Green fluorescent protein labeling of primordial germ cells using a nontransgenic method and its application for germ cell transplantation in salmonidae

Transplanting primordial germ cells (PGCs) has a number of potential applications in fish bioengineering. Previously, we established a system to visualize live PGCs in the rainbow trout by introducing the green fluorescent protein (Gfp) gene driven by rainbow trout vasa gene regulatory regions. However, for PGC transplantation to be practically useful in aquaculture, visualization of PGCs using a nontransgenic technique is required. In this study, we demonstrate a method for labeling PGCs from various fish species by introducing chimeric RNAs composed of the Gfp coding region and vasa gene 3'-untranslated regions (UTRs); these sequences play a critical role in stabilizing mRNA in zebrafish PGCs. The GFP chimeric RNAs, including vasa 3'-UTR RNAs from rainbow trout, Nibe croaker, and zebrafish, were microinjected into the cytoplasm of fertilized eggs of several Salmonidae species. All the resulting embryos showed specific labeling in PGCs after the somatogenesis stage, which continued to be visible for at least 50 days. To apply this technique to PGC transplantation, PGCs labeled with chimeric RNA were microinjected into the peritoneal cavity of newly hatched salmonid embryos. The GFP labeling was sufficiently long-lived for the initial stage of donor PGC behavior to be followed in the recipient embryos. Importantly, donor PGCs from brown trout and masu salmon were incorporated into xenogeneic genital ridges in recipient rainbow trout. This nontransgenic method for labeling fish PGCs should be extremely useful for applications of PGC transplantation where the resulting progeny are to be released into the environment, such as PGC cryopreservation for fish stocks and surrogate brood stock technology.     

Acyldepsipeptide antibiotics kill mycobacteria by preventing the physiological functions of the ClpP1P2 protease

The Clp protease complex in Mycobacterium tuberculosis is unusual in its composition, functional importance and activation mechanism. Whilst most bacterial species contain a single ClpP protein that is dispensable for normal growth, mycobacteria have two ClpPs, ClpP1 and ClpP2, which are essential for viability and together form the ClpP1P2 tetradecamer. Acyldepsipeptide antibiotics of the ADEP class inhibit the growth of Gram‐positive firmicutes by activating ClpP and causing unregulated protein degradation. Here we show that, in contrast, mycobacteria are killed by ADEP through inhibition of ClpP function. Although ADEPs can stimulate purified M. tuberculosis ClpP1P2 to degrade larger peptides and unstructured proteins, this effect is weaker than for ClpP from other bacteria and depends on the presence of an additional activating factor (e.g. the dipeptide benzyloxycarbonyl‐leucyl‐leucine in vitro) to form the active ClpP1P2 tetradecamer. The cell division protein FtsZ, which is a particularly sensitive target for ADEP‐activated ClpP in firmicutes, is not degraded in mycobacteria. Depletion of the ClpP1P2 level in a conditional Mycobacterium bovis BCG mutant enhanced killing by ADEP unlike in other bacteria. In summary, ADEPs kill mycobacteria by preventing interaction of ClpP1P2 with the regulatory ATPases, ClpX or ClpC1, thus inhibiting essential ATP‐dependent protein degradation.     

Correction to: Comparative analysis of sperm motility in liquid and seminal coagulum portions between Bornean orangutan (Pongo pygmaeus) and chimpanzee (Pan troglodytes)

Primates - In the original publication of the article, the coauthor “Takashi Hayakawa” was wrongly assigned as co-corresponding author.     

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.     

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.     

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.     

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.