A flexible multiplexed immunosensor for point-of-care in situ wound monitoring

Abstract

Chronic wounds arise from interruption of normal healing due to many potential pathophysiological factors. Monitoring these multivariate factors can provide personalized diagnostic information for wound management, but current sensing technologies use complex laboratory tests or track a limited number of wound parameters. We report a flexible biosensing platform for multiplexed profiling of the wound microenvironment, inflammation, and infection state at the point of care. This platform integrates a sensor array for measuring inflammatory mediators [tumor necrosis factor-α, interleukin-6 (IL-6), IL-8, and transforming growth factor-β1], microbial burden (Staphylococcus aureus), and physicochemical parameters (temperature and pH) with a microfluidic wound exudate collector and flexible electronics for wireless, smartphone-based data readout. We demonstrate in situ multiplexed monitoring in a mouse wound model and also profile wound exudates from patients with venous leg ulcers. This technology may facilitate more timely and personalized wound management to improve chronic wound healing outcomes.

Fig. 1. Schematic of a multiplexed immunosensing system for chronic wound monitoring.

(A) Illustration of a biomarker analytical dressing applied onto an open wound of patients with venous ulcer for in situ wound surveillance. (B) Illustration of a thin, soft, biomarker analytical dressing that allows normal skin function by letting oxygen in and moisture vapor out. Measurement data were wirelessly transmitted to a paired mobile system over Bluetooth Low Energy. (C) Envisioned biomarker analytical dressing constituting a perforated wound contact layer, a microfluidic wound exudate collector, an immunosensor, and a breathable barrier. The microfluidic collector was inspired by the skin of Texas horned lizard enabling predetermined flow direction toward the lizard’s snout defying gravity. (D) Schematic of the immunosensor for detection of TNF-α, IL-6, IL-8, TGF-β1, S. aureus, pH, and temperature. PANI, polyaniline; MB, methylene blue; RE, reference electrode; CE, counter electrode. (E) VeCare prototype for envisioned chronic wound monitoring. The prototype was applied to a leg dummy as a demonstration. The immunosensor interfacing with a wireless portable analyzer fabricated on a FPCB. A mobile application providing a GUI as a one-stop patient’s profiles, medical records, data recording, data analysis, and result visualization system is shown. (F) Hardware block diagram for the VeCare platform. WE1, working electrode 1; MUX, multiplexer.

Fig. 2. Microfluidic wound exudate collector enabling directional liquid transport.

(A) A biomimetic passive microfluidic collector formed by a polar array of interconnected half-open, sawtooth-shaped capillary channels with a decreasing width from 200 to 160 μm was fabricated on top of the base electrodes. (B) Mechanism of a directional liquid transport system exploiting the interconnection of adjacent sawtooth-shaped capillary channels. (C and D) COMSOL simulation of liquid transport in the interconnected capillary channels with decreasing width in forward and reverse directions with time, respectively (blue, liquid; red, air). (E) Dynamics of liquid transport process of a biomimetic prototype at different time points (scale bars, 500 μm). (F) Elapsed time of the liquid transport in capillary channels with decreasing width.

Fig. 3. Characterization of the TNF-α, IL-6, IL-8, TGF-β1, S. aureus, and pH sensors.

(A) Illustration of a microenvironment of venous ulcers. (B) Schematic of the sensing mechanism of the aptasensors for cytokine and bacteria detection, respectively. (C) Calibration of the resistance of the temperature sensor versus the temperature. (D to H) Variations in relative peak height reduction of the TNF-α, IL-6, IL-8, TGF-β1, and S. aureus sensors versus the concentration of corresponding targets in serum, respectively. Error bars denote the SD of the mean derived from three scans under same conditions. The insets of (D to H) show SWV scans of the TNF-α, IL-6, IL-8, TGF-β1, and S. aureus sensors when challenged with different analyte concentrations, respectively. (I) Calibration of the OCP of the pH sensor versus pH values in serum. Error bars denote the SD of the mean over a 20-s span under same conditions. The inset of (I) shows the real-time OCP of the pH sensor for different pH values.

Fig. 4. In situ monitoring on wound healing and biocompatibility in mouse wound model.

(A) Wound monitoring study design. (B) Photograph of a freely moving mouse with an immunosensor mounted on the skin wound. (C) Photograph of the excisional wounds. The immunosensor is in direct contact with right wound, while the left wound acts as a control. (D) In situ assessment of pH, temperature, mouse TNF-α, and S. aureus by the immunosensor. (E and F) Images of the wounds (scale bar, 5 mm) and changes in wound area from days 0 to 5. (G) Comparison of wound area on days 1, 3, and 5 (cumulative total of 2, 3, and 4 hours of sensor contact). (H and I) H&E images (20× stitches) of whole full-thickness wounds on day 3 and wound edges on days 1, 3, and 5, respectively (scale bars, 1000 and 250 μm). Black dotted lines show reepithelialization. (J and K) Comparison of epidermal thickness and reepithelialization distance, respectively. (L to N) H&E images of whole wounds on day 5, dermis at wound edges on days 1, 3, and 5, and area of granulation tissue on day 5, respectively (scale bars, 1000, 250, and 250 μm). Images are typical representations across all mice. Statistical comparisons use Wilcoxon signed-rank test (ns, nonsignificant result). Error bars show SD (D and F) or SE (G, J, and K) of the mean.

Fig. 5. Sensor-derived data analysis of wound exudate samples from patients with venous ulcer.

(A) Weekly assessment of pH, S. aureus, IL-6, IL-8, TNF-α, and TGF-β1 by the immunosensor for each patient. The axes represent independent scales for each of the quantified parameter, varying from 0% for the lowest level to 100% for the highest level. Weekly changes of the wound size are shown along with the biomarker assessment. (B) Patient-specific correlation matrices of parameters assessed by the immunosensor (pH, S. aureus, IL-6, IL-8, TNF-α, and TGF-β1) and the wound size over a 5-week period. The total number and duration of wounds (in months) are shown in the table for each patient. The color of standing person illustration indicates the gender of the patient (blue, male; pink, female). Scale bar represents Pearson’s correlation coefficient (r_p).