The number of inflammatory gastroenteritis outbreaks due to the food-borne pathogen Vibrio parahaemolyticus is rising sharply worldwide and in the United States in particular. Here we report the complete, annotated genome sequence of the prepandemic V. parahaemolyticus strain BB22OP and make some initial comparisons to the complete genome sequence for pandemic strain RIMD2210633.

Light-entrained circadian clocks confer rhythmic dynamics of cellular and molecular activities to animals and plants. These intrinsic clocks allow stable anticipations to light-dark (diel) cycles. Many genes in the model plant Arabidopsis thaliana are regulated by diel cycles via pathways independent of the clock, suggesting that the integration of circadian and light signals is important for the fitness of plants. Previous studies of light-clock signal integrations have focused on moderate phase adjustment of the two signals. However, dynamical features of integrations across a broad range of phases remain elusive. Phosphorylation of ribosomal protein of the small subunit 6 (eS6), a ubiquitous post-translational modification across kingdoms, is influenced by the circadian clock and the light-dark (diel) cycle in an opposite manner. To understand this striking phenomenon and its underlying information processing capabilities, we built a mathematical model for the eS6 phosphorylation (eS6-P) control circuit. We found that the dynamics of eS6-P can be explained by a feedforward circuit with inputs from both circadian and diel cycles. Furthermore, the early day response of this circuit with dual rhythmic inputs is sensitive to the changes in daylength, including both transient and gradual changes observed in realistic light intervals across a year, because of weather and seasons. By analyzing published gene expression data, we found that the dynamics produced by the eS6-P control circuit can be observed in the expression profiles of a large number of genes. Our work provides mechanistic insights into the complex dynamics of a ribosomal protein, and it proposes a previously underappreciated function of the circadian clock, which not only prepares organisms for normal diel cycles but also helps to detect both transient and seasonal changes with a predictive power.

Periodic gene expression dynamics are key to cell and organism physiology. Studies of oscillatory expression have focused on networks with intuitive regulatory negative feedback loops, leaving unknown whether other common biochemical reactions can produce oscillations. Oscillation and noise have been proposed to support mammalian progenitor cells' capacity to restore heterogenous, multimodal expression from extreme subpopulations, but underlying networks and specific roles of noise remained elusive. We use mass-action-based models to show that regulated RNA degradation involving as few as two RNA species-applicable to nearly half of human protein-coding genes-can generate sustained oscillations without explicit feedback. Diverging oscillation periods synergize with noise to robustly restore cell populations' bimodal expression on timescales of days. The global bifurcation organizing this divergence relies on an oscillator and bistable switch which cannot be decomposed into two structural modules. Our work reveals surprisingly rich dynamics of post-transcriptional reactions and a potentially widespread mechanism underlying development, tissue regeneration, and cancer cell heterogeneity.

Epithelial-to-mesenchymal transition (EMT), a fundamental transdifferentiation process in development, produces diverse phenotypes in different physiological or pathological conditions. Many genes involved in EMT have been identified to date, but mechanisms contributing to the phenotypic diversity and those governing the coupling between the dynamics of epithelial (E) genes and that of the mesenchymal (M) genes are unclear. In this study, we employed combinatorial perturbations to mammary epithelial cells to induce a series of EMT phenotypes by manipulating two essential EMT-inducing elements, namely TGF-β and ZEB1. By measuring transcriptional changes in more than 700 E-genes and M-genes, we discovered that the M-genes exhibit a significant diversity in their dependency to these regulatory elements and identified three groups of M-genes that are controlled by different regulatory circuits. Notably, functional differences were detected among the M-gene clusters in motility regulation and in survival of breast cancer patients. We computationally predicted and experimentally confirmed that the reciprocity and reversibility of EMT are jointly regulated by ZEB1. Our integrative analysis reveals the key roles of ZEB1 in coordinating the dynamics of a large number of genes during EMT, and it provides new insights into the mechanisms for the diversity of EMT phenotypes.

Dysregulation of the epidermal growth factor receptor (EGFR) promotes cancer cell growth, invasion and metastasis. However, its relevant downstream effectors are still limited. Here, we show that EGFR promotes breast tumor growth and metastasis by downregulating the tumor suppressor micoRNA-338-3p (miR-338-3p) and activating the EYA2 (EYA transcriptional coactivator and phosphatase 2) oncoprotein. EGFR represses miR-338-3p expression largely through HIF1α transcription factor. miR-338-3p inhibits EYA2 expression by binding to the 3'-untranslated region of EYA2. EGFR increases EYA2 expression via HIF1α repression of miR-338-3p. Through the miR-338-3p/EYA2 pathway, EGFR increases breast cancer cell growth, epithelial-to-mesenchymal transition, migration, invasion and lung metastasis in vitro and in a allograft tumor mouse model in vivo. In breast cancer patients, miR-338-3p expression negatively correlates with the expression of EGFR and EYA2, EGFR status positively associates with EYA2 expression, and miR-338-3p and EYA2 predict breast cancer lung metastasis when expressed in primary breast cancers. These data suggest that the miR-338-3p/EYA2 axis contributes to EGFR-mediated tumor growth and lung metastasis and that miR-338-3p activation or EYA2 inhibition or combination therapy targeting EGFR/miR-338-3p/EYA2 axis may be a promising way to treat patients with metastatic cancer.

Epithelial-mesenchymal transition (EMT), the conversion between rigid epithelial cells and motile mesenchymal cells, is a reversible cellular process involved in tumorigenesis, metastasis, and chemoresistance. Numerous studies have found that several types of tumor cells show a high degree of cell-to-cell heterogeneity in terms of their gene expression signatures and cellular phenotypes related to EMT. Recently, the prevalence and importance of partial or intermediate EMT states have been reported. It is unclear, however, whether there is a general pattern of cancer cell distribution in terms of the overall expression of epithelial-related genes and mesenchymal-related genes, and how this distribution is related to EMT process in normal cells. In this study, we performed integrative transcriptomic analysis that combines cancer cell transcriptomes, time course data of EMT in non-tumorigenic epithelial cells, and epithelial cells with perturbations of key EMT factors. Our statistical analysis shows that cancer cells are widely distributed in the EMT spectrum, and the majority of these cells can be described by an EMT path that connects the epithelial and the mesenchymal states via a hybrid expression region in which both epithelial genes and mesenchymal genes are highly expressed overall. We found that key patterns of this EMT path are observed in EMT progression in non-tumorigenic cells and that transcription factor ZEB1 plays a key role in defining this EMT path via diverse gene regulatory circuits connecting to epithelial genes. We performed Gene Set Variation Analysis to show that the cancer cells at hybrid EMT states also possess hybrid cellular phenotypes with both high migratory and high proliferative potentials. Our results reveal critical patterns of cancer cells in the EMT spectrum and their relationship to the EMT process in normal cells, and provide insights into the mechanistic basis of cancer cell heterogeneity and plasticity.

Tumour radiotherapy resistance involves the cell cycle pathway. CDC25 phosphatases are key cell cycle regulators. However, how CDC25 activity is precisely controlled remains largely unknown. Here, we show that LIM domain-containing proteins, such as FHL1, increase inhibitory CDC25 phosphorylation by forming a complex with CHK2 and CDC25, and sequester CDC25 in the cytoplasm by forming another complex with 14-3-3 and CDC25, resulting in increased radioresistance in cancer cells. FHL1 expression, induced by ionizing irradiation in a SP1- and MLL1-dependent manner, positively correlates with radioresistance in cancer patients. We identify a cell-penetrating 11 amino-acid motif within LIM domains (eLIM) that is sufficient for binding CHK2 and CDC25, reducing the CHK2-CDC25 and CDC25-14-3-3 interaction and enhancing CDC25 activity and cancer radiosensitivity accompanied by mitotic catastrophe and apoptosis. Our results provide novel insight into molecular mechanisms underlying CDC25 activity regulation. LIM protein inhibition or use of eLIM may be new strategies for improving tumour radiosensitivity.

The initial rostrocaudal patterning of the neural tube leads to differential expression of Hox genes that contribute to the specification of motor neuron (MN) subtype identity. Although several 3' Hox mRNAs are expressed in progenitors in a noisy manner, these Hox proteins are not expressed in the progenitors and only become detectable in postmitotic MNs. MicroRNA biogenesis impairment leads to precocious expression and propagates the noise of Hoxa5 at the protein level, resulting in an imprecise Hoxa5-Hoxc8 boundary. Here we uncover, using in silico simulation, two feed-forward Hox-miRNA loops accounting for the precocious and noisy Hoxa5 expression, as well as an ill-defined boundary phenotype in Dicer mutants. Finally, we identify mir-27 as a major regulator coordinating the temporal delay and spatial boundary of Hox protein expression. Our results provide a novel trans Hox-miRNA circuit filtering transcription noise and controlling the timing of protein expression to confer robust individual MN identity.

The conserved GTPase Cdc42 is a major regulator of polarized growth in most eukaryotes. Cdc42 periodically cycles between active and inactive states at sites of polarized growth. These periodic cycles are caused by positive feedback and time-delayed negative feedback loops. In the bipolar yeast S. pombe, both growing ends must regulate Cdc42 activity. At each cell end, Cdc42 activity recruits the Pak1 kinase which prevents further Cdc42 activation thus establishing negative feedback. It is unclear how Cdc42 activation returns to the end after Pak1-dependent negative feedback. Using genetic and chemical perturbations, we find that disrupting branched actin-mediated endocytosis disables Cdc42 reactivation at the cell ends. With our experimental data and mathematical models, we show that endocytosis-dependent Pak1 removal from the cell ends allows the Cdc42 activator Scd1 to return to that end to enable reactivation of Cdc42. Moreover, we show that Pak1 elicits its own removal via activation of endocytosis. In agreement with these observations, our model and experimental data show that in each oscillatory cycle, Cdc42 activation increases followed by an increase in Pak1 recruitment at that end. These findings provide a deeper insight into the self-organization of Cdc42 regulation and reveal previously unknown feedback with endocytosis in the establishment of cell polarity.

This study aimed to investigate the correlation of long noncoding RNA zinc finger antisense 1 (lncRNA ZFAS1) expression with disease risk, disease severity and inflammatory cytokines levels in lumbar disc degeneration (LDD) patients.83 LDD patients underwent surgery and 28 traumatized, non-LDD patients underwent lumbar disc surgery (controls) were consecutively enrolled in this case-control study. Lumbar disc tissue was obtained during surgery and herniated nucleus pulposus (HNP) was isolated to detect lncRNA ZFAS1 expression and inflammatory cytokines mRNA levels by RT-qPCR, and determine protein levels of inflammatory cytokines by western blot.HNP lncRNA ZFAS1 expression in LDD patients was up-regulated compared with controls (P < .001), and receiver operating characteristic (ROC) curve showed lncRNA ZFAS1 expression disclosed a good predictive value for LDD risk with area under curve (AUC) 0.753 (95% CI 0.646-0.859). And after adjustment by age, gender and body mass index (BMI), lncRNA ZFAS1 (P = .017) remained to be an independent predictive factor for higher LDD risk. In addition, lncRNA ZFAS1 expression was positively associated with Modified Pfirrmann Grade (P = .015). As to inflammatory cytokines, lncRNA ZFAS1 expression was observed to be positively correlated with TNF-α (P = .002), IL-1β (P = .007) and IL-6 (P = .015) mRNAs expressions while reversely associated with IL-10 mRNA level (P = .014); and lncRNA ZFAS1 expression was also positively correlated with protein levels of TNF-α (P = .038) and IL-6 (P = .027) while reversely associated with IL-10 protein expression (P = .039).lncRNA ZFAS1 expression associates with increased risk, elevated disease severity and higher inflammatory cytokines levels in LDD patients.

Epithelial-mesenchymal transition (EMT) is a cellular process involved in development and disease progression. Intermediate EMT states were observed in tumors and fibrotic tissues, but previous in vitro studies focused on time-dependent responses with single doses of signals; it was unclear whether single-cell transcriptomes support stable intermediates observed in diseases. Here, we performed single-cell RNA-sequencing with human mammary epithelial cells treated with multiple doses of TGF-β. We found that dose-dependent EMT harbors multiple intermediate states at nearly steady state. Comparisons of dose- and time-dependent EMT transcriptomes revealed that the dose-dependent data enable higher sensitivity to detect genes associated with EMT. We identified cell clusters unique to time-dependent EMT, reflecting cells en route to stable states. Combining dose- and time-dependent cell clusters gave rise to accurate prognosis for cancer patients. Our transcriptomic data and analyses uncover a stable EMT continuum at the single-cell resolution, and complementary information of two types of single-cell experiments.

Large-scale transcriptome data, such as single-cell RNA-sequencing data, have provided unprecedented resources for studying biological processes at the systems level. Numerous dimensionality reduction methods have been developed to visualize and analyze these transcriptome data. In addition, several existing methods allow inference of functional variations among samples using gene sets with known biological functions. However, it remains challenging to analyze transcriptomes with reduced dimensions that are interpretable in terms of dimensions' directionalities, transferrable to new data, and directly expose the contribution or association of individual genes. In this study, we used gene set non-negative principal component analysis (gsPCA) and non-negative matrix factorization (gsNMF) to analyze large-scale transcriptome datasets. We found that these methods provide low-dimensional information about the progression of biological processes in a quantitative manner, and their performances are comparable to existing functional variation analysis methods in terms of distinguishing multiple cell states and samples from multiple conditions. Remarkably, upon training with a subset of data, these methods allow predictions of locations in the functional space using data from experimental conditions that are not exposed to the models. Specifically, our models predicted the extent of progression and reversion for cells in the epithelial-mesenchymal transition (EMT) continuum. These methods revealed conserved EMT program among multiple types of single cells and tumor samples. Finally, we demonstrate this approach is broadly applicable to data and gene sets beyond EMT and provide several recommendations on the choice between the two linear methods and the optimal algorithmic parameters. Our methods show that simple constrained matrix decomposition can produce to low-dimensional information in functionally interpretable and transferrable space, and can be widely useful for analyzing large-scale transcriptome data.

Feedback loops in gene regulatory networks play pivotal roles in governing functional dynamics of cells. Systems approaches demonstrated characteristic dynamical features, including multistability and oscillation, of positive and negative feedback loops. Recent experiments and theories have implicated highly interconnected feedback loops (high-feedback loops) in additional nonintuitive functions, such as controlling cell differentiation rate and multistep cell lineage progression. However, it remains challenging to identify and visualize high-feedback loops in complex gene regulatory networks due to the myriad of ways in which the loops can be combined. Furthermore, it is unclear whether the high-feedback loop structures with these potential functions are widespread in biological systems. Finally, it remains challenging to understand diverse dynamical features, such as high-order multistability and oscillation, generated by individual networks containing high-feedback loops. To address these problems, we developed HiLoop, a toolkit that enables discovery, visualization, and analysis of several types of high-feedback loops in large biological networks.

Hematopoietic pre-B cell leukemia transcription factor interacting protein (HPIP) has been shown to play an important role in the development and progression of some cancers. However, the role of HPIP in gastric cancer (GC) is unclear. Here, we show that HPIP is upregulated in most GC patients and promotes GC cell proliferation, migration, and invasion. In GC patients, HPIP positively associates with tumor size and nodal metastasis, and negatively associates with tumor differentiation. Hematopoietic pre-B cell leukemia transcription factor interacting protein increases GC cell proliferation through activation of G1 /S and G2 /M cell cycle transitions, accompanied by a marked increase of the positive cell cycle regulators, including cyclin D1, cyclin A, and cyclin B1. Hematopoietic pre-B cell leukemia transcription factor interacting protein enhances GC cell migration and invasion, and modulates epithelial-mesenchymal transition, which plays a key role in cancer cell migration and invasion. These data underscore the critical role of HPIP in GC cell proliferation and progression and suggest that HPIP inhibition may be a useful therapeutic strategy for GC treatment.

Aerobic glycolysis (the Warburg effect) facilitates tumor growth, and drugs targeting aerobic glycolysis are being developed. However, how the Warburg effect is directly regulated is largely unknown. Here we show that transcription factor SIX1 directly increases the expression of many glycolytic genes, promoting the Warburg effect and tumor growth in vitro and in vivo. SIX1 regulates glycolysis through HBO1 and AIB1 histone acetyltransferases. Cancer-related SIX1 mutation increases its ability to promote aerobic glycolysis and tumor growth. SIX1 glycolytic function is directly repressed by microRNA-548a-3p, which is downregulated, inversely correlates with SIX1, and is a good predictor of prognosis in breast cancer patients. Thus, the microRNA-548a-3p/SIX1 axis strongly links aerobic glycolysis to carcinogenesis and may become a promising cancer therapeutic target.

CD4+ T cells have several subsets of functional phenotypes, which play critical yet diverse roles in the immune system. Pathogen-driven differentiation of these subsets of cells is often heterogeneous in terms of the induced phenotypic diversity. In vitro recapitulation of heterogeneous differentiation under homogeneous experimental conditions indicates some highly regulated mechanisms by which multiple phenotypes of CD4+ T cells can be generated from a single population of naïve CD4+ T cells. Therefore, conceptual understanding of induced heterogeneous differentiation will shed light on the mechanisms controlling the response of populations of CD4+ T cells under physiological conditions.

Atherosclerosis (AS) is the basis of cardiovascular diseases, characterized by chronic inflammatory and lipid metabolism disorders. Although the anti-inflammatory effect of Klotho in AS has been clearly shown, its lipid-lowering effect is unclear. In this study, we examined the effects of recombinant Klotho (Re-KL) protein on lipid accumulation in foam cells.

Human urothelial carcinoma (UC) has a high tendency to recur and progress to life-threatening advanced diseases. Advanced therapeutic regimens are needed to control UC development and recurrence.

Positive feedback driven by transcriptional regulation has long been considered a key mechanism underlying cell lineage segregation during embryogenesis. Using the developing spinal cord as a paradigm, we found that canonical, transcription-driven feedback cannot explain robust lineage segregation of motor neuron subtypes marked by two cardinal factors, Hoxa5 and Hoxc8. We propose a feedback mechanism involving elementary microRNA-mRNA reaction circuits that differ from known feedback loop-like structures. Strikingly, we show that a wide range of biologically plausible post-transcriptional regulatory parameters are sufficient to generate bistable switches, a hallmark of positive feedback. Through mathematical analysis, we explain intuitively the hidden source of this feedback. Using embryonic stem cell differentiation and mouse genetics, we corroborate that microRNA-mRNA circuits govern tissue boundaries and hysteresis upon motor neuron differentiation with respect to transient morphogen signals. Our findings reveal a previously underappreciated feedback mechanism that may have widespread functions in cell fate decisions and tissue patterning.

Multiple intermediate epithelial-mesenchymal transition (EMT) states reflecting hybrid epithelial and mesenchymal phenotypes were observed in physiological and pathological conditions. Previous theoretical models explaining multiple EMT states rely on regulatory loops involving transcriptional feedback, which produce three or four attractors. This is incompatible with the observed continuum-like EMT spectrum. Here, we used mass-action-based models to describe post-transcriptional regulations, finding that cooperative RNA degradation via multiple microRNA binding sites can generate four-attractor systems without transcriptional feedback. Furthermore, the newly identified intermediates-enabling circuits are common in the EMT regulatory network, and they can synergize with transcriptional feedback to support phenotypic continuum. Finally, our model predicted a role of miR-101 in multistate EMT, and we identified evidence from single-cell RNA-sequencing data that support the prediction. Our work reveals a previously unknown role of cooperative RNA degradation and microRNAs in EMT, providing a framework that can bridge the gap between mechanistic models and single-cell experiments.