Changes In Gene Expression Research Articles

Transcriptomic Insights: Phytogenic Modulation of Buffel Grass (Cenchrus ciliaris) Seedling Emergence.

This study explores the impact of a novel phytogenic product containing citric acid, carvacrol, and cinnamaldehyde on buffel grass (Cenchrus ciliaris) seedling emergence. A dilution series of the phytogenic solution revealed a concentration range that promoted seedling emergence, with an optimal concentration of 0.5%. Transcriptomic analysis using RNA-seq was performed to investigate gene expression changes in seedlings under the influence of the phytogenic product. The results revealed that the phytogenic treatment significantly altered the gene expression, with a prevalent boost in transcriptional activity compared to the control. Functional analysis indicated the positive alteration of key metabolic pathways, including the tricarboxylic acid (TCA) cycle, glycolysis, and pentose phosphate pathways. Moreover, pathways related to amino acids, nucleotide biosynthesis, heme biosynthesis, and formyltetrahydrofolate biosynthesis showed substantial modulation. The study provides valuable insights into the molecular mechanisms underlying the phytogenic product's effects on grass seedling establishment and highlights its ability to promote energy metabolism and essential biosynthetic pathways for plant growth.

Changes in Physiological Traits, Gene Expression and Phytochemical Profile of Mentha piperita in Response to Elicitor.

Peppermint (Mentha piperita) is a perennial medicinal plant containing active ingredients that can be used for treating liver and prostate cancers, acute respiratory infections, allergies, digestive problems, neuralgia, and migraines. The objective of this research is to investigate the expression of essential genes in the menthol pathway of Mentha piperita, including Pulegone reductase (Pr), Menthofuran synthase (Mfs), and limonene synthase (Ls) using qPCR, physiological analysis and essential oil composition in response to methyl jasmonate (MeJA) (0.5mM) elicitation. Physiological analysis showed that 0.5mM MeJA triggers defensive responsiveness in Mentha piperita by increasing superoxide dismutase (SOD) and Peroxidase (POD) enzymesactivity. The highest transcript levels of Pr and Mfs genes were observed during 8 and 12h after treatment respectively, but following 24h, they were down-regulated. Essential oil analysis indicated that the percentage of constituents in the essential oil was changed using MeJA at 48h and 96h after post-treatment. Effective antimicrobial compounds, α-pinene, β-pinene, linalool and methyl acetate, were induced after 48h. A non-significant positive relationship was detected between menthol content, and expression of the Pr and Mfs genes. Due to the significant change in the expression of Pr and Mfs genes in the menthol pathway, role of Pr gene in directing the pathway to the valuable compound menthol and deviation of the menthol pathway to the menthofuran as an undesirable component of essential oil by Mfs gene, it can be deduced that they are the most critical genes in response to MeJA treatment, which are appropriate candidates for metabolite engineering. In addition, MeJA improved defensive responsiveness and percentage of some constituents with antimicrobial properties in Mentha piperita.

Discovery of Three Bemisia tabaci Effectors and Their Effect on Gene Expression in Planta.

Bemisia tabaci (whitefly) is a polyphagous agroeconomic pest species complex. Two members of this species complex, Mediterranean (MED) and Middle-East-Asia Minor 1 (MEAM1), have a worldwide distribution and have been shown to manipulate plant defenses through effectors. In this study, we used three different strategies to identify three MEAM1 proteins that can act as effectors. Effector B1 was identified using a bioinformatics-driven effector-mining strategy, whereas effectors S1 and P1 were identified in the saliva of whiteflies collected from artificial diet and in phloem exudate of tomato on which nymphs were feeding, respectively. These three effectors were B. tabaci specific and able to increase whitefly fecundity when transiently expressed in tobacco plants (Nicotiana tabacum). Moreover, they reduced growth of Pseudomonas syringae pv. tabaci in Nicotiana benthamiana. All three effectors changed gene expression in planta, and B1 and S1 also changed phytohormone levels. Gene ontology and KEGG pathway enrichment analysis pinpointed plant-pathogen interaction and photosynthesis as the main enriched pathways for all three effectors. Our data thus show the discovery and validation of three new B. tabaci MEAM1 effectors that increase whitefly fecundity and modulate plant immunity. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

The genome regulatory landscape of Atlantic salmon liver through smoltification.

The anadromous Atlantic salmon undergo a preparatory physiological transformation before seawater entry, referred to as smoltification. Key molecular developmental processes involved in this life stage transition, such as remodeling of gill functions, are known to be synchronized and modulated by environmental cues like photoperiod. However, little is known about the photoperiod influence and genome regulatory processes driving other canonical aspects of smoltification such as the large-scale changes in lipid metabolism and energy homeostasis in the developing smolt liver. Here we generate transcriptome, DNA methylation, and chromatin accessibility data from salmon livers across smoltification under different photoperiod regimes. We find a systematic reduction of expression levels of genes with a metabolic function, such as lipid metabolism, and increased expression of energy related genes such as oxidative phosphorylation, during smolt development in freshwater. However, in contrast to similar studies of the gill, smolt liver gene expression prior to seawater transfer was not impacted by photoperiodic history. Integrated analyses of gene expression, chromatin accessibility, and transcription factor (TF) binding signatures highlight chromatin remodeling and TF dynamics underlying smolt gene regulatory changes. Differential peak accessibility patterns largely matched differential gene expression patterns during smoltification and we infer that ZNF682, KLFs, and NFY TFs are important in driving a liver metabolic shift from synthesis to break down of organic compounds in freshwater. Overall, chromatin accessibility and TFBS occupancy were highly correlated to changes in gene expression. On the other hand, we identified numerous differential methylation patterns across the genome, but associated genes were not functionally enriched or correlated to observed gene expression changes across smolt development. Taken together, this work highlights the relative importance of chromatin remodeling during smoltification and demonstrates that metabolic remodeling occurs as a preadaptation to life at sea that is not to a large extent driven by photoperiod history.

Exponential family measurement error models for single-cell CRISPR screens.

CRISPR genome engineering and single-cell RNA sequencing have accelerated biological discovery. Single-cell CRISPR screens unite these two technologies, linking genetic perturbations in individual cells to changes in gene expression and illuminating regulatory networks underlying diseases. Despite their promise, single-cell CRISPR screens present considerable statistical challenges. We demonstrate through theoretical and real data analyses that a standard method for estimation and inference in single-cell CRISPR screens-"thresholded regression"-exhibits attenuation bias and a bias-variance tradeoff as a function of an intrinsic, challenging-to-select tuning parameter. To overcome these difficulties, we introduce GLM-EIV ("GLM-based errors-in-variables"), a new method for single-cell CRISPR screen analysis. GLM-EIV extends the classical errors-in-variables model to responses and noisy predictors that are exponential family-distributed and potentially impacted by the same set of confounding variables. We develop a computational infrastructure to deploy GLM-EIV across hundreds of processors on clouds (e.g. Microsoft Azure) and high-performance clusters. Leveraging this infrastructure, we apply GLM-EIV to analyze two recent, large-scale, single-cell CRISPR screen datasets, yielding several new insights.

Sequence- and Structure-Dependent Cytotoxicity of Phosphorothioate and 2'-O-Methyl Modified Single-Stranded Oligonucleotides.

Single-stranded oligonucleotides (SSOs) are a rapidly expanding class of therapeutics that comprises antisense oligonucleotides, microRNAs, and aptamers, with ten clinically approved molecules. Chemical modifications such as the phosphorothioate backbone and the 2'-O-methyl ribose can improve the stability and pharmacokinetic properties of therapeutic SSOs, but they can also lead to toxicity in vitro and invivo through nonspecific interactions with cellular proteins, gene expression changes, disturbed RNA processing, and changes in nuclear structures and protein distribution. In this study, we screened a mini library of 277 phosphorothioate and 2'-O-methyl-modified SSOs, with or without mRNA complementarity, for cytotoxic properties in two cancer cell lines. Using circular dichroism, nucleic magnetic resonance, and molecular dynamics simulations, we show that phosphorothioate- and 2'-O-methyl-modified SSOs that form stable hairpin structures through Watson-Crick base pairing are more likely to be cytotoxic than those that exist in an extended conformation. In addition, moderate and highly cytotoxic SSOs in our dataset have a higher mean purine composition than pyrimidine. Overall, our study demonstrates a structure-cytotoxicity relationship and indicates that the formation of stable hairpins should be a consideration when designing SSOs toward optimal therapeutic profiles.

Two sequential gene expression programs bridged by cell division support long-distance collective cell migration.

The precise assembly of tissues and organs relies on spatiotemporal regulation of gene expression to coordinate cells' collective behavior. In Drosophila embryos, the midgut musculature is formed through collective migration of caudal visceral mesoderm (CVM) cells, but how gene expression changes as cells migrate is not well understood. Here, we focused on ten genes expressed in the CVM and cis-regulatory sequences controlling their expression. While some genes are continuously expressed, others are expressed only early or late during migration. Late expression relates to cell cycle progression, as driving string/Cdc25 causes earlier division of CVM cells and accelerates the transition to late gene expression. In particular, we found that cell cycle effector transcription factor E2f1 is a required input for late gene CG5080. Furthermore, while late genes are broadly expressed in all CVM cells, early gene transcripts are polarized to anterior or posterior ends of the migrating collective. We show this polarization requires transcription factors Snail, Zfh1, and Dorsocross. Collectively, these results identify two sequential gene expression programs bridged by cell division that support long-distance directional migration of CVM cells.

Carrageenan maintains the contractile phenotype of vascular smooth muscle cells by increasing macromolecular crowding in vitro

BackgroundThe contractile phenotype of vascular smooth muscle cells (VSMCs) results in good diastolic and contractile capacities, and its altered function is the main pathophysiological basis for diseases such as hypertension. VSMCs exist as a synthetic phenotype in vitro, making it challenging to maintain a contractile phenotype for research. It is widely recognized that the common medium in vitro is significantly less crowded than in the in vivo environment. Additionally, VSMCs have a heightened sense for detecting changes in medium crowding. However, it is unclear whether macromolecular crowding (MMC) helps maintain the VSMCs contractile phenotype.PurposeThis study aimed to explore the phenotypic, behavioral and gene expression changes of VSMCs after increasing the crowding degree by adding carrageenan (CR).MethodsThe degree of medium crowding was examined by a dynamic light scattering assay; VSMCs survival and activity were examined by calcein/PI cell activity and toxicity and CCK-8 assays; VSMCs phenotypes and migration were examined by WB and wound healing assays; and gene expression was examined by transcriptomic analysis and RT-qPCR.ResultsNotably, 225 μg/mL CR significantly increased the crowding degree of the medium and did not affect cell survival. Simultaneously, CR significantly promoted the contraction phenotypic marker expression in VSMCs, shortened cell length, decreased cell proliferation, and inhibited cell migration. CR significantly altered gene expression in VSMCs. Specifically, 856 genes were upregulated and 1207 genes were downregulated. These alterations primarily affect the cellular ion channel transport, microtubule movement, respiratory metabolism, amino acid transport, and extracellular matrix synthesis. The upregulated genes were primarily involved in the cytoskeleton and contraction processes of VSMCs, whereas the downregulated genes were mainly involved in extracellular matrix synthesis.ConclusionsThe in vitro study showed that VSMCs can maintain the contractile phenotype by sensing changes in the crowding of the culture environment, which can be maintained by adding CR.Graphical

Intact cell mass spectrometry coupled with machine learning reveals minute changes induced by single gene silencing

Intact (whole) cell MALDI TOF mass spectrometry is a commonly used tool in clinical microbiology for several decades. Recently it was introduced to analysis of eukaryotic cells, including cancer and stem cells. Besides targeted metabolomic and proteomic applications, the intact cell MALDI TOF mass spectrometry provides a sufficient sensitivity and specificity to discriminate cell types, isogenous cell lines or even the metabolic states. This makes the intact cell MALDI TOF mass spectrometry a promising tool for quality control in advanced cell cultures with a potential to reveal batch-to-batch variation, aberrant clones, or unwanted shifts in cell phenotype. However, cellular alterations induced by change in expression of a single gene has not been addressed by intact cell mass spectrometry yet. In this work we used a well-characterized human ovarian cancer cell line SKOV3 with silenced expression of a tumor suppressor candidate 3 gene (TUSC3). TUSC3 is involved in co-translational N-glycosylation of proteins with well-known global impact on cell phenotype. Altogether, this experimental design represents a highly suitable model for optimization of intact cell mass spectrometry and analysis of spectral data. Here we investigated five machine learning algorithms (k-nearest neighbors, decision tree, random forest, partial least squares discrimination, and artificial neural network) and optimized their performance either in pure populations or in two-component mixtures composed of cells with normal or silenced expression of TUSC3. All five algorithms reached accuracy over 90 % and were able to reveal even subtle changes in mass spectra corresponding to alterations of TUSC3 expression. In summary, we demonstrate that spectral fingerprints generated by intact cell MALDI-TOF mass spectrometry coupled to a machine learning classifier can reveal minute changes induced by alteration of a single gene, and therefore contribute to the portfolio of quality control applications in routine cell and tissue cultures.

Overexpression of WT1 in all molecular subtypes of breast cancer and its impact on survival: exploring oncogenic and tumor suppressor roles of distinct WT1 isoforms.

Breast cancer is a highly heterogeneous solid tumor, posing challenges in developing targeted therapies effective for all mammary carcinoma subtypes. WT1 emerges as a promising target for breast cancer therapy due to its potential oncogenic role in various cancer types. Previous works have yielded inconsistent results. Therefore, further studies are needed to clarify the behavior of this complex gene in breast cancer. In this study, we examined WT1 expression in both Formalin Fixed Paraffin Embedded breast tumors (n = 41) and healthy adjacent tissues (n = 41) samples from newly diagnosed cases of ductal invasive breast cancer. The fold change in gene expression between the tumor and healthy tissue was determined by calculating 2-∆∆Ct. Disease-free survival analysis was computed using the Kaplan-Meier method. To identify the expression levels of different WT1 isoforms, we explored the ISOexpresso database. Relative quantification of the WT1 gene revealed an overexpression of WT1 in most cases. The percentage of patients surviving free of disease at 8years of follow-up was lower in the group overexpressing WT1 compared to the group with down-regulated WT1. Interestingly, this overexpression was observed in all molecular subtypes of invasive breast cancer, underscoring the significance of WT1 as a potential target in all these subtypes. The observed WT1 down-expression in a few cases of invasive breast cancer, associated with better survival outcomes, may correspond to the down-regulation of a particular WT1-KTS (-) isoform: the WT1 A isoform (EX5-/KTS-). The co-expression of this WT1 oncogenic isoform with a regulated WT1- tumor suppressor isoform, such as the major WT1 F isoform (EX5-/KTS +), could also explain such survival outcomes. Due to its capacity to adopt dual roles, it becomes imperative to conduct individual molecular expression profiling of the WT1 gene. Such an approach holds great promise in the development of personalized treatment strategies for breast cancer.

Effects of Aronia melanocarpa juice-powder on hindgut function and performance in post-weaned pigs

Twenty-four gilts and barrows (n = 8/trt) were divided into three treatment groups: control (CON), 0.5 % Aronia melanocarpa juice powder (AM; LoBerry), and 1.0 % AM juice powder (HiBerry). Pigs were fed for 14 d and tissues were collected. No differences in performance were observed. Ileum IL-18 tended to be lower in LoBerry pigs, while colonic IFN-γ was increased in pigs fed either AM diet. There were several changes in ileal gene expression in pigs fed the LoBerry diet compared to pigs fed the CON diet, including BMI1, CLDN2, JAM2, and MYLK, which are largely related to barrier and stem cell function. In the colon, CLDN2, REG3G, SI, and SLC6A19 were increased in pigs fed the LoBerry diet. There were no differences found in the colonic microbiome due to diets. In conclusion, feeding AM juice powder may have a positive impact in young pigs, but may require longer feeding time to observe performance differences.

Yeast Crf1p is an activator with different roles in regulation of target genes.

Under stress conditions, ribosome biogenesis is downregulated. This process requires that expression of ribosomal RNA, ribosomal protein, and ribosome biogenesis genes be controlled in a coordinated fashion. The mechanistic Target of Rapamycin Complex 1 (mTORC1) participates in sensing unfavorable conditions to effect the requisite change in gene expression. In Saccharomyces cerevisiae, downregulation of ribosomal protein genes involves dissociation of the activator Ifh1p in a process that depends on Utp22p, a protein that also functions in pre-rRNA processing. Ifh1p has a paralog, Crf1p, which was implicated in communicating mTORC1 inhibition and hence was perceived as a repressor. We focus here on two ribosomal biogenesis genes, encoding Utp22p and the high mobility group protein Hmo1p, both of which are required for communication of mTORC1 inhibition to target genes. Crf1p functions as an activator on these genes as evidenced by reduced mRNA abundance and RNA polymerase II occupancy in a crf1Δ strain. Inhibition of mTORC1 has distinct effects on expression of HMO1 and UTP22; for example, on UTP22, but not on HMO1, the presence of Crf1p promotes the stable depletion of Ifh1p. Our data suggest that Crf1p functions as a weak activator, and that it may be required to prevent re-binding of Ifh1p to some gene promoters after mTORC1 inhibition in situations when Ifh1p is available. We propose that the inclusion of genes encoding proteins required for mTORC1-mediated downregulation of ribosomal protein genes in the same regulatory circuit as the ribosomal protein genes serves to optimize transcriptional responses during mTORC1 inhibition.

Multi-Omics Integration for Liver Cancer Using Regression Analysis.

Genetic biomarkers have played a pivotal role in the classification, prognostication, and guidance of clinical cancer therapies. Large-scale and multi-dimensional analyses of entire cancer genomes, as exemplified by projects like The Cancer Genome Atlas (TCGA), have yielded an extensive repository of data that holds the potential to unveil the underlying biology of these malignancies. Mutations stand out as the principal catalysts of cellular transformation. Nonetheless, other global genomic processes, such as alterations in gene expression and chromosomal re-arrangements, also play crucial roles in conferring cellular immortality. The incorporation of multi-omics data specific to cancer has demonstrated the capacity to enhance our comprehension of the molecular mechanisms underpinning carcinogenesis. This report elucidates how the integration of comprehensive data on methylation, gene expression, and copy number variations can effectively facilitate the unsupervised clustering of cancer samples. We have identified regressors that can effectively classify tumor and normal samples with an optimal integration of RNA sequencing, DNA methylation, and copy number variation while also achieving significant p-values. Further, these regressors were trained using linear and logistic regression with k-means clustering. For comparison, we employed autoencoder- and stacking-based omics integration and computed silhouette scores to evaluate the clusters. The proof of concept is illustrated using liver cancer data. Our analysis serves to underscore the feasibility of unsupervised cancer classification by considering genetic markers beyond mutations, thereby emphasizing the clinical relevance of additional global cellular parameters that contribute to the transformative process in cells. This work is clinically relevant because changes in gene expression and genomic re-arrangements have been shown to be signatures of cellular transformation across cancers, as well as in liver cancers.

Hydroxymethylglutaryl-CoA reductase activity is essential for mitochondrial β-oxidation of fatty acids to prevent lethal accumulation of long-chain acylcarnitines in the mouse liver.

Statins are competitive inhibitors of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase (HMGCR), and exert adverse effects on mitochondrial function, although the mechanisms underlying these effects remain unclear. We used a tamoxifen-induced Hmgcr-knockout (KO) mouse model, a multi-omics approach and mitochondrial function assessments to investigate whether decreased HMGCR activity impacts key liver energy metabolism pathways. We established a new mouse strain using the Cre/loxP system, which enabled whole-body deletion of Hmgcr expression. These mice were crossed with Rosa26Cre mice and treated with tamoxifen to delete Hmgcr in all cells. We performed transcriptomic and metabolomic analyses and thus evaluated time-dependent changes in metabolic functions to identify the pathways leading to cell death in Hmgcr-KO mice. Lack of Hmgcr expression resulted in lethality, due to acute liver damage caused by rapid disruption of mitochondrial fatty acid β-oxidation and very high accumulation of long-chain (LC) acylcarnitines in both male and female mice. Gene expression and KO-related phenotype changes were not observed in other tissues. The progression to liver failure was driven by diminished peroxisome formation, which resulted in impaired mitochondrial and peroxisomal fatty acid metabolism, enhanced glucose utilization and whole-body hypoglycaemia. Our findings suggest that HMGCR is crucial for maintaining energy metabolism balance, and its activity is necessary for functional mitochondrial β-oxidation. Moreover, statin-induced adverse reactions might be rescued by the prevention of LC acylcarnitine accumulation.

Multiome in the Same Cell Reveals the Impact of Osmotic Stress on Arabidopsis Root Tip Development at Single-Cell Level.

Cell-specific transcriptional regulatory networks (TRNs) play vital roles in plant development and response to environmental stresses. However, traditional single-cell mono-omics techniques are unable to directly capture the relationships and dynamics between different layers of molecular information within the same cells. While advanced algorithm facilitates merging scRNA-seq and scATAC-seq datasets, accurate data integration remains a challenge, particularly when investigating cell-type-specific TRNs. By examining gene expression and chromatin accessibility simultaneously in 16,670 Arabidopsis root tip nuclei, the TRNs are reconstructed that govern root tip development under osmotic stress. In contrast to commonly used computational integration at cell-type level, 12,968 peak-to-gene linkage is captured at the bona fide single-cell level and construct TRNs at an unprecedented resolution. Furthermore, the unprecedented datasets allow to more accurately reconstruct the coordinated changes of gene expression and chromatin states during cellular state transition. During root tip development, chromatin accessibility of initial cells precedes gene expression, suggesting that changes in chromatin accessibility may prime cells for subsequent differentiation steps. Pseudo-time trajectory analysis reveal that osmotic stress can shift the functional differentiation of trichoblast. Candidate stress-related gene-linked cis-regulatory elements(gl-cCREs) as well as potential target genes are also identified, and uncovered large cellular heterogeneity under osmotic stress.

The Microglial Transcriptome of Age-Associated Deep Subcortical White Matter Lesions Suggests a Neuroprotective Response to Blood-Brain Barrier Dysfunction.

Age-associated deep-subcortical white matter lesions (DSCLs) are an independent risk factor for dementia, displaying high levels of CD68+ microglia. This study aimed to characterize the transcriptomic profile of microglia in DSCLs and surrounding radiologically normal-appearing white matter (NAWM) compared to non-lesional control white matter. CD68+ microglia were isolated from white matter groups (n = 4 cases per group) from the Cognitive Function and Ageing Study neuropathology cohort using immuno-laser capture microdissection. Microarray gene expression profiling, but not RNA-sequencing, was found to be compatible with immuno-LCM-ed post-mortem material in the CFAS cohort and identified significantly differentially expressed genes (DEGs). Functional grouping and pathway analysis were assessed using the Database for Annotation Visualization and Integrated Discovery (DAVID) software, and immunohistochemistry was performed to validate gene expression changes at the protein level. Transcriptomic profiling of microglia in DSCLs compared to non-lesional control white matter identified 181 significant DEGs (93 upregulated and 88 downregulated). Functional clustering analysis in DAVID revealed dysregulation of haptoglobin-haemoglobin binding (Enrichment score 2.5, p = 0.017), confirmed using CD163 immunostaining, suggesting a neuroprotective microglial response to blood-brain barrier dysfunction in DSCLs. In NAWM versus control white matter, microglia exhibited 347 DEGs (209 upregulated, 138 downregulated), with significant dysregulation of protein de-ubiquitination (Enrichment score 5.14, p < 0.001), implying an inability to maintain protein homeostasis in NAWM that may contribute to lesion spread. These findings enhance understanding of microglial transcriptomic changes in ageing white matter pathology, highlighting a neuroprotective adaptation in DSCLs microglia and a potentially lesion-promoting phenotype in NAWM microglia.

Evaluation of Tumorigenic Properties of MDA-MB-231 Cancer Stem Cells Cocultured with Telocytes and Telocyte-Derived Mitochondria Following miR-146a Inhibition.

Telocytes have some cytoplasmic extensions called telopodes, which are thought to play a role in mitochondrial transfer in intercellular communication. Besides, it is hypothesized that telocytes establish cell membrane-mediated connections with breast cancer cells in coculture and may contribute to the survival of neoplastic cell clusters together with other stromal cells. The aim of this study is to investigate the contribution of telocytes and telocyte-derived mitochondria, which have also been identified in breast tumors, to the tumor development of breast cancer stem cells (CSCs) via miR-146a-5p. The isolation/characterization of telocytes from bone marrow mononuclear cells and the isolation of mitochondria from these cells were performed, respectively. In the next step, CSCs were isolated from the MDA-MB-231 cell line and were characterized. Then, miR-146a-5p expressions of CSCs were inhibited by anti-miR-146a-5p. The epithelial-mesenchymal transition (EMT) was determined by evaluating changes in vimentin protein levels and was evaluated by analyzing BRCA1, P53, SOX2, E-cadherin, and N-cadherin gene expression changes. Our results showed that miR-146a promoted stemness and oncogenic properties in CSCs. EMT (N-cadherin, vimentin, E-cadherin) and tumorigenic markers (BRCA1, P53, SOX2) of CSCs decreased after miR-146a inhibition. Bone marrow-derived telocytes and mitochondria derived from telocytes favored the reduction of CSC aggressiveness following this inhibition.

SOX4 exerts contrasting regulatory effects on labor-associated gene promoters in myometrial cells.

The uterine muscular layer, or myometrium, undergoes profound changes in global gene expression during its progression from a quiescent state during pregnancy to a contractile state at the onset of labor. In this study, we investigate the role of SOX family transcription factors in myometrial cells and provide evidence for the role of SOX4 in regulating labor-associated genes. We show that Sox4 has elevated expression in the murine myometrium during a term laboring process and in two mouse models of preterm labor. Additionally, SOX4 differentially affects labor-associated gene promoter activity in cooperation with activator protein 1 (AP-1) dimers. SOX4 exerted no effect on the Gja1 promoter; a JUND-specific activation effect at the Fos promoter; a positive activation effect on the Mmp11 promoter with the AP-1 dimers; and surprisingly, we noted that the reporter expression of the Ptgs2 promoter in the presence of JUND and FOSL2 was repressed by the addition of SOX4. Our data indicate SOX4 may play a diverse role in regulating gene expression in the laboring myometrium in cooperation with AP-1 factors. This study enhances our current understanding of the regulatory network that governs the transcriptional changes associated with the onset of labor and highlights a new molecular player that may contribute to the labor transcriptional program.

CoVar: A generalizable machine learning approach to identify the coordinated regulators driving variational gene expression.

Network inference is used to model transcriptional, signaling, and metabolic interactions among genes, proteins, and metabolites that identify biological pathways influencing disease pathogenesis. Advances in machine learning (ML)-based inference models exhibit the predictive capabilities of capturing latent patterns in genomic data. Such models are emerging as an alternative to the statistical models identifying causative factors driving complex diseases. We present CoVar, an ML-based framework that builds upon the properties of existing inference models, to find the central genes driving perturbed gene expression across biological states. Unlike differentially expressed genes (DEGs) that capture changes in individual gene expression across conditions, CoVar focuses on identifying variational genes that undergo changes in their expression network interaction profiles, providing insights into changes in the regulatory dynamics, such as in disease pathogenesis. Subsequently, it finds core genes from among the nearest neighbors of these variational genes, which are central to the variational activity and influence the coordinated regulatory processes underlying the observed changes in gene expression. Through the analysis of simulated as well as yeast expression data perturbed by the deletion of the mitochondrial genome, we show that CoVar captures the intrinsic variationality and modularity in the expression data, identifying key driver genes not found through existing differential analysis methodologies.

Cellular geometry and epithelial-mesenchymal plasticity intersect with PIEZO1 in breast cancer cells.

Differences in shape can be a distinguishing feature between different cell types, but the shape of a cell can also be dynamic. Changes in cell shape are critical when cancer cells escape from the primary tumor and undergo major morphological changes that allow them to squeeze between endothelial cells, enter the vasculature, and metastasize to other areas of the body. A shift from rounded to spindly cellular geometry is a consequence of epithelial-mesenchymal plasticity, which is also associated with changes in gene expression, increased invasiveness, and therapeutic resistance. However, the consequences and functional impacts of cell shape changes and the mechanisms through which they occur are still poorly understood. Here, we demonstrate that altering the morphology of a cell produces a remodeling of calcium influx via the ion channel PIEZO1 and identify PIEZO1 as an inducer of features of epithelial-to-mesenchymal plasticity. Combining automated epifluorescence microscopy and a genetically encoded calcium indicator, we demonstrate that activation of the PIEZO1 force channel with the PIEZO1 agonist, YODA 1, induces features of epithelial-to-mesenchymal plasticity in breast cancer cells. These findings suggest that PIEZO1 is a critical point of convergence between shape-induced changes in cellular signaling and epithelial-mesenchymal plasticity in breast cancer cells.