Abstract
Disulfide bond shuffling (DBS) critically influences protein
aggregation and stability, yet its spatial constraints and biological
implications remain poorly understood. Here, we demonstrate that
insulin undergoes DBS within an extended spatial range up to ~19 Å,
generating heterogeneous crosslinked oligomers that alter aggregation
pathway. While DBS products initially delay aggregation by inhibiting
primary nucleation and elongation steps, they ultimately promote the
formation of distinct fibrillar structures with enhanced β-sheet
content. Native ion mobility-mass spectrometry reveals molecular
crosstalk between DBS products and native insulin via both covalent and
non-covalent interactions. Notably, DBS-modified insulin fibrils
exhibit significantly increased neurotoxicity in neuronal and
pancreatic cells through mitochondrial apoptosis activation as
supported by proteomic and biophysical analysis. Our findings
underscore the importance of controlling DBS in insulin for therapeutic
applications and provide insights into the role of disulfide dynamics
in protein aggregation and cytotoxicity, with implications for insulin
and broader protein misfolding contexts.
Subject terms: Mass spectrometry, Protein aggregation, Proteomics,
Apoptosis
__________________________________________________________________
Researchers find that the shuffling of insulin’s disulfide bonds, while
initially slowing protein aggregation, ultimately forms distinct and
more toxic fibrils, providing key insights for therapeutic insulin
safety and protein misfolding diseases.
Introduction
Insulin, a protein characterized by its intricate disulfide bond
network, exhibits a propensity to aggregate under certain conditions.
This aggregation, often associated with loss of function and potential
cytotoxicity, presents a significant challenge in both therapeutic
applications and our understanding of protein misfolding diseases.
Accumulation of insulin amyloid-like proteins is frequently observed at
injection sites in type 2 diabetes patients, and in the brain has been
linked to the promotion of Tau protein accumulation, contributing to
neurodegenerative diseases^[40]1–[41]3. Additionally, Parkinson’s
patients show abnormally high levels of insulin oligomers in serum and
present potential therapeutic target against insulin
signaling^[42]4,[43]5. Generally, the formation of amyloid-like protein
fibrils involves several steps, including oligomers, protofibrils, and
mature fibrils^[44]6. Each form of insulin amyloid-like aggregation
exhibits distinct molecular conformations and varying degrees of
toxicity to neuronal cells^[45]7,[46]8. Understanding the intricate
mechanisms governing insulin aggregation and its associated
cytotoxicity, and developing strategies for disrupting its
oligomerization is crucial for mitigating these above-mentioned
challenges, including accelerating the onset of action of native
insulin in body^[47]9.
Insulin contains three disulfide bonds that play a crucial role in
maintaining its native structure and biological activity. Recent
research has highlighted the importance of disulfide bonds in protein
stability and aggregation propensity^[48]10,[49]11. In vivo, disulfide
bonds can reduce protein configurational entropy to stabilize proteins;
conversely, the absence of ordered crosslinking can lead to significant
diseases in organisms. In vitro, the proper formation of disulfide
bonds plays a decisive role in the efficacy of monoclonal antibody
drugs^[50]12. Changes in the physiological environment, such as
temperature, pH, and cascading reactions involving relevant enzymes
during disease progression, may disrupt disulfide bonds in insulin upon
dissociation.
Disulfide bond shuffling (DBS), a dynamic process of disulfide
interchange, has emerged as a significant factor in modulating protein
assembly and function^[51]13–[52]15. This phenomenon can lead to the
formation of various oligomeric states, potentially altering the
aggregation kinetics and the biological activity of proteins.
Importantly, disordered crosslinking of protein disulfide bonds has
been reported to promote the amyloid-like aggregation of native
proteins, potentially accelerating or exacerbating the onset of
diseases^[53]16. While numerous synthetic methods for disulfide bond
formation have been extensively reported^[54]17–[55]20, the manner of
bicarbonate heating^[56]21 offers an alternative for simple, fast, and
efficient formation of disulfide bonds, free of complicate chemistry
and multistep redox reactions. Prior research demonstrated that
bicarbonate buffer solutions facilitate crosslinking among protein
subunits through the formation of disulfide bond in a spatial
distance-constrained manner, where the attainable distance between two
cystines is likely confined to be ~9 Å, comparable to that of classic
amine-reactive crosslinkers^[57]21–[58]24.
In this study, we explore the potential of distance-constrained DBS on
regulating insulin aggregation and cytotoxicity. We employ a
combination of advanced ion mobility-mass spectrometry (IM-MS) and
other biophysical techniques, to elucidate the structural and kinetic
aspects of insulin oligomerization and aggregation under the influence
of disulfide bond dynamics. DBS was induced via gentle heating of
freshly reduced insulin in the presence of certain contents of ammonium
bicarbonate, featuring oxidative chemical-free creation of disulfides
in a spatial distance-constrained manner (Fig. [59]1a, b). Direct
evidence from native IM-MS have shown insulin DBS promotes the
formation of a variety of disulfide-crosslinked oligomers, facilitating
the noncovalent and covalent interactions between monomeric insulin and
DBS products. Our findings reveal that DBS-provoked molecular crosstalk
not only delays insulin aggregation via primarily targeting the primary
nucleation and elongation microscopic steps, but also exacerbates the
neurotoxicity of insulin amyloid aggregates in N2a, PC12 and PANC1
cells through selective upregulation and activation of the apoptotic
pathway (Fig. [60]1c). Understanding these mechanisms is crucial for
developing strategies to mitigate insulin aggregation, thereby
improving the therapeutic management of diabetes. Furthermore, the
implications of our findings extend beyond insulin, offering broader
perspectives on the role of disulfide bonds in protein aggregation and
cytotoxicity in various biological contexts.
Fig. 1. Disulfide bond shuffling (DBS)-provoked insulin crosstalk.
[61]Fig. 1
[62]Open in a new tab
a Bicarbonate heating as a spatial distance-constrained alternative to
induce disulfide bond shuffling. b Selected 3D structure models for
insulin DBS products predicted by AlphaFold, indicating the DBS working
distance ranging from 2 Å to ~19 Å. c DBS-provoked molecular crosstalk
between native insulin and DBS products delays insulin aggregation
likely through a distinct pathway of heterogeneous secondary
nucleation, leading to increased neurotoxicity via upregulation of the
apoptotic pathway in cells.
Results
Spatial distance-confined Insulin DBS
We previously have demonstrated the distance confinement for
bicarbonate heating-induced DBS products likely ranges from 2 Å (the
length for disulfide bond) to over 9 Å^[63]21. For insulin, the crystal
structure and primary structure with abundant disulfide sites clearly
supports the feasibility of this type of disulfide bond
shuffling^[64]25. Intriguingly, as shown by the selected 3D structure
models of DBS products from AlphaFold (Figs. [65]1b, [66]2a,
Supplementary figs. [67]1, [68]2), the attainable spatial distance for
DBS products has been effectively extended from 9 Å to ~19 Å, a value
significantly higher than that of previous report^[69]21. To
experimentally test the DBS of insulin, we first employed reducing
reagent TCEP to convert cysteine residues into free, highly reactive
thiol states. Distinct from our previous disulfide crosslinking within
nanoelectrospray microdroplets^[70]21, the insulin DBS in this study
was carried out in bulk solution with elevated incubation temperature
and extended reaction time to ensure the overall yield and to span the
attainable distance for DBS crosslinking (Figs. [71]1b, [72]2b).
Fig. 2. Bicarbonate heating-driven insulin DBS.
[73]Fig. 2
[74]Open in a new tab
a Primary structure of native human insulin. b Workflow for bicarbonate
heating-driven insulin DBS. c Characterization of insulin DBS products
with non-reducing, denaturing gel electrophoresis. Results in c were
validated through three independent experimental replicates,
establishing methodological reproducibility. d Representative IM-MS
heatmap and isotopic distribution for insulin DBS products (50 mM
bicarbonate, 50 °C, 4 h). Source data are provided as a Source Data
file.
SDS-PAGE images revealed that the number of high molecular weight bands
gradually increase along with prolonged heating of reduced insulin in
bicarbonate buffer (Fig. [75]2c, Supplementary figs. [76]3, [77]4),
indicative of the successful generation of a series of DBS products
with distinct crosslinking levels. Conversely, when the cysteine thiol
groups of reduced insulin chains were blocked with IAA, no bands for
DBS products were observed even with four-hour incubation. Similarly,
neither the reduced insulin without ammonium bicarbonate group nor the
intact insulin group showed high molecular weight bands. These
observations further demonstrate that ammonium bicarbonate solution
thermodynamically promotes disordered covalent reshuffling among free
thiols of insulin, leading to the reformation of disulfide bonds.
As a powerful tool for characterization of peptide and protein
oligomers^[78]26, native IM-MS was employed and tuned with optimal
conformation-resolving capability for capturing insulin DBS products.
Representative 2D IM-MS heatmap for insulin DBS products under the
intensive DBS condition (50 °C, 50 mM bicarbonate, 4 h), clearly
supports the presence of various degrees of thiol-crosslinked insulin
species (Fig. [79]2d). Accurate mass matching and charge state
assignments based on isotopic distributions for each species allow one
to reliably identify both the composition of subunits and the disulfide
numbers connecting these chains (Fig. [80]2d, Supplementary fig. [81]5,
Supplementary Table [82]1). Notably, ion mobility measurements further
confirm the identification of disulfide formation as indicated by the
shifts in their distinct drift time distributions for species with
varied thiol crosslinking degrees (Supplementary fig. [83]6).
Collectively, above-mentioned evidence has experimentally demonstrated
the effectiveness of spatial distance-confined DBS on the insulin
system with bicarbonate heating. The insulin disulfide shuffling
condition for subsequent exploration was also optimized (50 °C, 50 mM
bicarbonate, 4 h) based on the level of crosslinking products.
DBS delays insulin aggregation
As reported by previous microscopic and macroscopic-level
studies^[84]27–[85]37, insulin aggregation generally proceeds through a
series of microscopic steps: (1) destabilization of the native monomer,
exposing hydrophobic patches; (2) rate-limiting formation of oligomeric
nuclei via primary nucleation; (3) secondary nucleation, including
surface-catalyzed nucleation and fragmentation, accelerating the
aggregation; (4) elongation via monomer addition to fibril ends,
forming β-sheets and laterally associating protofibrils; (5) formation
of mature, twisted fibrils rich in cross-β structure. Notably, the
aggregation process of native insulin is highly concentration-dependent
and sensitive to environmental conditions such as pH, temperature, and
ionic strength, influencing both the kinetics and morphology of the
resulting fibrils, highlighting the complex nature of insulin
aggregation.
We firstly used ThT profiles to track the macroscopic processes of
insulin aggregation under agitation conditions. Data in Fig. [86]3a
clearly indicate the decreasing in lag time occurs with the increasing
of initial monomeric insulin concentrations. To further identify
microscopic steps underlying protein aggregation^[87]32–[88]34, we
plotted the half time of aggregation (t[1/2]) against insulin
concentrations and tentatively derived the linear dependence between
them upon exponent transformation (Fig. [89]3d). Surprisingly, a
negative curvature was observed from the half time-concentration
dependence curves for 0% DBS group using scaling exponents, suggesting
the presence of competition of multiple processes in parallel,
including primary nucleation, elongation and fragmentation-involved
secondary nucleation steps^[90]32,[91]33,[92]38. The presence of
multiple microscopic steps during insulin aggregation has been widely
acknowledged, featuring the primary nucleation and fragmentation
competing with well-adopted secondary nucleation pathway especially
under shaking conditions^[93]28,[94]29,[95]31–[96]33.
Fig. 3. DBS delays insulin aggregation.
[97]Fig. 3
[98]Open in a new tab
a Aggregation of native insulin with varied initial concentrations
(25 μM to 300 μM) monitored by ThT fluorescence. b Aggregation of
insulin in the presence of 1% (weight percentage) DBS products. c
Direct comparison of the aggregation behavior of insulin in the
presence of varied levels (0%, 0.1%, 1% and 10%) of DBS products.
Buffer conditions, 100 mM NaCl (HCl, pH 1.6); 50 °C, agitation at
200 rpm. d Log-log plots of the half time (t[1/2]) of aggregation in
different concentrations of insulin with or without 1% and 10% DBS
products. Data in (a–d) are presented as mean values +/- SD derived
from three biological replicates. Raw ThT curves for 10% DBS group were
shown in Supplementary fig. [99]7a. e CD and (f) ATR-FTIR measurements
of insulin fibrils with varied extents of DBS products. g AFM images of
insulin fibers at different time points during aggregation. Scale bar:
1 μm. h Distributions for height and length of insulin fibers.
Significance level is marked with an asterisk (p value was estimated
using the two-sided Wilcoxon test). Source data are provided as a
Source Data file.
To elucidate the specific molecular steps influenced by DBS products
during insulin aggregation, we performed a series of ThT fluorescence
monitoring experiments on solutions containing varied levels of DBS
products and 1 mg/mL native insulin (Fig. [100]3b–d). With 1% DBS
products, it was observed with apparently prolonged lag phase while
maintaining the half time-concentration dependence trends across the
tested concentration ranges of monomeric insulin (Fig. [101]3b,
Supplementary Table [102]2). Direct comparisons of ThT profiles for
insulin aggregation between with 1% DBS and without DBS group
throughout the concentration ranges (Supplementary fig. [103]7) suggest
that, DBS primarily affects insulin primary nucleation, as the lag
phase of the kinetic traces are prolonged by addition of the non-native
DBS products while the slope for the ThT traces seems to be not
significantly affected by 1% DBS products. Data with increasing DBS
levels show that, the final ThT fluorescence increases as a function of
the levels of insulin DBS products, featuring a fivefold elevation of
overall fluorescence for the 10% DBS group (Supplementary fig. [104]8).
However, when normalizing ThT fluorescence (Fig. [105]3c), we can
clearly observe the DBS-dependent prolonged lag phases and decreased
growth rates for the elongation and secondary nucleation steps, as
evidenced by the decreased ThT growth slopes and enlarged half time
values (0% DBS: t[1/2] = 12.42 ± 0.04 h, 0.1% DBS:
t[1/2] = 13.11 ± 0.05 h, 1% DBS: t[1/2] = 15.34 ± 0.04 h, 10% DBS:
t[1/2] = 18.96 ± 0.06 h; insulin, 172 μM). This type of microscopic
impact is likely linked to the inhibition of elongation
steps^[106]34,[107]38. Notably, even upon the addition of preformed
insulin fibrils to the aggregation samples (Supplementary fig. [108]9),
DBS continued to inhibit the aggregation rate of insulin, indicating
alterations at the microscopic level of the aggregation mechanism. When
fibrils were introduced into the insulin aggregation mixture
(Supplementary fig. [109]9), the presence of DBS products prolonged the
lag phase of aggregation to varying extents in a
concentration-dependent manner. Moreover, the growth rate of the ThT
fluorescence signal gradually decreased with increasing concentrations
of DBS products (Supplementary fig. [110]9). These observations suggest
that the influence of DBS on insulin aggregation extends beyond simple
primary nucleation. The persistence of this effect in seeded
experiments provides compelling evidence that elongation and/or
secondary nucleation processes are also affected. Additionally, the
observations of morphological changes in final aggregation
nanostructures (Fig. [111]3g, h) further imply that DBS may exert an
influence on the elongation and/or secondary nucleation process.
The variations in the scaling exponents in Fig. [112]3d are directly
linked to the impact of DBS on the aggregation kinetics of insulin. As
the scaling factor would be expected to be around 0.5 for purely
secondary nucleation pathway^[113]32,[114]33,[115]38, data in
Fig. [116]3d show significantly low values (~0.04) of scaling exponents
at low insulin concentrations ( < 100 μM), we observe significantly low
values (~0.04) for the scaling exponent. This near-zero scaling
suggests a weak dependence on monomer concentration, which can arise
from saturation within the composite steps of the aggregation process.
As previously detailed^[117]39, aggregation processes such as
elongation, secondary nucleation, and even primary nucleation can
exhibit multi-step mechanisms, often involving an initial
monomer-dependent step followed by a monomer-independent step.
Saturation of these monomer-dependent steps leads to a reduced
dependence of the overall aggregation rate on monomer concentration.
Fragmentation, by its nature, is already monomer-independent. When
multiple such saturated processes occur in parallel, scaling exponents
approaching zero can be observed. Therefore, the observed scaling
exponent of ~0.04 is consistent with a system where several aggregation
steps are operating near saturation, minimizing the dependence on
monomer concentration. The inhibition of insulin aggregation by DBS
products can be further observed at elevated insulin concentrations
(Supplementary fig. [118]10). Taken together, our findings demonstrate
that the DBS product modulates several microscopic stages in the
insulin aggregation pathway.
Next, we designed a series of experiments to explore the structural
impact of DBS products on insulin aggregation. The increase in β-sheet
structure is corroborated by CD spectroscopy (Fig. [119]3e), like
cryoEM structure evidence^[120]25, which confirms the presence of
β-sheet conformation of native insulin filament, the content of which
showing general dependency on the level of coexisting disulfide
cross-linked oligomers as demonstrated by the increased level of
negative peak at around 220 nm. ATR-FTIR data (Fig. [121]3f,
Supplementary Table [122]3) further demonstrated the increase in
β-sheet content upon addition of DBS products. Specifically, the
β-sheet level rises from 19.16% to 29.76% with the addition of 10% DBS
products. Considering the fact that DBS products alone do not form
observable fibrils (Supplementary fig. [123]11), which was seemingly in
line with previous observations on BSA and lysozyme^[124]16, we thus
suspect that insulin DBS products directly involve in native insulin
aggregation, presumably through unique molecular crosstalk between DBS
products and native insulin. In short, insulin DBS products delay the
microscopic steps of insulin aggregation presumably via targeting the
elongation process while enhancing β-sheet folding in insulin structure
(Fig. [125]3a–f), providing structural and kinetic basis for sequential
altering thermodynamic morphologies of the ultimate aggregation
nanostructures (Fig. [126]3g, h).
Given that we have identified the kinetically inhibitory role of DBS
products in native insulin aggregation as shown above, we next sought
to further investigate the potential impact of disulfide crosslinking
on the morphology of native insulin assembly nanostructures.
Representative AFM images in Fig. [127]3g show the morphological
changes of insulin nanostructures as formed in the presence of various
degrees of DBS products at distinct aggregation stages (7 h, 11 h,
14 h, 24 h). Firstly, all groups exhibited amyloid-like fibrillar
morphology except the group of 10% DBS at 7 h, the structure of which
we captured with evidence of amorphous aggregates. Compared to the 0%
group, the 10% group gradually formed longer, thinner fiber bundles
with prolonged aggregation time close to the final assembly stages.
Furthermore, at later assembly stages, varying degrees of disordered
cross-links of disulfide bonds were observed to reduce the height of
insulin fibers (Fig. [128]3h), significantly differentiating between
the 10% and 0% groups (p < 0.0001). However, concerning fiber length,
disordered cross-links of disulfide bonds facilitated the formation of
longer, thinner fibers (Fig. [129]3h), notably more pronounced in the
10% group compared to the 0% group (14 h, p < 0.0001). The
compositional heterogeneity of DBS products—featuring monomers,
oligomers, and co-aggregation-prone species—could modulate insulin
aggregation through multifaceted interactions with primary nucleation,
elongation, and secondary pathways, thereby diversifying the resultant
fibril polymorphs. These morphological changes in insulin fibers were
also evident in TEM experiments (Supplementary fig. [130]12). These
findings correlate well with the trends in the ThT-based aggregation
curves (Fig. [131]3c, Supplementary figs. [132]8–[133]10), where
disordered disulfide crosslinks effectively slow down the aggregation
process but enhance the final degree of insulin fibrillation.
Collective evidence from ThT, AFM, TEM, CD, and ATR-FTIR spectra have
thus pointed out a unique fibrillation pathway for insulin under the
influence of DBS products. Our data suggest that DBS products affect
processes beyond primary nucleation, such as elongation and/or
secondary nucleation. Notably, the presence of considerable degrees
(e.g., 10%) of DBS products might serve as a supplemental seed and
surface for heterogeneous primary and/or secondary nucleation and
downstream elongation, catalyzing the generation of finally enriched
cross-β fibrils. The current data resolution does not allow us to
definitively distinguish between the effects on these individual
processes.
DBS-insulin molecular crosstalk
The key to above-mentioned fibrillation pathway of heterogeneous
secondary nucleation and aggregation, notably, is the noncovalent
interactions and molecular crosstalk between DBS products and native
insulin molecules. To verify this putative molecular mechanism, we
conducted a series of native IM-MS experiments combined with tandem MS
activation by using the incubation sample of native insulin and freshly
reduced insulin. Representative MS spectra revealed significant
interaction peaks between reducing A/B chain and native intact insulin
for the incubation group compared to control groups of insulin alone
and A/B chain group (Fig. [134]4a). Accurate mass matching and isotopic
distribution examination confirm the presence of a series of DBS
products and noncovalent interacting complexes. For example, peaks at
m/z 1638.36 and m/z 1848.32 stand for noncovalent complexes between
insulin and the A (AB-A^5+) and B (AB-B^5+) chains, respectively.
Additionally, peaks at m/z 1143.58 (chain B with one disulfide bond),
m/z 1190.50 (chain A with one disulfide bond), and m/z 1810.06 (insulin
complexing with BB, AB-BB^7+) were observed. Conversely, no such
complex peaks were detected in the control groups (Fig. [135]4a).
Fig. 4. Molecular crosstalk between native insulin and DBS products.
[136]Fig. 4
[137]Open in a new tab
a Representative native IM-MS spectrum showing the noncovalent
interactions between monomeric insulin and DBS products. Insulin –
native, untreated group as a control (0.5 mg/mL); A/B – insulin treated
with TCEP (0.5 mg/mL); (Insulin + A/B) – the incubation group between
native insulin and TCEP reduction products. b Representative CID
spectrum for characteristic crosstalk products (AB-A/AB-B/AB-BB). c
Native IM-MS heatmap showing the disruption of native insulin
oligomerization with DBS products. Source data for (a, b) are provided
as a Source Data file.
To further ascertain the noncovalent interactions and the presence of
thiol crosslinking between chains, various tandem MS experiments were
performed in addition to collisional cross-section (CCS) measurements
for the differentiation of disulfide linkage isomer. Confirmation of
noncovalent interactions within a multichain complex relies on the
characteristic dissociation pattern of separating noncovalent subunits
at a relative gentle condition prior to the deep fragmentation of
protein backbones. For insulin-DBS complexes, as shown in Fig. [138]4b,
isolation and activation of putative noncovalent complexes [AB-A]^5+,
[AB-B]^5+ and [AB-BB]^7+ produce expected dominant ions for [AB], [A],
[B] and [BB] subunit chains at low collisional voltages ( < 30 V),
supporting the preferential stripping of noncovalent interactions among
these subunits. Quantification of dissociation products at various
voltages from these noncovalent complexes (Supplementary fig. [139]13)
further confirms the weak noncovalent interactions between intact
insulin [AB] and DBS products ([A], [B] and [BB]).
Survival yield curves for noncovalent [AB-A]^5+, [AB-B]^5+ and
[AB-BB]^7+ precursor ions feature a much steeper jump (precursor ion
intensity with changing ratio > 40%/10 V CID voltage) at certain
collision voltages compared to the control of covalent ion pairs
(Supplementary figs. [140]14, [141]15). Notably, the intensities of
[AB] and [BB] are significantly higher than that of [A] and [B] species
across all tested conditions (Fig. [142]4b, Supplementary
figs. [143]13, [144]14), suggesting the presence of covalent disulfide
crosslinking in [AB] and [BB] species that would require much higher
energy ( > 50 V) to break the covalent bridges and separate individual
[A] and [B] chains. Furthermore, we also performed a series of CCS
measurements for these noncovalent complexes, all of which show 3.2% to
8.4% increments in measured CCS values in comparison with their
covalent counterparts (Supplementary fig. [145]16). These observations
not only validated the successful DBS reactions of freshly reduced
insulin but also demonstrated the presence of complex interplay between
DBS products with native insulin through noncovalent and covalent
interactions.
Besides, native IM-MS was used to capture the self-assembly oligomers
of insulin and compare the impact of DBS products on insulin
oligomerization behavior. Representative heatmap (Fig. [146]4c) for
native insulin oligomerization present clear signal for dimer, tetramer
and hexamers, which are indispensable intermediates for insulin
fibrillation^[147]9,[148]25,[149]40,[150]41. Interestingly, larger
oligomers like tetramer and hexamer significantly diminished by the
incubation with both the freshly reduced insulin (A/B) and with mature
DBS products, albeit with slightly higher levels of small oligomers of
insulin observed upon mature DBS product treatment compared to freshly
reduced insulin chains (Fig. [151]4c).
Taken together, native IM-MS measurements and CID tandem experiments
have successfully enabled the validation of noncovalent and covalent
interactions between native intact insulin and DBS products, which is
vital for the elucidation of DBS-doped insulin aggregation pathway. We
thus suspect that, it is the molecular crosstalk induced via
noncovalent and covalent interactions between DBS and monomeric and
oligomeric insulin species during the primary nucleation step that
competing with the formation of native insulin hexamer for on-pathway
oligomerization, which potentially contributes to the delayed
aggregation process.
DBS enhances insulin neurotoxicity
Finally, we investigated the neurotoxicity induced by insulin fibers
with varying concentrations of disordered disulfide-linked aggregates.
Our findings demonstrated a concentration-dependent increase but varied
levels in neurotoxicity in mouse neuroblastoma (N2a) cells, rat
pheochromocytoma cells (PC12), and human pancreatic cancer cells
(PANC1) (Fig. [152]5a–c, Supplementary Table [153]4). Specifically,
insulin with increased DBS (10% DBS) showed significantly higher
neurotoxicity compared to control insulin (0% DBS) at various
concentrations, which was most pronounced at 50 μM in N2a cells and at
0.01 μM and 0.05 μM in PC12 cells (p < 0.001).
Fig. 5. Cytotoxicity and proteomic analysis of DBS-insulin cocktail.
[154]Fig. 5
[155]Open in a new tab
a–c MTT assay for the cellular viability of PC12, PANC1 and N2a cell
lines treated with insulin fibers. Significance level is marked with an
asterisk (p-values estimated using the Two-way ANOVA with multiple
comparisons test, *p-value < 0.05, **p-value < 0.01,
***p-value < 0.001, ****p-value < 0.0001, n = 5 biological replicates.
Error bars indicate SDs). d, e Western blotting images and
quantification of Bax/Bcl-2 associated with apoptotic N2a cells
(insulin, 50 μM). f, g Flow cytometric analysis and quantification of
N2a apoptosis (insulin, 50 μM). Significance level for (e, g) is marked
with an asterisk (p values estimated using two-sided unpaired t-test),
*p-value < 0.05, **p-value < 0.01. Data are presented as mean values
+/- SD derived from three biological replicates.). h Hierarchical
clustering analysis of 887 quantified proteins from label-free
bottom-up proteomics experiments. i Chord plot analysis of GO terms for
up-regulated proteins in the 10% DBS products group compared to control
group (no DBS treatment). Fisher’s exact test (one-tailed) with
Benjamini-Hochberg multiple testing correction was applied for GO term
enrichment analysis. Source data are provided as a Source Data file.
We further examined whether insulin fiber-induced neurotoxicity
involved the apoptosis pathway. Western blot analysis (Fig. [156]5d, e,
Supplementary fig. [157]17c, d) revealed a significant increase in the
Bax/Bcl-2 ratio in cells treated with 10% DBS insulin compared to the
control group (p < 0.01). This finding was further supported by flow
cytometry (Fig. [158]5f, g, Supplementary figs. [159]17a, b, 18), which
demonstrated a significantly higher apoptotic rate in the 10% DBS group
(p < 0.05).
Proteomic experiments with bottom-up LC-MS/MS setups identified 2,876
proteins, with 887 quantified (Fig. [160]5h, Supplementary
fig. [161]19a–d). Hierarchical clustering and Gene Set Variation
Analysis (GSVA) revealed functional alterations in protein expression
levels between groups. Pairwise comparisons identified differentially
expressed proteins, with 34 up-regulated and 68 down-regulated proteins
in the 10% vs Control group. GO and KEGG pathway analyses indicated
that up-regulated proteins were involved in energy metabolism,
mitochondrial membrane permeability alteration, apoptotic pathways, and
neurodegenerative diseases (Fig. [162]5i, Supplementary
fig. [163]19e–g, Supplementary fig. [164]20). Down-regulated proteins
were associated with protein-containing complex assembly regulation,
cell meiotic division cycle, protein catabolic process regulation, and
DNA geometric and conformational changes (Supplementary fig. [165]21).
In the 10% vs 0% and 0% vs Control groups, GO and KEGG enrichment
analyses revealed unique and shared pathways related to organelle
functions, protein metabolism, cholesterol synthesis and metabolism,
oxidation-reduction processes, and neuronal cell vesicle transport
(Supplementary figs. [166]22–[167]26).
In summary, our study provides compelling evidence that DBS in insulin
enhances its aggregation propensity, leading to increased neurotoxicity
via the induction of mitochondrial apoptosis. These findings highlight
the importance of controlling DBS during insulin production and storage
to minimize potential risks associated with neurotoxicity.
Discussion
This study provides insights into the impact of DBS on insulin
aggregation and its associated neurotoxicity. Our findings demonstrate
that DBS products significantly alter the aggregation pathway of
insulin, leading to the formation of morphologically distinct fibrils
with enhanced neurotoxic properties. We demonstrate that DBS in insulin
occurs within a spatially confined regime, likely facilitated by the
close proximity of cysteine residues within the insulin structure. This
process generates a heterogeneous mixture of disulfide-crosslinked
insulin oligomers, which exhibit a unique molecular crosstalk with
native insulin molecules. This crosstalk, evidenced by native IM-MS and
tandem MS analysis, disrupts the formation of native insulin hexamers
and delays the overall aggregation kinetics. Despite the delayed
kinetics, DBS ultimately enhances insulin aggregation, leading to the
formation of longer, thinner fibrils enriched with β-sheet content.
These observations demonstrate the primary inhibition of nucleation and
secondary inhibition of elongation steps during insulin aggregation
microscopic steps induced by the addition of DBS products.
Importantly, our study highlights the significant biological
implications of DBS in insulin. We demonstrate that insulin with
increased DBS exhibits significantly enhanced neurotoxicity in various
cell lines, including neuronal and pancreatic cells. This enhanced
toxicity is attributed to the induction of mitochondrial apoptosis,
evidenced by increased Bax/Bcl-2 ratios and apoptotic rates in cells
treated with DBS-rich insulin. Proteomic analysis further supports the
apoptotic mechanism, revealing the upregulation of proteins associated
with energy metabolism, mitochondrial membrane permeability, and
apoptotic pathways in cells exposed to DBS-rich insulin. Additionally,
we observed the downregulation of proteins involved in cell cycle
regulation, protein metabolism, and neuronal vesicle transport,
indicating a global cellular response to DBS-induced insulin
aggregation.
Many prior reports have explored the general principles of protein
aggregation and the influence of molecular chaperones and non-native
protein structures on amyloid
formation^[168]30,[169]33,[170]34,[171]42–[172]44. However, this study
advances beyond these general principles by directly examining the
implications of DBS in insulin for human health. Our findings might
bear significant implications for insulin production, storage, and
therapeutic applications, as similar DBS products can also be observed
in more clinically relevant buffer conditions (Supplementary
fig. [173]27). However, it is important to emphasize that a reducing
environment is a prerequisite for the formation of these species, as
demonstrated by the critical role of DTT in Supplementary fig. [174]27.
While reducing conditions are not typically maintained during standard
insulin storage or therapeutic use, they can arise in specific
contexts, such as during certain manufacturing processes, stability
testing, or in localized physiological environments. Additionally, our
data show that increased temperature accelerates DBS formation, but
these reactions can also occur at lower temperatures, including those
close to room temperature. These observations highlight the potential
relevance of our findings to real-world scenarios, while also
underscoring the importance of considering the specific environmental
conditions under which DBS formation may occur.
Specifically, the bicarbonate buffer and temperature ramping settings,
although distinct from typical insulin formulations, offer a controlled
environment relevant to challenging industrial conditions (e.g.,
fluctuating temperatures in hot climates or emergency settings) that
might promote the formation of DBS products^[175]33,[176]45,[177]46.
The current experimental design simply accelerates the reactions,
enabling observation and characterization of the DBS process and its
effects within a feasible experimental timeframe. Consequently, our
study suggests that controlling DBS during these processes is crucial
to minimize the formation of neurotoxic aggregates. Further research is
warranted to develop strategies to inhibit DBS in insulin and mitigate
its potential risks. This study provides a framework for understanding
the complex interplay between protein misfolding, aggregation, and
neurotoxicity, paving the way for the development of safer and more
effective protein therapeutic biosimilars more than the native insulin
system.
Methods
Chemicals
Human insulin standard was purchased from TargetMol Co., Ltd.
(Shanghai, China). Analytical grade ammonia bicarbonate (NH[4]HCO[3])
was obtained commercially from RHΛWN reagent (Shanghai, China).
Thioflavin T (ThT), Tris (2-carboxyethyl) phosphine (TCEP), and
iodoacetamide (IAA) were purchased from Sigma-Aldrich (St. Louis, MO).
Dithiothreitol (DTT) and BCA assay kit were provided commercially from
Beyotine Biotech Co., Ltd. (Shanghai, China). Purified water
(resistivity of 18.2 MΩ.cm) was obtained from a Milli-Q® Reference
System (Millipore Corp., Bedford, MA, USA). The peptide quantitation
analysis assay kit was commercially achieved from ThermoFisher
(Pittsburgh, PA, USA). Trypsin and LysC were purchased from Beijing
Shengxia Proteins Scientific Ltd. (Beijing, China). Annexin V-FITC/PI
apoptosis detection kit was purchased from Dalian Meilun Biotechnology
Co., Ltd. (Dalian, China). Anti-Bcl-2 antibody and anti-Bax antibody
were obtained from Abcam Trading Co., Ltd (Shanghai, China).
Mouse-β-actin antibody was provided commercially by Beyotine Biotech
Co., Ltd. (Shanghai, China). Goat anti-rabbit IgG, goat anti-mouse IgG
and horseradish enzyme tags were purchased from Beijing Zhongshan
Jinqiao Co., Ltd. (Beijing, China). Fetal bovine serum (FBS) and
Dulbecco’s modified Eagle’s medium (DMEM) were purchased from Gibco
(Carlsbad, CA). The mouse neuroblastoma N2a cell line (N2a), Rat
adrenal medullary pheochromocytoma cell line (PC12) and human
pancreatic cancer cell PANC1 were obtained from the American Type
Culture Collection (Manassas, VA).
Insulin disulfide bond shuffling
Firstly, native insulin was reduced through adding 20 mM TCEP to the
stock solution, where the final reaction concentration of insulin is
0.5 mg/mL. After 1 h incubation under room temperature, the disulfide
bonds of insulin were completely reduced. Subsequently, Sep-Pak C18
(Waters) was utilized to eliminate TCEP. Vacuum concentration dryer
condensed into A/B chain powder. The powder of mixed A/B chain was
redissolved in 0, 5, 10 and 50 mM ammonium bicarbonate buffer,
respectively. The total concentration of A/B chain was 1 mg/mL. The
solution was then heated at 50 °C for 0, 0.25, 0.5, 1, 2 and 4 h to
facilitate disordered cross-linking of the disulfide bonds between A
and B chains. Meanwhile, parallel preparation of 5 mM IAA blocked A/B
chain (1 mg/ml) sulfhydryl group and the intact insulin group. The
mixed of A/B chain with IAA was incubated at room temperature and dark
for 2 h.
Predicting DBS products with AlphaFold3
To predict potential disulfide bond formation between segments of
insulin peptides, we employed the AlphaFold3 structure prediction
tool^[178]47. The crystal structure of human insulin was obtained from
the Protein Data Bank (PDB ID: 1A7F), corresponding to UniProt entry
[179]P01308. The amino acid sequences of the A and B chains were
extracted as follows: A chain, GIVEQCCTSICSLYQLENYCN; B chain,
FVNQHLCGSHLVEALYLVCGERGFFYTPK. All cysteine residues in both chains
were maintained in their reduced state, with free thiol groups. Under
the “Protein” input type option, the sequences of the A and B chains
were entered in various combinations into the input fields, and
separate predictions were generated. The resulting structural models
were downloaded in.cif format for further analysis. The model was
obtained by AlphaFold3 on July 18, 2024. We assessed the confidence of
the predicted structures using the predicted Local Distance Difference
Test (pLDDT) scores provided by AlphaFold. Our analysis of cysteine
proximity primarily focused on residues within regions pLDDT scores >
70. To evaluate the potential for disulfide bond formation, we used
PyMOL to measure inter-cysteine distances within the predicted
structures. Thiol-thiol distances were analyzed to identify spatial
arrangements conducive to DBS formation, providing insights into the
structural feasibility of such interactions. It is important to note
that this in silico analysis provides a preliminary assessment of
potential disulfide bond formation and does not definitively confirm
the presence of such bonds. Further experimental validation, like
native IM-MS measurements shown in this study, is required to confirm
these predictions.
Non-reducing denaturing gel electrophoresis
Take 10 μL of samples incubated at each time point in the above groups
and boil 5 min at 2 × 10 μL loading buffer, 95 °C for electrophoretic
analysis. Loading buffer (2×) contains 100 mM Tris, 30% glycerol, 0.1%
bromophenol blue, SDS 4%, and lacks disulfide reducing agents such as
DTT. The anode Buffer contains 200 mM Tris, pH 9.0, the cathode buffer
is 100 mM Tris, 52.7 mM Tricine and 3.47 mM SDS, pH 8.25. The boiled
samples of each group with 10 microliters were added to the
concentrated glue channel and samples were separated by sodium dodecyl
sulfate polyacrylamide gel electrophoresis (SDS-PAGE). All
electrophoresis experiments were conducted at 100 V for 20 min through
the stacking gel and at 150 V for 60 min through the separating gel.
The gels were stained with Coomassie blue stain, and the image was
acquired using a scanner.
ThT fluorescence assays
Monomeric insulin (1 mg/mL) and cross-linking (0.1%, 1%, 10%) were
incubated alone or together in 100 mM NaCl buffer (HCl, pH 1.6) to
study the impact of disulfide cross-linking disorder on insulin
aggregation. In addition, to investigate the nucleation mechanism of
disordered disulfide cross-linked aggregates on insulin aggregation,
insulin at different concentrations was co-incubated with disordered
disulfide cross-linked aggregates at varied levels in 100 mM NaCl
buffer (HCl, pH 1.6). All samples of each group were incubated in the
metal bath at 50 °C for 200 rpm for a certain time. Each group of
samples was taken 3 µL at intervals of 1 h and put into a black 96 well
plate, and then 200 μL of ThT (10 μM) solution was added to incubate
for 10 min. ThT fluorescence measurements were carried out on a
multifunctional microplate reader (Molecular Devices Co., Ltd.) at the
excitation/emission wavelength of 430/490 nm. The signals from the
sample wells were corrected by subtracting the signal from the blanked
wells containing the buffer and ThT but no sample. All reactions were
performed with three replicates. All data were plotted using GraphPad
Prism 6.01, with the mean and SD (SD, n = 3) of the mean displayed as
points and connecting lines with error bars. The aggregation curves
were fitted by Boltzmann Sigmoidal model.
Circular Dichroism Spectroscopy (CD)
The CD spectra were recorded in the region from 190 to 260 nm on a
Biologic MOS-500 spectrometer. All spectra were recorded with a
wavelength interval of 1.0 nm and an acquisition time of 1 s. CD
samples with a concentration of 0.1 mg/mL were prepared by diluting
from the stock solution of the insulin fiber.
Attenuated Total Reflection Fourier-Transform Infrared Spectrophotometer
(ATR-FTIR)
The secondary structure of fibrils formed after insulin aggregation in
different groups was analyzed using ATR-FTIR (ThermoFisher Scientific
Nicolet iS50). Following established protocols, all ATR-FTIR samples
were centrifuged at 14,000 x g for 15 min at 4 °C after aggregation,
and the supernatant was discarded. The resulting pellets were
resuspended in D[2]O, thoroughly mixed, and washed three times to
eliminate residual salts or aggregation buffer. Peak deconvolution and
curve fitting in the 1600–1700 cm^−1 range were performed using OMNIC
software (version 8.3). The deconvoluted peaks were further processed
via second derivative analysis and numerical fitting using Peakfit
software (version 4.12), with the iteration threshold set to 0.07 and
an R² value greater than 0.99. The peak areas corresponding to specific
secondary structure components were then extracted for statistical
analysis.
Atomic Force Microscopy (AFM)
AFM images were taken by the BenYuan instrument under the tapping mode.
Dilute all sample (Insulin fiber) solutions to 0.1 mg/mL with deionized
water. 10 μL of the diluted sample on a clean mica slide. Allow it to
stand at room temperature for 20 min, then the retained liquid on the
mica surface was removed by filter paper. Conduct experiments after the
mica slide has dried at room temperature.
Transmission Electron Microscope (TEM)
TEM images were taken by a Tecnai G2 F20 microscope with an
accelerating voltage of 200 kV. TEM samples of all the insulin fiber
were prepared by diluting the stock solution to a concentration of
0.1 mg/mL. A volume of 10 µL of the diluted solution was pipetted onto
the surface of a carbon-coated copper grid for 10 min and removed by
filter paper. After that, the droplet was removed with filter paper.
The grid was dried in the fume cupboard before measurement.
Native IM-MS
The disulfide bond cross-linked samples of each group for 4 h were
diluted to an appropriate concentration with 10 mM ammonium acetate
buffer, and the dilution multiple was consistent among the samples of
each group. Approximately 8 μL sample was loaded into a homemade
nanospray source and MS instrument was run in positive ion mode to
represent the reformation of inter-chain disulfide bonds between the A
and B insulin chains. To investigate the interaction between insulin
and disordered disulfide bond crosslinked or free A/B chains during
aggregation, solutions of 1 mg/mL insulin and 1 mg/ml A/B chains or DBS
products were separately prepared. In the experimental group, equal
volumes (25 μL) of these solutions were mixed, and control groups
received 25 μL of deionized water each. The samples were subjected to
2 min of sonication at room temperature (300 W), following a 1-hour
equilibration period at room temperature before analysis. All reactions
were performed with three replicates. Nanospray voltages range between
1.0 ~ 1.8 kV and the sampling cone was used at 50 V. All IM-MS data
were collected using Waters Synapt XS instruments. The MS cone
temperature was 75 °C. The traveling-wave ion mobility separator was
operated at a pressure of ∼2.85 mbar, and DC voltage waves (40 V wave
height, traveling velocity of 700 m/s) to generate ion mobility
separation. The CCS calibration was carried out with Insulin, Melittin,
Bradykinin and Bovine Serum Albumin with mass ranges of m/z 100 ~ 5000.
Each sample was prepared three replicates and obtained stable and
reproducible signal. CCS calibration curves were generated using a
previously described protocol^[180]48, and using literature CCS values
with nitrogen (He) derived for use with the Synapt instrument platform.
To improve the accuracy, in our study, we have employed an updated
calibration method^[181]48 for CCS measurements. Similar to previous
studies^[182]49–[183]51, triplicate measurements were taken to obtain
uncertainty values using the following equation:
[MATH: Tota Uncertainty=σ2+ca
l_error2+data
base_er<
/mi>ror2
:MATH]
1
where σ is the relative standard deviation of triplicate measurements
(was 0.58%), cal_error is the uncertainty range for CCS calibration
(was 0.27%), and database_error is the uncertainty in database values
(set as 0.3%). The total uncertainty for TWIMS CCS of insulin is thus
estimated to be ~0.71%. All IM-MS data were processed using the
MassLynx v4.2 and Driftscope software affiliated with the instrument.
Cell culture and cytotoxicity assay
N2a (mouse neuroblastoma) and PC12 (rat pheochromocytoma) cells serve
as established neuronal and neuroendocrine models, respectively, with
well-characterized responses. These cell lines were used to assess
neurotoxicity via MTT assays and cellular responses to protein
aggregates using western immunoblotting for apoptotic markers. In
addition, PANC1 cells (human pancreatic cancer) were selected to
investigate potential pathological implications of insulin aggregation
in its native environment. Given that insulin transitions from a
hexameric storage form to monomers upon secretion, we hypothesized that
this physiological transition could, under pathological conditions,
increase the risk of amyloid aggregation and subsequent cytotoxicity
within pancreatic tissue. PANC1 cells allowed us to explore this
hypothesis using cell viability assays.
MTT assays were performed on PC12, N2a and PANC1 cells and was utilized
to test the cytotoxicity induced by insulin aggregates. In the presence
of 10% FBS and 1% penicillin/streptomycin, PC12, N2a and PANC1 cells
were cultured in a sterile DMEM medium at 37 °C in a humid atmosphere
with 5% CO[2]. The three kinds of cultured cells were inoculated in 96
well plates with a density of 5 × 10^3 cells/well and incubated for
24 h (n = 5). Insulin fibers of each group in the plateau stage were
dialyzed with sterilized PBS solution for 12 h. After that, it was
concentrated to an appropriate volume and diluted to the required
concentration with PBS (cell culture grade). The initial monomeric
insulin concentrations (10, 25, and 50 µM for N2a; 0.005, 0.01, and
0.05 µM for PC12; and 0.5, 1.0, and 5 µM for PANC1) were determined
using a NanoDrop spectrophotometer (Nano-300, Hangzhou Allsheng
Instruments Co., Ltd), measuring absorbance at 280 nm. These
concentrations were chosen based on preliminary cell viability assays
to ensure that the monomeric insulin itself did not induce significant
cytotoxicity before fibril formation. All insulin fibers were incubated
with cell lines for 24 h. Subsequently, MTT solution (10 μL, 5 mg/mL)
was added to each well and incubated for 4 h. To dissolve the formazan
crystals, DMSO (200 μL) was added to each well after removing the
medium. The absorbance at 570 nm and 690 nm were measured using a
microplate reader (Molecular Devices Co., Ltd.), and cell viability was
calculated accordingly. Measure the relative viability (RV) by
following formula:
[MATH: CellViability=ODSample−ODBlank
controlODNegative
control−ODBlank
control*100% :MATH]
2
Western blot analysis
Protein lysates were prepared from N2a and PC12 cells treated with
insulin fiber. Protein concentrations were measured using a BCA kit,
and the absorbance was measured at 562 nm using a miniature flat-panel
reader. Equal amounts of protein samples were separated by
electrophoresis and transferred to polyvinylidene difluoride (PVDF)
membranes. Subsequently, the PVDF membrane was blocked with 5% skimmed
milk powder (1 h, room temperature), followed by overnight incubation
at 4 °C with primary antibodies anti-Bax (1: 2000), anti-Bcl-2 (1:
2000), and β-actin (1: 3000). The membrane was washed with TBST and
then incubated with secondary antibodies at room temperature for 1.5 h.
Finally, protein bands were detected using Azure C600 (Azure
Biosystems, USA) instrument, and the density of each band was analyzed
using ImageJ (version 1.54) software.
Flow cytometric analysis
PC12 and N2a cells were seeded in the 6-well plates with a density of
8 × 10^5 cells/well. After adherent growth, 0.005 and 50 μM insulin
fibers were added to the cell culture plate and incubated for 24 h. All
experiments were performed with three replicates. The above cells were
washed with PBS three times and digested with trypsin without EDTA.
Staining the cells with Annexin V-FITC and PI for 10 min in the dark
led to the samples for cellular apoptotic studies estimated by a flow
cytometer (BD LSR Fortessa, USA) and analyzed by FlowJo software
(version 10.10)
Sample preparation for proteomics
N2a cells were lysed in lysis buffer containing 8 M urea, 50 mM
Tris-HCl, 5 mM CaCl[2], 30 mM NaCl and protease inhibitor (v/v, 1:100),
and add appropriate amount of HCl to adjust pH 8.0. Each sample was
prepared in triplicate. Then use probe sonicator to extract proteins
from cells, and further centrifuge at 14,000 x g for 15 min. Perform
protein assay according to the instructions for BCA Reagent Kit
manufacturer’s protocols. According to the measured protein
concentration, take a certain volume of supernatant containing 100 μg
of protein for subsequent experiments. The protein extract was reduced
with 10 mM DTT at 37 °C for 30 min and then alkylated with 50 mM IAA
for another 30 min in the dark. Add DTT again to a final concentration
of 10 mM to react with excess IAA and incubate at room temperature for
5 min. All samples were subjected to digestion with LysC and trypsin
(w/w, 1:100) and incubated at 37 °C for 4 h. Add tris buffer to dilute
urea to <1 M, and incubate at 37 °C overnight. The samples were
quenched with 10% TFA to a final concentration of 0.25% and centrifuged
at 14,000 x g for 15 min. Desalting the supernatant using Sep-Pak C18
(Waters) according to the manufacturer’s protocols and dry down the
sample. Resuspend samples with an appropriate volume of 0.1% formic
acid (FA)-H[2]O, centrifuge at 14,000 x g for 10 min. Determine the
peptide concentration of the supernatant using an assay kit and aliquot
an appropriate number of samples for LC-MS/MS analysis.
LC-MS/MS analysis for proteomics
Samples were analyzed on an Orbitrap Eclipse Mass Spectrometer
(ThermoFisher Scientific, Waltham, MA) coupled to a Dionex UltiMated
3000 UPLC system. Each sample was dissolved in 0.1% FA-H[2]O before
loading onto a 75 µm inner diameter NanoViper microcapillary column
that is packed with 25 cm of bridge Ethylene Hybrid C18 particles
(2 µm, 100 Å, ThermoFisher Scientific). Mobile phase composed of 0.1%
aqueous formic acid (A) and ACN containing 0.1% formic acid (B) was
pumped into homemade microcapillary column with a gradient program as
below: 0−20 min, 3%−15% B; 20−90 min, 15%−30% B; 90−105 min, 30%−45% B,
105−110 min, 45%−95% B, 110−120 min, 95% B; and flow rate, 300 nL/min.
The injection volume was fixed at 3.0 μL. The instrument was run in
data-dependent acquisition (DDA) mode, capturing survey scans of
peptide precursors in the m/z range of 300 to 2000 using the orbitrap
(OT) with a resolution of 120,000. Subsequently, MS/MS acquisition was
performed in the orbitrap (OT). The automatic gain control (AGC) target
for both MS1 and MS2 was set to Standards. Precursors underwent
fragmentation continuously for 3 s, with stepped normalized collision
energies of 25, 30, and 35. Maximum injection times were defined as
50 ms for MS1 scans and Dynamic for MS2 scans. A dynamic exclusion
period of 45 s, with a tolerance of 10 ppm, was applied to the
precursors. All acquisitions were conducted in positive polarity mode,
and a critical step was the prior equilibration of each sample before
injection.
Data analysis
Protein identification and quantification were conducted through
MaxQuant (version 2.5.2.0)^[184]50 with Uniport Mus Musculus reviewed
database (May 19, 2024) with trypsin/P as selected enzymes. Notably,
MS1 scans utilized a precursor ion mass tolerance of 10 ppm and allowed
for two missed cleavages. A false discovery rate (FDR) of 1% was
applied for both protein and peptide identification via the target
decoy strategy. Specific modifications, including carbamidomethyl of
cysteine residues, oxidation of methionine residues, and acetylation at
protein N-termini, were considered during analysis. Statistical
analysis involved filtering for reverse proteins, site-specific
proteins, and potential contaminants using Perseus (version 1.6.7.0).
To address individual expression variations, proteins detected <2 times
in one group were filtered post-grouping. Missing data points were
imputed using the normal distribution method with specified parameters.
Subsequent statistical analyses, including two-sample Student’s t-test
and one-way ANOVA, were performed, with p-values adjusted using the
Benjamini-Hochberg method. Visualization techniques such as
hierarchical clustering and volcano plots were generated using R
packages and Hiplot Pro online software. For protein intensity
profiling, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and
Genomes (KEGG) pathway enrichment analysis were conducted through R
packages. PPI analysis was accomplished on the STRING online website,
and Cytoscape 3.9.1 software was used to analyze PPI network nodes.
Reporting summary
Further information on research design is available in the [185]Nature
Portfolio Reporting Summary linked to this article.
Supplementary information
[186]Supplementary Information^ (3.7MB, pdf)
[187]Reporting Summary^ (245.3KB, pdf)
[188]Transparent Peer Review file^ (3MB, pdf)
Source data
[189]Source Data^ (12.8MB, xlsx)
Acknowledgements