Methods in molecular biology最新文献

Metabolic profiling (untargeted metabolomics) aims for a global unbiased analysis of metabolites in a cell or biological system. It remains a highly useful research tool used across various analytical platforms. Incremental improvements across multiple steps in the analytical process may have large consequences for the end quality of the data. Thus, this chapter concentrates on which aspects of quality assurance can be implemented by a lab in the (pre-)analytical stages of the analysis to improve the overall end quality of their data. The scope of this chapter is limited to liquid-chromatography-mass spectrometry (LC-MS)-based profiling, which is one of the most widely utilized platforms, although the general principles are applicable to all metabolomics experiments.

Untargeted analysis by LC-MS is a valuable tool for metabolic profiling (metabonomics/metabolomics), and applications of this technology have grown rapidly over the past decade. LC-MS offers advantages of speed, sensitivity, relative ease of sample preparation, and large dynamic range compared to other platforms in this role. However, like any analytical approach, there are still drawbacks and challenges that have to be overcome, some of which are being addressed by advances in both column chemistries and instrumentation. In particular, the combination of LC-MS with ion mobility offers many new possibilities for improved analyte separation, detection, and structural identification. There are many untargeted LC-MS approaches which can be applied to metabolic phenotyping, and these usually need to be optimized for the type of sample, the nature of the study, or the biological question. Some of the main LC-MS approaches for untargeted metabolic phenotyping are described in detail in the following protocol.

Negative staining electron microscopy is one of the easiest ways to determine the shape and dimensions of multimeric protein complexes over 100 kDa molecular weight. This method requires small volumes (< 10 μL) of dilute protein (0.01-0.1 mg/mL). Here we describe a method for quickly crosslinking a protein sample and preparing negative stained grids, and we also describe how to label a biotinylated protein subunit with avidin to determine its position within a complex using negative staining EM. This method should be generally applicable for most soluble protein complexes.

Trapped ion mobility spectrometry (TIMS) using parallel accumulation serial fragmentation (PASEF^®) is an advanced analytical technique that offers several advantages in mass spectrometry (MS)-based lipidomics. TIMS provides an additional dimension of separation to mass spectrometry and accurate collision cross-section (CCS) measurements for ions, aiding in the structural characterization of molecules. This is especially valuable in lipidomics for identifying and distinguishing isomeric or structurally similar compounds. On the other hand, PASEF technology allows for fast and efficient data acquisition by accumulating ions in parallel and then serially fragmenting them. This accelerates the analysis process and improves throughput, making it suitable for high-throughput applications. Moreover, the combination of TIMS and PASEF reduces co-elution and ion coalescence issues, leading to cleaner and more interpretable mass spectra. This results in higher data quality and more confident identifications. In this chapter, a data-dependent TIMS-PASEF^® workflow for lipidomics analysis is presented.

The thyroid hormones, thyroxine (T4) and triiodothyronine (T3), are pivotal in regulating various physiological processes including growth, development, and metabolism. The biological actions of thyroid hormones are primarily initiated by binding to nuclear thyroid hormone receptors (TRs). These receptors, belonging to the superfamily of nuclear receptors, act as ligand-dependent transcription factors. Transcriptional regulation by TRs is mediated by the recruitment of coregulators, governing activation and repression of target genes, thereby modulating cellular responses to thyroid hormones. Beyond this canonical genomic pathway, TH can regulate the expression of genes not directly bound by TRs through cross-talk mechanisms with other transcription factors and signaling pathways. Thyroid hormones can also elicit rapid non-genomic effects, potentially mediated by extranuclear TR proteins or by interactions with membrane receptors such as integrin αvβ3. This non-genomic mode of action adds another layer of complexity to the diverse array of physiological responses orchestrated by thyroid hormones, expanding our understanding of their multifaceted actions.

The generation of hypothyroid and hyperthyroid mouse models is one of the approaches used to investigate the complex interplay between thyroid hormones and the immune system. We present a detailed protocol describing how to induce endotoxic shock by lipopolysaccharide (LPS) administration, and how to investigate the role of immune populations, specifically macrophages, responding to endotoxemia.This book chapter provides the use of different molecular techniques, such as Western Blotting, Immunohistochemistry, q-PCR, Luciferase assays, or ChIP assays, with which researchers can gain valuable insights into the immune system's interaction with hormonal signaling pathways, for instance, examining the effect of thyroid hormones on signaling of STAT3, NF-κB, and ERK in response to LPS, and inflammatory mediators, such as interleukin-6 (IL-6) or tumor necrosis factor-alpha (TNFα) within these cells. The signaling pathways involved and the exploration of the relationship between thyroid hormones and the immune system can be analyzed using several molecular biology technologies in order to clarify their interplay in various disease states.

Hypothyroidism, characterized by inadequate production of thyroid hormones, and malaria, a mosquito-borne infectious disease caused by Plasmodium parasites, are significant health concerns worldwide. Understanding the interplay between these two conditions could offer insights into their complex relationship and potential therapeutic strategies. To induce hypothyroidism, pharmacological inhibition of thyroid hormone synthesis was employed. Subsequently, mice were infected with Plasmodium berghei ANKA to simulate cerebral malaria infection. It needs to monitor the progression of the disease in male mice before it can identify infiltrating immune system populations of interest in the brain by multiparametric techniques such as flow cytometry.

Electrophoretic Mobility Shift Assay (EMSA) is a powerful technique for studying nucleic acid and protein interactions. This technique is based on the principle that nucleic acid-protein complex and nucleic acid migrate at different rates due to differences in size and charge. Nucleic acid and protein interactions are fundamental to various biological processes, such as gene regulation, replication, transcription, and recombination. Transcription factors and DNA interaction regulate gene expression. Homeobox (Hox) genes encode a family of transcription factors and are essential during embryonic development. Understanding the specific interactions between Hox proteins and their DNA targets is critical for elucidating the mechanisms underlying their regulatory functions.This chapter explains the principles and methodologies of EMSA in the context of Hox genes. This chapter includes detailed experimental design, including the formulation of reagents, labeling DNA probes, preparation of nuclear extracts/recombinant proteins, and binding conditions. The step-by-step protocol has been provided as an initial reference point to help a researcher conduct EMSA.

A key goal of biology is to understand the origin of the many cell types that can be observed during diverse processes such as development, regeneration, and disease. Single-cell RNA-sequencing (scRNA-seq) is commonly used to identify cell types in a tissue or organ. However, organizing the resulting taxonomy of cell types into lineage trees to understand the origins of cell states and relationships between cells remains challenging. Here we present LINNAEUS (Spanjaard et al, Nat Biotechnol 36:469-473. https://doi.org/10.1038/nbt.4124 , 2018; Hu et al, Nat Genet 54:1227-1237. https://doi.org/10.1038/s41588-022-01129-5 , 2022) (LINeage tracing by Nuclease-Activated Editing of Ubiquitous Sequences)-a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA-seq with computational analysis of lineage barcodes, generated by genome editing of transgenic reporter genes, LINNAEUS can be used to reconstruct organism-wide single-cell lineage trees. LINNAEUS provides a systematic approach for tracing the origin of novel cell types, or known cell types under different conditions.

Measurements of cell phylogeny based on natural or induced mutations, known as lineage barcodes, in conjunction with molecular phenotype have become increasingly feasible for a large number of single cells. In this chapter, we delve into Quantitative Fate Mapping (QFM) and its computational pipeline, which enables the interrogation of the dynamics of progenitor cells and their fate restriction during development. The methods described here include inferring cell phylogeny with the Phylotime model, and reconstructing progenitor state hierarchy, commitment time, population size, and commitment bias with the ICE-FASE algorithm. Evaluation of adequate sampling based on progenitor state coverage statistics is emphasized for interpreting the QFM results. Overall, this chapter describes a general framework for characterizing the dynamics of cell fate changes using lineage barcoding data.