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The black soldier fly (BSF), Hermetia illucen s, has the potential to serve as a valuable resource for waste bioconversion due to the ability of the larvae to thrive in a microbial-rich environment. Being an ecological decomposer, the survival of BSF larvae (BSFL) relies on developing an efficient defense system. Cathepsin L (CTSL) is a cysteine protease that plays roles in physiological and pathological processes. In this study, the full-length of CTSL was obtained from BSF. The 1,020-bp open reading frame encoded a preprotein of 339 amino acids with a predicted molecular weight of 32 kDa. The pro-domain contained the conserved ERFNIN, GNYD, and GCNGG motifs, which are all characteristic of CTSL. Homology revealed that the deduced amino acid sequence of BSF CTSL shared 74.22–72.99% identity with Diptera flies. Immunohistochemical (IHC) analysis showed the CTSL was predominantly localized in the gut, especially in the midgut. The mRNA expression of CTSL in different larval stages was analyzed by quantitative real-time PCR (RT-qPCR), which revealed that CTSL was expressed in the second to sixth instar, with the highest expression in the fifth instar. Following an immune challenge in vivo using Escherichia coli ( E . coli ), CTSL mRNA was significantly up-regulated at 6 h post-stimulation. The Z-Phe-Arg-AMC was gradually cleaved by the BSFL extract after 3 h post-stimulation. These results shed light on the potential role of CTSL in the defense mechanism that helps BSFL to survive against pathogens in a microbial-rich environment.

Drug repurposing has become an increasingly attractive approach to drug development owing to the ever-growing cost of new drug discovery and frequent withdrawal of successful drugs caused by side effect issues. Here, we devised Functional Module Connectivity Map (FMCM) for the discovery of repurposed drug compounds for systems treatment of complex diseases, and applied it to colorectal adenocarcinoma. FMCM used multiple functional gene modules to query the Connectivity Map (CMap). The functional modules were built around hub genes identified, through a gene selection by trend-of-disease-progression (GSToP) procedure, from condition-specific gene-gene interaction networks constructed from sets of cohort gene expression microarrays. The candidate drug compounds were restricted to drugs exhibiting predicted minimal intracellular harmful side effects. We tested FMCM against the common practice of selecting drugs using a genomic signature represented by a single set of individual genes to query CMap (IGCM), and found FMCM to have higher robustness, accuracy, specificity, and reproducibility in identifying known anti-cancer agents. Among the 46 drug candidates selected by FMCM for colorectal adenocarcinoma treatment, 65% had literature support for association with anti-cancer activities, and 60% of the drugs predicted to have harmful effects on cancer had been reported to be associated with carcinogens/immune suppressors. Compounds were formed from the selected drug candidates where in each compound the component drugs collectively were beneficial to all the functional modules while no single component drug was harmful to any of the modules. In cell viability tests, we identified four candidate drugs: GW-8510, etacrynic acid, ginkgolide A, and 6-azathymine, as having high inhibitory activities against cancer cells. Through microarray experiments we confirmed the novel functional links predicted for three candidate drugs: phenoxybenzamine (broad effects), GW-8510 (cell cycle), and imipenem (immune system). We believe FMCM can be usefully applied to repurposed drug discovery for systems treatment of other types of cancer and other complex diseases.

Background In view of the limited knowledge of plasma biomarkers relating to cancer resistance to radiotherapy, we have set up screening, training and testing stages to investigate the microRNAs (miRNAs) expression profile in plasma to predict between the poor responsive and responsive groups after 6 months of radiotherapy. Methods Plasma was collected prior to and after radiotherapy, and the microRNA profiles were analyzed by quantitative reverse transcription polymerase chain reaction (qRT-PCR) arrays. Candidate miRNAs were validated by single qRT-PCR assays from the training and testing set. The classifier for ancillary prognosis was developed by multiple logistic regression analysis to correlate the ratios of miRNAs expression levels with clinical data. Results We revealed that eight miRNAs expressions had significant changes after radiotherapy and the expression levels of miR-374a-5p, miR-342-5p and miR-519d-3p showed significant differences between the responsive and poor responsive groups in the pre-radiotherapy samples. The Kaplan–Meier curve analysis also showed that low miR-342-5p and miR-519d-3p expressions were associated with worse prognosis. Our results revealed two miRNA classifiers from the pre- and post-radiotherapy samples to predict radiotherapy response with area under curve values of 0.8923 and 0.9405. Conclusions The expression levels of miR-374a-5p, miR-342-5p and miR-519d-3p in plasma are associated with radiotherapy responses. Two miRNA classifiers could be developed as a potential non-invasive ancillary tool for predicting patient response to radiotherapy.

[This corrects the article DOI: 10.1371/journal.pone.0298338.].

The black soldier fly (BSF), Hermetia illucens, has the potential to serve as a valuable resource for waste bioconversion due to the ability of the larvae to thrive in a microbial-rich environment. Being an ecological decomposer, the survival of BSF larvae (BSFL) relies on developing an efficient defense system. Cathepsin L (CTSL) is a cysteine protease that plays roles in physiological and pathological processes. In this study, the full-length of CTSL was obtained from BSF. The 1,020-bp open reading frame encoded a preprotein of 339 amino acids with a predicted molecular weight of 32 kDa. The pro-domain contained the conserved ERFNIN, GNYD, and GCNGG motifs, which are all characteristic of CTSL. Homology revealed that the deduced amino acid sequence of BSF CTSL shared 74.22-72.99% identity with Diptera flies. Immunohistochemical (IHC) analysis showed the CTSL was predominantly localized in the gut, especially in the midgut. The mRNA expression of CTSL in different larval stages was analyzed by quantitative real-time PCR (RT-qPCR), which revealed that CTSL was expressed in the second to sixth instar, with the highest expression in the fifth instar. Following an immune challenge in vivo using Escherichia coli (E. coli), CTSL mRNA was significantly up-regulated at 6 h post-stimulation. The Z-Phe-Arg-AMC was gradually cleaved by the BSFL extract after 3 h post-stimulation. These results shed light on the potential role of CTSL in the defense mechanism that helps BSFL to survive against pathogens in a microbial-rich environment.

Drug repurposing has become an increasingly attractive approach to drug development owing to the ever-growing cost of new drug discovery and frequent withdrawal of successful drugs caused by side effect issues. Here, we devised Functional Module Connectivity Map (FMCM) for the discovery of repurposed drug compounds for systems treatment of complex diseases, and applied it to colorectal adenocarcinoma. FMCM used multiple functional gene modules to query the Connectivity Map (CMap). The functional modules were built around hub genes identified, through a gene selection by trend-of-disease-progression (GSToP) procedure, from condition-specific gene-gene interaction networks constructed from sets of cohort gene expression microarrays. The candidate drug compounds were restricted to drugs exhibiting predicted minimal intracellular harmful side effects. We tested FMCM against the common practice of selecting drugs using a genomic signature represented by a single set of individual genes to query CMap (IGCM), and found FMCM to have higher robustness, accuracy, specificity, and reproducibility in identifying known anti-cancer agents. Among the 46 drug candidates selected by FMCM for colorectal adenocarcinoma treatment, 65% had literature support for association with anti-cancer activities, and 60% of the drugs predicted to have harmful effects on cancer had been reported to be associated with carcinogens/immune suppressors. Compounds were formed from the selected drug candidates where in each compound the component drugs collectively were beneficial to all the functional modules while no single component drug was harmful to any of the modules. In cell viability tests, we identified four candidate drugs: GW-8510, etacrynic acid, ginkgolide A, and 6-azathymine, as having high inhibitory activities against cancer cells. Through microarray experiments we confirmed the novel functional links predicted for three candidate drugs: phenoxybenzamine (broad effects), GW-8510 (cell cycle), and imipenem (immune system). We believe FMCM can be usefully applied to repurposed drug discovery for systems treatment of other types of cancer and other complex diseases.