Development of a cloud-based flow rate tool for eNAMPT biomarker detection.

Increased levels of extracellular nicotinamide phosphoribosyltransferase (eNAMPT) are increasingly recognized as a highly useful biomarker of inflammatory disease and disease severity. In preclinical animal studies, a monoclonal antibody that neutralizes eNAMPT has been generated to successfully reduce the extent of inflammatory cascade activation. Thus, the rapid detection of eNAMPT concentration in plasma samples at the point of care (POC) would be of great utility in assessing the benefit of administering an anti-eNAMPT therapeutic. To determine the feasibility of this POC test, we conducted a particle immunoagglutination assay on a paper microfluidic platform and quantified its extent with a flow rate measurement in less than 1 min. A smartphone and cloud-based Google Colab were used to analyze the flow rates automatically. A horizontal flow model and an immunoagglutination binding model were evaluated to optimize the detection time, sample dilution, and particle concentration. This assay successfully detected eNAMPT in both human whole blood and plasma samples (diluted to 10 and 1%), with the limit of detection of 1-20 pg/mL (equivalent to 0.1-0.2 ng/mL in undiluted blood and plasma) and a linear range of 5-40 pg/mL. Furthermore, the smartphone POC assay distinguished clinical samples with low, mid, and high eNAMPT concentrations. Together, these results indicate this POC assay, which utilizes low-cost materials, time-effective methods, and a straightforward immunoassay (without surface immobilization), may reliably allow rapid determination of eNAMPT blood/plasma levels to advantage patient stratification in clinical trials and guide ALT-100 mAb therapeutic decision-making.

Methotrexate Inhibits the Binding of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Receptor Binding Domain to the Host-Cell Angiotensin-Converting Enzyme-2 (ACE-2) Receptor.

As the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus mutates, finding effective drugs becomes more challenging. In this study, we use ultrasensitive frequency locked microtoroid optical resonators in combination with in silico screening to search for COVID-19 drugs that can stop the virus from attaching to the human angiotensin-converting enzyme 2 (hACE2) receptor in the lungs. We found 29 promising candidates that could block the binding site and selected four of them that were likely to bind very strongly. We tested three of these candidates using frequency locked optical whispering evanescent resonator (FLOWER), a label-free sensing method based on microtoroid resonators. FLOWER has previously been used for sensing single macromolecules. Here we show, for the first time, that FLOWER can provide accurate binding affinities and sense the inhibition effect of small molecule drug candidates without labels, which can be prohibitive in drug discovery. One of the candidates, methotrexate, showed binding to the spike protein 1.8 million times greater than that to the receptor binding domain (RBD) binding to hACE2, making it difficult for the virus to enter cells. We tested methotrexate against different variants of the SARS-CoV-2 virus and found that it is effective against all four of the tested variants. People taking methotrexate for other conditions have also shown protection against the original SARS-CoV-2 virus. Normally, it is assumed that methotrexate inhibits the replication and release of the virus. However, our findings suggest that it may also block the virus from entering cells. These studies additionally demonstrate the possibility of extracting candidate ligands from large databases, followed by direct receptor-ligand binding experiments on the best candidates using microtoroid resonators, thus creating a workflow that enables the rapid discovery of new drug candidates for a variety of applications.

An Integrated Approach to Protein Discovery and Detection From Complex Biofluids.

Ovarian cancer, a leading cause of cancer-related deaths among women, has been notoriously difficult to screen for and diagnose early, as early detection significantly improves survival. Researchers and clinicians seek routinely usable and noninvasive screening methods; however, available methods (i.e., biomarker screening) lack desirable sensitivity/specificity. The most fatal form, high-grade serous ovarian cancer, often originate in the fallopian tube; therefore, sampling from the vaginal environment provides more proximal sources for tumor detection. To address these shortcomings and leverage proximal sampling, we developed an untargeted mass spectrometry microprotein profiling method and identified cystatin A, which was validated in an animal model. To overcome the limits of detection inherent to mass spectrometry, we demonstrated that cystatin A is present at 100 pM concentrations using a label-free microtoroid resonator and translated our workflow to patient-derived clinical samples, highlighting the potential utility of early stage detection where biomarker levels would be low.

Rapid and sensitive detection of miRNA via light scatter-aided emulsion-based isothermal amplification using a custom low-cost device.

MicroRNAs are likely to be a next-generation clinical biomarker for many diseases. While gold-standard technologies, e.g., reverse transcription-quantitative polymerase chain reaction (RT-qPCR), exist for microRNA detection, there is a need for rapid and low-cost testing. Here, an emulsion loop-mediated isothermal amplification (eLAMP) assay was developed for miRNA that compartmentalizes a LAMP reaction and shortens the time-to-detection. The miRNA was a primer to facilitate the overall amplification rate of template DNA. Light scatter intensity decreased when the emulsion droplet got smaller during the ongoing amplification, which was utilized to moitor the amplification non-invasively. A custom low-cost device was designed and fabricated using a computer cooling fan, a Peltier heater, an LED, a photoresistor, and a temperature controller. It allowed more stable vortexing and accurate light scatter detection. Three miRNAs, miR-21, miR-16, and miR-192, were successfully detected using the custom device. Specifically, new template and primer sequences were developed for miR-16 and miR-192. Zeta potential measurements and microscopic observations confirmed emulsion size reduction and amplicon adsorption. The detection limit was 0.01 fM, corresponding to 2.4 copies per reaction, and the detection could be made in 5 min. Since the assays were rapid and both template and miRNA + template could eventually be amplified, we introduced the success rate (compared to the 95% confidence interval of the template result) as a new measure, which worked well with lower concentrations and inefficient amplifications. This assay brings us one step closer to allowing circulating miRNA biomarker detection to become commonplace in the clinical world.

Receptor-based detection of microplastics and nanoplastics: Current and future.

Plastic pollution is an emerging environmental concern, gaining significant attention worldwide. They are classified into microplastics (MP; defined from 1 µm to 5 mm) and smaller nanoplastics (NP; <1 µm). NPs may pose higher ecological risks than MPs. Various microscopic and spectroscopic techniques have been used to detect MPs, and the same methods have occasionally been used for NPs. However, they are not based on receptors, which provide high specificity in most biosensing applications. Receptor-based micro/nanoplastics (MNP) detection can provide high specificity, distinguishing MNPs from the environmental samples and, more importantly, identifying the plastic types. It can also offer a low limit of detection (LOD) required for environmental screening. Such receptors are expected to detect NPs specifically at the molecular level. This review categorizes the receptors into cells, proteins, peptides, fluorescent dyes, polymers, and micro/nanostructures. Detection techniques used with these receptors are also summarized and categorized. There is plenty of room for future research to test for broader classes of environmental samples and many plastic types, to lower the LOD, and to apply the current techniques for NPs. Portable and handheld MNP detection should also be demonstrated for field use since the current demonstrations primarily utilized laboratory instruments. Detection on microfluidic platforms will also be crucial in miniaturizing and automating the assay and, eventually, collecting an extensive database to support machine learning-based classification of MNP types.

Rapid, sensitive detection of PFOA with smartphone-based flow rate analysis utilizing competitive molecular interactions during capillary action.

Perfluorinated-alkyl substances (PFAS) pose an unmet threat to the public because they are not strictly monitored and regulated. Perfluorinated-carbon alkyl chains (PFOA), a type of PFAS, at 70 fg/µL is the current health and safety recommendation. Current testing methods for PFOA and PFAS chemicals include HPLC-MS/MS and molecularly imprinted polymers, which are expensive, time-consuming, and require training. In this work, PFOA and PFOS detection was performed on a paper microfluidic chip using competitive interactions between PFOA/PFOS, cellulose fibers, and various reagents (L-lysine, casein, and albumin). Such interactions altered the surface tension at the wetting front and, subsequently, the capillary flow rate. A smartphone captured the videos of this capillary action. The samples flowed through the channel in less than 2 min. Albumin worked the best in detecting PFOA, followed by casein. The detection limit was 10 ag/µL in DI water and 1 fg/µL in effluent (processed) wastewater. Specificity to other non-fluorocarbon surfactants was also tested, using anionic sodium dodecyl sulfate (SDS), non-ionic Tween 20, and cationic cetrimonium bromide (CTAB). A combination of the reagents successfully distinguished PFOA from all three surfactants at 100% accuracy. This low-cost, handheld assay can be an accessible alternative for rapid in situ estimation of PFOA concentration.

Part-per-Trillion Trace Selective Gas Detection Using Frequency Locked Whispering-Gallery Mode Microtoroids.

Rapid detection of toxic and hazardous gases at trace concentrations plays a vital role in industrial, battlefield, and laboratory scenarios. Of interest are both sensitive as well as highly selective sensors. Whispering-gallery mode (WGM) microresonator-based biochemical sensors are among the most sensitive sensors in existence due to their long photon confinement times. One main concern with these devices, however, is their selectivity toward specific classes of target analytes. Here, we employ frequency locked WGM microtoroid optical resonators covalently modified with various polymer coatings to selectively detect the chemical warfare agent surrogate diisopropyl methylphosphonate (DIMP) as well as the toxic industrial chemicals formaldehyde and ammonia at parts-per-trillion concentrations (304, 434, and 117 ppt, respectively). This is 1-2 orders of magnitude better than previously reported, depending on the target, except for pristine graphene and pristine carbon nanotube sensors, which demonstrate similar detection levels but in vacuum and without selectivity. Selective polymer coatings include polyethylene glycol for DIMP sensing, accessed by the modification of commercially available materials, and 3-(triethoxysilyl) propyl-terminated polyvinyl acetate (PVAc) for ammonia sensing. Notably, we developed for the first time an efficient one-pot procedure to access 3-(triethoxysilyl) propyl-terminated PVAc that utilizes cobalt-mediated living radical polymerization and a nitroxyl polymer-terminating agent. Alkaline hydrolysis of PVAc coatings to form polyvinyl alcohol coatings directly bound to the microtoroid proved to be reliable and reproducible, leading to WGM sensors capable of the rapid and selective detection of formaldehyde vapors. The selectivity of these three polymer coatings as sensing media was predicted, in part, based on their functional group content and known reactivity patterns with the target analytes. Furthermore, we demonstrate that microtoroids coated with a mixture of polymers can serve as an all-in-one sensor that can detect multiple agents. We anticipate that our results will facilitate rapid early detection of chemical agents, as well as their surrogates and precursors.

Cargo transport shapes the spatial organization of a microbial community.

The human microbiome is an assemblage of diverse bacteria that interact with one another to form communities. Bacteria in a given community are arranged in a 3D matrix with many degrees of freedom. Snapshots of the community display well-defined structures, but the steps required for their assembly are not understood. Here, we show that this construction is carried out with the help of gliding bacteria. Gliding is defined as the motion of cells over a solid or semisolid surface without the necessity of growth or the aid of pili or flagella. Genomic analysis suggests that gliding bacteria are present in human microbial communities. We focus on Capnocytophaga gingivalis, which is present in abundance in the human oral microbiome. Tracking of fluorescently labeled single cells and of gas bubbles carried by fluid flow shows that swarms of C. gingivalis are layered, with cells in the upper layers moving more rapidly than those in the lower layers. Thus, cells also glide on top of one another. Cells of nonmotile bacterial species attach to the surface of C. gingivalis and are propelled as cargo. The cargo cell moves along the length of a C. gingivalis cell, looping from one pole to the other. Multicolor fluorescent spectral imaging of cells of different live but nonmotile bacterial species reveals their long-range transport in a polymicrobial community. A swarm of C. gingivalis transports some nonmotile bacterial species more efficiently than others and helps to shape the spatial organization of a polymicrobial community.