Frontiers in antibiotics最新文献

Rifamycin and its derivatives are natural products that belong to the class of antibiotic-active polyketides and have significant therapeutic relevance within the therapy scheme of tuberculosis, a worldwide infectious disease caused by Mycobacterium tuberculosis. Improving the oral bioavailability of rifamycin B was achieved through semisynthetic modifications, leading to clinically effective derivatives such as rifampicin. Genetic manipulation of the rifamycin polyketide synthase gene cluster responsible for the production of rifamycin B in the Amycolatopsis mediterranei strain S699 represents a promising tool to generate new rifamycins. These new rifamycins have the potential to be further derivatized into new, ideally more effective, clinically usable compounds. However, the resulting genetically engineered strains only produce these new derivatives in low yields. One example is the strain DCO36, in which rifAT6 was replaced by rapAT2, resulting in the production of rifamycin B and the new derivative 24-desmethyl rifamycin B. Here we describe the successful method adaptation of the PCR-targeting Streptomyces gene replacement approach to Amycolatopsis mediterranei S699 and further on the implementation of genetic modifications that enable an increased production of the derivative 24-desmethyl rifamycin B in the mutant strain DCO36. The described genetic modifications resulted in a mutant strain of DCO36 with rifQ deletion showing a 62% increase in 24-desmethyl rifamycin B production, while a mutant with rifO overexpression showed a 27% increase.

Microorganisms, crucial for environmental equilibrium, could be destructive, resulting in detrimental pathophysiology to the human host. Moreover, with the emergence of antibiotic resistance (ABR), the microbial communities pose the century's largest public health challenges in terms of effective treatment strategies. Furthermore, given the large diversity and number of known bacterial strains, describing treatment choices for infected patients using experimental methodologies is time-consuming. An alternative technique, gaining popularity as sequencing prices fall and technology advances, is to use bacterial genotype rather than phenotype to determine ABR. Complementing machine learning into clinical practice provides a data-driven platform for categorization and interpretation of bacterial datasets. In the present study, k-mers were generated from nucleotide sequences of pathogenic bacteria resistant to antibiotics. Subsequently, they were clustered into groups of bacteria sharing similar genomic features using the Affinity propagation algorithm with a Silhouette coefficient of 0.82. Thereafter, a prediction model based on Random Forest algorithm was developed to explore the prediction capability of the k-mers. It yielded an overall specificity of 0.99 and a sensitivity of 0.98. Additionally, the genes and ABR drivers related to the k-mers were identified to explore their biological relevance. Furthermore, a multilayer perceptron model with a hamming loss of 0.05 was built to classify the bacterial strains into resistant and non-resistant strains against various antibiotics. Segregating pathogenic bacteria based on genomic similarities could be a valuable approach for assessing the severity of diseases caused by new bacterial strains. Utilization of this strategy could aid in enhancing our understanding of ABR patterns, paving the way for more informed and effective treatment options.

Clinical Microbiology has developed during the last 100 years, simultaneous with the discovery of microorganisms as causes of infections. Globalization and One Health determine present needs whereas molecular biology, automation, artificial intelligence, and bioinformatics are new tools that characterize the new developments in the field.

Orthotopic liver transplant (OLT) represents the standard of care for managing patients affected by end-stage and life-threatening liver diseases. Although a significant improvement in surgical techniques, immunosuppressant regimens, and prompt identification of early post-transplant complications resulted in better clinical outcome and survival in OLT recipients, the occurrence of early bacterial infections still represents a remarkable cause of morbidity and mortality. In this scenario, beta-lactams are the most frequent antimicrobials used in critical OLT recipients. The aim of this narrative review was to provide a comprehensive overview of the pathophysiological issues potentially affecting the pharmacokinetics of beta-lactams and to identify potential strategies for maximizing the likelihood of attaining adequate pharmacokinetic/pharmacodynamic (PK/PD) targets of beta-lactams in critically ill OLT recipients. A literature search was carried out on PubMed-MEDLINE database (until 31^st March 2024) in order to retrieve clinical trials, real-world observational evidence, and/or case series/reports evaluating the PK/PD of traditional and novel beta-lactams in settings potentially involving critically ill OLT recipients. Retrieved evidence were categorized according to the concepts of the so-called "antimicrobial therapy puzzle", specifically assessing a) beta-lactam PK/PD features, with specific regard to aggressive PK/PD target attainment; b) site of infection, with specific regard to beta-lactam penetration in the lung, ascitic fluid, and bile; and c) pathophysiological alterations, focusing mainly on those specifically associated with OLT. Overall, several research gaps still exist in assessing the PK behavior of beta-lactams in critical OLT recipients. The impact of specific OLT-associated pathophysiological alterations on the attainment of optimal PK/PD targets may represent an important field in which further studies are warranted. Assessing the relationship between aggressive beta-lactam PK/PD target attainment and clinical outcome in critical OLT recipients will represent a major challenge in the next future.