4µl Reduction, Alkylation, Digestion (overnight at 37ºC) Labeling with O-Methylisourea-Heavy (8h at room temperature) Labeling with O-Methylisourea-Light (8h at room temperature) Mixing the two samples Cleaning on C18 column Fractionation on SCX 2 fractions Mass spec

11 Sample 1 Trypsin Label with light isotope MS(/MS)-analysis - Quantitative information -Peptide identification Fractionation m/z Sample 2 Trypsin Label with heavy isotope

12 Metabolomics: need for Informatics The large number of data points in MR spectra requires an informatics approach: The strategy for pattern recognition has 4 stages: 1) Preprocessing : Area normalization, peak alignment 2) Feature selection: Identification of maximally discriminating averaged subregions of the spectra 3) Classifier development: With these subregions, develop crossvalidated linear discriminant analysis classifiers 4) Accurate visualization of results Somorjai RL et al. Artificial Intelligence Methods and Tools for Systems Biology (Dubitzky W and Azuaje F, (eds.)), Computational Biology Series, Vol. 5 Springer pp (24)

13 Omics Life Cycle Validation Bedside 1) Identification of Problem 2) Patient Cohorts 3) Clinical Databases 4) Specimen Collection Bench 1) Analysis Methods 2) Data Mining (Informatics) 3) Candidate(s) Selection 4) Assay Development

14 Rejection pathways Antigen recognition Proliferation Effector phase Destruction FasL APC Allorecognition Direct (Donor APC) Indirect (Recipient APC) Th IL-2 Costimuli B7:CD28 CD4-CD4L ICAM-LFA-1 etc. Th Th Th IL-2 IFNγ IL-5 CTL MØ M Eo Granzyme B Perforin TNFα etc. MBP Cellular rejection Tissue injury: IF/TA and TG IFNγ IL-4 IL-5 IL-13 B-cell anti-hla Ab C-activation ADCC Humoral rejection

15 Insights to Pathogenesis and Diagnostic Tools Cellular Level Urine Blood Gene mrna Protein Native forms Posttranslational Modifications Degraded Fragments Metabolism BK Mø CTL CNI Tox Tissue Where should we focus? At what level should we focus? On which aspect should we focus? Alloimmune Response Antibody Cellular Inflammatory Response Virus Drug Toxicity Ischemic Injury Parenchymal Response Virus Drug Toxicity Ischemic Injury Alloimmune Injury

16 Detection of urine proteins with SELDI-TOF-MS Laser Trace-view H H H H 333.+H H H H H H H H H H H H H H H H H H H H H H H H cm 5 μl L urine per spot Gel-view Quantification based on peak intensity Ion suppression Resolution >15kD Lower sensitivity + - High throughput Desalting Simple Resolution <15kD

17 Project Outline: Urine Proteomics Define the proteome associated with subclinical rejection Define the proteome associated with early interstitial fibrosis Identify novel pathways for therapeutic targeting Identify biomarkers useful for serial graft monitoring Identify patients who would benefit from additional immunosuppression Identify patients who could be safely withdrawn from immunosuppression

18 Barriers to Discovery Defining a Gold Standard The Biopsy is Tarnished Samples a fraction of the kidney when the underlying process may be patchy Fraction of the tissue processed from study is separate and often disparate from the tissue sample processed for histology Small sample size limits ability to look at specific cellular compartments or specific infiltrating cells Heterogeneity of the underlying process may not be recognized by pathology Inter-observer variability in pathological diagnosis Chronic graft injury is often pooled together, but the causes of injury may be very variable with different mechanisms.

19 Understanding the sample Timing - Urine concentration A B C D Creatinine 15 mmol/l Protein 11 mg/l 1:2 dilution of A 1:4 dilution of A 1:8 dilution of A Intensity H H H H H H H H H H H H H H H H H H H H H H H H H 581.+H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H 58.2+H H H H H H H H H H H H H H H H H H H H H H H H 57.3+H 552.+H H H H H H H H H H H H H H H H H 57.4+H H 586.+H H H H H H H E F 1:16 dilution of A H H H H H H 588.+H H H 1 5 Creatinine.9 mmol/l Protein 3 mg/l equals 1L/day equals 2L/day equals 4L/day equals 8L/day equals 16L/day equals 16.6L/day H H H 2 m/z 12 Schaub et al, Kidney International (24)

20 Understanding the sample First-void vs. midstream urine Da Da Da First-void Midstream First-void Midstream First-void Midstream First-void Midstream First-void Midstream First-void Midstream Male #1 Male #2 Male #3 Female #1 Female #2 Female #3 3 m/z 6 Schaub et al, Kidney International (24)

21 Understanding the sample Handling First-void urine Midstream urine Schaub et al, Kidney International (24)

22 Understanding the sample Blood in urine H H H H+1 Normal male urine Freeze-thaw Normal male urine plus blood (5:1) Freeze-thaw Intensity H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H * * Normal male urine Plus blood (5:1), Centrifugation Freeze-thaw H H H H H H H H H H H 466.+H H H H H H H H H H H H H H H H H H H H H H H 2 m/z 23 Schaub et al, Kidney International (24)

23 Understanding the sample Freeze-Thaw Schaub et al, Kidney International (24)

24 Understanding the sample Conclusions Grossly, mid-stream urine remains stable at 4C for 3 days, whereas first-void urine can undergo changes. Best to cool as soon as possible and freeze Up to 4 freeze-thaw cycles do not harm the sample Best to avoid freeze-thaw (Make aliquots) Consistent urine protein profiling needs mid-stream urines Blood in urine confounds the normal urine protein profile Need to spin urine prior to studying / freezing Urine protein profile remains unchanged up to a urine output of 3L/day Best to measure protein/creatinine ratios

25 Experimental Design Appropriate Patient Cohorts

26 Clinical grouping Transplanted patients Variable Stable transplant (n=22) Acute clinical rejection (n=18) ATN (n=5) Recurrent GN (n=5) Clinic Never had clinical or histological rejection before No DGF - DGF Proteinuria > 1.5g/day Allograft function Creatinine always stable within 11% of baseline Creatinine elevation >11% of baseline On dialysis or Creatinine > 88μmol/L on day 6 - Allograft biopsy (Banff 97) A-score= C-score= A-score 4 C-score 2 A-score= C-score 2 ATN A-score 2 GN Others Within 1st year post transplantation Negative Flow-XM Variable Schaub et al. J. Am. Soc. Nephrol. 15, 24

27 Clinical grouping Non-transplanted control groups Variable Normal Controls (n=28) Lower urinary tract infection (n=5) Clinic Healthy UTI symptoms Kidney function Normal Sediment Culture >4 leucocytes per hpf >1 8 cfu Schaub et al. J. Am. Soc. Nephrol. 15, 24

28 Experimental Design Sample Analysis

29 Understanding the technology Reproducibility Intensity m/z H H H H H H H H H H H H H H H H H H H H H 886.+H 998.+H H H H H H H H H H H H H H H 57.1+H H H H H H H H 996.+H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H Schaub et al, Kidney International (24)

30 Definition of the normal and rejection pattern H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H 969.+H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H H 2.5 Normal control with normal pattern Stable transplant with normal pattern Acute clinical rejection with rejection pattern Glomerulopathy Acute tubular necrosis Urinary tract infection 5 mass over charge (m/z) 12 Schaub et al. J. Am. Soc. Nephrol. 15, 24 intensity

31 All samples in gel-view Normal controls (n=28) Stable transplant (n=22) * * * * * Acute clinical rejection (n=18) Acute tubular necrosis (n=5) Glomerulopathy (n=5) Urinary tract infection (n=5) 5 mass over charge (m/z) 12 Schaub et al. J. Am. Soc. Nephrol. 15, 24

32 Correlation with clinico-pathological course Allograft biopsies (Banff 97) IB Normal Normal Urine protein profiles 12 mass over charge (m/z) 5 Rejn Norm III II I 18 Allograft function Creatinine [μmol/l] High dose steroids Week post transplantation 28 Schaub et al. J. Am. Soc. Nephrol. 15, 24

33 Identification Beyond Pattern Recognition

34 Purification of proteins Proteins can be separated / purified based on» Size (e.g. gel filtration chromatography)» Point of isoelectricity (e.g. anion/cation-exchange chromatography)» Hydrophobicity (reverse-phase chromatography)» Solubility

35 Intensity Enrichment of peaks of interest using Cation-Exchange Beads H H H H H H H H H Before incubation on CM-beads H H H H H H 795.+H 88.9+H H H H H H H H H 155.+H H H H H H Supernatant flow through after incubation on CM-beads H H H H H H H H H H 81.4+H H H H H H H H H H H H H H H H H 51.7+H H H H H 87.9+H H H H H H H 127.+H H H Elution fraction (2mM KCl) m/z Schaub et al AJT (25) 5:729

36 Absorbance [mau] Acetonitrile [%] Purification of peaks of interest Fraction A Fraction B Retention time [min] intensity A B IV I II III m/z Schaub et al AJT (25) 5:729

37 Peptide mass fingerprinting and peptide sequencing Reduction Alkylation Trypsin digest Intensity m/z Intensity m Results \\Protein-central\ms_data\wilkinslab\Tracey Weiler\143-MSMS\SP (14:28 4/15/3) Description: none available Mass spectrometry (MALDI) Select ion for sequencing (MS/MS) Identification? Submit for sequence analysis \\Protein-central\m s_data\wilkinslab\tracey W eiler\143-m SM S\SP (14:28 4/15/3) Description: none available Submit for peptide mass fingerprinting Database search

38 Identification of cleaved forms of β2-microglobulin β2-microglobulin sequence IQRTPKIQVY SRHPAENGKS NFLNCYVSGF HPSDIEVDLL KNGERIEKVE HSDLSFSKDW SFYLLYYTEF TPTEKDEYAC RVNHVTLSQP KIVKWDRDM IQR TPKIQVY SR HPAENGK S NFLNCYVSGF HPSDIEVDLL K NFLNCYVSGF HPSDIEVDLL K FLNCYVSGF HPSDIEVDLL K LNCYVSGF HPSDIEVDLL K CYVSGF HPSDIEVDLL K Non-tryptic cleaved YVSGF HPSDIEVDLL K VSGF HPSDIEVDLL K SGF HPSDIEVDLL K GF HPSDIEVDLL K HPSDIEVDLL K S NFLNCYVSGF HPSDIEVDLL S NFLNCYVSGF HPSDIEVDL S NFLNCYVSGF HPSDIEVD Non-tryptic cleaved Trypsin cleavage sites (R & K) Observed non-tryptic cleavage sites NGER IEK VE HSDLSFSK IEKVE HSDLSF IEKVE HSDLSFS IEKVE HSDLSFSKD IEKVE HSDLSFSKDW IEKVE HSDLSFSKDWS IEKVE HSDLSFSKDWSF IEKVE HSDLSFSKDWSFY Non-tryptic cleaved Missing piece DEYAC R EF TPTEKDEYAC R F TPTEKDEYAC R TPTEKDEYAC R PTEKDEYAC R TEKDEYAC R EKDEYAC R KDEYAC R VNHVTLSQP K IVK WDR WDRDM Identified peptides

39 Megalin α1-microglobulin 2-microglobulin Neutrophil gelatinase associated lipocalin Nat Rev Mol Cell Biol 3: , 22 Am J Physiol Renal Physiol 28: F , 21 FEBS 579(3): , 25

40 β2-microglobulin where is it cleaved Acute Rejection Normal Megalin receptor Re-uptake Secretion of proteases by tubular cells Lysosome Secretion of proteases by CTL, macrophages Release of proteases by tubular cells death

41 Aspartic proteases are responsible for β2-m cleavages Immediately after adding β2-m After 6 hours at 37 C β2-m ++ β2-m β2-m + IV II III A ph 5 No PI added B ph 5 + Pepstatin intensity C ph 5 + Complete, EDTA-free D ph 5 + EDTA E ph 6 No PI added m/z Schaub et al AJT (25) 5:729

42 Working hypothesis All patients in our study had tubulointerstitial rejection (Acute Banff-Score i2t2) Tubular cell stress/injury Reabsorption of intact β2-m Urine ph [Proteases] in urine Cleaved β2-m

43 Validation Importance of Separate Data Sets

44 Urine Proteomic Studies Identifying 2 -Microglobulin in Kidney Allograft Rejection Oetting et al, Am J Kidney Dis (26) 47:898 MALDI-TOF TOF-MS 3 patients with Acute Rejection 15 patients with Normal Kidney Function

45 Beyond SELDI-TOF TOF-MS Going Deeper into the Proteome to define molecular programs associated with Subclinical Rejection (LC- MS/MS)

46 Sample Type # of proteins identified # Common Proteins # Unique Proteins Clinical Rejection 385 Clinical Rejection 397 Clinical Rejection 459 Clinical Rejection 447 Clinical Rejection 473 Clinical Rejection 369 Subclinical Rejection 38 Subclinical Rejection 558 Subclinical Rejection 437 Subclinical Rejection 427 Subclinical Rejection 346 Subclinical Rejection 336 Bx Normal Transplant 512 Bx Normal Transplant 457 Bx Normal Transplant 357 Bx Normal Transplant 455 Bx Normal Transplant 524 Bx Normal Transplant 562 Bx Normal Transplant 558 No Transplant 687 No Transplant 815 No Transplant 681 No Transplant

47 Sample Type # of proteins identified # Common Proteins # Unique Proteins Clinical Rejection 385 Clinical Rejection 397 Clinical Rejection 459 Clinical Rejection 447 Clinical Rejection 473 Uncharacterized, 11 Clinical Rejection 369 Subclinical Rejection 38 Subclinical Rejection 558 Subclinical Rejection 437 Cell structure, 5 Subclinical Rejection 427 Subclinical Rejection 346 Subclinical Rejection 336 Bx Normal Transplant 512 Bx Normal Transplant 457 Cell metabolism & signaling, 1 Bx Normal Transplant 357 Bx Normal Transplant 455 Bx Normal Transplant 524 Bx Normal Transplant 562 Bx Normal Transplant 558 Normal Control 687 Normal Control 815 Normal Control 681 Normal Control 491 Cell cycle, 9 IRI, Fibrosis, Immune,

48 Beyond HPLC MS-MS Quantifying Candidate Proteins (ELISA)

49 CXCL9 and CXCL1 Increase in Subclincal/Clinical Rejection but not IF/TA 3 8 p=.1 25 p< p=.2 CXCL9 (ng/mmol) 15 p=.3 CXCL1 (ng/mmol) 4 p<.1 p=.3 p=.2 1 p=.6 p= p=.1 IF/TA (n=1) Normal histology (n=24) Subclinical borderline tubulitis (n=15) Subclinical tubulitis Ia/Ib (n=22) Clinical tubulitis Ia/Ib (n=17) IF/TA (n=1) Normal histology (n=24) Subclinical borderline tubulitis (n=15) Subclinical tubulitis Ia/Ib (n=22) Clinical tubulitis Ia/Ib (n=17) Schaub, et al AJT (29)

50 Tubular Injury Markers don t Separate Subclincal/Clinical Rejection from IF/TA A 5 B 5 p<.1 4 p=.3 4 P=.3 α1m/creat [mg/mmol] 3 2 p=.3 p=.19 3 NGAL/creat [μg/mmol] 2 p=.3 p=.2 p=.77 p= p=.4 IF/TA (n=1) Normal histology (n=24) Subclinical borderline tubulitis (n=15) Subclinical tubulitis Ia/Ib (n=23) Clinical tubulitis Ia/Ib (n=18) IF/TA (n=1) Normal histology (n=24) Subclinical borderline tubulitis (n=15) Subclinical tubulitis Ia/Ib (n=23) Clinical tubulitis Ia/Ib (n=18) Schaub, et al AJT (29)

51 Chemokines

52 Proteomic Strategy to Develop Monitoring Tools Define the proteome associated with subclinical rejection Define the proteome associated with early interstitial fibrosis (Dr. Ho) Next Step: Determine if proteins predictive Wpg Urine Biobank Identify novel pathways for therapeutic targeting (e.g. CXCL9, CXCL1) Identify biomarkers for serial graft monitoring (e.g. CXCL9/1, 2m, 1m) Next Step: validation in clinical studies NIAID CTOT-1 FKC 8 FKC 14 Identify patients who would benefit from additional immunosuppression Identify patients who could be safely withdrawn from immunosuppression NIAID CTOT-2

53 Lessons Learned: Collection, Handling & Processing Samples Critical Classification Critical Improved by Serial Pathology and Clinical Course SEDLI-TOF-MS (High-Throughput) Proteome patterns able to establish gross differences between groups Limited Sensitivity Can be used during protein isolation techniques to track protein of interest LC -MS/MS (Low-Throughput) Sensitivity increased by: Depletion of high abundant proteins Separation of proteins via 2 Dimensional HPLC pre MS/MS Assessment of candidate proteins requires: Quantitiative approach (i.e. ELISA)

54 Requirements of a Biomarker assay Evaluation beyond a single cohort (i.e. validated) Assessed in consecutive series of patients with multiple pathologies (i.e. true determination of sensitivity, specificity, PPV, NPV) Reproduced by an independent group to demonstrate robustness of the assay Longitudinally assessed to determine ability of a given assay to detect pathologic processes both early and late post-transplant Demonstrate the candidate assay returns toward baseline with effective therapy Capable of detecting subclinical levels of injury (acute inflammation, IFTA or TG) Nickerson P. Current Opinion in Immunology (29) 21: