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Genetically Engineered Phages Enable Rapid, Antibody-Free SARS-CoV-2 Detection

*Important notice: This news reports on a paper which has been accepted and is awaiting peer review. Scientific Reports sometimes publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive or treated as established information.

Researchers have developed a rapid electrochemical biosensor that uses engineered bacteriophages instead of antibodies to detect SARS-CoV-2 spike protein, achieving sub-second response times and femtogram-level sensitivity in laboratory testing.

The doctor Study: An engineered M13 phage–rGO electrochemical biosensor for rapid detection of viral protein in complex matrices. Image Credit: sergey kolesnikov/Shutterstock.com

Published in Scientific Reports, the study describes a reduced graphene oxide (rGO) sensor functionalized with genetically engineered M13 bacteriophages that display a peptide targeting the viral S1 spike subunit.

The platform is designed for rapid, label-free detection under low-voltage conditions and was evaluated in buffer and in complex matrices, including fetal bovine serum, pasteurized milk, and wastewater.

The system is positioned as a laboratory-scale proof-of-concept and was tested using synthetic S1 protein rather than intact virus or clinical samples.

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Antibody-based biosensors remain a gold standard in diagnostics, but they come with logistical constraints. Production can be costly and time-intensive, storage often requires cold-chain control, and batch-to-batch variability can complicate deployment, particularly in decentralized or resource-limited settings.

Aptamers offer a synthetic alternative but require extensive selection procedures and can lose structural stability in protein-rich environments.

M13 bacteriophages – filamentous viruses that infect E. coli – provide a different strategy. Using phage display, researchers can genetically program these particles to present target-binding peptides on their coat proteins. The resulting constructs are inexpensive to produce in bacterial hosts, genetically tunable, and robust to environmental fluctuations.

In this study, the team engineered M13 phages to display a previously identified SARS-CoV-2 spike-binding peptide on the pIII coat protein. A scrambled peptide variant served as a specificity control.

Building The Phage-Graphene Sensor

The sensing platform relies on reduced graphene oxide, a conductive nanomaterial known for its high surface area and electrical sensitivity. Graphene oxide was deposited onto glass substrates and thermally reduced to form rGO.

The surface was then functionalized with a pyrene-based linker (PBASE), which binds to graphene via π-π stacking while presenting reactive NHS ester groups. These esters form covalent bonds with primary amines on the phage coat proteins, immobilizing whole M13 particles onto the rGO surface.

Because M13 presents multiple amine groups along its filamentous body (pVIII proteins), immobilization is non-directional, forming a dense phage layer across the electrode.

In this proof-of-concept configuration, residual NHS esters were not quenched, and no additional blocking step was introduced. The authors note that this may permit minor nonspecific adsorption and could be optimized in future iterations.

Surface characterization using SEM, AFM, XRD, and EDS confirmed graphene reduction and stepwise functionalization.

Low-Voltage, Sub-Second Detection

Rather than relying on traditional redox electrochemistry, the device operates through a chemiresistive mechanism. When the target S1 protein binds to the displayed peptide, it perturbs charge distribution at the graphene interface, producing a transient change in electrical current.

Measurements were performed at a fixed low bias of -0.8 mV, a voltage identified as optimal for maximizing signal-to-noise while minimizing nonspecific activation, joule heating, and faradaic side reactions.

Each analyte addition generated a rapid current spike that peaked within approximately 300 milliseconds before returning to baseline. The peak amplitude (ΔIpeak) served as the analytical readout.

Detection Limit And Statistical Framework

In buffer, the biosensor achieved an operational limit of detection of 10-4 pg/mL for the S1 protein.

Detection was defined using a statistically conservative threshold calculated as the mean blank signal plus three standard deviations. A one-sample statistical test compared each concentration to baseline noise, reflecting the platform’s primary design for binary presence-or-absence detection rather than full quantitative analysis.

Although calibration curves in buffer showed moderate correlation (R² ≈ 0.88), the authors emphasize that more extensive concentration series and matrix-specific optimization would be required for validated quantitative deployment.

Reproducibility testing across independently fabricated electrodes yielded relative standard deviations below 5%.

Performance In Complex Matrices

To assess matrix tolerance, the team evaluated spiked samples of fetal bovine serum, pasteurized milk, and municipal wastewater.

Clear detection was observed in serum and milk at 5 pg/mL. Wastewater required 10 pg/mL for consistent statistical differentiation from blanks, with greater variability attributed to environmental heterogeneity.

All experiments were conducted under controlled laboratory conditions using the synthetic S1 protein. Intact virions were not tested, and diagnostic sensitivity and specificity in clinical specimens remain to be established.

For comparison, the researchers fabricated an antibody-functionalized rGO sensor on the same platform. The phage-based system demonstrated comparable sensitivity and similarly rapid response times.

While the antibody sensor produced larger absolute signal amplitudes, both platforms reliably distinguished spiked from unspiked samples. The authors argue that phage-based recognition offers advantages in genetic tunability, production scalability, and environmental robustness.

A Modular Platform For Protein Sensing

The study presents a laboratory-scale demonstration of a scalable, antibody-independent sensing strategy capable of rapid electrochemical protein detection.

By combining engineered phage particles with graphene electronics, the platform offers sub-second readout, femtogram-level sensitivity in buffer, and tolerance to several protein-rich matrices under tested conditions.

Future work will require clinical validation, evaluation with intact virus, long-term stability studies, and expanded quantitative calibration. If successful, engineered phage–graphene interfaces could provide a flexible foundation for rapid detection of viral proteins and other biomarkers in environmental and biomedical monitoring.

Journal Reference

Alshehhi H.Y. et al. (2026). An engineered M13 phage–rGO electrochemical biosensor for rapid detection of viral protein in complex matrices. Scientific Reports. DOI: 10.1038/s41598-026-37008-w

Dr. Noopur Jain

Written by

Dr. Noopur Jain

Dr. Noopur Jain is an accomplished Scientific Writer based in the city of New Delhi, India. With a Ph.D. in Materials Science, she brings a depth of knowledge and experience in electron microscopy, catalysis, and soft materials. Her scientific publishing record is a testament to her dedication and expertise in the field. Additionally, she has hands-on experience in the field of chemical formulations, microscopy technique development and statistical analysis.    

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