SHBG Is an Important Factor in Stemness Induction of Cells by DHT In Vitro and Associated with Poor Clinical Features of Prostate Carcinomas

Androgen plays a vital role in prostate cancer development. However, it is not clear whether androgens influence stem-like properties of prostate cancer, a feature important for prostate cancer progression. In this study, we show that upon DHT treatment in vitro, prostate cancer cell lines LNCaP and PC-3 were revealed with higher clonogenic potential and higher expression levels of stemness related factors CD44, CD90, Oct3/4 and Nanog. Moreover, sex hormone binding globulin (SHBG) was also simultaneously upregulated in these cells. When the SHBG gene was blocked by SHBG siRNA knock-down, the induction of Oct3/4, Nanog, CD44 and CD90 by DHT was also correspondingly blocked in these cells. Immunohistochemical evaluation of clinical samples disclosed weakly positive, and areas negative for SHBG expression in the benign prostate tissues, while most of the prostate carcinomas were strongly positive for SHBG. In addition, higher levels of SHBG expression were significantly associated with higher Gleason score, more seminal vesicle invasions and lymph node metastases. Collectively, our results show a role of SHBG in upregulating stemness of prostate cancer cells upon DHT exposure in vitro, and SHBG expression in prostate cancer samples is significantly associated with poor clinicopathological features, indicating a role of SHBG in prostate cancer progression.     

Relationships between Long-Term Demography and Weather in a Sub-Arctic Population of Common Eider

Effects of local weather on individuals and populations are key drivers of wildlife responses to climatic changes. However, studies often do not last long enough to identify weather conditions that influence demographic processes, or to capture rare but extreme weather events at appropriate scales. In Iceland, farmers collect nest down of wild common eider Somateria mollissima and many farmers count nests within colonies annually, which reflects annual variation in the number of breeding females. We collated these data for 17 colonies. Synchrony in breeding numbers was generally low between colonies. We evaluated 1) demographic relationships with weather in nesting colonies of common eider across Iceland during 1900–2007; and 2) impacts of episodic weather events (aberrantly cold seasons or years) on subsequent breeding numbers. Except for episodic events, breeding numbers within a colony generally had no relationship to local weather conditions in the preceding year. However, common eider are sexually mature at 2–3 years of age and we found a 3-year time lag between summer weather and breeding numbers for three colonies, indicating a positive effect of higher pressure, drier summers for one colony, and a negative effect of warmer, calmer summers for two colonies. These findings may represent weather effects on duckling production and subsequent recruitment. Weather effects were mostly limited to a few aberrant years causing reductions in breeding numbers, i.e. declines in several colonies followed severe winters (1918) and some years with high NAO (1992, 1995). In terms of life history, adult survival generally is high and stable and probably only markedly affected by inclement weather or aberrantly bad years. Conversely, breeding propensity of adults and duckling production probably do respond more to annual weather variations; i.e. unfavorable winter conditions for adults increase probability of death or skipped breeding, whereas favorable summers can promote boom years for recruitment.     

Predicting Physical Interactions between Protein Complexes

Protein complexes enact most biochemical functions in the cell. Dynamic interactions between protein complexes are frequent in many cellular processes. As they are often of a transient nature, they may be difficult to detect using current genome-wide screens. Here, we describe a method to computationally predict physical interactions between protein complexes, applied to both humans and yeast. We integrated manually curated protein complexes and physical protein interaction networks, and we designed a statistical method to identify pairs of protein complexes where the number of protein interactions between a complex pair is due to an actual physical interaction between the complexes. An evaluation against manually curated physical complex-complex interactions in yeast revealed that 50% of these interactions could be predicted in this manner. A community network analysis of the highest scoring pairs revealed a biologically sensible organization of physical complex-complex interactions in the cell. Such analyses of proteomes may serve as a guide to the discovery of novel functional cellular relationships.Protein complexes are central to nearly all biochemical processes in the cell (1). In physiologically relevant states, their protein members assemble with varying degrees of stability, over time and under different cellular conditions, to carry out specific cellular functions (1). Although it is a dynamic and tightly regulated process, there is much evidence to support the notion that protein complex assembly results in discrete signaling macromolecules (2). According to the modular organization of molecular networks of the cell (3), protein complexes cooperate in functional networks through dynamic physical interactions with other macromolecules, including other protein complexes (4–6). These physical interactions between pairs of protein complexes may form the backbone of cellular processes (7), such as the recruitment of complexes by other complexes to sites of genome reorganization or in signaling networks. In this study, we attempted to predict these physical interactions between all pairs of known protein complexes, using the manually curated protein complex databases in CORUM and CYC2008 for humans and yeast, respectively.The physical protein interactions that may occur between pairs of complexes have been reported to be more transient, compared with the combination of both permanent and transient interactions that occur within complexes (8). Indeed, the very stability of protein interactions within a protein complex lies between the two extremes of either transient or permanent states (9). Consequently, the experimental identification in a genome-wide manner of the physical interactions between pairs of complexes is very difficult. This challenge has recently been addressed (7, 10) by experiments where the weak interactions were preserved during affinity purifications, followed by inference of the less stable interactions of proteins with the core proteins within the complex. Guided by a computational method to predict the list of protein members in the complexes (10), this allowed a screen of putative inter-complex relationships from human cell lines (7). This adds to the many landmark developments in recent years to characterize protein complexes in a genome-wide manner (7, 11–13). However, in these experiments it is not always easy to infer accurately what constitutes the protein members of a protein complex. Because of various experimental limitations (14) and the dynamic nature of complex assembly in the cell (15), the protein members of the complexes must be predicted from thousands of purification measurements (10–12, 16). As a result, there are surprisingly large differences in the protein complexes inferred in these studies, depending on the algorithm used (17, 18). Hence, the inference of protein complexes from genome-wide screens (11, 12) is likely to contain significant noise from false-positives resulting from methodological uncertainty (9). This noise would in turn cause ambiguity when attempting to predict, genome-wide, interactions that may occur between protein complexes. One solution to this problem, as applied in this study, is the use of comprehensive databases of the so-called “gold standard” community definitions of protein complexes (19–22). In these resources, critical reading of the scientific literature by trained experts leads to definitions of the lists of protein members that are experimentally verified to form complexes. Each of these manually curated protein complexes are assigned functional annotations and a unique identifier. It is our assumption that this approach will allow for a more accurate resolution of the physical interactions between protein complexes.Based on this reasoning, we utilized all protein complex pairs from 1216 human protein complexes in CORUM (21) and 471 in the yeast CYC2008 databases (22, 23), and we attempted to predict physical interactions between them.To this end, we integrated only binary physical protein interactions that were experimentally verified and supported by Medline references, from the iRefIndex database (24, 25), and we developed a statistical method that compared the number of observed physical protein interactions between pairs of protein complexes versus the number of protein interactions expected to be present in pairs of randomized protein complexes. The highest scoring predicted pairs formed a network that was analyzed to identify communities of physically interacting protein complexes. Such higher order perspectives of cellular proteomes may aid discovery of novel functional relationships and lead to an improved understanding of cellular behavior.One recent study utilized manually curated protein complexes-complex interactions in yeast (23) as part of a machine learning strategy to identify complex-complex interactions. However, they added to the training data complex pairs enriched with protein interactions under the assumption that these were likely to contain complex-complex interactions but without a clear statistical argument to assess the reliability of these. Our aim has been to provide a more rigorous statistical approach applied to yeast and human, in which the main confounding factors, protein degrees and protein similarities within the complexes, have been taken into account.We used only the manually curated yeast complex-complex interactions from Ref. 23 as the reference set to evaluate our method after verifying with the authors that the manual curation had not been guided by enrichment in the protein network. Of these interactions, we predicted half at a 10% false discovery rate. Thus, although improvements in data as well as methods are still required for a more complete prediction of complex-complex interactions, a fair portion of these interactions can be reliably predicted now by using our method.     

Microevolution in time and space: SNP analysis of historical DNA reveals dynamic signatures of selection in Atlantic cod

Little is known about how quickly natural populations adapt to changes in their environment and how temporal and spatial variation in selection pressures interact to shape patterns of genetic diversity. We here address these issues with a series of genome scans in four overfished populations of Atlantic cod (Gadus morhua) studied over an 80‐year period. Screening of >1000 gene‐associated single‐nucleotide polymorphisms (SNPs) identified 77 loci that showed highly elevated levels of differentiation, likely as an effect of directional selection, in either time, space or both. Exploratory analysis suggested that temporal allele frequency shifts at certain loci may correlate with local temperature variation and with life history changes suggested to be fisheries induced. Interestingly, however, largely nonoverlapping sets of loci were temporal outliers in the different populations and outliers from the 1928 to 1960 period showed almost complete stability during later decades. The contrasting microevolutionary trajectories among populations resulted in sequential shifts in spatial outliers, with no locus maintaining elevated spatial differentiation throughout the study period. Simulations of migration coupled with observations of temporally stable spatial structure at neutral loci suggest that population replacement or gene flow alone could not explain all the observed allele frequency variation. Thus, the genetic changes are likely to at least partly be driven by highly dynamic temporally and spatially varying selection. These findings have important implications for our understanding of local adaptation and evolutionary potential in high gene flow organisms and underscore the need to carefully consider all dimensions of biocomplexity for evolutionarily sustainable management.     

A genomic island linked to ecotype divergence in Atlantic cod

The genomic architecture underlying ecological divergence and ecological speciation with gene flow is still largely unknown for most organisms. One central question is whether divergence is genome‐wide or localized in ‘genomic mosaics’ during early stages when gene flow is still pronounced. Empirical work has so far been limited, and the relative impacts of gene flow and natural selection on genomic patterns have not been fully explored. Here, we use ecotypes of Atlantic cod to investigate genomic patterns of diversity and population differentiation in a natural system characterized by high gene flow and large effective population sizes, properties which theoretically could restrict divergence in local genomic regions. We identify a genomic region of strong population differentiation, extending over approximately 20 cM, between pairs of migratory and stationary ecotypes examined at two different localities. Furthermore, the region is characterized by markedly reduced levels of genetic diversity in migratory ecotype samples. The results highlight the genomic region, or ‘genomic island’, as potentially associated with ecological divergence and suggest the involvement of a selective sweep. Finally, we also confirm earlier findings of localized genomic differentiation in three other linkage groups associated with divergence among eastern Atlantic populations. Thus, although the underlying mechanisms are still unknown, the results suggest that ‘genomic mosaics’ of differentiation may even be found under high levels of gene flow and that marine fishes may provide insightful model systems for studying and identifying initial targets of selection during ecological divergence.     

Characterization of Carnobacterium divergens strain 6251 isolated from intestine of Arctic charr (Salvelinus alpinus L.)

An atypical strain of Carnobacterium divergens, strain 6251, was isolated from the small intestine of Arctic charr (Salvelinus alpinus L.), fed high dietary carbohydrate. This strain showed marked growth inhibitory effects in vitro against the fish pathogens Aeromonas salmonicida subsp. salmonicida (furunculosis), Vibrio anguillarum (vibriosis) and Vibrio viscocus (winter ulcer). The strain is a non-motile Gram-positive psychrotrophic rod that lacks both catalase and oxidase, grows at pH 9.1 (CTAS agar), but not on acetate containing media (pH < or = 5.4), on TCBS or at < or =6% sodium chloride content. Strain 6251 is facultatively anaerobic and utilises tryptone as a sole source of nutrient. Further characterisation showed the most abundant cellular fatty acid of strain 6251 to be oleic acid (18:1) (n-9) (36.0%). Sequencing of a 16S rDNA region of 578 nucleotides and AFLP microbial fingerprinting suggested that strain 6251 is not closely related to any carnobacteria known, however, DNA-DNA similarity determinations showed high similarity (96.2%) with the type strain of Carnobacterium divergens. The unique phenotypic attributes of this strain represent new information on the biodiversity and ecology of carnobacteria and especially of the species C. divergens.     

Historical DNA documents long‐distance natal homing in marine fish

The occurrence of natal homing in marine fish remains a fundamental question in fish ecology as its unequivocal demonstration requires tracking of individuals from fertilization to reproduction. Here, we provide evidence of long‐distance natal homing (>1000 km) over more than 60 years in Atlantic cod (Gadus morhua), through genetic analysis of archived samples from marked and recaptured individuals. Using a high differentiation single‐nucleotide polymorphism assay, we demonstrate that the vast majority of cod tagged in West Greenland and recaptured on Icelandic spawning grounds belonged to the Iceland offshore population, strongly supporting a hypothesis of homing. The high degree of natal fidelity observed provides the evolutionary settings for development of locally adapted populations in marine fish and emphasize the need to consider portfolio effects in marine fisheries management strategies.     

Improved drought tolerance without undesired side effects in transgenic plants producing trehalose

Most organisms naturally accumulating trehalose upon stress produce the sugar in a two-step process by the action of the enzymes trehalose-6-phosphate synthase (TPS) and trehalose-6-phosphate phosphatase (TPP). Transgenic plants overexpressing TPS have shown enhanced drought tolerance in spite of minute accumulation of trehalose, amounts believed to be too small to provide a protective function. However, overproduction of TPS in plants has also been found combined with pleiotropic growth aberrations. This paper describes three successful strategies to circumvent such growth defects without loosing the improved stress tolerance. First, we introduced into tobacco a double construct carrying the genes TPS1 and TPS2 (encoding TPP) from Saccharomyces cerevisiae. Both genes are regulated by an Arabidopsis RuBisCO promoter from gene AtRbcS1A giving constitutive production of both enzymes. The second strategy involved stress-induced expression by fusing the coding region of ScTPS1 downstream of the drought-inducible Arabidopsis AtRAB18 promoter. In transgenic tobacco plants harbouring genetic constructs with either ScTPS1 alone, or with ScTPS1 and ScTPS2 combined, trehalose biosynthesis was turned on only when the plants experienced stress. The third strategy involved the use of AtRbcS1A promoter together with a transit peptide in front of the coding sequence of ScTPS1, which directed the enzyme to the chloroplasts. This paper confirms that the enhanced drought tolerance depends on unknown ameliorated water retention as the initial water status is the same in control and transgenic plants and demonstrates the influence of expression of heterologous trehalose biosynthesis genes on Arabidopsis root development.     

Genetic interactions of DNA repair pathways in the pathogen Neisseria meningitidis

The current increase in the incidence and severity of infectious diseases mandates improved understanding of the basic biology and DNA repair profiles of virulent microbes. In our studies of the major pathogen and model organism Neisseria meningitidis, we constructed a panel of mutants inactivating genes involved in base excision repair, mismatch repair, nucleotide excision repair (NER), translesion synthesis, and recombinational repair pathways. The highest spontaneous mutation frequency among the N. meningitidis single mutants was found in the MutY-deficient strain as opposed to mutS mutants in Escherichia coli, indicating a role for meningococcal MutY in antibiotic resistance development. Recombinational repair was recognized as a major pathway counteracting methyl methanesulfonate-induced alkylation damage in the N. meningitidis. In contrast to what has been shown in other species, meningococcal NER did not contribute significantly to repair of alkylation-induced DNA damage, and meningococcal recombinational repair may thus be one of the main pathways for removal of abasic (apurinic/apyrimidinic) sites and strand breaks in DNA. Conversely, NER was identified as the main meningococcal defense pathway against UV-induced DNA damage. N. meningitidis RecA single mutants exhibited only a moderate decrease in survival after UV exposure as opposed to E. coli recA strains, which are extremely UV sensitive, possibly reflecting the lack of a meningococcal SOS response. In conclusion, distinct differences between N. meningitidis and established DNA repair characteristics in E. coli and other species were identified.