A comprehensive LC–MS based study of factors influencing biotinylation of critical reagents

Abstract

Aim: Critical reagents (CR) are applied in ligand binding assays (LBA) and biotinylation is a widely conjugation method used for critical reagents. However, insufficient characterization and inconsistent biotinylation can lead to LBA failures and necessitate extensive troubleshooting. This publication developed the detection of biotinylated CR and evaluates efficiency of biotinylation conditions to ensure the reliability of reagents and accuracy when implemented in LBA.

Materials & methods: Intact mass analysis was applied to characterize a CR with complex glycosylation and biotinylation patterns. Peptide mapping was developed to identify the biotinylation sites.

Results: Biotinylation degrees and sites were clearly illustrated.

Conclusion: A CR and its biotinylation were successfully characterized. The relationship between biotinylation efficiency and labeling conditions was clearly illustrated.

Plain language summary

Article highlights.

• A critical reagent (NVS-protein) and the corresponding biotinylated products were characterized by intact mass spectrometry (MS) analysis with the use of an optimized deglycosylation and desialidation process.

• Biotin degrees of labeling on the critical reagent were successfully estimated by intact MS.

• The specific biotinylation sites were accurately identified by peptide mapping analysis.

• The factors that influence biotinylation of critical reagents were successfully evaluated with the combination of intact MS and peptide mapping analysis, such as challenge ratio, incubation time and light conditions.

1. Introduction

Critical reagents are predominantly large molecules, such as monoclonal antibodies, polyclonal antibodies, other protein or peptide and their conjugates and oligonucleotides, which are typically used to support ligand binding assays [1–7]. Characterization of critical reagents is an essential step to support the Lot-to-Lot comparison of critical reagents, evaluate their stability, select the optimal protein candidates and furthermore, better understand the roles of critical reagents in ligand binding assays [6,8–17]. Biotinylation is one of the most common conjugation processes for critical reagents, which allows the tight binding between the biotinylated critical reagents and streptavidin-coated plates for further product detection and quantification in ligand binding assays [18–23]. The efficiency and reproducibility of biotinylation can be influenced by various factors, such as challenge ratios (ratio of biotin labeling reagents to critical reagents), biotinylation time and light conditions [24,25]. Failure to optimize these factors may result in inconsistent biotinylation and consequently lead to the failure of reproducible and accurate ligand binding results [14–17]. In addition, incomplete characterization of prepared reagents could lead to poor assay performance or an increased frequency of failed runs over the long duration of pivotal clinical trials [3,4,14–17]. Therefore, it is essential to understand and optimize biotinylation conditions for critical reagents to ensure the consistent biotinylated product and reliable and accurate results in ligand binding assays.

The most common targets for biotinylation are proteins or peptides that contain primary amines, such as N-termini and lysine residues, which could form amide bonds with the carboxyl group of biotins [24–27]. Leveraging the sensitivity and accuracy of liquid chromatography–mass spectrometry (LC–MS) for the detection and quantitation of proteins and peptides, characterization of biotinylated critical reagents could be proposed by advanced LC–MS at both intact level and peptide level [28–32]. However, it is challenging to characterize critical reagents or their biotinylated patterns at intact level or peptide levels, due to their complicated structure and unknown post-translational modifications [24,25,27,33–37]. The lack of proper characterization and accurate quantification of biotin degrees of labeling (DOL) impedes an in depth understanding of biotinylation efficiency for critical reagents, which could lead to unreliable data interpretation and erroneous conclusions of the related ligand binding assays [3,4,14–17].

To address these issues and enhance the understanding of biotinylation efficiency of critical reagents, a targeted critical reagent in clinical studies (an 80 kDa protein, noted as NVS-protein) was selected as an example in our study. Comprehensive characterization of NVS-protein was prioritized in this study utilizing combined intact MS and peptide mapping workflows. The biotinylation efficiency of NVS-protein under different biotinylation conditions was further evaluated by the quantification of biotin DOL analyzed by the developed intact MS and peptide mapping analysis. As illustrated in Figure 1, using intact MS analysis, the biotinylated NVS-protein could be characterized as a whole target and the relative biotin DOL could be estimated accordingly. At the same time, the specific biotinylated sites of NVS-protein could be identified and quantified by the peptide mapping analysis, considering biotinylation similarly as other protein post-translational modifications [38–41]. We further examined various factors that may affect the protein biotinylation efficiency, such as the challenge ratios, biotinylation time and light conditions. The findings evaluated the labeling conditions and further highlighted how the efficiency of biotinylation could be improved by optimizing biotinylation conditions. This knowledge can be applied to enhance protein biotinylation and guide the labeling of other critical reagents.

Figure 1.

Mechanism and detection of protein biotinylation by Intact MS and peptide mapping analysis.

2. Materials & methods

2.1. Reagents

Biotin (EZ-Link NHS-PEG4-Biotin, A39259), 8 M Guanidine-HCl Solution (GnHCl, 24115), Pierce Dithiothreitol (DTT, No-Weight Format, A39255)and Zeba spin desalting columns (7 k MWCO, 89882) were purchased from Thermo Scientific. Phosphate-buffered saline (1 × PBS, D8537), Iodoacetamide (IAM, I6125-10G) and PNGaseF (PNGF, Elizabethkingia, P7367-50UN) were purchased from Sigma. 1 M Tris Buffer, pH 8.0 (351-007-101) was purchased from Quality Biological. Lysyl Endopeptidase (LysC, 125-05061) was purchased from FUJIFILM Wako Pure Chemical Corporation. Sequencing Grade Modified Trypsin (V5111) was purchased from Promega. AdvanceBio Sialidase A (GK80040) was purchased from Agilent. O-Glycosidase (PI85178) was purchased from BioLabs.

2.2. Protein biotinylation

The 80 kDa glycosylated NVS-protein intended for use in a ligand binding assay was reconstituted to be 1 mg/ml with Milli Q water. The protein solution was buffer exchanged in 1 × PBS buffer using Zeba columns. Biotin (NHS-PEG4-Biotin) was reconstituted to be 20 mM with cold Milli Q water and prepared right before biotinylation process. The free biotin after biotinylation procedure was further removed by Zeba columns. The challenge ratio (molar ratio of biotin to protein) was set as 6:1, 12:1 and 20:1, respectively, according to the experiment requirements. The biotinylation was conducted for 1, 2 and 4 h, respectively. Natural light and darkness conditions were selected for comparison.

2.3. Intact MS analysis

Fifteen microliter of 1 mg/ml protein and biotinylated protein was denatured at 95°C for 10 min. Two microliter of 0.5 U/μl PNGF was added to each protein solution and incubated at 37°C for 16–18 h by shaking at 350 rpm. Four microliter of 5 mU/μl Sialidase A was then added to each protein solution and incubated at 37°C for 2 h by shaking at 350 rpm.

Thermo QEHF-X mass spectrometer coupled with Thermo Scientific Vanquish Ultra-high-performance liquid chromatography (UHPLC) was used for the intact MS analysis. Waters 300SB-C3 Narrow-Bore HPLC Column (5 μm, 300 Å, 2.1 × 150 mm, Part #: 883750-909) was used for the intact MS analysis. 0.1% FA in LC–MS grade water and 0.1% FA in LC–MS grade acetonitrile were used as mobile Phase A and B, respectively. The LC gradient started with 10% B for 3 min at flow rate of 0.4 ml/min, and was then linearly increased to be 90% B in 9 min at flow rate of 0.2 ml/min. The column was washed at 90% B for 2 min and then equilibrated back to 10% B for 6.5 min at flow rate of 0.4 ml/min. MS range was 600–3600 m/z with positive mode. Biopharma Finder 3.0 (Thermo) was used for intact MS deconvolution.

2.4. Peptide mapping analysis

Thirty microliter of 1 mg/ml protein and biotinylated protein was dissolved in 100 mM Tris buffer, pH 8.0 and then denatured with 75 μl of 8 M GnHCl. 1 M DTT was added to each protein solution with final concentration of 50 mM, and then incubated at 56°C for 30 min by shaking at 350 rpm, and cooled down for 5 min. 1 M iodoacetamide (IAM) was added (final concentration as 100 mM) and incubated at room temperature for 45 min in the dark. Zeba columns were then used to remove the access DTT and IAM. Trypsin and LysC were added to the desalted protein solution with enzyme to protein ratio of 1:20 w/w, and incubated at 37°C for 3 h by shaking at 350 rpm.

Thermo QEHF-X Mass Spectrometer coupled with Thermo Scientific Vanquish UHPLC was used for the peptide mapping analysis. Waters ZORBAX RRHD 300 SB-C18 Column (5 μm, 300 Å, 2.1 × 150 mm, Part #: 883750-902) was used for the peptide mapping analysis. 0.1% FA in LC–MS grade water and 0.1% FA in LC–MS grade acetonitrile were used as mobile phase A and B, respectively. The LC gradient started with 2% B for 4 min at flow rate of 0.3 ml/min, and then was linearly increased to be 33% B in 45 min, to be 50% B in 7 min and then to be 95% B in 3 min at flow rate of 0.2 ml/min. The column was washed at 95% B for 5 min at flow rate of 0.2 ml/min, and then equilibrated back to 2% B in 9 min at flow rate of 0.3 ml/min. MS range was 300–2000 m/z with positive mode. Biopharma Finder 3.0 (Thermo) was used for peptide mapping database search.

3. Results

3.1. Biotinylation identification & quantification by intact MS

Intact MS analysis was initially developed to detect the targeted critical reagent (NVS-protein), intended to be used in a ligand binding assay, with and without biotinylation. However, the complex glycosylation prohibited the protein MS deconvolution due to poor intact MS signal. Removal of N-glycans by PNGF did not improve the signal to noise level (Figure 2A), until Sialidase A was used to remove sialic acid residuals of the potential O-glycosylation (Figure 2B). By applying PNGF and Sialidase A, the intact MS of NVS-protein could be deconvoluted with higher MS signal, which was 83815 Da as the major form (Figure 2B). Therefore, sample pretreatment was further optimized with PNGF and Sialidase A to minimize both N- and O-glycosylation interference on intact MS analysis.

Figure 2.

Intact mass spectrometry analysis was successfully developed and optimized to detect intact mass spectrometry of NVS-protein. (A) Intact MS of NVS-protein with or without treatment of PNGF; (B) Intact MS and deconvoluted MS of NVS-protein with treatment of PNGF and Sialidase A; (C) Intact MS and deconvoluted MS of biotinylated NVS-protein with optimized treatment of PNGF and Sialidase A.

MS: Mass spectrometry; PNGF: PNGaseF.

Using the optimized sample pretreatment, the biotinylated NVS-protein could be identified with deconvoluted MS at different biotin DOL at the intact level (Figure 2C). Not unexpectedly, the biotinylated NVS-protein was observed with lower MS signal to noise level, since biotinylation added more modifications to NVS-protein, interfering with the intact MS signal. The relative abundance of biotin DOL could be quantified by assuming the intensities of all of the NVS-protein species with or without biotinylation as 1 (Table 1). Using protein species labeled with one biotin (1Biotin-Protein) as the example, the equation can be applied to quantify 1Biotin-Protein as:

$$\begin{array}{c}\mathrm{Relative abundance of }1\mathrm{Biotin}-\mathrm{Protein}=\\ \frac{\mathrm{intensities of} 1 \mathrm{Biotin}-\mathrm{Protein}}{\mathrm{sum of intensities of all protein species}(0,1,2...x\mathrm{Biotin}-\mathrm{Protein})}\end{array}$$

Table 1.

The Biotin degrees of labeling was estimated by intact mass spectrometry with challenge ratio of 6:1, 2 h in the dark.

Biotin DOL	MW	Relative intensity	relative abundance
0Biotin-Protein (Not Labeled)	83814	5.9E + 06	0.13
1Biotin-Protein	84289	9.8E + 06	0.21
2Biotin-Protein	84762	1.3E + 07	0.28
3Biotin-Protein	85235	1.1E + 07	0.23
4Biotin-Protein	85711	4.5E + 06	0.10
5Biotin-Protein	86186	2.7E + 06	0.06
Averaged Biotin DOL		2.1

DOL: Degrees of labeling.

The averaged biotin DOL of NVS-Protein (averaged biotin DOL in Table 1) were calculated by applying the equation as

$$\begin{array}{c}\mathrm{Averaged}\mathrm{biotin}DOL=0\times \mathrm{relative abundance of} 0\mathrm{Biotin}\\ -\mathrm{Protein}+1\times \mathrm{relative}\mathrm{abundance}of1\mathrm{Biotin}-\mathrm{Protein}\\ +...+x\times \mathrm{relative}\mathrm{abundance}of\mathrm{xBiotin}-\mathrm{Protein}\end{array}$$

3.2. Biotinylation site configuration by peptide mapping

Peptide mapping analysis was performed to investigate the biotinylation sites. As shown in the biotinylation mechanism (Figure 1), the peptides with primary amines, including the N-terminus of the protein and the peptides containing Lysine (Lys, K), are the most likely potential targets for biotinylation. To be noted, the biotinylation process prohibited trypsin digestion by blocking the lysine site with Biotin, therefore, all the biotin-modified K sites would not be cleaved by trypsin. The biotinylation (+473 Da) was considered as a variable peptide modification of N-term and K site for database search. All the identified biotin-peptides were further verified with accurate MS1 and MS2 fragmentation. The criteria of peptide verification were set up as: the mass accuracy was less than 10 ppm; and the biotinylation sites were confirmed by MS2 fragmentations (Figure 3). All the biotinylated peptides were verified and named using their labeling position, for example, K40 indicated the peptide with biotinylation at Lys40 of NVS-protein. Based on the structure of the protein, 27 lysine sites were considered as potential biotinylation sites.

Figure 3.

Example of biotinylation at peptide K17 (K(Biotin)-ABCDE) was shown with verification of extracted ion chromatogram (XIC), MS and MS2.

MS: Mass spectrometry.

In our study, a peptide from NVS-protein with no lysine (to avoid biotinylation) and with no common post-translational modifications (such as oxidation or deamination) was selected as the internal standard (MW = 4 kDa). The intensities of all the biotinylated peptides were then normalized by assuming the peak area of the internal standard as 1, for example, the relative abundance of biotinylated K40 peptide (Biotin-K40) could be estimated by the equation as

$$\begin{array}{c}\mathrm{Relative abundance of Biotin}-K40=\\ \frac{\mathrm{peak area of Biotin}-K40}{\mathrm{peak area of internal standard}}\end{array}$$

K40, K225 and K17 were identified as the top three peptides with highest abundances. All the biotinylated peptides with biotin relative abundance >0.01 were considered for the comparison of biotinylation efficiency (Table 2).

Table 2.

Relative abundance of biotinylation at each K site with challenge ratio of 12:1, 2 h in the dark.

Lys site	Peak area	Relative abundance
Biotin-K40	1.3E + 08	0.25
Biotin-K225	9.3E + 07	0.18
Biotin-K17	6.5E + 07	0.12
Biotin-K84	5.6E + 07	0.11
Biotin-K212	4.9E + 07	0.09
Biotin-K111	4.9E + 07	0.09
Biotin-K8	4.4E + 07	0.08
Biotin-K58	1.6E + 07	0.03
Biotin-K67	1.3E + 07	0.02
Biotin-K103	1.3E + 07	0.02
Biotin-K66	1.3E + 07	0.02
Internal peptide	5.3E + 08	1

DOL: Degrees of labeling.

Overall, averaged biotin DOL and biotinylation at the specific peptide site could be successfully elucidated by combining the developed intact MS and peptide mapping analysis, which could be further applied to the investigation of factors that affect protein biotinylation efficiency under different labeling conditions.

3.3. Challenge ratio (biotin to protein ratio)

To investigate how the challenge ratio affects protein biotinylation process, NVS-protein was incubated with biotin under different challenge ratios (biotin to protein ration) of 6:1, 12:1 and 20:1. All the NVS-protein species with different biotin DOL were identified and verified by intact MS (Table 3).

Table 3.

Biotin degrees of labeling was estimated with different challenge ratios for 2 h incubation in the dark.

Biotin DOL challenge ratio	6:1	12:1	20:1
0Biotin-protein (Not Labeled)	0.01	0.03	ND
1Biotin-protein	0.16	0.03	ND
2Biotin-protein	0.33	0.20	ND
3Biotin-protein	0.37	0.22	0.02
4Biotin-protein	0.14	0.34	0.14
5Biotin-protein	ND	0.09	0.15
6Biotin-protein	ND	0.06	0.25
7Biotin-protein	ND	0.04	0.18
8Biotin-protein	ND	ND	0.18
9Biotin-protein	ND	ND	0.07
Averaged Biotin DOL	2.5	3.5	6.2

Most abundant biotin incorporation frequency highlighted in bold.

DOL: Degrees of labeling.

As shown in Table 3, the NVS-protein species were observed as 0–3 Biotin, 0–7 Biotin and 3–9 Biotin labels with challenge ratio of 6:1, 12:1 and 20:1, respectively. Considering relative abundance of biotinylated species, 3 Biotin, 4 Biotin and 6 Biotin were estimated as the highest abundant species with challenge ratio of 6:1, 12:1 and 20:1, respectively (highlighted in bold in the table). The averaged biotin DOL was estimated to be 2.5, 3.5 and 6.2 with challenge ratio 6:1, 12:1 and 20:1, respectively, by adding the abundance of each biotinylated protein. Good linearity (R² = 0.969, Figure 4A) was observed between the challenge ratio and the averaged biotin DOL. Thus, more biotin DOL was observed with higher challenge ratio at the intact MS level.

Figure 4.

Correlation was assessed between degree of biotinylation and challenge ratio. Good linearity (R² >0.95) was observed with increasing biotin challenge ratio for averaged biotin DOL (A) and relative abundance of biotinylation at each peptide site (B).

DOL: Degrees of labeling.

As follows, the accurate biotinylation site was also investigated with different challenge ratios using the developed peptide mapping analysis. All the biotinylated peptides with relative abundance >1% of the internal standard were considered. The same biotinylated peptides, especially the top three highest abundance (K40, K 225 and K17), were observed under different challenge ratios, indicating that the challenge ratio did not affect the biotinylation site (Supplementary Table S1). Consistently, similar with the results addressed by the intact MS analysis, increased biotinylation abundance at each K site was observed with higher challenge ratio (Supplementary Table S1). Using the top three biotinylated peptides as examples, good linearity (R² >0.96) was observed between the challenge ratio and the abundance of the biotinylated peptide (Figure 4B). Overall, higher challenge ratio could cause more biotinylation at the same peptide sites.

3.4. Incubation time

To investigate how the incubation time affects the protein biotinylation process, the incubation time of protein biotinylation was set up for 1, 2 and 4 h, respectively. All the NVS-protein species with series of biotin DOL were identified and verified by intact MS (Table 4).

Table 4.

Biotin degrees of labeling was estimated with different incubation time (challenge ratio = 12:1 in the dark).

Biotin DOL incubation time	1 h	2 h	4 h
0Biotin-protein (Not Labeled)	0.05	0.03	ND
1Biotin-protein	0.24	0.03	0.04
2Biotin-protein	0.42	0.20	0.07
3Biotin-protein	0.20	0.22	0.08
4Biotin-protein	0.07	0.34	0.15
5Biotin-protein	0.02	0.09	0.38
6Biotin-protein	ND	0.06	0.17
7Biotin-protein	ND	0.04	0.11
Averaged Biotin DOL	2.0	3.5	4.7

Most abundant biotin incorporation frequency highlighted in bold.

DOL: Degrees of labeling.

Using the same intact MS analysis, the biotinylated NVS-protein species were observed with incorporation frequencies of 0–3 Biotin, 0–7 Biotin and 1–7 Biotin with incubation time of 1, 2 and 4 h, respectively. While considering relative abundance of biotinylated species, 2 Biotin, 3 Biotin and 5 Biotin were estimated as the highest abundant species with incubation times of 1, 2 and 4 h, respectively (Table 4). Adding the abundance of each biotinylated protein, the averaged biotin DOL was also estimated to be 2.0, 3.5 and 4.7 for incubation times of 1, 2 and 4 h, respectively (Table 4 & Figure 5B). Thus, higher degrees of biotinylated protein species and higher averaged biotin DOL were observed with longer incubation times.

Figure 5.

Relative abundance of each biotinylation (A), averaged biotin DOL (B) and relative abundance of biotinylation at each peptide site (C) were estimated with 1, 2 and 4-hour incubation times.

DOL: Degrees of labeling.

Next, the accurate determination of biotinylation at a specific site was also determined under different incubation times. Similar with previous studies, the same biotinylated peptides were observed under different incubation times. For most of the biotinylated peptides, higher abundance was observed with longer incubation times (Figure 5C & Supplementary Table S2). Interestingly, K225 was estimated to be very low at 2.0% when the incubation time was set as 1 h, while K225 appeared to be in the top three highest abundance peptides (17.5 and 19.4%) after 2 and 4 h incubation (Supplementary Table S2).

3.5. Light conditions (darkness vs natural light)

It is commonly recommended that biotinylation reactions be run in the dark. In our experiments, light conditions were also considered as a factor to affect protein biotinylation efficiency. In this study, natural light and darkness were investigated. With a fixed challenge ratio at 12:1 and 2 h incubation, similar biotinylated protein species with similar abundance were observed under the natural light and darkness conditions, and 2–4 Biotin was identified as the top 3 abundant protein species under both conditions. Additionally, the averaged Biotin DOL was estimated to be 3.5 and 3.6 under the two light conditions (Supplementary Figure S1A & Supplementary Table S3).

Similarly, the biotinylated peptides were also identified using the developed peptide mapping analysis. The same lysine residues were observed with similar abundance under both natural light and darkness reaction conditions (Supplementary Figure S1B & Supplementary Table S4).

4. Discussion

Initially, the complexity of glycosylation on NVS-protein hindered the deconvolution of intact MS signals. This issue was addressed through enzymatic treatments with PNGF and Sialidase A, which effectively removed N- and O-glycosylation, similar approach reported before [42]. The optimized sample preparation improved MS signal clarity, enabling accurate measurement of biotinylation at different DOL. Our findings demonstrated that biotinylation also resulted in a lower signal-to-noise ratio, which underscores the challenge of quantifying biotinylation in complex protein samples using intact MS. Nevertheless, by normalizing the intensity of biotinylated species against total protein intensity, we successfully quantified the relative abundance and averaged biotin DOL.

Our peptide mapping results revealed that lysine residues of the NVS-protein are primary targets for biotinylation. The biotinylation at lysine residues blocked trypsin cleavage, necessitating the use of specific search parameters in our database analysis. It was observed that biotinylation at lysines K40, K225 and K17 had the highest abundance. These findings were consistent across different experimental conditions, affirming the reliability of our peptide mapping approach. By comparing the relative abundances of biotinylated peptides, we could determine and relatively quantify the most frequent biotinylation sites. Overall, by integrating observations from both intact MS and peptide mapping, we were able to elucidate the relationship between biotinylation efficiency and various biotinylation conditions.

The challenge ratio significantly influenced the degree of biotinylation. As expected, increasing the biotin-to-protein ratio led to higher biotin DOL and increased abundance of biotinylated species. The linear relationship between challenge ratio and averaged biotin DOL (R² = 0.969) confirmed that higher biotin concentrations enhanced biotinylation efficiency. Despite this, the biotinylation sites remained consistent, indicating that the challenge ratio primarily affects the extent of modification rather than the site of modification.

Extending the incubation time increased both the degree of biotinylation and the abundance of biotinylated peptides. For example, longer incubation times resulted in higher average biotin DOL and greater biotinylation at specific lysine residues, like K40 and particularly K225. This suggests that biotinylation efficiency can be improved with time for more thorough reaction between biotin and lysine residues. The observed variability in biotinylation efficiency at different lysine sites (K225), indicated that the efficiency of biotinylation varied across different lysine residues, which is consistent with the fact that most of the biotinylation protocol requests at least a 2 h incubation time to guarantee sufficient time for the reaction between biotin and lysine residues. Our observations stressed the importance of evaluation of the optimal incubation time in a labeling strategy due to the labeling variability for specific proteins and biotinylation reagents.

Interestingly, our study found that light conditions did not have a significant impact on the biotinylation efficiency of the protein being studied. While it's not necessarily burdensome to run the reaction in the dark, our example demonstrated that labeling consistency was possible under suboptimal reaction conditions as demonstrated by intact LC–MS analysis. This suggests that, under the conditions tested, biotinylation reactions can be conducted in natural light without compromising the consistency or efficiency of the labeling process. However, it is critical to consider the effect of light conditions on protein biotinylation efficiency, and the optimal light condition is highly dependent on the specific proteins and biotinylation reagents.

5. Conclusion

The study successfully developed an optimized mass spectrometry method to monitor the progress of the biotin labeling of a complex glycosylated and sialidated critical reagent (NVS-protein). Optimizing the method enabled the evaluation of factors that affect the biotinylation of critical reagents. The averaged biotin DOL and the specific labeling sites were accurately estimated and verified by the combination of intact MS and peptide mapping analysis. The study also provided a clear understanding of the relationship between biotinylation efficiency and labeling conditions, contributing to further optimization of protein biotinylation for accurate and reliable results in ligand–binding assays.

Supplemental material

Supplemental data for this article can be accessed at https://doi.org/10.1080/17576180.2024.2394317

Author contributions

W Qu: contributions to the conception or design, conduction, data analysis of the work; drafting the work and revising it critically; final approval of the version to be published; agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. J Glick: contributions to the conception of the work; guiding and revising the work critically; final approval of the version to be published; agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. P Dessanti: contributions to the conception of the work; revising the manuscript critically; final approval of the version to be published; agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. J Cunliffe: contributions to the conception of the work; revising the manuscript critically; final approval of the version to be published; agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Financial disclosure

This study was sponsored by Biomedical Research, Novartis, Cambridge, MA 02139, USA. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Competing interests disclosure

The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Writing disclosure

No writing assistance was utilized in the production of this manuscript.

Ethical conduct of research

The authors state that they have obtained appropriate review and approval from Novartis Legal Department. In addition, no investigations involving human or animal subjects were involved.