Ezrin Inhibition Overcomes Acquired Resistance to Vemurafenib in BRAFV600E-Mutated Colon Cancer and Melanoma Cells In Vitro.

Despite the advancements in targeted therapy for BRAFV600E-mutated metastatic colorectal cancer (mCRC), the development of resistance to BRAFV600E inhibition limits the response rate and durability of the treatment. Better understanding of the resistance mechanisms to BRAF inhibitors will facilitate the design of novel pharmacological strategies for BRAF-mutated mCRC. The aim of this study was to identify novel protein candidates involved in acquired resistance to BRAFV600E inhibitor vemurafenib in BRAFV600E-mutated colon cancer cells using an integrated proteomics approach. Bioinformatic analysis of obtained proteomics data indicated actin-cytoskeleton linker protein ezrin as a highly ranked protein significantly associated with vemurafenib resistance whose overexpression in the resistant cells was additionally confirmed at the gene and protein level. Ezrin inhibition by NSC305787 increased anti-proliferative and pro-apoptotic effects of vemurafenib in the resistant cells in an additive manner, which was accompanied by downregulation of CD44 expression and inhibition of AKT/c-Myc activities. We also detected an increased ezrin expression in vemurafenib-resistant melanoma cells harbouring the BRAFV600E mutation. Importantly, ezrin inhibition potentiated anti-proliferative and pro-apoptotic effects of vemurafenib in the resistant melanoma cells in a synergistic manner. Altogether, our study suggests a role of ezrin in acquired resistance to vemurafenib in colon cancer and melanoma cells carrying the BRAFV600E mutation and supports further pre-clinical and clinical studies to explore the benefits of combined BRAF inhibitors and actin-targeting drugs as a potential therapeutic approach for BRAFV600E-mutated cancers.

Roles of RbcX in Carboxysome Biosynthesis in the Cyanobacterium Synechococcus elongatus PCC7942.

Rubisco is the essential enzyme mediating the fixation of atmospheric CO2 during photosynthesis. In cyanobacteria, Rubisco enzymes are densely packed and encapsulated in a specialized organelle known as the carboxysome. Well-defined Rubisco assembly and carboxysome formation are pivotal for efficient CO2 fixation. Numerous chaperone proteins, including RbcX, are essential for proper protein folding and Rubisco assembly. In this study, we investigated the in vivo function of RbcX in the cyanobacterium Synechococcus elongatus PCC 7942 (Syn7942) using molecular, biochemical, and live-cell fluorescence imaging approaches. Our results show that genetic deletion of the rbcX gene affects Rubisco abundance, as well as carboxysome formation and spatial distribution. Moreover, RbcX appears as one component of the carboxysome and shows a dynamic interaction with Rubisco enzymes. These in vivo observations provide insight into the role of RbcX from Syn7942 in mediating carboxysome assembly. Understanding the molecular mechanism underlying Rubisco assembly and carboxysome biogenesis will provide essential information required for engineering functional CO2-fixing complexes in heterogeneous organisms, especially plants, with the aim of boosting photosynthesis and agricultural productivity.

Statistical analysis of human microarray data shows that dietary intervention with n-3 fatty acids, flavonoids and resveratrol enriches for immune response and disease pathways.

n-3 Fatty acids, flavonoids and resveratrol are well publicised for their beneficial effects on human health and wellbeing. Identifying common, underlying biological mechanisms targeted by these functional foods would therefore be informative for the public health sector for advising on nutritional health and disease, food and drug product development and consumer interest. The aim of this study was to explore the potential effects of gene expression changes associated with n-3 fatty acids EPA and DHA, flavonoids and resveratrol on modifying biological systems and disease pathways. To test this, publicly available human microarray data for significant gene expression changes associated with dietary intervention with EPA/DHA, flavonoids and resveratrol was subjected to pathway analysis and significance testing for overlap with signals from genome-wide association studies (GWAS) for common non-communicable diseases and biological functions. There was an enrichment of genes implicated in immune responses and disease pathways which was common to all of the treatment conditions tested. Analysis of biological functions and disease pathways indicated anti-tumorigenic properties for EPA/DHA. In line with this, significance testing of the intersection of genes associated with these functional foods and GWAS hits for common biological functions (ageing and cognition) and non-communicable diseases (breast cancer, CVD, diabesity, neurodegeneration and psychiatric disorders) identified significant overlap between the EPA/DHA and breast cancer gene sets. Dietary intervention with EPA/DHA, flavonoids and resveratrol can target important biological and disease pathways suggesting a potentially important role for these bioactive compounds in the prevention and treatment of dietary-related diseases.

An integrative in silico system for predicting dysregulated genes in the human epileptic focus: Application to SLC transporters.

OBJECTIVE: Many different gene families are currently being investigated for their potential role in epilepsy and in the response to antiepileptic drugs. A common research challenge is identifying the members of a gene family that are most significantly dysregulated within the human epileptic focus, before taking them forward for resource-intensive functional studies. Published data about transcriptomic changes within the human epileptic focus remains incomplete. A need exists for an accurate in silico system for the prediction of dysregulated genes within the epileptic focus. We present such a bioinformatic system. We demonstrate the validity of our approach by applying it to the solute carrier (SLC) gene family. There are >400 known SLCs. SLCs have never been systematically studied in epilepsy. METHODS: Using our in silico system, we predicted the SLCs likely to be dysregulated in the epileptic focus. We validated our in silico predictions by identifying ex vivo the SLCs dysregulated in epileptic foci, and determining the overlap between our in silico and ex vivo results. For the ex vivo analysis, we used a custom oligonucleotide microarray containing exon probes for all known SLCs to analyze 24 hippocampal samples obtained from surgery for pharmacoresistant mesial temporal lobe epilepsy and 24 hippocampal samples from normal postmortem controls. RESULTS: There was a highly significant (p < 9.99 × 10(-7) ) overlap between the genes identified by our in silico and ex vivo strategies. The SLCs identified were either metal ion exchangers or neurotransmitter transporters, which are likely to play a part in epilepsy by influencing neuronal excitability. SIGNIFICANCE: The identified SLCs are most likely to mediate pharmacoresistance in epilepsy by enhancing the intrinsic severity of epilepsy, but further functional work will be needed to fully evaluate their role. Our successful in silico strategy can be adapted in order to prioritize genes relevant to epilepsy from other gene families.

PNUTS/PP1 regulates RNAPII-mediated gene expression and is necessary for developmental growth.

In multicellular organisms, tight regulation of gene expression ensures appropriate tissue and organismal growth throughout development. Reversible phosphorylation of the RNA Polymerase II (RNAPII) C-terminal domain (CTD) is critical for the regulation of gene expression states, but how phosphorylation is actively modified in a developmental context remains poorly understood. Protein phosphatase 1 (PP1) is one of several enzymes that has been reported to dephosphorylate the RNAPII CTD. However, PP1's contribution to transcriptional regulation during animal development and the mechanisms by which its activity is targeted to RNAPII have not been fully elucidated. Here we show that the Drosophila orthologue of the PP1 Nuclear Targeting Subunit (dPNUTS) is essential for organismal development and is cell autonomously required for growth of developing tissues. The function of dPNUTS in tissue development depends on its binding to PP1, which we show is targeted by dPNUTS to RNAPII at many active sites of transcription on chromosomes. Loss of dPNUTS function or specific disruption of its ability to bind PP1 results in hyperphosphorylation of the RNAPII CTD in whole animal extracts and on chromosomes. Consistent with dPNUTS being a global transcriptional regulator, we find that loss of dPNUTS function affects the expression of the majority of genes in developing 1(st) instar larvae, including those that promote proliferative growth. Together, these findings shed light on the in vivo role of the PNUTS-PP1 holoenzyme and its contribution to the control of gene expression during early Drosophila development.

Library of Apicomplexan Metabolic Pathways: a manually curated database for metabolic pathways of apicomplexan parasites.

The Library of Apicomplexan Metabolic Pathways (LAMP, http://www.llamp.net) is a web database that provides near complete mapping from genes to the central metabolic functions for some of the prominent intracellular parasites of the phylum Apicomplexa. This phylum includes the causative agents of malaria, toxoplasmosis and theileriosis-diseases with a huge economic and social impact. A number of apicomplexan genomes have been sequenced, but the accurate annotation of gene function remains challenging. We have adopted an approach called metabolic reconstruction, in which genes are systematically assigned to functions within pathways/networks for Toxoplasma gondii, Neospora caninum, Cryptosporidium and Theileria species, and Babesia bovis. Several functions missing from pathways have been identified, where the corresponding gene for an essential process appears to be absent from the current genome annotation. For each species, LAMP contains interactive diagrams of each pathway, hyperlinked to external resources and annotated with detailed information, including the sources of evidence used. We have also developed a section to highlight the overall metabolic capabilities of each species, such as the ability to synthesize or the dependence on the host for a particular metabolite. We expect this new database will become a valuable resource for fundamental and applied research on the Apicomplexa.

Dissecting the gene network of dietary restriction to identify evolutionarily conserved pathways and new functional genes.

Dietary restriction (DR), limiting nutrient intake from diet without causing malnutrition, delays the aging process and extends lifespan in multiple organisms. The conserved life-extending effect of DR suggests the involvement of fundamental mechanisms, although these remain a subject of debate. To help decipher the life-extending mechanisms of DR, we first compiled a list of genes that if genetically altered disrupt or prevent the life-extending effects of DR. We called these DR-essential genes and identified more than 100 in model organisms such as yeast, worms, flies, and mice. In order for other researchers to benefit from this first curated list of genes essential for DR, we established an online database called GenDR (http://genomics.senescence.info/diet/). To dissect the interactions of DR-essential genes and discover the underlying lifespan-extending mechanisms, we then used a variety of network and systems biology approaches to analyze the gene network of DR. We show that DR-essential genes are more conserved at the molecular level and have more molecular interactions than expected by chance. Furthermore, we employed a guilt-by-association method to predict novel DR-essential genes. In budding yeast, we predicted nine genes related to vacuolar functions; we show experimentally that mutations deleting eight of those genes prevent the life-extending effects of DR. Three of these mutants (OPT2, FRE6, and RCR2) had extended lifespan under ad libitum, indicating that the lack of further longevity under DR is not caused by a general compromise of fitness. These results demonstrate how network analyses of DR using GenDR can be used to make phenotypically relevant predictions. Moreover, gene-regulatory circuits reveal that the DR-induced transcriptional signature in yeast involves nutrient-sensing, stress responses and meiotic transcription factors. Finally, comparing the influence of gene expression changes during DR on the interactomes of multiple organisms led us to suggest that DR commonly suppresses translation, while stimulating an ancient reproduction-related process.

Label-free mass spectrometric profiling of urinary proteins and metabolites from paediatric idiopathic nephrotic syndrome.

Idiopathic nephrotic syndrome (INS) is caused by renal diseases that increase the permeability of the glomerular filtration barrier without evidence of a specific systemic cause. The aim of the present work was to reveal inherent molecular features of INS in children using combined urinary proteomics and metabolomics profiling. In this study, label-free mass spectrometric analysis of urinary proteins and small molecule metabolites was carried out in 12 patients with INS versus 12 sex- and age-matched control subjects with normal renal function. Integration and biological interpretation of obtained results were carried out by Ingenuity IPA software. Validation of obtained proteomics data was carried out by Western blot method. Proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000765. This study indicates for the first time that paediatric INS is associated with up-regulation of afamin, hydroxyphenylacetate and uridine, and concomitant down-regulation in glutamine and phenylalanine levels, and many of these molecular species were previously shown to be involved in oxidative stress. Further studies in larger patient population are underway to investigate the role of oxidative stress in renal injury in paediatric INS.

Horizontal gene transfer facilitated the evolution of plant parasitic mechanisms in the oomycetes.

Horizontal gene transfer (HGT) can radically alter the genomes of microorganisms, providing the capacity to adapt to new lifestyles, environments, and hosts. However, the extent of HGT between eukaryotes is unclear. Using whole-genome, gene-by-gene phylogenetic analysis we demonstrate an extensive pattern of cross-kingdom HGT between fungi and oomycetes. Comparative genomics, including the de novo genome sequence of Hyphochytrium catenoides, a free-living sister of the oomycetes, shows that these transfers largely converge within the radiation of oomycetes that colonize plant tissues. The repertoire of HGTs includes a large number of putatively secreted proteins; for example, 7.6% of the secreted proteome of the sudden oak death parasite Phytophthora ramorum has been acquired from fungi by HGT. Transfers include gene products with the capacity to break down plant cell walls and acquire sugars, nucleic acids, nitrogen, and phosphate sources from the environment. Predicted HGTs also include proteins implicated in resisting plant defense mechanisms and effector proteins for attacking plant cells. These data are consistent with the hypothesis that some oomycetes became successful plant parasites by multiple acquisitions of genes from fungi.

Exploring the genomic basis of pharmacoresistance in epilepsy: an integrative analysis of large-scale gene expression profiling studies on brain tissue from epilepsy surgery.

Some patients with pharmacoresistant epilepsy undergo therapeutic resection of the epileptic focus. At least 12 large-scale microarray studies on brain tissue from epilepsy surgery have been published over the last 10 years, but they have failed to make a significant impact upon our understanding of pharmacoresistance, because (1) doubts have been raised about their reproducibility, (2) only a small number of the gene expression changes found in each microarray study have been independently validated and (3) the results of different studies have not been integrated to give a coherent picture of the genetic changes involved in epilepsy pharmacoresistance. To overcome these limitations, we (1) assessed the reproducibility of the microarray studies by calculating the overlap between lists of differentially regulated genes from pairs of microarray studies and determining if this was greater than would be expected by chance alone, (2) used an inter-study cross-validation technique to simultaneously verify the expression changes of large numbers of genes and (3) used the combined results of the different microarray studies to perform an integrative analysis based on enriched gene ontology terms, networks and pathways. Using this approach, we respectively (1) demonstrate that there are statistically significant overlaps between the gene expression changes in different publications, (2) verify the differential expression of 233 genes and (3) identify the biological processes, networks and genes likely to be most important in the development of pharmacoresistant epilepsy. Our analysis provides novel biologically plausible candidate genes and pathways which warrant further investigation to assess their causal relevance.

Transcriptomics and in vivo tests reveal novel mechanisms underlying endocrine disruption in an ecological sentinel, Nucella lapillus.

Anthropogenic endocrine disruptors now contaminate all environments globally, with concomitant deleterious effects across diverse taxa. While most studies on endocrine disruption (ED) have focused on vertebrates, the superimposition of male sexual characteristics in the female dogwhelk, Nucella lapillus (imposex), caused by organotins, provides one of the most clearcut ecological examples of anthropogenically induced ED in aquatic ecosystems. To identify the underpinning mechanisms of imposex for this 'nonmodel' species, we combined Roche 454 pyrosequencing with custom oligoarray fabrication inexpensively to both generate gene models and identify those responding to chronic tributyltin (TBT) treatment. The results supported the involvement of steroid, neuroendocrine peptide hormone dysfunction and retinoid mechanisms, but suggested additionally the involvement of putative peroxisome proliferator-activated receptor (PPAR) pathways. Application of rosiglitazone, a well-known vertebrate PPARγ ligand, to dogwhelks induced imposex in the absence of TBT. Thus, while TBT-induced imposex is linked to the induction of many genes and has a complex phenotype, it is likely also to be driven by PPAR-responsive pathways, hitherto not described in invertebrates. Our findings provide further evidence for a common signalling pathway between invertebrate and vertebrate species that has previously been overlooked in the study of endocrine disruption.

Mathematical modelling in developmental biology.

In recent decades, molecular and cellular biology has benefited from numerous fascinating developments in experimental technique, generating an overwhelming amount of data on various biological objects and processes. This, in turn, has led biologists to look for appropriate tools to facilitate systematic analysis of data. Thus, the need for mathematical techniques, which can be used to aid the classification and understanding of this ever-growing body of experimental data, is more profound now than ever before. Mathematical modelling is becoming increasingly integrated into biological studies in general and into developmental biology particularly. This review outlines some achievements of mathematics as applied to developmental biology and demonstrates the mathematical formulation of basic principles driving morphogenesis. We begin by describing a mathematical formalism used to analyse the formation and scaling of morphogen gradients. Then we address a problem of interplay between the dynamics of morphogen gradients and movement of cells, referring to mathematical models of gastrulation in the chick embryo. In the last section, we give an overview of various mathematical models used in the study of the developmental cycle of Dictyostelium discoideum, which is probably the best example of successful mathematical modelling in developmental biology.

Exploring Toxin Genes of Myanmar Russell's Viper, Daboia siamensis, through De Novo Venom Gland Transcriptomics.

The Russell's viper (Daboia siamensis) is a medically important venomous snake in Myanmar. Next-generation sequencing (NGS) shows potential to investigate the venom complexity, giving deeper insights into snakebite pathogenesis and possible drug discoveries. mRNA from venom gland tissue was extracted and sequenced on the Illumina HiSeq platform and de novo assembled by Trinity. The candidate toxin genes were identified via the Venomix pipeline. Protein sequences of identified toxin candidates were compared with the previously described venom proteins using Clustal Omega to assess the positional homology among candidates. Candidate venom transcripts were classified into 23 toxin gene families including 53 unique full-length transcripts. C-type lectins (CTLs) were the most highly expressed, followed by Kunitz-type serine protease inhibitors, disintegrins and Bradykinin potentiating peptide/C-type natriuretic peptide (BPP-CNP) precursors. Phospholipase A2, snake venom serine proteases, metalloproteinases, vascular endothelial growth factors, L-amino acid oxidases and cysteine-rich secretory proteins were under-represented within the transcriptomes. Several isoforms of transcripts which had not been previously reported in this species were discovered and described. Myanmar Russell's viper venom glands displayed unique sex-specific transcriptome profiles which were correlated with clinical manifestation of envenoming. Our results show that NGS is a useful tool to comprehensively examine understudied venomous snakes.

Engineering of increased L-Threonine production in bacteria by combinatorial cloning and machine learning.

The goal of this study is to develop a general strategy for bacterial engineering using an integrated synthetic biology and machine learning (ML) approach. This strategy was developed in the context of increasing L-threonine production in Escherichia coli ATCC 21277. A set of 16 genes was initially selected based on metabolic pathway relevance to threonine biosynthesis and used for combinatorial cloning to construct a set of 385 strains to generate training data (i.e., a range of L-threonine titers linked to each of the specific gene combinations). Hybrid (regression/classification) deep learning (DL) models were developed and used to predict additional gene combinations in subsequent rounds of combinatorial cloning for increased L-threonine production based on the training data. As a result, E. coli strains built after just three rounds of iterative combinatorial cloning and model prediction generated higher L-threonine titers (from 2.7 g/L to 8.4 g/L) than those of patented L-threonine strains being used as controls (4-5 g/L). Interesting combinations of genes in L-threonine production included deletions of the tdh, metL, dapA, and dhaM genes as well as overexpression of the pntAB, ppc, and aspC genes. Mechanistic analysis of the metabolic system constraints for the best performing constructs offers ways to improve the models by adjusting weights for specific gene combinations. Graph theory analysis of pairwise gene modifications and corresponding levels of L-threonine production also suggests additional rules that can be incorporated into future ML models.

A data mining approach for classifying DNA repair genes into ageing-related or non-ageing-related.

BACKGROUND: The ageing of the worldwide population means there is a growing need for research on the biology of ageing. DNA damage is likely a key contributor to the ageing process and elucidating the role of different DNA repair systems in ageing is of great interest. In this paper we propose a data mining approach, based on classification methods (decision trees and Naive Bayes), for analysing data about human DNA repair genes. The goal is to build classification models that allow us to discriminate between ageing-related and non-ageing-related DNA repair genes, in order to better understand their different properties. RESULTS: The main patterns discovered by the classification methods are as follows: (a) the number of protein-protein interactions was a predictor of DNA repair proteins being ageing-related; (b) the use of predictor attributes based on protein-protein interactions considerably increased predictive accuracy of attributes based on Gene Ontology (GO) annotations; (c) GO terms related to "response to stimulus" seem reasonably good predictors of ageing-relatedness for DNA repair genes; (d) interaction with the XRCC5 (Ku80) protein is a strong predictor of ageing-relatedness for DNA repair genes; and (e) DNA repair genes with a high expression in T lymphocytes are more likely to be ageing-related. CONCLUSIONS: The above patterns are broadly integrated in an analysis discussing relations between Ku, the non-homologous end joining DNA repair pathway, ageing and lymphocyte development. These patterns and their analysis support non-homologous end joining double strand break repair as central to the ageing-relatedness of DNA repair genes. Our work also showcases the use of protein interaction partners to improve accuracy in data mining methods and our approach could be applied to other ageing-related pathways.

RNA-Sequencing of Snake Venom Glands.

Next-generation sequencing (NGS), particularly RNA-sequencing (RNA-Seq) technique, allows detection and quantification of different RNA transcripts in a tissue sample, and in our case toxin transcripts from snake venom glands. Using this approach, novel toxin transcripts can be detected and abundancies of different isoforms of each toxin measured. The analytical pipeline can be briefly outlined as follows. Isolation of mRNA from tissue under RNase-free condition is essential to keep mRNA intact before sequencing. After mRNA fragmentation, the adapters are added to both ends of the fragments to synthesize complementary cDNAs. The obtained cDNA library is then sequenced on Illumina HiSeq 2000 platform. Quality of millions of reads produced from the NGS is checked and the sequences corresponding to the adapters and low-quality reads are removed. Subsequently, the NGS data are subjected to the workflow of de novo assembly, quantification of expression levels, annotation of transcripts, and identification of ORFs, signal peptides, structurally conserved domains, and functional motifs. In this report we describe the listed methodological steps and techniques in details and refer to the platforms and software that may be adopted for similar studies.

Analysis of snake venom metalloproteinases from Myanmar Russell's viper transcriptome.

Snake venom metalloproteinases (SVMPs) are the key enzymes in Russell's viper (RV) venom which target all important components of haemostasis, such as clotting factors, platelets, endothelial cells and basement membrane. The structural diversity of SVMPs contributes to the broad spectrum of biological activities. The aim of the study was to investigate the SVMP transcript profile to gain better insights into the characteristic clinical manifestations of the Myanmar Russell's viper (MRV) bites that distinguish it from the RVs of other habitats. Next generation sequencing (RNA-Seq) of mRNA from MRV venom glands (2 males and 1 female) was performed on an Illumina HiSeq2000 platform and then de novo assembled using Trinity software. A total of 59 SVMP contigs were annotated through a Blastn search against the serpent nucleotide database from NCBI. Among them, disintegrins were the most abundant transcripts (75%) followed by the P-III class SVMPs (25%). The P-II SVMPs were scarce (0.002%), while no P-I SVMPs were detectable in the transcriptome. For detailed structural analysis, contigs were conceptually translated and compared with amino acid sequences from other RVs and other vipers using Clustal Omega. The RTS-disintegrin (jerdostatin homolog) was the most abundant among transcripts corresponding to 5 disintegrin isoforms. From 10 isoforms of SVMPs, RVV-X, and Vipera lebetina apoptosis-inducing protease (VLAIP) homolog, hereby termed Daboia siamensis AIP (DSAIP), were found to be highly expressed. Venom protein analysis using SDS-PAGE followed by mass spectrometry revealed that the disintegrin was scarce, while the latter two SVMPs were abundant. These two proteins can contribute to severe clinical manifestations caused by MRV envenomation.

Peripheral blood RNA gene expression in children with pneumococcal meningitis: a prospective case-control study.

INTRODUCTION: Invasive pneumococcal disease (IPD), caused by Streptococcus pneumoniae, is a leading cause of pneumonia, meningitis and septicaemia worldwide, with increased morbidity and mortality in HIV-infected children. OBJECTIVES: We aimed to compare peripheral blood expression profiles between HIV-infected and uninfected children with pneumococcal meningitis and controls, and between survivors and non-survivors, in order to provide insight into the host inflammatory response leading to poorer outcomes. DESIGN AND SETTING: Prospective case-control observational study in a tertiary hospital in Malawi. PARTICIPANTS: Children aged 2 months to 16 years with pneumococcal meningitis or pneumonia. METHODS: We used the human genome HGU133A Affymetrix array to explore differences in gene expression between cases with pneumococcal meningitis (n=12) and controls, and between HIV-infected and uninfected cases, and validated gene expression profiles for 34 genes using real-time quantitative PCR (RT-qPCR) in an independent set of cases with IPD (n=229) and controls (n=13). Pathway analysis was used to explore genes differentially expressed. RESULTS: Irrespective of underlying HIV infection, cases showed significant upregulation compared with controls of the following: S100 calcium-binding protein A12 (S100A12); vanin-1 (VNN1); arginase, liver (ARG1); matrix metallopeptidase 9 (MMP9); annexin A3 (ANXA3); interleukin 1 receptor, type II (IL1R2); CD177 molecule (CD177); endocytic adaptor protein (NUMB) and S100 calcium-binding protein A9 (S100A9), cytoskeleton-associated protein 4 (CKAP4); and glycogenin 1 (GYG1). RT-qPCR confirmed differential expression in keeping with microarray results. There was no differential gene expression in HIV-infected compared with HIV-uninfected cases, but there was significant upregulation of folate receptor 3 (FOLR3), S100A12 in survivors compared with non-survivors. CONCLUSION: Children with IPD demonstrated increased expression in genes regulating immune activation, oxidative stress, leucocyte adhesion and migration, arginine metabolism, and glucocorticoid receptor signalling.

The ERGO genome analysis and discovery system.

The ERGO (http://ergo.integratedgenomics.com/ERGO/) genome analysis and discovery suite is an integration of biological data from genomics, biochemistry, high-throughput expression profiling, genetics and peer-reviewed journals to achieve a comprehensive analysis of genes and genomes. Far beyond any conventional systems that facilitate functional assignments, ERGO combines pattern-based analysis with comparative genomics by visualizing genes within the context of regulation, expression profiling, phylogenetic clusters, fusion events, networked cellular pathways and chromosomal neighborhoods of other functionally related genes. The result of this multifaceted approach is to provide an extensively curated database of the largest available integration of genomes, with a vast collection of reconstructed cellular pathways spanning all domains of life. Although access to ERGO is provided only under subscription, it is already widely used by the academic community. The current version of the system integrates 500 genomes from all domains of life in various levels of completion, 403 of which are available for subscription.

On the heterogeneity of human populations as reflected by mortality dynamics.

The heterogeneity of populations is used to explain the variability of mortality rates across the lifespan and their deviations from an exponential growth at young and very old ages. A mathematical model that combines the heterogeneity with the assumption that the mortality of each constituent subpopulation increases exponentially with age, has been shown to successfully reproduce the entire mortality pattern across the lifespan and its evolution over time. In this work we aim to show that the heterogeneity is not only a convenient consideration for fitting mortality data but is indeed the actual structure of the population as reflected by the mortality dynamics over age and time. In particular, we show that the model of heterogeneous population fits mortality data better than other commonly used mortality models. This was demonstrated using cohort data taken for the entire lifespan as well as for only old ages. Also, we show that the model can reproduce seemingly contradicting observations in late-life mortality dynamics. Finally, we show that the homogenisation of a population, observed by fitting the model to actual data of consecutive periods, can be associated with the evolution of allele frequencies if the heterogeneity is assumed to reflect the genetic variations within the population.