What Was the Set of Ubiquitin and Ubiquitin-Like Conjugating Enzymes in the Eukaryote Common Ancestor?

Ubiquitin (Ub)-conjugating enzymes (E2) are key enzymes in ubiquitination or Ub-like modifications of proteins. We searched for all proteins belonging to the E2 enzyme super-family in seven species (Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Schizosaccharomyces pombe, Saccharomyces cerevisiae, and Arabidopsis thaliana) to identify families and to reconstruct each family’s phylogeny. Our phylogenetic analysis of 207 genes led us to define 17 E2 families, with 37 E2 genes, in the human genome. The subdivision of E2 into four classes did not correspond to the phylogenetic tree. The sequence signature HPN (histidine–proline–asparagine), followed by a tryptophan residue at 16 (up to 29) amino acids, was highly conserved. When present, the active cysteine was found 7 to 8 amino acids from the C-terminal end of HPN. The secondary structures were characterized by a canonical alpha/beta fold. Only family 10 deviated from the common organization because the proteins were devoid of enzymatic activity. Family 7 had an insertion between beta strands 1 and 2; families 3, 5 and 14 had an insertion between the active cysteine and the conserved tryptophan. The three-dimensional data of these proteins highlight a strong structural conservation of the core domain. Our analysis shows that the primitive eukaryote ancestor possessed a diversified set of E2 enzymes, thus emphasizing the importance of the Ub pathway. This comprehensive overview of E2 enzymes emphasizes the diversity and evolution of this superfamily and helps clarify the nomenclature and true orthologies. A better understanding of the functions of these enzymes is necessary to decipher several human diseases

Soil-Transmitted Helminth Reinfection after Drug Treatment: A Systematic Review and Meta-Analysis

Infections with soil-transmitted helminths (the roundworm Ascaris lumbricoides, the whipworm Trichuris trichiura, and hookworm) affect over 1 billion people, particularly rural communities in the developing world. The global strategy to control soil-transmitted helminth infections is ‘preventive chemotherapy’, which means large-scale administration of anthelmintic drugs to at-risk populations. However, because reinfection occurs after treatment, ‘preventive chemotherapy’ must be repeated regularly. Our systematic review and meta-analysis found that at 3, 6, and 12 months after treatment, A. lumbricoides prevalence reached 26% (95% confidence interval (CI): 16–43%), 68% (95% CI: 60–76%) and 94% (95% CI: 88–100%) of pretreatment levels, respectively. For T. trichiura, respective reinfection prevalence at these time points were 36% (95% CI: 28–47%), 67% (95% CI: 42–100%), and 82% (95% CI: 62–100%); and for hookworm, 30% (95% CI: 26–34%), 55% (95% CI: 34–87%), and 57% (95% CI: 49–67%). Prevalence and intensity of reinfection were positively correlated with pretreatment infection status. Our results suggest a frequent anthelmintic drug administration to maximize the benefit of preventive chemotherapy. Moreover, an integrated control strategy, consisting of preventive chemotherapy combined with health education and environmental sanitation is needed to interrupt transmission of soil-transmitted helminths

Accurate Inference of Subtle Population Structure (and Other Genetic Discontinuities) Using Principal Coordinates

Accurate inference of genetic discontinuities between populations is an essential component of intraspecific biodiversity and evolution studies, as well as associative genetics. The most widely-used methods to infer population structure are model-based, Bayesian MCMC procedures that minimize Hardy-Weinberg and linkage disequilibrium within subpopulations. These methods are useful, but suffer from large computational requirements and a dependence on modeling assumptions that may not be met in real data sets. Here we describe the development of a new approach, PCO-MC, which couples principal coordinate analysis to a clustering procedure for the inference of population structure from multilocus genotype data.PCO-MC uses data from all principal coordinate axes simultaneously to calculate a multidimensional "density landscape", from which the number of subpopulations, and the membership within subpopulations, is determined using a valley-seeking algorithm. Using extensive simulations, we show that this approach outperforms a Bayesian MCMC procedure when many loci (e.g. 100) are sampled, but that the Bayesian procedure is marginally superior with few loci (e.g. 10). When presented with sufficient data, PCO-MC accurately delineated subpopulations with population F(st) values as low as 0.03 (G'(st)>0.2), whereas the limit of resolution of the Bayesian approach was F(st) = 0.05 (G'(st)>0.35).We draw a distinction between population structure inference for describing biodiversity as opposed to Type I error control in associative genetics. We suggest that discrete assignments, like those produced by PCO-MC, are appropriate for circumscribing units of biodiversity whereas expression of population structure as a continuous variable is more useful for case-control correction in structured association studies

Additional file 2: of Monitoring the impact of a national school based deworming programme on soil-transmitted helminths in Kenya: the first three years, 2012 - 2014

In 2012, the Kenyan Ministries of Health and of Education began a programme to deworm all school-age children living in areas at high risk of soil-transmitted helminths (STH) and schistosome infections. The impact of this school-based mass drug administration (MDA) programme in Kenya is monitored by the Kenya Medical Research Institute (KEMRI) as part of a five-year (2012–2017) study. The study involved a series of pre- and post-intervention, repeat cross-sectional surveys in a representative, stratified, two-stage sample of schools across Kenya. The programme contained two tiers of monitoring; a national baseline and mid-term survey including 200 schools, and surveys conducted among 60 schools pre- and post-intervention. This dataset contains a School-level aggregate of individual-level STH infection and demographic information. Information on treatment coverage, as reported by the schools, was obtained from Evidence Action, an international non-governmental organization, which provides technical support to government programmes