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Aryl Hydrocarbon Receptor Knockout Accelerates PanIN Formation and Fibro-Inflammation in a Mutant Kras -Driven Pancreatic Cancer Model

OBJECTIVES

The pathogenesis of pancreas cancer (PDAC) remains poorly understood, hindering efforts to develop a more effective therapy for PDAC. Recent discoveries show the aryl hydrocarbon receptor (AHR) plays a crucial role in the development of several cancers and can be targeted for therapeutic effect. However, its involvement in the pathogenesis of PDAC remains unclear. To address this gap, we evaluated the role of AHR in the development of PDAC precancerous lesions in vivo .

MATERIALS AND METHODS

We created a global AHR-null, mutant Kras -driven PDAC mouse model (A -/- KC) and evaluated the changes in PDAC precursor lesion formation (PanIN-1, 2, and 3) and associated fibro-inflammation between KC and A -/- KC at 5 months of age. We then examined the changes in the immune microenvironment followed by single-cell RNA-sequencing analysis to evaluate concomitant transcriptomic changes.

RESULTS

We identified a significant increase in PanIN-1 lesion formation and PanIN-1 associated fibro-inflammatory infiltrate in A -/- KC versus KC mice. This was associated with significant changes in the adaptive immune system, particularly a decrease in the CD4+/CD8+ T-cell ratio, as well as a decrease in the T-regulatory/Th17 T-cell ratio suggesting unregulated inflammation.

CONCLUSIONS

These findings show the loss of AHR results in heightened Kras -induced PanIN formation, through modulation of immune cells within the pancreatic tumor microenvironment.

Bayesian clustering with uncertain data

Clustering is widely used in bioinformatics and many other fields, with applications from exploratory analysis to prediction. Many types of data have associated uncertainty or measurement error, but this is rarely used to inform the clustering. We present Dirichlet Process Mixtures with Uncertainty (DPMUnc), an extension of a Bayesian nonparametric clustering algorithm which makes use of the uncertainty associated with data points. We show that DPMUnc out-performs existing methods on simulated data. We cluster immune-mediated diseases (IMD) using GWAS summary statistics, which have uncertainty linked with the sample size of the study. DPMUnc separates autoimmune from autoinflammatory diseases and isolates other subgroups such as adult-onset arthritis. We additionally consider how DPMUnc can be used to cluster gene expression datasets that have been summarised using gene signatures. We first introduce a novel procedure for generating a summary of a gene signature on a dataset different to the one where it was discovered, which incorporates a measure of the variability in expression across signature genes within each individual. We summarise three public gene expression datasets containing patients with a range of IMD, using three relevant gene signatures. We find association between disease and the clusters returned by DPMUnc, with clustering structure replicated across the datasets. The significance of this work is two-fold. Firstly, we demonstrate that when data has associated uncertainty, this uncertainty should be used to inform clustering and we present a method which does this, DPMUnc. Secondly, we present a procedure for using gene signatures in datasets other than where they were originally defined. We show the value of this procedure by summarising gene expression data from patients with immune-mediated diseases using relevant gene signatures, and clustering these patients using DPMUnc.

The Proteogenomics of Prostate Cancer Radioresistance

Prostate cancer is frequently treated with radiotherapy. Unfortunately, aggressive radioresistant relapses can arise, and the molecular underpinnings of radioresistance are unknown. Modern clinical radiotherapy is evolving to deliver higher doses of radiation in fewer fractions (hypofractionation). We therefore analyzed genomic, transcriptomic, and proteomic data to characterize prostate cancer radioresistance in cells treated with both conventionally fractionated and hypofractionated radiotherapy. Independent of fractionation schedule, resistance to radiotherapy involved massive genomic instability and abrogation of DNA mismatch repair. Specific prostate cancer driver genes were modulated at the RNA and protein levels, with distinct protein subcellular responses to radiotherapy. Conventional fractionation led to a far more aggressive biomolecular response than hypofractionation. Testing preclinical candidates identified in cell lines, we revealed POLQ (DNA Polymerase Theta) as a radiosensitizer. POLQ-modulated radioresistance in model systems and was predictive of it in large patient cohorts. The molecular response to radiation is highly multimodal and sheds light on prostate cancer lethality.

SIGNIFICANCE

Radiation is standard of care in prostate cancer. Yet, we have little understanding of its failure. We demonstrate a new paradigm that radioresistance is fractionation specific and identified POLQ as a radioresistance modulator.

Transcriptomic dysregulation and autistic-like behaviors in Kmt2c haploinsufficient mice rescued by an LSD1 inhibitor

Recent studies have consistently demonstrated that the regulation of chromatin and gene transcription plays a pivotal role in the pathogenesis of neurodevelopmental disorders. Among many genes involved in these pathways, KMT2C, encoding one of the six known histone H3 lysine 4 (H3K4) methyltransferases in humans and rodents, was identified as a gene whose heterozygous loss-of-function variants are causally associated with autism spectrum disorder (ASD) and the Kleefstra syndrome phenotypic spectrum. However, little is known about how KMT2C haploinsufficiency causes neurodevelopmental deficits and how these conditions can be treated. To address this, we developed and analyzed genetically engineered mice with a heterozygous frameshift mutation of Kmt2c (Kmt2c+/fs mice) as a disease model with high etiological validity. In a series of behavioral analyses, the mutant mice exhibit autistic-like behaviors such as impairments in sociality, flexibility, and working memory, demonstrating their face validity as an ASD model. To investigate the molecular basis of the observed abnormalities, we performed a transcriptomic analysis of their bulk adult brains and found that ASD risk genes were specifically enriched in the upregulated differentially expressed genes (DEGs), whereas KMT2C peaks detected by ChIP-seq were significantly co-localized with the downregulated genes, suggesting an important role of putative indirect effects of Kmt2c haploinsufficiency. We further performed single-cell RNA sequencing of newborn mouse brains to obtain cell type-resolved insights at an earlier stage. By integrating findings from ASD exome sequencing, genome-wide association, and postmortem brain studies to characterize DEGs in each cell cluster, we found strong ASD-associated transcriptomic changes in radial glia and immature neurons with no obvious bias toward upregulated or downregulated DEGs. On the other hand, there was no significant gross change in the cellular composition. Lastly, we explored potential therapeutic agents and demonstrate that vafidemstat, a lysine-specific histone demethylase 1 (LSD1) inhibitor that was effective in other models of neuropsychiatric/neurodevelopmental disorders, ameliorates impairments in sociality but not working memory in adult Kmt2c+/fs mice. Intriguingly, the administration of vafidemstat was shown to alter the vast majority of DEGs in the direction to normalize the transcriptomic abnormalities in the mutant mice (94.3 and 82.5% of the significant upregulated and downregulated DEGs, respectively, P < 2.2 × 10-16, binomial test), which could be the molecular mechanism underlying the behavioral rescuing. In summary, our study expands the repertoire of ASD models with high etiological and face validity, elucidates the cell-type resolved molecular alterations due to Kmt2c haploinsufficiency, and demonstrates the efficacy of an LSD1 inhibitor that might be generalizable to multiple categories of psychiatric disorders along with a better understanding of its presumed mechanisms of action.

Comparative single-cell transcriptomic analysis reveals putative differentiation drivers and potential origin of vertebrate retina

Despite known single-cell expression profiles in vertebrate retinas, understanding of their developmental and evolutionary expression patterns among homologous cell classes remains limited. We examined and compared approximately 240 000 retinal cells from four species and found significant similarities among homologous cell classes, indicating inherent regulatory patterns. To understand these shared patterns, we constructed gene regulatory networks for each developmental stage for three of these species. We identified 690 regulons governed by 530 regulators across three species, along with 10 common cell class-specific regulators and 16 highly preserved regulons. RNA velocity analysis pinpointed conserved putative driver genes and regulators to retinal cell differentiation in both mouse and zebrafish. Investigation of the origins of retinal cells by examining conserved expression patterns between vertebrate retinal cells and invertebrate Ciona intestinalis photoreceptor-related cells implied functional similarities in light transduction mechanisms. Our findings offer insights into the evolutionarily conserved regulatory frameworks and differentiation drivers of vertebrate retinal cells.

Clusters of mammalian conserved RNA structures in UTRs associate with RBP binding sites

RNA secondary structures play essential roles in the formation of the tertiary structure and function of a transcript. Recent genome-wide studies highlight significant potential for RNA structures in the mammalian genome. However, a major challenge is assigning functional roles to these structured RNAs. In this study, we conduct a guilt-by-association analysis of clusters of computationally predicted conserved RNA structure (CRSs) in human untranslated regions (UTRs) to associate them with gene functions. We filtered a broad pool of ∼500 000 human CRSs for UTR overlap, resulting in 4734 and 24 754 CRSs from the 5' and 3' UTR of protein-coding genes, respectively. We separately clustered these CRSs for both sets using RNAscClust, obtaining 793 and 2403 clusters, each containing an average of five CRSs per cluster. We identified overrepresented binding sites for 60 and 43 RNA-binding proteins co-localizing with the clustered CRSs. Furthermore, 104 and 441 clusters from the 5' and 3' UTRs, respectively, showed enrichment for various Gene Ontologies, including biological processes such as 'signal transduction', 'nervous system development', molecular functions like 'transferase activity' and the cellular components such as 'synapse' among others. Our study shows that significant functional insights can be gained by clustering RNA structures based on their structural characteristics.

Colocalised Genetic Associations Reveal Alternative Splicing Variants as Candidate Causal Links for Breast Cancer Risk in 10 Loci

Genome-wide association studies (GWASs) have revealed numerous loci associated with breast cancer risk, yet the precise causal variants, their impact on molecular mechanisms, and the affected genes often remain elusive. We hypothesised that specific variants exert their influence by affecting cis-regulatory alternative splice elements. An analysis of splicing quantitative trait loci (sQTL) in healthy breast tissue from female individuals identified multiple variants linked to alterations in splicing ratios. Through colocalisation analysis, we pinpointed 43 variants within twelve genes that serve as candidate causal links between sQTL and GWAS findings. In silico splice analysis highlighted a potential mechanism for three genes-FDPS, SGCE, and MRPL11-where variants in proximity to or on the splice site modulate usage, resulting in alternative splice transcripts. Further in vitro/vivo studies are imperative to fully understand how these identified changes contribute to breast oncogenesis. Moreover, investigating their potential as biomarkers for breast cancer risk could enhance screening strategies and early detection methods for breast cancer.

Association with TFIIIC limits MYCN localisation in hubs of active promoters and chromatin accumulation of non-phosphorylated RNA polymerase II

MYC family oncoproteins regulate the expression of a large number of genes and broadly stimulate elongation by RNA polymerase II (RNAPII). While the factors that control the chromatin association of MYC proteins are well understood, much less is known about how interacting proteins mediate MYC's effects on transcription. Here, we show that TFIIIC, an architectural protein complex that controls the three-dimensional chromatin organisation at its target sites, binds directly to the amino-terminal transcriptional regulatory domain of MYCN. Surprisingly, TFIIIC has no discernible role in MYCN-dependent gene expression and transcription elongation. Instead, MYCN and TFIIIC preferentially bind to promoters with paused RNAPII and globally limit the accumulation of non-phosphorylated RNAPII at promoters. Consistent with its ubiquitous role in transcription, MYCN broadly participates in hubs of active promoters. Depletion of TFIIIC further increases MYCN localisation to these hubs. This increase correlates with a failure of the nuclear exosome and BRCA1, both of which are involved in nascent RNA degradation, to localise to active promoters. Our data suggest that MYCN and TFIIIC exert an censoring function in early transcription that limits promoter accumulation of inactive RNAPII and facilitates promoter-proximal degradation of nascent RNA.

Host Transcriptional Meta-signatures Reveal Diagnostic Biomarkers for Plasmodium falciparum Malaria

BACKGROUND

Transcriptomics has been used to evaluate immune responses during malaria in diverse cohorts worldwide. However, the high heterogeneity of cohorts and poor generalization of transcriptional signatures reported in each study limit their potential clinical applications.

METHODS

We compiled 28 public data sets containing 1556 whole-blood or peripheral blood mononuclear cell transcriptome samples. We estimated effect sizes with Hedge's g value and the DerSimonian-Laird random-effects model for meta-analyses of uncomplicated malaria. Random forest models identified gene signatures that discriminate malaria from bacterial infections or malaria severity. Parasitological, hematological, immunological, and metabolomics data were used for validation.

RESULTS

We identified 3 gene signatures: the uncomplicated Malaria Meta-Signature, which discriminates Plasmodium falciparum malaria from uninfected controls; the Malaria or Bacteria Signature, which distinguishes malaria from sepsis and enteric fever; and the cerebral Malaria Meta-Signature, which characterizes individuals with cerebral malaria. These signatures correlate with clinical hallmark features of malaria. Blood transcription modules indicate immune regulation by glucocorticoids, whereas cell development and adhesion are associated with cerebral malaria.

CONCLUSIONS

Transcriptional meta-signatures reflecting immune cell responses provide potential biomarkers for translational innovation and suggest critical roles for metabolic regulators of inflammation during malaria.

Host response to influenza infections in human blood: association of influenza severity with host genetics and transcriptomic response

Introduction

Influenza virus infections are a major global health problem. Influenza can result in mild/moderate disease or progress to more severe disease, leading to high morbidity and mortality. Severity is thought to be primarily driven by immunopathology, but predicting which individuals are at a higher risk of being hospitalized warrants investigation into host genetics and the molecular signatures of the host response during influenza infections.

Methods

Here, we performed transcriptome and genotype analysis in healthy controls and patients exhibiting mild/moderate or severe influenza (ICU patients). A unique aspect of our study was the genotyping of all participants, which allowed us to assign ethnicities based on genetic variation and assess whether the variation was correlated with expression levels.

Results

We identified 169 differentially expressed genes and related molecular pathways between patients in the ICU and those who were not in the ICU. The transcriptome/genotype association analysis identified 871 genes associated to a genetic variant and 39 genes distinct between African-Americans and Caucasians. We also investigated the effects of age and sex and found only a few discernible gene effects in our cohort.

Discussion

Together, our results highlight select risk factors that may contribute to an increased risk of ICU admission for influenza-infected patients. This should help to develop better diagnostic tools based on molecular signatures, in addition to a better understanding of the biological processes in the host response to influenza.

Cross-species imputation and comparison of single-cell transcriptomic profiles

Cross-species comparison and prediction of gene expression profiles are important to understand regulatory changes during evolution and to transfer knowledge learned from model organisms to humans. Single-cell RNA-seq (scRNA-seq) profiles enable us to capture gene expression profiles with respect to variations among individual cells; however, cross-species comparison of scRNA-seq profiles is challenging because of data sparsity, batch effects, and the lack of one-to-one cell matching across species. Moreover, single-cell profiles are challenging to obtain in certain biological contexts, limiting the scope of hypothesis generation. Here we developed Icebear, a neural network framework that decomposes single-cell measurements into factors representing cell identity, species, and batch factors. Icebear enables accurate prediction of single-cell gene expression profiles across species, thereby providing high-resolution cell type and disease profiles in under-characterized contexts. Icebear also facilitates direct cross-species comparison of single-cell expression profiles for conserved genes that are located on the X chromosome in eutherian mammals but on autosomes in chicken. This comparison, for the first time, revealed evolutionary and diverse adaptations of X-chromosome upregulation in mammals.

Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells

BACKGROUND

Cells and tissues have a remarkable ability to adapt to genetic perturbations via a variety of molecular mechanisms. Nonsense-induced transcriptional compensation, a form of transcriptional adaptation, has recently emerged as one such mechanism, in which nonsense mutations in a gene trigger upregulation of related genes, possibly conferring robustness at cellular and organismal levels. However, beyond a handful of developmental contexts and curated sets of genes, no comprehensive genome-wide investigation of this behavior has been undertaken for mammalian cell types and conditions. How the regulatory-level effects of inherently stochastic compensatory gene networks contribute to phenotypic penetrance in single cells remains unclear.

RESULTS

We analyze existing bulk and single-cell transcriptomic datasets to uncover the prevalence of transcriptional adaptation in mammalian systems across diverse contexts and cell types. We perform regulon gene expression analyses of transcription factor target sets in both bulk and pooled single-cell genetic perturbation datasets. Our results reveal greater robustness in expression of regulons of transcription factors exhibiting transcriptional adaptation compared to those of transcription factors that do not. Stochastic mathematical modeling of minimal compensatory gene networks qualitatively recapitulates several aspects of transcriptional adaptation, including paralog upregulation and robustness to mutation. Combined with machine learning analysis of network features of interest, our framework offers potential explanations for which regulatory steps are most important for transcriptional adaptation.

CONCLUSIONS

Our integrative approach identifies several putative hits-genes demonstrating possible transcriptional adaptation-to follow-up on experimentally and provides a formal quantitative framework to test and refine models of transcriptional adaptation.

Epigenetic heterogeneity shapes the transcriptional landscape of regional microglia

Microglia, the innate immune cells in the central nervous system, exhibit distinct transcriptional profiles across brain regions that are important for facilitating their specialized function. There has been recent interest in identifying the epigenetic modifications associated with these distinct transcriptional profiles, as these may improve our understanding of the underlying mechanisms governing the functional specialization of microglia. One obstacle to achieving this goal is the large number of microglia required to obtain a genome-wide profile for a single histone modification. Given the cellular and regional heterogeneity of the brain, this would require pooling many samples which would impede biological applications that are limited by numbers of available animals. To overcome this obstacle, we have adapted a method of chromatin profiling known as Cleavage Under Targets and Tagmentation (CUT&Tag-Direct) to profile histone modifications associated with regional differences in gene expression throughout the brain reward system. Consistent with previous studies, we find that transcriptional profiles of microglia vary by brain region. However, here we report that these regional differences also exhibit transcriptional network signatures specific to each region. Additionally, we find that these region-dependent network signatures are associated with differential deposition of H3K27ac and H3K7me3, and while the H3K27me3 landscape is remarkably stable across brain regions, the H3K27ac landscape is most consistent with the anatomical location of microglia which explain their distinct transcriptional profiles. Altogether, these findings underscore the established role of H3K27me3 in cell fate determination and support the active role of H3K27ac in the dynamic regulation of microglial gene expression. In this study, we report a molecular and computational framework that can be applied to improve our understanding of the role of epigenetic regulation in microglia in both health and disease, using as few as 2,500 cells per histone mark.

Maturation of germinal center B cells after influenza virus vaccination in humans

Germinal centers (GC) are microanatomical lymphoid structures where affinity-matured memory B cells and long-lived bone marrow plasma cells are primarily generated. It is unclear how the maturation of B cells within the GC impacts the breadth and durability of B cell responses to influenza vaccination in humans. We used fine needle aspiration of draining lymph nodes to longitudinally track antigen-specific GC B cell responses to seasonal influenza vaccination. Antigen-specific GC B cells persisted for at least 13 wk after vaccination in two out of seven individuals. Monoclonal antibodies (mAbs) derived from persisting GC B cell clones exhibit enhanced binding affinity and breadth to influenza hemagglutinin (HA) antigens compared with related GC clonotypes isolated earlier in the response. Structural studies of early and late GC-derived mAbs from one clonal lineage in complex with H1 and H5 HAs revealed an altered binding footprint. Our study shows that inducing sustained GC reactions after influenza vaccination in humans supports the maturation of responding B cells.

Predictive signature of murine and human host response to typical and atypical pneumonia

BACKGROUND

Pneumonia due to typical bacterial, atypical bacterial and viral pathogens can be difficult to clinically differentiate. Host response-based diagnostics are emerging as a complementary diagnostic strategy to pathogen detection.

METHODS

We used murine models of typical bacterial, atypical bacterial and viral pneumonia to develop diagnostic signatures and understand the host's response to these types of infections. Mice were intranasally inoculated with Streptococcus pneumoniae, Mycoplasma pneumoniae, influenza or saline as a control. Peripheral blood gene expression analysis was performed at multiple time points. Differentially expressed genes were used to perform gene set enrichment analysis and generate diagnostic signatures. These murine-derived signatures were externally validated in silico using human gene expression data. The response to S. pneumoniae was the most rapid and robust.

RESULTS

Mice infected with M. pneumoniae had a delayed response more similar to influenza-infected animals. Diagnostic signatures for the three types of infection had 0.94-1.00 area under the receiver operator curve (auROC). Validation in five human gene expression datasets revealed auROC of 0.82-0.96.

DISCUSSION

This study identified discrete host responses to typical bacterial, atypical bacterial and viral aetiologies of pneumonia in mice. These signatures validated well in humans, highlighting the conserved nature of the host response to these pathogen classes.

Glucosylceramide synthase modulation ameliorates murine renal pathologies and promotes macrophage effector function in vitro

While significant advances have been made in understanding renal pathophysiology, less is known about the role of glycosphingolipid (GSL) metabolism in driving organ dysfunction. Here, we used a small molecule inhibitor of glucosylceramide synthase to modulate GSL levels in three mouse models of distinct renal pathologies: Alport syndrome (Col4a3 KO), polycystic kidney disease (Nek8jck), and steroid-resistant nephrotic syndrome (Nphs2 cKO). At the tissue level, we identified a core immune-enriched transcriptional signature that was shared across models and enriched in human polycystic kidney disease. Single nuclei analysis identified robust transcriptional changes across multiple kidney cell types, including epithelial and immune lineages. To further explore the role of GSL modulation in macrophage biology, we performed in vitro studies with homeostatic and inflammatory bone marrow-derived macrophages. Cumulatively, this study provides a comprehensive overview of renal dysfunction and the effect of GSL modulation on kidney-derived cells in the setting of renal dysfunction.

TransTEx: novel tissue-specificity scoring method for grouping human transcriptome into different expression groups

MOTIVATION

Although human tissues carry out common molecular processes, gene expression patterns can distinguish different tissues. Traditional informatics methods, primarily at the gene level, overlook the complexity of alternative transcript variants and protein isoforms produced by most genes, changes in which are linked to disease prognosis and drug resistance.

RESULTS

We developed TransTEx (Transcript-level Tissue Expression), a novel tissue-specificity scoring method, for grouping transcripts into four expression groups. TransTEx applies sequential cut-offs to tissue-wise transcript probability estimates, subsampling-based P-values and fold-change estimates. Application of TransTEx on GTEx mRNA-seq data divided 199 166 human transcripts into different groups as 17 999 tissue-specific (TSp), 7436 tissue-enhanced, 36 783 widely expressed (Wide), 79 191 lowly expressed (Low), and 57 757 no expression (Null) transcripts. Testis has the most (13 466) TSp isoforms followed by liver (890), brain (701), pituitary (435), and muscle (420). We found that the tissue specificity of alternative transcripts of a gene is predominantly influenced by alternate promoter usage. By overlapping brain-specific transcripts with the cell-type gene-markers in scBrainMap database, we found that 63% of the brain-specific transcripts were enriched in nonneuronal cell types, predominantly astrocytes followed by endothelial cells and oligodendrocytes. In addition, we found 61 brain cell-type marker genes encoding a total of 176 alternative transcripts as brain-specific and 22 alternative transcripts as testis-specific, highlighting the complex TSp and cell-type specific gene regulation and expression at isoform-level. TransTEx can be adopted to the analysis of bulk RNA-seq or scRNA-seq datasets to find tissue- and/or cell-type specific isoform-level gene markers.

AVAILABILITY AND IMPLEMENTATION

TransTEx database: https://bmi.cewit.stonybrook.edu/transtexdb/ and the R package is available via GitHub: https://github.com/pallavisurana1/TransTEx.

Development of a hepatic cryoinjury model to study liver regeneration

The liver is a remarkable organ that can regenerate in response to injury. Depending on the extent of injury, the liver can undergo compensatory hyperplasia or fibrosis. Despite decades of research, the molecular mechanisms underlying these processes are poorly understood. Here, we developed a new model to study liver regeneration based on cryoinjury. To visualise liver regeneration at cellular resolution, we adapted the CUBIC tissue-clearing approach. Hepatic cryoinjury induced a localised necrotic and apoptotic lesion characterised by inflammation and infiltration of innate immune cells. After this initial phase, we observed fibrosis, which resolved as regeneration re-established homeostasis in 30 days. Importantly, this approach enables the comparison of healthy and injured parenchyma within an individual animal, providing unique advantages to previous models. In summary, the hepatic cryoinjury model provides a fast and reproducible method for studying the cellular and molecular pathways underpinning fibrosis and liver regeneration.

Single generation epigenetic change in captivity and reinforcement in subsequent generations in a delta smelt (Hypomesus transpacificus) conservation hatchery

A refugial population of the endangered delta smelt (Hypomesus transpacificus) has been maintained at the Fish Conservation and Culture Laboratory (FCCL) at UC Davis since 2008. Despite intense genetic management, fitness differences between wild and cultured fish have been observed at the FCCL. To investigate the molecular underpinnings of hatchery domestication, we used whole-genome bisulfite sequencing to quantify epigenetic differences between wild and hatchery-origin delta smelt. Differentially methylated regions (DMRs) were identified from 104 individuals by comparing the methylation patterns in different generations of hatchery fish (G1, G2, G3) with their wild parents (G0). We discovered a total of 132 significant DMRs (p < .05) between G0 and G1, 132 significant DMRs between G0 and G2, and 201 significant DMRs between G0 and G3. Our results demonstrate substantial differences in methylation patterns emerged between the wild and hatchery-reared fish in the early generations in the hatchery, with a higher proportion of hypermethylated DMRs in hatchery-reared fish. The rearing environment was found to be a stronger predictor of individual clustering based on methylation patterns than family, sex or generation. Our study indicates a reinforcement of the epigenetic status with successive generations in the hatchery environment, as evidenced by an increase in methylation in hypermethylated DMRs and a decrease in methylation in hypomethylated DMRs over time. Lastly, our results demonstrated heterogeneity in inherited methylation pattern in families across generations. These insights highlight the long-term consequences of hatchery practices on the epigenetic landscape, potentially impacting wild fish populations.

Molecular basis of the unique osmoregulatory strategy in the inshore hagfish, Eptatretus burgeri

Hagfishes are characterized by omo- and iono-conforming nature similar to marine invertebrates. Conventionally, hagfishes had been recognized as the most primitive living vertebrate that retains plesiomorphic features. However, some of the "ancestral" features of hagfishes, such as rudimentary eyes and the lack of vertebrae, have been proven to be deceptive. Similarly, by the principle of maximum parsimony, the unique body fluid regulatory strategy of hagfishes seems to be apomorphic, since the lamprey, another cyclostome, adopts osmo- and iono-regulatory mechanisms as in jawed vertebrates. Although hagfishes are unequivocally important in discussing the origin and evolution of the vertebrate osmoregulatory system, the molecular basis for the body fluid homeostasis in hagfishes has been poorly understood. In the present study, we explored this matter in the inshore hagfish, Eptatretus burgeri, by analyzing the transcriptomes obtained from the gill, kidney, and muscle of the animals acclimated to distinct environmental salinities. Together with the measurement of parameters in the muscular fluid compartment, our data indicate that the hagfish possesses an ability to conduct free amino acid (FAA)-based osmoregulation at a cellular level, which is in coordination with the renal and branchial FAA absorption. We also revealed that the hagfish does possess the orthologs of the known osmoregulatory genes and that the transepithelial movement of inorganic ions in the hagfish gill and kidney is more complex than previously thought. These observations pose a challenge to the conventional view that the physiological features of hagfishes have been inherited from the last common ancestor of the extant vertebrates.

Diversity, abundance, and domain architecture of plant NLR proteins in Fabaceae

The resistance (R) gene family in plants is a vital component of the plant defense system, enabling host resistance against pathogens through interactions with pathogen effector proteins. These R genes often encode nucleotide-binding (NB-ARC or N) and leucine-rich-repeat (LRR or L) domains, collectively forming the NLR protein family. The NLR proteins have been widely explored in crops from Poaceae and Brassicaceae, but limited studies are available for crops in other families, including Fabaceae. To address this gap, we conducted a comprehensive genome-wide analysis of putative NLR proteins in nine Fabaceae crops, including Glycine max, Lupinus angustifolius, Medicago truncatula, Pisum sativum, Phaseolus vulgaris, Trifolium pratense, Vigna angularis, Vigna radiata, and Vigna unguiculata. Our study revealed a substantial variation in the number of NLR proteins, independent of genome size. Notably, the NB-ARC domain exhibited a preferential co-occurrence with a specific LRR domain (IPR001611) in Fabaceae. Furthermore, through protein signature analysis, we identified both species-specific and shared domains across the nine crops. By classifying the identified proteins into seven distinct classes (N, L, CN, TN, NL, CNL, and TNL), we observed species-specific clustering within the CN, TN, and CNL classes, reflecting the diversification of species within Fabaceae. This genome-wide study enhances our understanding of the NLR protein repertoire and comprehensive protein signatures in nine Fabaceae species and provides valuable insights into plant defense mechanisms.

A network-based trans-omics approach for predicting synergistic drug combinations

BACKGROUND

Combination therapy can offer greater efficacy on medical treatments. However, the discovery of synergistic drug combinations is challenging. We propose a novel computational method, SyndrumNET, to predict synergistic drug combinations by network propagation with trans-omics analyses.

METHODS

The prediction is based on the topological relationship, network-based proximity, and transcriptional correlation between diseases and drugs. SyndrumNET was applied to analyzing six diseases including asthma, diabetes, hypertension, colorectal cancer, acute myeloid leukemia (AML), and chronic myeloid leukemia (CML).

RESULTS

Here we show that SyndrumNET outperforms the previous methods in terms of high accuracy. We perform in vitro cell survival assays to validate our prediction for CML. Of the top 17 predicted drug pairs, 14 drug pairs successfully exhibits synergistic anticancer effects. Our mode-of-action analysis also reveals that the drug synergy of the top predicted combination of capsaicin and mitoxantrone is due to the complementary regulation of 12 pathways, including the Rap1 signaling pathway.

CONCLUSIONS

The proposed method is expected to be useful for discovering synergistic drug combinations for various complex diseases.

Transient peripheral blood transcriptomic response to ketamine treatment in children with ADNP syndrome

Activity-dependent neuroprotective protein (ADNP) syndrome is a rare neurodevelopmental disorder resulting in intellectual disability, developmental delay and autism spectrum disorder (ASD) and is due to mutations in the ADNP gene. Ketamine treatment has emerged as a promising therapeutic option for ADNP syndrome, showing safety and apparent behavioral improvements in a first open label study. However, the molecular perturbations induced by ketamine remain poorly understood. Here, we investigated the longitudinal effect of ketamine on the blood transcriptome of 10 individuals with ADNP syndrome. Transcriptomic profiling was performed before and at multiple time points after a single low-dose intravenous ketamine infusion (0.5 mg/kg). We show that ketamine triggers immediate and profound gene expression alterations, with specific enrichment of monocyte-related expression patterns. These acute alterations encompass diverse signaling pathways and co-expression networks, implicating upregulation of immune and inflammatory-related processes and down-regulation of RNA processing mechanisms and metabolism. Notably, these changes exhibit a transient nature, returning to baseline levels 24 hours to 1 week after treatment. These findings enhance our understanding of ketamine's molecular effects and lay the groundwork for further research elucidating its specific cellular and molecular targets. Moreover, they contribute to the development of therapeutic strategies for ADNP syndrome and potentially, ASD more broadly.

Repression of pervasive antisense transcription is the primary role of fission yeast RNA polymerase II CTD serine 2 phosphorylation

The RNA polymerase II carboxy-terminal domain (CTD) consists of conserved heptapeptide repeats that can be phosphorylated to influence distinct stages of the transcription cycle, including RNA processing. Although CTD-associated proteins have been identified, phospho-dependent CTD interactions have remained elusive. Proximity-dependent biotinylation (PDB) has recently emerged as an alternative approach to identify protein-protein associations in the native cellular environment. In this study, we present a PDB-based map of the fission yeast RNAPII CTD interactome in living cells and identify phospho-dependent CTD interactions by using a mutant in which Ser2 was replaced by alanine in every repeat of the fission yeast CTD. This approach revealed that CTD Ser2 phosphorylation is critical for the association between RNAPII and the histone methyltransferase Set2 during transcription elongation, but is not required for 3' end processing and transcription termination. Accordingly, loss of CTD Ser2 phosphorylation causes a global increase in antisense transcription, correlating with elevated histone acetylation in gene bodies. Our findings reveal that the fundamental role of CTD Ser2 phosphorylation is to establish a chromatin-based repressive state that prevents cryptic intragenic transcription initiation.

Targeted co-expression networks for the study of traits

Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used approach for the generation of gene co-expression networks. However, networks generated with this tool usually create large modules with a large set of functional annotations hard to decipher. We have developed TGCN, a new method to create Targeted Gene Co-expression Networks. This method identifies the transcripts that best predict the trait of interest based on gene expression using a refinement of the LASSO regression. Then, it builds the co-expression modules around those transcripts. Algorithm properties were characterized using the expression of 13 brain regions from the Genotype-Tissue Expression project. When comparing our method with WGCNA, TGCN networks lead to more precise modules that have more specific and yet rich biological meaning. Then, we illustrate its applicability by creating an APP-TGCN on The Religious Orders Study and Memory and Aging Project dataset, aiming to identify the molecular pathways specifically associated with APP role in Alzheimer's disease. Main biological findings were further validated in two independent cohorts. In conclusion, we provide a new framework that serves to create targeted networks that are smaller, biologically relevant and useful in high throughput hypothesis driven research. The TGCN R package is available on Github: https://github.com/aliciagp/TGCN .

A specialized population of monocyte-derived tracheal macrophages promote airway epithelial regeneration through a CCR2-dependent mechanism

Macrophages are critical for maintenance and repair of mucosal tissues. While functionally distinct subtypes of macrophage are known to have important roles in injury response and repair in the lungs, little is known about macrophages in the proximal conducting airways. Single-cell RNA sequencing and flow cytometry demonstrated murine tracheal macrophages are largely monocyte-derived and are phenotypically distinct from lung macrophages at homeostasis. Following sterile airway injury, monocyte-derived macrophages are recruited to the trachea and activate a pro-regenerative phenotype associated with wound healing. Animals lacking the chemokine receptor CCR2 have reduced numbers of circulating monocytes and tracheal macrophages, deficient pro-regenerative macrophage activation and defective epithelial repair. Together, these studies indicate that recruitment and activation of monocyte-derived tracheal macrophages is CCR2-dependent and is required for normal airway epithelial regeneration.

Expanded detection and impact of BAP1 alterations in cancer

Aberrant expression of the BAP1 tumor suppressor gene is a prominent risk factor for several tumor types and is important in tumor evolution and progression. Here we performed integrated multi-omic analyses using data from The Cancer Genome Atlas (TCGA) for 33 cancer types and over 10,000 individuals to identify alterations leading to BAP1 disruption. We combined existing variant calls and new calls derived from a de novo local realignment pipeline across multiple independent variant callers, increasing somatic variant detection by 41% from 182 to 257, including 11 indels ≥40bp. The expanded detection of mutations highlights the power of new tools to uncover longer indels and impactful mutations. We developed an expression-based BAP1 activity score and identified a transcriptional profile associated with BAP1 disruption in cancer. BAP1 has been proposed to play a critical role in controlling tumor plasticity and normal cell fate. Leveraging human and mouse liver datasets, BAP1 loss in normal cells resulted in lower BAP1 activity scores and lower scores were associated with a less-differentiated phenotype in embryonic cells. Together, our expanded BAP1 mutant samples revealed a transcriptional signature in cancer cells, supporting BAP1's influences on cellular plasticity and cell identity maintenance.

A multiomic atlas of the aging hippocampus reveals molecular changes in response to environmental enrichment

Aging involves the deterioration of organismal function, leading to the emergence of multiple pathologies. Environmental stimuli, including lifestyle, can influence the trajectory of this process and may be used as tools in the pursuit of healthy aging. To evaluate the role of epigenetic mechanisms in this context, we have generated bulk tissue and single cell multi-omic maps of the male mouse dorsal hippocampus in young and old animals exposed to environmental stimulation in the form of enriched environments. We present a molecular atlas of the aging process, highlighting two distinct axes, related to inflammation and to the dysregulation of mRNA metabolism, at the functional RNA and protein level. Additionally, we report the alteration of heterochromatin domains, including the loss of bivalent chromatin and the uncovering of a heterochromatin-switch phenomenon whereby constitutive heterochromatin loss is partially mitigated through gains in facultative heterochromatin. Notably, we observed the multi-omic reversal of a great number of aging-associated alterations in the context of environmental enrichment, which was particularly linked to glial and oligodendrocyte pathways. In conclusion, our work describes the epigenomic landscape of environmental stimulation in the context of aging and reveals how lifestyle intervention can lead to the multi-layered reversal of aging-associated decline.

Tumor Necrosis Factor-Alpha Modulates Expression of Genes Involved in Cytokines and Chemokine Pathways in Proliferative Myoblast Cells

Skeletal muscle regeneration after injury is a complex process involving inflammatory signaling and myoblast activation. Pro-inflammatory cytokines like tumor necrosis factor-alpha (TNF-α) are key mediators, but their effects on gene expression in proliferating myoblasts are unclear. We performed the RNA sequencing of TNF-α treated C2C12 myoblasts to elucidate the signaling pathways and gene networks regulated by TNF-α during myoblast proliferation. The TNF-α (10 ng/mL) treatment of C2C12 cells led to 958 differentially expressed genes compared to the controls. Pathway analysis revealed significant regulation of TNF-α signaling, along with the chemokine and IL-17 pathways. Key upregulated genes included cytokines (e.g., IL-6), chemokines (e.g., CCL7), and matrix metalloproteinases (MMPs). TNF-α increased myogenic factor 5 (Myf5) but decreased MyoD protein levels and stimulated the release of MMP-9, MMP-10, and MMP-13. TNF-α also upregulates versican and myostatin mRNA. Overall, our study demonstrates the TNF-α modulation of distinct gene expression patterns and signaling pathways that likely contribute to enhanced myoblast proliferation while suppressing premature differentiation after muscle injury. Elucidating the mechanisms involved in skeletal muscle regeneration can aid in the development of regeneration-enhancing therapeutics.

Transcriptomic Analysis Reveals Early Alterations Associated with Intrinsic Resistance to Targeted Therapy in Lung Adenocarcinoma Cell Lines

Lung adenocarcinoma is the most prevalent form of lung cancer, and drug resistance poses a significant obstacle in its treatment. This study aimed to investigate the overexpression of long non-coding RNAs (lncRNAs) as a mechanism that promotes intrinsic resistance in tumor cells from the onset of treatment. Drug-tolerant persister (DTP) cells are a subset of cancer cells that survive and proliferate after exposure to therapeutic drugs, making them an essential object of study in cancer treatment. The molecular mechanisms underlying DTP cell survival are not fully understood; however, long non-coding RNAs (lncRNAs) have been proposed to play a crucial role. DTP cells from lung adenocarcinoma cell lines were obtained after single exposure to tyrosine kinase inhibitors (TKIs; erlotinib or osimertinib). After establishing DTP cells, RNA sequencing was performed to investigate the differential expression of the lncRNAs. Some lncRNAs and one mRNA were overexpressed in DTP cells. The clinical relevance of lncRNAs was evaluated in a cohort of patients with lung adenocarcinoma from The Cancer Genome Atlas (TCGA). RT-qPCR validated the overexpression of lncRNAs and mRNA in the residual DTP cells and LUAD biopsies. Knockdown of these lncRNAs increases the sensitivity of DTP cells to therapeutic drugs. This study provides an opportunity to investigate the involvement of lncRNAs in the genetic and epigenetic mechanisms that underlie intrinsic resistance. The identified lncRNAs and CD74 mRNA may serve as potential prognostic markers or therapeutic targets to improve the overall survival (OS) of patients with lung cancer.

DNA methylation profile of inflammatory breast cancer and its impact on prognosis and outcome

BACKGROUND

Inflammatory breast cancer (IBC) is a rare disease characterized by rapid progression, early metastasis, and a high mortality rate.

METHODS

Genome-wide DNA methylation analysis (EPIC BeadChip platform, Illumina) and somatic gene variants (105 cancer-related genes) were performed in 24 IBCs selected from a cohort of 140 cases.

RESULTS

We identified 46,908 DMPs (differentially methylated positions) (66% hypomethylated); CpG islands were predominantly hypermethylated (39.9%). Unsupervised clustering analysis revealed three clusters of DMPs characterized by an enrichment of specific gene mutations and hormone receptor status. The comparison among DNA methylation findings and external datasets (TCGA-BRCA stages III-IV) resulted in 385 shared DMPs mapped in 333 genes (264 hypermethylated). 151 DMPs were associated with 110 genes previously detected as differentially expressed in IBC (GSE45581), and 68 DMPs were negatively correlated with gene expression. We also identified 4369 DMRs (differentially methylated regions) mapped on known genes (2392 hypomethylated). BCAT1, CXCL12, and TBX15 loci were selected and evaluated by bisulfite pyrosequencing in 31 IBC samples. BCAT1 and TBX15 had higher methylation levels in triple-negative compared to non-triple-negative, while CXCL12 had lower methylation levels in triple-negative than non-triple-negative IBC cases. TBX15 methylation level was associated with obesity.

CONCLUSIONS

Our findings revealed a heterogeneous DNA methylation profile with potentially functional DMPs and DMRs. The DNA methylation data provided valuable insights for prognostic stratification and therapy selection to improve patient outcomes.

Genetic and genomic analysis of Belgian Blue's susceptibility for psoroptic mange

BACKGROUND

Psoroptic mange, caused by Psoroptes ovis mites, is affecting Belgian Blue cattle's welfare and production potential. The Belgian Blue cattle-known for its high degree of muscling, low feed conversion ratio and high beef quality-is highly susceptible for this disease.

RESULTS

In this study, we phenotyped 1975 Belgian Blue cattle from more than 100 different groups on commercial beef farms for their psoroptic mange susceptibility. Substantial individual differences were observed within these management groups, with lesion extent differences up to ± 15%. Animal models showed that estimated heritabilities were low for lesion extent and severe lesion extent (0.07 and 0.09, respectively) and 0.12 for the number of mites. A genome wide association study for mange susceptibility revealed signals on BTA6, BTA11, BTA15 and BTA24. In these regions, candidate genes GBA3, RAG2, and TRAF6 were identified.

CONCLUSIONS

Despite the challenges in phenotyping for psoroptic mange due to the timing of screening, the continuous evolution of lesions and different management conditions, we successfully conducted a study on the genetic susceptibility to psoroptic mange in Belgian Blue cattle. Our results clearly indicate that psoroptic mange is under polygenic control and the underlying candidate genes should be studied more thoroughly. This is the first study providing candidate genes for this complex disease. These results are already valuable for Belgian Blue breeding, however, further research is needed to unravel the architecture of this disease and to identify causal mutations.

A complex receptor locus confers responsiveness to necrosis and ethylene-inducing like peptides in Brassica napus

Brassica crops are susceptible to diseases which can be mitigated by breeding for resistance. MAMPs (microbe-associated molecular patterns) are conserved molecules of pathogens that elicit host defences known as pattern-triggered immunity (PTI). Necrosis and Ethylene-inducing peptide 1-like proteins (NLPs) are MAMPs found in a wide range of phytopathogens. We studied the response to BcNEP2, a representative NLP from Botrytis cinerea, and showed that it contributes to disease resistance in Brassica napus. To map regions conferring NLP response, we used the production of reactive oxygen species (ROS) induced during PTI across a population of diverse B. napus accessions for associative transcriptomics (AT), and bulk segregant analysis (BSA) on DNA pools created from a cross of NLP-responsive and non-responsive lines. In silico mapping with AT identified two peaks for NLP responsiveness on chromosomes A04 and C05 whereas the BSA identified one peak on A04. BSA delimited the region for NLP-responsiveness to 3 Mbp, containing ~245 genes on the Darmor-bzh reference genome and four co-segregating KASP markers were identified. The same pipeline with the ZS11 genome confirmed the highest-associated region on chromosome A04. Comparative BLAST analysis revealed unannotated clusters of receptor-like protein (RLP) homologues on ZS11 chromosome A04. However, no specific RLP homologue conferring NLP response could be identified. Our results also suggest that BR-SIGNALLING KINASE1 may be involved with modulating the NLP response. Overall, we demonstrate that responsiveness to NLP contributes to disease resistance in B. napus and define the associated genomic location. These results can have practical application in crop improvement.

Microglial function interacts with the environment to affect sex-specific depression risk

There is a two-fold higher incidence of depression in females compared to men with recent studies suggesting a role for microglia in conferring this sex-dependent depression risk. In this study we investigated the nature of this relation. Using GWAS enrichment, gene-set enrichment analysis and Mendelian randomization, we found minimal evidence for a direct relation between genes functionally related to microglia and sex-dependent genetic risk for depression. We then used expression quantitative trait loci and single nucleus RNA-sequencing resources to generate polygenic scores (PGS) representative of individual variation in microglial function in the adult (UK Biobank; N = 54753-72682) and fetal (ALSPAC; N = 1452) periods. The adult microglial PGS moderated the association between BMI (UK Biobank; beta = 0.001, 95 %CI 0.0009 to 0.003, P = 7.74E-6) and financial insecurity (UK Biobank; beta = 0.001, 95 %CI 0.005 to 0.015, P = 2E-4) with depressive symptoms in females. The fetal microglia PGS moderated the association between maternal prenatal depressive symptoms and offspring depressive symptoms at 24 years in females (ALSPAC; beta = 0.04, 95 %CI 0.004 to 0.07, P = 0.03). We found no evidence for an interaction between the microglial PGS and depression risk factors in males. Our results illustrate a role for microglial function in the conferral of sex-dependent depression risk following exposure to a depression risk factor.

Developmental programming: Testosterone excess masculinizes female pancreatic transcriptome and function in sheep

Hyperandrogenic disorders, such as polycystic ovary syndrome, are often associated with metabolic disruptions such as insulin resistance and hyperinsulinemia. Studies in sheep, a precocial model of translational relevance, provide evidence that in utero exposure to excess testosterone during days 30-90 of gestation (the sexually dimorphic window where males naturally experience elevated androgens) programs insulin resistance and hyperinsulinemia in female offspring. Extending earlier findings that adverse effects of testosterone excess are evident in fetal day 90 pancreas, the end of testosterone treatment, the present study provides evidence that transcriptomic and phenotypic effects of in utero testosterone excess on female pancreas persist after cessation of treatment, suggesting lasting organizational changes, and induce a male-like phenotype in female pancreas. These findings demonstrate that the female pancreas is susceptible to programmed masculinization during the sexually dimorphic window of fetal development and shed light on underlying connections between hyperandrogenism and metabolic homeostasis.

Integration mapping of cardiac fibroblast single-cell transcriptomes elucidates cellular principles of fibrosis in diverse pathologies

Single-cell technology has allowed researchers to probe tissue complexity and dynamics at unprecedented depth in health and disease. However, the generation of high-dimensionality single-cell atlases and virtual three-dimensional tissues requires integrated reference maps that harmonize disparate experimental designs, analytical pipelines, and taxonomies. Here, we present a comprehensive single-cell transcriptome integration map of cardiac fibrosis, which underpins pathophysiology in most cardiovascular diseases. Our findings reveal similarity between cardiac fibroblast (CF) identities and dynamics in ischemic versus pressure overload models of cardiomyopathy. We also describe timelines for commitment of activated CFs to proliferation and myofibrogenesis, profibrotic and antifibrotic polarization of myofibroblasts and matrifibrocytes, and CF conservation across mouse and human healthy and diseased hearts. These insights have the potential to inform knowledge-based therapies.

Protocol to perform integrative analysis of high-dimensional single-cell multimodal data using an interpretable deep learning technique

The advent of single-cell multi-omics sequencing technology makes it possible for researchers to leverage multiple modalities for individual cells. Here, we present a protocol to perform integrative analysis of high-dimensional single-cell multimodal data using an interpretable deep learning technique called moETM. We describe steps for data preprocessing, multi-omics integration, inclusion of prior pathway knowledge, and cross-omics imputation. As a demonstration, we used the single-cell multi-omics data collected from bone marrow mononuclear cells (GSE194122) as in our original study. For complete details on the use and execution of this protocol, please refer to Zhou et al.1.

Early detection and diagnosis of cancer with interpretable machine learning to uncover cancer-specific DNA methylation patterns

Cancer, a collection of more than two hundred different diseases, remains a leading cause of morbidity and mortality worldwide. Usually detected at the advanced stages of disease, metastatic cancer accounts for 90% of cancer-associated deaths. Therefore, the early detection of cancer, combined with current therapies, would have a significant impact on survival and treatment of various cancer types. Epigenetic changes such as DNA methylation are some of the early events underlying carcinogenesis. Here, we report on an interpretable machine learning model that can classify 13 cancer types as well as non-cancer tissue samples using only DNA methylome data, with 98.2% accuracy. We utilize the features identified by this model to develop EMethylNET, a robust model consisting of an XGBoost model that provides information to a deep neural network that can generalize to independent data sets. We also demonstrate that the methylation-associated genomic loci detected by the classifier are associated with genes, pathways and networks involved in cancer, providing insights into the epigenomic regulation of carcinogenesis.

Capturing totipotency in human cells through spliceosomal repression

The cleavage of zygotes generates totipotent blastomeres. In human 8-cell blastomeres, zygotic genome activation (ZGA) occurs to initiate the ontogenesis program. However, capturing and maintaining totipotency in human cells pose significant challenges. Here, we realize culturing human totipotent blastomere-like cells (hTBLCs). We find that splicing inhibition can transiently reprogram human pluripotent stem cells into ZGA-like cells (ZLCs), which subsequently transition into stable hTBLCs after long-term passaging. Distinct from reported 8-cell-like cells (8CLCs), both ZLCs and hTBLCs widely silence pluripotent genes. Interestingly, ZLCs activate a particular group of ZGA-specific genes, and hTBLCs are enriched with pre-ZGA-specific genes. During spontaneous differentiation, hTBLCs re-enter the intermediate ZLC stage and further generate epiblast (EPI)-, primitive endoderm (PrE)-, and trophectoderm (TE)-like lineages, effectively recapitulating human pre-implantation development. Possessing both embryonic and extraembryonic developmental potency, hTBLCs can autonomously generate blastocyst-like structures in vitro without external cell signaling. In summary, our study provides key criteria and insights into human cell totipotency.

Comparative Analysis of Human-Chimpanzee Divergence in Brain Connectivity and its Genetic Correlates

Chimpanzees (Pan troglodytes) are humans' closest living relatives, making them the most directly relevant comparison point for understanding human brain evolution. Zeroing in on the differences in brain connectivity between humans and chimpanzees can provide key insights into the specific evolutionary changes that might have occured along the human lineage. However, conducting comparisons of brain connectivity between humans and chimpanzees remains challenging, as cross-species brain atlases established within the same framework are currently lacking. Without the availability of cross-species brain atlases, the region-wise connectivity patterns between humans and chimpanzees cannot be directly compared. To address this gap, we built the first Chimpanzee Brainnetome Atlas (ChimpBNA) by following a well-established connectivity-based parcellation framework. Leveraging this new resource, we found substantial divergence in connectivity patterns across most association cortices, notably in the lateral temporal and dorsolateral prefrontal cortex between the two species. Intriguingly, these patterns significantly deviate from the patterns of cortical expansion observed in humans compared to chimpanzees. Additionally, we identified regions displaying connectional asymmetries that differed between species, likely resulting from evolutionary divergence. Genes associated with these divergent connectivities were found to be enriched in cell types crucial for cortical projection circuits and synapse formation. These genes exhibited more pronounced differences in expression patterns in regions with higher connectivity divergence, suggesting a potential foundation for brain connectivity evolution. Therefore, our study not only provides a fine-scale brain atlas of chimpanzees but also highlights the connectivity divergence between humans and chimpanzees in a more rigorous and comparative manner and suggests potential genetic correlates for the observed divergence in brain connectivity patterns between the two species. This can help us better understand the origins and development of uniquely human cognitive capabilities.

Progressive senescence programs induce intrinsic vulnerability to aging-related female breast cancer

Cancer incidence escalates exponentially with advancing age; however, the underlying mechanism remains unclear. In this study, we build a chronological molecular clock at single-cell transcription level with a mammary stem cell-enriched population to depict physiological aging dynamics in female mice. We find that the mammary aging process is asynchronous and progressive, initiated by an early senescence program, succeeded by an entropic late senescence program with elevated cancer associated pathways, vulnerable to cancer predisposition. The transition towards senescence program is governed by a stem cell factor Bcl11b, loss of which accelerates mammary ageing with enhanced DMBA-induced tumor formation. We have identified a drug TPCA-1 that can rejuvenate mammary cells and significantly reduce aging-related cancer incidence. Our findings establish a molecular portrait of progressive mammary cell aging and elucidate the transcriptional regulatory network bridging mammary aging and cancer predisposition, which has potential implications for the management of cancer prevalence in the aged.

A secreted proteomic footprint for stem cell pluripotency

With a view to developing a much-needed non-invasive method for monitoring the healthy pluripotent state of human stem cells in culture, we undertook proteomic analysis of the waste medium from cultured embryonic (Man-13) and induced (Rebl.PAT) human pluripotent stem cells (hPSCs). Cells were grown in E8 medium to maintain pluripotency, and then transferred to FGF2 and TGFβ deficient E6 media for 48 hours to replicate an early, undirected dissolution of pluripotency. We identified a distinct proteomic footprint associated with early loss of pluripotency in both hPSC lines, and a strong correlation with changes in the transcriptome. We demonstrate that multiplexing of four E8- against four E6- enriched secretome biomarkers provides a robust, diagnostic metric for the pluripotent state. These biomarkers were further confirmed by Western blotting which demonstrated consistent correlation with the pluripotent state across cell lines, and in response to a recovery assay.

Aging and putative frailty biomarkers are altered by spaceflight

Human space exploration poses inherent risks to astronauts' health, leading to molecular changes that can significantly impact their well-being. These alterations encompass genomic instability, mitochondrial dysfunction, increased inflammation, homeostatic dysregulation, and various epigenomic changes. Remarkably, these changes bear similarities to those observed during the aging process on Earth. However, our understanding of the connection between these molecular shifts and disease development in space remains limited. Frailty syndrome, a clinical syndrome associated with biological aging, has not been comprehensively investigated during spaceflight. To bridge this knowledge gap, we leveraged murine data obtained from NASA's GeneLab, along with astronaut data gathered from the JAXA and Inspiration4 missions. Our objective was to assess the presence of biological markers and pathways related to frailty, aging, and sarcopenia within the spaceflight context. Through our analysis, we identified notable changes in gene expression patterns that may be indicative of the development of a frailty-like condition during space missions. These findings suggest that the parallels between spaceflight and the aging process may extend to encompass frailty as well. Consequently, further investigations exploring the utility of a frailty index in monitoring astronaut health appear to be warranted.

Expression of the membrane tetraspanin claudin 18 on cancer cells promotes T lymphocyte infiltration and antitumor immunity in pancreatic cancer

Tumors weakly infiltrated by T lymphocytes poorly respond to immunotherapy. We aimed to unveil malignancy-associated programs regulating T cell entrance, arrest, and activation in the tumor environment. Differential expression of cell adhesion and tissue architecture programs, particularly the presence of the membrane tetraspanin claudin (CLDN)18 as a signature gene, demarcated immune-infiltrated from immune-depleted mouse pancreatic tumors. In human pancreatic ductal adenocarcinoma (PDAC) and non-small cell lung cancer, CLDN18 expression positively correlated with more differentiated histology and favorable prognosis. CLDN18 on the cell surface promoted accrual of cytotoxic T lymphocytes (CTLs), facilitating direct CTL contacts with tumor cells by driving the mobilization of the adhesion protein ALCAM to the lipid rafts of the tumor cell membrane through actin. This process favored the formation of robust immunological synapses (ISs) between CTLs and CLDN18-positive cancer cells, resulting in increased T cell activation. Our data reveal an immune role for CLDN18 in orchestrating T cell infiltration and shaping the tumor immune contexture.

Innate acting memory Th1 cells modulate heterologous diseases

Through immune memory, infections have a lasting effect on the host. While memory cells enable accelerated and enhanced responses upon rechallenge with the same pathogen, their impact on susceptibility to unrelated diseases is unclear. We identify a subset of memory T helper 1 (Th1) cells termed innate acting memory T (TIA) cells that originate from a viral infection and produce IFN-γ with innate kinetics upon heterologous challenge in vivo. Activation of memory TIA cells is induced in response to IL-12 in combination with IL-18 or IL-33 but is TCR independent. Rapid IFN-γ production by memory TIA cells is protective in subsequent heterologous challenge with the bacterial pathogen Legionella pneumophila. In contrast, antigen-independent reactivation of CD4+ memory TIA cells accelerates disease onset in an autoimmune model of multiple sclerosis. Our findings demonstrate that memory Th1 cells can acquire additional TCR-independent functionality to mount rapid, innate-like responses that modulate susceptibility to heterologous challenges.

Spaceflight induces changes in gene expression profiles linked to insulin and estrogen

Organismal adaptations to spaceflight have been characterized at the molecular level in model organisms, including Drosophila and C. elegans. Here, we extend molecular work to energy metabolism and sex hormone signaling in mice and humans. We found spaceflight induced changes in insulin and estrogen signaling in rodents and humans. Murine changes were most prominent in the liver, where we observed inhibition of insulin and estrogen receptor signaling with concomitant hepatic insulin resistance and steatosis. Based on the metabolic demand, metabolic pathways mediated by insulin and estrogen vary among muscles, specifically between the soleus and extensor digitorum longus. In humans, spaceflight induced changes in insulin and estrogen related genes and pathways. Pathway analysis demonstrated spaceflight induced changes in insulin resistance, estrogen signaling, stress response, and viral infection. These data strongly suggest the need for further research on the metabolic and reproductive endocrinologic effects of space travel, if we are to become a successful interplanetary species.

Partial hepatectomy accelerates colorectal metastasis by priming an inflammatory premetastatic niche in the liver

Background

Resection of colorectal liver metastasis is the standard of care for patients with Stage IV CRC. Despite undoubtedly improving the overall survival of patients, pHx for colorectal liver metastasis frequently leads to disease recurrence. The contribution of this procedure to metastatic colorectal cancer at a molecular level is poorly understood. We designed a mouse model of orthograde metastatic colorectal cancer (CRC) to investigate the effect of partial hepatectomy (pHx) on tumor progression.

Methods

CRC organoids were implanted into the cecal walls of wild type mice, and animals were screened for liver metastasis. At the time of metastasis, 1/3 partial hepatectomy was performed and the tumor burden was assessed longitudinally using MRI. After euthanasia, different tissues were analyzed for immunological and transcriptional changes using FACS, qPCR, RNA sequencing, and immunohistochemistry.

Results

Mice that underwent pHx presented significant liver hypertrophy and an increased overall metastatic load compared with SHAM operated mice in MRI. Elevation in the metastatic volume was defined by an increase in de novo liver metastasis without any effect on the growth of each metastasis. Concordantly, the livers of pHx mice were characterized by neutrophil and bacterial infiltration, inflammatory response, extracellular remodeling, and an increased abundance of tight junctions, resulting in the formation of a premetastatic niche, thus facilitating metastatic seeding.

Conclusions

Regenerative pathways following pHx accelerate colorectal metastasis to the liver by priming a premetastatic niche.

Defining the KRAS- and ERK-dependent transcriptome in KRAS-mutant cancers

How the KRAS oncogene drives cancer growth remains poorly understood. Therefore, we established a systemwide portrait of KRAS- and extracellular signal-regulated kinase (ERK)-dependent gene transcription in KRAS-mutant cancer to delineate the molecular mechanisms of growth and of inhibitor resistance. Unexpectedly, our KRAS-dependent gene signature diverges substantially from the frequently cited Hallmark KRAS signaling gene signature, is driven predominantly through the ERK mitogen-activated protein kinase (MAPK) cascade, and accurately reflects KRAS- and ERK-regulated gene transcription in KRAS-mutant cancer patients. Integration with our ERK-regulated phospho- and total proteome highlights ERK deregulation of the anaphase promoting complex/cyclosome (APC/C) and other components of the cell cycle machinery as key processes that drive pancreatic ductal adenocarcinoma (PDAC) growth. Our findings elucidate mechanistically the critical role of ERK in driving KRAS-mutant tumor growth and in resistance to KRAS-ERK MAPK targeted therapies.

Determining the ERK-regulated phosphoproteome driving KRAS-mutant cancer

To delineate the mechanisms by which the ERK1 and ERK2 mitogen-activated protein kinases support mutant KRAS-driven cancer growth, we determined the ERK-dependent phosphoproteome in KRAS-mutant pancreatic cancer. We determined that ERK1 and ERK2 share near-identical signaling and transforming outputs and that the KRAS-regulated phosphoproteome is driven nearly completely by ERK. We identified 4666 ERK-dependent phosphosites on 2123 proteins, of which 79 and 66%, respectively, were not previously associated with ERK, substantially expanding the depth and breadth of ERK-dependent phosphorylation events and revealing a considerably more complex function for ERK in cancer. We established that ERK controls a highly dynamic and complex phosphoproteome that converges on cyclin-dependent kinase regulation and RAS homolog guanosine triphosphatase function (RHO GTPase). Our findings establish the most comprehensive molecular portrait and mechanisms by which ERK drives KRAS-dependent pancreatic cancer growth.

Comprehensive single cell transcriptomics analysis of murine osteosarcoma uncovers Skp2 function in metastasis, genomic instability and immune activation and reveals additional target pathways

Osteosarcoma (OS) is the most common primary pediatric bone malignancy. One promising new therapeutic target is SKP2, encoding a substrate recognition factor of the SCF E3 ubiquitin ligase responsible for ubiquitination and proteasome degradation of substrate p27, thus driving cellular proliferation. We have shown previously that knockout of Skp2 in an immunocompetent transgenic mouse model of OS improved survival, drove apoptosis, and induced tumor inflammation. Here, we applied single-cell RNA-sequencing (scRNA-seq) to study primary OS tumors derived from Osx-Cre driven conditional knockout of Rb1 and Trp53. We showed that murine OS models recapitulate the tumor heterogeneity and microenvironment complexity observed in patient tumors. We further compared this model with OS models with functional disruption of Skp2: one with Skp2 knockout and the other with the Skp2-p27 interaction disrupted (resulting in p27 overexpression). We found reduction of T cell exhaustion and upregulation of interferon activation, along with evidence of replicative and endoplasmic reticulum-related stress in the Skp2 disruption models, and showed that interferon induction was correlated with improved survival in OS patients. Additionally, our scRNA-seq analysis uncovered decreased activities of metastasis-related gene signatures in the Skp2-disrupted OS, which we validated by observation of a strong reduction in lung metastasis in the Skp2 knockout mice. Finally, we report several potential mechanisms of escape from targeting Skp2 in OS, including upregulation of Myc targets, DNA copy number amplification and overexpression of alternative E3 ligase genes, and potential alternative lineage activation. These mechanistic insights into OS tumor biology and Skp2 function suggest novel targets for new, synergistic therapies, while the data and our comprehensive analysis may serve as a public resource for further big data-driven OS research.