ACS Sensors

Nucleic acids in biofluids are emerging biomarkers for molecular diagnosis of diseases, whose clinical use has been hindered by the lack of sensitive and convenient detection assays. Herein, we report a sensitive nucleic acid detection method based on allosteric DNAzyme biosensors named SPOT (sensitive loop-initiated DNAzyme biosensor for nucleic acid detection) by rationally designing a programmable DNAzyme of endonuclease capability. SPOT can be activated once a nucleic acid target of specific sequence binds to its allosteric module to induce conformational reconfiguration of DNAzyme enabling continuous cleavage of molecular reporters. SPOT provides a highly robust platform for sensitive (LOD: femtomolar for miRNAs, attomolar for SARS-CoV-2 RNA), specific (single-nucleotide discrimination), and convenient (one-step, one-pot, preamplification-free) detection of low-abundant nucleic acid biomarkers. For clinical validation, we demonstrated that SPOT is capable of detecting serum miRNAs (e.g., miR-155, miR-21) from patients for the precise diagnosis of breast cancer, gastric cancer, and prostate cancer. Furthermore, SPOT exhibits potent detection capability over SARS-CoV-2 RNA from clinical swabs with high sensitivity and specificity. Lastly, SPOT is compatible with point-of-care testing modalities such as lateral flow assay to enable convenient visualization. Hence, we envision that SPOT may serve as a robust platform for sensitive detection of a variety of nucleic acid targets towards clinical applications in molecular diagnosis.

Real-time biosensors that can continuously measure circulating biomolecules in vivo would provide valuable insights into a patients health status and their response to therapeutics even when there is considerable variability in pharmacokinetics and pharmacodynamics across patient populations. Unfortunately, current real-time biosensors are limited to a handful of analytes (e.g. glucose and blood oxygen) and are limited in sensitivity (high nanomolar). In this work, we describe a general approach for continuously and simultaneously measuring multiple analytes with picomolar sensitivity and sub-second temporal resolution. As exemplars, we report the simultaneous detection of glucose and insulin at picomolar concentrations in live diabetic rats. Using our system, we demonstrate the capacity to resolve inter-individual differences in the pharmacokinetic responses to insulin and discriminate profiles from different insulin formulations at a high temporal resolution. Critically, our approach is general and could be readily modified to continuously and simultaneously measure other circulating analytes in vivo by swapping the affinity reagents, thus making it a versatile tool for biomedical research.

Over the last 6 years, five-year survival rate for pancreatic cancer patients has increased from 6 to 10% after the initial diagnosis, which makes it one of the deadliest cancer types. This disease is known as the "silent killer" because early detection is challenging due to the location of the pancreas in the body and the nonspecific clinical symptoms. The Bossmann group has developed ultrasensitive nanobiosensors for protease/arginase detection comprised of Fe/Fe3O4 nanoparticles, cyanine 5.5, and designer peptide sequences linked to TCPP. Initial data obtained from both gene expression analysis and protease/arginase activity detection in serum indicated the feasibility of early pancreatic cancer detection. Several matrix metalloproteinases (MMPs, -1, -3, and -9), cathepsins (CTS) B and E, neutrophil elastase, and urokinase plaminogen activator (uPA) have been identified as candidates for proximal biomarkers. In this study, we have confirmed our initial results from 2018 performing serum sample analysis assays using a larger group sample size (n=159), which included localized (n=33) and metastatic pancreatic cancer (n=50), pancreatitis (n=26), and an age-matched healthy control group (n=50). The data obtained from the eight nanobiosensors capable of ultrasensitive protease and arginase activity measurements were analyzed by means of an optimized information fusion-based hierarchical decision structure. This permits the modeling of early-stage detection of pancreatic cancer as a multi-class classification problem. The most striking result is that this methodology permits the detection of localized pancreatic cancers from serum analyses with 96% accuracy.

Cell fate decisions are regulated by intricate signaling networks, with Extracellular signal-Regulated Kinase (ERK) being a central regulator. However, ERK is rarely the only signaling pathway involved, creating a need to study multiple signaling pathways simultaneously at the single-cell level. Many existing fluorescent biosensors for ERK and other pathways have significant spectral overlap, limiting their ability to be multiplexed. To address this limitation, we developed two novel red-FRET ERK biosensors, REKAR67 and REKAR76, which operate in the 670-720 nm range using miRFP670nano3 and miRFP720. REKAR67 and REKAR76 differ in fluorophore position, which impacts biosensor characteristics; REKAR67 displayed a higher dynamic range but greater signal variance than REKAR76. Mixed populations of REKAR67 or REKAR76 displayed similar Signal-to-Noise ratio (SNR), but in clonal cell populations, REKAR76 had a significantly higher SNR. Overall, our red-FRET ERK biosensors were highly consistent with existing ERK FRET biosensors and in reporting ERK activity and are spectrally compatible with CFP/YFP FRET and cpGFP -based biosensors. Both REKAR biosensors expand the available methods for measuring single-cell ERK activity.

The relationship between hydrogen peroxide (H2O2) and nitric oxide (NO) in the vasculature is multifaceted and remains controversial because the dynamic detection of these reactive molecules is challenging. Genetically encoded biosensors (GEBs) allow visualizing real-time dynamics in living cells and permit multiparametric detection of several analytes. Although robust, GEBs utility depends on several parameters that need fine-tuning for proper imaging and correct data analysis: i.e., camera binning, temperature, and the resolution power of the imaging instruments are some critical parameters that require optimization. We have generated a new double-stable transgenic endothelial cell line stably expressing the biosensors HyPer7 and O-geNOp and systematically tested different imaging modes and their impact on the performance of each biosensor. Ambient temperature and the type of imaging mode did not influence the results, while camera resolution settings significantly affected readouts of HyPer probes but not O-geNOp. Changing a single parameter in a co-imaging mode significantly altered the biosensors dynamic measurements, potentially causing misinterpretation. This study provides a general guide and the pitfalls of employing GEBs in a multispectral imaging mode.

Trans-translation is a crucial bacterial process and a target for new antibiotics. We developed two Pseudomonas aeruginosa biosensor strains that detect trans-translation inhibitors by exploiting the bacteriums natural red fluorescence, linked to protoporphyrin IX accumulation. The first biosensor monitors tmRNA-SmpB-mediated tagging, while the second serves as control for biosensor 1 by keeping track of ClpP1-related proteolysis and porphyrin biosynthesis. Validation through gene deletions and complementation confirmed their specificity. These biosensors were effective in screening antibiotics and designed inhibitors, demonstrating their potential for high-throughput identification of trans-translation inhibitors in drug-resistant P. aeruginosa.

Disease prevention, diagnosis, and treatment monitoring often require ultrasensitive (sub-)femtomolar biomarker detection and quantification. While standard ELISA assays yield picomolar sensitivity, existing ultrasensitive approaches reach fM, aM or even zM sensitivity. This, however, is obtained at the expense of increased complexity and cost which hampers their biomedical applications. We propose a novel approach, NLISA, combining ultrasensitive, fM/sub-fM, quantitative detection with simplicity and ease of use based on 38-nm YVO4:Eu (20%) crystalline nanoparticles used as detection probes. These particles possess an extremely strong absorption in the UV leading to bright Eu3+-ion emission. We developed a transportable, multi-well plate reader providing LED excitation and detection with a photomultiplier enabling detection down to 16,000 nanoparticle probes/well. We obtained sensitivity gain factors with respect to ELISA ranging from 65 to 35,000 for insulin, IFN-{gamma}, and HIV-GAG-p24 while maintaining the same antibodies. We demonstrated femtomolar LOD and a dynamic range of 4-5 orders of magnitude and NLISA efficiency for HIV-positive patient diagnosis. This approach for straightforward, ultrasensitive polypeptide/protein detection is easily generalizable paving the way for a new generation of diagnostic tests.

Efficient pathogen detection is essential for the successful treatment and prevention of infectious disease; however, current methods are often too time intensive to be clinically relevant in cases requiring immediate intervention. We have developed a Surface Programmable Activation Receptor (SPAR) diagnostic platform comprised of universal biosensor cells engineered for use in combination with custom or commercial antibodies to achieve rapid and sensitive pathogen detection. SPAR cells are stably transfected Jurkat T cells designed to constitutively express a modified T cell mouse Fc{gamma}RI receptor on the cell surface and a high level of the luminescent reporter protein aequorin in the cytoplasm. The modified mFc{gamma}RI-CD3{zeta} receptor protein binds with high affinity to the Fc region of any full-length mouse IgG2a and some IgG2 antibodies: this allows customized target detection via the selection of specific antibodies. T-cell receptor aggregation in response to target antigen binding results in signal transduction which, when amplified via the endogenous T cell signal cascade, triggers the rapid intracellular release of calcium. Increased Ca2+ concentrations activate the expressed reporter protein aequorin resulting in the immediate emission of detectable light. Testing demonstrates the accurate and specific detection of numerous targets including P. aeruginosa, E. coli O111, and E. coli O157. We report that the SPAR biosensor cell platform is a reliable pathogen detection method that enables the rapid identification of bacterial causative agents using standard laboratory instrumentation. The technology lends itself to the development of efficient point-of-care testing and may aid in the implementation of effective and pathogen-specific clinical therapies.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers due in part to the cancer being diagnosed is at a late stage when effective treatment options are limited. Early detection of PDAC via liquid biopsy would revolutionize survival from the disease. To address the lack of effective non-invasive detection assays for PDAC, we developed a protease activity-based assay using a magnetic nanosensor (PAC*MANN). The PAC*MANN assay leverages protease activity in blood to amplify the signal of the target-probe based sensor. An initial screening revealed that the PAC*MANN assay could reliably differentiate patients with PDAC from healthy subjects and patients at high risk of PDAC. Finally, in two cohorts: training (n=145) and blinded validation (n=72), we demonstrated that the PAC*MANN assay had high specificity (86%) and sensitivity (78%) for detection of PDAC compared to healthy subjects. This performance was enhanced when combined with the current standard of care assay, CA19-9 (100% specificity, 84% sensitivity). Our results demonstrate a novel assay that is rapid, high-throughput, and requires low specimen volume, which may not only improve cancer detection but could be useful for monitoring of at-risk patients and could be deployed in low resource settings. One sentence summaryA high-throughput, non-invasive, rapid protease-activated nanosensor identifies pancreatic cancer from a small volume of blood

Glutamate, the principal excitatory neurotransmitter in the brain, is crucial for cognition and memory, and its dysregulation is implicated in several neurological disorders, including Alzheimers Disease and epilepsy. However, precise and high-throughput quantification of glutamate in physiological samples remains challenging. Here, we report an ultrasensitive and highly specific glutamate aptamer-based biosensor, or aptasensor, developed through in silico design and microfabrication, followed by in vitro and clinical validation. The biosensor consists of arrays of graphene field-effect transistors functionalized with a novel DNA aptamer, NG-Apt-Glu, designed and characterized computationally and biochemically, revealing two putative glutamate binding sites. The aptasensor detects glutamate in artificial cerebrospinal fluid with a 1 aM detection limit, a wide linear range (1 aM-10 pM), and 24 mV/decade sensitivity, showing strong selectivity against GABA, glutamine, dopamine, and serotonin. To evaluate clinical applicability, glutamate levels were measured in cerebrospinal fluid from patients with Alzheimers Disease, showing a significant increase relative to controls and correlating with neurofilament light chain concentrations, a biomarker of neuronal death. These findings underscore glutamates involvement in Alzheimers pathophysiology and its potential as a biomarker for neurodegeneration. This ultrasensitive graphene-based aptasensor enables point-of-care monitoring, paving the way for early diagnosis and the development of novel therapeutic strategies.

Following an ever-increased focus on personalized medicine, there is a continuing need to develop preclinical molecular imaging modalities to guide the development and optimization of targeted therapies. To date, non-invasive quantitative imaging modalities that can comprehensively assess simultaneous cellular drug delivery efficacy and therapeutic response are lacking. In this regard, Near-Infrared (NIR) Macroscopic Fluorescence Lifetime Forster Resonance Energy Transfer (MFLI-FRET) imaging offers a unique method to robustly quantify receptor-ligand engagement in vivo and subsequent intracellular internalization, which is critical to assess the delivery efficacy of targeted therapeutics. However, implementation of multiplexing optical imaging with FRET in vivo is challenging to achieve due to spectral crowding and cross-contamination. Herein, we report on a strategy that relies on a dark quencher that enables simultaneous assessment of receptor-ligand engagement and tumor metabolism in intact live mice. First, we establish that IRDye QC-1 (QC-1) is an effective NIR dark acceptor for the FRET-induced quenching of donor Alexa Fluor 700 (AF700) using in vitro NIR FLI microscopy and in vivo wide-field MFLI imaging. Second, we report on simultaneous in vivo imaging of the metabolic probe IRDye 800CW 2-deoxyglucose (2-DG) and MFLI-FRET imaging of NIR-labeled transferrin FRET pair (Tf-AF700/Tf-QC-1) uptake in tumors. Such multiplexed imaging revealed an inverse relationship between 2-DG uptake and Tf intracellular delivery, suggesting that 2-DG signal may predict the efficacy of intracellular targeted delivery. Overall, our methodology enables for the first time simultaneous non-invasive monitoring of intracellular drug delivery and metabolic response in preclinical studies.

Oral cancer, the sixth most common worldwide, is often diagnosed at an advanced stage, impacting patient survival and mortality. Liquid biopsy offers the potential for cancer diagnosis, enabling dynamic tumor monitoring and disease surveillance. Here we validates a novel diagnostic approach using optical images of dried micro-droplets (volume of one {micro}l) of saliva samples on glass and platinum substrates, employing Logistic Regression and Support Vector Machine (SVM) models. For each model, accuracy, sensitivity, specificity, and area under the ROC curve were calculated. Our findings indicated that optical density and surface area (SA) obtained from optical images of microdroplets are suitable paramters of discriminating oral cavity squamous cell carcinoma and health individuals. SVM models demonstrate impressive accuracy of 88.10% on glass and 95.00% on Pt substrates, ensuring robust and accurate detection of oral cancer based on these salient features.

Cyclic adenosine 3,5-monophosphate is an important second messenger molecule that regulates many downstream signaling pathways in cells. Detection of cAMP levels relies on screenings of cell lysates or the use of genetically encoded biosensors for detection in living cells. Genetically encoded biosensors are, however, primarily used for bioimaging and rarely in high-throughput screenings of potential drug candidates. Here, we describe a quantitative fluorescence-based imaging method based on measurements of single living cells. We used a genetically encoded Epac149 biosensor to investigate cAMP production in living cells following ligand stimulation. The study revealed a dependence of the measured cAMP levels on the expression level of the biosensor in transiently transfected cells. While the biosensor maintained linearity of the signal at high expression levels, the linearity of the biosensor was lost at lower expression levels due to a deficit of the biosensor compared to the maximum possible production of cAMP in the cells. This problem was circumvented by establishment of a stable cell line with constitutive expression of the biosensor. We established dose response curves by stimulation with the {beta}1-adrenergic receptor partial agonist denopamine and observed up to 1.48-fold difference in the cellular response as well as up to 4.27-fold difference in LogEC50 values between cells with insufficient and sufficient biosensor expression. Careful characterization and control of the biosensor expression is therefore important in order to conduct quantitative analysis of the cAMP production and it allows the use of genetically encoded biosensor to be applied in high-throughput screenings.

Pancreatic beta cells face exceptional protein folding demands from high insulin production requirements, placing extraordinary stress on the ER and contributing to dysfunction in diabetes pathogenesis. Monitoring ER stress dynamics in living cells remains challenging due to the destructive nature of traditional biochemical methods and the limitations of existing fluorescent sensors. Here, we present Apollo-IRE1, a genetically encoded sensor that reports on stress-induced IRE1 oligomerization and associated change in homoFRET via changes in fluorescence anisotropy. Apollo-IRE1 provides a ratiometric, intensity-independent readout, resulting in low day-to-day variability and a minimal spectral bandwidth, enabling multiplexed imaging alongside other cellular parameters. Photobleaching and enhancement curve analysis show that Apollo-IRE1 exists in apparent monomeric, dimeric, and oligomeric states corresponding to baseline, moderate, and terminal ER stress conditions. The sensor also responds rapidly to chemical and physiological ER stressors in both immortalized beta-cell lines and primary mouse islet cells. These data establish Apollo-IRE1 as a practical tool for investigating ER stress dynamics in beta cells and other contexts where longitudinal single-cell measurements are essential.

Next-generation sequencing (NGS) technologies have transformed biomarker discovery, enabling the detection of disease-associated markers at the earliest stages of illness. In this study, we introduce a blood-based, non-invasive test for multi-cancer detection using cell-free DNA (cfDNA) methylation sequencing. The test employs a novel methylation scoring system derived from sequencing data and integrates machine learning to analyze a retrospective cohort of newly diagnosed cancer cases and controls recruited from multiple centers across India. To enhance robustness, the study includes a substantial proportion of controls with habitual tobacco and alcohol use, ensuring the tests resilience against confounding factors. The tests accuracy was further validated through synthetic data augmentation, demonstrating reliability under conditions of random signal perturbation. At an approximate specificity of 97%, the assay achieves sensitivities of 79.3% for Stage I, 78.4% for Stage II, 78.4% for Stage III, and 86.8% for Stage IV cancers in an independent validation cohort. Additionally, the test demonstrates Top 2 Tissue of Origin (TOO) accuracies of 78.3% for Stage I, 79.3% for Stage II, 82.8% for Stage III, and 69.7% for Stage IV cancers. This blood-based test holds considerable promise for early cancer detection, offering a precise test for cancer screening.

The ability to track the levels of specific molecules, such as drugs, metabolites, and biomarkers, in the living body, in real time and for long durations would improve our understanding of health and our ability to diagnose, treat and monitor disease. To this end, we are developing electrochemical aptamer-based (E-AB) biosensors, a general platform supporting high-frequency, real-time molecular measurements in the living body. Here we report that the addition of an agarose hydrogel protective layer to E-AB sensors significantly improves their baseline stability when deployed in the complex, highly time-varying environments found in vivo. The improved stability is sufficient that these hydrogel-protected sensors achieved good baseline stability when deployed in situ in the veins, muscles, bladder, or tumors of living rats without the use of the drift correction approaches traditionally required in such placements. Finally, this improved stability is achieved without any significant, associated "costs" in terms of detection limits, response times, or biocompatibility.

Acute myocardial infarction (AMI) remains one of the most prevalent and fatal cardiovascular disease. Given the critical diagnostic significance of cardiac troponin I (cTnI) and myoglobin (Myo) in AMI, there is an urgent clinical demand for rapid and accurate detection methods to improve patient outcomes and reduce mortality. To meet this need, we developed a sensing platform that integrates functionalized gold nanoparticle-based lateral flow immunoassay (AuNPs-LFIA) with a machine vision model, enabling rapid quantitative detection of cTnI and Myo. By covalently conjugating antibodies to gold nanoparticles (AuNPs@Ab), we achieved greater probe specificity and stability. The integration of machine vision algorithms allowed quantitative readouts within 8 minutes, a 46.7% improvement of the detection time compared to conventional methods (15 minutes). The platform achieved limits of detection of 0.224 ng/mL for Myo and 0.071 ng/mL for cTnI, with excellent correlation to commercial kits (R2 > 0.99). Overall, these results demonstrate that machine vision-enhanced AuNPs-LFIA offers an efficient, sensitive and reliable strategy for point-of- care testing (POCT) in cardiovascular diagnostics, particularly in resource-limited settings.

Genetically encoded fluorescent biosensors are widely used to monitor small molecule and ion levels in living cells. Quantitative FRET and FLIM sensors and highly sensitive intensiometric sensors have been developed for many analytes. Notwithstanding notable advances over the last years, a universal high-performance sensor design for absolute quantification that does not require specialized equipment has yet to be developed. We here report the GEQO platform of quantitative biosensors featuring calcium, ATP, cAMP, and organelle-specific variants. We used GEQO sensors to follow calcium and cAMP transients in immortalised cells, human pancreatic progenitor cells, and zebrafish embryos. We show that GEQO-based absolute quantification allows to account for analyte buffering and retains information in time trace data lost during relative quantification. GEQO biosensors will enable quantitative analyte measurements across a wide range of imaging platforms, a key prerequisite for diagnostic applications and quantitative approaches in basic cell biology.

Non-invasive glucose monitoring (NIGM) is increasingly considered as an alternative to finger pricking for blood glucose assessment and management of diabetes in insulin-dependent patients, due to the pain, risk of infection, and inadequacy of finger pricking for frequent measurements. Nevertheless, current NIGM techniques do not measure glucose in blood, but rely on indirect bulk measurement of glucose in the interstitial fluid, where glucose is less concentrated, diluted in a generally unknown volume, and appears in a delayed fashion relative to blood glucose, impairing NIGM accuracy. We introduce a new biosensor, termed Depth-gated mid-InfraRed Optoacoustic Sensor (DIROS), which offers for the first time non-invasive glucose detection directly in blood, while simultaneously rejecting contributions from the metabolically inactive stratum corneum and other superficial skin layers. This unique ability is achieved by time-gating mid-infrared optoacoustic signals to enable glucose readings from depth-selective localization in the microvasculature of the skin. In measurements of mice in vivo, DIROS revealed marked accuracy improvement over conventional bulk-tissue glucose measurements. We showcase how skin rejection and signal localization are essential for improving the NIGM accuracy, and discuss key results and how DIROS offers a holistic approach to address limitations of current NIGM methods, with high translation potential.

Precise pH measurements in the immediate environment of receptors is essential for elucidating the mechanisms through which local pH changes associated with diseased phenotypes manifest into aberrant receptor function. However, current pH sensors lack the molecular specificity required to make these measurements. Herein we present the Litmus-body, our recombinant protein-based pH sensor, which through fusion to an anti-mouse IgG nanobody is capable of molecular targeting to specific proteins on the cell surface. By normalizing a pH-dependent green fluorescent protein to a long-Stokes shift red fluorophore or fluorescent protein, we readily report pH independent of sensor concentration using a single 488-nm excitation. Our Litmus-body showed excellent responsiveness in solution, with a greater than 50-fold change across the physiological regime of pH. The sensor was further validated for use on live cells, shown to be specific to the protein of interest, and was able to successfully recapitulate the numerous pH changes along the endocytic pathway.