Mimicking and analyzing the tumor microenvironment.

The tumor microenvironment (TME) is increasingly appreciated to play a decisive role in cancer development and response to therapy in all solid tumors. Hypoxia, acidosis, high interstitial pressure, nutrient-poor conditions, and high cellular heterogeneity of the TME arise from interactions between cancer cells and their environment. These properties, in turn, play key roles in the aggressiveness and therapy resistance of the disease, through complex reciprocal interactions between the cancer cell genotype and phenotype, and the physicochemical and cellular environment. Understanding this complexity requires the combination of sophisticated cancer models and high-resolution analysis tools. Models must allow both control and analysis of cellular and acellular TME properties, and analyses must be able to capture the complexity at high depth and spatial resolution. Here, we review the advantages and limitations of key models and methods in order to guide further TME research and outline future challenges.

Age-Related Decline in Pancreas Regeneration Is Associated With an Increased Proinflammatory Response to Injury.

Background and Aims: The regenerative capacity of the pancreas diminishes with age. Understanding acinar cell responses to injury and the resolution of regenerative processes is crucial for tissue homeostasis. However, knowledge about the impact of aging on these processes remains limited. Methods: To investigate the influence of aging on pancreas regeneration, we established a cohort of young (7-14 weeks) and old (18 months) C57bl/6 mice. Experimental pancreatitis was induced using caerulein, and pancreas samples were collected at various time points after induction, covering acute damage response, inflammation, peak proliferation, and inflammation resolution. Our analysis involved immunohistochemistry, quantitative imaging, and gene expression analyses. Results: Our study revealed a significant decline in the regenerative capacity of the pancreas in old mice. Despite similar morphology and transcriptional profiles between the pancreas of young and old mice under homeostasis, the aged pancreas is primed to generate an exacerbated proinflammatory reaction in response to injury. Specifically, we observed notable upregulation of Junb expression in acinar cells and aberrant myofibroblast activation in the aged pancreas. Conclusion: The response of acinar cells to injury in the pancreas of aged mice is characterized by an increased susceptibility to inflammation and stromal reactions. Our findings uncover a pre-existing proinflammatory state in aged acinar cells, offering insights into potential strategies to prevent the onset of pancreatic insufficiency and the development of inflammatory conditions. These insights hold implications for preventing conditions such as chronic pancreatitis and pancreatic ductal adenocarcinoma.

Adaptation to an acid microenvironment promotes pancreatic cancer organoid growth and drug resistance.

Harsh environments in poorly perfused tumor regions may select for traits driving cancer aggressiveness. Here, we investigated whether tumor acidosis interacts with driver mutations to exacerbate cancer hallmarks. We adapted mouse organoids from normal pancreatic duct (mN10) and early pancreatic cancer (mP4, KRAS-G12D mutation, ± p53 knockout) from extracellular pH 7.4 to 6.7, representing acidic niches. Viability was increased by acid adaptation, a pattern most apparent in wild-type (WT) p53 organoids, and exacerbated upon return to pH 7.4. This led to increased survival of acid-adapted organoids treated with gemcitabine and/or erlotinib, and, in WT p53 organoids, acid-induced attenuation of drug effects. New genetic variants became dominant during adaptation, yet they were unlikely to be its main drivers. Transcriptional changes induced by acid and drug adaptation differed overall, but acid adaptation increased the expression of gemcitabine resistance genes. Thus, adaptation to acidosis increases cancer cell viability after chemotherapy.

A data-driven genome annotation approach for cassava.

Genome annotation files play a critical role in dictating the quality of downstream analyses by providing essential predictions for gene positions and structures. These files are pivotal in decoding the complex information encoded within DNA sequences. Here, we generated experimental data resolving RNA 5'- and 3'-ends as well as full-length RNAs for cassava TME12 sticklings in ambient temperature and cold. We used these data to generate genome annotation files using the TranscriptomeReconstructoR (TR) tool. A careful comparison to high-quality genome annotations suggests that our new TR genome annotations identified additional genes, resolved the transcript boundaries more accurately and identified additional RNA isoforms. We enhanced existing cassava genome annotation files with the information from TR that maintained the different transcript models as RNA isoforms. The resultant merged annotation was subsequently utilized for comprehensive analysis. To examine the effects of genome annotation files on gene expression studies, we compared the detection of differentially expressed genes during cold using the same RNA-seq data but alternative genome annotation files. We found that our merged genome annotation that included cold-specific TR gene models identified about twice as many cold-induced genes. These data indicate that environmentally induced genes may be missing in off-the-shelf genome annotation files. In conclusion, TR offers the opportunity to enhance crop genome annotations with implications for the discovery of differentially expressed candidate genes during plant-environment interactions.

Pulmonary maternal immune activation does not cross the placenta but leads to fetal metabolic adaptation.

The fetal development of organs and functions is vulnerable to perturbation by maternal inflammation which may increase susceptibility to disorders after birth. Because it is not well understood how the placenta and fetus respond to acute lung- inflammation, we characterize the response to maternal pulmonary lipopolysaccharide exposure across 24 h in maternal and fetal organs using multi-omics, imaging and integrative analyses. Unlike maternal organs, which mount strong inflammatory immune responses, the placenta upregulates immuno-modulatory genes, in particular the IL-6 signaling suppressor Socs3. Similarly, we observe no immune response in the fetal liver, which instead displays metabolic changes, including increases in lipids containing docosahexaenoic acid, crucial for fetal brain development. The maternal liver and plasma display similar metabolic alterations, potentially increasing bioavailability of docosahexaenoic acid for the mother and fetus. Thus, our integrated temporal analysis shows that systemic inflammation in the mother leads to a metabolic perturbation in the fetus.

Spatially resolved analysis of microenvironmental gradient impact on cancer cell phenotypes.

Despite the physiological and pathophysiological significance of microenvironmental gradients, e.g., for diseases such as cancer, tools for generating such gradients and analyzing their impact are lacking. Here, we present an integrated microfluidic-based workflow that mimics extracellular pH gradients characteristic of solid tumors while enabling high-resolution live imaging of, e.g., cell motility and chemotaxis, and preserving the capacity to capture the spatial transcriptome. Our microfluidic device generates a pH gradient that can be rapidly controlled to mimic spatiotemporal microenvironmental changes over cancer cells embedded in a 3D matrix. The device can be reopened allowing immunofluorescence analysis of selected phenotypes, as well as the transfer of cells and matrix to a Visium slide for spatially resolved analysis of transcriptional changes across the pH gradient. This workflow is easily adaptable to other gradients and multiple cell types and can therefore prove invaluable for integrated analysis of roles of microenvironmental gradients in biology.

JASPAR 2024: 20th anniversary of the open-access database of transcription factor binding profiles.

JASPAR (https://jaspar.elixir.no/) is a widely-used open-access database presenting manually curated high-quality and non-redundant DNA-binding profiles for transcription factors (TFs) across taxa. In this 10th release and 20th-anniversary update, the CORE collection has expanded with 329 new profiles. We updated three existing profiles and provided orthogonal support for 72 profiles from the previous release's UNVALIDATED collection. Altogether, the JASPAR 2024 update provides a 20% increase in CORE profiles from the previous release. A trimming algorithm enhanced profiles by removing low information content flanking base pairs, which were likely uninformative (within the capacity of the PFM models) for TFBS predictions and modelling TF-DNA interactions. This release includes enhanced metadata, featuring a refined classification for plant TFs' structural DNA-binding domains. The new JASPAR collections prompt updates to the genomic tracks of predicted TF binding sites (TFBSs) in 8 organisms, with human and mouse tracks available as native tracks in the UCSC Genome browser. All data are available through the JASPAR web interface and programmatically through its API and the updated Bioconductor and pyJASPAR packages. Finally, a new TFBS extraction tool enables users to retrieve predicted JASPAR TFBSs intersecting their genomic regions of interest.

Lactate receptor GPR81 drives breast cancer growth and invasiveness through regulation of ECM properties and Notch ligand DLL4.

BACKGROUND: The lactate receptor GPR81 contributes to cancer development through unclear mechanisms. Here, we investigate the roles of GPR81 in three-dimensional (3D) and in vivo growth of breast cancer cells and study the molecular mechanisms involved. METHODS: GPR81 was stably knocked down (KD) in MCF-7 human breast cancer cells which were subjected to RNA-seq analysis, 3D growth, in situ- and immunofluorescence analyses, and cell viability- and motility assays, combined with KD of key GPR81-regulated genes. Key findings were additionally studied in other breast cancer cell lines and in mammary epithelial cells. RESULTS: GPR81 was upregulated in multiple human cancer types and further upregulated by extracellular lactate and 3D growth in breast cancer spheroids. GPR81 KD increased spheroid necrosis, reduced invasion and in vivo tumor growth, and altered expression of genes related to GO/KEGG terms extracellular matrix, cell adhesion, and Notch signaling. Single cell in situ analysis of MCF-7 cells revealed that several GPR81-regulated genes were upregulated in the same cell clusters. Notch signaling, particularly the Notch ligand Delta-like-4 (DLL4), was strikingly downregulated upon GPR81 KD, and DLL4 KD elicited spheroid necrosis and inhibited invasion in a manner similar to GPR81 KD. CONCLUSIONS: GPR81 supports breast cancer aggressiveness, and in MCF-7 cells, this occurs at least in part via DLL4. Our findings reveal a new GPR81-driven mechanism in breast cancer and substantiate GPR81 as a promising treatment target.

Detecting host responses to microbial stimulation using primary epithelial organoids.

The intestinal epithelium is constantly exposed to microbes residing in the lumen. Traditionally, the response to microbial interactions has been studied in cell lines derived from cancerous tissues, e.g. Caco-2. It is, however, unclear how the responses in these cancer cell lines reflect the responses of a normal epithelium and whether there might be microbial strain-specific effects. To address these questions, we derived organoids from the small intestine from a cohort of healthy individuals. Culturing intestinal epithelium on a flat laminin matrix induced their differentiation, facilitating analysis of microbial responses via the apical membrane normally exposed to the luminal content. Here, it was evident that the healthy epithelium across multiple individuals (n = 9) demonstrates robust acute both common and strain-specific responses to a range of probiotic bacterial strains (BB-12Ⓡ, LGGⓇ, DSM33361, and Bif195). Importantly, parallel experiments using the Caco-2 cell line provide no acute response. Collectively, we demonstrate that primary epithelial cells maintained as organoids represent a valuable resource for assessing interactions between the epithelium and luminal microbes across individuals, and that these models are likely to contribute to a better understanding of host microbe interactions.

Transcriptional and epigenomic profiling identifies YAP signaling as a key regulator of intestinal epithelium maturation.

During intestinal organogenesis, equipotent epithelial progenitors mature into phenotypically distinct stem cells that are responsible for lifelong maintenance of the tissue. While the morphological changes associated with the transition are well characterized, the molecular mechanisms underpinning the maturation process are not fully understood. Here, we leverage intestinal organoid cultures to profile transcriptional, chromatin accessibility, DNA methylation, and three-dimensional (3D) chromatin conformation landscapes in fetal and adult epithelial cells. We observed prominent differences in gene expression and enhancer activity, which are accompanied by local changes in 3D organization, DNA accessibility, and methylation between the two cellular states. Using integrative analyses, we identified sustained Yes-Associated Protein (YAP) transcriptional activity as a major gatekeeper of the immature fetal state. We found the YAP-associated transcriptional network to be regulated at various levels of chromatin organization and likely to be coordinated by changes in extracellular matrix composition. Together, our work highlights the value of unbiased profiling of regulatory landscapes for the identification of key mechanisms underlying tissue maturation.

Crosstalk between tumor acidosis, p53 and extracellular matrix regulates pancreatic cancer aggressiveness.

Pancreatic ductal adenocarcinoma (PDAC) is an extremely aggressive malignancy with minimal treatment options and a global rise in prevalence. PDAC is characterized by frequent driver mutations including KRAS and TP53 (p53), and a dense, acidic tumor microenvironment (TME). The relation between genotype and TME in PDAC development is unknown. Strikingly, when wild type (WT) Panc02 PDAC cells were adapted to growth in an acidic TME and returned to normal pH to mimic invasive cells escaping acidic regions, they displayed a strong increase of aggressive traits such as increased growth in 3-dimensional (3D) culture, adhesion-independent colony formation and invasive outgrowth. This pattern of acidosis-induced aggressiveness was observed in 3D spheroid culture as well as upon organotypic growth in matrigel, collagen-I and combination thereof, mimicking early and later stages of PDAC development. Acid-adaptation-induced gain of cancerous traits was further increased by p53 knockout (KO), but only in specific extracellular matrix (ECM) compositions. Akt- and Transforming growth factor-ß (TGFß) signaling, as well as expression of the Na+ /H+ exchanger NHE1, were increased by acid adaptation. Whereas Akt inhibition decreased spheroid growth regardless of treatment and genotype, stimulation with TGFßI increased growth of WT control spheroids, and inhibition of TGFß signaling tended to limit growth under acidic conditions only. Our results indicate that a complex crosstalk between tumor acidosis, ECM composition and genotype contributes to PDAC development. The findings may guide future strategies for acidosis-targeted therapies.

Chronic acidosis rewires cancer cell metabolism through PPARα signaling.

The mechanisms linking tumor microenvironment acidosis to disease progression are not understood. Here, we used mammary, pancreatic, and colon cancer cells to show that adaptation to growth at an extracellular pH (pHe ) mimicking acidic tumor niches is associated with upregulated net acid extrusion capacity and elevated intracellular pH at physiological pHe , but not at acidic pHe . Using metabolic profiling, shotgun lipidomics, imaging and biochemical analyses, we show that the acid adaptation-induced phenotype is characterized by a shift toward oxidative metabolism, increased lipid droplet-, triacylglycerol-, peroxisome content and mitochondrial hyperfusion. Peroxisome proliferator-activated receptor-α (PPARA, PPARα) expression and activity are upregulated, at least in part by increased fatty acid uptake. PPARα upregulates genes driving increased mitochondrial and peroxisomal mass and ß-oxidation capacity, including mitochondrial lipid import proteins CPT1A, CPT2 and SLC25A20, electron transport chain components, peroxisomal proteins PEX11A and ACOX1, and thioredoxin-interacting protein (TXNIP), a negative regulator of glycolysis. This endows acid-adapted cancer cells with increased capacity for utilizing fatty acids for metabolic needs, while limiting glycolysis. As a consequence, the acid-adapted cells exhibit increased sensitivity to PPARα inhibition. We conclude that PPARα is a key upstream regulator of metabolic changes favoring cancer cell survival in acidic tumor niches.

Computational identification of signals predictive for nuclear RNA exosome degradation pathway targeting.

The RNA exosome degrades transcripts in the nucleoplasm of mammalian cells. Its substrate specificity is mediated by two adaptors: the 'nuclear exosome targeting (NEXT)' complex and the 'poly(A) exosome targeting (PAXT)' connection. Previous studies have revealed some DNA/RNA elements that differ between the two pathways, but how informative these features are for distinguishing pathway targeting, or whether additional genomic features that are informative for such classifications exist, is unknown. Here, we leverage the wealth of available genomic data and develop machine learning models that predict exosome targets and subsequently rank the features the models use by their predictive power. As expected, features around transcript end sites were most predictive; specifically, the lack of canonical 3' end processing was highly predictive of NEXT targets. Other associated features, such as promoter-proximal G/C content and 5' splice sites, were informative, but only for distinguishing NEXT and not PAXT targets. Finally, we discovered predictive features not previously associated with exosome targeting, in particular RNA helicase DDX3X binding sites. Overall, our results demonstrate that nucleoplasmic exosome targeting is to a large degree predictable, and our approach can assess the predictive power of previously known and new features in an unbiased way.

PAMP-triggered genetic reprogramming involves widespread alternative transcription initiation and an immediate transcription factor wave.

Immune responses triggered by pathogen-associated molecular patterns (PAMPs) are key to pathogen defense, but drivers and stabilizers of the growth-to-defense genetic reprogramming remain incompletely understood in plants. Here, we report a time-course study of the establishment of PAMP-triggered immunity (PTI) using cap analysis of gene expression. We show that around 15% of all transcription start sites (TSSs) rapidly induced during PTI define alternative transcription initiation events. From these, we identify clear examples of regulatory TSS change via alternative inclusion of target peptides or domains in encoded proteins, or of upstream open reading frames in mRNA leader sequences. We also find that 60% of PAMP response genes respond earlier than previously thought. In particular, a cluster of rapidly and transiently PAMP-induced genes is enriched in transcription factors (TFs) whose functions, previously associated with biological processes as diverse as abiotic stress adaptation and stem cell activity, appear to converge on growth restriction. Furthermore, examples of known potentiators of PTI, in one case under direct mitogen-activated protein kinase control, support the notion that the rapidly induced TFs could constitute direct links to PTI signaling pathways and drive gene expression changes underlying establishment of the immune state.

Chromatin modifier HUSH co-operates with RNA decay factor NEXT to restrict transposable element expression.

Transposable elements (TEs) are widespread genetic parasites known to be kept under tight transcriptional control. Here, we describe a functional connection between the mouse-orthologous "nuclear exosome targeting" (NEXT) and "human silencing hub" (HUSH) complexes, involved in nuclear RNA decay and the epigenetic silencing of TEs, respectively. Knocking out the NEXT component ZCCHC8 in embryonic stem cells results in elevated TE RNA levels. We identify a physical interaction between ZCCHC8 and the MPP8 protein of HUSH and establish that HUSH recruits NEXT to chromatin at MPP8-bound TE loci. However, while NEXT and HUSH both dampen TE RNA expression, their activities predominantly affect shorter non-polyadenylated and full-length polyadenylated transcripts, respectively. Indeed, our data suggest that the repressive action of HUSH promotes a condition favoring NEXT RNA decay activity. In this way, transcriptional and post-transcriptional machineries synergize to suppress the genotoxic potential of TE RNAs.

Mesenchymal-epithelial crosstalk shapes intestinal regionalisation via Wnt and Shh signalling.

Organs are anatomically compartmentalised to cater for specialised functions. In the small intestine (SI), regionalisation enables sequential processing of food and nutrient absorption. While several studies indicate the critical importance of non-epithelial cells during development and homeostasis, the extent to which these cells contribute to regionalisation during morphogenesis remains unexplored. Here, we identify a mesenchymal-epithelial crosstalk that shapes the developing SI during late morphogenesis. We find that subepithelial mesenchymal cells are characterised by gradients of factors supporting Wnt signalling and stimulate epithelial growth in vitro. Such a gradient impacts epithelial gene expression and regional villus formation along the anterior-posterior axis of the SI. Notably, we further provide evidence that Wnt signalling directly regulates epithelial expression of Sonic Hedgehog (SHH), which, in turn, acts on mesenchymal cells to drive villi formation. Taken together our results uncover a mechanistic link between Wnt and Hedgehog signalling across different cellular compartments that is central for anterior-posterior regionalisation and correct formation of the SI.

JASPAR 2022: the 9th release of the open-access database of transcription factor binding profiles.

JASPAR (http://jaspar.genereg.net/) is an open-access database containing manually curated, non-redundant transcription factor (TF) binding profiles for TFs across six taxonomic groups. In this 9th release, we expanded the CORE collection with 341 new profiles (148 for plants, 101 for vertebrates, 85 for urochordates, and 7 for insects), which corresponds to a 19% expansion over the previous release. We added 298 new profiles to the Unvalidated collection when no orthogonal evidence was found in the literature. All the profiles were clustered to provide familial binding profiles for each taxonomic group. Moreover, we revised the structural classification of DNA binding domains to consider plant-specific TFs. This release introduces word clouds to represent the scientific knowledge associated with each TF. We updated the genome tracks of TFBSs predicted with JASPAR profiles in eight organisms; the human and mouse TFBS predictions can be visualized as native tracks in the UCSC Genome Browser. Finally, we provide a new tool to perform JASPAR TFBS enrichment analysis in user-provided genomic regions. All the data is accessible through the JASPAR website, its associated RESTful API, the R/Bioconductor data package, and a new Python package, pyJASPAR, that facilitates serverless access to the data.

Genomic Stability and Phenotypic Characteristics of Industrially Produced Lacticaseibacillus rhamnosus GG in a Yogurt Matrix.

Lacticaseibacillus rhamnosus GG is a widely marketed probiotic with well-documented probiotic properties. Previously, deletion of the mucus-adhesive spaCBA-srtC1 genes in dairy isolates was reported. In this study, we examined the genome preservation of industrially produced L. rhamnosus GG (DSM 33156) cofermented in yogurts. In total, DNA of 66 samples, including 60 isolates, was sequenced. Population samples and 59 isolates exhibited an intact genome. One isolate exhibited loss of spaCBA-srtC1. In addition, we examined phenotypes related to the probiotic properties of L. rhamnosus GG either from frozen pellets or cofermented in yogurt. L. rhamnosus GG from frozen pellets induced a response in intestinal barrier function in vitro, in contrast to frozen pellets of the starter culture. Yogurt matrix, containing only the starter culture, induced a response, but cofermentation with L. rhamnosus GG induced a higher response. Conversely, only the starter culture stimulated cytokine secretion in dendritic cells, and it was observed that the addition of L. rhamnosus GG to the starter culture reduced the response. We conclude that the L. rhamnosus GG genome is preserved in yogurt and that common in vitro probiotic effects of L. rhamnosus GG are observed when examined in the yogurt matrix. IMPORTANCELacticaseibacillus rhamnosus GG is a well-documented probiotic strain recognized for its high acid and bile tolerance and properties of adhesion to enterocytes and mucus. The strain exhibits SpaCBA pili, which have been demonstrated to play an important role in adhesion and therefore are relevant for persistence in the gastrointestinal tract. Recently we demonstrated that the genome and phenotypes of L. rhamnosus GG are preserved throughout an industrial production pipeline. However, as gene deletions in L. rhamnosus GG were previously reported for isolates from dairy products, a key question on the genomic stability of L. rhamnosus GG in a yogurt matrix remained. The aim of this study was to analyze genome stability and phenotypic characteristics of L. rhamnosus GG in yogurt. We found that the genome of L. rhamnosus GG is well conserved when the organism is cofermented in yogurt. Some phenotypic characteristics are consistent in all product matrixes, while other characteristics are modulated.

TrancriptomeReconstructoR: data-driven annotation of complex transcriptomes.

BACKGROUND: The quality of gene annotation determines the interpretation of results obtained in transcriptomic studies. The growing number of genome sequence information calls for experimental and computational pipelines for de novo transcriptome annotation. Ideally, gene and transcript models should be called from a limited set of key experimental data. RESULTS: We developed TranscriptomeReconstructoR, an R package which implements a pipeline for automated transcriptome annotation. It relies on integrating features from independent and complementary datasets: (i) full-length RNA-seq for detection of splicing patterns and (ii) high-throughput 5' and 3' tag sequencing data for accurate definition of gene borders. The pipeline can also take a nascent RNA-seq dataset to supplement the called gene model with transient transcripts. We reconstructed de novo the transcriptional landscape of wild type Arabidopsis thaliana seedlings and Saccharomyces cerevisiae cells as a proof-of-principle. A comparison to the existing transcriptome annotations revealed that our gene model is more accurate and comprehensive than the most commonly used community gene models, TAIR10 and Araport11 for A.thaliana and SacCer3 for S.cerevisiae. In particular, we identify multiple transient transcripts missing from the existing annotations. Our new annotations promise to improve the quality of A.thaliana and S.cerevisiae genome research. CONCLUSIONS: Our proof-of-concept data suggest a cost-efficient strategy for rapid and accurate annotation of complex eukaryotic transcriptomes. We combine the choice of library preparation methods and sequencing platforms with the dedicated computational pipeline implemented in the TranscriptomeReconstructoR package. The pipeline only requires prior knowledge on the reference genomic DNA sequence, but not the transcriptome. The package seamlessly integrates with Bioconductor packages for downstream analysis.