Large-Scale Identification of Bacteria–Host Crosstalk by Affinity Chromatography: Capturing the Interactions ofStreptococcus suisProteins with Host Cells

2011 ◽  
Vol 10 (11) ◽  
pp. 5163-5174 ◽  
Author(s):  
Bo Chen ◽  
Anding Zhang ◽  
Zhongmin Xu ◽  
Ran Li ◽  
Huanchun Chen ◽  
...  
2018 ◽  
Vol 115 (34) ◽  
pp. E7905-E7913 ◽  
Author(s):  
Xingcheng Lin ◽  
Jeffrey K. Noel ◽  
Qinghua Wang ◽  
Jianpeng Ma ◽  
José N. Onuchic

Influenza hemagglutinin (HA) mediates viral entry into host cells through a large-scale conformational rearrangement at low pH that leads to fusion of the viral and endosomal membranes. Crystallographic and biochemical data suggest that a loop-to-coiled-coil transition of the B-loop region of HA is important for driving this structural rearrangement. However, the microscopic picture for this proposed “spring-loaded” movement is missing. In this study, we focus on understanding the transition of the B loop and perform a set of all-atom molecular dynamics simulations of the full B-loop trimeric structure with the CHARMM36 force field. The free-energy profile constructed from our simulations describes a B loop that stably folds half of the postfusion coiled coil in tens of microseconds, but the full coiled coil is unfavorable. A buried hydrophilic residue, Thr59, is implicated in destabilizing the coiled coil. Interestingly, this conserved threonine is the only residue in the B loop that strictly differentiates between the group 1 and 2 HA molecules. Microsecond-scale constant temperature simulations revealed that kinetic traps in the structural switch of the B loop can be caused by nonnative, intramonomer, or intermonomer β-sheets. The addition of the A helix stabilized the postfusion state of the B loop, but introduced the possibility for further β-sheet structures. Overall, our results do not support a description of the B loop in group 2 HAs as a stiff spring, but, rather, it allows for more structural heterogeneity in the placement of the fusion peptides during the fusion process.


BMC Biology ◽  
2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Sung-Joon Park ◽  
Satoru Onizuka ◽  
Masahide Seki ◽  
Yutaka Suzuki ◽  
Takanori Iwata ◽  
...  

Abstract Background Microbial contamination poses a major difficulty for successful data analysis in biological and biomedical research. Computational approaches utilizing next-generation sequencing (NGS) data offer promising diagnostics to assess the presence of contaminants. However, as host cells are often contaminated by multiple microorganisms, these approaches require careful attention to intra- and interspecies sequence similarities, which have not yet been fully addressed. Results We present a computational approach that rigorously investigates the genomic origins of sequenced reads, including those mapped to multiple species that have been discarded in previous studies. Through the analysis of large-scale synthetic and public NGS samples, we estimate that 1000–100,000 contaminating microbial reads are detected per million host reads sequenced by RNA-seq. The microbe catalog we established included Cutibacterium as a prevalent contaminant, suggesting that contamination mostly originates from the laboratory environment. Importantly, by applying a systematic method to infer the functional impact of contamination, we revealed that host-contaminant interactions cause profound changes in the host molecular landscapes, as exemplified by changes in inflammatory and apoptotic pathways during Mycoplasma infection of lymphoma cells. Conclusions We provide a computational method for profiling microbial contamination on NGS data and suggest that sources of contamination in laboratory reagents and the experimental environment alter the molecular landscape of host cells leading to phenotypic changes. These findings reinforce the concept that precise determination of the origins and functional impacts of contamination is imperative for quality research and illustrate the usefulness of the proposed approach to comprehensively characterize contamination landscapes.


2011 ◽  
Vol 39 (3) ◽  
pp. 719-723 ◽  
Author(s):  
Zharain Bawa ◽  
Charlotte E. Bland ◽  
Nicklas Bonander ◽  
Nagamani Bora ◽  
Stephanie P. Cartwright ◽  
...  

Membrane proteins are drug targets for a wide range of diseases. Having access to appropriate samples for further research underpins the pharmaceutical industry's strategy for developing new drugs. This is typically achieved by synthesizing a protein of interest in host cells that can be cultured on a large scale, allowing the isolation of the pure protein in quantities much higher than those found in the protein's native source. Yeast is a popular host as it is a eukaryote with similar synthetic machinery to that of the native human source cells of many proteins of interest, while also being quick, easy and cheap to grow and process. Even in these cells, the production of human membrane proteins can be plagued by low functional yields; we wish to understand why. We have identified molecular mechanisms and culture parameters underpinning high yields and have consolidated our findings to engineer improved yeast host strains. By relieving the bottlenecks to recombinant membrane protein production in yeast, we aim to contribute to the drug discovery pipeline, while providing insight into translational processes.


2020 ◽  
Author(s):  
Fabio González-Arias ◽  
Tyler Reddy ◽  
John E. Stone ◽  
Jodi A. Hadden-Perilla ◽  
Juan R. Perilla

AbstractEnveloped viruses infect host cells via fusion of their viral envelope with the plasma membrane. Upon cell entry, viruses gain access to all the macromolecular machinery necessary to replicate, assemble, and bud their progeny from the infected cell. By employing molecular dynamics simulations to characterize the dynamical and chemical-physical properties of viral envelopes, researchers can gain insights into key determinants of viral infection and propagation. Here, the Frontera supercomputer is leveraged for large-scale analysis of authentic viral envelopes, whose lipid compositions are complex and realistic. VMD with support for MPI is employed on the massive parallel computer to overcome previous computational limitations and enable investigation into virus biology at an unprecedented scale. The modeling and analysis techniques applied to authentic viral envelopes at two levels of particle resolution are broadly applicable to the study of other viruses, including the novel coronavirus that causes COVID-19. A framework for carrying out scalable analysis of multi-million particle MD simulation trajectories on Frontera is presented, expanding the the utility of the machine in humanity’s ongoing fight against infectious disease.


Data ◽  
2021 ◽  
Vol 6 (9) ◽  
pp. 99
Author(s):  
Rafida Razali ◽  
Vijay Kumar Subbiah ◽  
Cahyo Budiman

The SARS-CoV-2 coronavirus expresses two essential proteases: firstly, the 3Chymotrypsin-like protease (3CLpro) or main protease (Mpro), and secondly, the papain-like protease (PLpro), both of which are considered as viable drug targets for the inhibition of viral replication. In order to perform drug discovery assays for SARS-CoV-2, it is imperative that efficient methods are established for the production and purification of 3CLpro and PLpro of SARS-CoV-2, designated as 3CLpro-CoV2 and PLpro-CoV2, respectively. This article expands the data collected in the attempts to express SARS-CoV-2 proteases under different conditions and purify them under single-step chromatography. Data showed that the use of E. coli BL21(DE3) strain was sufficient to express 3CLpro-CoV2 in a fully soluble form. Nevertheless, the single affinity chromatography step was only applicable for 3CLpro-CoV2 expressed at 18 °C, with a yield and purification fold of 92% and 49, respectively. Meanwhile, PLpro-CoV2 was successfully expressed in a fully soluble form in either BL21(DE3) or BL21-CodonPlus(DE3) strains. In contrast, the single affinity chromatography step was only applicable for PLpro-CoV2 expressed using E. coli BL21-CodonPlus(DE3) at 18 or 37 °C, with a yield and purification fold of 86% (18 °C) or 83.36% (37 °C) and 112 (18 °C) or 71 (37 °C), respectively. The findings provide a guide for optimizing the production of SARS-CoV-2 proteases of E. coli host cells.


Author(s):  
Cardon Tristan ◽  
Isabelle Fournier ◽  
Salzet Michel

Conventionally, eukaryotic mRNAs were thought to be monocistronic, leading to the translation of a single protein. However, large-scale proteomics has led to a massive identification of proteins translated from mRNAs of alternative ORF (AltORFs), in addition to the predicted proteins issued from the reference ORF or from ncRNAs. These alternative proteins (AltProts) are not represented in the conventional protein databases and this “Ghost proteome” was not considered until recently. Some of these proteins are functional and there is growing evidence that they are involved in central functions in physiological and physiopathological context. Based on our experience with AltProts we have got interested in finding out their involvement in development of the SARS-CoV-2 virus, responsible for the 2020 Covid-19 outbreak. Thus, we have scrutinized the recently published data by Krogan and coworkers (2020) on the SARS-CoV-2 interactome with host cells by co-IP in the perspective of drug repurposing. The initial work has revealed the interaction between 332 human cellular RefProts with the 27 viral proteins. Re-interrogation of this data using 23 viral targets and including AltProts, followed by enrichment of the interaction networks, leads to identify 218 RefProts (in common to initial study) plus 56 AltProts involved in 93 interactions. This demonstrates the necessity to take into account the Ghost proteome for discovering new therapeutic targets and establish new therapeutic strategies. Missing the ghost proteome in the drug metabolism and pharmacokinetic (DMPK) drug development pipeline will certainly be a major limitation to the establishment of efficient therapies.


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