Genome-scale metabolic models in translational medicine: the current status and potential of machine learning in improving the effectiveness of the models.

The genome-scale metabolic model (GEM) has emerged as one of the leading modeling approaches for systems-level metabolic studies and has been widely explored for a broad range of organisms and applications. Owing to the development of genome sequencing technologies and available biochemical data, it is possible to reconstruct GEMs for model and non-model microorganisms as well as for multicellular organisms such as humans and animal models. GEMs will evolve in parallel with the availability of biological data, new mathematical modeling techniques and the development of automated GEM reconstruction tools. The use of high-quality, context-specific GEMs, a subset of the original GEM in which inactive reactions are removed while maintaining metabolic functions in the extracted model, for model organisms along with machine learning (ML) techniques could increase their applications and effectiveness in translational research in the near future. Here, we briefly review the current state of GEMs, discuss the potential contributions of ML approaches for more efficient and frequent application of these models in translational research, and explore the extension of GEMs to integrative cellular models.

Attenuation of Type IV pili activity by natural products.

The virulence factor Type IV pili (T4P) are surface appendages used by the opportunistic pathogen Pseudomonas aeruginosa for twitching motility and adhesion in the environment and during infection. Additionally, the use of these appendages by P. aeruginosa for biofilm formation increases its virulence and drug resistance. Therefore, attenuation of the activity of T4P would be desirable to control P. aeruginosa infections. Here, a computational approach has been pursued to screen natural products that can be used for this purpose. PilB, the elongation ATPase of the T4P machinery in P. aeruginosa, has been selected as the target subunit and virtual screening of FDA-approved drugs has been conducted. Screening identified two natural compounds, ergoloid and irinotecan, as potential candidates for inhibiting this T4P-associated ATPase in P. aeruginosa. These candidate compounds underwent further rigorous evaluation through molecular dynamics (MD) simulations and then through in vitro twitching motility and biofilm inhibition assays. Notably, ergoloid emerged as a particularly promising candidate for weakening the T4P activity by inhibiting the elongation ATPases associated with T4P. This repurposing study paves the way for the timely discovery of antivirulence drugs as an alternative to classical antibiotic treatments to help combat infections caused by P. aeruginosa and related pathogens.Communicated by Ramaswamy H. Sarma.

Assessment of hazelnut husk as a lignocellulosic feedstock for the production of fermentable sugars and lignocellulolytic enzymes.

The present work focuses firstly on the evaluation of the effect of laccase on enzymatic hydrolysis of hazelnut husk which is one of the most abundant lignocellulosic agricultural residues generated in Turkey. In this respect, the co-enzymatic treatment of hazelnut husk by cellulase and laccase, without a conventional pretreatment step is evaluated. Using 2.75 FPU/g substrate (40 g/L substrate) and a ratio of 131 laccase U/FPU achieved the highest reducing sugars concentration. Gas chromatography mass spectrometry confirmed that the hydrolysate was composed of glucose, xylose, mannose, arabinose and galactose. The inclusion of laccase in the enzyme mixture [carboxymethyl cellulase (CMCase) and ß-glucosidase] increased the final glucose content of the reducing sugars from 20 to 50%. Therefore, a very significant increase in glucose content of the final reducing sugars concentration was obtained by laccase addition. Furthermore, the production of cellulases and laccase by Pycnoporus sanguineus DSM 3024 using hazelnut husk as substrate was also investigated. Among the hazelnut husk concentrations tested (1.5, 6, 12, 18 g/L), the highest CMCase concentration was obtained using 12 g/L husk concentration on the 10th day of fermentation. Besides CMCase, P. sanguineus DSM 3024 produced ß-glucosidase and laccase using hazelnut husk as carbon source. In addition to CMCase and ß-glucosidase, the highest laccase activity measured was 2240 ± 98 U/L (8.89 ± 0.39 U/mg). To the best of our knowledge, this is the first study to report hazelnut husk hydrolysis in the absence of pretreatment procedures.