Modeling of host genetics and resistance to infectious diseases: understanding and controlling nematode infections

This paper considers approaches to modeling the dynamics of infectious disease and the application of such models to nematode parasite infections in ruminants. Particularly, these models are developed to account for host genetics and may be used to assess the effects of using genetics to control nematode infections. Three main issues are critically examined: the infection transmission cycle from pasture to host to pasture, the expected genetic relationships between resistance and performance, and the risks of parasite evolution in response to genetic changes in the host. To obtain answers that are realistic and of practical use, the modeling approaches require a solid grounding in biology. This biology is formalized and described using mathematical techniques, with the models parameterized using experimental or field data. Transmission dynamics have been quantified by modeling and are backed by strong experimental data. Selection for resistance will be successful in reducing egg output, pasture larval contamination and hence subsequent larval challenge. Modeling frameworks have been developed to predict genetic relationships between resistance to infectious disease and performance in general, and genetic correlations predicted for nematode resistance are close to mean published values. These predicted correlations strengthen as the larval challenge increases and the dietary (protein) adequacy decreases, however modeling challenges remain. Lastly, although convincing experimental data is not yet available, arguments based on modeling suggest that the risks of parasite evolution in response to genetic changes in the host should be less than the risks arising from other control strategies, such as anthelmintics. Thus, modeling techniques predict that selective breeding for resistance should be an effective and sustainable complementary control measure.     

The association between plasma levels of acute phase proteins, haptoglobin, alpha-1 acid glycoprotein (AGP), pig-MAP, transthyretin and serum amyloid A (SAA) in Large White and Meishan pigs

During infection, the acute phase response triggers the release of acute phase proteins (APP), alpha-(1) acid glycoprotein (AGP), serum amyloid A (SAA) and Pig-MAP into the circulation, accompanied by a decrease in plasma levels of transthyretin. We quantified the association between these APP in 26 apparently healthy pigs from two breeds, 13 Large White and 13 Meishan (16 male; 10 female). There was a significant correlation between plasma levels of haptoglobin and Pig-MAP (r=0.57; p<0.05), but no significant associations between any of the other APP tested. We also measured the relationship between PigMAP, transthyretin and SAA, and the proportions of peripheral blood mononuclear sub-sets, CD8(+) cells, CD4(+) cells, CD11R1(+) cells, MHC DQ(+) cells, and monocytes. There were correlations between both plasma levels of Pig-MAP and the proportion of monocytes (r=0.55; p<0.05) and plasma levels of transthyretin and the proportion of MHC DQ(+) cells (r=0.40; p<0.01). Breed and sex influenced plasma levels of Pig-MAP but not plasma levels of transthyretin. Overall, these results suggest closer links between the mechanisms that regulate the release haptoglobin, Pig-MAP and monocytes compared to those that regulate the release of AGP, SAA and transthyretin.     

Recovery of photosynthetic capacity in Scots pine: a model analysis of forest plots with contrasting soil temperature

Both aboveground and belowground climate affects net primary production (NNP) and forest growth. Little is known about how above and belowground factors interact. The BIOMASS-model was tested to simulate photosynthetic recovery over a wide range of soil temperatures created by snow cover manipulations on tree-scale plots in a 20-year-old Scots pine stand in northern Sweden. The differences in timing of soil warming between the plots covered a span of two months. Carbon assimilation in needles, sap flow, needle water potential and climatic parameters were measured in the field. The simulations revealed that an early start of soil warming gave a relatively early photosynthetic recovery and a 7.5% increase of NPP. Late soil warming delayed the photosynthetic recovery and reduced the NPP by 13.7%. This indicated that soil temperature needed to be accounted for, as well as air temperature, when analysing photosynthetic recovery and NPP in boreal environment. The effects of differences in soil temperature were reflected in the simulated photosynthetic recovery. The model did not fully capture the delay of photosynthetic recovery caused by a late soil warming. It was possible to integrate the complexity of the soil climate effects into a threshold date for soil thaw, using sapflow measurements together with information about air temperature and a day degree sum, as long as water availability was not limiting water uptake by roots. Although a more realistic mechanism than that currently in BIOMASS is desirable as climate change shifts the typical patterns of interplay between air and soil temperature dynamics.     

Antiproliferative activity of Saponaria vaccaria constituents and related compounds

Total methanolic extracts of Saponaria vaccaria seed derived from several varieties, as well as various purified components obtained through successive chromatographic separations of total extracts were evaluated for their growth inhibitory activity in WiDr (colon), MDA-MB-231 (breast), NCI-417 (lung) and PC-3 (prostate) human cancer cells as well as the non-tumorigenic fibroblast BJ (CRL-2522) cell line using MTT colorimetric assay. Purified bisdesmosidic saponins segetoside H and I were further examined using microscopy and apoptosis assays. Bisdesmosidic saponins exhibited dose-dependent growth inhibitory and selective apoptosis-inducing activity. Growth inhibitory effects were particularly strong in a breast (MDA-MB-231) and a prostate (PC-3) cancer cell line. Total extracts exhibited a different preference being most active against a colon cancer cell line (WiDr). In a comparison of varieties, all of the total seed extracts exhibited similar dose-dependent activities, but with some variation in potency. Monodesmosidic saponins vaccarosides A and B, phenolic vaccarin, and cyclopeptide segetalin A, co-occurring seed substituents, did not exhibit activity. The non-tumorigenic fibroblast cell line BJ (CRL 2522) was growth inhibited but did not undergo apoptosis when treated with bisdesmosidic saponins at low micromolar concentrations. Saponin-rich extracts from Kochia scoparia seed and Chenopodium quinoa were also evaluated alongside Saponaria saponins but did not exhibit activity. Closely related Quillaja saponins exhibited activity but were less potent.     

Cokriging particle size fractions of the soil

It is often necessary to predict the distribution of mineral particles in soil between size fractions, given observations at sample sites. Because the contents in each fraction necessarily sum to 100%, these values constitute a composition, which we may assume is drawn from a random compositional variate. Elements of a D‐component composition are subject to non‐stochastic constraints; they are constrained to lie on a D– 1 dimensional simplex. This means we cannot treat them as realizations of unbounded random variables such as the multivariate Gaussian. For this reason, there are theoretical reasons not to use ordinary cokriging (or ordinary kriging) to map particle size distributions. Despite this, the compositional constraints on data on particle size fractions are not always accounted for by soil scientists. The additive log‐ratio (alr) transform can be used to transform data from a compositional variate into a form that can be treated as a realization of an unbounded random variable. Until now, while soil scientists have made use of the alr transform for the spatial prediction of particle size, there has been concern that the simple back‐transform of the optimal estimate of the alr‐transformed variables does not yield the optimal estimate of the composition. A numerical approximation to the conditional expectation of the composition has been proposed, but we are not aware of examples of its application and it has not been used in soil science. In this paper, we report two case studies in which we predicted clay, silt and sand contents of the soil at test sites by ordinary cokriging of the alr‐transformed data followed by both the direct (biased) back‐transform of the estimates and the unbiased back‐transform. We also computed estimates by ordinary cokriging of the untransformed data (which ignores the compositional constraints on the variables) for comparison. In one of our case studies, the benefit of using the alr transform was apparent, although there was no consistent advantage in using the unbiased back‐transform. In the other case study, there was no consistent advantage in using the alr transform, although the bias of the simple back‐transform was apparent. The differences between these case studies could be explained with respect to the distribution on the simplex of the particle size fractions at the two sites.     

Reduced effective population size in an overexploited population of the Nile crocodile (Crocodylus niloticus)

Unchecked exploitation of wildlife resources is one of the major factors influencing species persistence throughout the world today. A significant consequence of exploitation is the increasing rate at which genetic diversity is lost as populations decline. Recent studies suggest that life history traits affecting population growth, particularly in long-lived species, may act to moderate the impact of population decline on genetic variation and lead to remnant populations that appear genetically diverse despite having passed through substantial demographic bottlenecks. In this study we show that the retention of genetic variation in a partially recovered population of Nile crocodile is deceptive, as it masks the reality of a significant decline in the population’s effective size (N_e). Repeated episodes of unchecked hunting in the mid to late 20th century have today led to a five-fold decrease in the population’s N_e. Using current census data we estimate the contemporary N_e/N ratio as 0.05 and, in light of quotas that permit the ongoing removal of adults, simulated the likely effects of genetic drift on extant levels of variation. Results indicate that even if the current effective size is maintained, both allelic diversity and heterozygosity will decline. Our findings have complex implications for long-lived species; an emphasis on the retention of genetic variation alone, whilst disregarding the effects of population decline on effective size, may ultimately obscure the continued decline and extinction of exploited populations.