Nature Protocols最新文献

The properties of the interface between materials have practical implications in various fields, encompassing capillary action, foam and emulsion stability, adhesion properties of materials and mass and heat transfer processes. Studying the dynamics of interfaces is also fundamental for understanding intermolecular interactions, change of molecular conformations and molecular aggregations. Pendant-drop tensiometry and its extension, the oscillating drop method, are simple, versatile methods used to measure surface tension, interfacial tension and interfacial rheological properties. These methods can, however, generate unreliable results because of inadequate material preparation, an incorrect calibration method, inappropriate selection of data for analysis, neglect of optical influences or operating the system outside the linear viscoelastic regime. In addition, many studies fail to report accurate uncertainties. This protocol addresses all these critical points and provides detailed descriptions of some operation tips relating to purifying methods for different kinds of material, the time frame for analyzing measurement data, the correction method for optical effects, implementation of the oscillating method with a common programmable pump and remedies for some common problems encountered during the measurement. Examples of interfacial tension measurements for two- and three-phase systems, as well as interfacial dilational modulus measurements for N₂ and surfactant solutions, are provided to illustrate procedural details and results. A single measurement takes minutes to hours to complete, while the entire protocol, including the leak test, cleaning, repeated measurements and data analysis, may take several days.

Hematoxylin- and eosin-stained whole-slide images (WSIs) are the foundation of diagnosis of cancer. In recent years, development of deep learning-based methods in computational pathology has enabled the prediction of biomarkers directly from WSIs. However, accurately linking tissue phenotype to biomarkers at scale remains a crucial challenge for democratizing complex biomarkers in precision oncology. This protocol describes a practical workflow for solid tumor associative modeling in pathology (STAMP), enabling prediction of biomarkers directly from WSIs by using deep learning. The STAMP workflow is biomarker agnostic and allows for genetic and clinicopathologic tabular data to be included as an additional input, together with histopathology images. The protocol consists of five main stages that have been successfully applied to various research problems: formal problem definition, data preprocessing, modeling, evaluation and clinical translation. The STAMP workflow differentiates itself through its focus on serving as a collaborative framework that can be used by clinicians and engineers alike for setting up research projects in the field of computational pathology. As an example task, we applied STAMP to the prediction of microsatellite instability (MSI) status in colorectal cancer, showing accurate performance for the identification of tumors high in MSI. Moreover, we provide an open-source code base, which has been deployed at several hospitals across the globe to set up computational pathology workflows. The STAMP workflow requires one workday of hands-on computational execution and basic command line knowledge.

Recent advances in single-cell sequencing technologies offer an opportunity to explore cell–cell communication in tissues systematically and with reduced bias. A key challenge is integrating known molecular interactions and measurements into a framework to identify and analyze complex cell–cell communication networks. Previously, we developed a computational tool, named CellChat, that infers and analyzes cell–cell communication networks from single-cell transcriptomic data within an easily interpretable framework. CellChat quantifies the signaling communication probability between two cell groups using a simplified mass-action-based model, which incorporates the core interaction between ligands and receptors with multisubunit structure along with modulation by cofactors. Importantly, CellChat performs a systematic and comparative analysis of cell–cell communication using a variety of quantitative metrics and machine-learning approaches. CellChat v2 is an updated version that includes additional comparison functionalities, an expanded database of ligand–receptor pairs along with rich functional annotations, and an Interactive CellChat Explorer. Here we provide a step-by-step protocol for using CellChat v2 on single-cell transcriptomic data, including inference and analysis of cell–cell communication from one dataset and identification of altered intercellular communication, signals and cell populations from different datasets across biological conditions. The R implementation of CellChat v2 toolkit and its tutorials together with the graphic outputs are available at https://github.com/jinworks/CellChat. This protocol typically takes ~5 min depending on dataset size and requires a basic understanding of R and single-cell data analysis but no specialized bioinformatics training for its implementation.

Perfusable hydrogels have garnered substantial attention in recent years for the fabrication of microphysiological systems. However, current methodologies to fabricate microchannels in hydrogel platforms involve sophisticated equipment and techniques, which hinder progress of the field. In this protocol, we present a cost-effective, simple, versatile and ultrafast method to create perfusable microchannels of complex shapes in photopolymerizable hydrogels. Our method uses one-step UV photocross-linking and a photomask printed on inexpensive transparent films, to photopattern both synthetic (PEG-norbornene) and natural (hyaluronic acid-norbornene) hydrogels in just 0.8 s. Moreover, these perfusable hydrogels are fully integrated into a custom-made microfluidic device that allows continuous fluid perfusion when connected to an external pump system. This methodology can be easily reproduced by professionals with basic laboratory skills and a fundamental knowledge of polymers and materials science. In this protocol, we demonstrate the functionality of our photopatterned hydrogels by seeding human endothelial cells into the microchannels, culturing them under dynamic conditions for 7 d, and exposing them to inflammatory stimuli to elicit cellular responses. This highlights the versatility of our platform in fabricating microphysiological systems and different microenvironments. The fabrication of perfusable channels within the hydrogels, including the fabrication of the microfluidic devices, requires ~3 d. The development of the cell-seeded microphysiological system, including the stimulation of cells, takes ~7 d. In conclusion, our approach provides a straightforward and widely applicable solution to simplify and reduce the cost of biofabrication techniques for developing functional in vitro models using perfusable three-dimensional hydrogels.

The embryonic and extraembryonic tissue interactions underlying human embryogenesis at implantation stages are not currently understood. We have generated a pluripotent stem cell-derived model that mimics aspects of peri-implantation development, allowing tractable experimentation otherwise impossible in the human embryo. Activation of the extraembryonic lineage-specific transcription factors GATA6 and SOX17 (hypoblast factors) or GATA3 and TFAP2C (encoding AP2γ; trophoblast factors) in human embryonic stem (ES) cells drive conversion to extraembryonic-like cells. When combined with wild-type ES cells, self-organized embryo-like structures form in the absence of exogenous factors, termed human inducible embryoids (hiEmbryoids). The epiblast-like domain of hiEmbryoids polarizes and differentiates in response to extraembryonic-secreted extracellular matrix and morphogen cues. Extraembryonic mesenchyme, amnion and primordial germ cells are specified in hiEmbryoids in a stepwise fashion. After establishing stable inducible ES lines and converting ES cells to RSeT culture media, the protocol takes 7–10 d to generate hiEmbryoids. Generation of hiEmbryoids can be performed by researchers with basic expertise in stem cell culture.

One of the foremost challenges in nanobiotechnology is obtaining direct evidence of nanoparticles' absorption and internalization in plants. Although confocal laser scanning microscopy (CLSM) or transmission electron microscopy (TEM) are currently the most commonly used tools to characterize nanoparticles in plants, subjectivity of researchers, incorrect sample handling, inevitable fluorescence leakage and limitations of imaging instruments lead to false positives and non-reproducibility of experimental results. This protocol provides an easy-to-operate dual-step method, combining CLSM for macroscopic tissue examination and TEM for cellular-level analysis, to effectively trace single particles in plant roots with accuracy and precision. In addition, we also provide detailed methods for processing plant materials before imaging, including cleaning, and staining, to maximize the accuracy and reliability of imaging. This protocol involves currently commonly used nanomaterial types, such as metal-based and doped carbon-based materials, and enables accurate localization of nanoparticles with different sizes at the cell level in Arabidopsis thaliana root samples either through contrast or element mapping analysis. It serves as a valuable reference and benchmark for scholars in plant science, chemistry and environmental studies to understand the interaction between plant roots and nanomaterials and to detect the distribution of nanomaterials in plants. Excluding plant culture time, the protocol can be completed in 4-5 d.

We recently developed directed methylation with long-read sequencing (DiMeLo-seq) to map protein-DNA interactions genome wide. DiMeLo-seq is capable of mapping multiple interaction sites on single DNA molecules, profiling protein binding in the context of endogenous DNA methylation, identifying haplotype-specific protein-DNA interactions and mapping protein-DNA interactions in repetitive regions of the genome that are difficult to study with short-read methods. With DiMeLo-seq, adenines in the vicinity of a protein of interest are methylated in situ by tethering the Hia5 methyltransferase to an antibody using protein A. Protein-DNA interactions are then detected by direct readout of adenine methylation with long-read, single-molecule DNA sequencing platforms such as Nanopore sequencing. Here we present a detailed protocol and practical guidance for performing DiMeLo-seq. This protocol can be run on nuclei from fresh, lightly fixed or frozen cells. The protocol requires 1-2 d for performing in situ targeted methylation, 1-5 d for library preparation depending on desired fragment length and 1-3 d for Nanopore sequencing depending on desired sequencing depth. The protocol requires basic molecular biology skills and equipment, as well as access to a Nanopore sequencer. We also provide a Python package, dimelo, for analysis of DiMeLo-seq data.

Successful delivery of nucleic acid therapeutics to diseased sites would present a pivotal advancement in cancer treatment. However, progress has been hindered by the lack of efficient tumor-selective vectors via clinical systemic routes, the blood-brain barrier for brain tumors and problems with repeated administrations. We present a new generation of M13 phage-based vectors termed transmorphic phage/adeno-associated virus (AAV) (TPA), wherein the phage genome has been excised to facilitate exclusive packaging of human AAV DNA by phage coat proteins. Here we provide a detailed protocol for the molecular cloning of DNA into the TPA construct, display of disease-specific ligands on the helper phage capsid for cell targeting and entry, and packaging of TPA DNA by helper phage coat proteins in a bacterial host. Furthermore, we provide methods for mammalian cell transduction and assessment of transgene expression in vitro as well as in vivo application of TPA particles in tumor-bearing mice. Unlike other similar methods, our protocol enables high-yield production and control of helper phage quantity in TPA preparations. Moreover, compared with existing M13 phage vectors, TPA particles can accommodate large size transgene inserts, despite being considerably more compact, providing superior gene delivery through enhanced diffusion across the extracellular matrix, improved cellular binding and entry and increased vector DNA accumulation in the nucleus. The protocol encompasses a timeline of 4-5 months, including construction and production of TPA particles with transgene and targeted ligand and in vitro/in vivo testing. This protocol can be conducted by researchers trained in basic molecular biology/bacteriology research techniques.

Epigenetic modifications and spatial proximities of nucleic acids and proteins play important roles in regulating physiological processes and disease progression. Currently available cell imaging methods, such as fluorescence in situ hybridization (FISH) and immunofluorescence, struggle to detect low-abundance modifications and their spatial proximities. Here we describe a step-by-step protocol for three DNA-encoded amplifying FISH-based imaging strategies to overcome these challenges for varying applications: base-encoded amplifying FISH (BEA-FISH), pairwise proximity-differentiated amplifying FISH (PPDA-FISH) and cellular macromolecules-tethered DNA walking indexing (Cell-TALKING). They all use the similar core principle of DNA-encoded amplification, which transforms different nonsequence molecular features into unique DNA barcodes for in situ rolling circle amplification and FISH analysis. This involves three key reactions in fixed cell samples: target labeling, DNA encoding and rolling circle amplification imaging. Using this protocol, these three imaging strategies achieve in situ counting of low-abundance modifications alone, the pairwise proximity-differentiated visualization of two modifications and the exploration of multiple modifications around one protein (one-to-many proximity), respectively. Low-abundance modifications, including 5-hydroxymethylcytosine, 5-formylcytosine, 5-hydroxymethyluracil and 5-formyluracil, are clearly visualized in single cells. Various combinatorial patterns of nucleic acid modifications and/or histone modifications are found. The whole protocol takes ~2-4 d to complete, depending on different imaging applications.

Diffusion magnetic resonance imaging (dMRI) is a versatile imaging technique that has gained popularity thanks to its sensitive ability to measure displacement of water molecules within a living tissue on a micrometer scale. Although dMRI has been around since the early 1990s, its applications are constantly evolving, primarily regarding the inference of structural connectomics from nerve fiber trajectories. However, these applications require expertise in image processing and statistics, and it can be difficult for a newcomer to choose an appropriate pipeline to fit their research needs, not least because dMRI is such a flexible methodology that dozens of acquisition and analysis pipelines have been developed over the years. This introductory guide is designed for graduate students and researchers in the neuroscience community who are interested in integrating this new methodology regardless of their background in neuroimaging and computational tools. The guide provides a brief overview of the basic dMRI methodologies but focuses on its applications in neuroplasticity and connectomics. The guide starts with dMRI experimental designs and a complete step-by-step pipeline for structural connectomics. The following section covers the basics of dMRI, including parameters and clinical applications (apparent diffusion coefficient, mean diffusivity, fractional anisotropy and microscopic fractional anisotropy), as well as different approaches and models. The final section focuses on structural connectomics, covering subjects from fiber tracking (techniques, evaluation and limitations) to structural networks (constructing, analyzing and visualizing a network).