☆ 4.6 Review

Enablers and challenges of spatial omics, a melting pot of technologies

MOLECULAR SYSTEMS BIOLOGY (2023)

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Review Spectroscopy

Applications and continued evolution of glycan imaging mass spectrometry

Colin T. McDowell et al.

Summary: This article introduces the development of glycan imaging mass spectrometry and discusses its applications in different sample types. Glycan imaging mass spectrometry analyses broaden our understanding of the biological and clinical relevance of N-glycosylation to human disease.

MASS SPECTROMETRY REVIEWS (2023)

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Article Multidisciplinary Sciences

Integrated intracellular organization and its variations in human iPS cells

Matheus P. Viana et al.

NATURE (2023)

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Article Biotechnology & Applied Microbiology

Integration of whole transcriptome spatial profiling with protein markers

Nir Ben-Chetrit et al.

Summary: Spatial transcriptomics and proteomics have independently revolutionized our understanding of complex biological processes by providing complementary information. However, integrating these modalities in experiments has been limited. To address this, we developed Spatial PrOtein and Transcriptome Sequencing (SPOTS) for simultaneous high-throughput spatial transcriptomics and protein profiling. SPOTS significantly improves signal resolution, cell clustering, and enhances the discovery power for differential gene expression analysis across tissue regions compared to unimodal measurements.

NATURE BIOTECHNOLOGY (2023)

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Article Biochemical Research Methods

Screening cell-cell communication in spatial transcriptomics via collective optimal transport

Zixuan Cang et al.

Summary: COMMOT is a computational framework for spatially inferring cell-cell communication from transcriptomics data based on a variant of optimal transport (OT). It can handle complex molecular interactions and spatial constraints, and infer spatial signaling directionality and genes regulated by signaling using machine learning models.

NATURE METHODS (2023)

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Review Chemistry, Multidisciplinary

Current Progress in Expansion Microscopy: Chemical Strategies and Applications

Gang Wen et al.

Summary: Expansion microscopy (ExM) is a recently developed super-resolution technique that enables visualization of biological targets at nanoscale resolution on conventional fluorescence microscopes. This review summarizes recent advances in ExM, with a focus on the chemical aspects of the method, including chemistries for biomolecule grafting and polymer synthesis. The combination of ExM with other microscopy techniques and the impact of fixation methods on ultrastructure preservation are also discussed. The review concludes with a perspective on existing challenges and future directions.

CHEMICAL REVIEWS (2023)

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Review Immunology

Microbial Pathogenesis in the Era of Spatial Omics

Samantha Lempke et al.

Summary: The biology of a cell is influenced by cell type, temporal changes in cell state, and the cell's environment. Spatial cues play a critical role in microbial pathogenesis strategies. Recent advances in spatial omics techniques can help us understand how location regulates cellular functions during infection.

INFECTION AND IMMUNITY (2023)

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Article Biotechnology & Applied Microbiology

Modeling intercellular communication in tissues using spatial graphs of cells

David S. Fischer et al.

Summary: A graph neural network is used to model how cells communicate in tissues. Existing models of intercellular communication only consider receptor-ligand signaling and ignore spatial proximity. This study presents a node-centric expression modeling method that estimates the impact of niche composition on gene expression from spatial molecular profiling data. The method successfully recovers signatures of molecular processes involved in cell communication.

NATURE BIOTECHNOLOGY (2023)

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Article Multidisciplinary Sciences

Spatial epigenome-transcriptome co-profiling of mammalian tissues

Di Zhang et al.

Summary: Emerging spatial technologies such as spatial transcriptomics and spatial epigenomics have become powerful tools in profiling cellular states in tissue contexts. However, current methods only capture one layer of omics information at a time, limiting the examination of mechanistic relationships in molecular biology. In this study, two technologies are presented for joint profiling of the epigenome and transcriptome at a genome-wide, spatially resolved, and near-single-cell resolution. These technologies provide new insights into spatial epigenetic priming, differentiation, and gene regulation within tissue architecture.

NATURE (2023)

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Article Biotechnology & Applied Microbiology

High-plex protein and whole transcriptome co-mapping at cellular resolution with spatial CITE-seq

Yang Liu et al.

Summary: In this study, the researchers extended the co-indexing of transcriptomes and epitopes (CITE) to the spatial dimension and successfully mapped a large number of proteins and the whole transcriptome. They applied this method to analyze multiple mouse tissue types and human tissues, revealing spatially distinct reactions and immune activation. The co-indexing of transcriptomes and epitopes in the spatial dimension with large protein panels proved to be effective.

NATURE BIOTECHNOLOGY (2023)

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Article Biochemical Research Methods

Photoselective sequencing: microscopically guided genomic measurements with subcellular resolution

Sarah M. Mangiameli et al.

Summary: Photoselective sequencing is a new method for genomic and epigenomic profiling in morphologically distinct regions. It uses targeted illumination to selectively unblock a photocaged fragment library, enabling sequencing-based readout in microscopically identified spatial regions. The method was validated by analyzing chromatin accessibility profiles of fluorescently-labeled cell types in the mouse brain and comparing with published data. Photoselective sequencing is a flexible and generalizable platform for studying the interplay of spatial structures with genomic and epigenomic properties.

NATURE METHODS (2023)

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Review Genetics & Heredity

Best practices for single-cell analysis across modalities

Lukas Heumos et al.

Summary: Recent advances in single-cell technologies have allowed for high-throughput molecular profiling of cells across different modalities and locations. This article presents a summary of benchmarking studies and provides comprehensive best-practice workflows for single-cell (multi-)omic analysis. The article serves as a guide for both novice and advanced users in the field.

NATURE REVIEWS GENETICS (2023)

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Article Multidisciplinary Sciences

Spatial profiling of microbial communities by sequential FISH with error-robust encoding

Zhaohui Cao et al.

Summary: Spatial analysis of microbiomes at single cell resolution with high multiplexity and accuracy is challenging, but can be achieved using sequential error-robust fluorescence in situ hybridization (SEER-FISH). SEER-FISH allows mapping of microbial communities at micron-scale and increases multiplexity of RNA profiling through sequential rounds of probe hybridization and dissociation. With error-correction strategies, SEER-FISH enables accurate taxonomic identification in complex microbial communities and provides a useful method for profiling the spatial ecology of these communities in situ.

NATURE COMMUNICATIONS (2023)

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Article Chemistry, Multidisciplinary

MALDI HiPLEX-IHC: multiomic and multimodal imaging of targeted intact proteins in tissues

Mark J. J. Lim et al.

Summary: Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is widely used for imaging the spatial distribution of small molecules in tissues. However, imaging high molecular weight intact proteins has been challenging. A new approach called MALDI HiPLEX-IHC enables high-plex, multiomic and multimodal imaging of tissues and cells by using novel photocleavable mass-tags conjugated to antibody probes. This approach allows for the simultaneous imaging of small molecules and intact proteins. Future applications of MALDI-IHC are also discussed.

FRONTIERS IN CHEMISTRY (2023)

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Article Cell Biology

OME-Zarr: a cloud-optimized bioimaging file format with international community support

Josh Moore et al.

Summary: A growing community is developing a next-generation file format for bioimaging, called NGFF, to address scalability and heterogeneity issues. Organized by the Open Microscopy Environment (OME), individuals and institutes have designed a format specification process (OME-NGFF) to meet these needs. This paper discusses the cloud-optimized format, OME-Zarr, and the tools and data resources available to improve FAIR access and remove barriers in the scientific process. The momentum in this field presents an opportunity to unify the file format underlying bioimaging data management and analysis tasks.

HISTOCHEMISTRY AND CELL BIOLOGY (2023)

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Article Oncology

High-plex immunofluorescence imaging and traditional histology of the same tissue section for discovering image-based biomarkers

Jia-Ren Lin et al.

Summary: Researchers have developed a technique called Orion, which can analyze H&E histology and multiplex immunofluorescence imaging data from the same cells. They applied this technique to human colorectal cancer samples to identify spatial biomarkers of disease progression. Histopathology using H&E-stained tissue remains the primary diagnostic method in cancer.

NATURE CANCER (2023)

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Article Biochemical Research Methods

FISHFactor: a probabilistic factor model for spatial transcriptomics data with subcellular resolution

Florin C. Walter et al.

Summary: This study proposes a probabilistic factor model called FISHFactor that can take single molecule resolution data as input and explicitly model and account for its nature. Compared to existing methods, FISHFactor shows more accurate results on simulated data and can be applied to large datasets. Additionally, FISHFactor can identify major subcellular expression patterns and spatial gene clusters in a data-driven manner.

BIOINFORMATICS (2023)

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Article Biotechnology & Applied Microbiology

Super-resolved spatial transcriptomics by deep data fusion

Ludvig Bergenstrahle et al.

Summary: This method improves the low resolution of spatial transcriptomics by integrating gene expression data with histological images, allowing for higher-resolution expression maps to be inferred. The deep generative model used in this method can predict spatial gene expression solely from histology images.

NATURE BIOTECHNOLOGY (2022)

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Article Biotechnology & Applied Microbiology

Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning

Noah F. Greenwald et al.

Summary: In this study, the researchers created the TissueNet dataset and developed the Mesmer segmentation algorithm based on deep learning to address the challenge of cell segmentation. Mesmer showed improved accuracy, generalization to various tissue types and imaging platforms, and achieved human-level performance.

NATURE BIOTECHNOLOGY (2022)

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Article Biotechnology & Applied Microbiology

Cell segmentation in imaging-based spatial transcriptomics

Viktor Petukhov et al.

Summary: Single-molecule spatial transcriptomics protocols can reveal tissue organization, but distinguishing cell boundaries is challenging. The Baysor segmentation method optimizes cell boundaries by considering cell morphology and transcriptional composition, potentially increasing cell numbers and reducing segmentation artifacts. Baysor is suitable for data analysis from various protocols.

NATURE BIOTECHNOLOGY (2022)

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Review Biotechnology & Applied Microbiology

Spatial components of molecular tissue biology

Giovanni Palla et al.

Summary: Methods for profiling RNA and protein expression in a spatially resolved manner have rapidly advanced, but clear articulation of key biological questions and development of computational tools are crucial. Decisions on molecular features and inclusion of cell shape in analysis need to be made by developers. Optimal ways to compare tissue samples at different length scales are still being sought.

NATURE BIOTECHNOLOGY (2022)

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Article Biochemical Research Methods

Spatially resolved isotope tracing reveals tissue metabolic activity

Lin Wang et al.

Summary: Isotope imaging enables quantification of metabolic activity in mammalian tissues with spatial resolution, revealing metabolic heterogeneity in the kidney and brain and spatial gradients in metabolic processes.

NATURE METHODS (2022)

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Article Biochemical Research Methods

Benchmarking atlas-level data integration in single-cell genomics

Malte D. Luecken et al.

Summary: This study benchmarked 68 method and preprocessing combinations on 85 batches of gene expression data, highlighting the importance of highly variable gene selection in improving method performance. When dealing with complex integration tasks, scANVI, Scanorama, scVI, and scGen consistently performed well, while the performance of single-cell ATAC-sequencing integration was strongly influenced by the choice of feature space.

NATURE METHODS (2022)

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Article Biochemical Research Methods

Squidpy: a scalable framework for spatial omics analysis

Giovanni Palla et al.

Summary: Squidpy is a Python framework that combines tools from omics and image analysis to efficiently store, manipulate, and visualize spatial omics data. It is extensible and can be interfaced with other libraries for scalable analysis of spatial omics data.

NATURE METHODS (2022)

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Article Biochemical Research Methods

Spatial mapping of protein composition and tissue organization: a primer for multiplexed antibody-based imaging

John W. Hickey et al.

Summary: Recent developments in multiplexed protein imaging methods have provided detailed spatial and functional maps of complex tissues, utilizing antibodies against protein biomarkers. Key considerations for training future users, generating molecular tools, validating antibody panels, and harmonizing datasets are essential as these approaches become more widely adopted. This Perspective offers guidance for robust and reproducible antibody-based highly multiplexed tissue imaging.

NATURE METHODS (2022)

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Article Biochemical Research Methods

MCMICRO: a scalable, modular image-processing pipeline for multiplexed tissue imaging

Denis Schapiro et al.

Summary: MCMICRO is a modular and open-source computational pipeline that enables the transformation of highly multiplexed tissue whole-slide images into single-cell data. It is versatile and can be used with various imaging platforms, maintaining spatial context and providing a foundation for the continued development of tissue imaging software.

NATURE METHODS (2022)

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Article Biotechnology & Applied Microbiology

Robust decomposition of cell type mixtures in spatial transcriptomics

Dylan M. Cable et al.

Summary: RCTD is a computational method that leverages cell type profiles learned from single-cell RNA-seq to decompose cell type mixtures and correct for differences across sequencing technologies. It successfully detects mixtures, identifies cell types, and reproduces cell type localization patterns in simulated datasets and mouse brain data. By enabling spatial mapping of cell types, RCTD defines the spatial components of cellular identity and uncovers new principles of cellular organization in biological tissues.

NATURE BIOTECHNOLOGY (2022)

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Article Multidisciplinary Sciences

SM-Omics is an automated platform for high-throughput spatial multi-omics

S. Vickovic et al.

Summary: The spatial organization of cells and molecules is crucial for tissue function and disease. Spatial transcriptomics, a technique for capturing and locating RNA in tissues, has been advanced with the development of a fully automated platform called Spatial Multi-Omics (SM-Omics). SM-Omics combines spatial transcriptomics and antibody-based protein measurement, allowing high-throughput analysis of multiple omics in a short time.

NATURE COMMUNICATIONS (2022)

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Article Oncology

Clinical challenges of tissue preparation for spatial transcriptome

Xiaoxia Liu et al.

Summary: Spatial transcriptomics is important in bridging molecular information with clinical images. This study aims to identify factors that influence the quality of spatial transcriptomics, specifically in lung cancer. The results indicate that the isolated times and dry conditions of samples are critical for the quality of spatial transcriptomic samples. Therefore, further optimization and standardization of clinical procedures are necessary for the development of clinical spatial transcriptome.

CLINICAL AND TRANSLATIONAL MEDICINE (2022)

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Article Biochemical Research Methods

SpatialExperiment: infrastructure for spatially-resolved transcriptomics data in R using Bioconductor

Dario Righelli et al.

Summary: SpatialExperiment is a new data infrastructure for storing and accessing spatially-resolved transcriptomics data, implemented in the R/Bioconductor framework. It offers advantages such as modularity, interoperability, standardized operations, and comprehensive documentation. The project provides example datasets and visualization tools for users.

BIOINFORMATICS (2022)

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Article Biochemistry & Molecular Biology

Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays

Ao Chen et al.

Summary: Spatially resolved transcriptomic technologies enable us to study complex biological processes such as mammalian embryogenesis. However, current methods have limitations in resolution, gene capture, and field of view, which hinders their systematic application to large and three-dimensional mid- and late-gestation embryos. In this study, we developed Stereo-seq, a spatially enhanced resolution omics-sequencing method, by combining DNA nanoball-patterned arrays and in situ RNA capture. We used Stereo-seq to generate the mouse organogenesis spatiotemporal transcriptomic atlas, MOSTA, which provides single cell resolution and high sensitivity for mapping the kinetics and directionality of transcriptional variation during mouse organogenesis. By utilizing this atlas, we investigated the molecular basis of spatial cell heterogeneity and cell fate specification in developing tissues like the dorsal midbrain. Our panoramic atlas will facilitate in-depth research into long-standing questions about normal and abnormal mammalian development.

CELL (2022)

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Article Biotechnology & Applied Microbiology

Integration of spatial and single-cell transcriptomic data elucidates mouse organogenesis

T. Lohoff et al.

Summary: Improved integration of spatial and single-cell transcriptomic data through the seqFISH method provides insights into mouse development, revealing cell types across the embryo and uncovering axes of cell differentiation that are not apparent from scRNA-seq data. This approach offers a high-resolution spatial map for studying cell fate decisions in complex tissues and development.

NATURE BIOTECHNOLOGY (2022)

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Article Biotechnology & Applied Microbiology

Deep Visual Proteomics defines single-cell identity and heterogeneity

Andreas Mund et al.

Summary: Deep Visual Proteomics combines machine learning, automated image analysis and single-cell proteomics to link protein abundance to complex cellular or subcellular phenotypes while preserving spatial context. It successfully identifies distinct cell states with proteomic profiles and reveals spatial proteome changes in cancer progression.

NATURE BIOTECHNOLOGY (2022)

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Correction Biochemical Research Methods

Museum of spatial transcriptomics (Mar, 10.1038/s41592-022-01409-2, 2022)

Lambda Moses et al.

NATURE METHODS (2022)

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Editorial Material Biochemical Research Methods

MITI minimum information guidelines for highly multiplexed tissue images

Denis Schapiro et al.

Summary: The imminent release of tissue atlases combining multichannel microscopy with single-cell sequencing and other omics data from normal and diseased specimens calls for data and metadata standards to guide data deposition, curation and release. The Minimum Information about Highly Multiplexed Tissue Imaging (MITI) standard, derived from best practices in genomics and microscopy, is introduced for highly multiplexed tissue images and traditional histology.

NATURE METHODS (2022)

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Article Biochemical Research Methods

Benchmarking spatial and single-cell transcriptomics integration methods for transcript distribution prediction and cell type deconvolution

Bin Li et al.

Summary: This study compares 16 integration methods using 45 paired datasets and 32 simulated datasets, finding that Tangram, gimVI, and SpaGE perform best in predicting RNA transcript distribution, while Cell2location, SpatialDWLS, and RCTD are top-performing methods for cell type deconvolution. The benchmark pipeline provided in the study helps researchers in selecting optimal integration methods for their datasets. The comprehensive benchmarking analysis presented in this work evaluates computational methods integrating spatial and single-cell transcriptomics data for transcript distribution prediction and cell type deconvolution.

NATURE METHODS (2022)

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Article Multidisciplinary Sciences

PICASSO allows ultra-multiplexed fluorescence imaging of spatially overlapping proteins without reference spectra measurements

Junyoung Seo et al.

Summary: The authors present PICASSO, an ultra-multiplexed fluorescence imaging method that enables 15-color imaging of spatially overlapping proteins in a single imaging round. By combining PICASSO with cyclic immunofluorescence staining, they achieve 45-color imaging of the mouse brain in three cycles. PICASSO provides a highly accessible and accurate tool for multiplexed imaging for a broad range of researchers.

NATURE COMMUNICATIONS (2022)

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Article Multidisciplinary Sciences

Direct RNA targeted in situ sequencing for transcriptomic profiling in tissue

Hower Lee et al.

Summary: Highly multiplexed spatial mapping of transcripts allows for investigation of transcriptomic and cellular diversity. This study explores a new direct RNA detection approach, which significantly improves transcript detection efficiency and validates its multiplexing capabilities.

SCIENTIFIC REPORTS (2022)

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Review Endocrinology & Metabolism

Toward modeling metabolic state from single-cell transcriptomics

Karin Hrovatin et al.

Summary: Single-cell metabolic modeling provides a new perspective for understanding cellular functions. The presented modeling approaches vary in terms of input requirements, assumptions, scalability, modeled metabolic layers, and newly gained insights. We believe that the use of prior metabolic knowledge will lead to more robust predictions and will pave the way for mechanistic and interpretable machine-learning models.

MOLECULAR METABOLISM (2022)

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Article Biochemical Research Methods

Image-seq: spatially resolved single-cell sequencing guided by in situ and in vivo imaging

Christa Haase et al.

Summary: Image-seq is a technology that allows single-cell transcriptional data to be obtained from cells isolated from specific spatial locations under image guidance, preserving the spatial information of the cells. It can be used with in situ and in vivo imaging to document the temporal and dynamic history of the cells being analyzed. This technology combines spatial information with highly sensitive RNA sequencing, providing valuable insights into cellular organization and function.

NATURE METHODS (2022)

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Review Biochemistry & Molecular Biology

Integrating knowledge and omics to decipher mechanisms via large-scale models of signaling networks

Martin Garrido-Rodriguez et al.

Summary: The article reviews and classifies network approaches for studying signaling transduction based on their characteristics. It highlights challenges in the field, such as the lack of ground truth and limitations of prior knowledge, and mentions new omics developments that may have a significant impact.

MOLECULAR SYSTEMS BIOLOGY (2022)

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Article Multidisciplinary Sciences

Live-seq enables temporal transcriptomic recording of single cells

Wanze Chen et al.

Summary: Live-seq is a novel single-cell transcriptomic profiling approach that preserves cell viability during RNA extraction, allowing for the correlation analysis between a cell's ground-state transcriptome and its downstream molecular or phenotypic behavior. It accurately stratifies diverse cell types and states without major cellular perturbations, and can be used to map a cell's trajectory and evaluate gene effects on cell phenotypes.

NATURE (2022)

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Article Multidisciplinary Sciences

Spatial profiling of chromatin accessibility in mouse and human tissues

Yanxiang Deng et al.

Summary: This study presents a new method for spatial chromatin accessibility profiling in tissues, allowing researchers to explore the spatial epigenetic information at the cellular level and genome scale. The technology has been successfully applied to understand gene regulators in the development of the central nervous system and immune cell types in tonsil tissue. This advancement in spatial biology improves our understanding of cell identity, cell state, and cell fate decision in relation to epigenetic underpinnings in development and disease.

NATURE (2022)

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Article Multidisciplinary Sciences

Spatial multi-omic map of human myocardial infarction

Christoph Kuppe et al.

Summary: In this study, an integrative molecular map of human myocardial infarction was generated using multiple analysis methods. The results elucidated the molecular principles of cardiac tissue organization and provided an important reference for mechanistic and therapeutic studies of cardiac disease.

NATURE (2022)

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Article Multidisciplinary Sciences

Single-cell roadmap of human gonadal development

Luz Garcia-Alonso et al.

Summary: The study generated a comprehensive map of human and mouse gonadal differentiation using single-cell and spatial transcriptomics, chromatin accessibility assays, and fluorescent microscopy. It identified human-specific regulatory programs and resolved the cellular and molecular events in gonadal development, providing guidance for in vitro gonadogenesis.

NATURE (2022)

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Review Genetics & Heredity

The emerging landscape of spatial profiling technologies

Jeffrey R. Moffitt et al.

Summary: Improved scale, multiplexing and resolution of spatial nucleic acid and protein profiling methods have established them as a major component of cellular atlas building. These methods enable measurements at nano- to microscale resolutions, allowing the study of cellular heterogeneity, tissue architectures, and dynamic changes during development and disease. This review provides an overview of the emerging landscape of in situ spatial genome, transcriptome, and proteome technologies, highlighting their impact on cell biology and translational research.

NATURE REVIEWS GENETICS (2022)

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Article Biology

UnMICST: Deep learning with real augmentation for robust segmentation of highly multiplexed images of human tissues

Clarence Yapp et al.

Summary: This paper reports two findings that substantially improve image segmentation of tissues using a range of machine learning architectures. The inclusion of intentionally defocused and saturated images in training data and imaging the nuclear envelope using an antibody cocktail both significantly improve segmentation. These approaches have a positive impact on a wide range of tissue types and may have applications in image processing outside of microscopy.

COMMUNICATIONS BIOLOGY (2022)

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Article Biochemistry & Molecular Biology

Spatially resolved epigenomic profiling of single cells in complex tissues

Tian Lu et al.

Summary: The recent development of spatial omics methods has advanced our understanding of spatial regulation of cell and tissue functions. In this study, a new method for spatially resolved epigenomic profiling of single cells was introduced, allowing for high-resolution spatial mapping. This approach has the potential to enhance our understanding of how gene expression is temporally and spatially regulated.

CELL (2022)

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Article Biochemical Research Methods

ClampFISH 2.0 enables rapid, scalable amplified RNA detection in situ

Ian Dardani et al.

Summary: clampFISH 2.0 is an efficient method for detecting multiple RNA species and amplifying signals simultaneously, enabling the detection of 10 different RNA species in over 1 million cells and also applicable to tissue sections.

NATURE METHODS (2022)

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Article Biochemical Research Methods

Light-Seq: from microscopy to transcriptomics and back

Sinem K. Saka et al.

Summary: Light-Seq combines high resolution imaging with next generation sequencing to analyze selected cell populations in fixed biological samples, allowing for RNA expression profiling while preserving the integrity of the sample. This enables the assessment of cellular phenotypes and states in the context of the original tissue.

NATURE METHODS (2022)

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Article Biochemistry & Molecular Biology

Spatial proteomics in three-dimensional intact specimens

Harsharan Singh Bhatia et al.

Summary: DISCO-MS is a technology that combines various methods for 3D imaging and proteome analysis of large biological specimens, providing opportunities for diagnosis and treatment of complex diseases.

CELL (2022)

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Article Biochemistry & Molecular Biology

Polony gels enable amplifiable DNA stamping and spatial transcriptomics of chronic pain

Xiaonan Fu et al.

Summary: This study introduces a stamping method for fabricating polony gels, reducing the cost and time of barcode sequencing, and developing a single-cell spatial transcriptomic assay. This method offers high resolution and RNA capture efficiency for mapping and analyzing cell-cell communication in tissues.

CELL (2022)

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Review Biotechnology & Applied Microbiology

Spatial omics technologies at multimodal and single cell/subcellular level

Jiwoon Park et al.

Summary: Spatial omics technologies allow for a more in-depth understanding of cellular organizations and interactions within tissues. These technologies can identify specific regions in tissues with varying levels of gene transcripts or proteins, and describe their interactions, providing a comprehensive picture for research and clinical applications.

GENOME BIOLOGY (2022)

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Article Biochemical Research Methods

Light-Seq: light-directed in situ barcoding of biomolecules in fixed cells and tissues for spatially indexed sequencing

Jocelyn Y. Kishi et al.

Summary: Light-Seq is an approach that utilizes light-directed DNA barcoding for multiplexed spatial indexing in fixed cells and tissues. It enables in situ selection of multiple cell populations for sequencing, allowing analysis of rare cell types without dissociation. This method combines spatial and omics information, providing a workflow for in situ imaging, protein staining, and next generation sequencing of the same cells.

NATURE METHODS (2022)

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Article Endocrinology & Metabolism

Analyzing cell-type-specific dynamics of metabolism in kidney repair

Gangqi Wang et al.

Summary: In this study, the authors used mass spectrometry imaging, isotope tracing, and multiplexed immunofluorescence microscopy to study metabolic dynamics in the kidney during ischemia-reperfusion. They developed a high-spatial-resolution metabolomics approach that allows mapping of cell-type-specific changes in central carbon metabolism. This method, combined with immunofluorescence staining, can detect metabolic changes and nutrient partitioning in targeted cell types. The authors identified region-specific metabolic perturbations associated with the lesion and throughout recovery, providing insights into the homeostatic capacity of the kidney microenvironment.

NATURE METABOLISM (2022)

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Article Biotechnology & Applied Microbiology

Explainable multiview framework for dissecting spatial relationships from highly multiplexed data

Jovan Tanevski et al.

Summary: The paper presents MISTy, a machine learning framework that can extract relationships from any spatial omics data. The framework is flexible, scalable, and capable of dissecting different effects through the construction of multiple views.

GENOME BIOLOGY (2022)

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Review Biochemistry & Molecular Biology

Clinical and translational values of spatial transcriptomics

Linlin Zhang et al.

Summary: The combination of spatial transcriptomics (ST) and single cell RNA sequencing (scRNA-seq) is crucial for understanding molecular pathogenesis and discovering disease-specific biomarkers, but faces challenges in clinical application. Clear clinical objectives, optimized sampling procedures, and simplified analysis and interpretation are key to successfully translating ST from bench to clinic.

SIGNAL TRANSDUCTION AND TARGETED THERAPY (2022)

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Article Computer Science, Interdisciplinary Applications

An Optimized Mouse Brain Atlas for Automated Mapping and Quantification of Neuronal Activity Using iDISCO plus and Light Sheet Fluorescence Microscopy

Johanna Perens et al.

Summary: In recent years, advances in whole-brain immunolabelling and LSFM have led to the development of an optimized digital mouse brain atlas for more accurate and efficient registration of neuronal activity patterns. This atlas has shown to be beneficial in mapping changes in c-Fos expression and evaluating drug effects on whole-brain activity, providing a valuable tool for neuroscience research.

NEUROINFORMATICS (2021)

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Editorial Material Oncology

The Tumor Profiler Study: integrated, multi-omic, functional tumor profiling for clinical decision support

Anja Irmisch et al.

Summary: The Tumor Profiler Study combines a prospective diagnostic approach with an exploratory strategy to assess the relevance of in-depth tumor profiling in supporting clinical decision-making and improving the biological understanding of the disease.

CANCER CELL (2021)

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Article Biotechnology & Applied Microbiology

Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2

Robert R. Stickels et al.

Summary: Slide-seqV2 technology achieves an RNA capture efficiency close to 50% of single-cell RNA-seq data, which is 10 times higher than Slide-seq and approaches the detection efficiency of droplet-based single-cell RNA-seq techniques. Leveraging the high detection efficiency of Slide-seqV2, dendritically localized mRNAs in mouse hippocampal neurons were successfully identified, and spatial information was integrated with single-cell trajectory analysis tools to characterize the spatiotemporal development of the mouse neocortex, revealing underlying genetic programs that were poorly sampled with Slide-seq. The combination of near-cellular resolution and high transcript detection efficiency makes Slide-seqV2 applicable across various experimental contexts.

NATURE BIOTECHNOLOGY (2021)

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Editorial Material Biochemical Research Methods

Spatially resolved single-cell genomics and transcriptomics by imaging

Xiaowei Zhuang

Summary: The recent development of genome-scale imaging allows for single-cell omics analysis in intact cells and tissues, enabling gene expression profiling, identification of cell types, and spatial mapping in complex tissues. The high spatial resolution of these approaches also allows for determining the spatial organizations of the genome and transcriptome inside cells, which are key regulatory mechanisms for gene expression.

NATURE METHODS (2021)

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Editorial Material Biochemical Research Methods

Spatially resolved transcriptomics adds a new dimension to genomics

Ludvig Larsson et al.

Summary: Spatially resolved transcriptomics is a field that has emerged with the advancement of single-cell omics, utilizing experimental and computational methods to map out cell positions and gene expression profiles in space. Current methodologies and applications in genomics research are summarized in this field.

NATURE METHODS (2021)

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Editorial Material Biochemical Research Methods

Method of the Year: spatially resolved transcriptomics

Vivien Marx

Summary: Nature Methods has named spatially resolved transcriptomics as Method of the Year 2020.

NATURE METHODS (2021)

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Article Cell Biology

High-throughput single-cell epigenomic profiling by targeted insertion of promoters (TIP-seq)

Daniel A. Bartlett et al.

Summary: The study introduces a high-throughput single-cell DNA binding site mapping method, TIP-seq, that is simple, cost-effective, and capable of multiplexing multiple samples per experiment.

JOURNAL OF CELL BIOLOGY (2021)

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Article Biochemical Research Methods

SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network

Jian Hu et al.

Summary: SpaGCN is a spatially resolved transcriptomics data analysis tool that uses graph convolutional networks to identify spatial domains and spatially variable genes. By integrating gene expression, spatial location, and histology, SpaGCN can detect genes with enriched spatial expression patterns and transferable to other datasets for studying spatial gene expression variation. SpaGCN is computationally fast, platform independent, and ideal for diverse SRT studies.

NATURE METHODS (2021)

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Article Biochemical Research Methods

Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram

Tommaso Biancalani et al.

Summary: Tangram is a versatile tool that aligns single-cell and single-nucleus RNA-seq data to spatially resolved transcriptomics data using deep learning. By addressing the loss of spatial information in single-cell data and overcoming technical limitations, this method demonstrates genome-wide anatomically integrated spatial mapping at single-cell resolution on healthy mouse brain tissue.

NATURE METHODS (2021)

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Editorial Material Urology & Nephrology

Rationale and design of the Kidney Precision Medicine Project

Ian H. de Boer et al.

Summary: The Kidney Precision Medicine Project aims to characterize kidney diseases at a molecular level, identify disease subgroups, and discover novel therapies. This multicenter study involves obtaining kidney biopsies, creating a kidney tissue atlas, and conducting in-depth analysis to improve understanding of chronic and acute kidney diseases. Participants will be followed for 10 years to track clinical outcomes, and all data will be made available for broad use by researchers, clinicians, and patients.

KIDNEY INTERNATIONAL (2021)

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Article Multidisciplinary Sciences

Integrated spatial genomics reveals global architecture of single nuclei

Yodai Takei et al.

Summary: This study utilized DNA seqFISH+ technology to image 3,660 chromosomal loci in single mouse embryonic stem cells, along with observing 17 chromatin marks and subnuclear structures by sequential immunofluorescence and the expression profile of 70 RNAs. The results suggest that many loci are consistently associated with immunofluorescence marks and form "fixed points" in nuclear organizations in single cells, while highly expressed genes appear to be pre-positioned to active nuclear zones. The research also uncovered distinct mouse ES cell subpopulations with characteristic combinatorial chromatin states.

NATURE (2021)

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Article Biochemistry & Molecular Biology

SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes

Marc Elosua-Bayes et al.

Summary: SPOTlight is a computational tool that integrates spatial transcriptomics with single-cell RNA sequencing data to infer the location of cell types and states within complex tissues. Its high prediction accuracy and flexible application spectrum were demonstrated through applications in mouse brain and human pancreatic cancer.

NUCLEIC ACIDS RESEARCH (2021)

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Article Multidisciplinary Sciences

Single-cell nuclear architecture across cell types in the mouse brain

Yodai Takei et al.

Summary: By utilizing integrated spatial genomics, this study identified cell type-specific nuclear architecture and gene expression levels in mouse brain tissue sections, while also revealing that active and inactive X chromosomes access similar domain structures in single cells. This work represents a significant advancement in linking single-cell three-dimensional nuclear architecture, gene expression, and epigenetic modifications in a native tissue context.

SCIENCE (2021)

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Article Multidisciplinary Sciences

Expansion sequencing: Spatially precise in situ transcriptomics in intact biological systems

Shahar Alon et al.

Summary: Expansion microscopy is adapted for long-read untargeted and targeted in situ RNA sequencing, enabling highly multiplexed mapping of RNAs from nanoscale to system scale. This technology allows for detailed transcript localization in different cell types and spatial positions, with applications in both animal models and human cancer samples.

SCIENCE (2021)

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Article Multidisciplinary Sciences

The spatial landscape of lung pathology during COVID-19 progression

Andre F. Rendeiro et al.

Summary: Recent studies using high-parameter imaging mass cytometry have provided insights into the cellular composition and spatial architecture of acute lung injury in humans, including injuries derived from SARS-CoV-2 infection. It was found that SARS-CoV-2 predominantly infects alveolar epithelial cells and induces a localized hyperinflammatory cell state associated with lung damage. As COVID-19 progresses, there is increased macrophage extravasation, along with increased numbers of mesenchymal cells and fibroblasts, possibly indicating attempts to repair the damaged lung tissue. The data generated help in developing a biologically interpretable landscape of lung pathology at both macroscopic and single-cell levels, providing a basis for understanding COVID-19 and lung pathology.

NATURE (2021)

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Review Biotechnology & Applied Microbiology

Computational principles and challenges in single-cell data integration

Ricard Argelaguet et al.

Summary: The development of single-cell multimodal assays has provided a powerful tool for investigating cellular heterogeneity in multiple dimensions. Data integration is a key challenge in analyzing single-cell multimodal data, with existing strategies utilizing similar mathematical ideas but having distinct goals and principles.

NATURE BIOTECHNOLOGY (2021)

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Article Biochemistry & Molecular Biology

Barcoded oligonucleotides ligated on RNA amplified for multiplexed and parallel in situ analyses

Songlei Liu et al.

Summary: BOLORAMIS is a reverse transcription-free method for spatially-resolved, targeted in situ RNA identification with a specificity of 92% and sensitivities ranging from 11% to 35%. It has been demonstrated on various cell types and human cerebral organoids, showing potential applications in basic and translational research for single or multiple targets.

NUCLEIC ACIDS RESEARCH (2021)

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Article Biochemistry & Molecular Biology

Microscopic examination of spatial transcriptome using Seq-Scope

Chun-Seok Cho et al.

Summary: Seq-Scope is a spatial barcoding technology with resolution comparable to an optical microscope, allowing visualization of spatial transcriptome heterogeneity at multiple histological scales from tissue sections. The technology works by processing DNA clusters to expose RNA-capture moiety, making cell analysis simpler and more accurate.

CELL (2021)

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Article Multidisciplinary Sciences

A proximity-dependent biotinylation map of a human cell

Christopher D. Go et al.

Summary: The study utilized BioID technology to construct a map of subcellular compartments in human cells, identifying the intracellular locations of numerous unique proteins and demonstrating the superior predictive ability of this technique compared to previous methods.

NATURE (2021)

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Review Multidisciplinary Sciences

Exploring tissue architecture using spatial transcriptomics

Anjali Rao et al.

Summary: Spatial transcriptomic technologies have revolutionized the field of biological research by systematically measuring gene expression levels throughout tissue space. In addition to generating biological insights, these technologies can be used for exploratory data analysis, hypothesis testing, and integration with other data modalities, providing a framework for understanding tissue organization.

NATURE (2021)

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Article Biotechnology & Applied Microbiology

Spatial transcriptomics at subspot resolution with BayesSpace

Edward Zhao et al.

Summary: BayesSpace increases the resolution of spatial transcriptomics by utilizing neighborhood information. It outperforms current methods for spatial and non-spatial clustering, improving the identification of distinct intra-tissue transcriptional profiles. BayesSpace can resolve tissue structures undetectable at the original resolution and identify transcriptional heterogeneity inaccessible to histological analysis.

NATURE BIOTECHNOLOGY (2021)

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Review Biochemical Research Methods

Spatial omics and multiplexed imaging to explore cancer biology

Sabrina M. Lewis et al.

Summary: Understanding intratumoral heterogeneity through single-cell analyses has revealed new biomarkers, but lacks information on cellular location within the tumor microenvironment. New technologies enabling detection of cancer subclones in their native spatial context promise to drive the next generation of cancer research, diagnosis, and therapeutic strategies.

NATURE METHODS (2021)

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Article Biochemical Research Methods

Metabolomic profiling of single enlarged lysosomes

Hongying Zhu et al.

Summary: SLMS integrates lysosomal patch-clamp recording and induced nanoESI/MS for concurrent metabolic and electrophysiological profiling of individual enlarged lysosomes. This technique has been validated for accuracy and reliability, enabling the classification of lysosomes into subpopulations based on their chemical and biological differences in various cell types. SLMS has the potential to investigate heterogeneous lysosomal metabolic changes during physiological and pathological processes.

NATURE METHODS (2021)

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Article Multidisciplinary Sciences

Cell segmentation-free inference of cell types from in situ transcriptomics data

Jeongbin Park et al.

Summary: SSAM is a computational framework for identifying cell types and tissue domains without the need for cell segmentation, applicable to various in situ transcriptomics techniques. Applied to mouse brain tissue images, SSAM can detect regions occupied by known cell types that were previously missed and discover new cell types.

NATURE COMMUNICATIONS (2021)

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Article Multidisciplinary Sciences

Subcellular localization of biomolecules and drug distribution by high-definition ion beam imaging

Xavier Rovira-Clave et al.

Summary: This study introduces a high-definition multiplex ion beam imaging technology that allows simultaneous visualization of multiple biomolecules and their ligands or small molecules in cells. The subcellular localization of the chemotherapy drug cisplatin was found to be related to chromatin regions, with surviving cells after multi-drug treatment showing selective exclusion of cisplatin from the nucleus, potentially modulating resistance to chemotherapy treatment.

NATURE COMMUNICATIONS (2021)

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Article Biotechnology & Applied Microbiology

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Ruben Dries et al.

Summary: Giotto is a comprehensive open-source toolbox for spatial data analysis and visualization, providing end-to-end analysis with a wide range of algorithms for characterizing tissue composition and cellular interactions, as well as integrating single-cell RNAseq data for cell-type enrichment analysis. The visualization module allows interactive visualization of analysis outputs and imaging features, demonstrating its general applicability across diverse datasets and platforms.

GENOME BIOLOGY (2021)

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Article Multidisciplinary Sciences

In situ genome sequencing resolves DNA sequence and structure in intact biological samples

Andrew C. Payne et al.

Summary: In situ genome sequencing (IGS) allows for sequencing and imaging of genomes within intact biological samples, providing spatial localization of genomic loci and revealing parent-specific changes in genome structure across embryonic stages, single-cell chromatin domains in zygotes, and epigenetic memory of global chromosome positioning within individual embryos. These results demonstrate the capability of IGS to directly connect sequence and structure across length scales from single base pairs to whole organisms.

SCIENCE (2021)

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Review Genetics & Heredity

Deciphering cell-cell interactions and communication from gene expression

Erick Armingol et al.

Summary: Intercellular interactions and communication can be inferred from RNA sequencing data, such as ligand-receptor pairs, which has led to new insights and methodologies for studying cell-cell interactions.

NATURE REVIEWS GENETICS (2021)

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Article Multidisciplinary Sciences

Spatially resolved 3D metabolomic profiling in tissues

Shambavi Ganesh et al.

Summary: Researchers presented a three-dimensional spatially resolved metabolomic profiling framework (3D-SMF) to map out the spatial organization of metabolic fragments and protein signatures in immune cells of human tonsils. Various analyses were conducted to explore the relationships between metabolic and cellular features, revealing spatially distinct lipidomic fragment distributions in lymphatic tissue. The 3D-SMF pipeline impacts the study of immune cells in health and disease.

SCIENCE ADVANCES (2021)

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Article Multidisciplinary Sciences

B cells and tertiary lymphoid structures promote immunotherapy response

Beth A. Helmink et al.

NATURE (2020)

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Article Biochemical Research Methods

Statistical analysis of spatial expression patterns for spatially resolved transcriptomic studies

Shiquan Sun et al.

NATURE METHODS (2020)

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Article Microbiology

Spatial metabolomics of in situ host-microbe interactions at the micrometre scale

Benedikt Geier et al.

NATURE MICROBIOLOGY (2020)

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Review Biochemistry & Molecular Biology

The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution

Orit Rozenblatt-Rosen et al.

CELL (2020)

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Article Multidisciplinary Sciences

Metabolomics and mass spectrometry imaging reveal channeled de novo purine synthesis in cells

Vidhi Pareek et al.

SCIENCE (2020)

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Article Multidisciplinary Sciences

Inferring spatial and signaling relationships between cells from single cell transcriptomic data

Zixuan Cang et al.

NATURE COMMUNICATIONS (2020)

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Article Biotechnology & Applied Microbiology

Multiplex digital spatial profiling of proteins and RNA in fixed tissue

Christopher R. Merritt et al.

NATURE BIOTECHNOLOGY (2020)

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Article Biochemistry & Molecular Biology

OligoMinerApp: a web-server application for the design of genome-scale oligonucleotide in situ hybridization probes through the flexible OligoMiner environment

Marco Passaro et al.

NUCLEIC ACIDS RESEARCH (2020)

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Article Biochemistry & Molecular Biology

Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front

Christian M. Schurch et al.

CELL (2020)

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Article Multidisciplinary Sciences

Molecular atlas of the adult mouse brain

Cantin Ortiz et al.

SCIENCE ADVANCES (2020)

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Article Cell Biology

The cell biologist's guide to super-resolution microscopy

Guillaume Jacquemet et al.

JOURNAL OF CELL SCIENCE (2020)

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Article Biochemistry & Molecular Biology

Genome-Scale Imaging of the 3D Organization and Transcriptional Activity of Chromatin

Jun-Han Su et al.

CELL (2020)

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Article Biochemical Research Methods

3D mapping and accelerated super-resolution imaging of the human genome using in situ sequencing

Huy Q. Nguyen et al.

NATURE METHODS (2020)

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Article Biochemical Research Methods

ZipSeq: barcoding for real-time mapping of single cell transcriptomes

Kenneth H. Hu et al.

NATURE METHODS (2020)

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Article Biochemical Research Methods

Investigating higher-order interactions in single-cell data with scHOT

Shila Ghazanfar et al.

NATURE METHODS (2020)

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Article Biochemical Research Methods

Spatially resolved analysis of FFPE tissue proteomes by quantitative mass spectrometry

Katarzyna Buczak et al.

NATURE PROTOCOLS (2020)

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Review Biochemistry & Molecular Biology

Enhancing scientific discoveries in molecular biology with deep generative models

Romain Lopez et al.

MOLECULAR SYSTEMS BIOLOGY (2020)

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Article Multidisciplinary Sciences

LifeTime and improving European healthcare through cell-based interceptive medicine

Nikolaus Rajewsky et al.

NATURE (2020)

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Article Biochemistry & Molecular Biology

Hybridization-based in situ sequencing (HybISS) for spatially resolved transcriptomics in human and mouse brain tissue

Daniel Gyllborg et al.

NUCLEIC ACIDS RESEARCH (2020)

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Review Biochemical Research Methods

DNA-Barcoded Fluorescence Microscopy for Spatial Omics

Florian Schueder et al.

PROTEOMICS (2020)

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Article Multidisciplinary Sciences

Raman-guided subcellular pharmaco-metabolomics for metastatic melanoma cells

Jiajun Du et al.

NATURE COMMUNICATIONS (2020)

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Article Biology

Single-cell and spatial transcriptomics enables probabilistic inference of cell type topography

Alma Andersson et al.

COMMUNICATIONS BIOLOGY (2020)

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Article Biology

Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data

Jovan Tanevski et al.

LIFE SCIENCE ALLIANCE (2020)

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Article Biochemistry & Molecular Biology

High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue

Yang Liu et al.

CELL (2020)

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Article Multidisciplinary Sciences

ProbeDealer is a convenient tool for designing probes for highly multiplexed fluorescence in situ hybridization

Mengwei Hu et al.

SCIENTIFIC REPORTS (2020)

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Article Biochemistry & Molecular Biology

SCRINSHOT enables spatial mapping of cell states in tissue sections with single-cell resolution

Alexandros Sountoulidis et al.

PLOS BIOLOGY (2020)

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Article Biotechnology & Applied Microbiology

GCNG: graph convolutional networks for inferring gene interaction from spatial transcriptomics data

Ye Yuan et al.

GENOME BIOLOGY (2020)

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Review Biotechnology & Applied Microbiology

Eleven grand challenges in single-cell data science

David Laehnemann et al.

GENOME BIOLOGY (2020)

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Article Multidisciplinary Sciences

Visualizing DNA folding and RNA in embryos at single-cell resolution

Leslie J. Mateo et al.

NATURE (2019)

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Article Multidisciplinary Sciences

Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH

Chee-Huat Linus Eng et al.

NATURE (2019)

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Article Biochemistry & Molecular Biology

Immune and genomic correlates of response to anti-PD-1 immunotherapy in glioblastoma

Junfei Zhao et al.

NATURE MEDICINE (2019)

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Article Multidisciplinary Sciences

Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution

Samuel G. Rodriques et al.

SCIENCE (2019)

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Review Chemistry, Analytical

Advances in mass spectrometry imaging enabling observation of localised lipid biochemistry within tissues

Andrew P. Bowman et al.

TRAC-TRENDS IN ANALYTICAL CHEMISTRY (2019)

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Article Biochemical Research Methods

SABER amplifies FISH: enhanced multiplexed imaging of RNA and DNA in cells and tissues

Jocelyn Y. Kishi et al.

NATURE METHODS (2019)

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Article Biochemistry & Molecular Biology

DNA Microscopy: Optics-free Spatio-genetic Imaging by a Stand-Alone Chemical Reaction

Joshua A. Weinstein et al.

CELL (2019)

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Article Biochemical Research Methods

Gene expression atlas of a developing tissue by single cell expression correlation analysis

Josephine Bageritz et al.

NATURE METHODS (2019)

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Article Multidisciplinary Sciences

Multiplexed detection of RNA using MERFISH and branched DNA amplification

Chenglong Xia et al.

SCIENTIFIC REPORTS (2019)

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Article Biotechnology & Applied Microbiology

Immuno-SABER enables highly multiplexed and amplified protein imaging in tissues

Sinem K. Saka et al.

NATURE BIOTECHNOLOGY (2019)

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Article Biochemical Research Methods

Transmission-mode MALDI-2 mass spectrometry imaging of cells and tissues at subcellular resolution

M. Niehaus et al.

NATURE METHODS (2019)

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Article Biochemical Research Methods

High-definition spatial transcriptomics for in situ tissue profiling

Sanja Vickovic et al.

NATURE METHODS (2019)

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Article Multidisciplinary Sciences

A computational framework for DNA sequencing microscopy

Ian T. Hoffecker et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2019)

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Article Multidisciplinary Sciences

Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression

Chenglong Xia et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2019)

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Article Multidisciplinary Sciences

The human body at cellular resolution: the NIH Human Biomolecular Atlas Program

Michael P. Snyder et al.

NATURE (2019)

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Article Multidisciplinary Sciences

Gene expression cartography

Mor Nitzan et al.

NATURE (2019)

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Article Cell Biology

Modeling Cell-Cell Interactions from Spatial Molecular Data with Spatial Variance Component Analysis

Damien Arnol et al.

CELL REPORTS (2019)

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Article Biotechnology & Applied Microbiology

ClampFISH detects indivicual nucleic acid molecules using click chemistry-based amplification

Sara H. Rouhanifard et al.

NATURE BIOTECHNOLOGY (2019)

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Article Biotechnology & Applied Microbiology

Protection of tissue physicochemical properties using polyfunctional crosslinkers

Young-Gyun Park et al.

NATURE BIOTECHNOLOGY (2019)

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Article Developmental Biology

Third-generation in situ hybridization chain reaction: multiplexed, quantitative, sensitive, versatile, robust

Harry M. T. Choi et al.

DEVELOPMENT (2018)

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Article Biophysics

Single-Cell Analysis Using Hyperspectral Imaging Modalities

Nishir Mehta et al.

JOURNAL OF BIOMECHANICAL ENGINEERING-TRANSACTIONS OF THE ASME (2018)

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Article Biochemical Research Methods

Spatially Resolved Proteome Mapping of Laser Capture Microdissected Tissue with Automated Sample Transfer to Nanodroplets

Ying Zhu et al.

MOLECULAR & CELLULAR PROTEOMICS (2018)

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Article Biochemical Research Methods

Identification of spatial expression trends in single-cell gene expression data

Daniel Edsgard et al.

NATURE METHODS (2018)

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Article Biochemical Research Methods

SpatialDE: identification of spatially variable genes

Valentine Svensson et al.

NATURE METHODS (2018)

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Article Multidisciplinary Sciences

OligoMiner provides a rapid, flexible environment for the design of genome-scale oligonucleotide in situ hybridization probes

Brian J. Beliveau et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2018)

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Article Multidisciplinary Sciences

Three-dimensional intact-tissue sequencing of single-cell transcriptional states

Xiao Wang et al.

SCIENCE (2018)

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Article Multidisciplinary Sciences

Structural absorption by barbule microstructures of super black bird of paradise feathers

Dakota E. McCoy et al.

NATURE COMMUNICATIONS (2018)

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Article Multidisciplinary Sciences

Multiplexed imaging of high-density libraries of RNAs with MERFISH and expansion microscopy

Guiping Wang et al.

SCIENTIFIC REPORTS (2018)

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Article Biology

Highly multiplexed immunofluorescence imaging of human tissues and tumors using t-CyCIF and conventional optical microscopes

Jia-Ren Lin et al.

ELIFE (2018)

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Article Biology

Automated cell-type classification in intact tissues by single-cell molecular profiling

Monica Nagendran et al.

ELIFE (2018)

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Article Chemistry, Analytical

Spatially Resolved Proteome Profiling of <200 Cells from Tomato Fruit Pericarp by Integrating Laser-Capture Microdissection with Nanodroplet Sample Preparation

Yiran Liang et al.

ANALYTICAL CHEMISTRY (2018)

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Article Biochemistry & Molecular Biology

Deep Profiling of Mouse Splenic Architecture with CODEX Multiplexed Imaging

Yury Goltsev et al.

CELL (2018)

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Article Biochemistry & Molecular Biology

A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging

Leeat Keren et al.

CELL (2018)

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Article Biochemical Research Methods

Stellaris™ fluorescence in situ hybridization (FISH) probes: a powerful tool for mRNA detection

Arturo Orjalo et al.

NATURE METHODS (2018)

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Article Multidisciplinary Sciences

Multiplexed protein maps link subcellular organization to cellular states

Gabriele Gut et al.

SCIENCE (2018)

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Article Genetics & Heredity

Walking along chromosomes with super-resolution imaging, contact maps, and integrative modeling

Guy Nir et al.

PLOS GENETICS (2018)

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Article Chemistry, Multidisciplinary

Rapid Sequential in Situ Multiplexing with DNA Exchange Imaging in Neuronal Cells and Tissues

Yu Wang et al.

NANO LETTERS (2017)

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Article Multidisciplinary Sciences

Super-multiplex vibrational imaging

Lu Wei et al.

NATURE (2017)

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Article Multidisciplinary Sciences

Glucose feeds the TCA cycle via circulating lactate

Sheng Hui et al.

NATURE (2017)

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Article Multidisciplinary Sciences

The 4D nucleome project

Job Dekker et al.

NATURE (2017)

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Article Biochemical Research Methods

histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data

Denis Schapiro et al.

NATURE METHODS (2017)

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Article Biochemical Research Methods

Using hyperLOPIT to perform high-resolution mapping of the spatial proteome

Claire M. Mulvey et al.

NATURE PROTOCOLS (2017)

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Editorial Material Neurosciences

Editorial Note to: In Situ Transcription Profiling of Single Cells Reveals Spatial Organization of Cells in the Mouse Hippocampus

Sheel Shah et al.

NEURON (2017)

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Article Multidisciplinary Sciences

A subcellular map of the human proteome

Peter J. Thul et al.

SCIENCE (2017)

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Article Chemistry, Multidisciplinary

DNA-barcoded labeling probes for highly multiplexed Exchange-PAINT imaging

Sarit S. Agasti et al.

CHEMICAL SCIENCE (2017)

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Article Cell Biology

Synthetic DNA Synthesis and Assembly: Putting the Synthetic in Synthetic Biology

Randall A. Hughes et al.

COLD SPRING HARBOR PERSPECTIVES IN BIOLOGY (2017)

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Article Multidisciplinary Sciences

A DNA nanoscope via auto-cycling proximity recording

Thomas E. Schaus et al.

NATURE COMMUNICATIONS (2017)

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Article Biology

The Human Cell Atlas

Aviv Regev et al.

ELIFE (2017)

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Review Physiology

LungMAP: The Molecular Atlas of Lung Development Program

Maryanne E. Ardini-Poleske et al.

AMERICAN JOURNAL OF PHYSIOLOGY-LUNG CELLULAR AND MOLECULAR PHYSIOLOGY (2017)

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Review Microbiology

The Gut Microbiome: Connecting Spatial Organization to Function

Carolina Tropini et al.

CELL HOST & MICROBE (2017)

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Article Chemistry, Multidisciplinary

Universal Super-Resolution Multiplexing by DNA Exchange

Florian Schueder et al.

ANGEWANDTE CHEMIE-INTERNATIONAL EDITION (2017)

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Review Biochemistry & Molecular Biology

From single cells to our planet-recent advances in using mass spectrometry for spatially resolved metabolomics

Daniel Petras et al.

CURRENT OPINION IN CHEMICAL BIOLOGY (2017)

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Article Biochemistry & Molecular Biology

Absolute Quantification of Matrix Metabolites Reveals the Dynamics of Mitochondrial Metabolism

Walter W. Chen et al.

CELL (2016)

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Article Developmental Biology

Single-molecule RNA detection at depth by hybridization chain reaction and tissue hydrogel embedding and clearing

Sheel Shah et al.

DEVELOPMENT (2016)

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Article Endocrinology & Metabolism

Where imaging mass spectrometry stands: here are the numbers

Andrew Palmer et al.

METABOLOMICS (2016)

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Article Biotechnology & Applied Microbiology

Multiplexed and scalable super-resolution imaging of three-dimensional protein localization in size-adjustable tissues

Taeyun Ku et al.

NATURE BIOTECHNOLOGY (2016)

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Article Biochemical Research Methods

Shrinkage-mediated imaging of entire organs and organisms using uDISCO

Chenchen Pan et al.

NATURE METHODS (2016)

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ATAC-see reveals the accessible genome by transposase-mediated imaging and sequencing

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