Interaction Between Convection and Pulsation

This article reviews our current understanding of modelling convection dynamics in stars. Several semi-analytical time-dependent convection models have been proposed for pulsating one-dimensional stellar structures with different formulations for how the convective turbulent velocity field couples with the global stellar oscillations. In this review we put emphasis on two, widely used, time-dependent convection formulations for estimating pulsation properties in one-dimensional stellar models. Applications to pulsating stars are presented with results for oscillation properties, such as the effects of convection dynamics on the oscillation frequencies, or the stability of pulsation modes, in classical pulsators and in stars supporting solar-type oscillations.Comment: Invited review article for Living Reviews in Solar Physics. 88 pages, 14 figure

Maternal fecal microbiome predicts gestational age, birth weight and neonatal growth in rural Zimbabwe.

BACKGROUND: Preterm birth and low birth weight (LBW) affect one in ten and one in seven livebirths, respectively, primarily in low-income and middle-income countries (LMIC) and are major predictors of poor child health outcomes. However, both have been recalcitrant to public health intervention. The maternal intestinal microbiome may undergo substantial changes during pregnancy and may influence fetal and neonatal health in LMIC populations. METHODS: Within a subgroup of 207 mothers and infants enrolled in the SHINE trial in rural Zimbabwe, we performed shotgun metagenomics on 351 fecal specimens provided during pregnancy and at 1-month post-partum to investigate the relationship between the pregnancy gut microbiome and infant gestational age, birth weight, 1-month length-, and weight-for-age z-scores using extreme gradient boosting machines. FINDINGS: Pregnancy gut microbiome taxa and metabolic functions predicted birth weight and WAZ at 1 month more accurately than gestational age and LAZ. Blastoscystis sp, Brachyspira sp and Treponeme carriage were high compared to Western populations. Resistant starch-degraders were important predictors of birth outcomes. Microbiome capacity for environmental sensing, vitamin B metabolism, and signalling predicted increased infant birth weight and neonatal growth; while functions involved in biofilm formation in response to nutrient starvation predicted reduced birth weight and growth. INTERPRETATION: The pregnancy gut microbiome in rural Zimbabwe is characterized by resistant starch-degraders and may be an important metabolic target to improve birth weight. FUNDING: Bill and Melinda Gates Foundation, UK Department for International Development, Wellcome Trust, Swiss Agency for Development and Cooperation, US National Institutes of Health, and UNICEF

Automated functional classification of experimental and predicted protein structures

BACKGROUND: Proteins that are similar in sequence or structure may perform different functions in nature. In such cases, function cannot be inferred from sequence or structural similarity. RESULTS: We analyzed experimental structures belonging to the Structural Classification of Proteins (SCOP) database and showed that about half of them belong to multi-functional fold families for which protein similarity alone is not adequate to assign function. We also analyzed predicted structures from the LiveBench and the PDB-CAFASP experiments and showed that accurate homology-based functional assignments cannot be achieved approximately one third of the time, when the protein is a member of a multi-functional fold family. We then conducted extended performance evaluation and comparisons on both experimental and predicted structures using our Functional Signatures from Structural Alignments (FSSA) algorithm that we previously developed to handle the problem of classifying proteins belonging to multi-functional fold families. CONCLUSION: The results indicate that the FSSA algorithm has better accuracy when compared to homology-based approaches for functional classification of both experimental and predicted protein structures, in part due to its use of local, as opposed to global, information for classifying function. The FSSA algorithm has also been implemented as a webserver and is available at

A structural annotation resource for the selection of putative target proteins in the malaria parasite

<p>Abstract</p> <p>Background</p> <p>Protein structure plays a pivotal role in elucidating mechanisms of parasite functioning and drug resistance. Moreover, protein structure aids the determination of protein function, which can together with the structure be used to identify novel drug targets in the parasite. However, various structural features in <it>Plasmodium falciparum </it>proteins complicate the experimental determination of protein structures. Limited similarity to proteins in the Protein Data Bank and the shortage of solved protein structures in the malaria parasite necessitate genome-scale structural annotation of <it>P. falciparum </it>proteins. Additionally, the annotation of a range of structural features facilitates the identification of suitable targets for experimental and computational studies.</p> <p>Methods</p> <p>An integrated structural annotation system was developed and applied to <it>P. falciparum</it>, <it>Plasmodium vivax </it>and <it>Plasmodium yoelii</it>. The annotation included searches for sequence similarity, patterns and domains in addition to the following predictions: secondary structure, transmembrane helices, protein disorder, low complexity, coiled-coils and small molecule interactions. Subsequently, candidate proteins for further structural studies were identified based on the annotated structural features.</p> <p>Results</p> <p>The annotation results are accessible through a web interface, enabling users to select groups of proteins which fulfil multiple criteria pertaining to structural and functional features <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>. Analysis of features in the <it>P. falciparum </it>proteome showed that protein-interacting proteins contained a higher percentage of predicted disordered residues than non-interacting proteins. Proteins interacting with 10 or more proteins have a disordered content concentrated in the range of 60–100%, while the disorder distribution for proteins having only one interacting partner, was more evenly spread.</p> <p>Conclusion</p> <p>A series of <it>P. falciparum </it>protein targets for experimental structure determination, comparative modelling and <it>in silico </it>docking studies were putatively identified. The system is available for public use, where researchers may identify proteins by querying with multiple physico-chemical, sequence similarity and interaction features.</p

Bicyclic triterpenoid Iripallidal induces apoptosis and inhibits Akt/mTOR pathway in glioma cells

<p>Abstract</p> <p>Background</p> <p>The highly resistant nature of glioblastoma multiforme (GBM) to chemotherapy prompted us to evaluate the efficacy of bicyclic triterpenoid Iripallidal against GBM in vitro.</p> <p>Methods</p> <p>The effect of Iripallidal on proliferation and apoptosis in glioma cell lines was evaluated by MTS, colony formation and caspase-3 activity. The effect of iripallidal to regulate (i) Akt/mTOR and STAT3 signaling (ii) molecules associated with cell cycle and DNA damage was evaluated by Western blot analysis. The effect of Iripallidal on telomerase activity was also determined.</p> <p>Results</p> <p>Iripallidal (i) induced apoptosis, (ii) inhibited Akt/mTOR and STAT3 signaling, (iii) altered molecules associated with cell cycle and DNA damage, (iv) inhibited telomerase activity and colony forming efficiency of glioma cells. In addition, Iripallidal displayed anti-proliferative activity against non-glioma cancer cell lines of diverse origin.</p> <p>Conclusion</p> <p>The ability of Iripallidal to serve as a dual-inhibitor of Akt/mTOR and STAT3 signaling warrants further investigation into its role as a therapeutic strategy against GBM.</p

Modeling protein network evolution under genome duplication and domain shuffling

<p>Abstract</p> <p>Background</p> <p>Successive whole genome duplications have recently been firmly established in all major eukaryote kingdoms. Such <it>exponential </it>evolutionary processes must have largely contributed to shape the topology of protein-protein interaction (PPI) networks by outweighing, in particular, all <it>time-linear </it>network growths modeled so far.</p> <p>Results</p> <p>We propose and solve a mathematical model of PPI network evolution under successive genome duplications. This demonstrates, from first principles, that evolutionary conservation and scale-free topology are intrinsically linked properties of PPI networks and emerge from <it>i) </it>prevailing <it>exponential </it>network dynamics under duplication and <it>ii) asymmetric divergence </it>of gene duplicates. While required, we argue that this asymmetric divergence arises, in fact, spontaneously at the level of protein-binding sites. This supports a refined model of PPI network evolution in terms of protein domains under exponential and asymmetric duplication/divergence dynamics, with multidomain proteins underlying the combinatorial formation of protein complexes. Genome duplication then provides a powerful source of PPI network innovation by promoting local rearrangements of multidomain proteins on a genome wide scale. Yet, we show that the overall conservation and topology of PPI networks are robust to extensive domain shuffling of multidomain proteins as well as to finer details of protein interaction and evolution. Finally, large scale features of <it>direct </it>and <it>indirect </it>PPI networks of <it>S. cerevisiae </it>are well reproduced numerically with only two adjusted parameters of clear biological significance (<it>i.e</it>. network effective growth rate and average number of protein-binding domains per protein).</p> <p>Conclusion</p> <p>This study demonstrates the statistical consequences of genome duplication and domain shuffling on the conservation and topology of PPI networks over a broad evolutionary scale across eukaryote kingdoms. In particular, scale-free topologies of PPI networks, which are found to be robust to extensive shuffling of protein domains, appear to be a simple consequence of the conservation of protein-binding domains under asymmetric duplication/divergence dynamics in the course of evolution.</p

Cholera- and Anthrax-Like Toxins Are among Several New ADP-Ribosyltransferases

Chelt, a cholera-like toxin from Vibrio cholerae, and Certhrax, an anthrax-like toxin from Bacillus cereus, are among six new bacterial protein toxins we identified and characterized using in silico and cell-based techniques. We also uncovered medically relevant toxins from Mycobacterium avium and Enterococcus faecalis. We found agriculturally relevant toxins in Photorhabdus luminescens and Vibrio splendidus. These toxins belong to the ADP-ribosyltransferase family that has conserved structure despite low sequence identity. Therefore, our search for new toxins combined fold recognition with rules for filtering sequences – including a primary sequence pattern – to reduce reliance on sequence identity and identify toxins using structure. We used computers to build models and analyzed each new toxin to understand features including: structure, secretion, cell entry, activation, NAD+ substrate binding, intracellular target binding and the reaction mechanism. We confirmed activity using a yeast growth test. In this era where an expanding protein structure library complements abundant protein sequence data – and we need high-throughput validation – our approach provides insight into the newest toxin ADP-ribosyltransferases