Position preference of essential genes in prokaryotic operons.
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ABSTRACT:
SUBMITTER: Liu T
PROVIDER: S-EPMC8061932 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:We present a study on computational identification of uber-operons in a prokaryotic genome, each of which represents a group of operons that are evolutionarily or functionally associated through operons in other (reference) genomes. Uber-operons represent a rich set of footprints of operon evolution, whose full utilization could lead to new and more powerful tools for elucidation of biological pathways and networks than what operons have provided, and a better understanding of prokaryotic genome structures and evolution. Our prediction algorithm predicts uber-operons through identifying groups of functionally or transcriptionally related operons, whose gene sets are conserved across the target and multiple reference genomes. Using this algorithm, we have predicted uber-operons for each of a group of 91 genomes, using the other 90 genomes as references. In particular, we predicted 158 uber-operons in Escherichia coli K12 covering 1830 genes, and found that many of the uber-operons correspond to parts of known regulons or biological pathways or are involved in highly related biological processes based on their Gene Ontology (GO) assignments. For some of the predicted uber-operons that are not parts of known regulons or pathways, our analyses indicate that their genes are highly likely to work together in the same biological processes, suggesting the possibility of new regulons and pathways. We believe that our uber-operon prediction provides a highly useful capability and a rich information source for elucidation of complex biological processes, such as pathways in microbes. All the prediction results are available at our Uber-Operon Database: http://csbl.bmb.uga.edu/uber, the first of its kind.
| S-EPMC1458513 | biostudies-literature
Project description:Essential genes are thought to encode proteins that carry out the basic functions to sustain a cellular life, and genomic islands (GIs) usually contain clusters of horizontally transferred genes. It has been assumed that essential genes are not likely to be located in GIs, but systematical analysis of essential genes in GIs has not been explored before. Here, we have analyzed the essential genes in 28 prokaryotes by statistical method and reached a conclusion that essential genes in GIs are significantly fewer than those outside GIs. The function of 362 essential genes found in GIs has been explored further by BLAST against the Virulence Factor Database (VFDB) and the phage/prophage sequence database of PHAge Search Tool (PHAST). Consequently, 64 and 60 eligible essential genes are found to share the sequence similarity with the virulence factors and phage/prophages-related genes, respectively. Meanwhile, we find several toxin-related proteins and repressors encoded by these essential genes in GIs. The comparative analysis of essential genes in genomic islands will not only shed new light on the development of the prediction algorithm of essential genes, but also give a clue to detect the functionality of essential genes in genomic islands.
| S-EPMC4519734 | biostudies-literature
Project description:The tetralin biodegradation genes of Sphingomonas macrogolitabida strain TFA are clustered in two closely linked and divergent operons. To analyze expression of both operons under different growth conditions, transcriptional and translational gene fusions of the first genes of each operon to lacZ have been constructed in plasmids unable to replicate in Sphingomonas and integrated by recombination into the genome of strain TFA. Expression analysis indicated that the transcription of both genes is induced in similar ways by the presence of tetralin. Gene expression in both operons is also subjected to overimposed catabolic repression. Two additional genes named thnR and thnY have been identified downstream of thnCA3A4 genes. ThnR is similar to LysR-type regulators, and mutational analysis indicated that ThnR is strictly required for expression of the thn operons. Unlike other LysR-type regulators, ThnR does not repress its own synthesis. In fact, ThnR activates its own expression, since thnR is cotranscribed with the thnCA3A4 genes. ThnY is similar to the ferredoxin reductase components of dioxygenase systems and shows the fer2 domain, binding a Cys4[2Fe-2S] iron sulfur center, and the FAD-binding domain, common to those reductases. However, it lacks the NAD-binding domain. Intriguingly, ThnY has a regulatory role, since it is also strictly required for expression of the thn operons. Given the similarity of ThnY to reductases and the possibility of its being present in the two redox states, it is tempting to speculate that ThnY is a regulatory component connecting expression of the thn operons to the physiological status of the cell.
| S-EPMC515167 | biostudies-literature
Project description:Large-scale systematic analysis of gene essentiality is an important step closer toward unraveling the complex relationship between genotypes and phenotypes. Such analysis cannot be accomplished without unbiased and accurate annotations of essential genes. In current genomic databases, most of the essential gene annotations are derived from whole-genome transposon mutagenesis (TM), the most frequently used experimental approach for determining essential genes in microorganisms under defined conditions. However, there are substantial systematic biases associated with TM experiments. In this study, we developed a novel Poisson model-based statistical framework to simulate the TM insertion process and subsequently correct the experimental biases. We first quantitatively assessed the effects of major factors that potentially influence the accuracy of TM and subsequently incorporated relevant factors into the framework. Through iteratively optimizing parameters, we inferred the actual insertion events occurred and described each gene's essentiality on probability measure. Evaluated by the definite mapping of essential gene profile in Escherichia coli, our model significantly improved the accuracy of original TM datasets, resulting in more accurate annotations of essential genes. Our method also showed encouraging results in improving subsaturation level TM datasets. To test our model's broad applicability to other bacteria, we applied it to Pseudomonas aeruginosa PAO1 and Francisella tularensis novicida TM datasets. We validated our predictions by literature as well as allelic exchange experiments in PAO1. Our model was correct on six of the seven tested genes. Remarkably, among all three cases that our predictions contradicted the TM assignments, experimental validations supported our predictions. In summary, our method will be a promising tool in improving genomic annotations of essential genes and enabling large-scale explorations of gene essentiality. Our contribution is timely considering the rapidly increasing essential gene sets. A Webserver has been set up to provide convenient access to this tool. All results and source codes are available for download upon publication at http://research.cchmc.org/essentialgene/.
| S-EPMC3592911 | biostudies-literature
Project description:In 2003, we developed an ab initio program, ZCURVE 1.0, to find genes in bacterial and archaeal genomes. In this work, we present the updated version (i.e. ZCURVE 3.0). Using 422 prokaryotic genomes, the average accuracy was 93.7% with the updated version, compared with 88.7% with the original version. Such results also demonstrate that ZCURVE 3.0 is comparable with Glimmer 3.02 and may provide complementary predictions to it. In fact, the joint application of the two programs generated better results by correctly finding more annotated genes while also containing fewer false-positive predictions. As the exclusive function, ZCURVE 3.0 contains one post-processing program that can identify essential genes with high accuracy (generally >90%). We hope ZCURVE 3.0 will receive wide use with the web-based running mode. The updated ZCURVE can be freely accessed from http://cefg.uestc.edu.cn/zcurve/ or http://tubic.tju.edu.cn/zcurveb/ without any restrictions.
| S-EPMC4489317 | biostudies-literature
Project description:Geptop has performed effectively in the identification of prokaryotic essential genes since its first release in 2013. It estimates gene essentiality for prokaryotes based on orthology and phylogeny. Genome-scale essentiality data of more prokaryotic species are available, and the information has been collected into public essential gene repositories such as DEG and OGEE. A faster and more accurate toolkit is needed to meet the increasing prokaryotic genome data. We updated Geptop by supplementing more validated essentiality data into reference set (from 19 to 37 species), and introducing multi-process technology to accelerate the computing speed. Compared with Geptop 1.0 and other gene essentiality prediction models, Geptop 2.0 can generate more stable predictions and finish the computation in a shorter time. The software is available both as an online server and a downloadable standalone application. We hope that the improved Geptop 2.0 will facilitate researches in gene essentiality and the development of novel antibacterial drugs. The gene essentiality prediction tool is available at http://cefg.uestc.cn/geptop.
| S-EPMC6558110 | biostudies-literature
Project description:Understanding the unique features of triacylglycerol (TAG) metabolism in microalgae may be necessary to realize the full potential of these organisms for biofuel and biomaterial production. In the unicellular green alga Chlamydomonas reinhardtii a chloroplastic (prokaryotic) pathway has been proposed to play a major role in TAG precursor biosynthesis. However, as reported here, C. reinhardtii contains a chlorophyte-specific lysophosphatidic acid acyltransferase, CrLPAAT2, that localizes to endoplasmic reticulum (ER) membranes. Unlike canonical, ER-located LPAATs, CrLPAAT2 prefers palmitoyl-CoA over oleoyl-CoA as the acyl donor substrate. RNA-mediated suppression of CrLPAAT2 indicated that the enzyme is required for TAG accumulation under nitrogen deprivation. Our findings suggest that Chlamydomonas has a distinct glycerolipid assembly pathway that relies on CrLPAAT2 to generate prokaryotic-like TAG precursors in the ER.
| S-EPMC5816170 | biostudies-other
Project description:Scanning of bacterial genomes to identify essential genes is of biological interest, for understanding the basic functions required for life, and of practical interest, for the identification of novel targets for new antimicrobial therapies. In particular, the lack of efficacious antimicrobial treatments for infections caused by the Burkholderia cepacia complex is causing high morbidity and mortality of cystic fibrosis patients and of patients with nosocomial infections. Here, we present a method based on delivery of the tightly regulated rhamnose-inducible promoter P(rhaB) for identifying essential genes and operons in Burkholderia cenocepacia. We demonstrate that different levels of gene expression can be achieved by using two vectors that deliver P(rhaB) at two different distances from the site of insertion. One of these vectors places P(rhaB) at the site of transposon insertion, while the other incorporates the enhanced green fluorescent protein gene (e-gfp) downstream from P(rhaB). This system allows us to identify essential genes and operons in B. cenocepacia and provides a new tool for systematically identifying and functionally characterizing essential genes at the genomic level.
| S-EPMC1448982 | biostudies-literature
Project description:MotivationIt is a fundamental task to identify microRNAs (miRNAs) targets and accurately locate their target sites. Genome-scale experiments for miRNA target site detection are still costly. The prediction accuracies of existing computational algorithms and tools are often not up to the expectation due to a large number of false positives. One major obstacle to achieve a higher accuracy is the lack of knowledge of the target binding features of miRNAs. The published high-throughput experimental data provide an opportunity to analyze position-wise preference of miRNAs in terms of target binding, which can be an important feature in miRNA target prediction algorithms.ResultsWe developed a Markov model to characterize position-wise pairing patterns of miRNA-target interactions. We further integrated this model as a scoring method and developed a dynamic programming (DP) algorithm, MDPS (Markov model-scored Dynamic Programming algorithm for miRNA target site Selection) that can screen putative target sites of miRNA-target binding. The MDPS algorithm thus can take into account both the dependency of neighboring pairing positions and the global pairing information. Based on the trained Markov models from both miRNA-specific and general datasets, we discovered that the position-wise binding information specific to a given miRNA would benefit its target prediction. We also found that miRNAs maintain region-wise similarity in their target binding patterns. Combining MDPS with existing methods significantly improves their precision while only slightly reduces their recall. Therefore, position-wise pairing patterns have the promise to improve target prediction if incorporated into existing software tools.Availability and implementationThe source code and tool to calculate MDPS score is available at http://hulab.ucf.edu/research/projects/MDPS/index.html.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC8453239 | biostudies-literature
Project description:Microbial genes encode the majority of the functional repertoire of life on earth. However, despite increasing efforts in metagenomic sequencing of various habitats1-3, little is known about the distribution of genes across the global biosphere, with implications for human and planetary health. Here we constructed a non-redundant gene catalogue of 303 million species-level genes (clustered at 95% nucleotide identity) from 13,174 publicly available metagenomes across 14 major habitats and use it to show that most genes are specific to a single habitat. The small fraction of genes found in multiple habitats is enriched in antibiotic-resistance genes and markers for mobile genetic elements. By further clustering these species-level genes into 32 million protein families, we observed that a small fraction of these families contain the majority of the genes (0.6% of families account for 50% of the genes). The majority of species-level genes and protein families are rare. Furthermore, species-level genes, and in particular the rare ones, show low rates of positive (adaptive) selection, supporting a model in which most genetic variability observed within each protein family is neutral or nearly neutral.
| S-EPMC7613196 | biostudies-literature