Fighting Against Bacterial Lipopolysaccharide-Caused Infections through Molecular Dynamics Simulations: A Review

González-Fernández, Cristina; Basauri, Arantza; Fallanza, Marcos; Bringas, Eugenio; Oostenbrink, Chris; Ortiz, Inmaculada

doi:10.1021/acs.jcim.1c00613

Cited by 7 publications

(7 citation statements)

References 100 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Yet, the nature of distinct junction between the front line of the body defence (LDs) and bacteria is not well unknown (74). Furthermore, recent studies have revealed pathogen ability in the manipulation of the host membrane to facilitate pathogenic entry and recruitment of specific host lipids for the maintenance of favourable intracellular niche to augment their survival and proliferation (73, 74, 76).…”

Section: Resultsmentioning

confidence: 99%

dSeqSb: A systems biology approach to decipher dynamics of host-pathogen interactions using temporal dual RNA-seq data

Dinarvand

Koch

Mouiee

et al. 2022

Preprint

View full text Add to dashboard Cite

Infection triggers a dynamic cascade of reciprocal events between host and pathogen wherein the host activates complex mechanisms to recognise and kill pathogens while the pathogen adjusts its virulence and fitness to avoid eradication by the host. The interaction between the pathogen and the host results in large-scale changes in gene expression in both organisms. Dual RNA-seq, the simultaneous detection of host and pathogen transcripts, has become a leading approach to unravel complex molecular interactions between the host and the pathogen and is particularly informative for intracellular organisms. The amount of in vitro and in vivo dual RNA-seq data is rapidly growing which demands computational pipelines to effectively analyse such data. In particular, holistic, systems-level, and temporal analyses of dual RNA-seq data are essential to enable further insights into the host-pathogen transcriptional dynamics and potential interactions. Here, we developed an integrative network-driven bioinformatics pipeline, dRNASb, a systems biology-based computational pipeline to analyse temporal transcriptional clusters, incorporate molecular interaction networks (e.g., protein-protein interactions), identify topologically and functionally key transcripts in host and pathogen, and associate host and pathogen temporal transcriptome to decipher potential between-species interactions. The pipeline is applicable to various dual RNA-seq data from different species and experimental conditions. As a case study, we applied dRNASb to analyse temporal dual RNA-seq data of Salmonella-infected human cells, which enabled us to uncover genes contributing to the infection process and their potential functions and to identify potential host-pathogen interactions between host and pathogen genes. Overall, dRNASb has the potential to identify key genes involved in bacterial growth or host defence mechanisms for future uses as therapeutic targets.

show abstract

Section: Resultsmentioning

confidence: 99%

dSeqSb: A systems biology approach to decipher dynamics of host-pathogen interactions using temporal dual RNA-seq data

Dinarvand

Koch

Mouiee

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Yet, the nature of the distinct junction between the front line of the body defence (LDs) and bacteria is not well unknown [72]. Furthermore, recent studies have revealed pathogen ability in the manipulation of the host membrane to facilitate pathogenic entry and recruitment of specific host lipids for the maintenance of favourable intracellular niche to augment their survival and proliferation [71,72,74].…”

Section: Resultsmentioning

confidence: 99%

dRNASb: a systems biology approach to decipher dynamics of host-pathogen interactions using temporal dual RNA-seq data

et al. 2022

View full text Add to dashboard Cite

Infection triggers a dynamic cascade of reciprocal events between host and pathogen wherein the host activates complex mechanisms to recognise and kill pathogens while the pathogen often adjusts its virulence and fitness to avoid eradication by the host. The interaction between the pathogen and the host results in large-scale changes in gene expression in both organisms. Dual RNA-seq, the simultaneous detection of host and pathogen transcripts, has become a leading approach to unravelling complex molecular interactions between the host and the pathogen and is particularly informative for intracellular organisms. The amount of in vitro and in vivo dual RNA-seq data is rapidly growing, which demands computational pipelines to effectively analyse such data. In particular, holistic, systems-level, and temporal analyses of dual RNA-seq data are essential to enable further insights into the host-pathogen transcriptional dynamics and potential interactions. Here, we developed an integrative network-driven bioinformatics pipeline, dRNASb, a systems biology-based computational pipeline to analyse temporal transcriptional clusters, incorporate molecular interaction networks (e.g. protein-protein interactions), identify topologically and functionally key transcripts in host and pathogen, and associate host and pathogen temporal transcriptome to decipher potential between-species interactions. The pipeline is applicable to various dual RNA-seq data from different species and experimental conditions. As a case study, we applied dRNASb to analyse temporal dual RNA-seq data of Salmonella -infected human cells, which enabled us to uncover genes contributing to the infection process and their potential functions and to identify putative associations between host and pathogen genes during infection. Overall, dRNASb has the potential to identify key genes involved in bacterial growth or host defence mechanisms for future uses as therapeutic targets.

show abstract

“…A number of reviews have reported the amphiphatic structure of the LPS, namely the hydrophobic chains of fatty acids and hydrophilic rings of carbohydrates. ,− Lipid A, core saccharides, and the O-antigen are the three structural domains of the LPS (Figure ). Lipid A is a glycolipid, typically made up of a disaccharide of phosphorylated glucosamine and a backbone of fatty acids. , The endotoxicity of the LPS is attributed to lipid A .…”

Section: Introductionmentioning

confidence: 99%

Martini-3 Coarse-Grained Models for the Bacterial Lipopolysaccharide Outer Membrane of Escherichia coli

Vaiwala,

Ayappa

2023

J. Chem. Theory Comput.

View full text Add to dashboard Cite

The outer lipopolysaccharide (LPS) membrane of Gram-negative bacteria forms the main barrier for transport of antimicrobial molecules into the bacterial cell. In this study we develop coarse-grained models for the outer membrane of Escherichia coli in the Martini-3 framework. The coarse-grained model force field was parametrized and validated using all-atom simulations of symmetric membranes of lipid A and rough LPS as well as a complete asymmetric membrane of LPS with the Oantigen. The bonded parameters were obtained using an iterative refinement procedure with target bonded distributions obtained from all-atom simulations. The membrane thickness, area of the LPS, and density distributions for the different regions as well as the water and ion densities in Martini-3 simulations show excellent agreement with the all-atom data. Additionally the solvent accessible surface area for individual molecules in water was found to be in good agreement. The binding of calcium ions with phosphate and carboxylate moieties of LPS is accurately captured in the Martini-3 model, indicative of the integrity of the highly negatively charged LPS molecules in the outer membranes of Gram-negative bacteria. The melting transition of the coarse-grained lipid A membrane model was found to occur between 300 and 310 K, and the model captured variations in area per LPS, order parameter, and membrane thickness across the melting transition. Our study reveals that the proposed Martini-3 models for LPS are able to capture the physicochemical balance of the complex sugar architecture of the outer membrane of Escherichia coli. The coarse-grained models developed in this study would be useful for determining membrane protein interactions and permeation of potential antimicrobials through bacterial membranes at mesoscopic spatial and temporal scales.

show abstract

Fighting Against Bacterial Lipopolysaccharide-Caused Infections through Molecular Dynamics Simulations: A Review

Cited by 7 publications

References 100 publications

dSeqSb: A systems biology approach to decipher dynamics of host-pathogen interactions using temporal dual RNA-seq data

dSeqSb: A systems biology approach to decipher dynamics of host-pathogen interactions using temporal dual RNA-seq data

dRNASb: a systems biology approach to decipher dynamics of host-pathogen interactions using temporal dual RNA-seq data

Martini-3 Coarse-Grained Models for the Bacterial Lipopolysaccharide Outer Membrane of Escherichia coli

Contact Info

Product

Resources

About