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Epithelial-to-mesenchymal transition (EMT) is a cellular process important for numerous developmental processes, wound healing and cancer progression. In the context of heterogenous nature of cancer, EMT occurs at the forefront of tumor invasion, although the precise molecular mechanisms governing its spatial dynamics remain unclear. This study aimed to explore the diverse responses to EMT in monolayer cell cultures of MCF10A epithelial cell with induction of Zinc-finger E-box binding homeobox 1 (ZEB1), an EMT-inducing transcription factor. ZEB1-induced MCF10A cells exhibited EMT in space- and cell density-dependent manner. The expression of ZEB1 was modulated by the ubiquitin-proteasome pathway. We found that CDK4/6 and USP51 enhanced ZEB1 protein stability via deubiquitination. Moreover, suppressing USP51 and CDK4/6 activity attenuated cell migration, a characteristic of the mesenchymal phenotype, in ZEB1-induced MCF10A cells. Finally, we demonstrated that CDK4/6 kinase activity is important for cell migration as well as stabilizing ZEB1 in the mesenchymal breast cancer cell line MDA-MB-231. These insights could pave the way for developing more targeted and effective therapies targeting at ZEB1 and EMT in advanced cancers.

Mesenchymal-to-epithelial transition (MET) is an important step in cell reprogramming from fibroblasts (a cell type frequently used for this purpose) to various epithelial cell types. However, the mechanism underlying MET induction in fibroblasts remains to be understood. The present study aimed to identify the transcription factors (TFs) that efficiently induce MET in dermal fibroblasts. OVOL2 was identified as a potent inducer of key epithelial genes, and OVOL2 cooperatively enhanced MET induced by HNF1A, TP63, and KLF4, which are known reprogramming TFs to epithelial lineages. In TP63/KLF4-induced keratinocyte-like cell-state reprogramming, OVOL2 greatly facilitated the activation of epithelial and keratinocyte-specific genes. This was accompanied by enhanced changes in chromatin accessibility across the genome. Mechanistically, motif enrichment analysis revealed that the target loci of KLF4 and TP63 become accessible upon induction of TFs, whereas the OVOL2 target loci become inaccessible. This indicates that KLF4 and TP63 positively regulate keratinocyte-associated genes whereas OVOL2 suppresses fibroblast-associated genes. The exogenous expression of OVOL2 therefore disrupts fibroblast lineage identity and facilitates fibroblast cell reprogramming into epithelial lineages cooperatively with tissue-specific reprogramming factors. Identification of OVOL2 as an MET inducer and an epithelial reprogramming enhancer in fibroblasts provides new insights into cellular reprogramming improvement for future applications.

Owen Rackham, Jose Polo, Julian Gough and colleagues present a method, Mogrify, for predicting sets of transcription factors that can induce transdifferentiation between cell types. They show that Mogrify is able to predict known factors for published cell conversions and experimentally validate factors for two new conversions. Transdifferentiation, the process of converting from one cell type to another without going through a pluripotent state, has great promise for regenerative medicine. The identification of key transcription factors for reprogramming is currently limited by the cost of exhaustive experimental testing of plausible sets of factors, an approach that is inefficient and unscalable. Here we present a predictive system (Mogrify) that combines gene expression data with regulatory network information to predict the reprogramming factors necessary to induce cell conversion. We have applied Mogrify to 173 human cell types and 134 tissues, defining an atlas of cellular reprogramming. Mogrify correctly predicts the transcription factors used in known transdifferentiations. Furthermore, we validated two new transdifferentiations predicted by Mogrify. We provide a practical and efficient mechanism for systematically implementing novel cell conversions, facilitating the generalization of reprogramming of human cells. Predictions are made available to help rapidly further the field of cell conversion.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex and debilitating disease with no molecular diagnostics and no treatment options. To identify potential markers of this illness, we profiled 48 patients and 52 controls for standard laboratory tests, plasma metabolomics, blood immuno-phenotyping and transcriptomics, and fecal microbiome analysis. Here, we identified a set of 26 potential molecular markers that distinguished ME/CFS patients from healthy controls. Monocyte number, microbiome abundance, and lipoprotein profiles appeared to be the most informative markers. When we correlated these molecular changes to sleep and cognitive measurements of fatigue, we found that lipoprotein and microbiome profiles most closely correlated with sleep disruption while a different set of markers correlated with a cognitive parameter. Sleep, lipoprotein, and microbiome changes occur early during the course of illness suggesting that these markers can be examined in a larger cohort for potential biomarker application. Our study points to a cluster of sleep-related molecular changes as a prominent feature of ME/CFS in our Japanese cohort.

Familial platelet disorder with associated myeloid malignancies (FPDMM) is an autosomal dominant disease caused by heterozygous germline mutations in RUNX1 . It is characterized by thrombocytopenia, platelet dysfunction, and a predisposition to hematological malignancies. Although FPDMM is a precursor for diseases involving abnormal DNA methylation, the DNA methylation status in FPDMM remains unknown, largely due to a lack of animal models and challenges in obtaining patient-derived samples. Here, using genome editing techniques, we established two lines of human induced pluripotent stem cells (iPSCs) with different FPDMM-mimicking heterozygous RUNX1 mutations. These iPSCs showed defective differentiation of hematopoietic progenitor cells (HPCs) and megakaryocytes (Mks), consistent with FPDMM. The FPDMM-mimicking HPCs showed DNA methylation patterns distinct from those of wild-type HPCs, with hypermethylated regions showing the enrichment of ETS transcription factor (TF) motifs. We found that the expression of FLI1 , an ETS family member, was significantly downregulated in FPDMM-mimicking HPCs with a RUNX1 transactivation domain (TAD) mutation. We demonstrated that FLI1 promoted binding-site-directed DNA demethylation, and that overexpression of FLI1 restored their megakaryocytic differentiation efficiency and hypermethylation status. These findings suggest that FLI1 plays a crucial role in regulating DNA methylation and correcting defective megakaryocytic differentiation in FPDMM-mimicking HPCs with a RUNX1 TAD mutation.

Piero Carninci and colleagues report the discovery of a large class of noncoding RNAs, non-annotated stem cell transcripts (NASTs), which are implicated in the regulation of stem cell properties. The authors identify 8,873 mouse and 3,042 human NASTs and functionally validate 4 as having an important role in the maintenance of pluripotency. The importance of microRNAs and long noncoding RNAs in the regulation of pluripotency has been documented; however, the noncoding components of stem cell gene networks remain largely unknown. Here we investigate the role of noncoding RNAs in the pluripotent state, with particular emphasis on nuclear and retrotransposon-derived transcripts. We have performed deep profiling of the nuclear and cytoplasmic transcriptomes of human and mouse stem cells, identifying a class of previously undetected stem cell–specific transcripts. We show that long terminal repeat (LTR)-derived transcripts contribute extensively to the complexity of the stem cell nuclear transcriptome. Some LTR-derived transcripts are associated with enhancer regions and are likely to be involved in the maintenance of pluripotency.

Single-cell transcriptomic profiling is a powerful tool to explore cellular heterogeneity. However, most of these methods focus on the 3′-end of polyadenylated transcripts and provide only a partial view of the transcriptome. We introduce C1 CAGE, a method for the detection of transcript 5′-ends with an original sample multiplexing strategy in the C1 TM microfluidic system. We first quantifiy the performance of C1 CAGE and find it as accurate and sensitive as other methods in the C1 system. We then use it to profile promoter and enhancer activities in the cellular response to TGF-β of lung cancer cells and discover subpopulations of cells differing in their response. We also describe enhancer RNA dynamics revealing transcriptional bursts in subsets of cells with transcripts arising from either strand in a mutually exclusive manner, validated using single molecule fluorescence in situ hybridization. Single-cell transcriptomic profiling allows the exploration of cellular heterogeneity but commonly focuses on the 3′-end of the transcript. Here the authors introduce C1 CAGE, which detects the 5′ transcript end in a multiplexed microfluidic system.

Mycobacterium tuberculosis (Mtb) infection reveals complex and dynamic host-pathogen interactions, leading to host protection or pathogenesis. Using a unique transcriptome technology (CAGE), we investigated the promoter-based transcriptional landscape of IFNγ (M1) or IL-4/IL-13 (M2) stimulated macrophages during Mtb infection in a time-kinetic manner. Mtb infection widely and drastically altered macrophage-specific gene expression, which is far larger than that of M1 or M2 activations. Gene Ontology enrichment analysis for Mtb-induced differentially expressed genes revealed various terms, related to host-protection and inflammation, enriched in up-regulated genes. On the other hand, terms related to dis-regulation of cellular functions were enriched in down-regulated genes. Differential expression analysis revealed known as well as novel transcription factor genes in Mtb infection, many of them significantly down-regulated. IFNγ or IL-4/IL-13 pre-stimulation induce additional differentially expressed genes in Mtb-infected macrophages. Cluster analysis uncovered significant numbers, prolonging their expressional changes. Furthermore, Mtb infection augmented cytokine-mediated M1 and M2 pre-activations. In addition, we identified unique transcriptional features of Mtb-mediated differentially expressed lncRNAs. In summary we provide a comprehensive in depth gene expression/regulation profile in Mtb-infected macrophages, an important step forward for a better understanding of host-pathogen interaction dynamics in Mtb infection.

Background Tuberculosis is a life-threatening infectious disease caused by Mycobacterium tuberculosis ( M.tb ). M.tb subverts host immune responses to build a favourable niche and survive inside of host macrophages. Macrophages can control or eliminate the infection, if acquire appropriate functional phenotypes. Transcriptional regulation is a key process that governs the activation and maintenance of these phenotypes. Among the factors orchestrating transcriptional regulation during M.tb infection, transcriptional enhancers still remain unexplored. Results We analysed transcribed enhancers in M.tb -infected mouse bone marrow-derived macrophages. We established a link between known M.tb -responsive transcription factors and transcriptional activation of enhancers and their target genes. Our data suggest that enhancers might drive macrophage response via transcriptional activation of key immune genes, such as Tnf , Tnfrsf1b , Irg1 , Hilpda , Ccl3 , and Ccl4 . We report enhancers acquiring transcription de novo upon infection. Finally, we link highly transcriptionally induced enhancers to activation of genes with previously unappreciated roles in M.tb infection, such as Fbxl3 , Tapt1 , Edn1 , and Hivep1 . Conclusions Our findings suggest the importance of macrophage host transcriptional enhancers during M.tb infection. Our study extends current knowledge of the regulation of macrophage responses to M.tb infection and provides a basis for future functional studies on enhancer-gene interactions in this process.

Background Transcription factor (TF)-dependent DNA demethylation is associated with generation of specific DNA methylation profiles in normal cellular development and disease, although only a small fraction of TFs are known to promote DNA demethylation. Results Here, we systematically predicted which TFs have DNA-demethylation-promoting activity. Experiments with deletion mutants of the TFs RUNX1 and SPI1 revealed that this activity is associated with a relatively long intrinsically disordered region (IDR). Examination of the IDRs from eight TFs previously confirmed to have such activity revealed that at least one IDR was active in each TF. We constructed a Random Forest classifier based on 25 numeric physicochemical features extracted from length-controlled 26 positive (active) and 32 negative (inactive) IDRs. Four key features— aromaticity, aliphatic index, fractional charge ratio, and side chain hydrophobic density—were identified as the most informative contributors to prediction of positive IDRs. A model based on these features achieved an area under the receiver operating characteristic curve of 0.84, with an optimized decision threshold of 0.303. Applying this model to all TFs, we predicted 959 of 2364 IDRs to be positive, corresponding to 825 of 1308 TFs. The model correctly identified all of 14 previously validated positive TFs. The predicted positive TFs showed significant enrichment of Gene Ontology terms related to morphogenesis and development and may be clinically relevant to certain cancer types. Conclusion The developed model with high predictive performance and the predicted TFs with DNA-demethylation-promoting activity will be useful for further analysis of TFs involved in generation of DNA methylation profiles in normal cell development and disease.