Implementation of homology based and non-homology based computational methods for the identification and annotation of orphan enzymes: using Mycobacterium tuberculosis H37Rv as a case study
Authors: Sinha, Swati; Lynn, Andrew M.; Desai, Dhwani K.
BackgroundHomology based methods are one of the most important and widely used approaches for functional annotation of high-throughput microbial genome data. A major limitation of these methods is the absence of well-characterized sequences for certain functions. The non-homology methods based on the context and the interactions of a protein are very useful for identifying missing metabolic activities and functional annotation in the absence of significant sequence similarity. In the current work, we employ both homology and context-based methods, incrementally, to identify local holes and chokepoints, whose presence in the Mycobacterium tuberculosis genome is indicated based on its interaction with known proteins in a metabolic network context, but have not been annotated. We have developed two computational procedures using network theory to identify orphan enzymes ('Hole finding protocol') coupled with the identification of candidate proteins for the predicted orphan enzyme ('Hole filling protocol'). We propose an integrated interaction score based on scores from the STRING database to identify candidate protein sequences for the orphan enzymes from M. tuberculosis, as a case study, which are most likely to perform the missing function.ResultsThe application of an automated homology-based enzyme identification protocol, ModEnzA, on M. tuberculosis genome yielded 56 novel enzyme predictions. We further predicted 74 putative local holes, 6 choke points, and 3 high confidence local holes in the genome using 'Hole finding protocol'. The 'Hole-filling protocol' was validated on the E. coli genome using artificial in-silico enzyme knockouts where our method showed 25% increased accuracy, compared to other methods, in assigning the correct sequence for the knocked-out enzyme amongst the top 10 ranks. The method was further validated on 8 additional genomes.ConclusionsWe have developed methods that can be generalized to augment homology-based annotation to identify missing enzyme coding genes and to predict a candidate protein for them. For pathogens such as M. tuberculosis, this work holds significance in terms of increasing the protein repertoire and thereby, the potential for identifying novel drug targets.
Clean-in-place disinfection of dual-species biofilm (Listeria and Pseudomonas) by a green antibacterial product made from citrus extract
Authors: Medina-Rodriguez, Andrea C.; Avila-Sierra, Alejandro; Ariza, Juan J.; Guillamon, Enrique; Banos-Arjona, Alberto; Vicaria, Jose M.; Jurado, Encarnacion
Food industries, which must ensure safety and quality of manufactured products, require effective and regular cleaning and disinfection processes. One of the most difficult issues to overcome is to ensure the elimination of biofilms that can generate contamination during food processing. Despite chemical disinfection is the most used strategy, it also requires to be optimised, reducing energy costs, time, and the environmental impact of these operations. In this work, the effectiveness of an environmental-friendly commercial disinfectant (Mico E-PRO (R)) made from food-grade citrus extracts has been addressed by two methods (i) in-vitro tests for evaluation of antimicrobial efficacy and (ii) a lab-simulated CIP system, where the efficacy was compared with NaClO 1%. In both cases, Mico E-PRO (R) shows that it is an effective product for the killing of E. coli (MBC = 625 ppm), L. monocytogenes (MBC = 625 ppm), S. enterica (MBC = 625 ppm) and P. aeruginosa (MBC = 156.25 ppm), being P. aeruginosa the most sensible to the disinfectant. The product also shows good bactericidal effect against a mature biofilm formed by L. innocua and P. putida - similar efficacy to that obtained with NaClO 1%. Overall, results demonstrated that Mico E-PRO (R) is a good option as a natural sanitiser for CIP systems, running as an efficient and safe alternative to the traditional chemicals-based disinfectants.