Biology subjects

Ashari Ghomi, F.

Publications and source records attributed to Ashari Ghomi, F..

3 recordsLinked to original sources

bioRxiv2022

High-throughput transposon mutagenesis in the family Enterobacteriaceae reveals core essential genes and rapid turnover of essentiality

The Enterobacteriaceae are a scientifically and medically important clade of bacteria, containing the gut commensal and model organism Escherichia coli, as well as several major human pathogens including multiple serovars of Salmonella enterica and Klebsiella pneumoniae. Essential gene sets have been determined for several members of the Enterobacteriaceae, with the E. coli Keio single-gene deletion library often regarded as a gold standard for gene essentiality studies. However, it remains unclear how gene essentiality varies between related strains and species. To investigate this, we have assembled a collection of thirteen sequenced high-density transposon mutant libraries from five genera within the Enterobacteriaceae. We first benchmark a number of gene essentiality prediction approaches, investigate the effects of transposon density on essentiality prediction, and identify biases in transposon insertion sequencing data. Based on these investigations we develop a new classifier for gene essentiality. Using this new classifier, we define a core essential genome in the Enterobacteriaceae of 201 universally essential genes, and reconstruct an ancestral essential gene set of 296 genes. Despite the presence of a large cohort of variably essential genes, surprisingly we find an absence of evidence for genus-specific essential genes. A clear example of this sporadic essentiality is given by the set of genes regulating the {sigma}E extracytoplasmic stress response, which appears to have independently become essential multiple times in the Enterobacteriaceae. Finally, we compare our essential gene sets to the natural experiment of gene loss in obligate insect endosymbionts that have emerged from within the Enterobacteriaceae. This isolates a remarkably small set of genes absolutely required for survival, and uncovers several instances of essential stress responses masked by redundancy in free-living bacteria.

microbiology↗

bioRxiv2020

A benchmark of protein solubility prediction methods on UDP-dependent glycosyltransferases

UDP-dependent glycosyltransferases (UGTs) are enzymes that glycosylate a wide variety of natural products, thereby modifying their physico-chemical properties, i.e. solubility, stability, reactivity, and function. To successfully leverage the UGTs in biocatalytic processes, we need to be able to screen and characterise them in vitro, which requires efficient heterologous expression in amenable hosts, preferably Escherichia coli. However, many UGTs are insoluble when expressed in standard and attempted optimised E. coli conditions, resulting in many unproductive and costly experiments. To overcome this limitation, we have investigated the performance of 11 existing solubility predictors on a dataset of 57 UGTs expressed in E. coli. We show that SoluProt outperforms other methods in terms of both threshold-independent and threshold-dependent measures. Among the benchmarked methods, only SoluProt is significantly better than random predictors using both measures. Moreover, we show that SoluProt uses a threshold for separating soluble and insoluble proteins that is optimal for our dataset. Hence, we conclude that using SoluProt to select UGT sequences for in vitro investigation will significantly increase the success rate of soluble expression, thereby minimising cost and enabling efficient characterisation efforts for biocatalysis research.

biochemistry↗

bioRxiv2016

A meta-analysis of bioinformatics softwarebenchmarks reveals that publication-bias undulyinfluences software accuracy

BackgroundComputational biology provides widely used and powerful software tools for testing and making inferences about biological data. In the face of rapidly increasing volumes of data, heuristic methods that trade software speed for accuracy may be employed. We are have studied these trade-offs using the results of a large number of independent software benchmarks, and evaluated whether external factors are indicative of accurate software. MethodWe have extracted accuracy and speed ranks from independent benchmarks of different bioinformatic software tools, and evaluated whether the speed, author reputation, journal impact, recency and developer efforts are indicative of accuracy. ResultsWe found that software speed, author reputation, journal impact, number of citations and age are all unreliable predictors of software accuracy. This is unfortunate because citations, author and journal reputation are frequently cited reasons for selecting software tools. However, GitHub-derived records and high version numbers show that the accurate bioinformatic software tools are generally the product of many improvements over time, often from multiple developers. DiscussionWe also find that the field of bioinformatics has a large excess of slow and inaccurate software tools, and this is consistent across many sub-disciplines. Meanwhile, there are few tools that are middle-of-road in terms of accuracy and speed trade-offs. We hypothesise that a form of publication-bias influences the publication and development of bioinformatic software. In other words, software that is intermediate in terms of both speed and accuracy may be difficult to publish - possibly due to author, editor and reviewer practices. This leaves an unfortunate hole in the literature as the ideal tools may fall into this gap. For example, high accuracy tools are not always useful if years of CPU time are required, while high speed is not useful if the results are also inaccurate.

bioinformatics↗