STAT3 drives the expression of ACSL4 in acute kidney injury.

Long-chain acyl-CoA synthetase family 4 (ACSL4) metabolizes long-chain polyunsaturated fatty acids (PUFAs), enriching cell membranes with phospholipids susceptible to peroxidation and drive ferroptosis. The role of ACSL4 and ferroptosis upon endoplasmic-reticulum (ER)-stress-induced acute kidney injury (AKI) is unknown. We used lipidomic, molecular, and cellular biology approaches along with a mouse model of AKI induced by ER stress to investigate the role of ACSL4 regulation in membrane lipidome remodeling in the injured tubular epithelium. Tubular epithelial cells (TECs) activate ACSL4 in response to STAT3 signaling. In this context, TEC membrane lipidome is remodeled toward PUFA-enriched triglycerides instead of PUFA-bearing phospholipids. TECs expressing ACSL4 in this setting are not vulnerable to ferroptosis. Thus, ACSL4 activity in TECs is driven by STAT3 signaling, but ACSL4 alone is not enough to sensitize ferroptosis, highlighting the significance of the biological context associated with the study model.

scRNA-seq reveals the diversity of the developing cardiac cell lineage and molecular players in heart rhythm regulation.

We utilized scRNA-seq to delineate the diversity of cell types in the zebrafish heart. Transcriptome profiling of over 50,000 cells at 48 and 72 hpf defined at least 18 discrete cell lineages of the developing heart. Utilizing well-established gene signatures, we identified a population of cells likely to be the primary pacemaker and characterized the transcriptome profile defining this critical cell type. Two previously uncharacterized genes, atp1b3b and colec10, were found to be enriched in the sinoatrial cardiomyocytes. CRISPR/Cas9-mediated knockout of these two genes significantly reduced heart rate, implicating their role in cardiac development and conduction. Additionally, we describe other cardiac cell lineages, including the endothelial and neural cells, providing their expression profiles as a resource. Our results established a detailed atlas of the developing heart, providing valuable insights into cellular and molecular mechanisms, and pinpointed potential new players in heart rhythm regulation.

Single-cell RNA sequencing reveals epithelial cells driving brain metastasis in lung adenocarcinoma.

Brain metastases (BM) of lung adenocarcinoma (LUAD) are the most common intracranial malignancy leading to death. However, the cellular origins and drivers of BM from LUAD have not been clarified. Cellular composition was characterized by single-cell sequencing analysis of primary lung adenocarcinoma (pLUAD), BM and lymph node metastasis (LNM) samples in GSE131907. Our study briefly analyzed the tumor microenvironment (TME), focusing on the role of epithelial cells (ECs) in BM. We have discovered a population of brain metastasis-associated epithelial cells (BMAECs) expressing SPP1, SAA1, and CDKN2A, and it has been observed that this population is mainly composed of aneuploid cells from pLUAD, playing a crucial role in brain metastasis. Our study concluded that both LNM and BM in LUAD originated from pLUAD lesions, but there is currently insufficient evidence to prove a direct association between BM lesions and LNM lesions, which provides inspiration for further investigation of the TME in BM.

Systematic omics analysis identifies CCR6 as a therapeutic target to overcome cancer resistance to EGFR inhibitors.

Epidermal growth factor receptor inhibitors (EGFRi) have exhibited promising clinical outcomes in the treatment of various cancers. However, their widespread application has been limited by low patient eligibility and the emergence of resistance. Leveraging a multi-omics approach (>1000 cancer cell lines), we explored molecular signatures linked to EGFRi responsiveness and found that expression signatures involved in the estrogen response could recapitulate cancer cell dependency on EGFR, a phenomenon not solely attributable to EGFR-activating mutations. By correlating genome-wide function screening data with EGFRi responses, we identified chemokine receptor 6 (CCR6) as a potential druggable target to mitigate EGFRi resistance. In isogenic cell models, pharmacological inhibition of CCR6 effectively reversed acquired EGFRi resistance, disrupting mitochondrial oxidative phosphorylation, a cellular process commonly associated with therapy resistance. Our data-driven strategy unveils drug-response biomarkers and therapeutic targets for resistance, thus potentially expanding EGFRi applicability and efficacy.

Transcriptomic signatures of progressive and regressive liver fibrosis and portal hypertension.

Persistent liver injury triggers a fibrogenic program that causes pathologic remodeling of the hepatic microenvironment (i.e., liver fibrosis) and portal hypertension. The dynamics of gene regulation during liver disease progression and early regression remain understudied. Here, we generated hepatic transcriptome profiles in two well-established liver disease models at peak fibrosis and during spontaneous regression after the removal of the inducing agents. We linked the dynamics of key disease readouts, such as portal pressure, collagen area, and transaminase levels, to differentially expressed genes, enabling the identification of transcriptomic signatures of progressive vs. regressive liver fibrosis and portal hypertension. These candidate biomarkers (e.g., Tcf4, Mmp7, Trem2, Spp1, Scube1, Islr) were validated in RNA sequencing datasets of patients with cirrhosis and portal hypertension, and those cured from hepatitis C infection. Finally, deconvolution identified major cell types and suggested an association of macrophage and portal hepatocyte signatures with portal hypertension and fibrosis area.

Single-nucleus transcriptomics reveal cardiac cell type-specific diversification in metabolic disease transgenic pigs.

Cardiac damage is widely present in patients with metabolic diseases, but the exact pathophysiological mechanisms involved remain unclear. The porcine heart is an ideal material for cardiovascular research due to its similarities to the human heart. This study evaluated pathological features and performed single-nucleus RNA sequencing (snRNA-seq) on myocardial samples from both wild-type and metabolic disease-susceptible transgenic pigs (previously established). We found that transgenic pigs exhibited lipid metabolism disturbances and myocardial injury after a high-fat high-sucrose diet intervention. snRNA-seq reveals the cellular landscape of healthy and metabolically disturbed pig hearts and identifies the major cardiac cell populations affected by metabolic diseases. Within metabolic disorder hearts, metabolically active cardiomyocytes exhibited impaired function and reduced abundance. Moreover, massive numbers of reparative LYVE1+ macrophages were lost. Additionally, proinflammatory endothelial cells were activated with high expression of multiple proinflammatory cytokines. Our findings provide insights into the cellular mechanisms of metabolic disease-induced myocardial injury.

A transfer learning framework to elucidate the clinical relevance of altered proximal tubule cell states in kidney disease.

The application of single-cell technologies in clinical nephrology remains elusive. We generated an atlas of transcriptionally defined cell types and cell states of human kidney disease by integrating single-cell signatures reported in the literature with newly generated signatures obtained from 5 patients with acute kidney injury. We used this information to develop kidney-specific cell-level information ExtractoR (K-CLIER), a transfer learning approach specifically tailored to evaluate the role of cell types/states on bulk RNAseq data. We validated the K-CLIER as a reliable computational framework to obtain a dimensionality reduction and to link clinical data with single-cell signatures. By applying K-CLIER on cohorts of patients with different kidney diseases, we identified the most relevant cell types associated with fibrosis and disease progression. This analysis highlighted the central role of altered proximal tubule cells in chronic kidney disease. Our study introduces a new strategy to exploit the power of single-cell technologies toward clinical applications.

Transcriptomic characterization of lung pericytes in systemic sclerosis-associated pulmonary fibrosis.

Systemic sclerosis (SSc) is a chronic disease characterized by fibrosis and vascular abnormalities in the skin and internal organs, including the lung. SSc-associated pulmonary fibrosis (SSc-PF) is the leading cause of death in SSc patients. Pericytes are key regulators of vascular integrity and endothelial function. The role that pericytes play in SSc-PF remains unclear. We compared the transcriptome of pericytes from SSc-PF lungs (SScL) to pericytes from normal lungs (NORML). We identified 1,179 differentially expressed genes in SScL pericytes. Pathways enriched in SScL pericytes included prostaglandin, PI3K-AKT, calcium, and vascular remodeling signaling. Decreased cyclic AMP production and altered phosphorylation of AKT in response to prostaglandin E2 in SScL pericytes demonstrate the functional consequence of changes in the prostaglandin pathway that may contribute to fibrosis. The transcriptomic signature of SSc lung pericytes suggests that they promote vascular dysfunction and contribute to the loss of protection against lung inflammation and fibrosis.

sNucConv: A bulk RNA-seq deconvolution method trained on single-nucleus RNA-seq data to estimate cell-type composition of human adipose tissues.

Deconvolution algorithms mostly rely on single-cell RNA-sequencing (scRNA-seq) data applied onto bulk RNA-sequencing (bulk RNA-seq) to estimate tissues' cell-type composition, with performance accuracy validated on deposited databases. Adipose tissues' cellular composition is highly variable, and adipocytes can only be captured by single-nucleus RNA-sequencing (snRNA-seq). Here we report the development of sNucConv, a Scaden deep-learning-based deconvolution tool, trained using 5 hSAT and 7 hVAT snRNA-seq-based data corrected by (i) snRNA-seq/bulk RNA-seq highly correlated genes and (ii) individual cell-type regression models. Applying sNucConv on our bulk RNA-seq data resulted in cell-type proportion estimation of 15 and 13 cell types, with accuracy of R = 0.93 (range: 0.76-0.97) and R = 0.95 (range: 0.92-0.98) for hVAT and hSAT, respectively. This performance level was further validated on an independent set of samples (5 hSAT; 5 hVAT). The resulting model was depot specific, reflecting depot differences in gene expression patterns. Jointly, sNucConv provides proof-of-concept for producing validated deconvolution models for tissues un-amenable to scRNA-seq.

Population dynamics of EMT elucidates the timing and distribution of phenotypic intra-tumoral heterogeneity.

The Epithelial-to-Mesenchymal Transition (EMT) is a hallmark of cancer metastasis and morbidity. EMT is a non-binary process, and cells can be stably arrested en route to EMT in an intermediate hybrid state associated with enhanced tumor aggressiveness and worse patient outcomes. Understanding EMT progression in detail will provide fundamental insights into the mechanisms underlying metastasis. Despite increasingly available single-cell RNA sequencing (scRNA-seq) data that enable in-depth analyses of EMT at the single-cell resolution, current inferential approaches are limited to bulk microarray data. There is thus a great need for computational frameworks to systematically infer and predict the timing and distribution of EMT-related states at single-cell resolution. Here, we develop a computational framework for reliable inference and prediction of EMT-related trajectories from scRNA-seq data. Our model can be utilized across a variety of applications to predict the timing and distribution of EMT from single-cell sequencing data.

Sequence-directed concentration of G protein-coupled receptors in COPII vesicles.

G protein-coupled receptors (GPCRs) constitute the largest superfamily of plasma membrane signaling proteins. However, virtually nothing is known about their recruitment to COPII vesicles for forward delivery after synthesis in the endoplasmic reticulum (ER). Here, we demonstrate that some GPCRs are highly concentrated at ER exit sites (ERES) before COPII budding. Angiotensin II type 2 receptor (AT2R) and CXCR4 concentration are directed by a di-acidic motif and a 9-residue domain, respectively, and these motifs also control receptor ER-Golgi traffic. We further show that AT2R interacts with Sar1 GTPase and that distinct GPCRs have different ER-Golgi transport rates via COPII which is independent of their concentration at ERES. Collectively, these data demonstrate that GPCRs can be actively captured by COPII via specific motifs and direct interaction with COPII components that in turn affects their export dynamics, and provide important insights into COPII targeting and forward trafficking of nascent GPCRs.

Quantitative proteomics and RNA-sequencing of mouse liver endothelial cells identify novel regulators of BMP6 by iron.

Hepcidin is the master hormone governing systemic iron homeostasis. Iron regulates hepcidin by activating bone morphogenetic protein (BMP)6 expression in liver endothelial cells (LECs), but the mechanisms are incompletely understood. To address this, we performed proteomics and RNA-sequencing on LECs from iron-adequate and iron-loaded mice. Gene set enrichment analysis identified transcription factors activated by high iron, including Nrf-2, which was previously reported to contribute to BMP6 regulation, and c-Jun. Jun (encoding c-Jun) knockdown blocked Bmp6 but not Nrf-2 pathway induction by iron in LEC cultures. Chromatin immunoprecipitation of mouse livers showed iron-dependent c-Jun binding to predicted sites in Bmp6 regulatory regions. Finally, c-Jun inhibitor blunted induction of Bmp6 and hepcidin, but not Nrf-2 activity, in iron-loaded mice. However, Bmp6 and iron parameters were unchanged in endothelial Jun knockout mice. Our data suggest that c-Jun participates in iron-mediated BMP6 regulation independent of Nrf-2, though the mechanisms may be redundant and/or multifactorial.

Integrative analysis of single-cell RNA-seq and ATAC-seq reveals heterogeneity of induced pluripotent stem cell-derived hepatic organoids.

To gain deeper insights into transcriptomes and epigenomes of organoids, liver organoids from two states (expandable and more differentiated) were subjected to single-cell RNA-seq (scRNA-seq) and single-cell ATAC-seq (scATAC-seq) analyses. Mitochondrial gene expression was higher in differentiated than in non-differentiated hepatocytes, with ATAC-seq peaks increasing near the mitochondrial control region. Differentiation of liver organoids resulted in the expression of transcription factors that act as enhancers and repressors. In addition, epigenetic mechanisms regulating the expression of alpha-fetoprotein (AFP) and albumin (ALB) differed in liver organoids and adult liver. Knockdown of PDX1, an essential transcription factor for pancreas development, led to the hepatic maturation of liver organoids through regulation of AFP and ALB expression. This integrative analysis of the transcriptomes and epigenomes of liver organoids at the single-cell level may contribute to a better understanding of the regulatory networks during liver development and the further development of mature in vitro human liver models.

In silico analysis and theratyping of an ultra-rare CFTR genotype (W57G/A234D) in primary human rectal and nasal epithelial cells.

Mutation targeted therapy in cystic fibrosis (CF) is still not eligible for all CF subjects, especially for cases carrying rare variants such as the CFTR genotype W57G/A234D (c.169T>G/c.701C>A). We performed in silico analysis of the effects of these variants on protein stability, which we functionally characterized using colonoids and reprogrammed nasal epithelial cells. The effect of mutations on cystic fibrosis transmembrane conductance regulator (CFTR) protein was analyzed by western blotting, forskolin-induced swelling (FIS), and Ussing chamber analysis. We detected a residual CFTR function that increases following treatment with the CFTR modulators VX661±VX445±VX770, correlates among models, and is associated with increased CFTR protein levels following treatment with CFTR correctors. In vivo treatment with VX770 reduced sweat chloride concentration to non-CF levels, increased the number of CFTR-dependent sweat droplets, and induced a 6% absolute increase in predicted FEV1% after 27 weeks of treatment indicating the relevance of theratyping with patient-derived cells in CF.

Glycosylation network mapping and site-specific glycan maturation in vivo.

Glycoprotein processing along a complex highly compartmentalized pathway is a hallmark of eukaryotic cells. We followed the kinetics of intracellular, site-specific glycan processing of a model protein with five distinct N-glycosylation sites and deduced a mathematical model of the secretory pathway that describes a complex set of processing reactions localized in defined intracellular compartments such as the endoplasmic reticulum the Golgi, or the lysosome. The model was able to accommodate site-specific N-glycan processing and we identified phosphorylated glycan structures of the mannose-6-phosphate pathway responsible for the lysosomal sorting of the glycoprotein. Importantly, our model protein can take different routes of the cellular secretory pathway, resulting in an increased glycan complexity of the secreted protein.

Identification of lysine-lactylated substrates in gastric cancer cells.

Cancer cells tend to utilize aerobic glycolysis to generate energy and metabolites; the end product of aerobic glycolysis is lactate, which promotes lysine lactylation (Kla). Kla is a newly discovered histone post-translational modification (PTM) that plays important roles in regulating gene expression. However, Kla in non-histone mammalian proteins is unclear. Here, a comprehensive analysis of lactylated proteins in gastric cancer AGS cells was conducted. There were 2375 Kla sites found in 1014 proteins. Interestingly, KEGG pathway analysis showed that these proteins were significantly enriched in spliceosome function. In addition, Kla was more abundant in gastric tumors than in adjacent tissues, and high levels of Kla in gastric tumors were associated with poor prognosis. These results suggest that Kla could be a prognostic marker in gastric cancer. This lysine lactylome analysis in gastric cancer cells, the first of its kind, provides a valuable foundation for further studies of Kla.

Contribution of septins to human platelet structure and function.

Although septins have been well-studied in nucleated cells, their role in anucleate blood platelets remains obscure. Here, we elucidate the contribution of septins to human platelet structure and functionality. We show that Septin-2 and Septin-9 are predominantly distributed at the periphery of resting platelets and co-localize strongly with microtubules. Activation of platelets by thrombin causes clustering of septins and impairs their association with microtubules. Inhibition of septin dynamics with forchlorfenuron (FCF) reduces thrombin-induced densification of septins and lessens their colocalization with microtubules in resting and activated platelets. Exposure to FCF alters platelet shape, suggesting that septins stabilize platelet cytoskeleton. FCF suppresses platelet integrin αIIbß3 activation, promotes phosphatidylserine exposure on activated platelets, and induces P-selectin expression on resting platelets, suggesting septin involvement in these processes. Inhibition of septin dynamics substantially reduces platelet contractility and abrogates their spreading on fibrinogen-coated surfaces. Overall, septins strongly contribute to platelet structure, activation and biomechanics.

A fatal affair: Circulating tumor cell relationships that shape metastasis.

Circulating tumor cells are metastatic precursors in several cancer types. Their biology and clinical utility are subject to numerous investigations, yet one aspect that is often neglected is their entanglement with the tumor microenvironment, namely the cross talk with stromal and immune cells and their relationships with other tumor-derived components such as circulating tumor DNA and extracellular vesicles in circulation. We will focus our short review specifically on these aspects, i.e., providing some examples of the liaison that circulating tumor cells have with stromal or immune cells and illustrating their relationship with other circulating tumor derivatives such as circulating tumor DNA and extracellular vesicles.

Electrically synchronizing and modulating the dynamics of ERK activation to regulate cell fate.

Intracellular signaling dynamics play fundamental roles in cell biology. Precise modulation of the amplitude, duration, and frequency of signaling activation will be a powerful approach to investigate molecular mechanisms as well as to engineer signaling to control cell behaviors. Here, we showed a practical approach to achieve precise amplitude modulation (AM), frequency modulation (FM), and duration modulation (DM) of MAP kinase activation. Alternating current (AC) electrical stimulation induced synchronized ERK activation. Amplitude and duration of ERK activation were controlled by varying stimulation strength and duration. ERK activation frequencies were arbitrarily modulated with trains of short AC applications with accurately defined intervals. Significantly, ERK dynamics coded by well-designed AC can rewire PC12 cell fate independent of growth factors. This technique can be used to synchronize and modulate ERK activation dynamics, thus would offer a practical way to control cell behaviors in vivo without the use of biochemical agents or genetic manipulation.

Constraint-based modeling of yeast mitochondria reveals the dynamics of protein import and iron-sulfur cluster biogenesis.

Mitochondria are a hallmark of eukaryal cells and play an important role in cellular metabolism. There is a vast amount of knowledge available on mitochondrial metabolism and essential mitochondrial functions, such as protein import and iron-sulfur cluster biosynthesis, including multiple studies on the mitochondrial proteome. Therefore, there is a need for in silico approaches to facilitate the analysis of these data. Here, we present a detailed model of mitochondrial metabolism Saccharomyces cerevisiae, including protein import, iron-sulfur cluster biosynthesis, and a description of the coupling between charge translocation processes and ATP synthesis. Model analysis implied a dual dependence of absolute levels of proteins in protein import, iron-sulfur cluster biogenesis and cluster abundance on growth rate and respiratory activity. The model is instrumental in studying dynamics and perturbations in these processes and given the high conservation of mitochondrial metabolism in humans, it can provide insight into their role in human disease.