A5070436051- Single-cell and spatial transcriptomics
- Molecular Biology Techniques and Applications
- Cancer Cells and Metastasis
- Gene expression and cancer classification
- Advanced biosensing and bioanalysis techniques
- RNA Research and Splicing
- Cancer Genomics and Diagnostics
- Systemic Lupus Erythematosus Research
- Inflammatory Bowel Disease
- Immune cells in cancer
- Biosensors and Analytical Detection
- RNA modifications and cancer
- Cancer-related molecular mechanisms research
- Advanced Biosensing Techniques and Applications
- Gut microbiota and health
- Genetics, Aging, and Longevity in Model Organisms
- Cell Image Analysis Techniques
- Microscopic Colitis
- T-cell and B-cell Immunology
- Amyotrophic Lateral Sclerosis Research
- Genomics and Phylogenetic Studies
- Neuroinflammation and Neurodegeneration Mechanisms
- Rheumatoid Arthritis Research and Therapies
- Mycobacterium research and diagnosis
- Neurogenetic and Muscular Disorders Research
New York Genome Center
2018-2025
Broad Institute
2018-2023
Science for Life Laboratory
2013-2022
Uppsala University
2022
Columbia University
2022
KTH Royal Institute of Technology
2013-2019
Massachusetts Institute of Technology
2018
Spatial structure of RNA expression RNA-seq and similar methods can record gene within among cells. Current typically lose positional information many require arduous single-cell isolation sequencing. Ståhl et al. have developed a way measuring the spatial distribution transcripts by annealing fixed brain or cancer tissue samples directly to bar-coded reverse transcriptase primers, performing transcription followed sequencing computational reconstruction, they do so for multiple genes....
Charting an organs’ biological atlas requires us to spatially resolve the entire single-cell transcriptome, and relate such cellular features anatomical scale. Single-cell single-nucleus RNA-seq (sc/snRNA-seq) can profile cells comprehensively, but lose spatial information. Spatial transcriptomics allows for measurements, at lower resolution with limited sensitivity. Targeted in situ technologies solve both issues, are gene throughput. To overcome these limitations we present Tangram, a...
Intra-tumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression throughout a multifocal prostate using spatial transcriptomics (ST) technology. Utilizing novel approach for deconvolution, analyze transcriptomes nearly 6750 tissue regions and extract distinct profiles different components, such as stroma, normal PIN glands, immune cells cancer. We distinguish healthy diseased areas thereby provide insight into changes...
Spatiotemporal gene expression in ALS Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron disease that affects nerve cells the brain and spinal cord. It has proven difficult to identify early stages of where it spreads within body. Maniatis et al. used RNA sequencing define transcriptomic changes over course different regions cord mouse model postmortem human From expression, they identified disease-associated pathways established key steps degeneration observed ALS. Science ,...
The spatial organization of cells and molecules plays a key role in tissue function homeostasis disease. Spatial transcriptomics has recently emerged as technique to capture positionally barcode RNAs directly tissues. Here, we advance the application at scale, by presenting Multi-Omics (SM-Omics) fully automated, high-throughput all-sequencing based platform for combined spatially resolved antibody-based protein measurements. SM-Omics uses DNA-barcoded antibodies, immunofluorescence or...
Mucosal and barrier tissues, such as the gut, lung or skin, are composed of a complex network cells microbes forming tight niche that prevents pathogen colonization supports host-microbiome symbiosis. Characterizing these networks at high molecular cellular resolution is crucial for understanding homeostasis disease. Here we present spatial sequencing (SHM-seq), an all-sequencing-based approach captures tissue histology, polyadenylated RNAs bacterial 16S sequences directly from by modifying...
Abstract The inflamed rheumatic joint is a highly heterogeneous and complex tissue with dynamic recruitment expansion of multiple cell types that interact in multifaceted ways within localized area. Rheumatoid arthritis synovium has primarily been studied either by immunostaining or molecular profiling after homogenization. Here, we use Spatial Transcriptomics, where tissue-resident RNA spatially labeled situ barcodes transcriptome-wide fashion, to study local interactions at the site...
Abstract As spatially resolved multiplex profiling of RNA and proteins becomes more prominent, it is increasingly important to understand the statistical power available test specific hypotheses when designing interpreting such experiments. Ideally, would be possible create an oracle that predicts sampling requirements for generalized spatial However, unknown number relevant features complexity data analysis make this challenging. Here, we enumerate multiple parameters interest should...
Heart failure is a major health problem linked to poor quality of life and high mortality rates. Hence, novel biomarkers, such as fetal marker genes with low expression levels, could potentially differentiate disease states in order improve therapy. In many studies on heart failure, cardiac biopsies have been analyzed uniform pieces tissue bulk techniques, but this homogenization approach can mask medically relevant phenotypes occurring only isolated parts the tissue. This study examines...
Abstract Single-cell transcriptome analysis overcomes problems inherently associated with averaging gene expression measurements in bulk analysis. However, single-cell is currently challenging terms of cost, throughput and robustness. Here, we present a method enabling massive microarray-based barcoding patterns single cells, termed MASC-seq. This technology enables both imaging high-throughput analysis, characterizing thousands transcriptomes per day at low cost (0.13 USD/cell), which two...
Charting a biological atlas of an organ, such as the brain, requires us to spatially-resolve whole transcriptomes single cells, and relate cellular features histological anatomical scales. Single-cell single-nucleus RNA-Seq (sc/snRNA-seq) can map cells comprehensively 5,6 , but relating those their positions in context organ’s common coordinate framework remains major challenge barrier construction cell 7–10 . Conversely, Spatial Transcriptomics allows for in-situ measurements 11–13 at...
Transformative neuropathology is redefining human brain research by integrating foundational descriptive pathology with advanced methodologies to drive discoveries that inform diagnostics, therapeutics, and disease prevention. These approaches, spanning multi-omics studies machine learning applications, enable the identification of biomarkers, therapeutic targets, complex patterns through comprehensive analyses postmortem tissue. Yet critical challenges, including sustainability banks,...
Abstract Though incidence and mortality of colorectal cancer (CRC) in individuals older than 50 (late-onset, LO-CRC) have been declining over the last 30 years, they increasing among adults less (early onset, EO-CRC), constituting a significant public health concern. Detailed molecular comparison EO-CRC to LO-CRC tumors has thus far limited whole-exome sequencing confounded by complex tumor immune microenvironment (TME), with presence non-tumor cells. Here, we present integrated EO-...
Integrating spatial transcriptomics with antibody-based proteomics enables the investigation of biological regulation within intact tissue architecture. However, current approaches for multi-omics integration often depend on dimensionality reduction or autoencoders, which disregard context, limit interpretability, and face challenges scalability. To address these limitations, we developed INLAomics, a multivariate hierarchical Bayesian framework that models protein abundance in sections by...
Abstract The comprehensive analysis of tumor tissue heterogeneity is crucial for determining specific disease states and establishing suitable treatment regimes. Here, we analyze sections from ten patients diagnosed with HER2+ breast cancer. We obtain multidimensional, genome-wide transcriptomics data to resolve spatial immune cell distribution identity within the sections. Furthermore, determine extent infiltration in different regions tissue, including invasive cancer regions. combine...
Abstract Tissue function relies on the precise spatial organization of cells characterized by distinct molecular profiles. Single-cell RNA-Seq captures profiles but not organization. Conversely, profiling assays either lack global transcriptome information or are at single-cell level. Here, we develop High-Density Spatial Transcriptomics (HDST), a method for RNA-seq high resolution. Spatially barcoded reverse transcription oligonucleotides coupled to beads that then randomly deposited in...
Abstract Single cell analysis techniques have great potential in the cancer genomics field. The detection and characterization of circulating tumour cells are important for identifying metastatic disease at an early stage monitoring it. This protocol is based on transcript profiling using Reverse Transcriptase Multiplex Ligation-dependent Probe Amplification (RT-MLPA), which a specific method simultaneous multiple mRNA transcripts. Because small amount (circulating) cells, pre-amplification...
Abstract Spatial genomics technologies enable new approaches to study how cells interact and function in intact multicellular environments but present a host of technical computational challenges. Here we describe Splotch, novel framework for the analysis spatially resolved transcriptomics data. Splotch aligns data from multiple tissue sections timepoints generate improved posterior estimates gene expression. We demonstrate alignment large corpus single-cell RNA-seq into an automatically...
ABSTRACT Mucosal and barrier tissues such as the gut, lung or skin, are composed of a complex network cells microbes forming tight niche that prevents pathogen colonization supports host-microbiome symbiosis. Characterizing these networks at high molecular cellular resolution is crucial for our understanding homeostasis disease. Spatial transcriptomics has emerged key technology to positionally profile RNAs in tissues. Here, we present spatial sequencing, an all-sequencing based approach...