Production of a Dominant-Negative Fragment Due to G3BP1 Cleavage Contributes to the Disruption of Mitochondria-Associated Protective Stress Granules during CVB3 Infection

Stress granules (SGs) are dynamic cytosolic aggregates containing messenger ribonucleoproteins and target poly-adenylated (A)-mRNA. A key component of SGs is Ras-GAP SH3 domain binding protein-1 (G3BP1), which in part mediates protein-protein and protein-RNA interactions. SGs are modulated during infection by several viruses, however, the function and significance of this process remains poorly understood. In this study, we investigated the interplay between SGs and Coxsackievirus type B3 (CVB3), a member of the Picornaviridae family. Our studies demonstrated that SGs were formed early during CVB3 infection; however, G3BP1-positive SGs were actively disassembled at 5 hrs post-infection, while poly(A)-positive RNA granules persisted. Furthermore, we confirmed G3BP1 cleavage by 3C^pro at Q325. We also demonstrated that overexpression of G3BP1-SGs negatively impacted viral replication at the RNA, protein, and viral progeny levels. Using electron microscopy techniques, we showed that G3BP1-positive SGs localized near mitochondrial surfaces. Finally, we provided evidence that the C-terminal cleavage product of G3BP1 inhibited SG formation and promoted CVB3 replication. Taken together, we conclude that CVB3 infection selectively targets G3BP1-SGs by cleaving G3BP1 to produce a dominant-negative fragment that further inhibits G3BP1-SG formation and facilitates viral replication.     

PUMA: A Unified Framework for Penalized Multiple Regression Analysis of GWAS Data

Penalized Multiple Regression (PMR) can be used to discover novel disease associations in GWAS datasets. In practice, proposed PMR methods have not been able to identify well-supported associations in GWAS that are undetectable by standard association tests and thus these methods are not widely applied. Here, we present a combined algorithmic and heuristic framework for PUMA (Penalized Unified Multiple-locus Association) analysis that solves the problems of previously proposed methods including computational speed, poor performance on genome-scale simulated data, and identification of too many associations for real data to be biologically plausible. The framework includes a new minorize-maximization (MM) algorithm for generalized linear models (GLM) combined with heuristic model selection and testing methods for identification of robust associations. The PUMA framework implements the penalized maximum likelihood penalties previously proposed for GWAS analysis (i.e. Lasso, Adaptive Lasso, NEG, MCP), as well as a penalty that has not been previously applied to GWAS (i.e. LOG). Using simulations that closely mirror real GWAS data, we show that our framework has high performance and reliably increases power to detect weak associations, while existing PMR methods can perform worse than single marker testing in overall performance. To demonstrate the empirical value of PUMA, we analyzed GWAS data for type 1 diabetes, Crohns''s disease, and rheumatoid arthritis, three autoimmune diseases from the original Wellcome Trust Case Control Consortium. Our analysis replicates known associations for these diseases and we discover novel etiologically relevant susceptibility loci that are invisible to standard single marker tests, including six novel associations implicating genes involved in pancreatic function, insulin pathways and immune-cell function in type 1 diabetes; three novel associations implicating genes in pro- and anti-inflammatory pathways in Crohn''s disease; and one novel association implicating a gene involved in apoptosis pathways in rheumatoid arthritis. We provide software for applying our PUMA analysis framework.     

Novel Methods for Analysing Bacterial Tracks Reveal Persistence in Rhodobacter sphaeroides

Tracking bacteria using video microscopy is a powerful experimental approach to probe their motile behaviour. The trajectories obtained contain much information relating to the complex patterns of bacterial motility. However, methods for the quantitative analysis of such data are limited. Most swimming bacteria move in approximately straight lines, interspersed with random reorientation phases. It is therefore necessary to segment observed tracks into swimming and reorientation phases to extract useful statistics. We present novel robust analysis tools to discern these two phases in tracks. Our methods comprise a simple and effective protocol for removing spurious tracks from tracking datasets, followed by analysis based on a two-state hidden Markov model, taking advantage of the availability of mutant strains that exhibit swimming-only or reorientating-only motion to generate an empirical prior distribution. Using simulated tracks with varying levels of added noise, we validate our methods and compare them with an existing heuristic method. To our knowledge this is the first example of a systematic assessment of analysis methods in this field. The new methods are substantially more robust to noise and introduce less systematic bias than the heuristic method. We apply our methods to tracks obtained from the bacterial species Rhodobacter sphaeroides and Escherichia coli. Our results demonstrate that R. sphaeroides exhibits persistence over the course of a tumbling event, which is a novel result with important implications in the study of this and similar species.     

Reconstructing Native American Migrations from Whole-Genome and Whole-Exome Data

There is great scientific and popular interest in understanding the genetic history of populations in the Americas. We wish to understand when different regions of the continent were inhabited, where settlers came from, and how current inhabitants relate genetically to earlier populations. Recent studies unraveled parts of the genetic history of the continent using genotyping arrays and uniparental markers. The 1000 Genomes Project provides a unique opportunity for improving our understanding of population genetic history by providing over a hundred sequenced low coverage genomes and exomes from Colombian (CLM), Mexican-American (MXL), and Puerto Rican (PUR) populations. Here, we explore the genomic contributions of African, European, and especially Native American ancestry to these populations. Estimated Native American ancestry is in MXL, in CLM, and in PUR. Native American ancestry in PUR is most closely related to populations surrounding the Orinoco River basin, confirming the Southern America ancestry of the Taíno people of the Caribbean. We present new methods to estimate the allele frequencies in the Native American fraction of the populations, and model their distribution using a demographic model for three ancestral Native American populations. These ancestral populations likely split in close succession: the most likely scenario, based on a peopling of the Americas thousand years ago (kya), supports that the MXL Ancestors split kya, with a subsequent split of the ancestors to CLM and PUR kya. The model also features effective populations of in Mexico, in Colombia, and in Puerto Rico. Modeling Identity-by-descent (IBD) and ancestry tract length, we show that post-contact populations also differ markedly in their effective sizes and migration patterns, with Puerto Rico showing the smallest effective size and the earlier migration from Europe. Finally, we compare IBD and ancestry assignments to find evidence for relatedness among European founders to the three populations.     

Treadmill desks: A 1‐year prospective trial

Objective: Sedentariness is associated with weight gain and obesity. A treadmill desk is the combination of a standing desk and a treadmill that allow employees to work while walking at low speed. Design and Methods: The hypothesis was that a 1‐year intervention with treadmill desks is associated with an increase in employee daily physical activity (summation of all activity per minute) and a decrease in daily sedentary time (zero activity). Employees (n = 36; 25 women, 11 men) with sedentary jobs (87 ± 27 kg, BMI 29 ± 7 kg/m², n = 10 Lean BMI < 25 kg/m², n = 15 Overweight 25 < BMI < 30 kg/m², n = 11 Obese BMI > 30 kg/m²) volunteered to have their traditional desk replaced with a treadmill desk to promote physical activity for 1 year. Results: Daily physical activity (using accelerometers), work performance, body composition, and blood variables were measured at Baseline and 6 and 12 months after the treadmill desk intervention. Subjects who used the treadmill desk increased daily physical activity from baseline 3,353 ± 1,802 activity units (AU)/day to, at 6 months, 4,460 ± 2,376 AU/day (P < 0.001), and at 12 months, 4,205 ± 2,238 AU/day (P < 0.001). Access to the treadmill desks was associated with significant decreases in daily sedentary time (zero activity) from at baseline 1,020 ± 75 min/day to, at 6 months, 929 ± 84 min/day (P < 0.001), and at 12 months, 978 ± 95 min/day (P < 0.001). For the whole group, weight loss averaged 1.4 ± 3.3 kg (P < 0.05). Weight loss for obese subjects was 2.3 ± 3.5 kg (P < 0.03). Access to the treadmill desks was associated with increased daily physical activity compared to traditional chair‐based desks; their deployment was not associated with altered performance. For the 36 participants, fat mass did not change significantly, however, those who lost weight (n = 22) lost 3.4 ± 5.4 kg (P < 0.001) of fat mass. Weight loss was greatest in people with obesity. Conclusions: Access to treadmill desks may improve the health of office workers without affecting work performance.     

Does P-Cresylglucuronide Have the Same Impact on Mortality as Other Protein-Bound Uremic Toxins?

Background

Uremic toxins are emerging as important, non-traditional cardiovascular risk factors in chronic kidney disease (CKD). P-cresol has been defined as a prototype protein-bound uremic toxin. Conjugation of p-cresol creates p-cresylsulfate (PCS) as the main metabolite and p-cresylglucuronide (PCG), at a markedly lower concentration. The objective of the present study was to evaluate serum PCG levels, determine the latter’s association with mortality and establish whether the various protein-bound uremic toxins (i.e. PCS, PCG and indoxylsulfate (IS)) differed in their ability to predict mortality.

Methodology/Principal Findings

We studied 139 patients (mean ± SD age: 67±12; males: 60%) at different CKD stages (34.5% at CKD stages 2–3, 33.5% at stage 4–5 and 32% at stage 5D). A recently developed high-performance liquid chromatography method was used to assay PCG concentrations. Total and free PCG levels increased with the severity of CKD. During the study period (mean duration: 779±185 days), 38 patients died. High free and total PCG levels were correlated with overall and cardiovascular mortality independently of well-known predictors of survival, such as age, vascular calcification, anemia, inflammation and (in predialysis patients) the estimated glomerular filtration rate. In the same cohort, free PCS levels and free IS levels were both correlated with mortality. Furthermore, the respective predictive powers of three Cox multivariate models (free PCS+other risk factors, free IS+other risk factors and free PCS+other risk factors) were quite similar - suggesting that an elevated PCG concentration has much the same impact on mortality as other uremic toxins (such as PCS or IS) do.

Conclusions

Although PCG is the minor metabolite of p-cresol, our study is the first to reveal its association with mortality. Furthermore, the free fraction of PCG appears to have much the same predictive power for mortality as PCS and IS do.     

Psychosocial Working Conditions and Cognitive Complaints among Swedish Employees

Background

Cognitive complaints involving problems with concentration, memory, decision-making and thinking are relatively common in the work force. The sensitivity of both subjective and objective cognitive functioning to common psychiatric conditions, stress levels and to cognitive load makes it plausible that psychosocial working conditions play a role in cognitive complaints. Thus, this study aimed to test the associations between psychosocial work factors and cognitive complaints in nationally representative samples of the Swedish work force. Cross-sectional (n = 9751) and prospective (n = 3644; two time points two years apart) sequential multiple regression analyses were run, adjusting for general confounders, depressive- and sleeping problems. Additional prospective analyses were run adjusting for baseline cognitive complaints.

Cross-sectional results

High quantitative demands, information and communication technology (ICT) demands, underqualification and conflicts were positively associated with cognitive complaints, while social support, good resources at work and overqualification were negatively associated with cognitive complaints in all models. Skill discretion and decision authority were weakly associated with cognitive complaints. Conflicts were more strongly associated with cognitive complaints in women than in men, after adjustment for general confounders.

Prospective results

Quantitative job demands, ICT demands and underqualification were positively associated with future cognitive complaints in all models, including when adjusted for baseline cognitive complaints. Decision authority was weakly positively associated with future cognitive complaints, only after adjustment for depressive- and sleeping problems respectively. Social support was negatively associated with future cognitive complaints after adjustment for general confounders and baseline cognitive complaints. Skill discretion and resources were negatively associated with future cognitive complaints after adjustment for general confounders. The associations between quantitative demands and future cognitive complaints were stronger in women.

Discussion/Conclusions

The findings indicate that psychosocial working conditions should be taken into account when considering cognitive complaints among employees.