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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Development of Plasmonic Chitosan-Squarate Hydrogels via Bioinspired Nanoparticle Growth.

We report on the bioinspired growth of gold nanoparticles (GNPs) in biocompatible hydrogels to develop plasmonic hybrid materials. The new hydrogel (CS-Sq) is prepared from chitosan and diethylsquarate and is formed via noncovalent interactions rising between the in situ formed ionic squaric acid derivatives and chitosan. Interestingly, when the hydrogel is prepared in the presence of HAuCl4, GNPs with controlled sizes between 15 and 50 nm are obtained, which are homogeneously distributed within the plasmonic hydrogels (GNPs-CS-Sq). We found that the supramolecular nature and the composition of the CS-Sq hydrogels are key for the growth process of GNPs where the squaric derivatives act as reducing agents and the chitosan hydrogel network provides nucleation points and supports the GNPs. Accordingly, the hydrogel acts as a bioinspired reactor and permits to gain certain control on the size of GNPs by adjusting the concentration of chitosan and HAuCl4. Besides the intrinsic and tunable plasmonic properties of the GNPs-CS-Sq hydrogels, it was found that the gels could be useful as heterogeneous catalysts for organic reactions. Furthermore, cell viability studies indicate that the new hydrogels exhibit suitable biocompatibility. Thus, the proposed method for obtaining GNPs-CS-Sq hydrogels has the potential for the development of a wide variety of other hybrid chitosan materials useful for catalysis, biosensing, cell culture, tissue engineering, and drug delivery applications.

Addendum: Plasmonic nanosensors with inverse sensitivity by means of enzyme-guided crystal growth.

This corrects the article DOI: 10.1038/nmat3337.

Corrigendum: Plasmonic nanosensors with inverse sensitivity by means of enzyme-guided crystal growth.

This corrects the article DOI: 10.1038/nmat3337.

Erratum: Corrigendum: Plasmonic nanosensors with inverse sensitivity by means of enzyme-guided crystal growth.

Nature Materials 11, 604-607 (2012); published online 27 May 2012; corrected after print 15 December 2017. In the version of this Letter originally published, the x and y values of the data points in Fig. 2c were incorrect. The original and corrected versions are shown below. The authors have also made some changes to the Supplementary Information: Fig.

Light-Triggered Inactivation of Enzymes with Photothermal Nanoheaters.

A universal method for inactivating enzymes on demand is introduced, which involves irradiating nanorod-bound enzymes with near-infrared light. The subsequent generation of plasmonic heat denatures the enzymes selectively without damaging other proteins or cell membranes present in the same solution.

Naked-eye detection as a universal approach to lower the limit of detection of enzyme-linked immunoassays.

Colorimetric biosensors for the detection of analytes with the naked eye are required in environmental monitoring, point-of-care diagnostics, and analyses in resources constrained settings, where detection instruments may not be available. However, instrument-based detection methods are usually more adequate for detecting small variations in the signal compared to naked-eye detection schemes, and consequently the limit of detection of the latter is usually higher than the former. Here, we demonstrate that the limit of detection of colorimetric enzyme-linked immunoassays can be decreased several orders of magnitude when using naked-eye detection instead of a spectrophotometer for detecting the signal. The key step to lower the limit of detection is adding a small volume of chromogenic substrate during the signal generation step. This generates highly colored solutions that can be easily visualized with the naked eye and recorded with the camera of a mobile phone. The proposed method does not require expensive equipment or complex protocols to enhance the signal, and therefore it is a universal approach to lower the limit of detection of colorimetric enzyme-linked immunoassays.

Self-assembly of collagen building blocks guided by electric fields.

Show me the way: protein building blocks are programmed to assemble hierarchically and yield a defined fiber morphology of micrometric length and precise nanometric diameter. The key step of this method is to align the building blocks with an AC field prior to assembly. The resulting protein nanofibers are straightforwardly integrated with the circuitry for potential applications in bionanotechnology.