Harnessing model organism genomics to underpin the machine learning-based prediction of essential genes in eukaryotes - Biotechnological implications.

The availability of high-quality genomes and advances in functional genomics have enabled large-scale studies of essential genes in model eukaryotes, including the 'elegant worm' (Caenorhabditis elegans; Nematoda) and the 'vinegar fly' (Drosophila melanogaster; Arthropoda). However, this is not the case for other, much less-studied organisms, such as socioeconomically important parasites, for which functional genomic platforms usually do not exist. Thus, there is a need to develop innovative techniques or approaches for the prediction, identification and investigation of essential genes. A key approach that could enable the prediction of such genes is machine learning (ML). Here, we undertake an historical review of experimental and computational approaches employed for the characterisation of essential genes in eukaryotes, with a particular focus on model ecdysozoans (C. elegans and D. melanogaster), and discuss the possible applicability of ML-approaches to organisms such as socioeconomically important parasites. We highlight some recent results showing that high-performance ML, combined with feature engineering, allows a reliable prediction of essential genes from extensive, publicly available 'omic data sets, with major potential to prioritise such genes (with statistical confidence) for subsequent functional genomic validation. These findings could 'open the door' to fundamental and applied research areas. Evidence of some commonality in the essential gene-complement between these two organisms indicates that an ML-engineering approach could find broader applicability to ecdysozoans such as parasitic nematodes or arthropods, provided that suitably large and informative data sets become/are available for proper feature engineering, and for the robust training and validation of algorithms. This area warrants detailed exploration to, for example, facilitate the identification and characterisation of essential molecules as novel targets for drugs and vaccines against parasitic diseases. This focus is particularly important, given the substantial impact that such diseases have worldwide, and the current challenges associated with their prevention and control and with drug resistance in parasite populations.

Gene replacement and quantitative mass spectrometry approaches validate guanosine monophosphate synthetase as essential for Mycobacterium tuberculosis growth.

Guanosine monophosphate synthetase (GMPS), encoded by guaA gene, is a key enzyme for guanine nucleotide biosynthesis in Mycobacterium tuberculosis. The guaA gene from several bacterial pathogens has been shown to be involved in virulence; however, no information about the physiological effect of direct guaA deletion in M. tuberculosis has been described so far. Here, we demonstrated that the guaA gene is essential for M. tuberculosis H37Rv growth. The lethal phenotype of guaA gene disruption was avoided by insertion of a copy of the ortholog gene from Mycobacterium smegmatis, indicating that this GMPS protein is functional in M. tuberculosis. Protein validation of the guaA essentiality observed by PCR was approached by shotgun proteomic analysis. A quantitative method was performed to evaluate protein expression levels, and to check the origin of common and unique peptides from M. tuberculosis and M. smegmatis GMPS proteins. These results validate GMPS as a molecular target for drug design against M. tuberculosis, and GMPS inhibitors might prove to be useful for future development of new drugs to treat human tuberculosis.

The essential gene YMR134W from Saccharomyces cerevisiae is important for appropriate mitochondrial iron utilization and the ergosterol biosynthetic pathway.

A thermosensitive strain (YMR134W(ts)) of the essential gene YMR134W presented up to 40% less ergosterol, threefold lower oxygen consumption and impaired growth on respiratory conditions. The iron content in the mitochondrial fraction of YMR134W(ts) cells was considerably low, despite these cells uptake and accumulate more iron from the culture media than wild-type cells. YMR134W(ts) cells were also more susceptible to oxidative stress. The results suggest that Ymr134wp is essential to aerobic growth due to its function in ergosterol biosynthesis, playing a role in maintaining mitochondrial and plasma membrane integrity and consequently impacting the iron homeostasis, respiratory metabolism and antioxidant response.