Protein engineering is a very useful tool for probing structure-function relationships in proteins. Specifically, site-directed mutagenized proteins can provide useful insights into structural, binding and catalytic mechanisms of a protein, particularly when coupled with crystallization. In this chapter, we describe two protocols for performing site-directed mutagenesis of any protein-coding sequence, namely, megaprimer PCR and overlapping extension PCR (OE-PCR). We use as an example how these two SDM methods enhanced the function of a cyclodextrin glucosyltransferase (CGTase) from Bacillus lehensis strain G1.
This chapter describes the development of the science of cryopreservation of gametes and embryos of various species including human. It attempts to record in brief the main contributions of workers in their attempts to cryopreserve gametes and embryos. The initial difficulties faced and subsequent developments and triumphs leading to present-day state of the art are given in a concise manner. The main players and their contributions are mentioned and the authors' aim is to do justice to them. This work also attempts to ensure that credit is correctly attributed for significant advances in gamete and embryo cryopreservation. In general this chapter has tried to describe the historical development of the science of cryopreservation of gametes and embryos as accurately as possible without bias or partiality.
Reverse transcription followed by real-time or quantitative polymerase chain reaction (RT-qPCR) is the gold standard for validation of results from transcriptomic profiling studies such as microarray and RNA sequencing. The current need for most studies, especially biomarker studies, is to evaluate the expression levels or fold changes of many transcripts in a large number of samples. With conventional low to medium throughput qPCR platforms, many qPCR plates would have to be run and a significant amount of RNA input per sample will be required to complete the experiments. This is particularly challenging when the size of study material (small biopsy, laser capture microdissected cells, biofluid, etc.), time, and resources are limited. A sensitive and high-throughput qPCR platform is therefore optimal for the evaluation of many transcripts in a large number of samples because the time needed to complete the entire experiment is shortened and the usage of lab consumables as well as RNA input per sample are low. Here, the methods of high-throughput RT-qPCR for the analysis of circulating microRNAs are described. Two distinctive qPCR chemistries (probe-based and intercalating dye-based) can be applied using the methods described here.
The plant Catharanthus roseus is a rich source of terpenoid indole alkaloids (TIA). Some of the TIA are important as antihypertensive (ajmalicine) and anticancer (vinblastine and vincristine) drugs. However, production of the latter is very low in the plant. Therefore, in vitro plant cell cultures have been considered as a potential supply of these chemicals or their precursors. Some monomeric alkaloids can be produced by plant cell cultures, but not on a level feasible for commercialization, despite extensive studies on this plant that deepened the understanding of the TIA biosynthesis and its regulation. In order to analyze the metabolites in C. roseus cell cultures, this chapter presents the method of TIA, carotenoids, and phytosterols analyses. Furthermore, an NMR-based metabolomics approach to study C. roseus cell culture is described.
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.
Protein microarray is a miniaturized multi-analyte, solid-phased immunoassay where thousands of immobilized individual protein spots on a microscopic slide bind are bound to specific antibodies (immunoglobulins) from serum samples, which are then detected by fluorescent labeling. The image processing and pattern recognition are then quantitatively analyzed using advanced algorithms. Here, we describe the use of an in-house-produced complex protein microarray containing extracts and pure proteins that has been probed with antibodies present in the horse sera and detection by fluorophore-conjugated antibody and data analysis. The flexibility of the number and types of proteins that can be printed on the microarray allows different set of specific IgE immunoassay analysis to be carried out.
Reverse-phase high-performance liquid chromatography is commonly employed as a decomplexing strategy in snake venom proteomics. The chromatographic fractions often contain relatively pure toxins that can be assessed functionally for toxicity level through the determination of their median lethal doses (LD50). Further, antivenom efficacy can be evaluated specifically against these venom fractions to understand the limitation of the antivenom as the treatment for snake envenomation. However, methods of toxicity assessment and antivenom evaluation vary across laboratories; hence there is a need to standardize the protocols and parameters, in particular those related to the neutralizing efficacy of antivenom. This chapter outlines the important in vivo techniques and data interpretation that can be applied in the functional study of snake venom proteomes.
Snake venoms are complex mixtures of proteins and peptides that play vital roles in the survival of venomous snakes. As with their diverse pharmacological activities, snake venoms can be highly variable, hence the importance of understanding the compositional details of different snake venoms. However, profiling venom protein mixtures is challenging, in particular when dealing with the diversity of protein subtypes and their abundances. Here we described an optimized strategy combining a protein decomplexation method with in-solution trypsin digestion and mass spectrometry of snake venom proteins. The approach involves the integrated use of C18 reverse-phase high-performance liquid chromatography (RP-HPLC), sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), and nano-electrospray ionization tandem mass spectrometry (nano-ESI-LC-MS/MS).
The main strategy for lowering blood cholesterol levels is through the inhibition of the NADPH-dependent HMG-CoA reductase (3-hydroxy-3-methyl-glutaryl-CoA reductase). The enzyme catalyses the reduction of HMG-CoA to mevalonate and this process is inhibited by statins that form the bulk of the therapeutic agents to treat high cholesterol since the 1970s. Newer drugs that are safer than statins are constantly being developed. The inhibition of candidate drugs to HMG-CoA reductase remains the mainstay of drug development research. The determination of the enzyme activity is important for the correct assessment of potency of the enzyme as well as determining the inhibition of potential therapeutic agents from the plant and microbial extracts. Also, this chapter covers the use of the popular four-parameter logistics model that can yield accurate estimation of the IC50 values of therapeutic agents and their 95% confidence intervals.
Particular attention has been paid to capillary electrophoresis as versatile and environmentally friendly approach for enantioseparations of a wide spectrum of compounds. Cyclodextrin-modified micellar electrokinetic chromatography (CD-MEKC) is a method of choice to provide effective separation toward hydrophobic and uncharged stereoisomers. The chiral discrimination of the solutes relies upon the partitioning between a given CD in the aqueous phase and micelles formed from a surfactant. Synergistic combinations of chiral selectors, surfactant, and modifier contribute to successful enantioseparations of the enantiomers. In this chapter, an application of CD-MEKC for the enantioseparation of selected imidazole drugs employing a dual CDs system is described.
In gene expression studies, missing values are a common problem with important consequences for the interpretation of the final data (Satija et al., Nat Biotechnol 33(5):495, 2015). Numerous bioinformatics examination tools are used for cancer prediction, including the data set matrix (Bailey et al., Cell 173(2):371-385, 2018); thus, it is necessary to resolve the problem of missing-values imputation. This chapter presents a review of the research on missing-values imputation approaches for gene expression data. By using local and global correlation of the data, we were able to focus mostly on the differences between the algorithms. We classified the algorithms as global, hybrid, local, or knowledge-based techniques. Additionally, this chapter presents suitable assessments of the different approaches. The purpose of this review is to focus on developments in the current techniques for scientists rather than applying different or newly developed algorithms with identical functional goals. The aim was to adapt the algorithms to the characteristics of the data.
Life-cycle assessment (LCA) is one of the most attractive tools employed nowadays by environmental policy-makers as well as business decision-makers to ensure environmentally sustainable production/consumption of various goods/services. LCA is a systematic, rigorous, and standardized approach aimed at quantifying resources consumed/depleted, pollutants released, and the related environmental and health impacts through the course of consumption and production of goods/service. Algal fuels are no exception and their environmental sustainability could be well scrutinized using the LCA methodology. In line with that, this chapter is devoted to present guidelines on the technical aspects of LCA application in algal fuels while elaborating on major standards used, i.e., ISO 14040 and 14044 standards. Overall, LCA practitioners as well as technical experts dealing with algal fuels in both the public and private sectors could be the main target audience for these guidelines.
Acinetobacter baumannii is rapidly emerging as a multidrug-resistant pathogen responsible for nosocomial infections including pneumonia, bacteremia, wound infections, urinary tract infections, and meningitis. Metabolomics provides a powerful tool to gain a system-wide snapshot of cellular biochemical networks under defined conditions and has been increasingly applied to bacterial physiology and drug discovery. Here we describe an optimized sample preparation method for untargeted metabolomics studies in A. baumannii. Our method provides a significant recovery of intracellular metabolites to demonstrate substantial differences in global metabolic profiles among A. baumannii strains.
Leigh syndrome (LS) is a common neurodegenerative disease affecting neonates with devastating sequences. One of the characteristic features for LS is the phenotypic polymorphism, which-in part-can be dedicated to variety of genetic causes. A strong correlation with mitochondrial dysfunction has been assumed as the main cause of LS. This was based on the fact that most genetic causes are related to mitochondrial complex I genome. The first animal LS model was designed based on NDUFS4 knockdown. Interestingly, however, this one or others could not recapitulate the whole spectrum of manifestations encountered in different cases of LS. We show in this chapter a new animal model for LS based on silencing of one gene that is reported previously in clinical cases, FOXRED1. The new model carries some differences from previous models in the fact that more histopathological degeneration in dopaminergic system is seen and more behavioral changes can be recognized. FOXRED1 is an interesting gene that is related to complex I assembly, hence, plays important role in different neurodegenerative disorders leading to different clinical manifestations.
Reverse vaccinology (RV) was first introduced by Rappuoli for the development of an effective vaccine against serogroup B Neisseria meningitidis (MenB). With the advances in next generation sequencing technologies, the amount of genomic data has risen exponentially. Since then, the RV approach has widely been used to discover potential vaccine protein targets by screening whole genome sequences of pathogens using a combination of sophisticated computational algorithms and bioinformatic tools. In contrast to conventional vaccine development strategies, RV offers a novel method to facilitate rapid vaccine design and reduces reliance on the traditional, relatively tedious, and labor-intensive approach based on Pasteur"s principles of isolating, inactivating, and injecting the causative agent of an infectious disease. Advances in biocomputational techniques have remarkably increased the significance for the rapid identification of the proteins that are secreted or expressed on the surface of pathogens. Immunogenic proteins which are able to induce the immune response in the hosts can be predicted based on the immune epitopes present within the protein sequence. To date, RV has successfully been applied to develop vaccines against a variety of infectious pathogens. In this chapter, we apply a pipeline of bioinformatic programs for identification of Shigella flexneri potential vaccine candidates as an illustration immunoinformatic tools available for RV.
Bacteriophages have been explored for their uses in vaccine development, due to the ease of propagation while displaying epitopes in high density. Bacteriophage T7 has been demonstrated to be useful in the production of potential vaccine candidates for various diseases, including influenza A, foot-and mouth disease (FMD), and cancers. In this chapter, we described the use of phage T7 to display potential foot-and-mouth disease virus (FMDV) epitope, from cloning to expression, purification, and immunization in a mouse model.
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.
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.
Mast cells are part of the immune system and characteristically contain histamine- and heparin-rich basophilic granules. While these cells are usually associated with allergy and anaphylaxis, they also promote wound healing and angiogenesis and confer protection against pathogens. The presence of these cells is sometimes indicative of a poor prognosis, especially in skin cancer, pancreatic cancer, and lymphoma. Toluidine blue staining of acid-fast granules is an established method for the identification and quantification of mast cells. Generating detailed information on the location of mast cells within tissues is problematic using this technique and often requires serial sections from adjacent tissue to be separately stained with hematoxylin and eosin (H&E). Staining serial sections is not always possible, particularly if the sample is very small or rare. In such cases, a method of simultaneously identifying and localizing mast cells in a tissue would be advantageous. Toluidine blue and H&E are not commonly combined because H&E includes repetitive washes in water, which may affect the efficacy of the aqueous-soluble toluidine blue. We have developed and tested a novel staining technique that integrates toluidine blue between hematoxylin and eosin in one simple procedure. This protocol works on both frozen and formalin-fixed, paraffin-embedded tissue and readily allows for the identification of purple-stained mast cells against a clean H&E background. This facilitates a more accurate localization and proper counting of mast cells in normal and affected tissue.
DNA is widely used in plant genetic and molecular biology studies. In this chapter, we describe how to extract DNA from wheat tissues. The tissue samples are ground to disrupt the cell wall. Then cetyltrimethylammonium bromide (CTAB) or sodium dodecyl sulfate (SDS) is used to disrupt the cell and nuclear membranes to release the DNA into solution. A reducing agent, β-mercaptoethanol, is added to break the disulfide bonds between the cysteine residues and to help remove the tanins and polyphenols. A high concentration of salt is employed to remove polysaccharides. Ethylenediaminetetraacetic acid (EDTA) stops DNase activity by chelating the magnesium ions. The nucleic acid solution is extracted with chloroform-isoamyl alcohol (24:1) or 6 M ammonium acetate. The DNA in aqueous phase is precipated with ethanol or isopropanol, which makes DNA less hydrophilic in the presence of sodium ions (Na+).