Vesicular Delivery of the Antifungal Antibiotics of Lysobacter enzymogenes C3.

Lysobacter enzymogenes C3 is a predatory strain of Gram-negative gliding bacteria that produces antifungal antibiotics by the polyketide synthetic pathway. Outer membrane vesicles (OMV) are formed as a stress response and can deliver virulence factors to host cells. The production of OMV by C3 and their role in antifungal activity are reported here. Vesicles in the range of 130 to 150 nm in diameter were discovered in the cell-free supernatants of C3 cultures. These OMV contain molecules characteristic of bacterial outer membranes, such as lipopolysaccharide and phospholipids. In addition, they contain chitinase activity and essentially all of the heat-stable antifungal activity in cell supernatants. We show here that C3 OMV can directly inhibit growth of the yeast Saccharomyces cerevisiae as well as that of the filamentous fungus Fusarium subglutinans The activity is dependent on physical contact between OMV and the cells. Furthermore, fluorescent lipid labeling of C3 OMV demonstrated transfer of the membrane-associated probe to yeast cells, suggesting the existence of a mechanism of delivery for membrane-associated molecules. Mass spectrometric analysis of C3 OMV extracts indicates the presence of molecules with molecular weights identical to some of the previously identified antifungal products of C3. These data together suggest that OMV act as an important remote mobile component of predation by LysobacterIMPORTANCE The data presented here suggest a newly discovered function of outer membrane vesicles (OMV) that are produced from the outer membrane of the bacterial species Lysobacter enzymogenes strain C3. We show that these OMV can be released from the surface of the cells to deliver antibiotics to target fungal organisms as a mechanism of killing or growth inhibition. Understanding the role of OMV in antibiotic delivery can generally lead to improved strategies for dealing with antibiotic-resistant organisms. These results also add to the evidence that some bacterially produced antibiotics can be discovered and purified using methods designed for isolation of nanoscale vesicles. Information on these systems can lead to better identification of active molecules or design of delivery vehicles for these molecules.

On-Line Ion Exchange Liquid Chromatography as a Process Analytical Technology for Monoclonal Antibody Characterization in Continuous Bioprocessing.

Combining process analytical technology (PAT) with continuous production provides a powerful tool to observe and control monoclonal antibody (mAb) fermentation and purification processes. This work demonstrates on-line liquid chromatography (on-line LC) as a PAT tool for monitoring a continuous biologics process and forced degradation studies. Specifically, this work focused on ion exchange chromatography (IEX), which is a critical separation technique to detect charge variants. Product-related impurities, including charge variants, that impact function are classified as critical quality attributes (CQAs). First, we confirmed no significant differences were observed in the charge heterogeneity profile of a mAb through both at-line and on-line sampling and that the on-line method has the ability to rapidly detect changes in protein quality over time. The robustness and versatility of the PAT methods were tested by sampling from two purification locations in a continuous mAb process. The PAT IEX methods used with on-line LC were a weak cation exchange (WCX) separation and a newly developed shorter strong cation exchange (SCX) assay. Both methods provided similar results with the distribution of percent acidic, main, and basic species remaining unchanged over a 2 week period. Second, a forced degradation study showed an increase in acidic species and a decrease in basic species when sampled on-line over 7 days. These applications further strengthen the use of on-line LC to monitor CQAs of a mAb continuously with various PAT IEX analytical methods. Implementation of on-line IEX will enable faster decision making during process development and could potentially be applied to control in biomanufacturing.