Dataset Information

Large-scale patterning of living colloids for dynamic studies of neutrophil-microbe interactions.

ABSTRACT: Neutrophils are the first white blood cells to respond to microbes and to limit their invasion of the body. However, the growth of the microbes into colonies often challenges the neutrophils ability to contain them. To study the interactions between neutrophils and microbial colonies, we designed an assay for arranging microbes in clusters of controlled size (i.e. living colloids). The patterned microbes in the living colloid are mechanically trapped inside the wells and fully accessible to neutrophils. Using the assay, we studied the interactions between human neutrophils and Candida albicans and Staphylococcus aureus, two common human pathogens. We also probed the susceptibility of C. albicans colloids to caspofungin, a common antifungal drug.

SUBMITTER: Kim JJ

PROVIDER: S-EPMC5995581 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Large-scale patterning of living colloids for dynamic studies of neutrophil-microbe interactions.

Kim Jae Jung JJ Reátegui Eduardo E Hopke Alex A Jalali Fatemeh F Roushan Maedeh M Doyle Patrick S PS Irimia Daniel D

Lab on a chip 20180501 11

Neutrophils are the first white blood cells to respond to microbes and to limit their invasion of the body. However, the growth of the microbes into colonies often challenges the neutrophils ability to contain them. To study the interactions between neutrophils and microbial colonies, we designed an assay for arranging microbes in clusters of controlled size (i.e. living colloids). The patterned microbes in the living colloid are mechanically trapped inside the wells and fully accessible to neut ...[more]

PMID: 29770423

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Project description:Despite the success of genome-wide association studies in medical genetics, the underlying genetics of many complex diseases remains enigmatic. One plausible reason for this could be the failure to account for the presence of genetic interactions in current analyses. Exhaustive investigations of interactions are typically infeasible because the vast number of possible interactions impose hard statistical and computational challenges. There is, therefore, a need for computationally efficient methods that build on models appropriately capturing interaction. We introduce a new methodology where we augment the interaction hypothesis with a set of simpler hypotheses that are tested, in order of their complexity, against a saturated alternative hypothesis representing interaction. This sequential testing provides an efficient way to reduce the number of non-interacting variant pairs before the final interaction test. We devise two different methods, one that relies on a priori estimated numbers of marginally associated variants to correct for multiple tests, and a second that does this adaptively. We show that our methodology in general has an improved statistical power in comparison to seven other methods, and, using the idea of closed testing, that it controls the family-wise error rate. We apply our methodology to genetic data from the PROCARDIS coronary artery disease case/control cohort and discover three distinct interactions. While analyses on simulated data suggest that the statistical power may suffice for an exhaustive search of all variant pairs in ideal cases, we explore strategies for a priori selecting subsets of variant pairs to test. Our new methodology facilitates identification of new disease-relevant interactions from existing and future genome-wide association data, which may involve genes with previously unknown association to the disease. Moreover, it enables construction of interaction networks that provide a systems biology view of complex diseases, serving as a basis for more comprehensive understanding of disease pathophysiology and its clinical consequences.

Dataset Information

Large-scale patterning of living colloids for dynamic studies of neutrophil-microbe interactions.

Publications

Large-scale patterning of living colloids for dynamic studies of neutrophil-microbe interactions.

Similar Datasets

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