Browsing by Subject "Stochasticity"

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    Land use–transport interaction modeling: A review of the literature and future research directions
    (Journal of Transport and Land Use, 2015) Acheampong, Ransford A.; Silva, Elisabete A.
    The aim of this review paper is to provide comprehensive and up-to-date material for both researchers and practitioners interested in land-use-transport interaction (LUTI) modeling. The paper brings together some 60 years of published research on the subject. The review discusses the dominant theoretical and conceptual propositions underpinning research in the field and the existing operational LUTI modeling frameworks as well as the modeling methodologies that have been applied over the years. On the basis of these, the paper discusses the challenges, on-going progress and future research directions around the following thematic areas: 1) the challenges imposed by disaggregation—data availability, computation time, stochastic variation and output uncertainty; 2) the challenges of and progress in integrating activity-based travel demand models into LUTI models; 3) the quest for a satisfactory measure of accessibility; and 4) progress and challenges toward integrating the environment into LUTI models.
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    Systems analysis of pheromone signaling and antibiotic resistance transfer in Enterococcus faecalis
    (2018-01) Bandyopadhyay, Arpan Anup
    Antibiotics have been an extremely important weapon in the fight against bacterial infections for over half a century. However, excessive use of antibiotics has led to increased frequencies of resistance among bacteria. Antibiotic resistance is an inevitable outcome of natural selection as organisms undergo random mutations to escape lethal selective pressure. Many of these resistant bacteria can also transfer their genetic material to other bacteria through direct cell-cell contact via conjugation, further facilitating the spread of resistance. The human gastrointestinal tract, replete with a high density of bacteria and often exposed to antibiotics, provides an ideal environment for antibiotic resistance genes to arise and propagate through bacterial populations. Enterococcus faecalis, a commensal bacterium of the human intestinal tract, has emerged as a major cause of healthcare-associated infections. Treatment of these infections has become increasingly difficult with the emergence of E. faecalis strains that are resistant to multiple major classes of antibiotics. The organism’s ability to acquire and transfer resistance genes and virulence determinants through conjugative plasmids poses a serious clinical concern. Here we present our study on conjugation of a tetracycline-resistance plasmid pCF10 which is regulated by intercellular communication using two antagonistic signaling peptides. An inducer peptide produced by the plasmid-free recipient cells functions as a “mate-sensing” signal and triggers the conjugative plasmid transfer in donors. The donors encode an inhibitor peptide on the plasmid which represses conjugation and functions as a "self-sensing" signal, reducing the response to the inducer in a density-dependent fashion. This form of dual signaling-controlled conjugation was also found to be prevalent across other pheromone-responsive plasmids, including pAD1 and pAM373. Though the donors calibrate their conjugation response in accordance with the relative abundance of donors and recipients, plasmid transfer can occur under otherwise unfavorable conditions, such as low inducing pheromone and high inhibitor concentrations. To better understand this apparent inconsistency, we formulated a stochastic mathematical model that integrates intracellular molecular regulation of conjugation and interactions between donors and recipients through the signaling peptides. Kinetic parameters for the model were estimated from literature and augmented by experimental RNA-Seq data and binding constant measurements. Simulations of the stochastic model and single-cell analysis using transcript quantification by HCR-FISH and GFP reporter fusions revealed distinct subpopulations of rapid responders under unfavorable conditions for plasmid transfer. We developed a series of fluorescent reporters to track the uninduced/induced donors, recipients, and uninduced/induced transconjugants in real-time using confocal microscopy and flow cytometry. We are further developing a microfluidic gut model which allow for co-culturing of human and bacteria cells in an in vivo-simulated microenvironment. This system will be used to model the in vivo biology of conjugation and gain a better mechanistic understanding of the community balance between the microbial inhabitants of the GI tract. A better understanding of the bacterial signaling mechanisms in vivo and the downstream effects on microbiome community balance may help us identify alternate strategies to prevent the spread of antibiotic resistance.