Antimicrobial agents are used in both veterinary and human medicine. The intensive use of antimicrobials in animals may promote the fixation of antimicrobial resistance genes in bacteria, which may be zoonotic or capable to transfer these genes to human-adapted pathogens or to human gut microbiota via direct contact, food or the environment. This review summarizes the current knowledge of the use of antimicrobial agents in animal health and explores the role of bacteria from animals as a pool of antimicrobial resistance genes for human bacteria. This review focused in relevant examples within the ESC(K)APE (Enterococcus faecium, Staphylococcus aureus, Clostridium difficile (Klebsiella pneumoniae), Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacteriaceae) group of bacterial pathogens that are the leading cause of nosocomial infections throughout the world.
SummaryThe type III secretion apparatus (T3SA) is a multiprotein complex central to the virulence of many Gram-negative pathogens. Currently, the mechanisms controlling the hierarchical addressing of needle subunits, translocators and effectors to the T3SA are still poorly understood. In Shigella, MxiC is known to sequester effectors within the cytoplasm prior to receiving the activation signal from the needle. However, molecules involved in linking the needle and MxiC are unknown. Here, we demonstrate a molecular interaction between MxiC and the predicted inner-rod component MxiI suggesting that this complex plugs the T3SA entry gate. Our results suggest that MxiIMxiC complex dissociation facilitates the switch in secretion from translocators to effectors. We identified MxiC F206S variant, unable to interact with MxiI, which exhibits a constitutive secretion phenotype although it remains responsive to induction. Moreover, we identified the mxiI Q67A mutant that only secretes translocators, a phenotype that was suppressed by coexpression of the MxiC F206S variant. We demonstrated the interaction between MxiI and MxiC homologues in Yersinia and Salmonella. Lastly, we identified an interaction between MxiC and chaperone IpgC which contributes to understanding how translocators secretion is regulated. In summary, this study suggests the existence of a widely conserved T3S mechanism that regulates effectors secretion.
SummaryType III secretion apparatus (T3SA) are complex nanomachines that insert a translocation pore into the host cell membrane through which effector proteins are injected into the cytosol. In Shigella, the pore is inserted by a needle tip complex that also controls secretion. IpaD is the key protein that rules the composition of the tip complex before and upon cell contact or Congo red (CR) induction. However, how IpaD is involved in secretion control and translocon insertion remains not fully understood. Here, we report the phenotypic analysis of 20 10-amino acids deletion variants all along the coiled-coil and the central domains of IpaD (residues 131-332). Our results highlight three classes of T3S phenotype; (i) wild-type secretion, (ii) constitutive secretion of all classes of effectors, and (iii) constitutive secretion of translocators and early effectors, but not of late effectors. Our data also suggest that the composition of the tip complex defines both the T3SA inducibility state and late effectors secretion. Finally, we shed light on a new aspect regarding the contact of the needle tip with cell membrane by uncoupling the Shigella abilities to escape macrophage vacuole, and to insert the translocation pore or to invade nonphagocytic cells.
The number of reported cases with Legionnaires' disease (LD) is increasing in Belgium. Previous studies have investigated the associations between LD incidence and meteorological factors, but the Belgian data remained unexplored. We investigated data collected between 2011 and 2019. Daily exposure data on temperature, relative humidity, precipitation and wind speed was obtained from the Royal Meteorological Institute for 29 weather stations. Case data were collected from the national reference centre and through mandatory notification. Daily case and exposure data were aggregated by province. We conducted a time-stratified case-crossover study. The ‘at risk’ period was defined as 10 to 2 days prior to disease onset. The corresponding days in the other study years were selected as referents. We fitted separate conditional Poisson models for each day in the ‘at risk’ period and a distributed lag non-linear model (DLNM) which fitted all data in one model. LD incidence showed a yearly peak in August and September. A total of 614 cases were included. Given seasonality, a sequence of precipitation, followed by high relative humidity and low wind speed showed a statistically significant association with the number of cases 6 to 4 days later. We discussed the advantages of DLNM in this context.
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