Differences in Alzheimer’s disease (AD) susceptibility are observed between brain regions as they accumulate disease related pathology. We have used spatial transcriptome and in situ sequencing to characterize amyloid plaque-related and grey matter expression changes from multiple tissues from a single AD individual. Our spatial approach is providing insight into the mechanisms of AD development and may guide future therapeutic strategies aimed at preventing disease progression.

As the field of cancer immunotherapy advances and new therapeutics are developed, there has been much emphasis on understanding tumor-specific aspects of a patient’s individualized disease, and subsequently targeting treatment towards specific biomarkers. Multiplexed imaging platforms to simultaneously detect multiple markers in a single cell resolution in the same tissue section emerged in the last years as powerful tools to immuno-profiling several tumor tissues and cell-cell interactions which suggest improved diagnostic benefit. Characterize the applicability of these technologies will be important in the field of cancer immunotherapy by helping identify the best options for the application of multiplex technologies.

The spatial organization of cells and subcellular variations in tissues can be considered as a quantitative metric in determining the health and disease states. Single-cell analyses of molecular profiles with in-situ detection methods dissect spatial heterogeneity of distinct cell types. Such detailed cellular maps shed light on spatial regulation mechanisms of diseases. In this talk, I will introduce multiplex imaging modalities (genomics, proteomics, and metabolomics) to quantify up to a hundred markers at macromolecular resolution in single cells for Immuno-engineering, precision oncology, and regenerative medicine applications.

Unbiased single cell proteomics (SCP) is undergoing a revolution due to the increased sensitivity of mass spectrometers and the increased level of multiplexing within quantitative approaches. Here, we describe the characterization of quantitative accuracy within current approaches to mass spectrometry based single cell proteomics and describe novel data acquisition methods aimed at improving the quality and depth of SCP analyses. We then describe how these methods are being utilized to better understand therapeutically relevant pathways within research and early development.

Our lab has developed microscopy-based functional single-cell sequencing(FUNseq) and analysis technologies, which can be applied to subtype heterogeneous populations of cells and link tumorigenic phenotypes to causative genotypes. FUNseq can be combined with single-cell genome, transcriptome, and proteome profiling. FUNseq has been exploited to identify driving pathways related to aggressive migration in different (patient-derived) tumors and to profile subpopulations of cancer cells displaying chromosomal instability or abnormal DNA damage response.

10x Genomics Chromium Single Cell products enable molecular profiling with multiomic capabilities in hundreds of thousands of single cells, and our Visium Spatial products provide a comprehensive understanding of the relationships between cellular function, phenotype, and location in intact tissue sections. Join us to learn how you can uncover molecular insights, dissect cell-type differences, detect novel cell subtypes and biomarkers, define gene regulatory interactions, and decipher spatiotemporal gene expression patterns.

We applied a multi-faceted, highly multiplexed tissue analysis approach to quantitate and characterize spatial arrangement of key IO protein markers in a solid tumor cohort using GeoMx^TM DSP and MultiOmyx^TM Immunofluorescence. Direct correlation was observed for eight out of 10 IO markers between DSP counts and MultiOmyx positive cell densities. This study showed that integrated analysis by both technologies provides a comprehensive understanding of the immune landscape in oncology FFPE tissues.

Genomic DNA transitions between single-stranded and double-stranded states during transcription, DNA repair and replication. This interconversion is critical to the maintenance of cellular homeostasis and plasticity. To assess the single-stranded DNA chromatin landscape at the level of a single cell, we have developed spatially light-activated CHEX-seq (CHromatin EXposed) that utilizes our in situ transcription technology, for identifying the non-B-form single-stranded open chromatin in situ in individual, formalin-fixed cells. 

Fluorescence-based techniques have become an indispensable tool kit in both basic cellular studies and in vitro diagnostics. However, the intrinsic limitations of conventional dyes, such as short Stoke’s shift and low absorptivity, have posed difficulties for advancing highly multiplexed assays. We have developed a new class of fluorescent probes called Pdots, and this talk will highlight their development to enable high multiplex single-cell analysis and spatial biology.

We will discuss the application of image-guided single-cell sorter to recognize and isolate cell types and intracellular cellular features. Image-guided sorter can generate a very large amount of cell images with high resolution and throughput. Applying artificial intelligence with CNN, we show that rich information can be obtained to produce insight in cell types, behaviors, and health. The ability to isolate cells for verification helps the semi-supervised deep-learning system improve its performance.

Understanding the spatial distribution of immune cell populations is critical in advancing our understanding of cancer.  Here we present the analysis of tissue samples using ChipCytometry, which combines iterative immuno-fluorescent staining with high-dynamic range imaging to facilitate quantitative phenotyping with single-cell resolution. Standard FCS files are generated from multichannel images, enabling quantification of dozens of protein biomarkers and accurate identification of cellular phenotypes via flow cytometry-like gating. 

For decades, neuropathological tissue analysis has been hypothesis-driven: genes or pathways are nominated by experimental models, and then tested in human samples. However, single cell and spatial genomics technologies enable much more detailed characterization of tissue, allowing us to build disease hypotheses directly from the human tissue itself. In this talk I will describe our technology development in single-cell (Drop-seq) and spatial genomics (Slide-seq) and our application to Parkinson's disease.

Spatial transcriptomic technologies promise to resolve cellular wiring diagrams of tissues in health and disease, but comprehensive mapping of cell types in situ remains a challenge. We present сell2location, a principled Bayesian model that can resolve fine-grained cell types in spatial transcriptomic data and create comprehensive cellular maps of diverse tissues. We comprehensively assess cell2location in three different tissues and consistently demonstrate improved mapping of fine-grained cell types. Cell2location provides as a versatile first-line analysis tool for mapping tissue architectures in a comprehensive manner.

Single-cell experiments are rapidly evolving to embrace scale following the introduction of a commercial solution that enables up to 1 million cells at a time. Cohorts and replicates simplified for cost or assay compatibility are being pursued ambitiously. This rapid expansion has highlighted opportunities for more effective single-cell research at scale. This session explores historical considerations and highlights effective strategies to embrace this newfound power.

The precise spatial localization of molecular signals within tissues richly informs the mechanisms of tissue formation and function. Here, we’ll introduce Slide-seq, a technology which enables transcriptome-wide measurements with near-single cell spatial resolution. We’ll describe recent experimental and computational advances to enable Slide-seq in biological contexts in biological contexts where high detection sensitivity is important. More broadly, we’ll discuss the promise and challenges of spatial transcriptomics for tissue genomics.

Spatial technologies have started to revolutionize our ability to deeply interrogate tissue and capture layers of information which were not previously possible. During this talk, I will provide an overview of our efforts to seamlessly integrate spatial transcriptomics with single nucleus sequencing to capture cellular and transcriptional alterations observed in human pathologies, with an emphasis on an extensive collaborative project focusing on COVID-19 phenotypes.