Mesoderm-specific B104 expression in the Drosophila embryo is mediated by internal cis-acting elements of the transposon

The Drosophila melanogaster genome contains about 100 copies of the B104 transposable element, which is strongly expressed during embryogenesis. Here we show that B104 expression is restricted to the esophageal and amnioproctodeal regions of the embryo and to the developing mesoderm. Mesoderm-specific B104 expression requires the activity of the mesoderm-determining factors twist and snail. Virtually the same expression patterns were observed in Drosophila yakuba, a species that a separated from D. melanogaster by some 15 million years of evolution. We show that B104 expression is directed by internal sequences of the retrotransposon that are capable of acting as a cis-acting regulatory element in front of a heterologous Drosophila promoter. Our findings suggest that retrotransposon insertions can affect the expression patterns of endogenous genes by adding and distributing specific cis-acting control elements throughout the host genome. We therefore propose that transposable elements in addition to reducing the fitness of their hosts may also provide a rich pool of cis-acting sequences that contribute to the long-term evolutionary potential of the population in a beneficial manner.     

Genomic deletion and promoter methylation status of Hypermethylated in Cancer 1 (HIC1) in mantle cell lymphoma

Mantle cell lymphomas (MCL), characterized by the t(11;14)(q13;q32), frequently carry secondary genetic alterations such as deletions in chromosome 17p involving the TP53 locus. Given that the association between TP53-deletions and concurrent mutations of the remaining allele is weak and based on our recent report that the Hypermethylated in Cancer 1 (HIC1) gene, that is located telomeric to the TP53 gene, may be targeted by deletions in 17p in diffuse large B-cell lymphoma (DLBCL), we investigated whether HIC1 inactivations might also occur in MCL. Monoallelic deletions of the TP53 locus were detected in 18 out of 59 MCL (31%), while overexpression of p53 protein occurred in only 8 out of 18 of these MCL (44%). In TP53-deleted MCL, the HIC1 gene locus was co-deleted in 11 out of 18 cases (61%). However, neither TP53 nor HIC1 deletions did affect survival of MCL patients. In most analyzed cases, no hypermethylation of the HIC1 exon 1A promoter was observed (17 out of 20, 85%). However, in MCL cell lines without HIC1-hypermethylation, the mRNA expression levels of HIC1 were nevertheless significantly reduced, when compared to reactive lymph node specimens, pointing to the occurrence of mechanisms other than epigenetic or genetic events for the inactivation of HIC1 in this entity.     

The tyrosine‐sulfated peptide receptors PSKR1 and PSY1R modify the immunity of Arabidopsis to biotrophic and necrotrophic pathogens in an antagonistic manner

The tyrosine‐sulfated peptides PSKα and PSY1 bind to specific leucine‐rich repeat surface receptor kinases and control cell proliferation in plants. In a reverse genetic screen, we identified the phytosulfokine (PSK) receptor PSKR1 as an important component of plant defense. Multiple independent loss‐of‐function mutants in PSKR1 are more resistant to biotrophic bacteria, show enhanced pathogen‐associated molecular pattern responses and less lesion formation after infection with the bacterial pathogen Pseudomonas syringae pv. tomato DC3000. By contrast, pskr1 mutants are more susceptible to necrotrophic fungal infection with Alternaria brassicicola, show more lesion formation and fungal growth which is not observed on wild‐type plants. The antagonistic effect on biotrophic and necrotrophic pathogen resistance is reflected by enhanced salicylate and reduced jasmonate responses in the mutants, suggesting that PSKR1 suppresses salicylate‐dependent defense responses. Detailed analysis of single and multiple mutations in the three paralogous genes PSKR1, ‐2 and PSY1‐receptor (PSY1R) determined that PSKR1 and PSY1R, but not PSKR2, have a partially redundant effect on plant immunity. In animals and plants, peptide sulfation is catalyzed by a tyrosylprotein sulfotransferase (TPST). Mutants lacking TPST show increased resistance to bacterial infection and increased susceptibility to fungal infection, mimicking the triple receptor mutant phenotypes. Feeding experiments with PSKα in tpst‐1 mutants partially restore the defense‐related phenotypes, indicating that perception of the PSKα peptide has a direct effect on plant defense. These results suggest that the PSKR subfamily integrates growth‐promoting and defense signals mediated by sulfated peptides and modulates cellular plasticity to allow flexible adjustment to environmental changes.     

Human male recombination maps for individual chromosomes

Meiotic recombination is essential for the segregation of chromosomes and the formation of normal haploid gametes, yet we know very little about the meiotic process in humans. We present the first (to our knowledge) recombination maps for every autosome in the human male obtained by new immunofluorescence techniques followed by centromere-specific multicolor fluorescence in situ hybridization in human spermatocytes. The mean frequency of autosomal recombination foci was 49.8+/-4.3, corresponding to a genetic length of 2,490 cM. All autosomal bivalents had at least one recombination focus. In contrast, the XY bivalent had a recombination focus in 73% of nuclei, suggesting that a relatively large proportion of spermatocytes may be at risk for nondisjunction of the XY bivalent or elimination by meiotic arrest. There was a very strong correlation between mean length of the synaptonemal complex (SC) and the number of recombination foci per SC. Each bivalent presented a distinct distribution of recombination foci, but in general, foci were near the distal parts of the chromosome, with repression of foci near the centromere. The position of recombination foci demonstrated positive interference, but, in rare instances, foci were very close to one another.     

Combination of a Proteomics Approach and Reengineering of Meso Scale Network Models for Prediction of Mode-of-Action for Tyrosine Kinase Inhibitors

In drug discovery, the characterisation of the precise modes of action (MoA) and of unwanted off-target effects of novel molecularly targeted compounds is of highest relevance. Recent approaches for identification of MoA have employed various techniques for modeling of well defined signaling pathways including structural information, changes in phenotypic behavior of cells and gene expression patterns after drug treatment. However, efficient approaches focusing on proteome wide data for the identification of MoA including interference with mutations are underrepresented. As mutations are key drivers of drug resistance in molecularly targeted tumor therapies, efficient analysis and modeling of downstream effects of mutations on drug MoA is a key to efficient development of improved targeted anti-cancer drugs. Here we present a combination of a global proteome analysis, reengineering of network models and integration of apoptosis data used to infer the mode-of-action of various tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML) cell lines expressing wild type as well as TKI resistance conferring mutants of BCR-ABL. The inferred network models provide a tool to predict the main MoA of drugs as well as to grouping of drugs with known similar kinase inhibitory activity patterns in comparison to drugs with an additional MoA. We believe that our direct network reconstruction approach, demonstrated on proteomics data, can provide a complementary method to the established network reconstruction approaches for the preclinical modeling of the MoA of various types of targeted drugs in cancer treatment. Hence it may contribute to the more precise prediction of clinically relevant on- and off-target effects of TKIs.     

Cost of resistance and tolerance under competition: the defense-stress benefit hypothesis

Defense costs provide a major explanation for why plants in nature have not evolved to be better defended against pathogens and herbivores; however, evidence for defense costs is often lacking. Plants defend by deploying resistance traits that reduce damage, and tolerance traits that reduce the fitness effects of damage. We first tested the defense-stress cost (DSC) hypothesis that costs of defenses increase and become important under competitive stress. In a greenhouse experiment, uniparental maternal families of the host plant Arabis perennans were grown in the presence and absence of the bunch grass Bouteloua gracilis and the herbivore Plutella xylostella. Costs of resistance and tolerance manifest as reduced growth in the absence of herbivory were significant when A. perennans grew alone, but not in the competitive environment, in contrast to the DSC hypothesis. We then tested the defense-stress benefit (DSB) hypothesis that plant defenses may benefit plants in competitive situations thereby reducing net costs. For example, chemical resistance agents and tolerance may also have functions in competitive interactions. To test the DSB hypothesis, we compared differentially competitive populations for defense costs, assuming that poorer competitors from less dense habitats were less likely to have evolved defenses that also function in competition. Without competitive benefits of defenses, poorer competitors were expected to have higher net costs of defenses under competition in accordance with DSB. Populations of A. perennans and A. drummondii that differed dramatically in competitiveness were compared for costs, and as the DSB hypothesis predicts, only the poor competitor population showed costs of resistance under competition. However, cost of tolerance under competition did not differ among populations, suggesting that the poor competitors might have evolved a general stress tolerance. Although the DSC hypothesis may explain cases where defense costs increase under stress, the DSB hypothesis may explain some cases where costs decrease under competitive stress.     

Functional Proteomics Identifies Acinus L as a Direct Insulin- and Amino Acid-Dependent Mammalian Target of Rapamycin Complex 1 (mTORC1) Substrate

The serine/threonine kinase mammalian target of rapamycin (mTOR) governs growth, metabolism, and aging in response to insulin and amino acids (aa), and is often activated in metabolic disorders and cancer. Much is known about the regulatory signaling network that encompasses mTOR, but surprisingly few direct mTOR substrates have been established to date. To tackle this gap in our knowledge, we took advantage of a combined quantitative phosphoproteomic and interactomic strategy. We analyzed the insulin- and aa-responsive phosphoproteome upon inhibition of the mTOR complex 1 (mTORC1) component raptor, and investigated in parallel the interactome of endogenous mTOR. By overlaying these two datasets, we identified acinus L as a potential novel mTORC1 target. We confirmed acinus L as a direct mTORC1 substrate by co-immunoprecipitation and MS-enhanced kinase assays. Our study delineates a triple proteomics strategy of combined phosphoproteomics, interactomics, and MS-enhanced kinase assays for the de novo-identification of mTOR network components, and provides a rich source of potential novel mTOR interactors and targets for future investigation.The serine/threonine kinase mammalian target of rapamycin (mTOR)¹ is conserved in all eukaryotes from yeast to mammals (1). mTOR is a central controller of cellular growth, whole body metabolism, and aging, and is frequently deregulated in metabolic diseases and cancer (2). Consequently, mTOR as well as its upstream and downstream cues are prime candidates for targeted drug development to alleviate the causes and symptoms of age-related diseases (3, 4). The identification of novel mTOR regulators and effectors thus remains a major goal in biomedical research. A vast body of literature describes a complex signaling network around mTOR. However, our current comparatively detailed knowledge of mTOR''s upstream cues contrasts with a rather limited set of known direct mTOR substrates.mTOR exists in two structurally and functionally distinct multiprotein complexes, termed mTORC1 and mTORC2. Both complexes contain mTOR kinase as well as the proteins mLST8 (mammalian lethal with SEC thirteen 8) (5–7), and deptor (DEP domain-containing mTOR-interacting protein) (8). mTORC1 contains the specific scaffold protein raptor (regulatory-associated protein of mTOR) (9, 10), whereas mTORC2 contains the specific binding partners rictor (rapamycin-insensitive companion of mTOR) (5–7), mSIN1 (TORC2 subunit MAPKAP1) (11–13), and PRR5/L (proline rich protein 5/-like) (14–16). The small macrolide rapamycin acutely inhibits mTORC1, but can also have long-term effects on mTORC2 (17, 18). More recently, ATP-analogs (19) that block both mTOR complexes, such as Torin 1 (20), have been developed. As rapamycin has already been available for several decades, our knowledge of signaling events associated with mTORC1 as well as its metabolic inputs and outputs is much broader as compared with mTORC2. mTORC1 responds to growth factors (insulin), nutrients (amino acids, aa) and energy (ATP). In response, mTORC1 activates anabolic processes (protein, lipid, nucleotide synthesis) and blocks catabolic processes (autophagy) to ultimately allow cellular growth (21). The insulin signal is transduced to mTORC1 via the insulin receptor (IR), and the insulin receptor substrate (IRS), which associates with class I phosphoinositide 3-kinases (PI3Ks). Subsequent phosphatidylinositol 3,4,5 trisphosphate (PIP3) binding leads to relocalization of the AGC kinases phosphoinositide-dependent protein kinase 1 (PDK1) and Akt (also termed protein kinase B, PKB) to the plasma membrane, where PDK1 phosphorylates Akt at T308 (22, 23). In response, Akt phosphorylates and inhibits the heterocomplex formed by the tuberous sclerosis complex proteins 1 and 2 (TSC1-TSC2) (24, 25). TSC1-TSC2 is the inhibitory, GTPase-activating protein for the mTORC1-inducing GTPase Ras homolog enriched in brain (rheb) (26–30), which activates mTORC1 at the lysosome. mTORC1 localization depends on the presence of aa, which in a rag GTPase-dependent manner induce mTORC1 relocalization to lysosomes (31, 32). Low energy levels are sensed by the AMP-dependent kinase (AMPK), which in turn phosphorylates the TSC1-TSC2 complex (33) and raptor (34), thereby inhibiting mTORC1.mTORC1 phosphorylates its well-described downstream substrate S6-kinase (S6K) at T389, the proline-rich Akt substrate of 40 kDa (PRAS40) at S183, and the translational repressor 4E-binding protein (4E-BP) at T37/46 (35–41). Unphosphorylated 4E-BP binds and inhibits the translation initiation factor 4G (eIF4G), which within the eIF4F complex mediates the scanning process of the ribosome to reach the start codon. Phosphorylation by mTORC1 inhibits 4E-BP''s interaction with eIF4E, thus allowing for assembly of eIF4F, and translation initiation (42, 43). More recently, also the IR-activating growth factor receptor-bound protein 10 (Grb10) (44, 45), the autophagy-initiating Unc-51-like kinase ULK1 (46), and the trifunctional enzymatic complex CAD composed of carbamoyl-phosphate synthetase 2, aspartate transcarbamoylase, and dihydroorotase (47, 48), which is required for nucleotide synthesis, have been described as direct mTORC1 substrates.mTORC2 activation is mostly described to be mediated by insulin, and this is mediated by a PI3K variant that is distinct from the PI3K upstream of mTORC1 (49, 50). Furthermore, mTORC2 responds to aa (5, 51). In response, mTORC2 phosphorylates the AGC kinases Akt at S473 (52–55), and serum and glucocorticoid kinase SGK (56) and protein kinase C alpha (PKCalpha) (7) within their hydrophobic motifs (57, 58), to control cellular motility (5–7), hepatic glycolysis, and lipogenesis (59). In addition, mTOR autophosphorylation at S2481 has been established as an mTORC2 readout in several cell lines including HeLa cells (49).Given the multiplicity of effects via which mTOR controls cellular and organismal growth and metabolism, it is surprising that only relatively few direct mTOR substrates have been established to date. Proteomic studies are widely used to identify novel interactors and substrates of protein kinases. Two studies have recently shed light on the interaction of rapamycin and ATP-analog mTOR inhibitors with TSC2 inhibition in mammalian cells (44, 45), and one study has analyzed the effects of raptor and rictor knockouts in non-stimulated cells (48).In this work, we report a functional proteomics approach to study mTORC1 substrates. We used an inducible raptor knockdown to inhibit mTORC1 in HeLa cells, and analyzed the effect in combination with insulin and aa induction by quantitative phosphoproteomics using stable isotope labeling by amino acids in cell culture (SILAC) (60). In parallel, we purified endogenous mTOR complexes and studied the interactome of mTOR by SILAC-MS. Through comparative data evaluation, we identified acinus L as a potential novel aa/insulin-sensitive mTOR substrate. We further validated acinus L by co-immunoprecipitation and MS-enhanced kinase assays as a new direct mTORC1 substrate.     

Erratum to: Rostrocaudal Dynamics of CSF Biomarkers

Neurochemical Research -     

Dating the arthropod tree based on large-scale transcriptome data

Molecular sequences do not only allow the reconstruction of phylogenetic relationships among species, but also provide information on the approximate divergence times. Whereas the fossil record dates the origin of most multicellular animal phyla during the Cambrian explosion less than 540 million years ago(mya), molecular clock calculations usually suggest much older dates. Here we used a large multiple sequence alignment derived from Expressed Sequence Tags and genomes comprising 129genes (37,476 amino acid positions) and 117 taxa, including 101 arthropods. We obtained consistent divergence time estimates applying relaxed Bayesian clock models with different priors and multiple calibration points. While the influence of substitution rates, missing data, and model priors were negligible, the clock model had significant effect. A log-normal autocorrelated model was selected on basis of cross-validation. We calculated that arthropods emerged ~600 mya. Onychophorans (velvet worms) and euarthropods split ~590 mya, Pancrustacea and Myriochelata ~560 mya, Myriapoda and Chelicerata ~555 mya, and 'Crustacea' and Hexapoda ~510 mya. Endopterygote insects appeared ~390 mya. These dates are considerably younger than most previous molecular clock estimates and in better agreement with the fossil record. Nevertheless, a Precambrian origin of arthropods and other metazoan phyla is still supported. Our results also demonstrate the applicability of large datasets of random nuclear sequences for approximating the timing of multicellular animal evolution.     

Distant land use affects terrestrial and aquatic habitats of high naturalness

Biotas from all ecosystems need to respond to factors that determine habitat suitability. These factors originate from different scales. Effects can be assumed to be hierarchical in the order large-scale geographic > regional > local > small-scale in-habitat factors. We aimed at the identification of general patterns by comparisons between ecosystems (forest floor snails, hololimnic stream macroinvertebrates) and across scales, and include potential seasonal effects. Sampling sites displayed signs of naturalness, such as high levels of deadwood accumulation in the forests, or a lack of artificial stream bed fixation plus a “good” to “high” score for the assemblage-derived Multimetric Index (MMI) in the streams. Terrestrial and aquatic assemblages of non-emergent taxa fluctuated independent of seasonal effects. They differed in their relative correlation with environmental matrices with quasi-concentric effects in forests, and longitudinal effects in streams. Large-scale factors, namely geographic position, strongly influenced assemblage turnover, but the effect is based on a high covariation between geographic position and environmental factors. We thus extracted variables that best explained species turnover after correcting for spatio-temporal effects. The terrestrial community assembling was habitat-based and mainly responded to soil acidification, distance to disturbances, and regional scale deforestation and deciduous/mixed forest cover. The stream assemblages were structured by regional pasture cover, organic pollution, regional deciduous forest cover and microlithal cover. Apparently, community assembly occurs along with changes in regional forest cover and the transport of nutrients and matter that can originate from a distance, irrespective of ecosystem and assumed “naturalness”.