Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b10699

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b10675

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b09602

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b09385

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b06814

Background: A central question for disease studies and crop improvements is how genetics variants drive phenotypes. Genome Wide Association Study (GWAS) provides a powerful tool for characterizing the genotype-phenotype relationships in complex traits and diseases. Epistasis (gene-gene interaction), including high-order interaction among more than two genes, often plays important roles in complex traits and diseases, but current GWAS analysis usually just focuses on additive effects of single nucleotide polymorphisms (SNPs). The lack of effective computational modelling of high-order functional interactions often leads to significant under-utilization of GWAS data. Results: We have developed a novel Bayesian computational method with a Markov Chain Monte Carlo (MCMC) search, and implemented the method as a Bayesian High-order Interaction Toolkit (BHIT) for detecting epistatic interactions among SNPs. BHIT first builds a Bayesian model on both continuous data and discrete data, which is capable of detecting high-order interactions in SNPs related to case—control or quantitative phenotypes. We also developed a pipeline that enables users to apply BHIT on different species in different use cases. Conclusions: Using both simulation data and soybean nutritional seed composition studies on oil content and protein content, BHIT effectively detected some high-order interactions associated with phenotypes, and it outperformed a number of other available tools. BHIT is freely available for academic users at http://digbio.missouri.edu/BHIT/.

Background: As a valuable medicinal plant, the yield of Panax ginseng is seriously affected by autotoxicity, which is a common phenomenon due to continuous cropping. However, the mechanism of autotoxicity in P. ginseng is still unknown. Results: In total, high throughput sequencing of 18 RNA-Seq libraries produced 996,000 000 100-nt reads that were assembled into 72,732 contigs. Compared with control, 3697 and 2828 genes were significantly up- and down-regulated across different tissues and time points, respectively. Gene Ontology enrichment analysis showed that ‘enzyme inhibitor activity’, ‘carboxylesterase activity’, ‘pectinesterase activity’, ‘centrosome cycle and duplication’ and ‘mitotic spindle elongation’ were enriched for the up-regulated genes. Transcription factors including AP2s/ERFs, MYBs, and WRKYs were up-regulated in roots after benzoic acid treatment. Moreover, reactive oxygen species, peroxidases and superoxide dismutase contigs were up-regulated in roots after benzoic acid treatment. Physiological and biochemical indexes showed that the proline and malondialdehyde content were restored to lower levels at a later stage after benzoic acid treatment. Benzoic acid inhibited the root hair development in a dose-dependent manner, and several differential expressed genes potentially involved in hair development were identified. Several key contigs in the flavonoid and ginsenoside biosynthesis pathways were repressed. Finally, 58,518 alternative splicing (AS) events from 12,950 genes were found after benzoic acid treatment. Interestingly, contigs in the ginsenoside biosynthetic pathway underwent AS, providing useful information about post-transcriptional regulation in P. ginseng. Conclusions: This study revealed the stress-response molecular mechanisms in P. ginseng induced by benzoic acid.

Background: Identification of bacteria may be based on sequencing and molecular analysis of a specific locus such as 16S rRNA, or a set of loci such as in multilocus sequence typing. In the near future, healthcare institutions and routine diagnostic microbiology laboratories may need to sequence the entire genome of microbial isolates. Therefore we have developed Reads2Type, a web-based tool for taxonomy identification based on whole bacterial genome sequence data. Results: Raw sequencing data provided by the user are mapped against a set of marker probes that are derived from currently available bacteria complete genomes. Using a dataset of 1003 whole genome sequenced bacteria from various sequencing platforms, Reads2Type was able to identify the species with 99.5 % accuracy and on the minutes time scale. Conclusions: In comparison with other tools, Reads2Type offers the advantage of not needing to transfer sequencing files, as the entire computational analysis is done on the computer of whom utilizes the web application. This also prevents data privacy issues to arise. The Reads2Type tool is available at http://www.cbs.dtu.dk/~dhany/reads2type.html.

The viscoelastic behaviour of a biological material is central to its functioning and is an indicator of its health. The Fung quasi-linear viscoelastic (QLV) model, a standard tool for characterizing biological materials, provides excellent fits to most stress–relaxation data by imposing a simple form upon a material's temporal relaxation spectrum. However, model identification is challenging because the Fung QLV model's ‘box’-shaped relaxation spectrum, predominant in biomechanics applications, can provide an excellent fit even when it is not a reasonable representation of a material's relaxation spectrum. Here, we present a robust and simple discrete approach for identifying a material's temporal relaxation spectrum from stress–relaxation data in an unbiased way. Our ‘discrete QLV’ (DQLV) approach identifies ranges of time constants over which the Fung QLV model's typical box spectrum provides an accurate representation of a particular material's temporal relaxation spectrum, and is effective at providing a fit to this model. The DQLV spectrum also reveals when other forms or discrete time constants are more suitable than a box spectrum. After validating the approach against idealized and noisy data, we applied the methods to analyse medial collateral ligament stress–relaxation data and identify the strengths and weaknesses of an optimal Fung QLV fit.

Biological information is stored in DNA, RNA and protein sequences, which can be understood as genotypes that are translated into phenotypes. The properties of genotype–phenotype (GP) maps have been studied in great detail for RNA secondary structure. These include a highly biased distribution of genotypes per phenotype, negative correlation of genotypic robustness and evolvability, positive correlation of phenotypic robustness and evolvability, shape-space covering, and a roughly logarithmic scaling of phenotypic robustness with phenotypic frequency. More recently similar properties have been discovered in other GP maps, suggesting that they may be fundamental to biological GP maps, in general, rather than specific to the RNA secondary structure map. Here we propose that the above properties arise from the fundamental organization of biological information into ‘constrained' and ‘unconstrained' sequences, in the broadest possible sense. As ‘constrained' we describe sequences that affect the phenotype more immediately, and are therefore more sensitive to mutations, such as, e.g. protein-coding DNA or the stems in RNA secondary structure. ‘Unconstrained' sequences, on the other hand, can mutate more freely without affecting the phenotype, such as, e.g. intronic or intergenic DNA or the loops in RNA secondary structure. To test our hypothesis we consider a highly simplified GP map that has genotypes with ‘coding' and ‘non-coding' parts. We term this the Fibonacci GP map, as it is equivalent to the Fibonacci code in information theory. Despite its simplicity the Fibonacci GP map exhibits all the above properties of much more complex and biologically realistic GP maps. These properties are therefore likely to be fundamental to many biological GP maps.

Nature presents multiple intriguing examples of processes that proceed with high precision and regularity. This remarkable stability is frequently counter to modellers' experience with the inherent stochasticity of chemical reactions in the regime of low-copy numbers. Moreover, the effects of noise and nonlinearities can lead to ‘counterintuitive’ behaviour, as demonstrated for a basic enzymatic reaction scheme that can display stochastic focusing (SF). Under the assumption of rapid signal fluctuations, SF has been shown to convert a graded response into a threshold mechanism, thus attenuating the detrimental effects of signal noise. However, when the rapid fluctuation assumption is violated, this gain in sensitivity is generally obtained at the cost of very large product variance, and this unpredictable behaviour may be one possible explanation of why, more than a decade after its introduction, SF has still not been observed in real biochemical systems. In this work, we explore the noise properties of a simple enzymatic reaction mechanism with a small and fluctuating number of active enzymes that behaves as a high-gain, noisy amplifier due to SF caused by slow enzyme fluctuations. We then show that the inclusion of a plausible negative feedback mechanism turns the system from a noisy signal detector to a strong homeostatic mechanism by exchanging high gain with strong attenuation in output noise and robustness to parameter variations. Moreover, we observe that the discrepancy between deterministic and stochastic descriptions of stochastically focused systems in the evolution of the means almost completely disappears, despite very low molecule counts and the additional nonlinearity due to feedback. The reaction mechanism considered here can provide a possible resolution to the apparent conflict between intrinsic noise and high precision in critical intracellular processes.

In HIV-infected patients, an individual's set point viral load (SPVL) strongly predicts disease progression. Some think that SPVL is evolving, indicating that the virulence of the virus may be changing, but the data are not consistent. In addition, the widespread use of antiretroviral therapy (ART) has the potential to drive virulence evolution. We develop a simple deterministic model designed to answer the following questions: what are the expected patterns of virulence change in the initial decades of an epidemic? Could administration of ART drive changes in virulence evolution and, what is the potential size and direction of this effect? We find that even without ART we would not expect monotonic changes in average virulence. Transient decreases in virulence following the peak of an epidemic are not necessarily indicative of eventual evolution to avirulence. In the short term, we would expect widespread ART to cause limited downward pressure on virulence. In the long term, the direction of the effect is determined by a threshold condition, which we define. We conclude that, given the surpassing benefits of ART to the individual and in reducing onward transmission, virulence evolution considerations need have little bearing on how we treat.

We present a novel method for the unsupervised discovery of behavioural motifs in larval Drosophila melanogaster and Caenorhabditis elegans. A motif is defined as a particular sequence of postures that recurs frequently. The animal's changing posture is represented by an eigenshape time series, and we look for motifs in this time series. To find motifs, the eigenshape time series is segmented, and the segments clustered using spline regression. Unlike previous approaches, our method can classify sequences of unequal duration as the same motif. The behavioural motifs are used as the basis of a probabilistic behavioural annotator, the eigenshape annotator (ESA). Probabilistic annotation avoids rigid threshold values and allows classification uncertainty to be quantified. We apply eigenshape annotation to both larval Drosophila and C. elegans and produce a good match to hand annotation of behavioural states. However, we find many behavioural events cannot be unambiguously classified. By comparing the results with ESA of an artificial agent's behaviour, we argue that the ambiguity is due to greater continuity between behavioural states than is generally assumed for these organisms.

Abstract

Retroviral DNA integration is mediated by nucleoprotein complexes (intasomes) comprising a pair of viral DNA ends synapsed by a tetramer of integrase. Current integrase inhibitors act on intasomes rather than free integrase protein. Structural and functional studies of intasomes are essential to understand their mechanism of action and how the virus can escape by mutation. To date, prototype foamy virus (PFV) is the only retrovirus for which high-resolution structures of intasomes have been determined. In the PFV intasome structure, only the core domains of the outer subunits are ordered; the N-terminal domain, C-terminal domain, and N-terminal extension domain are disordered. Are these “missing domains” required for function or are they dispensable? We have devised a strategy to assemble “hetero-intasomes” in which the outer domains are not present as a tool to assess the functional role of the missing domains for catalysis of integration. We find that the disordered domains of outer subunits are not required for intasome assembly or catalytic activity as catalytic core domains can substitute for the outer subunits in the case of both PFV and HIV-1 intasomes.

Abstract

Arginine methylation is important in biological systems. Recent studies link the deregulation of protein arginine methyltransferases with certain cancers. To assess the impact of methylation on interaction with other biomolecules, the pKa values of methylated arginine variants were determined using NMR data. The pKa values of monomethylated, symmetrically dimethylated, and asymmetrically dimethylated arginine are similar to the unmodified arginine (14.2 ± 0.4). Although the pKa value has not been significantly affected by methylation, consequences of methylation include changes in charge distribution and steric effects, suggesting alternative mechanisms for recognition.

Abstract

Most members of the p53 family of transcription factors form tetramers. Responsible for determining the oligomeric state is a short oligomerization domain consisting of one β-strand and one α-helix. With the exception of human p53 all other family members investigated so far contain a second α-helix as part of their tetramerization domain. Here we have used nuclear magnetic resonance spectroscopy to characterize the oligomerization domains of the two p53-like proteins from the tunicate Ciona intestinalis, representing the closest living relative of vertebrates. Structure determination reveals for one of the two proteins a new type of packing of this second α-helix on the core domain that was not predicted based on the sequence, while the other protein does not form a second helix despite the presence of crucial residues that are conserved in all other family members that form a second helix. By mutational analysis, we identify a proline as well as large hydrophobic residues in the hinge region between both helices as the crucial determinant for the formation of a second helix.

Abstract

The serine protease inhibitor (serpin), plasminogen activator inhibitor-1 (PAI-1), is an important biomarker for cardiovascular disease and many cancers. It is therefore a desirable target for pharmaceutical intervention. However, to date, no PAI-1 inhibitor has successfully reached clinical trial, indicating the necessity to learn more about the mechanics of the serpin. Although its kinetics of inhibition have been extensively studied, less is known about the latency transition of PAI-1, in which the solvent-exposed reactive center loop (RCL) inserts into its central β-sheet, rendering the inhibitor inactive. This spontaneous transition is concomitant with a large translocation of the RCL, but no change in covalent structure. Here, we conjugated the fluorescent probe, NBD, to single positions along the RCL (P13-P5′) to detect changes in solvent exposure that occur during the latency transition. The results support a mousetrap-like RCL-insertion that occurs with a half-life of 1–2 h in accordance with previous reports. Importantly, this study exposes unique transitions during latency that occur with a half-life of ∼5 and 25 min at the P5′ and P8 RCL positions, respectively. We hypothesize that the process detected at P5′ represents s1C detachment, while that at P8 results from a steric barrier to RCL insertion. Together, these findings provide new insights by characterizing multiple steps in the latency transition.

Abstract

Carnosine dipeptidase II (CN2/CNDP2) is an M20 family metallopeptidase that hydrolyses various dipeptides including β-alanyl-l-histidine (carnosine). Crystallographic analysis showed that CN2 monomer is composed of one catalytic and one dimerization domains, and likely to form homodimer. In this crystal, H228 residue of the dimerization domain interacts with the substrate analogue bestatin on the active site of the dimer counterpart, indicating that H228 is involved in enzymatic reaction. In the present study, the role of intradimer interaction of CN2 in its catalytic activity was investigated using electrospray-ionization time-of-flight mass spectrometry (ESI-TOF MS). First, a dimer interface mutant I319K was prepared and shown to be present as a folded monomer in solution as examined by using ESI-TOF MS. Since the mutant was inactive, it was suggested that dimer formation is essential to its enzymatic activity. Next, we prepared H228A and D132A mutant proteins with different N-terminal extended sequences, which enabled us to monitor dimer exchange reaction by ESI-TOF MS. The D132A mutant is a metal ligand mutant and also inactive. But the activity was partially recovered time-dependently when H228A and D132A mutant proteins were incubated together. In parallel, H228A/D132A heterodimer was formed as detected by ESI-TOF MS, indicating that interaction of a catalytic center with H228 residue of the other subunit is essential to the enzymatic reaction. These results provide evidence showing that intradimer interaction of H228 with the reaction center of the dimer counterpart is essential to the enzymatic activity of CN2.

The way forward is through Paris

Nature 527, 7579 (2015). doi:10.1038/527409a

Leaders must come together on a solid agreement at the United Nations climate conference — and then get to work at home by meeting commitments and finding new ways to reduce emissions.