Bacteroidales as a fecal contamination indicator in fresh produce industry: A baseline measurement.

Foodborne outbreaks caused by fecal contamination of fresh produce represent a serious concern to public health and the economy. As the consumption of fresh produce increases, public health officials and organizations have pushed for improvements in food safety procedures and environmental assessments to reduce the risk of contamination. Visual inspections and the establishment of "buffer zones" between animal feeding operations and producing fields are the current best practices for environmental assessments. However, a generalized distance guideline and visual inspections may not be enough to account for all environmental risk variables. Here, we report a baseline measurement surveying the background Bacteroidales concentration, as a quantitative fecal contamination indicator, in California's Salinas Valley. We collected a total of 1632 samples from two romaine lettuce commercial fields at the time of harvesting through two seasons in a year. The quantification of Bacteroidales concentration was performed using qPCR, revealing a notably low concentration (0-2.00 copies/cm2) in the commercial fields. To further enhance the applicability of our findings, we developed a user-friendly method for real-world fecal contamination risk assessment that seamlessly integrates with industry practices. Through the generation of heatmaps that visually illustrate varying risk levels across fields, this approach can identify site-specific risks and offer fresh produce stakeholders a more comprehensive understanding of their land. We anticipate this work can encourage the use of Bacteroidales in the fresh produce industry to monitor fecal contamination and prevent future foodborne outbreaks.

A loop-mediated isothermal amplification assay to detect Bacteroidales and assess risk of fecal contamination.

Fecal contamination of fresh produce from human and animal sources is a public health concern due to the risk of foodborne illnesses. The current standard laboratory procedures for microbiological analyses usually require an enrichment step that involves several hours. Molecular techniques such as polymerase chain reaction (PCR) have been used to directly detect pathogens from the samples, however, due to the low quantity of pathogen present and small volumes used for PCR, enrichment is usually required. Additionally, the need for specialized equipment and experienced workers hinders the use of these molecular techniques for field testing. Here, we developed a rapid risk-assessment assay for fecal contamination by targeting Bacteroidales using loop-mediated isothermal amplification (LAMP). The assay allows for naked-eye observation of reactions with as few as ∼8 copies of Bacteroidales per cm2 of the surface in the field. We evaluated this assay with complex field samples as well as on-site field studies. Our on-field studies demonstrated that the Bacteroidales LAMP assay enables us to easily and quickly (<50 min) assess the risk of fecal contamination from animal operations, with a concordance of 85.3% when compared to lab-based qPCR. These results were obtained without expensive equipment (when compared to standard laboratory procedures). These assays could be used to determine site-specific risk and help the decision-making process of fresh produce growers.

The Quest for Immunity: Exploring Human Herpesviruses as Vaccine Vectors.

Herpesviruses are large DNA viruses that have long been used as powerful gene therapy tools. In recent years, the ability of herpesviruses to stimulate both innate and adaptive immune responses has led to their transition to various applications as vaccine vectors. This vaccinology branch is growing at an unprecedented and accelerated rate. To date, human herpesvirus-based vectors have been used in vaccines to combat a variety of infectious agents, including the Ebola virus, foot and mouth disease virus, and human immunodeficiency viruses. Additionally, these vectors are being tested as potential vaccines for cancer-associated antigens. Thanks to advances in recombinant DNA technology, immunology, and genomics, numerous steps in vaccine development have been greatly improved. A better understanding of herpesvirus biology and the interactions between these viruses and the host cells will undoubtedly foster the use of herpesvirus-based vaccine vectors in clinical settings. To overcome the existing drawbacks of these vectors, ongoing research is needed to further advance our knowledge of herpesvirus biology and to develop safer and more effective vaccine vectors. Advanced molecular virology and cell biology techniques must be used to better understand the mechanisms by which herpesviruses manipulate host cells and how viral gene expression is regulated during infection. In this review, we cover the underlying molecular structure of herpesviruses and the strategies used to engineer their genomes to optimize capacity and efficacy as vaccine vectors. Also, we assess the available data on the successful application of herpesvirus-based vaccines for combating diseases such as viral infections and the potential drawbacks and alternative approaches to surmount them.

On-farm colorimetric detection of Pasteurella multocida, Mannheimia haemolytica, and Histophilus somni in crude bovine nasal samples.

This work modifies a loop-mediated isothermal amplification (LAMP) assay to detect the bovine respiratory disease (BRD) bacterial pathogens Pasteurella multocida, Mannheimia haemolytica, and Histophilus somni in a colorimetric format on a farm. BRD causes a significant health and economic burden worldwide that partially stems from the challenges involved in determining the pathogens causing the disease. Methods such as polymerase chain reaction (PCR) have the potential to identify the causative pathogens but require lab equipment and extensive sample processing making the process lengthy and expensive. To combat this limitation, LAMP allows accurate pathogen detection in unprocessed samples by the naked eye allowing for potentially faster and more precise diagnostics on the farm. The assay developed here offers 66.7-100% analytical sensitivity, and 100% analytical specificity (using contrived samples) while providing 60-100% concordance with PCR results when tested on five steers in a feedlot. The use of a consumer-grade water bath enabled on-farm execution by collecting a nasal swab from cattle and provided a colorimetric result within 60 min. Such an assay holds the potential to provide rapid pen-side diagnostics to cattle producers and veterinarians.

Discrimination of Proteins Using an Array of Surfactant-Stabilized Gold Nanoparticles.

Protein analysis is a fundamental aspect of biochemical research. Gold nanoparticles are an emerging platform for various biological applications given their high surface area, biocompatibility, and unique optical properties. The colorimetric properties of gold nanoparticles make them ideal for point-of-care diagnostics. Different aspects of gold nanoparticle-protein interactions have been investigated to predict the effect of protein adsorption on colloidal stability, but the role of surfactants is often overlooked, despite their potential to alter both protein and nanoparticle properties. Herein we present a method by which gold nanoparticles can be prepared in various surfactants and used for array-based quantification and identification of proteins. The exchange of surfactant not only changed the zeta potential of those gold nanoparticles but also drastically altered their aggregation response to five different proteins (bovine serum albumin, human serum albumin, immunoglobulin G, lysozyme, and hemoglobin) in a concentration-dependent manner. Finally, we demonstrate that varying surfactant concentration can be used to control assay sensitivity.

A "chemical nose" biosensor for detecting proteins in complex mixtures.

A growing understanding of the fundamental role of proteins in diseases has advanced the development of quantitative protein assays in the medical field. Current techniques for protein analysis include enzyme-linked immunosorbent assays (ELISA), flow cytometry, mass spectrometry, and immunohistochemistry. However, many of these conventional strategies require specialized training, expensive antibodies, or sophisticated equipment, raising assay costs and limiting their application to laboratory analysis. Here, we present the application of a "chemical nose" type colorimetric gold nanoparticle sensor for detection, quantification, and identification of single proteins, protein mixtures, and proteins within the complex environment of human serum. The unique interactions between a mixture of two different gold nanoparticle morphologies (spherical and branched) and six separate proteins (bovine serum albumin, human serum albumin, immunoglobulin G, fibrinogen, lysozyme, and hemoglobin) generated distinguishable protein- and concentration-dependent absorption spectra, even at nanomolar concentrations. Furthermore, we show that this response is sensitive to the relative abundance of different proteins in solution, permitting analysis of protein mixtures. Finally, we demonstrate the ability to distinguish human serum samples with and without a clinically relevant two-fold increase in immunoglobulin G, without the use of expensive reagents or complicated sample processing.

Optimization of Polydiacetylene-Coated Superparamagnetic Magnetite Biosensor for Colorimetric Detection of Biomarkers.

Biosensors for point-of-care testing of critical illnesses are urgently needed, especially in many areas of poor healthcare infrastructure. Polydiacetylene-based sensors are ideal because of their unique colorimetric properties where blue to red color shifts can be observed with the naked eye. In this work, a colorimetric biosensor capable of simple, rapid magnetic separation is optimized, using horse IgG as a model antibody, to obtain higher sensitivity. Composed of a unique combination of polydiacetylene and superparamagnetic iron oxide, the biosensor is fabricated at varying ratios of polydiacetylene to demonstrate optimization of color responsiveness. At increasing polydiacetylene ratios, improved color responsiveness and aqueous dispersion are observed, but the magnetic separation efficiency starts to suffer. The optimal color response is obtained at 90 wt% polydiacetylene. In addition, a 50 times improved lower detection limit of 0.01 mg/mL horse IgG is achieved, a relevant biomarker concentration for diagnosing sepsis. This platform provides a promising colorimetric biosensor for point-of-care use.

Strategies for Bovine Respiratory Disease (BRD) Diagnosis and Prognosis: A Comprehensive Overview.

Despite significant advances in vaccination strategies and antibiotic therapy, bovine respiratory disease (BRD) continues to be the leading disease affecting the global cattle industry. The etiology of BRD is complex, often involving multiple microbial agents, which lead to intricate interactions between the host immune system and pathogens during various beef production stages. These interactions present environmental, social, and geographical challenges. Accurate diagnosis is essential for effective disease management. Nevertheless, correct identification of BRD cases remains a daunting challenge for animal health technicians in feedlots. In response to current regulations, there is a growing interest in refining clinical diagnoses of BRD to curb the overuse of antimicrobials. This shift marks a pivotal first step toward establishing a structured diagnostic framework for this disease. This review article provides an update on recent developments and future perspectives in clinical diagnostics and prognostic techniques for BRD, assessing their benefits and limitations. The methods discussed include the evaluation of clinical signs and animal behavior, biomarker analysis, molecular diagnostics, ultrasound imaging, and prognostic modeling. While some techniques show promise as standalone diagnostics, it is likely that a multifaceted approach-leveraging a combination of these methods-will yield the most accurate diagnosis of BRD.

A portable, easy-to-use paper-based biosensor for rapid in-field detection of fecal contamination on fresh produce farms.

Laboratory-based nucleic acid amplification tests (NAATs) are highly sensitive and specific, but they require the transportation of samples to centralized testing facilities and have long turnaround times. During the Coronavirus Disease 2019 (COVID-19) pandemic, substantial advancement has been achieved with the development of paper-based point-of-care (POC) NAATs, offering features such as low cost, being easy to use, and providing rapid sample-to-answer times. Although most of the POC NAATs innovations are towards clinical settings, we have developed a portable, paper-based loop-mediated isothermal amplification (LAMP) testing platform for on-farm applications, capable of detecting Bacteroidales as a fecal contamination biomarker. Our integrated platform includes a drop generator, a heating and imaging unit, and paper-based biosensors, providing sensitive results (limit of detection 3 copies of Bacteroidales per cm2) within an hour of sample collection. We evaluated this integrated platform on a commercial lettuce farm with a concordance of 100% when compared to lab-based tests. Our integrated paper-based LAMP testing platform holds great promise as a reliable and convenient tool for on-site NAATs. We expect that this innovation will encourage the fresh produce industry to adopt NAATs as a complementary tool for decision-making in growing and harvesting. We also hope that our work can stimulate further research in the development of on-farm diagnostic tools for other agricultural applications, leading to improved food safety and technology innovation.

Bacteriophage-based biosensors for detection of pathogenic microbes in wastewater.

Wastewater is discarded from several sources, including industry, livestock, fertilizer application, and municipal waste. If the disposed of wastewater has not been treated and processed before discharge to the environment, pathogenic microorganisms and toxic chemicals are accumulated in the disposal area and transported into the surface waters. The presence of harmful microbes is responsible for thousands of human deaths related to water-born contamination every year. To be able to take the necessary step and quick action against the possible presence of harmful microorganisms and substances, there is a need to improve the effective speed of identification and treatment of these problems. Biosensors are such devices that can give quantitative information within a short period of time. There have been several biosensors developed to measure certain parameters and microorganisms. The discovered biosensors can be utilized for the detection of axenic and mixed microbial strains from the wastewaters. Biosensors can further be developed for specific conditions and environments with an in-depth understanding of microbial organization and interaction within that community. In this regard, bacteriophage-based biosensors have become a possibility to identify specific live bacteria in an infected environment. This paper has investigated the current scenario of microbial community analysis and biosensor development in identifying the presence of pathogenic microorganisms.

Interactions between Humans and Dogs during the COVID-19 Pandemic: Recent Updates and Future Perspectives.

COVID-19 is one of the deadliest epidemics. This pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but the role of dogs in spreading the disease in human society is poorly understood. This review sheds light on the limited susceptibility of dogs to COVID-19 infections which is likely attributed to the relatively low levels of angiotensin-converting enzyme 2 (ACE2) in the respiratory tract and the phylogenetic distance of ACE2 in dogs from the human ACE2 receptor. The low levels of ACE2 affect the binding affinity between spike and ACE2 proteins resulting in it being uncommon for dogs to spread the disease. To demonstrate the role of dogs in spreading COVID-19, we reviewed the epidemiological studies and prevalence of SARS-CoV-2 in dogs. Additionally, we discussed the use of detection dogs as a rapid and reliable method for effectively discriminating between SARS-CoV-2 infected and non-infected individuals using different types of samples (secretions, saliva, and sweat). We considered the available information on COVID-19 in the human-dog interfaces involving the possibility of transmission of COVID-19 to dogs by infected individuals and vice versa, the human-dog behavior changes, and the importance of preventive measures because the risk of transmission by domestic dogs remains a concern.

The bovine nasal fungal community and associations with bovine respiratory disease.

Introduction: Effective identification and treatment of bovine respiratory disease (BRD) is an ongoing health and economic issue for the dairy and beef cattle industries. Bacteria pathogens Pasteurellamultocida, Mycoplasmabovis, Mannheimia haemolytica, and Histophilus somni and the virus Bovine herpesvirus-1 (BHV-1), Bovine parainfluenza-3 virus (BPIV-3), Bovine respiratory syncytial virus (BRSV), Bovine adenovirus 3 (BAdV3), bovine coronavirus (BoCV) and Bovine viral diarrhea virus (BVDV) have commonly been identified in BRD cattle; however, no studies have investigated the fungal community and how it may also relate to BRD. Methods: The objective of this study was to understand if the nasal mycobiome differs between a BRD-affected (n = 56) and visually healthy (n = 73) Holstein steers. Fungal nasal community was determined by using Internal Transcribed Spacer (ITS) sequencing. Results: The phyla, Ascomycota and Basidiomycota, and the genera, Trichosporon and Issatchenkia, were the most abundant among all animals, regardless of health status. We identified differences between healthy and BRD animals in abundance of Trichosporon and Issatchenkia orientalis at a sub-species level that could be a potential indicator of BRD. No differences were observed in the nasal fungal alpha and beta diversity between BRD and healthy animals. However, the fungal community structure was affected based on season, specifically when comparing samples collected in the summer to the winter season. We then performed a random forest model, based on the fungal community and abundance of the BRD-pathobionts (qPCR data generated from a previous study using the same animals), to classify healthy and BRD animals and determine the agreement with visual diagnosis. Classification of BRD or healthy animals using ITS sequencing was low and agreed with the visual diagnosis with an accuracy of 51.9%. A portion of the ITS-predicted BRD animals were not predicted based on the abundance of BRD pathobionts. Lastly, fungal and bacterial co-occurrence were more common in BRD animals than healthy animals. Discussion: The results from this novel study provide a baseline understanding of the fungal diversity and composition in the nasal cavity of BRD and healthy animals, upon which future interaction studies, including other nasal microbiome members to further understand and accurately diagnose BRD, can be designed.

Smart capsule for monitoring inflammation profile throughout the gastrointestinal tract.

Inflammatory bowel disease (IBD) has become alarmingly prevalent in the last two decades affecting 6.8 million people worldwide with a starkly high relapse rate of 40% within 1 year of remission. Existing visual endoscopy techniques rely on subjective assessment of images that are error-prone and insufficient indicators of early-stage IBD, rendering them unsuitable for frequent and quantitative monitoring of gastrointestinal health necessary for detecting regular relapses in IBD patients. To address these limitations, we have implemented a miniaturized smart capsule (2.2 cm × 11 mm) that allows monitoring reactive oxygen species (ROS) levels as a biomarker of inflammation for quantitative and frequent profiling of inflammatory lesions throughout the gastrointestinal tract. The capsule is composed of a pH and oxidation reduction potential (ORP) sensor to track the capsule's location and ROS levels throughout the gastrointestinal tract, respectively, and an optimized electronic interface for wireless sensing and data communication. The designed sensors provided a linear and stable performance within the physiologically relevant range of the GI tract (pH: 1-8 and ORP: -500 to +500 mV). Additionally, systematic design optimization of the wireless interface electronics offered an efficient sampling rate of 10 ms for long-running measurements up to 48 h for a complete evaluation of the entire gastrointestinal tract. As a proof-of-concept, the capsule the capsule's performance in detecting inflammation risks was validated by conducting tests on in vitro cell culture conditions, simulating healthy and inflamed gut-like environments. The capsule presented here achieves a new milestone in addressing the emerging need for smart ingestible electronics for better diagnosis and treatment of digestive diseases.

Characterizing viral samples using machine learning for Raman and absorption spectroscopy.

Machine learning methods can be used as robust techniques to provide invaluable information for analyzing biological samples in pharmaceutical industries, such as predicting the concentration of viral particles of interest in biological samples. Here, we utilized both convolutional neural networks (CNNs) and random forests (RFs) to predict the concentration of the samples containing measles, mumps, rubella, and varicella-zoster viruses (ProQuad®) based on Raman and absorption spectroscopy. We prepared Raman and absorption spectra data sets with known concentration values, then used the Raman and absorption signals individually and together to train RFs and CNNs. We demonstrated that both RFs and CNNs can make predictions with R2 values as high as 95%. We proposed two different networks to jointly use the Raman and absorption spectra, where our results demonstrated that concatenating the Raman and absorption data increases the prediction accuracy compared to using either Raman or absorption spectrum alone. Additionally, we further verified the advantage of using joint Raman-absorption with principal component analysis. Furthermore, our method can be extended to characterize properties other than concentration, such as the type of viral particles.

Paper-Based Biosensors for the Detection of Nucleic Acids from Pathogens.

Paper-based biosensors are microfluidic analytical devices used for the detection of biochemical substances. The unique properties of paper-based biosensors, including low cost, portability, disposability, and ease of use, make them an excellent tool for point-of-care testing. Among all analyte detection methods, nucleic acid-based pathogen detection offers versatility due to the ease of nucleic acid synthesis. In a point-of-care testing context, the combination of nucleic acid detection and a paper-based platform allows for accurate detection. This review offers an overview of contemporary paper-based biosensors for detecting nucleic acids from pathogens. The methods and limitations of implementing an integrated portable paper-based platform are discussed. The review concludes with potential directions for future research in the development of paper-based biosensors.

Identification of bovine respiratory disease through the nasal microbiome.

BACKGROUND: Bovine respiratory disease (BRD) is an ongoing health and economic challenge in the dairy and beef cattle industries. Multiple risk factors make an animal susceptible to BRD. The presence of Mannheimia haemolytica, Pasteurella multocida, Histophilus somni, and Mycoplasma bovis in lung tissues have been associated with BRD mortalities, but they are also commonly present in the upper respiratory tract of healthy animals. This study aims to compare the cattle nasal microbiome (diversity, composition and community interaction) and the abundance of BRD pathogens (by qPCR) in the nasal microbiome of Holstein steers that are apparently healthy (Healthy group, n = 75) or with BRD clinical signs (BRD group, n = 58). We then used random forest models based on nasal microbial community and qPCR results to classify healthy and BRD-affected animals and determined the agreement with the visual clinical signs. Additionally, co-occurring species pairs were identified in visually BRD or healthy animal groups. RESULTS: Cattle in the BRD group had lower alpha diversity than pen-mates in the healthy group. Amplicon sequence variants (ASVs) from Trueperella pyogenes, Bibersteinia and Mycoplasma spp. were increased in relative abundance in the BRD group, while ASVs from Mycoplasma bovirhinis and Clostridium sensu stricto were increased in the healthy group. Prevalence of H. somni (98%) and P. multocida (97%) was high regardless of BRD clinical signs whereas M. haemolytica (81 and 61%, respectively) and M. bovis (74 and 51%, respectively) were more prevalent in the BRD group than the healthy group. In the BRD group, the abundance of M. haemolytica and M. bovis was increased, while H. somni abundance was decreased. Visual observation of clinical signs agreed with classification by the nasal microbial community (misclassification rate of 32%) and qPCR results (misclassification rate 34%). Co-occurrence analysis demonstrated that the nasal microbiome of BRD-affected cattle presented fewer bacterial associations than healthy cattle. CONCLUSIONS: This study offers insight into the prevalence and abundance of BRD pathogens and the differences in the nasal microbiome between healthy and BRD animals. This suggests that nasal bacterial communities provide a potential platform for future studies and potential pen-side diagnostic testing.

Smart capsule for targeted proximal colon microbiome sampling.

The gastrointestinal (GI) tract, particularly the colon region, holds a highly diverse microbial community that plays an important role in the metabolism, physiology, nutrition, and immune function of the host body. Accumulating evidence has revealed that alteration in these microbial communities is the pivotal step in developing various metabolic diseases, including obesity, inflammatory bowel disease (IBD), and colorectal cancer. However, there is still a lack of clear understanding of the interrelationship between microbiota and diet as well as the effectiveness of chemoprevention strategies, including pre and probiotic agents in modifying the colonic microbiota and preventing digestive diseases. Existing methods for assessing these microbiota-diet interactions are often based on samples collected from the feces or endoscopy techniques which are incapable of providing information on spatial variations of the gut microbiota or are considered invasive procedures. To address this need, here we have developed an electronic-free smart capsule that enables site-specific sampling of the gut microbiome within the proximal colon region of the GI tract. The 3D printed device houses a superabsorbent hydrogel bonded onto a flexible polydimethylsiloxane (PDMS) disk that serves as a milieu to collect the fluid in the gut lumen and its microbiome by rapid swelling and providing the necessary mechanical actuation to close the capsule after the sampling is completed. The targeted colonic sampling is achieved by coating the sampling aperture on the capsule with a double-layer pH-sensitive enteric coating, which delays fluid in the lumen from entering the capsule until it reaches the proximal colon of the GI tract. To identify the appropriate pH-responsive double-layer coating and processing condition, a series of systematic dissolution characterizations in different pH conditions that mimicked the GI tract was conducted. The effective targeted microbial sampling performance and preservation of the smart capsule with the optimized design were validated using both realistic in vitro GI tract models with mixed bacteria cultures and in vivo with pigs as an animal model. The results from 16s rRNA and WideSeq analysis in both in vitro and in vivo studies showed that the bacterial population sampled within the retrieved capsule closely matched the bacterial population within the targeted sampling region (proximal colon). Herein, it is envisioned that such smart sampling capsule technology will provide new avenues for gastroenterological research and clinical applications, including diet-host-microbiome relationships, focused on human GI function and health. STATEMENT OF SIGNIFICANCE: The colonic microbiota plays a major role in the etiology of numerous diseases. Extensive efforts have been conducted to monitor the gut microbiome using sequencing technologies based on samples collected from feces or mucosal biopsies that are typically obtained by colonoscopy. Despite the simplicity of fecal sampling procedures, they are incapable of preserving spatial and temporal information about the bacteria through the gastrointestinal (GI) tract. In contrast, colonoscopy is an invasive and impractical approach to frequently assess the effect of dietary and therapeutic intake on the microbiome and their impact on the health of the patient. Here, we developed a non-invasive capsule that enables targeted sampling from the ascending colon, thereby providing crucial information for disease prediction and monitoring.

Fabrication of a paper-based colorimetric molecular test for SARS-CoV-2.

The ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused unprecedented damage to the global economy. Diagnostic testing is a key factor in limiting virus transmission and safeguarding public health. We present the fabrication process of a paper-based device that uses reverse-transcription loop-mediated isothermal amplification (RT-LAMP) to detect SARS-CoV-2 in complex matrices by providing a colorimetric response apparent to the naked eye. Because of LAMP's functionality, this device just requires a simple heat source (e.g., water bath, incubator), it can be deployed in resource-constrained areas and can be used as a supplement to current point-of-care (POC) and community testing procedures. Since the test is based on nucleic acids, the testing platform itself lends to further applications including food safety monitoring, animal diagnostics, etc. simply by changing the specific primers.•We developed a platform capable of on-paper detection of SARS-CoV-2 using colorimetric reporters that produce responses visible to the naked eye.•The platform is easily reconfigurable to target different pathogens by changing the primer sets, and multiplexing is possible by adding additional reaction sites to the device.

A paper-based colorimetric molecular test for SARS-CoV-2 in saliva.

Herein, we describe the development of a paper-based device to detect nucleic acids of pathogens of interest in complex samples using loop-mediated isothermal amplification (LAMP) by producing a colorimetric response visible to the human eye. To demonstrate the utility of this device in emerging public health emergencies, we developed and optimized our device to detect SARS-CoV-2 in human saliva without preprocessing. The resulting device was capable of detecting the virus within 60 min and had an analytical sensitivity of 97% and a specificity of 100% with a limit of detection of 200 genomic copies/µL of patient saliva using image analysis. The device consists of a configurable number of reaction zones constructed of Grade 222 chromatography paper separated by 20 mil polystyrene spacers attached to a Melinex® backing via an ARclean® double-sided adhesive. The resulting device is easily configurable to detect multiple targets and has the potential to detect a variety of pathogens simply by changing the LAMP primer sets.

Process Analytical Technologies and Data Analytics for the Manufacture of Monoclonal Antibodies.

Process analytical technology (PAT) for the manufacture of monoclonal antibodies (mAbs) is defined by an integrated set of advanced and automated methods that analyze the compositions and biophysical properties of cell culture fluids, cell-free product streams, and biotherapeutic molecules that are ultimately formulated into concentrated products. In-line or near-line probes and systems are remarkably well developed, although challenges remain in the determination of the absence of viral loads, detecting microbial or mycoplasma contamination, and applying data-driven deep learning to process monitoring and soft sensors. In this review, we address the current status of PAT for both batch and continuous processing steps and discuss its potential impact on facilitating the continuous manufacture of biotherapeutics.