70 research outputs found

    Speed-dependent chemotactic precision in marine bacteria

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    Chemotaxis underpins important ecological processes in marine bacteria, from the association with primary producers to the colonization of particles and hosts. Marine bacteria often swim with a single flagellum at high speeds, alternating "runs" with either 180° reversals or ∼90° "flicks," the latter resulting from a buckling instability of the flagellum. These adaptations diverge from Escherichia coli's classic run-And-Tumble motility, yet how they relate to the strong and rapid chemotaxis characteristic of marine bacteria has remained unknown. We investigated the relationship between swimming speed, run-reverse-flick motility, and high-performance chemotaxis by tracking thousands of Vibrio alginolyticus cells in microfluidic gradients. At odds with current chemotaxis models, we found that chemotactic precision the strength of accumulation of cells at the peak of a gradient is swimming-speed dependent in V. alginolyticus. Faster cells accumulate twofold more tightly by chemotaxis compared with slower cells, attaining an advantage in the exploitation of a resource additional to that of faster gradient climbing. Trajectory analysis and an agent-basedmathematicalmodel revealed that this unexpected advantage originates from a speed dependence of reorientation frequency and flicking, which were higher for faster cells, and was compounded by chemokinesis, an increase in speedwith resource concentration. The absence of any one of these adaptations led to a 65-70% reduction in the populationlevel resource exposure. These findings indicate that, contrary to what occurs in E. coli, swimming speed can be a fundamental determinant of the gradient-seeking capabilities of marine bacteria, and suggest a new model of bacterial chemotaxis. Keywords: ocean; motility; run-reverse-flick; chemotaxis; chemokinesisNational Institutes of Health (U.S.) (Grant 1R01GM100473)Gordon and Betty Moore Foundation (Award GBMF3783

    In vitro models for non-alcoholic fatty liver disease: Emerging platforms and their applications

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    Non-alcoholic fatty liver disease (NAFLD) represents a global healthcare challenge, affecting 1 in 4 adults, and death rates are predicted to rise inexorably. The progressive form of NAFLD, non-alcoholic steatohepatitis (NASH), can lead to fibrosis, cirrhosis, and hepatocellular carcinoma. However, no medical treatments are licensed for NAFLD-NASH. Identifying efficacious therapies has been hindered by the complexity of disease pathogenesis, a paucity of predictive preclinical models and inadequate validation of pharmacological targets in humans. The development of clinically relevant in vitro models of the disease will pave the way to overcome these challenges. Currently, the combined application of emerging technologies (e.g., organ-on-a-chip/microphysiological systems) and control engineering approaches promises to unravel NAFLD biology and deliver tractable treatment candidates. In this review, we will describe advances in preclinical models for NAFLD-NASH, the recent introduction of novel technologies in this space, and their importance for drug discovery endeavors in the future

    Identification of Tumor Evolution Patterns by Means of Inductive Logic Programming

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    In considering key events of genomic disorders in the development and progression of cancer, the correlation between genomic instability and carcinogenesis is currently under investigation. In this work, we propose an inductive logic programming approach to the problem of modeling evolution patterns for breast cancer. Using this approach, it is possible to extract fingerprints of stages of the disease that can be used in order to develop and deliver the most adequate therapies to patients. Furthermore, such a model can help physicians and biologists in the elucidation of molecular dynamics underlying the aberrations-waterfall model behind carcinogenesis. By showing results obtained on a real-world dataset, we try to give some hints about further approach to the knowledge-driven validations of such hypotheses

    In-Vivo Real-Time Control of Protein Expression from Endogenous and Synthetic Gene Networks

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    We describe an innovative experimental and computational approach to control the expression of a protein in a population of yeast cells. We designed a simple control algorithm to automatically regulate the administration of inducer molecules to the cells by comparing the actual protein expression level in the cell population with the desired expression level. We then built an automated platform based on a microfluidic device, a time-lapse microscopy apparatus, and a set of motorized syringes, all controlled by a computer. We tested the platform to force yeast cells to express a desired fixed, or time-varying, amount of a reporter protein over thousands of minutes. The computer automatically switched the type of sugar administered to the cells, its concentration and its duration, according to the control algorithm. Our approach can be used to control expression of any protein, fused to a fluorescent reporter, provided that an external molecule known to (indirectly) affect its promoter activity is available

    "Sequencing-grade" screening for BRCA1 variants by oligo-arrays

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    The need for fast, efficient, and less costly means to screen genetic variants associated with disease predisposition led us to develop an oligo-nucleotide array-based process for gene-specific single nucleotide polymorphism (SNP) genotyping. This cost-effective, high-throughput strategy has high sensitivity and the same degree of accuracy as direct sequencing, the current gold standard for genetic screening. We used the BRCA1 breast and ovarian cancer predisposing gene model for the validation of the accuracy and efficiency of our strategy. This process could detect point mutations, insertions or deletions of any length, of known and unknown variants even in heterozygous conditions without affecting sensitivity and specificity. The system could be applied to other disorders and can also be custom-designed to include a number of genes related to specific clinical conditions. This system is particularly useful for the screening of long genomic regions with relatively infrequent but clinically relevant variants, while drastically cutting time and costs in comparison to high-throughput sequencing
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