A Bayesian palaeoenvironmental transfer function model for acidified lakes

A Bayesian approach to palaeoecological environmental reconstruction deriving from the unimodal responses generally exhibited by organisms to an environmental gradient is described. The approach uses Bayesian model selection to calculate a collection of probability-weighted, species-specific response curves (SRCs) for each taxon within a training set, with an explicit treatment for zero abundances. These SRCs are used to reconstruct the environmental variable from sub-fossilised assemblages. The approach enables a substantial increase in computational efficiency (several orders of magnitude) over existing Bayesian methodologies. The model is developed from the Surface Water Acidification Programme (SWAP) training set and is demonstrated to exhibit comparable predictive power to existing Weighted Averaging and Maximum Likelihood methodologies, though with improvements in bias; the additional explanatory power of the Bayesian approach lies in an explicit calculation of uncertainty for each individual reconstruction. The model is applied to reconstruct the Holocene acidification history of the Round Loch of Glenhead, including a reconstruction of recent recovery derived from sediment trap data.The Bayesian reconstructions display similar trends to conventional (Weighted Averaging Partial Least Squares) reconstructions but provide a better reconstruction of extreme pH and are more sensitive to small changes in diatom assemblages. The validity of the posteriors as an apparently meaningful representation of assemblage-specific uncertainty and the high computational efficiency of the approach open up the possibility of highly constrained multiproxy reconstructions

A global perspective on marine photosynthetic picoeukaryote community structure

A central goal in ecology is to understand the factors affecting the temporal dynamics and spatial distribution of microorganisms and the underlying processes causing differences in community structure and composition. However, little is known in this respect for photosynthetic picoeukaryotes (PPEs), algae that are now recognised as major players in marine CO2 fixation. Here, we analysed dot blot hybridisation and cloning–sequencing data, using the plastid-encoded 16S rRNA gene, from seven research cruises that encompassed all four ocean biomes. We provide insights into global abundance, α- and β-diversity distribution and the environmental factors shaping PPE community structure and composition. At the class level, the most commonly encountered PPEs were Prymnesiophyceae and Chrysophyceae. These taxa displayed complementary distribution patterns, with peak abundances of Prymnesiophyceae and Chrysophyceae in waters of high (25:1) or low (12:1) nitrogen:phosphorus (N:P) ratio, respectively. Significant differences in phylogenetic composition of PPEs were demonstrated for higher taxonomic levels between ocean basins, using Unifrac analyses of clone library sequence data. Differences in composition were generally greater between basins (interbasins) than within a basin (intrabasin). These differences were primarily linked to taxonomic variation in the composition of Prymnesiophyceae and Prasinophyceae whereas Chrysophyceae were phylogenetically similar in all libraries. These data provide better knowledge of PPE community structure across the world ocean and are crucial in assessing their evolution and contribution to CO2 fixation, especially in the context of global climate change

Monitoring and evaluation of malaria in pregnancy – developing a rational basis for control

Monitoring and evaluation of malaria control in pregnancy is essential for assessing the efficacy and effectiveness of health interventions aimed at reducing the major burden of this disease on women living in endemic areas. Yet there is no currently integrated strategic approach on how this should be achieved. Malaria control in pregnancy is formulated in relation to epidemiological patterns of exposure. Current emphasis is on intermittent preventive treatment (IPTp) during pregnancy with sulphadoxine-pyrimethamine in higher transmission areas, combined with insecticide treated bed nets (ITNs) and case management. Emphasis in lower transmission areas is primarily on case management. This paper discusses a rational basis for monitoring and evaluation based on: assessments of therapeutic and prophylactic drug efficacy; proportional reductions in parasite prevalence; seasonal effects; rapid assessment methodologies; birthweight and/or anaemia nomograms; case-coverage methods; maternal mortality indices; operational and programmatic indicators; and safety and pharmacovigilance of antimalarials in pregnancy. These approaches should be incorporated more effectively within National Programmes in order to facilitate surveillance and improve identification of high-risk women. Systems for utilizing routinely collected data should be strengthened, with greater attention to safety and pharmacovigilance with the advent of artemisinin combination therapies, and prospects of inadvertent exposures to artemisinins in the first trimester. Integrating monitoring activities within malaria control, reproductive health and adolescent-friendly services will be critical for implementation. Large-scale operational research is required to further evaluate the validity of currently proposed indicators, and in order to clarify the breadth and scale of implementation to be deployed

Sequenceserver: A Modern Graphical User Interface for Custom BLAST Databases

Comparing newly obtained and previously known nucleotide and amino-acid sequences underpins modern biological research. BLAST is a well-established tool for such comparisons but is challenging to use on new data sets. We combined a user-centric design philosophy with sustainable software development approaches to create Sequenceserver, a tool for running BLAST and visually inspecting BLAST results for biological interpretation. Sequenceserver uses simple algorithms to prevent potential analysis errors and provides flexible text-based and visual outputs to support researcher productivity. Our software can be rapidly installed for use by individuals or on shared servers

RNA-Seq improves annotation of protein-coding genes in the cucumber genome

<p>Abstract</p> <p>Background</p> <p>As more and more genomes are sequenced, genome annotation becomes increasingly important in bridging the gap between sequence and biology. Gene prediction, which is at the center of genome annotation, usually integrates various resources to compute consensus gene structures. However, many newly sequenced genomes have limited resources for gene predictions. In an effort to create high-quality gene models of the cucumber genome (<it>Cucumis sativus </it>var. <it>sativus</it>), based on the EVidenceModeler gene prediction pipeline, we incorporated the massively parallel complementary DNA sequencing (RNA-Seq) reads of 10 cucumber tissues into EVidenceModeler. We applied the new pipeline to the reassembled cucumber genome and included a comparison between our predicted protein-coding gene sets and a published set.</p> <p>Results</p> <p>The reassembled cucumber genome, annotated with RNA-Seq reads from 10 tissues, has 23, 248 identified protein-coding genes. Compared with the published prediction in 2009, approximately 8, 700 genes reveal structural modifications and 5, 285 genes only appear in the reassembled cucumber genome. All the related results, including genome sequence and annotations, are available at <url>http://cmb.bnu.edu.cn/Cucumis_sativus_v20/</url>.</p> <p>Conclusions</p> <p>We conclude that RNA-Seq greatly improves the accuracy of prediction of protein-coding genes in the reassembled cucumber genome. The comparison between the two gene sets also suggests that it is feasible to use RNA-Seq reads to annotate newly sequenced or less-studied genomes.</p

CodingQuarry: Highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts

Background: The impact of gene annotation quality on functional and comparative genomics makes gene prediction an important process, particularly in non-model species, including many fungi. Sets of homologous protein sequences are rarely complete with respect to the fungal species of interest and are often small or unreliable, especially when closely related species have not been sequenced or annotated in detail. In these cases, protein homology-based evidence fails to correctly annotate many genes, or significantly improve ab initio predictions. Generalised hidden Markov models (GHMM) have proven to be invaluable tools in gene annotation and, recently, RNA-seq has emerged as a cost-effective means to significantly improve the quality of automated gene annotation. As these methods do not require sets of homologous proteins, improving gene prediction from these resources is of benefit to fungal researchers. While many pipelines now incorporate RNA-seq data in training GHMMs, there has been relatively little investigation into additionally combining RNA-seq data at the point of prediction, and room for improvement in this area motivates this study. Results: CodingQuarry is a highly accurate, self-training GHMM fungal gene predictor designed to work with assembled, aligned RNA-seq transcripts. RNA-seq data informs annotations both during gene-model training and in prediction. Our approach capitalises on the high quality of fungal transcript assemblies by incorporating predictions made directly from transcript sequences. Correct predictions are made despite transcript assembly problems, including those caused by overlap between the transcripts of adjacent gene loci. Stringent benchmarking against high-confidence annotation subsets showed CodingQuarry predicted 91.3% of Schizosaccharomyces pombe genes and 90.4% of Saccharomyces cerevisiae genes perfectly. These results are 4-5% better than those of AUGUSTUS, the next best performing RNA-seq driven gene predictor tested. Comparisons against whole genome Sc. pombe and S. cerevisiae annotations further substantiate a 4-5% improvement in the number of correctly predicted genes. Conclusions: We demonstrate the success of a novel method of incorporating RNA-seq data into GHMM fungal gene prediction. This shows that a high quality annotation can be achieved without relying on protein homology or a training set of genes. CodingQuarry is freely available (https://sourceforge.net/projects/codingquarry/), and suitable for incorporation into genome annotation pipelines

Silencing Early Viral Replication in Macrophages and Dendritic Cells Effectively Suppresses Flavivirus Encephalitis

West Nile (WN) and St. Louis encephalitis (SLE) viruses can cause fatal neurological infection and currently there is neither a specific treatment nor an approved vaccine for these infections. In our earlier studies, we have reported that siRNAs can be developed as broad-spectrum antivirals for the treatment of infection caused by related viruses and that a small peptide called RVG-9R can deliver siRNA to neuronal cells as well as macrophages. To increase the repertoire of broad-spectrum antiflaviviral siRNAs, we screened 25 siRNAs targeting conserved regions in the viral genome. Five siRNAs were found to inhibit both WNV and SLE replication in vitro reflecting broad-spectrum antiviral activity and one of these was also validated in vivo. In addition, we also show that RVG-9R delivers siRNA to macrophages and dendritic cells, resulting in effective suppression of virus replication. Mice were challenged intraperitoneally (i.p.) with West Nile virus (WNV) and treated i.v. with siRNA/peptide complex. The peritoneal macrophages isolated on day 3 post infection were isolated and transferred to new hosts. Mice receiving macrophages from the anti-viral siRNA treated mice failed to develop any disease while the control mice transferred with irrelevant siRNA treated mice all died of encephalitis. These studies suggest that early suppression of viral replication in macrophages and dendritic cells by RVG-9R-mediated siRNA delivery is key to preventing the development of a fatal neurological disease

Therapeutic efficacy of sulphadoxine-pyrimethamine and chloroquine for the treatment of uncomplicated malaria in pregnancy in Burkina Faso

BACKGROUND: A reduction in the therapeutic efficacy of chloroquine (CQ) and sulphadoxine-pyrimethamine (SP) has recently been observed in Burkina Faso. As these two drugs are used in pregnancy, their efficacy in pregnant women was studied to directly assess the level of drug resistance in this specific population, rather than to extrapolate results of studies conducted in children < 5 years of age. METHODS: During the malaria transmission season of 2003 in Ouagadougou, the clinical efficacy of SP and CQ, using the WHO 28-day protocol, was assessed in primigravidae and secundigravidae presenting with uncomplicated malaria. RESULTS: PCR-corrected results by day 28 showed that among 62 women treated with SP, eight (12.9%) experienced late parasitological failure, but no clinical failures. Among 60 women treated with CQ, the overall failure rate was 46.7% including 1.7% early treatment failures, 5% late clinical failures and 40% late parasitological failures. SP induced a haemoglobin gain of 0.3 g/dL by day 14 and 0.9 g/dL by day 28. Treatment responses were independent of gravidity, gestational age and prior antenatal care visits. CONCLUSION: While CQ should no longer be used, the efficacy of SP is still compatible with use for intermittent preventive treatment (IPT) in pregnancy. However, given the possible spread of resistance, the drug should be restricted in its use

Intermittent Screening and Treatment versus Intermittent Preventive Treatment of Malaria in Pregnancy: A Randomised Controlled Non-Inferiority Trial

BACKGROUND: The effectiveness of intermittent preventive treatment of malaria in pregnancy (IPTp) may be compromised by the spread of resistance to sulphadoxine/pyrimethamine (SP) across Africa. But little information exists on alternative drugs for IPTp or alternative strategies for the prevention of malaria in pregnancy. Therefore, we have investigated whether screening with a rapid diagnostic test and treatment of those who are positive (IST) at routine antenatal clinic attendances is as effective and as safe as SP-IPTp in pregnant women. METHODS AND FINDINGS: During antenatal clinic sessions in six health facilities in Ghana held between March 2007 and September 2007, 3333 pregnant women who satisfied inclusion criteria were randomised into three intervention arms (1) standard SP-IPTp, (2) IST and treatment with SP or (3) IST and treatment with amodiaquine+artesunate (AQ+AS). All women received a long-lasting insecticide treated net. Study women had a maximum of three scheduled follow-up visits following enrollment. Haemoglobin concentration and peripheral parasitaemia were assessed between 36 and 40 weeks of gestation. Birth weight was measured at delivery or within 72 hours for babies delivered at home. Parasite prevalence at enrollment in primigravidae and in multigravidae was 29.6% and 10.2% respectively. At 36-40 weeks of gestation the prevalence of asymptomatic parasitaemia was 12.1% in study women overall and was very similar in all treatment groups. The risk of third trimester severe anaemia or low birth weight did not differ significantly between the three treatment groups regardless of gravidity. IST with AQ+AS or SP was not inferior to SP-IPTp in reducing the risk of low birth weight (RD  =  -1.17[95%CI; -4.39-1.02] for IST-SP vs. SP-IPTp and RD = 0.78[95%CI; -2.11-3.68] for IST-AQAS vs. SP-IPTp); third trimester severe anaemia (RD = 0.29[95%CI; -0.69-1.30] for IST-SP vs. SP-IPTp and RD  =  -0.36[95%CI;-1.12-0.44] for IST-AQAS vs. SP-IPTp). CONCLUSION: The results of this study suggest that in an area of moderately high malaria transmission, IST with SP or AS+AQ may be a safe and effective strategy for the control of malaria in pregnancy. However, it is important that these encouraging findings are confirmed in other geographical areas and that the impact of IST on placental malaria is investigated. TRIAL REGISTRATION: ClinicalTrials.gov NCT00432367 [NCT00432367]