Longitudinal single cell atlas identifies complex temporal relationship between type I interferon response and COVID-19 severity.

Due to the paucity of longitudinal molecular studies of COVID-19, particularly those covering the early stages of infection (Days 1-8 symptom onset), our understanding of host response over the disease course is limited. We perform longitudinal single cell RNA-seq on 286 blood samples from 108 age- and sex-matched COVID-19 patients, including 73 with early samples. We examine discrete cell subtypes and continuous cell states longitudinally, and we identify upregulation of type I IFN-stimulated genes (ISGs) as the predominant early signature of subsequent worsening of symptoms, which we validate in an independent cohort and corroborate by plasma markers. However, ISG expression is dynamic in progressors, spiking early and then rapidly receding to the level of severity-matched non-progressors. In contrast, cross-sectional analysis shows that ISG expression is deficient and IFN suppressors such as SOCS3 are upregulated in severe and critical COVID-19. We validate the latter in four independent cohorts, and SOCS3 inhibition reduces SARS-CoV-2 replication in vitro. In summary, we identify complexity in type I IFN response to COVID-19, as well as a potential avenue for host-directed therapy.

MethMotif.Org 2024: a database integrating context-specific transcription factor-binding motifs with DNA methylation patterns.

MethMotif (https://methmotif.org) is a publicly available database that provides a comprehensive repository of transcription factor (TF)-binding profiles, enriched with DNA methylation patterns. In this release, we have enhanced the platform, expanding our initial collection to over 700 position weight matrices (PWM), all of which include DNA methylation profiles. One of the key advancements in this release is the segregation of TF-binding motifs based on their cofactors and DNA methylation status. We have previously demonstrated that gene ontology (GO) enriched terms associated with TF target genes may differ based on their association with alternative cofactors and DNA methylation status. MethMotif provides precomputed GO annotations for each human TF of interest, as well as for TF-co-TF complexes, enabling a comprehensive analysis of TF functions in the context of their co-factors. Additionally, MethMotif has been updated to encompass data for two new species, Mus musculus and Arabidopsis thaliana, widening its applicability to a broader community. MethMotif stands out as the first and only TF-binding motifs database to incorporate context-specific PWM coupled with epigenetic information, thereby enlightening context-specific TF functions. This enhancement allows the community to explore and gain deeper insights into the regulatory mechanisms governing transcriptional processes.

Human Nasal Epithelial Cells Sustain Persistent SARS-CoV-2 Infection In Vitro, despite Eliciting a Prolonged Antiviral Response.

The dynamics of SARS-CoV-2 infection in COVID-19 patients are highly variable, with a subset of patients demonstrating prolonged virus shedding, which poses a significant challenge for disease management and transmission control. In this study, the long-term dynamics of SARS-CoV-2 infection were investigated using a human well-differentiated nasal epithelial cell (NEC) model of infection. NECs were observed to release SARS-CoV-2 virus onto the apical surface for up to 28 days postinfection (dpi), further corroborated by viral antigen staining. Single-cell transcriptome sequencing (sc-seq) was utilized to explore the host response from infected NECs after short-term (3-dpi) and long-term (28-dpi) infection. We identified a unique population of cells harboring high viral loads present at both 3 and 28 dpi, characterized by expression of cell stress-related genes DDIT3 and ATF3 and enriched for genes involved in tumor necrosis factor alpha (TNF-α) signaling and apoptosis. Remarkably, this sc-seq analysis revealed an antiviral gene signature within all NEC cell types even at 28 dpi. We demonstrate increased replication of basal cells, absence of widespread cell death within the epithelial monolayer, and the ability of SARS-CoV-2 to replicate despite a continuous interferon response as factors likely contributing to SARS-CoV-2 persistence. This study provides a model system for development of therapeutics aimed at improving viral clearance in immunocompromised patients and implies a crucial role for immune cells in mediating viral clearance from infected epithelia. IMPORTANCE Increasing medical attention has been drawn to the persistence of symptoms (long-COVID syndrome) or live virus shedding from subsets of COVID-19 patients weeks to months after the initial onset of symptoms. In vitro approaches to model viral or symptom persistence are needed to fully dissect the complex and likely varied mechanisms underlying these clinical observations. We show that in vitro differentiated human NECs are persistently infected with SARS-CoV-2 for up to 28 dpi. This viral replication occurred despite the presence of an antiviral gene signature across all NEC cell types even at 28 dpi. This indicates that epithelial cell intrinsic antiviral responses are insufficient for the clearance of SARS-CoV-2, implying an essential role for tissue-resident and infiltrating immune cells for eventual viral clearance from infected airway tissue in COVID-19 patients.

LncRNA SFTA1P mediates positive feedback regulation of the Hippo-YAP/TAZ signaling pathway in non-small cell lung cancer.

Long non-coding RNAs (lncRNAs) regulate numerous biological processes involved in both development and carcinogenesis. Hippo-YAP/TAZ signaling, a critical pathway responsible for organ size control, is often dysregulated in a variety of cancers. However, the nature and function of YAP/TAZ-regulated lncRNAs during tumorigenesis remain largely unexplored. By profiling YAP/TAZ-regulated lncRNAs, we identified SFTA1P as a novel transcriptional target and a positive feedback regulator of YAP/TAZ signaling. Using non-small cell lung cancer (NSCLC) cell lines, we show that SFTA1P is transcriptionally activated by YAP/TAZ in a TEAD-dependent manner. Functionally, knockdown of SFTA1P in NSCLC cell lines inhibited proliferation, induced programmed cell death, and compromised their tumorigenic potential. Mechanistically, SFTA1P knockdown decreased TAZ protein abundance and consequently, the expression of YAP/TAZ transcriptional targets. We provide evidence that this phenomenon could potentially be mediated via its interaction with TAZ mRNA to regulate TAZ translation. Our results reveal SFTA1P as a positive feedback regulator of Hippo-YAP/TAZ signaling, which may serve as the molecular basis for lncRNA-based therapies against YAP/TAZ-driven cancers.

RCA2: a scalable supervised clustering algorithm that reduces batch effects in scRNA-seq data.

The transcriptomic diversity of cell types in the human body can be analysed in unprecedented detail using single cell (SC) technologies. Unsupervised clustering of SC transcriptomes, which is the default technique for defining cell types, is prone to group cells by technical, rather than biological, variation. Compared to de-novo (unsupervised) clustering, we demonstrate using multiple benchmarks that supervised clustering, which uses reference transcriptomes as a guide, is robust to batch effects and data quality artifacts. Here, we present RCA2, the first algorithm to combine reference projection (batch effect robustness) with graph-based clustering (scalability). In addition, RCA2 provides a user-friendly framework incorporating multiple commonly used downstream analysis modules. RCA2 also provides new reference panels for human and mouse and supports generation of custom panels. Furthermore, RCA2 facilitates cell type-specific QC, which is essential for accurate clustering of data from heterogeneous tissues. We demonstrate the advantages of RCA2 on SC data from human bone marrow, healthy PBMCs and PBMCs from COVID-19 patients. Scalable supervised clustering methods such as RCA2 will facilitate unified analysis of cohort-scale SC datasets.

Hydrogel-based colorectal cancer organoid co-culture models.

The lack of cancer-associated fibroblasts (CAFs) in patient-derived organoid (PDO) models is a major limitation as CAFs contribute to tumor progression and drug resistance. In the present study, we addressed this problem by establishing in vitro conditions that enable the co-culture of colorectal cancer (CRC) PDO with patient-derived CAFs. Considering that the CRC extracellular matrix is high in hyaluronan and collagen I, we hypothesized that hyaluronan-gelatin hydrogels may serve as a suitable alternative 3D matrix to traditionally used basement membrane extracts to support the co-culture of CRC PDO and CAFs. We report the development of in vitro models consisting of CRC PDO encapsulated within a well-defined three-dimensional (3D) hyaluronan-gelatin hydrogel and co-cultured with patient-derived CAFs. Through RNA- and whole -exome sequencing, we first show that these hydrogels are capable of maintaining key molecular characteristics of the original patient tumors in CRC PDO but not support the culture of CAFs. Further, based on our findings that CRC PDO culture medium poorly supports CAF viability, we developed a co-culture strategy that maintains the viability of both CRC PDO and CAFs. We found that even in the absence of growth factors conventionally used to support CRC PDO culture, CAFs were able to maintain the proliferation of the cultured CRC PDO in the hydrogels and restore distinct biological pathways absent in the PDO culture alone but present in patient tissues. Lastly, we demonstrate that these CRC PDO-CAFs co-culture models are suitable for evaluating standard-of-care drugs, making them potentially very useful for realizing personalized cancer medicine. STATEMENT OF SIGNIFICANCE: We report the development of an engineered tumor microenvironment consisting of colorectal cancer patient-derived organoids (CRC PDO) encapsulated within a well-defined three-dimensional (3D) hyaluronan-gelatin hydrogel and co-cultured with patient-derived cancer-associated fibroblasts (CAFs). Through sequential culture, we found that in the absence of growth factors added to the co-culture, CAFs were able to maintain the proliferation of the cultured CRC PDO in the hydrogels and restore distinct biological pathways absent in the PDO culture alone but present in patient tissues. Lastly, we demonstrate that these CRC PDO-CAFs models are suitable for evaluating standard-of-care drugs, making them potentially very useful for realizing personalized cancer medicine.

Targeted Inhibition of Purine Metabolism Is Effective in Suppressing Hepatocellular Carcinoma Progression.

Tumor-specific metabolic rewiring, acquired to confer a proliferative and survival advantage over nontransformed cells, represents a renewed focus in cancer therapy development. Hepatocellular carcinoma (HCC), a malignancy that has hitherto been resistant to compounds targeting oncogenic signaling pathways, represents a candidate cancer to investigate the efficacy of selectively antagonizing such adaptive metabolic reprogramming. To this end, we sought to characterize metabolic changes in HCC necessary for tumorigenesis. We analyzed gene expression profiles in three independent large-scale patient cohorts who had HCC. We identified a commonly deregulated purine metabolic signature in tumors with the extent of purine biosynthetic enzyme up-regulation correlated with tumor grade and a predictor of clinical outcome. The functional significance of enhanced purine metabolism as a hallmark in human HCC was then validated using a combination of HCC cell lines, patient-derived xenograft (PDX) organoids, and mouse models. Targeted ablation of purine biosynthesis by knockdown of the rate-limiting enzyme inosine-5'-monophosphate dehydrogenase (IMPDH) or using the drug mycophenolate mofetil (MMF) reduced HCC proliferation in vitro and decreased the tumor burden in vivo. In comparing the sensitivities of PDX tumor organoids to MMF therapy, we found that HCC tumors defined by high levels of IMPDH and guanosine nucleosides were most susceptible to treatment. Mechanistically, a phosphoinositide 3-kinase (PI3K)-E2F transcription factor 1 (E2F1) axis coordinated purine biosynthetic enzyme expression, deregulation of which altered the activity of mitogen-activated protein kinase/RAS signaling. Simultaneously abolishing PI3K signaling and IMPDH activity with clinically approved inhibitors resulted in greatest efficacy in reducing tumor growth in a PDX mouse model. Conclusion: Enhanced purine metabolic activity regulated by PI3K pathway-dependent activation of E2F1 promotes HCC carcinogenesis, suggesting the potential for targeting purine metabolic reprogramming as a precision therapeutic strategy for patients with HCC.

TFregulomeR reveals transcription factors' context-specific features and functions.

Transcription factors (TFs) are sequence-specific DNA binding proteins, fine-tuning spatiotemporal gene expression. Since genomic occupancy of a TF is highly dynamic, it is crucial to study TF binding sites (TFBSs) in a cell-specific context. To date, thousands of ChIP-seq datasets have portrayed the genomic binding landscapes of numerous TFs in different cell types. Although these datasets can be browsed via several platforms, tools that can operate on that data flow are still lacking. Here, we introduce TFregulomeR (https://github.com/benoukraflab/TFregulomeR), an R-library linked to an up-to-date compendium of cistrome and methylome datasets, implemented with functionalities that facilitate integrative analyses. In particular, TFregulomeR enables the characterization of TF binding partners and cell-specific TFBSs, along with the study of TF's functions in the context of different partnerships and DNA methylation levels. We demonstrated that TFs' target gene ontologies can differ notably depending on their partners and, by re-analyzing well characterized TFs, we brought to light that numerous leucine zipper TFBSs derived from ChIP-seq experiments documented in current databases were inadequately characterized, due to the fact that their position weight matrices were assembled using a mixture of homodimer and heterodimer binding sites. Altogether, analyses of context-specific transcription regulation with TFregulomeR foster our understanding of regulatory network-dependent TF functions.

Sphingosine-1-phosphate signaling modulates terminal erythroid differentiation through the regulation of mitophagy.

Erythropoiesis is a highly coordinated stepwise process involving the progressive clearance of mitochondria via mitophagy. Based on the expression of several macroautophagy and mitophagy specific genes, we identified a sequential change in the transcriptional pattern during terminal erythroid differentiation. Because erythroid cells are a major source of serum sphingosine-1-phosphate, we analyzed the role of sphingolipid signaling in erythropoiesis and demonstrate that sphingosine kinase activity promotes terminal erythroid differentiation by regulating the expression of key mitophagy genes Pink1 and Bnip3l/Nix. Sphingosine kinase 1 (Sphk1) inhibition also disrupted Pink1-p62 mediated mitochondria clearance in late erythroblasts. Notably, we show that supplementing sphingosine-1-phosphate in vitro can promote erythroid differentiation. Our study clarifies the role of sphingolipid signaling in regulating mitophagy during terminal erythroid differentiation and highlights the potential utility of modulating sphingolipid signaling to facilitate the large-scale production of transfusable red blood cells.

Datasets describing the growth and molecular features of hepatocellular carcinoma patient-derived xenograft cells grown in a three-dimensional macroporous hydrogel.

This data article presents datasets associated with the research article entitled "Generation of matched patient-derived xenograft in vitro-in vivo models using 3D macroporous hydrogels for the study of liver cancer" (Fong et al., 2018) [1]. A three-dimensional macroporous sponge system was used to generate in vitro counterparts to various hepatocellular carcinoma patient-derived xenograft (HCC-PDX) lines. This article describes the viability, proliferative capacity and molecular features (genomic and transcriptomic profiles) of the cultured HCC-PDX cells. The sequencing datasets are made publicly available to enable critical or further analyzes.

Generation of matched patient-derived xenograft in vitro-in vivo models using 3D macroporous hydrogels for the study of liver cancer.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide, often manifesting at the advanced stage when cure is no longer possible. The discrepancy between preclinical findings and clinical outcome in HCC is well-recognized. So far, sorafenib is the only targeted therapy approved as first-line therapy for patients with advanced HCC. There is an urgent need for improved preclinical models for the development of HCC-targeted therapies. Patient-derived xenograft (PDX) tumor models have been shown to closely recapitulate human tumor biology and predict patient drug response. However, the use of PDX models is currently limited by high costs and low throughput. In this study, we engineered in vitro conditions conducive for the culture of HCC-PDX organoids derived from a panel of 14 different HCC-PDX lines through the use of a three-dimensional macroporous cellulosic sponge system. To validate the in vitro HCC-PDX models, both in vivo and in vitro HCC-PDX models were subjected to whole exome sequencing and RNA-sequencing. Correlative studies indicate strong concordance in genomic and transcriptomic profiles as well as intra-tumoral heterogeneity between each matched in vitro-in vivo HCC-PDX pairs. Furthermore, we demonstrate the feasibility of using these in vitro HCC-PDX models for drug testing, paving the way for more efficient preclinical studies in HCC drug development.