Validated predictive modelling of the environmental resistome

Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome.     

Parental Age Affects Somatic Mutation Rates in the Progeny of Flowering Plants

In humans, it is well known that the parental reproductive age has a strong influence on mutations transmitted to their progeny. Meiotic nondisjunction is known to increase in older mothers, and base substitutions tend to go up with paternal reproductive age. Hence, it is clear that the germinal mutation rates are a function of both maternal and paternal ages in humans. In contrast, it is unknown whether the parental reproductive age has an effect on somatic mutation rates in the progeny, because these are rare and difficult to detect. To address this question, we took advantage of the plant model system Arabidopsis (Arabidopsis thaliana), where mutation detector lines allow for an easy quantitation of somatic mutations, to test the effect of parental age on somatic mutation rates in the progeny. Although we found no significant effect of parental age on base substitutions, we found that frameshift mutations and transposition events increased in the progeny of older parents, an effect that is stronger through the maternal line. In contrast, intrachromosomal recombination events in the progeny decrease with the age of the parents in a parent-of-origin-dependent manner. Our results clearly show that parental reproductive age affects somatic mutation rates in the progeny and, thus, that some form of age-dependent information, which affects the frequency of double-strand breaks and possibly other processes involved in maintaining genome integrity, is transmitted through the gametes.In humans, it has long been recognized that the reproductive age of the parents has an influence on the health of their progeny. An older reproductive age of the mother is known to increase the fraction of aneuploid gamete formation (Hurles, 2012). For instance, the risk for a trisomy increases from 2% to 3% for mothers in their 20s to more than 30% for mothers in their 40s (Hassold and Hunt, 2009). The age of the father also has an effect on the frequency of spontaneous congenital disorders and common complex diseases, such as autism and some cancers (Goriely and Wilkie, 2012). Indeed, sperm from 36- to 57-year-old men have more double-strand breaks (DSBs) than those of 20- to 35-year-old individuals (Singh et al., 2003). Similarly, the efficiency of DSB repair was reported to decrease with age in vegetative tissues of the plant model system Arabidopsis (Arabidopsis thaliana; Boyko et al., 2006).Owing to the continuous divisions of spermatogonial stem cells, the male germline of humans is thought to be more mutagenic than the female germline. Indeed, it was shown that the paternal germline is more mutagenic than the maternal one with respect to base substitutions (Kong et al., 2012) and replication slippage errors at microsatellites (Sun et al., 2012). It is also known that carriers of germline mutations in mismatch repair (MMR) genes in humans are prone to get colorectal cancer and that the risk depends on the parent-of-origin of the mutation (van Vliet et al., 2011). The molecular basis of these parental effects is not entirely clear but is likely to involve higher rates of nondisjunction during female meiosis, higher mutation rates during spermatogenesis, and probably additional effects of aging.In contrast to the effect of parental age on germline mutations, not much is known about potential effects of parental reproductive age on somatic mutation rates in the offspring. However, it has been shown in animal studies that radiation of males can lead to somatic mutations in their progeny—and subsequent generations—that cannot be attributed to mutations in the paternal germline (for review, see Little et al., 2013). Moreover, several recent studies have illustrated the existence of complex parental and transgenerational effects in humans, although their molecular basis is not clear (Grossniklaus et al., 2013). These effects can be of either genetic nature (but the effect is seen even in offspring that did not inherit the genetic variant from their parents; for review, see Nadeau, 2009) or epigenetic nature (where environmental influences can possibly exert effects on subsequent generations; for review, see Pembrey et al., 2006; Pembrey, 2010; Curley et al., 2011). It is currently not known whether such parental effects affect the somatic mutation rates in the offspring or whether the effects are modulated by parental age.Taking advantage of the plant model system Arabidopsis, in which various somatic mutation rates can readily be assessed (Bashir et al., 2014), we investigated the effects of parental reproductive age on somatic mutation rates in the progeny. We report that there is a pronounced effect of parental age on somatic mutation rates in their offspring in a parent-of-origin-dependent fashion. Thus, some form of parental information, which is inherited through the gametes to the next generation, seems to alter the somatic mutation rates in the progeny and changes with parental reproductive age.     

Relationship of aerobic and anaerobic parameters with 400 m front crawl swimming performance

The aims of the present study were to investigate the relationship of aerobic and anaerobic parameters with 400 m performance, and establish which variable better explains long distance performance in swimming. Twenty-two swimmers (19.1±1.5 years, height 173.9±10.0 cm, body mass 71.2±10.2 kg; 76.6±5.3% of 400 m world record) underwent a lactate minimum test to determine lactate minimum speed (LMS) (i.e., aerobic capacity index). Moreover, the swimmers performed a 400 m maximal effort to determine mean speed (S400m), peak oxygen uptake (V.O2PEAK) and total anaerobic contribution (C_ANA). The C_ANA was assumed as the sum of alactic and lactic contributions. Physiological parameters of 400 m were determined using the backward extrapolation technique (V.O2PEAK and alactic contributions of C_ANA) and blood lactate concentration analysis (lactic anaerobic contributions of C_ANA). The Pearson correlation test and backward multiple regression analysis were used to verify the possible correlations between the physiological indices (predictor factors) and S400m (independent variable) (p < 0.05). Values are presented as mean ± standard deviation. Significant correlations were observed between S400m (1.4±0.1 m·s^-1) and LMS (1.3±0.1 m·s^-1; r = 0.80), V.O2PEAK (4.5±3.9 L·min^-1; r = 0.72) and C_ANA (4.7±1.5 L·O₂; r= 0.44). The best model constructed using multiple regression analysis demonstrated that LMS and V.O2PEAK explained 85% of the 400 m performance variance. When backward multiple regression analysis was performed, C_ANA lost significance. Thus, the results demonstrated that both aerobic parameters (capacity and power) can be used to predict 400 m swimming performance.     

Genetic Variation in Healthy Oldest-Old

Individuals who live to 85 and beyond without developing major age-related diseases may achieve this, in part, by lacking disease susceptibility factors, or by possessing resistance factors that enhance their ability to avoid disease and prolong lifespan. Healthy aging is a complex phenotype likely to be affected by both genetic and environmental factors. We sequenced 24 candidate healthy aging genes in DNA samples from 47 healthy individuals aged eighty-five years or older (the ‘oldest-old’), to characterize genetic variation that is present in this exceptional group. These healthy seniors were never diagnosed with cancer, cardiovascular disease, pulmonary disease, diabetes, or Alzheimer disease. We re-sequenced all exons, intron-exon boundaries and selected conserved non-coding sequences of candidate genes involved in aging-related processes, including dietary restriction (PPARG, PPARGC1A, SIRT1, SIRT3, UCP2, UCP3), metabolism (IGF1R, APOB, SCD), autophagy (BECN1, FRAP1), stem cell activation (NOTCH1, DLL1), tumor suppression (TP53, CDKN2A, ING1), DNA methylation (TRDMT1, DNMT3A, DNMT3B) Progeria syndromes (LMNA, ZMPSTE24, KL) and stress response (CRYAB, HSPB2). We detected 935 variants, including 848 single nucleotide polymorphisms (SNPs) and 87 insertion or deletions; 41% (385) were not recorded in dbSNP. This study is the first to present a comprehensive analysis of genetic variation in aging-related candidate genes in healthy oldest-old. These variants and especially our novel polymorphisms are valuable resources to test for genetic association in models of disease susceptibility or resistance. In addition, we propose an innovative tagSNP selection strategy that combines variants identified through gene re-sequencing- and HapMap-derived SNPs.     

心脏特异表达LMNA^E82K转基因小鼠的建立

目的建立心脏特异表达LMNAE82K转基因小鼠,为研究LMNAE82K与心肌病发病机制的关系提供工具动物。方法把LMNAE82K基因插入α-MHC启动子下游,构建转基因表达载体,显微注射法建立C57BL/6JLMNAE82K转基因小鼠,PCR鉴定转基因小鼠的基因型,采用Western Blot鉴定LMNAE82K在心脏组织中的表达,H＆E染色和超声检测转基因小鼠心脏的病理改变。结果建立了2个心脏组织特异表达LMNAE82K的转基因小鼠品系。超声检查显示转基因小鼠心室壁变薄,收缩期容积和舒张期容积增加,射血分数及短轴缩短率降低。结论LMNAE82K转基因小鼠具有LMNAE82K引起的家族性扩心病有类似的病理变化,为研究LMNAE82K与心肌病发病机制的关系的研究提供了有价值的疾病动物模型。     

东亚飞蝗hunchback基因在卵子形成和胚胎发育过程中的原位表达

hb（hunchback）基因是昆虫胚胎前后轴模式形成的关键基因．对东亚飞蝗（Locusta migratoria manilensis,Meyen）hb基因的功能已有报道,但其表达模式还不清楚．为了研究胁基因在东亚飞蝗卵子形成和胚胎发育过程中的时空表达情况,本研究采用免疫组化方法在蛋白质水平上检测了hb基因的时空表达模式．在卵子形成过程中,hb基因局限在卵细胞核区中表达,随着卵子的发育逐渐移至卵细胞的后端;卵受精后,核区里的Hb蛋白向外扩散,在卵后端形成浓度梯度;胚盘期,hb基因在胚盘中央呈带状表达;胚盘分化为原头和原躯干后,表达条带变宽,并呈现出梯度表达,该表达区域将形成颌、胸部的部分体节;随着腹节开始形成,hb基因在颌胸部的表达逐渐减弱,而在腹部后端的“生长区”表达,并呈现出不连续性．经比较,hb易基因在昆虫颌胸部的表达较为保守,而在卵子形成过程中和腹部的表达具有较大的变异性．与黑腹果蝇等长胚带昆虫相比,东亚飞蝗hb基因在体节形成的基因级联调控中具有更重要、更直接的调控作用．     

Global transcriptional response of pig brain and lung to natural infection by Pseudorabies virus

Background  

Pseudorabies virus (PRV) is an alphaherpesviruses whose native host is pig. PRV infection mainly causes signs of central nervous system disorder in young pigs, and respiratory system diseases in the adult.     

Ant versus bird exclusion effects on the arthropod assemblage of an organic citrus grove

1. Predation‐exclusion experiments have highlighted that top‐down control is pervasive in terrestrial communities, but most of these experiments are simplistic in that they only excluded a single group of predators and the effect of removal was evaluated on a few species from the community. The main goal of our study was to experimentally establish the relative effects of ants and birds on the same arthropod assemblage of canopy trees. 2. We conducted 1‐year long manipulative experiments in an organic citrus grove intended to quantify the independent effects of bird and ant predators on the abundance of arthropods. Birds were excluded with plastic nets whereas ants were excluded with sticky barriers on the trunks. The sticky barrier also excluded other ground dwelling insects, like the European earwig Forficula auricularia L. 3. Both the exclusion of ants and birds affected the arthropod community of the citrus canopies, but the exclusion of ants was far more important than the exclusion of birds. Indeed, almost all groups of arthropods had higher abundance in ant‐excluded than in control trees, whereas only dermapterans were more abundant in bird‐excluded than in control trees. A more detailed analysis conducted on spiders also showed that the effect of ant exclusion was limited to a few families rather than being widespread over the entire diverse spectrum of spiders. 4. Our results suggest that the relative importance of vertebrate and invertebrate predators in regulating arthropod populations largely depends on the nature of the predator–prey system.