RAE-1 ligands for the NKG2D receptor are regulated by E2F transcription factors, which control cell cycle entry.

The NKG2D stimulatory receptor expressed by natural killer cells and T cell subsets recognizes cell surface ligands that are induced on transformed and infected cells and facilitate immune rejection of tumor cells. We demonstrate that expression of retinoic acid early inducible gene 1 (RAE-1) family NKG2D ligands in cancer cell lines and proliferating normal cells is coupled directly to cell cycle regulation. Raet1 genes are directly transcriptionally activated by E2F family transcription factors, which play a central role in regulating cell cycle entry. Induction of RAE-1 occurred in primary cell cultures, embryonic brain cells in vivo, and cells in healing skin wounds and, accordingly, wound healing was delayed in mice lacking NKG2D. Transcriptional activation by E2Fs is likely coordinated with posttranscriptional regulation by other stress responses. These findings suggest that cellular proliferation, as occurs in cancer cells but also other pathological conditions, is a key signal tied to immune reactions mediated by NKG2D-bearing lymphocytes

Transcriptome changes and cAMP oscillations in an archaeal cell cycle

Background The cell cycle of all organisms includes mass increase by a factor of two, replication of the genetic material, segregation of the genome to different parts of the cell, and cell division into two daughter cells. It is tightly regulated and typically includes cell cycle-specific oscillations of the levels of transcripts, proteins, protein modifications, and signaling molecules. Until now cell cycle-specific transcriptome changes have been described for four eukaryotic species ranging from yeast to human, but only for two prokaryotic species. Similarly, oscillations of small signaling molecules have been identified in very few eukaryotic species, but not in any prokaryote. Results A synchronization procedure for the archaeon Halobacterium salinarum was optimized, so that nearly 100% of all cells divide in a time interval that is 1/4th of the generation time of exponentially growing cells. The method was used to characterize cell cycle-dependent transcriptome changes using a genome-wide DNA microarray. The transcript levels of 87 genes were found to be cell cycle-regulated, corresponding to 3% of all genes. They could be clustered into seven groups with different transcript level profiles. Cluster-specific sequence motifs were detected around the start of the genes that are predicted to be involved in cell cycle-specific transcriptional regulation. Notably, many cell cycle genes that have oscillating transcript levels in eukaryotes are not regulated on the transcriptional level in H. salinarum. Synchronized cultures were also used to identify putative small signaling molecules. H. salinarum was found to contain a basal cAMP concentration of 200 uM, considerably higher than that of yeast. The cAMP concentration is shortly induced directly prior to and after cell division, and thus cAMP probably is an important signal for cell cycle progression. Conclusions The analysis of cell cycle-specific transcriptome changes of H. salinarum allowed to identify a strategy of transcript level regulation that is different from all previously characterized species. The transcript levels of only 3% of all genes are regulated, a fraction that is considerably lower than has been reported for four eukaryotic species (6% - 28%) and for the bacterium C. crescentus (19%). It was shown that cAMP is present in significant concentrations in an archaeon, and the phylogenetic profile of the adenylate cyclase indicates that this signaling molecule is widely distributed in archaea. The occurrence of cell cycle-dependent oscillations of the cAMP concentration in an archaeon and in several eukaryotic species indicates that cAMP level changes might be a phylogenetically old signal for cell cycle progression

Group SCAD Regression Analysis for Microarray Time Course Gene Expression Data

Since many important biological systems or processes are dynamic systems, it is important to study the gene expression patterns over time in a genomic scale in order to capture the dynamic behavior of gene expression. Microarray technologies have made it possible to measure the gene expression levels of essentially all the genes during a given biological process. In order to determine the transcriptional factors involved in gene regulation during a given biological process, we propose to develop a functional response model with varying coefficients in order to model the transcriptional effects on gene expression levels and to develop a group smoothly clipped absolute deviation (SCAD) regression procedure for selecting the transcriptional factors with varying coefficients that are involved in gene regulation during a biological process. Simulation studies indicated that such a procedure is quite effective in selecting the relevant variables with time-varying coefficients and in estimating the coefficients. Application to the yeast cell cycle microarray time course gene expression data set identified 19 of the 21 known transcriptional factors related to the cell cycle process. In addition, we have identified another 52 TFs that also have periodic transcriptional effects on gene expression during the cell cycle process. Compared to simple linear regression analysis at each time point, our procedure identified more known cell cycle related transcriptional factors. The proposed group SCAD regression procedure is very effective for identifying variables with time-varying coefficients, in particular, for identifying the transcriptional factors that are related to gene expression over time. By identifying the transcriptional factors that are related to gene expression variations over time, the procedure can potentially provide more insight into the gene regulatory networks

A bioinformatic analysis identifies circadian expression of splicing factors and time-dependent alternative splicing events in the HD-MY-Z cell line

The circadian clock regulates key cellular processes and its dysregulation is associated to several pathologies including cancer. Although the transcriptional regulation of gene expression by the clock machinery is well described, the role of the clock in the regulation of post-transcriptional processes, including splicing, remains poorly understood. In the present work, we investigated the putative interplay between the circadian clock and splicing in a cancer context. For this, we applied a computational pipeline to identify oscillating genes and alternatively spliced transcripts in time-course high-throughput data sets from normal cells and tissues, and cancer cell lines. We investigated the temporal phenotype of clock-controlled genes and splicing factors, and evaluated their impact in alternative splice patterns in the Hodgkin Lymphoma cell line HD-MY-Z. Our data points to a connection between clock-controlled genes and splicing factors, which correlates with temporal alternative splicing in several genes in the HD-MY-Z cell line. These include the genes DPYD, SS18, VIPR1 and IRF4, involved in metabolism, cell cycle, apoptosis and proliferation. Our results highlight a role for the clock as a temporal regulator of alternative splicing, which may impact malignancy in this cellular model

Fluorescence activated cell sorting followed by small RNA sequencing reveals stable microRNA expression during cell cycle progression.

BACKGROUND: Previously, drug-based synchronization procedures were used for characterizing the cell cycle dependent transcriptional program. However, these synchronization methods result in growth imbalance and alteration of the cell cycle machinery. DNA content-based fluorescence activated cell sorting (FACS) is able to sort the different cell cycle phases without perturbing the cell cycle. MiRNAs are key transcriptional regulators of the cell cycle, however, their expression dynamics during cell cycle has not been explored. METHODS: Following an optimized FACS, a complex initiative of high throughput platforms (microarray, Taqman Low Density Array, small RNA sequencing) were performed to study gene and miRNA expression profiles of cell cycle sorted human cells originating from different tissues. Validation of high throughput data was performed using quantitative real time PCR. Protein expression was detected by Western blot. Complex statistics and pathway analysis were also applied. RESULTS: Beyond confirming the previously described cell cycle transcriptional program, cell cycle dependently expressed genes showed a higher expression independently from the cell cycle phase and a lower amplitude of dynamic changes in cancer cells as compared to untransformed fibroblasts. Contrary to mRNA changes, miRNA expression was stable throughout the cell cycle. CONCLUSIONS: Cell cycle sorting is a synchronization-free method for the proper analysis of cell cycle dynamics. Altered dynamic expression of universal cell cycle genes in cancer cells reflects the transformed cell cycle machinery. Stable miRNA expression during cell cycle progression may suggest that dynamical miRNA-dependent regulation may be of less importance in short term regulations during the cell cycle

Common CHD8 Genomic Targets Contrast With Model-Specific Transcriptional Impacts of CHD8 Haploinsufficiency.

The packaging of DNA into chromatin determines the transcriptional potential of cells and is central to eukaryotic gene regulation. Case sequencing studies have revealed mutations to proteins that regulate chromatin state, known as chromatin remodeling factors, with causal roles in neurodevelopmental disorders. Chromodomain helicase DNA binding protein 8 (CHD8) encodes a chromatin remodeling factor with among the highest de novo loss-of-function mutation rates in patients with autism spectrum disorder (ASD). However, mechanisms associated with CHD8 pathology have yet to be elucidated. We analyzed published transcriptomic data across CHD8 in vitro and in vivo knockdown and knockout models and CHD8 binding across published ChIP-seq datasets to identify convergent mechanisms of gene regulation by CHD8. Differentially expressed genes (DEGs) across models varied, but overlap was observed between downregulated genes involved in neuronal development and function, cell cycle, chromatin dynamics, and RNA processing, and between upregulated genes involved in metabolism and immune response. Considering the variability in transcriptional changes and the cells and tissues represented across ChIP-seq analysis, we found a surprisingly consistent set of high-affinity CHD8 genomic interactions. CHD8 was enriched near promoters of genes involved in basic cell functions and gene regulation. Overlap between high-affinity CHD8 targets and DEGs shows that reduced dosage of CHD8 directly relates to decreased expression of cell cycle, chromatin organization, and RNA processing genes, but only in a subset of studies. This meta-analysis verifies CHD8 as a master regulator of gene expression and reveals a consistent set of high-affinity CHD8 targets across human, mouse, and rat in vivo and in vitro studies. These conserved regulatory targets include many genes that are also implicated in ASD. Our findings suggest a model where perturbation to dosage-sensitive CHD8 genomic interactions with a highly-conserved set of regulatory targets leads to model-specific downstream transcriptional impacts

Tissue-specific regulation of cyclin E transcription during Drosophila melanogaster embryogenesis

Cyclin E is an essential regulator of S phase entry. We have previously shown that transcriptional regulation of the gene that encodes Drosophila cyclin E, DmcycE, plays an important role in the control of the G(1) to S phase transition during development. We report here the first comprehensive analysis of the transcriptional regulation of a G(1 )phase cell cycle regulatory gene during embryogenesis. Analysis of deficiencies, a genomic transformant and reporter gene constructs revealed that DmcycE transcription is controlled by a large and complex cis-regulatory region containing tissue- and stage-specific components. Separate regulatory elements for transcription in epidermal cells during cell cycles 14-16, central nervous system cells and peripheral nervous system cells were found. An additional cis-regulatory element drives transcription in thoracic epidermal cells that undergo a 17th cell cycle when other epidermal cells have arrested in G(1 )phase prior to terminal differentiation. The complexity of DmcycE transcriptional regulation argues against a model in which DmcycE transcription is regulated simply and solely by G(1) to S phase transcription regulators such as RB, E2F and DP. Rather, our study demonstrates that tissue-specific transcriptional regulatory mechanisms are important components of the control of cyclin E transcription and thus of cell proliferation in metazoans.Lynn Jones, Helena Richardson and Robert Sain

Mammalian gene expression variability is explained by underlying cell state.

Gene expression variability in mammalian systems plays an important role in physiological and pathophysiological conditions. This variability can come from differential regulation related to cell state (extrinsic) and allele-specific transcriptional bursting (intrinsic). Yet, the relative contribution of these two distinct sources is unknown. Here, we exploit the qualitative difference in the patterns of covariance between these two sources to quantify their relative contributions to expression variance in mammalian cells. Using multiplexed error robust RNA fluorescent in situ hybridization (MERFISH), we measured the multivariate gene expression distribution of 150 genes related to Ca2+ signaling coupled with the dynamic Ca2+ response of live cells to ATP. We show that after controlling for cellular phenotypic states such as size, cell cycle stage, and Ca2+ response to ATP, the remaining variability is effectively at the Poisson limit for most genes. These findings demonstrate that the majority of expression variability results from cell state differences and that the contribution of transcriptional bursting is relatively minimal

Acanthamoeba induces cell-cycle arrest in host cells

Acanthamoeba can cause fatal granulomatous amoebic encephalitis (GAE) and eye keratitis. However, the pathogenesis and pathophysiology of these emerging diseases remain unclear. In this study, the effects of Acanthamoeba on the host cell cycle using human brain microvascular endothelial cells (HBMEC) and human corneal epithelial cells (HCEC) were determined. Two isolates of Acanthamoeba belonging to the T1 genotype (GAE isolate) and T4 genotype (keratitis isolate) were used, which showed severe cytotoxicity on HBMEC and HCEC, respectively. No tissue specificity was observed in their ability to exhibit binding to the host cells. To determine the effects of Acanthamoeba on the host cell cycle, a cell-cycle-specific gene array was used. This screened for 96 genes specific for host cell-cycle regulation. It was observed that Acanthamoeba inhibited expression of genes encoding cyclins F and G1 and cyclin-dependent kinase 6, which are proteins important for cell-cycle progression. Moreover, upregulation was observed of the expression of genes such as GADD45A and p130 Rb, associated with cell-cycle arrest, indicating cell-cycle inhibition. Next, the effect of Acanthamoeba on retinoblastoma protein (pRb) phosphorylation was determined. pRb is a potent inhibitor of G1-to-S cell-cycle progression; however, its function is inhibited upon phosphorylation, allowing progression into S phase. Western blotting revealed that Acanthamoeba abolished pRb phosphorylation leading to cell-cycle arrest at the G1-to-S transition. Taken together, these studies demonstrated for the first time that Acanthamoeba inhibits the host cell cycle at the transcriptional level, as well as by modulating pRb phosphorylation using host cell-signalling mechanisms. A complete understanding of Acanthamoeba–host cell interactions may help in developing novel strategies to treat Acanthamoeba infections