OriPlex: Origami-enabled multiplexed detection of respiratory pathogens.

Origami biosensors leverage paper foldability to develop total analysis systems integrated in a single piece of paper. This capability can also be utilized to incorporate additional features that would be difficult to achieve with rigid substrates. In this article, we report a new design for 3D origami biosensors called OriPlex, which leverages the foldability of filter paper for the multiplexed detection of bacterial pathogens. OriPlex immunosensors detect pathogens by folding nanoparticle reservoirs containing different types of nanoprobes. This releases antibody-coated nanoparticles in a central channel where targets are captured through physical interactions. The OriPlex concept was demonstrated by detecting the respiratory pathogens Pseudomonas aeruginosa (PA) and Klebsiella pneumoniae (KP) with a limit of detection of 3.4·103 cfu mL-1 and 1.4·102 cfu mL-1, respectively, and with a turn-around time of 25 min. Remarkably, the OriPlex biosensors allowed the multiplexed detection of both pathogens spiked into real bronchial aspirate (BAS) samples at a concentration of 105 cfu mL-1 (clinical infection threshold), thus demonstrating their suitability for diagnosing lower tract respiratory infections. The results shown here pave the way for implementing OriPlex biosensors as a screening test for detecting superbugs requiring personalized antibiotics in suspected cases of nosocomial pneumonia.

A paper biosensor for overcoming matrix effects interfering with the detection of sputum pyocyanin with competitive immunoassays.

Detecting sputum pyocyanin (PYO) with a competitive immunoassay is a promising approach for diagnosing Pseudomonas aeruginosa respiratory infections. However, it is not possible to perform a negative control to evaluate matrix-effects in competitive immunoassays, and the highly complex sputum matrix often interferes with target detection. Here, we show that these issues are alleviated by performing competitive immunoassays with a paper biosensor. The biosensing platform consists of a paper reservoir, which contains antibody-coated gold nanoparticles, and a substrate containing a competing recognition element, which is a piece of paper modified with an albumin-antigen conjugate. Detection of PYO with a limit of detection of 4.7·10-3 µM and a dynamic range between 4.7·10-1 µM and 47.6 µM is accomplished by adding the sample to the substrate with the competing element and pressing the reservoir against it for 5 min. When tested with patient samples, the biosensor was able to qualitatively differentiate spiked from non-spiked samples, whereas ELISA did not show a clear cut-off between them. Furthermore, the relative standard deviation was lower when determining sputum with the paper-based biosensor. These features, along with a mild liquefaction step that circumvents the use of harsh chemicals or instruments, make our biosensor a good candidate for diagnosing Pseudomonas infections at the bedside through the detection of sputum PYO.

Facemask analyses for the non-invasive detection of chronic and acute P. aeruginosa lung infections using nanoparticle-based immunoassays.

Pseudomonas aeruginosa (P. aeruginosa) is a pathogen that persistently colonizes the respiratory tract of patients with chronic lung diseases. The risk of acquiring a chronic P. aeruginosa infection can be minimized by rapidly detecting the pathogen in the patient's airways and promptly administrating adequate antibiotics. However, the rapid detection of P. aeruginosa in the lungs involves the analysis of sputum, which is a highly complex matrix that is not always available. Here, we propose an alternative diagnosis based on analyzing breath aerosols. In this approach, nanoparticle immunosensors identify bacteria adhered to the polypropylene layer of a surgical facemask that was previously worn by the patient. A polypropylene processing protocol was optimized to ensure the efficient capture and analysis of the target pathogen. The proposed analytical platform has a theoretical limit of detection of 105 CFU mL-1 in aerosolized mock samples, and a dynamic range between 105 and 108 CFU mL-1. When tested with facemasks worn by patients, the biosensors were able to detect chronic and acute P. aeruginosa lung infections, and to differentiate them from respiratory infections caused by other pathogens. The results shown here pave the way to diagnose Pseudomonas infections at the bedside, as well as to identify the progress from chronic to acute infection.

Correction: Label free localization of nanoparticles in live cancer cells using spectroscopic microscopy.

Correction for 'Label free localization of nanoparticles in live cancer cells using spectroscopic microscopy' by Graham L. C. Spicer et al., Nanoscale, 2018, 10, 19125-19130, https://doi.org/10.1039/C8NR07481J.

Engineering a Point-of-Care Paper-Microfluidic Electrochemical Device Applied to the Multiplexed Quantitative Detection of Biomarkers in Sputum.

Health initiatives worldwide demand affordable point-of-care devices to aid in the reduction of morbidity and mortality rates of high-incidence infectious and noncommunicable diseases. However, the production of robust and reliable easy-to-use diagnostic platforms showing the ability to quantitatively measure several biomarkers in physiological fluids and that could in turn be decentralized to reach any relevant environment remains a challenge. Here, we show the particular combination of paper-microfluidic technology, electrochemical transduction, and magnetic nanoparticle-based immunoassay approaches to produce a unique, compact, and easily deployable multiplex device to simultaneously measure interleukin-8, tumor necrosis factor-α, and myeloperoxidase biomarkers in sputum, developed with the aim of facilitating the timely detection of acute exacerbations of chronic obstructive pulmonary disease. The device incorporates an on-chip electrochemical cell array and a multichannel paper component, engineered to be easily aligned into a polymeric cartridge and exchanged if necessary. Calibration curves at clinically relevant biomarker concentration ranges are produced in buffer and artificial sputum. The analysis of sputum samples of healthy individuals and acutely exacerbated patients produces statistically significant biomarker concentration differences between the two studied groups. The device can be mass-produced at a low cost, being an easily adaptable platform for measuring other disease-related target biomarkers.

Improved cytometric analysis of untouched lung leukocytes by enzymatic liquefaction of sputum samples.

BACKGROUND: Phenotyping sputum-resident leukocytes and evaluating their functional status are essential analyses for exploring the cellular basis of pathological processes in the lungs, and flow cytometry is widely recognized as the gold-standard technique to address them. However, sputum-resident leukocytes are found in respiratory samples which need to be liquefied prior to cytometric analysis. Traditional liquefying procedures involve the use of a reducing agent such as dithiothreitol (DTT) in temperature-controlled conditions, which does not homogenize respiratory samples efficiently and impairs cell viability and functionality. METHODS: Here we propose an enzymatic method that rapidly liquefies samples by means of generating O2 bubbles with endogenous catalase. Sputum specimens from patients with suspected pulmonary infection were treated with DTT, the enzymatic method or PBS. We used turbidimetry to compare the liquefaction degree and cell counts were determined using a hemocytometer. Finally, we conducted a comparative flow cytometry study for evaluating frequencies of sputum-resident neutrophils, eosinophils and lymphocytes and their activation status after liquefaction. RESULTS: Enzymatically treated samples were better liquefied than those treated with DTT or PBS, which resulted in a more accurate cytometric analysis. Frequencies of all cell subsets analyzed within liquefied samples were comparable between liquefaction methods. However, the gentle cell handling rendered by the enzymatic method improves cell viability and retains in vivo functional characteristics of sputum-resident leukocytes (with regard to HLA-DR, CD63 and CD11b expression). CONCLUSION: In conclusion, the proposed enzymatic liquefaction method improves the cytometric analysis of respiratory samples and leaves the cells widely untouched for properly addressing functional analysis of lung leukocytes.

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.

Rapid Identification and Classification of Pathogens That Produce Carbapenemases and Cephalosporinases with a Colorimetric Paper-Based Multisensor.

Infections caused by bacteria that produce ß-lactamases (BLs) are a major problem in hospital settings. The phenotypic detection of these bacterial strains requires culturing samples prior to analysis. This procedure may take up to 72 h, and therefore it cannot be used to guide the administration of the first antibiotic regimen. Here, we propose a multisensor for identifying pathogens bearing different types of ß-lactamases above the infectious dose threshold within 90 min that does not require culturing samples. Instead, bacterial cells are preconcentrated in the cellulose scaffold of a paper-based multisensor. Then, 12 assays are performed in parallel to identify whether the pathogens produce carbapenemases and/or cephalosporinases, including metallo-ß-lactamases, extended-spectrum ß-lactamases (ESBLs), and AmpC enzymes. The multisensor generates an array of colored spots that can be quantified with image processing software and whose interpretation leads to the detection of the different enzymes depending on their specificity toward the hydrolysis of certain antibiotics, and/or their pattern of inhibition or cofactor activation. The test was validated for the diagnosis of urinary tract infections. The inexpensive paper platform along with the uncomplicated colorimetric readout makes the proposed prototypes promising for developing fully automated platforms for streamlined clinical diagnosis.

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.

Dissolvable Polymer Valves for Sweat Chrono-Sampling in Wearable Paper-Based Analytical Devices.

Paper sensors with colorimetric signal transduction mechanisms are promising for developing single-use wearable patches that only require a smartphone to quantify signals. However, measuring biomarker fluctuations with colorimetric wearable sensors requires implementing a chrono-sampling method for performing sequential measurements. In this article, we report on a chrono-sampling method that enables the fabrication of wearable devices made entirely of filter paper. It consists of using dried polymers as closed valves that deflect the flow of liquids to different transducers of a multisensor. As time passes by, the polymer dissolves and the valve opens. The sequential opening of the valves results in a succession of measurements that reveals fluctuations in the concentration of the target analyte. This concept was demonstrated with a paper multisensor capable of performing nine consecutive pH measurements. The device was also adapted for developing a urea biosensor that detects pH measurements generated by the hydrolysis of the analyte catalyzed by urease. The proposed analytical platform could monitor the pH of sweat with an accuracy and precision comparable to a laboratory-based method when worn during an exercise routine. The results shown here pave the way for developing colorimetric wearable biosensors that measure variations in the concentration of biomarkers such as glucose, lactate, creatinine, or uric acid over time.

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.

Colorimetric Detection of Sepsis-Derived Hyperdegranulation with Plasmonic Nanosensors.

Hyperdegranulation of neutrophilic granulocytes is a common finding in sepsis that directly contributes to the heightened immune response leading to organ dysfunction. Currently, cell degranulation is detected by flow cytometry, which requires large infrastructure that is not always available at the point of care. Here, we propose a plasmonic assay for detecting the degranulation status of septic cells colorimetrically. It is based on triggering the aggregation of gold nanoparticles with cationic granule proteins. Cells from septic patients contain fewer granules and therefore release less cationic proteins than healthy cells. This results in red-colored assays than can be easily detected by eye. The assay can selectively detect cationic granule proteins even in the presence of an excess of unrelated proteins, which is key to detect degranulation with high specificity. Coupling this signal generation mechanism with a magnetic purification step enabled the identification of septic cells with the same performance as flow cytometry. This makes the proposed method a promising alternative for diagnosing sepsis in decentralized healthcare schemes.

Optimized detection of lung IL-6 via enzymatic liquefaction of low respiratory tract samples: application for managing ventilated patients.

Lung IL-6 is a promising biomarker for predicting respiratory failure during pulmonary infections. This biomarker is found in respiratory samples which need to be liquefied prior to analysis. Traditional liquefying methods use reducing agents such as dithiothreitol (DTT). However, DTT impairs immunodetection and does not liquefy highly viscous samples. We propose an enzymatic method that liquefies samples by means of generating O2 bubbles with endogenous catalase. Low respiratory tract specimens from 48 mechanically ventilated patients (38 with SARS-CoV-2 infection) were treated with DTT or with the enzymatic method. We used turbidimetry to compare the liquefaction degree and IL-6 was quantified with ELISA. Finally, we used AUC-ROC, time-to-event and principal component analysis to evaluate the association between respiratory compromise or local inflammation and IL-6 determined with both methods. Enzymatically treated samples were better liquefied than those reduced by DTT, which resulted in higher ELISA signals. Lung IL-6 levels obtained with the enzymatic procedure were negatively correlated with the oxygenation index (PaO2/FiO2) and the time of mechanical ventilation. The proposed enzymatic liquefaction method improves the sensitivity for lung IL-6 detection in respiratory samples, which increases its predictive power as a biomarker for evaluating respiratory compliance.

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.

Detection of low glucose levels in sweat with colorimetric wearable biosensors.

Low glucose levels during exercise may lead to hypoglycemia, which can have grave consequences in diabetic athletes. Mobile colorimetric wearable biosensors that measure glucose levels in sweat are ideal for self-monitoring as they can utilize the camera in smartphones for signal reading. However, colorimetric biosensors proposed thus far have higher limit of detection (LOD) than electrochemical devices, which makes them unsuitable for detecting hypoglycemia. In this manuscript we describe colorimetric wearable biosensors that detect glucose in sweat with an LOD of 0.01 mM and a dynamic range up to 0.15 mM. The devices are made of filter paper and incorporate a sweat volume sensor and a color chart for signal correction. The biosensors do not suffer from interferences originated by delayed sample readings, or differences in bending angle and sample pH. When applied to volunteers performing an exercise routine, sweat glucose levels corrected with sweat volume measurements correlated well with blood glucose measurements performed with a commercial device. The devices are lightweight and easily disposable. These features, along with the smartphone-based colorimetric readout, makes them promising as "over-the-counter" tests for measuring glucose levels non-invasively during exercise.

Immunodetection of Lung IgG and IgM Antibodies against SARS-CoV-2 via Enzymatic Liquefaction of Respiratory Samples from COVID-19 Patients.

Lung-secreted IgG and IgM antibodies are valuable biomarkers for monitoring the local immune response against respiratory infections. These biomarkers are found in lower airway secretions that need to be liquefied prior to analysis. Traditional methods for sample liquefaction rely on reducing disulfide bonds, which may damage the structure of the biomarkers and hamper their immunodetection. Here, we propose an alternative enzymatic method that uses O2 bubbles generated by endogenous catalase enzymes in order to liquefy respiratory samples. The proposed method is more efficient for liquefying medium- and high-viscosity samples and does not fragment the antibodies. This prevents damage to antigen recognition domains and recognition sites for secondary antibodies that can decrease the signal of immunodetection techniques. The suitability of the enzymatic method for detecting antibodies in respiratory samples is demonstrated by detecting anti-SARS-CoV-2 IgG and IgM to viral N-protein with gold standard ELISA in bronchial aspirate specimens from a multicenter cohort of 44 COVID-19 patients. The enzymatic detection sharply increases the sensitivity toward IgG and IgM detection compared to the traditional approach based on liquefying samples with dithiothreitol. This improved performance could reveal new mechanisms of the early local immune response against respiratory infections that may have gone unnoticed with current sample treatment methods.

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.

Wearable Analytical Platform with Enzyme-Modulated Dynamic Range for the Simultaneous Colorimetric Detection of Sweat Volume and Sweat Biomarkers.

In this manuscript, we introduce a wearable analytical platform that simultaneously measures the concentration of sweat lactate and sample volume. It contains two sensors entirely made of filter paper that can be easily affixed on the skin with medical-grade tape. The lactate biosensor features a unique signal modulation mechanism that enables fine-tuning the dynamic range. It consists of adding a competitive enzyme inhibitor in different reservoirs. Thanks to this, it is possible to choose between a very low limit of detection (0.06 mM) and a linear response in the physiological concentration range (10-30 mM). The sweat volume sensor was obtained by adding a reservoir containing gold nanoparticles. As the wearer sweats, the nanoparticles are carried through a paper channel. This is used to gauge the volume of sample by measuring the distance traveled by the nanoprobes. Using fine-tuned lactate biosensors and combining them with the volume sensors allowed us to quantify variations in the levels of sweat lactate independently of the wearer's sweat rate during an exercise routine. The platform design can be customized to meet the end user's needs, which makes it ideal for developing a wide array of disposable wearable biosensors.

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.