Single-Cell Meta-Analysis Uncovers the Pancreatic Endothelial Cell Transcriptomic Signature and Reveals a Key Role for NKX2-3 in PLVAP Expression.

BACKGROUND: The pancreatic vasculature displays tissue-specific physiological and functional adaptations that support rapid insulin response by ß-cells. However, the digestive enzymes have made it difficult to characterize pancreatic endothelial cells (ECs), resulting in the poor understanding of pancreatic EC specialization. METHODS: Available single-nuclei/single-cell RNA-sequencing data sets were mined to identify pancreatic EC-enriched signature genes and to develop an integrated atlas of human pancreatic ECs. We validated the findings using independent single-nuclei/single-cell RNA-sequencing data, bulk RNA-sequencing data of isolated ECs, spatial transcriptomics data, immunofluorescence, and RNAScope of selected markers. The TF (transcription factor) NKX2-3 was expressed in HUVECs via gene transfection, and the expression of pancreatic EC-enriched signature genes was assessed via RT-qPCR. RESULTS: We defined a pancreatic EC-enriched gene signature conserved across species and developmental stages that included genes involved in ECM (extracellular matrix) composition (COL15A1 and COL4A1), permeability and barrier function (PLVAP, EHD4, CAVIN3, HSPG2, ROBO4, HEG1, and CLEC14A), and key signaling pathways (S1P, TGF-ß [transforming growth factor-ß], RHO-RAC GTPase, PI3k-AKT, and PDGF [platelet-derived growth factor]). The integrated atlas revealed the vascular hierarchy within the pancreas. We identified and validated a specialized islet capillary subpopulation characterized by genes involved in permeability (PLVAP and EHD4), immune-modulation (FABP5, HLA-C, and B2M), ECM composition (SPARC and SPARCL1), IGF (insulin-like growth factor) signaling (IGFBP7), and membrane transport (SLCO2A1, SLC2A3, and CD320). Importantly, we identified NKX2-3 as a key TF enriched in pancreatic ECs. DNA-binding motif analysis found NKX2-3 motifs in ≈40% of the signature genes. Induction of NKX2-3 in HUVECs promoted the expression of the islet capillary EC-enriched genes PLVAP and SPARCL1. CONCLUSIONS: We defined a validated transcriptomic signature of pancreatic ECs and uncovered their intratissue transcriptomic heterogeneity. We showed that NKX2-3 acts upstream of PLVAP and provided a single-cell online resource that can be further explored by the community: https://vasconcelos.shinyapps.io/pancreatic_endothelial/.

Cell and transcriptomic diversity of infrapatellar fat pad during knee osteoarthritis.

OBJECTIVES: In this study, we employ a multiomic approach to identify major cell types and subsets, and their transcriptomic profiles within the infrapatellar fat pad (IFP), and to determine differences in the IFP based on knee osteoarthritis (KOA), sex and obesity status. METHODS: Single-nucleus RNA sequencing of 82 924 nuclei from 21 IFPs (n=6 healthy control and n=15 KOA donors), spatial transcriptomics and bioinformatic analyses were used to identify contributions of the IFP to KOA. We mapped cell subclusters from other white adipose tissues using publicly available literature. The diversity of fibroblasts within the IFP was investigated by bioinformatic analyses, comparing by KOA, sex and obesity status. Metabolomics was used to further explore differences in fibroblasts by obesity status. RESULTS: We identified multiple subclusters of fibroblasts, macrophages, adipocytes and endothelial cells with unique transcriptomic profiles. Using spatial transcriptomics, we resolved distributions of cell types and their transcriptomic profiles and computationally identified putative cell-cell communication networks. Furthermore, we identified transcriptomic differences in fibroblasts from KOA versus healthy control donor IFPs, female versus male KOA-IFPs and obese versus normal body mass index (BMI) KOA-IFPs. Finally, using metabolomics, we defined differences in metabolite levels in supernatants of naïve, profibrotic stimuli-treated and proinflammatory stimuli-treated fibroblasts from obese compared to normal BMI KOA-IFPs. CONCLUSIONS: Overall, by employing a multiomic approach, this study provides the first comprehensive map of the cellular and transcriptomic diversity of human IFP and identifies IFP fibroblasts as key cells contributing to transcriptomic and metabolic differences related to KOA disease, sex or obesity.

Interrupting reactivation of immunologic memory diverts the allergic response and prevents anaphylaxis.

BACKGROUND: IgE production against innocuous food antigens can result in anaphylaxis, a severe life-threatening consequence of allergic reactions. The maintenance of IgE immunity is primarily facilitated by IgG+ memory B cells, as IgE+ memory B cells and IgE+ plasma cells are extremely scarce and short-lived, respectively. OBJECTIVE: Our aim was to investigate the critical requirements for an IgE recall response in peanut allergy. METHODS: We used a novel human PBMC culture platform, a mouse model of peanut allergy, and various experimental readouts to assess the IgE recall response in the presence and absence of IL-4Rα blockade. RESULTS: In human PBMCs, we have demonstrated that blockade of IL-4/IL-13 signaling aborted IgE production after activation of a recall response and skewed the cytokine response away from a dominant type 2 signature. TH2A cells, identified by single-cell RNA sequencing, expanded with peanut stimulation and maintained their pathogenic phenotype in spite of IL-4Rα blockade. In mice with allergy, anti-IL-4Rα provided long-lasting suppression of the IgE recall response beyond antibody treatment and fully protected against anaphylaxis. CONCLUSION: The findings reported here advance our understanding of events mediating the regeneration of IgE in food allergy.

Glutaminolysis is a metabolic dependency in FLT3ITD acute myeloid leukemia unmasked by FLT3 tyrosine kinase inhibition.

FLT3 internal tandem duplication (FLT3ITD) mutations are common in acute myeloid leukemia (AML) associated with poor patient prognosis. Although new-generation FLT3 tyrosine kinase inhibitors (TKI) have shown promising results, the outcome of FLT3ITD AML patients remains poor and demands the identification of novel, specific, and validated therapeutic targets for this highly aggressive AML subtype. Utilizing an unbiased genome-wide clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 screen, we identify GLS, the first enzyme in glutamine metabolism, as synthetically lethal with FLT3-TKI treatment. Using complementary metabolomic and gene-expression analysis, we demonstrate that glutamine metabolism, through its ability to support both mitochondrial function and cellular redox metabolism, becomes a metabolic dependency of FLT3ITD AML, specifically unmasked by FLT3-TKI treatment. We extend these findings to AML subtypes driven by other tyrosine kinase (TK) activating mutations and validate the role of GLS as a clinically actionable therapeutic target in both primary AML and in vivo models. Our work highlights the role of metabolic adaptations as a resistance mechanism to several TKI and suggests glutaminolysis as a therapeutically targetable vulnerability when combined with specific TKI in FLT3ITD and other TK activating mutation-driven leukemias.

Primitive macrophages induce sarcomeric maturation and functional enhancement of developing human cardiac microtissues via efferocytic pathways.

Yolk sac macrophages are the first to seed the developing heart, however we have no understanding of their roles in human heart development and function due to a lack of accessible tissue. Here, we bridge this gap by differentiating human embryonic stem cells (hESCs) into primitive LYVE1+ macrophages (hESC-macrophages) that stably engraft within contractile cardiac microtissues composed of hESC-cardiomyocytes and fibroblasts. Engraftment induces a human fetal cardiac macrophage gene program enriched in efferocytic pathways. Functionally, hESC-macrophages trigger cardiomyocyte sarcomeric protein maturation, enhance contractile force and improve relaxation kinetics. Mechanistically, hESC-macrophages engage in phosphatidylserine dependent ingestion of apoptotic cardiomyocyte cargo, which reduces microtissue stress, leading hESC-cardiomyocytes to more closely resemble early human fetal ventricular cardiomyocytes, both transcriptionally and metabolically. Inhibiting hESC-macrophage efferocytosis impairs sarcomeric protein maturation and reduces cardiac microtissue function. Taken together, macrophage-engineered human cardiac microtissues represent a considerably improved model for human heart development, and reveal a major beneficial role for human primitive macrophages in enhancing early cardiac tissue function.

The activation of the CGRP receptor.

The CGRP (calcitonin gene-related peptide) receptor is a family B GPCR (G-protein-coupled receptor). It consists of a GPCR, CLR (calcitonin receptor-like receptor) and an accessory protein, RAMP1 (receptor activity modifying protein 1). RAMP1 is needed for CGRP binding and also cell-surface expression of CLR. CLR is an example of a family B GPCR. Unlike family A GPCRs, little is known about how these receptors are activated by their endogenous ligands. This review considers what is known about the activation of family B GPCRs and then considers how this might be applied to CLR, particularly in light of new knowledge of the crystal structures of family A GPCRs.

Multiomics data integration to reveal chromatin remodeling and reorganization induced by gene mutational synergy.

Recurrent gene mutations often cooperate in a predefined stepwise and synergistic manner to alter global transcription, through directly or indirectly remodeling epigenetic landscape on linear and three-dimensional (3D) scales. Here, we present a multiomics data integration approach to investigate the impact of gene mutational synergy on transcription, chromatin states, and 3D chromatin organization in a murine leukemia model. This protocol provides an executable framework to study epigenetic remodeling induced by cooperating gene mutations and to identify the critical regulatory network involved. For complete details on the use and execution of this protocol, please refer to Yun et al. (2021).

Three tissue resident macrophage subsets coexist across organs with conserved origins and life cycles.

Resident macrophages orchestrate homeostatic, inflammatory, and reparative activities. It is appreciated that different tissues instruct specialized macrophage functions. However, individual tissues contain heterogeneous subpopulations, and how these subpopulations are related is unclear. We asked whether common transcriptional and functional elements could reveal an underlying framework across tissues. Using single-cell RNA sequencing and random forest modeling, we observed that four genes could predict three macrophage subsets that were present in murine heart, liver, lung, kidney, and brain. Parabiotic and genetic fate mapping studies revealed that these core markers predicted three unique life cycles across 17 tissues. TLF+ (expressing TIMD4 and/or LYVE1 and/or FOLR2) macrophages were maintained through self-renewal with minimal monocyte input; CCR2+ (TIMD4−LYVE1−FOLR2−) macrophages were almost entirely replaced by monocytes, and MHC-IIhi macrophages (TIMD4−LYVE1−FOLR2−CCR2−), while receiving modest monocyte contribution, were not continually replaced. Rather, monocyte-derived macrophages contributed to the resident macrophage population until they reached a defined upper limit after which they did not outcompete pre-existing resident macrophages. Developmentally, TLF+ macrophages were first to emerge in the yolk sac and early fetal organs. Fate mapping studies in the mouse and human single-cell RNA sequencing indicated that TLF+ macrophages originated from both yolk sac and fetal monocyte precursors. Furthermore, TLF+ macrophages were the most transcriptionally conserved subset across mouse tissues and between mice and humans, despite organ- and species-specific transcriptional differences. Here, we define the existence of three murine macrophage subpopulations based on common life cycle properties and core gene signatures and provide a common starting point to understand tissue macrophage heterogeneity.

Mutational synergy during leukemia induction remodels chromatin accessibility, histone modifications and three-dimensional DNA topology to alter gene expression.

Altered transcription is a cardinal feature of acute myeloid leukemia (AML); however, exactly how mutations synergize to remodel the epigenetic landscape and rewire three-dimensional DNA topology is unknown. Here, we apply an integrated genomic approach to a murine allelic series that models the two most common mutations in AML: Flt3-ITD and Npm1c. We then deconvolute the contribution of each mutation to alterations of the epigenetic landscape and genome organization, and infer how mutations synergize in the induction of AML. Our studies demonstrate that Flt3-ITD signals to chromatin to alter the epigenetic environment and synergizes with mutations in Npm1c to alter gene expression and drive leukemia induction. These analyses also allow the identification of long-range cis-regulatory circuits, including a previously unknown superenhancer of Hoxa locus, as well as larger and more detailed gene-regulatory networks, driven by transcription factors including PU.1 and IRF8, whose importance we demonstrate through perturbation of network members.

Early loss of Crebbp confers malignant stem cell properties on lymphoid progenitors.

Loss-of-function mutations of cyclic-AMP response element binding protein, binding protein (CREBBP) are prevalent in lymphoid malignancies. However, the tumour suppressor functions of CREBBP remain unclear. We demonstrate that loss of Crebbp in murine haematopoietic stem and progenitor cells (HSPCs) leads to increased development of B-cell lymphomas. This is preceded by accumulation of hyperproliferative lymphoid progenitors with a defective DNA damage response (DDR) due to a failure to acetylate p53. We identify a premalignant lymphoma stem cell population with decreased H3K27ac, which undergoes transcriptional and genetic evolution due to the altered DDR, resulting in lymphomagenesis. Importantly, when Crebbp is lost later in lymphopoiesis, cellular abnormalities are lost and tumour generation is attenuated. We also document that CREBBP mutations may occur in HSPCs from patients with CREBBP-mutated lymphoma. These data suggest that earlier loss of Crebbp is advantageous for lymphoid transformation and inform the cellular origins and subsequent evolution of lymphoid malignancies.

Identifying subset errors in multiple sequence alignments.

Multiple sequence alignment (MSA) accuracy is important, but there is no widely accepted method of judging the accuracy that different alignment algorithms give. We present a simple approach to detecting two types of error, namely block shifts and the misplacement of residues within a gap. Given a MSA, subsets of very similar sequences are generated through the use of a redundancy filter, typically using a 70-90% sequence identity cut-off. Subsets thus produced are typically small and degenerate, and errors can be easily detected even by manual examination. The errors, albeit minor, are inevitably associated with gaps in the alignment, and so the procedure is particularly relevant to homology modelling of protein loop regions. The usefulness of the approach is illustrated in the context of the universal but little known [K/R]KLH motif that occurs in intracellular loop 1 of G protein coupled receptors (GPCR); other issues relevant to GPCR modelling are also discussed.

Mutationmapper: a tool to aid the mapping of protein mutation data.

There has been a rapid increase in the amount of mutational data due to, amongst other things, an increase in single nucleotide polymorphism (SNP) data and the use of site-directed mutagenesis as a tool to help dissect out functional properties of proteins. Many manually curated databases have been developed to index point mutations but they are not sustainable with the ever-increasing volume of scientific literature. There have been considerable efforts in the automatic extraction of mutation specific information from raw text involving use of various text-mining approaches. However, one of the key problems is to link these mutations with its associated protein and to present this data in such a way that researchers can immediately contextualize it within a structurally related family of proteins. To aid this process, we have developed an application called MutationMapper. Point mutations are extracted from abstracts and are validated against protein sequences in Uniprot as far as possible. Our methodology differs in a fundamental way from the usual text-mining approach. Rather than start with abstracts, we start with protein sequences, which facilitates greatly the process of validating a potential point mutation identified in an abstract. The results are displayed as mutations mapped on to the protein sequence or a multiple sequence alignment. The latter enables one to readily pick up mutations performed at equivalent positions in related proteins. We demonstrate the use of MutationMapper against several examples including a single sequence and multiple sequence alignments. The application is available as a web-service at http://mutationmapper.bioch.ox.ac.uk.

The dynamics of camphor in the cytochrome P450 CYP101D2.

The recent crystal structures of CYP101D2, a cytochrome P450 protein from the oligotrophic bacterium Novosphingobium aromaticivorans DSM12444 revealed that both the native (substrate-free) and camphor-soaked forms have open conformations. Furthermore, two other potential camphor-binding sites were also identified from electron densities in the camphor-soaked structure, one being located in the access channel and the other in a cavity on the surface near the F-helix side of the F-G loop termed the substrate recognition site. These latter sites may be key intermediate positions on the pathway for substrate access to or product egress from the active site. Here, we show via the use of unbiased atomistic molecular dynamics simulations that despite the open conformation of the native and camphor-bound crystal structures, the underlying dynamics of CYP101D2 appear to be very similar to other CYP proteins. Simulations of the native structure demonstrated that the protein is capable of sampling many different conformational substates. At the same time, simulations with the camphor positioned at various locations within the access channel or recognition site show that movement towards the active site or towards bulk solvent can readily occur on a short timescale, thus confirming many previously reported in silico studies using steered molecular dynamics. The simulations also demonstrate how the fluctuations of an aromatic gate appear to control access to the active site. Finally, comparison of camphor-bound simulations with the native simulations suggests that the fluctuations can be of similar level and thus are more representative of the conformational selection model rather than induced fit.

Similarity between class A and class B G-protein-coupled receptors exemplified through calcitonin gene-related peptide receptor modelling and mutagenesis studies.

Modelling class B G-protein-coupled receptors (GPCRs) using class A GPCR structural templates is difficult due to lack of homology. The plant GPCR, GCR1, has homology to both class A and class B GPCRs. We have used this to generate a class A-class B alignment, and by incorporating maximum lagged correlation of entropy and hydrophobicity into a consensus score, we have been able to align receptor transmembrane regions. We have applied this analysis to generate active and inactive homology models of the class B calcitonin gene-related peptide (CGRP) receptor, and have supported it with site-directed mutagenesis data using 122 CGRP receptor residues and 144 published mutagenesis results on other class B GPCRs. The variation of sequence variability with structure, the analysis of polarity violations, the alignment of group-conserved residues and the mutagenesis results at 27 key positions were particularly informative in distinguishing between the proposed and plausible alternative alignments. Furthermore, we have been able to associate the key molecular features of the class B GPCR signalling machinery with their class A counterparts for the first time. These include the [K/R]KLH motif in intracellular loop 1, [I/L]xxxL and KxxK at the intracellular end of TM5 and TM6, the NPXXY/VAVLY motif on TM7 and small group-conserved residues in TM1, TM2, TM3 and TM7. The equivalent of the class A DRY motif is proposed to involve Arg(2.39), His(2.43) and Glu(3.46), which makes a polar lock with T(6.37). These alignments and models provide useful tools for understanding class B GPCR function.

Bookshelf: a simple curation system for the storage of biomolecular simulation data.

Molecular dynamics simulations can now routinely generate data sets of several hundreds of gigabytes in size. The ability to generate this data has become easier over recent years and the rate of data production is likely to increase rapidly in the near future. One major problem associated with this vast amount of data is how to store it in a way that it can be easily retrieved at a later date. The obvious answer to this problem is a database. However, a key issue in the development and maintenance of such a database is its sustainability, which in turn depends on the ease of the deposition and retrieval process. Encouraging users to care about meta-data is difficult and thus the success of any storage system will ultimately depend on how well used by end-users the system is. In this respect we suggest that even a minimal amount of metadata if stored in a sensible fashion is useful, if only at the level of individual research groups. We discuss here, a simple database system which we call 'Bookshelf', that uses python in conjunction with a mysql database to provide an extremely simple system for curating and keeping track of molecular simulation data. It provides a user-friendly, scriptable solution to the common problem amongst biomolecular simulation laboratories; the storage, logging and subsequent retrieval of large numbers of simulations. Download URL: http://sbcb.bioch.ox.ac.uk/bookshelf/