Disrupted phylogeographical microsatellite and chloroplast DNA patterns indicate a vicariance rather than long‐distance dispersal origin for the disjunct distribution of the Chilean endemic Dioscorea biloba (Dioscoreaceae) around the Atacama Desert

Aim The Chilean endemic Dioscorea biloba (Dioscoreaceae) is a dioecious geophyte that shows a remarkable 600 km north–south disjunction in the peripheral arid area of the Atacama Desert. Its restricted present‐day distribution and probable Neogene origin indicate that its populations have a history linked to that of the Atacama Desert, making this an ideal model species with which to investigate the biogeography of the region. Location Chile, Atacama Desert and peripheral arid area. Methods Two hundred and seventy‐five individuals from nine populations were genotyped for seven nuclear microsatellite loci, and plastid trnL–F and trnT–L sequences were obtained for a representative subset of these. Analyses included the estimation of genetic diversity and population structure through clustering, Bayesian and analysis of molecular variance analyses, and statistical parsimony networks of chloroplast haplotypes. Isolation by distance was tested against alternative dispersal hypotheses. Results Microsatellite markers revealed moderate to high levels of genetic diversity within populations, with those from the southern Limarí Valley showing the highest values and northern populations showing less exclusive alleles. Bayesian analysis of microsatellite data identified three genetic groups that corresponded to geographical ranges. Chloroplast phylogeography revealed no haplotypes shared between northern and southern ranges, and little haplotype sharing between the two neighbouring southern valleys. Dispersal models suggested the presence of extinct hypothetical populations between the southern and northern ranges. Main conclusions Our results are consistent with prolonged isolation of the northern and southern groups, mediated by the life‐history traits of the species. Significant isolation was revealed at both large and moderate distances as gene flow was not evident even between neighbouring valleys. Bayesian analyses of microsatellite and chloroplast haplotype diversity identified the southern area of Limarí as the probable area of origin of the species. Our data do not support recent dispersal of D. biloba from the southern range into Antofagasta, but indicate the fragmentation of an earlier wider range, concomitant with the Pliocene–Pleistocene climatic oscillations, with subsequent extinctions of the Atacama Desert populations and the divergence of the peripheral ones as a consequence of genetic drift.     

Structural Basis for Silicic Acid Uptake by Higher Plants

Many of the world's most important food crops such as rice, barley and maize accumulate silicon (Si) to high levels, resulting in better plant growth and crop yields. The first step in Si accumulation is the uptake of silicic acid by the roots, a process mediated by the structurally uncharacterised NIP subfamily of aquaporins, also named metalloid porins. Here, we present the X-ray crystal structure of the archetypal NIP family member from Oryza sativa (OsNIP2;1). The OsNIP2;1 channel is closed in the crystal structure by the cytoplasmic loop D, which is known to regulate channel opening in classical plant aquaporins. The structure further reveals a novel, five-residue extracellular selectivity filter with a large diameter. Unbiased molecular dynamics simulations show a rapid opening of the channel and visualise how silicic acid interacts with the selectivity filter prior to transmembrane diffusion. Our results will enable detailed structure–function studies of metalloid porins, including the basis of their substrate selectivity.     

Absolute configuration and conformation of the pure opioid antagonist (+)-2,9 alpha-dimethyl-5-(m-hydroxyphenyl)morphan.

(+)-2,9 alpha-Dimethyl-5-(m-hydroxyphenyl)morphan is the only phenylmorphan analog whose affinity for opioid kappa-receptors is greater than its affinity for opioid mu-receptors. Pharmacologically, the compound is a pure opioid antagonist devoid of agonist activity in in vivo assays of antinociception. The absolute configuration of the compound has been determined to be (1R,5S,9R) from an X-ray crystallographic study of the chloride salt. Thus, the absolute configuration corresponds to that of the atypical opioid agonist (-)-phenylmorphan while the weak atypical agonist (-)-2,9 alpha-dimethyl-5-(m- hydroxyphenyl)morphan corresponds to the potent morphine-like (+)-phenylmorphan. The preferred orientations of the phenyl ring for the two stereoisomers were determined using the molecular mechanics program MM2-87 and found to vary from that of the two parent compounds. The atypical properties of the two 9 alpha-methyl analogs is consistent with an opioid ligand model which proposes that morphine-like properties require a particular range of phenyl orientations. There was good agreement between the structure obtained from X-ray crystallography and computed with the MM2-87 program.     

Increased Expression of Apolipoprotein D Following Experimental Traumatic Brain Injury

Increasing evidence suggests that apolipoprotein D (apoD) could play a major role in mediating neuronal degeneration and regeneration in the CNS and the PNS. To investigate further the temporal pattern of apoD expression after experimental traumatic brain injury in the rat, male Sprague-Dawley rats were subjected to unilateral cortical impact injury. The animals were killed and examined for apoD mRNA and protein expression and for immunohistological analysis at intervals from 15 min to 14 days after injury. Increased apoD mRNA and protein levels were seen in the cortex and hippocampus ipsilateral to the injury site from 48 h to 14 days after the trauma. Immunohistological investigation demonstrated a differential pattern of apoD expression in the cortex and hippocampus, respectively: Increased apoD immunoreactivity in glial cells was detected from 2 to 3 days after the injury in cortex and hippocampus. In contrast, increased expression of apoD was seen in cortical and hippocampal neurons at later time points following impact injury. Concurrent histopathological examination using hematoxylin and eosin demonstrated dark, shrunken neurons in the cortex ipsilateral to the injury site. In contrast, no evidence of cell death was observed in the hippocampus ipsilateral to the injury site up to 14 days after the trauma. No evidence of increased apoD mRNA or protein expression or neuronal pathology by hematoxylin and eosin staining was detected in the contralateral cortex and hippocampus. Our results reveal induction of apoD expression in the cortex and hippocampus following traumatic brain injury in the rat. Our data also suggest that increased apoD expression may play an important role in cortical neuronal degeneration after brain injury in vivo. However, increased expression of apoD in the hippocampus may not necessarily be indicative of neuronal death.     

Socially isolated? How parents and neighbourhood adults influence youth behaviour in disadvantaged communities

William Julius Wilson’s model of adult joblessness, community disorganization and their effects on youth problem behaviour de-emphasizes the range in children’s outcomes across socially disorganized communities, and says little about the factors that influence this variation. It also does not address the processes by which family structure and relationships affect the well-being of African-American and poor youth. My work is part of a larger research agenda that has begun to address these issues by focusing on the differential rates of sexual activity among youth living in disadvantaged environments, and developing models to explain this variation. This work suggests that units of socially cohesive, stable adults exist among the social networks of successful children and families in poor neighbourhoods. It also points to the existence and functioning of alternative two-parent family structures and offers hypotheses for how family environment interacts with neighbourhood context to influence youth behaviour.     

The distribution of carbohydrate side chains along the polypeptide chain of glucoamylase

Glucoamylase is a starch-hydrolyzing enzyme with a glycoprotein structure, used industrially for the conversion of starch to glucose, citric acid, corn syrups, and high-fructose sweeteners. This enzyme possesses an unusual type of structure in which many carbohydrate side chains are linked O-glycosidically to serine and threonine residues of the polypeptide chain. The carbohydrate side chains may be single monosaccharide residues or oligosaccharides of mannose, glucose, galactose, and in some cases N-acetylglucosamine. New data from experiments on the CNBr fragmentation of glucoamylase followed by chemical and immunological characterization of the fragments show that the carbohydrate side chains are distributed randomly along the polypeptide chain. Such a structure is appropriately termed a random model reprensentation for the glucoamylase molecule.     

Akt Activation Emulates Chk1 Inhibition and Bcl2 Overexpression and Abrogates G2 Cell Cycle Checkpoint by Inhibiting BRCA1 Foci

Akt is perhaps the most frequently activated oncoprotein in human cancers. Overriding cell cycle checkpoint in combination with the inhibition of apoptosis are two principal requirements for predisposition to cancer. Here we show that the activation of Akt is sufficient to promote these two principal processes, by inhibiting Chk1 activation with concomitant inhibition of apoptosis. These activities of Akt cannot be recapitulated by the knockdown of Chk1 alone or by overexpression of Bcl2. Rather the combination of Chk1 knockdown and Bcl2 overexpression is required to recapitulate Akt activities. Akt was shown to directly phosphorylate Chk1. However, we found that Chk1 mutants in the Akt phosphorylation sites behave like wild-type Chk1 in mediating G2 arrest, suggesting that the phosphorylation of Chk1 by Akt is either dispensable for Chk1 activity or insufficient by itself to exert an effect on Chk1 activity. Here we report a new mechanism by which Akt affects G2 cell cycle arrest. We show that Akt inhibits BRCA1 function that induces G2 cell cycle arrest. Akt prevents the translocation of BRCA1 to DNA damage foci and, thereby, inhibiting the activation of Chk1 following DNA damage.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Structure-based protein design with deep learning

Since the first revelation of proteins functioning as macromolecular machines through their three dimensional structures, researchers have been intrigued by the marvelous ways the biochemical processes are carried out by proteins. The aspiration to understand protein structures has fueled extensive efforts across different scientific disciplines. In recent years, it has been demonstrated that proteins with new functionality or shapes can be designed via structure-based modeling methods, and the design strategies have combined all available information — but largely piece-by-piece — from sequence derived statistics to the detailed atomic-level modeling of chemical interactions. Despite the significant progress, incorporating data-derived approaches through the use of deep learning methods can be a game changer. In this review, we summarize current progress, compare the arc of developing the deep learning approaches with the conventional methods, and describe the motivation and concepts behind current strategies that may lead to potential future opportunities.