p38γ is essential for cell cycle progression and liver tumorigenesis.

The cell cycle is a tightly regulated process that is controlled by the conserved cyclin-dependent kinase (CDK)-cyclin protein complex1. However, control of the G0-to-G1 transition is not completely understood. Here we demonstrate that p38 MAPK gamma (p38γ) acts as a CDK-like kinase and thus cooperates with CDKs, regulating entry into the cell cycle. p38γ shares high sequence homology, inhibition sensitivity and substrate specificity with CDK family members. In mouse hepatocytes, p38γ induces proliferation after partial hepatectomy by promoting the phosphorylation of retinoblastoma tumour suppressor protein at known CDK target residues. Lack of p38γ or treatment with the p38γ inhibitor pirfenidone protects against the chemically induced formation of liver tumours. Furthermore, biopsies of human hepatocellular carcinoma show high expression of p38γ, suggesting that p38γ could be a therapeutic target in the treatment of this disease.

Predicting conformational ensembles and genome-wide transcription factor binding sites from DNA sequences.

DNA shape is emerging as an important determinant of transcription factor binding beyond just the DNA sequence. The only tool for large scale DNA shape estimates, DNAshape was derived from Monte-Carlo simulations and predicts four broad and static DNA shape features, Propeller twist, Helical twist, Minor groove width and Roll. The contributions of other shape features e.g. Shift, Slide and Opening cannot be evaluated using DNAshape. Here, we report a novel method DynaSeq, which predicts molecular dynamics-derived ensembles of a more exhaustive set of DNA shape features. We compared the DNAshape and DynaSeq predictions for the common features and applied both to predict the genome-wide binding sites of 1312 TFs available from protein interaction quantification (PIQ) data. The results indicate a good agreement between the two methods for the common shape features and point to advantages in using DynaSeq. Predictive models employing ensembles from individual conformational parameters revealed that base-pair opening - known to be important in strand separation - was the best predictor of transcription factor-binding sites (TFBS) followed by features employed by DNAshape. Of note, TFBS could be predicted not only from the features at the target motif sites, but also from those as far as 200 nucleotides away from the motif.

Chromerid genomes reveal the evolutionary path from photosynthetic algae to obligate intracellular parasites.

The eukaryotic phylum Apicomplexa encompasses thousands of obligate intracellular parasites of humans and animals with immense socio-economic and health impacts. We sequenced nuclear genomes of Chromera velia and Vitrella brassicaformis, free-living non-parasitic photosynthetic algae closely related to apicomplexans. Proteins from key metabolic pathways and from the endomembrane trafficking systems associated with a free-living lifestyle have been progressively and non-randomly lost during adaptation to parasitism. The free-living ancestor contained a broad repertoire of genes many of which were repurposed for parasitic processes, such as extracellular proteins, components of a motility apparatus, and DNA- and RNA-binding protein families. Based on transcriptome analyses across 36 environmental conditions, Chromera orthologs of apicomplexan invasion-related motility genes were co-regulated with genes encoding the flagellar apparatus, supporting the functional contribution of flagella to the evolution of invasion machinery. This study provides insights into how obligate parasites with diverse life strategies arose from a once free-living phototrophic marine alga.

A Drosophila-centric view of protein tyrosine phosphatases.

Most of our knowledge on protein tyrosine phosphatases (PTPs) is derived from human pathologies and mouse knockout models. These models largely correlate well with human disease phenotypes, but can be ambiguous due to compensatory mechanisms introduced by paralogous genes. Here we present the analysis of the PTP complement of the fruit fly and the complementary view that PTP studies in Drosophila will accelerate our understanding of PTPs in physiological and pathological conditions. With only 44 PTP genes, Drosophila represents a streamlined version of the human complement. Our integrated analysis places the Drosophila PTPs into evolutionary and functional contexts, thereby providing a platform for the exploitation of the fly for PTP research and the transfer of knowledge onto other model systems.

Genomic analysis of LPS-stimulated myeloid cells identifies a common pro-inflammatory response but divergent IL-10 anti-inflammatory responses.

Inflammation is an essential physiological response to infection and injury that must be kept within strict bounds. The IL-10/STAT3 anti-inflammatory response (AIR) is indispensable for controlling the extent of inflammation, although the complete mechanisms downstream of STAT3 have not yet been elucidated. The AIR is widely known to extend to other myeloid cells, but it has best been characterized in macrophages. Here we set out to characterize the LPS-mediated pro-inflammatory response and the AIR across a range of myeloid cells. We found that whereas the LPS-induced pro-inflammatory response is broadly similar among macrophages, dendritic cells, neutrophils, mast cells and eosinophils, the AIR is drastically different across all myeloid cell types that respond to IL-10 (all bar eosinophils). We propose a model whereby the IL-10/STAT3 AIR works by selectively inhibiting specific pathways in distinct cell types: in macrophages the AIR most likely works through the inhibition of NF-κB target genes; in DCs and mast cells through indirect IRF disruption; and in neutrophils through IRF disruption and possibly also indirect NF-κB inhibition. In summary, no conserved IL-10/STAT3 AIR effectors were identified; instead a cell type-specific model of the AIR is proposed.

glbase: a framework for combining, analyzing and displaying heterogeneous genomic and high-throughput sequencing data.

Genomic datasets and the tools to analyze them have proliferated at an astonishing rate. However, such tools are often poorly integrated with each other: each program typically produces its own custom output in a variety of non-standard file formats. Here we present glbase, a framework that uses a flexible set of descriptors that can quickly parse non-binary data files. glbase includes many functions to intersect two lists of data, including operations on genomic interval data and support for the efficient random access to huge genomic data files. Many glbase functions can produce graphical outputs, including scatter plots, heatmaps, boxplots and other common analytical displays of high-throughput data such as RNA-seq, ChIP-seq and microarray expression data. glbase is designed to rapidly bring biological data into a Python-based analytical environment to facilitate analysis and data processing. In summary, glbase is a flexible and multifunctional toolkit that allows the combination and analysis of high-throughput data (especially next-generation sequencing and genome-wide data), and which has been instrumental in the analysis of complex data sets. glbase is freely available at http://bitbucket.org/oaxiom/glbase/.

Human dermal CD14⁺ cells are a transient population of monocyte-derived macrophages.

Dendritic cells (DCs), monocytes, and macrophages are leukocytes with critical roles in immunity and tolerance. The DC network is evolutionarily conserved; the homologs of human tissue CD141(hi)XCR1⁺ CLEC9A⁺ DCs and CD1c⁺ DCs are murine CD103⁺ DCs and CD64⁻ CD11b⁺ DCs. In addition, human tissues also contain CD14⁺ cells, currently designated as DCs, with an as-yet unknown murine counterpart. Here we have demonstrated that human dermal CD14⁺ cells are a tissue-resident population of monocyte-derived macrophages with a short half-life of <6 days. The decline and reconstitution kinetics of human blood CD14⁺ monocytes and dermal CD14⁺ cells in vivo supported their precursor-progeny relationship. The murine homologs of human dermal CD14⁺ cells are CD11b⁺ CD64⁺ monocyte-derived macrophages. Human and mouse monocytes and macrophages were defined by highly conserved gene transcripts, which were distinct from DCs. The demonstration of monocyte-derived macrophages in the steady state in human tissue supports a conserved organization of human and mouse mononuclear phagocyte system.

Genomic analysis of the causative agents of coccidiosis in domestic chickens.

Global production of chickens has trebled in the past two decades and they are now the most important source of dietary animal protein worldwide. Chickens are subject to many infectious diseases that reduce their performance and productivity. Coccidiosis, caused by apicomplexan protozoa of the genus Eimeria, is one of the most important poultry diseases. Understanding the biology of Eimeria parasites underpins development of new drugs and vaccines needed to improve global food security. We have produced annotated genome sequences of all seven species of Eimeria that infect domestic chickens, which reveal the full extent of previously described repeat-rich and repeat-poor regions and show that these parasites possess the most repeat-rich proteomes ever described. Furthermore, while no other apicomplexan has been found to possess retrotransposons, Eimeria is home to a family of chromoviruses. Analysis of Eimeria genes involved in basic biology and host-parasite interaction highlights adaptations to a relatively simple developmental life cycle and a complex array of co-expressed surface proteins involved in host cell binding.

rTRM-web: a web tool for predicting transcriptional regulatory modules for ChIP-seq-ed transcription factors.

Transcription factors (TFs) bind to specific DNA regions, although their binding specificities cannot account for their cell type-specific functions. It has been shown in well-studied systems that TFs combine with co-factors into transcriptional regulatory modules (TRMs), which endow them with cell type-specific functions and additional modes of regulation. Therefore, the prediction of TRMs can provide fundamental mechanistic insights, especially when experimental data are limiting or when no regulatory proteins have been identified. Our method rTRM predicts TRMs by integrating genomic information from TF ChIP-seq data, cell type-specific gene expression and protein-protein interaction data. Here we present a freely available web interface to rTRM (http://www.rTRM.org/) supporting all the options originally described for rTRM while featuring flexible display and network calculation parameters, publication-quality figures as well as annotated information on the list of genes constituting the TRM.

Protein tyrosine phosphatase 1B is a regulator of the interleukin-10-induced transcriptional program in macrophages.

Both pro- and anti-inflammatory cytokines activate the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway; however, they elicit distinct transcriptional programs. Posttranslational modifications of STAT proteins, such as tyrosine phosphorylation, are critical to ensure the differential expression of STAT target genes. Although JAK-STAT signaling is dependent on reversible tyrosine phosphorylation, whether phosphatases contribute to the specificity of STAT-dependent gene expression is unclear. We examined the role of protein tyrosine phosphatase 1B (PTP1B) in regulating the interleukin-10 (IL-10)-dependent, STAT3-mediated anti-inflammatory response. We found that IL-10-dependent STAT3 phosphorylation and anti-inflammatory gene expression were enhanced in macrophages from PTP1B(-/-) mice compared to those in macrophages from wild-type mice. Consistent with this finding, the IL-10-dependent suppression of lipopolysaccharide-induced macrophage activation was increased in PTP1B(-/-) macrophages compared to that in wild-type macrophages, as was the IL-10-dependent increase in the cell surface expression of the anti-inflammatory cytokine receptor IL-4Rα. Furthermore, RNA sequencing revealed the expression of genes encoding proinflammatory factors in IL-10-treated PTP1B(-/-) macrophages, which correlated with increased phosphorylation of STAT1, which is not normally highly activated in response to IL-10. These findings identify PTP1B as a central regulator of IL-10R-STAT3 and IL-10R-STAT1 signaling, and demonstrate that phosphatases can tailor the quantitative and qualitative properties of cytokine-induced transcriptional responses.

Characterization of PTPN2 and its use as a biomarker.

For years, the two main isoforms of PTPN2 have been an interesting yet academic topic of debate for researchers working on this phosphatase. In recent years, several studies were published in which these isoforms were attributed specific functions. Most importantly, differences in their stoichiometry have been reported to be associated with certain diseases such as inflammatory bowel diseases (IBDs). Hence, understanding the evolutionary ontogeny of the main transcripts and the physiological consequences of their expression have now become clinically relevant issues. Herein we describe the genomic controls placed upon PTPN2, the identified splice variants, the encoded PTPN2 proteins, and both the known and putative post-translational modifications that have been reported. Moreover, we examine the expression of PTPN2 isoforms in specific tissues as well as in a disease setting. PTPN2 is an important negative regulator of inflammation. Therefore, the following protocols are effective approaches for its adequate monitoring in inflammatory diseases' progression and outcome.

PTP-central: a comprehensive resource of protein tyrosine phosphatases in eukaryotic genomes.

Reversible tyrosine phosphorylation is a fundamental signaling mechanism controlling a diversity of cellular processes. Whereas protein tyrosine kinases have long been implicated in many diseases, aberrant protein tyrosine phosphatase (PTP) activity is also increasingly being associated with a wide spectrum of conditions. PTPs are now regarded as key regulators of biochemical processes instead of simple "off" switches operating in tyrosine kinase signaling pathways. Despite the central importance that PTPs play in the cell's biochemistry, the tyrosine phosphatomes of most species remain uncharted. Here we present a highly sensitive and specific sequence-based method for the automatic classification of PTPs. As proof of principle we re-annotated the human tyrosine phosphatome, and discovered four new PTP genes that had not been reported before. Our method and the predicted tyrosine phosphatomes of 65 eukaryotic genomes are accessible online through the user-friendly PTP-central resource (http://www.PTP-central.org/), where users can also submit their own sequences for prediction. PTP-central is a comprehensive and continually developing resource that currently integrates the predicted tyrosine phosphatomes with structural data and genetic association disease studies, as well as homology relationships. PTP-central thus fills an important void for the systematic study of PTPs, both in model organisms and from an evolutionary perspective.

Systematic identification of transcriptional regulatory modules from protein-protein interaction networks.

Transcription factors (TFs) combine with co-factors to form transcriptional regulatory modules (TRMs) that regulate gene expression programs with spatiotemporal specificity. Here we present a novel and generic method (rTRM) for the reconstruction of TRMs that integrates genomic information from TF binding, cell type-specific gene expression and protein-protein interactions. rTRM was applied to reconstruct the TRMs specific for embryonic stem cells (ESC) and hematopoietic stem cells (HSC), neural progenitor cells, trophoblast stem cells and distinct types of terminally differentiated CD4(+) T cells. The ESC and HSC TRM predictions were highly precise, yielding 77 and 96 proteins, of which ∼75% have been independently shown to be involved in the regulation of these cell types. Furthermore, rTRM successfully identified a large number of bridging proteins with known roles in ESCs and HSCs, which could not have been identified using genomic approaches alone, as they lack the ability to bind specific DNA sequences. This highlights the advantage of rTRM over other methods that ignore PPI information, as proteins need to interact with other proteins to form complexes and perform specific functions. The prediction and experimental validation of the co-factors that endow master regulatory TFs with the capacity to select specific genomic sites, modulate the local epigenetic profile and integrate multiple signals will provide important mechanistic insights not only into how such TFs operate, but also into abnormal transcriptional states leading to disease.

Cellular network entropy as the energy potential in Waddington's differentiation landscape.

Differentiation is a key cellular process in normal tissue development that is significantly altered in cancer. Although molecular signatures characterising pluripotency and multipotency exist, there is, as yet, no single quantitative mark of a cellular sample's position in the global differentiation hierarchy. Here we adopt a systems view and consider the sample's network entropy, a measure of signaling pathway promiscuity, computable from a sample's genome-wide expression profile. We demonstrate that network entropy provides a quantitative, in-silico, readout of the average undifferentiated state of the profiled cells, recapitulating the known hierarchy of pluripotent, multipotent and differentiated cell types. Network entropy further exhibits dynamic changes in time course differentiation data, and in line with a sample's differentiation stage. In disease, network entropy predicts a higher level of cellular plasticity in cancer stem cell populations compared to ordinary cancer cells. Importantly, network entropy also allows identification of key differentiation pathways. Our results are consistent with the view that pluripotency is a statistical property defined at the cellular population level, correlating with intra-sample heterogeneity, and driven by the degree of signaling promiscuity in cells. In summary, network entropy provides a quantitative measure of a cell's undifferentiated state, defining its elevation in Waddington's landscape.

The IL-10/STAT3-mediated anti-inflammatory response: recent developments and future challenges.

Inflammation is a fundamental response of the immune system whose successful termination involves the elimination of the invading pathogens, the resolution of inflammation and the repair of the local damaged tissue. In this context, the interleukin 10 (IL-10)-mediated anti-inflammatory response (AIR) represents an essential homeostatic mechanism that controls the degree and duration of inflammation. Here, we review recent work on the mechanistic characterization of the IL-10-mediated AIR on multiple levels: from the cataloguing of the in vivo genomic targets of STAT3 (the transcription factor downstream of IL-10) to the identification of specific co-factors that endow STAT3 with genomic-binding specificity, and how genomic and computational methods are being used to elucidate the regulatory mechanisms of this essential physiological response in macrophages.

Hard-wired heterogeneity in blood stem cells revealed using a dynamic regulatory network model.

MOTIVATION: Combinatorial interactions of transcription factors with cis-regulatory elements control the dynamic progression through successive cellular states and thus underpin all metazoan development. The construction of network models of cis-regulatory elements, therefore, has the potential to generate fundamental insights into cellular fate and differentiation. Haematopoiesis has long served as a model system to study mammalian differentiation, yet modelling based on experimentally informed cis-regulatory interactions has so far been restricted to pairs of interacting factors. Here, we have generated a Boolean network model based on detailed cis-regulatory functional data connecting 11 haematopoietic stem/progenitor cell (HSPC) regulator genes. RESULTS: Despite its apparent simplicity, the model exhibits surprisingly complex behaviour that we charted using strongly connected components and shortest-path analysis in its Boolean state space. This analysis of our model predicts that HSPCs display heterogeneous expression patterns and possess many intermediate states that can act as 'stepping stones' for the HSPC to achieve a final differentiated state. Importantly, an external perturbation or 'trigger' is required to exit the stem cell state, with distinct triggers characterizing maturation into the various different lineages. By focusing on intermediate states occurring during erythrocyte differentiation, from our model we predicted a novel negative regulation of Fli1 by Gata1, which we confirmed experimentally thus validating our model. In conclusion, we demonstrate that an advanced mammalian regulatory network model based on experimentally validated cis-regulatory interactions has allowed us to make novel, experimentally testable hypotheses about transcriptional mechanisms that control differentiation of mammalian stem cells. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PTP1B: a simple enzyme for a complex world.

Our understanding of the fundamental regulatory roles that tyrosine phosphatases play within cells has advanced significantly in the last two decades. Out-dated ideas that tyrosine phosphatases acts solely as the "off" switch counterbalancing the action of tyrosine kinases has proved to be flawed. PTP1B is the most characterized of all the tyrosine phosphatases and it acts as a critical negative and positive regulator of numerous signaling cascades. PTP1B's direct regulation of the insulin and the leptin receptors makes it an ideal therapeutic target for type II diabetes and obesity. Moreover, the last decade has also seen several reports establishing PTP1B as key player in cancer serving as both tumor suppressor and tumor promoter depending on the cellular context. Despite many key advances in these fields one largely ignored area is what role PTP1B may play in the modulation of immune signaling. The important recognition that PTP1B is a major negative regulator of Janus kinase - signal transducer and activator of transcription (JAK-STAT) signaling throughout evolution places it as a key link between metabolic diseases and inflammation, as well as a unique regulator between immune response and cancer. This review looks at the emergence of PTP1B through evolution, and then explore at the cell and systemic levels how it is controlled physiologically. The second half of the review will focus on the role(s) PTP1B can play in disease and in particular its involvement in metabolic syndromes and cancer. Finally we will briefly examine several novel directions in the development of PTP1B pharmacological inhibitors.

The repertoires of ubiquitinating and deubiquitinating enzymes in eukaryotic genomes.

Reversible protein ubiquitination regulates virtually all known cellular activities. Here, we present a quantitatively evaluated and broadly applicable method to predict eukaryotic ubiquitinating enzymes (UBE) and deubiquitinating enzymes (DUB) and its application to 50 distinct genomes belonging to four of the five major phylogenetic supergroups of eukaryotes: unikonts (including metazoans, fungi, choanozoa, and amoebozoa), excavates, chromalveolates, and plants. Our method relies on a collection of profile hidden Markov models, and we demonstrate its superior performance (coverage and classification accuracy >99%) by identifying approximately 25% and approximately 35% additional UBE and DUB genes in yeast and human, which had not been reported before. In yeast, we predict 85 UBE and 24 DUB genes, for 814 UBE and 107 DUB genes in the human genome. Most UBE and DUB families are present in all eukaryotic lineages, with plants and animals harboring massively enlarged repertoires of ubiquitin ligases. Unicellular organisms, on the other hand, typically harbor less than 300 UBEs and less than 40 DUBs per genome. Ninety-one UBE/DUB genes are orthologous across all four eukaryotic supergroups, and these likely represent a primordial core of enzymes of the ubiquitination system probably dating back to the first eukaryotes approximately 2 billion years ago. Our genome-wide predictions are available through the Database of Ubiquitinating and Deubiquitinating Enzymes (www.DUDE-db.org), where users can also perform advanced sequence and phylogenetic analyses and submit their own predictions.

Genome of Acanthamoeba castellanii highlights extensive lateral gene transfer and early evolution of tyrosine kinase signaling.

BACKGROUND: The Amoebozoa constitute one of the primary divisions of eukaryotes, encompassing taxa of both biomedical and evolutionary importance, yet its genomic diversity remains largely unsampled. Here we present an analysis of a whole genome assembly of Acanthamoeba castellanii (Ac) the first representative from a solitary free-living amoebozoan. RESULTS: Ac encodes 15,455 compact intron-rich genes, a significant number of which are predicted to have arisen through inter-kingdom lateral gene transfer (LGT). A majority of the LGT candidates have undergone a substantial degree of intronization and Ac appears to have incorporated them into established transcriptional programs. Ac manifests a complex signaling and cell communication repertoire, including a complete tyrosine kinase signaling toolkit and a comparable diversity of predicted extracellular receptors to that found in the facultatively multicellular dictyostelids. An important environmental host of a diverse range of bacteria and viruses, Ac utilizes a diverse repertoire of predicted pattern recognition receptors, many with predicted orthologous functions in the innate immune systems of higher organisms. CONCLUSIONS: Our analysis highlights the important role of LGT in the biology of Ac and in the diversification of microbial eukaryotes. The early evolution of a key signaling facility implicated in the evolution of metazoan multicellularity strongly argues for its emergence early in the Unikont lineage. Overall, the availability of an Ac genome should aid in deciphering the biology of the Amoebozoa and facilitate functional genomic studies in this important model organism and environmental host.