Computational modeling identifies key gene regulatory interactions underlying phenobarbital-mediated tumor promotion

Automated and unbiased discrimination of ALS from control tissue at single cell resolution

Histopathological analysis of tissue sections is invaluable in neurodegeneration research. However, cell-to-cell variation in both the presence and severity of a given phenotype is a key limitation of this approach, reducing the signal to noise ratio and leaving unresolved the potential of single-cell scoring for a given disease attribute. Here, we tested different machine learning methods to analyse high-content microscopy measurements of hundreds of motor neurons (MNs) from amyotrophic lateral sclerosis (ALS) post-mortem tissue sections. Furthermore, we automated the identification of phenotypically distinct MN subpopulations in VCP- and SOD1-mutant transgenic mice, revealing common morphological cellular phenotypes. Additionally we established scoring metrics to rank cells and tissue samples for both disease probability and severity. By adapting this paradigm to human post-mortem tissue, we validated our core finding that morphological descriptors robustly discriminate ALS from control healthy tissue at single cell resolution. Determining disease presence, severity and unbiased phenotypes at single cell resolution might prove transformational in our understanding of ALS and neurodegeneration more broadly.

The transcriptional landscape of a hepatoma cell line grown on scaffolds of extracellular matrix proteins

Background

The behavior of cells in vivo is complex and highly dynamic, as it results from an interplay between intercellular matrix proteins with surface receptors and other microenvironmental cues. Although the effects of the cellular niche have been investigated for a number of cell types using different molecular approaches, comprehensive assessments of how the global transcriptome responds to 3D scaffolds composed of various extracellular matrix (ECM) constituents at different concentrations are still lacking.

Results

In this study, we explored the effects of two diverse extracellular matrix (ECM) components, Collagen I and Matrigel, on the transcriptional profile of cells in a cell culture system. Culturing Huh-7 cells on traditional cell culture plates (Control) or on the ECM components at different concentrations to modulate microenvironment properties, we have generated transcriptomics data that may be further explored to understand the differentiation and growth potential of this cell type for the development of 3D cultures. Our analysis infers transcription factors that are most responsible for the transcriptome response to the extracellular cues.

Conclusion

Our data indicates that the Collagen I substrate induces a robust transcriptional response in the Huh-7 cells, distinct from that induced by Matrigel. Enhanced hepatocyte markers (ALB and miR-122) reveal a potentially robust remodelling towards primary hepatocytes. Our results aid in defining the appropriate culture and transcription pathways while using hepatoma cell lines. As systems mimicking the in vivo structure and function of liver cells are still being developed, our study could potentially circumvent bottlenecks of limited availability of primary hepatocytes for preclinical studies of drug targets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07532-2.

Molecular and phenotypic analysis of rodent models reveals conserved and species-specific modulators of human sarcopenia

Sarcopenia, the age-related loss of skeletal muscle mass and function, affects 5-13% of individuals aged over 60 years. While rodents are widely-used model organisms, which aspects of sarcopenia are recapitulated in different animal models is unknown. Here we generated a time series of phenotypic measurements and RNA sequencing data in mouse gastrocnemius muscle and analyzed them alongside analogous data from rats and humans. We found that rodents recapitulate mitochondrial changes observed in human sarcopenia, while inflammatory responses are conserved at pathway but not gene level. Perturbations in the extracellular matrix are shared by rats, while mice recapitulate changes in RNA processing and autophagy. We inferred transcription regulators of early and late transcriptome changes, which could be targeted therapeutically. Our study demonstrates that phenotypic measurements, such as muscle mass, are better indicators of muscle health than chronological age and should be considered when analyzing aging-related molecular data.

Meta-Analysis of Transcriptome Data Detected New Potential Players in Response to Dioxin Exposure in Humans

Dioxins are one of the most potent anthropogenic poisons, causing systemic disorders in embryonic development and pathologies in adults. The mechanism of dioxin action requires an aryl hydrocarbon receptor (AhR), but the downstream mechanisms are not yet precisely clear. Here, we performed a meta-analysis of all available transcriptome datasets taken from human cell cultures exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Differentially expressed genes from different experiments overlapped partially, but there were a number of those genes that were systematically affected by TCDD. Some of them have been linked to toxic dioxin effects, but we also identified other attractive targets. Among the genes that were affected by TCDD, there are functionally related gene groups that suggest an interplay between retinoic acid, AhR, and Wnt signaling pathways. Next, we analyzed the upstream regions of differentially expressed genes and identified potential transcription factor (TF) binding sites overrepresented in the genes responding to TCDD. Intriguingly, the dioxin-responsive element (DRE), the binding site of AhR, was not overrepresented as much as other cis-elements were. Bioinformatics analysis of the AhR binding profile unveils potential cooperation of AhR with E2F2, CTCFL, and ZBT14 TFs in the dioxin response. We discuss the potential implication of these predictions for further dioxin studies.

The neuromuscular junction is a focal point of mTORC1 signaling in sarcopenia

With human median lifespan extending into the 80s in many developed countries, the societal burden of age-related muscle loss (sarcopenia) is increasing. mTORC1 promotes skeletal muscle hypertrophy, but also drives organismal aging. Here, we address the question of whether mTORC1 activation or suppression is beneficial for skeletal muscle aging. We demonstrate that chronic mTORC1 inhibition with rapamycin is overwhelmingly, but not entirely, positive for aging mouse skeletal muscle, while genetic, muscle fiber-specific activation of mTORC1 is sufficient to induce molecular signatures of sarcopenia. Through integration of comprehensive physiological and extensive gene expression profiling in young and old mice, and following genetic activation or pharmacological inhibition of mTORC1, we establish the phenotypically-backed, mTORC1-focused, multi-muscle gene expression atlas, SarcoAtlas (https://sarcoatlas.scicore.unibas.ch/), as a user-friendly gene discovery tool. We uncover inter-muscle divergence in the primary drivers of sarcopenia and identify the neuromuscular junction as a focal point of mTORC1-driven muscle aging.

Drug-induced chromatin accessibility changes associate with sensitivity to liver tumor promotion

Liver cancer susceptibility varies amongst humans and between experimental animal models because of multiple genetic and epigenetic factors. The molecular characterization of such susceptibilities has the potential to enhance cancer risk assessment of xenobiotic exposures and disease prevention strategies. Here, using DNase I hypersensitivity mapping coupled with transcriptomic profiling, we investigate perturbations in cis-acting gene regulatory elements associated with the early stages of phenobarbital (PB)-mediated liver tumor promotion in susceptible versus resistant mouse strains (B6C3F1 versus C57BL/6J). Integrated computational analyses of strain-selective changes in liver chromatin accessibility underlying PB response reveal differential epigenetic regulation of molecular pathways associated with PB-mediated tumor promotion, including Wnt/β-catenin signaling. Complementary transcription factor motif analyses reveal mouse strain-selective gene regulatory networks and a novel role for Stat, Smad, and Fox transcription factors in the early stages of PB-mediated tumor promotion. Mapping perturbations in cis-acting gene regulatory elements provides novel insights into the molecular basis for susceptibility to xenobiotic-induced rodent liver tumor promotion and has the potential to enhance mechanism-based cancer risk assessments of xenobiotic exposures.

Intron retention and nuclear loss of SFPQ are molecular hallmarks of ALS

Mutations causing amyotrophic lateral sclerosis (ALS) strongly implicate ubiquitously expressed regulators of RNA processing. To understand the molecular impact of ALS-causing mutations on neuronal development and disease, we analysed transcriptomes during in vitro differentiation of motor neurons (MNs) from human control and patient-specific VCP mutant induced-pluripotent stem cells (iPSCs). We identify increased intron retention (IR) as a dominant feature of the splicing programme during early neural differentiation. Importantly, IR occurs prematurely in VCP mutant cultures compared with control counterparts. These aberrant IR events are also seen in independent RNAseq data sets from SOD1- and FUS-mutant MNs. The most significant IR is seen in the SFPQ transcript. The SFPQ protein binds extensively to its retained intron, exhibits lower nuclear abundance in VCP mutant cultures and is lost from nuclei of MNs in mouse models and human sporadic ALS. Collectively, we demonstrate SFPQ IR and nuclear loss as molecular hallmarks of familial and sporadic ALS.

Perturbations of PIP3 signalling trigger a global remodelling of mRNA landscape and reveal a transcriptional feedback loop

PIP3 is synthesized by the Class I PI3Ks and regulates complex cell responses, such as growth and migration. Signals that drive long-term reshaping of cell phenotypes are difficult to resolve because of complex feedback networks that operate over extended times. PIP3-dependent modulation of mRNA accumulation is clearly important in this process but is poorly understood. We have quantified the genome-wide mRNA-landscape of non-transformed, breast epithelium-derived MCF10a cells and its response to acute regulation by EGF, in the presence or absence of a PI3Kα inhibitor, compare it to chronic activation of PI3K signalling by cancer-relevant mutations (isogenic cells expressing an oncomutant PI3Kα allele or lacking the PIP3-phosphatase/tumour-suppressor, PTEN). Our results show that whilst many mRNAs are changed by long-term genetic perturbation of PIP3 signalling ('butterfly effect'), a much smaller number do so in a coherent fashion with the different PIP3 perturbations. This suggests a subset of more directly regulated mRNAs. We show that mRNAs respond differently to given aspects of PIP3 regulation. Some PIP3-sensitive mRNAs encode PI3K pathway components, thus suggesting a transcriptional feedback loop. We identify the transcription factor binding motifs SRF and PRDM1 as important regulators of PIP3-sensitive mRNAs involved in cell movement.

ARMADA: Using motif activity dynamics to infer gene regulatory networks from gene expression data

Analysis of gene expression data remains one of the most promising avenues toward reconstructing genome-wide gene regulatory networks. However, the large dimensionality of the problem prohibits the fitting of explicit dynamical models of gene regulatory networks, whereas machine learning methods for dimensionality reduction such as clustering or principal component analysis typically fail to provide mechanistic interpretations of the reduced descriptions. To address this, we recently developed a general methodology called motif activity response analysis (MARA) that, by modeling gene expression patterns in terms of the activities of concrete regulators, accomplishes dramatic dimensionality reduction while retaining mechanistic biological interpretations of its predictions (Balwierz, 2014). Here we extend MARA by presenting ARMADA, which models the activity dynamics of regulators across a time course, and infers the causal interactions between the regulators that drive the dynamics of their activities across time. We have implemented ARMADA as part of our ISMARA webserver, ismara.unibas.ch, allowing any researcher to automatically apply it to any gene expression time course. To illustrate the method, we apply ARMADA to a time course of human umbilical vein endothelial cells treated with TNF. Remarkably, ARMADA is able to reproduce the complex observed motif activity dynamics using a relatively small set of interactions between the key regulators in this system. In addition, we show that ARMADA successfully infers many of the key regulatory interactions known to drive this inflammatory response and discuss several novel interactions that ARMADA predicts. In combination with ISMARA, ARMADA provides a powerful approach to generating plausible hypotheses for the key interactions between regulators that control gene expression in any system for which time course measurements are available.

Nrf2, but not β-catenin, mutation represents an early event in rat hepatocarcinogenesis

Hepatocellular carcinoma (HCC) develops through a multistage process, but the nature of the molecular changes associated with the different steps, the very early ones in particular, is largely unknown. Recently, dysregulation of the NRF2/KEAP1 pathway and mutations of these genes have been observed in experimental and human tumors, suggesting their possible role in cancer development. To assess whether Nrf2/Keap1 mutations are early or late events in HCC development, we investigated their frequency in the rat Resistant Hepatocyte model, consisting of the administration of diethylnitrosamine followed by a brief exposure to 2-acetylaminofluorene. This model enables the dissection of all stages of hepatocarcinogenesis. We found that Nrf2/Keap1 mutations were present in 71% of early preneoplastic lesions and in 78.6% and 59.3% of early and advanced HCCs, respectively. Mutations of Nrf2 were more frequent, missense, and located in the Nrf2-Keap1 binding region. Mutations of Keap1 occurred at a much lower frequency in both preneoplastic lesions and HCCs and were mutually exclusive with those of Nrf2. Functional in vitro and in vivo studies showed that Nrf2 silencing inhibited the ability of tumorigenic rat cells to grow in soft agar and to form tumors. Unlike Nrf2 mutations, those of Ctnnb1, which are frequent in human HCC, were a later event as they appeared only in fully advanced HCCs (18.5%).

CONCLUSION

In the Resistant Hepatocyte model of hepatocarcinogenesis the onset of Nrf2 mutations is a very early event, likely essential for the clonal expansion of preneoplastic hepatocytes to HCC, while Ctnnb1 mutations occur only at very late stages. Moreover, functional experiments demonstrate that Nrf2 is an oncogene critical for HCC progression and development.

Importance of investigating epigenetic alterations for industry and regulators: An appraisal of current efforts by the Health and Environmental Sciences Institute

Recent technological advances have led to rapid progress in the characterization of epigenetic modifications that control gene expression in a generally heritable way, and are likely involved in defining cellular phenotypes, developmental stages and disease status from one generation to the next. On November 18, 2013, the International Life Sciences Institute (ILSI) Health and Environmental Sciences Institute (HESI) held a symposium entitled "Advances in Assessing Adverse Epigenetic Effects of Drugs and Chemicals" in Washington, D.C. The goal of the symposium was to identify gaps in knowledge and highlight promising areas of progress that represent opportunities to utilize epigenomic profiling for risk assessment of drugs and chemicals. Epigenomic profiling has the potential to provide mechanistic information in toxicological safety assessments; this is especially relevant for the evaluation of carcinogenic or teratogenic potential and also for drugs that directly target epigenetic modifiers, like DNA methyltransferases or histone modifying enzymes. Furthermore, it can serve as an endpoint or marker for hazard characterization in chemical safety assessment. The assessment of epigenetic effects may also be approached with new model systems that could directly assess transgenerational effects or potentially sensitive stem cell populations. These would enhance the range of safety assessment tools for evaluating xenobiotics that perturb the epigenome. Here we provide a brief synopsis of the symposium, update findings since that time and then highlight potential directions for future collaborative efforts to incorporate epigenetic profiling into risk assessment.