Methods in molecular biology最新文献

Plant growth relies on flexible gene regulation to adapt to environmental changes. This process is ultimately controlled by transcription factors (TFs), which bind to specific DNA motifs, known as TF-binding sites (TFBS), located in the gene regulatory regions to regulate their expression. These interactions play crucial roles in plant development and responses to environmental cues, as well as in plant evolution and domestication, making both cis- (i.e., TFBS) and trans-regulatory factors as potential molecular targets in plant breeding for traits such as yield, quality, and stress resilience. These biotechnological approaches require precise knowledge of the target gene sets and TFBS specifically recognized by TFs. Recent advances in high-throughput sequencing techniques have enabled precise identification of TF target genes, especially thanks to methodologies that combine the main features of both in vitro and in vivo approaches. However, small scale and targeted approaches are still needed to evaluate the relative contribution of specific nucleotide positions in TF recognition. In this chapter, we describe a modified version of DNA Affinity Purification sequencing (DAP-seq) that replaces genomic DNA with a PCR-generated library of TFBS variants. This approach, termed targeted-DAP, allows a flexible and quantitative analysis of TF-binding using next-generation sequencing. Additionally, expressing TFs in Escherichia coli provides an economical source of proteins, enabling scalable and cost-effective analysis of DNA-binding specificities. We showed the benefits of this technique to demonstrate the contribution of the genomic context around the TFBS for specific recognition of a bHLH TF. Development of targeted DAP-seq would be of interest for the evaluation of nucleotide variation-either allelic or generated by CRISPR/Cas-within TFBS in TF recognition with predictable consequences on plant phenotypes.

Ferroptosis is a unique form of regulated cell death characterized by the toxic buildup of lipid peroxides in plasma membranes. Uncontrolled ferroptosis has been linked to various pathological conditions, including cancer progression, neurodegeneration, kidney damage, ischemia/reperfusion injury, and T-cell immunity. In this article, we present a method for detecting ferroptosis by measuring lipid peroxides in cellular membranes with the Liperfluo and BODIPY-C11 probes. The potential role of ferroptosis in immune-modulatory cells can also be assessed using this approach.

The human gut has 200-600 million neurons coordinated by an integrative system called the enteric nervous system (ENS). The ENS forms a vast network that controls all the complex activities of the gastrointestinal tract (GIT). In some intestinal alterations, this complex control is impaired by the loss or reduction of enteric neurons/glial cells due to inflammation, which affects neurotransmitter and motility activities and leads to the development of disease. Elucidating the mechanism of intestinal inflammation-induced dysfunction of GIT is one of the major gaps in inflammatory disease research. In this chapter, we present a detailed protocol that opens up the study of enteric neurons, glial cells, and smooth muscle cell activity in infectious models of murine intestinal inflammation. Primary myenteric culture mimics aspects of in vivo tissue and is an excellent platform for studying intestinal disease.

Fibroblast activation protein (FAP), scarcely expressed by fibroblasts in normal tissue, is highly expressed in activated fibroblasts, which are commonly associated with chronic inflammation and in cancer microenvironment. FAP is being explored as a therapeutic target for the treatment of fibrotic pathology. Here, we describe an FAP mRNA encapsulated in lipid nanoparticles (FAP mRNA-LNP) for use as a vaccine to attenuate the severity of experimental arthritis. This FAP mRNA-LNP vaccine may have a broader application, such as therapy for cancer and other fibrotic conditions.

Cancer-associated fibroblasts (CAFs) are a critical heterogeneous component of the tumor microenvironment (TME), playing dual roles in tumor progression. They contribute to immune evasion, epithelial-to-mesenchymal transition (EMT), angiogenesis, and extracellular matrix remodeling, while certain subsets of CAFs exhibit tumor-suppressive functions. Understanding the diversity and plasticity of CAFs is essential for developing effective therapeutic strategies. Identifying key regulators of CAFs would expand the possibility of CAF-targeted cancer therapy. Here, we present step-by-step experimental methodologies to explore potential therapeutic targets aimed at selectively suppressing the pro-tumoral activities of CAFs, while preserving or enhancing their tumor-suppressive functions.

Macrophages orchestrate multiple functions in the tumor microenvironment leading to metastatic progression including promotion of tumor cell invasion, intravasation, and extravasation at metastatic sites. In vitro assays have been developed to explore these processes in high resolution. Here we describe an in vitro protocol used to examine macrophage enhanced tumor cell extravasation and intravasation in 3D using a stratified co-culture transendothelial migration (TEM) transwell system. These assays may be generally applied in order to study different aspect of metastatic dissemination, and we show here usefulness with breast and pancreatic tumor cell lines.

Phenotypic characterization allows the study of cellular effects caused by substances or genetic modifications. Here, we demonstrate how deep learning tools can help advance phenotypic characterization using high-throughput microscopy imaging. We focus on a particular example, segmenting and classifying different cellular phenotypes, to demonstrate how an automated image analysis can be performed using open-source software that can be used without advanced deep learning knowledge. In particular, we give in-depth descriptions of how to train and deploy a deep learning pipeline for phenotypic characterization, including troubleshooting when things go wrong in different scenarios.

Major histocompatibility complex class I (MHC I) molecules play a crucial role in activating adaptive immune responses by presenting viral and tumor antigens to cytotoxic CD8⁺ T cells. Additionally, MHC I molecules have been implicated in autoimmunity through the presentation of self-peptides. The effective presentation of antigenic peptides depends on the stability of MHC I allotypes. Evaluating MHC I stability involves analyzing its degradation kinetics and determining its half-life. In this chapter, we present an assay to evaluate the degradation kinetics of MHC I molecules (both endogenous and overexpressed) in cell lines by inhibiting protein synthesis with cycloheximide. Additionally, we incorporated MG132, a proteasomal degradation inhibitor, to examine the impact of the proteasome on MHC I degradation. Furthermore, we detail a method for calculating the half-life of MHC I molecules by fitting the degradation data into a one-phase decay model.

Circular dichroism (CD) is a valuable technique for studying the structure and conformational changes of short RNAs. In this chapter, we describe how to analyze CD data from thermal unfolding experiments using the online tool ChiraKit. Different thermodynamic models that explain the CD signal are presented, along with best practices for fitting the data and reporting results. A 37-base pair-long RNA is used as an example. The spectra are first decomposed using singular value decomposition, and then the associated coefficients are fitted with a two-state reversible unfolding model to estimate the melting temperature and enthalpy of unfolding.

Linear Dichroism (LD) spectroscopy uses linearly polarized light to measure how a molecule orients itself with respect to a reference axis or, more precisely, how the transition moment of a chromophore in the molecule is oriented. This provides insight into how, e.g., molecules assemble into macromolecules and their orientation with respect to each other. Prerequisites for LD is a medium in which the molecules orient in a preferred direction and that the molecules under investigation are long enough to allow orientation. For long biomolecules such as RNA/DNA or fibrils of proteins in solution, Couette flow is an efficient way of creating a flow-induced orientation of the molecules, while recirculating a small volume of sample. In this chapter, we present the methodology behind LD spectroscopy including best practice for sample handling and data collection, as well as the interpretation of LD spectra including examples of RNA, DNA, proteins, and their complexes.