Pan msr gene deleted strain of Salmonella Typhimurium suffers oxidative stress, depicts macromolecular damage and attenuated virulence.

Salmonella encounters but survives host inflammatory response. To defend host-generated oxidants, Salmonella encodes primary antioxidants and protein repair enzymes. Methionine (Met) residues are highly prone to oxidation and convert into methionine sulfoxide (Met-SO) which compromises protein functions and subsequently cellular survival. However, by reducing Met-SO to Met, methionine sulfoxide reductases (Msrs) enhance cellular survival under stress conditions. Salmonella encodes five Msrs which are specific for particular Met-SO (free/protein bound), and 'R'/'S' types. Earlier studies assessed the effect of deletions of one or two msrs on the stress physiology of S. Typhimurium. We generated a pan msr gene deletion (Δ5msr) strain in S. Typhimurium. The Δ5msr mutant strain shows an initial lag in in vitro growth. However, the Δ5msr mutant strain depicts very high sensitivity (p < 0.0001) to hypochlorous acid (HOCl), chloramine T (ChT) and superoxide-generating oxidant paraquat. Further, the Δ5msr mutant strain shows high levels of malondialdehyde (MDA), protein carbonyls, and protein aggregation. On the other side, the Δ5msr mutant strain exhibits lower levels of free amines. Further, the Δ5msr mutant strain is highly susceptible to neutrophils and shows defective fitness in the spleen and liver of mice. The results of the current study suggest that the deletions of all msrs render S. Typhimurium highly prone to oxidative stress and attenuate its virulence.

Data and methods for studying commercial motor vehicle driver fatigue, highway safety and long-term driver health.

This article summarizes the recommendations on data and methodology issues for studying commercial motor vehicle driver fatigue of a National Academies of Sciences, Engineering, and Medicine study. A framework is provided that identifies the various factors affecting driver fatigue and relating driver fatigue to crash risk and long-term driver health. The relevant factors include characteristics of the driver, vehicle, carrier and environment. Limitations of existing data are considered and potential sources of additional data described. Statistical methods that can be used to improve understanding of the relevant relationships from observational data are also described. The recommendations for enhanced data collection and the use of modern statistical methods for causal inference have the potential to enhance our understanding of the relationship of fatigue to highway safety and to long-term driver health.