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Psoriasis is a disease caused by genetics and immune system dysfunction, affecting the skin and joints. Toll-like receptors (TLRs) play an important role in triggering the innate immune response and controlling adaptive immunity. The role of TLR2 in the progression of psoriasis is not well understood.

To systematically elucidate how metal-binding antimicrobial peptide SIF4 exerts its antimicrobial activity by targeting DNA topoisomerase without destroying the cytoplasmic membrane, Escherichia coli was used as a model strain to investigate the binding mode of SIF4 with its genomic DNA and the impact of SIF4 on DNA topoisomerase I and II activities and intracellular nucleic acid biosynthesis. Results showed that SIF4 could bind to genomic DNA in a manner similar to ethidium bromide (EB) intercalation with strong inhibitory effect on topoisomerase I but weak effect on topoisomerase II, and catalyzed RNA transcription to exert antimicrobial activity by interfering with the unwinding of negative DNA supercoils and RNA polymerase binding. It was also found that the biosynthesis of intracellular DNA and RNA was inhibited to different degrees after 12 h treatment with SIF4, which exhibited a good dose-effect relationship. There was no significant difference in the amounts of intracellular DNA and RNA between the 1/2 minimum inhibitory concentration (MIC) group and the control group (P > 0.05), but there was a significant difference between the MIC and 2 MIC groups and the control group (P < 0.05). Our results may provide theoretical support for the application of SIF4 in the biocontrol of foodborne E. coli.

To explore how metal-binding antimicrobial peptide SIF4 kills foodborne Escherichia coli by targeting nucleic acid and protein in the cytoplasmic membrane without cytoplasmic membrane damage, the effect of SIF4 on intracellular nucleic acid biosynthesis was investigated, and fluorescence spectral analysis of the competition between SIF4 and ethidium bromide (EB) for binding to genomic DNA, ultraviolet (UV) spectral analysis of the interaction between SIF4 and genomic DNA, and the binding mode between SIF4 and genomic DNA were studied. Besides, the effect of SIF4 on intracellular protein biosynthesis was systematically evaluated. Results demonstrated that SIF4 could bind to E. coli genomic DNA through groove insertion and inhibit dose-dependently nucleic acid biosynthesis. Fluorescence spectral analysis showed that SIF4 could compete with EB for binding to genomic DNA through intercalation binding and electrostatic adsorption. UV spectroscopy showed that combination with SIF4 changed the molecular conformation of genomic DNA, but did not break its double strand structure. Circular dichroism (CD) spectroscopy showed that the base stacking force of genomic DNA was weakened, the double helix structure became loose, and the genomic DNA structure was changed from B to C configuration after combination with SIF4. In addition, SIF4 could significantly affect intracellular protein biosynthesis, and its inhibition effect was positively correlated with the treatment time and dose of SIF4. It is believed that SIF4 can enter the DNA groove through electrostatic adsorption or intercalation with genomic DNA, affecting DNA replication, RNA transcriptional biomass and protein translation to produce antimicrobial effect against Escherichia coli without cytoplasmic membrane damage. These results can provide support for the biocontrol of foodborne E. coli.

This study aimed to systematically elaborate on the inhibitory mechanism of metal-binding antimicrobial peptide SIF4 on the respiratory and energy metabolism of Escherichia coli. By analyzing changes in the metabolic activity, individual and synergistic respiratory inhibition rate, cytoplasmic membrane ion channel ATPase and intracellular ATP level of E. coli after being treated with SIF4, the effects of SIF4 on the cell metabolic activity, respiratory metabolic pathway, cytoplasmic membrane ion channel ATPase and intracellular ATP biosynthesis were studied. Results showed that the metabolic activity of E. coli decreased significantly with increasing dose of SIF4 (P < 0.05), and decreased by 70.41% in the 2 × minimal inhibitory concentration (MIC) group compared with the control group. SIF4 had good inhibitory effect on the respiration of Escherichia coli, with an inhibition rate of (19.387 ± 0.168)% and (25.222 ± 0.326)% at MIC and 2 × MIC, respectively. The synergistic respiratory inhibition rate of SIF4 combined with iodoacetic acid was the lowest ((19.982 ± 0.133)%), indicating that SIF4 could exhibit high antimicrobial activity mainly by inhibiting the glycolysis pathway of E. coli. The activities of cytoplasmic membrane ion channel Na+K+-ATPase and Ca2+Mg2+-ATPase decreased after treatment with SIF4, and this effect was positively correlated with SIF4 dose and treatment time, but weaker than that of the positive control Triton X-100. As SIF4 dose and treatment time increased, the intracellular ATP concentration decreased significantly, and after 12 h, the intracellular ATP concentration in the 2 × MIC group was significantly lower than that in the control group but higher than that in the positive control group (P < 0.05). All results confirmed that SIF4 could exhibit high antimicrobial activity against E. coli by interfering with respiratory metabolism, weakening cytoplasmic membrane ion channel ATPase activity and inhibiting the biosynthesis of intracellular ATP, which can provide theoretical support for the biocontrol of foodborne E. coli.

In the study of mineral resources evaluation model, the problem that the number of positive samples must be specified in the TSVM in the unlabeled samples.Then this article applied the improved algorithm to the evaluation of mineral resources, and the algorithm is TSVM based on BP neural network and BP-TSVM for short.The SVM is applied to studying the discernment and classification of labeling samples.We will annotate the plus or minus of unlabeled data within the boundary of already classified by utilizing BP neural network.The labeling samples as learned by SVM in the next iteration.The new algorithm will avoid decreased classified ability.TSVM can have more accurate estimates of number of plus of labeled data.Also, the number of training samples can reduce training times.The experimental result proves that compared with conventional SVM, TSVM and BP neural network the BP-TSVM is more accurate in evaluation of mineral resources.

Due to the complexity, aggressiveness, and heterogeneity of malignant melanoma, it is difficult to eradicate the whole tumor through conventional treatment. Herein, a strategy of metabolic engineering labeled anaerobic oncolytic bacteria (Clostridium butyricum) is demonstrated to achieve the ablation of melanoma. In this system, the metabolic substrate of C. butyricum d-alanine (d-Ala) is first conjugated with a photosensitizer (TPApy) showing aggregation-induced emission (AIE). The yielded metabolic substrate of d-Ala-TPAPy can be metabolically incorporated into bacterial peptidoglycan to form engineered C. Butyricum. Once the engineered C. butyricum is injected into melanoma, the bacteria can only proliferate in an anaerobic zone, stimulate the tumor immune microenvironment, and ablate the tumor hypoxia region. Following that, the relatively rich oxygen content in the peripheral area can induce the death of C. butyricum. The photosensitizer (PS) on the bacteria can subsequently exert a photodynamic effect in the oxygen-rich region and further remove the melanoma residue under light irradiation. Prominent in vivo melanoma ablation results revealed that the engineering oncolytic bacteria can provide a promising regime for solid tumor eradication.