scholarly journals Temporal Analyses of Postnatal Liver Development and Maturation by Single Cell Transcriptomics

2021 ◽  
Author(s):  
Yan Liang ◽  
Kota Kaneko ◽  
Bing Xin ◽  
Jin Lee ◽  
Xin Sun ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Function ◽  
Cell Types ◽  
Hepatic Cell ◽  
Liver Development ◽  
Special Group ◽  
Metabolic Functions ◽  
Hepatocyte Heterogeneity ◽  
Gene Regulatory ◽  
Treg Cell Function

Liver is the major metabolic organ, although its postnatal development and maturation are inadequately understood. We analyzed 52,834 single cell transcriptomes and identified 31 cell types or states in mouse livers at postnatal day 1, 3, 7, 21 and 56. We observed unexpectedly high levels of hepatocyte heterogeneity in the developing liver and progressive construction of the zonated metabolic functions from pericentral to periportal hepatocytes, which was orchestrated with development of sinusoid endothelial, stellate and Kupffer cells. Trajectory and gene regulatory analyses captured 36 transcription factors, including a circadian regulator Bhlhe40, in programming liver development. Remarkably, we identified a special group of macrophages enriched at day 7 with a hybrid phenotype of macrophages and endothelial cells, which may regulate sinusoidal construction and Treg cell function. This study provides a comprehensive atlas that covers all hepatic cell types instrumental for further dissection of liver development, metabolic functions and diseases.

scholarly journals Intra-tumoral injection of caerin 1.1 and 1.9 peptides in vaccinated TC-1 tumour bearing mice with PD-1 blockade modulates macrophage heterogeneity and the activation of CD8+ T cells in the tumour microenvironment

2020 ◽  
Author(s):  
Guoying Ni ◽  
Xiaolian Wu ◽  
Ying Liu ◽  
Hejie Li ◽  
Shu Chen ◽  
...  
Keyword(s):  
T Cells ◽  
Single Cell ◽  
Cd8 T Cells ◽  
Cell Function ◽  
Cell Types ◽  
Tumour Microenvironment ◽  
Effector Memory ◽  
Proteomic Profiling ◽  
T Subsets ◽  
Cell Transcriptome

Abstract Development of a vaccine formula that alters the tumour-infiltrating lymphocytes to be more immune active against a tumour is key to the improvement of clinical responses to immunotherapy. Here, we demonstrate that, in conjunction with E7 antigen specific immunotherapy, and IL-10 and PD-1 blockade, intra-tumoral administration of caerin 1.1 and 1.9 peptides further improves the tumour microenvironment (TME) when compared with injection of a control peptide. We used single cell transcriptomics and mass spectrometry-based proteomics to quantify changes in cellular activity across different cell types within the TME. We show that the injection of caerin 1.1/1.9 increases immune activating macrophages and NK cells, while reducing immunosuppressive macrophages with M2 phenotype, and increased numbers of activated CD8+ T cells with higher populations of memory and effector-memory CD8+ T subsets. Proteomic profiling demonstrated activation of Stat1 modulated apoptosis and production of nitric oxide. Further, computational integration of the proteome with the single cell transcriptome was consistent with deactivation of immune suppressive B cell function following caerin 1.1 and 1.9 treatment.

scholarly journals Single cell and single nucleus RNA-Seq reveal cellular heterogeneity and homeostatic regulatory networks in adult mouse stria vascularis

2019 ◽  
Author(s):  
Soumya Korrapati ◽  
Ian Taukulis ◽  
Rafal Olszewski ◽  
Madeline Pyle ◽  
Shoujun Gu ◽  
...  
Keyword(s):  
Single Cell ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Stria Vascularis ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Genetic Mechanisms ◽  
Single Nucleus ◽  
Gene Regulatory

AbstractThe stria vascularis (SV) generates the endocochlear potential (EP) in the inner ear and is necessary for proper hair cell mechanotransduction and hearing. While channels belonging to SV cell types are known to play crucial roles in EP generation, relatively little is known about gene regulatory networks that underlie the ability of the SV to generate and maintain the EP. Using single cell and single nucleus RNA-sequencing, we identify and validate known and rare cell populations in the SV. Furthermore, we establish a basis for understanding molecular mechanisms underlying SV function by identifying potential gene regulatory networks as well as druggable gene targets. Finally, we associate known deafness genes with adult SV cell types. This work establishes a basis for dissecting the genetic mechanisms underlying the role of the SV in hearing and will serve as a basis for designing therapeutic approaches to hearing loss related to SV dysfunction.

scholarly journals Predicting gene regulatory networks from cell atlases

2020 ◽  
Author(s):  
Andreas Fønss Møller ◽  
Kedar Nath Natarajan
Keyword(s):  
Single Cell ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Cell Types ◽  
Mouse Cell ◽  
Cell Type ◽  
Integrated Network ◽  
Mouse Tissues ◽  
Cell Type Specific ◽  
Gene Regulatory

AbstractRecent single-cell RNA-sequencing atlases have surveyed and identified major cell-types across different mouse tissues. Here, we computationally reconstruct gene regulatory networks from 3 major mouse cell atlases to capture functional regulators critical for cell identity, while accounting for a variety of technical differences including sampled tissues, sequencing depth and author assigned cell-type labels. Extracting the regulatory crosstalk from mouse atlases, we identify and distinguish global regulons active in multiple cell-types from specialised cell-type specific regulons. We demonstrate that regulon activities accurately distinguish individual cell types, despite differences between individual atlases. We generate an integrated network that further uncovers regulon modules with coordinated activities critical for cell-types, and validate modules using available experimental data. Inferring regulatory networks during myeloid differentiation from wildtype and Irf8 KO cells, we uncover functional contribution of Irf8 regulon activity and composition towards monocyte lineage. Our analysis provides an avenue to further extract and integrate the regulatory crosstalk from single-cell expression data.SummaryIntegrated single-cell gene regulatory network from three mouse cell atlases captures global and cell-type specific regulatory modules and crosstalk, important for cellular identity.

scholarly journals An Arabidopsis root phloem pole cell atlas reveals PINEAPPLE genes as transitioners to autotrophy

2021 ◽  
Author(s):  
Sofia Otero ◽  
Iris Sevilem ◽  
Pawel Roszak ◽  
Yipeng Lu ◽  
Valerio Di Vittori ◽  
...  
Keyword(s):  
Single Cell ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Developmental Trajectories ◽  
Cell Types ◽  
Holistic View ◽  
Arabidopsis Root ◽  
Single Cell Sequencing ◽  
Gene Regulatory ◽  
Dof Transcription Factors

AbstractSingle cell sequencing has recently allowed the generation of exhaustive root cell atlases. However, some cell types are elusive and remain underrepresented. Here, we use a second- generation single cell approach, where we zoom in on the root transcriptome sorting with specific markers to profile the phloem poles at an unprecedented resolution. Our data highlight the similarities among the developmental trajectories and gene regulatory networks communal to protophloem sieve element (PSE) adjacent lineages in relation to PSE enucleation, a key event in phloem biology.As a signature for early PSE-adjacent lineages, we have identified a set of DNA-binding with one finger (DOF) transcription factors, the PINEAPPLEs (PAPL), that act downstream of PHLOEM EARLY DOF (PEAR) genes, and are important to guarantee a proper root nutrition in the transition to autotrophy.Our data provide a holistic view of the phloem poles that act as a functional unit in root development.

scholarly journals A single-cell catalogue of regulatory states in the ageing Drosophila brain

2017 ◽  
Author(s):  
Kristofer Davie ◽  
Jasper Janssens ◽  
Duygu Koldere ◽  
Uli Pech ◽  
Sara Aibar ◽  
...  
Keyword(s):  
Single Cell ◽  
Regulatory Networks ◽  
Neuronal Cell ◽  
Cell Types ◽  
Disease Mutations ◽  
Drosophila Brain ◽  
Gene Regulatory ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
The Brain

SummaryThe diversity of cell types and regulatory states in the brain, and how these change during ageing, remains largely unknown. Here, we present a single-cell transcriptome catalogue of the entire adult Drosophila melanogaster brain sampled across its lifespan. Both neurons and glia age through a process of “regulatory erosion”, characterized by a strong decline of RNA content, and accompanied by increasing transcriptional and chromatin noise. We identify more than 50 cell types by specific transcription factors and their downstream gene regulatory networks. In addition to neurotransmitter types and neuroblast lineages, we find a novel neuronal cell state driven by datilografo and prospero. This state relates to neuronal birth order, the metabolic profile, and the activity of a neuron. Our single-cell brain catalogue reveals extensive regulatory heterogeneity linked to ageing and brain function and will serve as a reference for future studies of genetic variation and disease mutations.

scholarly journals Multifactorial chromatin regulatory landscapes at single cell resolution

2021 ◽  
Author(s):  
Michael P. Meers ◽  
Derek H. Janssens ◽  
Steven Henikoff
Keyword(s):  
Single Cell ◽  
Target Identification ◽  
Developmental Trajectories ◽  
Single Cells ◽  
High Sensitivity ◽  
Cell Types ◽  
Specific Gene ◽  
Gene Regulatory ◽  
Chromatin Profiling ◽  
Regulatory Landscapes

Chromatin profiling at locus resolution uncovers gene regulatory features that define cell types and developmental trajectories, but it remains challenging to map and compare distinct chromatin-associated proteins within the same sample. Here we describe a scalable antibody barcoding approach for profiling multiple chromatin features simultaneously in the same individual cells, Multiple Target Identification by Tagmentation (MulTI-Tag). MulTI-Tag is optimized to retain high sensitivity and specificity of enrichment for multiple chromatin targets in the same assay. We use MulTI-Tag to resolve distinct cell types using multiple chromatin features on a commercial single-cell platform, and to distinguish unique, coordinated patterns of active and repressive element regulatory usage in the same individual cells. Multifactorial profiling allows us to detect novel associations between histone marks in single cells and holds promise for comprehensively characterizing cell-specific gene regulatory landscapes in development and disease.

scholarly journals A single-cell expression simulator guided by gene regulatory networks

2019 ◽  
Author(s):  
Payam Dibaeinia ◽  
Saurabh Sinha
Keyword(s):  
Experimental Data ◽  
Single Cell ◽  
Regulatory Networks ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Synthetic Data ◽  
Cell Types ◽  
Data Sets ◽  
Statistical Measures ◽  
Gene Regulatory

AbstractA common approach to benchmarking of single-cell transcriptomics tools is to generate synthetic data sets that resemble experimental data in their statistical properties. However, existing single-cell simulators do not incorporate known principles of transcription factor-gene regulatory interactions that underlie expression dynamics. Here we present SERGIO, a simulator of single-cell gene expression data that models the stochastic nature of transcription as well as linear and non-linear influences of multiple transcription factors on genes according to a user-provided gene regulatory network. SERGIO is capable of simulating any number of cell types in steady-state or cells differentiating to multiple fates according to a provided trajectory, reporting both unspliced and spliced transcript counts in single-cells. We show that data sets generated by SERGIO are comparable with experimental data in terms of multiple statistical measures. We also illustrate the use of SERGIO to benchmark several popular single-cell analysis tools, including GRN inference methods.

scholarly journals Predicting gene regulatory networks from cell atlases

2020 ◽  
Vol 3 (11) ◽  
pp. e202000658 ◽  
Author(s):  
Andreas Fønss Møller ◽  
Kedar Nath Natarajan
Keyword(s):  
Single Cell ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Cell Types ◽  
Mouse Cell ◽  
Cell Type ◽  
Integrated Network ◽  
Mouse Tissues ◽  
Multiple Cell ◽  
Gene Regulatory

Recent single-cell RNA-sequencing atlases have surveyed and identified major cell types across different mouse tissues. Here, we computationally reconstruct gene regulatory networks from three major mouse cell atlases to capture functional regulators critical for cell identity, while accounting for a variety of technical differences, including sampled tissues, sequencing depth, and author assigned cell type labels. Extracting the regulatory crosstalk from mouse atlases, we identify and distinguish global regulons active in multiple cell types from specialised cell type–specific regulons. We demonstrate that regulon activities accurately distinguish individual cell types, despite differences between individual atlases. We generate an integrated network that further uncovers regulon modules with coordinated activities critical for cell types, and validate modules using available experimental data. Inferring regulatory networks during myeloid differentiation from wild-type and Irf8 KO cells, we uncover functional contribution of Irf8 regulon activity and composition towards monocyte lineage. Our analysis provides an avenue to further extract and integrate the regulatory crosstalk from single-cell expression data.

scholarly journals Calvariae-Resident Osteomacs That Are Phenotypically and Functionally Distinct from Marrow-Derived Macrophages Interact with Megakaryocytes to Regulate Hematopoietic Stem Cell Function

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 28-28 ◽  
Author(s):  
Safa F Mohamad ◽  
Linlin Xu ◽  
Himes R Evan ◽  
Hao Wu ◽  
Marta Alvarez ◽  
...  
Keyword(s):  
Stem Cell ◽  
Single Cell ◽  
Cell Function ◽  
Flow Cytometric Analysis ◽  
Genomic Analysis ◽  
Cell Types ◽  
Hematopoietic Stem ◽  
Flow Cytometric ◽  
Multiple Cell ◽  
Hematopoietic Niche

Abstract Maintenance of stem cell function is an orchestrated event requiring the participation of multiple cell types within the hematopoietic niche. Precise networking between hematopoietic stem cells (HSC) and these cell types is critical for the maintenance of the stem cell pool. Evidence is accumulating that multiple cell types cooperate to collectively maintain HSC function in the hematopoietic niche. We report here a detailed characterization of calvariae-resident osteomacs (OM) and outline how these cells require cooperation from megakaryocytes (MK) to sustain HSC function. We also describe in detail discriminating phenotypic and functional properties that clearly distinguish OM from marrow-derived macrophages (Mφ). Osteomacs, identified as CD45+F4/80+ cells, were easily detectable in calvarial cell (CC) preparations (3-5% of total CC) collected by the enzymatic digestion of calvariae from 2d-old pups. To assess the effect of MK, a known regulator of osteoblast (OB) proliferation and differentiation, on OM, we performed co-cultures using CC and MK prepared from fetal liver. In the absence of MK, OM did not increase in numbers over a period of 5 days in culture and remained approximately 5% of total cultured cells. However, in the presence of MK, OM significantly increased to become between 25% and 30% of total cells demonstrating that MK regulate OM proliferation. Clonogenic assays established that OM support hematopoiesis enhancing activity of OB and that this activity can be upregulated by MK. Interestingly, marrow-derived Mφ were unable to mediate the same hematopoiesis enhancing activity regardless of whether MK were present in the co-culture or not. These results were validated via primary and secondary transplantations in lethally irradiated hosts whereby the highest repopulating potential was observed among marrow-derived LSK cells co-cultured for 5 days with a mixture of OB, OM, and MK. Using eight surface markers and flow cytometric analysis, we established that although marrow-derived Mφ and OM share many phenotypic similarities (CD45, F4/80, CD68, CD11b, Mac2, and GR-1), only OM expressed MCSFR and CD166, thus providing a distinct and unique profile for these cells. To assess changes in pathway activation between resting and MK-activated OM, we performed single cell genomic analysis. This approach detected the upregulation of several canonical pathways important in HSC maintenance such as Ephrin receptor signaling, PDGF signaling, and leukocyte extravasation signaling in MK-stimulated OM. Single cell genomic analysis between CC-derived OM and marrow-derived Mφ (isolated from each tissue as CD45+F4/80+ cells) revealed 39 genes to be significantly different between the two cell types. Strikingly, many genes such as IGF1, KITL and NOTCH2 that have previously been implicated in HSC regulation were upregulated in OM. MCSFR1 a known regulator of proliferation, differentiation and survival of Mφ was also upregulated in OM corroborating the data previously collected from flow cytometric analyses. However, OM did not respond to exogenous MCSF stimulation suggesting that MCSF alone is not sufficient to induce OM proliferation or that direct contact with MK is required for induction of proliferation. To investigate changes at the protein translational level, we examined both cell types using CyTOF and a panel of 24 surface and intracellular antibodies. The surface marker CD169 which was previously associated with HSC retention when present on cellular components of the hematopoietic niche was expressed on OM but not on Mφ. Intriguingly, OM expressed both CD86 and CD206 which are known M1 and M2 Mφ markers, respectively. TNF-α, TIMP2, FGF2 and MCP1 which are known HSC regulators were also upregulated in OM. Finally, the majority of OM expressed embigin and IL-18, both of which have been implicated in the maintenance of HSC function. These data demonstrate that although bone-associated OM share many properties with marrow-derived Mφ, they are phenotypically and functionally distinct and are critical for the maintenance of HSC function. Furthermore, the function of OM, and consequently that of the two components of CC, namely OB and OM, is significantly augmented by interactions with MK demonstrating that the crosstalk between OM, OB and MK form a novel network in supporting HSC function. Disclosures No relevant conflicts of interest to declare.

scholarly journals Gene biomarker prediction in glioma by integrating scRNA-seq data and gene regulatory network

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Guimin Qin ◽  
Longting Du ◽  
Yuying Ma ◽  
Yu Yin ◽  
Liming Wang
Keyword(s):  
Gene Family ◽  
Single Cell ◽  
Regulatory Network ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
Malignant Cells ◽  
Gene Regulatory ◽  
Tumor Gene

Abstract Background Although great efforts have been made to study the occurrence and development of glioma, the molecular mechanisms of glioma are still unclear. Single-cell sequencing technology provides a new perspective for researchers to explore the pathogens of tumors to further help make treatment and prognosis decisions for patients with tumors. Methods In this study, we proposed an algorithm framework to explore the molecular mechanisms of glioma by integrating single-cell gene expression profiles and gene regulatory relations. First, since there were great differences among malignant cells from different glioma samples, we analyzed the expression status of malignant cells for each sample, and then tumor consensus genes were identified by constructing and analyzing cell-specific networks. Second, to comprehensively analyze the characteristics of glioma, we integrated transcriptional regulatory relationships and consensus genes to construct a tumor-specific regulatory network. Third, we performed a hybrid clustering analysis to identify glioma cell types. Finally, candidate tumor gene biomarkers were identified based on cell types and known glioma-related genes. Results We got six identified cell types using the method we proposed and for these cell types, we performed functional and biological pathway enrichment analyses. The candidate tumor gene biomarkers were analyzed through survival analysis and verified using literature from PubMed. Conclusions The results showed that these candidate tumor gene biomarkers were closely related to glioma and could provide clues for the diagnosis and prognosis of patients with glioma. In addition, we found that four of the candidate tumor gene biomarkers (NDUFS5, NDUFA1, NDUFA13, and NDUFB8) belong to the NADH ubiquinone oxidoreductase subunit gene family, so we inferred that this gene family may be strongly related to glioma.

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