Methods in molecular biology最新文献

Analysis of the cell cycle in kinetoplastid parasites involves the assessment of the replication of single copy organelles, such as the nucleus, kinetoplast, and flagellum, alongside the observation of cell cycle stage-associated morphological changes, e.g., cell shape changes and the appearance of a mitotic spindle or cytokinesis furrow, which together allow the cell cycle stage of individual parasites to be determined. To date, most kinetoplastid cell cycle analysis has been performed using light microscopy and/or flow cytometry of fixed cells, but while these methods have proven highly valuable, microscopy can be time-consuming and flow cytometry can lack resolution. We have previously shown that imaging flow cytometry offers significant benefits for depth and speed of analysis. This is due to its ability to directly link the high-throughput and quantitative nature of standard flow cytometry with the visual and spatial data of microscopy, over an extensive array of morphological and fluorescence parameters, which can be calculated for both brightfield and fluorescence images of each cell. Furthermore, the ability to automate image analysis ensures high throughput. Here, we provide a step-by-step guide to analyzing the cell cycle of live promastigote Leishmania mexicana using imaging flow cytometry. We outline a method for quantitative DNA staining in live L. mexicana promastigotes using Vybrant™ DyeCycle™ Orange and provide protocols, guidance, and example analysis templates for using an ImageStream^®X MkII imaging flow cytometer (Cytek) to acquire and analyze brightfield and fluorescence images of the parasite to determine cell cycle stage. We also detail how to employ mNeonGreen tagging of the orphan spindle kinesin, KINF, to provide greater resolution of cell cycle position. Our automated masking and gating pipeline enables rapid, high-throughput and semi-automated analysis of the L. mexicana cell cycle in live cells, in near real time, offering many advantages over conventional analysis methods. In addition, we envisage that this pipeline could be adapted to allow similar high-throughput analysis of the cell cycle of other kinetoplastid species and outline the approaches that could be taken to achieve this.

Phytoplasmas are plant pathogens transmitted by insects that pose significant challenges for the most common experimental tasks. This is especially true concerning analyses that aim at genome sequencing, due to the phytoplasma's low abundance and its association with the host cellular matrix. This protocol provides a roadmap for researchers in the field of phytoplasma genomics, focusing on three crucial aspects: (1) DNA extraction from plant hosts, including a protocol for low-concentration samples, (2) Sequencing strategies, emphasizing accurate base calling (particularly for Oxford Nanopore) and addressing mixed plant/phytoplasma samples, (3) Phytoplasma genome assembly and analysis, detailing methodologies and exploring computational/comparative techniques to decode phytoplasma genomes. With a focus on tackling pivotal challenges and harnessing possibilities proposed by these advancements, this approach equips researchers to unlock the secrets of these enigmatic plant pathogens.

GeneDiscoveR, a novel R package, facilitates gene discovery in plant traits via comparative genomics. Despite the advancements in plant genome sequencing technologies, gene discovery in model and even more in non-model plants remains challenging. To address this gap, we introduce GeneDiscoveR, which enables the identification of orthogroups linked to specific plant traits or treatment responses. Leveraging extensive genomic data from diverse plant lineages, for instance, liverworts, we showcase its efficacy in identifying trait-specific genes. OrthoFinder defines orthologs, while GeneDiscoveR statistically detects trait-associated orthogroups. Here, we applied GeneDiscoveR to liverwort genomes to find enriched orthogroups in species with oil bodies within specialized cells or with many oil bodies in all cells. Additionally, we used it to identify OGs related to self-incompatibility from Brassicaceae genomes. This bioinformatics pipeline offers insights into plant trait genetics, aiding future gene discovery endeavors.

Germination is a highly dynamic developmental transition from dry quiescent seeds to vegetative seedlings which involves major chromatin rearrangements and changes in transcriptional programs. Assay for transposase-accessible chromatin with sequencing (ATAC-seq) is a quick and reproducible method for quantifying relative chromatin accessibility genome-wide. In this chapter, we describe the use of ATAC-seq for profiling chromatin accessibility changes and differential transcription factor binding site accessibility during germination from enriched embryos.

Biosensors are devices leveraging biological modules for the detection of molecules of interest, including biomarkers of inflammation and cancer. Using elements capable of detecting small molecules, such as transcription factors, aptamers, and antibodies, they specifically and sensitively interact with a target analyte, producing a detectable response. By applying traditional and synthetic biology approaches, these modules can be engineered to detect different molecules. A whole-cell biosensor (WCB) is a subtype of biosensor in which a whole living organism with an active metabolism is used to detect a compound. WCBs based on synthetic transcription factors are adaptable and accessible sensing tools for the detection of small soluble molecules. In this chapter, we describe a pipeline for the construction of a prokaryotic biosensor strain bearing a genetic circuit that integrates a custom-made transcription factor. As an example, we use the strain Escherichia coli MG1655 (pCKT-Sphnx, pHC_DYO-LacI-R), which has been engineered to detect neuraminic acid, an oral cancer biomarker present in saliva.

Enzyme assays are used to measure the activity or concentration of enzymes in biochemical or cell-based systems. Most enzyme assays are based on the detection of fluorescent, luminescent, or spectrophotometric endpoint signals. In recent years, they have been developed and widely used for diagnostics, mechanisms of action, and inflammatory activities. An enzyme assay essentially works by the conversion of a substrate into a product by the enzyme of interest. In this case, it is extremely important to know the optimal conditions for enzyme activity, as these affect the specificity and efficacy of the assay. For optimal reaction conditions, temperature, pH, and the presence of ions should be considered. In this chapter, the enzymatic assays for the detection of the enzymes N-acetylglucosaminidase (NAG), myeloperoxidase (MPO), and eosinophil peroxidase (EPO) are addressed. These assays are used to assess inflammatory parameters, for example, at the peripheral level in models of viral disease. They are based on an index of neutrophil, macrophage, or eosinophil accumulation in inflammatory tissues from animals by measuring the specific activity of the marker enzymes. The enzyme activity assays discussed here are based on colorimetric reactions compatible with any experimental model in which the respective cells has an active role. The advantage of using these enzymatic assays in inflammation response models is that they are simpler and less expensive compared to techniques such as Western blot or quantitative PCR.

Understanding the dynamic changes in the intracellular metabolism of immune cells has become fundamental to understanding the regulation of their effector functions. Optical metabolic imaging, consisting of optical redox ratio and fluorescence lifetime imaging microscopy of endogenous coenzymes NAD(P)H and FAD, offers a label-free and non-invasive approach to assess intracellular metabolism at the single-cell level. The major advantage of optical metabolic imaging is that it can assess heterogeneity in the sample with spatiotemporal resolution. While this approach has been mainly used to perform metabolic imaging on in vitro samples, studies have demonstrated that it also performs well in live, intact animals, and is sensitive to dynamic changes in immune cell activation. This chapter describes protocols for performing optical metabolic imaging of innate immune cells at the caudal fin wound microenvironment of larval zebrafish following sterile injuries. However, the protocol can be readily applied to other cell types and in different biological contexts.

Tight junctions, which are located on the apical side of epithelial cells, are key components of epithelial intercellular junctional complexes. Tight junctions seal the space between neighboring cells and act as a semipermeable barrier, preventing the paracellular transport of ions and molecules. The tight junctions are calcium-dependent as their disassembly can be triggered by the depletion of calcium ions, and the subsequent addition of calcium promotes the formation of tight junctions and the restoration of their barrier function. This reversible process, known as the calcium switch, is often used to study tight junction dynamics. This chapter describes the calcium switch protocol for disrupting and reestablishing tight junctions using MDCK cells as an in vitro model. It also provides protocols for evaluating tight junction formation and integrity using the noninvasive, quantitative transepithelial electrical resistance (TEER) assay.

Somatic hypermutation (SHM) is a critical process in adaptive immunity, enabling the generation of high-affinity antibodies through targeted mutations in immunoglobulin variable (IgV) regions. Here, we provide a comprehensive workflow combining immunization, molecular biology, and bioinformatics to investigate SHM mechanisms and outcomes. This is a general protocol for studying SHM at the VH186.2 region in C57BL/6 mice. While this method can be applied broadly, this chapter will detail the protocol used to test the effects of exonuclease 1(EXO1) knock-in mutation (Exo1^D173A, or Exo1^DA) or knock-out (KO) on hypermutation post-immunization by immunizing age-matched mice with NP(33)-CGG on alum. We start by immunizing and sacrificing the animals to obtain spleens for RNA extraction. We then create cDNA libraries and investigate VH186.2 region mutation to analyze SHM.

Clinical metagenomics (CMg) involves the untargeted sequencing of the genetic content of samples collected from patients and is a highly promising method for the diagnosis of infectious disease. Depending on the sample type, CMg can be reliant on the removal of the host genetic material from the sample to support detection of microbial pathogens, and this selective process (or an otherwise low abundance of microbial cells in the sample) may result in concentrations of DNA too low for productive sequencing. Whole genome amplification (WGA), the nonselective amplification of the total DNA of a sample, can be applied to significantly increase the concentration of DNA and enable CMg sequencing. This chapter describes the methods for the amplification of microbial DNA extracted from host-depleted wound swab samples using the GenomiPhi^™ V3 Ready-To-Go^™ (Cytiva) DNA WGA kit and host-depleted whole blood samples using the REPLI-g^® Single-Cell WGA kit (Qiagen). This is followed by the de-branching and bead-based clean-up of the amplified DNA, resulting in highly concentrated DNA ready for CMg DNA sequencing.