MutDB services: interactive structural analysis of mutation data

Non-synonymous single nucleotide polymorphisms (SNPs) and mutations have been associated with human phenotypes and disease. As more and more SNPs are mapped to phenotypes, understanding how these variations affect the function and expression of genes and gene products becomes an important endeavor. We have developed a set of tools to aid in the understanding of how amino acid substitutions affect protein structures. To do this, we have annotated SNPs in dbSNP and amino acid substitutions in Swiss-Prot with protein structural information, if available. We then developed a novel web interface to this data that allows for visualization of the location of these substitutions. We have also developed a web service interface to the dataset and developed interactive plugins for UCSF's Chimera structural modeling tool and PyMOL that integrate our annotations with these sophisticated structural visualization and modeling tools. The web services portal and plugins can be downloaded from http://www.lifescienceweb.org/ and the web interface is at http://www.mutdb.org/

Indirect effects on fitness between individuals that have never met via an extended phenotype

Interactions between organisms are ubiquitous and have important consequences for phenotypes and fitness. Individuals can even influence those they never meet, if they have extended phenotypes that alter the environments others experience. North American red squirrels (Tamiasciurus hudsonicus) guard food hoards, an extended phenotype that typically outlives the individual and is usually subsequently acquired by non‐relatives. Hoarding by previous owners can, therefore, influence subsequent owners. We found that red squirrels breed earlier and had higher lifetime fitness if the previous hoard owner was a male. This was driven by hoarding behaviour, as males and mid‐aged squirrels had the largest hoards, and these effects persisted across owners, such that if the previous owner was male or died in mid‐age, subsequent occupants had larger hoards. Individuals can, therefore, influence each other’s resource‐dependent traits and fitness without ever meeting, such that the past can influence contemporary population dynamics through extended phenotypes.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148423/1/ele13230.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148423/2/ele13230_am.pd

Identification of multiple rare variants associated with a disease

Identifying rare variants that are responsible for complex disease has been promoted by advances in sequencing technologies. However, statistical methods that can handle the vast amount of data generated and that can interpret the complicated relationship between disease and these variants have lagged. We apply a zero-inflated Poisson regression model to take into account the excess of zeros caused by the extremely low frequency of the 24,487 exonic variants in the Genetic Analysis Workshop 17 data. We grouped the 697 subjects in the data set as Europeans, Asians, and Africans based on principal components analysis and found the total number of rare variants per gene for each individual. We then analyzed these collapsed variants based on the assumption that rare variants are enriched in a group of people affected by a disease compared to a group of unaffected people. We also tested the hypothesis with quantitative traits Q1, Q2, and Q4. Analyses performed on the combined 697 individuals and on each ethnic group yielded different results. For the combined population analysis, we found that UGT1A1, which was not part of the simulation model, was associated with disease liability and that FLT1, which was a causal locus in the simulation model, was associated with Q1. Of the causal loci in the simulation models, FLT1 and KDR were associated with Q1 and VNN1 was correlated with Q2. No significant genes were associated with Q4. These results show the feasibility and capability of our new statistical model to detect multiple rare variants influencing disease risk

Associative Learning Contributes to the Persistence of Fatigue-Like Behavior in Male Mice in a Model of Cancer Survivorship

Persistent fatigue is a debilitating side effect that impacts a significant proportion of cancer survivors for which there is not yet an FDA-approved treatment. While certainly a multi-factorial problem, persistent fatigue could be due, in part, to associations learned during treatment. Therefore, we sought to investigate the role of associative learning in the persistence of fatigue using a preclinical model of cancer survivorship. For this purpose, we used a murine model of human papilloma virus-related head and neck cancer paired with a curative regimen of cisplatin-based chemoradiation in male C57BL/6J mice. Fatigue-like behavior was assessed by measuring variations in voluntary wheel running using a longitudinal design. Treatment robustly decreased voluntary wheel running, and this effect persisted for more than a month posttreatment. However, when wheels were removed during treatment, to minimize treatment-related fatigue, mice showed a more rapid return to baseline running levels. We confirmed that the delayed recovery observed in mice with continual wheel access was not due to increased treatment-related toxicity, in fact running attenuated cisplatin-induced kidney toxicity. Finally, we demonstrated that re-exposure to a treatment-related olfactory cue acutely re-instated fatigue. These data provide the first demonstration that associative processes can modulate the persistence of cancer-related fatigue-like behavior

Sexually selected infanticide by male red squirrels in advance of a mast year

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143645/1/ecy2158-sup-0002-AppendixS2.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143645/2/ecy2158-sup-0001-AppendixS1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143645/3/ecy2158.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143645/4/ecy2158_am.pd

Long term impact of systemic bacterial infection on the cerebral vasculature and microglia

Background: Systemic infection leads to generation of inflammatory mediators that result in metabolic and behavioural changes. Repeated or chronic systemic inflammation leads to a state of innate immune tolerance: a protective mechanism against over-activity of the immune system. In this study we investigated the immune adaptation of microglia and brain vascular endothelial cells in response to systemic inflammation or bacterial infection. Methods: Mice were given repeated doses of lipopolysaccharide (LPS) or a single injection of live Salmonella typhimurium. Inflammatory cytokines were measured in serum, spleen and brain, and microglial phenotype studied by immunohistochemistry.mice were infected with Salmonella typhimurium and subsequently challenged with a focal unilateral, intracerebral injection of LPS. Results: Repeated systemic LPS challenges resulted in increased brain IL-1?, TNF? and IL-12 levels, despite attenuated systemic cytokine production. Each LPS challenge induced significant changes in burrowing behaviour. In contrast, brain IL-1? and IL-12 levels in Salmonella typhimurium infected mice increased over three weeks, with high interferon-? levels in the circulation. Behavioural changes were only observed during the acute phase of the infection. Microglia and cerebral vasculature display an activated phenotype, and focal intracerebral injection of LPS 4 weeks after infection results in an exaggerated local inflammatory response when compared to non-infected mice. Conclusions: These studies reveal that the innate immune cells in the brain do not become tolerant to systemic infection, but are primed instead. This may lead to prolonged and damaging cytokine production that may have aprofound effect on the onset and/ or progression of pre-existing neurodegenerative disease.Humans and animals are regularly exposed to bacterial and viral pathogens that can have a considerable impact on our day-to-day living [1]. Upon infection, a set of immune, physiological, metabolic, and behavioural responses is initiated, representing a highly organized strategy of the organism to fight infection. Pro-inflammatory mediators generated in peripheral tissue communicate with the brain to modify behaviour [2], which aids our ability to fight and eliminate the pathogen. The communication pathways from the site of inflammation to the brain have been investigated in animal models and systemic challenge with lipopolysaccharide (LPS) or double stranded RNA (poly I:C) have been widely used to mimic aspects of bacterial and viral infection respectively [3, 4]. These studies have provided evidence that systemically generated inflammatory mediators signal to the brain via both neural and humoral routes, the latter signalling via the circumventricular organs or across the blood-brain barrier (BBB). Signalling into the brain via these routes evokes a response in the perivascular macrophages (PVMs) and microglia, which in turn synthesise diverse inflammatory mediators including cytokines, prostaglandins and nitric oxide [2, 5, 6]. Immune-to-brain communication also occurs in humans who show changes in mood and cognition following systemic inflammation or infection, which are associated with changes in activity in particular regions of the CNS [7-9]. While these changes are part of our normal homeostasis, it is increasingly evident that systemic inflammation has a detrimental effect in animals and also humans, that suffer from chronic neurodegeneration [10, 11]. We, and others, have shown that microglia become primed by on-going neuropathology in the brain, which increases their response towards subsequent inflammatory stimuli, including systemic inflammation [12, 13] Similar findings have been made in aged rodents [14, 15], where it has been shown that there is an exaggerated behavioural and innate immune response in the brainto systemic bacterial and viral infections, but the molecular mechanisms underlying the microglial priming under these conditions is far from understood.Humans and animals are rarely exposed to a single acute systemic inflammatory event: they rather encounter infectious pathogens that replicate in vivo or are exposed to low concentrations of LPS over a prolonged period of time. There is limited information on the impact of non-neurotrophic bacterial infections on the CNS and whether prolonged systemic inflammation will give rise to either a hyper-(priming) or hypo-(tolerance) innate immune response in the brain in response to a subsequent inflammatory stimulus.In this study we measured the levels of cytokines in the serum, spleen and brain as well as assessing sickness behaviour following a systemic bacterial infection using attenuated Salmonella typhimurium SL3261: we compared the effect to that of repeated LPS injections. We show that Salmonella typhimurium caused acute, transient behavioural changes and a robust peripheral immune response that peaks at day 7. Systemic inflammation resulted in a delayed increase in cytokine production in the brain and priming of microglia, which persisted up to four weeks post infection. These effects were not mimicked by repeated LPS challenges. It is well recognised that systemic bacterial and viral infections are significant contributors to morbidity in the elderly [16], and it has been suggested that primed microglia play a role in the increased clinical symptoms seen in patients with Alzheimer’s disease who have systemic inflammation or infections [11, 17]. We show here that systemic infection leads to prolonged cytokine synthesis in the brain and also priming of brain innate immune cells to a subsequent focal inflammatory challenge in the brain parenchyma

Genetic Associations With Toxicity-related Discontinuation of Aromatase Inhibitor Therapy for Breast Cancer

Up to 25 % of patients discontinue adjuvant aromatase inhibitor (AI) therapy due to intolerable symptoms. Predictors of which patients will be unable to tolerate these medications have not been defined. We hypothesized that inherited variants in candidate genes are associated with treatment discontinuation because of AI-associated toxicity. We prospectively evaluated reasons for treatment discontinuation in women with hormone receptor-positive breast cancer initiating adjuvant AI through a multicenter, prospective, randomized clinical trial of exemestane versus letrozole. Using multiple genetic models, we evaluated potential associations between discontinuation of AI therapy because of toxicity and 138 variants in 24 candidate genes, selected a priori, primarily with roles in estrogen metabolism and signaling. To account for multiple comparisons, statistical significance was defined as p < 0.00036. Of the 467 enrolled patients with available germline DNA, 152 (33 %) discontinued AI therapy because of toxicity. Using a recessive statistical model, an intronic variant in ESR1 (rs9322336) was associated with increased risk of musculoskeletal toxicity-related exemestane discontinuation [HR 5.0 (95 % CI 2.1-11.8), p < 0.0002]. An inherited variant potentially affecting estrogen signaling may be associated with exemestane-associated toxicity, which could partially account for intra-patient differences in AI tolerability. Validation of this finding is required

MASTREE+: Time-series of plant reproductive effort from six continents.

Significant gaps remain in understanding the response of plant reproduction to environmental change. This is partly because measuring reproduction in long-lived plants requires direct observation over many years and such datasets have rarely been made publicly available. Here we introduce MASTREE+, a data set that collates reproductive time-series data from across the globe and makes these data freely available to the community. MASTREE+ includes 73,828 georeferenced observations of annual reproduction (e.g. seed and fruit counts) in perennial plant populations worldwide. These observations consist of 5971 population-level time-series from 974 species in 66 countries. The mean and median time-series length is 12.4 and 10 years respectively, and the data set includes 1122 series that extend over at least two decades (≥20 years of observations). For a subset of well-studied species, MASTREE+ includes extensive replication of time-series across geographical and climatic gradients. Here we describe the open-access data set, available as a.csv file, and we introduce an associated web-based app for data exploration. MASTREE+ will provide the basis for improved understanding of the response of long-lived plant reproduction to environmental change. Additionally, MASTREE+ will enable investigation of the ecology and evolution of reproductive strategies in perennial plants, and the role of plant reproduction as a driver of ecosystem dynamics