Radical footprinting in mammalian whole blood

Domain: neuroscience
Published: 2026-02-07
Editorial outcome: major_revision

Abstract
Hydroxyl Radical Protein Footprinting is a powerful tool to probe protein higher-order structure, protein-protein and protein-ligand interactions. It is mostly performed in vitro, but recent advances have extended its use to live cells, nematodes, and 3D cultures. However, to the best of our knowledge, application in living mammalian tissues has not been accomplished. Here, we present the successful use of radical protein footprinting (RPF) in mammalian whole blood from wild-type and type 2 diabetes mellitus (T2DM) mice. Using persulfate photoactivated with the FOX Photolysis System, we achieve effective protein labeling without significant disruption to blood cell morphology. An optimized quenching protocol eliminates background labeling. We report oxidative modifications for the eleven most abundant proteins detected, revealing disease-associated conformational changes in multiple proteins. We validate that in-blood RPF identifies changes in protein structure resulting from complement activation and increased transferrin iron saturation in T2DM mice. These findings demonstrate the feasibility of RPF in mammalian blood and create opportunities for structural proteomics in preclinical models and clinical samples.

Introduction
The biological function of a protein is determined by its higher order structure (HOS)1. Characterizing protein HOS in their native environment is essential for understanding their function, but this remains challenging in complex mammalian biological samples.

Hydroxyl radical protein footprinting (HRPF), as originally reported by Chance2 has become a powerful structural biology approach for elucidating protein HOS. Hydroxyl radicals (•OH) generated in situ diffuse to the protein surface, covalently modifying amino acid side chains at a rate proportional to their average solvent accessible surface area3,4. The amount of oxidation at each site is measured by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), generating a protein footprint. Alterations in the protein footprint under different conditions reflect changes in the protein HOS5. HRPF can probe protein dynamic conformational changes6–8, protein-protein and protein-ligand interactions6–8, and the conformational consequences of post-translational modifications9. Most recently, HRPF has been introduced to facilitate protein HOS analysis in vivo in living systems, including cancer spheroids10 and nematodes11.

Despite these advances, to the best of our knowledge, HRPF has not been demonstrated in any mammalian tissue, including blood, due to barriers like UV absorption by solid tissues. Another major technical hurdle to the implementation of HRPF in blood is the high concentration of catalase, which rapidly decomposes H2O2 (the predominant hydroxyl radical precursor for HRPF) before photolysis and •OH generation. For radical protein footprinting (RPF) to be achieved in blood, catalase must be inhibited, or an alternative radical precursor must be employed. The sulfate radical anion (SO4−•) generated by direct photolysis of persulfate was demonstrated for RPF by Gau and co-workers in 2010 and generates a protein footprint strikingly similar to that of •OH, possibly through a mixed sulfate and hydroxyl radical mechanism12. Although persulfate was recently employed for in-cell RPF in HEK293 cells13, it remains poorly characterized for use in RPF. As far as we are aware, no dosimetry method exists for SO4−• footprinting, which would detect and normalize the effective radical dose across replicates. Further, previous studies have photolyzed persulfate using custom excimer laser set-ups, which complicate standardization for clinical and many pre-clinical applications.

Here, we report the use of sodium persulfate for the RPF of mammalian whole blood, using the biomedically relevant system of T2DM (BKS. Cg Dock7m +/+ Leprdb/J; Homozygous for Leprdb; db/db) mouse model as illustrated in Fig. 1. We introduce SO4−• RPF with the Flash Oxidation (FOX) Photolysis System, a commercially available, standardized system that uses a broadband UV flash lamp14. We demonstrate both a real-time radical dosimetry system for in vitro SO4−• RPF as well as an effective secondary oxidant quench scheme that eliminates background oxidation from the RPF process as illustrated in Supplementary Fig. 1. Using this workflow, we successfully perform RPF in whole murine blood, and oxidatively modify extracellular proteins. Comparison of protein footprint in non-diabetic, wild type (WT) mouse (BKS. Cg-Dock7m +/+ Leprdb/J; Heterozygous for Leprdb, Heterozygous for Dock7m) to our T2DM model murine blood reveals disease-associated protein conformational changes in two of the eleven proteins analyzed. We demonstrate that these conformational changes detected by our in-blood SO4−• RPF approach are consistent with complement activation and increased transferrin (Tf) iron saturation in T2DM condition by measuring circulating complement C3 and its activated product (C3b) as well as serum iron and Tf iron binding capacity. Finally, we show that in-blood RPF accurately reflects protein topography by comparison with in vitro footprints of purified protein. This work opens powerful possibilities using RPF to investigate protein HOS in complex biological matrices, particularly whole blood, with potential applications in identifying molecular mechanisms underlying protein therapeutic efficacy, detection of conformational biomarkers of disease, and discovery of drug targets, among a myriad of biological and pharmaceutical applications.

Results
Selection of a stable radical precursor for whole blood
Most previous cell-based and in vivo radical footprinting experiments have used hydrogen peroxide-based FPOP for fast radical generation10,15. However, blood notably displays high catalase activity16, which complicates the use of hydrogen peroxide as a radical precursor. We tested four catalase inhibitors to determine if catalase and/or peroxidase activity in whole blood could be sufficiently reduced without altering the gross physiological properties of the blood sample. We also assessed gas generation in blood from Na2S2O8, previously utilized for in-cell FPOP13. Of the four inhibitors, hydroxylamine was the most effective, with a 95% reduction in catalase activity at 200 mM concentration, 5:1 v/v blood to inhibitor stock, and room temperature, as seen in Supplementary Fig. 2a. Thiosemicarbazide (TSC) and hydroxylamine induced gross changes in blood coloration and constitution, clearly disrupting the native blood environment. At a more physiologically relevant 20:1 v/v, substantial catalase activity remained. Importantly, none of the four inhibitors prevented foam generation in the blood at concentrations compatible with physiological conditions. Barring the identification of some other effective inhibitor, HRPF is likely not feasible in whole blood with H2O2 as a radical precursor. Conversely, when Na2S2O8 was spiked into blood at final 200 mM concentration as shown in Supplementary Fig. 2b, c, no gas generation or gross changes in blood properties were observed. Additionally, a key advantage of Na2S2O8 is the absence of intrinsic signaling activity within cells. In contrast, hydrogen peroxide presents a limitation due to its established involvement in intracellular signaling pathways that can elicit biological responses13. Therefore, Na2S2O8 was used for all in-blood RPF experiments.

Photoactivation of Na2S2O8 using the FOX system
The peroxydisulfate bond of Na2S2O8 enables efficient photochemical cleavage to generate potent, fast-reacting sulfate radicals under RPF laser conditions, whereas sulfate ions cannot be directly photoactivated to sulfate radicals at convenient wavelengths17–19. While RPF has been reported using Na2S2O8 with a KrF excimer laser12,13, Na2S2O8 has not been documented as an effective radical precursor using the FOX Footprinting system. We tested whether Na2S2O8 could be effectively photoactivated by the FOX flash lamp and whether the inline adenine dosimetry was compatible with SO4−• RPF in vitro. Dosimetry results are presented in Fig. 2. When adenine is oxidized, the loss of UV absorbance signal at 265 nm allow effective measurement of the radical generation and scavenging. As sulfate and hydroxyl radicals are broadly reactive and can be consumed by solutes like buffers and excipients20, real-time dosimetry allows for compensation to ensure that analytes receive equivalent radical doses21–23. Accordingly, we examined the relationship between in-line UV absorbance of 1 mM adenine and sulfate radical effective dose under various conditions.

Adenine dosimeter response was assessed first in response to an increase in the effective radical dose, achieved via increased light fluence as modulated by flash voltage. Abs265 decreased from ~140 to ~116 mAU as lamp voltage was increased from 600 to 900 V in the presence of 50 mM persulfate (Fig. 2a), indicating an inverse relationship between adenine absorbance and effective radical dose, similar to that observed with hydroxyl radicals. Adenine dosimetry obtained with varied radical precursor concentrations, however, is confounded by the intrinsic Abs of Na2S2O8. Thus, Abs265 was recorded for triplicate samples containing 1 mM adenine and varied Na2S2O8 concentrations that were irradiated at either 0 or 900 V. These values were compared to find the magnitude of the decrease in Abs265, hereafter denoted by ΔAbs265. As seen in Fig. 2b, ΔAbs265 increased by 0.45 mAU per mM Na2S2O8 again indicating an inverse relationship between adenine absorbance and effective radical dose, once corrected for the absorbance of the Na2S2O8 precursor. To determine that dosimetry is sensitive to radical scavenging rather than just a measurement of radical generation, concentration of a radical scavenger (sucrose) was increased across triplicate samples to decrease effective radical dose. This yielded a linear response within the range tested, with Abs265 increasing by 0.992 mAU per mM sucrose (Fig. 2c), again verifying that adenine absorbance varies inversely with effective radical dose.

These dosimetry results show that Na2S2O8 can be photoactivated using the FOX Footprinting system, and that adenine can be a highly reliable SO4−• dosimeter in the appropriate buffer systems if the Na2S2O8 concentration is kept constant. This allows for the real-time compensation of in vitro conditions across SO4−• RPF experiments. However, compound changes of Na2S2O8 concentration and either lamp voltage or scavenger concentration must carefully account for the inherent Abs265 of Na2S2O8. We recommend only changing lamp voltage for compensation efforts21,22 in Na2S2O8-based labeling when possible.

Selection of an effective quench solution for SO4−•
Insufficient scavenging of slower-acting reactive oxygen/nitrogen species (ROS/RNS) could allow for secondary oxidations, which are not formed directly during the fast-labeling event by reaction of SO4−• and •OH with the protein target, but instead arise from less reactive ROS/RNS generated as secondary intermediates from the initial radical chemistry24,25. An effective quench is critical as secondary oxidation after primary radical modification can introduce artifactual modifications to non-native structures26. Recent observations suggest that standard HRPF quenching protocols are not sufficient for SO4−• RPF (L.M.Jones, unpublished results), contrary to previous reports12,13. In this study, two quench solution systems were tested. Quench solution I contained 200 mM N,N′-Dimethylthiourea (DMTU) and 70 mM Met amide, a standard HRPF quench that has been demonstrated effective for photoactivated H2O2 27. Quench solution II included 200 mM imidazole in addition to 200 mM DMTU and 70 mM methionine amide. The efficacy of the Na2S2O8 quench solutions was assessed by quantifying secondary oxidation products. To induce secondary oxidation, Na2S2O8 was photoactivated and subsequently collected into quench solutions already containing myoglobin and GluB. Quench efficacy was assessed at flash lamp voltages of 900 and 0 V. Persulfate can oxidize some organics directly, without involving radical species19, generating background oxidation. In the 0 V condition, myoglobin or GluB was injected into the FOX with Na2S2O8 before collecting in a quench to test background oxidation and the ability of an effective quench to limit it.

The results of these quenching experiments are shown in Fig. 3 and Supplementary Fig. 3. We detected seven peptides from myoglobin. During electrospray ionization, significant in-source oxidation occurred for peptide 2–17, even in samples without Na2S2O8. This in-source oxidation can be differentiated from pre-existing oxidation by the perfect chromatographic co-elution of the in-source oxidation product with the unmodified peptide. These in-source oxidation products are consistent in intensity and can be observed in the no-Na2S2O8 controls. Some peptides exhibited a significant increase in background oxidation in quench solution I, which only contains DMTU and methionine amide. For instance, peptide 120–134 showed a three to fourfold increase in modification in quenches lacking imidazole. Quenches with 200 mM imidazole showed no significant difference in peptide modification with or without Na2S2O8. Moreover, there was not a significant increase in oxidation when myoglobin was injected in-line with Na2S2O8 without illumination as reported by Gau et al.12. These results indicate that a quench solution containing DMTU, methionine amide, and imidazole effectively prevents secondary oxidation artifacts and limits background oxidation in SO4−• RPF experiments on the FOX system.

Effect of Na2S2O8 on blood cell morphology and hemolysis
To determine if SO4−• RPF preserved native-like conditions in stabilized whole blood before photoactivation, murine blood was mixed (9:1, V/V) with either 2 M Na2S2O8 or NaCl. Murine blood cell morphology was visualized with a Leica SP8 confocal microscope and RBCs cell size was measured using ImageJ software. Results are shown in Fig. 4. In conditions of 2 M NaCl or Na2S2O8 addition, a slight morphological alteration of the erythrocytes was evidenced by few spicules protruding from the surface of the cell membrane attributable to echinocytes. However, no significant changes were observed in RBCs cell size caused by treatment of 2 M Na2S2O8 compared to that of the equal concentration of NaCl (Supplementary Tables 1 and 2). To further determine the effect of Na2S2O8 on RBCs membrane integrity, the hemolysis ratio (%) was evaluated. As shown in Fig. 4g, blood cells mixed with 2 M Na2S2O8 caused less than 2% hemolysis and showed no significant differences (Supplementary Table 3) from treatment with equal concentration of NaCl, indicating that treatment of 2 M Na2S2O8 is non-hemolytic to RBCs.

Peptide-level modification of intracellular proteins in whole blood by SO4−• RPF
The resulting modified murine blood was subjected to a bottom-up proteomics workflow. To determine whether the blood proteome was successfully modified, we focused on the top 11 proteins identified by Byonic with highest sequence coverage. The average sequence coverage of each of these proteins was higher than 50%, as shown in Supplementary Table 4. Oxidation was quantified at the peptide level. Interestingly, significant differences in modification extent were found between extracellular and intracellular proteins. As shown in Fig. 5a, in both WT and T2DM mouse whole blood samples, significantly higher modification coverage was observed in extracellular proteins compared to intracellular proteins once background oxidation was subtracted (Supplementary Fig. 4 and Supplementary Tables 5 and 6).

In WT mice whole blood, 54 peptides derived from extracellular proteins were detected, of which 20.0% exhibited an average modification extent (AME) per peptide greater than 0.3 in 4 biological and 2 technical replicates. In contrast, 68 peptides from intracellular proteins were identified, with only 1.5% showing an AME above 0.3. Similarly, in T2DM mouse whole blood, 13% of extracellular peptides were oxidatively modified to an extent greater than 0.3, while no intracellular peptides exhibited a modification extent above this threshold (shown in Supplementary Fig. 5).

To determine whether the observed discrepancies were due to differences in the abundance of intracellular versus extracellular proteins, we performed hierarchical clustering heatmaps based on the intensity of proteins detected by Byonic. As shown in Supplementary Fig. 6, alpha and beta globin, both intracellular proteins, exhibited the highest abundance across all T2DM and WT samples. Overall, intracellular proteins displayed comparable, if not higher, abundance than extracellular proteins. These results suggest that the reduced extent of oxidation among intracellular proteins is not due to lower abundance. Rather, it is more likely attributed to the limited cell permeability of Na2S2O8. This indicates that SO4−• RPF can be successfully performed in mammalian whole blood and is capable of substantially modifying extracellular proteins. Efficient modification of intracellular proteins may require additional steps to increase reagent permeability28.

Additionally, as illustrated in Supplementary Fig. 5a–f, we subtracted the background oxidation (0 V) and localized the peptide-level modifications in the top six intracellular proteins. Three peptides showed significant differences in the extent of modification between WT and T2DM mice after Šídák correction for the number of oxidized peptides measured in the protein. These included peptides 10–41 and 30–60 from beta-globin, and peptide 64–92 from flavin reductase. However, due to the low level of overall oxidation of intracellular proteins, these results should be interpreted with caution.

Peptide-level modification of extracellular proteins in whole blood by SO4−• RPF
The increased modification coverage in extracellular proteins provided greater structural information. As demonstrated in Fig. 5a–f, a total of 54 peptides from the top five extracellular proteins were modified. For each protein, at least one peptide exhibited a modification extent greater than 0.3. Oxidation coverage of the detected peptides ranged from sparse to very high, which is consistent with other reported in vivo findings29,30, suggesting that optimization for protein system(s) of interest may permit interrogation of any target of interest in the blood proteome.

The highest changes in modification levels between T2DM and WT were observed in two proteins: complement C3 and Tf (Supplementary Tables 7 and 8). To further interrogate disease-associated protein conformational changes, we probed the peptide-level modification data to identify in-blood SO4−• RPF oxidation patterns in WT and T2DM environment. These results were mapped onto the crystal structures of each protein (Fig. 5g–i). Peptide 75–85 from protein complement C3 was significantly protected from oxidation in T2DM, compared to WT after Šídák correction. Notably, it showed an AME of 0.74 in WT samples, whereas it remained unmodified in T2DM samples. In contrast, peptides 741–748 was significantly exposed to oxidation in T2DM whole blood, compared to WT. In the case of protein Tf, two peptides (548–554, 555–565) were significantly protected from oxidation in T2DM, while one peptide (566–572) was moderately exposed to oxidation in T2DM.

In-blood SO4−• RPF captured substantial activation of the complement cascade in T2DM
The complement system is a fundamental arm of innate immunity, playing essential roles in shaping adaptive immune responses and in the clearance of immune complexes. Activation of complement proceeds through three distinct pathways, all of which intersect at the proteolytic processing of complement component C3, yielding the effector fragment C3b. Conversion of C3 into C3b represents the pivotal event that drives complement activation31–37. This transformation from C3 to C3b is accompanied by extensive conformational changes. As shown in Fig. 6, the native C3 is organized into 13 structural domains. Upon activation, these domains undergo varying degrees of conformational reorganization. Some regions display relatively subtle positional shifts, exemplified by the macroglobulin (MG) 7 and MG8 domains, whereas others undergo pronounced, large-scale rearrangements, most notably the thioester-containing domain (TED) and the complement C1r/C1s, UEGF, BMP1 (CUB) domain33,36.

Two key conformational changes stand out during the complement activation. The most dramatic involves the TED domain, which undergoes a substantial ~85Å translation, thereby uncovering the intramolecular thioester that is buried in the native C3 structure. In the activated C3b form, the TED shifts into proximity with the MG1 domain, leading to the exposure of previously inaccessible surfaces while also creating new interaction interfaces. These newly formed and revealed regions enable binding to other complement components that participate in both amplification and regulation of the cascade. A second major change is initiated by cleavage of C3 at the Arg726–Ser727 bond by C3 convertases. This reaction releases the anaphylatoxin (ANA) domain from the N-terminus of the α-chain, producing the larger C3b molecule alongside the small soluble fragment C3a. In the intact C3 protein, the ANA domain contributes indirectly to structural stability by maintaining the relative positioning of the MG8 domain and supporting the TED–MG8 interface. Loss of the ANA domain destabilizes this arrangement, triggering rotational movements of the MG7 and MG8 domains and permitting outward displacement of both the CUB domain and the TED34–36. By our RPF result, peptide 75–85 and 905–913, which locates in MG1 and MG7 domain respectively, was significantly protected in T2DM. In native C3, peptide 75–85 is fully solvent-exposed, making it readily accessible to oxidative radicals. In C3b, however, the relocation of the TED domain brings it into direct contact with the MG1 domain at this region. As a result, peptide 75–85 becomes buried within the interface and is no longer solvent-accessible (shown in Fig. 6a–d). While peptide 905–913 lies at the junction between the MG7 and CUB domains. In C3b, release of the ANA domain alters the position of the CUB domain, causing this region to become shielded and less accessible to solvent (Fig. 6a, b, g, and h). On the other hand, we found that peptide 741–748 was strongly exposed in T2DM. In native C3, this region is buried within the core of the MG ring, located immediately adjacent to the C3 convertase cleavage site and positioned against the ANA and TED domains, which together shield it from solvent access. In C3b, however, convertase cleavage removes the entire ANA domain and repositions the TED domain, generating an open conformation that renders peptide 741–748 fully exposed (Fig. 6a, b, e, and f). The conformational alterations detected across these three peptides are collectively consistent with increased activation of C3 in T2DM relative to WT.

To validate that the conformational changes in C3 detected by our RPF approach reflect complement activation in T2DM, we assessed the amount of the activation of the complement cascade by measuring circulating native C3 and its activated products (C3b, iC3b, and C3c, hereafter collectively referred to as C3b in reference to the epitope the ELISA antibody was raised against) in T2DM and WT mice by ELISA. The results are shown in Fig. 6i, j and Supplementary Tables 9–11. Interestingly, both plasma C3 and C3b levels were significantly elevated in T2DM mice compared with WT controls. However, while C3 level was only about two fold higher in T2DM, C3b exhibited a striking six fold increase. This disproportionate rise in C3b indicates markedly enhanced activation of the complement cascade in T2DM relative to WT. These findings align with prior studies showing that complement signaling is altered in diabetes. Increased complement activity results in greater cleavage of C3 to C3b, which contributes to local inflammation, increased opsonization, and the development of insulin resistance37–41. Evidence of activation of C3 has been reported to enhance pancreatic β-cell function and survival and to help maintain glucose homeostasis in T2DM42. Overall, the markedly activated complement cascade in T2DM explains the conformational changes in C3 detected by our in-blood SO4−• RPF approach. These findings suggest that distinct, disease-associated alterations in protein surface solvent accessibility are detectable by in-blood RPF.

In-blood SO4−• RPF detected increased Tf iron saturation in T2DM
Tf, commonly referred to as serotransferrin, is a circulating glycoprotein responsible for regulating systemic iron balance by delivering iron from sites of uptake to cells throughout the body via the bloodstream43–47. As shown in Fig. 7a, b, structurally, Tf is composed of an N-terminal and a C-terminal lobe. Each lobe is further divided into two subdomains that together form a metal-binding cleft, enabling a single Tf molecule to coordinate up to two ferric ions. Tf predominantly adopts two distinct and stable conformational states depending on its iron-loading status43,47–50. In the iron-free (apo) form, the protein assumes an open configuration in which the lobes are exposed to the surrounding solvent. Upon iron binding, Tf transitions to the iron-loaded (holo) form, characterized by a closed architecture in which each lobe folds around its bound metal ion. In this closed state, the coordinated iron becomes sequestered approximately 10Å beneath the protein surface43,50,51.

Conformational changes were detected in three peptides by our RPF approach, two of which (peptide 548–554 and 555–565) showed pronounced protection in T2DM, followed by a moderately exposed peptide immediately downstream. As shown in Fig. 7c, these two adjacent, strongly protected peptides reside in the C-lobe, directly adjacent to the iron binding site. Based on their position and protection pattern, we hypothesize that Tf iron saturation is increased in T2DM, leading to enhanced structural stabilization around the metal-binding cleft. Such elevated iron saturation would expand the dynamic pool of molecules undergoing the open-to-closed transition and could account for the unexpectedly strong protection observed in this region. In order to test this hypothesis, we evaluated Tf iron binding in T2DM and WT mice by measuring serum iron, TIBC, and Tf iron saturation. As illustrated in Fig. 7d, serum iron levels were significantly elevated in T2DM, whereas TIBC was markedly reduced. Consequently, the percentage of Tf saturation was substantially higher in T2DM (Supplementary Table 12), reflecting a shift in the distribution of apo- versus holo-Tf. Interestingly, the C-lobe typically loads iron first under physiological conditions44, which explains the conformational changes we observed in C-lobe under heavier iron saturation condition of T2DM. These findings are consistent with previous studies demonstrating perturbed iron metabolism, increased Tf turnover, and a positive association between Tf iron saturation and diabetes risk52–56. Together, these results validated that the conformational changes detected by our RPF approach in Tf arise from elevated Tf iron saturation in T2DM. More broadly, they highlight that our RPF method is capable of detecting complex, physiologically driven conformational processes that depend on the native biological matrix.

Testing the influence of HOS on in-blood RPF
To determine whether the oxidation pattern observed in whole blood was reflective of the protein’s native structure, we correlated the footprint of complement C3 from murine whole blood with our in vitro footprint of mouse complement C3 (95% sequence identity, 90% sequence similarity). The results are shown in Supplementary Fig. 7 and the correlation between in vitro and in-blood results is shown in Fig. 8. Because the effective radical dose between in vitro and in-blood cannot be normalized due to a lack of effective radical dosimetry for in-blood measurements, we measured the Spearman correlation between the two experiments, finding a strong correlation (r=0.8286). This analysis supports that in-blood RPF reasonably reflects the topography of the measured proteins.

Methods
Materials and reagents
sTRAP microcolumns were obtained from Protifi (Prod# CO2-micro-80, New York, NY, USA). Sodium chloride (NaCl), Sodium persulfate (Na2S2O8), equine myoglobin, bovine hemoglobin, DMTU, iodoacetamide (IAA), hydroxylamine, sucrose, acetone, LC-MS grade of methanol, formic acid (FA), acetonitrile, water, and isopropanol were obtained from Sigma Aldrich Corp. (St. Louis, MO). Triton ×-100, imidazole, EDTA, and 13×100 mm test tubes were purchased from VWR International (Radner, PA). Adenine, 3-amino-1:2:4-triazole (3AT), dithiothreitol, Tris(2-carboxyethyl)phosphine (TCEP), sodium dodecyl sulfate (SDS), mono- and di-basic sodium phosphate, imidazole, aminoguanidine, 30% hydrogen peroxide (H2O2), MS-grade trypsin, EDTA-coated tubes (Catalog No. 22-040-101), protease inhibitor tablets, 10× phosphate buffered saline (PBS, pH 7.4) and TSC were purchased from Thermo Fisher Scientific (Waltham, MA). Methionine amide was purchased from Bachem (Bubendorf, Switzerland). Mouse complement C3 was acquired from Acro Biosystems (Newark, DE, USA). Bovine blood was generously provided by Home Place Pastures (Como, MS). Canine blood was generously provided by Dr. Harry Fyke, University of Mississippi. Initial wild-type mouse blood for method development was provided by Dr. Michael Bouvet at the University of California San Diego School of Medicine. Diabetic and wild-type mouse blood reported here was collected as described below in Animals and Whole Blood Collection.

Assessment of radical precursor for in-blood RPF using foam assay
Four previously reported catalase inhibitors (hydroxylamine, 3-AT, aminoguanidine, and TSC) were assessed in blood via a test tube foam assay modified from Iwase et al.71. This assay correlates the height of trapped catalase-generated oxygen gas to catalase activity. Bovine blood was collected during routine exsanguination for beef production, immediately stabilized with 1.8 mg/mL EDTA, and flash frozen with dry ice/ethanol. 50 µL thawed blood was incubated with an inhibitor in a test tube, into which 50 μL of 2% Triton X-100 and 100 μL of 30% H2O2 or 2.5 M Na2S2O8 were spiked. Foam height was recorded after 30 min. To optimize inhibition, we varied inhibitor concentrations, incubation duration, temperature, and volumetric (v/v) ratio of blood to inhibitor.

Photoactivation of Na2S2O8 using the FOX system
Samples containing 1 mM adenine and 50 mM Na2S2O8 were irradiated by a FOX Photolysis system (GenNext Technologies, Inc., Half Moon Bay, CA) at 2 Hz. UV lamp voltage increased in 100 V increments from 600 to 900 V. Other triplicate samples were irradiated at 900 V and contained varied Na2S2O8 concentrations (0, 50, 75, 100, 125, 150, 175 mM) or varied sucrose concentrations (0, 25, 50, 75, 100, 125 mM). Real-time changes in adenine absorbance were monitored at 265 nm (Abs265) by the in-line dosimetry module72. Background oxidation was measured by injecting the above samples at 0 V and measuring oxidation post-quench.

Sulfate radical quenching
The efficacy of the Na2S2O8 quench solution was assessed by quantifying secondary oxidation products. To measure secondary oxidation, Na2S2O8 was photoactivated and subsequently collected into quench solutions spiked with 5 μM myoglobin and 5 μM [Glu]1-fibrinopeptide B (GluB) to ensure that only oxidations occurring post-radical formation were measured. 20 μL samples containing 100 mM Na2S2O8, 1 mM adenine, and 25 mM sodium phosphate (pH 7.2) were injected into the FOX and irradiated at 900 V. Quench solutions consisted of 200 mM DMTU and 70 mM methionine amide, with or without 200 mM imidazole, in 25 mM sodium phosphate buffer (pH 7.2). The secondary oxidation extent was evaluated by quantifying the modified myoglobin and GluB.

Blood cell morphology imaging
18 μL stabilized murine blood was mixed with 2 μL 2 M NaCl or Na2S2O8. Murine blood cell morphology was visualized with a Leica SP8 confocal microscope at ×40 magnification. Three slices per condition were prepared independently. Confocal image acquisition settings were kept constant across treatments. Images were captured as 12-bit .lif files of 1024×1024 pixel resolution. Cell size measurement of red blood cells (RBCs) was conducted using ImageJ v1.54p software (https://imagej.nih.gov/ij/). Using ImageJ, confocal microscopy images were first separated into individual fluorescence channels, after which a lower intensity threshold was manually set to eliminate background signal prior to measurement.

Whole blood hemolysis assays
Hemolysis was assessed using freshly collected EDTA-stabilized murine whole blood. Whole blood samples were mixed at a 9:1 (v/v) ratio with one of the following solutions: 10% Triton ×-100 as a positive control, 1× PBS (pH 7.4) as a negative control, 2 M NaCl, or 2 M Na2S2O8. After incubation, samples were centrifuged at 800×g for 5 min to sediment intact erythrocytes. The resulting supernatants were carefully collected and dispensed into 96-well plates. Hemoglobin release was determined by measuring absorbance at 560 nm using a SpectraMax ABS microplate reader. Absorbance values from treated samples (ODtest) were normalized against those from the negative control (ODneg) and the positive control (ODpos, defined as 100% hemolysis) to calculate the percentage of hemolysis according to the equation below73.:

Hemolysis ratio (%) = (ODtest - ODneg) / (ODpos - ODneg) * 100 (1)

Animals and whole blood collection
C57BL/6J (WT: BKS. Cg-Dock7m +/+ Leprdb/J; Heterozygous for Leprdb, Heterozygous for Dock7m; Strain 000642 and T2DM: BKS. Cg Dock7m +/+ Leprdb/J, db/db: Homozygous for Leprdb; Strain 000642) male mice of 8 weeks of age were obtained from the Jackson Laboratory and housed at the i3S animal facility under specific pathogen-free conditions. Sex was not considered as a biological variable for this initial method development experiment. Animals were group-housed in an AAALAC-approved animal facility following the National Institutes of Health “Guide for the Care and Use of Laboratory Animals.” Mice experienced a 12 h/12 h light/dark cycle at an ambient temperature of 22±2°C and relative humidity of 40–60%, and food (2014S Teklad Diets) and water were ad libitum.

At 16 weeks of age, the animals were weighed, and their blood glucose levels were measured (Supplementary Table 13). Mice were euthanized by CO2 asphyxiation followed by cervical dislocation to collect whole blood, which was drawn into EDTA-coated tubes and maintained at room temperature during transport. Blood samples were irradiated within 4 h of collection.

In-blood SO4−• RPF
EDTA-stabilized whole blood was collected respectively from four db/db mice and four WT control mice. In-Blood RPF was performed for each mouse blood draw using a FOX Protein Footprinting System (GenNext Technologies, Inc., Half Moon Bay, CA). A flow rate of 15 μL/min at a flash repetition rate of 2 Hz maintained the desired illuminated FOX exclusion volume of 20% as previously defined24. For each injection, 20 μL samples were injected to overload the FOX Photolysis System’s injection loop. The FOX Photolysis System’s fluidics module pumps the sample using 1× PBS as the carrier fluid. Immediately prior to injection, 2 μL of Na2S2O8 or NaCl at final concentration of 200 mM was added to 18 μL whole blood sample. The whole blood of all biological samples was irradiated in technical duplicate under three experimental conditions: Na2S2O8 and 0 V (unilluminated control); Na2S2O8 and 800 V (RPF); NaCl at 0 V (negative control). Immediately after labeling, whole blood samples were collected at 20 μL of quench solution containing 200 mM imidazole, 200 mM DMTU, and 70 mM methionine amide.

Whole blood proteome sample preparation
After RPF and quench, samples were precipitated with four volumes of cold acetone and stored at −20°C overnight. Thawed samples were centrifuged (14,000×g, 10 min), washed twice with 1× PBS, and resuspended in 300 µL of 50 mM Tris buffer. Proteins were lysed and digested using Profiti Micro S-Trap columns (CO2-micro-80) with minor modifications. Samples were lysed in 10% SDS buffer, ultrasonicated (5 min, 50 N, 1 kHz), reduced with 5 mM TCEP at 65°C for 20 min, and alkylated with 20 mM IAA in the dark for 40 min. Proteins were trapped, washed, digested overnight with trypsin (1:10 ratio), and sequentially eluted with Tris buffer, FA, and acetonitrile.

In vitro SO4−• RPF of complement C3
Protein labeling samples in a total volume of 20 μL consisting of 1 mM adenine, 25 mM sodium phosphate, pH 7.2, and 200 mM Na2S2O8 were irradiated at 800 V and collected in the same quench solution as used in blood. To digest the protein samples, a final concentration of 1 mM NaCl and 100 mM Tris, pH 8.0, were added to the samples and heated at 95°C for 15 min and immediately placed on ice for 2 min. 333 ng trypsin was added to the samples and incubated at 37°C with rotation for 14 h. A final concentration of 0.1% FA was added to the samples to stop trypsin activity.

Liquid chromatography mass spectrometry (LC-MS) analysis of eluted peptides
Eluted peptides were analyzed by an Orbitrap Fusion Tribrid mass spectrometer coupled with a Dionex Ultimate 3000 system nanoLC system (Thermo Fisher, CA). Samples were loaded onto a trap column (Thermo Fisher C18 5 μM, 0.3×5 mm) and peptide separation was achieved through a nano C18 column (Acclaim 2 μM, 0.075×150 mm) at a flow rate of 0.3 μL/min. Solvent A was 0.1% FA in LC-MS water, and solvent B was 0.1% FA in acetonitrile. The gradient consists of 2% solvent B held for 2 min, 2–7% solvent B over 2 min, 7–32% solvent B over 58 min, 32–95% solvent B over 3 min and held for 3 min, returned to 2% solvent B over 4 min and held for 8 min. The total gradient runtime was 80 min.

Mass spectrometric analysis was performed on an Orbitrap Fusion Tribrid in data dependent acquisition mode using Xcalibur software v4.3 (Thermo Fisher Scientific, Waltham, MA). Mass spectra of the peptides were analyzed over a 250–2000 m/z range at normal mass resolving power with a dynamic exclusion (Orbitrap Resolution 60000). Peptides with +1 charge state were excluded. Electrospray ionization was carried out in a positive ion mode. The ion source voltage was kept at 2450 V. Data-dependent mode MS/MS was used, with CID applied to each selected precursor. The CID intensity threshold was set at 5.0×103, and the CID collision energy was set at 32% with a rapid ion trap scan.

Proteomic data processing
Byonic (v4.4.2, Protein Metrics, San Carlos, CA) was used to identify the peptide and determine the protein sequence coverage. LC-MS data were searched against the complete Mus musculus proteome. Trypsin cleavage specificity was set to Lys and Arg residues, except before Pro residues, with up to 2 missed cleavages permitted. Precursor mass tolerance was set to 10 ppm, and the fragment mass tolerance was set to 0.4 Da. Met oxidation was set as a variable modification and Cys residues were set for carbamidomethylation modification. Protein false discovery rate was set at 1%. The identified proteins in whole blood were ranked by average sequence coverage to select the top eleven proteins for footprinting analysis. Peptide-level oxidation was quantified using Foxware v2.1.2 (GenNext Technologies, Half Moon Bay, CA). The retention time window for modified peptides was set to 6 min relative to their unmodified counterparts. XIC smoothing was applied using 17 points, and both the left and right shoulder ratios were set to 1.1. For all peptides detected, the major oxidation products detected were net additions of one or more oxygen atoms. The major mass shifts observed were +15.995 Da (+O), +31.990 Da (+2O), and +47.985 Da (+3O). All of these major products were used for quantitation of modification extent. The average number of oxidation events per peptide molecule (APO, or Average Peptide Oxidation) was determined by summing the ion abundance (IA) of each peptide oxidation product multiplied by the number of oxidation events on the peptide required to generate that product and divided by the sum of IA for all oxidized and unoxidized versions of that peptide, as shown in the following equation74:

APO = (1*IA(+O) + 2*IA(+2O) + 3*IA(+3O)) / (IA(unmodified) + IA(+O) + IA(+2O) + IA(+3O)) (2)

The AME reported is the average APO of technical replicates that are repeated measurements of the same sample under identical conditions.

Serum iron and Tf iron saturation (%) measurement
Serum samples of 8 mice of each condition (WT and T2DM) were freshly collected. Total iron binding capacity (TIBC), i.e., the total amount of iron that can be accommodated by Tf, as well as the Serum iron were determined within 2 h of sample collection in non-hemolyzed serum samples using TIBC and serum iron assay kit by Cayman Chemical (Prod# 702230, Michigan, USA) according to the instructions provided by manufacture. Tf iron saturation (%) was calculated as56,75:

Tf iron saturation (%) = (serum iron / TIBC) * 100 (3)

All spectrometric readings were done using a SpectraMax ABS ELISA microplate reader (Molecular Devices, San Jose, CA).

Determination on complement activation by ELISA
To assess quantitatively the amount of native complement C3 and its cleaved and activated fragments (C3b), and thus the activation of the complement cascade, plasma of 8 male mice of each condition (WT and T2DM) were sampled in EDTA tubes and kept on ice to avoid ex vivo activation, C3 and C3b were measure with C3 and C3b mouse ELISA Kit (Prod# HK2002 for C3 and HK216 for C3b, Hycult, Uden, The Netherlands) respectively76,77, following the manufacturer’s instructions. The C3 ELISA assay is specific for mouse C3, while the C3b ELISA kit uses antibodies raised against C3b, and recognize epitopes that preserved in C3b and its downstream fragments. As a result, the assay detects activated C3 species (C3b, iC3b, and C3c) but does not detect intact native C3. Thus, the measured signal reflects the overall level of C3 activation, with C3b representing the major and immediate product and its derivatives contributing to the total detected activated C3 cascade.

Statistics and reproducibility
All experiments were performed in a minimum of three independent replicates. No data points were omitted from the analyses. Experiments were conducted without randomization, and investigators were aware of group assignment throughout both experimental execution and outcome evaluation. All data are expressed as the mean ± standard deviation (SD), unless otherwise stated. A two-tailed unpaired t-test was used to compare two groups. One-way analysis of variance (ANOVA) followed by Dunnett’s test was used to compare three or more groups (P<0.05 was considered statistically significant difference, NS denotes not significant). GraphPad Prism 10.0 was used for analysis.

Ethical statement
All animal experiments were conducted in compliance with relevant ethical regulations and were approved by the University of Mississippi Animal Care and Use Committee (IACUC; protocol number 23-011).

Reporting summary
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability
The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE78 partner repository with the dataset identifier PXD064571. Protein structures used in this work are available under PDB IDs 2A73, 2I07, 3V83, and 2HAU. All data supporting the findings of this study are available within the article and Supplementary Information and Source Data files. Source data are provided with this paper.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The paper by Sharp et al. is an interesting application study of hydroxyl radical footprinting, a relatively new technique for\nstructural proteomics, which highlights new approaches for structural labelling of whole cells (here, red blood cells). The\nwork presented is mostly novel, and although in part specific for the use of a commercial footprinting system most of the\nfindings should also be applicable to laser-based and synchrotron footprinting approaches.\nThe work is of sufficient interest to a broader readership and I recommend the paper for publication subject to a number of\nrevisions as suggested below.\nThe paper talks about labelling of mammalian tissue, but I would not call blood a tissue - these are cells.\nCan you speculate about the oxidation reaction with the sulfate radical anion, is that radical more stable than hydroxyl and\ndoes it not also lead to other secondary reagent ions (i.e. ROS/RONS)? I would assume that more is known about the\nmechanism here albeit maybe not in the context of footprinting. Is it important that persulfate rather than sulfate is used, given\nthat both could in theory generate a sulfate radical anion? This is a prominent outcome of the research presented here and\nshould be discussed in more detail.\nFigure 1 is suggestive of two samples being pooled, which I presume is not the case - please edit the figure to make it clear\nthat two different biological conditions are being compared and that readouts of the experiment are relative changes in\noxidation/modification at the peptide level.\nUnless I missed it, the specific modifications (e.g. +16 Da) which are detected and used for determining relative\ndifferences\nare not specified. Which types of mass shifts occur with (per)sulfate and which ones form the basis of relative quantitation\nhere? The section on \"Proteomic data processing\" also lacks information on how those modifications considered here were\nquantified.\nMost readers will not know what is meant by \"secondary oxidation products\". Are these oxidations mediated by secondary\nreagents produced from (per)sulfate, e.g. ROS/RONS? or specific types of modifications found on amino acids, e.g. those\ndue to slow oxidation reactions due to incomplete quenching? Please provide a clear definition of the term, and why these\nare potentially problematic (although it could be argued that slow labelling products are likely still structurally\ninformative).\nClarify why background oxidation is measured in the presence of reagent (but no UV) rather than in absence of reagent?\nDoes imidazole really make a difference for the quench - I see hardly any significant difference apart from the one instance\nwhich was highlighted already.\nWere the peptides of the two types of conditions (mice) also checked for changes in PTMs which could confound the results\nof the peptide oxidation searches?\nThe two proteins found to carry significant differences between wt/disease variant are interesting, can you suggest what type\nof conformational change or aggregation could cause these, in the light of what is known from literature? It would be good to\nfollow these results up a bit more what they can tell us about the state of these proteins in the red blood cells (?), and how\nthat relates to disease mechanism in the pancreas or liver (?).\nMinor corrections:\nAbstract - why are specifically carbohydrate interactions highlighted, the method should also be applicable to e.g.\nDNA/RNA\ninteractions? There are too many \"mice\" in the sentence which specifies the types.\nWhat is the desired FOX exclusion volume - this needs an explanation.\n\"Peptides with single charge state were excluded\" - this makes little sense unless it is meant that 1+ charge states were\nexcluded.\n\"Each data point represents a biological replicate that is the mean of two technical replicates.\" - please explain the\ndifference of biological and technical replicates in this context, this statement is confusing.\nWith the in-source oxidation observed for peptide 2-17, what residues are causing this (e.g. methionine)?\nWhat is meant by \"background secondary oxidation artifacts\" - see earlier, \"secondary\" and \"background\" need a clear\ndefinition here.\nHow is the \"average modification extent (AME) per peptide\" defined, is that the percentage of peptide modified with a\nspecific Da shift? needs a definition.", "reviewer_2": "The authors describe radical protein footprinting (RPF) with mass spectrometry detection on proteins in whole blood,\nrepresenting an expansion of footprinting methods to more biologically-relevant samples. The authors demonstrate that a\ndifferent radical precursor (i.e. persulfate) than hydrogen peroxide, which is typically used in RPF, is needed because of the\nhigh concentration of catalase in blood that causes foaming in the presence of hydrogen peroxide.\nOverall, I think the manuscript should be published after some significant revisions. The ability to do RPF in whole blood is\nimportant, but the manuscript needs some additions and changes, which are listed below, to make it suitable for publication.\n1. Because Figure 2 primarily reports the results of H2O2 treatment of blood, which is not used in the rest of the manuscript, I\nrecommend that this Figure be moved to the SI. This move would make room for an additional figure that I recommend\nbelow.\n2. How is the 'Modification extent' shown on the y-axes of Figures 4, 6, 7, and 8 calculated? This information should be\nincluded in the methods section.\n3. In discussing the data associated with Figure 6, the authors indicate that 20% of the peptides from extracellular proteins\nexhibit an average modification extent of greater than 0.3, while only 1.5% of the intracellular proteins passed this threshold.\nFor some frame of reference, it would be helpful to indicate what percentages of peptides from a pure protein in buffered\nsolution would exceed an average modification extent of 0.3.\n4. The authors note that three peptides from intracellular proteins have significant differences in the extent of modification\nbetween the WT and T2DM mice. Can the authors speculate about the structural or biological significance of these\nobservations? Or, are these changes simply method related (e.g. differential permeability of persulfate into blood cells from\nthe different samples)? If the authors are going to note this observation, then some comment on it would improve the\nmanuscript.\n5. In discussing the data in Figure 7, the authors note that \"Oxidation coverage of the detected peptides ranged from sparse\nto very high, which is consistent with reported findings…\" I think that they mean that this observation is consistent with other\nin vivo findings, correct? The ‘in vivo’ qualifier should be added to the text.\n6. It appears that there are 4 biological replicates for the data shown in Figures 6 and 7. I think that the methods section says\nblood from 4 mice (of each type) were taken, but it would be good to note this value in the figure captions.\n7. In Figure 7, are the peptides indicated in parts A-E only those that are oxidized or are these all the detected peptides?\nThis information would be helpful for knowing if the information is limited by overall sequence coverage or are only certain\npeptides oxidized (while more are not)?\n8. The structures shown in Figure 7G and F are small and difficult to see. Perhaps the authors could put these structures in\ntheir own figure. If Figure 2 is moved to the SI, as suggested above, then the total number of figures would be the same.\n9. Any speculation as to what specific factors cause the alterations in the protein surface accessibility of complement c3 and\nserotransferrin peptides that are noted to change? Some biological or structural explanation would substantially strengthen\nthe paper.\n10. The comparison of the in vitro footprinting of complement c3 to the in-blood results is interesting and important; however,\nthe details about in vitro data must be included in the manuscript, beyond what is shown in Figure 8. The authors need to\nadd the actual data in Table form or bar graph form, probably to the SI. It would also be helpful to map the footprinting results\nfrom the in vitro experiments on the structure of complement c3; this could go in the SI as well. In my opinion, this information\nis essential for indicating the sequence coverage, the different extents of modification, etc. that are seen in-blood vs. in vitro\nfootprinting.", "reviewer_3": "The paper describes a method to detect peptides accessible to oxidation in the most abundant extracellular proteins present\nin blood.\nGiven that the structure of C3, including its conformational changes during activation, has been extensively studied, the\nauthors should make an effort to interpret their findings (differences in peptide accessibility) in the context of existing\nknowledge about C3. Can differences be attributed to the presence of various conformational forms of C3 like C3b, iC3b,\nC3d? Can C3 be glycated and therefore less accessible?\nWhy was canine blood used to test for morphological changes? Wouldn’t it be more appropriate to focus on a single species\n(e.g., mouse) or, alternatively, include a broader range of species (including mouse) for comparative purposes?\nSince intracellular proteins were apparently not oxidized, presumably due to the poor permeability of sodium persulfate,\nwouldn’t it be more straightforward to use plasma-EDTA as the starting material?\nIn Figures 6 and 7, it is unclear which data points correspond to wild-type and which to db/db mice. The symbols are too\nsmall, and the color coding of the bars is not explained in the legend.\nWhat conclusions can be drawn regarding protein conformation or function based on the presented data? C3 is a secreted\nprotein present at high concentrations in blood, but it is also expressed intracellularly. In particular, the intracellular form of\nC3 in pancreatic beta cells has been associated with diabetes development. Therefore, the claim that “In-blood RPF found\nsignificant differences in complement C3 topography in T2DM mice compared to WT, indicating that we have detected a\nstructural basis behind the role of complement C3 in T2DM” appears to be an overstatement.\nIt is unclear how ref 32 pertains to role of extracellular C3 in diabetes, better ones would be:\nAdipsin preserves beta cells in diabetic mice and associates with protection from type 2 diabetes in humans.\nGómez-Banoy N, Guseh JS, Li G, Rubio-Navarro A, Chen T, Poirier B, Putzel G, Rosselot C, Pabón MA, Camporez JP,\nBhambhani V, Hwang SJ, Yao C, Perry RJ, Mukherjee S, Larson MG, Levy D, Dow LE, Shulman GI, Dephoure N, Garcia-\nOcana A, Hao M, Spiegelman BM, Ho JE, Lo JC.Nat Med. 2019 Nov;25(11):1739-1747. doi: 10.1038/s41591-019-0610-4.\nEpub 2019 Nov 7.PMID: 31700183\nC3aR1 on β cells enhances β cell function and survival to maintain glucose homeostasis.\nPereira de Lima R, Li A, Gilani A, Rubio-Navarro A, Warren CD, Kong IY, Geri JB, Lo JC.Mol Metab. 2025 Jun;96:102134.\ndoi: 10.1016/j.molmet.2025.102134. Epub 2025 Apr 4.PMID: 40189102\nFor roles of intracellular C3 in diabetes please see:\nIntracellular cytosolic complement component C3 regulates cytoprotective autophagy in pancreatic beta cells by interaction\nwith ATG16L1.\nKing BC, Renström E, Blom AM.Autophagy. 2019 May;15(5):919-921. doi: 10.1080/15548627.2019.1580515. Epub 2019\nFeb 20.PMID: 30741587\nIntracellular C3 protects β-cells from IL-1β-driven cytotoxicity via interaction with Fyn-related kinase.\nKulak K, Kuska K, Colineau L, Mckay M, Maziarz K, Slaby J, Blom AM, King BC.Proc Natl Acad Sci U S A. 2024 Feb\n20;121(8):e2312621121. doi: 10.1073/pnas.2312621121. Epub 2024 Feb 12.\nSome spelling mistakes need to be sorted out like ”Boday weight” in table S1.", "reviewer_4": "In this manuscript by Zhao et al, the authors describe radical protein foot printing (RFP) in mammalian whole blood of mice\nthat are WT or BKS.Cg-Dock7m+/+ Leprdb/J, a mouse model of type 2 diabetes (T2D). Using state of art techniques, they\nlabelled proteins with minimal disruption of RBC morphology and show oxidative modifications of both intracellular and\nextracellular proteins. While I am aware of the technique, I am not familiar with the fine details and therefore my review will\navoid assessing the methodology and will focus mainly, but not exclusively, on the “diabetes findings” comparing WT with\nT2D mice.\n1. In Figure 5: using NaCl at 200mM represents significant “hypertonic” conditions and it is therefore not surprising to see\nthose morphological changes. Did the authors measure cell size? Also, are the authors concerned that such\nmorphological changes may have resulted in increased cellular stress (which may affect intracellular proteins)? Also, how\nlong was the exposure to these hypertonic conditions (should be made clear in the Figure legend). Finally, the authors may\nwish to better clarify why canine RBCs were used.\n2. In Figure 6: it is reassuring to see α-globin and β-globin oxidation (part of haemoglobin). However, what about\ncytoskeletal proteins (i.e. spectrin and actin); were these supposed to show differences? The same applies to RBC membrane\nproteins.\nWould be interesting to know the views of the authors.\n3. In Figure 7: these data are very interesting indeed. I suggest adding to the Figure legend before the volcano plot “Figure\n7A-E show that the highest and broadest modifications occurred in two proteins, serotransferrin and complement C3\". Also, I\nsuggest a slight expansion of the discussion to better cover the findings in this Figure.\n4. Discussion: The sentence “Complement c3 has emerged as a significant contributor but also a potential effector of\ndisease progression of T2DM” is an overstatement and needs to be toned down. There are certainly changes in the\ncomplement system in T2D but these are mainly associations (as part of the metabolic derangement) and the evidence for\nC3 causing the progression of diabetes is weak at best (despite some mechanistic studies showing a potential causative\nlink). Rather than focusing on C3 changes as the cause for diabetes progression, the authors may wish to discuss the\npotential role of protein oxidation in the development of vascular complications of diabetes (through increased inflammation),\nwhich would be far more interesting. Also, the discussion needs a bit more on the limitations of the current technique at\nassessing intracellular protein modifications (while this is mentioned, it is somewhat indirect and needs to be more explicit)."}, "author_response": "Response to Reviewer Comments\nReviewer #1 (Remarks to the Author):\nThe paper by Sharp et al. is an interesting application study of hydroxyl radical footprinting, a relatively new technique for\nstructural proteomics, which highlights new approaches for structural labelling of whole cells (here, red blood cells). The\nwork presented is mostly novel, and although in part specific for the use of a commercial footprinting system most of the\nfindings should also be applicable to laser-based and synchrotron footprinting approaches.\nThe work is of sufficient interest to a broader readership and I recommend the paper for publication subject to a number of\nrevisions as suggested below.\nComment: The paper talks about labelling of mammalian tissue, but I would not call blood a tissue - these are cells.\nResponse: We respectfully disagree with the reviewer’s comment. Blood is widely classified as a specialized connective\ntissue in biological and medical literature (one representative citation given below), having its origin from mesenchyme and\nits function in transport and homeostasis. Blood is thus a connective tissue whose matrix consists of free-flowing ground\nsubstance (plasma) with no fibers. However, as this is not key to the manuscript, we are willing to change the wording at the\neditor’s discretion.\nReference:\nKamrani, P., Marston, G., Arbor, T. C. & Jan, A. Anatomy, Connective Tissue. In: StatPearls [Internet]. Treasure Island (FL):\nStatPearls Publishing; 2023 Mar 5. PMID: 30860769.\nComment: Can you speculate about the oxidation reaction with the sulfate radical anion, is that radical more stable than\nhydroxyl and does it not also lead to other secondary reagent ions (i.e. ROS/RONS)? I would assume that more is known about the\nmechanism here albeit maybe not in the context of footprinting. Is it important that persulfate rather than sulfate is used, given\nthat both could in theory generate a sulfate radical anion? This is a prominent outcome of the research presented here and\nshould be discussed in more detail.\nResponse: One reason for choosing SO₄⁻• over other potential radicals is its reduction potential is 2430 mV, which is higher\nthan that of •OH (1900 mV). In vitro RPF studies with the sulfate anion radical show that the same level of global\nmodification can be achieved as the hydroxyl radical at three times lower precursor concentration [1-3].\nGross and coworkers [1] showed that the commonality of the sets of modifications produced by in vitro SO₄⁻• and •OH RPF\nmethod suggests that the dominant chemical pathways of SO4−• labeling are similar to the better understood •OH\nmechanisms. Gross and co-workers postulated that a likely explanation for these similar outcomes is that both processes\nbegin with an initial hydrogen abstraction reaction at aliphatic sites. Additionally, formation of hydroxyl radicals by sulfate\nradical reaction with water (equation 1) may compete, giving rise to an •OH active radical [1]:\nSO₄⁻• + H₂O → SO₄²⁻ + H⁺ + •OH (1)\nThis interpretation is supported by kinetic analysis from McElroy and Waygood [2].\nIn the present study, we describe why the more commonly used hydrogen peroxide is unsuitable for radical protein\nfootprinting in blood due to the decreased stability of the radical precursor in blood. The lack of signaling activity of the\nsodium persulfate in cells is another of the major advantages. A caveat of using hydrogen peroxide is its preexisting role in\nsignaling pathways which lead to biological changes within the cell [4].\nSodium persulfate is chosen over sulfate because the peroxydisulfate bond enables efficient photochemical cleavage to\ngenerate potent, fast-reacting sulfate radicals under commonly used RPF laser wavelengths, whereas sulfate ions cannot be\ndirectly photoactivated at convenient wavelengths. This ensures effective and rapid protein labeling even in the highly\ncomplex, radical-scavenging environment of whole blood. Herrmann (2007) reviewed the photolysis of simple anions,\nincluding persulfate, confirming its properties for formation of sulfate radicals [5].\nWe have added a brief discussion of our choice of persulfate to the manuscript.\nReferences\n1. Gau, B. C., Chen, H., Zhang, Y. & Gross, M. L. Sulfate radical anion as a new reagent for fast photochemical\noxidation of proteins. Anal. Chem. 82, 7821-7827 (2010).\n2. McElroy, W. J. & Waygood, S. J. Kinetics of the reactions of the SO –4 radical with SO –4, S O –8, H O and Fe2+. J.\n2 2 2\nChem. Soc., Faraday Trans. 86, 2557-2564 (1990).\n3. Lee, J., von Gunten, U. & Kim, J. H. Persulfate-Based Advanced Oxidation: Critical Assessment of Opportunities\nand Roadblocks. Environ. Sci. Technol. 54, 3064-3081 (2020).\n4. McKenzie-Coe, A. A., Johnson, D. T., Peacock, R. B., Zhang, Z. & Jones, L. M. Evaluating the Sulfate Radical\nAnion as a New Reagent for In-Cell Fast Photochemical Oxidation of Proteins. J. Am. Soc. Mass Spectrom. 32, 1644-\n1647 (2021).\n5. Herrmann, H. On the photolysis of simple anions and neutral molecules as sources of O−/OH, SOx− and Cl in\naqueous solution. Phys. Chem. Chem. Phys. 9, 3935-3964 (2007).\nComment: Figure 1 is suggestive of two samples being pooled, which I presume is not the case - please edit the figure to\nmake it clear that two different biological conditions are being compared and that readouts of the experiment are relative\nchanges in oxidation/modification at the peptide level.\nResponse: We thank the reviewer for the comment. Figure 1 has been edited accordingly.\nComment: Unless I missed it, the specific modifications (e.g. +16 Da) which are detected and used for determining relative\ndifferences are not specified. Which types of mass shifts occur with (per)sulfate and which ones form the basis of relative\nquantitation here? The section on \"Proteomic data processing\" also lacks information on how those modifications considered\nhere were quantified.\nResponse: We have now clarified the specific modifications detected and used for relative quantitation in the revised\nmanuscript. For all peptides detected, the major oxidation products detected were net additions of one or more oxygen atoms.\nThe major mass shifts observed include +15.995 Da (+O), +31.990 Da (+2O) and +47.985 Da (+3O). All of them were used\nfor quantitation of modification extent. In short, the average number of oxidation events per peptide molecule (APO, or\nAverage Peptide Oxidation) was determined by summing the ion abundance (IA) of each peptide oxidation prod-uct\nmultiplied by the number of oxidation events on the peptide required to generate that product and divided by the sum of IA\nfor all oxidized and unoxidized versions of that peptide, as shown in the following equation:\n1∙𝐼𝐴 (+𝑂)+2∙𝐼𝐴 (+2𝑂)+3∙𝐼𝐴 (+3𝑂)\n𝐴𝑃𝑂 =\n𝐼𝐴 (𝑢𝑛𝑚𝑜𝑑𝑖𝑓𝑖𝑒𝑑)+𝐼𝐴 (+𝑂)+𝐼𝐴 (+2𝑂)+𝐼𝐴 (+3𝑂)\nWe have revised the Proteomic data processing section to explicitly describe the quantitation workflow in FoxWare software\nand filtering criteria applied in the parameters.\nThese additions can now be found in the revised manuscript.\nComment: Most readers will not know what is meant by \"secondary oxidation products\". Are these oxidations mediated by\nsecondary reagents produced from (per)sulfate, e.g. ROS/RONS? or specific types of modifications found on amino acids,\ne.g. those due to slow oxidation reactions due to incomplete quenching? Please provide a clear definition of the term, and\nwhy these are potentially problematic (although it could be argued that slow labelling products are likely still structurally\ninformative).\nResponse: We agree that “secondary oxidation products” should be defined more explicitly. In the revised manuscript, we\nnow clarify that by “secondary oxidation products,” we refer to oxidative protein modifications that are not formed directly\nduring the fast-labeling event by reaction of SO₄⁻• and •OH with the protein target, but instead arise from less reactive\nreactive oxygen/nitrogen species (ROS/RNS) generated as secondary intermediates from the initial radical chemistry. These\nproducts are most commonly created by insufficient scavenging of these slower-acting ROS/RNS and/or prolonged exposure\nto the photoactivatable precursor, which itself is a reactive species.\nSuch modifications are problematic for our workflow because they may occur after protein conformations have changed post-\nperturbation, leading to artifacts not reflective of the native structure. Discussion of this issue can be found throughout FPOP\nliterature, but we cite Gau et al 2009 and Venkatesh, Tomer and Sharp 2007 where the issue of artifactual contributions of\nslow oxidation were approached quantitatively.\nThis definition and rationale have been added to the revised manuscript for clarity.\nGau, B. C., Sharp, J. S., Rempel, D. L. & Gross, M. L. Fast Photochemical Oxidation of Protein Footprints Faster than\nProtein Unfolding. Anal. Chem. 81, 6563-6571 (2009).\nVenkatesh, S., Tomer, K. B. & Sharp, J. S. Rapid identification of oxidation-induced conformational changes by kinetic\nanalysis. Rapid Commun. Mass Spectrom. 21, 3927-3936 (2007).\nComment: Clarify why background oxidation is measured in the presence of reagent (but no UV) rather than in absence of\nreagent?\nResponse: Persulfate can oxidize some organics directly, without involving radical species [1]. To account for background\noxidation caused by the reagent itself and more accurately reflect the modifications resulting from the labeling chemistry,\nbackground oxidation was subtracted using control samples containing the reagent but no UV exposure. This captures both\npre-existing protein oxidation products, as well as any persulfate-induced protein oxidation products generated independently\nof photo-activation (which are minimized by our workflow, but should nevertheless be included). This practice is in line with\nthe current community-recommended best practices for radical protein footprinting [2]. However, as these recommendations\nare currently only available as a pre-print and are undergoing revision, we will not cite them in this manuscript.\nReferences:\n1. Lee, J., von Gunten, U. & Kim, J. H. Persulfate-Based Advanced Oxidation: Critical Assessment of Opportunities\nand Roadblocks. Environ. Sci. Technol. 54, 3064-3081 (2020).\n2. Wecksler, A.T. et al, Recommendations and Considerations for Hydroxyl Radical Protein Footprinting - Mass\nSpectrometry. ChemRxiv 2025 DOI: 10.26434/chemrxiv-2025-2rp6h\nComment: Does imidazole really make a difference for the quench - I see hardly any significant difference apart from the\none instance which was highlighted already.\nResponse: Our results shown in Figure 4 are in agreement with anecdotal data: while traditional quench is sufficient for many\npeptides in persulfate-based RPF, there are a subset of peptides where we find the traditional quench insufficient. We\nidentified two such peptides (α = 0.05) in our test system, and found imidazole to be sufficient to eliminate this background\noxidation from persulfate.\nComment: Were the peptides of the two types of conditions (mice) also checked for changes in PTMs which could confound the results\nof the peptide oxidation searches?\nResponse: We thank the reviewer for this important comment. Adding a PTM search compounded with the RPF search\nquickly creates a problem with a search space that rapidly expands as each new potential differential modification is added to\nthe search. We have included a brief discussion of this limitation to the manuscript. Additionally, we searched all proteins\ndetected in this manuscript in UniProt for reported PTMs. We found that several intracellular proteins, particularly β-globin,\nα-globin, 60S ribosomal protein L40, and flavin reductase, contain extensive reported PTMs. In contrast, among the\nextracellular proteins investigated, no oxidized peptides from complement C3, serotransferrin, or apolipoproteins contain any\nreported PTMs. Only two peptides each from transthyretin and albumin contained previously reported phosphoserine\nmodifications, which are unlikely to confound the significant conformational changes we observed in C3 and serotransferrin.\nComment: The two proteins found to carry significant differences between wt/disease variant are interesting, can you\nsuggest what type of conformational change or aggregation could cause these, in the light of what is known from literature?\nIt would be good to\nfollow these results up a bit more what they can tell us about the state of these proteins in the red blood cells (?), and how\nthat relates to disease mechanism in the pancreas or liver (?).\nResponse: In the revised manuscript, we demonstrate the conformational change of C3 detected by our RPF approach is\nconsistent with complement activation in T2DM, which we assess by ELISA of C3 and its activated product C3b. The C3\nELISA assay is specific for mouse C3, while the C3b ELISA kit uses antibodies raised against C3b, and these antibodies\nrecognize epitopes that are preserved in C3b and its downstream fragments. As a result, the assay detects activated C3 species\n(C3b, iC3b, and C3c) but does not detect intact native C3. Thus, the measured signal reflects the overall level of C3 activation,\nwith C3b representing the major and immediate product and its derivatives contributing to the total detected activated C3\ncascade. The result is shown in Figure 6. We also found that the conformational changes in transferrin is consistent with an\nincreasing transferrin iron saturation in T2DM, which has been validated in the revised manuscript by\nmeasuring the serum iron and transferrin iron binding capability. The result is shown in Figure 7.\nMinor corrections:\nComment: Abstract - why are specifically carbohydrate interactions highlighted, the method should also be applicable to e.g.\nDNA/RNA\ninteractions? There are too many \"mice\" in the sentence which specifies the types.\nResponse: The reviewer makes an excellent point. Carbohydrate interactions were highlighted in the abstract because, in our\nhands, the RPF method is particularly well suited for probing carbohydrate-protein related interactions that are very\nchallenging to characterize by other means. However, we agree that the method is broadly applicable to other biomolecular\ninteractions and have revised the abstract to reflect this broader applicability. In addition, we have rephrased the sentence\ndescribing the types of mice to reduce redundancy and improve readability.\nComment: What is the desired FOX exclusion volume - this needs an explanation.\nResponse: We thank the reviewer for noting our omission. In the present study, the desired FOX exclusion volume is 20%,\nin keeping with previous results [1]. We included the key parameters that control the exclusion volume as well as the final\nexclusion volume in the revised manuscript.\n[1] Gau, B. C., Sharp, J. S., Rempel, D. L. & Gross, M. L. Fast Photochemical Oxidation of Protein Footprints Faster than\nProtein Unfolding. Anal. Chem. 81, 6563-6571 (2009).\nComment: \"Peptides with single charge state were excluded\" - this makes little sense unless it is meant that 1+ charge states\nwere excluded.\nResponse: The reviewer is correct. In the revised manuscript, we have corrected it as: +1 charge state ions were excluded.\nComment: \"Each data point represents a biological replicate that is the mean of two technical replicates.\" - please explain the\ndifference of biological and technical replicates in this context, this statement is confusing.\nResponse: We thank the reviewer for pointing out the need for clarification. In our study, biological replicates refer to\nindependent samples obtained from individual mice, which capture the compound effect of biological variability and method\nprecision. Technical replicates refer to repeated measurements of the same biological sample (mice) under identical\nexperimental conditions, which assess the precision and reproducibility of the analytical procedure. We have clarified this in\nthe revised manuscript.\nComment: With the in-source oxidation observed for peptide 2-17, what residues are causing this (e.g. methionine)?\nResponse: We appreciate the reviewer’s question. The in-source oxidation observed for peptide 2–17 is most likely caused\nby the two tryptophan residues (W8 and W15), which can undergo oxidation during even fairly soft electrospray ionization\nconditions in LC-MS analysis.\nComment: What is meant by \"background secondary oxidation artifacts\" - see earlier, \"secondary\" and \"background\" need a\nclear definition here.\nResponse: We thank the reviewer for pointing out the need for explicit definitions. In the revised manuscript, we have\nrephrased this into “secondary oxidation artifacts” which we define earlier.\nComment: How is the \"average modification extent (AME) per peptide\" defined, is that the percentage of peptide modified\nwith a specific Da shift? needs a definition.\nResponse: We thank the reviewer for the feedback. In the present study, the major oxidation products detected were net\nadditions of one or more oxygen atoms for all peptides modified. The major mass shifts observed include +15.995 Da (+O),\n+31.990 Da (+2O) and +47.985 Da (+3O). All of them were used for quantitation of modification extent. In short, the average\nnumber of oxidation events per peptide molecule (APO, or Average Peptide Oxidation) was determined by summing the ion\nabundance (IA) of each peptide oxidation product multiplied by the number of oxidation events on the peptide required to\ngenerate that product and divided by the sum of IA for all oxidized and unoxidized versions of that peptide, as shown in the\nfollowing equation:\n1∙𝐼𝐴 (+𝑂)+2∙𝐼𝐴 (+2𝑂)+3∙𝐼𝐴 (+3𝑂)+⋯\n𝐴𝑃𝑂 =\n𝐼𝐴 (𝑢𝑛𝑚𝑜𝑑𝑖𝑓𝑖𝑒𝑑)+𝐼𝐴 (+𝑂)+𝐼𝐴 (+2𝑂)+𝐼𝐴 (+3𝑂)+⋯\nThe average modification extent (AME) per peptide refers to the average APO per peptide in 2 technical replicates.\nIn the revised manuscript, we have clarified the definition.\nReviewer #2 (Remarks to the Author):\nThe authors describe radical protein footprinting (RPF) with mass spectrometry detection on proteins in whole blood,\nrepresenting an expansion of footprinting methods to more biologically relevant samples. The authors demonstrate that a\ndifferent radical precursor (i.e. persulfate) than hydrogen peroxide, which is typically used in RPF, is needed because of the\nhigh concentration of catalase in blood that causes foaming in the presence of hydrogen peroxide.\nOverall, I think the manuscript should be published after some significant revisions. The ability to do RPF in whole blood is\nimportant, but the manuscript needs some additions and changes, which are listed below, to make it suitable for publication.\nComment: 1. Because Figure 2 primarily reports the results of H O treatment of blood, which is not used in the rest of the\n2 2\nmanuscript, I recommend that this Figure be moved to the SI. This move would make room for an additional figure that I\nrecommend below.\nResponse: We appreciate the reviewer’s suggestions. This Figure has been moved to the supplementary in the revised\nmanuscript.\nComment: 2. How is the 'Modification extent' shown on the y-axes of Figures 4, 6, 7, and 8 calculated? This information\nshould be included in the methods section.\nResponse: We have revised the Proteomic data processing section to explicitly describe the quantitation workflow in\nFoxWare software and filtering criteria applied in the parameters.\nComment: 3. In discussing the data associated with Figure 6, the authors indicate that 20% of the peptides from extracellular\nproteins exhibit an average modification extent of greater than 0.3, while only 1.5% of the intracellular proteins passed this\nthreshold. For some frame of reference, it would be helpful to indicate what percentages of peptides from a pure protein in\nbuffered solution would exceed an average modification extent of 0.3.\nResponse: In this study, the 0.3 modification extent threshold was not derived from measurements of a pure protein in\nbuffered solution. Rather, it was chosen solely as a comparative benchmark to highlight the difference between extracellular\nand intracellular proteins under the same experimental conditions. However, for reference, our in vitro RPF data with\nisolated complement C3 showed that ~35% of the oxidized peptides had greater modification extent than 0.3. This is broadly\nin line with what we commonly observe for in vitro oxidation of proteins, and would be consistent with a mild decrease in\noxidation of extracellular proteins in blood due to increased scavenging coupled with a large decrease in oxidation of\nintracellular proteins in blood. We have included a description of the C3 in vitro oxidation in the manuscript. The in vitro\nRPF results of complement c3 are shown in Supplementary Figure S7 in the revised manuscript.\nComment: 4. The authors note that three peptides from intracellular proteins have significant differences in the extent of\nmodification between the WT and T2DM mice. Can the authors speculate about the structural or biological significance of\nthese observations? Or, are these changes simply method related (e.g. differential permeability of persulfate into blood cells\nfrom the different samples)? If the authors are going to note this observation, then some comment on it would improve the\nmanuscript.\nResponse: We thank the reviewer for the comment. Our observations of intracellular proteins are included for the sake of\ncompleteness. Because the overall amount of oxidation is much less for intracellular proteins than extracellular, it would be\nchallenging to use the current protocol for robust measurement of intracellular protein topography. It is for that reason that we\nhave focused on interpretation of extracellular protein results. It is possible that these results reflect actual topographical\nchanges – an increase in methemoglobin levels has been reported in RBCs incubated in diabetic plasma, which could\npotentially impact both beta-globin and flavin reductase conformation and/or interactions [1]. The portion of beta-globin that\nis protected in T2DM has interactions with both the heme and the neighboring alpha-chains. The protected portion of flavin\nreductase includes a region in the NADP binding site. Plausible interpretations of these data are possible; however, we are\nreluctant to include such interpretations of data that we believe are not ideal due to the low modification extent. We would\nprefer to include the data for community review, but not speculate on potential causes until we are able to generate much\nbetter oxidation levels for intracellular proteins. We have included a statement in the manuscript suggesting caution when\ninterpreting intracellular protein footprinting results due to the low level of oxidation.\nWe do not believe that the modification differences observed are methodological, e.g. differential permeability of persulfate\nto the T2DM RBCs, or differential extracellular presence of these proteins in T2DM. Such differences would result in a\nglobal decrease in almost all peptides observed, rather than just the three peptides (two overlapping) that showed protection\nin T2DM. To the contrary, we see several peptides that show statistically-insignificant increases in mean oxidation in T2DM,\nwith most showing little to no change in mean oxidation.\n[1] Chemlal H, Bournine L, Mimoune S, Boufeniche S, Beddou L, Bensalem S, Iguer-Ouada M. Close relationship between\nhigh HbA1c levels and methemoglobin generation in human erythrocytes: The enhancement of oxidative stress in the\nprocess. J Diabetes Complications. 2023 Aug;37(8):108543. doi: 10.1016/j.jdiacomp.2023.108543. Epub 2023 Jun 13.\nPMID: 37331270.\nComment: 5. In discussing the data in Figure 7, the authors note that \"Oxidation coverage of the detected peptides ranged\nfrom sparse to very high, which is consistent with reported findings…\" I think that they mean that this observation is\nconsistent with other in vivo findings, correct? The ‘in vivo’ qualifier should be added to the text.\nResponse: We thank the reviewer for your suggestions. We have added the ‘in vivo’ qualifier to the text.\nComment: 6. It appears that there are 4 biological replicates for the data shown in Figures 6 and 7. I think that the methods\nsection says blood from 4 mice (of each type) were taken, but it would be good to note this value in the figure captions.\nResponse: We have added this value in the figure captions in the revised manuscript.\nComment: 7. In Figure 7, are the peptides indicated in parts A-E only those that are oxidized or are these all the detected\npeptides? This information would be helpful for knowing if the information is limited by overall sequence coverage or are\nonly certain peptides oxidized (while more are not)?\nResponse: The peptides in original Figure 7 are oxidized peptides only. We have only included oxidized peptides for\ncomparison in this study. The sequence coverage of top 11 proteins analyzed is shown in Supplementary Table S2. We have\nclarified this in the revised manuscript.\nComment: 8. The structures shown in Figure 7G and F are small and difficult to see. Perhaps the authors could put these\nstructures in their own figure. If Figure 2 is moved to the SI, as suggested above, then the total number of figures would be\nthe same.\nResponse: We appreciate the reviewer’s suggestions. Larger and clearer structures of C3 and transferrin have been included\nin the revised manuscript, as shown in Figure 6 and 7.\nComment: 9. Any speculation as to what specific factors cause the alterations in the protein surface accessibility of\ncomplement c3 and serotransferrin peptides that are noted to change? Some biological or structural explanation would\nsubstantially strengthen the paper.\nResponse: We appreciate the reviewer’s suggestions. In the revised manuscript, we demonstrate the conformational change\nof C3 detected by our RPF approach reflects the complement activation in T2DM by assessing the C3 and its activated\nproduct (C3b) with ELISA. The C3 ELISA assay is specific for mouse C3, while the C3b ELISA kit uses antibodies raised\nagainst C3b, and these antibodies recognize epitopes that are preserved in C3b and its downstream fragments. As a result, the\nassay detects activated C3 species (C3b, iC3b, and C3c) but does not detect intact native C3. Thus, the measured signal\nreflects the overall level of C3 activation, with C3b representing the major and immediate product and its derivatives\ncontributing to the total detected activated C3 cascade. The result is shown in Figure 6. We also found that the conformational\nchanges in transferrin is a result of increasing transferrin iron saturation in T2DM, which has been validated in the revised\nmanuscript by measuring the serum iron and transferrin iron binding capability. The result is shown in Figure 7.\nComment: 10. The comparison of the in vitro footprinting of complement c3 to the in-blood results is interesting and\nimportant; however, the details about in vitro data must be included in the manuscript, beyond what is shown in Figure 8. The\nauthors need to add the actual data in Table form or bar graph form, probably to the SI. It would also be helpful to map the\nfootprinting results from the in vitro experiments on the structure of complement c3; this could go in the SI as well. In my\nopinion, this information is essential for indicating the sequence coverage, the different extents of modification, etc. that are\nseen in-blood vs. in vitro footprinting.\nResponse: We appreciate the reviewer’s suggestions. We have added the in vitro complement c3 oxidation bar graph in the\nnew Supplementary Figure S7 A, and the footprinting results from the in vitro experiments is mapped on the structure of\ncomplement c3 in Figure S7 B in the revised manuscript.\nReviewer #3 (Remarks to the Author):\nThe paper describes a method to detect peptides accessible to oxidation in the most abundant extracellular proteins present in\nblood.\nComment: Given that the structure of C3, including its conformational changes during activation, has been extensively\nstudied, the authors should make an effort to interpret their findings (differences in peptide accessibility) in the context of\nexisting knowledge about C3. Can differences be attributed to the presence of various conformational forms of C3 like C3b,\niC3b, C3d? Can C3 be glycated and therefore less accessible?\nResponse: We appreciate the reviewer’s valuable comments. In the revised manuscript, we demonstrate the conformational\nchange of C3 detected by our RPF approach reflects the complement activation in T2DM by assessing the C3 and its\nactivated product (C3b) with ELISA. The C3 ELISA assay is specific for mouse C3, while the C3b ELISA kit uses antibodies\nraised against C3b, and these antibodies recognize epitopes that are preserved in C3b and its downstream fragments. As a\nresult, the assay detects activated C3 species (C3b, iC3b, and C3c) but does not detect intact native C3. Thus, the measured\nsignal reflects the overall level of C3 activation, with C3b representing the major and immediate product and its derivatives\ncontributing to the total detected activated C3 cascade. The result is shown in Figure 6. We also found that the conformational\nchanges in transferrin is a result of increasing transferrin iron saturation in T2DM, which has been validated in the revised\nmanuscript by measuring the serum iron and transferrin iron binding capability. The result is shown in Figure 7.\nComment: Why was canine blood used to test for morphological changes? Wouldn’t it be more appropriate to focus on a\nsingle species (e.g., mouse) or, alternatively, include a broader range of species (including mouse) for comparative purposes?\nResponse: Canine blood was used to reduce the number of animals necessary to be sacrificed, as the canine blood was excess\nobtained during the routine course of veterinary care. We think that potential differences in gross morphological properties\nbetween canine blood and murine blood would be minimal, making canine blood a suitable replacement. However, we\nrecognize that opinions may reasonably differ on this matter. As such, we have included mouse blood for morphological\nchanges in the revised manuscript (Figure 4).\nComment: Since intracellular proteins were apparently not oxidized, presumably due to the poor permeability of sodium\npersulfate, wouldn’t it be more straightforward to use plasma-EDTA as the starting material?\nResponse: We thank the reviewer for the comment. The reviewer is correct: plasma would almost certainly easier to analyze,\nas would serum. By tackling whole blood, generalizability is much more reasonably inferred than if we started with plasma.\nGiven the complexities that exist, one can foresee cases when plasma or serum would be inappropriate for examination of\nextracellular proteins (e.g. cell surface-associated extracellular proteins). Using whole blood successfully gives us maximum\nflexibility in sample analysis; this same approach could almost certainly be used with plasma or serum. We have included this\ninference in the discussion, with caveats that it needs to be tested.\nComment: In Figures 6 and 7, it is unclear which data points correspond to wild-type and which to db/db mice. The symbols\nare too small, and the color coding of the bars is not explained in the legend.\nResponse: We appreciate the reviewer’s valuable feedback. We have included the color coding in the legend in original\nFigure 6 and 7 in the revised manuscript, and have enlarged the symbols.\nComment: What conclusions can be drawn regarding protein conformation or function based on the presented data? C3 is a\nsecreted protein present at high concentrations in blood, but it is also expressed intracellularly. In particular, the intracellular\nform of C3 in pancreatic beta cells has been associated with diabetes development. Therefore, the claim that “In-blood RPF\nfound significant differences in complement C3 topography in T2DM mice compared to WT, indicating that we have\ndetected a structural basis behind the role of complement C3 in T2DM” appears to be an overstatement.\nResponse: We thank the reviewer for the valuable comments. In the revised manuscript, we demonstrate the conformational\nchange of C3 detected by our RPF approach reflects the complement activation in T2DM by assessing the C3 and its\nactivated product (C3b) with ELISA. The result is shown in Figure 6. We also found that the conformational changes in\ntransferrin is a result of increasing transferrin iron saturation in T2DM, which has been validated in the revised manuscript by\nmeasuring the serum iron and transferrin iron binding capability. The result is shown in Figure 7.\nComment: It is unclear how ref 32 pertains to role of extracellular C3 in diabetes, better ones would be:\nAdipsin preserves beta cells in diabetic mice and associates with protection from type 2 diabetes in humans.\nGómez-Banoy N, Guseh JS, Li G, Rubio-Navarro A, Chen T, Poirier B, Putzel G, Rosselot C, Pabón MA, Camporez JP,\nBhambhani V, Hwang SJ, Yao C, Perry RJ, Mukherjee S, Larson MG, Levy D, Dow LE, Shulman GI, Dephoure N, Garcia-\nOcana A, Hao M, Spiegelman BM, Ho JE, Lo JC.Nat Med. 2019 Nov;25(11):1739-1747. doi: 10.1038/s41591-019-0610-4.\nEpub 2019 Nov 7.PMID: 31700183\nC3aR1 on β cells enhances β cell function and survival to maintain glucose homeostasis.\nPereira de Lima R, Li A, Gilani A, Rubio-Navarro A, Warren CD, Kong IY, Geri JB, Lo JC.Mol Metab. 2025 Jun;96:102134.\ndoi: 10.1016/j.molmet.2025.102134. Epub 2025 Apr 4.PMID: 40189102\nFor roles of intracellular C3 in diabetes please see:\nIntracellular cytosolic complement component C3 regulates cytoprotective autophagy in pancreatic beta cells by interaction\nwith ATG16L1.\nKing BC, Renström E, Blom AM.Autophagy. 2019 May;15(5):919-921. doi: 10.1080/15548627.2019.1580515. Epub 2019\nFeb 20.PMID: 30741587\nIntracellular C3 protects β-cells from IL-1β-driven cytotoxicity via interaction with Fyn-related kinase.\nKulak K, Kuska K, Colineau L, Mckay M, Maziarz K, Slaby J, Blom AM, King BC.Proc Natl Acad Sci U S A. 2024 Feb\n20;121(8):e2312621121. doi: 10.1073/pnas.2312621121. Epub 2024 Feb 12.\nResponse: We thank the reviewer for the valuable inputs on the role of complement C3 in diabetes. In the revised\nmanuscript, we have replaced ref 32 accordingly.\nComment: Some spelling mistakes need to be sorted out like ”Boday weight” in table S1.\nResponse: We thank the reviewer for pointing this out. The typo error “Boday weight” in Table S1 has been corrected to\n“Body weight,” and the manuscript has been carefully proofread to address any other spelling mistakes.\nReviewer #4 (Remarks to the Author): In this manuscript by Zhao et al, the authors describe radical protein foot printing\n(RFP) in mammalian whole blood of mice that are WT or BKS.Cg-Dock7m+/+ Leprdb/J, a mouse model of type 2 diabetes\n(T2D). Using state of art techniques, they labelled proteins with minimal disruption of RBC morphology and show oxidative\nmodifications of both intracellular and extracellular proteins. While I am aware of the technique, I am not familiar with the\nfine details and therefore my review will avoid assessing the methodology and will focus mainly, but not exclusively, on the\n“diabetes findings” comparing WT with T2D mice.\nComment: 1. In Figure 5: using NaCl at 200mM represents significant “hypertonic” conditions and it is therefore not\nsurprising to see those morphological changes. Did the authors measure cell size? Also, are the authors concerned that such\nmorphological changes may have resulted in increased cellular stress (which may affect intracellular proteins)? Also, how\nlong was the exposure to these hypertonic conditions (should be made clear in the Figure legend). Finally, the authors may\nwish to better clarify why canine RBCs were used.\nResponse: We thank the reviewer for the valuable comments. We included mouse blood for morphological changes in the\nrevised manuscript. We have measured cell size and also performed hemolysis test on the effects of sodium persulfate at\n200mM to the RBCs integrity in mouse blood. The results are included in the revised manuscript. Those morphological\nchanges are measured immediately after the exposure to these hypertonic conditions. We have made this clear in the Figure\nlegend in the revised manuscript.\nComment: 2. In Figure 6: it is reassuring to see α-globin and β-globin oxidation (part of haemoglobin). However, what about\ncytoskeletal proteins (i.e. spectrin and actin); were these supposed to show differences? The same applies to RBC membrane\nproteins. Would be interesting to know the views of the authors.\nResponse: As shown in the figure below for review purposes only, our dataset revealed oxidation in a few peptides from\nmembrane or peripheral membrane proteins, including band 3 anion transport protein and ankyrin 1. In contrast, the modified\npeptides in the two major cytoskeletal proteins, actin and α-spectrin, exhibited relatively low levels of oxidation (less than 0.1\nAME maximum). Moreover, no significant differences in oxidation extent were observed between T2DM and WT samples\nfor these proteins. We also note that all data have been made publicly available to enable the community to explore proteins\nof interest.\nReview Figure 1. Comparison of in-blood RPF of membrane or cytoskeleton proteins detected in WT and T2DM\nwhole blood. (A) band 3 anion transport protein (average sequence coverage: 51%); (B) actin (average sequence coverage:\n47%); (C) ankyrin 1 (average sequence coverage: 33%); (D) α-spectrin (average sequence coverage: 42%); Blood was\nsampled from 4 mice of each condition. The modification extent at 0V was subtracted for each peptide.\nOnly oxidized\npeptides were included for comparison. No significant difference was found between T2DM and WT samples by unpaired T-\ntest after Šídák correction.\nComment: 3. In Figure 7: these data are very interesting indeed. I suggest adding to the Figure legend before the volcano\nplot “Figure 7A-E show that the highest and broadest modifications occurred in two proteins, serotransferrin and complement\nC3\". Also, I suggest a slight expansion of the discussion to better cover the findings in this Figure.\nResponse: We thank the reviewer for the valuable comments. To be more precise, we have revised the statement to indicate\nthat the greatest changes in modification levels between T2DM and WT were observed in two proteins: complement C3 and\nserotransferrin. In the revised manuscript, we demonstrate the conformational change of C3 detected by our RPF approach\nreflects the complement activation in T2DM by assessing the C3 and its activated product (C3b) with ELISA. The C3 ELISA\nassay is specific for mouse C3, while the C3b ELISA kit uses antibodies raised against C3b, and these antibodies recognize\nepitopes that are preserved in C3b and its downstream fragments. As a result, the assay detects activated C3 species (C3b,\niC3b, and C3c) but does not detect intact native C3. Thus, the measured signal reflects the overall level of C3 activation, with\nC3b representing the major and immediate product and its derivatives contributing to the total detected activated C3 cascade.\nThe result is shown in Figure 6. We also found that the conformational changes in transferrin is a result of the serum iron and\nincreasing transferrin iron saturation in T2DM, which has been validated in the revised manuscript by measuring the serum\niron and transferrin iron binding capability. The result is shown in Figure 7.\nComment: 4. Discussion: The sentence “Complement c3 has emerged as a significant contributor but also a potential effector\nof disease progression of T2DM” is an overstatement and needs to be toned down. There are certainly changes in the\ncomplement system in T2D but these are mainly associations (as part of the metabolic derangement) and the evidence for\nC3 causing the progression of diabetes is weak at best (despite some mechanistic studies showing a potential causative\nlink). Rather than focusing on C3 changes as the cause for diabetes progression, the authors may wish to discuss the\npotential role of protein oxidation in the development of vascular complications of diabetes (through increased inflammation),\nwhich would be far more interesting. Also, the discussion needs a bit more on the limitations of the current technique at\nassessing intracellular protein modifications (while this is mentioned, it is somewhat indirect and needs to be more explicit).\nResponse: We agree with the reviewer’s critique, and have toned down the statement as: Complement c3 has been reported\nto be linked to the disease progression of T2DM.\nIn addition, the limitations of the current technique at assessing intracellular protein modifications have been explicated in the\nrevised discussion in the manuscript."}, {"round": 2, "reviewer_comments": {"reviewer_1": "I stand corrected that blood can be called a mammalian tissue - I was not aware of that. Nevertheless,\n\"blood samples\" vs \"tissue samples\" have distinct meanings in biomarker research.\nThe authors have addressed all my comments and also implemented changes or expanded the\ndiscussion where appropriate, which has considerably strengthened the manuscript particularly for\nthose not familiar with the approach and details of the technique. I can now recommended that the\npaper be published in the journal \"as is\".", "reviewer_2": "I am generally fine with the authors' revisions, and I do not think any additional changes are necessary. I\nwould like to make the following point, which might be helpful for the authors as they consider doing\nmore protein footprinting on blood in the future.\nI agree that interpretation of the intracellular protein footprinting results must be done cautiously due to\nthe low levels of oxidation, and it is good that the authors have added a comment to that effect.\nHowever, might the high concentration of iron in RBCs cause catalytic production of radicals from\npersulfate (such chemistry is well known - J. Am. Chem. Soc. 1974, 96, 860-869)? Considering that and\nknown perturbations to iron homeostasis in T2DM, the 'background' oxidation might be different and\nmore structurally localized inside the cell for this blood. I don't think the authors need to comment on\nthis in their manuscript, but they might consider more the role that iron could play in the production of\npersulfate radicals, especially if iron concentrations are different in different samples.", "reviewer_3": "When applied to C3, this very complex method appears to indicate only that C3 is activated in a mouse\nmodel of diabetes. As this can be readily measured using a simple ELISA, it is unclear how the method\nadvances our understanding of blood proteins in diabetes.", "reviewer_4": "Thank you for addressing my comments."}, "author_response": "Response: We sincerely thank the reviewer for their thoughtful comments and careful evaluation of our\nmanuscript. We appreciate the clarification regarding terminology and are grateful for the constructive\nfeedback, which has helped strengthen the clarity and accessibility of the work. We are pleased that the\nrevisions have addressed all concerns and thank the reviewer for recommending the manuscript for\npublication.\nResponse: We thank the reviewer for this insightful comment.\nResponse: We respectfully disagree with this assessment. First, the measurement of complement\nactivation was made during a proteome-wide measurement of the blood. While one could measure\ncomplement activation by ELISA after the fact (which, indeed, we took advantage of for validation\npurposes), one would not know to look at complement activation a priori. The same is true of serum\ntransferrin iron loading—these were validation tests whose very use was prompted by our structural\nproteomics data. Moreover, while we focused on the top eleven proteins for the sake of making the data\nset tractable, the data (which are publicly available to the readers) includes information on a wide\nvariety of extracellular proteins. ELISA is excellent for targeted analyses, but the method presented here\noffers proteome-wide analyses which enables discovery well beyond ELISA.\nFinally, while ELISA measurements report bulk abundance or activation state, our approach provides site-\nresolved, structural information on oxidative modifications that report on protein conformation and\ninteraction states in native whole blood. Importantly, the goal of this study is not to replace established\nassays, but to demonstrate the feasibility of in-blood radical protein footprinting as a structural\nproteomics tool, enabling insights into protein structure and dynamics in complex, physiologically\nrelevant environments.\nResponse: We thank the reviewer for their time and thoughtful evaluation of our manuscript. We\nappreciate the constructive feedback and are glad that our revisions addressed your comments."}]

Decision letter