The fitness trade-off between growth and stress resistance determines the phenotypic landscape.

BACKGROUND: A central challenge in biology is to discover a principle that determines individual phenotypic differences within a species. The growth rate is particularly important for a unicellular organism, and the growth rate under a certain condition is negatively associated with that of another condition, termed fitness trade-off. Therefore, there should exist a common molecular mechanism that regulates multiple growth rates under various conditions, but most studies so far have focused on discovering those genes associated with growth rates under a specific condition. RESULTS: In this study, we found that there exists a recurrent gene expression signature whose expression levels are related to the fitness trade-off between growth preference and stress resistance across various yeast strains and multiple conditions. We further found that the genomic variation of stress-response, ribosomal, and cell cycle regulators are potential causal genes that determine the sensitivity between growth and survival. Intriguingly, we further observed that the same principle holds for human cells using anticancer drug sensitivities across multiple cancer cell lines. CONCLUSIONS: Together, we suggest that the fitness trade-off is an evolutionary trait that determines individual growth phenotype within a species. By using this trait, we can possibly overcome anticancer drug resistance in cancer cells.

Mature microRNA-binding protein QKI promotes microRNA-mediated gene silencing.

Although Argonaute (AGO) proteins have been the focus of microRNA (miRNA) studies, we observed AGO-free mature miRNAs directly interacting with RNA-binding proteins, implying the sophisticated nature of fine-tuning gene regulation by miRNAs. To investigate microRNA-binding proteins (miRBPs) globally, we analyzed PAR-CLIP data sets to identify RBP quaking (QKI) as a novel miRBP for let-7b. Potential existence of AGO-free miRNAs were further verified by measuring miRNA levels in genetically engineered AGO-depleted human and mouse cells. We have shown that QKI regulates miRNA-mediated gene silencing at multiple steps, and collectively serves as an auxiliary factor empowering AGO2/let-7b-mediated gene silencing. Depletion of QKI decreases interaction of AGO2 with let-7b and target mRNA, consequently controlling target mRNA decay. This finding indicates that QKI is a complementary factor in miRNA-mediated mRNA decay. QKI, however, also suppresses the dissociation of let-7b from AGO2, and slows the assembly of AGO2/miRNA/target mRNA complexes at the single-molecule level. We also revealed that QKI overexpression suppresses cMYC expression at post-transcriptional level, and decreases proliferation and migration of HeLa cells, demonstrating that QKI is a tumour suppressor gene by in part augmenting let-7b activity. Our data show that QKI is a new type of RBP implicated in the versatile regulation of miRNA-mediated gene silencing.

Hidden patterns of gene expression provide prognostic insight for colorectal cancer.

Cancer tissue samples contain cancer cells and non-cancer cells with each biopsied site containing distinct proportions of these populations. Consequently, assigning useful tumor subtypes based on gene expression measurements from clinical samples is challenging. We applied a blind source separation approach to extract cancer cell-intrinsic gene expression patterns within clinical tumor samples of colorectal cancer. After a blind source separation, we found that a cancer cell-intrinsic gene expression program unique to each patient exists in the "residual" expression profile remaining after separation of the gene expression data. We performed a consensus clustering analysis of the extracted gene expression profiles to identify novel and robust cancer cell-intrinsic subtypes. We validated the identified subtypes using an independent clinical gene expression dataset. The cancer cell-intrinsic subtypes are independent of biopsy site and provided prognostic information in addition to currently available clinical and molecular variables. After validating this approach in colorectal cancer, we further identified novel tumor subtypes with unique clinical information across multiple types of cancer. These cancer cell-intrinsic molecular subtypes provide novel prognostic value for clinical assessment of cancer.

Network Inference Analysis Identifies SETDB1 as a Key Regulator for Reverting Colorectal Cancer Cells into Differentiated Normal-Like Cells.

Cancer cells exhibit properties of cells in a less differentiated state than the adjacent normal cells in the tissue. We explored whether cancer cells can be converted to a differentiated normal-like state by restoring the gene regulatory network (GRN) of normal cells. Here, we report that colorectal cancer cells exhibit a range of developmental states from embryonic and intestinal stem-like cells to differentiated normal-like cells. To identify the transcription factors (TF) that commit stem-like colorectal cancer cells into a differentiated normal-like state, we reconstructed GRNs of normal colon mucosa and identified core TFs (CDX2, ELF3, HNF4G, PPARG, and VDR) that govern the cellular state. We further found that SET Domain Bifurcated 1 (SETDB1), a histone H3 lysine 9-specific methyltransferase, hinders the function of the identified TFs. SETDB1 depletion effectively converts stem-like colorectal cancer cells into postmitotic cells and restores normal morphology in patient-derived colorectal cancer organoids. RNA-sequencing analyses revealed that SETDB1 depletion recapitulates global gene expression profiles of normal differentiated cells by restoring the transcriptional activity of core TFs on their target genes. IMPLICATIONS: Our study provides insights into the molecular regulatory mechanism underlying the developmental hierarchy of colorectal cancer and suggests that induction of a postmitotic state may be a therapeutic alternative to destruction of cancer cells.

Stage-Dependent Gene Expression Profiling in Colorectal Cancer.

Temporal gene expression profiles have been widely considered to uncover the mechanism of cancer development and progression. Gene expression patterns, however, have been analyzed for limited stages with small samples, without proper data pre-processing, in many cases. With those approaches, it is difficult to unveil the mechanism of cancer development over time. In this study, we analyzed gene expression profiles of two independent colorectal cancer sample datasets, each of which contained 556 and 566 samples, respectively. To find specific gene expression changes according to cancer stage, we applied the linear mixed-effect regression model (LMER) that controls other clinical variables. Based on this methodology, we found two types of gene expression patterns: continuously increasing and decreasing genes as cancer develops. We found that continuously increasing genes are related to the nervous and developmental system, whereas the others are related to the cell cycle and metabolic processes. We further analyzed connected sub-networks related to the two types of genes. From these results, we suggest that the gene expression profile analysis can be used to understand underlying the mechanisms of cancer development such as cancer growth and metastasis. Furthermore, our approach can provide a good guideline for advancing our understanding of cancer developmental processes.

The core regulatory network in human cells.

In order to discover the common characteristics of various cell types in the human body, many researches have been conducted to find the set of genes commonly expressed in various cell types and tissues. However, the functional characteristics of a cell is determined by the complex regulatory relationships among the genes rather than by expressed genes themselves. Therefore, it is more important to identify and analyze a core regulatory network where all regulatory relationship between genes are active across all cell types to uncover the common features of various cell types. Here, based on hundreds of tissue-specific gene regulatory networks constructed by recent genome-wide experimental data, we constructed the core regulatory network. Interestingly, we found that the core regulatory network is organized by simple cascade and has few complex regulations such as feedback or feed-forward loops. Moreover, we discovered that the regulatory links from genes in the core regulatory network to genes in the peripheral regulatory network are much more abundant than the reverse direction links. These results suggest that the core regulatory network locates at the top of regulatory network and plays a role as a 'hub' in terms of information flow, and the information that is common to all cells can be modified to achieve the tissue-specific characteristics through various types of feedback and feed-forward loops in the peripheral regulatory networks. We also found that the genes in the core regulatory network are evolutionary conserved, essential and non-disease, non-druggable genes compared to the peripheral genes. Overall, our study provides an insight into how all human cells share a common function and generate tissue-specific functional traits by transmitting and processing information through regulatory network.

The reverse control of irreversible biological processes.

Most biological processes have been considered to be irreversible for a long time, but some recent studies have shown the possibility of their reversion at a cellular level. How can we then understand the reversion of such biological processes? We introduce a unified conceptual framework based on the attractor landscape, a molecular phase portrait describing the dynamics of a molecular regulatory network, and the phenotype landscape, a map of phenotypes determined by the steady states of particular output molecules in the attractor landscape. In this framework, irreversible processes involve reshaping of the phenotype landscape, and the landscape reshaping causes the irreversibility of processes. We suggest reverse control by network rewiring which changes network dynamics with constant perturbation, resulting in the restoration of the original phenotype landscape. The proposed framework provides a conceptual basis for the reverse control of irreversible biological processes through network rewiring. WIREs Syst Biol Med 2016, 8:366-377. doi: 10.1002/wsbm.1346 For further resources related to this article, please visit the WIREs website.

Heterozygous mutations in cyclic AMP phosphodiesterase-4D (PDE4D) and protein kinase A (PKA) provide new insights into the molecular pathology of acrodysostosis.

Acrodysostosis without hormone resistance is a rare skeletal disorder characterized by brachydactyly, nasal hypoplasia, mental retardation and occasionally developmental delay. Recently, loss-of-function mutations in the gene encoding cAMP-hydrolyzing phosphodiesterase-4D (PDE4D) have been reported to cause this rare condition but the pathomechanism has not been fully elucidated. To understand the pathogenetic mechanism of PDE4D mutations, we conducted 3D modeling studies to predict changes in the binding efficacy of cAMP to the catalytic pocket in PDE4D mutants. Our results indicated diminished enzyme activity in the two mutants we analyzed (Gly673Asp and Ile678Thr; based on PDE4D4 residue numbering). Ectopic expression of PDE4D mutants in HEK293 cells demonstrated this reduction in activity, which was identified by increased cAMP levels. However, the cells from an acrodysostosis patient showed low cAMP accumulation, which resulted in a decrease in the phosphorylated cAMP Response Element-Binding Protein (pCREB)/CREB ratio. The reason for this discrepancy was due to a compensatory increase in expression levels of PDE4A and PDE4B isoforms, which accounted for the paradoxical decrease in cAMP levels in the patient cells expressing mutant isoforms with a lowered PDE4D activity. Skeletal radiographs of 10-week-old knockout (KO) rats showed that the distal part of the forelimb was shorter than in wild-type (WT) rats and that all the metacarpals and phalanges were also shorter in KO, as the name acrodysostosis implies. Like the G-protein α-stimulatory subunit and PRKAR1A, PDE4D critically regulates the cAMP signal transduction pathway and influences bone formation in a way that activity-compromising PDE4D mutations can result in skeletal dysplasia. We propose that specific inhibitory PDE4D mutations can lead to the molecular pathology of acrodysostosis without hormone resistance but that the pathological phenotype may well be dependent on an over-compensatory induction of other PDE4 isoforms that can be expected to be targeted to different signaling complexes and exert distinct effects on compartmentalized cAMP signaling.

A checkpoints capturing timing-robust Boolean model of the budding yeast cell cycle regulatory network.

BACKGROUND: Cell cycle process of budding yeast (Saccharomyces cerevisiae) consists of four phases: G1, S, G2 and M. Initiated by stimulation of the G1 phase, cell cycle returns to the G1 stationary phase through a sequence of the S, G2 and M phases. During the cell cycle, a cell verifies whether necessary conditions are satisfied at the end of each phase (i.e., checkpoint) since damages of any phase can cause severe cell cycle defect. The cell cycle can proceed to the next phase properly only if checkpoint conditions are met. Over the last decade, there have been several studies to construct Boolean models that capture checkpoint conditions. However, they mostly focused on robustness to network perturbations, and the timing robustness has not been much addressed. Only recently, some studies suggested extension of such models towards timing-robust models, but they have not considered checkpoint conditions. RESULTS: To construct a timing-robust Boolean model that preserves checkpoint conditions of the budding yeast cell cycle, we used a model verification technique, 'model checking'. By utilizing automatic and exhaustive verification of model checking, we found that previous models cannot properly capture essential checkpoint conditions in the presence of timing variations. In particular, such models violate the M phase checkpoint condition so that it allows a division of a budding yeast cell into two before the completion of its full DNA replication and synthesis. In this paper, we present a timing-robust model that preserves all the essential checkpoint conditions properly against timing variations. Our simulation results show that the proposed timing-robust model is more robust even against network perturbations and can better represent the nature of cell cycle than previous models. CONCLUSIONS: To our knowledge this is the first work that rigorously examined the timing robustness of the cell cycle process of budding yeast with respect to checkpoint conditions using Boolean models. The proposed timing-robust model is the complete state-of-the-art model that guarantees no violation in terms of checkpoints known to date.

The core regulation module of stress-responsive regulatory networks in yeast.

How does a cell respond to numerous external stresses with a limited number of internal molecular components? It has been observed that there are some common responses of yeast to various stresses, but most observations were based on gene-expression profiles and only some part of the common responses were intensively investigated. So far there has been no system-level analysis to identify commonly responsive or regulated genes against various stresses. In this study, we identified a core regulation module (CRM), a commonly involved regulation structure in the regulatory networks of yeast, which cells reuse in response to an array of environmental stresses. We found that regulators in the CRM constitute a hierarchical backbone of the yeast regulatory network and that the CRM is evolutionarily well conserved, stable against genetic variations and crucial for cell growth. All these findings were consistently held up to considerable noise levels that we introduced to address experimental noise and the resulting false positives of regulatory interactions. We conclude that the CRM of yeast might be an evolutionarily conserved information processing unit that endows a cell with enhanced robustness and efficiency in dealing with numerous environmental stresses with a limited number of internal elements.

Spatiotemporal network motif reveals the biological traits of developmental gene regulatory networks in Drosophila melanogaster.

BACKGROUND: Network motifs provided a "conceptual tool" for understanding the functional principles of biological networks, but such motifs have primarily been used to consider static network structures. Static networks, however, cannot be used to reveal time- and region-specific traits of biological systems. To overcome this limitation, we proposed the concept of a "spatiotemporal network motif," a spatiotemporal sequence of network motifs of sub-networks which are active only at specific time points and body parts. RESULTS: On the basis of this concept, we analyzed the developmental gene regulatory network of the Drosophila melanogaster embryo. We identified spatiotemporal network motifs and investigated their distribution pattern in time and space. As a result, we found how key developmental processes are temporally and spatially regulated by the gene network. In particular, we found that nested feedback loops appeared frequently throughout the entire developmental process. From mathematical simulations, we found that mutual inhibition in the nested feedback loops contributes to the formation of spatial expression patterns. CONCLUSIONS: Taken together, the proposed concept and the simulations can be used to unravel the design principle of developmental gene regulatory networks.

Multiple roles of the NF-kappaB signaling pathway regulated by coupled negative feedback circuits.

The NF-kappaB signaling pathway can perform multiple functional roles depending on specific cellular environments and cell types. Even in the same cell clones, the pathway can show different kinetic and phenotypic properties. It is believed that the complex networks controlling the NF-kappaB signaling pathway can generate these diverse and sometimes ambiguous phenomena. We noted, however, that the dynamics of NF-kappaB signaling pathway is highly stochastic and that the NF-kappaB signaling pathway contains multiple negative feedback circuits formed by IkappaB isoform proteins, IkappaBalpha and IkappaBepsilon in particular. Considering the topological similarity, their functional roles seem to be redundant, raising the question why different types of IkappaB isoforms need to exist. From extensive stochastic simulations of the NF-kappaB signaling pathway, we found that each IkappaB isoform actually conducts a different regulatory role through its own negative feedback. Specifically, our data suggest that IkappaBalpha controls the dynamic patterns of nuclear NF-kappaB, while IkappaBepsilon induces cellular heterogeneity of the NF-kappaB activities. These results may provide an answer to the question of how a single NF-kappaB signaling pathway can perform multiple biological functions even in the same clonal populations.

The biphasic behavior of incoherent feed-forward loops in biomolecular regulatory networks.

An incoherent feed-forward loop (FFL) is one of the most-frequently observed motifs in biomolecular regulatory networks. It has been thought that the incoherent FFL is designed simply to induce a transient response shaped by a 'fast activation and delayed inhibition'. We find that the dynamics of various incoherent FFLs can be further classified into two types: time-dependent biphasic responses and dose-dependent biphasic responses. Why do the structurally identical incoherent FFLs play such different dynamical roles? Through computational studies, we show that the dynamics of the two types of incoherent FFLs are mutually exclusive. Following from further computational results and experimental observations, we hypothesize that incoherent FFLs have been optimally designed to achieve distinct biological function arising from different cellular contexts. Additional Supporting Information may be found in the online version of the article.

Coupled positive and negative feedback circuits form an essential building block of cellular signaling pathways.

Cellular circuits have positive and negative feedback loops that allow them to respond properly to noisy external stimuli. It is intriguing that such feedback loops exist in many cases in a particular form of coupled positive and negative feedback loops with different time delays. As a result of our mathematical simulations and investigations into various experimental evidences, we found that such coupled feedback circuits can rapidly turn on a reaction to a proper stimulus, robustly maintain its status, and immediately turn off the reaction when the stimulus disappears. In other words, coupled feedback loops enable cellular systems to produce perfect responses to noisy stimuli with respect to signal duration and amplitude. This suggests that coupled positive and negative feedback loops form essential signal transduction motifs in cellular signaling systems.

Switching feedback mechanisms realize the dual role of MCIP in the regulation of calcineurin activity.

Calcineurin (CaN) assists T-cell activation, growth and differentiation of skeletal and cardiac myocytes, memory, and apoptosis. It also activates transcription of the nuclear factor of activated T-cells (NFAT) family including hypertrophic target genes. It has been reported that the modulatory calcineurin-interacting protein (MCIP) inhibits the CaN activity and thereby reduces the hypertrophic response. However, it has been shown that MCIP facilitates or permits the hypertrophic response under some stress conditions such as isoproterenol infusion or pressure overload by transverse aortic constriction. As there is no direct experimental evidence that can explain these paradoxical phenomena, there has been a controversy concerning the functional role of MCIP in developing the hypertrophic response. It is therefore crucial to establish a hypothesis that can clearly explain these phenomena. Towards this end, we propose in this paper a hypothesis that is based on available experimental evidence as well as mathematical modeling and computer simulations. We hypothesize that there is a threshold in the nuclear NFAT concentration above which MCIP is switched on. Below this threshold, the inhibition of active CaN by MCIP is negligible, while the activated protein kinase increases the dissociation rate of the CaN/MCIP complex. This leads to an augmentation of active CaN. This mechanism realizes the positive effect (i.e., removing any negative feedback) of MCIP in the hypertrophic response. On the other hand, the over-expression of active CaN increases nuclear NFAT to values above the threshold, while CaN is inhibited through binding of MCIP (expressed by the nuclear NFAT). This mechanism realizes the introduction of a negative feedback mechanism. To unravel this switching feedback mechanism, we have developed a mathematical model for which computer simulations are in agreement with the existing experimental data. The simulations demonstrate how the apparently paradoxical behavior can emerge as a result of cellular conditions.