Bone morphogenetic protein (BMP) signaling is known to support differentiation of human embryonic stem cells (hESCs) into mesoderm and extraembryonic lineages, whereas other signaling pathways can largely influence this lineage specification. Here, we set out to reinvestigate the influence of ACTIVIN/NODAL and fibroblast growth factor (FGF) pathways on the lineage choices made by hESCs during BMP4-driven differentiation. We show that BMP activation, coupled with inhibition of both ACTIVIN/NODAL and FGF signaling, induces differentiation of hESCs, specifically to βhCG hormone-secreting multinucleated syncytiotrophoblast and does not support induction of embryonic and extraembryonic lineages, extravillous trophoblast, and primitive endoderm. It has been previously reported that FGF2 can switch BMP4-induced hESC differentiation outcome to mesendoderm. Here, we show that FGF inhibition alone, or in combination with either ACTIVIN/NODAL inhibition or BMP activation, supports hESC differentiation to hCG-secreting syncytiotrophoblast. We show that the inhibition of the FGF pathway acts as a key in directing BMP4-mediated hESC differentiation to syncytiotrophoblast.
Mutation is a fundamental process in tumorigenesis. However, the degree to which the rate of somatic mutation varies across the human genome and the mechanistic basis underlying this variation remain to be fully elucidated. Here, we performed a cross-cancer comparison of 402 whole genomes comprising a diverse set of childhood and adult tumors, including both solid and hematopoietic malignancies. Surprisingly, we found that the inactive X chromosome of many female cancer genomes accumulates on average twice and up to four times as many somatic mutations per megabase, as compared to the individual autosomes. Whole-genome sequencing of clonally expanded hematopoietic stem/progenitor cells (HSPCs) from healthy individuals and a premalignant myelodysplastic syndrome (MDS) sample revealed no X chromosome hypermutation. Our data suggest that hypermutation of the inactive X chromosome is an early and frequent feature of tumorigenesis resulting from DNA replication stress in aberrantly proliferating cells.
•X chromosome has up to 4× more mutations than the autosomes in female cancer genomes•Hypermutations only affect the inactive X chromosome•X hypermutation involves somatic point mutations and indels, but not germline mutations•No X hypermutation is found in clonal expansions of normal or premalignant cells
A comparison of 402 cancer genomes identifies a surprisingly high level of somatic mutations in the inactive X chromosome of female cancer genomes. As hypermutability of the inactive X was not observed in clonal hematopoietic progenitor or preleukemic samples, it is likely that it may be a contributing factor to tumorigenesis.
Genomes of animals as different as sponges and humans show conservation of global architecture. Here we show that multiple genomic features including transposon diversity, developmental gene repertoire, physical gene order, and intron-exon organization are shattered in the tunicate Oikopleura, belonging to the sister group of vertebrates and retaining chordate morphology. Ancestral architecture of animal genomes can be deeply modified and may therefore be largely nonadaptive. This rapidly evolving animal lineage thus offers unique perspectives on the level of genome plasticity. It also illuminates issues as fundamental as the mechanisms of intron gain.
DNA sequencing has revolutionized biological and medical research, and is poised to have a similar impact in medicine. This tool is just one of a number of developments in our capability to identify, quantitate and functionally characterize the components of the biological networks keeping us healthy or making us sick, but in many respects it has played the leading role in this process. The new technologies do, however, also provide a bridge between genotype and phenotype, both in man and model (as well as all other) organisms, revolutionize the identification of elements involved in a multitude of human diseases or other phenotypes, and generate a wealth of medically relevant information on every single person, as the basis of a truly personalized medicine of the future.
The Forkhead (Fkh) box family of transcription factors is evolutionary conserved from yeast to higher eukaryotes and its members are involved in many physiological processes including metabolism, DNA repair, cell cycle, stress resistance, apoptosis, and aging. In budding yeast, four Fkh transcription factors were identified, namely Fkh1, Fkh2, Fhl1, and Hcm1, which are implicated in chromatin silencing, cell cycle regulation, and stress response. These factors impinge transcriptional regulation during cell cycle progression, and histone deacetylases (HDACs) play an essential role in this process, e.g., the nuclear localization of Hcm1 depends on Sir2 activity, whereas Sin3/Rpd3 silence cell cycle specific gene transcription in G2/M phase. However, a direct involvement of Sir2 in Fkh1/Fkh2-dependent regulation of target genes is at present unknown. Here, we show that Fkh1 and Fkh2 associate with Sir2 in G1 and M phase, and that Fkh1/Fkh2-mediated activation of reporter genes is antagonized by Sir2. We further report that Sir2 overexpression strongly affects cell growth in an Fkh1/Fkh2-dependent manner. In addition, Sir2 regulates the expression of the mitotic cyclin Clb2 through Fkh1/Fkh2-mediated binding to the CLB2 promoter in G1 and M phase. We finally demonstrate that Sir2 is also enriched at the CLB2 promoter under stress conditions, and that the nuclear localization of Sir2 is dependent on Fkh1 and Fkh2. Taken together, our results show a functional interplay between Fkh1/Fkh2 and Sir2 suggesting a novel mechanism of cell cycle repression. Thus, in budding yeast, not only the regulation of G2/M gene expression but also the protective response against stress could be directly coordinated by Fkh1 and Fkh2.
Fkh1; Fkh2; Sir2; silencing; cell cycle; stress; budding yeast
MiRNAs are discussed as diagnostic and therapeutic molecules. However, effective miRNA drug treatments with miRNAs are, so far, hampered by the complexity of the miRNA networks. To identify potential miRNA drugs in colorectal cancer, we profiled miRNA and mRNA expression in matching normal, tumor and metastasis tissues of eight patients by Illumina sequencing. We validated six miRNAs in a large tissue screen containing 16 additional tumor entities and identified miRNA-1, miRNA-129, miRNA-497 and miRNA-215 as constantly de-regulated within the majority of cancers. Of these, we investigated miRNA-1 as representative in a systems-biology simulation of cellular cancer models implemented in PyBioS and assessed the effects of depletion as well as overexpression in terms of miRNA-1 as a potential treatment option. In this system, miRNA-1 treatment reverted the disease phenotype with different effectiveness among the patients. Scoring the gene expression changes obtained through mRNA-Seq from the same patients we show that the combination of deep sequencing and systems biological modeling can help to identify patient-specific responses to miRNA treatments. We present this data as guideline for future pre-clinical assessments of new and personalized therapeutic options.
Aberrant activation of Hedgehog (HH) signaling has been identified as a key etiologic factor in many human malignancies. Signal strength, target gene specificity, and oncogenic activity of HH signaling depend profoundly on interactions with other pathways, such as epidermal growth factor receptor-mediated signaling, which has been shown to cooperate with HH/GLI in basal cell carcinoma and pancreatic cancer. Our experimental data demonstrated that the Daoy human medulloblastoma cell line possesses a fully inducible endogenous HH pathway. Treatment of Daoy cells with Sonic HH or Smoothened agonist induced expression of GLI1 protein and simultaneously prevented the processing of GLI3 to its repressor form. To study interactions between HH- and EGF-induced signaling in greater detail, time-resolved measurements were carried out and analyzed at the transcriptomic and proteomic levels. The Daoy cells responded to the HH/EGF co-treatment by downregulating GLI1, PTCH, and HHIP at the transcript level; this was also observed when Amphiregulin (AREG) was used instead of EGF. We identified a novel crosstalk mechanism whereby EGFR signaling silences proteins acting as negative regulators of HH signaling, as AKT- and ERK-signaling independent process. EGFR/HH signaling maintained high GLI1 protein levels which contrasted the GLI1 downregulation on the transcript level. Conversely, a high-level synergism was also observed, due to a strong and significant upregulation of numerous canonical EGF-targets with putative tumor-promoting properties such as MMP7, VEGFA, and IL-8. In conclusion, synergistic effects between EGFR and HH signaling can selectively induce a switch from a canonical HH/GLI profile to a modulated specific target gene profile. This suggests that there are more wide-spread, yet context-dependent interactions, between HH/GLI and growth factor receptor signaling in human malignancies.
Overexpression of ERG transcription factor due to genomic ERG-rearrangements defines a separate molecular subtype of prostate tumors. One of the consequences of ERG accumulation is modulation of the cell’s gene expression profile. Tudor domain-containing protein 1 gene (TDRD1) was reported to be differentially expressed between TMPRSS2:ERG-negative and TMPRSS2:ERG-positive prostate cancer. The aim of our study was to provide a mechanistic explanation for the transcriptional activation of TDRD1 in ERG rearrangement-positive prostate tumors.
Gene expression measurements by real-time quantitative PCR revealed a remarkable co-expression of TDRD1 and ERG (r2 = 0.77) but not ETV1 (r2<0.01) in human prostate cancer in vivo. DNA methylation analysis by MeDIP-Seq and bisulfite sequencing showed that TDRD1 expression is inversely correlated with DNA methylation at the TDRD1 promoter in vitro and in vivo (ρ = −0.57). Accordingly, demethylation of the TDRD1 promoter in TMPRSS2:ERG-negative prostate cancer cells by DNA methyltransferase inhibitors resulted in TDRD1 induction. By manipulation of ERG dosage through gene silencing and forced expression we show that ERG governs loss of DNA methylation at the TDRD1 promoter-associated CpG island, leading to TDRD1 overexpression.
We demonstrate that ERG is capable of disrupting a tissue-specific DNA methylation pattern at the TDRD1 promoter. As a result, TDRD1 becomes transcriptionally activated in TMPRSS2:ERG-positive prostate cancer. Given the prevalence of ERG fusions, TDRD1 overexpression is a common alteration in human prostate cancer which may be exploited for diagnostic or therapeutic procedures.
Inhibition of Hedgehog (HH)/GLI signaling in cancer is a promising therapeutic approach. Interactions between HH/GLI and other oncogenic pathways affect the strength and tumorigenicity of HH/GLI. Cooperation of HH/GLI with Epidermal Growth Factor Receptor (EGFR) signaling promotes transformation and cancer cell proliferation in vitro. However, the in vivo relevance of HH-EGFR signal integration and the critical downstream mediators are largely undefined. In this report we show that genetic and pharmacologic inhibition of EGFR signaling reduces tumor growth in mouse models of HH/GLI driven basal cell carcinoma (BCC). We describe HH-EGFR cooperation response genes including SOX2, SOX9, JUN, CXCR4 and FGF19 that are synergistically activated by HH-EGFR signal integration and required for in vivo growth of BCC cells and tumor-initiating pancreatic cancer cells. The data validate EGFR signaling as drug target in HH/GLI driven cancers and shed light on the molecular processes controlled by HH-EGFR signal cooperation, providing new therapeutic strategies based on combined targeting of HH-EGFR signaling and selected downstream target genes.
Liquid chromatography mass spectrometry (LC-MS) maps in shotgun proteomics are often too complex to select every detected peptide signal for fragmentation by tandem mass spectrometry (MS/MS). Standard methods for precursor ion selection, commonly based on data dependent acquisition, select highly abundant peptide signals in each spectrum. However, these approaches produce redundant information and are biased towards high-abundance proteins.
We present two algorithms for inclusion list creation that formulate precursor ion selection as an optimization problem. Given an LC-MS map, the first approach maximizes the number of selected precursors given constraints such as a limited number of acquisitions per RT fraction. Second, we introduce a protein sequence-based inclusion list that can be used to monitor proteins of interest. Given only the protein sequences, we create an inclusion list that optimally covers the whole protein set. Additionally, we propose an iterative precursor ion selection that aims at reducing the redundancy obtained with data dependent LC-MS/MS. We overcome the risk of erroneous assignments by including methods for retention time and proteotypicity predictions. We show that our method identifies a set of proteins requiring fewer precursors than standard approaches. Thus, it is well suited for precursor ion selection in experiments with limited sample amount or analysis time.
We present three approaches to precursor ion selection with LC-MALDI MS/MS. Using a well-defined protein standard and a complex human cell lysate, we demonstrate that our methods outperform standard approaches. Our algorithms are implemented as part of OpenMS and are available under http://www.openms.de.
Aberrant CpG methylation is a universal epigenetic trait of cancer cell genomes. However, human cancer samples or cell lines preclude the investigation of epigenetic changes occurring early during tumour development. Here, we have used MeDIP-seq to analyse the DNA methylome of APCMin adenoma as a model for intestinal cancer initiation, and we present a list of more than 13,000 recurring differentially methylated regions (DMRs) characterizing intestinal adenoma of the mouse. We show that Polycomb Repressive Complex (PRC) targets are strongly enriched among hypermethylated DMRs, and several PRC2 components and DNA methyltransferases were up-regulated in adenoma. We further demonstrate by bisulfite pyrosequencing of purified cell populations that the DMR signature arises de novo in adenoma cells rather than by expansion of a pre-existing pattern in intestinal stem cells or undifferentiated crypt cells. We found that epigenetic silencing of tumour suppressors, which occurs frequently in colon cancer, was rare in adenoma. Quite strikingly, we identified a core set of DMRs, which is conserved between mouse adenoma and human colon cancer, thus possibly revealing a global panel of epigenetically modified genes for intestinal tumours. Our data allow a distinction between early conserved epigenetic alterations occurring in intestinal adenoma and late stochastic events promoting colon cancer progression, and may facilitate the selection of more specific clinical epigenetic biomarkers.
The formation and progression of tumours to metastatic disease is driven by two major mechanisms, i.e. genetic alterations that activate oncogenes or inactivate tumour suppressor genes, and changes in the epigenome that cause variations in the expression of the genetic information. A deeper understanding of the interaction between the genetic and epigenetic mechanisms is critical for the selection of tumour biomarkers and for the future development of therapies. Human tumour specimens and cell lines contain a plethora of genetic and epigenetic changes, which complicate data analysis. In contrast, mouse tumour models such as the APCMin mouse used in this study arise by a single initiating genetic mutation, yet share key traits with human cancer. Here we show that mouse adenomas acquire a multitude of epigenetic alterations, which are recurring in mouse adenoma and in human colon cancer, representing early and advanced tumours, respectively. The use of a mouse model thus allowed us to uncover a sequence of epigenetic changes occurring in tumours, which may facilitate the identification of novel clinical colon cancer biomarkers.
The immune system protects us from foreign substances or pathogens by generating specific antibodies. The variety of immunoglobulin (Ig) paratopes for antigen recognition is a result of the V(D)J rearrangement mechanism, while a fast and efficient immune response is mediated by specific immunoglobulin isotypes obtained through class switch recombination (CSR). To get a better understanding on how antibody-based immune protection works and how it changes with age, the interdependency between these two parameters need to be addressed. Here, we have performed an in depth analysis of antibody repertoires of 14 healthy donors representing different gender and age groups. For this task, we developed a unique pyrosequencing approach, which is able to monitor the expression levels of all immunoglobulin V(D)J recombinations of all isotypes including subtypes in an unbiased and quantitative manner. Our results show that donors have individual immunoglobulin repertoires and cannot be clustered according to V(D)J recombination patterns, neither by age nor gender. However, after incorporating isotype-specific analysis and considering CSR information into hierarchical clustering the situation changes. For the first time the donors cluster according to age and separate into young adults and elderly donors (>50). As a direct consequence, this clustering defines the onset of immune senescence at the age of fifty and beyond. The observed age-dependent reduction of CSR ability proposes a feasible explanation why reduced efficacy of vaccination is seen in the elderly and implies that novel vaccine strategies for the elderly should include the “Golden Agers”.
Paralogs for several proteins implicated in neurodegenerative disorders have been identified and explored to further facilitate the identification of molecular mechanisms contributing to disease pathogenesis. For the disease-causing protein in spinocerebellar ataxia type 2, ataxin-2, a paralog of unknown function, termed ataxin-2-like, has been described. We discovered that ataxin-2-like associates with known interaction partners of ataxin-2, the RNA helicase DDX6 and the poly(A)-binding protein, and with ataxin-2 itself. Furthermore, we found that ataxin-2-like is a component of stress granules. Interestingly, sole ataxin-2-like overexpression led to the induction of stress granules, while a reduction of stress granules was detected in case of a low ataxin-2-like level. Finally, we observed that overexpression of ataxin-2-like as well as its reduction has an impact on the presence of microscopically visible processing bodies. Thus, our results imply a functional overlap between ataxin-2-like and ataxin-2, and further indicate a role for ataxin-2-like in the regulation of stress granules and processing bodies.
Knowledge of the various interactions between molecules in the cell is crucial for understanding cellular processes in health and disease. Currently available interaction databases, being largely complementary to each other, must be integrated to obtain a comprehensive global map of the different types of interactions. We have previously reported the development of an integrative interaction database called ConsensusPathDB (http://ConsensusPathDB.org) that aims to fulfill this task. In this update article, we report its significant progress in terms of interaction content and web interface tools. ConsensusPathDB has grown mainly due to the integration of 12 further databases; it now contains 215 541 unique interactions and 4601 pathways from overall 30 databases. Binary protein interactions are scored with our confidence assessment tool, IntScore. The ConsensusPathDB web interface allows users to take advantage of these integrated interaction and pathway data in different contexts. Recent developments include pathway analysis of metabolite lists, visualization of functional gene/metabolite sets as overlap graphs, gene set analysis based on protein complexes and induced network modules analysis that connects a list of genes through various interaction types. To facilitate the interactive, visual interpretation of interaction and pathway data, we have re-implemented the graph visualization feature of ConsensusPathDB using the Cytoscape.js library.
The glycolytic enzyme pyruvate kinase (PK) is required for cancer development, and has been implicated in the metabolic transition from oxidative to fermentative metabolism, the Warburg effect. However, the global metabolic response that follows changes in PK activity is not yet fully understood. Using shotgun proteomics, we identified 31 yeast proteins that were regulated in a PK-dependent manner. Selective reaction monitoring confirmed that their expression was dependent on PK isoform, level and activity. Most of the PK targets were amino acid metabolizing enzymes or factors of protein translation, indicating that PK plays a global regulatory role in biosynthethic amino acid metabolism. Indeed, we found strongly altered amino acid profiles when PK levels were changed. Low PK levels increased the cellular glutamine and glutamate concentrations, but decreased the levels of seven amino acids including serine and histidine. To test for evolutionary conservation of this PK function, we quantified orthologues of the identified PK targets in thyroid follicular adenoma, a tumor characterized by high PK levels and low respiratory activity. Aminopeptidase AAP-1 and serine hydroxymethyltransferase SHMT1 both showed PKM2- concentration dependence, and were upregulated in the tumor. Thus, PK expression levels and activity were important for maintaining cellular amino acid homeostasis. Mediating between energy production, ROS clearance and amino acid biosynthesis, PK thus plays a central regulatory role in the metabolism of proliferating cells.
cancer metabolism; pyruvate kinase; proteomics; amino acid profile
In this review, we discuss the latest targeted enrichment methods and aspects of their utilization along with second-generation sequencing for complex genome analysis. In doing so, we provide an overview of issues involved in detecting genetic variation, for which targeted enrichment has become a powerful tool. We explain how targeted enrichment for next-generation sequencing has made great progress in terms of methodology, ease of use and applicability, but emphasize the remaining challenges such as the lack of even coverage across targeted regions. Costs are also considered versus the alternative of whole-genome sequencing which is becoming ever more affordable. We conclude that targeted enrichment is likely to be the most economical option for many years to come in a range of settings.
targeted enrichment; next-generation sequencing; genome partitioning; exome; genetic variation
miRNAs are short single-stranded non-coding RNAs involved in post-transcriptional gene regulation that play a major role in normal biological functions and diseases. Little is currently known about how expression of miRNAs is regulated. We surveyed variation in miRNA abundance in the hippocampus of mouse inbred strains, allowing us to take a genetic approach to the study of miRNA regulation, which is novel for miRNAs. The BXD recombinant inbred panel is a very well characterized genetic reference panel which allows quantitative trait locus (QTL) analysis of miRNA abundance and detection of correlates in a large store of brain and behavioural phenotypes.
We found five suggestive trans QTLs for the regulation of miRNAs investigated. Further analysis of these QTLs revealed two genes, Tnik and Phf17, under the miR-212 regulatory QTLs, whose expression levels were significantly correlated with miR-212 expression. We found that miR-212 expression is correlated with cocaine-related behaviour, consistent with a reported role for this miRNA in the control of cocaine consumption. miR-31 is correlated with anxiety and alcohol related behaviours. KEGG pathway analysis of each miRNA’s expression correlates revealed enrichment of pathways including MAP kinase, cancer, long-term potentiation, axonal guidance and WNT signalling.
The BXD reference panel allowed us to establish genetic regulation and characterize biological function of specific miRNAs. QTL analysis enabled detection of genetic loci that regulate the expression of these miRNAs. eQTLs that regulate miRNA abundance are a new mechanism by which genetic variation influences brain and behaviour. Analysis of one of these QTLs revealed a gene, Tnik, which may regulate the expression of a miRNA, a molecular pathway and a behavioural phenotype. Evidence of genetic covariation of miR-212 abundance and cocaine related behaviours is strongly supported by previous functional studies, demonstrating the value of this approach for discovery of new functional roles and downstream processes regulated by miRNA.
Non-alcoholic fatty liver disease comprises a broad spectrum of disease states ranging from simple steatosis to non-alcoholic steatohepatitis. As a result of increases in the prevalences of obesity, insulin resistance, and hyperlipidemia, the number of people with hepatic steatosis continues to increase. Differences in susceptibility to steatohepatitis and its progression to cirrhosis have been attributed to a complex interplay of genetic and external factors all addressing the intracellular network. Increase in sugar or refined carbohydrate consumption results in an increase of insulin and insulin resistance that can lead to the accumulation of fat in the liver. Here we demonstrate how a multidisciplinary approach encompassing cellular reprogramming, transcriptomics, proteomics, metabolomics, modeling, network reconstruction, and data management can be employed to unveil the mechanisms underlying the progression of steatosis. Proteomics revealed reduced AKT/mTOR signaling in fibroblasts derived from steatosis patients and further establishes that the insulin-resistant phenotype is present not only in insulin-metabolizing central organs, e.g., the liver, but is also manifested in skin fibroblasts. Transcriptome data enabled the generation of a regulatory network based on the transcription factor SREBF1, linked to a metabolic network of glycerolipid, and fatty acid biosynthesis including the downstream transcriptional targets of SREBF1 which include LIPIN1 (LPIN) and low density lipoprotein receptor. Glutathione metabolism was among the pathways enriched in steatosis patients in comparison to healthy controls. By using a model of the glutathione pathway we predict a significant increase in the flux through glutathione synthesis as both gamma-glutamylcysteine synthetase and glutathione synthetase have an increased flux. We anticipate that a larger cohort of patients and matched controls will confirm our preliminary findings presented here.
NAFLD; induced pluripotent stem cells; sterol biosynthesis; glutathione metabolism; lipid metabolism; AKT/mTOR signaling; systems biology; modeling
Saccharomyces cerevisiae strain W303 is a widely used model organism. However, little is known about its genetic origins, as it was created in the 1970s from crossing yeast strains of uncertain genealogy. To obtain insights into its ancestry and physiology, we sequenced the genome of its variant W303-K6001, a yeast model of ageing research. The combination of two next-generation sequencing (NGS) technologies (Illumina and Roche/454 sequencing) yielded an 11.8 Mb genome assembly at an N50 contig length of 262 kb. Although sequencing was substantially more precise and sensitive than whole-genome tiling arrays, both NGS platforms produced a number of false positives. At a 378× average coverage, only 74 per cent of called differences to the S288c reference genome were confirmed by both techniques. The consensus W303-K6001 genome differs in 8133 positions from S288c, predicting altered amino acid sequence in 799 proteins, including factors of ageing and stress resistance. The W303-K6001 (85.4%) genome is virtually identical (less than equal to 0.5 variations per kb) to S288c, and thus originates in the same ancestor. Non-S288c regions distribute unequally over the genome, with chromosome XVI the most (99.6%) and chromosome XI the least (54.5%) S288c-like. Several of these clusters are shared with Σ1278B, another widely used S288c-related model, indicating that these strains share a second ancestor. Thus, the W303-K6001 genome pictures details of complex genetic relationships between the model strains that date back to the early days of experimental yeast genetics. Moreover, this study underlines the necessity of combining multiple NGS and genome-assembling techniques for achieving accurate variant calling in genomic studies.
next-generation sequencing; yeast models; phylogeny reconstruction; mapping
Alternative splicing is a fundamental posttranscriptional mechanism for controlling gene expression, and splicing defects have been linked to various human disorders. The splicing factor FOX-2 is part of a main protein interaction hub in a network related to human inherited ataxias, however, its impact remains to be elucidated. Here, we focused on the reported interaction between FOX-2 and ataxin-1, the disease-causing protein in spinocerebellar ataxia type 1. In this line, we further evaluated this interaction by yeast-2-hybrid analyses and co-immunoprecipitation experiments in mammalian cells. Interestingly, we discovered that FOX-2 localization and splicing activity is affected in the presence of nuclear ataxin-1 inclusions. Moreover, we observed that FOX-2 directly interacts with ataxin-2, a protein modulating spinocerebellar ataxia type 1 pathogenesis. Finally, we provide evidence that splicing of pre-mRNA of ataxin-2 depends on FOX-2 activity, since reduction of FOX-2 levels led to increased skipping of exon 18 in ataxin-2 transcripts. Most striking, we observed that ataxin-1 overexpression has an effect on this splicing event as well. Thus, our results demonstrate that FOX-2 is involved in splicing of ataxin-2 transcripts and that this splicing event is altered by overexpression of ataxin-1.
Modern biomedical research is often organized in collaborations involving labs worldwide. In particular in systems biology, complex molecular systems are analyzed that require the generation and interpretation of heterogeneous data for their explanation, for example ranging from gene expression studies and mass spectrometry measurements to experimental techniques for detecting molecular interactions and functional assays. XML has become the most prominent format for representing and exchanging these data. However, besides the development of standards there is still a fundamental lack of data integration systems that are able to utilize these exchange formats, organize the data in an integrative way and link it with applications for data interpretation and analysis.
We have developed DIPSBC, an interactive data integration platform supporting collaborative research projects, based on Foswiki, Solr/Lucene, and specific helper applications. We describe the main features of the implementation and highlight the performance of the system with several use cases. All components of the system are platform independent and open-source developments and thus can be easily adopted by researchers. An exemplary installation of the platform which also provides several helper applications and detailed instructions for system usage and setup is available at http://dipsbc.molgen.mpg.de.
DIPSBC is a data integration platform for medium-scale collaboration projects that has been tested already within several research collaborations. Because of its modular design and the incorporation of XML data formats it is highly flexible and easy to use.
Data integration; XML; Data visualization
Inhibition of Hedgehog (HH)/GLI signalling in cancer is a promising therapeutic approach. Interactions between HH/GLI and other oncogenic pathways affect the strength and tumourigenicity of HH/GLI. Cooperation of HH/GLI with epidermal growth factor receptor (EGFR) signalling promotes transformation and cancer cell proliferation in vitro. However, the in vivo relevance of HH-EGFR signal integration and the critical downstream mediators are largely undefined. In this report we show that genetic and pharmacologic inhibition of EGFR signalling reduces tumour growth in mouse models of HH/GLI driven basal cell carcinoma (BCC). We describe HH-EGFR cooperation response genes including SOX2, SOX9, JUN, CXCR4 and FGF19 that are synergistically activated by HH-EGFR signal integration and required for in vivo growth of BCC cells and tumour-initiating pancreatic cancer cells. The data validate EGFR signalling as drug target in HH/GLI driven cancers and shed light on the molecular processes controlled by HH-EGFR signal cooperation, providing new therapeutic strategies based on combined targeting of HH-EGFR signalling and selected downstream target genes.
cancer; epidermal growth factor receptor; Hedgehog signalling; signal transduction
The heat shock protein 90 (Hsp90) is required for the stability of many signalling kinases. As a target for cancer therapy it allows the simultaneous inhibition of several signalling pathways. However, its inhibition in healthy cells could also lead to severe side effects. This is the first comprehensive analysis of the response to Hsp90 inhibition at the kinome level.
We quantitatively profiled the effects of Hsp90 inhibition by geldanamycin on the kinome of one primary (Hs68) and three tumour cell lines (SW480, U2OS, A549) by affinity proteomics based on immobilized broad spectrum kinase inhibitors ("kinobeads"). To identify affected pathways we used the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway classification. We combined Hsp90 and proteasome inhibition to identify Hsp90 substrates in Hs68 and SW480 cells. The mutational status of kinases from the used cell lines was determined using next-generation sequencing. A mutation of Hsp90 candidate client RIPK2 was mapped onto its structure.
We measured relative abundances of > 140 protein kinases from the four cell lines in response to geldanamycin treatment and identified many new potential Hsp90 substrates. These kinases represent diverse families and cellular functions, with a strong representation of pathways involved in tumour progression like the BMP, MAPK and TGF-beta signalling cascades. Co-treatment with the proteasome inhibitor MG132 enabled us to classify 64 kinases as true Hsp90 clients. Finally, mutations in 7 kinases correlate with an altered response to Hsp90 inhibition. Structural modelling of the candidate client RIPK2 suggests an impact of the mutation on a proposed Hsp90 binding domain.
We propose a high confidence list of Hsp90 kinase clients, which provides new opportunities for targeted and combinatorial cancer treatment and diagnostic applications.
MicroRNAs have gained significant interest due to their widespread occurrence and diverse functions as regulatory molecules, which are essential for cell division, growth, development and apoptosis in eukaryotes. The epidermal growth factor receptor (EGFR) signaling pathway is one of the best investigated cellular signaling pathways regulating important cellular processes and its deregulation is associated with severe diseases, such as cancer. In this study, we introduce a systems biological model of the EGFR signaling pathway integrating validated miRNA-target information according to diverse studies, in order to demonstrate essential roles of miRNA within this pathway. The model consists of 1241 reactions and contains 241 miRNAs. We analyze the impact of 100 specific miRNA inhibitors (anit-miRNAs) on this pathway and propose that the embedded miRNA-network can help to identify new drug targets of the EGFR signaling pathway and thereby support the development of new therapeutic strategies against cancer.
SELEX is an iterative process in which highly diverse synthetic nucleic acid libraries are selected over many rounds to finally identify aptamers with desired properties. However, little is understood as how binders are enriched during the selection course. Next-generation sequencing offers the opportunity to open the black box and observe a large part of the population dynamics during the selection process.
We have performed a semi-automated SELEX procedure on the model target streptavidin starting with a synthetic DNA oligonucleotide library and compared results obtained by the conventional analysis via cloning and Sanger sequencing with next-generation sequencing. In order to follow the population dynamics during the selection, pools from all selection rounds were barcoded and sequenced in parallel.
High affinity aptamers can be readily identified simply by copy number enrichment in the first selection rounds. Based on our results, we suggest a new selection scheme that avoids a high number of iterative selection rounds while reducing time, PCR bias, and artifacts.