Evaluation of peptide fractionation and native digestion as two novel

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Evaluation of peptide fractionation and native digestion as two novel sample preparation workflows to improve HCP characterization by LC-MS/MS Regina Kufer, Markus Haindl, Harald Wegele, and Stefanie Wohlrab Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.9b01259 • Publication Date (Web): 01 Jul 2019 Downloaded from pubs.acs.org on July 21, 2019

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Analytical Chemistry

Evaluation of peptide fractionation and native digestion as two novel sample preparation workflows to improve HCP characterization by LC-MS/MS Regina Kufer*1, Markus Haindl1, Harald Wegele1, Stefanie Wohlrab1 1

Pharma Technical Development Analytics, Roche Diagnostics GmbH, Nonnenwald 2, 82377 Penzberg, Germany

ABSTRACT: Host cell proteins (HCPs) are the predominant class of impurities during manufacturing of therapeutic proteins. Previous reports have successfully shown that HCP characterization by LC-MS/MS ultimately leads to drug products of superior safety and quality. Here, we present two sample preparation strategies to approach the wide dynamic range required and compared them systematically to a standard protocol. First, we describe PreOmics fractionation as an effective 2D offline strategy. Second, we evaluate an alternative digestion approach specifically designed for purified antibodies – native (non-denaturing) digestion. Both protocols increased detection sensitivity as shown by two low level HCP models. Out of a 5 ppm spike of eight common HCPs into antibody product, all spiked proteins were positively identified. Additionally, by Universal Proteomics Standard 1 (UPS-1) spiking we obtained a comprehensive coverage of 77 % below 10 ppm for the native digestion. Furthermore, we were able to detect 27 to 173 % more HCPs in protein A elution pools of five different antibodies and to reject new concerns of HCP co-precipitation by pellet digestion. Although it encounters new challenges, the native digestion is very attractive due its simplicity and comparability to 2D workflows. However, for complex samples such as mock transfected cell culture fermentation, best results were obtained with peptide fractionation. This study highlights the advantages of both methods and their value to facilitate LC-MS/MS approaches to become an even more powerful tool for HCP profiling.

Therapeutic proteins are mainly manufactured in an expression host system such as Chinese hamster ovary cells (CHO). Throughout a multi column process the desired drug substance is purified. However, the biologic may still contain trace level host cell proteins (HCPs) as predominant side product of bioprocessing. In rare cases it is possible that residual HCPs trigger adverse events such as immune reactions. Furthermore, on drug substance and drug product level, a direct or indirect influence on product stability caused by HCP enzymatic activity is possible. Cathepsin D, for example, has been shown to cause antibody fragmentation and particle formation by its proteolytic activity.1,2 Also, it has been reported that HCPs with inherent hydrolytic activity may negatively impact product quality by degradation of the surfactant polysorbate, leading to increased release of fatty acids, associated with the tendency to form particles composed of free fatty acids.3,4 HCP composition and abundance are impacted by basically all unit operations in biopharmaceutical processing. Upstream, the HCP impurity profile is influenced by many factors like specific cell line, cell age, viability and harvest conditions.5,6 Downstream purification is primarily designed to remove HCPs and thus includes many steps with major influence on the HCP impurity profile towards final drug level. A small subset of HCPs has been previously reported to have the propensity to associate with monoclonal antibodies (mAbs), and thus are potentially co-purified even by multicolumn processing, e.g. Clusterin, 78 kDa glucose-regulated protein, protein disulfide-isomerase, putative phospholipase B-like 2 (PLBL2) and Peroxiredoxin-1 (PRDX-1).7-10 Abovementioned reports underscore the criticality of monitoring HCP impurities to ensure product quality and safety. Recently a mass spectrometry (MS)-based platform was developed in-house for robust HCP characterization above 50 ppm level to complement immune-based assays and to support purification process development.11 In contrast to immunoassay detection, LCMS/MS analysis provides the identity of HCPs. Knowledge of HCP identities enables targeted support and actions in

bioprocess and formulation development facilitating the production of a stable, active and save drug product. However, MS-based methods pose their own challenges: due to high mAb excess a wide dynamic range is required to detect HCPs in desirable range of 1-10 ppm reflecting a concentration of 1-10 ng HCP per mg antibody. Targeted MS methods provide the most sensitive detection limits down to single-digit ppm11,12 but due to the requirement to detect unknown proteins in in-process samples, unbiased MS based discovery approaches are still the method of choice.7 Another challenge, which has not been explored to the same extent as the inherent dynamic range issues is the variability of complexity in HCP samples. To demonstrate the suitability of immune-based HCP assays critical reagents (e.g. HCP antigen) should be characterized by MS. Such samples and protein standards are a proteomic-like, heterologous and complex mixture of proteins.13 In contrast, inprocess samples contain mAb in excess even in the harvested cell culture fluid (HCCF), with the dynamic range increasing to 5-6 orders of magnitude in the final product. Due to similar characteristics between proteomic samples and HCP samples many proteomic strategies have been applied in the HCP field during the last years to advance the standard 1-dimensional LCMS/MS for HCP identification. One widely practiced approach is the introduction of multidimensional chromatography. Orthogonal separation of tryptic peptides increases the dynamic range and reduces sample complexity enabling more sensitive detection.14,15 Both offline and online strategies have been established as well as coupling different separation methods such as strong cation exchange combined with RP or preferably the combination of RP/RP at high/low pH.15-19 Even further enhancement in regard to number of peptides and proteins identified was obtained by implementing a concatenation pooling step between the first and second dimension.20,21 This concept has already been successfully applied to HCP analysis and provides a robust detection of residual HCPs down to a level of 10 ppm.22 Alternatively, dynamic range issues can be faced by depletion of the antibody itself and HCP enrichment

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traditionally achieved by affinity chromatography.23,24 With the same idea Huang et al recently published a novel procedure, the native digestion, enabling mAb removal upon heat treatment and precipitation.25 There is no doubt that all of these strategies have helped to evolve HCP characterization and revised the standard procedure of the 1D method. However, in analytical routine the practicability and time needed to perform an assay equally contributes to efficiency as a potent assay. Most of the above mentioned traditional 2D LC-MS/MS approaches require multistep sample preparation workflows which are very time consuming and are often constrained by low throughput, sample loss and contaminations. The aim of this study was to combine the described advantages of these complex methods - increased number of proteins identified and gains in sensitivity - with a fast, simple and practical workflow. Here, we describe a straightforward offline 2D approach with fractionation based on StageTips, the PreOmics fractionation, and compared it to the previously reported conventional approach11 and improvements of the native digestion (adapted from Huang et al)25. We discuss the reasonable application to HCP profiling of all three methods. As a result, both PreOmics fractionation and native digestion have considerable advantages over the traditional approach. However, both methods have their advantages and challenges, which have to be carefully evaluated according to the nature and complexity of the sample of interest.

EXPERIMENTAL SECTION Materials All monoclonal antibodies (mAb1 - mAb5) were produced at Roche Diagnostics GmbH. For the 8 protein standard two Eschericha coli (E. coli) recombinant proteins, transcriptional regulatory protein (phoP) (#CSB-MP326097ENV) and cytidylate kinase (cmk) (#CSB-EP363865ENV) and six CHO recombinant proteins, glyceraldehyde-3-phophat dehydrogenase (GAPDH) (#CSB-YP009232DXU), cathepsin D (#CSB-EP006187DXU), gluthamine synthetase (GLUL) (#CSB-YP009553DXU), actin cytoplasmic (ACTB) (#CSBYP344170DXU), elongation factor 1-alpha (EEF1A1) (#CSBYP007409DXU), protein disulfideisomerase (P4HB) (#CSBYP823188DXU) and peroxiredoxin-1 (PRDX1) (#CSBYP872876DXU) were purchased from Cusabio Technology LLC. The proteins were spiked at 5, 20 and 50 ppm level into mAb1. For a larger range of ppm levels and size range mAb1 was spiked with Universal Proteomic Standard (UPS-1) from Sigma- Aldrich containing 48 human proteins at equimolar concentration. Notably, the composition changed to the previously sold UPS-1, the two proteins cathepsin D (P07339) and cathepsin G (P08311) were permanently replaced by gamma-synuclein (O76070) and interferon gamma (IFNgamma) (P01579). The calculation for all ppm levels was based on the concentration relative to mAb (1 ppm corresponds to 1 ng protein/mg mAb) and on the respective molecular weight of each protein. The CHO standard solution was produced inhouse at Roche by protein precipitation with ammonium sulfate of a null strain HCCF. iST kits for proteomic sample preparation were obtained from PreOmics GmbH. Chemicals used and chromatographic solvents were LC-MS grade. Dithiothreitol (DTT) and iodoacetic acid were commercially purchased from Sigma-Aldrich. Endoproteinase trypsin

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proteomics grade (Roche, #03 708 985 001) was used for protein digestion.

Standard digestion The sample preparation referred to as standard digestion is a widely used standardized protocol for proteomic applications.26,27 D. Walker and F. Yang evaluated such a standard protocol as platform method for tracking host cell protein clearance.11 The method used for our studies is based on this platform method with following conditions: Aliquots containing 350 µg spiked mAbs or CHO standard were denatured with 8 M Guanidiniumchloride in 0.4 M Tris/HCl, pH 8.5, reduced with DTT for 60 min at 50 °C and carboxymethylated by iodoacetic acid for 30 min at room temperature. Next, samples were subjected to buffer exchange by NAP-5 columns into pH 7 digestion buffer (0.1 M Tris/HCl, pH 7.0) for desalting before 2.5 µg of trypsin was added and incubated at 37 °C overnight. The reaction was stopped with 50 µl 10 % trifluoroacetic acid and 65 µg were loaded onto LCMS/MS.

Native digestion The protocol was adapted from Huang et al.25 200 µg of protein sample was diluted with purified water to a total volume of 185 µl. Then, 5 µl of 1 M Tris/HCl buffer (pH 8.0) were added to adjust the sample pH. The lyophilized recombinant porcine trypsin was reconstituted in 10 mM HCl solution and 10 µl of a 0.25 mg/ml solution was mixed directly with the sample under non-denaturing conditions. The preparations were incubated at 37 °C for overnight or 2 h in the optimized protocol, respectively. Samples were reduced with 4 µl of a 100 mg/ml DTT solution and subsequently heated to 95 °C for 10 min. Undigested and denatured protein was precipitated by a 2 min centrifugation step at 13 000 g. Around 180 µl of the supernatant was transferred into a new tube and acidified with 5 µl of 10 % formic acid in water. 65 µg (based on starting concentration) of each processed sample were injected for LCMS/MS analysis.

PreOmics digestion PreOmics preparation was carried out according to the manufacturer’s protocol. Each sample (200 µg) was lysed with 50 µl of 1x or for low concentrated samples 2x lyse buffer and denatured at 95 °C at 1000 rpm for 10 min. The denatured sample was mixed with 50 µl trypsin solution and incubated for 2 h at 37 °C on the iST cartridge. The reaction was subsequently quenched with 100 µl stop solution and mixed thoroughly. Peptides were cleaned up by spinning the cartridge 2 min at 3800 g followed by two wash steps. Next, peptides were eluted. At this point fractionation can optionally be performed. In our studies, we used a six step salt gradient for SCX material ranging from SCX1 (75 mM Ammonium acetate, 20 % ACN, 0.5 % Formic acid) to SCX5 (500 mM Ammonium acetate, 20 % ACN, 0.5 % Formic acid). For SDB-RPS material, we used a six step salt and organic gradient ranging from SDB1 (75 mM Ammonium formate, 30 % ACN, 0.5 % Formic acid) to SDB5 (175 mM Ammonium formate, 70 % ACN, 0.5 % Formic acid). The last fractionation step was performed with the elution buffer provided by the PreOmics kit. Every elution pool was dried using a speed-vacuum at 45 °C. Then, the peptides were dissolved in LC-load solution and sonicated for 5 min. To test


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co-precipitation of HCPs with the mAb in the native digestion, lyse buffer was directly added to the pellet and the protocol was performed as described.

UHPLC-MS/MS Peptides were separated at 60 °C on a CSH130 C18 (1.7 µm, 2.1 mm x 150 mm) column (Waters) using a Thermo Fisher Scientific Vanquish-H UHPLC System. Sample loads of 65 µg (calculated based on input concentration) were injected at 300 µl/min flow rate. Mobile phase A consisted of 0.1 % formic acid in water and mobile phase B consisted of 0.1 % formic acid in acetonitrile. The 65-min gradient started with a linear increase of 0 % to 40 % B in 45 min, followed by a 5-min column wash at 95 % B and column re-equilibration for 10 min at 1 % B. Additionally, an eluent A run (65-min gradient) before and a 30-min wash gradient with 10 % methanol after each sample was implemented to prevent carry over and distortion of results. The UHPLC system was coupled with a TripleTOF 6600 mass spectrometer (Sciex) with DuoSpray Ion Source. Tandem mass spectrometric analysis was performed using data dependent acquisition (DDA) with following settings: the top 20 most abundant ions were selected from every MS survey scan (250 ms) over a mass range of 200 – 2000 m/z. The MS/MS scans (69 ms) were acquired within a mass range of 100 – 1600 m/z (high sensitivity mode) including charge states of +2 to +5. For MS/MS selection the dynamic exclusion was set for a period of 6 s and the precursor ion threshold to 150 counts per second.

fast sample preparation by using only one enclosed reaction chamber. Many steps of a previously used standard protocol were eliminated or combined resulting in a very fast procedure which can be performed (excluding the digestion time) in less than 30 min.28 In detail, the kit couples denaturation, alkylation and reduction to only one step prior to digestion. The digestion is then carried out in the iST cartridge with the column material serving as a barrier. Peptides are subsequently cleaned up and eluted by means of the cartridge. In addition, we used the column material optionally as separation medium during elution. For fractionation a six step salt and organic gradient was used. Hence, PreOmics fractionation constitutes a novel offline 2D method to approach dynamic range issues while gaining higher throughput at the same time. In contrast, the alternative sample preparation procedure for antibody removal published by Huang et al in 2017, native digestion, typically achieves 1 or 2 orders of magnitude less dynamic range in the prepared samples.25 In the latter procedure trypsin is directly added to the pH adjusted sample of interest under nondenaturing conditions. Native antibodies have been shown to be resistant to the enzymatic activity of trypsin and thus primarily HCPs are digested.25 Subsequently, undigested antibody is denatured by a heating step followed by precipitation. The HCP peptides remained in solution can now be analyzed by LCMS/MS with less matrix effects caused by antibody. Both methods provide very little hands-on time and just a few manual steps and thus minimize contamination and sample loss.

Increased sensitivity in purified samples with low level HCP by PreOmics fractionation and native digestion

Protein identification and data analysis The MS/MS data was searched against a customized CHO database with 35,862 protein sequences containing all CHO proteins from Uniprot.org (Swiss-Prot and TrEMBL annotations included), drug product sequences and human keratin impurities using the ProteinPilot software (Sciex, Version 5.0). For the experiment with the 8 protein standard the two E. coli sequences of P0A6I0 and P23836 were added to the CHO database (35,864 protein sequences). For UPS-1 spiked samples the CHO database was merged with the UPS-1 FASTA file, downloaded from the homepage of Sigma-Aldrich (July 2018). Our set acceptance criteria for positive protein identification was a false discovery rate of < 1 % with at least two unique peptides at a confidence of 95 %. For filtering and comparison of database results we used an internally developed software package. Using this automated data analysis immunoglobulin related, reversed, putative uncharacterized proteins and proteins with an unused score of 0 have been removed from database hits. Furthermore, protein duplicates in accession or protein name were excluded.

RESULTS AND DISCUSSION Overview of the PreOmics fractionation and native digestion Not only a high performing instrument but also a smart sample processing is crucial for obtaining best possible sensitivity and robustness of any mass spectrometry based analysis.11 Thus, we focused in our studies on sample preparation strategies for HCP identification by LC-MS/MS (DDA only). For the PreOmics fractionation we employed an in-StageTip (iST) kit for proteomic sample preparation developed by Nils Kulak and Garwin Pichler (PreOmics GmbH). The kit is commercially available and was designed to ensure robust, reproducible and

Antibody biologics expressed by CHO cells are typically purified from the cell culture supernatant by a multi-column process. The cell culture supernatant contains potentially thousands of CHO proteins which have been identified as supernatant-ome.29 Before purification protein impurities are present in the HCCF at a mass ratio of around 1:1 compared to mAb.11 Throughout the purification process HCPs are removed down to low levels (less than 10 ng/mg mAb, ppm) of residual HCPs in final drug substance.30 Thus, the ratio of HCP to mAb reflects the wide dynamic range of 5-6 orders of magnitude. As rule of thumb, most biotherapeutics approved by health authorities contain less than 100 ppm measured as aggregate sum in immune-based assays.31 However, characterization of low level HCPs is highly desirable for process development since even residual amounts of enzymatic activity can potentially compromise product quality dependent on storage time.32 The presence of trace level HCPs in antibody product was simulated by mAb1 spiked with recombinant proteins at 5, 20 and 50 ppm level. To compile a protein standard for spiking experiments we selected eight HCPs which have been previously reported as difficult-to-remove, mAb associating or have at least been detected repeatedly in final drug substance.7,9,33-35 Protein size and isoelectric point varies between 22.3 and 57.0 kDa, and 4.78 and 9.10 pI, respectively. The 8 protein mixture comprised six Cricetulus griseus (CRIGR) and two E. coli proteins presented in Table 1.



Table 1: Internal 8 protein standard spiked into mAb1 #

Name

1 2 3 4

Actin, cytoplasmic 1 Cathepsin D Cytidylate kinase Elongation factor 1-alpha 1 Glyceraldehyde-3phosphate dehydrogenase Peroxiredoxin-1 Protein disulfide-isomerase Transcriptional regulatory protein PhoP

5 6 7 8

P48975 G3I4W7 P0A6I0 P62629

CRIGR CRIGR ECOLI CRIGR

MW [kDa] 44.7 44.1 24.7 50.1

P17244

CRIGR

35.7

8.49

Q9JKY1 Q8R4U2

CRIGR CRIGR

22.3 57.0

8.22 4.78

P23836

ECOLI

25.5

5.10

Accession Species

pI 5.22 6.54 5.56 9.10

All spiked samples either prepared with PreOmics kit, fractionation workflow or native digestion were analyzed by LC-MS/MS using a charge-surface hybrid (CSH) C18 column and a TripleTOF 6600 mass spectrometer with a 65-min gradient. The proficient reproducibility of the LC separation in this setup has been shown previously.11 The prior report of the 1D UHPLC-MS/MS method demonstrated a robust detection of unknown proteins at ≥ 50 ppm level.11 Therefore, we compared the different sample preparation protocols on 50 ppm level and to reveal higher sensitivity as a result of sample preparation strategy we included 20 and 5 ppm spike samples. The PreOmics digestion (unfractionated) performed in regard to number of identified proteins and sensitivity comparable to the standard protocol (data not shown). Thus, we used PreOmics (unfractionated) as control to evaluate the benefit of the fractionated 2D version and the native digestion. The detected number of unique peptides is exemplarily shown for the 5 ppm spike in Figure 1A. In samples prepared with the PreOmics workflow without subsequent fractionation five of the eight spiked proteins were identified with our acceptance criteria of ≥ 2 unique peptides at 95 % confidence. Whereas, both PreOmics fractionation and native digestion resulted in positive IDs of all eight spiked proteins due to higher sensitivity. We verified higher sensitivity for the 5 ppm spike with seven replicates (SI Figure 1-S) and measurement of three process replicates on a Thermo Fisher Orbitrap Fusion ETD (SI Figure 2-S). All three methods were able to reliably detect all eight proteins at 20 and 50 ppm level. However, the number of unique peptides per protein was increased for fractionation and native digestion. These results suggest – in agreement with the 5 ppm experiment – a higher sensitivity achieved by the two newly described procedures. To further illustrate these results we plotted the percentage increase of peptides found per protein related to the non-fractionated procedure and averaged them for all eight proteins (Figure 1B). For clarification, each plot per protein which has been used to average is separately presented in SI Figure 3-S. The strongest effect was observed for the 5 ppm sample, since this spike level is closest to the detection limit. In the 5 ppm spiked samples over 450 % more peptides have been detected in fractionated and native (2 h) digested samples compared to standard protocol. “Native overnight (oN)” describes the originally published method25 and also resulted in more detected peptides on average than with nonfractionated sample procedure. However, we found that a shorter digestion time of 2h was beneficial, resulting in an even higher number of peptides per protein detected compared to overnight digestion (Figure 1B). We suppose that this improvement can be explained by non-denaturing sample conditions and absence of quenchers resulting in shorter time

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for sufficient digestion. Moreover, shorter incubation time prevents digestion of the mAb itself which we observed by less high intense peaks caused by the antibody in total ion chromatograms (TICs) (SI Figure 4-S) which further facilitates identification of HCPs. We therefore adopted the protocol with 2 h digestion time for all further experiments performed in this study. For protein identification by LC-MS/MS a repeatability and reproducibility of 70 – 80% has previously been reported.36 To assess variability in low level HCP samples we ran 50 ppm recombinant PLBL2 spiked into antibody product as method control sample. Control samples were prepared according to the standard protocol and measured in 104 test sessions over 29 months. The number of identified peptides ranged from 2 to 9 peptides resulting in a standard deviation of 1.6 (SI Figure 5-S). Even when a certain technical variance is taken into account this spiking experiment revealed superior sensitivity obtained by fractionation and native digestion (2h). To further confirm that the observed increased sensitivity is related to the applied sample processing method, and to enable comparison to recent literature11,22,36,37, Universal Proteomic Standard-1 (UPS-1) was spiked into mAb1. UPS-1 is a commercially available protein standard containing 48 recombinant human proteins at equimolar level. At different molecular weights ranging from 6.3 to 8.9 kDa, the spike level was determined ranging from 3 to 44 ppm. The results displayed in Figure 2 demonstrate a 60 % comprehensive coverage of positive IDs for the standard digestion. Whereas, the success rate for identification increased to 83 % when native digestion was employed. By comparison, with concatenation fractionation – a previously reported 2D method – a comprehensive coverage of 85 % was achieved in the same experimental setup.22 Higher sensitivity obtained by native digestion becomes particularly obvious in the coverage of protein ID below 10 ppm: 77 % of all spiked proteins were identified in native digested samples compared to 41 % for the standard digestion. Moreover, native digestion led to detection of 8 unique peptides of the hitchhiker PRDX-1 (Q06830) at 12 ppm spike level compared to 4 peptides with standard digestion. PRDX-1 was consistently identified at even 5 ppm level with all sample preparation methods achieved in the same experimental setup.22

Increased sensitivity and number of identified proteins in high level HCP in-process pools The ease of use combined with fast sample preparation as well as comparable sensitivity of the native digestion to the wellaccepted 2D approach encouraged us to perform further investigations. So far, we tested artificial samples with low level HCP spikes, but technical details of the native digestion rose new questions, such as possibility of hitchhiker proteins interacting with antibody which are potentially not detected by the method. Thus, we tested real life in-process pools. We compared the total number of identified HCPs in 5 different mAb Protein A eluate pools which represent pools with considerable high HCP levels. In native digested samples we identified 27 to 173 % more HCPs compared to our standard procedure (SI Figure 6-S). Figure 3A depicts a comparison between the proportions of proteins found with native and with standard digestion measured in three replicates. A Venn diagram was calculated for each HCP proportion per mAb and replicate. In particular, 25 to 64 % of all identified HCPs were only found in native digested samples, whereas merely 0.7 to


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4.9 % were unique to the platform method. These the few proteins uniquely detected by the standard method were primary low abundant HCPs, identified by a low number of peptides close to the acceptance criteria of ≥ 2 unique peptides at 95 % confidence. Considering technical variability of LCMS-based protein identification36,38,39, we are very confident that no relevant HCPs are missed by the native digestion. One Venn diagram is exemplarily shown for mAb3 in Figure 3B. Despite of these very promising results the robustness of every manual step performed in native digestion has to be considered to guarantee a precise analysis of biopharmaceuticals and thus ensure patients’ safety. One major critical manual step is the precipitation. Although this step enables the reduction of the dynamic range and helps to detect more HCPs, there is the risk of unintentionally removing certain HCPs by co-precipitation with the native antibody. To test whether any HCPs were coprecipitated, we subjected the pellet to PreOmics digestion and PreOmics fractionation. For both sample preparation methods all HCPs found in the pellet digestion could be aligned with the ones in the supernatant demonstrating that no HCPs are lost during this crucial step of sample preparation (SI Figure 7-S). The Venn diagram of protein A eluate of mAb3 is exemplarily shown in Figure 3C. Furthermore, during preparation we observed a correlation between the amount of starting material and pellet size suggesting precipitation of mainly the antibody product (SI Figure 8-S).

Increased number of identified proteins in proteomic samples by PreOmics fractionation Most studies7,9,33-35 on HCP tracking focus on in-process pools and drug substance samples since these are undoubtedly most relevant. However, LC-MS/MS is also an important orthogonal tool to evaluate ELISA suitability40 and therefore robust HCP analysis of highly complex, proteomic-like samples such as ELISA reference material (CHO standard) is required. CHO standard material contains ideally all proteins of a mock fermentation and thus contains thousands of CHO proteins. Proteomic studies on the CHO proteome have identified over 3000 proteins with 1015 of them in the supernatant-ome.29 Despite many strategies previously reported to improve the 1D LC-MS/MS, a faster and simpler workflow with higher throughput is still desirable for this application. Therefore, we explored the performance of the two methods described in this study on the CHO standard as a representative complex sample. We tested two column materials in the iST cartridge: a strong cation exchange (SCX) and a mixed-mode (SDB-RPS) material. Then, tandem mass spectrometry was performed of multiple fractions obtained from SCX and SDB-RPS fractionation compared to 6-fold measurements of platform protocol11, PreOmics w/o fractionation and native digested CHO standard (combined database search). We compared all methods based on the number of identified proteins and confidence in detection (Figure 4). Considering technical and instrumental variance a comparable number of HCPs were identified for standard sample processing and PreOmics prepared samples. In fractionated samples, a total number of 2855 proteins (SDB-RPS) and 2582 (SCX) were identified, representing a 54 % and 39 % increase compared to measurements without fractionation (Figure 4). Subgroups, representing the fractions of proteins detected with one, two, three or more than three peptides in the stacked bar graph, elucidate the real increase of HCPs identified: The most notable

increase occurred in the group of HCPs identified by more than three identified peptides. On the contrary, for this proteomic type of sample the native digestion was not beneficial. The total number of identified HCPs was even 28 % lower compared to the platform digestion and no pellet was observed during sample preparation. We suggest that the reason for this observation is sample loss through the precipitation step while no antibody excess is present.

Benefits and limitations of PreOmics with and w/o fractionation and native digestion Both the proteomics field as well as in the HCP field made a lot of effort to evolve mass spectrometry methodologies to gain more information about the sample of interest.22,25,28 Targeted MS provides a highly sensitive strategy to accomplish the extremely wide dynamic range and track proteins at a very low level. However, this technique requires prior knowledge of the sample content and for HCP analytics a broadly applicable approach to detect unknown proteins such as DDA/DIA is in most cases preferred.7,11 Higher sensitivity for DDA has been achieved by offline and online multidimensional chromatography, concatenation pooling and HCP enrichment by affinity chromatography.14-24 Despite of the uncontested success of these strategies, we provide two very powerful tools to facilitate a simpler and more efficient sample preparation for HCP identification with the same advantages. The PreOmics approach itself has a fast, reproducible, robust and well established protocol for proteomic applications.28,41,42 In our studies we showed the great value of iST based methods for HCP profiling by increased sensitivity and number of proteins identified. The PreOmics preparation is suitable for every type of sample for in-process pools with both high and low level HCP but also for proteomic samples such as CHO standard material. The required time periods needed for each step of each sample processing method for a full HCP analysis is summarized in Figure 5. Compared to the previous platform method, PreOmics digestion is substantially shorter but has no remarkable advantages on the results, whereas the option of fractionation is highly beneficial. However, fractionation generates longer acquisition time which adds on to the total analysis time while the hands on time remains fairly similar to the workflow without fractionation. The native digestion constitutes the fastest sample preparation in total but in contrast to PreOmics, reproducibility is not yet verified to the same extend and, moreover, the technical details arose further challenges. One major concern was the potential removal of critical HCPs due to interaction with the drug product as it has been reported for several HCPs such as Cathepsin D or PRDX1.33 Persistent HCPs are the most relevant ones to detect due to possible presence in purified pools. An accompanying factor of difficult-to-remove proteins is a higher chance for coprecipitation in native digestion. In our low level HCP model mAb1 spiked with known ppm levels of eight HCPs including hitchhiker such as Cathepsin D and PRDX-1, all proteins were consistently identified at 5 ppm, suggesting that the native digestion cover persistent HCPs despite a high likelihood of mAb association. Furthermore, HCPs detected in the pellets of five different mAbs were subsets of all identified, soluble HCPs of the particular process sample. Another challenge relates to LC load and how this parameter affects comparability and reproducibility of the results. For standard LC-MS/MS methods the LC load is calculated based on the starting material but for



native digestion a certain sample proportion is removed by precipitation containing mainly the antibody. This issue appeared to be even more complex since the ratio of mAb to HCP changes throughout the purification process. We observed a correlation between pellet size and mAb concentration but for qualification as a platform method, precipitation efficiency and all aspects influencing it, e.g. digestion time, have to be investigated comprehensively to ensure reproducibility and robustness. Furthermore, no peptide clean-up is included in the protocol so far but was useful for better peptide recovery and to prevent interference of column binding, elution and ionization by any component.43 On the one hand, our findings demonstrated the great potential of the native digestion to obtain comparable results to a well-established 2D approach with a drastically higher throughput. On the other hand, this procedure was specifically designed for low level HCP samples and indeed appeared to be limited in regard to complex proteomic samples such as CHO standard material. Thus, the question to which extend of complexity the native digestion is suitable has to be addressed adequately in method validation. Based on our results we advise the use of this method for biopharmaceutical samples from HCCF to purified drug product excluding proteomic samples.

CONCLUSIONS In this study, we presented two powerful tools combining increased sensitivity and number of identified proteins with a fast, simple and robust workflow for LC-MS/MS HCP sample processing. Both methods showed clear advantages compared to the conventional approach. The native digestion provides a highly efficient means for bioprocess samples, but has its limitations when proteomic samples are assessed. In contrast, the PreOmics fractionation approach requires longer acquisition - dependent on the number of fractions - but is a very effective method suitable for all types of sample in the HCP field. Their ease of use and fast workflow also facilitate a complete automation of sample preparation. Not least, if quantitation is desired, both methods can equally be applied to DIA samples and samples dedicated for targeted MS.

ASSOCIATED CONTENT AUTHOR INFORMATION Corresponding Author * E.mail: [email protected]. Phone : +49 8856 60-13294

Author Contributions All authors have given approval to the final version of the manuscript.

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT The authors thank Kieu Trinh Do for her help with automated data analysis; Garwin Pichler and Nils Kulak for providing PreOmics test material; Don Walker for valuable discussion about spiking techniques and protein ID by LC-MS/MS; and Michael Leiss for proofreading the manuscript.

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Figure 1. HCP detection of 8 protein standard. A) 5 ppm of protein standard spiked into mAb1, dashed red line depicts the threshold for positive identification (≥ 2 unique peptides at 95 % confidence). B) Comparison of averaged increase [%] of detected unique peptides relative to non-fractionated digestion at 5, 20 and 50 ppm level. Within each spike level performance of the tested methods were compared. Avg, average.

Figure 2. UPS-1 spike for determination of the comprehensive coverage sorted from low to high ppm. A) standard digestion with a protein ID coverage of 41 % and B) native (2h) digestion with 77 % coverage below a 10 ppm threshold. Light grey: negative IDs, dark grey: positive IDs (≥ 2 unique peptides at 95 % confidence).


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Figure 3. A) Comparison of number of identified HCPs in Protein A eluate pools of five different mAbs prepared by native and standard digestion. Bar graph shows the proportion of proteins which were unique to the respective sample preparation. Error bars show the standard deviation of three replicates. B) Example Venn diagram of mAb3 with total number of proteins identified in one replicate comparing native digestion (light blue) and standard digestion (dark blue). C) Example Venn diagram of mAb3 with total number of proteins identified in one replicate comparing supernatant of native digestion (light blue) and pellet digestion (orange).

Figure 4. Number of identified HCPs in CHO standard for each sample processing method; platform procedure (6-fold measurement), PreOmics, fractionation over two different column materials and native digestion. For every sample preparation groups of HCPs, identified by one, two, three or more unique peptides, are stacked per column.



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Figure 5. Overview of time required for sample preparation strategies comparing previous platform method to PreOmics, PreOmics fractionation and native digestion. PreOmics and native digestion are the quickest procedures. However, PreOmics fractionation and native digestions show the best sensitivity, whereby the native digestion appeared to be limited to in-process samples.

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Evaluation of peptide fractionation and native digestion as two novel

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