Albumin-On-A-Chip: Binding Profiling of Circulating Human Albumin via Selective Immunocapture and Real-Time SPR Analysis

Albumin-On-A-Chip: Binding Profiling of Circulating Human Albumin via Selective Immunocapture and Real-Time SPR Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Albumin-On-A-Chip: Binding Profiling of Circulating Human Albumin via Selective Immunocapture and Real-Time SPR Analysis Marta Nugnes, Maurizio Baldassarre, Paolo Caraceni, Marina Naldi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7190507/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Mar, 2026 Read the published version in Scientific Reports → Version 1 posted 13 You are reading this latest preprint version Abstract A cost-effective surface plasmon resonance (SPR)-based sensing platform was developed to evaluate alterations in albumin binding capacity under clinically relevant conditions. This ex vivo approach enables real-time assessment of albumin–ligand interactions using albumin directly isolated from plasma, thus overcoming key limitations of conventional in vitro approaches. The sensing surface was prepared by covalently immobilizing a polyclonal anti-albumin antibody onto a CM5 chip, followed by a single-step immunocapture of albumin from patient plasma samples. Mass spectrometry confirmed the selective retrieval of both native and structurally modified albumin forms, preserving their relative abundance and disease-associated microheterogeneity. The sensing surface demonstrated high reusability and analytical reproducibility over ~ 500 capture–release cycles, significantly lowering per-sample costs. Functional validation was conducted using ligands targeting the three main albumin binding sites. As proof of application, the system was used to investigate albumin binding properties in plasma from (i) type 2 diabetic patients with (n = 10) and without (n = 10) moderate kidney impairment, and (ii) patients with cirrhosis and acute-on-chronic liver failure (n = 6), a condition associated with extensive albumin damage. The proposed approach provides a robust analytical framework for the functional characterization of circulating albumin in healthy and diseased conditions. Biological sciences/Biochemistry Health sciences/Biomarkers Health sciences/Medical research sensing device surface plasmon resonance ex vivo binding studies personalized profiling albumin functional alterations mass spectrometry Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Human serum albumin (HA) is the most abundant plasma protein and plays a central role in maintaining oncotic pressure, exerting antioxidant effects, and transporting a wide variety of endogenous and exogenous ligands, including fatty acids, hormones, metal ions, and pharmaceutical compounds 1 – 3 . Its ligand-binding versatility arises from a flexible, multidomain structure, which features several binding pockets, most notably Sudlow sites I and II, and site III 4 – 6 . HA–ligand interactions contribute to drug solubility and distribution, influencing pharmacokinetics and therapeutic efficacy 7 . Because these functional properties depend on HA’s structural integrity, structural alterations can impact its folding, binding affinity, and clearance 8 . HA exists in plasma as a heterogeneous mixture of native and modified forms. This microheterogeneity is dynamic and reflects physiological and pathological conditions. Structural modifications, including oxidation, glycation, cysteinylation, and terminal truncations, are known to increase in settings of systemic inflammation and oxidative stress, such as liver or kidney disease and diabetes 9 – 11 . Structural changes were reported to impact the binding capacity of HA toward clinically relevant ligands and drugs, including warfarin 12 – 14 , nonsteroidal anti-inflammatory drugs 15 , sulfonylureas 16 , and others 17 , which may compromise drug efficacy and safety. Most studies of HA binding have relied on in vitro models using chemically modified, commercially available HA. These models typically assess the impact of single alterations, often without detailed structural characterization of the modified forms 18 . As a result, they fail to replicate the complex mixture of HA forms present in clinical samples, where multiple modifications coexist and evolve in response to disease severity and patient condition. Additionally, in vitro assays generally use defatted HA, whereas HA circulates bound to fatty acids, which are known to influence ligand binding 19 , 20 . These limitations have led to divergent findings across studies 21 . While some ex vivo approaches have been proposed, including direct plasma studies or HA isolation prior to binding assays, these are either confounded by the presence of other binding proteins or involve time-consuming purification steps. There remains a need for analytical strategies capable of assessing HA binding in clinically relevant samples, preserving structural microheterogeneity, and enabling efficient, reproducible measurements 21 – 24 . In this context, the present study aimed to develop a cost-effective and reusable sensing surface for the real-time assessment of HA binding properties under clinically relevant conditions. A sensor chip was functionalized with a covalently immobilized anti-HA antibody, enabling selective, single-step immunocapture of HA from patient plasma without any extensive pretreatment. To ensure broad applicability, the setup was designed to be compatible with high-throughput use, minimal sample preparation, and low per-analysis costs. Surface plasmon resonance (SPR) was employed for binding measurements due to its sensitivity and real-time monitoring capabilities. Although SPR has been extensively applied to the study of biomolecular interactions, its use with complex biofluids remains limited 25 . Prior SPR studies involving HA have largely relied on commercial preparations or covalent immobilization methods that do not capture circulating microheterogeneity 26 – 31 . Here, as proof-of-concept of application, we applied the newly developed sensing surface to assess HA binding in two patient cohorts characterized by distinct levels of HA structural damage: (i) patients with type 2 diabetes mellitus, with or without moderate kidney impairment (n = 10 each), and (ii) patients with cirrhosis and acute-on-chronic liver failure (n = 6), a condition associated with extensive HA modification 11 , 32 – 34 . Results and discussion Design of the sensing surface The strategy for designing an analytical device capable of capturing albumin in a single step from patient plasma was defined, considering its final application: performing in vitro binding studies on a sensing surface that reflects patient-specific HA heterogeneity. Hence, SPR technology was selected because it represents one of the most suitable methods for studying biorecognition phenomena in real-time, with a mid-throughput wizard-supported workflow that is well-suited to the aims of this work. The ability to detect both weak and strong interactions, along with easy access to affinity and kinetic data on complex formation/disruption, makes this technique highly informative. To generate the SPR sensing surface, we opted for immunocapture-based immobilization of HA, as this approach enables the selective immobilization of the plasma target protein without pre-purification while minimizing the risk of contamination from other plasma proteins. Indeed, direct immobilization of circulating HA through covalent coupling would not provide the necessary selectivity, as competing, abundant plasma proteins would also be bound to the sensor chip surface, leading to a multi-protein sensing surface. Additionally, the immunocapture approach also ensures the device is cost-effective. Indeed, immunocapture, as a reversible immobilization process, allows for the removal of the target molecule from the sensing surface through a suitable surface regeneration procedure without damaging the capturing antibody. This allows for the repeated use of the same “activated” sensing surface over multiple analysis cycles. To this end, we first prepared an anti-HA sensor chip by covalently immobilizing a polyclonal anti-HA antibody using a well-established covalent immobilization procedure 35 . Then, the anti-HA sensor chip was used to capture HA from plasma samples without any pre-purification step. The amount of plasma needed to assess HA affinity toward an analyte is limited to a few dozen microliters. After the analysis cycle is completed, the capture surface is regenerated. Surface regeneration prepares the sensing surface for reuse in another capture cycle, enabling multiple analysis cycles. The general design and workflow are summarized in Fig. 1 . Validation of polyclonal anti-HA antibody for quantitative capture of HA microheterogeneity. To effectively sample the various forms of HA present under both physiological and pathological conditions, it is essential that the immunocapture method allows for the comprehensive collection of all circulating HA forms while maintaining their relative abundances. To evaluate this, we assessed the capturing performance of the selected commercial polyclonal anti-HA antibody against circulating HA using liquid chromatography-mass spectrometry (LC–MS). This technique is crucial for distinguishing among the structurally altered forms of albumin, which differ in mass. Since SPR cannot be directly interfaced with mass spectrometry, the polyclonal anti-HA antibody was covalently bound to a short monolithic column (CIMac-αHSA, 5.0 mm × 5.2 mm I.D.), and the antibody’s capturing performance was evaluated using plasma samples characterized by varying albumin integrity and different microheterogeneity profile (namely samples from patients with type 2 diabetes mellitus - T2DM, with and without renal impairment). The relative abundances of the immunocaptured HA forms were profiled by LC-MS/MS and compared to those in untreated samples. As depicted in Fig. 2 , no significant differences (P > 0.5) were observed between the relative levels of HA forms before and after extraction for both sets of samples, although their HA microheterogeneity profiles were markedly different. In addition, mass spectrometric analysis confirmed that no other plasma proteins were co-captured under the applied conditions. These results demonstrate that the selected anti-HA antibody effectively captures native and modified HA forms, preserving their relative abundance and, hence, reproducing disease-associated HA microheterogeneity profiles. Development and validation of the sensing surface As mentioned above, the sensing surface was developed in two steps: first, the anti-HA antibody was covalently bound to the surface to provide a stable immunocapturing sensor chip; second, this anti-HA sensor chip was used to reversibly immunocapture HA. In the first step, an anti-HA sensor chip was obtained by covalently immobilizing the selected anti-HA antibody onto the carboxymethyl dextran layer of a CM5 sensor chip using an established amine coupling reaction 37 . Optimal preconcentration conditions were achieved at pH 5.0. The final immobilization level was 18,000 RU. The immunocapture procedure used to obtain the anti-HA sensing surface was initially optimized using the commercial HA. To maximize the capture level, the concentration of the HA solution, flow rate, and contact time were optimized (Supplementary Fig. S1 ). The maximum capture level was achieved when a 50 µM HA solution was infused over the anti-HA sensor chip at a rate of 5 µL/min for 840 s. Under optimized conditions, reversible HA immobilization was achieved in a single step in approximately 5 min. Based on these data, for ex vivo studies, the total HA concentration was normalized to 50 µM prior to immunocapture to achieve similar immobilization levels across all samples ( Fig. 3 ). Surface regeneration was achieved by injecting glycine buffer at pH 2.0, followed by 0.1 N NaOH. This step enabled the removal of HA from the chip surface without damaging the antibody, hence allowing restoration of the chip surface for further capture and analysis cycles. After regeneration, blank injections were performed to monitor the baseline stability and account for systematic and random variations. Regeneration conditions did not significantly affect the antibody binding capacity, as shown by the lack of a significant difference in the capture efficacy after two subsequent capture cycles ( Supplementary Fig. S2 ). The HA sensing surface was validated prior to its application to plasma samples from the study participants. False-positive interactions were ruled out by analyzing galantamine, a non-binding drug, confirming no interaction with HA 27 . On the other hand, to assess whether HA maintains its unaltered binding capacity at its three high-affinity binding sites, three reference binders were analyzed, namely, (i) phenylbutazone (PBZ), a marker for Sudlow site I 37 ; (ii) dansyl-L-phenylalanine (DAP), a marker for Sudlow site II 38 ; and (iii) biliverdin (BVD), a marker for site III 39 . For all markers, a good concentration–response relationship was observed ( Supplementary Fig. S3 ). Notably, for BVD, significant interactions with the anti-HA antibody were observed, as confirmed by injecting BVD on the bare anti-HSA sensor chip without any immobilized HA. Hence, to properly account for those “aspecific” interactions, investigations involving BVD were performed using a sensor chip with the antibody immobilized in both sample and reference flow cells. The K D values obtained for PBZ, DAP, and BVD were in good agreement with those reported in the literature (PBZ: 14 ± 0.5 µM vs 0.12–3.3 µM 4041 ; DAP: 1.7 ± 0.3 µM vs 6.0 µM 5 ; BVD: 13.0 ± 3.0 µM vs 10 − 6 -10 − 8 M 42 ). Application of the HA-sensing surface for the evaluation of HA-binding properties in cirrhotic patients and DKD patients Ex vivo assessment of HA binding functions in patients with decompensated cirrhosis The validated sensing surface was utilized in a pilot study examining HA binding functions in patients with decompensated cirrhosis and ACLF, a syndrome characterized by elevated systemic inflammation and oxidative stress, as well as reduced levels of circulating HA. Indeed, several reports have highlighted that severe HA damage is encountered in advanced stages of liver cirrhosis and is mainly associated with high levels of oxidation 11 , 32 , 43 . Due to the accumulation of these altered molecular forms, the amount of native, fully functional HA significantly decreases 44 . Furthermore, clinical evidence of altered HA binding properties in ACLF patients was observed together with alterations in its conformation 20 , 22 . Based on these observations and as proof of concept of the application of the proposed approach to real samples, plasma samples from 6 hospitalized patients with ACLF (2 males and 4 females, aged 68–72) and 6 age-matched healthy volunteers (CTRL, 5 males and 1 female, aged 38–73) were selected. HA microheterogeneity in the samples under study was initially profiled by LC-MS analysis ( Supplementary Tab. S1 ) 36 , 45 . Analysis showed that, compared with healthy individuals, ACLF patients presented a drastically lower relative amount of the native form of HA (nHA) (8.5% vs 43.1%) and a concomitant significant increase in the oxidized forms of HNA1 (from 37.9 to 87.9%) and glycated forms (from 11.6 to 23.0%). For each subject, the HA binding capacity at the three high-affinity binding sites was evaluated by deriving K D values for PBZ, DPA, and BVD ( Supplementary Table S2 ). Furthermore, the affinity of teicoplanin (TEICO), a non-site-specific HA binder 46 commonly administered to cirrhotic patients to counteract infections, was also evaluated ( Supplementary Fig. 4 and Supplementary Tab. S2 ). HA from ACLF patients showed a slightly greater affinity for PBZ at Sudlow site I than did HA from CTRL subjects (P00.0280) (Fig. 4 a). On the other hand, no significant differences in affinities for DPA or BDV were detected at sites II and III, respectively (Figs. 4 b and 4 c). Indeed, notwithstanding the extensive structural changes that HA undergoes in ACLF patients, binding properties at high-affinity binding sites are quite preserved, although a warning might be considered for drug binding at Sudlow site I. Importantly, these findings should be considered preliminary because the study was undertaken as proof-of-application for the developed device, hence involving a limited number of patients. Interestingly, a significant alteration in the TEICO binding capacity was observed in ACLF patients, in which structural changes affecting HA led to an overall reduction in its binding affinity (Fig. 4 d). To our knowledge, this is the first study to investigate the binding of TEICO in ACLF patients. Since teicoplanin is one of the antibiotics of choice for treating infections in cirrhotic patients, these results are potentially relevant and require further evaluation, especially considering that ACLF patients also exhibit reduced plasma levels of HA (hypoalbuminemia) 44 , 47 , 48 . Ex vivo assessment of HA binding functions in patients with T2-DM A second pilot study involved a small cohort of diabetic patients with renal impairment (DM + DKD). Indeed, exacerbated inflammation and oxidative stress are also typical pathological conditions in patients suffering from DKD and are major causes of morbidity and mortality in patients with DM. In agreement with this observation, more oxidized forms have been observed in albumin from DM patients [13,14]. Additionally, patients may also experience hypoalbuminemia due to alterations in glomerular filtration, a condition that may exacerbate HA dysfunction. As a pilot screening, 20 diabetic patients were selected: 10 subjects without renal damage (DM-DKD) (4 females and 6 males; aged 46–87 years), and 10 subjects classified according to KDIGO classification parameters 50 as subjects with very high risk renal impairment (DM + DKD) (1 female and 9 males; aged 28–71 years) 50 . Previous investigations have shown that HA from DM + DKD patients also undergoes structural damage, although to a more limited extent when the glycemic level is under drug control 51 . In agreement with these findings, MS analysis revealed a significant, although not extensive, decrease in the relative abundance of native HA, from 58.5 to 51.7%, in DM + DKD patients with a concomitant increase in (mainly) oxidized forms (details in Supplementary Tab. S3 ). Notably, after treatment with glucose-lowering drugs, the levels of the glycated forms of HA were not significantly greater than those in the controls (P = 0.089; Supplementary Tab. S3 ). Since in ACLF patients the affinity of TEICO for HA resulted impaired, this drug was chosen as a pilot marker to assess whether the albumin binding capacity in DM + DKD patients was also affected (single K D values in Supplementary Tab. S4 ). Results show that the binding capacity of TEICO did not significantly affect this cohort of patients (Fig. 5 ). This finding suggests that only substantial alterations to the HA structure can lead to significant changes in the protein's binding properties. To conclude, these preliminary investigations demonstrate that the developed and optimized chip-based tool enables patient-specific binding studies. Sensing surface stability The stability of the sensing surface was monitored by evaluating the HA capture level at each analysis cycle (Fig. 6 ) throughout the sensor chip’s lifetime. Preliminary optimization revealed that to prolong the life of the sensor chip, it was crucial to add a cocktail of protease inhibitors when diluting plasma samples to prevent digestion of HA and/or antibody over multiple cycles. Under the optimized operating conditions, the same sensor chip could be used for more than 500 analyses. Materials and methods Chemicals Anti-human albumin antibody produced in rabbits (whole antiplasma, product code A3293; antigen 66.437–66.600 kDa), standard HA (essentially fatty acid-free, ≥ 96%, product code A1887; MW: 66.4 kDa), sodium dihydrogen phosphate (NaH 2 PO 4 ), disodium hydrogen phosphate (Na 2 HPO 4 ), dimethyl sulfoxide (DMSO), phenylbutazone (PBZ; MW: 308.4 Da), biliverdin hydrochloride (BVD; MW: 619.12 Da), teicoplanin (TEICO; MW: 1880 Da), sodium chloride (NaCl), sodium acetate and protease inhibitor cocktail were all purchased from Sigma–Aldrich Millipore (Milan, Italy). Dansyl-L-phenylalanine (DAP; MW: 398.5 Da) was purchased from Tokyo Chemical Industry (Tokyo, Japan). Galantamine hydrobromide (GAL; MW: 368.3 Da) was obtained from Tocris (Cookson, UK). CM5 sensor chips, along with an amine coupling kit containing N-ethyl-N-(3-dimethylaminopropyl)carbodiimide (EDC), N-hydroxysuccinimide (NHS), and 1 M ethanolamine hydrochloride at pH 8.5, were obtained from Cytiva (Milan, Italy). Bromocresol green (BCG; MW: 698.1 Da) was purchased from Fluka Honeywell (Milan, Italy), and succinic acid was purchased from Carlo Erba (Milan, Italy). Thermo Scientific Nunc Microwell 96-well plates were purchased from Fisher Scientific Italia (Rodano, Milan, Italy). HPLC-grade (≥ 99.9%) acetonitrile (ACN) was obtained from Honeywell (Milan, Italy). Deionized water was obtained with a Milli-Q system (Millipore, Milford, MA, USA), and all aqueous solutions were filtered through 0.22 µm membrane filters prior to use. Preparation and Validation of an HA-sensing surface SPR analyses were performed on a Biacore™ X100 system (Cytiva, Uppsala, Sweden) equipped with an inline degasser and thermostated at 25°C. The data were analyzed and processed using BiacoreTM X100 4.1 evaluation software. Preparation of the anti-HA sensing surface for reversible capture of HA For the immobilization process, phosphate-buffered saline (PBS; 20 mM, pH 7.4) containing 0.05% (v/v) Tween-20 (designated as running buffer A) was used. Binding studies were carried out using running buffer B, consisting of running buffer A supplemented with 2% (v/v) DMSO (pH 7.4). Buffer solutions were freshly prepared each day and filtered through a 0.22 µm cellulose nitrate membrane before use. To determine the optimal pH for immobilization, a pH-scouting investigation was performed by sequentially injecting 50 µg/mL anti-HA antibody solution in sodium acetate buffer (10 mM) at various pH values (pH 4.00, 4.35, 4.50, 4.76, 5.00, 5.22, and 5.50) for 120 s at 10 µL/min using running buffer A. After each injection, the baseline was re-established by injecting a NaOH solution (50 mM). The best preconcentration was obtained using a pH 5.0 solution. Accordingly, these conditions were utilized to covalently attach the antibody to the test flow cell (FC2) of a CM5 carboxymethyl-dextran sensor chip via standard amine coupling chemistry, as specified in the Biacore protocol. Briefly, the sensor chip was allowed to equilibrate at room temperature for 30 minutes before docking, followed by three priming cycles of the instrument with running buffer A. The sensor-chip test surface was activated by flushing a freshly prepared mixture of 0.4 M EDC and 0.1 M NHS (final concentrations) for 420 seconds at 10 µL/min. Then, 50 µg/mL anti-HA antibody solution was injected over the activated flow cell(s) at a flow rate of 10 µL/min for 120 s to achieve the desired immobilization level, i.e., 18,000 RU, which is approximately equivalent to a surface density of 18 ng/mm2. The remaining active esters were quenched by injecting a 1 M solution of ethanolamine hydrochloride (pH 8.5) for 420 s at the same flow rate. Finally, the system was left to equilibrate for at least 12 h to achieve a steady baseline. Two chips were prepared according to the described procedure: a sensor chip 1 (SC-1), in which the anti-HA antibody was immobilized only on the test flow cell, and a sensor chip 2 (SC-2), in which it was immobilized in both the test and reference flow cells. The sensor chips functionalized with the anti-HA antibody were used to immunocapture HA. Preparation of a reversibly functionalized HA-sensing surface by immunocapture The optimal conditions for HA immunocapture were achieved by injecting a 50 µM solution of HA in 10 mM sodium acetate buffer (pH 7.4) at a rate of 5 µL/min for 840 s. Validation of the Sensing Surface To confirm the correctness of the capture procedure and validate the binding capacity of the chip surface, the affinities of three well-known HA markers, PBZ, DAP, and BVD, were evaluated as site I, site II, and site III HA binders, respectively. The steady-state dissociation constant (K D ) was measured for each sample by multiple-cycle analysis. Stock solutions of 10 mM PBZ, DAP, and BVD in DMSO were further diluted with running buffer B to obtain the desired final concentrations: PBZ (0.620 to 50.0 µM), DAP (0.940 to 30.0 µM), and BVD (3.13 to 50.0 µM). The analytes were injected into both flow cells at a flow rate of 75 µL/min, with a contact time of 40 s, followed by a 40 s dissociation time. Due to the high bulk response of DMSO compared to the intrinsically low response of small molecules, a solvent correction procedure was employed to correct for the observed responses to DMSO and to improve the robustness of the measurements. Furthermore, based on binding data available in the literature 27 , galantamine was chosen as a negative control to assess the absence of possible artifacts. To assess the binding of galantamine, starting from a 3 mM stock solution in running buffer A, test solutions of increasing concentrations of galantamine, namely, 0.370, 1.11, 3.33, 10.0, and 30.0 µM, were prepared in running buffer B and injected at a flow rate of 10 µL/min for 60 s. Data analysis The sensorgram responses from the test flow cell were corrected by double-referencing, using both the signal from the reference flow cell and the averaged response from blank injections recorded at the start of each analytical multicycle. A correction for solvent refractive index effects was also applied 52 . The equilibrium dissociation constant (K D ) for the ligand–analyte interaction was calculated by fitting the steady-state response data to a 1:1 binding isotherm, as described by Eq. (1): $$\:{R}_{eq}\:=\:\frac{C{R}_{max}}{{K}_{D}\:+C\:}\:+\:offset\:\left(1\right)$$ where K D is expressed in M, C is the analyte concentration (in M), R eq is the SPR response of the binding complex at equilibrium (in RU), R max is the maximum response upon saturation of the analyte (in RU) and the offset is the response at zero analyte concentration (in RU). Each dataset was fitted separately in the binding model using at least two independent repetitions of the measurements. The resulting parameters (n = 3) were averaged and are expressed with the corresponding standard deviation. Patients Two study populations were selected for the pilot studies conducted in this work. The first involved six cirrhotic patients admitted to the IRCCS Azienda Ospedaliero-Universitaria di Bologna in Bologna (Italy) due to acute-on-chronic liver failure (ACLF) between January 2014 and March 2016. The selection of those patients was driven by the evaluation of the relative amount of the native form of the protein (nHA): selected patients had the lowest amount of nHA. Six age-matched healthy volunteers were considered the reference population. The second study involved 20 patients attending the outpatient clinic of the Metabolic Diseases & Clinical Dietetics Unit and the Nephrology, Dialysis and Transplantation Unit of the IRCCS Azienda Ospedaliero-Universitaria di Bologna (Italy). The inclusion criteria were a diagnosis of T2DM for at least one year without renal impairment (n = 10), or with renal impairment at the “very high risk” stage (n = 10) according to the guidelines for the evaluation and management of chronic kidney disease 50 . Vital parameters, weight, height, BMI, and systolic and diastolic blood pressure were assessed in all patients. A medical history was also collected to document current drug therapy. Blood samples were collected from all subjects after fasting in EDTA tubes (Becton Dickinson Italia, Milan, Italy) and were centrifuged at 3,000 × g for 10 minutes; the plasma was aliquoted into cryotubes (Corning, Inc., Corning BV, Amsterdam, The Netherlands) and stored at − 80°C until analysis. The study protocol was approved by the local institutional review board, and written informed consent was obtained from patients or legal surrogates before enrollment, in accordance with the 1975 Declaration of Helsinki. Ethics approval The study protocols were approved by the Ethics Committee of Sant’Orsola Malpighi University Hospital (protocol codes 88_2017U\Sper, 2017, and 75/2012/U/OSS) and were conducted in accordance with the 1964 Helsinki Declaration and subsequent revisions. Informed consent was obtained from all participants prior to their enrollment in the study Evaluation of albumin microheterogeneity before and after immunoextraction from plasma samples Plasma from ten T2DM patients with (n = 5) or without (n = 5) renal impairment was divided into two aliquots and stored at -80°C before use. One aliquot was diluted 1:100 with 10 mM phosphate buffer (pH 7.4), filtered through 0.22 µm syringe filters, and directly analyzed via LC‒MS analysis following the methods described in the following section. The second aliquot was diluted with phosphate-buffered saline (PBS), filtered through 0.22 µm syringe filters, and subjected to albumin immunoextraction using a monolithic affinity column that contained the selected anti-HA polyclonal antibody immobilized on the monolithic stationary phase (Sartorius BIA Separations, Slovenia, beta version affinity column). Extraction was performed according to the vendor protocol. The collected HA eluate was concentrated, and the elution buffer was replaced with 10 mM phosphate buffer (pH 7.4) using ultrafiltration (Amicon Ultra tubes, 0.5 mL, cutoff 10 kDa). The HA concentration in the collected samples was assessed via spectrophotometric analysis. Prior to LC-ESI-MS analysis, the samples were diluted to a final protein concentration of 100 µg/mL. Liquid chromatography‒mass spectrometry (LC-MS) analyses To perform relative quantification of structural modifications in HA, the LC–MS method previously described by Nignes et al. 53 was employed. Plasma samples were diluted 1:100 with ultrapure water and then filtered through a 0.22 µm syringe filter (Merck KGaA, Darmstadt, Germany). Chromatographic separation from other plasma proteins was carried out using a Phenomenex Jupiter C4 column (5 µm, 300 Å, 150 × 2.0 mm i.d.) on an Agilent 1200 HPLC system (Walbronn, Germany). A binary gradient elution was applied using mobile phase A [water/acetonitrile/formic acid, 99:1:0.1 (v/v/v)] and mobile phase B [acetonitrile/water/formic acid, 98:2:0.1 (v/v/v)]: 20–70% B over 5 minutes, followed by a 1-minute hold at 70% B. The column was then re-equilibrated for 5 minutes. The flow rate was maintained at 0.4 mL/min, with an injection volume of 3 µL. A quadrupole-time of flight hybrid mass analyzer (Q-ToF Micro, Micromass, Manchester, UK) with a Z-spray electrospray ionization (ESI) source was used for mass spectrometry analysis. The capillary and cone voltages were set at 3.0 kV and 40 V, respectively. The ESI-Q-ToF source temperature was 150°C, and the desolvation temperature was 300°C. The scan and interscan times were set at 2.4 s and 0.1 s, respectively. The desolvation gas flow rate was 1,000 L/h, and the cone gas flow rate was 120 L/h. Total ion current (TIC) chromatograms were acquired in positive polarity within the 1,000–1,800 m/z range. Using MassLynx software with the maximum entropy (MaxEnt1)-based tool, the HA baseline-subtracted spectrum ( m/z 1,084–1,534) was deconvoluted into a genuine mass scale, with parameters set at a mass range of 61,500–71,500 Da and a resolution of 2 Da/channel. The relative abundance of HA forms was determined by dividing the intensity of each form (from the deconvoluted spectrum) by the sum of the intensities of all the forms multiplied by 100. Microsoft Excel software (Microsoft Corporation, 2016) was used for the data analysis. Bromocresol green (BCG) colorimetric method The HA concentration in the plasma samples under investigation was determined using a BCG colorimetric assay as described by Nugnes et al. 53 . The BCG working solution was composed of 0.2 mM bromocresol green (BCG), 0.1 mM succinate buffer (pH 4.2), and 0.8% (v/v) Tween® 20. Plasma samples were diluted 1:5 with ultrapure water, and a 5 µL aliquot of each diluted sample was added to 200 µL of BCG reagent and gently mixed. The mixture was incubated at room temperature for 5 minutes. Blank solutions, prepared in parallel, contained all components except for plasma. Subsequently, 200 µL of each sample and blank solution were transferred to individual wells of a clear 96-well flat-bottom microplate. Absorbance was measured at 620 nm (within a 570–670 nm range) using a Spark® multimode microplate reader (Tecan, Austria). HA concentration was determined by interpolating the absorbance at 620 nm against a calibration curve constructed from standard HA solutions at concentrations of 5.0, 7.5, 10, 15, and 20 mg/mL. A new standard curve was generated for each assay set. All measurements were performed in triplicate. Ex vivo SPR-based assessment of HA binding functions in cirrhotic patients and T2DM + DKD patients Prior to SPR analysis, the samples were diluted to match the analysis conditions, HA degradation by proteases was inhibited, and the HA concentration was normalized. In detail, based on the HA concentration (as determined by the BCG method), each plasma sample was diluted with PBS (pH 7.4) containing 2% ( v/v ) protease inhibitor mixture to obtain a final HA concentration of 100 µM. The samples were then filtered through a 0.22 µm syringe filter and further diluted 1 to 2 in 1× PBS (pH 7.4) + 0.1% (v/v) TWEEN® 20 + 4% (v/v) DMSO to obtain a final concentration of 50 µM HA and to match running buffer B. HA immunocapture was perfor 53 med by injecting a diluted plasma solution (HA concentration = 50 µM) over the functionalized sensor chip (SC1 or SC2) at 5 µL/min for 840 s. The surface was allowed to stabilize for 420 s. Association and dissociation profiles of the selected site-specific binders, namely, PBZ, DAP, and BVD, were monitored for 40 s at a flow rate of 75 µL/min. For each subject-specific HA-sensing surface, the steady-state dissociation constants for the three site-specific markers PBZ, DAP, and BVD were determined using the same concentration range adopted for sensor chip validation. Furthermore, for each patient, the affinity of teicoplanin (TEICO), a non-site-specific HA binder, was also assessed. To this aim, solutions of TEICO with final concentrations ranging from 0.880 to 550 µM in running buffer B were screened. At the end of each multicycle analysis, two subsequent regeneration steps were performed by injecting 100 mM Gly-HCl (pH 2) and 50 mM NaOH at a flow rate of 10 µL/min for 40 s. All the assays were performed at 25°C. Statistical analysis Data are presented as mean ± standard deviation or median with interquartile range, as appropriate. Normality was assessed using the Shapiro–Wilk test. Differences between plasma and extracted samples for each HSA form were tested against a mean of zero using one-sample t-tests. The Mann‒Whitney U test was used to compare the relative amounts of HA forms (as determined by LC–MS) between groups. Student’s t-test was used to assess differences in SPR binding. All tests were two-sided, and p-values less than 0.05 were used to indicate statistical significance. The data were analyzed using SPSS version 28 (IBM) and GraphPad Prism 8.4.2 software (GraphPad Software, Inc.). Conclusions We developed a robust and cost-effective SPR-based method for analyzing albumin binding capacity in clinically relevant settings. By combining single-step selective immunocapture with label-free, real-time detection, this approach enables the cost-effective assessment of HA–drug interactions, preserving the intrinsic and clinically relevant HA microheterogeneity. This enables the evaluation of HA binding properties under clinically meaningful conditions, without the need for prior purification or protein modification. The method requires only minimal sample volumes, is highly reproducible, and supports extended reusability of the sensing surface for several hundred analytical cycles without loss of performance. These features make it a practical and scalable tool for the reliable investigation of HA functional alterations associated with pathological states or therapeutic interventions. Overall, this analytical approach provides a solid foundation for the future implementation of personalized and condition-specific assessments of albumin functionality in both research and clinical settings. Declarations Conflict of Interest: There are no conflicts of interest to disclose. Funding: This work was financially supported by the University of Bologna (RFO funding scheme). Author Contribution Marta Nugnes: Investigation, Validation, Data curation, Writing-Original draft preparation; Maurizio Baldassarre: Visualization, Formal analysis, Resources; Paolo Caraceni: Resources, Writing - Review & Editing; Marina Naldi: Visualization, Methodology, Supervision, Writing - Review & Editing; Manuela Bartolini: Conceptualization, Project administration, Writing - Review & Editing. Acknowledgement MBar and MN would like to thank Drs Francesca Marchignoli and Chiara Carrisi from the Unit of Clinical Nutrition, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy, for collecting and handling the plasma samples from DM patients, which were used in this study. Miss Martina Chimisso, Miss Alessia Cavaliere, and Miss Claudia Dal Monte are also acknowledged for technical support. Data Availability The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. References Quinlan, G. J., Martin, G. S. & Evans, T. W. Albumin: Biochemical properties and therapeutic potential. Hepatology 41 , 1211–1219 (2005). Ascenzi, P., Fanali, G., Fasano, M., Pallottini, V. & Trezza, V. Clinical relevance of drug binding to plasma proteins q. J. Mol. Struct. 1077 , 4–13 (2014). Fasano, M. et al. The extraordinary ligand binding properties of human serum albumin. IUBMB Life . 57 , 787–796 (2005). Sudlow, G., Birkett, D. J. & Wade, D. N. Further characterization of specific drug binding sites on human serum albumin. Mol. Pharmacol. 12 , 1052–1061 (1976). Sudlow, G., Birkett, D. J. & Wade, D. N. The characterization of two specific drug binding sites on human serum albumin. Mol. Pharmacol. 11 , 824–832 (1975). Zsila, F. & Subdomain IB is the third major drug binding region of human serum albumin: Toward the three-sites model. Mol. Pharm. 10 , 1668–1682 (2013). Ghuman, J. et al. Structural basis of the drug-binding specificity of human serum albumin. J. Mol. Biol. 353 , 38–52 (2005). Fanali, G. et al. Human serum albumin: From bench to bedside. Mol. Aspects Med. 33 , 209–290 (2012). Paramasivan, S. et al. Serum albumin cysteine trioxidation is a potential oxidative stress biomarker of type 2 diabetes mellitus. Sci. Rep. 10 , 1–12 (2020). Watanabe, H. Oxidized Albumin: Evaluation of Oxidative Stress as a Marker for the Progression of Kidney Disease. Biol. Pharm. Bull. 45 , 1728–1732 (2022). Domenicali, M. et al. Posttranscriptional changes of serum albumin: Clinical and prognostic significance in hospitalized patients with cirrhosis. Hepatology 60 , 1851–1860 (2014). Nakajou, K., Watanabe, H., Kragh-Hansen, U., Maruyama, T. & Otagiri, M. The effect of glycation on the structure, function and biological fate of human serum albumin as revealed by recombinant mutants. Biochim. Biophys. Acta - Gen. Subj. 1623 , 88–97 (2003). Qiu, H. et al. Comprehensive Glycomic Analysis Reveals That Human Serum Albumin Glycation Specifically Affects the Pharmacokinetics and Efficacy of Different Anticoagulant Drugs in Diabetes. Diabetes 69 , 760–770 (2020). Fender, A. C. & Dobrev, D. Bound to bleed: How altered albumin binding may dictate warfarin treatment outcome. IJC Hear. Vasc . 22 , 214–215 (2019). Bertozo, L., de Neto, C. T., de Oliveira, E., Ximenes, V. F. & L. C. & Oxidative Alteration of Trp-214 and Lys-199 in Human Serum Albumin Increases Binding Affinity with Phenylbutazone: A Combined Experimental and Computational Investigation. Int. J. Mol. Sci. 2018 . 19 , 2868 (2018). Michalcová, L. & Glatz, Z. Study on the interactions of sulfonylurea antidiabetic drugs with normal and glycated human serum albumin by capillary electrophoresis-frontal analysis. J. Sep. Sci. 39 , 3631–3637 (2016). Joseph, K. S. S. & Hage, D. S. The effects of glycation on the binding of human serum albumin to warfarin and l-tryptophan. J. Pharm. Biomed. Anal. 53 , 811–818 (2010). Wilting, J. et al. The effect of albumin conformation on the binding of warfarin to human serum albumin. The dependence of the binding of warfarin to human serum albumin on the hydrogen, calcium, and chloride ion concentrations as studied by circular dichroism, fluorescence. J. Biol. Chem. 255 , 3032–3037 (1980). Fredrickson, D. S. & Gordon, R. S. The metabolism of albumin-bound C14-labeled unesterified fatty acids in normal human subjects. J. Clin. Invest. 37 , 1504–1515 (1958). Paar, M. et al. Albumin in patients with liver disease shows an altered conformation. Commun. Biol. 4 , 1–9 (2021). Baraka-Vidot, J., Guerin-Dubourg, A., Bourdon, E. & Rondeau, P. Impaired drug-binding capacities of in vitro and in vivo glycated albumin. Biochimie 94 , 1960–1967 (2012). Oettl, K. et al. Oxidative albumin damage in chronic liver failure: Relation to albumin binding capacity, liver dysfunction and survival. J. Hepatol. 59 , 978–983 (2013). Nagumo, K. et al. Cys34-cysteinylated human serum albumin is a sensitive plasma marker in oxidative stress-related chronic diseases. PLoS One . 9 , e85216 (2014). Blache, D. et al. Glycated Albumin With Loss of Fatty Acid Binding Capacity Contributes to Enhanced Arachidonate Oxygenation and Platelet Hyperactivity: Relevance in Patients With Type 2 Diabetes. Diabetes 64 , 960–972 (2015). Masson, J. F. Surface Plasmon Resonance Clinical Biosensors for Medical Diagnostics. ACS Sens. 2 , 16–30 (2017). Lai, T., Hou, Q., Yang, H., Luo, X. & Xi, M. Clinical application of a novel sliver nanoparticles biosensor based on localized surface plasmon resonance for detecting the microalbuminuria. Acta Biochim. Biophys. Sin (Shanghai) . 42 , 787–792 (2010). Fabini, E., Tramarin, A. & Bartolini, M. Combination of human acetylcholinesterase and serum albumin sensing surfaces as highly informative analytical tool for inhibitor screening. J. Pharm. Biomed. Anal. 155 , 177–184 (2018). Fabini, E., Fiori, G. M. L., Tedesco, D., Lopes, N. P. & Bertucci, C. Surface plasmon resonance and circular dichroism characterization of cucurbitacins binding to serum albumins for early pharmacokinetic profiling. J. Pharm. Biomed. Anal. 122 , 166–172 (2016). Sharifi, M. et al. Surface plasmon resonance and molecular docking studies of bovine serum albumin interaction with neomycin: Kinetic and thermodynamic analysis. BioImpacts 7 , 91–97 (2017). Onishi, R. et al. Surface plasmon resonance assay of binding properties of antisense oligonucleotides to serum albumins and lipoproteins. Anal. Sci. 31 , 1255–1260 (2015). Fabini, E. & Danielson, U. H. Monitoring drug–serum protein interactions for early ADME prediction through Surface Plasmon Resonance technology. J. Pharm. Biomed. Anal. 144 , 188–194 (2017). Baldassarre, M. et al. Albumin Homodimers in Patients with Cirrhosis: Clinical and Prognostic Relevance of a Novel Identified Structural Alteration of the Molecule. Sci. Rep. 2016 61 (6), 1–9 (2016). Jha, J. C., Banal, C., Chow, B. S. M., Cooper, M. E. & Jandeleit-Dahm, K. Diabetes and Kidney Disease: Role of Oxidative Stress. Antioxid. Redox Signal. 25 , 657–684 (2016). Naldi, M., Baldassarre, M., Domenicali, M., Bartolini, M. & Caraceni, P. Structural and functional integrity of human serum albumin: Analytical approaches and clinical relevance in patients with liver cirrhosis. J Pharm. Biomed. Anal 144 , (2017). de Mol, N. J. & Fischer, M. J. E. Surface Plasmon Resonance: Methods and Protocols. Life Sci. 55–73. 10.1007/978-1-60761-670-2 (2010). Naldi, M. et al. A fast and validated mass spectrometry method for the evaluation of human serum albumin structural modifications in the clinical field. Eur. J. Mass. Spectrom. 19 , 491–496 (2013). Kuroda, Y., Saito, M., Sakai, H. & Yamaoka, T. Rapid characterization of drug-drug interaction in plasma protein binding using a surface plasmon resonance biosensor. Drug Metab. Pharmacokinet. 23 , 120–127 (2008). Wang, Y. et al. A fluorescent fatty acid probe, DAUDA, selectively displaces two myristates bound in human serum albumin. Protein Sci. 20 , 2095–2101 (2011). Brodersen, R. Competitive binding of bilirubin and drugs to human serum albumin studied by enzymatic oxidation. J. Clin. Invest. 54 , 1353–1364 (1974). Day, Y. S. N. & Myszka, D. G. Characterizing a drug’s primary binding site on albumin. J. Pharm. Sci. 9 , 333–343 (2003). Bakar, K. A. & Feroz, S. R. A critical view on the analysis of fluorescence quenching data for determining ligand–protein binding affinity. Spectrochim Acta - Part. Mol. Biomol. Spectrosc. 223 , 1–5 (2019). Goncharova, I. & Urbanová, M. Stereoselective bile pigment binding to polypeptides and albumins: A circular dichroism study. Anal. Bioanal Chem. 392 , 1355–1365 (2008). Clària, J. et al. Systemic inflammation in decompensated cirrhosis: Characterization and role in acute-on-chronic liver failure. Hepatology 64 , 1249–1264 (2016). Baldassarre, M. et al. Determination of Effective Albumin in Patients With Decompensated Cirrhosis: Clinical and Prognostic Implications. Hepatology 74 , 2058–2073 (2021). Naldi, M. et al. Mass spectrometry characterization of circulating human serum albumin microheterogeneity in patients with alcoholic hepatitis. J. Pharm. Biomed. Anal. 122 , 141–147 (2016). Assandri, A. & Bernareggi, A. Binding of teicoplanin to human serum albumin. Eur. J. Clin. Pharmacol. 33 , 191–195 (1987). Zoratti, C. et al. Antibiotics and Liver Cirrhosis: What the Physicians Need to Know. Antibiotics 11 , 1–19 (2022). Ulldemolins, M., Roberts, J. A., Rello, J., Paterson, D. L. & Lipman, J. The effects of hypoalbuminaemia on optimizing antibacterial dosing in critically ill patients. Clin. Pharmacokinet. 50 , 99–110 (2011). Prakash, S. Role of Human Serum Albumin and Oxidative Stress in Diabetes. J. Appl. Biotechnol. Bioeng. 3 , 281–285 (2017). International, K. K. D. I. G. O. Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease. Kidney Int. 98, S1–S115 (2020). (2020). Babu Kondaveeti, S., Kumaraswamy, D., Mishra, S. & Aravind Kumar, R. Anand Shaker, I. Evaluation of glycated albumin and microalbuminuria as early risk markers of nephropathy in type 2 diabetes mellitus. J. Clin. Diagn. Res. 7 , 1280–1283 (2013). Myszka, D. G. Improving biosensor analysis. J. Mol. Recognit. 12 , 279–284 (1999). Nugnes, M. et al. Association between Albumin Alterations and Renal Function in Patients with Type 2 Diabetes Mellitus. Int J. Mol. Sci 25 , (2024). Additional Declarations No competing interests reported. Supplementary Files ArticoloSPRChipAntiHSAsupplementaryInformationScientificReportsfinal.docx Cite Share Download PDF Status: Published Journal Publication published 27 Mar, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 20 Nov, 2025 Reviews received at journal 14 Nov, 2025 Reviewers agreed at journal 28 Oct, 2025 Reviewers agreed at journal 28 Oct, 2025 Reviews received at journal 16 Sep, 2025 Reviewers agreed at journal 11 Sep, 2025 Reviews received at journal 08 Sep, 2025 Reviewers agreed at journal 03 Aug, 2025 Reviewers invited by journal 29 Jul, 2025 Editor assigned by journal 29 Jul, 2025 Editor invited by journal 29 Jul, 2025 Submission checks completed at journal 26 Jul, 2025 First submitted to journal 26 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7190507","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":493301821,"identity":"572ebd05-0427-49cd-a6be-24e764671403","order_by":0,"name":"Marta Nugnes","email":"","orcid":"","institution":"Alma Mater Studiorum University of Bologna","correspondingAuthor":false,"prefix":"","firstName":"Marta","middleName":"","lastName":"Nugnes","suffix":""},{"id":493301822,"identity":"70af1c66-15ce-4d23-9cae-e13d4c9041bd","order_by":1,"name":"Maurizio Baldassarre","email":"","orcid":"","institution":"IRCCS Azienda Ospedaliero-Universitaria di Bologna","correspondingAuthor":false,"prefix":"","firstName":"Maurizio","middleName":"","lastName":"Baldassarre","suffix":""},{"id":493301823,"identity":"b3ebc3a9-83b6-47f6-a40a-2019ddd179c9","order_by":2,"name":"Paolo Caraceni","email":"","orcid":"","institution":"IRCCS Azienda Ospedaliero-Universitaria di Bologna","correspondingAuthor":false,"prefix":"","firstName":"Paolo","middleName":"","lastName":"Caraceni","suffix":""},{"id":493301824,"identity":"cd5a3328-0916-4e6f-adcc-59a421c9d476","order_by":3,"name":"Marina Naldi","email":"","orcid":"","institution":"Alma Mater Studiorum University of Bologna","correspondingAuthor":false,"prefix":"","firstName":"Marina","middleName":"","lastName":"Naldi","suffix":""},{"id":493301825,"identity":"7967478d-92d5-4f1a-b804-715f2b5668db","order_by":4,"name":"Manuela Bartolini","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIiWNgGAWjYNCCAgYGAwhDgoGNv/kAkAvEzPi0GIARYwODAVCLxLEEqBZ8ehBaQLwcEAnUgsMa3fazxyQ+GNgxmLOfff7gg4FFHh/DmW/SBQV35BjY+Q9g02J2Ji9NcoZBMoNlT7ph4wwDiWI25t5t0jMMnhnjcpjZgRwzaR4DZqDj0xibeQwkEtsYzm4DihxObMCl5fwbM+k/BvUMBuefwbTkPMOv5QbQFgaDwwwGN+C25LAR0PLG2LLH4DiP5YxnjDNngLRIHDO25gH6hY2Z2QC7w3IMb/yoqJYz509j+PChoi5xfn/zw9s8f+7I8fMffIDVGijgwRRiw6d+FIyCUTAKRgFeAAArUFYtaoPn0AAAAABJRU5ErkJggg==","orcid":"","institution":"Alma Mater Studiorum University of Bologna","correspondingAuthor":true,"prefix":"","firstName":"Manuela","middleName":"","lastName":"Bartolini","suffix":""}],"badges":[],"createdAt":"2025-07-22 21:53:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7190507/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7190507/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-026-44934-2","type":"published","date":"2026-03-27T16:09:22+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88097163,"identity":"91a8e3ad-3e9d-4e4d-bfed-69d78d8563b6","added_by":"auto","created_at":"2025-08-01 11:03:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":224010,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSensing surface design. \u003c/strong\u003eSchematic representation of the experimental design of the sensing surface along with the illustration of the instrumental setup for SPR binding measurement with the Biacore X100 system.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7190507/v1/aa81048bf1839826d6e68cee.png"},{"id":88097165,"identity":"f320dc48-6446-4c56-9344-596201260fd6","added_by":"auto","created_at":"2025-08-01 11:03:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":140274,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAbility of anti-HA antibody to maintain HA microheterogeneity.\u003c/strong\u003e Relative amount of HA forms before (white bars) and after (grey bars) extraction from \u003cstrong\u003ea\u003c/strong\u003eT2DM patients without renal impairment (n=5) and \u003cstrong\u003eb \u003c/strong\u003ea T2DM patients with renal impairment (n=5) by using an affinity column with the selected anti-HA antibody. The different forms of HA were identified, and relative abundances were assessed using a previously developed LC–MS method.\u003csup\u003e36\u003c/sup\u003e HA-DA: truncation at the N-terminal portion; HA-L: truncation at the C-terminal portion; HA+Cys-DA: N-terminal truncated form cysteinylated at Cys34; HSA: native albumin; HA-SO\u003csub\u003e2\u003c/sub\u003eH: albumin sulfonylated at Cys34; HSA-Cys: cysteinylation at the level of Cys34; HA+Glyc: monoglycation; HA+Cys+Glyc: cysteinylated form carrying one glycation; HA+2Glyc: glyc; HA+Cys+2Glyc: cysteinylated form carrying two glycations.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7190507/v1/a49707d45881f4864c30d0cd.png"},{"id":88095805,"identity":"116258c6-cf94-41b3-a345-02c0c9023b85","added_by":"auto","created_at":"2025-08-01 10:55:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":61870,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImmunocapture profiles of HA from different sources. \u003c/strong\u003eOverlaid representative sensorgrams depicting the immunocapture profiles of commercial HA (black), HA from a plasma control (orange), and from an ACLF patient (red) under optimized experimental conditions. All the samples were diluted to a final concentration of 50 µg/mL and infused at a rate of 10 µL/min for 840 s. Under the given conditions, the same final capture level was achieved when both the plasma samples and commercial HA solutions were used.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7190507/v1/9857554157f08a4b478c1d1e.png"},{"id":88095807,"identity":"fde513d9-26d5-483c-9b84-c6f7ded13611","added_by":"auto","created_at":"2025-08-01 10:55:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":71592,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImpact of structural damages associated with ACLF on albumin binding capacity.\u003c/strong\u003e Individual values plots showing average K\u003csub\u003eD \u003c/sub\u003evalues with standard error mean (SEM) for the three site-specific binding markers and teicoplanin (TEICO) for controls (CTRL, gray) and for patients with decompensated cirrhosis with ACLF (in red). Column graph graphs for \u003cstrong\u003ea\u003c/strong\u003e PBZ as a marker for Sudlow site I, \u003cstrong\u003eb\u003c/strong\u003e DPA as a marker for Sudlow site II, \u003cstrong\u003ec\u003c/strong\u003e BVD as a marker for site III, and \u003cstrong\u003ed\u003c/strong\u003e TEICO as a non-site-specific HA binder.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7190507/v1/b6483ec861144b8298b643a8.png"},{"id":88095814,"identity":"546228e1-6d10-4c71-aa4e-4a7316d5c1ea","added_by":"auto","created_at":"2025-08-01 10:55:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":22439,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImpact of structural damages associated with DM+DKD on albumin binding capacity.\u003c/strong\u003e Individual values plot showing average K\u003csub\u003eD\u003c/sub\u003e values with SEM for teicoplanin binding to HA in control DM-DKD patients (gray) and DM+DKD patients.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7190507/v1/7cff6af0e9aea55c955d65dd.png"},{"id":88095809,"identity":"8be45e1e-91e0-4d58-b590-e826b25661e6","added_by":"auto","created_at":"2025-08-01 10:55:23","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":46968,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStability study. \u003c/strong\u003eVariation in commercial HA captured by anti-HA antibody (expressed as percentage, %) as a function of the number of overall HA capture cycles (commercial and plasma samples).\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7190507/v1/48485bbd924148e18d85ad86.png"},{"id":105755083,"identity":"85699cf1-aa8b-43c0-afde-95332990b12b","added_by":"auto","created_at":"2026-03-30 16:25:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1809191,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7190507/v1/b3908654-315e-4f50-b7d9-dbeefe5b8ca2.pdf"},{"id":88097162,"identity":"6e675663-44b2-4777-bf1f-42ce633a0d6a","added_by":"auto","created_at":"2025-08-01 11:03:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":154867,"visible":true,"origin":"","legend":"","description":"","filename":"ArticoloSPRChipAntiHSAsupplementaryInformationScientificReportsfinal.docx","url":"https://assets-eu.researchsquare.com/files/rs-7190507/v1/60df8e2a26f5b00c36108b27.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Albumin-On-A-Chip: Binding Profiling of Circulating Human Albumin via Selective Immunocapture and Real-Time SPR Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHuman serum albumin (HA) is the most abundant plasma protein and plays a central role in maintaining oncotic pressure, exerting antioxidant effects, and transporting a wide variety of endogenous and exogenous ligands, including fatty acids, hormones, metal ions, and pharmaceutical compounds \u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Its ligand-binding versatility arises from a flexible, multidomain structure, which features several binding pockets, most notably Sudlow sites I and II, and site III \u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. HA\u0026ndash;ligand interactions contribute to drug solubility and distribution, influencing pharmacokinetics and therapeutic efficacy \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Because these functional properties depend on HA\u0026rsquo;s structural integrity, structural alterations can impact its folding, binding affinity, and clearance \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eHA exists in plasma as a heterogeneous mixture of native and modified forms. This microheterogeneity is dynamic and reflects physiological and pathological conditions. Structural modifications, including oxidation, glycation, cysteinylation, and terminal truncations, are known to increase in settings of systemic inflammation and oxidative stress, such as liver or kidney disease and diabetes \u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eStructural changes were reported to impact the binding capacity of HA toward clinically relevant ligands and drugs, including warfarin \u003csup\u003e\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, nonsteroidal anti-inflammatory drugs \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, sulfonylureas \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, and others \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, which may compromise drug efficacy and safety.\u003c/p\u003e\u003cp\u003eMost studies of HA binding have relied on in vitro models using chemically modified, commercially available HA. These models typically assess the impact of single alterations, often without detailed structural characterization of the modified forms \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. As a result, they fail to replicate the complex mixture of HA forms present in clinical samples, where multiple modifications coexist and evolve in response to disease severity and patient condition. Additionally, in vitro assays generally use defatted HA, whereas HA circulates bound to fatty acids, which are known to influence ligand binding \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. These limitations have led to divergent findings across studies \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. While some \u003cem\u003eex vivo\u003c/em\u003e approaches have been proposed, including direct plasma studies or HA isolation prior to binding assays, these are either confounded by the presence of other binding proteins or involve time-consuming purification steps. There remains a need for analytical strategies capable of assessing HA binding in clinically relevant samples, preserving structural microheterogeneity, and enabling efficient, reproducible measurements \u003csup\u003e\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn this context, the present study aimed to develop a cost-effective and reusable sensing surface for the real-time assessment of HA binding properties under clinically relevant conditions. A sensor chip was functionalized with a covalently immobilized anti-HA antibody, enabling selective, single-step immunocapture of HA from patient plasma without any extensive pretreatment. To ensure broad applicability, the setup was designed to be compatible with high-throughput use, minimal sample preparation, and low per-analysis costs.\u003c/p\u003e\u003cp\u003eSurface plasmon resonance (SPR) was employed for binding measurements due to its sensitivity and real-time monitoring capabilities. Although SPR has been extensively applied to the study of biomolecular interactions, its use with complex biofluids remains limited \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Prior SPR studies involving HA have largely relied on commercial preparations or covalent immobilization methods that do not capture circulating microheterogeneity \u003csup\u003e\u003cspan additionalcitationids=\"CR27 CR28 CR29 CR30\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Here, as proof-of-concept of application, we applied the newly developed sensing surface to assess HA binding in two patient cohorts characterized by distinct levels of HA structural damage: (i) patients with type 2 diabetes mellitus, with or without moderate kidney impairment (n\u0026thinsp;=\u0026thinsp;10 each), and (ii) patients with cirrhosis and acute-on-chronic liver failure (n\u0026thinsp;=\u0026thinsp;6), a condition associated with extensive HA modification \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Results and discussion","content":"\u003cp\u003e\u003cb\u003eDesign of the sensing surface\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe strategy for designing an analytical device capable of capturing albumin in a single step from patient plasma was defined, considering its final application: performing in vitro binding studies on a sensing surface that reflects patient-specific HA heterogeneity.\u003c/p\u003e\u003cp\u003eHence, SPR technology was selected because it represents one of the most suitable methods for studying biorecognition phenomena in real-time, with a mid-throughput wizard-supported workflow that is well-suited to the aims of this work. The ability to detect both weak and strong interactions, along with easy access to affinity and kinetic data on complex formation/disruption, makes this technique highly informative.\u003c/p\u003e\u003cp\u003eTo generate the SPR sensing surface, we opted for immunocapture-based immobilization of HA, as this approach enables the selective immobilization of the plasma target protein without pre-purification while minimizing the risk of contamination from other plasma proteins. Indeed, direct immobilization of circulating HA through covalent coupling would not provide the necessary selectivity, as competing, abundant plasma proteins would also be bound to the sensor chip surface, leading to a multi-protein sensing surface.\u003c/p\u003e\u003cp\u003eAdditionally, the immunocapture approach also ensures the device is cost-effective. Indeed, immunocapture, as a reversible immobilization process, allows for the removal of the target molecule from the sensing surface through a suitable surface regeneration procedure without damaging the capturing antibody. This allows for the repeated use of the same \u0026ldquo;activated\u0026rdquo; sensing surface over multiple analysis cycles.\u003c/p\u003e\u003cp\u003eTo this end, we first prepared an anti-HA sensor chip by covalently immobilizing a polyclonal anti-HA antibody using a well-established covalent immobilization procedure\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThen, the anti-HA sensor chip was used to capture HA from plasma samples without any pre-purification step. The amount of plasma needed to assess HA affinity toward an analyte is limited to a few dozen microliters. After the analysis cycle is completed, the capture surface is regenerated. Surface regeneration prepares the sensing surface for reuse in another capture cycle, enabling multiple analysis cycles. The general design and workflow are summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eValidation of polyclonal anti-HA antibody for quantitative capture of HA microheterogeneity.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo effectively sample the various forms of HA present under both physiological and pathological conditions, it is essential that the immunocapture method allows for the comprehensive collection of all circulating HA forms while maintaining their relative abundances. To evaluate this, we assessed the capturing performance of the selected commercial polyclonal anti-HA antibody against circulating HA using liquid chromatography-mass spectrometry (LC\u0026ndash;MS). This technique is crucial for distinguishing among the structurally altered forms of albumin, which differ in mass.\u003c/p\u003e\u003cp\u003eSince SPR cannot be directly interfaced with mass spectrometry, the polyclonal anti-HA antibody was covalently bound to a short monolithic column (CIMac-αHSA, 5.0 mm \u0026times; 5.2 mm I.D.), and the antibody\u0026rsquo;s capturing performance was evaluated using plasma samples characterized by varying albumin integrity and different microheterogeneity profile (namely samples from patients with type 2 diabetes mellitus - T2DM, with and without renal impairment). The relative abundances of the immunocaptured HA forms were profiled by LC-MS/MS and compared to those in untreated samples.\u003c/p\u003e\u003cp\u003eAs depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, no significant differences (P\u0026thinsp;\u0026gt;\u0026thinsp;0.5) were observed between the relative levels of HA forms before and after extraction for both sets of samples, although their HA microheterogeneity profiles were markedly different. In addition, mass spectrometric analysis confirmed that no other plasma proteins were co-captured under the applied conditions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThese results demonstrate that the selected anti-HA antibody effectively captures native and modified HA forms, preserving their relative abundance and, hence, reproducing disease-associated HA microheterogeneity profiles.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDevelopment and validation of the sensing surface\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAs mentioned above, the sensing surface was developed in two steps: first, the anti-HA antibody was covalently bound to the surface to provide a stable immunocapturing sensor chip; second, this anti-HA sensor chip was used to reversibly immunocapture HA. In the first step, an anti-HA sensor chip was obtained by covalently immobilizing the selected anti-HA antibody onto the carboxymethyl dextran layer of a CM5 sensor chip using an established amine coupling reaction \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Optimal preconcentration conditions were achieved at pH 5.0. The final immobilization level was 18,000 RU.\u003c/p\u003e\u003cp\u003eThe immunocapture procedure used to obtain the anti-HA sensing surface was initially optimized using the commercial HA. To maximize the capture level, the concentration of the HA solution, flow rate, and contact time were optimized \u003cb\u003e(Supplementary Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). The maximum capture level was achieved when a 50 \u0026micro;M HA solution was infused over the anti-HA sensor chip at a rate of 5 \u0026micro;L/min for 840 s. Under optimized conditions, reversible HA immobilization was achieved in a single step in approximately 5 min. Based on these data, for \u003cem\u003eex vivo\u003c/em\u003e studies, the total HA concentration was normalized to 50 \u0026micro;M prior to immunocapture to achieve similar immobilization levels across all samples \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSurface regeneration was achieved by injecting glycine buffer at pH 2.0, followed by 0.1 N NaOH. This step enabled the removal of HA from the chip surface without damaging the antibody, hence allowing restoration of the chip surface for further capture and analysis cycles. After regeneration, blank injections were performed to monitor the baseline stability and account for systematic and random variations. Regeneration conditions did not significantly affect the antibody binding capacity, as shown by the lack of a significant difference in the capture efficacy after two subsequent capture cycles (\u003cb\u003eSupplementary Fig. S2\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e The HA sensing surface was validated prior to its application to plasma samples from the study participants. False-positive interactions were ruled out by analyzing galantamine, a non-binding drug, confirming no interaction with HA \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. On the other hand, to assess whether HA maintains its unaltered binding capacity at its three high-affinity binding sites, three reference binders were analyzed, namely, (i) phenylbutazone (PBZ), a marker for Sudlow site I \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e; (ii) dansyl-L-phenylalanine (DAP), a marker for Sudlow site II \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e; and (iii) biliverdin (BVD), a marker for site III \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. For all markers, a good concentration\u0026ndash;response relationship was observed (\u003cb\u003eSupplementary Fig. S3\u003c/b\u003e). Notably, for BVD, significant interactions with the anti-HA antibody were observed, as confirmed by injecting BVD on the bare anti-HSA sensor chip without any immobilized HA. Hence, to properly account for those \u0026ldquo;aspecific\u0026rdquo; interactions, investigations involving BVD were performed using a sensor chip with the antibody immobilized in both sample and reference flow cells. The K\u003csub\u003eD\u003c/sub\u003e values obtained for PBZ, DAP, and BVD were in good agreement with those reported in the literature (PBZ: 14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 \u0026micro;M vs 0.12\u0026ndash;3.3 \u0026micro;M \u003csup\u003e4041\u003c/sup\u003e; DAP: 1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 \u0026micro;M vs 6.0 \u0026micro;M \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e; BVD: 13.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0 \u0026micro;M vs 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e-10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e M \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eApplication of the HA-sensing surface for the evaluation of HA-binding properties in cirrhotic patients and DKD patients\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eEx vivo assessment of HA binding functions in patients with decompensated cirrhosis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe validated sensing surface was utilized in a pilot study examining HA binding functions in patients with decompensated cirrhosis and ACLF, a syndrome characterized by elevated systemic inflammation and oxidative stress, as well as reduced levels of circulating HA. Indeed, several reports have highlighted that severe HA damage is encountered in advanced stages of liver cirrhosis and is mainly associated with high levels of oxidation \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Due to the accumulation of these altered molecular forms, the amount of native, fully functional HA significantly decreases \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Furthermore, clinical evidence of altered HA binding properties in ACLF patients was observed together with alterations in its conformation \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eBased on these observations and as proof of concept of the application of the proposed approach to real samples, plasma samples from 6 hospitalized patients with ACLF (2 males and 4 females, aged 68\u0026ndash;72) and 6 age-matched healthy volunteers (CTRL, 5 males and 1 female, aged 38\u0026ndash;73) were selected.\u003c/p\u003e\u003cp\u003eHA microheterogeneity in the samples under study was initially profiled by LC-MS analysis (\u003cb\u003eSupplementary Tab. S1\u003c/b\u003e) \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Analysis showed that, compared with healthy individuals, ACLF patients presented a drastically lower relative amount of the native form of HA (nHA) (8.5% vs 43.1%) and a concomitant significant increase in the oxidized forms of HNA1 (from 37.9 to 87.9%) and glycated forms (from 11.6 to 23.0%). For each subject, the HA binding capacity at the three high-affinity binding sites was evaluated by deriving K\u003csub\u003eD\u003c/sub\u003e values for PBZ, DPA, and BVD (\u003cb\u003eSupplementary Table S2\u003c/b\u003e). Furthermore, the affinity of teicoplanin (TEICO), a non-site-specific HA binder \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e commonly administered to cirrhotic patients to counteract infections, was also evaluated (\u003cb\u003eSupplementary Fig.\u0026nbsp;4\u003c/b\u003e and \u003cb\u003eSupplementary Tab. S2\u003c/b\u003e). HA from ACLF patients showed a slightly greater affinity for PBZ at Sudlow site I than did HA from CTRL subjects (P00.0280) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). On the other hand, no significant differences in affinities for DPA or BDV were detected at sites II and III, respectively (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eb and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). Indeed, notwithstanding the extensive structural changes that HA undergoes in ACLF patients, binding properties at high-affinity binding sites are quite preserved, although a warning might be considered for drug binding at Sudlow site I.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eImportantly, these findings should be considered preliminary because the study was undertaken as proof-of-application for the developed device, hence involving a limited number of patients.\u003c/p\u003e\u003cp\u003eInterestingly, a significant alteration in the TEICO binding capacity was observed in ACLF patients, in which structural changes affecting HA led to an overall reduction in its binding affinity (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). To our knowledge, this is the first study to investigate the binding of TEICO in ACLF patients. Since teicoplanin is one of the antibiotics of choice for treating infections in cirrhotic patients, these results are potentially relevant and require further evaluation, especially considering that ACLF patients also exhibit reduced plasma levels of HA (hypoalbuminemia) \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEx vivo assessment of HA binding functions in patients with T2-DM\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA second pilot study involved a small cohort of diabetic patients with renal impairment (DM\u0026thinsp;+\u0026thinsp;DKD). Indeed, exacerbated inflammation and oxidative stress are also typical pathological conditions in patients suffering from DKD and are major causes of morbidity and mortality in patients with DM. In agreement with this observation, more oxidized forms have been observed in albumin from DM patients [13,14]. Additionally, patients may also experience hypoalbuminemia due to alterations in glomerular filtration, a condition that may exacerbate HA dysfunction.\u003c/p\u003e\u003cp\u003eAs a pilot screening, 20 diabetic patients were selected: 10 subjects without renal damage (DM-DKD) (4 females and 6 males; aged 46\u0026ndash;87 years), and 10 subjects classified according to KDIGO classification parameters \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e as subjects with very high risk renal impairment (DM\u0026thinsp;+\u0026thinsp;DKD) (1 female and 9 males; aged 28\u0026ndash;71 years) \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. Previous investigations have shown that HA from DM\u0026thinsp;+\u0026thinsp;DKD patients also undergoes structural damage, although to a more limited extent when the glycemic level is under drug control \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. In agreement with these findings, MS analysis revealed a significant, although not extensive, decrease in the relative abundance of native HA, from 58.5 to 51.7%, in DM\u0026thinsp;+\u0026thinsp;DKD patients with a concomitant increase in (mainly) oxidized forms (details in \u003cb\u003eSupplementary Tab. S3\u003c/b\u003e). Notably, after treatment with glucose-lowering drugs, the levels of the glycated forms of HA were not significantly greater than those in the controls (P\u0026thinsp;=\u0026thinsp;0.089; \u003cb\u003eSupplementary Tab. S3\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eSince in ACLF patients the affinity of TEICO for HA resulted impaired, this drug was chosen as a pilot marker to assess whether the albumin binding capacity in DM\u0026thinsp;+\u0026thinsp;DKD patients was also affected (single K\u003csub\u003eD\u003c/sub\u003e values in \u003cb\u003eSupplementary Tab. S4\u003c/b\u003e). Results show that the binding capacity of TEICO did not significantly affect this cohort of patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This finding suggests that only substantial alterations to the HA structure can lead to significant changes in the protein's binding properties.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo conclude, these preliminary investigations demonstrate that the developed and optimized chip-based tool enables patient-specific binding studies.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSensing surface stability\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe stability of the sensing surface was monitored by evaluating the HA capture level at each analysis cycle (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003e) throughout the sensor chip\u0026rsquo;s lifetime. Preliminary optimization revealed that to prolong the life of the sensor chip, it was crucial to add a cocktail of protease inhibitors when diluting plasma samples to prevent digestion of HA and/or antibody over multiple cycles. Under the optimized operating conditions, the same sensor chip could be used for more than 500 analyses.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cb\u003eChemicals\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAnti-human albumin antibody produced in rabbits (whole antiplasma, product code A3293; antigen 66.437\u0026ndash;66.600 kDa), standard HA (essentially fatty acid-free, \u0026ge;\u0026thinsp;96%, product code A1887; MW: 66.4 kDa), sodium dihydrogen phosphate (NaH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e), disodium hydrogen phosphate (Na\u003csub\u003e2\u003c/sub\u003eHPO\u003csub\u003e4\u003c/sub\u003e), dimethyl sulfoxide (DMSO), phenylbutazone (PBZ; MW: 308.4 Da), biliverdin hydrochloride (BVD; MW: 619.12 Da), teicoplanin (TEICO; MW: 1880 Da), sodium chloride (NaCl), sodium acetate and protease inhibitor cocktail were all purchased from Sigma\u0026ndash;Aldrich Millipore (Milan, Italy). Dansyl-L-phenylalanine (DAP; MW: 398.5 Da) was purchased from Tokyo Chemical Industry (Tokyo, Japan). Galantamine hydrobromide (GAL; MW: 368.3 Da) was obtained from Tocris (Cookson, UK). CM5 sensor chips, along with an amine coupling kit containing N-ethyl-N-(3-dimethylaminopropyl)carbodiimide (EDC), N-hydroxysuccinimide (NHS), and 1 M ethanolamine hydrochloride at pH 8.5, were obtained from Cytiva (Milan, Italy).\u003c/p\u003e\u003cp\u003eBromocresol green (BCG; MW: 698.1 Da) was purchased from Fluka Honeywell (Milan, Italy), and succinic acid was purchased from Carlo Erba (Milan, Italy). Thermo Scientific Nunc Microwell 96-well plates were purchased from Fisher Scientific Italia (Rodano, Milan, Italy). HPLC-grade (\u0026ge;\u0026thinsp;99.9%) acetonitrile (ACN) was obtained from Honeywell (Milan, Italy). Deionized water was obtained with a Milli-Q system (Millipore, Milford, MA, USA), and all aqueous solutions were filtered through 0.22 \u0026micro;m membrane filters prior to use.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePreparation and Validation of an HA-sensing surface\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSPR analyses were performed on a Biacore\u0026trade; X100 system (Cytiva, Uppsala, Sweden) equipped with an inline degasser and thermostated at 25\u0026deg;C. The data were analyzed and processed using BiacoreTM X100 4.1 evaluation software.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePreparation of the anti-HA sensing surface for reversible capture of HA\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor the immobilization process, phosphate-buffered saline (PBS; 20 mM, pH 7.4) containing 0.05% (v/v) Tween-20 (designated as running buffer A) was used. Binding studies were carried out using running buffer B, consisting of running buffer A supplemented with 2% (v/v) DMSO (pH 7.4). Buffer solutions were freshly prepared each day and filtered through a 0.22 \u0026micro;m cellulose nitrate membrane before use.\u003c/p\u003e\u003cp\u003eTo determine the optimal pH for immobilization, a pH-scouting investigation was performed by sequentially injecting 50 \u0026micro;g/mL anti-HA antibody solution in sodium acetate buffer (10 mM) at various pH values (pH 4.00, 4.35, 4.50, 4.76, 5.00, 5.22, and 5.50) for 120 s at 10 \u0026micro;L/min using running buffer A. After each injection, the baseline was re-established by injecting a NaOH solution (50 mM). The best preconcentration was obtained using a pH 5.0 solution. Accordingly, these conditions were utilized to covalently attach the antibody to the test flow cell (FC2) of a CM5 carboxymethyl-dextran sensor chip via standard amine coupling chemistry, as specified in the Biacore protocol. Briefly, the sensor chip was allowed to equilibrate at room temperature for 30 minutes before docking, followed by three priming cycles of the instrument with running buffer A. The sensor-chip test surface was activated by flushing a freshly prepared mixture of 0.4 M EDC and 0.1 M NHS (final concentrations) for 420 seconds at 10 \u0026micro;L/min. Then, 50 \u0026micro;g/mL anti-HA antibody solution was injected over the activated flow cell(s) at a flow rate of 10 \u0026micro;L/min for 120 s to achieve the desired immobilization level, i.e., 18,000 RU, which is approximately equivalent to a surface density of 18 ng/mm2. The remaining active esters were quenched by injecting a 1 M solution of ethanolamine hydrochloride (pH 8.5) for 420 s at the same flow rate. Finally, the system was left to equilibrate for at least 12 h to achieve a steady baseline.\u003c/p\u003e\u003cp\u003eTwo chips were prepared according to the described procedure: a sensor chip 1 (SC-1), in which the anti-HA antibody was immobilized only on the test flow cell, and a sensor chip 2 (SC-2), in which it was immobilized in both the test and reference flow cells. The sensor chips functionalized with the anti-HA antibody were used to immunocapture HA.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePreparation of a reversibly functionalized HA-sensing surface by immunocapture\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe optimal conditions for HA immunocapture were achieved by injecting a 50 \u0026micro;M solution of HA in 10 mM sodium acetate buffer (pH 7.4) at a rate of 5 \u0026micro;L/min for 840 s.\u003c/p\u003e\u003cp\u003e\u003cb\u003eValidation of the Sensing Surface\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo confirm the correctness of the capture procedure and validate the binding capacity of the chip surface, the affinities of three well-known HA markers, PBZ, DAP, and BVD, were evaluated as site I, site II, and site III HA binders, respectively. The steady-state dissociation constant (K\u003csub\u003eD\u003c/sub\u003e) was measured for each sample by multiple-cycle analysis. Stock solutions of 10 mM PBZ, DAP, and BVD in DMSO were further diluted with running buffer B to obtain the desired final concentrations: PBZ (0.620 to 50.0 \u0026micro;M), DAP (0.940 to 30.0 \u0026micro;M), and BVD (3.13 to 50.0 \u0026micro;M). The analytes were injected into both flow cells at a flow rate of 75 \u0026micro;L/min, with a contact time of 40 s, followed by a 40 s dissociation time.\u003c/p\u003e\u003cp\u003eDue to the high bulk response of DMSO compared to the intrinsically low response of small molecules, a solvent correction procedure was employed to correct for the observed responses to DMSO and to improve the robustness of the measurements.\u003c/p\u003e\u003cp\u003eFurthermore, based on binding data available in the literature \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, galantamine was chosen as a negative control to assess the absence of possible artifacts. To assess the binding of galantamine, starting from a 3 mM stock solution in running buffer A, test solutions of increasing concentrations of galantamine, namely, 0.370, 1.11, 3.33, 10.0, and 30.0 \u0026micro;M, were prepared in running buffer B and injected at a flow rate of 10 \u0026micro;L/min for 60 s.\u003c/p\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eThe sensorgram responses from the test flow cell were corrected by double-referencing, using both the signal from the reference flow cell and the averaged response from blank injections recorded at the start of each analytical multicycle. A correction for solvent refractive index effects was also applied \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. The equilibrium dissociation constant (K\u003csub\u003eD\u003c/sub\u003e) for the ligand\u0026ndash;analyte interaction was calculated by fitting the steady-state response data to a 1:1 binding isotherm, as described by Eq.\u0026nbsp;(1):\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:{R}_{eq}\\:=\\:\\frac{C{R}_{max}}{{K}_{D}\\:+C\\:}\\:+\\:offset\\:\\left(1\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003eD\u003c/em\u003e\u003c/sub\u003e is expressed in M, \u003cem\u003eC\u003c/em\u003e is the analyte concentration (in M), \u003cem\u003eR\u003c/em\u003e\u003csub\u003e\u003cem\u003eeq\u003c/em\u003e\u003c/sub\u003e is the SPR response of the binding complex at equilibrium (in RU), \u003cem\u003eR\u003c/em\u003e\u003csub\u003e\u003cem\u003emax\u003c/em\u003e\u003c/sub\u003e is the maximum response upon saturation of the analyte (in RU) and the \u003cem\u003eoffset\u003c/em\u003e is the response at zero analyte concentration (in RU).\u003c/p\u003e\u003cp\u003eEach dataset was fitted separately in the binding model using at least two independent repetitions of the measurements. The resulting parameters (n\u0026thinsp;=\u0026thinsp;3) were averaged and are expressed with the corresponding standard deviation.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePatients\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTwo study populations were selected for the pilot studies conducted in this work. The first involved six cirrhotic patients admitted to the IRCCS Azienda Ospedaliero-Universitaria di Bologna in Bologna (Italy) due to acute-on-chronic liver failure (ACLF) between January 2014 and March 2016. The selection of those patients was driven by the evaluation of the relative amount of the native form of the protein (nHA): selected patients had the lowest amount of nHA. Six age-matched healthy volunteers were considered the reference population.\u003c/p\u003e\u003cp\u003eThe second study involved 20 patients attending the outpatient clinic of the Metabolic Diseases \u0026amp; Clinical Dietetics Unit and the Nephrology, Dialysis and Transplantation Unit of the IRCCS Azienda Ospedaliero-Universitaria di Bologna (Italy). The inclusion criteria were a diagnosis of T2DM for at least one year without renal impairment (n\u0026thinsp;=\u0026thinsp;10), or with renal impairment at the \u0026ldquo;very high risk\u0026rdquo; stage (n\u0026thinsp;=\u0026thinsp;10) according to the guidelines for the evaluation and management of chronic kidney disease \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. Vital parameters, weight, height, BMI, and systolic and diastolic blood pressure were assessed in all patients. A medical history was also collected to document current drug therapy.\u003c/p\u003e\u003cp\u003eBlood samples were collected from all subjects after fasting in EDTA tubes (Becton Dickinson Italia, Milan, Italy) and were centrifuged at 3,000 \u0026times; \u003cem\u003eg\u003c/em\u003e for 10 minutes; the plasma was aliquoted into cryotubes (Corning, Inc., Corning BV, Amsterdam, The Netherlands) and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until analysis. The study protocol was approved by the local institutional review board, and written informed consent was obtained from patients or legal surrogates before enrollment, in accordance with the 1975 Declaration of Helsinki.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003cp\u003e The study protocols were approved by the Ethics Committee of Sant\u0026rsquo;Orsola Malpighi University Hospital (protocol codes 88_2017U\\Sper, 2017, and 75/2012/U/OSS) and were conducted in accordance with the 1964 Helsinki Declaration and subsequent revisions. Informed consent was obtained from all participants prior to their enrollment in the study\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eEvaluation of albumin microheterogeneity before and after immunoextraction from plasma samples\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePlasma from ten T2DM patients with (n\u0026thinsp;=\u0026thinsp;5) or without (n\u0026thinsp;=\u0026thinsp;5) renal impairment was divided into two aliquots and stored at -80\u0026deg;C before use. One aliquot was diluted 1:100 with 10 mM phosphate buffer (pH 7.4), filtered through 0.22 \u0026micro;m syringe filters, and directly analyzed via LC‒MS analysis following the methods described in the following section. The second aliquot was diluted with phosphate-buffered saline (PBS), filtered through 0.22 \u0026micro;m syringe filters, and subjected to albumin immunoextraction using a monolithic affinity column that contained the selected anti-HA polyclonal antibody immobilized on the monolithic stationary phase (Sartorius BIA Separations, Slovenia, beta version affinity column). Extraction was performed according to the vendor protocol. The collected HA eluate was concentrated, and the elution buffer was replaced with 10 mM phosphate buffer (pH 7.4) using ultrafiltration (Amicon Ultra tubes, 0.5 mL, cutoff 10 kDa). The HA concentration in the collected samples was assessed via spectrophotometric analysis. Prior to LC-ESI-MS analysis, the samples were diluted to a final protein concentration of 100 \u0026micro;g/mL.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLiquid chromatography‒mass spectrometry (LC-MS) analyses\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo perform relative quantification of structural modifications in HA, the LC\u0026ndash;MS method previously described by Nignes et al.\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e was employed. Plasma samples were diluted 1:100 with ultrapure water and then filtered through a 0.22 \u0026micro;m syringe filter (Merck KGaA, Darmstadt, Germany). Chromatographic separation from other plasma proteins was carried out using a Phenomenex Jupiter C4 column (5 \u0026micro;m, 300 \u0026Aring;, 150 \u0026times; 2.0 mm i.d.) on an Agilent 1200 HPLC system (Walbronn, Germany). A binary gradient elution was applied using mobile phase A [water/acetonitrile/formic acid, 99:1:0.1 (v/v/v)] and mobile phase B [acetonitrile/water/formic acid, 98:2:0.1 (v/v/v)]: 20\u0026ndash;70% B over 5 minutes, followed by a 1-minute hold at 70% B. The column was then re-equilibrated for 5 minutes. The flow rate was maintained at 0.4 mL/min, with an injection volume of 3 \u0026micro;L.\u003c/p\u003e\u003cp\u003eA quadrupole-time of flight hybrid mass analyzer (Q-ToF Micro, Micromass, Manchester, UK) with a Z-spray electrospray ionization (ESI) source was used for mass spectrometry analysis. The capillary and cone voltages were set at 3.0 kV and 40 V, respectively. The ESI-Q-ToF source temperature was 150\u0026deg;C, and the desolvation temperature was 300\u0026deg;C. The scan and interscan times were set at 2.4 s and 0.1 s, respectively. The desolvation gas flow rate was 1,000 L/h, and the cone gas flow rate was 120 L/h. Total ion current (TIC) chromatograms were acquired in positive polarity within the 1,000\u0026ndash;1,800 \u003cem\u003em/z\u003c/em\u003e range. Using MassLynx software with the maximum entropy (MaxEnt1)-based tool, the HA baseline-subtracted spectrum (\u003cem\u003em/z\u003c/em\u003e 1,084\u0026ndash;1,534) was deconvoluted into a genuine mass scale, with parameters set at a mass range of 61,500\u0026ndash;71,500 Da and a resolution of 2 Da/channel. The relative abundance of HA forms was determined by dividing the intensity of each form (from the deconvoluted spectrum) by the sum of the intensities of all the forms multiplied by 100. Microsoft Excel software (Microsoft Corporation, 2016) was used for the data analysis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eBromocresol green (BCG) colorimetric method\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe HA concentration in the plasma samples under investigation was determined using a BCG colorimetric assay as described by Nugnes et al. \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. The BCG working solution was composed of 0.2 mM bromocresol green (BCG), 0.1 mM succinate buffer (pH 4.2), and 0.8% (v/v) Tween\u0026reg; 20. Plasma samples were diluted 1:5 with ultrapure water, and a 5 \u0026micro;L aliquot of each diluted sample was added to 200 \u0026micro;L of BCG reagent and gently mixed. The mixture was incubated at room temperature for 5 minutes. Blank solutions, prepared in parallel, contained all components except for plasma. Subsequently, 200 \u0026micro;L of each sample and blank solution were transferred to individual wells of a clear 96-well flat-bottom microplate. Absorbance was measured at 620 nm (within a 570\u0026ndash;670 nm range) using a Spark\u0026reg; multimode microplate reader (Tecan, Austria). HA concentration was determined by interpolating the absorbance at 620 nm against a calibration curve constructed from standard HA solutions at concentrations of 5.0, 7.5, 10, 15, and 20 mg/mL. A new standard curve was generated for each assay set. All measurements were performed in triplicate.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEx vivo SPR-based assessment of HA binding functions in cirrhotic patients and T2DM\u0026thinsp;+\u0026thinsp;DKD patients\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePrior to SPR analysis, the samples were diluted to match the analysis conditions, HA degradation by proteases was inhibited, and the HA concentration was normalized. In detail, based on the HA concentration (as determined by the BCG method), each plasma sample was diluted with PBS (pH 7.4) containing 2% (\u003cem\u003ev/v\u003c/em\u003e) protease inhibitor mixture to obtain a final HA concentration of 100 \u0026micro;M. The samples were then filtered through a 0.22 \u0026micro;m syringe filter and further diluted 1 to 2 in 1\u0026times; PBS (pH 7.4)\u0026thinsp;+\u0026thinsp;0.1% \u003cem\u003e(v/v)\u003c/em\u003e TWEEN\u0026reg; 20\u0026thinsp;+\u0026thinsp;4% \u003cem\u003e(v/v)\u003c/em\u003e DMSO to obtain a final concentration of 50 \u0026micro;M HA and to match running buffer B.\u003c/p\u003e\u003cp\u003eHA immunocapture was perfor\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003emed by injecting a diluted plasma solution (HA concentration\u0026thinsp;=\u0026thinsp;50 \u0026micro;M) over the functionalized sensor chip (SC1 or SC2) at 5 \u0026micro;L/min for 840 s. The surface was allowed to stabilize for 420 s. Association and dissociation profiles of the selected site-specific binders, namely, PBZ, DAP, and BVD, were monitored for 40 s at a flow rate of 75 \u0026micro;L/min. For each subject-specific HA-sensing surface, the steady-state dissociation constants for the three site-specific markers PBZ, DAP, and BVD were determined using the same concentration range adopted for sensor chip validation. Furthermore, for each patient, the affinity of teicoplanin (TEICO), a non-site-specific HA binder, was also assessed. To this aim, solutions of TEICO with final concentrations ranging from 0.880 to 550 \u0026micro;M in running buffer B were screened. At the end of each multicycle analysis, two subsequent regeneration steps were performed by injecting 100 mM Gly-HCl (pH 2) and 50 mM NaOH at a flow rate of 10 \u0026micro;L/min for 40 s. All the assays were performed at 25\u0026deg;C.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median with interquartile range, as appropriate. Normality was assessed using the Shapiro\u0026ndash;Wilk test. Differences between plasma and extracted samples for each HSA form were tested against a mean of zero using one-sample t-tests.\u003c/p\u003e\u003cp\u003eThe Mann‒Whitney U test was used to compare the relative amounts of HA forms (as determined by LC\u0026ndash;MS) between groups. Student\u0026rsquo;s t-test was used to assess differences in SPR binding.\u003c/p\u003e\u003cp\u003eAll tests were two-sided, and p-values less than 0.05 were used to indicate statistical significance. The data were analyzed using SPSS version 28 (IBM) and GraphPad Prism 8.4.2 software (GraphPad Software, Inc.).\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWe developed a robust and cost-effective SPR-based method for analyzing albumin binding capacity in clinically relevant settings. By combining single-step selective immunocapture with label-free, real-time detection, this approach enables the cost-effective assessment of HA\u0026ndash;drug interactions, preserving the intrinsic and clinically relevant HA microheterogeneity. This enables the evaluation of HA binding properties under clinically meaningful conditions, without the need for prior purification or protein modification. The method requires only minimal sample volumes, is highly reproducible, and supports extended reusability of the sensing surface for several hundred analytical cycles without loss of performance. These features make it a practical and scalable tool for the reliable investigation of HA functional alterations associated with pathological states or therapeutic interventions. Overall, this analytical approach provides a solid foundation for the future implementation of personalized and condition-specific assessments of albumin functionality in both research and clinical settings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflict of Interest:\u003c/h2\u003e\n\u003cp\u003eThere are no conflicts of interest to disclose.\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eThis work was financially supported by the University of Bologna (RFO funding scheme).\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eMarta Nugnes: Investigation, Validation, Data curation, Writing-Original draft preparation; Maurizio Baldassarre: Visualization, Formal analysis, Resources; Paolo Caraceni: Resources, Writing - Review \u0026amp; Editing; Marina Naldi: Visualization, Methodology, Supervision, Writing - Review \u0026amp; Editing; Manuela Bartolini: Conceptualization, Project administration, Writing - Review \u0026amp; Editing.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eMBar and MN would like to thank Drs Francesca Marchignoli and Chiara Carrisi from the Unit of Clinical Nutrition, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy, for collecting and handling the plasma samples from DM patients, which were used in this study. Miss Martina Chimisso, Miss Alessia Cavaliere, and Miss Claudia Dal Monte are also acknowledged for technical support.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eQuinlan, G. J., Martin, G. S. \u0026amp; Evans, T. W. Albumin: Biochemical properties and therapeutic potential. \u003cem\u003eHepatology\u003c/em\u003e \u003cb\u003e41\u003c/b\u003e, 1211\u0026ndash;1219 (2005).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAscenzi, P., Fanali, G., Fasano, M., Pallottini, V. \u0026amp; Trezza, V. Clinical relevance of drug binding to plasma proteins q. \u003cem\u003eJ. Mol. Struct.\u003c/em\u003e \u003cb\u003e1077\u003c/b\u003e, 4\u0026ndash;13 (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFasano, M. et al. The extraordinary ligand binding properties of human serum albumin. \u003cem\u003eIUBMB Life\u003c/em\u003e. \u003cb\u003e57\u003c/b\u003e, 787\u0026ndash;796 (2005).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSudlow, G., Birkett, D. J. \u0026amp; Wade, D. N. Further characterization of specific drug binding sites on human serum albumin. \u003cem\u003eMol. Pharmacol.\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e, 1052\u0026ndash;1061 (1976).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSudlow, G., Birkett, D. J. \u0026amp; Wade, D. N. The characterization of two specific drug binding sites on human serum albumin. \u003cem\u003eMol. Pharmacol.\u003c/em\u003e \u003cb\u003e11\u003c/b\u003e, 824\u0026ndash;832 (1975).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZsila, F. \u0026amp; Subdomain IB is the third major drug binding region of human serum albumin: Toward the three-sites model. \u003cem\u003eMol. Pharm.\u003c/em\u003e \u003cb\u003e10\u003c/b\u003e, 1668\u0026ndash;1682 (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGhuman, J. et al. Structural basis of the drug-binding specificity of human serum albumin. \u003cem\u003eJ. Mol. Biol.\u003c/em\u003e \u003cb\u003e353\u003c/b\u003e, 38\u0026ndash;52 (2005).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFanali, G. et al. Human serum albumin: From bench to bedside. \u003cem\u003eMol. Aspects Med.\u003c/em\u003e \u003cb\u003e33\u003c/b\u003e, 209\u0026ndash;290 (2012).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eParamasivan, S. et al. Serum albumin cysteine trioxidation is a potential oxidative stress biomarker of type 2 diabetes mellitus. \u003cem\u003eSci. Rep.\u003c/em\u003e \u003cb\u003e10\u003c/b\u003e, 1\u0026ndash;12 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWatanabe, H. Oxidized Albumin: Evaluation of Oxidative Stress as a Marker for the Progression of Kidney Disease. \u003cem\u003eBiol. Pharm. Bull.\u003c/em\u003e \u003cb\u003e45\u003c/b\u003e, 1728\u0026ndash;1732 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDomenicali, M. et al. Posttranscriptional changes of serum albumin: Clinical and prognostic significance in hospitalized patients with cirrhosis. \u003cem\u003eHepatology\u003c/em\u003e \u003cb\u003e60\u003c/b\u003e, 1851\u0026ndash;1860 (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNakajou, K., Watanabe, H., Kragh-Hansen, U., Maruyama, T. \u0026amp; Otagiri, M. The effect of glycation on the structure, function and biological fate of human serum albumin as revealed by recombinant mutants. \u003cem\u003eBiochim. Biophys. Acta - Gen. Subj.\u003c/em\u003e \u003cb\u003e1623\u003c/b\u003e, 88\u0026ndash;97 (2003).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQiu, H. et al. Comprehensive Glycomic Analysis Reveals That Human Serum Albumin Glycation Specifically Affects the Pharmacokinetics and Efficacy of Different Anticoagulant Drugs in Diabetes. \u003cem\u003eDiabetes\u003c/em\u003e \u003cb\u003e69\u003c/b\u003e, 760\u0026ndash;770 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFender, A. C. \u0026amp; Dobrev, D. Bound to bleed: How altered albumin binding may dictate warfarin treatment outcome. \u003cem\u003eIJC Hear. Vasc\u003c/em\u003e. \u003cb\u003e22\u003c/b\u003e, 214\u0026ndash;215 (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBertozo, L., de Neto, C. T., de Oliveira, E., Ximenes, V. F. \u0026amp; L. C. \u0026amp; Oxidative Alteration of Trp-214 and Lys-199 in Human Serum Albumin Increases Binding Affinity with Phenylbutazone: A Combined Experimental and Computational Investigation. \u003cem\u003eInt. J. Mol. Sci. 2018\u003c/em\u003e. \u003cb\u003e19\u003c/b\u003e, 2868 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMichalcov\u0026aacute;, L. \u0026amp; Glatz, Z. Study on the interactions of sulfonylurea antidiabetic drugs with normal and glycated human serum albumin by capillary electrophoresis-frontal analysis. \u003cem\u003eJ. Sep. Sci.\u003c/em\u003e \u003cb\u003e39\u003c/b\u003e, 3631\u0026ndash;3637 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJoseph, K. S. S. \u0026amp; Hage, D. S. The effects of glycation on the binding of human serum albumin to warfarin and l-tryptophan. \u003cem\u003eJ. Pharm. Biomed. Anal.\u003c/em\u003e \u003cb\u003e53\u003c/b\u003e, 811\u0026ndash;818 (2010).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilting, J. et al. The effect of albumin conformation on the binding of warfarin to human serum albumin. The dependence of the binding of warfarin to human serum albumin on the hydrogen, calcium, and chloride ion concentrations as studied by circular dichroism, fluorescence. \u003cem\u003eJ. Biol. Chem.\u003c/em\u003e \u003cb\u003e255\u003c/b\u003e, 3032\u0026ndash;3037 (1980).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFredrickson, D. S. \u0026amp; Gordon, R. S. The metabolism of albumin-bound C14-labeled unesterified fatty acids in normal human subjects. \u003cem\u003eJ. Clin. Invest.\u003c/em\u003e \u003cb\u003e37\u003c/b\u003e, 1504\u0026ndash;1515 (1958).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePaar, M. et al. Albumin in patients with liver disease shows an altered conformation. \u003cem\u003eCommun. Biol.\u003c/em\u003e \u003cb\u003e4\u003c/b\u003e, 1\u0026ndash;9 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaraka-Vidot, J., Guerin-Dubourg, A., Bourdon, E. \u0026amp; Rondeau, P. Impaired drug-binding capacities of in vitro and in vivo glycated albumin. \u003cem\u003eBiochimie\u003c/em\u003e \u003cb\u003e94\u003c/b\u003e, 1960\u0026ndash;1967 (2012).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOettl, K. et al. Oxidative albumin damage in chronic liver failure: Relation to albumin binding capacity, liver dysfunction and survival. \u003cem\u003eJ. Hepatol.\u003c/em\u003e \u003cb\u003e59\u003c/b\u003e, 978\u0026ndash;983 (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNagumo, K. et al. Cys34-cysteinylated human serum albumin is a sensitive plasma marker in oxidative stress-related chronic diseases. \u003cem\u003ePLoS One\u003c/em\u003e. \u003cb\u003e9\u003c/b\u003e, e85216 (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBlache, D. et al. Glycated Albumin With Loss of Fatty Acid Binding Capacity Contributes to Enhanced Arachidonate Oxygenation and Platelet Hyperactivity: Relevance in Patients With Type 2 Diabetes. \u003cem\u003eDiabetes\u003c/em\u003e \u003cb\u003e64\u003c/b\u003e, 960\u0026ndash;972 (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMasson, J. F. Surface Plasmon Resonance Clinical Biosensors for Medical Diagnostics. \u003cem\u003eACS Sens.\u003c/em\u003e \u003cb\u003e2\u003c/b\u003e, 16\u0026ndash;30 (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLai, T., Hou, Q., Yang, H., Luo, X. \u0026amp; Xi, M. Clinical application of a novel sliver nanoparticles biosensor based on localized surface plasmon resonance for detecting the microalbuminuria. \u003cem\u003eActa Biochim. Biophys. Sin (Shanghai)\u003c/em\u003e. \u003cb\u003e42\u003c/b\u003e, 787\u0026ndash;792 (2010).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFabini, E., Tramarin, A. \u0026amp; Bartolini, M. Combination of human acetylcholinesterase and serum albumin sensing surfaces as highly informative analytical tool for inhibitor screening. \u003cem\u003eJ. Pharm. Biomed. Anal.\u003c/em\u003e \u003cb\u003e155\u003c/b\u003e, 177\u0026ndash;184 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFabini, E., Fiori, G. M. L., Tedesco, D., Lopes, N. P. \u0026amp; Bertucci, C. Surface plasmon resonance and circular dichroism characterization of cucurbitacins binding to serum albumins for early pharmacokinetic profiling. \u003cem\u003eJ. Pharm. Biomed. Anal.\u003c/em\u003e \u003cb\u003e122\u003c/b\u003e, 166\u0026ndash;172 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSharifi, M. et al. Surface plasmon resonance and molecular docking studies of bovine serum albumin interaction with neomycin: Kinetic and thermodynamic analysis. \u003cem\u003eBioImpacts\u003c/em\u003e \u003cb\u003e7\u003c/b\u003e, 91\u0026ndash;97 (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOnishi, R. et al. Surface plasmon resonance assay of binding properties of antisense oligonucleotides to serum albumins and lipoproteins. \u003cem\u003eAnal. Sci.\u003c/em\u003e \u003cb\u003e31\u003c/b\u003e, 1255\u0026ndash;1260 (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFabini, E. \u0026amp; Danielson, U. H. Monitoring drug\u0026ndash;serum protein interactions for early ADME prediction through Surface Plasmon Resonance technology. \u003cem\u003eJ. Pharm. Biomed. Anal.\u003c/em\u003e \u003cb\u003e144\u003c/b\u003e, 188\u0026ndash;194 (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaldassarre, M. et al. Albumin Homodimers in Patients with Cirrhosis: Clinical and Prognostic Relevance of a Novel Identified Structural Alteration of the Molecule. \u003cem\u003eSci. Rep.\u003c/em\u003e \u003cb\u003e2016 61\u003c/b\u003e (6), 1\u0026ndash;9 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJha, J. C., Banal, C., Chow, B. S. M., Cooper, M. E. \u0026amp; Jandeleit-Dahm, K. Diabetes and Kidney Disease: Role of Oxidative Stress. \u003cem\u003eAntioxid. Redox Signal.\u003c/em\u003e \u003cb\u003e25\u003c/b\u003e, 657\u0026ndash;684 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNaldi, M., Baldassarre, M., Domenicali, M., Bartolini, M. \u0026amp; Caraceni, P. Structural and functional integrity of human serum albumin: Analytical approaches and clinical relevance in patients with liver cirrhosis. \u003cem\u003eJ Pharm. Biomed. Anal\u003c/em\u003e \u003cb\u003e144\u003c/b\u003e, (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Mol, N. J. \u0026amp; Fischer, M. J. E. Surface Plasmon Resonance: Methods and Protocols. \u003cem\u003eLife Sci.\u003c/em\u003e 55\u0026ndash;73. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/978-1-60761-670-2\u003c/span\u003e\u003cspan address=\"10.1007/978-1-60761-670-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNaldi, M. et al. A fast and validated mass spectrometry method for the evaluation of human serum albumin structural modifications in the clinical field. \u003cem\u003eEur. J. Mass. Spectrom.\u003c/em\u003e \u003cb\u003e19\u003c/b\u003e, 491\u0026ndash;496 (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKuroda, Y., Saito, M., Sakai, H. \u0026amp; Yamaoka, T. Rapid characterization of drug-drug interaction in plasma protein binding using a surface plasmon resonance biosensor. \u003cem\u003eDrug Metab. Pharmacokinet.\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e, 120\u0026ndash;127 (2008).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang, Y. et al. A fluorescent fatty acid probe, DAUDA, selectively displaces two myristates bound in human serum albumin. \u003cem\u003eProtein Sci.\u003c/em\u003e \u003cb\u003e20\u003c/b\u003e, 2095\u0026ndash;2101 (2011).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrodersen, R. Competitive binding of bilirubin and drugs to human serum albumin studied by enzymatic oxidation. \u003cem\u003eJ. Clin. Invest.\u003c/em\u003e \u003cb\u003e54\u003c/b\u003e, 1353\u0026ndash;1364 (1974).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDay, Y. S. N. \u0026amp; Myszka, D. G. Characterizing a drug\u0026rsquo;s primary binding site on albumin. \u003cem\u003eJ. Pharm. Sci.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e, 333\u0026ndash;343 (2003).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBakar, K. A. \u0026amp; Feroz, S. R. A critical view on the analysis of fluorescence quenching data for determining ligand\u0026ndash;protein binding affinity. \u003cem\u003eSpectrochim Acta - Part. Mol. Biomol. Spectrosc.\u003c/em\u003e \u003cb\u003e223\u003c/b\u003e, 1\u0026ndash;5 (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoncharova, I. \u0026amp; Urbanov\u0026aacute;, M. Stereoselective bile pigment binding to polypeptides and albumins: A circular dichroism study. \u003cem\u003eAnal. Bioanal Chem.\u003c/em\u003e \u003cb\u003e392\u003c/b\u003e, 1355\u0026ndash;1365 (2008).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCl\u0026agrave;ria, J. et al. Systemic inflammation in decompensated cirrhosis: Characterization and role in acute-on-chronic liver failure. \u003cem\u003eHepatology\u003c/em\u003e \u003cb\u003e64\u003c/b\u003e, 1249\u0026ndash;1264 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaldassarre, M. et al. Determination of Effective Albumin in Patients With Decompensated Cirrhosis: Clinical and Prognostic Implications. \u003cem\u003eHepatology\u003c/em\u003e \u003cb\u003e74\u003c/b\u003e, 2058\u0026ndash;2073 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNaldi, M. et al. Mass spectrometry characterization of circulating human serum albumin microheterogeneity in patients with alcoholic hepatitis. \u003cem\u003eJ. Pharm. Biomed. Anal.\u003c/em\u003e \u003cb\u003e122\u003c/b\u003e, 141\u0026ndash;147 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAssandri, A. \u0026amp; Bernareggi, A. Binding of teicoplanin to human serum albumin. \u003cem\u003eEur. J. Clin. Pharmacol.\u003c/em\u003e \u003cb\u003e33\u003c/b\u003e, 191\u0026ndash;195 (1987).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZoratti, C. et al. Antibiotics and Liver Cirrhosis: What the Physicians Need to Know. \u003cem\u003eAntibiotics\u003c/em\u003e \u003cb\u003e11\u003c/b\u003e, 1\u0026ndash;19 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUlldemolins, M., Roberts, J. A., Rello, J., Paterson, D. L. \u0026amp; Lipman, J. The effects of hypoalbuminaemia on optimizing antibacterial dosing in critically ill patients. \u003cem\u003eClin. Pharmacokinet.\u003c/em\u003e \u003cb\u003e50\u003c/b\u003e, 99\u0026ndash;110 (2011).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePrakash, S. Role of Human Serum Albumin and Oxidative Stress in Diabetes. \u003cem\u003eJ. Appl. Biotechnol. Bioeng.\u003c/em\u003e \u003cb\u003e3\u003c/b\u003e, 281\u0026ndash;285 (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eInternational, K. K. D. I. G. O. Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease. \u003cem\u003eKidney Int.\u003c/em\u003e 98, S1\u0026ndash;S115 (2020). (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBabu Kondaveeti, S., Kumaraswamy, D., Mishra, S. \u0026amp; Aravind Kumar, R. Anand Shaker, I. Evaluation of glycated albumin and microalbuminuria as early risk markers of nephropathy in type 2 diabetes mellitus. \u003cem\u003eJ. Clin. Diagn. Res.\u003c/em\u003e \u003cb\u003e7\u003c/b\u003e, 1280\u0026ndash;1283 (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMyszka, D. G. Improving biosensor analysis. \u003cem\u003eJ. Mol. Recognit.\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e, 279\u0026ndash;284 (1999).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNugnes, M. et al. Association between Albumin Alterations and Renal Function in Patients with Type 2 Diabetes Mellitus. \u003cem\u003eInt J. Mol. Sci\u003c/em\u003e \u003cb\u003e25\u003c/b\u003e, (2024).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"sensing device, surface plasmon resonance, ex vivo binding studies, personalized profiling, albumin functional alterations, mass spectrometry","lastPublishedDoi":"10.21203/rs.3.rs-7190507/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7190507/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA cost-effective surface plasmon resonance (SPR)-based sensing platform was developed to evaluate alterations in albumin binding capacity under clinically relevant conditions. This ex vivo approach enables real-time assessment of albumin\u0026ndash;ligand interactions using albumin directly isolated from plasma, thus overcoming key limitations of conventional in vitro approaches. The sensing surface was prepared by covalently immobilizing a polyclonal anti-albumin antibody onto a CM5 chip, followed by a single-step immunocapture of albumin from patient plasma samples. Mass spectrometry confirmed the selective retrieval of both native and structurally modified albumin forms, preserving their relative abundance and disease-associated microheterogeneity. The sensing surface demonstrated high reusability and analytical reproducibility over ~\u0026thinsp;500 capture\u0026ndash;release cycles, significantly lowering per-sample costs. Functional validation was conducted using ligands targeting the three main albumin binding sites. As proof of application, the system was used to investigate albumin binding properties in plasma from (i) type 2 diabetic patients with (n\u0026thinsp;=\u0026thinsp;10) and without (n\u0026thinsp;=\u0026thinsp;10) moderate kidney impairment, and (ii) patients with cirrhosis and acute-on-chronic liver failure (n\u0026thinsp;=\u0026thinsp;6), a condition associated with extensive albumin damage. The proposed approach provides a robust analytical framework for the functional characterization of circulating albumin in healthy and diseased conditions.\u003c/p\u003e","manuscriptTitle":"Albumin-On-A-Chip: Binding Profiling of Circulating Human Albumin via Selective Immunocapture and Real-Time SPR Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-01 10:55:18","doi":"10.21203/rs.3.rs-7190507/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-21T03:36:53+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-14T10:12:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"166857076604871660634826759901323824630","date":"2025-10-28T08:57:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"321557289281758113994592456428736575244","date":"2025-10-28T05:31:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-16T08:19:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"178947005160718998486062144065168959730","date":"2025-09-11T07:13:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-08T17:18:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"240829979470299804947316397679568321663","date":"2025-08-03T15:22:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-29T09:45:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-29T09:27:06+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-29T06:58:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-26T21:00:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-07-26T18:25:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1a06e4bc-2dc1-485c-9d10-d68c1939a8c0","owner":[],"postedDate":"August 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":52386597,"name":"Biological sciences/Biochemistry"},{"id":52386598,"name":"Health sciences/Biomarkers"},{"id":52386599,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-03-30T16:21:03+00:00","versionOfRecord":{"articleIdentity":"rs-7190507","link":"https://doi.org/10.1038/s41598-026-44934-2","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-03-27 16:09:22","publishedOnDateReadable":"March 27th, 2026"},"versionCreatedAt":"2025-08-01 10:55:18","video":"","vorDoi":"10.1038/s41598-026-44934-2","vorDoiUrl":"https://doi.org/10.1038/s41598-026-44934-2","workflowStages":[]},"version":"v1","identity":"rs-7190507","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7190507","identity":"rs-7190507","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}