A strategy of novel molecular hydrogen-producing antioxidative auxiliary system improves virus production in cell bioreactor.

In the increasing demand for virus vaccines, large-scale production of safe, efficient, and economical viral antigens has become a significant challenge. High-cell-density manufacturing processes are the most commonly used to produce vaccine antigens and protein drugs. However, the cellular stress response in large-scale cell culture may directly affect host cell growth and metabolism, reducing antigen production and increasing production costs. This study provided a novel strategy of the antioxidant auxiliary system (AAS) to supply molecular hydrogen (H2) into the cell culture media via proton exchange membrane (PEM) electrolysis. Integrated with a high-density cell bioreactor, the AAS aims to alleviate cellular stress response and increase viral vaccine production. In the results, the AAS stably maintained H2 concentration in media even in the high-air exposure tiding cell bioreactor. H2 treatment was shown safe to cell culture and effectively alleviated oxidative stress. In two established virus cultures models, bovine epidemic fever virus (BEFV) and porcine circovirus virus type 2 (PCV-2), were employed to verify the efficacy of AAS. The virus yield was increased by 3.7 and 2.5 folds in BEFV and PCV-2 respectively. In conclusion, the AAS-connected bioreactor effectively alleviated cellular oxidative stress and enhanced virus production in high-density cell culture.

A Senescence-Like Cellular Response Inhibits Bovine Ephemeral Fever Virus Proliferation.

During industrial-scale production of viruses for vaccine manufacturing, anti-viral response of host cells can dampen maximal viral antigen yield. In addition to interferon responses, many other cellular responses, such as the AMPK signaling pathway or senescence-like response may inhibit or slow down virus amplification in the cell culture system. In this study, we first performed a Gene Set Enrichment Analysis of the whole-genome mRNA transcriptome and found a senescence-like cellular response in BHK-21 cells when infected with bovine ephemeral fever virus (BEFV). To demonstrate that this senescence-like state may reduce virus growth, BHK-21 subclones showing varying degrees of a senescence-like state were infected with BEFV. The results showed that the BHK-21 subclones showing high senescence staining could inhibit BEFV replication while low senescence-staining subclones are permissive to virus replication. Using a different approach, a senescence-like state was induced in BHK-21 using a small molecule, camptothecin (CPT), and BEFV susceptibility were examined. The results showed that CPT-treated BHK-21 is more resistant to virus infection. Overall, these results indicate that a senescence-like response may be at play in BHK-21 upon virus infection. Furthermore, cell clone selection and modulating treatments using small molecules may be tools in countering anti-viral responses.

LipidSig: a web-based tool for lipidomic data analysis.

With the continuing rise of lipidomic studies, there is an urgent need for a useful and comprehensive tool to facilitate lipidomic data analysis. The most important features making lipids different from general metabolites are their various characteristics, including their lipid classes, double bonds, chain lengths, etc. Based on these characteristics, lipid species can be classified into different categories and, more interestingly, exert specific biological functions in a group. In an effort to simplify lipidomic analysis workflows and enhance the exploration of lipid characteristics, we have developed a highly flexible and user-friendly web server called LipidSig. It consists of five sections, namely, Profiling, Differential Expression, Correlation, Network and Machine Learning, and evaluates lipid effects on cellular or disease phenotypes. One of the specialties of LipidSig is the conversion between lipid species and characteristics according to a user-defined characteristics table. This function allows for efficient data mining for both individual lipids and subgroups of characteristics. To expand the server's practical utility, we also provide analyses focusing on fatty acid properties and multiple characteristics. In summary, LipidSig is expected to help users identify significant lipid-related features and to advance the field of lipid biology. The LipidSig webserver is freely available at http://chenglab.cmu.edu.tw/lipidsig.

NMD Classifier: A reliable and systematic classification tool for nonsense-mediated decay events.

Nonsense-mediated decay (NMD) degrades mRNAs that include premature termination codons to avoid the translation and accumulation of truncated proteins. This mechanism has been found to participate in gene regulation and a wide spectrum of biological processes. However, the evolutionary and regulatory origins of NMD-targeted transcripts (NMDTs) have been less studied, partly because of the complexity in analyzing NMD events. Here we report NMD Classifier, a tool for systematic classification of NMD events for either annotated or de novo assembled transcripts. This tool is based on the assumption of minimal evolution/regulation-an event that leads to the least change is the most likely to occur. Our simulation results indicate that NMD Classifier can correctly identify an average of 99.3% of the NMD-causing transcript structural changes, particularly exon inclusions/exclusions and exon boundary alterations. Researchers can apply NMD Classifier to evolutionary and regulatory studies by comparing NMD events of different biological conditions or in different organisms.

Non-small-cell lung cancer cells combat epidermal growth factor receptor tyrosine kinase inhibition through immediate adhesion-related responses.

BACKGROUND: Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs), such as gefitinib, erlotinib, and afatinib, have greatly improved treatment efficacy in non-small cell lung cancer (NSCLC) patients with drug-sensitive EGFR mutations. However, in some TKI responders, the benefits of such targeted therapies are limited by the rapid development of resistance, and strategies to overcome this resistance are urgently needed. Studies of drug resistance in cancer cells typically involve long term in vitro induction to obtain stably acquired drug-resistant cells followed by elucidation of resistance mechanisms, but the immediate responses of cancer cells upon drug treatment have been ignored. The aim of this study was to investigate the immediate responses of NSCLC cells upon treatment with EGFR TKIs. RESULTS: Both NSCLC cells, ie, PC9 and H1975, showed immediate enhanced adhesion-related responses as an apoptosis-countering mechanism upon first-time TKI treatment. By gene expression and pathway analysis, adhesion-related pathways were enriched in gefitinib-treated PC9 cells. Pathway inhibition by small-hairpin RNAs or small-molecule drugs revealed that within hours of EGFR TKI treatment, NSCLC cells used adhesion-related responses to combat the drugs. Importantly, we show here that the Src family inhibitor, dasatinib, dramatically inhibits cell adhesion-related response and greatly enhances the cell-killing effects of EGFR TKI (gefitinib for the PC9 cells; afatinib for the H1975 cells) in NSCLC cells, which would otherwise escape the TKI-induced apoptosis. CONCLUSION: Results from this study indicate that NSCLC cells can employ the adhesion response as a survival pathway to survive under EGFR-targeted therapy. Simultaneous targeting of EGFR signaling and adhesion pathways would further boost the efficacy of EGFR-targeted therapy in NSCLC.

NF-κB-driven suppression of FOXO3a contributes to EGFR mutation-independent gefitinib resistance.

Therapy with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (EGFR-TKIs, such as gefitinib or erlotinib) significantly prolongs survival time for patients with tumors harboring an activated mutation on EGFR; however, up to 40% of lung cancer patients exhibit acquired resistance to EGFR-TKIs with an unknown mechanism. FOXO3a, a transcription factor of the forkhead family, triggers apoptosis, but the mechanistic details involved in EGFR-TKI resistance and cancer stemness remain largely unclear. Here, we observed that a high level of FOXO3a was correlated with EGFR mutation-independent EGFR-TKI sensitivity, the suppression of cancer stemness, and better progression-free survival in lung cancer patients. The suppression of FOXO3a obviously increased gefitinib resistance and enhanced the stem-like properties of lung cancer cells; consistent overexpression of FOXO3a in gefitinib-resistant lung cancer cells reduced these effects. Moreover, we identified that miR-155 targeted the 3'UTR of FOXO3a and was transcriptionally regulated by NF-κB, leading to repressed FOXO3a expression and increased gefitinib resistance, as well as enhanced cancer stemness of lung cancer in vitro and in vivo. Our findings indicate that FOXO3a is a significant factor in EGFR mutation-independent gefitinib resistance and the stemness of lung cancer, and suggest that targeting the NF-κB/miR-155/FOXO3a pathway has potential therapeutic value in lung cancer with the acquisition of resistance to EGFR-TKIs.

Functional divergence and convergence between the transcript network and gene network in lung adenocarcinoma.

INTRODUCTION: Alternative RNA splicing is a critical regulatory mechanism during tumorigenesis. However, previous oncological studies mainly focused on the splicing of individual genes. Whether and how transcript isoforms are coordinated to affect cellular functions remain underexplored. Also of great interest is how the splicing regulome cooperates with the transcription regulome to facilitate tumorigenesis. The answers to these questions are of fundamental importance to cancer biology. RESULTS: Here, we report a comparative study between the transcript-based network (TN) and the gene-based network (GN) derived from the transcriptomes of paired tumor-normal tissues from 77 lung adenocarcinoma patients. We demonstrate that the two networks differ significantly from each other in terms of patient clustering and the number and functions of network modules. Interestingly, the majority (89.5%) of multi-transcript genes have their transcript isoforms distributed in at least two TN modules, suggesting regulatory and functional divergences between transcript isoforms. Furthermore, TN and GN modules share only50%-60% of their biological functions. TN thus appears to constitute a regulatory layer separate from GN. Nevertheless, our results indicate that functional convergence and divergence both occur between TN and GN, implying complex interactions between the two regulatory layers. Finally, we report that the expression profiles of module members in both TN and GN shift dramatically yet concordantly during tumorigenesis. The mechanisms underlying this coordinated shifting remain unclear yet are worth further explorations. CONCLUSION: We show that in lung adenocarcinoma, transcript isoforms per se are coordinately regulated to conduct biological functions not conveyed by the network of genes. However, the two networks may interact closely with each other by sharing the same or related biological functions. Unraveling the effects and mechanisms of such interactions will significantly advance our understanding of this deadly disease.

Triple-layer dissection of the lung adenocarcinoma transcriptome: regulation at the gene, transcript, and exon levels.

Lung adenocarcinoma is one of the most deadly human diseases. However, the molecular mechanisms underlying this disease, particularly RNA splicing, have remained underexplored. Here, we report a triple-level (gene-, transcript-, and exon-level) analysis of lung adenocarcinoma transcriptomes from 77 paired tumor and normal tissues, as well as an analysis pipeline to overcome genetic variability for accurate differentiation between tumor and normal tissues. We report three major results. First, more than 5,000 differentially expressed transcripts/exonic regions occur repeatedly in lung adenocarcinoma patients. These transcripts/exonic regions are enriched in nicotine metabolism and ribosomal functions in addition to the pathways enriched for differentially expressed genes (cell cycle, extracellular matrix receptor interaction, and axon guidance). Second, classification models based on rationally selected transcripts or exonic regions can reach accuracies of 0.93 to 1.00 in differentiating tumor from normal tissues. Of the 28 selected exonic regions, 26 regions correspond to alternative exons located in such regulators as tumor suppressor (GDF10), signal receptor (LYVE1), vascular-specific regulator (RASIP1), ubiquitination mediator (RNF5), and transcriptional repressor (TRIM27). Third, classification systems based on 13 to 14 differentially expressed genes yield accuracies near 100%. Genes selected by both detection methods include C16orf59, DAP3, ETV4, GABARAPL1, PPAR, RADIL, RSPO1, SERTM1, SRPK1, ST6GALNAC6, and TNXB. Our findings imply a multilayered lung adenocarcinoma regulome in which transcript-/exon-level regulation may be dissociated from gene-level regulation. Our described method may be used to identify potentially important genes/transcripts/exonic regions for the tumorigenesis of lung adenocarcinoma and to construct accurate tumor vs. normal classification systems for this disease.

The evolution of the coding exome of the Arabidopsis species--the influences of DNA methylation, relative exon position, and exon length.

BACKGROUND: The evolution of the coding exome is a major driving force of functional divergence both between species and between protein isoforms. Exons at different positions in the transcript or in different transcript isoforms may (1) mutate at different rates due to variations in DNA methylation level; and (2) serve distinct biological roles, and thus be differentially targeted by natural selection. Furthermore, intrinsic exonic features, such as exon length, may also affect the evolution of individual exons. Importantly, the evolutionary effects of these intrinsic/extrinsic features may differ significantly between animals and plants. Such inter-lineage differences, however, have not been systematically examined. RESULTS: Here we examine how DNA methylation at CpG dinucleotides (CpG methylation), in the context of intrinsic exonic features (exon length and relative exon position in the transcript), influences the evolution of coding exons of Arabidopsis thaliana. We observed fairly different evolutionary patterns in A. thaliana as compared with those reported for animals. Firstly, the mutagenic effect of CpG methylation is the strongest for internal exons and the weakest for first exons despite the stringent selective constraints on the former group. Secondly, the mutagenic effect of CpG methylation increases significantly with length in first exons but not in the other two exon groups. Thirdly, CpG methylation level is correlated with evolutionary rates (dS, dN, and the dN/dS ratio) with markedly different patterns among the three exon groups. The correlations are generally positive, negative, and mixed for first, last, and internal exons, respectively. Fourthly, exon length is a CpG methylation-independent indicator of evolutionary rates, particularly for dN and the dN/dS ratio in last and internal exons. Finally, the evolutionary patterns of coding exons with regard to CpG methylation differ significantly between Arabidopsis species and mammals. CONCLUSIONS: Our results suggest that intrinsic features, including relative exonic position in the transcript and exon length, play an important role in the evolution of A. thaliana coding exons. Furthermore, CpG methylation is correlated with exonic evolutionary rates differentially between A. thaliana and animals, and may have served different biological roles in the two lineages.