Andrew R. Dalby

Identification of Schistosoma mansoni microRNAs

BackgroundMicroRNAs (miRNAs) constitute a class of single-stranded RNAs which play a crucial role in regulating development and controlling gene expression by targeting mRNAs and triggering either translation repression or messenger RNA (mRNA) degradation. miRNAs are widespread in eukaryotes and to date over 14,000 miRNAs have been identified by computational and experimental approaches. Several miRNAs are highly conserved across species. In Schistosoma, the full set of miRNAs and their expression patterns during development remain poorly understood. Here we report on the development and implementation of a homology-based detection strategy to search for miRNA genes in Schistosoma mansoni. In addition, we report results on the experimental detection of miRNAs by means of cDNA cloning and sequencing of size-fractionated RNA samples.ResultsHomology search using the high-throughput pipeline was performed with all known miRNAs in miRBase. A total of 6,211 mature miRNAs were used as reference sequences and 110 unique S. mansoni sequences were returned by BLASTn analysis. The existing mature miRNAs that produced these hits are reported, as well as the locations of the homologous sequences in the S. mansoni genome. All BLAST hits aligned with at least 95% of the miRNA sequence, resulting in alignment lengths of 19-24 nt. Following several filtering steps, 15 potential miRNA candidates were identified using this approach. By sequencing small RNA cDNA libraries from adult worm pairs, we identified 211 novel miRNA candidates in the S. mansoni genome. Northern blot analysis was used to detect the expression of the 30 most frequent sequenced miRNAs and to compare the expression level of these miRNAs between the lung stage schistosomula and adult worm stages. Expression of 11 novel miRNAs was confirmed by northern blot analysis and some presented a stage-regulated expression pattern. Three miRNAs previously identified from S. japonicum were also present in S. mansoni.ConclusionEvidence for the presence of miRNAs in S. mansoni is presented. The number of miRNAs detected by homology-based computational methods in S. mansoni is limited due to the lack of close relatives in the miRNA repository. In spite of this, the computational approach described here can likely be applied to the identification of pre-miRNA hairpins in other organisms. Construction and analysis of a small RNA library led to the experimental identification of 14 novel miRNAs from S. mansoni through a combination of molecular cloning, DNA sequencing and expression studies. Our results significantly expand the set of known miRNAs in multicellular parasites and provide a basis for understanding the structural and functional evolution of miRNAs in these metazoan parasites.

A Comparative Proteomic Analysis of the Simple Amino Acid Repeat Distributions in Plasmodia Reveals Lineage Specific Amino Acid Selection

Background Microsatellites have been used extensively in the field of comparative genomics. By studying microsatellites in coding regions we have a simple model of how genotypic changes undergo selection as they are directly expressed in the phenotype as altered proteins. The simplest of these tandem repeats in coding regions are the tri-nucleotide repeats which produce a repeat of a single amino acid when translated into proteins. Tri-nucleotide repeats are often disease associated, and are also known to be unstable to both expansion and contraction. This makes them sensitive markers for studying proteome evolution, in closely related species. Results The evolutionary history of the family of malarial causing parasites Plasmodia is complex because of the life-cycle of the organism, where it interacts with a number of different hosts and goes through a series of tissue specific stages. This study shows that the divergence between the primate and rodent malarial parasites has resulted in a lineage specific change in the simple amino acid repeat distribution that is correlated to A–T content. The paper also shows that this altered use of amino acids in SAARs is consistent with the repeat distributions being under selective pressure. Conclusions The study shows that simple amino acid repeat distributions can be used to group related species and to examine their phylogenetic relationships. This study also shows that an outgroup species with a similar A–T content can be distinguished based only on the amino acid usage in repeats, and suggest that this might be a useful feature for proteome clustering. The lineage specific use of amino acids in repeat regions suggests that comparative studies of SAAR distributions between proteomes gives an insight into the mechanisms of expansion and the selective pressures acting on the organism.

A global phylogenetic analysis in order to determine the host species and geography dependent features present in the evolution of avian H9N2 influenza hemagglutinin

A complete phylogenetic analysis of all of the H9N2 hemagglutinin sequences that were collected between 1966 and 2012 was carried out in order to build a picture of the geographical and host specific evolution of the hemagglutinin protein. To improve the quality and applicability of the output data the sequences were divided into subsets based upon location and host species. The phylogenetic analysis of hemagglutinin reveals that the protein has distinct lineages between China and the Middle East, and that wild birds in both regions retain a distinct form of the H9 molecule, from the same lineage as the ancestral hemagglutinin. The results add further evidence to the hypothesis that the current predominant H9N2 hemagglutinin lineage might have originated in Southern China. The study also shows that there are sampling problems that affect the reliability of this and any similar analysis. This raises questions about the surveillance of H9N2 and the need for wider sampling of the virus in the environment. The results of this analysis are also consistent with a model where hemagglutinin has predominantly evolved by neutral drift punctuated by occasional selection events. These selective events have produced the current pattern of distinct lineages in the Middle East, Korea and China. This interpretation is in agreement with existing studies that have shown that there is widespread intra-country sequence evolution.

The European and Japanese outbreaks of H5N8 derive from a single source population providing evidence for the dispersal along the long distance bird migratory flyways

The origin of recent parallel outbreaks of the high pathogenicity H5N8 avian flu virus in Europe and in Japan can be traced to a single source population, which has most likely been spread by migratory birds. By using Bayesian coalescent methods to analyze the DNA sequences of the virus to find the times for divergence and combining this sequence data with bird migration data we can show the most likely locations and migratory pathways involved in the origin of the current outbreak. This population was most likely located in the Siberian summer breeding grounds of long-range migratory birds. These breeding grounds provide a connection between different migratory flyways and explain the current outbreaks in remote locations. By combining genetic methods and epidemiological data we can rapidly identify the sources and the dispersion pathways for novel avian influenza outbreaks.

Molecular Dynamics Simulations of the Temperature Induced Unfolding of Crambin Follow the Arrhenius Equation.

Molecular dynamics simulations have been used extensively to model the folding and unfolding of proteins. The rates of folding and unfolding should follow the Arrhenius equation over a limited range of temperatures. This study shows that molecular dynamic simulations of the unfolding of crambin between 500K and 560K do follow the Arrhenius equation. They also show that while there is a large amount of variation between the simulations the average values for the rate show a very high degree of correlation.

Analysis of gene expression data from non-small cell lung carcinoma cell lines reveals distinct sub-classes from those identified at the phenotype level.

Microarray data from cell lines of Non-Small Cell Lung Carcinoma (NSCLC) can be used to look for differences in gene expression between the cell lines derived from different tumour samples, and to investigate if these differences can be used to cluster the cell lines into distinct groups. Dividing the cell lines into classes can help to improve diagnosis and the development of screens for new drug candidates. The micro-array data is first subjected to quality control analysis and then subsequently normalised using three alternate methods to reduce the chances of differences being artefacts resulting from the normalisation process. The final clustering into sub-classes was carried out in a conservative manner such that sub-classes were consistent across all three normalisation methods. If there is structure in the cell line population it was expected that this would agree with histological classifications, but this was not found to be the case. To check the biological consistency of the sub-classes the set of most strongly differentially expressed genes was be identified for each pair of clusters to check if the genes that most strongly define sub-classes have biological functions consistent with NSCLC.

Grade Retention in Primary Education Is Associated with Quarter of Birth and Socioeconomic Status

Grade retention is still common practice in some countries though longstanding experience tells us that it is a highly criticised practice for its unclear benefits, its important costs for the educational systems and its relation with school dropout. Therefore, the aim of the present study is to analyse which variables increase the probability of being retained in primary education differentiating between being retained in second or in fourth grade, and paying special attention to the role of the socioeconomic status of the families. By knowing which analysed variables are related to grade retention, and how, we may offer some suggestions to reduce it. We use a national dataset with more observations for Spain than any other international ones, called ‘Evaluación General de Diagnóstico’, conducted in Spain in 2009 with the participation of 28708 students of fourth grade of primary education from 874 schools, considered to be representative for every Spanish autonomous region. This assessment focused on four competences and includes information about the learning context collected through questionnaires for students, families, school management and teachers. Estimating different multilevel random-intercept logistic regressions we obtain the following three main findings: 1) the existence of a ‘quarter of birth’ effect, that nearly doubles the probability of grade retention in second grade of primary –compared to the probability of grade retention in fourth grade–, for the youngest students of their same age cohort (OR = 1.93 vs. OR = 1.53, both p<0.001); 2) that the mothers’ education level influences more than the fathers’ one –especially in second grade (OR = 0.20 vs. OR = 0.45, both p<0.001)–; and 3) that having an unemployed father increases the probability of grade retention much more than having an unemployed mother –especially in second grade (OR = 1.48, p<0.005 vs. OR = 1.18, p>0.05)–.

Developing Stochastic Models for Spatial Inference: Bacterial Chemotaxis

Background Biological systems are inherently inhomogeneous and spatial effects play a significant role in processes such as pattern formation. At the cellular level proteins are often localised either through static attachment or via a dynamic equilibrium. As well as spatial heterogeneity many cellular processes exhibit stochastic fluctuations and so to make inferences about the location of molecules there is a need for spatial stochastic models. A test case for spatial models has been bacterial chemotaxis which has been studied extensively as a model of signal transduction. Results By creating specific models of a cellular system that incorporate the spatial distributions of molecules we have shown how the fit between simulated and experimental data can be used to make inferences about localisation, in the case of bacterial chemotaxis. This method allows the robust comparison of different spatial models through alternative model parameterisations. Conclusions By using detailed statistical analysis we can reliably infer the parameters for the spatial models, and also to evaluate alternative models. The statistical methods employed in this case are particularly powerful as they reduce the need for a large number of simulation replicates. The technique is also particularly useful when only limited molecular level data is available or where molecular data is not quantitative.

Microbial adaptation to venom is common in snakes and spiders

Animal venoms are considered sterile sources of antimicrobial compounds with strong membrane disrupting activity against multi-drug resistant bacteria. However, bite wound infections are common in developing nations. Investigating the oral and venom microbiome of five snake and two spider species, we evidence viable microorganisms potentially unique to venom for black-necked spitting cobras (Naja nigricollis). Among these are two novel sequence types of Enterococcus faecalis misidentified by commonly used clinical biochemistry procedures as Staphylococcus; the genome sequence data of venom-specific isolates feature an additional 45 genes, at least 11 of which improve membrane integrity. Our findings challenge the dogma of venom sterility and indicate an increased primary infection risk in the clinical management of venomous animal bite wounds. One Sentence Summary Independent bacterial colonization of cobra venom drives acquisition of genes antagonistic to venom antimicrobial peptides.

Topological and kinetic determinants of the modal matrices of dynamic models of metabolism

Large-scale kinetic models of metabolism are becoming increasingly comprehensive and accurate. A key challenge is to understand the biochemical basis of the dynamic properties of these models. Linear analysis methods are well-established as useful tools for characterizing the dynamic response of metabolic networks. Central to linear analysis methods are two key matrices: the Jacobian matrix (J) and the modal matrix (M-1) arising from its eigendecomposition. The modal matrix M-1 contains dynamically independent motions of the kinetic model near a reference state, and it is sparse in practice for metabolic networks. However, connecting the structure of M-1 to the kinetic properties of the underlying reactions is non-trivial. In this study, we analyze the relationship between J, M-1, and the kinetic properties of the underlying network for kinetic models of metabolism. Specifically, we describe the origin of mode sparsity structure based on features of the network stoichiometric matrix S and the reaction kinetic gradient matrix G. First, we show that due to the scaling of kinetic parameters in real networks, diagonal dominance occurs in a substantial fraction of the rows of J, resulting in simple modal structures with clear biological interpretations. Then, we show that more complicated modes originate from topologically-connected reactions that have similar reaction elasticities in G. These elasticities represent dynamic equilibrium balances within reactions and are key determinants of modal structure. The work presented should prove useful towards obtaining an understanding of the dynamics of kinetic models of metabolism, which are rooted in the network structure and the kinetic properties of reactions.