Identifying antibiotic-resistant strains via cell sorting and elastic-light-scatter phenotyping.

The proliferation and dissemination of antimicrobial-resistant bacteria is an increasingly global challenge and is attributed mainly to the excessive or improper use of antibiotics. Currently, the gold-standard phenotypic methodology for detecting resistant strains is agar plating, which is a time-consuming process that involves multiple subculturing steps. Genotypic analysis techniques are fast, but they require pure starting samples and cannot differentiate between viable and non-viable organisms. Thus, there is a need to develop a better method to identify and prevent the spread of antimicrobial resistance. This work presents a novel method for detecting and identifying antibiotic-resistant strains by combining a cell sorter for bacterial detection and an elastic-light-scattering method for bacterial classification. The cell sorter was equipped with safety mechanisms for handling pathogenic organisms and enabled precise placement of individual bacteria onto an agar plate. The patterning was performed on an antibiotic-gradient plate, where the growth of colonies in sections with high antibiotic concentrations confirmed the presence of a resistant strain. The antibiotic-gradient plate was also tested with an elastic-light-scattering device where each colony's unique colony scatter pattern was recorded and classified using machine learning for rapid identification of bacteria. Sorting and patterning bacteria on an antibiotic-gradient plate using a cell sorter reduced the number of subculturing steps and allowed direct qualitative binary detection of resistant strains. Elastic-light-scattering technology is a rapid, label-free, and non-destructive method that permits instantaneous classification of pathogenic strains based on the unique bacterial colony scatter pattern. KEY POINTS: • Individual bacteria cells are placed on gradient agar plates by a cell sorter • Laser-light scatter patterns are used to recognize antibiotic-resistant organisms • Scatter patterns formed by colonies correspond to AMR-associated phenotypes.

Surface Environment and Energy Density Effects on the Detection and Disinfection of Microorganisms Using a Portable Instrument.

Real-time detection and disinfection of foodborne pathogens are important for preventing foodborne outbreaks and for maintaining a safe environment for consumers. There are numerous methods for the disinfection of hazardous organisms, including heat treatment, chemical reaction, filtration, and irradiation. This report evaluated a portable instrument to validate its simultaneous detection and disinfection capability in typical laboratory situations. In this challenging study, three gram-negative and two gram-positive microorganisms were used. For the detection of contamination, inoculations of various concentrations were dispensed on three different surface types to estimate the performance for minimum-detectable cell concentration. Inoculations higher than 103~104 CFU/mm2 and 0.15 mm of detectable contaminant size were estimated to generate a sufficient level of fluorescence signal. The evaluation of disinfection efficacy was conducted on three distinct types of surfaces, with the energy density of UVC light (275-nm) ranging from 4.5 to 22.5 mJ/cm2 and the exposure time varying from 1 to 5 s. The study determined the optimal energy dose for each of the microorganisms species. In addition, surface characteristics may also be an important factor that results in different inactivation efficacy. These results demonstrate that the proposed portable device could serve as an in-field detection and disinfection unit in various environments, and provide a more efficient and user-friendly way of performing disinfection on large surface areas.

Bacterial Colony Phenotyping with Hyperspectral Elastic Light Scattering Patterns.

The elastic light-scatter (ELS) technique, which detects and discriminates microbial organisms based on the light-scatter pattern of their colonies, has demonstrated excellent classification accuracy in pathogen screening tasks. The implementation of the multispectral approach has brought further advantages and motivated the design and validation of a hyperspectral elastic light-scatter phenotyping instrument (HESPI). The newly developed instrument consists of a supercontinuum (SC) laser and an acousto-optic tunable filter (AOTF). The use of these two components provided a broad spectrum of excitation light and a rapid selection of the wavelength of interest, which enables the collection of multiple spectral patterns for each colony instead of relying on single band analysis. The performance was validated by classifying microflora of green-leafed vegetables using the hyperspectral ELS patterns of the bacterial colonies. The accuracy ranged from 88.7% to 93.2% when the classification was performed with the scattering pattern created at a wavelength within the 473-709 nm region. When all of the hyperspectral ELS patterns were used, owing to the vastly increased size of the data, feature reduction and selection algorithms were utilized to enhance the robustness and ultimately lessen the complexity of the data collection. A new classification model with the feature reduction process improved the overall classification rate to 95.9%.

Hybrid Raman and Laser-Induced Breakdown Spectroscopy for Food Authentication Applications.

The issue of food fraud has become a significant global concern as it affects both the quality and safety of food products, ultimately resulting in the loss of customer trust and brand loyalty. To address this problem, we have developed an innovative approach that can tackle various types of food fraud, including adulteration, substitution, and dilution. Our methodology utilizes an integrated system that combines laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy. Although both techniques emerged as valuable tools for food analysis, they have until now been used separately, and their combined potential in food fraud has not been thoroughly tested. The aim of our study was to demonstrate the potential benefits of integrating Raman and LIBS modalities in a portable system for improved product classification and subsequent authentication. In pursuit of this objective, we designed and tested a compact, hybrid Raman/LIBS system, which exhibited distinct advantages over the individual modalities. Our findings illustrate that the combination of these two modalities can achieve higher accuracy in product classification, leading to more effective and reliable product authentication. Overall, our research highlights the potential of hybrid systems for practical applications in a variety of industries. The integration and design were mainly focused on the detection and characterization of both elemental and molecular elements in various food products. Two different sets of solid food samples (sixteen Alpine-style cheeses and seven brands of Arabica coffee beans) were chosen for the authentication analysis. Class detection and classification were accomplished through the use of multivariate feature selection and machine-learning procedures. The accuracy of classification was observed to improve by approximately 10% when utilizing the hybrid Raman/LIBS spectra, as opposed to the analysis of spectra from the individual methods. This clearly demonstrates that the hybrid system can significantly improve food authentication accuracy while maintaining the portability of the combined system. Thus, the successful implementation of a hybrid Raman-LIBS technique is expected to contribute to the development of novel portable devices for food authentication in food as well as other various industries.

Detection of Salmonella Typhimurium with Gold Nanoparticles Using Quartz Crystal Microbalance Biosensor.

Demonstration of the Salmonella Typhimurium detection system was shown utilizing a quartz crystal microbalance (QCM) biosensor and signal enhancement by gold nanoparticles. In this study, a benchtop system of a QCM biosensor was utilized for the detection of Salmonella Typhimurium. It was designed with a peristaltic pump system to achieve immobilization of antibodies, detection of Salmonella, and the addition of gold nanoparticles to the sensor. As a series of biochemical solutions were introduced to the surface, the proposed system was able to track the changes in the resonant frequency which were proportional to the variations of mass on the sensor. For antibody immobilization, polyclonal antibodies were immobilized via self-assembled monolayers to detect Salmonella O-antigen. Subsequently, Salmonella Typhimurium was detected by antibodies and the average frequency before and after detecting Salmonella was compared. The highest frequency shifts were −26.91 Hz for 109 CFU/mL while the smallest frequency shift was −3.65 Hz corresponding to 103 CFU/mL. For the specificity tests, non-Salmonella samples such as E. coli, Listeria, and Staphylococcus resulted in low cross-reactivity. For signal amplification, biotinylated antibodies reacted to Salmonella followed by streptavidin­100 nm AuNPs through biotin-avidin interaction. The frequency shifts of 103 CFU/mL showed −28.04 Hz, and consequently improved the limit of detection.

Development of a Smartphone-Integrated Reflective Scatterometer for Bacterial Identification.

We present a smartphone-based bacterial colony phenotyping instrument using a reflective elastic light scattering (ELS) pattern and the resolving power of the new instrument. The reflectance-type device can acquire ELS patterns of colonies on highly opaque media as well as optically dense colonies. The novel instrument was built using a smartphone interface and a 532 nm diode laser, and these essential optical components made it a cost-effective and portable device. When a coherent and collimated light source illuminated a bacterial colony, a reflective ELS pattern was created on the screen and captured by the smartphone camera. The collected patterns whose shapes were determined by the colony morphology were then processed and analyzed to extract distinctive features for bacterial identification. For validation purposes, the reflective ELS patterns of five bacteria grown on opaque growth media were measured with the proposed instrument and utilized for the classification. Cross-validation was performed to evaluate the classification, and the result showed an accuracy above 94% for differentiating colonies of E. coli, K. pneumoniae, L. innocua, S. enteritidis, and S. aureus.

Quantum approach for nanoparticle fluorescence by sub-ns photon detection.

Well defined detection and analysis of nanoparticle-sized samples such as extracellular vesicles or viruses may be important for potential disease diagnostics. However, using conventional flow-cytometry optical methods to evaluate such small particles is quite challenging. The reason is that the particle is smaller than the diffraction limit, making detection difficult. An alternative approach is fluorescence detection via conjugated fluorochromes attached to the nanoparticles; the challenge in this case is the limitation imposed upon detection of a very small number of emitted photons buried in high background photon counts. Emitted fluorescence is described by the well-known equation kf = σa I Q, which describes the emitted fluorescence rate (kf) (photons/s) as the multiplication of molecular absorption cross section(σa), excitation intensity (I), and quantum yield (Q). In addition, the excitation rate is equal to 1/t, which is the inverse of the lifetime of several ns representing the most typical conjugated fluorescent molecules used in flow cytometry. We recently developed a sub-ns photon sensor that is faster than most fluorescence lifetimes, since sub-ns speed is a critically important parameter for the separation of individual emitted photons. Based on our observation of fluorescence and background levels on typical commercial flow cytometers it is evident that a significant component of the background is induced by water-molecular vibrations. Therefore, understanding what constitutes all the components that contribute to the signals we measure in flow cytometry would help in defining what we currently call "background signals." We attempted to define a theoretical model to try to unravel these issues. This model was based on use of a reflective dry surface in the absence of water molecules. Our objective was to determine if it is possible to minimize background and enhance signal, and to provide valuable information on the contributing components of the signals collected. In order to test this model, we tested a single dried particle 50 nm in diameter on a reflective surface with minimum background. While this is clearly not a standard biological system, our results suggest that this quantum approach closely follows established photon base theory. Our goal was to define the parameters for practical nanoparticle-fluorescence analysis while enhancing our knowledge of the contribution of background properties.

Detection of E. coli labeled with metal-conjugated antibodies using lateral-flow assay and laser-induced breakdown spectroscopy.

This study explores the adoption of laser-induced breakdown spectroscopy (LIBS) for the analysis of lateral-flow immunoassays (LFIAs). Gold (Au) nanoparticles are standard biomolecular labels among LFIAs, typically detected via colorimetric means. A wide diversity of lanthanide-complexed polymers (LCPs) are also used as immunoassay labels but are inapt for LFIAs due to lab-bound detection instrumentation. This is the first study to show the capability of LIBS to transition LCPs into the realm of LFIAs, and one of the few to apply LIBS to biomolecular label detection in complete immunoassays. Initially, an in-house LIBS system was optimized to detect an Au standard through a process of line selection across acquisition delay times, followed by determining limit of detection (LOD). The optimized LIBS system was applied to Au-labeled Escherichia coli detection on a commercial LFIA; comparison with colorimetric detection yielded similar LODs (1.03E4 and 8.890E3 CFU/mL respectively). Optimization was repeated with lanthanide standards to determine if they were viable alternatives to Au labels. It was found that europium (Eu) and ytterbium (Yb) may be more favorable biomolecular labels than Au. To test whether Eu-complexed polymers conjugated to antibodies could be used as labels in LFIAs, the conjugates were successfully applied to E. coli detection in a modified commercial LFIA. The results suggest interesting opportunities for creating highly multiplexed LFIAs. Multiplexed, sensitive, portable, and rapid LIBS detection of biomolecules concentrated and labeled on LFIAs is highly relevant for applications like food safety, where in-field food contaminant detection is critical. Graphical abstract.

Alternatives to current flow cytometry data analysis for clinical and research studies.

Flow cytometry has well-established methods for data analysis based on traditional data collection techniques. These techniques typically involved manual insertion of tube samples into an instrument that, historically, could only measure 1-3 colors. The field has since evolved to incorporate new technologies for faster and highly automated sample preparation and data collection. For example, the use of microwell plates on benchtop instruments is now a standard on virtually every new instrument, and so users can easily accumulate multiple data sets quickly. Further, because the user must carefully define the layout of the plate, this information is already defined when considering the analytical process, expanding the opportunities for automated analysis. Advances in multi-parametric data collection, as demonstrated by the development of hyperspectral flow-cytometry, 20-40 color polychromatic flow cytometry, and mass cytometry (CyTOF), are game-changing. As data and assay complexity increase, so too does the complexity of data analysis. Complex data analysis is already a challenge to traditional flow cytometry software. New methods for reviewing large and complex data sets can provide rapid insight into processes difficult to define without more advanced analytical tools. In settings such as clinical labs where rapid and accurate data analysis is a priority, rapid, efficient and intuitive software is needed. This paper outlines opportunities for analysis of complex data sets using examples of multiplexed bead-based assays, drug screens and cell cycle analysis - any of which could become integrated into the clinical environment.

Spectral analysis and sorting of microbial organisms using a spectral sorter.

This chapter discusses the problems related to the application of conventional flow cytometers to microbiology. To address some of those limitations, the concept of spectral flow cytometry is introduced and the advantages over conventional flow cytometry for bacterial sorting are presented. We demonstrate by using ThermoFisher's Bigfoot spectral sorter where the spectral signatures of different stains for staining bacteria are demonstrated with an example of performing unmixing on spectral datasets. In addition to the Bigfoot's spectral analysis, the special biosafety features of this instrument are discussed. Utilizing these biosafety features, the sorting and patterning at the single cell level is optimized using non-pathogenic bacteria. Finally, the chapter is concluded by presenting a novel, label free, non-destructive, and rapid phenotypic method called Elastic Light Scattering (ELS) technology for identification of the patterned bacterial cells based on their unique colony scatter patterns.

Photodynamic treatment of Staphylococcus aureus with non-iron hemin analogs in the presence of hydrogen peroxide.

Bacteria subjected to antiseptic or antibiotic stress often develop tolerance, a trait that can lead to permanent resistance. To determine whether photodynamic agents could be used to counter tolerance, we evaluated three non-iron hemin analogs (M-PpIX; M = Al, Ga, In) as targeted photosensitizers for antimicrobial photodynamic inactivation (aPDI) following exposure to sublethal H2O2. Al-PpIX is an active producer of ROS whereas Ga- and In-PpIX are more efficient at generating singlet oxygen. Al- and Ga-PpIX are highly potent aPDI agents against S. aureus and methicillin-resistant strains (MRSA) with antimicrobial activity (3 log reduction in colony-forming units) at nanomolar concentrations. The aPDI activities of Al- and Ga-PpIX against S. aureus were tested in the presence of 1 mM H2O2 added at different stages of growth. Bacteria exposed to H2O2 during log-phase growth were less susceptible to aPDI but bacteria treated with H2O2 in their postgrowth phase exhibited aPDI hypersensitivity, with no detectable colony growth after treatment with 15 nM Ga-PpIX.

Mouse and human islets survive and function after coating by biosilicification.

Inorganic materials have properties that can be advantageous in bioencapsulation for cell transplantation. Our aim was to engineer a hybrid inorganic/soft tissue construct by inducing pancreatic islets to grow an inorganic shell. We created pancreatic islets surrounded by porous silica, which has potential application in the immunoprotection of islets in transplantation therapies for type 1 diabetes. The new method takes advantage of the islet capsule surface as a template for silica formation. Mouse and human islets were exposed to medium containing saturating silicic acid levels for 9-15 min. The resulting tissue constructs were then cultured for up to 4 wk under normal conditions. Scanning electron microscopy and energy dispersive X-ray spectroscopy was used to monitor the morphology and elemental composition of the material at the islet surface. A cytokine assay was used to assess biocompatibility with macrophages. Islet survival and function were assessed by confocal microscopy, glucose-stimulated insulin release assays, oxygen flux at the islet surface, expression of key genes by RT-PCR, and syngeneic transplant into diabetic mice.

Wallace H. Coulter: decades of invention and discovery.

Only a few inventors can be said to have made as great an impact on mankind as Wallace Coulter. His inquisitive mind and ability to see well beyond what existed served him well for 40 years of inventing. So many of the fundamental tools that exist today in the area of hematology were derived from or driven by Coulter's inventions that he could be called the most technological innovator in the field of modern hematology. In achieving these discoveries Wallace Coulter was clearly capable of visualizing future opportunities that few others recognized. His vision was combined with an uncanny ability to translate his ideas into products. He developed a large number of tools that shaped the fields of cytometry, image analysis, and industrial materials. His understanding of the future power of computation drove him to link these technologies in a unique way. In the end, Coulter shaped the technologies that ultimately drove hematology in a new direction, one that remains on a critical pathway linking technology innovation all the way to true translational impact. It was said of Henry Ford that "[h]e has no notion that wealth has made him great, and any one who is imprest merely by his wealth bores him. In his personal contacts he likes to dodge the subject. He would prefer to talk with a machinist about machinery, or with somebody who likes birds about birds. In these contacts, he asks no deference; and if he gets it, he suspects it is mere deference to wealth, and that ends his interest."(1) The same could be said of Wallace Coulter, who, like Ford, understood the concepts of mass production and customer service. Coulter had the ability to recognize the opportunity and fulfill the need for development of a blood-cell counter that could be placed in every pathology laboratory, and in so doing transformed a field from a qualitative to a quantitative environment. Every person who has ever entered a medical lab, hospital, or doctor's office has felt the impact of Coulter's discovery.

Flow Cytometry: The Next Revolution.

Unmasking the subtleties of the immune system requires both a comprehensive knowledge base and the ability to interrogate that system with intimate sensitivity. That task, to a considerable extent, has been handled by an iterative expansion in flow cytometry methods, both in technological capability and also in accompanying advances in informatics. As the field of fluorescence-based cytomics matured, it reached a technological barrier at around 30 parameter analyses, which stalled the field until spectral flow cytometry created a fundamental transformation that will likely lead to the potential of 100 simultaneous parameter analyses within a few years. The simultaneous advance in informatics has now become a watershed moment for the field as it competes with mature systematic approaches such as genomics and proteomics, allowing cytomics to take a seat at the multi-omics table. In addition, recent technological advances try to combine the speed of flow systems with other detection methods, in addition to fluorescence alone, which will make flow-based instruments even more indispensable in any biological laboratory. This paper outlines current approaches in cell analysis and detection methods, discusses traditional and microfluidic sorting approaches as well as next-generation instruments, and provides an early look at future opportunities that are likely to arise.

Rapid Food Authentication Using a Portable Laser-Induced Breakdown Spectroscopy System.

Laser-induced breakdown spectroscopy (LIBS) is an atomic-emission spectroscopy technique that employs a focused laser beam to produce microplasma. Although LIBS was designed for applications in the field of materials science, it has lately been proposed as a method for the compositional analysis of agricultural goods. We deployed commercial handheld LIBS equipment to illustrate the performance of this promising optical technology in the context of food authentication, as the growing incidence of food fraud necessitates the development of novel portable methods for detection. We focused on regional agricultural commodities such as European Alpine-style cheeses, coffee, spices, balsamic vinegar, and vanilla extracts. Liquid examples, including seven balsamic vinegar products and six representatives of vanilla extract, were measured on a nitrocellulose membrane. No sample preparation was required for solid foods, which consisted of seven brands of coffee beans, sixteen varieties of Alpine-style cheeses, and eight different spices. The pre-processed and standardized LIBS spectra were used to train and test the elastic net-regularized multinomial classifier. The performance of the portable and benchtop LIBS systems was compared and described. The results indicate that field-deployable, portable LIBS devices provide a robust, accurate, and simple-to-use platform for agricultural product verification that requires minimal sample preparation, if any.

Development of an Anti-canine PD-L1 Antibody and Caninized PD-L1 Mouse Model as Translational Research Tools for the Study of Immunotherapy in Humans.

Immune checkpoint blockade therapy, one of the most promising cancer immunotherapies, has shown remarkable clinical impact in multiple cancer types. Despite the recent success of immune checkpoint blockade therapy, however, the response rates in patients with cancer are limited (∼20%-40%). To improve the success of immune checkpoint blockade therapy, relevant preclinical animal models are essential for the development and testing of multiple combination approaches and strategies. Companion dogs naturally develop several types of cancer that in many respects resemble clinical cancer in human patients. Therefore, the canine studies of immuno-oncology drugs can generate knowledge that informs and prioritizes new immuno-oncology therapy in humans. The challenge has been, however, that immunotherapeutic antibodies targeting canine immune checkpoint molecules such as canine PD-L1 (cPD-L1) have not been commercially available. Here, we developed a new cPD-L1 antibody as an immuno-oncology drug and characterized its functional and biological properties in multiple assays. We also evaluated the therapeutic efficacy of cPD-L1 antibodies in our unique caninized PD-L1 mice. Together, these in vitro and in vivo data, which include an initial safety profile in laboratory dogs, support development of this cPD-L1 antibody as an immune checkpoint inhibitor for studies in dogs with naturally occurring cancer for translational research. Our new therapeutic antibody and caninized PD-L1 mouse model will be essential translational research tools in raising the success rate of immunotherapy in both dogs and humans. Significance: Our cPD-L1 antibody and unique caninized mouse model will be critical research tools to improve the efficacy of immune checkpoint blockade therapy in both dogs and humans. Furthermore, these tools will open new perspectives for immunotherapy applications in cancer as well as other autoimmune diseases that could benefit a diverse and broader patient population.

Hyperspectral cytometry at the single-cell level using a 32-channel photodetector.

Despite recent progress in cell-analysis technology, rapid classification of cells remains a very difficult task. Among the techniques available, flow cytometry (FCM) is considered especially powerful, because it is able to perform multiparametric analyses of single biological particles at a high flow rate-up to several thousand particles per second. Moreover, FCM is nondestructive, and flow cytometric analysis can be performed on live cells. The current limit for simultaneously detectable fluorescence signals in FCM is around 8-15 depending upon the instrument. Obtaining multiparametric measurements is a very complex task, and the necessity for fluorescence spectral overlap compensation creates a number of additional difficulties to solve. Further, to obtain well-separated single spectral bands a very complex set of optical filters is required. This study describes the key components and principles involved in building a next-generation flow cytometer based on a 32-channel PMT array detector, a phase-volume holographic grating, and a fast electronic board. The system is capable of full-spectral data collection and spectral analysis at the single-cell level. As demonstrated using fluorescent microspheres and lymphocytes labeled with a cocktail of antibodies (CD45/FITC, CD4/PE, CD8/ECD, and CD3/Cy5), the presented technology is able to simultaneously collect 32 narrow bands of fluorescence from single particles flowing across the laser beam in <5 µs. These 32 discrete values provide a proxy of the full fluorescence emission spectrum for each single particle (cell). Advanced statistical analysis has then been performed to separate the various clusters of lymphocytes. The average spectrum computed for each cluster has been used to characterize the corresponding combination of antibodies, and thus identify the various lymphocytes subsets. The powerful data-collection capabilities of this flow cytometer open up significant opportunities for advanced analytical approaches, including spectral unmixing and unsupervised or supervised classification.