Publications

This paper describes a method to detect the presence of bacteria in aqueous samples, based on the capture of bacteria on a syringe filter, and the infection of targeted bacterial species with a bacteriophage (phage). The use of phage as a reagent provides two opportunities for signal amplification: (i) the replication of phage inside a live bacterial host and (ii) the delivery and expression of the complementing gene that turns on enzymatic activity and produces a colored or fluorescent product. Here we demonstrate a phage-based amplification scheme with an M13KE phage that delivers a small peptide motif to an F+, α-complementing strain of Escherichia coli K12, which expresses the ω-domain of β-galactosidase (β-gal). The result of this complementation—an active form of β-gal—was detected colorimetrically, and the high level of expression of the ω-domain of β-gal in the model K12 strains allowed us to detect, on average, five colony-forming units (CFUs) of this strain in 1 L of water with an overnight culture-based assay. We also detected 50 CFUs of the model K12 strain in 1 L of water (or 10 mL of orange juice, or 10 mL of skim milk) in less than 4 h with a solution-based assay with visual readout. The solution-based assay does not require specialized equipment or access to a laboratory, and is more rapid than existing tests that are suitable for use at the point of access. This method could potentially be extended to detect many different bacteria with bacteriophages that deliver genes encoding a full-length enzyme that is not natively expressed in the target bacteria.

We analyze earthquake ruptures propagating along a straight “main” fault and encountering a finite‐length branch fault. Such intersections are often observed in natural fault systems. The predicted effects of the interaction with the branch that we report can be remarkable; they can strongly perturb the propagation velocity on the main fault and, in some cases, even arrest that propagation. Earlier work (Kame et al., 2003; Bhat et al., 2004) emphasized the role of the fault pre‐stress state, branch geometry (i.e., branching angle), and the incoming rupture velocity at the branching junction in determining whether the rupture would follow the branch or continue on the main fault or both, through simulations which did not let a rupture on the branch encounter a barrier or a fault end (called ‘infinite’ branch cases henceforth). In this study we look at “finite” branch cases, and study the effect also of branch length, with rupture being blocked from propagation beyond the branch end. It is known that sudden stoppage of a dynamic rupture front leads to the propagation of large dynamic stress perturbations in the medium. These have been known to nucleate or terminate ruptures on adjacent fault segments (Harris et al., 1991; Harris and Day, 1993, 1999; Harris et al., 2002; Fliss et al., 2005, among others). We thus anticipate interaction between the rupture on the main fault and the branched one at two stages, when the rupture is propagating on the branch and when it is suddenly blocked at the branch end. We show that in general rupture termination on a compressional branch little affects propagation on the main fault compared to the infinite branch cases. For branches on the extensional side, we show in some cases, that whereas an infinite' branch would have allowed (or stopped) rupture propagation on the main fault, a finite branch stops (or allows) propagation on the main fault. Such results have a dependence on branch length that we document. We also illustrate branch‐related complexities in rupture velocity evolution which could be one of the sources of the high‐frequency content of strong ground motion record. Complexities in the slip distribution, often associated with a presumed heterogeneous strength distribution along the fault, can also be observed when rupture is terminated on a branch.

BACKGROUND: We aimed to investigate prospective associations of circulating or adipose tissue odd-chain fatty acids 15:0 and 17:0 and trans-palmitoleic acid, t16:1n-7, as potential biomarkers of dairy fat intake, with incident type 2 diabetes (T2D). METHODS AND FINDINGS: Sixteen prospective cohorts from 12 countries (7 from the United States, 7 from Europe, 1 from Australia, 1 from Taiwan) performed new harmonised individual-level analysis for the prospective associations according to a standardised plan. In total, 63,682 participants with a broad range of baseline ages and BMIs and 15,180 incident cases of T2D over the average of 9 years of follow-up were evaluated. Study-specific results were pooled using inverse-variance-weighted meta-analysis. Prespecified interactions by age, sex, BMI, and race/ethnicity were explored in each cohort and were meta-analysed. Potential heterogeneity by cohort-specific characteristics (regions, lipid compartments used for fatty acid assays) was assessed with metaregression. After adjustment for potential confounders, including measures of adiposity (BMI, waist circumference) and lipogenesis (levels of palmitate, triglycerides), higher levels of 15:0, 17:0, and t16:1n-7 were associated with lower incidence of T2D. In the most adjusted model, the hazard ratio (95% CI) for incident T2D per cohort-specific 10th to 90th percentile range of 15:0 was 0.80 (0.73-0.87); of 17:0, 0.65 (0.59-0.72); of t16:1n7, 0.82 (0.70-0.96); and of their sum, 0.71 (0.63-0.79). In exploratory analyses, similar associations for 15:0, 17:0, and the sum of all three fatty acids were present in both genders but stronger in women than in men (pinteraction < 0.001). Whereas studying associations with biomarkers has several advantages, as limitations, the biomarkers do not distinguish between different food sources of dairy fat (e.g., cheese, yogurt, milk), and residual confounding by unmeasured or imprecisely measured confounders may exist. CONCLUSIONS: In a large meta-analysis that pooled the findings from 16 prospective cohort studies, higher levels of 15:0, 17:0, and t16:1n-7 were associated with a lower risk of T2D.

Abstract Background Maternal pre-pregnancy body mass index (BMI) is positively associated with offspring birth weight (BW) and BMI in childhood and adulthood. Each of these associations could be due to causal intrauterine effects, or confounding (genetic or environmental), or some combination of these. Here we estimate the extent to which the association between maternal BMI and offspring body size is explained by offspring genotype, as a first step towards establishing the importance of genetic confounding. Methods We examined the associations of maternal pre-pregnancy BMI with offspring BW and BMI at 1, 5, 10 and 15 years, in three European birth cohorts (n ≤11 498). Bivariate Genomic-relatedness-based Restricted Maximum Likelihood implemented in the GCTA software (GCTA-GREML) was used to estimate the extent to which phenotypic covariance was explained by offspring genotype as captured by common imputed single nucleotide polymorphisms (SNPs). We merged individual participant data from all cohorts, enabling calculation of pooled estimates. Results Phenotypic covariance (equivalent here to Pearson’s correlation coefficient) between maternal BMI and offspring phenotype was 0.15 [95% confidence interval (CI): 0.13, 0.17] for offspring BW, increasing to 0.29 (95% CI: 0.26, 0.31) for offspring 15 year BMI. Covariance explained by offspring genotype was negligible for BW [–0.04 (95% CI: –0.09, 0.01)], but increased to 0.12 (95% CI: 0.04, 0.21) at 15 years, which is equivalent to 43% (95% CI: 15%, 72%) of the phenotypic covariance. Sensitivity analyses using weight, BMI and ponderal index as the offspring phenotype at all ages showed similar results. Conclusions Offspring genotype explains a substantial fraction of the covariance between maternal BMI and offspring adolescent BMI. This is consistent with a potentially important role for genetic confounding as a driver of the maternal BMI–offspring BMI association.

We found no significant interactions between dietary heme iron intake and common SNPs in relation to T2D.

An elastomeric stamp, containing defined features on the micrometer scale, was used to imprint gold surfaces with specific patterns of self-assembled monolayers of alkanethiols and, thereby, to create islands of defined shape and size that support extracellular matrix protein adsorption and cell attachment. Through this technique, it was possible to place cells in predetermined locations and arrays, separated by defined distances, and to dictate their shape. Limiting the degree of cell extension provided control over cell growth and protein secretion. This method is experimentally simple and highly adaptable. It should be useful for applications in biotechnology that require analysis of individual cells cultured at high density or repeated access to cells placed in specified locations.

OBJECTIVE—Epidemiological studies suggest that high body iron stores are associated with insulin resistance and type 2 diabetes. The aim of this study was to evaluate the association between dietary intake of iron and the risk of type 2 diabetes. RESEARCH DESIGN AND METHODS—We conducted a prospective cohort study within the Nurses’ Health Study. We followed 85,031 healthy women aged 34–59 years from 1980 to 2000. Dietary data were collected every 4 years, and data on medical history and lifestyle factors were updated biennially. RESULTS—During the 20 years of follow-up, we documented 4,599 incident cases of type 2 diabetes. We found no association between total, dietary, supplemental, or nonheme iron and the risk of type 2 diabetes. However, heme iron intake (derived from animal products) was positively associated with risk; relative risks (RRs) across increasing quintiles of cumulative intake were 1.00, 1.08 (95% CI 0.97–1.19), 1.20 (1.09–1.33), 1.27 (1.14–1.41), and 1.28 (1.14–1.45) (Ptrend < 0.0001) after controlling for age, BMI, and other nondietary and dietary risk factors. In addition, when we modeled heme iron in seven categories, the multivariate RR comparing women who consumed ≥2.25 mg/day and those with intake <0.75 mg/day was 1.52 (1.22–1.88). The association between heme iron and the risk of diabetes was significant in both overweight and lean women. CONCLUSIONS—This large cohort study suggests that higher heme iron intake is associated with a significantly increased risk of type 2 diabetes.

Abstract Motivation Our work is motivated by the search for metabolite Quantitative Trait Loci (QTL) in a cohort of more than 5,000 people. There are 158 metabolites measured by NMR spectroscopy measured in the 31-year follow-up of the Northern Finland Birth Cohort 1966 (NFBC66). These metabolites, as with many multivariate phenotypes produced by high-throughput biomarker technology, exhibit strong correlation structures. Existing approaches for combining such data with genetic variants for multivariate QTL analysis generally ignore phenotypic correlations or make restrictive assumptions about the associations between phenotypes and genetic loci. Results We present a computationally efficient Bayesian Seemingly Unrelated Regressions (SUR) model for high-dimensional data, with cell-sparse variable selection and sparse graphical structure for covariance selection. Cell-sparsity allows different phenotype responses to be associated with different genetic predictors and the graphical structure is used to represent the conditional dependencies between phenotype variables. To achieve feasible computation of the large model space, we exploit a factorisation of the covariance matrix. Applying the model to the NFBC66 data with 9,000 directly-genotyped Single Nucleotide Polymorphisms, we are able to simultaneously estimate genotype-phenotype associations and the residual dependence structure amongst the metabolites at the same time. Availability and implementation The R package BayesSUR with full documentation is available at https://cran.r-project.org/web/packages/BayesSUR/ Contact alex.lewin@lshtm.ac.uk