Quantifying cellular traction forces in three dimensions

Cells engage in mechanical force exchange with their extracellular environment through tension generated by the cytoskeleton. A method combining laser scanning confocal microscopy (LSCM) and digital volume correlation (DVC) enables tracking and quantification of cell-mediated deformation of the extracellular matrix in all three spatial dimensions. Time-lapse confocal imaging of migrating 3T3 fibroblasts on fibronectin (FN)-modified polyacrylamide gels of varying thickness reveals significant in-plane (x, y) and normal (z) displacements, and illustrates the extent to which cells, even in nominally two-dimensional (2-D) environments, explore their surroundings in all three dimensions. The magnitudes of the measured displacements are independent of the elastic moduli of the gels. Analysis of the normal displacement profiles suggests that normal forces play important roles even in 2-D cell migration

Results from a 13-Year Prospective Cohort Study Show Increased Mortality Associated with Bloodstream Infections Caused by Pseudomonas aeruginosa Compared to Other Bacteria

ABSTRACT The impact of bacterial species on outcome in bloodstream infections (BSI) is incompletely understood. We evaluated the impact of bacterial species on BSI mortality, with adjustment for patient, bacterial, and treatment factors. From 2002 to 2015, all adult inpatients with monomicrobial BSI caused by Staphylococcus aureus or Gram-negative bacteria at Duke University Medical Center were prospectively enrolled. Kaplan-Meier curves and multivariable Cox regression with propensity score models were used to examine species-specific bacterial BSI mortality. Of the 2,659 enrolled patients, 999 (38%) were infected with S. aureus , and 1,660 (62%) were infected with Gram-negative bacteria. Among patients with Gram-negative BSI, Enterobacteriaceae (81% [1,343/1,660]) were most commonly isolated, followed by non-lactose-fermenting Gram-negative bacteria (16% [262/1,660]). Of the 999 S. aureus BSI isolates, 507 (51%) were methicillin resistant. Of the 1,660 Gram-negative BSI isolates, 500 (30%) were multidrug resistant. The unadjusted time-to-mortality among patients with Gram-negative BSI was shorter than that of patients with S. aureus BSI ( P = 0.003), due to increased mortality in patients with non-lactose-fermenting Gram-negative BSI generally ( P < 0.0001) and Pseudomonas aeruginosa BSI ( n = 158) in particular ( P < 0.0001). After adjustment for patient demographics, medical comorbidities, bacterial antibiotic resistance, timing of appropriate antibiotic therapy, and source control in patients with line-associated BSI, P. aeruginosa BSI remained significantly associated with increased mortality (hazard ratio = 1.435; 95% confidence interval = 1.043 to 1.933; P = 0.02). P. aeruginosa BSI was associated with increased mortality relative to S. aureus or other Gram-negative BSI. This effect persisted after adjustment for patient, bacterial, and treatment factors

Triblock Copolymer as an Effective Membrane-Sealing Material

An intact cell membrane serves as a permeable barrier, regulating the influx and efflux of ions and small molecules. When the integrity of the membrane is compromised, its barrier function is also disrupted, threatening the survival of the cell. Triblock copolymer surfactants of the form poly(ethylene oxide)-poly(propylene oxide)-poly(ethylene oxide) have been shown to help seal structurally damaged membranes, arresting the leakage of intracellular materials. In order to understand how this particular family of triblock copolymers helps seal damaged membranes, model lipid monolayer and bilayer systems have been used to unravel the nature of the lipid/copolymer interaction. The copolymer surfactant is found to selectively insert into structurally compromised membranes, thus localizing its sealing effect on the damaged regions. The inserted polymer is “squeezed out” when the lipid packing density is increased, suggesting a mechanism for the cell to be rid of the polymer when the membrane integrity is restored

Lithographic Patterning of Photoreactive Cell-Adhesive Proteins

We describe a novel, simple method for the photolithographic patterning of cell-adhesive proteins. Intrinsically photoreactive proteins are synthesized in Escherichia coli through incorporation of the non-canonical, photosensitive amino acid para-azidophenylalanine. Upon ultraviolet irradiation at 365 nm, proteins form cross-linked films with elastic moduli that can be tuned by varying the concentration of photoreactive amino acid in the expression medium. Films of these proteins can be directly patterned using standard photolithographic techniques. We demonstrate the utility of this method of protein patterning by creating stable arrays of fibroblast cells on an engineered protein “photoresist”

Breast cancer susceptibility loci and mammographic density

Introduction Recently, the Breast Cancer Association Consortium (BCAC) conducted a multi-stage genome-wide association study and identified 11 single nucleotide polymorphisms (SNPs) associated with breast cancer risk. Given the high degree of heritability of mammographic density and its strong association with breast cancer, it was hypothesised that breast cancer susceptibility loci may also be associated with breast density and provide insight into the biology of breast density and how it influences breast cancer risk. Methods We conducted an analysis in the Nurses\u27 Health Study (n = 1121) to assess the relation between 11 breast cancer susceptibility loci and mammographic density. At the time of their mammogram, 217 women were premenopausal and 904 women were postmenopausal. We used generalised linear models adjusted for covariates to determine the mean percentage of breast density according to genotype. Results Overall, no association between the 11 breast cancer susceptibility loci and mammographic density was seen. Among the premenopausal women, three SNPs (rs12443621 [TNRc9/LOC643714], rs3817198 [lymphocyte-specific protein-1] and rs4666451) were marginally associated with mammographic density (p \u3c 0.10). All three of these SNPs showed an association that was consistent with the direction in which these alleles influence breast cancer risk. The difference in mean percentage mammographic density comparing homozygous wildtypes to homozygous variants ranged from 6.3 to 8.0%. None of the 11 breast cancer loci were associated with postmenopausal breast density. Conclusion Overall, breast cancer susceptibility loci identified through a genome-wide association study do not appear to be associated with breast cancer risk

Three-Dimensional Traction Force Microscopy: A New Tool for Quantifying Cell-Matrix Interactions

The interactions between biochemical processes and mechanical signaling play important roles during various cellular processes such as wound healing, embryogenesis, metastasis, and cell migration. While traditional traction force measurements have provided quantitative information about cell matrix interactions in two dimensions, recent studies have shown significant differences in the behavior and morphology of cells when placed in three-dimensional environments. Hence new quantitative experimental techniques are needed to accurately determine cell traction forces in three dimensions. Recently, two approaches both based on laser scanning confocal microscopy have emerged to address this need. This study highlights the details, implementation and advantages of such a three-dimensional imaging methodology with the capability to compute cellular traction forces dynamically during cell migration and locomotion. An application of this newly developed three-dimensional traction force microscopy (3D TFM) technique to single cell migration studies of 3T3 fibroblasts is presented to show that this methodology offers a new quantitative vantage point to investigate the three-dimensional nature of cell-ECM interactions

Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk

Background Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk. Methods Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies. Results Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38–1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28–1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45–1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile. Conclusions The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.Includes Cancer Research UK, Horizon 2020 and FP

Polymorphisms in a Putative Enhancer at the 10q21.2 Breast Cancer Risk Locus Regulate NRBF2 Expression.

Genome-wide association studies have identified SNPs near ZNF365 at 10q21.2 that are associated with both breast cancer risk and mammographic density. To identify the most likely causal SNPs, we fine mapped the association signal by genotyping 428 SNPs across the region in 89,050 European and 12,893 Asian case and control subjects from the Breast Cancer Association Consortium. We identified four independent sets of correlated, highly trait-associated variants (iCHAVs), three of which were located within ZNF365. The most strongly risk-associated SNP, rs10995201 in iCHAV1, showed clear evidence of association with both estrogen receptor (ER)-positive (OR = 0.85 [0.82-0.88]) and ER-negative (OR = 0.87 [0.82-0.91]) disease, and was also the SNP most strongly associated with percent mammographic density. iCHAV2 (lead SNP, chr10: 64,258,684:D) and iCHAV3 (lead SNP, rs7922449) were also associated with ER-positive (OR = 0.93 [0.91-0.95] and OR = 1.06 [1.03-1.09]) and ER-negative (OR = 0.95 [0.91-0.98] and OR = 1.08 [1.04-1.13]) disease. There was weaker evidence for iCHAV4, located 5' of ADO, associated only with ER-positive breast cancer (OR = 0.93 [0.90-0.96]). We found 12, 17, 18, and 2 candidate causal SNPs for breast cancer in iCHAVs 1-4, respectively. Chromosome conformation capture analysis showed that iCHAV2 interacts with the ZNF365 and NRBF2 (more than 600 kb away) promoters in normal and cancerous breast epithelial cells. Luciferase assays did not identify SNPs that affect transactivation of ZNF365, but identified a protective haplotype in iCHAV2, associated with silencing of the NRBF2 promoter, implicating this gene in the etiology of breast cancer.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.ajhg.2015.05.002

Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170.

We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.352