Tools to Detect sub-1ppm Host Cell Proteins in Biological Products at Every Development Stage
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In a Single-One Hour Run, SCIEX can: PROFILE the HCP complement up to 1000s of proteins to sub-ppm level; IDENTIFY HCPs without bias [without inclusion/ exclusion lists]; Provide a CATALOG of HCPs for a process; Provide precursor and fragment information to allow easy MONITORING; Easy transfer to (QQQ or QTRAP®) ABSOLUTE QUANTITATION of HCPs
![2 © 2015 AB Sciex
SCIEX has a Strong Track Record with HCP Detection
In a Single-One Hour Run, SCIEX can:
PROFILE the HCP complement up to 1000s of proteins to sub-ppm level
IDENTIFY HCPs without bias [without inclusion/ exclusion lists]
Provide a CATALOG of HCPs for a process
Provide precursor and fragment information to allow easy MONITORING
Easy transfer to (QQQ or QTRAP®) ABSOLUTE QUANTITATION of HCPs](https://image.slidesharecdn.com/swathhcpslideshare-160401204119/85/Tools-to-Detect-sub-1ppm-Host-Cell-Proteins-in-Biological-Products-at-Every-Development-Stage-2-320.jpg)
![7 © 2015 AB Sciex
UniProt Protein Name [Synonym] MW (Da)
PPM At Lowest
Dilution UniProt Protein Name [Synonym] MW (Da)
PPM At
Lowest
Dilution
Gelsolin 82,954 7.56 Ubiquitin-conjugating enzyme E2 C [UbcH10] 20,473 1.87
Lactotransferrin 78,289 7.14 Peptidyl-prolyl cis-trans isomerase A [Cyclophilin A] 17,947 1.64
Serotransferrin [Apotransferrin] 75,143 6.85 Tumor necrosis factor [TNF-alpha] 17,350 1.58
Serum Albumin 66,393 6.05 Myoglobin C 17,051 1.55
Catalase 59,583 5.43 Interferon gamma (IFN-gamma) 16,879 1.54
Histidyl-tRNA synthetase [Jo-1] 58,223 5.31 Leptin 16,024 1.46
Antithrombin-III 49,033 4.47 Cytochrome b5 16,021 1.46
Microtubule-associated protein tau [Tau protein] 46,810 4.27 Hemoglobin beta chain 15,867 1.45
Creatine kinase M-type [CK-MM] 43,070 3.93 Superoxide dismutase [Cu-Zn] 15,800 1.44
Small ubiquitin-related modifier 1 [SUMO-1] 37,420 3.41 Gamma-Synuclein 15,363 1.40
Annexin A 5 35,782 3.26 Hemoglobin alpha chain 15,127 1.38
NAD(P)H dehydrogenase [quinone] 1 [DT Diaphorase] C 30,984 2.82 Fatty acid-binding protein 14,716 1.34
Carbonic anhydrase 2 29,095 2.65 Lysozyme C 14,692 1.34
Carbonic anhydrase 1 28,738 2.62 Alpha-lactalbumin 14,070 1.28
Ribosyldihydronicotinamide dehydrogenase [quinone]
[Quinone oxidoreductase 2] [NQO2] 25,817 2.35 Thioredoxin 12,424 1.13
Glutathione S-transferase A1 [GST A1-1] 25,482 2.32 Platelet-derived growth factor B chain 12,286 1.12
Glutathione S-transferase P [GST] 23,220 2.12 Beta-2-microglobulin 11,729 1.07
C-reactive protein 23,030 2.10 Cytochrome c[Apocytochrome c] 11,608 1.06
Ubiquitin-conjugating enzyme E2 I [UbcH9] 22,907 2.09 Ubiquitin 9,387 0.86
Ubiquitin-conjugating enzyme E2 E1 [UbcH6] 22,222 2.03 Neddylin [Nedd8] 9,071 0.83
Peroxiredoxin 1 22,106 2.01 Interleukin-8 8,381 0.76
BH3 Interacting domain death agonist [BID] 21,978 2.00 Complement C5 [Complement C5a] 8,266 0.75
GTPase HRas [Ras protein] 21,292 1.94 Insulin-like growth factor IA 7,643 0.70
Retinol-binding protein 21,065 1.92 Insulin-like growth factor II 7,464 0.68
Ubiquitin-conjugating enzyme E2 C [UbcH10] 20,473 1.87 Epidermal Growth Factor 6,211 0.57
48 Proteins Ranging From
7.56 ppm Down to 0.57
PPM at the Lowest
Dilution Level
The Number of Proteins Analyzed is Not Limited](https://image.slidesharecdn.com/swathhcpslideshare-160401204119/85/Tools-to-Detect-sub-1ppm-Host-Cell-Proteins-in-Biological-Products-at-Every-Development-Stage-7-320.jpg)
![12 © 2015 AB Sciex
Complement C5 [Complement C5a]
90 ppm45 ppm22.5 ppm11.25 ppm
5.63 ppm2.81 ppm1.40 ppm0.70 ppm
PEPTIDE: AFTEC[MSH]C[MSH]VVASQLR
Example Data: sub-1 ppm Detection](https://image.slidesharecdn.com/swathhcpslideshare-160401204119/85/Tools-to-Detect-sub-1ppm-Host-Cell-Proteins-in-Biological-Products-at-Every-Development-Stage-12-320.jpg)
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Tools to Detect sub-1ppm Host Cell Proteins in Biological Products at Every Development Stage
Editor's Notes
- #5: This infographic is all about showing the massive time savings of 19 hours and how that adds up.
- #7: Study design for the data I’m about to present, now we have this in place at a number of sites but they’re generally protective of host cell protein data, so we spiked the sigma UPS1 into a model IgG1 to determine the level at which we could detect our spike ins.
- #8: There were eight dilutions, but because the UPS1 has different sized proteins, even though they’re equimolar, we get a range of PPM values at each dilution level. This was the table of PPM levels from the lowest of eight dilutions.
- #9: This method is well worked out all the way down to the gradient, and type of peeksil we use. We used a variable windows swath method to achieve these results, that method is available to anyone who wants it.
- #10: Figure 5. SWATH™ Analysis Software. Top Left: List of proteins and peptides from an ion library (in this case a Protein Pilot™ .Group file). Top Right: TIC chromatograms of each SWATH™ data file. Bottom Left: XIC chromatograms of six fragment ions from the selected peptide. Bottom Right: Mirror plot showing the MSMS Spectrum collected at the top of the chromatogram in the bottom left pane (Blue) over the Spectrum from the ion library (Pink).
- #11: Instead of working our way through the data one transition at a time we can export ALL the peak areas and use Markerview to identify where the trends are coming from. The SWATH data includes 6 transitions per peptide, up to 100 peptides per protein, for each of the 48 proteins, so that’s 28, 800 transitions to monitor. Keep in mind that only ~half of the peptides from a given protein usually turn out to respond in a linear manner to a concentration curve. Add in the HUGE amount of interference from the mAb product that is present at up to a million times more abundance and you can see how finding diagnostic peptides For a trend could take you a very long time if you had to process all 28,880 transitions across eight samples manually, one at a time. Markerview gets you to this data very quickly. Now you can let the data dictate which Heavy IS peptides to order, not order them first and hope that they’re linear…
- #12: Example one that we found using markerview. We know this is real because you can see the counts decreasing at each concentration. Big deal that we can get down to 1 PPM without a second dimension of LC!!!!!!! Yay!!! Hooray!!!
- #13: Even more Yay and Hooray. !!!
- #14: Now the workflow I’ve been reporting on is the microflow application, but we’ve also developed this workflow into different flow rates that will be useful in a number of different stages of a biopharmaceutical’s development…
- #15: Microflow, we’ve already discussed.
- #16: Here’s a poster that was presented at CASSS Mass Spec last year in partnership with Biogen Idec using this exact approach.
- #17: Some with an abundance of material are choosing to use high flow, but we do generally need to load ~30 ug for this flow rate, as we’re looking for the low-level proteins, not the product itself…
- #18: Here’s an example of someone in industry putting this to use. Chris Yu and Don walker were able to use the High throughput of this test to screen 23 different products at genentech that were all grown in the same cell line, after they discovered a host cell protein that wasn’t detectable by Elisa.
- #19: Additionally, as researchers are starting to screen for issues with a developing biopharmaceutical earlier and earlier, we have developed a technique that can accomplish the same level of sensitivity at much lower product loads. This allows screening for purification issues at very small scales and saves more of the precious product for uses elsewhere.
- #21: High Quality Quantitation. Extracted Ion Chromatogram peak areas of five fragments per peptide were summed to produce the abobe bar graphs. Triplicate measurements of each peptide and or it’s modified forms were all below 10% C.V.
- #22: High Quality Quantitation. Extracted Ion Chromatogram peak areas of five fragments per peptide were summed to produce the abobe bar graphs. Triplicate measurements of each peptide and or it’s modified forms were all below 10% C.V.