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Host Cell Protein Analysis by Mass Spectrometry | KBI Biopharma

Host Cell Protein Analysis by Mass Spectrometry. Originally presented at the 2018 Sciex Users Meeting by Michael J Nold, Ph.D., Mass Spectrometry Core Facility at KBI Biopharma.

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Host Cell Protein Analysis by Mass Spectrometry | KBI Biopharma

  1. 1. a customer and science-focused contract development & manufacturing organization HOST CELL PROTEIN ANALYSIS BY MASS SPECTROMETRY Michael J Nold, Ph.D. Director, Mass Spectrometry Core Facility
  2. 2. • Challenges with HCPs • HCP Spectral Library Generation • Process Clearance Monitoring HCP– Analysis by Mass Spectrometry Overview 2
  3. 3. HCP– Analysis by Mass Spectrometry Challenges with HCPs • HCPs are impurities generated when recombinant proteins are manufactured. Recombinant proteins are frequently expressed in host cells from various cell lines. • Mammalian, Microbial, Bacterial, Yeast, Plant, Insect • Residual HCPs may affect product quality, safety and efficacy. • Toxicity, immune response to target, adjuvant effect, augment ADA response, bioactivity, product stability, product potency • Risks from a variety of factors • Dosing and dose frequency, patient demographics, route of administration
  4. 4. HCP– Analysis by Mass Spectrometry Challenges with HCPs Many Challenges: • Variability of host cell substrates • Large number of protein analytes • Variability of protein population during upstream processing • Parental cell line, cell age, cell viability, feeding strategy, etc. • Dynamic range difference between DP and HCPs ( ≥e6 ) • Detection of HCPs that are not immunogenic à Immunoassay may miss these • HCP population can change during process development • HCPs may copurify with DP – “Hitchhiker” effect
  5. 5. HCP– Analysis by Mass Spectrometry Challenges with HCPs Mass Spectrometry Challenges: • Column capacity, sample loading • DP overload on column • Mass spectrometer sensitivity • Dynamic range for ion detections • False positives, negatives • Ion statistics for identification, quantitation • Speed – Data to results to support process development • Does library reflect the process? • Time to generate a new library
  6. 6. KBI HCP Reagents and Applications PHYSICAL CHEMICAL ATTRIBUTE #1 PHYSICAL CHEMICAL ATTRIBUTE #3 PHYSICAL CHEMICAL ATTRIBUTE #2 6
  7. 7. HCP– MS Workflow Overview LCMS via ACQUITY/6600 TripleTOF Spectral Library Generation Sample Analysis Data Processing and Library Searching Data Independent Acquisition SWATH MS Data Dependent Acquisition LC-MS/MS CHO HCCF Various Separation Methodologies Protein Level Additional Separation/ Digest Peptide Level Spectral Library 1% FDR Various Separation Methodologies Protein Level Additional Separation/ Digest Peptide Level List of identified proteins and peptides Spectral library matching based on set search criteria and thresholds Sample 7
  8. 8. HCP– MS Workflow Overview LCMS via ACQUITY/6600 TripleTOF Spectral Library Generation Sample Analysis Data Processing and Library Searching Data Independent Acquisition SWATH MS Data Dependent Acquisition LC-MS/MS CHO HCCF Various Separation Methodologies Protein Level Additional Separation/ Digest Peptide Level Spectral Library 1% FDR Various Separation Methodologies Protein Level Additional Separation/ Digest Peptide Level List of identified proteins and peptides Spectral library matching based on set search criteria and thresholds Sample 7
  9. 9. HCP Spectral Library Generation Sample Preparation on the Protein and Peptide Level Process Samples 1D Analysis - No peptide level fractionation Process Samples 2D Analysis - High pH RP-HPLC peptide level fractionation Fraction 3 Fraction 2 Fraction 1 Fraction 4 Fraction 5 Peptide level fractionation of 5 of the 8 protein fractionated samples PHYSICAL CHEMICAL ATTRIBUTE #1 PHYSICAL CHEMICAL ATTRIBUTE #3 PHYSICAL CHEMICAL ATTRIBUTE #2 8
  10. 10. HCP Spectral Library Generation Sample Load Optimization • Load Optimization Goal: achieve a dynamic range of ≥ 3 logs at the protein level for each experiment. • Utilize the ITC (ion transmission control) Count Conversion of the TOF MS TIC to determine the appropriate amount on column: optimized load when the TOF MS TIC apex is between 10-20%. • ITC: dynamically adjusts percent of the ion beam (voltage gate) according to an observed TIC signal to prevent saturation. • ITC Count Conversion plots the ITC voltage gate response: no signal / gate fully open = 100% saturation / gate fully closed = 0% TOF MS TIC – SWATH ITC Count Conversion of the TOF MS TIC – SWATH TOF MS TIC Apex 9
  11. 11. 1.E+04 1.E+06 1.E+08 0 10 20 30 40 50 ProteinArea Protein Number Log Plot of Protein Dynamic Range HCP Spectral Library Generation Sample Load Optimization – Depth of Database • ADH: spiked in all samples at 300 fmol/µL**, used as a system suitability test and the signal response for relative quantitation. • PCM: spiked in all samples at 100 fmol/µL**, used as a retention time calibrator allowing for retention time alignment on any chromatographic system or timescale. ** Concentration of ADH and PCM is relative to 2 µg/µL of total HCP concentration. XIC - Yeast Alcohol Dehydrogenase (ADH) XIC - Peptide Calibration Mix (PCM) Graph generated using the HCPs identified in sample S3 to conceptually show the dynamic range of identified HCPs. 10
  12. 12. HCP Spectral Library Generation IDA Library Data Collection and Processing ProteinPilot™ data processing w/ Paragon™ Algorithm. IDA spectral library Filter IDA spectral library based on acceptance criteria. • Acceptance Criteria for Library: • 1% FDR • No modifications or clipped peptides • Minimum of 2 peptide identifications per protein • Peptide Confidence Level: 95% • 10 ppm mass error tolerance • 2/2 identification replication Acquire IDA data in duplicate for each of 28 HCP samples/fractions. 11
  13. 13. HCP Spectral Library Generation Contributions from 3 physiochemical preparations & fractionation Physiochemical Attribute 1 1850 Proteins Physiochemical Attribute 2 2925 Proteins Physiochemical Attribute 3 2137 Proteins 3802 Proteins 114 304 1047 598 976 385 378
  14. 14. • HCPs are monitored from samples collected along a purification process, either for process development feedback, or monitoring a final process for one or more batches. • Samples are analyzed in triplicate, and identifications will have to meet a set of criteria at both peptide and protein levels. • Results include the list of identified HCPs, and relative quantitative information. • As an illustration, samples were obtained from the last four points of sampling from one of our programs. Protein A Viral Inactivation AEX* Based Polishing (Flow Through mode) CEX* Based Polishing Viral Filtration UF/DF Clarified Harvest *May be mixed mode S3 S4 S5 S6 HCP Process Clearance Monitoring Stand Alone, ELISA Support, or Process Development Support 7193 ppm 125 ppm 10 ppm 4 ppm 12
  15. 15. SWATH data file HCP Ion Library Selected Protein Selected Peptide Acceptance Criteria • 2 Peptides per protein • 4 transitions per peptide • FDR: 1.0% • Peptide Confidence Threshold > 99% • MS/MS ppm: 20.0 ppm • Score > 2 • 2/3 identification replication SWATH MS/MS Library IDA MS/MS XIC – SWATH MS/MS SWATH Data File Processing in PeakView® SWATH™ microapp Note: Protein selected is HCP ID 83 HCP Process Clearance Monitoring Data Processing and Library Searching – Acceptance Criteria 13
  16. 16. 83541324 TOF MS of sample S3 indicating the retention times of identified HCP ID 83, 324, and 541. S3 S4 S5 S6 HCP 83 HCP 324 HCP 541 XICs of identified HCPs Note: XICs are generated from the sum of the top four transitions per peptide. HCP Process Clearance Monitoring Sample Analysis 14
  17. 17. Library ID S3 S4 S5 S6 48 100.00 4.67 2.74 ND 58 100.00 37.61 4.98 ND 83 100.00 1.26 0.19 ND 301 100.00 3.77 6.03 ND 324 100.00 3.83 0.64 0.76 541 100.00 32.97 30.47 31.28 672 100.00 6.83 3.36 ND HCP Process Clearance Monitoring HCP Clearance in Percentage-Step 3 through Step 6 HCPs present in S5 shown 17 0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 100.00 S3 S4 S5 S6 % Timepoint HCP's Clearance in Percentage 48 58 83 301 324 541 672
  18. 18. Library ID S3 S4 S5 S6 48 5.74E+05 2.68E+04 1.58E+04 ND 58 6.25E+05 2.35E+05 3.11E+04 ND 83 1.27E+07 1.64E+06 2.38E+04 ND 301 3.81E+05 1.43E+04 2.30E+04 ND 324 2.17E+06 8.28E+04 1.38E+04 1.65E+04 541 1.87E+05 6.16E+04 5.70E+04 5.85E+04 672 3.18E+05 2.17E+04 1.07E+04 ND HCP Process Clearance Monitoring HCP Clearance in Area-Step 3 through Step 6 HCPs present in S5 shown 18 1.00E+04 1.00E+05 1.00E+06 1.00E+07 S3 S4 S5 S6 ProteinArea Timepoint Log Plot of HCP's Clearance in Area 48 58 83 301 324 541 672
  19. 19. HCP- Quantitation Proof of Concept – Determining Performance Expectation Six digested proteins were spiked into a mAb digest. Dilutions were carried out maintaining [mAb]. *MS Qual/Quant QC Mix from Sigma-Aldrich P/N MSQC1 20 Values are ppm, 30 µg of mAb was loaded on column
  20. 20. 11.6 ppm 2.32 ppm HCP- Quantitation Proof of Concept: Carbonic Anhydrase I, VLDALQAIK 0.464 ppm 0.0928 ppm 21
  21. 21. 62 ppm 12.4 ppm HCP- Quantitation Proof of Concept: NAD(P)H dehydrogenase, EGHLSPDIVAEQK 2.48 ppm 0.496 ppm 22
  22. 22. 46 ppm 9.2 ppm HCP- Quantitation Proof of Concept: C-reactive Protein, ESDTSYVSLK 1.84 ppm 0.368 ppm 23
  23. 23. 24 ppm 4.8 ppm HCP- Quantitation Proof of Concept: Catalase, NLSVEDAAR 0.96 ppm 0.192 ppm 25
  24. 24. HCP- Quantitation Proof of Concept - Determining Performance Expectation Range established to sub ppm levels Green = Confirmed; Red = Not Confirmed Values are ppm, 30 µg of mAb was loaded on column 26
  25. 25. • CHO Database in place containing 4 CHO cell lines • 3802 Proteins • Generation of new HCP databases within ~2-3 months • Identifications of HCPs for process monitoring can be made < 1 ppm, and in some cases <100 ppb • • Thank you SCIEX for your support! HCP– Analysis by Mass Spectrometry SUMMARY 27

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