***TASK***
the task is to simplify the input abstract of a biomedical literature

***INPUT***
the input is the abstract of a biomedical literature

***OUTPUT***
the output is the simplified abstract for the input abstract of a biomedical literature
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Input: Functionally analogous enzymes are those that catalyze similar reactions on similar substrates but do not share common ancestry, providing a window on the different structural strategies nature has used to evolve required catalysts. Identification and use of this information to improve reaction classification and computational annotation of enzymes newly discovered in the genome projects would benefit from systematic determination of reaction similarities. Here, we quantified similarity in bond changes for overall reactions and catalytic mechanisms for 95 pairs of functionally analogous enzymes (non-homologous enzymes with identical first three numbers of their EC codes) from the MACiE database. Similarity of overall reactions was computed by comparing the sets of bond changes in the transformations from substrates to products. For similarity of mechanisms, sets of bond changes occurring in each mechanistic step were compared; these similarities were then used to guide global and local alignments of mechanistic steps. Using this metric, only 44% of pairs of functionally analogous enzymes in the dataset had significantly similar overall reactions. For these enzymes, convergence to the same mechanism occurred in 33% of cases, with most pairs having at least one identical mechanistic step. Using our metric, overall reaction similarity serves as an upper bound for mechanistic similarity in functional analogs. For example, the four carbon-oxygen lyases acting on phosphates (EC 4.2.3) show neither significant overall reaction similarity nor significant mechanistic similarity. By contrast, the three carboxylic-ester hydrolases (EC 3.1.1) catalyze overall reactions with identical bond changes and have converged to almost identical mechanisms. The large proportion of enzyme pairs that do not show significant overall reaction similarity (56%) suggests that at least for the functionally analogous enzymes studied here, more stringent criteria could be used to refine definitions of EC sub-subclasses for improved discrimination in their classification of enzyme reactions. The results also indicate that mechanistic convergence of reaction steps is widespread, suggesting that quantitative measurement of mechanistic similarity can inform approaches for functional annotation.
Output:  When species evolve, their genes duplicate and diverge to allow for adaptation of their functional repertoires to the changing environment. In this scenario, unrelated genes can convergently evolve to produce proteins with the same molecular function, termed “functionally analogous.” A quantitative determination of the reaction similarities among functionally analogous enzymes could provide insight about the different structural solutions nature has used to evolve similar catalysts. Bond changes between substrates and products, and between successive reaction intermediates, were used to compare the reactions catalyzed and the mechanisms of catalysis for 95 pairs of functionally analogous enzymes. Less than half of the reactions catalyzed by unrelated enzymes, but defined as similar by the Enzyme Commission (EC) classification, are similar in terms of bond changes, suggesting that this classification often fails to capture quantitative differences between many enzyme reactions. Furthermore, we addressed for the first time whether the chemical mechanisms by which similar overall reactions are achieved in functional analogs are also similar. We conclude that convergence of reaction is often accompanied by convergence of chemical mechanism. These results will be useful for classifying enzymes, guiding functional annotation of newly determined enzyme sequences and structures and for informing the engineering of enzymes with new functions.

Input:  Antibiotic susceptibility of bacterial pathogens is typically evaluated using in vitro assays that do not consider the complex host microenvironment. This may help explaining a significant discrepancy between antibiotic efficacy in vitro and in vivo, with some antibiotics being effective in vitro but not in vivo or vice versa. Nevertheless, it is well-known that antibiotic susceptibility of bacteria is driven by environmental factors. Lung epithelial cells enhance the activity of aminoglycoside antibiotics against the opportunistic pathogen Pseudomonas aeruginosa, yet the mechanism behind is unknown. The present study addresses this gap and provides mechanistic understanding on how lung epithelial cells stimulate aminoglycoside activity. To investigate the influence of the local host microenvironment on antibiotic activity, an in vivo-like three-dimensional (3-D) lung epithelial cell model was used. We report that conditioned medium of 3-D lung cells, containing secreted but not cellular components, potentiated the bactericidal activity of aminoglycosides against P. aeruginosa, including resistant clinical isolates, and several other pathogens. In contrast, conditioned medium obtained from the same cell type, but grown as conventional (2-D) monolayers did not influence antibiotic efficacy. We found that 3-D lung cells secreted endogenous metabolites (including succinate and glutamate) that enhanced aminoglycoside activity, and provide evidence that bacterial pyruvate metabolism is linked to the observed potentiation of antimicrobial activity. Biochemical and phenotypic assays indicated that 3-D cell conditioned medium stimulated the proton motive force (PMF), resulting in increased bacterial intracellular pH. The latter stimulated antibiotic uptake, as determined using fluorescently labelled tobramycin in combination with flow cytometry analysis. Our findings reveal a cross-talk between host and bacterial metabolic pathways, that influence downstream activity of antibiotics. Understanding the underlying basis of the discrepancy between the activity of antibiotics in vitro and in vivo may lead to improved diagnostic approaches and pave the way towards novel means to stimulate antibiotic activity.


Output:

There is a poor correlation between the activity of antibiotics in the laboratory and in patients, including in several infectious diseases of the respiratory tract. What may help explaining differences between antibiotic activity in vitro and in vivo is that current antibiotic susceptibility tests do not consider the in vivo lung environment. The lung environment contains many factors that may influence bacterial susceptibility to antibiotics. This includes lung epithelial cells, which have been shown to improve the activity of aminoglycoside antibiotics. Yet, how lung epithelial cells increase aminoglycoside activity is currently unknown. Here, we cultured lung epithelial cells in an in vivo-like model and found that they secrete metabolites that enhance the activity of aminoglycoside antibiotics. We found that host cell secretions increased antibiotic uptake through stimulation of bacterial metabolism, which in turn resulted in enhanced activity. Our findings highlight that cross-talk between host and bacterial metabolisms contributes to the efficacy of antibiotic treatment. Understanding how the host metabolism influences antibiotic activity may open up therapeutic avenues to exploit host metabolism for improving antibiotic activity and help explaining discrepancies between antibiotic efficacy in vitro and in vivo.
