ANT(9)-Ic, a Novel Chromosomally Encoded Aminoglycoside Nucleotidyltransferase from Brucella intermedia.

Aminoglycoside-modifying enzymes are among the most important mechanisms of resistance to aminoglycoside antibiotics, typically conferring high-level resistance by enzymatic drug inactivation. Previously, we isolated a multidrug-resistant Brucella intermedia strain ZJ499 from a cancer patient, and whole-genome sequencing revealed several putative novel aminoglycoside-modifying enzyme genes in this strain. Here, we report the characterization of one of them that encodes an intrinsic, chromosomal aminoglycoside nucleotidyltransferase designated ANT(9)-Ic, which shares only 33.05% to 47.44% amino acid identity with the most closely related ANT(9)-I enzymes. When expressed in Escherichia coli, ANT(9)-Ic conferred resistance only to spectinomycin and not to any other aminoglycosides tested, indicating a substrate profile typical of ANT(9)-I enzymes. Consistent with this, deletion of ant(9)-Ic in ZJ499 resulted in a specific and significant decrease in MIC of spectinomycin. Furthermore, the purified ANT(9)-Ic protein showed stringent substrate specificity for spectinomycin with a Km value of 44.83 µM and a kcat/Km of 2.8 × 104 M-1 s-1, echoing the above observations of susceptibility testing. In addition, comparative genomic analysis revealed that the genetic context of ant(9)-Ic was conserved in Brucella, with no mobile genetic elements found within its 20-kb surrounding region. Overall, our results demonstrate that ANT(9)-Ic is a novel member of the ANT(9)-I lineage, contributing to the intrinsic spectinomycin resistance of ZJ499. IMPORTANCE The emergence, evolution, and worldwide spread of antibiotic resistance present a significant global public health crisis. For aminoglycoside antibiotics, enzymatic drug modification is the most common mechanism of resistance. We identify a novel chromosomal aminoglycoside nucleotidyltransferase from B. intermedia, called ANT(9)-Ic, which shares the highest identity (47.44%) with the previously known ANT(9)-Ia and plays an important role in spectinomycin resistance of the host strain. Analysis of the genetic environment and origin of ant(9)-Ic shows that the gene and its surrounding region are widely conserved in Brucella, and no mobile elements are detected, indicating that ANT(9)-Ic may be broadly important in the natural resistance to spectinomycin of Brucella species.

Development and Validation of an Individualized Immune Prognostic Signature for Recurrent Prostate Cancer.

BACKGROUND: Immune-related genes possess promising prognostic potential in multiple cancer types. Here, we describe the development of an immune-related prognostic signature for predicting prostate cancer recurrence. METHODS: Prostate cancer gene expression profiles for 477 prostate cases, as well as accompanying follow-up information were downloaded from The Cancer Genome Atlas (TCGA) and GEO. The samples were divided into 3 groups and immune gene sets significantly associated with prognosis were identified by evaluating the relationship between the expression of 1039 immune genes and prognosis in the training set. Relative expression levels of these genes were used to identify prognostic gene pairs. LASSO was used for feature selection and robust biomarkers selected. Finally, the identified immune prognostic markers were validated using dataset and GEO validation dataset and their performance compared with existing prognostic models. RESULTS: In total, 87 immune genes, significantly associated with prognosis, were identified and 2447 immune gene pairs (IRGPs) established. Univariate survival analysis identified 641 prognosis-associated immune gene pairs. 8-IRGPs were obtained via LASSO feature selection and an 8-IRGPs signature established. The 8-IRGPs signature exhibited an independent prognosis value in prostate cancer of the training set, test set, and external validation set (p = <0.001). The 5- year survival AUC in both the training set and the validation set was >0.7. The 8-IRGPs outperformed clinical tumor classification features, including T, N, radiation therapy (RT) and targeted molecular therapy (TMT) (p <0.01). In addition, we compared the prognostic characteristics of 8-IRGPs with 3 reported prostate cancers and found that 8-IRGPs achieved a high C index (0.85) and had the highest predictive performance within 10 years of follow-up (HR: 10.5). Finally, we integrated T, N, RT, TMT, and 8-IRGPs and generated a novel alignment chart to aid the prediction of prostate cancer recurrence in individual patients (p <0.01). CONCLUSION: Here, we identified an 8-IRGP novel prognostic signature for the prediction of prostate cancer recurrence.