JOINTLY: interpretable joint clustering of single-cell transcriptomes.

Single-cell and single-nucleus RNA-sequencing (sxRNA-seq) is increasingly being used to characterise the transcriptomic state of cell types at homeostasis, during development and in disease. However, this is a challenging task, as biological effects can be masked by technical variation. Here, we present JOINTLY, an algorithm enabling joint clustering of sxRNA-seq datasets across batches. JOINTLY performs on par or better than state-of-the-art batch integration methods in clustering tasks and outperforms other intrinsically interpretable methods. We demonstrate that JOINTLY is robust against over-correction while retaining subtle cell state differences between biological conditions and highlight how the interpretation of JOINTLY can be used to annotate cell types and identify active signalling programs across cell types and pseudo-time. Finally, we use JOINTLY to construct a reference atlas of white adipose tissue (WATLAS), an expandable and comprehensive community resource, in which we describe four adipocyte subpopulations and map compositional changes in obesity and between depots.

Automatic quality control of single-cell and single-nucleus RNA-seq using valiDrops.

Single-cell and single-nucleus RNA-sequencing (sxRNA-seq) measures gene expression in individual cells or nuclei enabling comprehensive characterization of cell types and states. However, isolation of cells or nuclei for sxRNA-seq releases contaminating RNA, which can distort biological signals, through, for example, cell damage and transcript leakage. Thus, identifying barcodes containing high-quality cells or nuclei is a critical analytical step in the processing of sxRNA-seq data. Here, we present valiDrops, an automated method to identify high-quality barcodes and flag dead cells. In valiDrops, barcodes are initially filtered using data-adaptive thresholding on community-standard quality metrics, and subsequently, valiDrops uses a novel clustering-based approach to identify barcodes with distinct biological signals. We benchmark valiDrops and show that biological signals from cell types and states are more distinct, easier to separate and more consistent after filtering by valiDrops compared to existing tools. Finally, we show that valiDrops can predict and flag dead cells with high accuracy. This novel classifier can further improve data quality or be used to identify dead cells to interrogate the biology of cell death. Thus, valiDrops is an effective and easy-to-use method to improve data quality and biological interpretation. Our method is openly available as an R package at www.github.com/madsen-lab/valiDrops.

Analysis of Enhancers and Transcriptional Networks in Thermogenic Adipocytes.

Transcription factor (TF) networks orchestrate the regulation of gene programs in mammalian cells, including white and brown adipocytes. In this protocol, we outline how genomics and transcriptomics data can be integrated to infer causal TFs of a given cellular response or cell type using "Integrated analysis of Motif Activity and Gene Expression changes of transcription factors" (IMAGE). Here, we show how key regulatory TFs controlling white and brown adipocyte gene programs can be predicted from chromatin accessibility and RNA-seq data. Furthermore, we demonstrate how information about target sites and target genes of the predicted key regulators can be integrated to propose testable hypotheses regarding the role and mechanisms of TFs.

Glucolipotoxicity promotes the capacity of the glycerolipid/NEFA cycle supporting the secretory response of pancreatic beta cells.

AIMS/HYPOTHESIS: Chronic exposure of pancreatic beta cells to high glucose and fatty acids has been proposed to induce glucolipotoxicity. However, contradictory results suggest adaptations of the beta cells, which might be instrumental for partial preservation of the secretory response. In this context, we delineated the expression pattern of genes related to lipid pathways along with fat storage/mobilisation during glucose-stimulated insulin secretion. METHODS: Insulin-secreting cells were cultured for 3 days at different glucose concentrations (5.5, 11.1, 25 mmol/l) without or with BSA-complexed 0.4 mmol/l palmitate and oleate. Then, transcriptomic analyses of lipid pathways were performed in human islets by RNA-Seq and in INS-1E cells and rat islets by quantitative RT-PCR. Storage of fat was assessed in INS-1E cells by electron microscopy and Bodipy staining, which was also used for measuring lipid mobilisation rate. The secretory response was monitored during acute 15 mmol/l glucose stimulation using online luminescence assay for INS-1E cells and by radioimmunoassay for rat islets. RESULTS: In human islets, chronic exposure to palmitate and oleate modified expression of a panel of genes involved in lipid handling. Culture at 25 mmol/l glucose upregulated genes encoding for enzymes of the glycerolipid/NEFA cycle and downregulated receptors implicated in fatty acid signalling. Similar results were obtained in INS-1E cells, indicating enhanced capacity of the glycerolipid/NEFA cycle under glucotoxic conditions. Exposure to unsaturated C18:1 fatty acid favoured intracellular lipid accumulation in a glucose-dependent way, an effect also observed with saturated C16:0 fatty acid when combined with the panlipase inhibitor Orlistat. After the glucolipotoxic culture, intracellular fat mobilisation was required for acute glucose-stimulated secretion, particularly in oleate-treated cells under glucotoxic culture conditions. The lipid mobilisation rate was governed chiefly by the levels of stored fat as a direct consequence of the culture conditions rather than energetic demands, except in palmitate-loaded cells. CONCLUSIONS/INTERPRETATION: Glucolipotoxic conditions promote the capacity of the glycerolipid/NEFA cycle thereby preserving part of the secretory response. The cycle of fat storage/mobilisation emerges as a mechanism helping the beta cell to cope with glucotoxic conditions.

Isolation of nuclei from mouse white adipose tissues for single-nucleus genomics.

Lipid-filled adipocytes are incompatible with droplet-based single-cell methods, such as 10x Genomics-based technology, thus restricting droplet-based single-cell analyses of adipose tissues to the stromal vascular fraction. To overcome this limitation and obtain cellular and molecular insight into adipose tissue composition and plasticity, single-nucleus sequencing-based technologies can be applied. Here, we provide an optimized protocol for nuclei isolation from mouse adipose tissues suitable for single-nucleus RNA sequencing. This allows for transcriptomic profiling of the entire adipose tissue at single-cell resolution. For complete details on the use of this protocol, please refer to Sárvári et al., 2021.

Plasticity of Epididymal Adipose Tissue in Response to Diet-Induced Obesity at Single-Nucleus Resolution.

Adipose tissues display a remarkable ability to adapt to the dietary status. Here, we have applied single-nucleus RNA-seq to map the plasticity of mouse epididymal white adipose tissue at single-nucleus resolution in response to high-fat-diet-induced obesity. The single-nucleus approach allowed us to recover all major cell types and to reveal distinct transcriptional stages along the entire adipogenic trajectory from preadipocyte commitment to mature adipocytes. We demonstrate the existence of different adipocyte subpopulations and show that obesity leads to disappearance of the lipogenic subpopulation and increased abundance of the stressed lipid-scavenging subpopulation. Moreover, obesity is associated with major changes in the abundance and gene expression of other cell populations, including a dramatic increase in lipid-handling genes in macrophages at the expense of macrophage-specific genes. The data provide a powerful resource for future hypothesis-driven investigations of the mechanisms of adipocyte differentiation and adipose tissue plasticity.

AMPK Profiling in Rodent and Human Pancreatic Beta-Cells under Nutrient-Rich Metabolic Stress.

Chronic exposure of pancreatic ß-cells to elevated nutrient levels impairs their function and potentially induces apoptosis. Like in other cell types, AMPK is activated in ß-cells under conditions of nutrient deprivation, while little is known on AMPK responses to metabolic stresses. Here, we first reviewed recent studies on the role of AMPK activation in ß-cells. Then, we investigated the expression profile of AMPK pathways in ß-cells following metabolic stresses. INS-1E ß-cells and human islets were exposed for 3 days to glucose (5.5-25 mM), palmitate or oleate (0.4 mM), and fructose (5.5 mM). Following these treatments, we analyzed transcript levels of INS-1E ß-cells by qRT-PCR and of human islets by RNA-Seq; with a special focus on AMPK-associated genes, such as the AMPK catalytic subunits α1 (Prkaa1) and α2 (Prkaa2). AMPKα and pAMPKα were also evaluated at the protein level by immunoblotting. Chronic exposure to the different metabolic stresses, known to alter glucose-stimulated insulin secretion, did not change AMPK expression, either in insulinoma cells or in human islets. Expression profile of the six AMPK subunits was marginally modified by the different diabetogenic conditions. However, the expression of some upstream kinases and downstream AMPK targets, including K-ATP channel subunits, exhibited stress-specific signatures. Interestingly, at the protein level, chronic fructose treatment favored fasting-like phenotype in human islets, as witnessed by AMPK activation. Collectively, previously published and present data indicate that, in the ß-cell, AMPK activation might be implicated in the pre-diabetic state, potentially as a protective mechanism.

Integrated analysis of motif activity and gene expression changes of transcription factors.

The ability to predict transcription factors based on sequence information in regulatory elements is a key step in systems-level investigation of transcriptional regulation. Here, we have developed a novel tool, IMAGE, for precise prediction of causal transcription factors based on transcriptome profiling and genome-wide maps of enhancer activity. High precision is obtained by combining a near-complete database of position weight matrices (PWMs), generated by compiling public databases and systematic prediction of PWMs for uncharacterized transcription factors, with a state-of-the-art method for PWM scoring and a novel machine learning strategy, based on both enhancers and promoters, to predict the contribution of motifs to transcriptional activity. We applied IMAGE to published data obtained during 3T3-L1 adipocyte differentiation and showed that IMAGE predicts causal transcriptional regulators of this process with higher confidence than existing methods. Furthermore, we generated genome-wide maps of enhancer activity and transcripts during human mesenchymal stem cell commitment and adipocyte differentiation and used IMAGE to identify positive and negative transcriptional regulators of this process. Collectively, our results demonstrate that IMAGE is a powerful and precise method for prediction of regulators of gene expression.

Dynamic Rewiring of Promoter-Anchored Chromatin Loops during Adipocyte Differentiation.

Interactions between transcriptional promoters and their distal regulatory elements play an important role in transcriptional regulation; however, the extent to which these interactions are subject to rapid modulations in response to signals is unknown. Here, we use promoter capture Hi-C to demonstrate a rapid reorganization of promoter-anchored chromatin loops within 4 hr after inducing differentiation of 3T3-L1 preadipocytes. The establishment of new promoter-enhancer loops is tightly coupled to activation of poised (histone H3 lysine 4 mono- and dimethylated) enhancers, as evidenced by the acquisition of histone H3 lysine 27 acetylation and the binding of MED1, SMC1, and P300 proteins to these regions, as well as to activation of target genes. Intriguingly, formation of loops connecting activated enhancers and promoters is also associated with extensive recruitment of corepressors such as NCoR and HDACs, indicating that this class of coregulators may play a previously unrecognized role during enhancer activation.

Integrative Genomics Outlines a Biphasic Glucose Response and a ChREBP-RORγ Axis Regulating Proliferation in ß Cells.

Glucose is an important inducer of insulin secretion, but it also stimulates long-term adaptive changes in gene expression that can either promote or antagonize the proliferative potential and function of ß cells. Here, we have generated time-resolved profiles of enhancer and transcriptional activity in response to glucose in the INS-1E pancreatic ß cell line. Our data outline a biphasic response with a first transcriptional wave during which metabolic genes are activated, and a second wave where cell-cycle genes are activated and ß cell identity genes are repressed. The glucose-sensing transcription factor ChREBP directly activates first wave enhancers, whereas repression and activation of second wave enhancers are indirect. By integrating motif enrichment within late-regulated enhancers with expression profiles of the associated transcription factors, we have identified multiple putative regulators of the second wave. These include RORγ, the activity of which is important for glucose-induced proliferation of both INS-1E and primary rat ß cells.

RNA-Seq and Mass-Spectrometry-Based Lipidomics Reveal Extensive Changes of Glycerolipid Pathways in Brown Adipose Tissue in Response to Cold.

Cold exposure greatly alters brown adipose tissue (BAT) gene expression and metabolism to increase thermogenic capacity. Here, we used RNA sequencing and mass-spectrometry-based lipidomics to provide a comprehensive resource describing the molecular signature of cold adaptation at the level of the transcriptome and lipidome. We show that short-term (3-day) cold exposure leads to a robust increase in expression of several brown adipocyte genes related to thermogenesis as well as the gene encoding the hormone irisin. However, pathway analysis shows that the most significantly induced genes are those involved in glycerophospholipid synthesis and fatty acid elongation. This is accompanied by significant changes in the acyl chain composition of triacylglycerols (TAGs) as well as subspecies-selective changes of acyl chains in glycerophospholipids. These results indicate that cold adaptation of BAT is associated with significant and highly species-selective remodeling of both TAGs and glycerophospholipids.

Acute TNF-induced repression of cell identity genes is mediated by NFκB-directed redistribution of cofactors from super-enhancers.

The proinflammatory cytokine tumor necrosis factor (TNF) plays a central role in low-grade adipose tissue inflammation and development of insulin resistance during obesity. In this context, nuclear factor κ-light-chain-enhancer of activated B cells (NFκB) is directly involved and required for the acute activation of the inflammatory gene program. Here, we show that the major transactivating subunit of NFκB, v-rel avian reticuloendotheliosis viral oncogene homolog A (RELA), is also required for acute TNF-induced suppression of adipocyte genes. Notably, this repression does not involve RELA binding to the associated enhancers but rather loss of cofactors and enhancer RNA (eRNA) selectively from high-occupancy sites within super-enhancers. Based on these data, we have developed models that, with high accuracy, predict which enhancers and genes are repressed by TNF in adipocytes. We show that these models are applicable to other cell types where TNF represses genes associated with super-enhancers in a highly cell-type-specific manner. Our results propose a novel paradigm for NFκB-mediated repression, whereby NFκB selectively redistributes cofactors from high-occupancy enhancers, thereby specifically repressing super-enhancer-associated cell identity genes.

iRNA-seq: computational method for genome-wide assessment of acute transcriptional regulation from total RNA-seq data.

RNA-seq is a sensitive and accurate technique to compare steady-state levels of RNA between different cellular states. However, as it does not provide an account of transcriptional activity per se, other technologies are needed to more precisely determine acute transcriptional responses. Here, we have developed an easy, sensitive and accurate novel computational method, IRNA-SEQ: , for genome-wide assessment of transcriptional activity based on analysis of intron coverage from total RNA-seq data. Comparison of the results derived from iRNA-seq analyses with parallel results derived using current methods for genome-wide determination of transcriptional activity, i.e. global run-on (GRO)-seq and RNA polymerase II (RNAPII) ChIP-seq, demonstrate that iRNA-seq provides similar results in terms of number of regulated genes and their fold change. However, unlike the current methods that are all very labor-intensive and demanding in terms of sample material and technologies, iRNA-seq is cheap and easy and requires very little sample material. In conclusion, iRNA-seq offers an attractive novel alternative to current methods for determination of changes in transcriptional activity at a genome-wide level.

Browning of human adipocytes requires KLF11 and reprogramming of PPARγ superenhancers.

Long-term exposure to peroxisome proliferator-activated receptor γ (PPARγ) agonists such as rosiglitazone induces browning of rodent and human adipocytes; however, the transcriptional mechanisms governing this phenotypic switch in adipocytes are largely unknown. Here we show that rosiglitazone-induced browning of human adipocytes activates a comprehensive gene program that leads to increased mitochondrial oxidative capacity. Once induced, this gene program and oxidative capacity are maintained independently of rosiglitazone, suggesting that additional browning factors are activated. Browning triggers reprogramming of PPARγ binding, leading to the formation of PPARγ "superenhancers" that are selective for brown-in-white (brite) adipocytes. These are highly associated with key brite-selective genes. Based on such an association, we identified an evolutionarily conserved metabolic regulator, Kruppel-like factor 11 (KLF11), as a novel browning transcription factor in human adipocytes that is required for rosiglitazone-induced browning, including the increase in mitochondrial oxidative capacity. KLF11 is directly induced by PPARγ and appears to cooperate with PPARγ in a feed-forward manner to activate and maintain the brite-selective gene program.