scholarly journals Spatial-ATAC-seq: spatially resolved chromatin accessibility profiling of tissues at genome scale and cellular level

2021 ◽  
Author(s):  
Yanxiang Deng ◽  
Marek Bartosovic ◽  
Sai Ma ◽  
Di Zhang ◽  
Yang Liu ◽  
...  
Keyword(s):  
Immune Cell ◽  
System Development ◽  
Local Environment ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Cellular Level ◽  
Human Tonsil ◽  
Spatially Resolved ◽  
Fate Decision ◽  
Genome Scale

Cellular function in tissue is dependent upon the local environment, requiring new methods for spatial mapping of biomolecules and cells in the tissue context. The emergence of spatial transcriptomics has enabled genome-scale gene expression mapping, but it remains elusive to capture spatial epigenetic information of tissue at cellular level and genome scale. Here we report on spatial-ATAC-seq: spatially resolved chromatin accessibility profiling of tissue section via next-generation sequencing by combining in situ Tn5 transposition chemistry and microfluidic deterministic barcoding. Spatial chromatin accessibility profiling of mouse embryos delineated tissue region-specific epigenetic landscapes and identified gene regulators implicated in the central nerve system development. Mapping the accessible genome in human tonsil tissue with 20μm pixel size revealed spatially distinct organization of immune cell types and states in lymphoid follicles and extrafollicular zones. This technology takes spatial biology to a new realm by enabling spatially resolved epigenomics to improve our understanding of cell identity, state, and fate decision in relation to epigenetic underpinnings in development and disease.

scholarly journals Spatial-ATAC-seq: spatially resolved chromatin accessibility profiling of tissues at genome scale and cellular level

2021 ◽  
Author(s):  
Rong Fan ◽  
Yanxiang Deng ◽  
Marek Bartosovic ◽  
Sai Ma ◽  
Di Zhang ◽  
...  
Keyword(s):  
Immune Cell ◽  
System Development ◽  
Local Environment ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Cellular Level ◽  
Human Tonsil ◽  
Spatially Resolved ◽  
Fate Decision ◽  
Genome Scale

Abstract Cellular function in tissue is dependent upon the local environment, requiring new methods for spatial mapping of biomolecules and cells in the tissue context. The emergence of spatial transcriptomics has enabled genome-scale gene expression mapping, but it remains elusive to capture spatial epigenetic information of tissue at cellular level and genome scale. Here we report on spatial-ATAC-seq: spatially resolved chromatin accessibility profiling of tissue section via next-generation sequencing by combining in situ Tn5 transposition chemistry and microfluidic deterministic barcoding. Spatial chromatin accessibility profiling of mouse embryos delineated tissue region-specific epigenetic landscapes and identified gene regulators implicated in the central nerve system development. Mapping the accessible genome in human tonsil tissue with 20μm pixel size revealed spatially distinct organization of immune cell types and states in lymphoid follicles and extrafollicular zones. This technology takes spatial biology to a new realm by enabling spatially resolved epigenomics to improve our understanding of cell identity, state, and fate decision in relation to epigenetic underpinnings in development and disease.

scholarly journals Jointly leveraging spatial transcriptomics and deep learning models for pathology image annotation improves cell type identification over either approach alone.

2021 ◽  
Author(s):  
Asif Zubair ◽  
Richard H. Chapple ◽  
Sivaraman Natarajan ◽  
William C. Wright ◽  
Min Pan ◽  
...  
Keyword(s):  
Immune Cell ◽  
Image Annotation ◽  
Cell Types ◽  
Tissue Cell ◽  
Cell Type ◽  
Spatially Resolved ◽  
Transcriptomics Data ◽  
Diagnostic Applications ◽  
The Many ◽  
Level Performance

The disorganization of cell types within tissues underlies many human diseases and has been studied for over a century using the conventional tools of pathology, including tissue-marking dyes such as the H&E stain. Recently, spatial transcriptomics technologies were developed that can measure spatially resolved gene expression directly in pathology-stained tissues sections, revealing cell types and their dysfunction in unprecedented detail. In parallel, artificial intelligence (AI) has approached pathologist-level performance in computationally annotating H&E images of tissue sections. However, spatial transcriptomics technologies are limited in their ability to separate transcriptionally similar cell types and AI-based pathology has performed less impressively outside their training datasets. Here, we describe a methodology that can computationally integrate AI-annotated pathology images with spatial transcriptomics data to markedly improve inferences of tissue cell type composition made over either class of data alone. We show that this methodology can identify regions of clinically relevant tumor immune cell infiltration, which is predictive of response to immunotherapy and was missed by an initial pathologist's manual annotation. Thus, combining spatial transcriptomics and AI-based image annotation has the potential to exceed pathologist-level performance in clinical diagnostic applications and to improve the many applications of spatial transcriptomics that rely on accurate cell type annotations.

Deep characterization of paired chromatin and transcriptomes in four immune cell types from multiple sclerosis patients

Epigenomics ◽  
2021 ◽  
Author(s):  
Sunjay Jude Fernandes ◽  
Matilda Ericsson ◽  
Mohsen Khademi ◽  
Maja Jagodic ◽  
Tomas Olsson ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Immune Cell ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Primary Role ◽  
Nucleotide Polymorphisms ◽  
Multiple Sclerosis Patients ◽  
Accessible Chromatin

Background: The putative involvement of chromatin states in multiple sclerosis (MS) is thus far unclear. Here we determined the association of chromatin-accessibility with concurrent genetic, epigenetic and transcriptional events. Material & methods: We generated paired assay for transposase-accessible chromatin sequencing and RNA-seq profiles from sorted blood immune CD4+ and CD8+ T cells, CD14+ monocytes and CD19+ B cells from healthy controls (HCs) and MS patients. Results: We identified differentially accessible regions between MS and HCs, primarily in CD4+ and CD19+. CD4+ regions were enriched for MS-associated single nucleotide polymorphisms and differentially methylated loci. In the vicinity of differentially accessible regions of CD4+ cells, 42 differentially expressed genes were identified. The top two dysregulated genes identified in this multilayer analysis were CCDC114 and SERTAD1. Conclusion: These findings provide new insight into the primary role of CD4+ and CD19+ cells in MS.

scholarly journals Single-cell atlas of a non-human primate reveals new pathogenic mechanisms of COVID-19

2020 ◽  
Author(s):  
Lei Han ◽  
Xiaoyu Wei ◽  
Chuanyu Liu ◽  
Giacomo Volpe ◽  
Zhifeng Wang ◽  
...  
Keyword(s):  
Single Cell ◽  
Viral Entry ◽  
Immune Cell ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
List Type ◽  
Innate Immune Responses ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
Substantial Heterogeneity

ABSTRACTStopping COVID-19 is a priority worldwide. Understanding which cell types are targeted by SARS-CoV-2 virus, whether interspecies differences exist, and how variations in cell state influence viral entry is fundamental for accelerating therapeutic and preventative approaches. In this endeavor, we profiled the transcriptome of nine tissues from a Macaca fascicularis monkey at single-cell resolution. The distribution of SARS-CoV-2 facilitators, ACE2 and TMRPSS2, in different cell subtypes showed substantial heterogeneity across lung, kidney, and liver. Through co-expression analysis, we identified immunomodulatory proteins such as IDO2 and ANPEP as potential SARS-CoV-2 targets responsible for immune cell exhaustion. Furthermore, single-cell chromatin accessibility analysis of the kidney unveiled a plausible link between IL6-mediated innate immune responses aiming to protect tissue and enhanced ACE2 expression that could promote viral entry. Our work constitutes a unique resource for understanding the physiology and pathophysiology of two phylogenetically close species, which might guide in the development of therapeutic approaches in humans.Bullet pointsWe generated a single-cell transcriptome atlas of 9 monkey tissues to study COVID-19.ACE2+TMPRSS2+ epithelial cells of lung, kidney and liver are targets for SARS-CoV-2.ACE2 correlation analysis shows IDO2 and ANPEP as potential therapeutic opportunities.We unveil a link between IL6, STAT transcription factors and boosted SARS-CoV-2 entry.

scholarly journals Immune system development varies according to age, location, and anemia in African children

2020 ◽  
Vol 12 (529) ◽  
pp. eaaw9522 ◽  
Author(s):  
Danika L. Hill ◽  
Edward J. Carr ◽  
Tobias Rutishauser ◽  
Gemma Moncunill ◽  
Joseph J. Campo ◽  
...  
Keyword(s):  
T Cells ◽  
Immune System ◽  
Immune Cell ◽  
System Development ◽  
High Titer ◽  
Geographical Location ◽  
Cell Types ◽  
Iron Bioavailability ◽  
Immune System Development

Children from low- and middle-income countries, where there is a high incidence of infectious disease, have the greatest need for the protection afforded by vaccination, but vaccines often show reduced efficacy in these populations. An improved understanding of how age, infection, nutrition, and genetics influence immune ontogeny and function is key to informing vaccine design for this at-risk population. We sought to identify factors that shape immune development in children under 5 years of age from Tanzania and Mozambique by detailed immunophenotyping of longitudinal blood samples collected during the RTS,S malaria vaccine phase 3 trial. In these cohorts, the composition of the immune system is dynamically transformed during the first years of life, and this was further influenced by geographical location, with some immune cell types showing an altered rate of development in Tanzanian children compared to Dutch children enrolled in the Generation R population–based cohort study. High-titer antibody responses to the RTS,S/AS01E vaccine were associated with an activated immune profile at the time of vaccination, including an increased frequency of antibody-secreting plasmablasts and follicular helper T cells. Anemic children had lower frequencies of recent thymic emigrant T cells, isotype-switched memory B cells, and plasmablasts; modulating iron bioavailability in vitro could recapitulate the B cell defects observed in anemic children. Our findings demonstrate that the composition of the immune system in children varies according to age, geographical location, and anemia status.

scholarly journals Deep learning of immune cell differentiation

2020 ◽  
Vol 117 (41) ◽  
pp. 25655-25666 ◽  
Author(s):  
Alexandra Maslova ◽  
Ricardo N. Ramirez ◽  
Ke Ma ◽  
Hugo Schmutz ◽  
Chendi Wang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Cell Differentiation ◽  
Dna Sequences ◽  
Immune Cell ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Regulatory Sequence ◽  
B Lineage ◽  
Additional Support

Although we know many sequence-specific transcription factors (TFs), how the DNA sequence of cis-regulatory elements is decoded and orchestrated on the genome scale to determine immune cell differentiation is beyond our grasp. Leveraging a granular atlas of chromatin accessibility across 81 immune cell types, we asked if a convolutional neural network (CNN) could learn to infer cell type-specific chromatin accessibility solely from regulatory DNA sequences. With a tailored architecture and an ensemble approach to CNN parameter interpretation, we show that our trained network (“AI-TAC”) does so by rediscovering ab initio the binding motifs for known regulators and some unknown ones. Motifs whose importance is learned virtually as functionally important overlap strikingly well with positions determined by chromatin immunoprecipitation for several TFs. AI-TAC establishes a hierarchy of TFs and their interactions that drives lineage specification and also identifies stage-specific interactions, like Pax5/Ebf1 vs. Pax5/Prdm1, or the role of different NF-κB dimers in different cell types. AI-TAC assigns Spi1/Cebp and Pax5/Ebf1 as the drivers necessary for myeloid and B lineage fates, respectively, but no factors seemed as dominantly required for T cell differentiation, which may represent a fall-back pathway. Mouse-trained AI-TAC can parse human DNA, revealing a strikingly similar ranking of influential TFs and providing additional support that AI-TAC is a generalizable regulatory sequence decoder. Thus, deep learning can reveal the regulatory syntax predictive of the full differentiative complexity of the immune system.

scholarly journals Toll-Like Receptor Signaling in the Establishment and Function of the Immune System

Cells ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1374
Author(s):  
Jahnavi Aluri ◽  
Megan A. Cooper ◽  
Laura G. Schuettpelz
Keyword(s):  
Immune System ◽  
Immune Cell ◽  
System Development ◽  
Cell Types ◽  
Tlr Signaling ◽  
Inborn Errors ◽  
Immune System Dysfunction ◽  
Immune System Development ◽  
And Function ◽  
Immune Defects

Toll-like receptors (TLRs) are pattern recognition receptors that play a central role in the development and function of the immune system. TLR signaling promotes the earliest emergence of hematopoietic cells during development, and thereafter influences the fate and function of both primitive and effector immune cell types. Aberrant TLR signaling is associated with hematopoietic and immune system dysfunction, and both loss- and gain-of- function variants in TLR signaling-associated genes have been linked to specific infection susceptibilities and immune defects. Herein, we will review the role of TLR signaling in immune system development and the growing number of heritable defects in TLR signaling that lead to inborn errors of immunity.

scholarly journals Spatially mapped single-cell chromatin accessibility

2019 ◽  
Author(s):  
Casey A. Thornton ◽  
Ryan M. Mulqueen ◽  
Andrew Nishida ◽  
Kristof A. Torkenczy ◽  
Eve G. Lowenstein ◽  
...  
Keyword(s):  
Single Cell ◽  
Spatial Information ◽  
Three Dimensional ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Artery Occlusion ◽  
Cell Type ◽  
Cell Type Specificity ◽  
Spatially Resolved ◽  
Typical Experiment

AbstractHigh-throughput single-cell epigenomic assays can resolve the heterogeneity of cell types and states in complex tissues, however, spatial orientation within the network of interconnected cells is lost. Here, we present a novel method for highly scalable, spatially resolved, single-cell profiling of chromatin states. We use high-density multiregional sampling to perform single-cell combinatorial indexing on Microbiopsies Assigned to Positions for the Assay for Transposase Accessible Chromatin (sciMAP-ATAC) to produce single-cell data of an equivalent quality to non-spatially resolved single-cell ATAC-seq, where each cell is localized to a three-dimensional position within the tissue. A typical experiment comprises between 96 and 384 spatially mapped tissue positions, each producing 10s to over 100 individual single-cell ATAC-seq profiles, and a typical resolution of 214 cubic microns; with the ability to tune the resolution and cell throughput to suit each target application. We apply sciMAP-ATAC to the adult mouse primary somatosensory cortex, where we profile cortical lamination and demonstrate the ability to analyze data from a single tissue position or compare a single cell type in adjacent positions. We also profile the human primary visual cortex, where we produce spatial trajectories through the cortex. Finally, we characterize the spatially progressive nature of cerebral ischemic infarct in the mouse brain using a model of transient middle cerebral artery occlusion. We leverage the spatial information to identify novel and known transcription factor activities that vary by proximity to the ischemic infarction core with cell type specificity.

scholarly journals Unbiased integration of single cell multi-omics data

2020 ◽  
Author(s):  
JINZHUANG DOU ◽  
Shaoheng Liang ◽  
Vakul Mohanty ◽  
Xuesen Cheng ◽  
Sangbae Kim ◽  
...  
Keyword(s):  
Single Cell ◽  
Immune Cell ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Mouse Retina ◽  
Transcriptomics Data ◽  
Mouse Brain Cortex ◽  
Broad Variety ◽  
Data Matrices

Acquiring accurate single-cell multiomics profiles often requires performing unbiased in silico integration of data matrices generated by different single-cell technologies from the same biological sample. However, both the rows and the columns can represent different entities in different data matrices, making such integration a computational challenge that has only been solved approximately by existing approaches. Here, we present bindSC, a single-cell data integration tool that realizes simultaneous alignment of the rows and the columns between data matrices without making approximations. Using datasets produced by multiomics technologies as gold standard, we show that bindSC generates accurate multimodal co-embeddings that are substantially more accurate than those generated by existing approaches. Particularly, bindSC effectively integrated single cell RNA sequencing (scRNA-seq) and single cell chromatin accessibility sequencing (scATAC-seq) data towards discovering key regulatory elements in cancer cell-lines and mouse cells. It achieved accurate integration of both common and rare cell types (<0.25% abundance) in a novel mouse retina cell atlas generated using the 10x Genomics Multiome ATAC+RNA kit. Further, it achieves unbiased integration of scRNA-seq and 10x Visium spatial transcriptomics data derived from mouse brain cortex samples. Lastly, it demonstrated efficacy in delineating immune cell types via integrating single-cell RNA and protein data. Thus, bindSC, available at https://github.com/KChen-lab/bindSC, can be applied in a broad variety of context to accelerate discovery of complex cellular and biological identities and associated molecular underpinnings in diseases and developing organisms.

scholarly journals Spatial Epigenome Sequencing at Tissue Scale and Cellular Level

2021 ◽  
Author(s):  
Yanxiang Deng ◽  
Di Zhang ◽  
Yang Liu ◽  
Graham Su ◽  
Archibald Enninful ◽  
...  
Keyword(s):  
Cell Function ◽  
Cellular Level ◽  
Tissue Type ◽  
Olfactory Bulbs ◽  
Spatially Resolved ◽  
Genome Wide ◽  
New Frontier ◽  
Fate Decision ◽  
Generation Sequencing

AbstractSpatial biology is emerging as a new frontier of biomedical research in development and disease, but currently limited to transcriptome and a panel of proteins. Here we present spatial epigenome profiling for three histone modifications (H3K27me3, H3K4me3, H3K27ac) via next-generation sequencing by combining in-tissue CUT&Tag chemistry and microfluidic deterministic barcoding. Spatial chromatin states in mouse embryos or olfactory bulbs revealed tissue type-specific epigenetic regulations, in concordance with ENCODE reference data, but providing spatially resolved genome-wide profiles at tissue scale. Using fluorescence imaging to identify the tissue pixels (20μm) each containing one nucleus allowed us to extract single-cell epigenomes in situ. Spatial chromatin state profiling in tissue may enable unprecedented opportunities to study epigenetic regulation, cell function and fate decision in normal physiology and pathogenesis.

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