Humour reactions in crisis: a proximal analysis of Chinese posts on Sina Weibo in reaction to the salt panicof March 2011

This paper presents an analysis of humour use in Sina Weibo in reaction to the Chinese salt panic, which occurred as a result of the Fukushima disaster in March 2011. Basing the investigation on the humour Proximal Distancing Theory (PDT), and utilising a dataset from Sina Weibo in 2011, an examination of humour reactions is performed to identify the proximal spread of humourous Weibo posts in relation to the consequent salt panic in China. As a result of this method, we present a novel methodology for understanding humour reactions in social media, and provide recommendations on how such a method could be applied to a variety of other social media, crises, cultural and spatial settings

An NGS-Independent Strategy for Proteome-Wide Identification of Single Amino Acid Polymorphisms by Mass Spectrometry

Detection of proteins containing single amino acid polymorphisms (SAPs) encoded by nonsynonymous SNPs (nsSNPs) can aid researchers in studying the functional significance of protein variants. Most proteogenomic approaches for large-scale SAPs mapping require construction of a sample-specific database containing protein variants predicted from the next-generation sequencing (NGS) data. Searching shotgun proteomic data sets against these NGS-derived databases allowed for identification of SAP peptides, thus validating the proteome-level sequence variation. Contrary to the conventional approaches, our study presents a novel strategy for proteome-wide SAP detection without relying on sample-specific NGS data. By searching a deep-coverage proteomic data set from an industrial thermotolerant yeast strain using our strategy, we identified 337 putative SAPs compared to the reference genome. Among the SAP peptides identified with stringent criteria, 85.2% of SAP sites were validated using whole-genome sequencing data obtained for this organism, which indicates high accuracy of SAP identification with our strategy. More interestingly, for certain SAP peptides that cannot be predicted by genomic sequencing, we used synthetic peptide standards to verify expression of peptide variants in the proteome. Our study has provided a unique tool for proteogenomics to enable proteome-wide direct SAP identification and capture nongenetic protein variants not linked to nsSNPs

Distinct Proteome Remodeling of Industrial <i>Saccharomyces cerevisiae</i> in Response to Prolonged Thermal Stress or Transient Heat Shock

To gain a deep understanding of yeast-cell response to heat stress, multiple laboratory strains have been intensively studied via genome-wide expression analysis for the mechanistic dissection of classical heat-shock response (HSR). However, robust industrial strains of <i>Saccharomyces cerevisiae</i> have hardly been explored in global analysis for elucidation of the mechanism of thermotolerant response (TR) during fermentation. Herein, we employed data-independent acquisition and sequential window acquisition of all theoretical mass spectra based proteomic workflows to characterize proteome remodeling of an industrial strain, ScY01, responding to prolonged thermal stress or transient heat shock. By comparing the proteomic signatures of ScY01 in TR versus HSR as well as the HSR of the industrial strain versus a laboratory strain, our study revealed disparate response mechanisms of ScY01 during thermotolerant growth or under heat shock. In addition, through proteomics data-mining for decoding transcription factor interaction networks followed by validation experiments, we uncovered the functions of two novel transcription factors, Mig1 and Srb2, in enhancing the thermotolerance of the industrial strain. This study has demonstrated that accurate and high-throughput quantitative proteomics not only provides new insights into the molecular basis for complex microbial phenotypes but also pinpoints upstream regulators that can be targeted for improving the desired traits of industrial microorganisms

Distinct Proteome Remodeling of Industrial <i>Saccharomyces cerevisiae</i> in Response to Prolonged Thermal Stress or Transient Heat Shock

To gain a deep understanding of yeast-cell response to heat stress, multiple laboratory strains have been intensively studied via genome-wide expression analysis for the mechanistic dissection of classical heat-shock response (HSR). However, robust industrial strains of <i>Saccharomyces cerevisiae</i> have hardly been explored in global analysis for elucidation of the mechanism of thermotolerant response (TR) during fermentation. Herein, we employed data-independent acquisition and sequential window acquisition of all theoretical mass spectra based proteomic workflows to characterize proteome remodeling of an industrial strain, ScY01, responding to prolonged thermal stress or transient heat shock. By comparing the proteomic signatures of ScY01 in TR versus HSR as well as the HSR of the industrial strain versus a laboratory strain, our study revealed disparate response mechanisms of ScY01 during thermotolerant growth or under heat shock. In addition, through proteomics data-mining for decoding transcription factor interaction networks followed by validation experiments, we uncovered the functions of two novel transcription factors, Mig1 and Srb2, in enhancing the thermotolerance of the industrial strain. This study has demonstrated that accurate and high-throughput quantitative proteomics not only provides new insights into the molecular basis for complex microbial phenotypes but also pinpoints upstream regulators that can be targeted for improving the desired traits of industrial microorganisms