Effect of some psychotropic drugs and a barbiturate on mycoplasmas

Mycoplasma pneumoniae IgG positivity is associated with tic severity in chronic tic disorders

Infectious pathogens may represent an environmental risk factor for chronic tic disorders (CTD). This cross-sectional study aimed to determine whether Mycoplasma pneumoniae (M. pneumoniae) IgG positivity is associated with the presence or severity of tics. We compared M. pneumoniae IgG positivity across three groups: children and adolescents (3-16 years) with CTD (CTD group; n = 302); siblings (3-10 years) of people with CTD who developed tics within a seven-year follow-up period (tic onset group; n = 51); siblings (4-10 years) who did not develop tics within the study period and were ≥10-years-old at their last assessment (unaffected group; n = 88). The relationship between M. pneumoniae IgG positivity and the presence and severity of tics was analysed using multilevel models controlling for site, family relatedness, sex, age, presence of comorbid obsessive-compulsive and/or attention-deficit/hyperactivity disorder and use of psychotropic medication. M. pneumoniae IgG positivity was not associated with the presence of CTD, or the first onset of tics as compared to siblings who remained unaffected. M. pneumoniae IgG positivity was associated with a higher tic severity score within the CTD group (β = 2.64, s.e. = 1.15, p = 0.02). It is possible that M. pneumoniae infection influences tic severity in CTD or, that having more severe tics, increases the risk of infection. However, it is more likely that the association observed in this study reflects a propensity toward enhanced immune responses in people with CTD and that, rather than a causal relationship, infection and greater tic severity are indirectly linked via shared underlying immune mechanisms.

A chemical screen to identify inducers of the mitochondrial unfolded protein response in C. elegans

We previously showed that inhibition of the mevalonate pathway in C. elegans causes inhibition of protein prenylation, developmental arrest and lethality. We also showed that constitutive activation of the mitochondrial unfolded protein response, UPR^mt, is an effective way for C. elegans to become resistant to the negative effects of mevalonate pathway inhibition. This was an important finding since statins, a drug class prescribed to lower cholesterol levels in patients, act by inhibiting the mevalonate pathway, and it is therefore possible that some of their undesirable side effects could be alleviated by activating the UPR^mt. Here, we screened a chemical library and identified 4 compounds that specifically activated the UPR^mt. One of these compounds, methacycline hydrochloride (a tetracycline antibiotic) also protected C. elegans and mammalian cells from statin toxicity. Methacycline hydrochloride and ethidium bromide, a known UPR^mt activator, were also tested in mice: only ethidium bromide significantly activate the UPR^mt in skeletal muscles.

Psychotropic effects of antimicrobials and immune modulation by psychotropics: implications for neuroimmune disorders

Antimicrobial compounds and psychotropic medications often share overlapping mechanisms of actions and pharmacological effects. The immune system appears to be an important site of interaction as several antimicrobials display neurological and, at times, direct psychotropic effects, while psychotropics have shown significant immunomodulatory properties. The isoniazid class of antibiotics for example has been shown to possess monoamine oxidase activity, while selective serotonin reuptake inhibitors have shown significant effects on leukocyte populations. As the importance of the immune system's role in CNS homeostasis and disease continues to move to the forefront of neuropsychiatric research, these shared pharmacological effects may provide an important insight, elucidating the complexities in neuroimmune pathophysiology and guiding the development of potential treatments.

Can ‘Bacterial-Metabolite-Likeness' Model Improve Odds of ‘in Silico' Antibiotic Discovery?

'Inductive' QSAR descriptors have been used to develop the series of QSAR models enabling 'in silico' distinguishing between antimicrobial compounds, conventional drugs, and druglike substances. The constructed neural network-based models operating by 30 'inductive' parameters have been validated on an extensive set of 2686 chemical structures and resulted in up to 97% accurate separation of the three types of molecular activities. The demonstrated ability of 'inductive' parameters to adequately capture molecular features determining 'antibiotic-like' and 'druglike' potentials have been further utilized to construct a model of 'Bacterial-Metabolite-Likeness' (BML). The same 'inductive' descriptors have been used to train a neural network that could very accurately recognize substances involved into bacterial metabolism (that have been experimentally identified). When the developed model has been applied to the mixed set of antimicrobials, drugs, and druglike chemicals (not used for training the BML model), it exhibited a 2-5-fold recognition preference toward antimicrobial compounds compared to general drugs and an 18- to 45-fold preference when compared to a druglike substance (depending on the model stringency). These results illustrate immanent similarity between conventional antimicrobials and native bacterial metabolites and suggest that the developed BML model can be an effective classification tool for 'in silico' antibiotic studies.