Design and Implementation of an Open-Access Arsenic Biosensor

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Teijeiro, Ezequiel J. Alba Posse, Alejandro Daniel Nadra This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7196795/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Feb, 2026 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Arsenic contamination in groundwater is a critical global issue, affecting over 140 million people worldwide and posing severe public health risks, particularly in low-resource and rural communities. Argentina alone has approximately 4 million people exposed to arsenic. The measurement of arsenic in private wells is often limited by high costs, specialized personnel requirements, and geographical distances to analytical laboratories. In this paper, we describe the design and implementation of a portable, open-access arsenic biosensor that combines synthetic biology and industrial design. The biosensor employs genetically modified Escherichia coli and a colorimetric readout to detect arsenic concentrations as low as 5 µg/L. Validation studies on 61 samples yielded a sensitivity of 98.1% and specificity of 99.0%. By using paper-based, dehydrated bacterial modules and a 3D-printed housing, this device is cost-effective, easy to use, and amenable to replication in low-resource settings. In addition, the open-access approach ensures that critical knowledge such as plasmid sequences, device schematics, and protocols can be freely shared and locally adapted. Beyond the technical advantages, this biosensor can potentially influence global policies and Argentinian programs on water quality monitoring, empowering communities to take charge of arsenic surveillance and safeguard public health. Biological sciences/Biological techniques Biological sciences/Biotechnology Earth and environmental sciences/Environmental sciences Biological sciences/Microbiology Arsenic biosensor Groundwater monitoring whole cell Figures Figure 1 Figure 2 Figure 3 Introduction Arsenic Contamination: A Global and Local Challenge Access to safe drinking water is recognized as a fundamental human right [ 1 – 3 ], yet over two billion people worldwide still lack reliable access [ 4 – 6 ]. One significant factor contributing to unsafe water is the presence of both natural and anthropogenic contaminants. Among these, arsenic poses one of the most severe risks to public health due to its toxicity and carcinogenic properties [ 7 – 9 ]. Chronic exposure to elevated arsenic levels is associated with cancers (skin, lung, bladder, and kidney, among others), and non-carcinogenic illnesses such as arsenicosis, diabetes mellitus, and various cardiovascular and respiratory diseases [ 8 , 10 , 11 ] . While arsenic contamination in groundwater is a global concern - affecting regions in Bangladesh, India, China, and the United States [ 9 ]- it is particularly significant in Latin America, with over 14 million people consuming water exceeding WHO’s 10 µg/L guideline for arsenic [ 12 ]. Argentina is among the most affected nations; estimates suggest around 4 million individuals, especially in the Chaco-Pampean plain and various other peripheral regions, rely on arsenic-contaminated water sources ( Fig. 1 ) [ 11 – 14 ]. Vulnerable populations in these areas often have limited awareness of arsenic-related health risks, and are geographically and economically constrained from accessing accurate testing or mitigation solutions [ 15 ]. Arsenic in water is odorless, tasteless, and colorless, making it imperceptible to human senses and posing a hidden threat. Limitations of Existing Detection Methods Current standard analytical methods for arsenic, such as atomic absorption spectroscopy (AAS) and inductively coupled plasma mass spectrometry (ICP-MS), provide high sensitivity and specificity [ 16 ]. However, these techniques are costly, require trained personnel, and necessitate specialized laboratory facilities , making them impractical for routine monitoring in remote or underprivileged regions. On the other end, affordable field kits (often colorimetric based on chemical reagents) sometimes lack the required sensitivity or reproducibility to confidently detect arsenic at or below the WHO guideline [ 17 – 19 ]. Argentina’s situation illustrates this challenge: many residents obtain water from private wells in rural areas, where infrequent or expensive testing can delay intervention until serious health effects emerge [ 10 , 13 , 14 ]. Consequently, there is a growing need for community-friendly, low-cost, robust, and highly sensitive detection technologies to enable timely decision-making on water potability. Biosensors for Arsenic Detection Biosensors engineered to detect arsenic offer a promising solution that balances cost, sensitivity, and ease of operation [ 19 – 21 ]. These devices harness biological components - such as bacteria or enzymes - to produce measurable signals (e.g., color changes) upon exposure to arsenic. By integrating synthetic biology with user-centric industrial design, biosensors can be made portable, simple, and resilient enough for wide-scale deployment in resource-constrained settings [ 19 , 20 , 22 ]. Our previous biological device was based on a red colored protein whose lower limit was hardly 50 µg.L−1 and took several hours to reach a color level detectable by the naked eye (particularly difficult for people with the most frequent red color blindness). Thus, we evaluated alternatives to improve the detection limit and response time. [ 23 ][ 24 ] Here, we describe the conception, design, and validation of an open-access arsenic biosensor, optimized for low-cost manufacturing and decentralized distribution. Our approach leverages genetically modified Escherichia coli to yield a colorimetric response in the presence of arsenic concentrations as low as 5 µg/L. We also introduce an ergonomic, 3D-printed housing that simplifies assay operation and ensures user safety. The device’s open-access model is central to our mission: all plasmid sequences, device blueprints, and protocols are publicly shared to foster local production, encourage user-driven improvements, and lower barriers to adoption. Materials and Methods Biosensor Module: Genetically Engineered E. coli The biosensor module consists of E. coli DH5α cells carrying the pMV-arsR-ABS1595 plasmid [25], which places the lacZ (β-galactosidase) gene under an arsenic-responsive promoter. This promoter is triggered by the presence of arsenite (As(III)), leading to β-galactosidase production. When the cells come into contact with X-gal substrate, the enzymatic reaction produces a blue color proportional to arsenic concentration. Bacterial Growth: E. coli DH5α was grown in Luria-Bertani (LB) medium with 100 µg/mL ampicillin at 30°C, 215 rpm, overnight. Cells were harvested by centrifugation at 2,800 × g for 5 minutes and resuspended in a solution containing 34% (w/v) trehalose and 1.5% (w/v) polyvinylpyrrolidone to OD=2. Dehydration on Paper: Aliquots (12 µL) of the resuspended cells were deposited onto 10×7 mm pieces of Whatman 3MM chromatography paper. Paper strips were placed in 2 mL Eppendorf tubes and dehydrated for 2 hours using a SpeedVac vacuum concentrator. These dried, bacteria-impregnated strips (biosensor modules) can be stored at room temperature for up to 30 days without significant loss of responsiveness. 3D-Printed Device Fabrication To ensure ease of use, portability, and user safety, we designed a multi-part device using parametric Computer-Aided Design (CAD) software (Solidworks 3d CAD, Waltham, MA). The device includes (see figure 3): Sample Holder (Part 1) : Three wells (blank, sample, and arsenic standard) for fluid loading. Plastic Circuit Holder (Part 4) : Houses the paper biosensor module and facilitates capillary flow. Paper Components (A, B, C, D) : A layered arrangement of dehydrated bacteria (B), substrate-containing paper (D), and flow paths (A, C) to direct samples to the bacteria. All plastic parts were printed with polylactic acid (PLA) filament (1.75 mm diameter) on a standard RepRap FDM 3D printer at 0.15 mm layer height. The final device assembly ensures a sealed environment for the bacterial module, preventing user contact with live microorganisms. Once the assay is complete, the used module can be inactivated with bleach and discarded. Assay Procedure 1. Activation Buffer : An activation solution (LB broth : 20 mg/mL X-gal in DMSF : 0.4 M EDTA at an 8:1:1 ratio) is added to the dehydrated strip (12 µL) to rehydrate the bacteria. 2. Sample Loading : 1 mL of water sample or standard arsenic solution is introduced into the designated well on the sample holder. The sample flows via capillary action through the biosensor module, contacting the E. coli cells. 3. Incubation and Detection : The device is kept at ambient temperature (16-25°C) for 8-16 hours. If arsenic is present, β-galactosidase expression results in a visible blue color, which intensifies with increasing arsenic concentrations. 4. Color analysis script: The images are analyzed with a python-based script written on Python using OpenCV library [26] for image analysis (https://github.com/SensAr-Biosensor). The script calculates an inverse-intensity value, yielding a numerical readout that correlates with the visible blue hue. The color is analyzed on a user-defined area of a jpg image. The RGB channels of every pixel of the selected area are splitted and inverted. The output value is calculated as follows: 5. Smartphone Data Capture (optional): An Android-based app (“SensAr”) assists with color analysis. Users align the device’s reaction zones on their phone camera; the app automatically measures color intensities, geotags the location, and uploads data to a central database for map-based arsenic tracking. 6. Disposal : After completing the assay, each used paper module should be immersed in a 10% (v/v) household bleach solution for 30 minutes to ensure inactivation of E. coli cells. Treated strips can then be discarded as regular waste, in accordance with local biosafety regulations. This step complies with standard BSL-1 disposal protocols [1], mitigating any potential release of viable genetically modified microorganisms into the environment. Validation with Field Samples A total of 61 water samples from Buenos Aires Province (Argentina) were collected by the National Water Institute (N=32) and Instituto de Hidrología de Llanuras “Dr. Eduardo Jorge Usunoff” (IHLLA; N=29) as part of routine arsenic monitoring campaigns [27]. Arsenic concentrations in these samples ranged from below detection limits to 101.7 μg/L (mean ± SD = 36.1 ± 24.4 μg/L), as measured by AAS-hydride generation following standard methods (APHA Standard Methods 3113, 3114) [26].[1,16] To validate the biosensor, each sample was tested qualitatively against a 10 μg/L cutoff. Sensitivity, specificity, and false positive/negative rates were calculated as follows: Statistical Analysis of Colorimetric Responses Images of the biosensor strips were taken under consistent lighting conditions using a standard smartphone camera. Color intensities (RGB channels) were quantified using a Python-based script yielding a numerical readout that correlates with the visible blue hue. Repeated-measures ANOVA with Tukey’s post hoc test was used to compare mean intensities at different arsenic concentrations (GraphPad Prism 8, GraphPad Software, Inc.). Results Biosensor Performance and Sensitivity Among the different constructs we evaluated including SensAr variants with mRFP, GFP or β-galactosidase as reporter [23], the one with best performance was construction 1595 from Stocker et al [25] generously sent by Drs J.R. Van der Meer and V. Sentchilo, with a robust and sharp response in the range 0 - 1000 μg.L-1 (Fig S1), a linear range between 0- 50 μg.L-1, and a detection limit of 5 μg.L-1 (Fig S2). The optimal response time was between 2-4 hs at 30°C (Fig S3). To evaluate the response to arsenic, the biosensor modules were re-hydrated in 48 wells plates with 500 μl of arsenic standards prepared from 100 mg/L sodium arsenite stock solution and incubated at room temperature for 8 - 16 h. After the induction period, papers were taken out and the excess of water was absorbed with tissue paper. Color development was evaluated on images taken under even white background and fluorescent tube illumination with a standard cell-phone camera without flash. A single image was taken for all the modules to be analyzed on each bath in order to avoid differences on white balance or illumination intensity. On every 17 independent assays made on different days, the response produced increased at each concentration step 0 to 50 μg/l As (Fig 2A). Although individual values, including blanks, were not stable between days, the analysis of each assay independently gave a consistent increasing response. The assays were performed at variable room temperature (16-25℃) and time (8-16 h) in order to resemble not controlled user operator conditions and evaluate robustness at the same time. Furthermore, despite blank modules showed background color development (Mean color0 μg/l As = 0.301 ± 0.017 ), the mean response produced at 5, 10 and 50 μg/l were significantly higher than blank and between them (Mean color 5 μg/l As = 0.379 ± 0.021; Mean color 10 μg/l As = 0.448 ± 0.024; Mean color 50 μg/l As = 0.531 ± 0.026; p < 0.0001; repeated measures ANOVA, Tukey post hoc test ) (Fig 2B.). Thus, colorimetric assays performed under ambient conditions (16-25°C) showed robust and consistent detection of arsenic concentrations as low as 5 μg/L. Despite some day-to-day variation in absolute color values, the biosensor demonstrated consistent increases in blue color intensity from 0 to 50 μg/L (Figure 2). Validation with Field Samples In order to validate the performance of the assay we analyzed samples from the Buenos Aires Province of Argentina obtained during 2020 from annual water analysis campaigns performed by the National Water Institute and IHLLA (see Supplementary Table 1). The arsenic concentrations on the samples were analyzed by those Institutions laboratories using the gold standard atomic absorption spectrometry method. The arsenic level ranged from not detectable to 101.7 μg/L (Mean ± SD = 36.1 ± 24.4 μg/L). When tested against the 61 field samples with known arsenic concentrations, including 9 negative samples; 52 positive samples (As ≽ 10 μg/L) of which 19 had high arsenic concentration (As ≽ 50 μg/L) [16]. The biosensor accurately classified samples above or below the 10 μg/L threshold, with only one false positive and one false negative (Table 1). Overall sensitivity was 98.1% and specificity was 99.0%, indicating excellent performance relative to standard laboratory methods. Table 1. Validation Results Comparing Biosensor Qualitative Output with AAS Measurements Parameter Value Number of Samples 61 Total Positives (TP) 52 Total Negatives (TN) 9 False Positives (FP) 1 False Negatives (FN) 1 False Positive Rate 0.0100 False Negative Rate 0.0189 Sensitivity 98.1 % Specificity 99.0% Arsenic level in field samples ranged from <1 to 101.7 μg/L. Cut-off for positivity: 10 μg/L Device Assembly and Operation The final prototype, called “SensAr,” was designed and developed in order to be cost effective, accessible and as easy to use, with a graphical and ergonomic interface that does not require a qualified user. It consists of 3D-printed PLA parts holding layered paper components impregnated with dehydrated E. coli and X-gal (Figure 3). Its parts are joined and sealed after the bacteria are placed, resulting in a safe and tight compartment. The modular design allows easy assembly and replacement of individual components. Operation is straightforward, involving sample loading, passive incubation, and a final color readout. The integrated smartphone application can optionally quantify results and provide a geo-referenced data log (Figure 3C). The μPAD device consists of paper components (A-D) which make up the biosensor circuit itself, and PLA plastic components (parts 1-5) that form the circuit and sample holders. The sample holder (1) contains three wells where the blank, sample, and arsenic standard are placed. The circuit holder (4) contains the paper components of the device and facilitates liquid flow through the biosensor module. The X-gal carrying paper is secured to the button with paper glue, which is supported on the back of the device. The paper circuit contains the input impregnated with dehydrated LB, which allows the sample to enter via capillarity. The sample then flows through the biosensor module and onto an absorbent pad Device Assembly Three pieces of paper, denoted as D, are each loaded with 1.5 μL of X-gal (20mg/ml DMSO). Subsequently, part 3 is inserted onto part 2, and the resulting 2-3 set is attached to part 1 using ethyl cyanoacrylate super glue (UHU, Germany) adhesive. The paper circuit is then assembled on the plastic circuit holder (4) in a specific order. Firstly, parts A and C are placed at the base of the holder. Secondly, the biosensor modules (B) are gently laid on top, ensuring that they are in contact with their corresponding parts A and C. Finally, a PET lid is firmly sealed on top of the circuit using liquid silicone adhesive (UHU, Germany) ensuring the integrity of the device. Device operation The sample holder (1 in Figure 3) is used to load the sample, blank, and standard solution (1 mL) onto their respective wells using either a Pasteur pipette or a syringe. The assay is initiated by inserting the circuit holder (4+3+2 in figure 3 assembled and sealed) onto the sample holder, which triggers the absorption of the sample through the pads. The flow is sustained for 1.5 hours, after which button 3 is pressed firmly from behind, causing the X-gal paper D to push up the B. This action has two effects: it interrupts the circuit by separating B from A, and it allows the X-gal substrate to come into contact with the bacteria. The results are assessed and documented using the SensAr Android application after 4 hours. Android app usage After the user has signed in on the SensAr. The following sample information is entry: data source (well/red/fresh), the temperature of the assay and other observations concerning the sample. The app will ask to acquire the QR code info (date and batch data is obtained from the QR code). Afterwards, three zones will be displayed to frame the image in the three reaction zones. The app detects and delimit the rectangles automatically and the user can record the image by tapping the screen. If the user confirms that the zones are well located, the app will save the image and perform the analysis. The result is reported instantly, and a complete report can be sent by mail or shared through other smartphone apps. Also, the results are sent to a database including the geolocation of the analysis obtained from the phone. Discussion In this work we described the design and implementation of a portable, open-access arsenic biosensor useful for low cost and field monitoring of contaminant levels. The biosensor employs genetically modified Escherichia coli and a colorimetric readout with limit of detection as low as 5 µg/L. Our original design included an incoherent feed forward system to make the signal independent of the evaluation time and only depend on the contaminant concentration [ 23 , 24 ]. However, the complexity of the design, which required the incorporation of several extra genes, made it less robust to operate under uncontrolled conditions. Thus, we decided to exclude the incoherent feed forward and rely on an internal growth and color development reference. In addition we switched from mRFP to b-galactosidase as a reporter which improved the sensitivity, speed and detection for red color blind people. Precise colors quantification is done with an Android application developed for this purpose. The reference standard was set to 10 micrograms per liter, in line with WHO limit to drinking water and Argentinian regulation [ 28 , 29 ] and can be easily modified to fit changes in local regulation. The arsenic biosensor in water has been designed to be distributed as a kit that allows a determination of the water in evaluation by an unqualified user. Being open access, its production can be decentralized, though it needs some infrastructure that is easily available in most science schools and universities. The ease by which the bacteria can reproduce and the low bacterial concentration required, make the product easy to be massively produced and with a very low cost of the active agent. Furthermore, being based on bacteria, purification of active ingredients is not required. The biomass that is generated when cultivating bacteria is directly the "system" of measurement. These characteristics result in a very low production cost and mostly independent of imported supplies. Validation studies on 61 samples yielded a sensitivity of 98.1% and specificity of 99.0%. By using paper-based, dehydrated bacterial modules and a 3D-printed housing, this device is cost-effective, easy to use, and amenable to replication in low-resource settings. Comparative Analysis with Existing Arsenic Detection Technologies A variety of arsenic detection techniques are available, each with distinct strengths and limitations : Laboratory-Based Methods Atomic Absorption Spectroscopy (AAS) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) exhibit detection limits down to parts-per-trillion levels and offer high precision [ 16 ]. However, they require specialized equipment, well-trained operators, and sample transport to centralized labs, making routine surveillance expensive and logistically challenging for remote communities [ 16 – 18 ] Chemical Field Test Kits Conventional test kits (e.g., based on Gutzeit or mercuric bromide indicator methods) are more affordable and portable than AAS or ICP-MS [ 16 – 18 ]. Yet, they often struggle to reliably detect arsenic near the 10 µg/L threshold, can suffer from interfering substances (e.g., sulfide), and may yield subjective or semi-quantitative colorimetric readings. Electrochemical Sensors Electroanalytical methods (e.g., anodic stripping voltammetry) can achieve low detection limits [ 16 – 18 , 30 ]. Still, they typically require instrumentation (potentiostats) and often need careful calibration, limiting accessibility in low-resource settings [ 31 ]. Biosensors The biosensor described here uses genetically engineered E. coli to detect arsenic. By encoding β-galactosidase under an arsenite-responsive promoter, color development occurs in response to low µg/L arsenic concentrations. Compared to chemical field kits, our biosensor shows higher sensitivity and specificity around the critical 10 µg/L cutoff, while remaining lower in cost and simpler to operate than electrochemical or advanced laboratory techniques [ 20 , 32 ]. In summary, the SensAr biosensor offers a balanced solution for communities requiring on-site, low-cost monitoring at relevant regulatory limits. The open-access nature further enables local manufacturing and adaptation to specific contexts or additional target analytes. Policy Implications: A Global and Argentinian Perspective Global Policies Arsenic contamination intersects with global water governance frameworks, including the WHO guidelines of 10 µg/L [ 28 ] and the United Nations Sustainable Development Goal (SDG) 6 [ 28 , 33 ], which calls for universal access to safe drinking water ]. Many low- and middle-income countries strive to meet these standards [ 28 , 29 , 33 ] but lack adequate resources for widespread testing infrastructure [ 34 ]. An affordable, user-friendly arsenic biosensor can empower communities to self-monitor their water sources, facilitating data-driven decisions and supporting compliance with regulatory requirements. Beyond local surveillance, widespread deployment of biosensors can contribute to real-time water quality mapping at national or regional scales. Policymakers can harness these data to prioritize interventions, allocate resources, and refine regulatory strategies x. Additionally, the integration of open-access tools aligns with recent calls for increased transparency and data sharing in global health initiatives, enabling broader stakeholder engagement [ 35 ]. Argentinian Programs In Argentina, high arsenic levels in groundwater are well-documented, particularly in the Chaco-Pampean region [ 13 , 14 ]. Existing programs under the Ministry of Health and local water authorities aim to mitigate exposure through infrastructure projects (e.g., water treatment installations) and public health campaigns [ 15 ]. However, these efforts often rely on sporadic laboratory testing, which may overlook temporal or spatial fluctuations in arsenic levels. An easily deployable biosensor can strengthen Argentina’s arsenic mitigation efforts by providing real-time data in underserved or remote communities. This approach complements national or provincial policies by enabling local stakeholders (as municipalities, community health workers, and even individual well owners ) to detect arsenic surges rapidly, reducing the risk of chronic exposure. As the Argentinian government continues to revise its strategies (e.g., Plan Nacional de Agua or other rural water safety programs), low-cost biosensing can be a valuable component to expand monitoring coverage and inform timely responses. Open-Access Model: Ethical, Practical, and Scientific Benefits Ethical Rationale Open-access dissemination of technology and knowledge is especially critical for addressing public health challenges in underserved regions [ 36 ]. By freely sharing device schematics, plasmid sequences, and protocols, we promote equitable access to essential tools that can save lives. This democratizes innovation, ensuring that patent barriers or licensing fees do not hinder communities from adapting or producing the biosensor locally [ 36 – 38 ]. Practical Advantages Cost-Effectiveness : With the bacterial modules grown in basic lab conditions and device parts 3D-printed from inexpensive PLA filament, production costs remain low (< $1 per test estimated). Local Adaptation : Open designs permit iterative improvements based on local materials, cultural practices, or environmental factors (e.g., water hardness). Community Engagement : Shared protocols enable universities, NGOs, and grassroots organizations to build capacity, train local users, and maintain a distributed network of arsenic monitoring sites. Scientific Benefits Collaboration and Transparency : Open-access fosters cross-institutional collaborations, spurring new ideas and accelerating iterative design improvements [ 36 , 37 ]. Reproducibility : Publicly available genetic constructs and device designs reduce ambiguity and facilitate validation by independent groups, building a broader consensus on performance and reliability. In the case of the SensAr device, we have released our plasmid maps, paper-cutting patterns, and 3D-printing files to ensure any research lab or community-based science initiative can replicate or improve upon our work. This strategy helps overcome traditional limitations in technology transfer to remote settings and aligns with the ethos of open science by lowering entry barriers for others who wish to address arsenic contamination. However, it does not address certain 'contextual' limitations discussed elsewhere [ 39 ]. Additionally, the biosensor’s modular design allows for minimal modifications to enable the detection of other substances, such as lead [ 38 ]. Replication in Low-Resource Settings Designing the biosensor with a focus on low-resource environments was integral to this project. Key considerations included : Room-Temperature Shipping and Storage : The bacterial modules remain viable for ~ 30 days without refrigeration, simplifying last-mile delivery. Minimal Equipment : Assays only require a pipette or syringe and minimal reagents, eliminating the need for advanced laboratory tools. Ease of Disposal : Post-assay disposal is straightforward; the bacterial strips can be inactivated with mild bleach solution or incineration, complying with biosafety guidelines [ 1 ]. By alleviating common logistical hurdles (cost, refrigeration, specialized training), our biosensor can be implemented by local health workers, NGOs, or even directly by residents. Coupled with the open-access model, these features ensure the device is not only affordable but also culturally and infrastructurally adaptable across diverse settings. Conclusion We developed a low-cost, open-access arsenic biosensor through an interdisciplinary effort uniting synthetic biology and industrial design. The resulting tool demonstrates high sensitivity and specificity, meets WHO guidelines (10 µg/L), and can be easily mass-produced and deployed in low-resource environments. By integrating user-friendly design with freely available blueprints and protocols, we aim to empower communities with real-time water quality information, ultimately reducing chronic arsenic exposure and improving public health outcomes. Looking ahead, scaling this open-access model can foster collaborative innovation, allowing global communities to customize and expand biosensor technologies. Such grassroots-driven surveillance supports policymaking at the local, national, and international levels, aligning with SDG 6 and other global health initiatives. In Argentina, the biosensor offers a valuable complement to existing arsenic mitigation policies, particularly in rural or marginalized populations. More broadly, our approach highlights how open science and cost-efficient biotechnology can jointly advance the human right to safe drinking water. Declarations Acknowledgments Since the inception of this project at the end of 2012, many individuals and institutions have contributed. We thank B. Basanta, H. Bonomi, N. Carlotto, M. Giménez, A. Grande, N. Nieto Moreno, F. Barone, F. Dorr, L. Marasco, S. Mildiner, I. Patop, S. Sosa, L. Vattino, and F. Vignale for initial steps in designing the biological components. We also acknowledge Romina Mathieu and Luciana Feo Mourelle for early physical prototypes. Special thanks to I. Patop, S. Sosa, and F. Vignale for pushing the project to receive the “Innovative Product” Prize at the Argentinian Innovation Contest Innovar 2014. We are grateful to the Facultad de Ciencias Exactas y Naturales (University of Buenos Aires) and GarageLab for providing the foundational environment. This project was supported by the Ministry of Science and Technology (MINCyT), the Ministry of Education (SPU), ANPCYT (PICT-2015-3834), Universidad de Buenos Aires (PDE 24, 2024), and numerous contributors to our crowdfunding campaign on idea.me. We also thank Dr. J.R. Van der Meer and Dr. Vladimir Sentchilo for providing the ArsR plasmids and INA and IHLLA for sharing samples and data of their water campaigns. Finally, we acknowledge Prof. Verónica Liñares for assistance in translating sections of the article. Author Contributions & Data Availability Author Contributions Conceptualization: A.D. Nadra, J. Gasulla. Methodology and Investigation: J. Gasulla, E. Alba Posse, A. Teijeiro. Visualization: A. Teijeiro, J. Gasulla, E. Alba Posse. Supervision, Project Administration and Funding Acquisition: A.D. Nadra. Writing Original Draft: A.D. Nadra. Writing Review & Editing : All authors Data Availability Statement : All relevant data supporting the findings of this study are provided within the manuscript and its Supplementary Information files. Additional raw data (images, colorimetric outputs, Python scripts, and 3D design files) are openly available at GitHub SensAr-Biosensor under license CC-BY 4.0 Open Hardware Documentation : STL files, CAD designs, Plasmid sequence, and instructions for printing/assembly are available at GitHub SensAr-Biosensor. Physical plasmid can be requested in Addgene 240494. Funding Agencia Nacional de Promoción Científica y Tecnológica (PICT-2015-3834); Universidad de Buenos Aires (PDE 24, 2024) Additional Information The author(s) declare no competing interests. References Third edition. Laboratory biosafety manual. [cited 19 May 2025]. Available: https://iris.who.int/bitstream/handle/10665/42981/9241546506_eng.pdf United Natios. General Assembly United Nations. Sixty-fourth session Agenda item. [cited 19 May 2025]. Available: https://documents.un.org/doc/undoc/gen/n09/479/35/pdf/n0947935.pdf World Health Organization. Progress on drinking water, sanitation and hygiene in schools. 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Available: https://www.undp.org/sustainable-development-goals Litter, M. I. et al. Arsenic in Argentina: Occurrence, human health, legislation and determination. Sci. Total Environ. 10.1016/j.scitotenv.2019.04.262 (2019). Fecher, B., Friesike, S., Hebing, M. & Linek, S. A reputation economy: how individual reward considerations trump systemic arguments for open access to data. Palgrave Commun. 3 , 1–10 (2017). Pearce, J. M. Building Research Equipment with Free, Open-Source Hardware. Science. 2012 [cited 19 May 2025]. 10.1126/science.1228183 Bezuidenhout, L. M., Leonelli, S., Kelly, A. H. & Rappert, B. Beyond the digital divide: Towards a situated approach to open data. Sci. Public. Policy . 44 , 464–475 (2017). Dias, A. et al. PlomBOX: a low cost bioassay for the sensitive detection of lead in drinking water. Commun. Eng. 4 , 2 (2025). Nadra, A. D. Navigating tensions between public and commercial interests: a case study of open source biosensors for detecting water contaminants in Argentina. Front. Med. (Lausanne) . 11 , 1268950 (2024). Red de Seguridad Alimentaria. ARSÉNICO EN AGUA. Consejo Nacional de Investigaciones Científicas y Técnicas. (2018). Available: https://rsa.conicet.gov.ar/wp-content/uploads/2018/08/Informe-Arsenico-en-agua-RSA.pdf ITBA. Mapa de arsénico en Argentina. [cited 19 May 2025]. Available: https://mapa-de-arsenico.web.app/ Nonna, S., EPIDEMIOLOGÍA DEL HIDROARSENICISMO CRÓNICO REGIONAL ENDÉMICO EN LA & REPÚBLICA ARGENTINA. (2006). https://www.argentina.gob.ar/sites/default/files/2006_epidemiologia_del_hacre_en_argentina.pdf : Asociación Toxicológica Argentina. de Rodriguez, G. M. GP. Cartografía de radios censales de Argentina corregidos, completados y estandarizados de 1991, 2001, 2010 y 2022. Available: https://ri.conicet.gov.ar/handle/11336/149711 Instituto Nacional de Estadísitca y Censo (INDEC). Base de datos de Asentamientos humanos de la República Argentina. [cited 19 May 2025]. Available: http://www.bahra.gob.ar/ Additional Declarations No competing interests reported. Supplementary Files SensArSuppMat.docx Cite Share Download PDF Status: Published Journal Publication published 07 Feb, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 03 Oct, 2025 Reviews received at journal 30 Sep, 2025 Reviews received at journal 29 Sep, 2025 Reviewers agreed at journal 20 Sep, 2025 Reviewers agreed at journal 19 Sep, 2025 Reviewers invited by journal 18 Sep, 2025 Editor invited by journal 16 Sep, 2025 Editor assigned by journal 13 Aug, 2025 Submission checks completed at journal 25 Jul, 2025 First submitted to journal 25 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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14:17:46","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":127773,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7196795/v1/6299c61ff6f7b2e7459a9083.html"},{"id":92516144,"identity":"c1fe567c-ab9f-4d51-95f5-7fd1d98d452e","added_by":"auto","created_at":"2025-09-30 14:09:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":255603,"visible":true,"origin":"","legend":"\u003cp\u003eArsenic survey in Argentina. Population density (violet/yellow gradient) and measured arsenic concentrations (circles) across Argentina. Arsenic data was compiled from the arsenic measurement databases and reports of the Technical Institute of Buenos Aires (ITBA), the Toxicological Argentinian Association (ATA), and the Food Security Network of the National Council of Science and Technology (RSA-CONICET). The figure was generated using the software QGIS, incorporating geographic divisions from the census tract map (Rodriguez, 2022) and the Human Settlements Database of Argentina (BAHRA).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7196795/v1/8c53444e30422622529c3955.png"},{"id":92516143,"identity":"a92746f1-c299-4f8e-877c-8641191168b8","added_by":"auto","created_at":"2025-09-30 14:09:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":82864,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eArsenic Induction Assay.\u003c/strong\u003e\u003cbr\u003e\n(A) Fold increase in color intensity (relative to blank) for 5, 10, and 50 μg/L arsenic solution. (B) Mean color intensity of 16 independent assays captured via the OpenCV-based script. Letters indicate statistical difference (Repeated measure ANOVA, Tukey post´hoc test; p \u0026lt; 0.01).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7196795/v1/5f44cc44d3392b2f939077cd.png"},{"id":92516148,"identity":"086cfd4c-8d04-400f-aa29-f0f6b0ce08ab","added_by":"auto","created_at":"2025-09-30 14:09:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":372280,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePortable arsenic biosensor device SensAr\u003c/strong\u003e\u003cbr\u003e\n(A) Exploded 3D render of the SensAr device, showing its 3D-printed plastic parts (labeled 1-4) and paper layers (labeled A-D). (B) Partially assembled device, showing the paper flow circuit. Red rectangle highlights paper B. The inset highlights paper D, impregnated with X-gal, positioned 0.5 mm below paper C. (C) Smartphone screen capture of the SensAr app automatically detecting the reaction zones. The app darkens the rest of the interface, highlighting each reaction area with green rectangles.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7196795/v1/03608fdc838cf41e9793e1de.png"},{"id":102234207,"identity":"9e5d0de1-a2f2-45d4-a67d-be0b14e6a4c2","added_by":"auto","created_at":"2026-02-09 16:07:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1744462,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7196795/v1/2677db7e-a342-4ceb-9bd6-e2bd81a20d15.pdf"},{"id":92516146,"identity":"dc1cb0d3-5f55-4555-81a0-2e6a842b435f","added_by":"auto","created_at":"2025-09-30 14:09:45","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":118558,"visible":true,"origin":"","legend":"","description":"","filename":"SensArSuppMat.docx","url":"https://assets-eu.researchsquare.com/files/rs-7196795/v1/0662ecfcb403e595692978ef.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Design and Implementation of an Open-Access Arsenic Biosensor","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cb\u003eArsenic Contamination: A Global and Local Challenge\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eAccess to safe drinking water is recognized as a fundamental human right\u003c/span\u003e [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eyet over two billion people worldwide still lack reliable access\u003c/span\u003e [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eOne significant factor contributing to unsafe water is the presence of both natural and anthropogenic contaminants. Among these, arsenic poses one of the most severe risks to public health due to its toxicity and carcinogenic properties\u003c/span\u003e [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eChronic exposure to elevated arsenic levels is associated with cancers (skin, lung, bladder, and kidney, among others), and non-carcinogenic illnesses such as arsenicosis, diabetes mellitus, and various cardiovascular and respiratory diseases\u003c/span\u003e [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eWhile arsenic contamination in groundwater is a global concern\u003c/span\u003e -\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eaffecting regions in Bangladesh, India, China, and the United States\u003c/span\u003e [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]- \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eit is particularly significant in Latin America, with over 14\u0026nbsp;million people consuming water exceeding WHO\u0026rsquo;s 10 \u0026micro;g/L guideline for arsenic\u003c/span\u003e [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eArgentina is among the most affected nations; estimates suggest around 4\u0026nbsp;million individuals, especially in the Chaco-Pampean plain and various other peripheral regions, rely on arsenic-contaminated water sources (\u003c/span\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e)\u003c/span\u003e [\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eVulnerable populations in these areas often have limited awareness of arsenic-related health risks, and are geographically and economically constrained from accessing accurate testing or mitigation solutions\u003c/span\u003e [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eArsenic in water is odorless, tasteless, and colorless, making it imperceptible to human senses and posing a hidden threat.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations of Existing Detection Methods\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eCurrent standard analytical methods for arsenic, such as atomic absorption spectroscopy (AAS) and inductively coupled plasma mass spectrometry (ICP-MS), provide high sensitivity and specificity\u003c/span\u003e [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eHowever, these techniques are costly, require trained personnel, and necessitate specialized laboratory facilities\u003c/span\u003e, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003emaking them impractical for routine monitoring in remote or underprivileged regions. On the other end, affordable field kits (often colorimetric based on chemical reagents) sometimes lack the required sensitivity or reproducibility to confidently detect arsenic at or below the WHO guideline\u003c/span\u003e [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eArgentina\u0026rsquo;s situation illustrates this challenge: many residents obtain water from private wells in rural areas, where infrequent or expensive testing can delay intervention until serious health effects emerge\u003c/span\u003e [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eConsequently, there is a growing need for community-friendly, low-cost, robust, and highly sensitive detection technologies to enable timely decision-making on water potability.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eBiosensors for Arsenic Detection\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eBiosensors engineered to detect arsenic offer a promising solution that balances cost, sensitivity, and ease of operation\u003c/span\u003e [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eThese devices harness biological components\u003c/span\u003e -\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003esuch as bacteria or enzymes\u003c/span\u003e- \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eto produce measurable signals (e.g., color changes) upon exposure to arsenic. By integrating synthetic biology with user-centric industrial design, biosensors can be made portable, simple, and resilient enough for wide-scale deployment in resource-constrained settings\u003c/span\u003e [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eOur previous biological device was based on a red colored protein whose lower limit was hardly 50 \u0026micro;g.L\u0026minus;1 and took several hours to reach a color level detectable\u003c/span\u003e by the naked \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eeye (particularly difficult for people with the\u003c/span\u003e most frequent \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ered color blindness). Thus, we evaluated alternatives to improve the detection limit and response time.\u003c/span\u003e [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e][\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eHere, we describe the conception, design, and validation of an open-access arsenic biosensor, optimized for low-cost manufacturing and decentralized distribution. Our approach leverages genetically modified\u003c/span\u003e \u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eEscherichia coli\u003c/span\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eto yield a colorimetric response in the presence of arsenic concentrations as low as 5 \u0026micro;g/L. We also introduce an ergonomic, 3D-printed housing that simplifies assay operation and ensures user safety. The device\u0026rsquo;s open-access model is central to our mission: all plasmid sequences, device blueprints, and protocols are publicly shared to foster local production, encourage user-driven improvements, and lower barriers to adoption.\u003c/span\u003e\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003ch3\u003eBiosensor Module: Genetically Engineered \u003cem\u003eE. coli\u003c/em\u003e\u003c/h3\u003e\n\u003cp\u003eThe biosensor module consists of \u003cem\u003eE. coli\u003c/em\u003e DH5\u0026alpha; cells carrying the pMV-arsR-ABS1595 plasmid [25], which places the \u003cem\u003elacZ\u003c/em\u003e (\u0026beta;-galactosidase) gene under an arsenic-responsive promoter. This promoter is triggered by the presence of arsenite (As(III)), leading to \u0026beta;-galactosidase production. When the cells come into contact with X-gal substrate, the enzymatic reaction produces a blue color proportional to arsenic concentration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBacterial Growth:\u0026nbsp;\u003c/strong\u003e\u003cem\u003eE. coli\u003c/em\u003e DH5\u0026alpha; was grown in Luria-Bertani (LB) medium with 100 \u0026micro;g/mL ampicillin at 30\u0026deg;C, 215 rpm, overnight. Cells were harvested by centrifugation at 2,800 \u0026times; g for 5 minutes and resuspended in a solution containing 34% (w/v) trehalose and 1.5% (w/v) polyvinylpyrrolidone to OD=2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDehydration on Paper:\u0026nbsp;\u003c/strong\u003eAliquots (12 \u0026micro;L) of the resuspended cells were deposited onto 10\u0026times;7 mm pieces of Whatman 3MM chromatography paper. Paper strips were placed in 2 mL Eppendorf tubes and dehydrated for 2 hours using a SpeedVac vacuum concentrator. These dried, bacteria-impregnated strips (biosensor modules) can be stored at room temperature for up to 30 days without significant loss of responsiveness.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e3D-Printed Device Fabrication\u003c/h3\u003e\n\u003cp\u003eTo ensure ease of use, portability, and user safety, we designed a multi-part device using parametric Computer-Aided Design (CAD) software\u0026nbsp;(Solidworks 3d CAD, Waltham, MA). The device includes (see figure 3):\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample Holder (Part 1)\u003c/strong\u003e: Three wells (blank, sample, and arsenic standard) for fluid loading.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlastic Circuit Holder (Part 4)\u003c/strong\u003e: Houses the paper biosensor module and facilitates capillary flow.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePaper Components (A, B, C, D)\u003c/strong\u003e: A layered arrangement of dehydrated bacteria (B), substrate-containing paper (D), and flow paths (A, C) to direct samples to the bacteria.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll plastic parts were printed with polylactic acid (PLA) filament (1.75 mm diameter) on a standard RepRap FDM 3D printer at 0.15 mm layer height. The final device assembly ensures a sealed environment for the bacterial module, preventing user contact with live microorganisms. Once the assay is complete, the used module can be inactivated with bleach and discarded.\u003c/p\u003e\n\u003ch3\u003eAssay Procedure\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003e1. Activation Buffer\u003c/strong\u003e:\u0026nbsp;An activation solution (LB broth : 20 mg/mL X-gal in DMSF : 0.4 M EDTA at an 8:1:1 ratio) is added to the dehydrated strip (12 \u0026micro;L) to rehydrate the bacteria.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. Sample Loading\u003c/strong\u003e: 1 mL of water sample or standard arsenic solution is introduced into the designated well on the sample holder. The sample flows via capillary action through the biosensor module, contacting the \u003cem\u003eE. coli\u003c/em\u003e cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. Incubation and Detection\u003c/strong\u003e:\u0026nbsp;The device is kept at ambient temperature (16-25\u0026deg;C) for 8-16 hours. If arsenic is present, \u0026beta;-galactosidase expression results in a visible blue color, which intensifies with increasing arsenic concentrations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4. Color analysis script:\u0026nbsp;\u003c/strong\u003eThe images are analyzed with a python-based script written on Python using OpenCV library [26] for image analysis (https://github.com/SensAr-Biosensor). The script calculates an inverse-intensity value, yielding a numerical readout that correlates with the visible blue hue. The color is analyzed on a user-defined area of a jpg image. The RGB channels of every pixel of the selected area are splitted and inverted. The output value is calculated as follows:\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5. Smartphone Data Capture\u003c/strong\u003e (optional): An Android-based app (\u0026ldquo;SensAr\u0026rdquo;) assists with color analysis. Users align the device\u0026rsquo;s reaction zones on their phone camera; the app automatically measures color intensities, geotags the location, and uploads data to a central database for map-based arsenic tracking.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6. Disposal\u003c/strong\u003e: After completing the assay, each used paper module should be immersed in a 10% (v/v) household bleach solution for 30 minutes to ensure inactivation of E. coli cells. Treated strips can then be discarded as regular waste, in accordance with local biosafety regulations. This step complies with standard BSL-1 disposal protocols [1], mitigating any potential release of viable genetically modified microorganisms into the environment.\u003c/p\u003e\n\u003ch3\u003eValidation with Field Samples\u003c/h3\u003e\n\u003cp\u003eA total of 61 water samples from Buenos Aires Province (Argentina) were collected by the National Water Institute (N=32) and Instituto de Hidrolog\u0026iacute;a de Llanuras \u0026ldquo;Dr. Eduardo Jorge Usunoff\u0026rdquo; (IHLLA; N=29) as part of routine arsenic monitoring campaigns [27]. Arsenic concentrations in these samples ranged from below detection limits to 101.7 \u0026mu;g/L (mean \u0026plusmn; SD = 36.1 \u0026plusmn; 24.4 \u0026mu;g/L), as measured by AAS-hydride generation following standard methods (APHA Standard Methods 3113, 3114) [26].[1,16]\u003c/p\u003e\n\u003cp\u003eTo validate the biosensor, each sample was tested qualitatively against a 10 \u0026mu;g/L cutoff. Sensitivity, specificity, and false positive/negative rates were calculated as follows:\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003ch3\u003eStatistical Analysis of Colorimetric Responses\u003c/h3\u003e\n\u003cp\u003eImages of the biosensor strips were taken under consistent lighting conditions using a standard smartphone camera. Color intensities (RGB channels) were quantified using a Python-based script \u0026nbsp;yielding a numerical readout that correlates with the visible blue hue. Repeated-measures ANOVA with Tukey\u0026rsquo;s post hoc test was used to compare mean intensities at different arsenic concentrations (GraphPad Prism 8, GraphPad Software, Inc.).\u003c/p\u003e"},{"header":"Results","content":"\u003ch3\u003eBiosensor Performance and Sensitivity\u003c/h3\u003e\n\u003cp\u003eAmong the different constructs we evaluated including SensAr variants with mRFP, GFP or \u0026beta;-galactosidase as reporter [23], the one with best performance was construction 1595 from Stocker et al [25] generously sent by Drs J.R. Van der Meer and V. Sentchilo, with a robust and sharp response in the range 0 - 1000 \u0026mu;g.L-1 (Fig S1), a linear range between 0- 50 \u0026mu;g.L-1, and a detection limit of 5 \u0026mu;g.L-1 (Fig S2). The optimal response time was between 2-4 hs at 30\u0026deg;C (Fig S3).\u003c/p\u003e\n\u003cp\u003eTo evaluate the response to arsenic, the biosensor modules were re-hydrated in 48 wells plates with 500 \u0026mu;l of arsenic standards prepared from 100 mg/L sodium arsenite stock solution and incubated at room temperature for 8 - 16 h. After the induction period, papers were taken out and the excess of water was absorbed with tissue paper. Color development was evaluated on images taken under even white background and fluorescent tube illumination with a standard cell-phone camera without flash. A single image was taken for all the modules to be analyzed on each bath in order to avoid differences on white balance or illumination intensity.\u003c/p\u003e\n\u003cp\u003eOn every 17 independent assays made on different days, the response produced increased at each concentration step 0 to 50 \u0026mu;g/l As (Fig 2A). Although individual values, including blanks, were not stable between days, the analysis of each assay independently gave a consistent increasing response. The assays were performed at variable room temperature (16-25℃) and time (8-16 h) in order to resemble not controlled user operator conditions and evaluate robustness at the same time. Furthermore, despite blank modules showed background color development (Mean color0 \u0026mu;g/l As = 0.301 \u0026plusmn; 0.017 ), the mean response produced at 5, 10 and 50 \u0026mu;g/l were significantly higher than blank and between them (Mean color 5 \u0026mu;g/l As = 0.379 \u0026plusmn; 0.021; Mean color 10 \u0026mu;g/l As = 0.448 \u0026plusmn; 0.024; Mean color 50 \u0026mu;g/l As = 0.531 \u0026plusmn; 0.026; p \u0026lt; 0.0001; repeated measures ANOVA, Tukey post hoc test ) (Fig 2B.).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThus, colorimetric assays performed under ambient conditions (16-25\u0026deg;C) showed robust and consistent detection of arsenic concentrations as low as 5 \u0026mu;g/L. Despite some day-to-day variation in absolute color values, the biosensor demonstrated consistent increases in blue color intensity from 0 to 50 \u0026mu;g/L (Figure 2).\u003c/p\u003e\n\u003ch3\u003eValidation with Field Samples\u003c/h3\u003e\n\u003cp\u003eIn order to validate the performance of the assay we analyzed samples from the Buenos Aires Province of Argentina obtained during 2020 from annual water analysis campaigns performed by the National Water Institute and IHLLA (see Supplementary Table 1). The arsenic concentrations on the samples were analyzed by those\u0026nbsp;Institutions laboratories using the gold standard atomic absorption spectrometry method. The arsenic level ranged from not detectable to 101.7 \u0026mu;g/L (Mean \u0026plusmn; SD = 36.1 \u0026plusmn; 24.4 \u0026mu;g/L).\u003c/p\u003e\n\u003cp\u003eWhen tested against the 61 field samples with known arsenic concentrations, including 9 negative samples; 52 positive samples (As ≽ 10 \u0026mu;g/L) of which 19 had high arsenic concentration (As ≽ 50 \u0026nbsp;\u0026mu;g/L) [16]. The biosensor accurately classified samples above or below the 10 \u0026mu;g/L threshold, with only one false positive and one false negative (Table 1). Overall sensitivity was 98.1% and specificity was 99.0%, indicating excellent performance relative to standard laboratory methods.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Validation Results Comparing Biosensor Qualitative Output with AAS Measurements\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"330\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eValue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eNumber of Samples\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eTotal Positives (TP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eTotal Negatives (TN)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eFalse Positives (FP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eFalse Negatives (FN)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eFalse Positive Rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.0100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eFalse Negative Rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.0189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e98.1 %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e99.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eArsenic level in field samples ranged from \u0026lt;1 to 101.7 \u0026mu;g/L. Cut-off for positivity: 10 \u0026mu;g/L\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eDevice Assembly and Operation\u003c/h3\u003e\n\u003cp\u003eThe final prototype, called \u0026ldquo;SensAr,\u0026rdquo; was designed and developed in order to be cost effective, accessible and as easy to use, with a graphical and ergonomic interface that does not require a qualified user. It consists of 3D-printed PLA parts holding layered paper components impregnated with dehydrated \u003cem\u003eE. coli\u003c/em\u003e and X-gal (Figure 3). Its parts are joined and sealed after the bacteria are placed, resulting in a safe and tight compartment. The modular design allows easy assembly and replacement of individual components. Operation is straightforward, involving sample loading, passive incubation, and a final color readout. The integrated smartphone application can optionally quantify results and provide a geo-referenced data log (Figure 3C).\u003c/p\u003e\n\u003cp\u003eThe \u0026mu;PAD device consists of paper components (A-D) which make up the biosensor circuit itself, and PLA plastic components (parts 1-5) that form the circuit and sample holders. The sample holder (1) contains three wells where the blank, sample, and arsenic standard are placed. The circuit holder (4) contains the paper components of the device and facilitates liquid flow through the biosensor module. The X-gal carrying paper is secured to the button with paper glue, which is supported on the back of the device. The paper circuit contains the input impregnated with dehydrated LB, which allows the sample to enter via capillarity. The sample then flows through the biosensor module and onto an absorbent pad\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDevice Assembly\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThree pieces of paper, denoted as D, are each loaded with 1.5 \u0026mu;L of X-gal (20mg/ml DMSO). Subsequently, part 3 is inserted onto part 2, and the resulting 2-3 set is attached to part 1 using ethyl cyanoacrylate super glue (UHU, Germany) adhesive. The paper circuit is then assembled on the plastic circuit holder (4) in a specific order. Firstly, parts A and C are placed at the base of the holder. Secondly, the biosensor modules (B) are gently laid on top, ensuring that they are in contact with their corresponding parts A and C. Finally, a PET lid is firmly sealed on top of the circuit using liquid\u0026nbsp;silicone adhesive (UHU, Germany) ensuring the integrity of the device.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDevice operation\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe sample holder (1 in Figure 3) is used to load the sample, blank, and standard solution (1 mL) onto their respective wells using either a Pasteur pipette or a syringe. The assay is initiated by inserting the circuit holder (4+3+2 in figure 3 assembled and sealed) onto the sample holder, which triggers the absorption of the sample through the pads. The flow is sustained for 1.5 hours, after which button 3 is pressed firmly from behind, causing the X-gal paper D to push up the B. This action has two effects: it interrupts the circuit by separating B from A, and it allows the X-gal substrate to come into contact with the bacteria. The results are assessed and documented using the SensAr Android application after 4 hours.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAndroid app usage\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter the user has signed in on the SensAr. The following sample information is entry: data source (well/red/fresh), the temperature of the assay and other observations concerning the sample. The app will ask to acquire the QR code info (date and batch data is obtained from the QR code). Afterwards, three zones will be displayed to frame the image in the three reaction zones. The app detects and delimit the rectangles automatically and the user can record the image by tapping the screen. If the user confirms that the zones are well located, the app will save the image and perform the analysis. The result is reported instantly, and a complete report can be sent by mail or shared through other smartphone apps. Also, the results are sent to a database including the geolocation of the analysis obtained from the phone.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eIn this work we described the design and implementation of a portable, open-access arsenic biosensor useful for low cost and field monitoring of contaminant levels. The biosensor employs genetically modified Escherichia coli and a colorimetric readout with limit of\u003c/span\u003e detection \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eas low as 5 \u0026micro;g/L. Our original\u003c/span\u003e design \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eincluded an incoherent feed forward system to make the signal independent of the evaluation time and only depend on the contaminant concentration\u003c/span\u003e [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eHowever, the complexity of the design, which required the incorporation of several extra genes, made it less robust to operate under uncontrolled conditions. Thus, we decided to exclude the incoherent feed forward and rely on an internal growth and color development reference. In addition we switched from mRFP to b-galactosidase as a reporter which improved the sensitivity, speed and detection for red color\u003c/span\u003e blind \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003epeople. Precise colors quantification is done with an Android application developed\u003c/span\u003e for this \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003epurpose. The reference standard was set to 10 micrograms per liter, in line with WHO limit to drinking water and Argentinian regulation\u003c/span\u003e [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eand can be easily modified to fit changes in local regulation.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eThe arsenic biosensor in water has been designed to be distributed as a kit that allows a determination of the water in evaluation by an unqualified user. Being open access, its production can be decentralized, though it needs some infrastructure that is easily available in most science schools and universities. The ease by which the bacteria can reproduce and the low bacterial concentration required, make the product easy to be massively produced and with a very low cost of the active agent. Furthermore, being based on bacteria, purification of active ingredients is not required. The biomass that is generated when cultivating bacteria is directly the \"system\" of measurement. These characteristics result in a very low production cost and mostly independent of imported supplies.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eValidation studies on 61 samples yielded a sensitivity of 98.1% and specificity of 99.0%. By using paper-based, dehydrated bacterial modules and a 3D-printed housing, this device is cost-effective, easy to use, and amenable to replication in low-resource settings.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eComparative Analysis with Existing Arsenic Detection Technologies\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eA variety of arsenic detection techniques are available, each with distinct strengths and limitations\u003c/span\u003e:\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eLaboratory-Based Methods\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eAtomic Absorption Spectroscopy (AAS)\u003c/span\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eand\u003c/span\u003e \u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eInductively Coupled Plasma Mass Spectrometry (ICP-MS)\u003c/span\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eexhibit detection limits down to parts-per-trillion levels and offer high precision\u003c/span\u003e [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eHowever, they require specialized equipment, well-trained operators, and sample transport to centralized labs, making routine surveillance expensive and logistically challenging for remote communities\u003c/span\u003e [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eChemical Field Test Kits\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eConventional test kits (e.g., based on Gutzeit or mercuric bromide indicator methods) are more affordable and portable than AAS or ICP-MS\u003c/span\u003e [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eYet, they often struggle to reliably detect arsenic near the 10 \u0026micro;g/L threshold, can suffer from interfering substances (e.g., sulfide), and may yield subjective or semi-quantitative colorimetric readings.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eElectrochemical Sensors\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eElectroanalytical methods (e.g., anodic stripping voltammetry) can achieve low detection limits\u003c/span\u003e [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eStill, they typically require instrumentation (potentiostats) and often need careful calibration, limiting accessibility in low-resource settings\u003c/span\u003e [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eBiosensors\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eThe biosensor described here uses genetically engineered\u003c/span\u003e \u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eE. coli\u003c/span\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eto detect arsenic. By encoding β-galactosidase under an arsenite-responsive promoter, color development occurs in response to low \u0026micro;g/L arsenic concentrations. Compared to chemical field kits, our biosensor shows higher sensitivity and specificity around the critical 10 \u0026micro;g/L cutoff, while remaining lower in cost and simpler to operate than electrochemical or advanced laboratory techniques\u003c/span\u003e [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eIn summary, the SensAr biosensor offers a balanced solution for communities requiring on-site, low-cost monitoring at relevant regulatory limits. The open-access nature further enables local manufacturing and adaptation to specific contexts or additional target analytes.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003ePolicy Implications: A Global and Argentinian Perspective\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eGlobal Policies\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eArsenic contamination intersects with global water governance frameworks, including the WHO guidelines of 10 \u0026micro;g/L\u003c/span\u003e [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eand the United Nations Sustainable Development Goal (SDG) 6\u003c/span\u003e [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ewhich calls for universal access to safe drinking water ]. Many low- and middle-income countries strive to meet these standards\u003c/span\u003e [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ebut lack adequate resources for widespread testing infrastructure\u003c/span\u003e [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eAn affordable, user-friendly arsenic biosensor can empower communities to self-monitor their water sources, facilitating data-driven decisions and supporting compliance with regulatory requirements.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eBeyond local surveillance, widespread deployment of biosensors can contribute to real-time water quality mapping at national or regional scales. Policymakers can harness these data to prioritize interventions, allocate resources, and refine regulatory strategies\u003c/span\u003e x. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eAdditionally, the integration of open-access tools aligns with recent calls for increased transparency and data sharing in global health initiatives, enabling broader stakeholder engagement\u003c/span\u003e [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eArgentinian Programs\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eIn Argentina, high arsenic levels in groundwater are well-documented, particularly in the Chaco-Pampean region\u003c/span\u003e [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eExisting programs under the Ministry of Health and local water authorities aim to mitigate exposure through infrastructure projects (e.g., water treatment installations) and public health campaigns\u003c/span\u003e [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eHowever, these efforts often rely on sporadic laboratory testing, which may overlook temporal or spatial fluctuations in arsenic levels.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eAn easily deployable biosensor can strengthen Argentina\u0026rsquo;s arsenic mitigation efforts by providing real-time data in underserved or remote communities. This approach complements national or provincial policies by enabling local stakeholders\u003c/span\u003e (as \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003emunicipalities, community health workers, and even individual well owners\u003c/span\u003e) \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eto detect arsenic surges rapidly, reducing the risk of chronic exposure. As the Argentinian government continues to revise its strategies (e.g., Plan Nacional de Agua or other rural water safety programs), low-cost biosensing can be a valuable component to expand monitoring coverage and inform timely responses.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eOpen-Access Model: Ethical, Practical, and Scientific Benefits\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eEthical Rationale\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eOpen-access dissemination of technology and knowledge is especially critical for addressing public health challenges in underserved regions\u003c/span\u003e [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eBy freely sharing device schematics, plasmid sequences, and protocols, we promote equitable access to essential tools that can save lives. This democratizes innovation, ensuring that patent barriers or licensing fees do not hinder communities from adapting or producing the biosensor locally\u003c/span\u003e [\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003ePractical Advantages\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eCost-Effectiveness\u003c/span\u003e: \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eWith the bacterial modules grown in basic lab conditions and device parts 3D-printed from inexpensive PLA filament, production costs remain low (\u0026lt; $1 per test estimated).\u003c/span\u003e \u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eLocal Adaptation\u003c/span\u003e: \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eOpen designs permit iterative improvements based on local materials, cultural practices, or environmental factors (e.g., water hardness).\u003c/span\u003e \u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eCommunity Engagement\u003c/span\u003e: \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eShared protocols enable universities, NGOs, and grassroots organizations to build capacity, train local users, and maintain a distributed network of arsenic monitoring sites.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eScientific Benefits\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eCollaboration and Transparency\u003c/span\u003e: \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eOpen-access fosters cross-institutional collaborations, spurring new ideas and accelerating iterative design improvements\u003c/span\u003e [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. \u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eReproducibility\u003c/span\u003e: \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ePublicly available genetic constructs and device designs reduce ambiguity and facilitate validation by independent groups, building a broader consensus on performance and reliability.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eIn the case of the SensAr device, we have released our plasmid maps, paper-cutting patterns, and 3D-printing files to ensure any research lab or community-based science initiative can replicate or improve upon our work. This strategy helps overcome traditional limitations in technology transfer to remote settings and aligns with the ethos of open science by lowering entry barriers for others who wish to address arsenic contamination. However, it does not address certain 'contextual' limitations discussed elsewhere\u003c/span\u003e [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eAdditionally, the biosensor\u0026rsquo;s modular design allows for minimal modifications to enable the detection of other substances, such as lead\u003c/span\u003e [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eReplication in Low-Resource Settings\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eDesigning the biosensor with a focus on low-resource environments was integral to this project. Key considerations included\u003c/span\u003e:\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eRoom-Temperature Shipping and Storage\u003c/span\u003e: \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eThe bacterial modules remain viable for ~\u0026thinsp;30 days without refrigeration, simplifying last-mile delivery.\u003c/span\u003e \u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eMinimal Equipment\u003c/span\u003e: \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eAssays only require a pipette or syringe and minimal reagents, eliminating the need for advanced laboratory tools.\u003c/span\u003e \u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eEase of Disposal\u003c/span\u003e: \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ePost-assay disposal is straightforward; the bacterial strips can be inactivated with mild bleach solution or incineration, complying with biosafety guidelines\u003c/span\u003e [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eBy alleviating common logistical hurdles (cost, refrigeration, specialized training), our biosensor can be implemented by local health workers, NGOs, or even directly by residents. Coupled with the open-access model, these features ensure the device is not only affordable but also culturally and infrastructurally adaptable across diverse settings.\u003c/span\u003e\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eWe developed a low-cost, open-access arsenic biosensor through an interdisciplinary effort uniting synthetic biology and industrial design. The resulting tool demonstrates high sensitivity and specificity, meets WHO guidelines (10 \u0026micro;g/L), and can be easily mass-produced and deployed in low-resource environments. By integrating user-friendly design with freely available blueprints and protocols, we aim to empower communities with real-time water quality information, ultimately reducing chronic arsenic exposure and improving public health outcomes.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eLooking ahead, scaling this open-access model can foster collaborative innovation, allowing global communities to customize and expand biosensor technologies. Such grassroots-driven surveillance supports policymaking at the local, national, and international levels, aligning with SDG 6 and other global health initiatives. In Argentina, the biosensor offers a valuable complement to existing arsenic mitigation policies, particularly in rural or marginalized populations. More broadly, our approach highlights how open science and cost-efficient biotechnology can jointly advance the human right to safe drinking water.\u003c/span\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eSince the inception of this project at the end of 2012, many individuals and institutions have contributed. We thank B. Basanta, H. Bonomi, N. Carlotto, M. Gim\u0026eacute;nez, A. Grande, N. Nieto Moreno, F. Barone, F. Dorr, L. Marasco, S. Mildiner, I. Patop, S. Sosa, L. Vattino, and F. Vignale for initial steps in designing the biological components. We also acknowledge Romina Mathieu and Luciana Feo Mourelle for early physical prototypes. Special thanks to I. Patop, S. Sosa, and F. Vignale for pushing the project to receive the \u0026ldquo;Innovative Product\u0026rdquo; Prize at the Argentinian Innovation Contest Innovar 2014.\u003c/p\u003e\n\u003cp\u003eWe are grateful to the Facultad de Ciencias Exactas y Naturales (University of Buenos Aires) and GarageLab for providing the foundational environment. This project was supported by the Ministry of Science and Technology (MINCyT), the Ministry of Education (SPU), ANPCYT (PICT-2015-3834), Universidad de Buenos Aires (PDE 24, 2024), and numerous contributors to our crowdfunding campaign on idea.me. We also thank Dr. J.R. Van der Meer and Dr. Vladimir Sentchilo for providing the ArsR plasmids and INA and IHLLA for sharing samples and data of their water campaigns. Finally, we acknowledge Prof. Ver\u0026oacute;nica Li\u0026ntilde;ares for assistance in translating sections of the article.\u003c/p\u003e\n\u003cp\u003eAuthor Contributions \u0026amp; Data Availability\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eConceptualization: A.D. Nadra, J. Gasulla. Methodology and Investigation: J. Gasulla, E. Alba Posse, A. Teijeiro. Visualization: A. Teijeiro, J. Gasulla, E. Alba Posse. Supervision, Project Administration and Funding Acquisition: A.D. Nadra. Writing Original Draft: A.D. Nadra. Writing Review \u0026amp; Editing\u003cem\u003e: All authors\u003c/em\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e: All relevant data supporting the findings of this study are provided within the manuscript and its Supplementary Information files. Additional raw data (images, colorimetric outputs, Python scripts, and 3D design files) are openly available at GitHub SensAr-Biosensor under license CC-BY 4.0\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eOpen Hardware Documentation\u003c/strong\u003e: STL files, CAD designs, Plasmid sequence, and instructions for printing/assembly are available at GitHub SensAr-Biosensor. Physical plasmid can be requested in Addgene 240494.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eAgencia Nacional de Promoci\u0026oacute;n Cient\u0026iacute;fica y Tecnol\u0026oacute;gica (PICT-2015-3834); Universidad de Buenos Aires (PDE 24, 2024)\u003c/p\u003e\n\u003cp\u003eAdditional Information\u003c/p\u003e\n\u003cp\u003eThe author(s) declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eThird edition. Laboratory biosafety manual. [cited 19 May 2025]. 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Available: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.bahra.gob.ar/\u003c/span\u003e\u003cspan address=\"http://www.bahra.gob.ar/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\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":"Arsenic, biosensor, Groundwater monitoring, whole cell","lastPublishedDoi":"10.21203/rs.3.rs-7196795/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7196795/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eArsenic contamination in groundwater is a critical global issue, affecting over 140\u0026nbsp;million people worldwide and posing severe public health risks, particularly in low-resource and rural communities. Argentina alone has approximately 4\u0026nbsp;million people exposed to arsenic. The measurement of arsenic in private wells is often limited by high costs, specialized personnel requirements, and geographical distances to analytical laboratories. In this paper, we describe the design and implementation of a portable, open-access arsenic biosensor that combines synthetic biology and industrial design. The biosensor employs genetically modified\u003c/span\u003e \u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eEscherichia coli\u003c/span\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eand a colorimetric readout to detect arsenic concentrations as low as 5 \u0026micro;g/L. Validation studies on 61 samples yielded a sensitivity of 98.1% and specificity of 99.0%. By using paper-based, dehydrated bacterial modules and a 3D-printed housing, this device is cost-effective, easy to use, and amenable to replication in low-resource settings. In addition, the open-access approach ensures that critical\u003c/span\u003e knowledge such as plasmid \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003esequences, device schematics, and protocols can be freely shared and locally adapted. Beyond the technical advantages, this biosensor can potentially influence global policies and Argentinian programs on water quality monitoring, empowering communities to take charge of arsenic surveillance and safeguard public health.\u003c/span\u003e\u003c/p\u003e","manuscriptTitle":"Design and Implementation of an Open-Access Arsenic Biosensor","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-30 14:09:41","doi":"10.21203/rs.3.rs-7196795/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-03T06:51:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-30T06:43:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-29T20:53:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"233929091568957502662738660523791811053","date":"2025-09-20T17:39:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"61489864757017276788455223499469906918","date":"2025-09-19T08:07:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-18T16:54:22+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-16T09:45:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-13T04:19:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-25T18:21:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-07-25T14:12:40+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":"a24b6e10-a3ef-4077-966f-b4cd21197363","owner":[],"postedDate":"September 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":55534831,"name":"Biological sciences/Biological techniques"},{"id":55534832,"name":"Biological sciences/Biotechnology"},{"id":55534833,"name":"Earth and environmental sciences/Environmental sciences"},{"id":55534834,"name":"Biological sciences/Microbiology"}],"tags":[],"updatedAt":"2026-02-09T16:05:15+00:00","versionOfRecord":{"articleIdentity":"rs-7196795","link":"https://doi.org/10.1038/s41598-026-38693-3","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-02-07 15:58:32","publishedOnDateReadable":"February 7th, 2026"},"versionCreatedAt":"2025-09-30 14:09:41","video":"","vorDoi":"10.1038/s41598-026-38693-3","vorDoiUrl":"https://doi.org/10.1038/s41598-026-38693-3","workflowStages":[]},"version":"v1","identity":"rs-7196795","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7196795","identity":"rs-7196795","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}