Aneesh Kshirsagar

While most children with COVID-19 experience mild symptoms or remain asymptomatic, some may develop severe complications. Early identification of children at risk for severe outcomes is essential to ensuring timely and effective intervention. Recent studies have identified alterations in salivary microRNA (miRNA) expression levels as promising biomarkers for predicting severe complications in children. However, there remains a need for a rapid, noninvasive, and quantitative method to detect miRNA expression level changes, as their upregulation or downregulation serves as a hallmark of various diseases, providing an alternative to sequencing-based methods. Here, we developed a highly specific and sensitive ligation-coupled recombinase polymerase amplification (RPA) assay for quantitatively detecting multiplex severe and nonsevere miRNAs on a portable platform. The assay begins with an miRNA-templated annealing and ligation reaction of miR-1273, miR-296, and miR-29, followed by an RPA reaction. We quantified 100 pM to 1 fM, resolving 1 fM, with 100% specificity. Next, we validated portable extraction against benchtop extraction, achieving R² > 0.85 and r > 0.92 in clinical samples. Finally, testing 154 clinical samples revealed severe miRNA downregulation compared to nonsevere cases. The assay achieved high diagnostic accuracy with an area under the curve (AUC) of 0.98. This platform would empower clinicians to make informed decisions, optimize resource allocation, and improve outcomes, particularly in point-of-care (POC) settings.

The availability of effective antiretroviral therapy has made HIV manageable, provided patients have consistent access to routine viral load (VL) testing. Nonetheless, access to frequent VL testing remains limited. There is a need for accessible, user-friendly testing systems that allow people living with HIV (PLHIV) to monitor their VL more frequently and empower self-management. Here, we developed ViraLite, a sample-to-answer, compact, accessible, and battery-powered system for HIV viral load monitoring. The system is built upon a probe-based RT-LAMP assay that allows for multiplexed detection and quantification. An internal quality control targeting the RNase P was incorporated to enhance the reliability of the results. A software-reconfigurable real-time sensing system empowered by machine learning and a smartphone-guided protocol was developed in tandem to analyze the multiplexed assay. We analyzed 45 clinically archived samples using ViraLite and benchmarked our results against qRT-PCR, which showed 21 positive and 23 negative samples. Using our process control, ViraLite first identified 17 inconclusive samples that would otherwise be classified as negative. Then, ViraLite classified 14 out of 15 HIV-positive samples (93.3%) and 13 out of 13 HIV-negative samples (100%). The incorporation of RNase P as a process control increased the sensitivity of ViraLite from 66.66% to 93.33%, while maintaining a high specificity (100%). To assess the acceptance of ViraLite among PLHIV, we recruited 480 participants from online and three clinical sites to complete a survey. Over 86% of participants indicated ViraLite had benefits in convenience and privacy, on the other hand 61% of participants indicated concerns with test accuracy. The integration of compact hardware, a reliable assay, and smartphone guidance provides an accurate, easy to use system for PLHIV to self-manage their viral load and update their prescriptions frequently.

Most children with SARS-CoV-2 have mild or asymptomatic symptoms, but some develop severe complications. Early identification of high-risk cases is crucial for timely intervention. Alterations in salivary microRNA (miRNA) levels serve as biomarkers for severity prediction. However, a rapid, non-invasive method is needed to quantify miRNA level changes as an alternative to sequencing. Here, we developed a highly specific and sensitive ligation-recombinase polymerase amplification (RPA) assay for quantifying severe and non-severe miRNAs on a portable platform. The assay begins with a miRNA-templated annealing and ligation-RPA reaction of miR-1273, miR-296, and miR-29. We quantified 100 pM to 1 fM, resolving 1 fM, with 100% specificity. Next, we validated portable extraction against benchtop extraction, achieving R-square > 0.85 and r > 0.92 in clinical samples. Finally, testing 154 clinical samples revealed severe miRNA downregulation compared to non-severe cases. The assay achieved high diagnostic accuracy with an AUC of 0.98. This platform enables informed clinical decisions and optimizes resources, especially in resource-limited settings.

Loop-mediated isothermal amplification (LAMP) is a promising method for point-of-care nucleic acid testing due to its simplicity, rapidity, and high sensitivity. Coupling LAMP with solid-state nanopores enables label-free, single-molecule sensing, enhancing diagnostic accuracy. However, conventional LAMP-coupled nanopore protocols require high-salt buffers (>1 M) to improve signal strength and translocation frequency, complicating workflows and increasing contamination risks. In native LAMP buffers (50 mM KCl), electroosmotic flow (EOF) hinders amplicon transport in sub-10 nm pores, while large amplicons increase the risk of clogging. These challenges limit event rates, data throughput, and device reliability. To address these limitations, we developed a glass nanopore device optimized for direct sensing of amplicons in native buffers, featuring integrated declogging capabilities. Our results revealed that 200 nm pores provided the best balance between minimizing EOF interference and maintaining strong signal strength, achieving the highest event rates. Smaller pores (1 μm) showed weakened signal strength. We discovered that clogging in low-salt conditions differs from high-salt environments, with physical vibration effectively resolving clogging in low-salt settings. This led to the integration of an automated vibration motor, extending nanopore lifespan and ensuring continuous data acquisition. Our clog-free, native-buffer sensing platform demonstrated a sensitivity of 0.12 parasite/μL using Plasmodium vivax (P. vivax) as a model organism, exceeding the threshold for detecting asymptomatic infections. These advancements highlight the potential of our nanopore device for rapid, reliable, and user-friendly diagnostics for point-of-care testing.

Respiratory viral infections pose a significant global public health challenge, partly due to the difficulty in rapidly and accurately distinguishing between viruses with similar symptoms at the point of care, hindering timely and appropriate treatment and limiting effective infection control and prevention efforts. Here, we developed a multiplexed, non- invasive saliva-based, reverse transcription loop-mediated isothermal amplification (RT- LAMP) test that enables the simultaneous detection of three of the most common respiratory infections, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Influenza (Flu), and respiratory syncytial virus (RSV), in a single reaction via specific probes and monitored in real-time by a machine-learning-enabled compact analyzer. Our results demonstrate that the multiplexed assay can effectively detect three target RNAs with high accuracy. Further, testing with spiked saliva samples showed strong agreement with reverse transcription polymerase chain reaction (RT-PCR) assay, with area under the curve (AUC) values of 0.82, 0.93, and 0.96 for RSV, Influenza, and SARS-CoV-2, respectively. By enabling the rapid detection of respiratory infections from easily collected saliva samples at the point of care, the device presented here offers a practical and efficient tool for improving outcomes and helping prevent the spread of contagious diseases. Significance: This research presents an innovative approach to respiratory infection diagnostics by combining a one-pot isothermal molecular test with machine learning-based analysis to simultaneously detect SARS-CoV-2, Influenza, and RSV in saliva samples. The battery- powered portable analyzer features novel machine-learning-assisted fluorescence detection for multiplexed reporter quantification, eliminating the need for traditional filter- based optical components and enabling adaptation to new targets without hardware changes. The test demonstrates high accuracy in detecting single and co-infections in spiked saliva samples, providing a rapid, cost-effective point-of-need solution. This tool can expand testing access, improve patient outcomes, and support more effective disease control, particularly in resource-limited or decentralized healthcare settings.

There is a significant demand for multiplexed fluorescence sensing and detection across a range of applications. Yet, the development of portable and compact multiplexable systems remains a substantial challenge. This difficulty largely stems from the inherent need for spectrum separation, which typically requires sophisticated and expensive optical components. Here, we demonstrate a compact, lens-free, and cost-effective fluorescence sensing setup that incorporates machine learning for scalable multiplexed fluorescence detection. This method utilizes low-cost optical components and a pretrained machine learning (ML) model to enable multiplexed fluorescence sensing without optical adjustments. Its multiplexing capability can be easily scaled up through updates to the machine learning model without altering the hardware. We demonstrate its real-world application in a probe-based multiplexed Loop-Mediated Isothermal Amplification (LAMP) assay designed to simultaneously detect three common respiratory viruses within a single reaction. The effectiveness of this approach highlights the system's potential for point-of-care applications that require cost-effective and scalable solutions. The machine learning-enabled multiplexed fluorescence sensing demonstrated in this work would pave the way for widespread adoption in diverse settings, from clinical laboratories to field diagnostics.

Loop-mediated isothermal amplification (LAMP) is a rapid, sensitive, and cost-effective method for developing point-of-care nucleic acid testing due to its isothermal nature. Yet, LAMP can suffer from the issue of false positives, which can compromise the specificity of the results. LAMP false positives typically arise due to contamination, nonspecific amplification, and nonspecific signal reporting (intercalating dyes, colorimetric, turbidity, etc.). While dye-labeled primers or probes have been introduced for multiplexed detection and enhanced specificity in LAMP assays, they carry the risk of reaction inhibition. This inhibition can result from the labeled primers with fluorophores or quenchers and probes that do not fully dissociate during reaction. This work demonstrated a nanopore-based system for probe-free LAMP readouts by employing amplicon sizing and counting, analogous to an electronic version of gel electrophoresis. We first developed a model to explore LAMP kinetics and verified distinct patterns between true and false positives via gel electrophoresis. Subsequently, we implemented nanopore sized counting and calibrated the event charge deficit (ECD) values and frequencies to ensure a fair analysis of amplicon profiles. This sized counting method, integrated with machine learning, achieved 91.67% accuracy for false positive discrimination, enhancing LAMP's reliability for nucleic acid detection.

Human immunodeficiency virus (HIV) is a significant problem to consider as it can lead to acquired immune deficiency syndrome (AIDS). Fortunately, AIDS is manageable through antiretroviral therapy (ART). However, frequent viral load monitoring is needed to monitor the effectiveness of the therapy. The current reverse transcription-polymerase chain reaction (RT-PCR) viral load monitoring is highly effective, but is challenged by being resource-intensive and inaccessible, and its turnaround time does not meet demand. An unmet need exists for an affordable, rapid, and user-friendly point-of-care device that could revolutionize and ensure therapeutic effectiveness, particularly in resource-limited settings. In this work, we explored a point-of-care HIV viral load device to address this need. This device can perform streamlined plasma separation, viral RNA extraction, and real-time reverse transcription loop-mediated isothermal amplification (RT-LAMP) semiquantitative testing in an ultracompact device. We developed an absorption-based membrane plasma separation method suitable for finger-prick blood samples, achieving an efficiency of 80%. We also designed a syringe-based RNA extraction method for on-site plasma processing with a viral recovery efficiency of 86%. We created a portable device with a smartphone interface for real-time semiquantitative RT-LAMP, which is useful for monitoring viral load. The device uses lyophilized reagents, processed with our lyophilization method, which remain stable for 16 weeks. The device can accurately categorize viral load into low, medium, and high categories with 95% accuracy. We believe this point-of-care HIV self-test device, offering convenience and long-term storage, could aid patients in home-based ART treatment monitoring.

World Health Organization's aim to eliminate malaria from developing/resource-limited economies requires easy access to low-cost, highly sensitive, and specific screening. We present a handheld nucleic acid testing device with on-chip automated sample preparation to detect malaria (Plasmodium falciparum) infection from a whole blood sample as a feasibility study. We used a simple two-reagent-based purification-free protocol to prepare the whole blood sample on a piezo pump pressure-driven microfluidic cartridge. The cartridge includes a unique mixing chamber for sample preparation and metering structures to dispense a predetermined volume of the sample lysate mixture into four chambers containing a reaction mix. The parasite genomic DNA concentration can be estimated by monitoring the fluorescence generated from the loop-mediated isothermal amplification reaction in real time. We achieved a sensitivity of ∼0.42 parasite/μL of whole blood, sufficient for detecting asymptomatic malaria parasite carriers.

Regular, accurate, rapid, and inexpensive self-testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is urgently needed to quell pandemic propagation. The existing at-home nucleic acid testing (NAT) test has high sensitivity and specificity, but it requires users to mail the sample to the central lab, which often takes 3–5 days to obtain the results. On the other hand, rapid antigen tests for the SARS-CoV-2 antigen provide a fast sample to answer the test (15 min). However, the sensitivity of antigen tests is 30 to 40% lower than nucleic acid testing, which could miss a significant portion of infected patients. Here, we developed a fully integrated SARS-CoV-2 reverse transcription loop-mediated isothermal amplification (RT-LAMP) device using a self-collected saliva sample. This platform can automatically handle the complexity and can perform the functions, including (1) virus particles’ thermal lysis preparation, (2) sample dispensing, (3) target sequence RT-LAMP amplification, (4) real-time detection, and (5) result report and communication. With a turnaround time of less than 45 min, our device achieved the limit of detection (LoD) of 5 copies/μL of the saliva sample, which is comparable with the LoD (6 copies/μL) using FDA-approved quantitative real-time polymerase chain reaction (qRT-PCR) assays with the same heat-lysis saliva sample preparation method. With clinical samples, our platform showed a good agreement with the results from the gold-standard RT-PCR method. These results show that our platform can perform self-administrated SARS-CoV-2 nucleic acid testing by laypersons with noninvasive saliva samples. We believe that our self-testing platform will have an ongoing benefit for COVID-19 control and fighting future pandemics.