Stem cells undergo dynamic changes in response to injury to regenerate lost cells. However, the identity of transitional states and the mechanisms that drive their trajectories remain understudied. Using lung organoids, multiple in vivo repair models, single-cell transcriptomics, and lineage tracing, we find that alveolar type-2 epithelial cells undergoing differentiation into type-1 cells acquire pre-alveolar type-1 transitional cell state (PATS) en route to terminal maturation. Transitional cells undergo extensive stretching during differentiation, making them vulnerable to DNA damage. PATS show an enrichment of TP53, TGFβ, DNA-damage response signalling, and cellular senescence. Gain and loss of function and genomic binding assays revealed a direct transcriptional control of PATS by TP53 signalling. Notably, PATS-like cells were accumulated in human fibrotic lungs, suggesting persistence of the transitional state in fibrosis. Our study thus
Microbial electrosynthesis, a process in which microorganisms use electrons derived from electrodes to reduce carbon dioxide to multicarbon, extracellular organic compounds, is a potential strategy for capturing electrical energy in carbon-carbon bonds of readily stored and easily distributed products, such as transportation fuels. To date, only one organism, the acetogen Sporomusa ovata, has been shown to be capable of electrosynthesis. The purpose of this study was to determine if a wider range of microorganisms is capable of this process. Several other acetogenic bacteria, including two other Sporomusa species, Clostridium ljungdahlii, Clostridium aceticum, and Moorella thermoacetica, consumed current with the production of organic acids. In general acetate was the primary product, but 2-oxobutyrate and formate also were formed, with 2-oxobutyrate being the predominant identified product of electrosynthesis by C. aceticum. S. sphaeroides, C. ljungdahlii, and M. thermoacetica had high (>80%) efficiencies of electrons consumed and recovered in identified products. The acetogen Acetobacterium woodii was unable to consume current. These results expand the known range of microorganisms capable of electrosynthesis, providing multiple options for the further optimization of this process.
SUMMARY The Tead family transcription factors are the major intracellular mediators of the Hippo-Yap pathway. Despite the importance of Hippo signaling in tumorigenesis, Tead-dependent downstream oncogenic programs and target genes in cancer cells remain poorly understood. Here we characterize Tead4-mediated transcriptional networks in a diverse range of cancer cells, including neuroblastoma, colorectal, lung, and endometrial carcinomas. By intersecting genome-wide chromatin occupancy analyses of Tead4, JunD and Fra1/2, we find that Tead4 cooperates with AP1 transcription factors to coordinate target gene transcription. We find that Tead-AP1 interaction is JNK independent, but engages the SRC1-3 coactivators to promote downstream transcription. Furthermore we show that Tead-AP1 cooperation regulates the activity of the Dock-Rac/CDC42 module and drives the expression of a unique core set of target genes, thereby directing cell migration and invasion. Together, our data unveil a critical regulatory mechanism underlying Tead- and AP1-controlled transcriptional and functional outputs in cancer cells.
SUMMARY Most colorectal cancers (CRCs) containing activated BRAF (BRAF[V600E]) have a CpG island methylator phenotype (CIMP) characterized by aberrant hypermethylation of many genes, including the mismatch repair gene MLH1. MLH1 silencing results in microsatellite instability and a hypermutable phenotype. Through an RNA interference screen, here we identify the transcriptional repressor MAFG as the pivotal factor required for MLH1 silencing and CIMP in CRCs containing BRAF(V600E). In BRAF-positive human CRC cell lines and tumors, MAFG is bound at the promoters of MLH1 and other CIMP genes, and recruits a corepressor complex that includes its heterodimeric partner BACH1, the chromatin remodeling factor CHD8, and the DNA methyltransferase DNMT3B, resulting in hypermethylation and transcriptional silencing. BRAF(V600E) increases BRAF/MEK/ERK signaling resulting in phosphorylation and elevated levels of MAFG, which drives DNA binding. Analysis of transcriptionally silenced CIMP genes in KRAS-positive CRCs indicates that different oncoproteins direct the assembly of distinct repressor complexes on common promoters.
BackgroundATAC-seq (Assays for Transposase-Accessible Chromatin using sequencing) is a recently developed technique for genome-wide analysis of chromatin accessibility. Compared to earlier methods for assaying chromatin accessibility, ATAC-seq is faster and easier to perform, does not require cross-linking, has higher signal to noise ratio, and can be performed on small cell numbers. However, to ensure a successful ATAC-seq experiment, step-by-step quality assurance processes, including both wet lab quality control and in silico quality assessment, are essential. While several tools have been developed or adopted for assessing read quality, identifying nucleosome occupancy and accessible regions from ATAC-seq data, none of the tools provide a comprehensive set of functionalities for preprocessing and quality assessment of aligned ATAC-seq datasets.ResultsWe have developed a Bioconductor package, ATACseqQC, for easily generating various diagnostic plots to help researchers quickly assess the quality of their ATAC-seq data. In addition, this package contains functions to preprocess aligned ATAC-seq data for subsequent peak calling. Here we demonstrate the utilities of our package using 25 publicly available ATAC-seq datasets from four studies. We also provide guidelines on what the diagnostic plots should look like for an ideal ATAC-seq dataset.ConclusionsThis software package has been used successfully for preprocessing and assessing several in-house and public ATAC-seq datasets. Diagnostic plots generated by this package will facilitate the quality assessment of ATAC-seq data, and help researchers to evaluate their own ATAC-seq experiments as well as select high-quality ATAC-seq datasets from public repositories such as GEO to avoid generating hypotheses or drawing conclusions from low-quality ATAC-seq experiments. The software, source code, and documentation are freely available as a Bioconductor package at https://bioconductor.org/packages/release/bioc/html/ATACseqQC.html.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4559-3) contains supplementary material, which is available to authorized users.
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