Bethan S McAvan1, Leo A Bowsher2, Thomas Powell2, John F O'Hara2, Mariangela Spitali2, Royston Goodacre3, Andrew J Doig4. 1. School of Chemistry, Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester M1 7DN, United Kingdom. 2. UCB Celltech, UCB Pharma, Limited, 208 Bath Road, Slough, Berkshire SL1 3WE, United Kingdom. 3. Department of Biochemistry, Institute of Integrative Biology, University of Liverpool, Biosciences Building, Crown Street, Liverpool L69 7ZB, United Kingdom. 4. Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom.
Abstract
Monoclonal antibodies (mAbs) represent a rapidly expanding market for biotherapeutics. Structural changes in the mAb can lead to unwanted immunogenicity, reduced efficacy, and loss of material during production. The pharmaceutical sector requires new protein characterization tools that are fast, applicable in situ and to the manufacturing process. Raman has been highlighted as a technique to suit this application as it is information-rich, minimally invasive, insensitive to water background and requires little to no sample preparation. This study investigates the applicability of Raman to detect Post-Translational Modifications (PTMs) and degradation seen in mAbs. IgG4 molecules have been incubated under a range of conditions known to result in degradation of the therapeutic including varied pH, temperature, agitation, photo, and chemical stresses. Aggregation was measured using size-exclusion chromatography, and PTM levels were calculated using peptide mapping. By combining principal component analysis (PCA) with Raman spectroscopy and circular dichroism (CD) spectroscopy structural analysis we were able to separate proteins based on PTMs and degradation. Furthermore, by identifying key bands that lead to the PCA separation we could correlate spectral peaks to specific PTMs. In particular, we have identified a peak which exhibits a shift in samples with higher levels of Trp oxidation. Through separation of IgG4 aggregates, by size, we have shown a linear correlation between peak wavenumbers of specific functional groups and the amount of aggregate present. We therefore demonstrate the capability for Raman spectroscopy to be used as an analytical tool to measure degradation and PTMs in-line with therapeutic production.
Monoclonal antibodies (mAbs) represent a rapidly expanding market for biotherapeutics. Structural changes in the mAb can lead to unwanted immunogenicity, reduced efficacy, and loss of material during production. The pharmaceutical sector requires new protein characterization tools that are fast, applicable in situ and to the manufacturing process. Raman has been highlighted as a technique to suit this application as it is information-rich, minimally invasive, insensitive to water background and requires little to no sample preparation. This study investigates the applicability of Raman to detect Post-Translational Modifications (PTMs) and degradation seen in mAbs. IgG4 molecules have been incubated under a range of conditions known to result in degradation of the therapeutic including varied pH, temperature, agitation, photo, and chemical stresses. Aggregation was measured using size-exclusion chromatography, and PTM levels were calculated using peptide mapping. By combining principal component analysis (PCA) with Raman spectroscopy and circular dichroism (CD) spectroscopy structural analysis we were able to separate proteins based on PTMs and degradation. Furthermore, by identifying key bands that lead to the PCA separation we could correlate spectral peaks to specific PTMs. In particular, we have identified a peak which exhibits a shift in samples with higher levels of Trp oxidation. Through separation of IgG4 aggregates, by size, we have shown a linear correlation between peak wavenumbers of specific functional groups and the amount of aggregate present. We therefore demonstrate the capability for Raman spectroscopy to be used as an analytical tool to measure degradation and PTMs in-line with therapeutic production.
The pharmaceutical
industry
constantly strives for improved process analytical technology (PAT)
to monitor and determine drug product quality. The need for enhanced
analytics arises in turn from the demand of the health authorities,
the largest two being the Food and Drug Administration and the European
Medicines Agency, for greater pharmaceutical process understanding
and in-depth product characterization.[1,2] Raman spectroscopy
is an analytical technique that has been highlighted as a tool that
could be used for in-line and possible online quality control monitoring
in the largescale manufacture of drug molecules.[3−6] Raman spectroscopy is a vibrational
technique that can provide molecular fingerprints using unique vibrations
from different bonds within a molecular structure to build a picture
of the functional groups and overall chemical arrangement. The technique
is currently widely employed in the pharmaceutical sector to monitor
chemical synthesis of drug molecules providing real-time critical
quality attribute information.[7,8] However, biological
therapeutics are typically complex, multidomain globular proteins
made up of hundreds of amino acids that can all influence the function
of the protein. Monoclonal antibodies (mAbs) are now the biological
therapeutic market leader,[9] but the structural
complexity of these molecules increases the manufacturing cost due
to a diverse range of possible degradation pathways. The possible
batch heterogeneity therefore means extensive characterization is
needed requiring time and expertise.[10−12] MAbs are typically ∼150
kDa and composed of multiple domains that result in the typical “Y”
shape higher order structure. In general, the domains can be summarized
as the Fab domain consisting of the FV (Fab variable), CH1 and CL (heavy constant and light constant) domains, and the
Fc region containing the CH2 and CH3 domains. In terms of degradation, it is well
documented that mAbs are prone to aggregation and fragmentation, as
well as a range of PTMs including oxidation of amino acids, induced
by processing conditions.[13] The difficulty
in avoiding these conditions comes from the fact that all mAbs have
different propensities and mechanisms to aggregate or fragment. Many
stress induced aggregates can cause protein precipitation, although
it is the soluble, subvisible aggregates that lead to immune responses.
Fragmentation can also cause batch heterogeneity, as certain purification
conditions can lead to nonenzymatic covalent bond breakage resulting
in cleaving antibody domains from the intact mAb. Fragmentation is
usually caused by hydrolysis of the peptide backbone, but is also
common with certain amino acids, such as Asp, Gly, Ser, Thr, Cys,
and Asn.[14] PTMs are chemical modifications
to the amino acids that occur after expression of the antibodies.
The most common PTMs include glycation, glycosylation, deamidation,
and oxidation. These amino acid modifications can cause changes to
the structure and physical properties of an antibody and may lead
to a higher propensity to aggregate. PTMs can also significantly reduce
the binding specificity of the FV region
when the modification occurs at a site that is important to binding,
leading to reduced therapeutic efficacy. Current methodologies for
assessing the amount of aggregation and PTMs, such as Size-Exclusion
Chromatography (SEC) and peptide mapping, require sample collection
and preparation and are therefore not suitable as a real-time PAT.
Ideally industries that specialize in protein therapeutic processing
need a PAT that can work in real-time, is used in-line with current
industrial set-ups without sample preparation, and can be applied
at different stages of the therapeutic manufacture without interfering
with the process. This study investigates the sensitivity of Raman
spectroscopy to measure degradation of an IgG4 therapeutic antibody,
including fragmentation and aggregation, as well as PTMs such as oxidation
and deamidation. A forced degradation study approach was used to induce
degradation and PTMs using conditions known to cause measurable changes.
Ten different conditions were chosen, including a reference sample
that was stored at 4 °C. Aggregation and fragmentation was measured
using SEC, and peptide mapping was used to quantify the induced PTMs.
CD spectroscopy was used to determine tertiary and secondary structural
information for the IgG4. CD spectral changes in the IgG4 degraded
samples appeared to be minimal, however by combining PCA with CD,
we were able to separate the samples based on PTMs and degradation
using the loadings plots to identify the key spectral changes. Thismethod was then applied to Raman spectroscopy and again PCA demonstrated
the sensitivity and applicability of Raman to monitor degradation
and PTMs for quality control of antibody therapeutics.
Experimental
Section
IgG4 Forced Degradation
All forced degraded samples
were made up to 3 mL at 25 mg mL–1 in the IgG4 UCB
formulation buffer and incubated under varying conditions for 14 days
unless otherwise stated. Heat degraded samples were incubated at 4,
40, and 50 °C. The 4 °C sample served as the control for
degradation after 14 days. The pH degraded samples were adjusted to
pH 3 with HCl and to pH 10 with NaOH. Both pH samples were incubated
at 4 °C. Agitation degraded samples were placed on a 1400 rpm
orbital shaker, at 25 °C. Deamidation conditions were created
by buffer exchanging one sample into 1% ammonium bicarbonate buffer
pH 8.1. pH was adjusted using NH4OH 1 M. Oxidation conditions
consisted of adding H2O2, 30% (w/w), to the
IgG4 and formulation buffer to a final concentration of 1%. Both the
deamidation and oxidation samples were stored at 4 °C. Light
stressed samples were prepared by aliquoting IgG4 samples into quartz
cuvettes and incubating in an Atlas Suntest XLS+ chamber with an intensity
of 250 W/m2 at 25 °C. The samples were exposed to
1000 and 5000 kLux·h of light, respectively, and were then incubated
at 4 °C for the remainder of the 14 days.
Generation of IgG4 Aggregates
for Separation
IgG4 was
exposed to 5000 kLux·h of light at 25 °C. The samples were
prepared as 45 mg mL–1 in formulation buffer.
Peptide Mapping
IgG4 was digested using trypsin, separated,
analyzed by mass spectrometry, and compared to a database to give
levels of modification. Details are given in the Supporting Information (SI).
Raman Spectroscopy
Raman measurements were undertaken
on a Renishaw inVia Raman microscope (Renishaw Plc., Gloucestershire,
U.K.) using a 785 nm laser. The experimental parameters used for all
data collection were 100% laser power with a 10 s exposure and 20
accumulations, resulting in an overall acquisition time of 200 s per
measurement. A 96 well quartz plate (Hellma) was used. The plate wells
were randomized with 2 wells per sample. For each well, 4 repeats
were obtained, leading to total of 8 repeats per sample. Raw and preprocessed
spectra are shown in Figure S5.
Results
and Discussion
In order to determine the applicability of
Raman spectroscopy for
the PAT monitoring of antibody therapeutics we force degraded an IgG4
protein. Most antibody therapeutics are based on the IgG1 subclass,
with IgG4 being the second most commonly used. IgG4 is known to be
more susceptible to PTMs and degradation and therefore provided us
with a wider range of samples to analyze.[15,16] The 10 different degradation conditions were selected to best represent
current stability tests used within the pharmaceutical sector. The
conditions are outlined in the Experimental Section.
Quantification of Aggregates and Fragments
SEC was
used to determine the amount of aggregation and fragmentation that
had occurred in each of the degradation conditions. The results are
summarized in Figure S1. The control 4
°C sample shows that even the IgG4 held under nondegrading conditions
for 14 days shows a small amount of aggregation (∼1%). IgG4
irradiated with 5000 kLux·h of light at 300 to 800 nm shows the
most degradation with 26% aggregation and 2% fragmentation. The oxidizing
condition also led to 9% aggregation and 2% fragmentation. Incubation
at pH 3 caused the most fragmentation (5%) with no aggregates present.
The approximate masses derived from the reduced SDS page gels (Figure S2a) suggest that the fragments are ∼30
kDa and therefore likely to be a fragment of the light chain (∼25
kDa). The mass of the aggregates seen in the 5000 kLux·h condition
are at least ∼245 kDa (Figure S2) under nonreducing conditions. Under reduced conditions the size
of the aggregates is significantly smaller, as the disulfide bond
in the hinge region of the antibody is broken resulting in a fragment
half the size of an intact IgG4. However, there are also bands at
a higher MW than half an intact IgG4 suggesting that the aggregates
are still intact when the disulfide bridge in the hinge region is
broken. The remaining degradation conditions showed very similar aggregation
levels as in the 4 °C control. The full SEC traces and analysis
are shown in Figure S3 and Table S1.
Quantification of PTMs
To determine the extent of PTMs,
peptide mapping of the IgG4 was used. This allowed an estimation of
the quantity and identification of the chemical changes made to the
amino acid side chains caused by the chosen conditions. The estimated
PTM level for each site is shown as a percentage of the total ion
count (TIC) of the most abundant charge state of the modified peptide
against the corresponding unmodified peptide. It should be noted that
mass spectrometry is a semiquantitative technique. These percentages
are calculated from the ionization intensities reported by BioPharmaLynx
for a particular modification within a peptide. The intensity of the
modification is reported as a percentage of the total intensity of
all variants of that peptide present from the tryptic digest. Often
the unmodified peptides will have different ionization intensities
compared with that of the modified and therefore the values are not
necessarily an ultimate quantification. The full PTM report is in Tables S2 and S3.The full PTM report are
summarized in Figure S4. The control 4
°C sample shows the levels of post-translational modifications
in an IgG4 sample after purification and stored under optimal conditions
for this particular protein. In the control, oxidation of the Met,
Trp, and His are 65%, 8%, and 3%, respectively. In general, Met usually
oxidizes to form a sulfoxide and His has an addition of a carbonyl
group to the imidazole ring to give 2-oxohistidine. Trp oxidation
can be more complex as different products can be formed either through
the addition of hydroxyl group to the benzene ring or a carbonyl to
the indole.[17,18] Both heat incubated samples show
similar levels of oxidation for all three amino acids but show an
increase in deamidation as a function of temperature to 54% at 50
°C. Agitation shows little or no change compared to the control
group. The light stressed samples both showed a large increase in
the Met oxidation, rising to 100% with at least one oxidized Met in
the 5000 kLux·h condition. Deamidation and Trp oxidation showed
slight increases with longer duration of light, while His oxidation
remained similar to that of the control. The oxidation samples showed
an increase in oxidized Trp to 46% which was more than double that
of any other sample and a 10-fold increase in the amount of His oxidation
present to 30%. Oxidizing conditions also increased Met oxidation
to 100%. The ease with which each amino acid side chain oxidizes can
be summarized as Met > Trp > His, in agreement with previously
published
work on antibody oxidation.[17,19]
Structural Analysis Using
Circular Dichroism
A typical
IgG4 will be mainly β-sheet (40%) with little contribution from
α-helices (4%).[20] CD is limited in
terms of protein concentration and buffer and therefore the samples
were diluted to 0.8 mg mL–1.Figure shows the averaged CD spectra
of three scans of three preparations of each degradation condition
for the IgG4 in both (a) far and (b) near UV regions. CD spectra for
β-structures are diverse, but in general it is expected that
the spectra would have a maximum between 195–205 nm and a minimum
at ∼218 nm. Figure a shows the far UV CD of all the averaged degradation conditions
with maxima at 203 nm and minima at 218 nm from antiparallel β-sheets.
The small negative band at ∼230 nm is thought to arise from
aromatic side chains.[21] pH 3 stressed samples
have secondary structures deviating from that of the control 4 °C
sample. In particular, this sample has lower intensity at 203 nm and
the peak at 218 nm has shifted to a lower wavelength suggesting that
the protein may have lost some β-sheet structure and is more
disordered than the other sample conditions. In Figure b the tertiary structure of the IgG4 under
different degradation conditions can be seen. In the near UV region,
it is more difficult to relate exact wavelengths to specific structural
components and instead ranges usually depict different amino acids
groups in the tertiary structure. In terms of the amino acid side
chains, Trp absorbs at ∼290 nm, Tyr at ∼280 nm, Phe
at ∼260 nm, and disulfide bonds between 250–280 nm.
To identify these smaller changes, we have used PCA, shown in Figure a,c. PCA reduces
the dimensions of the data into a 2D plot which maximizes variation
between the spectra using a scores plot. The loadings (Figures b and 2d) identify the key peaks or regions that lead to most separation
in the data sets.
Figure 1
CD analysis of degraded IgG4 samples: (a) Far UV CD spectra
and
(b) Near UV CD spectra. Samples were diluted to 0.8 mg mL–1. Data shown is an average of 9 spectra. *In the far UV CD Control
4 °C, 50 °C, and 1000 kLux·h is an average of 6 spectra
due to three well repeats being outliers.
Figure 2
PCA and
respective loadings plots for the far and near UV CD spectra
of IgG4. (a) PCA of far UV CD, (b) loadings plot for far UV CD PCA,
(c) PCA of near UV CD, and (d) loadings plot for near UV CD. TEV is
the total explained variance of each PC. For each IgG4 degraded sample,
three wells were aliquoted and measured in triplicate. Data are reported
as an average of the triplicate repeats from one well. (1) Control
4 °C, (2) 40 °C, (3) 50 °C, (4) agitation, (5) deamidation,
(6) 1000 kLux·h, (7) 5000 kLux·h, (8) oxidation, (9) pH
10, and (10) pH 3. *In the far UV CD 4 °C control, 50 °C,
1000 kLux·h is shown as an average of three repeats from two
wells due to a well outlier from each.
CD analysis of degraded IgG4 samples: (a) Far UV CD spectra
and
(b) Near UV CD spectra. Samples were diluted to 0.8 mg mL–1. Data shown is an average of 9 spectra. *In the far UV CD Control
4 °C, 50 °C, and 1000 kLux·h is an average of 6 spectra
due to three well repeats being outliers.PCA and
respective loadings plots for the far and near UV CD spectra
of IgG4. (a) PCA of far UV CD, (b) loadings plot for far UV CD PCA,
(c) PCA of near UV CD, and (d) loadings plot for near UV CD. TEV is
the total explained variance of each PC. For each IgG4 degraded sample,
three wells were aliquoted and measured in triplicate. Data are reported
as an average of the triplicate repeats from one well. (1) Control
4 °C, (2) 40 °C, (3) 50 °C, (4) agitation, (5) deamidation,
(6) 1000 kLux·h, (7) 5000 kLux·h, (8) oxidation, (9) pH
10, and (10) pH 3. *In the far UV CD 4 °C control, 50 °C,
1000 kLux·h is shown as an average of three repeats from two
wells due to a well outlier from each.In Figure a, PC
1 accounts for 85% of the total explained variance (TEV), meaning
the data are mainly separated across the x-axis.
Replicates of the same conditions cluster close together showing that
the measurements were reproducible. The pH 3, 5000 kLux·h, and
oxidation conditions all fall within separate regions, showing that
they form distinct structures. All other conditions cluster into “other”
with the control conditions, suggesting that these conditions cause
little change to the structure of the antibody. The loading plots
shown in Figure b
highlight the spectral regions that were most important to clustering
in the PCA scores plot. PC 1 is separated on the intensity at 203
nm where it is decreased in conditions pH 3, 5000 kLux·h and
oxidation, suggesting a change in the antiparallel β-sheet structure.
The loadings plot in Figure d shows that an increasing peak at 290 nm is the main cause
for the separation which signifies changes to Trp. There is also a
difference in the baseline intensity of the absorbance across 250–280
nm suggesting changes in the disulfide bonding of the IgG4 seen in
previous forced degradation studies.[22]
Structural Analysis Using Raman Spectroscopy
In general,
secondary structural information can be gained from the Raman spectral
region between 1700 and 1200 cm–1, which includes
the amide I, II, and III regions.[23] A full
spectral assignment can be found in Table S6. Specifically, here is it possible to determine the α-helical,
β-sheet, and disordered content. The main advantage of Raman
is the quick spectral collection time and little to no sample preparation
(water does not interfere); hence Raman is a strong candidate for
real-time analysis of biotherapeutics production.[24,25]Figure a shows the
Raman spectra as an average of 8 replicates. SI Figure S5a shows the raw data, and Figure S5b shows the buffer subtracted data highlighting the difference
in the baseline across the degradation conditions. Figure S6 shows the buffer spectrum. Due to this difference
in baselines and decreased intensity in samples with higher levels
of aggregation, we have placed more emphasis on peak centers than
the intensity. For all samples, the amide I peak is at 1666 cm–1 suggesting all samples have retained their β-sheet
structure. All samples also retain a peak at 532 cm–1 suggesting that the disulfide bonding in the proteins is not affected
by the degradation conditions. However, peak intensity ratios should
be less affected by the buffer subtraction. A change in the peak intensity
between two peaks, when compared across spectra, could therefore indicate
real structural changes. In Figure a, the changes in peak ratios for the different degradation
conditions are apparent in the amide III region between 1312 and 1334
cm–1 (assigned to Trp). This suggests real differences
in the amide III and tertiary structure caused by the incubation conditions.
Raman bands for the amino side chains are mainly located between 700
and 1000 cm–1. As with the CD spectrum analysis,
we have used PCA to look at differences between the spectra.
Figure 3
Raman spectra
of degraded IgG4 samples with the respective PCA
and loading plots. (a) Raman spectra (shown as an average of 8 repeats
per condition), (b) PCA (showing 8 replicates individually), and (c)
loadings plot showing PC 1 and PC 2. TEV is the total explained variance
of each of PCs. (1) Control 4 °C, (2) 40 °C, (3) 50 °C,
(4) agitation, (5) deamidation, (6) 1000 kLux·h, (7) 5000 kLux·h,
(8) oxidation, (9) pH 10, and (10) pH 3.
Raman spectra
of degraded IgG4 samples with the respective PCA
and loading plots. (a) Raman spectra (shown as an average of 8 repeats
per condition), (b) PCA (showing 8 replicates individually), and (c)
loadings plot showing PC 1 and PC 2. TEV is the total explained variance
of each of PCs. (1) Control 4 °C, (2) 40 °C, (3) 50 °C,
(4) agitation, (5) deamidation, (6) 1000 kLux·h, (7) 5000 kLux·h,
(8) oxidation, (9) pH 10, and (10) pH 3.The PCA of the Raman data is shown in Figure b. The PCA shows clustering of the repeats
from the same conditions, meaning the data were reproducible. The
samples that cluster separately to the control are oxidation, pH 3,
5000 kLux·h, and 1000 kLux·h. The remaining conditions were
clustered with the control as “other”. In Figure b both UV degrading conditions
cluster above the “other” group, whereas the pH 3 and
oxidation cluster below showing that different degradation conditions
affect the antibodies in different ways. Figure c summarizes the loading plots of PC 1 and
PC 2. Due to the baseline differences, the PC 1 is mainly attributed
to signal intensities. PC 2 only accounts for 7% of the variance and
although it does explain separation between the sample conditions
it also highlights differences within the clusters especially of pH
3 and oxidation. The peaks at 1637 and 1670 cm–1 could be due to the buffer subtraction from samples with higher
heterogeneity. Hence, we place higher emphasis on wavelengths of peak
centers rather than intensities. When comparing both PC 1 and PC 2
of the Trp region at around 885 cm–1, PC 1 shows
an increase in a peak at 900 cm–1 for pH 3, while
PC 2 has an increase in the peak intensity at 887 cm–1 for 5000 kLux·h and 1000 kLux·h, showing that the peak
assigned to the Trp indole is important to the sample separation.[26,27]Figure a shows the
average peak centers of the Trp peak for each degradation condition
across the 8 sample repeats. The peak center positions show that the
conditions that caused the largest shift in the Trp 885 cm–1 peak are oxidation, pH 3, 5000 kLux·h, and 1000 kLux·h,
in agreement with the Raman PCA results. The oxidation samples show
the largest shift to a lower wavenumber which suggests an increase
in the strength of the indole N–H hydrogen bonding. In contrast,
at pH 3, 5000 kLux·h, and 1000 kLux·h, there was a shift
to a higher wavenumber indicating that Trp had weaker hydrogen bonding.[28]
Figure 4
Peak centers of the Trp vibration in the force degraded
samples
and the possible degradation products. (a) Average peak center of
the Trp vibration from 8 Raman repeats (colors highlight the clusters
for comparison to PCA in Figure b. Error bars highlight the standard error (SE), (b)
Trp vibrations of Trp, Kynurenine (Kyn), N-formylkynurenine,
and 5-hydroxy Trp (Trp-OH); and (c) corresponding chemical structures.
Peak centers of the Trp vibration in the force degraded
samples
and the possible degradation products. (a) Average peak center of
the Trp vibration from 8 Raman repeats (colors highlight the clusters
for comparison to PCA in Figure b. Error bars highlight the standard error (SE), (b)
Trp vibrations of Trp, Kynurenine (Kyn), N-formylkynurenine,
and 5-hydroxy Trp (Trp-OH); and (c) corresponding chemical structures.
Figure 5
Raman spectra of separated aggregate species of IgG4 samples from
exposure to UV light with the respective PCA and loadings plots. (a)
Raman spectra (shown as an average of 8 repeats), (b) PCA (showing
8 replicates individually), and (c) loadings plot showing PC 1. (1)
Fraction 1 (monomer), (2) Fraction 2, and (3) Fraction 3. TEV is the
total explained variance of each PC.
The oxidation samples show the highest amount of Trp oxidation
compared to all other conditions at 46% (Figure
S5), which can be correlated to the largest shift in the Raman
Trp peak in Figure . UV exposure to antibody therapeutics has been reported to follow
specific Trp degradation pathways similar to that of H2O2 oxidation. For both H2O2 and
UV induced Trp degradation, the most common products were hydroxytryptophan
(OH-Trp), N-formylkynurenine (NFK), and kynurenine
(Kyn) (Figure c).[17,29] The main difference between these degraded samples was the observed
color change. For UV degraded proteins, the solutions turned yellow,
whereas for H2O2, we observed no color change
(Figure S7), suggesting there is a different
mixture of Trp degradation products in the samples. The yellow color
has previously been assigned primarily to the formation of Kyn and
NFK.[17] Previously, a yellowing of mAb samples
has been assigned to glycation; however, glycation levels are highest
(9.7%) in the control 4 °C sample, which is colorless.[30,31] To rationalize the Trp indole peak shift we acquired spectra of
the oxidized forms of Trp (Full spectra in Figure S8). The spectrum of dried Trp has a peak at 872 cm–1 (Figure b); however,
in IgG4 in solution this peak is at ∼884 cm–1. These differences show that Trp peaks are sensitive to the environment;
i.e., whether the side chains are in the hydrophobic core or exposed
to solvent. We assume the shifts seen in the standard compounds apply
to Trp in the protein. Kyn has a peak in the Raman spectrum at 870
cm–1, a decrease in wavenumber compared to the control
Trp. Kyn is also yellow. NFK is the only compound that has a peak
at 885 cm–1, as seen in both the 1000 kLux·h
and 5000 kLux·h samples. We therefore suggest that the yellowing
of the samples and increase in wavenumber in the 1000 kLux·h
and 5000 kLux·h samples is due to formation of NFK. As there
is also a shift to higher wavenumber in the pH 3 sample (5% fragmentation)
there may be an environmental change within the protein structure.
The oxidation sample shows a shift to a lower wavenumber in Figure b but no color change
in Figure S7. Trp-OH is a colorless product
and shows no peak around 870 cm–1. The shift to
a lower number can be assigned to the loss of the Trp band at 885
cm–1 and therefore leaving a peak at 876 cm–1 from the phosphate in the analysis buffer due to
differences in the buffer subtraction of the degraded samples (Figure S5). This can be further seen in Table S4 where larger peaks shifts are seen in
the buffer subtracted data compared to the data with no buffer subtraction
suggesting that the phosphate peak may be masking the center of the
Trp peak.
IgG4 Aggregate Separation
The forced degradation conditions
produced a wide range of both degradation and PTMs resulting in complex
mixtures. By far the largest problem in therapeutic degradation is
the formation of aggregates that leads to the loss of material during
downstream processing involving the mAbs being passed through a range
of different columns to purify and remove waste from expression. IgG4
incubated under 5000 kLux·h light was therefore investigated
further, as this condition produced the largest amount of aggregates
(Figure S1). After incubation the sample
was separated using SEC (Figure S9) into
monomers, aggregate peak 1 (Fraction 2), and aggregate peak 2 (Fraction
3) which both resulted in a mixture of aggregates summarized in Table below (separation
and full SEC results are shown in SI Figures S10 and S11). Fragment concentrations were too low to be measured.
Table 1
Amount of Monomer and Aggregate in
Each of the SEC Separated Fractions Determined by SE-UPLCa
SEC fraction
monomer (%)
aggregate 1 (%)
aggregate 2 (%)
1
100
2
51
49
3
17
33
50
Analysis
was carried out at 1
mg mL–1.
Analysis
was carried out at 1
mg mL–1.Each of the sample fractions shown in Table was concentrated to 20 mg mL–1 and analyzed using the same Raman setup as described previously
(section 2.4, Raman Spectroscopy). The average
Raman spectrum across 8 repeats of each sample is shown in Figure a. Buffer was treated with 5000 kLux·h light before its
spectrum was collected for subtraction (Figure S12). It was found that the higher quantity of the larger aggregates
found in the sample correlated with an increased baseline slope (Figure S13). We therefore focused on peak shifts
rather than intensities. The peak at 532 cm–1 due
to S–S bonds is present in all three samples suggesting that
the disulfide bonding is still intact.[32,33] However, there
is a small shift to a higher wavenumber in the Fraction 2 sample suggesting
that although the S–S bonding is present there may be a small
change in its environment or conformation. The amide I peak at 1666
cm–1 has not shifted, suggesting that aggregation
is not significantly changing the overall secondary structure of the
antibody.Raman spectra of separated aggregate species of IgG4 samples from
exposure to UV light with the respective PCA and loadings plots. (a)
Raman spectra (shown as an average of 8 repeats), (b) PCA (showing
8 replicates individually), and (c) loadings plot showing PC 1. (1)
Fraction 1 (monomer), (2) Fraction 2, and (3) Fraction 3. TEV is the
total explained variance of each PC.The PCA plotted in Figure b shows the sample fractions are all spectrally distinct from
each other. PC 1 accounts for 83% of the TEV and shows that fractions
2 and 3 are more spectrally similar to each other than to the monomer.
Although the repeats from the same fraction cluster, they also show
some separation on PC 2, accounting for only 12% of the TEV, which
is possibly due to baseline differences from the well repeats. The
separation of samples within the same fraction increases with higher
levels of larger aggregates in the sample suggesting that the heterogeneity
of the sample increases with aggregation, leading to difficulty in
buffer subtraction. Figure c summarizes the loadings for PC 1. In general, PC 1 resembles
an antibody spectrum as the main differences in the PCA are the peak
intensities. However, a few peaks can be seen to differ in position
compared to the spectrum in Figure a. This shift is particularly apparent at 901, 1123,
and 1448 cm–1. Figure S14 shows the peak shifts across the three sample fractions. Figure S14a shows the peak centers at ∼1121
cm–1, 8b ∼ 1450 cm–1 and
8c ∼ 890 cm–1. An increase in the Trp wavenumber
from monomer to Fraction 3 suggests that the strength of the N–H
hydrogen bonding decreases as the protein aggregates. The peak at
1450 cm–1 is assigned to C–H deformation.[23,34,35] This is specifically vibrations
from CH2 and CH3 groups. From the Monomer to
Fractions 2 and 3, the peak shifts to a higher wavenumber suggesting
a change in the environment of the C–H bonding and possibly
the protein structure. In most amino acid side chains, there is a
CH2, making explaining the shift difficult. The peak centered
at 1121 cm–1 has been assigned to C–N bonding
which is mainly found in the protein backbone.[35,36] From Monomer to Fraction 3, the peak center of the C–N vibrations
is shifted to a lower wavenumber. Again, as the C–N bond is
seen throughout the protein backbone, it is difficult to correlate
the peak shift with a specific structural change, but it does show
that there are differences in the overall protein structure. Figure a shows peak ratio
differences between 1313 and 1332 cm–1 (also seen
in Figure a) in which
the ratio decreases from monomers to dimers to aggregates. This suggests
a structural change within the amide III region and tertiary structure
of the antibody. These Raman spectral shifts have also been reported
in a recent paper by Zhang et al.,[37] where
samples of varying mAb aggregate levels were generated and analyzed
using Raman spectroscopy and chemometrics, such as two-dimensional
correlational spectroscopy (2DCOS) and support vector machines (SVM).
Similarly to our results, they found changes in Amide II, CH deformation
region, of the Raman spectrum in aggregated samples. Unfortunately,
due to buffer excipients, they were not able to analyze peaks below
1160 cm–1, such as the 1121 and 885 cm–1 shown in this work. The combination of these results suggests peak
shifts measured in aggregates, especially in the Amide II region,
may be applicable to aggregates in other types of mAb therapeutics.
Conclusions
We have demonstrated, for the first time, the
ability of Raman
spectroscopy to differentiate between force degraded samples of an
IgG4 with differing PTMs, fragmentation, and aggregation. Furthermore,
we have shown the ability of Raman to distinguish between samples
of monomers and mixed aggregate species. Structural differences between
the force degraded samples are small and difficult to distinguish
when interpreting conventional CD and Raman spectra. However, by combining
spectroscopic analysis with chemometrics, such as PCA, we are able
to draw out subtle structural differences. Furthermore, by using the
peak shifts highlighted in the loadings plots we were able to assign
spectral features to specific PTMs and degradation types that were
used by the PCA to separate the data. Thus, the loadings identified
key peaks that could be used to monitor structural changes in mAbs
for quality control. Both the PCAs of the CD and Raman data showed
that the 5000 kLux·h, pH 3 and oxidation conditions gave samples
that differed most to the control. Specifically, in Raman, we saw
peak shifts in the N–H vibration (∼885 cm–1) of the indole of Trp, indicating hydrogen bonding and environmental
changes. Peak shifts were assigned to different degradation products
of Trp caused by oxidation. IgG4 incubated with H2O2 has the highest amount of Trp oxidation (46%) but remains
colorless when degraded. Under UV light, at 1000 kLux·h and 5000
kLux·h, the sample become increasingly yellow with a longer UV
exposure. However, the total oxidation is less than half that seen
with H2O2 (20% and 13%, respectively). Using
the color changes reported previously in literature and the standard
spectra of the degradation products, we have assigned the peak shifts
to different degradation products of Trp. Our investigations show
that a decrease in the wavenumber at ∼885 cm–1 is indicative of Trp-OH (colorless), whereas an increase shows NFK
formation (yellow). These peak shifts have been further extended to
an investigation into the sensitivity of Raman to detect aggregates
where monomers and aggregates were separated by size. The Raman analysis
identified peak shifts at 885, 1121, and 1450 cm–1 attributed to Trp, C–N backbone, and C–H, respectively.
Both the Trp and C–H vibrations shift to a higher wavenumber
with increasing size and amounts of aggregates in the sample. The
C–N backbone shows a decrease in wavenumber from monomer to
more aggregates in the sample. Overall these findings suggest a backbone
structural change and a change of the environment to the Trp as protein
aggregates allowing for discrimination between samples. Biological
therapeutics often show only subtle changes or structural rearrangements
that are difficult to detect in such a large molecule. The development
of PAT testing for biological therapeutics is therefore complex and
difficult to implement. These results therefore provide the first
demonstration of the applicability and sensitivity of Raman spectroscopy
to detect structural changes in a range of force degraded mAbs. The
spectral characteristics attributed to these structural changes can
be exploited in developing in-line analytics for therapeutic mAb quality
control.
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