Paracetamol modulates biofilm formation in Staphylococcus aureus clonal complex 8 strains

The role of NSAID in mediating the effect of genetically predicted major depressive disorder on osteomyelitis: A Mendelian randomization study

BACKGROUND

Osteomyelitis and major depressive disorder (MDD) are significant health concerns with potential interconnections. However, the underlying mechanisms linking these conditions remain unknown. This study aimed to investigate the potential mediating role of non-steroidal anti-inflammatory drug (NSAID) medication in the association between MDD and the risk of osteomyelitis.

METHODS

We utilized summary data from large-scale genome-wide association studies (GWAS) to perform Mendelian randomization (MR) mediation analysis. Instrumental variables were selected based on genome-wide significance, and instrumental strength was assessed using F-statistics. Univariable and multivariable MR analyses were conducted to estimate causal effects and proportions mediated by NSAID medication.

RESULTS

The univariable MR analysis revealed significant associations between MDD and osteomyelitis (odds ratio [OR] = 1.44, 95 % confidence interval [CI]: 1.18-1.874) and between MDD and NSAID medication (OR = 1.36, 95 % CI 1.24-1.49). In the multivariable MR analysis, the direct effect of MDD on osteomyelitis was OR 1.35 (95 % CI: 1.09, 1.67) after adjusting for NSAID medication. The proportion of mediation by NSAID medication was 23 % (95 % CI: 0.05 %, 38.6 %).

CONCLUSION

This MR study provides evidence for a genetically predicted causal association between MDD, NSAID medication, and osteomyelitis. The findings emphasize the need for a comprehensive approach in managing individuals with comorbid depression and osteomyelitis, considering the potential risks and benefits of NSAID medication. Future research should address limitations and explore additional mediators and confounding factors to enhance understanding of this complex relationship.

Unveiling the stealthy tactics: mycoplasma's immune evasion strategies

Mycoplasmas, the smallest known self-replicating organisms, possess a simple structure, lack a cell wall, and have limited metabolic pathways. They are responsible for causing acute or chronic infections in humans and animals, with a significant number of species exhibiting pathogenicity. Although the innate and adaptive immune responses can effectively combat this pathogen, mycoplasmas are capable of persisting in the host, indicating that the immune system fails to eliminate them completely. Recent studies have shed light on the intricate and sophisticated defense mechanisms developed by mycoplasmas during their long-term co-evolution with the host. These evasion strategies encompass various tactics, including invasion, biofilm formation, and modulation of immune responses, such as inhibition of immune cell activity, suppression of immune cell function, and resistance against immune molecules. Additionally, antigen variation and molecular mimicry are also crucial immune evasion strategies. This review comprehensively summarizes the evasion mechanisms employed by mycoplasmas, providing valuable insights into the pathogenesis of mycoplasma infections.

Dehydration Tolerance in Epidemic versus Nonepidemic MRSA Demonstrated by Isothermal Microcalorimetry

Methicillin-resistant Staphylococcus aureus (MRSA) clusters are considered epidemic or nonepidemic based on their ability to spread effectively. Successful transmission could be influenced by dehydration tolerance. Current methods for determination of dehydration tolerance lack accuracy. Here, a climate-controlled in vitro dehydration assay using isothermal microcalorimetry (IMC) was developed and linked with mathematical modeling to determine survival of 44 epidemic versus 54 nonepidemic MRSA strains from France, the United Kingdom, and the Netherlands after 1 week of dehydration. For each MRSA strain, the growth parameters time to end of first growth phase (tmax [h]) and maximal exponential growth rate (μ_m) were deduced from IMC data for 3 experimental replicates, 3 different starting inocula, and before and after dehydration. If the maximal exponential growth rate was within predefined margins (±36% of the mean), a linear relationship between tmax and starting inoculum could be utilized to predict log reduction after dehydration for individual strains. With these criteria, 1,330 of 1,764 heat flow curves (data sets) (75%) could be analyzed to calculate the post-dehydration inoculum size, and thus the log reduction due to dehydration, for 90 of 98 strains (92%). Overall reduction was ~1 log after 1 week. No difference in dehydration tolerance was found between the epidemic and nonepidemic strains. Log reduction was negatively correlated with starting inoculum, indicating better survival of higher inocula. This study presents a framework to quantify bacterial survival. MRSA strains showed great capacity to persist in the environment, irrespective of epidemiological success. This finding strengthens the need for effective surface cleaning to contain MRSA transmission. IMPORTANCE Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of infections globally. While some MRSA clusters have spread worldwide, others are not able to disseminate successfully beyond certain regions despite frequent introduction. Dehydration tolerance facilitates transmission in hospital environments through enhanced survival on surfaces and fomites, potentially explaining differences in transmission success between MRSA clusters. Unfortunately, the currently available techniques to determine dehydration tolerance of cluster-forming bacteria like S. aureus are labor-intensive and unreliable due to their dependence on quantitative culturing. In this study, bacterial survival was assessed in a newly developed assay using isothermal microcalorimetry. With this technique, the effect of drying can be determined without the disadvantages of quantitative culturing. In combination with a newly developed mathematical algorithm, we determined dehydration tolerance of a large number of MRSA strains in a systematic, unbiased, and robust manner.