Cell-Free Peanut Allergen Biosensor ABSTRACT Food allergies affect over 32 million Americans, with peanut allergies being among the most severe and life-threatening. Current peanut detection methods rely on laboratory-based immunoassays that require hours to days and specialized equipment, creating critical gaps in real-time food safety monitoring. This project develops a CRISPR-Cas12a biosensor system for rapid, field-deployable detection of the major peanut allergen Ara h1. The system leverages Cas12a’s trans-cleavage activity upon target recognition to generate a fluorescent readout, enabling detection within 15-20 minutes with an isothermal amplification step.
Food allergies affect over 32 million Americans, with peanut allergies being among the most severe and life-threatening. Current peanut detection methods rely on laboratory-based immunoassays that require hours to days and specialized equipment, creating critical gaps in real-time food safety monitoring. This project develops a CRISPR-Cas12a biosensor system for rapid, field-deployable detection of the major peanut allergen Ara h1. The system leverages Cas12a’s trans-cleavage activity upon target recognition to generate a fluorescent readout, enabling detection within 15-20 minutes with an isothermal amplification step.
Aim 1 validates proof-of-concept detection by designing custom crRNAs targeting specific regions of the Ara h1 gene and demonstrating dose-dependent fluorescence responses in cell-free reactions. Aim 2 integrates isothermal amplification (RPA) to achieve high sensitivity and tests specificity against other food allergens. Aim 3 envisions development of a handheld device for point-of-use allergen screening in restaurants and homes. This approach could revolutionize food safety by enabling rapid, on-site allergen detection, potentially preventing severe allergic reactions and improving quality of life for millions of individuals with food allergies.
PROJECT AIMS
Aim 1: Experimental Aim (this project)
The first aim of my final project is to develop and validate a CRISPR-Cas12a detection system for peanut allergen Ara h1 by utilizing custom-designed crRNAs, synthetic target DNA, and fluorescent reporter assays to demonstrate specific target recognition and quantitative detection capabilities. This involves designing high-specificity crRNAs targeting the Ara h1 coding sequence, combining them with Cas12a protein and fluorescent reporters in a cell-free system, and testing dose-dependent detection using qPCR instrumentation for fluorescence monitoring. Expected outcomes include demonstrating specific detection of Ara h1 DNA with minimal background signal and establishing detection limit parameters for the system.
Aim 2: Development Aim
Integrate recombinase polymerase amplification (RPA) with the CRISPR detection system to achieve single-copy sensitivity and validate specificity against cross-reactive allergens in real food matrices. This approach builds on the SURVEY methodology (Cheng et al., 2025) demonstrating cell-free one-pot RPA-CRISPR detection with heparin sodium regulation, potentially improving detection limits by 1000-fold. Development includes designing RPA primers, optimizing one-pot reactions, and testing the system in processed food samples to achieve detection below regulatory allergen labeling thresholds.
Aim 3: Visionary Aim
Develop a portable, handheld device capable of detecting multiple food allergens simultaneously within 15 minutes, enabling real-time allergen screening in restaurants, food manufacturing, and home kitchens. This technology could prevent allergic reactions, transform food safety practices, and establish new standards where allergen-free claims are verified in real-time rather than relying solely on ingredient lists and manufacturing protocols.
BACKGROUND
Literature Context
Current handheld food allergen detection faces significant technological and commercial limitations. The Nima sensor was the pioneer in consumer handheld allergen detection, launching a gluten sensor in 2017 and peanut sensor in 2018, using antibody-based immunoassay technology to detect 10 ppm for peanuts with above 98.7% accuracy when comparing to leading food diagnostic lab ELISA tests. However, the device required expensive disposable test capsules (~$6 each), took several minutes per test, made noise during operation, and couldn’t test certain food types like soy sauce or alcohol, ultimately leading to the company being acquired and discontinuing manufacturing. A breakthrough in CRISPR-based detection was demonstrated by Cheng et al. in their paper “Tunable control of Cas12 activity promotes universal and fast one-pot nucleic acid detection” (2025). In their SURVEY methodology, which combined recombinase polymerase amplification (RPA) with CRISPR-Cas12a detection for nucleic acid targets. Their cell-free system achieved single-copy sensitivity within 15-20 minutes using heparin sodium to regulate enzyme interactions, demonstrating that CRISPR-based detection can match or exceed PCR sensitivity while operating at constant temperature without thermal cycling equipment. This work proved that isothermal amplification coupled with CRISPR detection can achieve laboratory-grade sensitivity in portable formats.
Project Innovation
This project represents a novel application of CRISPR-Cas12a technology to food allergen detection, addressing critical limitations in current testing methodologies. Unlike existing immunoassays that detect proteins (which can be denatured during food processing), this approach targets the stable Ara h1 gene sequence that remains detectable even in highly processed foods. The innovation extends the SURVEY methodology from nucleic acid detection to food allergen screening, developing a cell-free detection system that eliminates the need for specialized laboratory infrastructure. This represents a paradigm shift from antibody-based detection (like the discontinued Nima sensor) to programmable nucleic acid detection that could enable multi-allergen detection through different crRNA designs in a single platform.
Project Impact and Significance
Food allergies affect over 32 million Americans, with peanut allergies being among the most severe and potentially fatal, causing approximately 150-200 deaths annually in the United States. Current emerging solutions like Allergen Alert (unveiled at CES 2026) are expected to retail for approximately $200 with subscription-based single-use pouches, representing significant ongoing costs for users. This project addresses the critical need for rapid, cost-effective allergen detection that can prevent allergic reactions before they occur. The technology could transform food service industries by enabling real-time verification of allergen-free food preparation, reducing liability and improving customer safety. Beyond immediate health benefits, successful development could establish new regulatory standards for allergen verification, moving from ingredient-list reliance to direct molecular confirmation. The CRISPR-based approach offers potential advantages in cost-per-test, multiplexing capability, and technological flexibility compared to current antibody-based systems, potentially making allergen detection accessible to a broader population while reducing healthcare costs associated with allergic reactions.
Ethical Implications
The development of rapid allergen detection technology raises important ethical considerations centered on the principles of beneficence and justice. The primary ethical benefit involves preventing potentially fatal allergic reactions through improved food safety monitoring, directly supporting the principle of “do good” by protecting vulnerable populations. However, implementation must consider justice and equitable access, as advanced detection technology could create disparities where only affluent establishments or individuals can afford comprehensive allergen testing, potentially excluding lower-income communities from the safety benefits. Additionally, there are concerns about creating false confidence in “allergen-free” claims if the technology has limitations not clearly communicated to users.
To ensure ethical implementation, several measures should be established including rigorous validation studies to clearly define detection limits and potential failure modes, transparent communication about technology limitations to prevent overconfidence in results, and development of cost-effective versions to ensure broad accessibility across socioeconomic levels. Regulatory oversight should require proper training for device operators and clear labeling of detection capabilities and limitations. The project should also consider potential unintended consequences such as increased anxiety among individuals with allergies if testing reveals previously unknown contamination, or potential misuse by food manufacturers to justify inadequate allergen control practices. Alternative approaches might include developing the technology as a complement to, rather than replacement for, existing allergen management protocols, ensuring that improved detection enhances rather than substitutes for proper food handling and ingredient management practices.
EXPERIMENTAL DESIGN, TECHNIQUES, TOOLS, AND TECHNOLOGY
Detailed Experimental Plan:
Phase 0: crRNA Design and Target Selection (Completed)
Target sequence retrieval and analysis: Downloaded the complete Ara h1 coding sequence (1845bp) from NCBI GenBank and systematically scanned for optimal CRISPR-Cas12a target sites using computational tools
PAM site identification: Used CRISPOR web tool to identify all potential target sequences following TTTV protospacer adjacent motif (PAM) sequences throughout the Ara h1 CDS, generating a comprehensive list of candidate sites with predicted efficiency scores
Efficiency assessment: Evaluated three promising target sites based on CRISPOR efficiency predictions: position 526 (GCACCCGCTACGGGAACCAAA, 67% efficiency), position 1077 (ACTATCACTCCTTCATTATCA, 73% efficiency), and position 1219 (efficiency data available)
Specificity validation through BLAST analysis: Performed BLAST searches against major food genome databases including tree nuts, legumes, grains, and common food crops to ensure target sequences would not cross-react with non-peanut foods
Cross-reactivity screening and final selection: Initially selected the highest efficiency targets but subsequently rejected position 1219 due to significant sequence overlap with chicken and turkey genomes that could cause false positives in poultry-containing foods, ultimately choosing positions 526 and 1077 for their combination of good efficiency and clean specificity profiles
Phase 1: Reagent Preparation and Characterization
Measure reagent concentrations using NanoDrop spectrophotometer for Ara h1 CDS DNA (Twist Biosciences), FAM-BHQ1 reporter oligo, and crRNA (IDT Alt-R system) - 30 minutes
Verify Cas12a protein concentration from NEB EnGen Lba Cas12a kit and calculate dilutions needed for working stocks - 15 minutes
Prepare target DNA dilution series creating stocks at 2000, 1000, 500, 200, and 100 nM concentrations from measured Ara h1 CDS - 45 minutes
Resuspend and prepare reporter stock at 5000 nM (5 μM) working concentration in nuclease-free water - 30 minutes
Form ribonucleoprotein (RNP) complex by mixing Cas12a and crRNA at 100 nM each in 1:1 ratio, incubate 30 minutes at room temperature for complex formation - 45 minutes
Phase 2: Master Mix Preparation
Calculate volumes for 48 reactions (24 per recipe plus 10% excess) based on final concentrations: Recipe 1 (25 nM RNP, 250 nM reporter) and Recipe 2 (50 nM RNP, 500 nM reporter) - 15 minutes
Prepare Recipe 1 master mix combining RNP complex, reporter, reaction buffer, and nuclease-free water for 18 μL per well - 20 minutes
Prepare Recipe 2 master mix with higher RNP and reporter concentrations for 18 μL per well - 20 minutes
Prepare control master mixes including no-crRNA controls (Cas12a only) and reporter-only controls - 15 minutes
Phase 3: Plate Setup and Detection
Load qPCR plate dispensing 18 μL master mix per well according to plate layout (columns 1-6 Recipe 1, columns 7-12 Recipe 2) - 30 minutes
Add target DNA adding 2 μL of appropriate concentration to each well (200, 100, 50, 20, 10, 0 nM final concentrations) - 20 minutes
Load plate into qPCR machine (Bio-Rad CFX series or equivalent) and program for continuous 37°C incubation with FAM fluorescence reading every 10 minutes - 10 minutes
Monitor fluorescence kinetics for 60-90 minutes, collecting data points to generate time-course curves - 90 minutes
Data analysis plotting fluorescence vs time for each condition, calculating signal-to-noise ratios, and determining detection limits - 45 minutes
Target DNA Wells (Rows A-E): Each well contains Cas12a-crRNA complex, FAM-BHQ1 fluorescent reporter, Ara h1 target DNA at the specified concentration, and reaction buffer. Recipe 1 uses 25 nM RNP with 250 nM reporter, while Recipe 2 uses 50 nM RNP with 500 nM reporter to test two different concentration combinations simultaneously. When Cas12a finds and binds to its target sequence, it activates and cuts the reporter molecules, separating FAM from BHQ1 to produce fluorescence proportional to the amount of target DNA present.
No Target Control (Row F) Contains all reaction components except target DNA to test whether the RNP complex produces false positive signals through non-specific reporter cleavage. Should show minimal fluorescence similar to baseline.
No crRNA Control (Row G) Contains Cas12a protein, target DNA, and reporter, but lacks the guide RNA needed for target recognition. Tests whether Cas12a requires crRNA for specific detection or can cut reporters non-specifically. Should show minimal fluorescence, confirming that both protein and guide RNA are required.
Reporter Only Control (Row H) Contains only the FAM-BHQ1 reporter and buffer to establish the baseline fluorescence level before any nuclease activity. Provides the zero point for calculating signal-to-noise ratios and determining detection thresholds.
Expected Results by Experimental Component:
RNP Complex Formation: Successful complex formation verified by stable fluorescence baseline in control wells without target DNA.
Dose-Response Detection: Recipe 2 (higher concentrations) expected to show stronger signal and faster kinetics than Recipe 1, with detectable fluorescence increase starting within 20-30 minutes for high target concentrations (≥50 nM).
Target Specificity: Clear dose-dependent response with fluorescence increases proportional to target DNA concentration, demonstrating quantitative detection capability.
Control Validation: No-target controls showing minimal fluorescence increase (<10% of positive signals), no-crRNA controls demonstrating requirement for guide RNA, reporter-only controls establishing baseline fluorescence.
Detection Limits: Anticipated detection threshold between 10-50 nM target DNA for direct detection without amplification, with Recipe 2 potentially detecting lower concentrations than Recipe 1.
Techniques Utilized:
☑ Bioethical Considerations
☑ Pipetting
☑ DNA Construct Design
☑ Databases (GenBank, NCBI for Ara h1 sequence)
☑ Designing a Twist Order
☑ Use of Asimov Kernel
☑ CRISPR/Cas9 (Cas12a system)
☑ Cell-Free Systems
Detailed Technique Applications:
DNA Construct Design: The project centers on designing synthetic DNA constructs including the full-length Ara h1 CDS (1845bp) ordered from Twist Biosciences as the target template, and custom crRNAs designed through a systematic computational approach that began with CRISPOR analysis to identify optimal TTTV PAM sites throughout the Ara h1 sequence and predict Cas12a cutting efficiency using machine learning algorithms. The crRNA design process involved evaluating multiple candidate target sites, ultimately selecting positions 526 (GCACCCGCTACGGGAACCAAA, 67% efficiency) and 1077 (ACTATCACTCCTTCATTATCA, 73% efficiency) based on their high efficiency scores, while rejecting other promising sites like position 1219 due to cross-reactivity concerns identified through BLAST database searches against food genomes. Comprehensive BLAST analysis against major food genome databases including tree nuts, legumes, grains, and common food crops confirmed that the selected target sequences would detect only peanut allergens without cross-reactivity to chicken, turkey, or other common food proteins, ensuring the specificity required for reliable allergen detection in complex food matrices.
DNA construct design was central to the validation, involving computational design of both the target Ara h1 sequence and the guide RNA spacer sequences using bioinformatics tools like CRISPOR and BLAST to ensure optimal targeting efficiency and specificity. The crRNA design process specifically utilized CRISPOR’s machine learning algorithms to predict Cas12a cutting efficiency while BLAST database searches against food genomes confirmed that selected targets would detect only peanut allergens without cross-reactivity to chicken, turkey, or other common food proteins.
Cell-Free Systems: The experimental approach utilizes a completely cell-free detection system, eliminating the need for bacterial cultures or living cells. This cell-free approach enables rapid detection (1-2 hours vs days for cell-based assays) and simplifies the workflow for potential field deployment. The system combines purified Cas12a protein, synthetic crRNAs, target DNA, and fluorescent reporters in optimized buffer conditions, allowing direct measurement of CRISPR activity through trans-cleavage of reporter molecules. This cell-free design is inspired by recent advances in portable diagnostics and aligns with the goal of developing field-deployable allergen detection systems.
Industry Council Companies Associated with Project:
Twist Biosciences - DNA synthesis for Ara h1 target gene
New England Biolabs - Cas12a enzyme
Asimov - Project planning and DNA sequence management
Ginkgo Bioworks - Potential partnership for automated assay development
RESULTS AND QUANTITIVE EXPECTATIONS
What aspect of your final project did you choose to validate?
I chose to validate the core CRISPR-Cas12a detection mechanism by designing custom crRNAs targeting the Ara h1 peanut allergen gene and testing their ability to guide Cas12a for specific DNA detection with fluorescent readout. This validation demonstrates the fundamental detection principle underlying the entire biosensor system, proving that programmable nucleic acid recognition can generate measurable signals for allergen identification.
Detailed validation protocol:
Target sequence analysis: Retrieved Ara h1 CDS from NCBI GenBank and used CRISPOR to identify optimal target sites with TTTV PAM sequences
Specificity validation: Performed BLAST searches against food genome databases to confirm target sequences are peanut-specific
crRNA design: Selected position 526 target sequence (GCACCCGCTACGGGAACCAAA) with 67% efficiency score and clean specificity profile
Reagent preparation: Ordered synthetic Ara h1 CDS from Twist Biosciences, custom crRNA from IDT Alt-R system, and Cas12a protein from NEB
RNP complex formation: Combined Cas12a protein with crRNA at 1:1 ratio, incubated 30 minutes at room temperature
Detection assay setup: Prepared two recipe formulations (25 nM vs 50 nM RNP concentrations) with FAM-BHQ1 fluorescent reporters
Kinetic analysis: Tested target concentrations from 10-200 nM with measurements at 5, 10, 15, and 30-minute intervals
Control validation: Included no-target and no-crRNA controls to verify signal specificity
Data collection: Used qPCR fluorescence detection to monitor trans-cleavage activity over time
Synthetic biology techniques utilized:
DNA construct design was central to the validation, involving computational design of both the target Ara h1 sequence and the guide RNA spacer sequences using bioinformatics tools like CRISPOR and BLAST to ensure optimal targeting efficiency and specificity. Cell-free systems development enabled the entire detection mechanism to operate using purified components rather than living cells, combining Cas12a protein, synthetic crRNAs, target DNA, and fluorescent reporters in optimized buffer conditions. CRISPR/Cas12a programming involved designing guide sequences that direct the nuclease to recognize specific DNA targets, utilizing the programmable nature of CRISPR systems where changing the 20-nucleotide spacer sequence redirects the enzyme to new targets. Database utilization was essential for target validation, using NCBI resources for sequence retrieval and BLAST analysis against multiple food genomes to confirm the designed system would detect only peanut allergens without cross-reactivity.
Data presentation and analysis:
Due to reagent ordering delays, I was unable to perform the experimental validation and instead generated theoretical data based on expected CRISPR detection performance to demonstrate anticipated results and data analysis approaches. The simulated data shows quantitative fluorescence kinetics with dose-dependent responses from 10-200 nM target concentrations and time-dependent signal development over 30 minutes, with Recipe 1 achieving detection from 20-100 nM (2.1× to 6.2× baseline fluorescence) and Recipe 2 showing enhanced sensitivity down to 10 nM with maximum signals reaching 8.1× baseline. This theoretical framework establishes the expected experimental outcomes and analysis methods that would validate the CRISPR detection system’s functionality, providing a foundation for future experimental work when reagents become available.
Challenges and limitations encountered:
The primary challenge was that reagent orders (Twist DNA synthesis, IDT crRNA synthesis, and NEB protein) did not arrive in time for experimental validation, requiring the use of simulated data based on literature expectations rather than actual laboratory results. This highlighted the importance of earlier reagent ordering and longer lead times for custom DNA synthesis and specialized molecular biology reagents in future project planning. Beyond logistical challenges, the designed system faces technical limitations including the detection limit of 10-20 nM being insufficient for real-world food samples without amplification, and potential optimization needs for balancing signal strength versus background fluorescence in different recipe formulations. Future strategies to overcome these limitations include implementing isothermal amplification (RPA) to achieve single-copy sensitivity, testing alternative reporter designs to improve signal-to-noise ratios, and developing robust supply chain planning to ensure reagent availability aligns with experimental timelines for reliable project execution.
ADDITIONAL INFORMATION
References
Cheng et al. (2025). SURVEY methodology: Cell-free one-pot RPA-CRISPR detection with heparin sodium regulation for isothermal amplification and nucleic acid detection
Nima sensor development and commercial history (2017-2018): Pioneer handheld allergen detection device using antibody-based immunoassay technology Nut Free WokWikipedia
Allergen Alert (2026): Next-generation portable allergen detection device unveiled at CES 2026, developed by bioMérieux spinout company
Certified Laboratories: Description of the current challenges in allergen detection
Integration of biosensing technologies and portable detection devices for reliable on-site food allergen detection ScienceDirect
Recent advances in CRISPR-Cas biosensors for food safety applications and aflatoxin detection
NCBI GenBank database: Ara h1 gene sequence retrieval and analysis
CRISPOR web tool: Guide RNA design and efficiency scoring for Cas12a targeting
BLAST database: Specificity analysis and cross-reactivity screening against food genomes
Claude: for documentation drafting and hypothetical data generation/presentation
Supply list and budget for project
Core Reagents:
Synthetic Ara h1 target DNA (Twist Biosciences): $110.70
