Protein turnover analysis in <i>Salmonella</i> Typhimurium during infection by dynamic SILAC, Topograph, and quantitative proteomics

Wang, Zhe; Han, Qiang‐Qiang; Zhou, Maotian; Chen, Xi; Guo, Lin

doi:10.1002/jobm.201500315

Cited by 8 publications

(4 citation statements)

References 64 publications

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“…After elution, the immunoprecipitates were in-gel digested and analyzed by mass spectrometry as described by Wang et al [ 61 ] with minor modification. In brief, the total protein was loaded to the gel and SDS-PAGE was conducted.…”

Section: Methodsmentioning

confidence: 99%

Functional divergence of chloroplast Cpn60α subunits during Arabidopsis embryo development

Zou

Ren

et al. 2017

PLoS Genet

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Chaperonins are a class of molecular chaperones that assist in the folding and assembly of a wide range of substrates. In plants, chloroplast chaperonins are composed of two different types of subunits, Cpn60α and Cpn60β, and duplication of Cpn60α and Cpn60β genes occurs in a high proportion of plants. However, the importance of multiple Cpn60α and Cpn60β genes in plants is poorly understood. In this study, we found that loss-of-function of CPNA2 (AtCpn60α2), a gene encoding the minor Cpn60α subunit in Arabidopsis thaliana, resulted in arrested embryo development at the globular stage, whereas the other AtCpn60α gene encoding the dominant Cpn60α subunit, CPNA1 (AtCpn60α1), mainly affected embryonic cotyledon development at the torpedo stage and thereafter. Further studies demonstrated that CPNA2 can form a functional chaperonin with CPNB2 (AtCpn60β2) and CPNB3 (AtCpn60β3), while the functional partners of CPNA1 are CPNB1 (AtCpn60β1) and CPNB2. We also revealed that the functional chaperonin containing CPNA2 could assist the folding of a specific substrate, KASI (β-ketoacyl-[acyl carrier protein] synthase I), and that the KASI protein level was remarkably reduced due to loss-of-function of CPNA2. Furthermore, the reduction in the KASI protein level was shown to be the possible cause for the arrest of cpna2 embryos. Our findings indicate that the two Cpn60α subunits in Arabidopsis play different roles during embryo development through forming distinct chaperonins with specific AtCpn60β to assist the folding of particular substrates, thus providing novel insights into functional divergence of Cpn60α subunits in plants.

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Section: Methodsmentioning

confidence: 99%

Functional divergence of chloroplast Cpn60α subunits during Arabidopsis embryo development

Zou

Ren

et al. 2017

PLoS Genet

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“…The same data set gives a maximum value of k dE of 3.9 × 10 −4 s −1 . For prokaryotes, values larger than this by an order of magnitude are possible [89]. Rate constants for enzyme-substrate association (k 1 ) can be as low as 10 3 M −1 s −1 [90,91].…”

Section: Elimination Of the Fastest Relaxation Modementioning

confidence: 99%

Perturbative-Iterative Computation of Inertial Manifolds of Systems of Delay-Differential Equations with Small Delays

Roussel

2020

Algorithms

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Delay-differential equations belong to the class of infinite-dimensional dynamical systems. However, it is often observed that the solutions are rapidly attracted to smooth manifolds embedded in the finite-dimensional state space, called inertial manifolds. The computation of an inertial manifold yields an ordinary differential equation (ODE) model representing the long-term dynamics of the system. Note in particular that any attractors must be embedded in the inertial manifold when one exists, therefore reducing the study of these attractors to the ODE context, for which methods of analysis are well developed. This contribution presents a study of a previously developed method for constructing inertial manifolds based on an expansion of the delayed term in small powers of the delay, and subsequent solution of the invariance equation by the Fraser functional iteration method. The combined perturbative-iterative method is applied to several variations of a model for the expression of an inducible enzyme, where the delay represents the time required to transcribe messenger RNA and to translate that RNA into the protein. It is shown that inertial manifolds of different dimensions can be computed. Qualitatively correct inertial manifolds are obtained. Among other things, the dynamics confined to computed inertial manifolds display Andronov–Hopf bifurcations at similar parameter values as the original DDE model.

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“…Identification of newly synthesized proteins, possible through a “click chemistry” labeling strategy (Dieterich et al , ), led to the discovery of nascent proteins synthesized at axon terminals during infection by neurotropic viruses (Koyuncu et al , ). Changes in protein turnover rates of Salmonella (Wang et al , ) have been measured using dynamic SILAC (Claydon & Beynon, ) to identify how this pathogen regulates its proteome as it invades the host. Viruses can also trigger protein degradation using proteases encoded in their genome.…”

Section: Proteomics: a Powerful Tool For Studying Of Infectious Diseasesmentioning

confidence: 99%

Proteomics and integrative omic approaches for understanding host–pathogen interactions and infectious diseases

Beltran

Federspiel

Sheng

et al. 2017

Molecular Systems Biology

169

119

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Organisms are constantly exposed to microbial pathogens in their environments. When a pathogen meets its host, a series of intricate intracellular interactions shape the outcome of the infection. The understanding of these host–pathogen interactions is crucial for the development of treatments and preventive measures against infectious diseases. Over the past decade, proteomic approaches have become prime contributors to the discovery and understanding of host–pathogen interactions that represent anti‐ and pro‐pathogenic cellular responses. Here, we review these proteomic methods and their application to studying viral and bacterial intracellular pathogens. We examine approaches for defining spatial and temporal host–pathogen protein interactions upon infection of a host cell. Further expanding the understanding of proteome organization during an infection, we discuss methods that characterize the regulation of host and pathogen proteomes through alterations in protein abundance, localization, and post‐translational modifications. Finally, we highlight bioinformatic tools available for analyzing such proteomic datasets, as well as novel strategies for integrating proteomics with other omic tools, such as genomics, transcriptomics, and metabolomics, to obtain a systems‐level understanding of infectious diseases.

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Protein turnover analysis in Salmonella Typhimurium during infection by dynamic SILAC, Topograph, and quantitative proteomics

Cited by 8 publications

References 64 publications

Functional divergence of chloroplast Cpn60α subunits during Arabidopsis embryo development

Functional divergence of chloroplast Cpn60α subunits during Arabidopsis embryo development

Perturbative-Iterative Computation of Inertial Manifolds of Systems of Delay-Differential Equations with Small Delays

Proteomics and integrative omic approaches for understanding host–pathogen interactions and infectious diseases

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