High Cell Selectivity and Bactericidal Mechanism of Symmetric Peptides Centered on d-Pro-Gly Pairs.

Antimicrobial peptides (AMPs) have a unique action mechanism that can help to solve global problems in antibiotic resistance. However, their low therapeutic index and poor stability seriously hamper their development as therapeutic agents. In order to overcome these problems, we designed peptides based on the sequence template XXRXXRRzzRRXXRXX-NH2, where X represents a hydrophobic amino acid like Phe (F), Ile (I), and Leu (L), while zz represents Gly-Gly (GG) or d-Pro-Gly (pG). Showing effective antimicrobial activity against Gram-negative bacteria and low toxicity, designed peptides had a tendency to form an α-helical structure in membrane-mimetic environments. Among them, peptide LRpG (X: L, zz: pG) showed the highest geometric mean average treatment index (GMTI = 73.1), better salt, temperature and pH stability, and an additive effect with conventional antibiotics. Peptide LRpG played the role of anti-Gram-negative bacteria through destroying the cell membrane. In addition, peptide LRpG also exhibited an anti-inflammatory activity by effectively neutralizing endotoxin. Briefly, peptide LRpG has the potential to serve as a therapeutic agent to reduce antibiotic resistance owing to its high therapeutic index and great stability.

Serological, fragmentomic, and epigenetic characteristics of cell-free DNA in patients with lupus nephritis.

Objectives: The biological characteristics of plasma circulating cell-free DNA (cfDNA) are related to the pathogenesis of lupus nephritis (LN). The aim of this study was to explore the biological characteristics of cfDNA in patients with LN in terms of serology, fragment omics, and epigenetics, and to discuss the possibility of liquid biopsy for cfDNA as an alternative to conventional tissue biopsy. Methods: cfDNA was extracted from plasma samples of 127 patients with systemic lupus erythematosus (64 with LN, 63 without LN). The cfDNA concentration was determined using the Qubit method. Next-generation sequencing cfDNA methylation profiling was performed for three LN patients and six non-LN patients. The methylation panel was designed based on data from The Cancer Genome Atlas cohort. The fragmentation index, motif score, and DELFI score were calculated to explore the fragmentation profile of cfDNA in patients with LN. Statistical and machine learning methods were used to select features to calculate the methylation scores of the samples. Results: Patients with LN had significantly lower cfDNA concentrations (P = 0.0347) than those without LN. This may be associated with the presence of anti-double-stranded DNA antibodies (r = -0.4189; P = 0.0296). The mean DELFI score (proportion of short fragments of cfDNA) in patients with LN was significantly higher than that in patients without LN (P = 0.0238). Based on the pan-cancer data, 73, 66, 8, and 10 features were selected and used to calculate the methylation scores. The mean methylation scores of these features in patients with LN differed significantly from those in patients without LN (P = 0.0238). Conclusions: The specificity of cfDNA in patients with LN was identified using serological, fragmentomic, and epigenetic analyses. The findings may have implications for the development of new molecular markers of LN.

A Noninvasive Multianalytical Approach for Lung Cancer Diagnosis of Patients with Pulmonary Nodules.

Addressing the high false-positive rate of conventional low-dose computed tomography (LDCT) for lung cancer diagnosis, the efficacy of incorporating blood-based noninvasive testing for assisting practicing clinician's decision making in diagnosis of pulmonary nodules (PNs) is investigated. In this prospective observative study, next generation sequencing- (NGS-) based cell-free DNA (cfDNA) mutation profiling, NGS-based cfDNA methylation profiling, and blood-based protein cancer biomarker testing are performed for patients with PNs, who are diagnosed as high-risk patients through LDCT and subsequently undergo surgical resections, with tissue sections pathologically examined and classified. Using pathological classification as the gold standard, statistical and machine learning methods are used to select molecular markers associated with tissue's malignant classification based on a 98-patient discovery cohort (28 benign and 70 malignant), and to construct an integrative multianalytical model for tissue malignancy prediction. Predictive models based on individual testing platforms have shown varying levels of performance, while their final integrative model produces an area under the receiver operating characteristic curve (AUC) of 0.85. The model's performance is further confirmed on a 29-patient independent validation cohort (14 benign and 15 malignant, with power > 0.90), reproducing AUC of 0.86, which translates to an overall sensitivity of 80% and specificity of 85.7%.

Antimicrobial susceptibility and molecular characterization of macrolide resistance of Mycoplasma bovis isolates from multiple provinces in China.

Mycoplasma bovis has spread widely throughout the world via animal movement and has become an important pathogen of bovine respiratory disease. However, the minimum inhibitory concentrations of antimicrobials for Mycoplasma bovis have not been studied in China. The objective of this study was to determine the prevalence and antibiotic resistance of Mycoplasma bovis isolated from young cattle with respiratory infection in China. Mycoplasma bovis was detected in 32/45 bovine respiratory infection outbreaks at beef farms in 8 provinces in China. The isolates were susceptible or had medium sensitivity to ciprofloxacin, enrofloxacin and doxycycline, but were frequently resistant to macrolides (13/32, 41%). An A2058G (Escherichia coli Numbering) mutation located in the rrnA operon in domain V of 23S rRNA was observed in strains that were resistant to macrolides. This single mutations at the rrnA operon in domain V of 23S rRNA may play an important role in the resistance of Mycoplasma bovis strains to macrolides.