Nanoparticle immunoagglutination Rayleigh scatter assay to complement microparticle immunoagglutination Mie scatter assay in a microfluidic device

Microparticle-Based Detection of Viruses

Surveillance of viral pathogens in both point-of-care and clinical settings is imperative to preventing the widespread propagation of disease-undetected viral outbreaks can pose dire health risks on a large scale. Thus, portable, accessible, and reliable biosensors are necessary for proactive measures. Polymeric microparticles have recently gained popularity for their size, surface area, and versatility, which make them ideal biosensing tools. This review cataloged recent investigations on polymeric microparticle-based detection platforms across eight virus families. These microparticles were used as labels for detection (often with fluorescent microparticles) and for capturing viruses for isolation or purification (often with magnetic microparticles). We also categorized all methods by the characteristics, materials, conjugated receptors, and size of microparticles. Current approaches were compared, addressing strengths and weaknesses in the context of virus detection. In-depth analyses were conducted for each virus family, categorizing whether the polymeric microparticles were used as labels, for capturing, or both. We also summarized the types of receptors conjugated to polymeric microparticles for each virus family.

Machine Learning Enhances the Performance of Bioreceptor-Free Biosensors

Since their inception, biosensors have frequently employed simple regression models to calculate analyte composition based on the biosensor's signal magnitude. Traditionally, bioreceptors provide excellent sensitivity and specificity to the biosensor. Increasingly, however, bioreceptor-free biosensors have been developed for a wide range of applications. Without a bioreceptor, maintaining strong specificity and a low limit of detection have become the major challenge. Machine learning (ML) has been introduced to improve the performance of these biosensors, effectively replacing the bioreceptor with modeling to gain specificity. Here, we present how ML has been used to enhance the performance of these bioreceptor-free biosensors. Particularly, we discuss how ML has been used for imaging, Enose and Etongue, and surface-enhanced Raman spectroscopy (SERS) biosensors. Notably, principal component analysis (PCA) combined with support vector machine (SVM) and various artificial neural network (ANN) algorithms have shown outstanding performance in a variety of tasks. We anticipate that ML will continue to improve the performance of bioreceptor-free biosensors, especially with the prospects of sharing trained models and cloud computing for mobile computation. To facilitate this, the biosensing community would benefit from increased contributions to open-access data repositories for biosensor data.

Smartphone-Based Paper Microfluidic Immunoassay of Salmonella and E. coli

Previous studies from our lab have created a simple procedure for single-cell count of bacteria on a paper chip platform using optical detection from a smartphone. The procedure and steps employed are outlined along with the lessons learned and details of certain steps and how the design was optimized. Smartphone optical detection is easy to use, low cost, and potentially field deployable, which can be useful for early and rapid detection of pathogens. Smartphone imaging of a paper microfluidic chip preloaded with antibody-conjugated particles provides an adaptable platform for detection of different bacterial targets. The paper microfluidic chip was fabricated with a multichannel design. Each channel was preloaded with either a negative control of bovine serum albumin (BSA) conjugated particles, anti-Salmonella Typhimurium-conjugated particles with varying amounts (to cover different ranges of assay), or anti-Escherichia coli-conjugated particles. Samples were introduced to the paper microfluidic chip using pipetting. Antigens of Salmonella Typhimurium traveled through the channel by capillary action confined within the paper fibers surrounded by the hydrophobic barrier. The paper channel was observed to act as a filter for unwanted particles and contaminants found in field samples. Serial dilutions of known concentrations of bacterial targets were also tested using this procedure to construct a standard curve prior to the assays. The antibody-conjugated particles were able to immunoagglutinate which was quantified through evaluation of Mie scatter intensity. This Mie scattering was quantified in images taken with a smartphone at an optimized angle and distance. Mie scatter simulation provided a method of optimizing the experimental setup and could translate easily to other types of target sample matrices. A smartphone application was developed to help the user position the smartphone optimally in relation to the paper microfluidic chip. The application integrated both image capturing capability and a simple image processing algorithm that calculated bacteria concentrations. The detection limit was at a single-cell level with a total assay time ranging from 90 to less than 60 s depending on the target.

On-chip immuno-agglutination assay based on a dynamic magnetic bead clump and a sheath-less flow cytometry

Immunoagglutination assay is a promising approach for the detection of waterborne analytes like virus, cells, proteins with its advantages such as a smaller amount of reagents and easier operation. This paper presents a microfluidic agglutination assay on which all the assay processes including analyte capture, agglutination, and detection are performed. The chip integrates an on-chip pump for sample loading, a dynamic magnetic bead (MB) clump for analyte capture and agglutination, and a sheath-less flow cytometry for particle detection, sizing, and counting. The chip is tested with streptavidin-coated MBs and biotinylated bovine serum albumin as a model assay, which realizes a limit of detection (LOD) of 1 pM. Then, an antigen/antibody assay using rabbit IgG and goat anti-rabbit IgG coated MBs is tested and a LOD of 5.5 pM is achieved. At last, human ferritin in 10% fetal bovine serum is tested with Ab-functionalized MBs and the detection achieves a LOD of 8.5 pM. The whole procedure takes only 10 min in total.

Applications of nanomaterials as vaccine adjuvants

Vaccine adjuvants are applied to amplify the recipient's specific immune responses against pathogen infection or malignancy. A new generation of adjuvants is being developed to meet the demands for more potent antigen-specific responses, specific types of immune responses, and a high margin of safety. Nanotechnology provides a multifunctional stage for the integration of desired adjuvant activities performed by the building blocks of tailor-designed nanoparticles. Using nanomaterials for antigen delivery can provide high bioavailability, sustained and controlled release profiles, and targeting and imaging properties resulting from manipulation of the nanomaterials' physicochemical properties. Moreover, the inherent immune-regulating activity of particular nanomaterials can further promote and shape the cellular and humoral immune responses toward desired types. The combination of both the delivery function and immunomodulatory effect of nanomaterials as adjuvants is thought to largely benefit the immune outcomes of vaccination. In this review, we will address the current achievements of nanotechnology in the development of novel adjuvants. The potential mechanisms by which nanomaterials impact the immune responses to a vaccine and how physicochemical properties, including size, surface charge and surface modification, impact their resulting immunological outcomes will be discussed. This review aims to provide concentrated information to promote new insights for the development of novel vaccine adjuvants.

Droplet-based immunoassay on a 'sticky' nanofibrous surface for multiplexed and dual detection of bacteria using smartphones

We have developed a rapid, sensitive, and specific droplet-based immunoassay for the detection of Escherichia coli and Salmonella within a single-pipetted sample. Polycaprolactone (PCL) electrospun fibers on indium-tin-oxide (ITO) glass provide a sufficient surface to render a non-slip droplet condition, and while the PCL fibers lend a local hydrophilicity (contact angle θ=74°) for sufficient sub-micron particle adhesion, air pockets within the fibers lend an apparent hydrophobicity. Overall, the contact angle of water on this electrospun surface is 119°, and the air pockets cause the droplet to be completely immobile and resistant to movement, protecting it from external vibration. By using both anti-E. coli conjugated, 510 nm diameter green fluorescent particles (480 nm excitation and 520 nm emission) and anti-Salmonella conjugated, 400 nm diameter red fluorescent particles (640 nm excitation and 690 nm emission), we can detect multiple targets in a single droplet. Using appropriate light sources guided by fiber optics, we determined a detection limit of 10(2) CFU mL(-1). Immunoagglutination can be observed under a fluorescence microscope. Fluorescence detection (at the emission wavelength) of immunoagglutination was maximum at 90° from the incident light, while light scattering (at the excitation wavelength) was still present and behaved similarly, indicating the ability of double detection, greatly improving credibility and reproducibility of the assay. A power function (light intensity) simulation of elastic Mie scatter confirmed that both fluorescence and light scattering were present. Due to the size of the fluorescent particles relative to their incident excitation wavelengths, Mie scatter conditions were observed, and fluorescence signals show a similar trend to light scattering signals. Smartphone detection was included for true portable detection, in which the high contact angle pinning of the droplet makes this format re-usable and re-configurable.

Rapid and reagentless detection of microbial contamination within meat utilizing a smartphone-based biosensor

A smartphone-utilized biosensor was developed for detecting microbial spoilage on ground beef, without using antibodies, microbeads or any other reagents, towards a preliminary screening tool for microbial contamination on meat products, and potentially towards wound infection. Escherichia coli K12 solutions (10(1)-10(8) CFU/mL) were added to ground beef products to simulate microbial spoilage. An 880 nm near infrared LED was irradiated perpendicular to the surface of ground beef, and the scatter signals at various angles were evaluated utilizing the gyro sensor and the digital camera of a smartphone. The angle that maximized the Mie scatter varied by the E. coli concentration: 15° for 10(8) CFU/mL, 30° for 10(4) CFU/mL, and 45° for 10 CFU/mL, etc. SEM and fluorescence microscopy experiments revealed that the antigens and cell fragments from E. coli bonded preferably to the fat particles within meat, and the size and morphologies of such aggregates varied by the E. coli concentration.

Smartphone quantifies Salmonella from paper microfluidics

Smartphone-based optical detection is a potentially easy-to-use, handheld, true point-of-care diagnostic tool for the early and rapid detection of pathogens. Paper microfluidics is a low-cost, field-deployable, and easy-to-use alternative to conventional microfluidic devices. Most paper-based microfluidic assays typically utilize dyes or enzyme-substrate binding, while bacterial detection on paper microfluidics is rare. We demonstrate a novel application of smartphone-based detection of Salmonella on paper microfluidics. Each paper microfluidic channel was pre-loaded with anti-Salmonella Typhimurium and anti-Escherichia coli conjugated submicroparticles. Dipping the paper microfluidic device into the Salmonella solutions led to the antibody-conjugated particles that were still confined within the paper fibers to immunoagglutinate. The extent of immunoagglutination was quantified by evaluating Mie scattering from the digital images taken at an optimized angle and distance with a smartphone. A smartphone application was designed and programmed to allow the user to position the smartphone at an optimized angle and distance from the paper microfluidic device, and a simple image processing algorithm was implemented to calculate and display the bacterial concentration on the smartphone. The detection limit was single-cell-level and the total assay time was less than one minute.

Lab-on-a-chip pathogen sensors for food safety

There have been a number of cases of foodborne illness among humans that are caused by pathogens such as Escherichia coli O157:H7, Salmonella typhimurium, etc. The current practices to detect such pathogenic agents are cell culturing, immunoassays, or polymerase chain reactions (PCRs). These methods are essentially laboratory-based methods that are not at all real-time and thus unavailable for early-monitoring of such pathogens. They are also very difficult to implement in the field. Lab-on-a-chip biosensors, however, have a strong potential to be used in the field since they can be miniaturized and automated; they are also potentially fast and very sensitive. These lab-on-a-chip biosensors can detect pathogens in farms, packaging/processing facilities, delivery/distribution systems, and at the consumer level. There are still several issues to be resolved before applying these lab-on-a-chip sensors to field applications, including the pre-treatment of a sample, proper storage of reagents, full integration into a battery-powered system, and demonstration of very high sensitivity, which are addressed in this review article. Several different types of lab-on-a-chip biosensors, including immunoassay- and PCR-based, have been developed and tested for detecting foodborne pathogens. Their assay performance, including detection limit and assay time, are also summarized. Finally, the use of optical fibers or optical waveguide is discussed as a means to improve the portability and sensitivity of lab-on-a-chip pathogen sensors.

Cell-phone-based measurement of TSH using Mie scatter optimized lateral flow assays

Semi-quantitative thyr oid stimulating hormone (TSH) lateral flow immunochromatographic assays (LFA) are used to screen for serum TSH concentration >5 mIUL(-1) (hypothyroidism). The LFA format, however, is unable to measure TSH in the normal range or detect suppressed levels of TSH (<0.4 mIU L(-1); hyperthyroidism). In fact, it does not provide quantitative TSH values at all. Obtaining quantitative TSH results, especially in the low concentration range, has until now required the use of centralized clinical laboratories which require specimen transport, specialized equipment and personnel, and result in increased cost and delays in the timely reporting of important clinical results. We have conducted a series of experiments to develop and validate an optical system and image analysis algorithm based upon a cell phone platform. It is able to provide point-of-care quantitative TSH results with a high level of sensitivity and reproducibility comparable to that of a clinical laboratory-based third-generation TSH immunoassay. Our research approach uses the methodology of the optimized Rayleigh/Mie scatter detection by taking into consideration the optical characteristics of a nitrocellulose membrane and gold nanoparticles on an LFA for quantifying TSH levels. Using a miniature spectrometer, LED light source, and optical fibers on a rotating benchtop apparatus, the light intensity from different angles of incident light and angles of detection to the LFA were measured. The optimum angles were found that the minimized Mie scattering from nitrocellulose membrane, consequently maximizes the Rayleigh scatter detection from the gold nanoparticles in the LFA bands. Using the results from the benchtop apparatus, a cell-phone-based apparatus was designed which utilized the embedded flash in the cell phone camera as the light source, piped the light with an optical fiber from the flash through a collimating lens to illuminate the LFA. Quantification of TSH was performed in an iOS application directly on the phone and verified using the code written in MATLAB. The limit of detection of the system was determined to be 0.31 mIU L(-1) (never achieved before on an LFA format), below the commonly accepted minimum concentration of 0.4 mIU L(-1) indicating clinical significance of hyperthyroidism. The system was further evaluated using human serum showing an accurate and reproducible platform for rapid and point-of-care quantification of TSH using a cell phone.

Direct and sensitive detection of foodborne pathogens within fresh produce samples using a field-deployable handheld device

Direct and sensitive detection of foodborne pathogens from fresh produce samples was accomplished using a handheld lab-on-a-chip device, requiring little to no sample processing and enrichment steps for a near-real-time detection and truly field-deployable device. The detection of Escherichia coli K12 and O157:H7 in iceberg lettuce was achieved utilizing optimized Mie light scatter parameters with a latex particle immunoagglutination assay. The system exhibited good sensitivity, with a limit of detection of 10 CFU mL(-1) and an assay time of <6 min. Minimal pretreatment with no detrimental effects on assay sensitivity and reproducibility was accomplished with a simple and cost-effective KimWipes filter and disposable syringe. Mie simulations were used to determine the optimal parameters (particle size d, wavelength λ, and scatter angle θ) for the assay that maximize light scatter intensity of agglutinated latex microparticles and minimize light scatter intensity of the tissue fragments of iceberg lettuce, which were experimentally validated. This introduces a powerful method for detecting foodborne pathogens in fresh produce and other potential sample matrices. The integration of a multi-channel microfluidic chip allowed for differential detection of the agglutinated particles in the presence of the antigen, revealing a true field-deployable detection system with decreased assay time and improved robustness over comparable benchtop systems. Additionally, two sample preparation methods were evaluated through simulated field studies based on overall sensitivity, protocol complexity, and assay time. Preparation of the plant tissue sample by grinding resulted in a two-fold improvement in scatter intensity over washing, accompanied with a significant increase in assay time: ∼5 min (grinding) versus ∼1 min (washing). Specificity studies demonstrated binding of E. coli O157:H7 EDL933 to only O157:H7 antibody conjugated particles, with no cross-reactivity to K12. This suggests the adaptability of the system for use with a wide variety of pathogens, and the potential to detect in a variety of biological matrices with little to no sample pretreatment.