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Pseudomonas putida (P. putida) KT2440 is a paradigmatic environmental-bacterium that possesses significant potential in synthetic biology, metabolic engineering and biodegradation applications. However, most genome editing methods of P. putida KT2440 depend on heterologous repair proteins and the provision of donor DNA templates, which is laborious and inefficient. In this report, an efficient cytosine base editing system was established by using cytidine deaminase (APOBEC1), enhanced specificity Cas9 nickase (eSpCas9pp D10A) and the uracil DNA glycosylase inhibitor (UGI). This constructed base editor converts C-G into T-A in the absence of DNA strands breaks and donor DNA templates. By introducing a premature stop codon in target spacers, we successfully applied this system for gene inactivation with an efficiency of 25-100% in various Pseudomonas species, including P. putida KT2440, P. aeruginosa PAO1, P. fluorescens Pf-5 and P. entomophila L48. We engineered an eSpCas9pp D10A-NG variant with a NG protospacer adjacent motif to expand base editing candidate sites. By modifying the APOBEC1 domain, we successfully narrowed the editable window to increase gene inactivation efficiency in cytidine-rich spacers. Additionally, multiplex base editing in double and triple loci was achieved with mutation efficiencies of 90-100% and 25-35%, respectively. Taken together, the establishment of a fast, convenient and universal base editing system will accelerate the pace of future research undertaken with P. putida KT2440 and other Pseudomonas species.

The association between inflammation and cancer provides a new target for tumor biotherapy. The inflammatory cells and molecules within the tumor microenvironment have decisive dual roles in antitumor immunity and immune evasion. In the present study, phytohemagglutinin (PHA) was used to stimulate peripheral blood mononuclear cells (PBMCs) to simulate the tumor inflammatory microenvironment. The effect of immune cells and inflammatory cytokines on the surface expression of programmed cell death-1 ligand 1 (PD-L1) and tumor immune evasion was investigated using flow cytometry (FCM) and an in vivo xenotransplantation model. Based on the data, PHA-activated, but not resting, immune cells were able to promote the surface expression of PD-L1 in Tca8113 oral squamous carcinoma cells via the secretion of inflammatory cytokines, but not by cell-cell contact. The majority of the inflammatory cytokines had no significant effect on the proliferation, cell cycle progression and apoptosis of the Tca8113 cells, although they each induced the expression of PD-L1 in a dose-dependent manner. In total, 99% of the Tca8113 cells expressed PD-L1 following treatment with the supernatant of PHA-stimulated PBMCs. The PHA-supernatant pretreated Tca8113 cells unusually induced Tca8113 antigen-specific CD8+ T cell apoptosis in vitro and the evasion of antigen-specific T cell attraction in a nude mouse tumor-bearing model. These results indicate a new mechanism for the promotion of tumor immune evasion by the tumor inflammatory microenvironment

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Background To investigate the value of semi-quantitative and quantitative parameters (PI-RADS score, T2WI score, ADC, Ktrans, and Kep) based on multiparametric MRI (mpMRI) or biparametric MRI (bpMRI) combined with prostate specific antigen density (PSAD) in detecting clinically significant prostate cancer (csPCa).Methods A total of 561 patients (276 with csPCa; 285 with non-csPCa) with biopsy-confirmed prostate diseases who underwent preoperative mpMRI were included. Prostate volume was measured for calculation of PSAD. Prostate index lesions were scored on a five-point scale on T2WI images (T2WI score) and mpMRI images (PI-RADS score) according to the PI-RADS v2.1 scoring standard. DWI and DCE-MRI images were processed to measure the quantitative parameters of the index lesion, including ADC, Kep, and Ktrans values. The predictors of csPCa were screened by logistics regression analysis. Predictive models of bpMRI and mpMRI were established. ROC curves were used to evaluate the efficacy of parameters and the model in diagnosing csPCa.Results The independent diagnostic accuracy of PSA density, PI-RADS score, T2WI score, ADCrec, Ktrans, and Kep for csPCa were 80.2%, 89.5%, 88.3%, 84.6%, 58.5% and 61.6%, respectively. The diagnostic accuracy of BP-MRI T2WI score and ADC value combined with PSAD was higher than that of PI-RADS score. The combination of MP‑MRI PI‑RADS score, ADC value with PSAD had the highest diagnostic accuracy.Conclusions PI-RADS score was the most accurate independent diagnostic index. The predictive value of BP-MRI model for csPCa was slightly lower than that of MP-MRI model, but higher than that of PI-RADS score.