Fitness of bacteria is determined both by how fast cells grow when nutrients are abundant and by how well they survive when conditions worsen. Here, we study how prior growth conditions affect the death rate of Escherichia coli during carbon starvation. We control the growth rate prior to starvation either via the carbon source or via a carbon-limited chemostat. We find a consistent dependence where death rate depends on the prior growth conditions only via the growth rate, with slower growth leading to exponentially slower death. Breaking down the observed death rate into two factors, maintenance rate and recycling yield, reveals that slower growing cells display a decreased maintenance rate per cell volume during starvation, thereby decreasing their death rate. In contrast, the ability to scavenge nutrients from carcasses of dead cells (recycling yield) remains constant. Our results suggest a physiological trade-off between rapid proliferation and long survival. We explore the implications of this trade-off within a mathematical model, which can rationalize the observation that bacteria outside of lab environments are not optimized for fast growth.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273699 | PMC |
http://dx.doi.org/10.15252/msb.20209478 | DOI Listing |
Kidney360
January 2025
Division of Nephrology and Hypertension, Department of Internal Medicine, University of Kansas Medical Centre, 3901 Rainbow Blvd, MS3002, Kansas City, KS, USA.
Background: Patient involvement in research can help to ensure that the evidence generated aligns with their needs and priorities. In the Establishing Meaningful Patient-Centered Outcomes With Relevance for Patients with Polycystic Kidney Disease (EMPOWER PKD) project we aimed to identify patient-important outcomes and discuss the impact of PKD on patients.
Methods: Nine focus groups were held with adult patients with PKD, caregivers, and clinical or research experts in PKD.
J Agric Food Chem
January 2025
Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.
Inadvertent exposure to aristolochic acids (AAs) is causing chronic renal disease worldwide, with aristolochic acid I (AA-I) identified as the primary toxic agent. This study employed chemical methods to investigate the mechanisms underlying the nephrotoxicity and carcinogenicity of AA-I. Aristolochic acid II (AA-II), which has a structure similar to that of AA-I, was investigated with the same methods for comparison.
View Article and Find Full Text PDFImportance: Fragility fractures result in significant morbidity.
Objective: To review evidence on osteoporosis screening to inform the US Preventive Services Task Force.
Data Sources: PubMed, Embase, Cochrane Library, and trial registries through January 9, 2024; references, experts, and literature surveillance through July 31, 2024.
JAMA Netw Open
January 2025
Division of Population Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts.
Importance: Adolescent and young adult (AYA) patients with advanced cancer often die in hospital settings. Data characterizing the degree to which this pattern of care is concordant with patient goals are sparse.
Objective: To evaluate the extent of concordance between the preferred and actual location of death among AYA patients with cancer.
Biometrics
January 2025
School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai 200433, China.
As a commonly employed method for analyzing time-to-event data involving functional predictors, the functional Cox model assumes a linear relationship between the functional principal component (FPC) scores of the functional predictors and the hazard rates. However, in practical scenarios, such as our study on the survival time of kidney transplant recipients, this assumption often fails to hold. To address this limitation, we introduce a class of high-dimensional partially linear functional Cox models, which accommodates the non-linear effects of functional predictors on the response and allows for diverging numbers of scalar predictors and FPCs as the sample size increases.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!