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Mechanism of Drug Resistance in Staphylococcus aureus and Future Drug Discovery
Published in Peter Grunwald, Pharmaceutical Biocatalysis, 2020
Felipe Wakasuqui, Ana Leticia Gori Lusa, Sven Falke, Christian Betzel, Carsten Wrenger
One recent new approach in drug discovery uses bioinformatics tools and the so-called genome mining approach. It is based on the search of biosynthetic gene clusters which correspond to new secondary metabolites. The approach has the advantage to utilize an enormous quantity of data; however, it is hard to predict the biological activity of these compounds (Ziemert et al., 2016). Further, the use of bioinformatics allowed the discovery of biosynthetic products that are silent under standard laboratory conditions. Cloning these genes and changing their natural promoter may render interesting bioactive metabolites (Wohlleben et al., 2016). However, genome mining relies on homology search and genes with still unknown pathways may remain unrecognized. One alternative is to look at regulatory sequences and their DNA sequences motifs, which are in the focus of strategies to Identify Natural compound Biosynthesis pathways by Exploiting knowledge of Transcriptional regulation (INBEKT) (Spohn et al., 2016).
Supermolecular Catalysts
Published in Qingmin Ji, Harald Fuchs, Soft Matters for Catalysts, 2019
Shangbin Jin, Jiang He, Qingmin Ji, Jonathan P. Hill, Katsuhiko Ariga
Nature provides a vast amount of enzyme resources. As the total number of microbial cells on Earth is estimated to be 1030, microbial hosts have been treated as a huge natural wealth for protein resources. Microorganisms such as E. Coli and S. cerevisiae have been used extensively as microbial hosts for the scale-up production of proteins. However, because the majority of microorganisms have not yet been isolated in pure culture, useful characterization of their enzymes remains quite difficult. Various tools have been expanded for new enzymes, which are (i) metagenome screening [30, 31], (ii) genome mining [32], and (iii) exploring the diversity of extremophiles [33]. Metagenomic screening can be based on either function or sequence approaches. Function-based screening is a straightforward way to isolate genes that show the desired function by direct phenotypical detection, heterologous complementation, and induced gene expression [34]. The sequence-based screening is performed using either the polymerase chain reaction (PCR) or hybridization procedures [35]. The genome mining is based on the vast available information from genome sequence databases, which create large opportunity to find new natural products (including enzymes). Extremophiles are a very interesting source of enzymes with extreme stability under critical conditions. These tools facilitate the easy generation of chimeric enzymes with diverse substrate specificity.
Engineered enzymes and enzyme systems
Published in Ruben Michael Ceballos, Bioethanol and Natural Resources, 2017
Bioprospecting for high-performance natural lignocellulolytic enzymes and enzyme engineering are the ways in which the scientific community has been addressing this need. Common strategies include genome mining in sequenced microbial genomes (Ahmed, 2009; Davidsen et al., 2010); metagenome screening (Handelsman et al., 1998; Srivastava et al., 2013); bioprospecting in extremo- or mesophilic fungi and bacteria (Schiraldi and De Rosa, 2002; Kumar et al., 2011a); and engineering enzymes with properties such as higher efficiency, increased thermostability, and greater tolerance to end-product inhibition.
Evidence of p-nitrophenol Biodegradation and Study of Genomic Attributes from a Newly Isolated Aquatic Bacterium Pseudomonas Asiatica Strain PNPG3
Published in Soil and Sediment Contamination: An International Journal, 2022
Sk Aftabul Alam, Pradipta Saha
The manuscript discusses a PNP degrading Gram-negative bacterial strain designated as PNPG3, isolated from a novel site, Ganges water, Chinsura, in Hooghly district, W.B, India. The strain was identified as Pseudomonas asiatica based on genome sequence data. The strain was capable of utilizing PNP under catabolic conditions and was able to carry out biodegradation of 97% of the 0.5 mM PNP within 60 h with concomitant release of nitrite. It could tolerate PNP up to 6 mM and is one of the highest tolerances ever reported. It was able to degrade PNP via the PBQ pathway. The presence of the 9322bp PNP catabolic gene cluster (pdcABC1C2DEFG) was recorded by the genome mining study of its draft genome, sequenced using the Illumina HiseqX platform. Among the genes with the catabolic gene cluster, pdcA was confirmed to be a homolog of PNP 4-monooxygenase. Multiomics approaches may be used to enhance a better understanding of the molecular mechanism of PNP biodegradation. Further bioremediation studies may be attempted for the effective removal of PNP-contaminated waterbodies by this strain.