Plasma-induced nanoparticle aggregation for stratifying COVID-19 patients according to disease severity.

Stratifying patients according to disease severity has been a major hurdle during the COVID-19 pandemic. This usually requires evaluating the levels of several biomarkers, which may be cumbersome when rapid decisions are required. In this manuscript we show that a single nanoparticle aggregation test can be used to distinguish patients that require intensive care from those that have already been discharged from the intensive care unit (ICU). It consists of diluting a platelet-free plasma sample and then adding gold nanoparticles. The nanoparticles aggregate to a larger extent when the samples are obtained from a patient in the ICU. This changes the color of the colloidal suspension, which can be evaluated by measuring the pixel intensity of a photograph. Although the exact factor or combination of factors behind the different aggregation behavior is unknown, control experiments demonstrate that the presence of proteins in the samples is crucial for the test to work. Principal component analysis demonstrates that the test result is highly correlated to biomarkers of prognosis and inflammation that are commonly used to evaluate the severity of COVID-19 patients. The results shown here pave the way to develop nanoparticle aggregation assays that classify COVID-19 patients according to disease severity, which could be useful to de-escalate care safely and make a better use of hospital resources.

Improving the Quantification of Colorimetric Signals in Paper-Based Immunosensors with an Open-Source Reader.

Measuring the colorimetric signals produced by the biospecific accumulation of colorimetric probes and recording the results is a key feature for next-generation paper-based rapid tests. Manual processing of these tests is time-consuming and prone to a loss of accuracy when interpreting faint and patchy signals. Proprietary, closed-source readers and software companies offering automated smartphone-based assay readings have both been criticized for interoperability issues. Here, we introduce a minimal reader prototype composed of open-source hardware and open-source software that has the benefits of automatic assay quantification while avoiding the interoperability issues associated with closed-source readers. An image-processing algorithm was developed to automate the selection of an optimal region of interest and measure the average pixel intensity. When used to quantify signals produced by lateral flow immunoassays for detecting antibodies against SARS-CoV-2, results obtained with the proposed algorithm were comparable to those obtained with a manual method but with the advantage of improving the precision and accuracy when quantifying small spots or faint and patchy signals.

Micro- and nanosensors for detecting blood pathogens and biomarkers at different points of sepsis care.

Severe infections can cause a dysregulated response leading to organ dysfunction known as sepsis. Sepsis can be lethal if not identified and treated right away. This requires measuring biomarkers and pathogens rapidly at the different points where sepsis care is provided. Current commercial approaches for sepsis diagnosis are not fast, sensitive, and/or specific enough for meeting this medical challenge. In this article, we review recent advances in the development of diagnostic tools for sepsis management based on micro- and nanostructured materials. We start with a brief introduction to the most popular biomarkers for sepsis diagnosis (lactate, procalcitonin, cytokines, C-reactive protein, and other emerging protein and non-protein biomarkers including miRNAs and cell-based assays) and methods for detecting bacteremia. We then highlight the role of nano- and microstructured materials in developing biosensors for detecting them taking into consideration the particular needs of every point of sepsis care (e.g., ultrafast detection of multiple protein biomarkers for diagnosing in triage, emergency room, ward, and intensive care unit; quantitative detection to de-escalate treatment; ultrasensitive and culture-independent detection of blood pathogens for personalized antimicrobial therapies; robust, portable, and web-connected biomarker tests outside the hospital). We conclude with an overview of the most utilized nano- and microstructured materials used thus far for solving issues related to sepsis diagnosis and point to new challenges for future development.

Nanoparticle transfer biosensors for the non-invasive detection of SARS-CoV-2 antigens trapped in surgical face masks.

Detecting SARS-CoV-2 antigens in respiratory tract samples has become a widespread method for screening new SARS-CoV-2 infections. This requires a nasopharyngeal swab performed by a trained healthcare worker, which puts strain on saturated healthcare services. In this manuscript we describe a new approach for non-invasive COVID-19 diagnosis. It consists of using mobile biosensors for detecting viral antigens trapped in surgical face masks worn by patients. The biosensors are made of filter paper containing a nanoparticle reservoir. The nanoparticles transfer from the biosensor to the mask on contact, where they generate colorimetric signals that are quantified with a smartphone app. Sample collection requires wearing a surgical mask for 30 min, and the total assay time is shorter than 10 min. When tested in a cohort of 27 patients with mild or no symptoms, an area under the receiving operating curve (AUROC) of 0.99 was obtained (96.2 % sensitivity and 100 % specificity). Serial measurements revealed a high sensitivity and specificity when masks were worn up to 6 days after diagnosis. Surgical face masks are inexpensive and widely available, which makes this approach easy to implement anywhere. The excellent sensitivity, even when tested with asymptomatic patient samples, along with the mobile detection scheme and non-invasive sampling procedure, makes this biosensor design ideal for mass screening.

Paper biosensors for detecting elevated IL-6 levels in blood and respiratory samples from COVID-19 patients.

Decentralizing COVID-19 care reduces contagions and affords a better use of hospital resources. We introduce biosensors aimed at detecting severe cases of COVID-19 in decentralized healthcare settings. They consist of a paper immunosensor interfaced with a smartphone. The immunosensors have been designed to generate intense colorimetric signals when the sample contains ultralow concentrations of IL-6, which has been proposed as a prognosis biomarker of COVID-19. This is achieved by combining a paper-based signal amplification mechanism with polymer-filled reservoirs for dispensing antibody-decorated nanoparticles and a bespoken app for color quantification. With this design we achieved a low limit of detection (LOD) of 10-3 pg mL-1 and semi-quantitative measurements in a wide dynamic range between 10-3 and 102 pg mL-1 in PBS. The assay time is under 10 min. The low LOD allowed us to dilute blood samples and detect IL-6 with an LOD of 1.3 pg mL-1 and a dynamic range up to 102 pg mL-1. Following this protocol, we were able to stratify COVID-19 patients according to different blood levels of IL-6. We also report on the detection of IL-6 in respiratory samples (bronchial aspirate, BAS) from COVID-19 patients. The test could be easily adapted to detect other cytokines such as TNF-α and IL-8 by changing the antibodies decorating the nanoparticles accordingly. The ability of detecting cytokines in blood and respiratory samples paves the way for monitoring local inflammation in the lungs as well as systemic inflammation levels in the body.

Mobile origami immunosensors for the rapid detection of urinary tract infections.

Urinary tract infections (UTI) have a high prevalence and can yield poor patient outcomes if they progress to urosepsis. Here we introduce mobile origami biosensors that detect UTIs caused by E. coli at the bedside in less than 7 minutes. The origami biosensors are made of a single piece of paper that contains antibody-decorated nanoparticles. When the urine sample contains E. coli, the biosensors generate colored spots on the paper strip. These are then quantified with a mobile app that calculates the pixel intensity in real time. The tests are highly specific and do not cross-react with other common uropathogens. Furthermore, the biosensors only yielded one false negative result when queried with a panel containing 57 urine samples from patients, which demonstrates that they have excellent sensitivity and specificity. This, along with the rapid assay time and smartphone-based detection, makes them useful for aiding in the diagnosis of UTIs at the point of care.

Rapid Detection of Pseudomonas aeruginosa Biofilms via Enzymatic Liquefaction of Respiratory Samples.

Respiratory infections caused by multi-drug-resistant Pseudomonas aeruginosa often yield poor outcomes if not detected right away. However, detecting this pathogen in respiratory samples with a rapid diagnostic test is challenging because the protective biofilms created by the pathogen are themselves surrounded by a high-viscosity sputum matrix. Here, we introduce a method for liquefying respiratory samples and disrupting bacterial biofilms on the spot within a minute. It relies on the generation of oxygen bubbles by bacterial catalase through the addition of hydrogen peroxide. When coupled with a mobile biosensor made of paper, the resulting diagnostic kit was able to detect P. aeruginosa infections in sputa from patients with excellent sensitivity and specificity within 8 min. The quick turnaround time along with few infrastructure requirements make this method ideal for the rapid screening of P. aeruginosa infections at the point of care.

Biosensors for Managing the COVID-19 Cytokine Storm: Challenges Ahead.

The global COVID-19 pandemic has oversaturated many intensive care units to the point of collapse, leading to enormous spikes in death counts. Before critical care becomes a necessity, identifying patients who are likely to become critically ill and providing prompt treatment is a strategy to avoid ICU oversaturation. There is a consensus that a hyperinflammatory syndrome or a "cytokine storm" is responsible for poor outcomes in COVID-19. Measuring cytokine levels at the point of care is required in order to better understand this process. In this Perspective, we summarize the main events behind the cytokine storm in COVID-19 as well as current experimental treatments. We advocate for a new biosensor-enabled paradigm to personalize the management of COVID-19 and stratify patients. Biosensor-guided dosing and timing of immunomodulatory therapies could maximize the benefits of these anti-inflammatory treatments while minimizing deleterious effects. Biosensors will also be essential in order to detect complications such as coinfections and sepsis, which are common in immunosuppressed patients. Finally, we propose the ideal features of these biosensors using some prototypes from the recent literature as examples. Multisensors, lateral flow tests, mobile biosensors, and wearable biosensors are seen as key players for precision medicine in COVID-19.

Nanoparticle-based mobile biosensors for the rapid detection of sepsis biomarkers in whole blood.

Detecting small variations in the levels of IL-6 is crucial for the early diagnosis of sepsis. To be useful in clinical decision-making, this requires detecting IL-6 rapidly in whole blood and with portable readers. Here we introduce immunosensors made of filter paper that use plasmonic nanoprobes to detect IL-6 rapidly in unprocessed blood with an unmodified smartphone. Key aspects of the biosensor fabrication were optimized in order to reduce the assay time without losing sensitivity. This included testing three bioconjugation routes for protein attachment to nanoprobes using gold nanoparticles covered with carboxylate or amine moieties, or polyvinylpyrrolidone (PVP), as starting materials, and using alternating layers of polyelectrolytes to bind the capture antibody to the paper substrate. Smartphone-based signal quantification was achieved with a custom-made app featuring a unique augmented reality guidance system that circumvents the need for smartphone attachments and automates all the steps involved in color quantification. The biosensors were able to detect IL-6 with a limit of detection of 0.1 pg mL-1 and a total assay time within 17 min. They could also detect an increase in IL-6 of only 12.5 pg mL-1 over basal levels in whole blood with 99% confidence. The high sensitivity and rapid turnaround time afforded by the optimized biosensors and the fully automated real-time densitometry app make our biosensors well suited for emergency healthcare situations such as the identification of potential sepsis cases.

Multifunctional motion-to-color janus transducers for the rapid detection of sepsis biomarkers in whole blood.

Self-propelled particles are revolutionizing sensing applications thanks to a unique motion-based signal generation mechanism in which biorecognition reactions are detected as changes in the velocity of the colloids. Here a new family of self-propelled multifunctional Janus particles is introduced that enables detecting changes in particle motion colorimetrically. The particles consist of an iron oxide core that provides color and magnetism, and a Janus coating that provides biospecific recognition and locomotive properties. In this approach, biomolecular interactions trigger changes in particle motion that are detected as variations in color when spotted on a piece of paper. These variations in color are then read and quantified with a custom-made smartphone app. The high surface area and magnetism of the particles makes them ideal building blocks for developing biosensors because they allow for the rapid capture of a target molecule and the removal of non-specific interactions. Biosensors engineered with the proposed multifunctional particles were able to detect the sepsis biomarker procalcitonin at clinically relevant concentrations within 13 min in whole blood, which is faster than other approaches requiring hour-long incubation steps under controlled conditions to detect the same biomarker in purified serum. The short assay time along with the point-of-need design makes these biosensors suitable for stratifying patients according to their sepsis risk level during triage independently of resource constraints.

Ultrafast and Ultrasensitive Naked-Eye Detection of Urease-Positive Bacteria with Plasmonic Nanosensors.

Identifying the pathogen responsible for an infection is a requirement in order to personalize antimicrobial treatments. Detecting bacterial enzymes, such as proteases, lipases, and oxidoreductases, is a winning approach for detecting pathogens at the point of care. In this Article, a new method for detecting urease-producing bacteria rapidly and at ultralow concentrations is reported. In this method, longsome bacteriological culture steps are substituted for a 10 min capture procedure with positively charged magnetic beads. The presence of urease-positive bacteria on the particles is then queried with a plasmonic signal generation step that generates blue- or red-colored nanoparticle suspensions upon addition of the enzyme substrate. These colorimetric signals, which can be easily identified by eye, are generated by the NH3-dependent assembly of gold nanoparticles in the presence of bovine serum albumin (BSA). The proposed method can detect Proteus mirabilis with a limit of detection of 101 cells mL-1, with a total assay time of 40 min, even in the presence of a large excess of urease-negative bacteria ( Pseudomonas aeruginosa). Furthermore, it does not require bulky equipment, and it can detect P. mirabilis at clinically relevant concentrations within minutes, making it suitable for detecting urease-positive pathogens at the point of care.

A Robust and User-Friendly Alternative to Densitometry Using Origami Biosensors and Digital Logic.

Colorimetric detection with smartphones is ideal for point-of-care measurements because the signal reader is easily available. Densitometric detection schemes enable semiquantitative measurements but require a lightproof box to control photographic conditions and/or extensive data treatment to extract information. Approaches based on pattern recognition are not so sensitive to light artifacts but can only yield a yes/no type of answer when the signal is above or below a certain threshold. Here, we introduce a new method for detecting different concentrations of proteins as well as light artifacts with origami immunosensors and digital logic. The origami design consists of a folded piece of paper with three identical biorecognition sites so that one drop of sample generates three colorimetric signals simultaneously. The three colorimetric signals are then evaluated with an augmented reality app that generates a virtual semaphore that sequentially turns on its green, yellow, and red lights depending on the concentration of analyte. These three Boolean variables pass through "and" and "not" logic gates in a 3-to-8 decoder that enables the semiquantitative detection of proteins and adds a failsafe against erroneous results. The proposed method can detect the model analyte mouse IgG with a limit of detection and sensitivity comparable to densitometry performed under light-controlled conditions. It can also detect the sepsis biomarker procalcitonin at clinically relevant concentrations. With our approach, the detection is performed in real time, and signal processing is not required, which makes it suitable for rapid analyses by nonspecialists at the point of need.

Policy Considerations for Mobile Biosensors.

Meeting policy requirements is essential for advancing molecular diagnostic devices from the laboratory to real-world applications and commercialization. Considering policy as a starting point in the design of new technology is a winning strategy. Rapid developments have put mobile biosensors at the frontier of molecular diagnostics, at times outpacing policymakers, and therefore offering new opportunities for breakthroughs in global health. In this Perspective we survey influential global health policies and recent developments in mobile biosensing in order to gain a new perspective for the future of the field. We summarize the main requirements for mobile diagnostics outlined by policy makers such as the World Health Organization (WHO), the World Bank, the European Union (EU), and the Food and Drug Administration (FDA). We then classify current mobile diagnostic technologies according to the manner in which the biosensor interfaces with a smartphone. We observe a trend in reducing hardware components and substituting instruments and laborious data processing steps for user-friendly apps. From this perspective we see software application developers as key collaborators for bridging the gap between policy and practice.

Augmented Reality for Real-Time Detection and Interpretation of Colorimetric Signals Generated by Paper-Based Biosensors.

Colorimetric tests are becoming increasingly popular in point-of-need analyses due to the possibility of detecting the signal with the naked eye, which eliminates the utilization of bulky and costly instruments only available in laboratories. However, colorimetric tests may be interpreted incorrectly by nonspecialists due to disparities in color perception or a lack of training. Here we solve this issue with a method that not only detects colorimetric signals but also interprets them so that the test outcome is understandable for anyone. It consists of an augmented reality (AR) app that uses a camera to detect the colored signals generated by a nanoparticle-based immunoassay, and that yields a warning symbol or message when the concentration of analyte is higher than a certain threshold. The proposed method detected the model analyte mouse IgG with a limit of detection of 0.3 µg mL-1, which was comparable to the limit of detection afforded by classical densitometry performed with a nonportable device. When adapted to the detection of E. coli, the app always yielded a "hazard" warning symbol when the concentration of E. coli in the sample was above the infective dose (106 cfu mL-1 or higher). The proposed method could help nonspecialists make a decision about drinking from a potentially contaminated water source by yielding an unambiguous message that is easily understood by anyone. The widespread availability of smartphones along with the inexpensive paper test that requires no enzymes to generate the signal makes the proposed assay promising for analyses in remote locations and developing countries.