Dataset Information

Optimal Allocation of Bacterial Protein Resources under Nonlethal Protein Maturation Stress.

ABSTRACT: Under different environmental stresses, bacteria optimize the allocation of cellular resources through a variety of mechanisms. Recently, researchers have used phenomenological models to quantitatively characterize the allocation of bacterial protein resources under metabolic and translational limitations. Some stresses interfere with protein maturation, thereby enhancing the expression of chaperones and proteases. However, the reallocation of protein resources caused by such environmental stresses has not been modeled quantitatively. Here, we developed a dynamic model of coarse-grained protein resource fluxes based on a self-replicator that includes protein maturation and degradation. Through flux balance analysis, it produces a constrained optimization problem that can be solved analytically. Accordingly, we predicted protein allocation fractions as functions of growth rate under different limitations, which are basically in line with empirical data. We cultured Escherichia coli in media containing different concentrations of chloramphenicol, acetic acid, and paraquat and measured the functional relationship between the expression level of ?-galactosidase driven by a constitutive promoter and the bacterial growth rate, respectively. Taking into account the possible mode of stress limitation on the fluxes, our model reproduces this experimentally measured relationship. In addition, our model is in good agreement with the experimental relationship between growth rate and proteome fraction of unnecessary protein in E. coli, considering the unoptimized upregulation of chaperones with useless protein overexpression. The results provide a more systematic view of bacterial stress adaptation that may help in designing for bioengineering or medical interventions.

SUBMITTER: Zhang Q

PROVIDER: S-EPMC6127457 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Optimal Allocation of Bacterial Protein Resources under Nonlethal Protein Maturation Stress.

Zhang Qing Q Li Rui R Li Junbai J Shi Hualin H

Biophysical journal 20180731 5

Under different environmental stresses, bacteria optimize the allocation of cellular resources through a variety of mechanisms. Recently, researchers have used phenomenological models to quantitatively characterize the allocation of bacterial protein resources under metabolic and translational limitations. Some stresses interfere with protein maturation, thereby enhancing the expression of chaperones and proteases. However, the reallocation of protein resources caused by such environmental stres ...[more]

PMID: 30122293

Similar Datasets

Project description:BACKGROUND:Health resources are limited, which means spending should be focused on the people, places and programs that matter most. Choosing the mix of programs to maximize a health outcome is termed allocative efficiency. Here, we extend the methodology of allocative efficiency to answer the question of how resources should be distributed among different geographic regions. METHODS:We describe a novel geographical optimization algorithm, which has been implemented as an extension to the Optima HIV model. This algorithm identifies an optimal funding of services and programs across regions, such as multiple countries or multiple districts within a country. The algorithm consists of three steps: (1) calibrating the model to each region, (2) determining the optimal allocation for each region across a range of different budget levels, and (3) finding the budget level in each region that minimizes the outcome (such as reducing new HIV infections and/or HIV-related deaths), subject to the constraint of fixed total budget across all regions. As a case study, we applied this method to determine an illustrative allocation of HIV program funding across three representative oblasts (regions) in Ukraine (Mykolayiv, Poltava, and Zhytomyr) to minimize the number of new HIV infections. RESULTS:Geographical optimization was found to identify solutions with better outcomes than would be possible by considering region-specific allocations alone. In the case of Ukraine, prior to optimization (i.e. with status quo spending), a total of 244,000 HIV-related disability-adjusted life years (DALYs) were estimated to occur from 2016 to 2030 across the three oblasts. With optimization within (but not between) oblasts, this was estimated to be reduced to 181,000. With geographical optimization (i.e., allowing reallocation of funds between oblasts), this was estimated to be further reduced to 173,000. CONCLUSIONS:With the increasing availability of region- and even facility-level data, geographical optimization is likely to play an increasingly important role in health economic decision making. Although the largest gains are typically due to reallocating resources to the most effective interventions, especially treatment, further gains can be achieved by optimally reallocating resources between regions. Finally, the methods described here are not restricted to geographical optimization, and can be applied to other problems where competing resources need to be allocated with constraints, such as between diseases.

Project description:IntroductionGreat strides in responding to the HIV epidemic have led to improved access to and uptake of HIV services in Guyana, a lower-middle-income country with a generalized HIV epidemic. Despite efforts to scale up HIV treatment and adopt the test and start strategy, little is known about costs of HIV services across the care cascade.MethodsWe collected cost data from the national laboratory and nine selected treatment facilities in five of the country's ten Regions, and estimated the costs associated with HIV testing and services (HTS) and antiretroviral therapy (ART) from a provider perspective from January 1, 2016 to December 31, 2016. We then used the unit costs to construct four resource allocation scenarios. In the first two scenarios, we calculated how close Guyana would currently be to its 2020 targets if the allocation of funding across programs and regions over 2017-2020 had (a) remained unchanged from latest-reported levels, or (b) been optimally distributed to minimize incidence and deaths. In the next two, we estimated the resources that would have been required to meet the 2020 targets if those resources had been distributed (a) according to latest-reported patterns, or (b) optimally to minimize incidence and deaths.ResultsThe mean cost per test was US$15 and the mean cost per person tested positive was US$796. The mean annual cost per of maintaining established adult and pediatric patients on ART were US$428 and US$410, respectively. The mean annual cost of maintaining virally suppressed patients was US$648. Cost variation across sites may suggest opportunities for improvements in efficiency, or may reflect variation in facility type and patient volume. There may also be scope for improvements in allocative efficiency; we estimated a 28% reduction in the total resources required to meet Guyana's 2020 targets if funds had been optimally distributed to minimize infections and deaths.ConclusionsWe provide the first estimates of costs along the HIV cascade in the Caribbean and assessed efficiencies using novel context-specific data on the costs associated with diagnostic, treatment, and viral suppression. The findings call for better targeting of services, and efficient service delivery models and resource allocation, while scaling up HIV services to maximize investment impact.

Project description:Background and aimsHeteroblasty is an encompassing term referring to ontogenetic changes in the plant shoot. A shaded environment is known to affect the process of heteroblastic development; however, it is not known whether crowded or high density growing conditions can also alter heteroblasty. Compound leaves of the shade-intolerant Acacia implexa allocate less biomass per unit photosynthetic area than transitional leaves or phyllodes and it is hypothesized that this trait will convey an advantage in a crowded environment. Compound leaves also have larger photosynthetic capture area - a trait known to be advantageous in shade. This studied tested the hypothesis that more compound leaves will be developed under shade and crowded environments. Furthermore, this species should undergo optimal allocation of biomass to shoots and roots given shaded and crowded environments.MethodsA full factorial design of irradiance (high and low) and density levels (high, medium and low) on three populations sourced from varying rainfall regions (high, medium and low) was established under controlled glasshouse conditions. Traits measured include the number of nodes expressing a compound leaf, biomass allocation to shoots and roots, and growth traits. Key Results A higher number of nodes expressed a compound leaf under low irradiance and in high density treatments; however, there were no significant interactions across treatments. Phenotypes strongly associated with the shade avoidance syndrome were developed under low irradiance; however, this was not observed under high density. There was no significant difference in relative growth rates across light treatments, but growth was significantly slower in a crowded environment. Conclusions Heteroblastic development in Acacia can be altered by shade and crowded environments. In this experiment, light was clearly the most limiting factor to growth in a shaded environment; however, in a crowded environment there were additional limiting resources to growth.

Dataset Information

Optimal Allocation of Bacterial Protein Resources under Nonlethal Protein Maturation Stress.

Publications

Optimal Allocation of Bacterial Protein Resources under Nonlethal Protein Maturation Stress.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets