Acid stress induces differential accumulation of metabolites in<i>Escherichia coli</i>O26:H11

Shayanfar, Shima; Broumand, Ariana; Pillai, Suresh D.

doi:10.1111/jam.14081

Cited by 31 publications

(16 citation statements)

References 41 publications

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“…The response of bacterial cells to stressors such as acid, temperature, and ionizing radiation have been extensively studied (Foster, 1991; Arsène et al, 2000; Castanié-Cornet et al, 2010; Daly, 2012; Pin et al, 2012; Swenson et al, 2012; Castillo and Smith, 2017; Villa et al, 2017). Recently, we have shown that E. coli O26:H11 when exposed to acid stress (pH 3.6), the key differentially expressed pathways were peptidoglycan biosynthesis, purine metabolism, D-Glutamine/D-glutamate metabolism, nitrogen metabolism, unsaturated fatty acid biosynthesis, and inositol phosphate metabolism (Shayanfar et al, 2018 J. Appl. Microbial .…”

Section: Discussionmentioning

confidence: 99%

A Comparative Analysis of the Metabolomic Response of Electron Beam Inactivated E. coli O26:H11 and Salmonella Typhimurium ATCC 13311

Bhatia¹,

Pillai²

2019

Front. Microbiol.

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Ionizing radiation such as Electron beam (EB) and gamma irradiation inactivate microbial cells preventing their multiplication. These cells, however, are structurally intact and appear to have residual metabolic activity. We were interested in understanding the metabolic pathways that were still functional in EB-inactivated cells. Therefore, the primary objective of this study was to compare the metabolites accumulating in EB-inactivated pathogens E. coli 026:H11 and S. Typhimurium immediately after EB inactivation and 24 h post inactivation. Defined aliquots (10 9 CFU/mL) of E. coli O26-H11 (TW 1597) and S. Typhimurium (ATCC 13311) suspended in phosphate-buffered saline were exposed to lethal EB doses of 3 kGy and 2 kGy, respectively. Complete inactivation (inability of cells to multiply) was confirmed by traditional plating methods. An untargeted analysis of the primary metabolites accumulating in un-irradiated (control) cells, EB-inactivated cells immediately after irradiation, and EB-inactivated cells that were incubated at room temperature for 24 h post EB inactivation was performed using gas chromatography/mass spectrometry. A total of 349 different metabolites were detected in the EB-inactivated S . Typhimurium and E. coli O26:H11 cells, out of which, only 50% were identifiable. In S . Typhimurium, 98 metabolites were expressed at statistically different concentrations ( P < 0.05) between the three treatment groups. In E. coli O26:H11, 63 metabolites were expressed at statistically different concentrations ( P < 0.05) between the three treatment groups. In both these pathogens, the β-alanine, alanine, aspartate, and glutamate metabolic pathways were significantly impacted ( P < 0.01). Furthermore, the metabolomic changes in EB-inactivated cells were amplified significantly after 24 h storage at room temperature in phosphate-buffered saline. These results suggest that EB-inactivated cells are very metabolically active and, therefore, the term Metabolically Active yet Non-culturable is an apt term describing EB-inactivated bacterial cells.

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Section: Discussionmentioning

confidence: 99%

A Comparative Analysis of the Metabolomic Response of Electron Beam Inactivated E. coli O26:H11 and Salmonella Typhimurium ATCC 13311

Bhatia¹,

Pillai²

2019

Front. Microbiol.

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“…The lower computational cost provided the opportunity to investigate the effect of DBS on large-scale networks. However, the computational models such as the one developed in this paper do not represent the whole complexity of physiological systems [ 80 – 82 ]. For instance, our model does not consider the direct projections from the Th cells to STN cells [ 83 ].…”

Section: Discussionmentioning

confidence: 99%

Robust desynchronization of Parkinson’s disease pathological oscillations by frequency modulation of delayed feedback deep brain stimulation

2018

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The hyperkinetic symptoms of Parkinson’s Disease (PD) are associated with the ensembles of interacting oscillators that cause excess or abnormal synchronous behavior within the Basal Ganglia (BG) circuitry. Delayed feedback stimulation is a closed loop technique shown to suppress this synchronous oscillatory activity. Deep Brain Stimulation (DBS) via delayed feedback is known to destabilize the complex intermittent synchronous states. Computational models of the BG network are often introduced to investigate the effect of delayed feedback high frequency stimulation on partially synchronized dynamics. In this study, we develop a reduced order model of four interacting nuclei of the BG as well as considering the Thalamo-Cortical local effects on the oscillatory dynamics. This model is able to capture the emergence of 34 Hz beta band oscillations seen in the Local Field Potential (LFP) recordings of the PD state. Train of high frequency pulses in a delayed feedback stimulation has shown deficiencies such as strengthening the synchronization in case of highly fluctuating neuronal activities, increasing the energy consumed as well as the incapability of activating all neurons in a large-scale network. To overcome these drawbacks, we propose a new feedback control variable based on the filtered and linearly delayed LFP recordings. The proposed control variable is then used to modulate the frequency of the stimulation signal rather than its amplitude. In strongly coupled networks, oscillations reoccur as soon as the amplitude of the stimulus signal declines. Therefore, we show that maintaining a fixed amplitude and modulating the frequency might ameliorate the desynchronization process, increase the battery lifespan and activate substantial regions of the administered DBS electrode. The charge balanced stimulus pulse itself is embedded with a delay period between its charges to grant robust desynchronization with lower amplitudes needed. The efficiency of the proposed Frequency Adjustment Stimulation (FAS) protocol in a delayed feedback method might contribute to further investigation of DBS modulations aspired to address a wide range of abnormal oscillatory behavior observed in neurological disorders.

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“…Metabolomics is on the verge of potentially making major impacts including in the areas of foodomics. Previous studies have characterized the metabolic response of different foodborne pathogens in acid environment bacteria [33][34][35]. It has been suggested that altered metabolites or metabolomics profiles could predict specific metabolic diseases with high accuracy and help to understand related fundamental mechanisms as well as affected metabolic pathways [36].…”

Section: Discussionmentioning

confidence: 99%

Untitled

2021

BJSTR

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Survival of bacteria in acidic environments is critical for pathogens to successfully multiply and infect the gastrointestinal tract. In this study, a metabolomics approach was conducted to understand and explain the effect of pH-induced stress metabolites in Yersinia enterocolitica. Cells were cultured in tryptic soy broth with or without pH adjustment using HCl (pH 6.8 or pH 3, respectively). In this study, we employed untargeted proton nuclear magnetic resonance (1H-NMR) spectroscopy followed by statistical multivariate analysis was used to identify the metabolites and measure the metabolic profiles and pathways impacted by acid stress. Under conditions of low pH, increased branched-chain amino acid biosynthesis and protein acetylation were predominantly observed. There was also evidence of osmotic dysregulation during acid challenge. Modulation of these systems might confer bacteria with resistance to stressors encountered during infection of organisms or food contamination. The study presented here with other related researches may help to explain further, how pathogenic bacteria survive and tolerate the environmental stresses.

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Acid stress induces differential accumulation of metabolites inEscherichia coliO26:H11

Cited by 31 publications

References 41 publications

A Comparative Analysis of the Metabolomic Response of Electron Beam Inactivated E. coli O26:H11 and Salmonella Typhimurium ATCC 13311

A Comparative Analysis of the Metabolomic Response of Electron Beam Inactivated E. coli O26:H11 and Salmonella Typhimurium ATCC 13311

Robust desynchronization of Parkinson’s disease pathological oscillations by frequency modulation of delayed feedback deep brain stimulation

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