The Effect of Proteolytic Queues on Antibiotic Tolerance and Persistence Cells Population in Escherichia Coli

A major contributing factor to the abundance of antibiotic-resistant microorganisms and failed antibiotic treatment is survival due to antibiotic tolerance and persistence. Antibiotic tolerance is a widespread phenomenon that enables cells to survive treatment without carrying a resistance gene. This phenomenon renders antibiotic treatments less effective and facilitates antibiotic resistance. We are particularly interested in proteases, responsible for degradation of proteins, because of their known relationship to tolerance and persistence. Here, we examine the effects of proteases and antibiotic survival using queueing theory, in which one type of customer competes for processing by servers, that has traditionally been applied to systems such as computer networks and call centers. The biological queueing theory principally assumes that there are limited processing resources in a cell. Using synthetic systems engineered to form proteolytic queues, we can now examine tolerance/persistence in a new manner. In this work, we demonstrated in E. coli that the overproducing of protein engineered to be digested by the protease ClpXP can form a proteolytic queue, and this queue results in an increase in antibiotic tolerance ~80 and ~60 fold with ampicillin and ciprofloxacin, respectively. The proteolytic queue had no apparent effect on bacterial persistence levels. Furthermore, we showed that the queueing at the other two major proteases, ClpAP and Lon, have a slight effect on tolerant cell population

A multiple channel queueing model under an uncertain environment with multiclass arrivals for supplying demands in a cement industry

In recent years, cement consumption has increased in most Asian countries, including Malaysia. There are many factors which affect the supply of the increasing order demands in the cement industry, such as traffic congestion, logistics, weather and machine breakdowns. These factors hinder smooth and efficient supply, especially during periods of peak congestion at the main gate of the industry where queues occur as a result of inability to keep to the order deadlines. Basic elements, such as arrival and service rates, that cannot be predetermined must be considered under an uncertain environment. Solution approaches including conventional queueing techniques, scheduling models and simulations were unable to formulate the performance measures of the cement queueing system. Hence, a new procedure of fuzzy subset intervals is designed and embedded in a queuing model with the consideration of arrival and service rates. As a result, a multiple channel queueing model with multiclass arrivals, (M1, M2)/G/C/2Pr, under an uncertain environment is developed. The model is able to estimate the performance measures of arrival rates of bulk products for Class One and bag products for Class Two in the cement manufacturing queueing system. For the (M1, M2)/G/C/2Pr fuzzy queueing model, two defuzzification techniques, namely the Parametric Nonlinear Programming and Robust Ranking are used to convert fuzzy queues into crisp queues. This led to three proposed sub-models, which are sub-model 1, MCFQ-2Pr, sub-model 2, MCCQESR-2Pr and sub-model 3, MCCQ-GSR-2Pr. These models provide optimal crisp values for the performance measures. To estimate the performance of the whole system, an additional step is introduced through the TrMF-UF model utilizing a utility factor based on fuzzy subset intervals and the α-cut approach. Consequently, these models help decision-makers deal with order demands under an uncertain environment for the cement manufacturing industry and address the increasing quantities needed in future