T cells are a key component of the adaptive immune system, playing a central role in the body's defense against pathogens and diseases. Antigen discovery and longitudinal immunomonitoring of antigen-specific T cell responses offer valuable insights into the activity and efficacy of immunotherapies and can guide development of new prophylactic or therapeutic treatments, such as vaccines and cellular therapies. Traditional immunomonitoring methods for T cell analysis, while foundational, offer limited insights because of the complexity and vast heterogeneity of antigen-specific T cells. Here, traditional and cutting-edge technologies for profiling antigen-specific T cells are reviewed, highlighting the evolution from low- to high-dimensional analyses. The principles, applications, benefits and limitations of each technique are outlined, and the need for assay harmonization and standardization is discussed. The importance of careful sample processing is also considered. This review highlights how immunomonitoring techniques can complement each other to maximize understanding of T cell-mediated immunity, a key aspect shaping immunotherapeutic development, now and in the future.

Super-resolution structured illumination microscopy (SIM) is a powerful and versatile technique for investigating fundamental cell biological processes underlying development and disease. With the growing availability of commercial SIM systems, the emergence of advanced SIM modalities and increased access through imaging facilities, adoption of SIM across research laboratories is accelerating. However, fully leveraging the capabilities of SIM remains challenging, even for experienced microscopists, due to its susceptibility to imaging artifacts and the limited availability of accessible analysis pipelines. Here, to address these challenges, we developed SIMworks, a broadly compatible, integrated software platform designed to streamline quality control, processing and quantitative analysis of large-scale SIM datasets. Building on our previously established tools-SIMcheck, Chromagnon, ChaiN and SIMinspector-SIMworks provides a unified framework compatible with both custom and commercial SIM systems and modalities. Its modular architecture includes tools for calibration, alignment and data processing, as well as robust artifact detection and correction. These are complemented by segmentation and quantification modules for a broad range of cellular and nuclear structures, enabling automated, intensity-based analysis. Each module includes detailed guidance on interpretation and troubleshooting to support usability and reproducibility, enabling both new learners and experienced users to apply best practices in SIM imaging. The complete workflow can be performed within approximately half a day, depending on dataset size and complexity. SIMworks represents the first comprehensive, modular solution for SIM data processing, augmentation and quantitative analysis, lowering technical barriers and enhancing data reliability. By facilitating rigorous workflows, SIMworks promotes the broader integration of quantitative SIM imaging into biomedical research.

Organoids provide a versatile platform for studying fundamental biology, complementing traditional cell culture and in vivo models. Their unique features, such as self-organization and the possibility for their precise manipulation, have enabled key discoveries in tissue homeostasis, development and disease. This tutorial presents an overview of organoid technologies and protocols across a broad spectrum of applications, from investigating cell fate decisions and cell-cell or cell-microbe interactions to the study of genetic diseases, species evolution and translational/clinical questions. By focusing on adult stem cell-derived intestinal and human pluripotent stem cell-derived brain organoids, we highlight models with distinct characteristics that together reflect the broader spectrum of organoid systems, tissue types and research contexts. For applications not supported by these models, we discuss organoids derived from other tissues. We also outline current challenges in the field and highlight emerging innovations that are promising to shape future directions.

Fibrosis is characterized by excessive deposition of extracellular matrix, leading to organ stiffening and progressive dysfunction. Cardiac fibrosis, in particular, is a common feature in ischemic heart failure, genetic cardiomyopathies, diabetes mellitus and aging, which exacerbates cardiac dysfunction and ultimately contributes to increased morbidity and mortality. Despite its clinical burden and importance, there are currently no US Food and Drug Administration-approved drugs that specifically target cardiac fibrosis. This gap is largely due to the lack of reliable translational drug discovery platforms. To address this unmet clinical need, we present our new approach methodology drug screening platform for identifying novel compounds to treat cardiac fibrosis. This high-throughput screening system uses human reporter induced pluripotent stem (iPS) cell-derived cardiac fibroblasts to identify initial hits with potential antifibrotic effects, followed by counter-screening using iPS cell-derived cardiomyocytes to exclude compounds with potential cardiotoxicity. Compared to traditional primary cell-based approaches, our iPS cell-based workflow is robust, scalable and capable of screening ~5,000 compounds within 6-8 weeks. This protocol provides a versatile and efficient platform for phenotypic drug discovery with broad potential for translational applications in medicine.

High-spatial-resolution in situ mapping of biomolecules within tissue reveals critical insights into the complex molecular landscape and spatial organization of biological systems. Mass spectrometry imaging (MSI) is a powerful tool for spatially resolved molecular analysis of biological samples, with ongoing demand for improved spatial resolution. Tissue expansion combined with MSI (TEMI) is a recently developed approach that enables multiomics molecular mapping across various biological tissues with significantly improved spatial resolution. Unlike conventional methods that depend on instrument-based enhancements in spatial resolution, TEMI physically enlarges tissue samples via harsh-condition-free hydrogel expansion, achieving more than 3.5-fold increase in effective imaging resolution using standard MSI instrumentation. TEMI delivers single-cell spatial resolution in tissue samples and enables detection of biomolecular heterogeneity that remains uncharacterizable in unexpanded tissue using conventional MSI. Notably, TEMI supports high-spatial-resolution mapping of multiple biomolecular classes-including lipids, metabolites, N-glycans, peptides and proteins-within a single tissue sample. Here, we provide a detailed, step-by-step guide for TEMI, including hydrogel-based tissue expansion under mild conditions, cryosectioning of the expanded tissue-hydrogel sample, a comprehensive experimental workflow for multiomics TEMI on a single tissue section, data acquisition and visualization pipelines, as well as troubleshooting tips. Overall, we demonstrate that TEMI overcomes the long-standing spatial limitations of MSI without requiring hardware modifications, ensuring compatibility with existing MSI instruments and promoting broad accessibility and adoption within the research community.

Neuronal innervation plays a pivotal role in controlling tissue function during homeostasis and regeneration, as well as in pathological contexts such as inflammation, autoimmune disorders, fibrosis and cancer. A major obstacle in understanding neuron-tissue interactions at the molecular level is that neuronal cell bodies reside in peripheral ganglia often far outside the organ of interest and are therefore typically excluded in common single-cell datasets of tissues. Here we developed Trace-n-Seq to address this issue-a method that combines retrograde tracing with fluorescence-activated cell sorting and single-cell sequencing to molecularly profile individual neurons innervating healthy or diseased tissues. Trace-n-Seq can be used to explore the specific gene expression signatures of peripheral neurons at single-cell resolution. The method utilizes retrograde axonal tracing using Fast Blue, ganglia dissociation and fluorescence-activated cell sorting followed by single-cell RNA sequencing to enable the isolation and transcriptomic analysis of ganglia. Unlike bulk or whole-ganglia single-cell RNA sequencing without retrograde labeling, Trace-n-Seq allows the characterization of organ-specific neurons with single-cell resolution, eliminating background from uninvolved neurons and unrelated cell types located in the same ganglion. The procedure allows researchers to obtain molecular transcriptomes of tissue-innervating neurons and to study their plasticity, subtype identity and potential interactions with the tissue microenvironment. The complete Trace-n-Seq workflow can be performed in 2 weeks and is suitable for researchers with experience in molecular biology, neuronal tissue handling, sequencing techniques and bioinformatic analysis.

Developing reproducible human disease models is a central goal of biomedical research and personalized medicine. Induced pluripotent stem (iPS) cell-derived models enable investigation of underlying cellular and molecular mechanisms in humans. However, obtaining reprogrammable somatic cells is a challenge, especially when patients have limited access to hospital and research facilities. Here we provide a step-by-step protocol for noninvasive isolation of human keratinocytes via trypsinization from scalp hair with intact follicles. The samples can be collected remotely by the donor, a family member or a healthcare provider using a kit and shipped long distance at ambient temperature. This offers a major advantage over widely used methods for iPS cell generation from other somatic cells, for example, dermal fibroblasts or peripheral blood mononuclear cells (PBMCs) (from invasive skin biopsies or blood collection), or renal epithelial cells (from urine). Keratinocytes can be reprogrammed to iPS cells that give rise to all three cell lineages, including the neural lineage, and used to generate cerebral organoids. The protocol yields iPS cells within 2 months of receiving the hair samples and requires basic familiarity with mammalian cell culture techniques without the need for specialized equipment. Generation of cerebral organoids from iPS cells requires 30-40 d and specialized equipment (an orbital shaker) for culture.

Organoids are powerful models for studying tissue dynamics across multiple cellular generations and offer key insights into organ homeostasis, cellular differentiation and disease. Live imaging of organoids is an essential tool for understanding dynamic processes on the cell level, while still in the tissue context. It allows for simultaneous quantification of gene expression and reconstruction of lineage trees, while tracking cells over space and time. Here, we present protocols for long-term imaging and quantitative analysis of intestinal organoids. Our workflow consists of sample preparation, experimental manipulations (such as drug treatments, laser ablations and fluorescence recovery after photobleaching), long-term live imaging (120 h), in situ fixation and permeabilization, multiplexed antibody staining and single-cell tracking with lineage reconstruction. The workflow is broadly applicable to studying dynamic cellular processes in both 2D and 3D organoids, at timescales from minutes to days. We outline strategies for optimizing organoid health, imaging conditions and experimental interventions to ensure efficient downstream analysis. In addition, we describe how this workflow enables real-time quantification of gene expression using fluorescent reporters and inferring cell type changes by combining multiplexed antibody staining with cell-tracking data. The skills required for following these protocols are organoid culturing and standard live-cell confocal microscopy, and the full experimental protocol takes ~2 weeks. Together, these protocols provide a comprehensive approach for studying cellular behavior, lineage trees, expression dynamics and cell-cell interactions in organoids.

The dynamic structural reconstruction of Cu-based catalysts profoundly influences activity, selectivity and stability during electrochemical CO2 reduction (CO2RR). However, it lacks standardized methodologies for probing and actively managing these transformations. Here we present a modular, reproducible Protocol that integrates electrochemical control, in situ/operando spectroscopy and mechanistic analysis to systematically investigate and regulate Cu catalyst reconstruction under CO2RR conditions. This Protocol establishes a comprehensive 'reconstruction-understanding-intervention' workflow comprising (1) the identification and taxonomy of reconstruction phenomena, (2) quantification of electrochemical and environmental factors governing reconstruction, (3) correlation of structural dynamics with catalytic behavior through complementary in situ/operando Raman, infrared, X-ray absorption spectroscopy and quasi-in situ X-ray photoelectron spectroscopy measurements, and (4) development of rational reconstruction-control strategies that steer catalysts toward desired active states. A systematic approach is delineated to correlate reconstruction dynamics with catalytic performance and actively direct the process toward desired active states via three primary strategies: catalyst structure modulation, electrochemical operation regulation and reaction microenvironment management. The methodology is validated using representative Cu-based systems, including commercial Cu, oxide-derived Cu and bimetallic Cu-X catalysts, demonstrating enhanced performance and stability of CO2RR. This workflow also provides an adaptable framework for investigating dynamic surface evolution in other electrocatalytic reactions. This Protocol provides useful framework for the rational development of adaptive, stable and selective electrocatalysts.

Mammalian embryonic development is a highly orchestrated process initiated by the fusion of the oocyte with sperm to generate the zygote. In humans, the zygote remains transcriptionally quiescent until the major wave of zygotic genome activation (ZGA) occurs around the eight-cell (8C) stage (day 3 after fertilization). These cells and the derived morula cells are totipotent: they have the capacity to form a whole individual. Our understanding of human totipotency is very limited because of ethical concerns using embryos and the scarcity of material available for research. Recently, we established a controllable transgene-free methodology to generate totipotent eight-cell embryo-like cells (8CLCs) from human pluripotent stem cells (PSCs) in vitro. These 8CLCs are produced using a novel medium, formulated by us, containing specific chemical compounds and cytokines. Here, we provide a detailed protocol for inducing, isolating and characterizing 8CLCs generated with this medium. The induction process can be done either in a stepwise manner (primed-naive-8CLC) that requires only 5 d starting from naive PSCs or directly from primed PSCs, which takes ~7 d. The resulting 8CLCs exhibit transcriptional and epigenetic features resembling those of human 8C embryo cells. On the basis of our experience, we expect that an individual with ~1 year of experience working with human PSC culture would be able to carry out this protocol. Our approach provides a valuable model for studying human early embryogenesis, particularly the molecular events surrounding ZGA.

Brain imaging is an increasingly interdisciplinary field, encompassing multiple data types and multiple analytic traditions. Projects typically involve many moving parts, such as building customized preprocessing pipelines, transforming between data formats, preparing datasets for analysis and, ultimately, displaying results. The field is conventionally built on highly specialized software packages that solve these individual challenges well but are not necessarily designed to be interoperable. Trainees new to the field are therefore often left to come up with isolated heuristics and workarounds to complete a project. Here we present a set of tools to navigate the increasingly complex informatics ecosystem of brain imaging. netneurotools is a Python toolkit that has been continuously developed and maintained by this laboratory's trainees. The philosophy of the toolkit is that it should be the Swiss army knife of the laboratory: functions and routines that we often use but that are not part of any established pipeline or package. Since its inception, the toolkit has been open and welcomes contributions from neuroscientists across the globe. netneurotools presents a necessary counterweight to out-of-the-box software packages and highlights the importance of smaller, ad hoc functions for implementing projects. By opening a window into the inner workings of a laboratory, netneurotools also presents an opportunity to begin a new type of discourse among groups and establish tangible links within the community.

The engineering of living cells represents a promising biomedical frontier that enables the design of cells with tailored functionalities for advanced therapeutic applications. Genetic manipulation serves as a primary approach in cell engineering, yet it faces inherent limitations, including the complexity of multigene editing and poor cross-species applicability, which restrict the development of cells with sophisticated functionalities. Therefore, flexible and versatile engineering strategies capable of functionalizing living cells to address diverse therapeutic requirements are highly desirable. Given its pivotal role in mediating cellular interactions, the cell surface is an attractive target for directing cell engineering. The diverse functional groups present in surface biomolecules offer abundant chemical modification sites, making them highly amenable to functionalization. Leveraging this inherent chemical accessibility, we have recently developed a flexible and versatile platform for surface functionalization of living cells through in situ dopamine polymerization that allows us to design personalized living cells with customizable functions by tuning the surface components. Here we provide a detailed protocol describing two distinct methods for bacterial functionalization. The first method uses dopamine polymerization-mediated mono-functionalization to construct mucus-penetrating bacteria that can reinforce intestinal mucosal barrier to prevent colitis. The second method uses dopamine polymerization-mediated dual-functionalization to generate synergy-immunoactivation bacteria that can simultaneously induce anticancer and antiviral immunity to treat cancer and prevent infection. Excluding bacterial culture, preparation of mucus-penetrating bacteria and synergy-immunoactivation bacteria takes ~3 h and 1 h, respectively. We anticipate that this protocol can offer valuable guidance for the engineering of living cells with designable and tailorable functionalities for innovative cell-based therapy.