Dengue is an arthropod-borne viral disease that has become endemic and a global threat in over 100 countries. The increase in prevalence would require a long-term measure to control outbreaks. Sanofi Pasteur has licensed the tetravalent dengue vaccine (Dengvaxia) in certain dengue endemic countries. However, the efficacy of the vaccine is limited against certain dengue serotypes and can only be used for individuals from the age from 9 to 45 years old. Over the years, there has been intense research conducted on the development of antivirals against dengue virus (DENV) through either inhibiting the virus replication or targeting the host cell mechanism to block the virus entry. However, no approved antiviral drug against dengue is yet available. In this chapter, we describe the dengue antiviral development workflow including (i) prophylactic, (ii) virucidal, and (iii) postinfection assays that are employed in the antiviral drug screening process against DENV. Further, we demonstrate different methods that can be used to enumerate the reduction in virus foci number including foci-forming unit reduction assay (FFURA), estimation of viral RNA copy number through quantitative real-time PCR, and a high-throughput enzyme linked immunosorbent assay (ELISA)-based quantification of virus particles.
Enteroviruses 71 (EV71) is a single-stranded, neurotrophic RNA virus responsible for the numerous outbreaks of hand, foot, and mouth disease (HFMD) in the Asia-Pacific regions. HFMD primarily affects children to cause range of infection, from mild symptoms to acute flaccid paralysis, and hemorrhage. Despite increased incidence of EV71 epidemics globally and research against EV71 becoming prioritized, no antiviral agent against EV71 has yet been licensed and approved worldwide. In this chapter, detailed EV71 antiviral screening techniques are described, including plaque assay which determines viral titers through the use of a semisolid overlay, carboxymethyl cellulose to allow even viral spread and infection across the host cellular monolayers as well as a crystal violet, a distinct counterstain to visualize circular regions of infectious zones-plaques. qRT-PCR is used to quantify the viral genomic RNA in the infected samples and MTS cell viability assay to quantify the cell viability after infection or toxicity of the compound on the cells. Furthermore, various antiviral inhibition assays including prophylactic, post infection, and virucidal assays are demonstrated for estimation of the antiviral activity of potential antiviral drugs against EV71. These methods can be effectively utilized in virology laboratories for effective high-throughput screening of antiviral molecules against EV71 that can assist in the future development of antiviral drugs.
Constitutive secretion is predominantly measured by collecting the media from cells and performing plate-based assays. This approach is particularly sensitive to changes in cell number, and a significant amount of effort has to be spent to overcome this. We have developed a panel of quantitative flow cytometry-based assays and reporter cell lines that can be used to measure constitutive secretion. These assays are insensitive to changes in cell number making them very robust and well suited to functional genomic and chemical screens. Here, we outline the key steps involved in generating and using these assays for studying constitutive secretion.
This chapter describes the generation of the data in the CATH-Gene3D online resource and how it can be used to study protein domains and their evolutionary relationships. Methods will be presented for: comparing protein structures, recognizing homologs, predicting domain structures within protein sequences, and subclassifying superfamilies into functionally pure families, together with a guide on using the webpages.
Immunohistochemistry is a histological technique that allows detection of one or more proteins of interest within a cell using specific antibody binding, followed by microscopic visualization of a chromogenic substrate catalyzed by peroxidase and/or alkaline phosphatase. Here, we describe a method to localize Chikungunya virus (CHIKV) antigens in formalin-fixed and paraffin-embedded infected mouse brain.
Feline infectious peritonitis (FIP) is a lethal systemic disease caused by FIP virus (FIPV). There are no effective vaccines or treatment available, and the virus virulence determinants and pathogenesis are not fully understood. Here, we describe the sequencing of RNA extracted from Crandell Rees Feline Kidney (CRFK) cells infected with FIPV using the Illumina next-generation sequencing approach. Bioinformatics analysis, based on Felis catus 2X annotated shotgun reference genome, using CLC bio Genome Workbench is used to map both control and infected cells. Kal's Z test statistical analysis is used to analyze the differentially expressed genes from the infected CRFK cells. In addition, RT-qPCR analysis is used for further transcriptional profiling of selected genes in infected CRFK cells and Peripheral Blood Mononuclear Cells (PBMCs) from healthy and FIP-diagnosed cats.
Recombineering is a powerful genetic engineering technique based on homologous recombination that can be used to accurately modify DNA independent of its sequence or size. One novel application of recombineering is the assembly of linear BACs in E. coli that can replicate autonomously as linear plasmids. A circular BAC is inserted with a short telomeric sequence from phage N15, which is subsequently cut and rejoined by the phage protelomerase enzyme to generate a linear BAC with terminal hairpin telomeres. Telomere-capped linear BACs are protected against exonuclease attack both in vitro and in vivo in E. coli cells and can replicate stably. Here we describe step-by-step protocols to linearize any BAC clone by recombineering, including inserting and screening for presence of the N15 telomeric sequence, linearizing BACs in vivo in E. coli, extracting linear BACs, and verifying the presence of hairpin telomere structures. Linear BACs may be useful for functional expression of genomic loci in cells, maintenance of linear viral genomes in their natural conformation, and for constructing innovative artificial chromosome structures for applications in mammalian and plant cells.
Gene delivery using invasive bacteria as vectors is a robust method that is feasible for plasmid and artificial chromosome DNA construct delivery to human cells presenting β1 integrin receptors. This technique is relatively underutilized owing to the inefficiency of gene transfer to targeted cell populations. Bacterial vectors must successfully adhere to the cell membrane, internalize into the cytoplasm, undergo lysis, and deliver DNA to the nucleus. There are limited studies on the use of exogenous reagents to improve the efficiency of bacteria-mediated gene delivery to mammalian cells. In this chapter, we describe how cationic lipids, conventionally used for DNA and protein transfection, as well as antimicrobial compounds, can be used to synergistically enhance the adherence of invasive bacterial vectors to the cell membrane and improve their predisposition to internalize into the cytoplasm to deliver DNA. Using simple combinatorial methods, functional DNA transfer can be improved by up to four-fold of invaded cell populations. These methods are easy to perform and are likely to be applicable for other bacterial vectors including Listeria and Salmonella.
Visual analysis of the gene delivery process when using invasive bacteria as a vector has been conventionally performed using standard light and fluorescence microscopy. These microscopes can provide basic information on the invasiveness of the bacterial vector including the ability of the vector to successfully adhere to the cell membrane. Standard microscopy techniques however fall short when finer details including membrane attachment as well as internalization into the cytoplasm are desired. High-resolution visual analysis of bacteria-mediated gene delivery can allow accurate measurement of the adherence and internalization capabilities of engineered vectors. Here, we describe the use of scanning electron microscopy (SEM) to directly quantify vectors when they are external to the cell wall, and confocal microscopy to evaluate the vectors when they have internalized into the cytoplasm. By performing the invasion procedure on microscope coverslips, cells can be easily prepared for analysis using electron or confocal microscopes. Imaging the invasion complexes in high resolution can provide important insights into the behavior of bacterial vectors including E. coli, Listeria, and Salmonella when invading their target cells to deliver DNA and other molecules.
Shotgun proteomics has been widely applied to study proteins in complex biological samples. Combination of high-performance liquid chromatography with mass spectrometry has allowed for comprehensive protein analysis with high resolution, sensitivity, and mass accuracy. Prior to mass spectrometry analysis, proteins are extracted from biological samples and subjected to in-solution trypsin digestion. The digested proteins are subjected for clean-up and injected into the liquid chromatography-mass spectrometry system for peptide mass identification. Protein identification is performed by analyzing the mass spectrometry data on a protein search engine software such as PEAKS studio loaded with protein database for the species of interest. Results such as protein score, protein coverage, number of peptides, and unique peptides identified will be obtained and can be used to determine proteins identified with high confidence. This method can be applied to understand the proteomic changes or profile brought by bio-carrier-based therapeutics in vitro. In this chapter, we describe methods in which proteins can be extracted for proteomic analysis using a shotgun approach. The chapter outlines important in vitro techniques and data analysis that can be applied to investigate the proteome dynamics.
In this post-genomic era, protein network can be used as a complementary way to shed light on the growing amount of data generated from current high-throughput technologies. Protein network is a powerful approach to describe the molecular mechanisms of the biological events through protein-protein interactions. Here, we describe the computational methods used to construct the protein network using expression data. We provide a list of available tools and databases that can be used in constructing the network.
The importance of protein detection system for protein functions analyses in recent post-genomic era is rising with the emergence of label-free protein detection methods. We are focusing on a simple and practical label-free optical-detection method called anomalous reflection (AR) of gold. When a molecular layer forms on the gold surface, significant reduction in reflectivity can be observed at wavelengths of 400-500 nm. This allows the detection of molecular interactions by monitoring changes in reflectivity. In this chapter, we describe the AR method with three different application platforms: (1) gold, (2) gold containing alloy/composite (AuAg2O), and (3) metal-insulator-metal (MIM) thin layers. The AuAg2O composite and MIM are implemented as important concepts for signal enhancement process for the AR technique. Moreover, the observed molecular adsorption and activity is aided by a three-dimensional surface geometry, performed using poly(amidoamine) or PAMAM dendrimer modification. The described system is suitable to be used as a platform for high-throughput detection system in a chip format.
Evidence on the role of the oral microbiome in health and disease is changing the way we understand, diagnose, and treat ailments. Numerous studies on diseases affecting the oral cavity have revealed a large amount of data that is invaluable for the advancements in diagnosing and treating these diseases. However, the clinical translation of most of these exploratory data is stalled by variable methodology between studies and non-uniform reporting of the data.Understanding the key areas that are gateways to bias in microbiome studies is imperative to overcome this challenge faced by oral microbiome research. Bias can be multifactorial and may be introduced in a microbiome research study during the formulation of the study design, sample collection and storage, or the sample processing protocols before sequencing. This chapter summarizes the recommendations from literature to eliminate bias in the microbiome research studies and to ensure the reproducibility of the microbiome research data.
Transgenic oil palm (Elaeis guineensis Jacq.) plantlets are regenerated after Agrobacterium tumefaciens-mediated transformation of embryogenic calli derived from young leaves of oil palm. The calli are transformed with an Agrobacterium strain, LBA4404, harboring the plasmid pUBA, which carries a selectable marker gene (bar) for resistance to the herbicide Basta and is driven by a maize ubiquitin promoter. Modifications of the transformation method, treatment of the target tissues using acetosyringone, exposure to a plasmolysis medium, and physical injury via biolistics are applied. The main reasons for such modifications are to activate the bacterial virulence system and, subsequently, to increase the transformation efficiency. Transgenic oil palm cells are selected and regenerated on a medium containing herbicide Basta. Molecular analyses revealed the presence and integration of the introduced bar gene into the genome of the transformants.
The Malaysian strain of Nipah virus (NiV) first emerged in 1998/99 and caused a major disease outbreak in pigs and humans. While humans developed fatal encephalitis due to a prominent infection of brain microvessels, NiV-infected pigs mostly suffered from an acute respiratory disease and efficiently spread the infection via airway secretions. To elucidate the molecular basis of the highly productive NiV replication in porcine airways in vitro, physiologically relevant cell models that have maintained functional characteristics of airway epithelia in vivo are needed. Here, we describe in detail the method of isolating bronchial epithelial cells (PBEpC) from pig lungs that can be used for NiV infection studies. After the dissection of primary bronchia and removal of the mucus and protease digestion, bronchi segments are cut open and epithelial cells are scraped off and seeded on collagen-coated cell culture flasks. With this method, it is possible to isolate about 2 × 106 primary cells from the primary bronchi of one pig lung which can be cryopreserved or further subcultured. PBEpC form polarized monolayers on Transwell membrane inserts as controlled by immunostainings of epithelial marker proteins. NiV infection causes rapid formation of syncytia, allowing productive NiV infections in living PBEpC cultures to be monitored by phase-contrast microscopy.
Affinity purification coupled to mass spectrometry (AP-MS) is a powerful method to analyze protein-protein interactions (PPIs). The AP-MS approach provides an unbiased analysis of the entire protein complex and is useful to identify indirect interactors. However, reliable protein identification from the complex AP-MS experiments requires appropriate control of false identifications and rigorous statistical analysis. Another challenge that can arise from AP-MS analysis is to distinguish bona fide interacting proteins from the non-specifically bound endogenous proteins or the "background contaminants" that co-purified by the bait experiments. In this chapter, we will first describe the protocol for performing in-solution trypsinization for the samples from the AP experiment followed by LC-MS/MS analysis. We will then detail the MaxQuant workflow for protein identification and quantification for the PPI data derived from the AP-MS experiment. Finally, we describe the CRAPome interface to process the data by filtering against contaminant lists, score the interactions and visualize the protein interaction networks.
Spillovers of Nipah virus (NiV) from its pteropid bat reservoir into the human population continue to cause near-annual outbreaks of fatal encephalitis and respiratory disease in Bangladesh and India since its emergence in Malaysia over 20 years ago. The current lack of effective antiviral therapeutics against NiV merits further testing of compound libraries against NiV using rapid quantitative antiviral assays. The development of recombinant henipaviruses expressing reporter fluorescence and/or luminescence proteins has facilitated the screening of such libraries. In this chapter, we provide a basic protocol for both types of reporter viruses. Utilizing these live NiV-based reporter assays requires modest instrumentation and sidesteps the labor-intensive steps associated with traditional cytopathic effect or viral antigen-based assays.
From its discovery in Malaysia in the late 1990s, the spillover of the Nipah virus from its pteropid reservoir into the human population has resulted in sporadic outbreaks of fatal encephalitis and respiratory disease. In this chapter, we revise a previously described quantitative reverse transcription polymerase chain reaction method, which now utilizes degenerate nucleotides at certain positions in the probe and the reverse primer to accommodate the sequence heterogeneity observed within the Nipah henipavirus species.
The biomass concentration of microalgae growth in photobioreactor was predicted using the Monod-based growth models. Kinetic parameters such as maximum specific growth rate and saturation constant of light intensity were evaluated by nonlinear least squares methods that focused on minimizing the sum of squares error (SSE). The importance of good initial guess for the nonlinear least squares method was also discussed. The optimal control problem of the microalgae growth model was determined based on parameter sensitivity. Therefore, a dynamic optimization approach was used where an optimal input design method was formulated to obtain a control function of a problem. The dynamic state equations, additional state equations, cost function, and Hamiltonian function were used to establish a control function of microalgae growth in a photobioreactor. Hence, the biomass production of microalgae can be predicted using numerical methods such as the Taylor series method.