In vitro protective effect and antioxidant mechanism of Resveratrol induced by Dapsone Hydroxylamine in human cells

Dapsone (DDS) hydroxylamine metabolites cause oxidative stress- linked adverse effects in patients, such as methemoglobin formation and DNA damage. This study evaluated the ameliorating effect of the antioxidant resveratrol (RSV) on DDS hydroxylamine (DDSNHOH) mediated toxicity in vitro using human erythrocytes and lymphocytes. The antioxidant mechanism was also studied using in-silico methods. In addition, RSV provided intracellular protection by inhibiting DNA damage in human lymphocytes induced by DDS-NHOH. However, whilst pretreatment with RSV (10-1000 μM significantly attenuated DDS-NHOH-induced methemoglobinemia, but it was not only significantly less effective than methylene blue (MET), but also post-treatment with RSV did not reverse methemoglobin formation, contrarily to that observed with MET. DDS-NHOH inhibited catalase (CAT) activity and reactive oxygen species (ROS) generation, but did not alter superoxide dismutase (SOD) activity in erythrocytes. Pretreatment with RSV did not alter these antioxidant enzymes activities in erythrocytes treated with DDS-NHOH. Theoretical calculations using density functional theory methods showed that DDS-NHOH has a pro-oxidant effect, whereas RSV and MET have antioxidant effect on ROS. The effect on methemoglobinemia reversion for MET was significantly higher than that of RSV. These data suggest that the pretreatment with resveratrol may decrease heme-iron oxidation and DNA damage through reduction of ROS generated in cells during DDS therapy.

Innovative biomarkers for predicting type 2 diabetes mellitus:relevance to dietary management of frailty in older adults

Type 2 diabetes mellitus (T2DM) increases in prevalence in the elderly. There is evidence for significant muscle loss and accelerated cognitive impairment in older adults with T2DM; these comorbidities are critical features of frailty. In the early stages of T2DM, insulin sensitivity can be improved by a “healthy” diet. Management of insulin resistance by diet in people over 65 years of age should be carefully re-evaluated because of the risk for falling due to hypoglycaemia. To date, an optimal dietary programme for older adults with insulin resistance and T2DM has not been described. The use of biomarkers to identify those at risk for T2DM will enable clinicians to offer early dietary advice that will delay onset of disease and of frailty. Here we have used an in silico literature search for putative novel biomarkers of T2DM risk and frailty. We suggest that plasma bilirubin, plasma, urinary DPP4-positive microparticles and plasma pigment epithelium-derived factor merit further investigation as predictive biomarkers for T2DM and frailty risk in older adults. Bilirubin is screened routinely in clinical practice. Measurement of specific microparticle frequency in urine is less invasive than a blood sample so is a good choice for biomonitoring. Future studies should investigate whether early dietary changes, such as increased intake of whey protein and micronutrients that improve muscle function and insulin sensitivity, affect biomarkers and can reduce the longer term complication of frailty in people at risk for T2DM.

Identification of Conserved Splicing Motifs in Mutually Exclusive Exons of 15 Insect Species

Background: During alternative splicing, the inclusion of an exon in the final mRNA molecule is determined by nuclear proteins that bind cis-regulatory sequences in a target pre-mRNA molecule. A recent study suggested that the regulatory codes of individual RNA-binding proteins may be nearly immutable between very diverse species such as mammals and insects. The model system Drosophila melanogaster therefore presents an excellent opportunity for the study of alternative splicing due to the availability of quality EST annotations in FlyBase. Methods: In this paper, we describe an in silico analysis pipeline to extract putative exonic splicing regulatory sequences from a multiple alignment of 15 species of insects. Our method, ESTs-to-ESRs (E2E), uses graph analysis of EST splicing graphs to identify mutually exclusive (ME) exons and combines phylogenetic measures, a sliding window approach along the multiple alignment and the Welch’s t statistic to extract conserved ESR motifs. Results: The most frequent 100% conserved word of length 5 bp in different insect exons was “ATGGA”. We identified 799 statistically significant “spike” hexamers, 218 motifs with either a left or right FDR corrected spike magnitude p-value < 0.05 and 83 with both left and right uncorrected p < 0.01. 11 genes were identified with highly significant motifs in one ME exon but not in the other, suggesting regulation of ME exon splicing through these highly conserved hexamers. The majority of these genes have been shown to have regulated spatiotemporal expression. 10 elements were found to match three mammalian splicing regulator databases. A putative ESR motif, GATGCAG, was identified in the ME-13b but not in the ME-13a of Drosophila N-Cadherin, a gene that has been shown to have a distinct spatiotemporal expression pattern of spliced isoforms in a recent study. Conclusions: Analysis of phylogenetic relationships and variability of sequence conservation as implemented in the E2E spikes method may lead to improved identification of ESRs. We found that approximately half of the putative ESRs in common between insects and mammals have a high statistical support (p < 0.01). Several Drosophila genes with spatiotemporal expression patterns were identified to contain putative ESRs located in one exon of the ME exon pairs but not in the other.

Variable mutation rates as an adaptive strategy in replicator populations

For evolving populations of replicators, there is much evidence that the effect of mutations on fitness depends on the degree of adaptation to the selective pressures at play. In optimized populations, most mutations have deleterious effects, such that low mutation rates are favoured. In contrast to this, in populations thriving in changing environments a larger fraction of mutations have beneficial effects, providing the diversity necessary to adapt to new conditions. What is more, non-adapted populations occasionally benefit from an increase in the mutation rate. Therefore, there is no optimal universal value of the mutation rate and species attempt to adjust it to their momentary adaptive needs. In this work we have used stationary populations of RNA molecules evolving in silico to investigate the relationship between the degree of adaptation of an optimized population and the value of the mutation rate promoting maximal adaptation in a short time to a new selective pressure. Our results show that this value can significantly differ from the optimal value at mutation-selection equilibrium, being strongly influenced by the structure of the population when the adaptive process begins. In the short-term, highly optimized populations containing little variability respond better to environmental changes upon an increase of the mutation rate, whereas populations with a lower degree of optimization but higher variability benefit from reducing the mutation rate to adapt rapidly. These findings show a good agreement with the behaviour exhibited by actual organisms that replicate their genomes under broadly different mutation rates. © 2010 Stich et al.

Interpreting Human Genetic Variation through Genomics and In Vivo Models

Improvements in genomic technology, both in the increased speed and reduced cost of sequencing, have expanded the appreciation of the abundance of human genetic variation. However the sheer amount of variation, as well as the varying type and genomic content of variation, poses a challenge in understanding the clinical consequence of a single mutation. This work uses several methodologies to interpret the observed variation in the human genome, and presents novel strategies for the prediction of allele pathogenicity.

Using the zebrafish model system as an in vivo assay of allele function, we identified a novel driver of Bardet-Biedl Syndrome (BBS) in CEP76. A combination of targeted sequencing of 785 cilia-associated genes in a cohort of BBS patients and subsequent in vivo functional assays recapitulating the human phenotype gave strong evidence for the role of CEP76 mutations in the pathology of an affected family. This portion of the work demonstrated the necessity of functional testing in validating disease-associated mutations, and added to the catalogue of known BBS disease genes.

Further study into the role of copy-number variations (CNVs) in a cohort of BBS patients showed the significant contribution of CNVs to disease pathology. Using high-density array comparative genomic hybridization (aCGH) we were able to identify pathogenic CNVs as small as several hundred bp. Dissection of constituent gene and in vivo experiments investigating epistatic interactions between affected genes allowed for an appreciation of several paradigms by which CNVs can contribute to disease. This study revealed that the contribution of CNVs to disease in BBS patients is much higher than previously expected, and demonstrated the necessity of consideration of CNV contribution in future (and retrospective) investigations of human genetic disease.

Finally, we used a combination of comparative genomics and in vivo complementation assays to identify second-site compensatory modification of pathogenic alleles. These pathogenic alleles, which are found compensated in other species (termed compensated pathogenic deviations [CPDs]), represent a significant fraction (from 3 – 10%) of human disease-associated alleles. In silico pathogenicity prediction algorithms, a valuable method of allele prioritization, often misrepresent these alleles as benign, leading to omission of possibly informative variants in studies of human genetic disease. We created a mathematical model that was able to predict CPDs and putative compensatory sites, and functionally showed in vivo that second-site mutation can mitigate the pathogenicity of disease alleles. Additionally, we made publically available an in silico module for the prediction of CPDs and modifier sites.

These studies have advanced the ability to interpret the pathogenicity of multiple types of human variation, as well as made available tools for others to do so as well.

Pro-inflammatory flagellin proteins of prevalent motile commensal bacteria are variably abundant in the intestinal microbiome of elderly humans

Some Eubacterium and Roseburia species are among the most prevalent motile bacteria present in the intestinal microbiota of healthy adults. These flagellate species contribute "cell motility" category genes to the intestinal microbiome and flagellin proteins to the intestinal proteome. We reviewed and revised the annotation of motility genes in the genomes of six Eubacterium and Roseburia species that occur in the human intestinal microbiota and examined their respective locus organization by comparative genomics. Motility gene order was generally conserved across these loci. Five of these species harbored multiple genes for predicted flagellins. Flagellin proteins were isolated from R. inulinivorans strain A2-194 and from E. rectale strains A1-86 and M104/1. The amino-termini sequences of the R. inulinivorans and E. rectale A1-86 proteins were almost identical. These protein preparations stimulated secretion of interleukin-8 (IL-8) from human intestinal epithelial cell lines, suggesting that these flagellins were pro-inflammatory. Flagellins from the other four species were predicted to be pro-inflammatory on the basis of alignment to the consensus sequence of pro-inflammatory flagellins from the beta- and gamma-proteobacteria. Many fliC genes were deduced to be under the control of sigma(28). The relative abundance of the target Eubacterium and Roseburia species varied across shotgun metagenomes from 27 elderly individuals. Genes involved in the flagellum biogenesis pathways of these species were variably abundant in these metagenomes, suggesting that the current depth of coverage used for metagenomic sequencing (3.13-4.79 Gb total sequence in our study) insufficiently captures the functional diversity of genomes present at low (<= 1%) relative abundance. E. rectale and R. inulinivorans thus appear to synthesize complex flagella composed of flagellin proteins that stimulate IL-8 production. A greater depth of sequencing, improved evenness of sequencing and improved metagenome assembly from short reads will be required to facilitate in silico analyses of complete complex biochemical pathways for low-abundance target species from shotgun metagenomes.

p.(L576P) -KIT mutation in GIST: Favorable prognosis and sensitive to imatinib?

Exon 11 KIT mutations are found in a majority of gastrointestinal stromal tumors (GIST) and are usually predictive of response to imatinib, a KIT, PDGFRA and ABL inhibitor. Exon 11 mutations with poor sensitivity to imatinib and poor outcome can be observed on rare occasions, including p.(L576P). In silico and in vitro studies suggested a decreased binding affinity for imatinib in p.(L576P) KIT mutations, thereby offering an explanation for their poor outcome and poor response to standard therapy. These observations were further corroborated with anecdotal case reports of refractoriness or non-durable response to imatinib therapy. However, we describe the favorable response to imatinib and outcome in 5 p.(L576P)-KIT mutant GIST patients treated at a tertiary sarcoma referral center. The sensitivity of p.(L576P)-KIT mutations to imatinib, and the prognostic impact of this mutation need to be further evaluated in a larger cohort. Based on our observations, p.(L576P) mutated GISTs should be treated with standard first line imatinib therapy.

Insight into determinants of substrate binding and transport in a multidrug efflux protein

Multidrug resistance arising from the activity of integral membrane transporter proteins presents a global public health threat. In bacteria such as Escherichia coli, transporter proteins belonging to the major facilitator superfamily make a considerable contribution to multidrug resistance by catalysing efflux of myriad structurally and chemically different antimicrobial compounds. Despite their clinical relevance, questions pertaining to mechanistic details of how these promiscuous proteins function remain outstanding, and the role(s) played by individual amino acid residues in recognition, binding and subsequent transport of different antimicrobial substrates by multidrug efflux members of the major facilitator superfamily requires illumination. Using in silico homology modelling, molecular docking and mutagenesis studies in combination with substrate binding and transport assays, we identified several amino acid residues that play important roles in antimicrobial substrate recognition, binding and transport by Escherichia coli MdtM, a representative multidrug efflux protein of the major facilitator superfamily. Furthermore, our studies suggested that 'aromatic clamps' formed by tyrosine and phenylalanine residues located within the substrate binding pocket of MdtM may be important for antimicrobial substrate recognition and transport by the protein. Such 'clamps' may be a structurally and functionally important feature of all major facilitator multidrug efflux proteins.

Reversibility Iteration Method to Understand Reaction Networks and to Solve Micro-Kinetics in Heterogeneous Catalysis

Solving microkinetics of catalytic systems, which bridges microscopic processes and macroscopic reaction rates, is currently vital for understanding catalysis in silico. However, traditional microkinetic solvers possess several drawbacks that make the process slow and unreliable for complicated catalytic systems. In this paper, a new approach, the so-called reversibility iteration method (RIM), is developed to solve microkinetics for catalytic systems. Using the chemical potential notation we previously proposed to simplify the kinetic framework, the catalytic systems can be analytically illustrated to be logically equivalent to the electric circuit, and the reaction rate and coverage can be calculated by updating the values of reversibilities. Compared to the traditional modified Newton iteration method (NIM), our method is not sensitive to the initial guess of the solution and typically requires fewer iteration steps. Moreover, the method does not require arbitrary-precision arithmetic and has a higher probability of successfully solving the system. These features make it ∼1000 times faster than the modified Newton iteration method for the systems we tested. Moreover, the derived concept and the mathematical framework presented in this work may provide new insight into catalytic reaction networks.

Investigating the role of glutathione and glutathione biosynthetic genes in the adaptation of Anopheles gambiae to insecticides

Malaria remains a serious public health challenge in the tropical world, with 584,000 deaths globally in 2013, of which 90% occurred in Africa, and mostly in pregnant women and children under the age of five. Anopheles gambiae (An. gambiae) is the principal malaria vector in Africa, where vector control measures involve the use of insecticides in the forms of long-lasting insecticide-treated nets (LLINs) and indoor residual spraying (IRS). The development of insecticides resistance mitigates these approaches. Glutathione (GSH) is widely distributed among all living organisms, and is associated with detoxification pathways, especially the Glutathione S-transferases (GSTs). Its direct involvement and relevance in insecticide resistance in An. gambiae has not been determined. Thus, this work examines the contribution of GSH, its biosynthetic genes (GCLM, GCLC) and their possible transcriptional regulator Nrf2 in insecticide resistance in An. gambiae sampled from agricultural setting (areas of intensive agriculture) and residential setting (domestic area). Bioinformatics analysis, W.H.O. adult susceptibility bioassays and molecular techniques were employed to investigate. Total RNA was first isolated from the adults An. gambiae mosquitoes raised from agricultural and residential field-caught larvae which had been either challenged or unchallenged with insecticides. Semi-quantitative RT-PCR using gel image densitometry was used to determine the expression levels of GCLM, GCLC genes and Nrf2. Bioinformatics’ results established the presence of putative AGAP010259 (AhR) and AGAP005300 (Nf2e1) transcription factor binding sites in An. gambiae GCLC and GCLM promoters in silico. An. gambiae s.l. studied here were highly resistant to DDT and permethrin but less resistant to bendiocarb. Both knockdown resistance (kdr) mutation variants L1014S and L1014F that confers resistance to pyrethroid insecticides were identified in both An. coluzzii and An. arabiensis sampled from northern Nigeria. The L1014F was much associated with An. coluzzii. A significant positive correlation (P=0.04) between the frequency of the L1014F point mutation and resistance to DDT and permethrin was observed. However, a weak or non-significant correlation (P=0.772) between the frequency of the L1014S point mutation and resistance was also found. L1014S and L1014F mutations co-occurred in both agricultural and residential settings with high frequencies. However, the frequencies of the two mutations were greater in the agricultural settings than in the residential settings. The levels of total, reduced and oxidized GSH were significantly higher in mosquitoes from agricultural sites than those from residential sites. Increased oxidized GSH levels appears to correlate with higher DDT resistance. The expression levels of GCLM, GCLC and Nrf2 were also significantly up-regulated in adults An. gambiae raised from agricultural and residential field-caught larvae when challenged with insecticide. However, there was higher constitutive expression of GCLM, GCLC and Nrf2 in mosquitoes from agricultural setting. The increased expression levels of these genes and also GSH levels in this population suggest their roles in the response and adaptation of An. gambiae to insecticide challenges. There exists the feasibility of using GSH status in An. gambiae to monitor adaptation and resistance to insecticides.

Développement, validation et nouvelles applications d’un modèle d’analyse des modes normaux basé sur la séquence et la structure de protéines

Les protéines existent sous différents états fonctionnels régulés de façon précise par leur environnement afin de maintenir l‘homéostasie de la cellule et de l‘organisme vivant. La prévalence de ces états protéiques est dictée par leur énergie libre de Gibbs alors que la vitesse de transition entre ces états biologiquement pertinents est déterminée par le paysage d‘énergie libre. Ces paramètres sont particulièrement intéressants dans un contexte thérapeutique et biotechnologique, où leur perturbation par la modulation de la séquence protéique par des mutations affecte leur fonction. Bien que des nouvelles approches expérimentales permettent d‘étudier l‘effet de mutations en haut débit pour une protéine, ces méthodes sont laborieuses et ne couvrent qu‘une fraction de l‘ensemble des structures primaires d‘intérêt. L‘utilisation de modèles bio-informatiques permet de tester et générer in silico différentes hypothèses afin d‘orienter les approches expérimentales. Cependant, ces méthodes basées sur la structure se concentrent principalement sur la prédiction de l‘enthalpie d‘un état, alors que plusieurs évidences expérimentales ont démontré l‘importance de la contribution de l‘entropie. De plus, ces approches ignorent l‘importance de l‘espace conformationnel protéique dicté par le paysage énergétique cruciale à son fonctionnement. Une analyse des modes normaux peut être effectuée afin d‘explorer cet espace par l‘approximation que la protéine est dans une conformation d‘équilibre où chaque acide aminé est représenté par une masse régie par un potentiel harmonique. Les approches actuelles ignorent l‘identité des résidus et ne peuvent prédire l‘effet de mutations sur les propriétés dynamiques. Nous avons développé un nouveau modèle appelé ENCoM qui pallie à cette lacune en intégrant de l‘information physique et spécifique sur les contacts entre les atomes des chaînes latérales. Cet ajout permet une meilleure description de changements conformationnels d‘enzymes, la prédiction de l‘effet d‘une mutation allostérique dans la protéine DHFR et également la prédiction de l‘effet de mutations sur la stabilité protéique par une valeur entropique. Comparativement à des approches spécifiquement développées pour cette application, ENCoM est plus constant et prédit mieux l‘effet de mutations stabilisantes. Notre approche a également été en mesure de capturer la pression évolutive qui confère aux protéines d‘organismes thermophiles une thermorésistance accrue.

Elucidating the interactions between the adhesive and transcriptioanl functions of beta-catenin in normal and cancerous cells

Wnt signalling is involved in a wide range of physiological and pathological processes. The presence of an extracellular Wnt stimulus induces cytoplasmic stabilisation and nuclear translocation of beta-catenin, a protein that also plays an essential role in cadherin-mediated adhesion. Two main hypotheses have been proposed concerning the balance between beta-catenin's adhesive and transcriptional functions: either beta-catenin's fate is determined by competition between its binding partners, or Wnt induces folding of beta-catenin into a conformation allocated preferentially to transcription. The experimental data supporting each hypotheses remain inconclusive. In this paper we present a new mathematical model of the Wnt pathway that incorporates beta-catenin's dual function. We use this model to carry out a series of in silico experiments and compare the behaviour of systems governed by each hypothesis. Our analytical results and model simulations provide further insight into the current understanding of Wnt signalling and, in particular, reveal differences in the response of the two modes of interaction between adhesion and signalling in certain in silico settings. We also exploit our model to investigate the impact of the mutations most commonly observed in human colorectal cancer. Simulations show that the amount of functional APC required to maintain a normal phenotype increases with increasing strength of the Wnt signal, a result which illustrates that the environment can substantially influence both tumour initiation and phenotype.

The Kinome of Pacific Oyster Crassostrea gigas, Its Expression during Development and in Response to Environmental Factors

Oysters play an important role in estuarine and coastal marine habitats, where the majority of humans live. In these ecosystems, environmental degradation is substantial, and oysters must cope with highly dynamic and stressful environmental constraints during their lives in the intertidal zone. The availability of the genome sequence of the Pacific oyster Crassostrea gigas represents a unique opportunity for a comprehensive assessment of the signal transduction pathways that the species has developed to deal with this unique habitat. We performed an in silico analysis to identify, annotate and classify protein kinases in C. gigas, according to their kinase domain taxonomy classification, and compared with kinome already described in other animal species. The C. gigas kinome consists of 371 protein kinases, making it closely related to the sea urchin kinome, which has 353 protein kinases. The absence of gene redundancy in some groups of the C. gigas kinome may simplify functional studies of protein kinases. Through data mining of transcriptomes in C. gigas, we identified part of the kinome which may be central during development and may play a role in response to various environmental factors. Overall, this work contributes to a better understanding of key sensing pathways that may be central for adaptation to a highly dynamic marine environment.

High hydrostatic pressure adaptive strategies in an obligate piezophile Pyrococcus yayanosii

Pyrococcus yayanosii CH1, as the first and only obligate piezophilic hyperthermophilic microorganism discovered to date, extends the physical and chemical limits of life on Earth. It was isolated from the Ashadze hydrothermal vent at 4,100 m depth. Multi-omics analyses were performed to study the mechanisms used by the cell to cope with high hydrostatic pressure variations. In silico analyses showed that the P. yayanosii genome is highly adapted to its harsh environment, with a loss of aromatic amino acid biosynthesis pathways and the high constitutive expression of the energy metabolism compared with other non-obligate piezophilic Pyrococcus species. Differential proteomics and transcriptomics analyses identified key hydrostatic pressure-responsive genes involved in translation, chemotaxis, energy metabolism (hydrogenases and formate metabolism) and Clustered Regularly Interspaced Short Palindromic Repeats sequences associated with Cellular apoptosis susceptibility proteins.

I. Quantal effects in biochemical cooperativity and a proposed mechanism for the differentiation of calcium signaling in synaptic plasticity. II. Evolutionary algorithms for the optimization of methods in computational chemistry

In Part 1 of this thesis, we propose that biochemical cooperativity is a fundamentally non-ideal process. We show quantal effects underlying biochemical cooperativity and highlight apparent ergodic breaking at small volumes. The apparent ergodic breaking manifests itself in a divergence of deterministic and stochastic models. We further predict that this divergence of deterministic and stochastic results is a failure of the deterministic methods rather than an issue of stochastic simulations.

Ergodic breaking at small volumes may allow these molecular complexes to function as switches to a greater degree than has previously been shown. We propose that this ergodic breaking is a phenomenon that the synapse might exploit to differentiate Ca$^{2+}$ signaling that would lead to either the strengthening or weakening of a synapse. Techniques such as lattice-based statistics and rule-based modeling are tools that allow us to directly confront this non-ideality. A natural next step to understanding the chemical physics that underlies these processes is to consider \textit{in silico} specifically atomistic simulation methods that might augment our modeling efforts.

In the second part of this thesis, we use evolutionary algorithms to optimize \textit{in silico} methods that might be used to describe biochemical processes at the subcellular and molecular levels. While we have applied evolutionary algorithms to several methods, this thesis will focus on the optimization of charge equilibration methods. Accurate charges are essential to understanding the electrostatic interactions that are involved in ligand binding, as frequently discussed in the first part of this thesis.