A rigidifying salt-bridge favors the activity of thermophilic enzyme at high temperatures at the expense of low-temperature activity

Background

Thermophilic enzymes are often less active than their mesophilic homologues at low temperatures. One hypothesis to explain this observation is that the extra stabilizing interactions increase the rigidity of thermophilic enzymes and hence reduce their activity. Here we employed a thermophilic acylphosphatase from Pyrococcus horikoshii and its homologous mesophilic acylphosphatase from human as a model to study how local rigidity of an active-site residue affects the enzymatic activity.

Methods and Findings

Acylphosphatases have a unique structural feature that its conserved active-site arginine residue forms a salt-bridge with the C-terminal carboxyl group only in thermophilic acylphosphatases, but not in mesophilic acylphosphatases. We perturbed the local rigidity of this active-site residue by removing the salt-bridge in the thermophilic acylphosphatase and by introducing the salt-bridge in the mesophilic homologue. The mutagenesis design was confirmed by x-ray crystallography. Removing the salt-bridge in the thermophilic enzyme lowered the activation energy that decreased the activation enthalpy and entropy. Conversely, the introduction of the salt-bridge to the mesophilic homologue increased the activation energy and resulted in increases in both activation enthalpy and entropy. Revealed by molecular dynamics simulations, the unrestrained arginine residue can populate more rotamer conformations, and the loss of this conformational freedom upon the formation of transition state justified the observed reduction in activation entropy.

Conclusions

Our results support the conclusion that restricting the active-site flexibility entropically favors the enzymatic activity at high temperatures. However, the accompanying enthalpy-entropy compensation leads to a stronger temperature-dependency of the enzymatic activity, which explains the less active nature of the thermophilic enzymes at low temperatures.     

New views of tapetum ultrastructure and pollen exine development in Arabidopsis thaliana

Background and Aims

The Arabidopsis thaliana pollen cell wall is a complex structure consisting of an outer sporopollenin framework and lipid-rich coat, as well as an inner cellulosic wall. Although mutant analysis has been a useful tool to study pollen cell walls, the ultrastructure of the arabidopsis anther has proved to be challenging to preserve for electron microscopy.

Methods

In this work, high-pressure freezing/freeze substitution and transmission electron microscopy were used to examine the sequence of developmental events in the anther that lead to sporopollenin deposition to form the exine and the dramatic differentiation and death of the tapetum, which produces the pollen coat.

Key Results

Cryo-fixation revealed a new view of the interplay between sporophytic anther tissues and gametophytic microspores over the course of pollen development, especially with respect to the intact microspore/pollen wall and the continuous tapetum epithelium. These data reveal the ultrastructure of tapetosomes and elaioplasts, highly specialized tapetum organelles that accumulate pollen coat components. The tapetum and middle layer of the anther also remain intact into the tricellular pollen and late uninucleate microspore stages, respectively.

Conclusions

This high-quality structural information, interpreted in the context of recent functional studies, provides the groundwork for future mutant studies where tapetum and microspore ultrastructure is assessed.     

Chronic Upper Airway Obstruction Induces Abnormal Sleep/Wake Dynamics in Juvenile Rats

Objectives

Conventional scoring of sleep provides little information about the process of transitioning between vigilance-states. We used the state space technique to explore whether rats with chronic upper airway obstruction (UAO) have abnormal sleep/wake states, faster movements between states, or abnormal transitions between states.

Design

The tracheae of 22-day-old Sprague-Dawley rats were surgically narrowed to increase upper airway resistance with no evidence for frank obstructed apneas or hypopneas; 24-h electroencephalography of sleep/wake recordings of UAO and sham-control animals was analyzed using state space technique. This non-categorical approach allows quantitative and unbiased examination of vigilance-states and state transitions. Measurements were performed 2 weeks post-surgery at baseline and following administration of ritanserin (5-HT2 receptor antagonist) the next day to stimulate sleep.

Measurements and Results

UAO rats spent less time in deep (delta-rich) slow wave sleep (SWS) and near transition zones between states. State transitions from light SWS to wake and vice versa and microarousals were more frequent and rapid in UAO rats, indicating that obstructed animals have more regions where vigilance-states are unstable. Ritanserin consolidated sleep in both groups by decreasing the number of microarousals and trajectories between wake and light SWS, and increasing deep SWS in UAO.

Conclusions

State space technique enables visualization of vigilance-state transitions and velocities that were not evident by traditional scoring methods. This analysis provides new quantitative assessment of abnormal vigilance-state dynamics in UAO in the absence of frank obstructed apneas or hypopneas.     

Index cohesive force analysis reveals that the US market became prone to systemic collapses since 2002

Background

The 2007–2009 financial crisis, and its fallout, has strongly emphasized the need to define new ways and measures to study and assess the stock market dynamics.

Methodology/Principal Findings

The S&P500 dynamics during 4/1999–4/2010 is investigated in terms of the index cohesive force (ICF - the balance between the stock correlations and the partial correlations after subtraction of the index contribution), and the Eigenvalue entropy of the stock correlation matrices. We found a rapid market transition at the end of 2001 from a flexible state of low ICF into a stiff (nonflexible) state of high ICF that is prone to market systemic collapses. The stiff state is also marked by strong effect of the market index on the stock-stock correlations as well as bursts of high stock correlations reminiscence of epileptic brain activity.

Conclusions/Significance

The market dynamical states, stability and transition between economic states was studies using new quantitative measures. Doing so shed new light on the origin and nature of the current crisis. The new approach is likely to be applicable to other classes of complex systems from gene networks to the human brain.     

Optimisation Modelling to Assess Cost of Dietary Improvement in Remote Aboriginal Australia

Background

The cost and dietary choices required to fulfil nutrient recommendations defined nationally, need investigation, particularly for disadvantaged populations.

Objective

We used optimisation modelling to examine the dietary change required to achieve nutrient requirements at minimum cost for an Aboriginal population in remote Australia, using where possible minimally-processed whole foods.

Design

A twelve month cross-section of population-level purchased food, food price and nutrient content data was used as the baseline. Relative amounts from 34 food group categories were varied to achieve specific energy and nutrient density goals at minimum cost while meeting model constraints intended to minimise deviation from the purchased diet.

Results

Simultaneous achievement of all nutrient goals was not feasible. The two most successful models (A & B) met all nutrient targets except sodium (146.2% and 148.9% of the respective target) and saturated fat (12.0% and 11.7% of energy). Model A was achieved with 3.2% lower cost than the baseline diet (which cost approximately AUD$13.01/person/day) and Model B at 7.8% lower cost but with a reduction in energy of 4.4%. Both models required very large reductions in sugar sweetened beverages (−90%) and refined cereals (−90%) and an approximate four-fold increase in vegetables, fruit, dairy foods, eggs, fish and seafood, and wholegrain cereals.

Conclusion

This modelling approach suggested population level dietary recommendations at minimal cost based on the baseline purchased diet. Large shifts in diet in remote Aboriginal Australian populations are needed to achieve national nutrient targets. The modeling approach used was not able to meet all nutrient targets at less than current food expenditure.     

The Associations between Self-Consciousness,Depressive State and Craving to Drink among Alcohol Dependent Patients Undergoing Protracted Withdrawal

Context

In order to understand how certain personality traits influence the relation between depression symptoms and craving for alcohol, trait self-consciousness (trait SC) was examined during a withdrawal and detoxification program.

Methods

Craving (Obsessive and Compulsive Drinking Scale), depressive state (Beck Depression Inventory) and trait SC (Revised Self-Consciousness Scale) were assessed in alcohol-dependent inpatients (DSM-IV, N = 30) both at the beginning (T1: day 1 or 2) and at the end (T2: day 14 to18) of protracted withdrawal during rehabilitation.

Results

A significant decrease in craving and depressive symptoms was observed from T1 to T2, while SC scores remained stable. At both times, strong positive correlations were observed between craving and depression. Moreover, regression analyses indicated that trait SC significantly moderated the impact of depression on cravings for alcohol.

Limitations

This study was performed on a relatively small sample size. Administration of medications during detoxification treatment can also be a confounding factor. Finally, craving could have been evaluated through other types of measurements.

Conclusions

During protracted withdrawal, alcohol craving decreased with the same magnitude as depressive mood. Depressive symptoms were related to alcohol craving but only among patients with high trait SC scores. Our results suggest that metacognitive approaches targeting SC could decrease craving and, in turn, prevent future relapses.     

A comparison of phylogenetic network methods using computer simulation

Background

We present a series of simulation studies that explore the relative performance of several phylogenetic network approaches (statistical parsimony, split decomposition, union of maximum parsimony trees, neighbor-net, simulated history recombination upper bound, median-joining, reduced median joining and minimum spanning network) compared to standard tree approaches, (neighbor-joining and maximum parsimony) in the presence and absence of recombination.

Principal Findings

In the absence of recombination, all methods recovered the correct topology and branch lengths nearly all of the time when the substitution rate was low, except for minimum spanning networks, which did considerably worse. At a higher substitution rate, maximum parsimony and union of maximum parsimony trees were the most accurate. With recombination, the ability to infer the correct topology was halved for all methods and no method could accurately estimate branch lengths.

Conclusions

Our results highlight the need for more accurate phylogenetic network methods and the importance of detecting and accounting for recombination in phylogenetic studies. Furthermore, we provide useful information for choosing a network algorithm and a framework in which to evaluate improvements to existing methods and novel algorithms developed in the future.     

The shoot apical meristem of oil palm (Elaeis guineensis; Arecaceae): developmental progression and dynamics

Background and Aims

Oil palm, an unbranched perennial monocotyledon, possesses a single shoot apical meristem (SAM), which is responsible for the initiation of the entire above-ground structure of the plant. To compare the palm SAM structure with those of other monocots and to study variations in its structure throughout the life of the plant, its organization was characterized from the embryonic stage to that of the reproductive plant.

Methods

SAM structure was studied by a combination of stained histological sections, light and confocal microscopy, and serial section-based three-dimensional reconstructions.

Key Results

The oil palm SAM is characterized by two developmental phases: a juvenile phase with a single tunica-corpus structure displaying a gradual increase in size; and a mature phase characterized by a stable size, a modified shape and an established histological zonation pattern. In mature plants, fluctuations in SAM shape and volume occur, mainly as a consequence of changes in the central zone, possibly in relation to leaf initiation.

Conclusions

Development of the oil palm SAM is characterized by a juvenile to mature phase transition accompanied by establishment of a zonal pattern and modified shape. SAM zonation is dynamic during the plastochron period and displays distinct features compared with other monocots.     

Identification of horizontally transferred genes in the genus Colletotrichum reveals a steady tempo of bacterial to fungal gene transfer

Background

Horizontal gene transfer (HGT) is the stable transmission of genetic material between organisms by means other than vertical inheritance. HGT has an important role in the evolution of prokaryotes but is relatively rare in eukaryotes. HGT has been shown to contribute to virulence in eukaryotic pathogens. We studied the importance of HGT in plant pathogenic fungi by identifying horizontally transferred genes in the genomes of three members of the genus Colletotrichum.

Results

We identified eleven HGT events from bacteria into members of the genus Colletotrichum or their ancestors. The HGT events include genes involved in amino acid, lipid and sugar metabolism as well as lytic enzymes. Additionally, the putative minimal dates of transference were calculated using a time calibrated phylogenetic tree. This analysis reveals a constant flux of genes from bacteria to fungi throughout the evolution of subphylum Pezizomycotina.

Conclusions

Genes that are typically transferred by HGT are those that are constantly subject to gene duplication and gene loss. The functions of some of these genes suggest roles in niche adaptation and virulence. We found no evidence of a burst of HGT events coinciding with major geological events. In contrast, HGT appears to be a constant, albeit rare phenomenon in the Pezizomycotina, occurring at a steady rate during their evolution.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-16-2) contains supplementary material, which is available to authorized users.     

DiscML: an R package for estimating evolutionary rates of discrete characters using maximum likelihood

Background

The study of discrete characters is crucial for the understanding of evolutionary processes. Even though great advances have been made in the analysis of nucleotide sequences, computer programs for non-DNA discrete characters are often dedicated to specific analyses and lack flexibility. Discrete characters often have different transition rate matrices, variable rates among sites and sometimes contain unobservable states. To obtain the ability to accurately estimate a variety of discrete characters, programs with sophisticated methodologies and flexible settings are desired.

Results

DiscML performs maximum likelihood estimation for evolutionary rates of discrete characters on a provided phylogeny with the options that correct for unobservable data, rate variations, and unknown prior root probabilities from the empirical data. It gives users options to customize the instantaneous transition rate matrices, or to choose pre-determined matrices from models such as birth-and-death (BD), birth-death-and-innovation (BDI), equal rates (ER), symmetric (SYM), general time-reversible (GTR) and all rates different (ARD). Moreover, we show application examples of DiscML on gene family data and on intron presence/absence data.

Conclusion

DiscML was developed as a unified R program for estimating evolutionary rates of discrete characters with no restriction on the number of character states, and with flexibility to use different transition models. DiscML is ideal for the analyses of binary (1s/0s) patterns, multi-gene families, and multistate discrete morphological characteristics.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-320) contains supplementary material, which is available to authorized users.     

Eukaryotic richness in the abyss: insights from pyrotag sequencing

Background

The deep sea floor is considered one of the most diverse ecosystems on Earth. Recent environmental DNA surveys based on clone libraries of rRNA genes confirm this observation and reveal a high diversity of eukaryotes present in deep-sea sediment samples. However, environmental clone-library surveys yield only a modest number of sequences with which to evaluate the diversity of abyssal eukaryotes.

Methodology/Principal Findings

Here, we examined the richness of eukaryotic DNA in deep Arctic and Southern Ocean samples using massively parallel sequencing of the 18S ribosomal RNA (rRNA) V9 hypervariable region. In very small volumes of sediments, ranging from 0.35 to 0.7 g, we recovered up to 7,499 unique sequences per sample. By clustering sequences having up to 3 differences, we observed from 942 to 1756 Operational Taxonomic Units (OTUs) per sample. Taxonomic analyses of these OTUs showed that DNA of all major groups of eukaryotes is represented at the deep-sea floor. The dinoflagellates, cercozoans, ciliates, and euglenozoans predominate, contributing to 17%, 16%, 10%, and 8% of all assigned OTUs, respectively. Interestingly, many sequences represent photosynthetic taxa or are similar to those reported from the environmental surveys of surface waters. Moreover, each sample contained from 31 to 71 different metazoan OTUs despite the small sample volume collected. This indicates that a significant faction of the eukaryotic DNA sequences likely do not belong to living organisms, but represent either free, extracellular DNA or remains and resting stages of planktonic species.

Conclusions/Significance

In view of our study, the deep-sea floor appears as a global DNA repository, which preserves genetic information about organisms living in the sediment, as well as in the water column above it. This information can be used for future monitoring of past and present environmental changes.     

Design and construction of a double inversion recombination switch for heritable sequential genetic memory

Background

Inversion recombination elements present unique opportunities for computing and information encoding in biological systems. They provide distinct binary states that are encoded into the DNA sequence itself, allowing us to overcome limitations posed by other biological memory or logic gate systems. Further, it is in theory possible to create complex sequential logics by careful positioning of recombinase recognition sites in the sequence.

Methodology/Principal Findings

In this work, we describe the design and synthesis of an inversion switch using the fim and hin inversion recombination systems to create a heritable sequential memory switch. We have integrated the two inversion systems in an overlapping manner, creating a switch that can have multiple states. The switch is capable of transitioning from state to state in a manner analogous to a finite state machine, while encoding the state information into DNA. This switch does not require protein expression to maintain its state, and “remembers” its state even upon cell death. We were able to demonstrate transition into three out of the five possible states showing the feasibility of such a switch.

Conclusions/Significance

We demonstrate that a heritable memory system that encodes its state into DNA is possible, and that inversion recombination system could be a starting point for more complex memory circuits. Although the circuit did not fully behave as expected, we showed that a multi-state, temporal memory is achievable.     

Association of Maximum Weight with Hyperuricemia Risk: A Retrospective Study of 21,414 Chinese People

Background

Obesity has been demonstrated to be associated with increased serum uric acid (SUA); however, little is known regarding the relationship between maximum weight, or maximum weight fluctuation, and uric acid concentration. Through retrospective means, we determined the association of maximum weight with SUA risk.

Methods

Data of 21,414 participants (8,630 males and 12,784 females) from the 2007-8 China National Diabetes and Metabolic Disorders Study were analyzed for parameters including lifestyle habits, biochemical blood analysis and self-reported maximum weight.

Results

Elevated SUA subjects shared a cluster of demographic features. After adjustment for age, gender, education, smoking, drinking, physical activity, WHR, height, eGFR(evaluate glomerular filtration rate), and diuretic usage, multivariate logistic regression models demonstrated maximum weight was associated with increased risk of elevated SUA level (P<0.001). Duration of maximum weight was related with decreased risk of elevated SUA level (P<0.001). There was a significant correlation between time of weight loss and risk of increased SUA level reduction (P<0.001). Furthermore, our data indicated that the degree of weight loss from maximum weight was another important factor for the risk of increased SUA level reduction (P<0.001). Finally, ROC curve analysis revealed area under the curve was 0.661 (95% CI, 0.647-0.674), statistically significant for maximum weight association with hyperuricemia (P<0.001).

Conclusions

Maximum weight is a strong risk factor for increased uric acid level in the Chinese population, which might serve as a novel clinical indicator suggesting hyperuricemia. Controlling maximum weight, keeping weight to the appropriate range, and maintaining the stable weight may be conducive for decreasing risk of hyperuricemia.     

When the optimal is not the best: parameter estimation in complex biological models

Background

The vast computational resources that became available during the past decade enabled the development and simulation of increasingly complex mathematical models of cancer growth. These models typically involve many free parameters whose determination is a substantial obstacle to model development. Direct measurement of biochemical parameters in vivo is often difficult and sometimes impracticable, while fitting them under data-poor conditions may result in biologically implausible values.

Results

We discuss different methodological approaches to estimate parameters in complex biological models. We make use of the high computational power of the Blue Gene technology to perform an extensive study of the parameter space in a model of avascular tumor growth. We explicitly show that the landscape of the cost function used to optimize the model to the data has a very rugged surface in parameter space. This cost function has many local minima with unrealistic solutions, including the global minimum corresponding to the best fit.

Conclusions

The case studied in this paper shows one example in which model parameters that optimally fit the data are not necessarily the best ones from a biological point of view. To avoid force-fitting a model to a dataset, we propose that the best model parameters should be found by choosing, among suboptimal parameters, those that match criteria other than the ones used to fit the model. We also conclude that the model, data and optimization approach form a new complex system and point to the need of a theory that addresses this problem more generally.     

Implications from a network-based topological analysis of ubiquitin unfolding simulations

Background

The architectural organization of protein structures has been the focus of intense research since it can hopefully lead to an understanding of how proteins fold. In earlier works we had attempted to identify the inherent structural organization in proteins through a study of protein topology. We obtained a modular partitioning of protein structures with the modules correlating well with experimental evidence of early folding units or “foldons”. Residues that connect different modules were shown to be those that were protected during the transition phase of folding.

Methodology/Principal Findings

In this work, we follow the topological path of ubiquitin through molecular dynamics unfolding simulations. We observed that the use of recurrence quantification analysis (RQA) could lead to the identification of the transition state during unfolding. Additionally, our earlier contention that the modules uncovered through our graph partitioning approach correlated well with early folding units was vindicated through our simulations. Moreover, residues identified from native structure as connector hubs and which had been shown to be those that were protected during the transition phase of folding were indeed more stable (less flexible) well beyond the transition state. Further analysis of the topological pathway suggests that the all pairs shortest path in a protein is minimized during folding.

Conclusions

We observed that treating a protein native structure as a network by having amino acid residues as nodes and the non-covalent interactions among them as links allows for the rationalization of many aspects of the folding process. The possibility to derive this information directly from 3D structure opens the way to the prediction of important residues in proteins, while the confirmation of the minimization of APSP for folding allows for the establishment of a potentially useful proxy for kinetic optimality in the validation of sequence-structure predictions.     

Cost-Effectiveness of a Community Pharmacist-Led Sleep Apnea Screening Program – A Markov Model

Background

Despite the high prevalence and major public health ramifications, obstructive sleep apnea syndrome (OSAS) remains underdiagnosed. In many developed countries, because community pharmacists (CP) are easily accessible, they have been developing additional clinical services that integrate the services of and collaborate with other healthcare providers (general practitioners (GPs), nurses, etc.). Alternative strategies for primary care screening programs for OSAS involving the CP are discussed.

Objective

To estimate the quality of life, costs, and cost-effectiveness of three screening strategies among patients who are at risk of having moderate to severe OSAS in primary care.

Design

Markov decision model.

Data Sources

Published data.

Target Population

Hypothetical cohort of 50-year-old male patients with symptoms highly evocative of OSAS.

Time Horizon

The 5 years after initial evaluation for OSAS.

Perspective

Societal.

Interventions

Screening strategy with CP (CP-GP collaboration), screening strategy without CP (GP alone) and no screening.

Outcomes measures

Quality of life, survival and costs for each screening strategy.

Results of base-case analysis

Under almost all modeled conditions, the involvement of CPs in OSAS screening was cost effective. The maximal incremental cost for “screening strategy with CP” was about 455€ per QALY gained.

Results of sensitivity analysis

Our results were robust but primarily sensitive to the treatment costs by continuous positive airway pressure, and the costs of untreated OSAS. The probabilistic sensitivity analysis showed that the “screening strategy with CP” was dominant in 80% of cases. It was more effective and less costly in 47% of cases, and within the cost-effective range (maximum incremental cost effectiveness ratio at €6186.67/QALY) in 33% of cases.

Conclusions

CP involvement in OSAS screening is a cost-effective strategy. This proposal is consistent with the trend in Europe and the United States to extend the practices and responsibilities of the pharmacist in primary care.     

Estimation of the Optimal Statistical Quality Control Sampling Time Intervals Using a Residual Risk Measure

Background

An open problem in clinical chemistry is the estimation of the optimal sampling time intervals for the application of statistical quality control (QC) procedures that are based on the measurement of control materials. This is a probabilistic risk assessment problem that requires reliability analysis of the analytical system, and the estimation of the risk caused by the measurement error.

Methodology/Principal Findings

Assuming that the states of the analytical system are the reliability state, the maintenance state, the critical-failure modes and their combinations, we can define risk functions based on the mean time of the states, their measurement error and the medically acceptable measurement error. Consequently, a residual risk measure rr can be defined for each sampling time interval. The rr depends on the state probability vectors of the analytical system, the state transition probability matrices before and after each application of the QC procedure and the state mean time matrices. As optimal sampling time intervals can be defined those minimizing a QC related cost measure while the rr is acceptable. I developed an algorithm that estimates the rr for any QC sampling time interval of a QC procedure applied to analytical systems with an arbitrary number of critical-failure modes, assuming any failure time and measurement error probability density function for each mode. Furthermore, given the acceptable rr, it can estimate the optimal QC sampling time intervals.

Conclusions/Significance

It is possible to rationally estimate the optimal QC sampling time intervals of an analytical system to sustain an acceptable residual risk with the minimum QC related cost. For the optimization the reliability analysis of the analytical system and the risk analysis of the measurement error are needed.