Spatially explicit predictions of blood parasites in a widely distributed African rainforest bird

Critical to the mitigation of parasitic vector-borne diseases is the development of accurate spatial predictions that integrate environmental conditions conducive to pathogen proliferation. Species of Plasmodium and Trypanosoma readily infect humans, and are also common in birds. Here, we develop predictive spatial models for the prevalence of these blood parasites in the olive sunbird (Cyanomitra olivacea). Since this species exhibits high natural parasite prevalence and occupies diverse habitats in tropical Africa, it represents a distinctive ecological model system for studying vector-borne pathogens. We used PCR and microscopy to screen for haematozoa from 28 sites in Central and West Africa. Species distribution models were constructed to associate ground-based and remotely sensed environmental variables with parasite presence. We then used machine-learning algorithm models to identify relationships between parasite prevalence and environmental predictors. Finally, predictive maps were generated by projecting model outputs to geographically unsampled areas. Results indicate that for Plasmodium spp., the maximum temperature of the warmest month was most important in predicting prevalence. For Trypanosoma spp., seasonal canopy moisture variability was the most important predictor. The models presented here visualize gradients of disease prevalence, identify pathogen hotspots and will be instrumental in studying the effects of ecological change on these and other pathogens.     

Zea ribosomal repeat evolution and substitution patterns

Zea and Tripsacum nuclear ribosomal internal transcribed spacer (ITS) sequences were used to evaluate patterns of concerted evolution, rates of substitutions, patterns of methylation-induced deamination, and structural constraints of the ITS. ITS pseudogenes were identified by their phylogenetic position, differences in nucleotide composition, extensive deamination at ancestral methylation sites, and substitutions resulting in low-stability secondary RNA structures. Selection was important in shaping the kinds of polymorphisms and substitutions observed in the ITS. ITS substitution rates were significantly different among the Zea taxa. Deamination of cytosines at methylation sites was a potent mutation source, but selection appeared to maintain high methylation site density throughout the ribosomal repeat except for the gene promoter. Nucleotide divergence statistics identified selectively constrained regions at the 5' ends of the ITS1 and ITS2.      

Uncommon pathways of immune escape attenuate HIV-1 integrase replication capacity

An attenuation of the HIV-1 replication capacity (RC) has been observed for immune-mediated escape mutations in Gag restricted by protective HLA alleles. However, the extent to which escape mutations affect other viral proteins during natural infection is not well understood. We generated recombinant viruses encoding plasma HIV-1 RNA integrase sequences from antiretroviral-naïve individuals with early (n = 88) and chronic (n = 304) infections and measured the in vitro RC of each. In contrast to data from previous studies of Gag, we observed little evidence that host HLA allele expression was associated with integrase RC. A modest negative correlation was observed between the number of HLA-B-associated integrase polymorphisms and RC in chronic infection (R = −0.2; P = 0.003); however, this effect was not driven by mutations restricted by protective HLA alleles. Notably, the integrase variants S119R, G163E, and I220L, which represent uncommon polymorphisms associated with HLA-C*05, -A*33, and -B*52, respectively, correlated with lower RC (all q < 0.2). We identified a novel C*05-restricted epitope (HTDNGSNF_114–121) that likely contributes to the selection of the S119R variant, the polymorphism most significantly associated with lower RC in patient sequences. An NL4-3 mutant encoding the S119R polymorphism displayed a ∼35%-reduced function that was rescued by a single compensatory mutation of A91E. Together, these data indicate that substantial HLA-driven attenuation of integrase is not a general phenomenon during HIV-1 adaptation to host immunity. However, uncommon polymorphisms selected by HLA alleles that are not conventionally regarded to be protective may be associated with impaired protein function. Vulnerable epitopes in integrase might therefore be considered for future vaccine strategies.     

The Werner syndrome protein operates in base excision repair and cooperates with DNA polymerase beta

Genome instability is a characteristic of cancer and aging, and is a hallmark of the premature aging disorder Werner syndrome (WS). Evidence suggests that the Werner syndrome protein (WRN) contributes to the maintenance of genome integrity through its involvement in DNA repair. In particular, biochemical evidence indicates a role for WRN in base excision repair (BER). We have previously reported that WRN helicase activity stimulates DNA polymerase beta (pol β) strand displacement synthesis in vitro. In this report we demonstrate that WRN exonuclease activity can act cooperatively with pol β, a polymerase lacking 3′–5′ proofreading activity. Furthermore, using small interference RNA technology, we demonstrate that WRN knockdown cells are hypersensitive to the alkylating agent methyl methanesulfonate, which creates DNA damage that is primarily repaired by the BER pathway. In addition, repair assays using whole cell extracts from WRN knockdown cells indicate a defect in long patch (LP) BER. These findings demonstrate that WRN plays a direct role in the repair of methylation-induced DNA damage, and suggest a role for both WRN helicase and exonuclease activities together with pol β during LP BER.     

Predicting alpha diversity of African rain forests: models based on climate and satellite‐derived data do not perform better than a purely spatial model

Aim Our aim was to evaluate the extent to which we can predict and map tree alpha diversity across broad spatial scales either by using climate and remote sensing data or by exploiting spatial autocorrelation patterns. Location Tropical rain forest, West Africa and Atlantic Central Africa. Methods Alpha diversity estimates were compiled for trees with diameter at breast height ≥ 10 cm in 573 inventory plots. Linear regression (ordinary least squares, OLS) and random forest (RF) statistical techniques were used to project alpha diversity estimates at unsampled locations using climate data and remote sensing data [Moderate Resolution Imaging Spectroradiometer (MODIS), normalized difference vegetation index (NDVI), Quick Scatterometer (QSCAT), tree cover, elevation]. The prediction reliabilities of OLS and RF models were evaluated using a novel approach and compared to that of a kriging model based on geographic location alone. Results The predictive power of the kriging model was comparable to that of OLS and RF models based on climatic and remote sensing data. The three models provided congruent predictions of alpha diversity in well‐sampled areas but not in poorly inventoried locations. The reliability of the predictions of all three models declined markedly with distance from points with inventory data, becoming very low at distances > 50 km. According to inventory data, Atlantic Central African forests display a higher mean alpha diversity than do West African forests. Main conclusions The lower tree alpha diversity in West Africa than in Atlantic Central Africa may reflect a richer regional species pool in the latter. Our results emphasize and illustrate the need to test model predictions in a spatially explicit manner. Good OLS or RF model predictions from inventory data at short distance largely result from the strong spatial autocorrelation displayed by both the alpha diversity and the predictive variables rather than necessarily from causal relationships. Our results suggest that alpha diversity is driven by history rather than by the contemporary environment. Given the low predictive power of models, we call for a major effort to broaden the geographical extent and intensity of forest assessments to expand our knowledge of African rain forest diversity.     

Stacking transgenic event DAS‐Ø15Ø7‐1 alters maize composition less than traditional breeding

The impact of crossing (‘stacking’) genetically modified (GM) events on maize‐grain biochemical composition was compared with the impact of generating nonGM hybrids. The compositional similarity of seven GM stacks containing event DAS‐Ø15Ø7‐1, and their matched nonGM near‐isogenic hybrids (iso‐hybrids) was compared with the compositional similarity of concurrently grown nonGM hybrids and these same iso‐hybrids. Scatter plots were used to visualize comparisons among hybrids and a coefficient of identity (per cent of variation explained by line of identity) was calculated to quantify the relationships within analyte profiles. The composition of GM breeding stacks was more similar to the composition of iso‐hybrids than was the composition of nonGM hybrids. NonGM breeding more strongly influenced crop composition than did transgenesis or stacking of GM events. These findings call into question the value of uniquely requiring composition studies for GM crops, especially for breeding stacks composed of GM events previously found to be compositionally normal.