Identification Of Essential Genes Research Articles

Pan-genomic analysis of the species Salmonella enterica: Identification of core essential and putative essential genes

BackgroundEssential genes are defined as the minimal gene set required to support bacterial life. In order to develop new antimicrobials to treat multidrug-resistant pathogens, such as serovars of Salmonella enterica, the identification of essential genes is crucial. MethodologyIn the present work, we hypothesize that essential genes within a group of evolutionary closely related organisms may be highly conserved. We, therefore, conducted an extensive comparative genomic analysis of 44 genome sequences representing 17 serovars of S. enterica to gain an improved understanding of conserved essential genes for its survival. ResultsPan-genome estimates indicate that the genus Salmonella displays an open pan-genome structure comprising a reservoir of 10,775 gene families. Of these, 2847, 4657, and 3271 constitute the core gene families (CGFs), dispensable gene families (DGFs), and strain-specific gene families (SSGFs), respectively. The pan-genome family tree based on the presence/absence of gene families is highly concordant with the 16S rRNA tree, though the former provides a more robust phylogenetic resolution. The Clusters of Orthologous Groups of proteins (COGs) database categorized the vast majority of the CGFs (40.9%) to metabolism, whereas a large proportion of the DGFs (70.6%) was uncharacterized. Homology analysis of the CGFs against the Database of essential genes (DEG) identified 1695 essential CGFs (E-CGFs). Of these, 687 are experimentally verified as essential in Salmonella, 1157 are identified in ≥2 species, 159 are conserved in ≥7 species, and 538 were present in at least one species. Thus, for the species, S. enterica 69%, 52%, and 31% of the genome are dedicated to the core, essential, and dispensable functions, respectively. ConclusionThe E-CGFs identified may serve as important targets for the development of novel antimicrobials, and their detailed analysis may shed new light on a better understanding of Salmonella's survival.

Genome-wide identification of essential genes in Mycobacterium intracellulare by transposon sequencing \u2014 Implication for metabolic remodeling

The global incidence of the human nontuberculous mycobacteria (NTM) disease is rapidly increasing. However, knowledge of gene essentiality under optimal growth conditions and conditions relevant to the natural ecology of NTM, such as hypoxia, is lacking. In this study, we utilized transposon sequencing to comprehensively identify genes essential for growth in Mycobacterium intracellulare. Of 5126 genes of M. intracellulare ATCC13950, 506 genes were identified as essential genes, of which 280 and 158 genes were shared with essential genes of M. tuberculosis and M. marinum, respectively. The shared genes included target genes of existing antituberculous drugs including SQ109, which targets the trehalose monomycolate transporter MmpL3. From 175 genes showing decreased fitness as conditionally essential under hypoxia, preferential carbohydrate metabolism including gluconeogenesis, glyoxylate cycle and succinate production was suggested under hypoxia. Virulence-associated genes including proteasome system and mycothiol redox system were also identified as conditionally essential under hypoxia, which was further supported by the higher effective suppression of bacterial growth under hypoxia compared to aerobic conditions in the presence of these inhibitors. This study has comprehensively identified functions essential for growth of M. intracellulare under conditions relevant to the host environment. These findings provide critical functional genomic information for drug discovery.

Intelligent Classification and Analysis of Essential Genes Using Quantitative Methods

Essential genes are considered to be the genes required to sustain life of different organisms. These genes encode proteins that maintain central metabolism, DNA replications, translation of genes, and basic cellular structure, and mediate the transport process within and out of the cell. The identification of essential genes is one of the essential problems in computational genomics. In this present study, to discriminate essential genes from other genes from a non-biologists perspective, the purine and pyrimidine distribution over the essential genes of four exemplary species, namely Homo sapiens , Arabidopsis thaliana , Drosophila melanogaster , and Danio rerio are thoroughly experimented using some quantitative methods. Moreover, the Indigent classification method has also been deployed for classification on the essential genes of the said species. Based on Shannon entropy, fractal dimension, Hurst exponent, and purine and pyrimidine bases distribution, 10 different clusters have been generated for the essential genes of the four species. Some proximity results are also reported herewith for the clusters of the essential genes.

A Novel Tool for the Generation of Conditional Knockouts To Study Gene Function across the Plasmodium falciparum Life Cycle.

Plasmodium falciparum has a complex life cycle that involves interaction with multiple tissues inside the human and mosquito hosts. Identification of essential genes at all different stages of the P. falciparum life cycle is urgently required for clinical development of tools for malaria control and eradication. However, the study of P. falciparum is limited by the inability to genetically modify the parasite throughout its life cycle with the currently available genetic tools. Here, we describe the detailed characterization of a new marker-free P. falciparum parasite line that expresses rapamycin-inducible Cre recombinase across the full life cycle. Using this parasite line, we were able to conditionally delete the essential invasion ligand AMA1 in three different developmental stages for the first time. We further confirm efficient gene deletion by targeting the nonessential kinase FIKK7.1.IMPORTANCE One of the major limitations in studying P. falciparum is that so far only asexual stages are amenable to rapid conditional genetic modification. The most promising drug targets and vaccine candidates, however, have been refractory to genetic modification because they are essential during the blood stage or for transmission in the mosquito vector. This leaves a major gap in our understanding of parasite proteins in most life cycle stages and hinders genetic validation of drug and vaccine targets. Here, we describe a method that supports conditional gene deletion across the P. falciparum life cycle for the first time. We demonstrate its potential by deleting essential and nonessential genes at different parasite stages, which opens up completely new avenues for the study of malaria and drug development. It may also allow the realization of novel vaccination strategies using attenuated parasites.

EPath: an online database towards comprehensive essential gene annotation for prokaryotes

Experimental techniques for identification of essential genes (EGs) in prokaryotes are usually expensive, time-consuming and sometimes unrealistic. Emerging in silico methods provide alternative methods for EG prediction, but often possess limitations including heavy computational requirements and lack of biological explanation. Here we propose a new computational algorithm for EG prediction in prokaryotes with an online database (ePath) for quick access to the EG prediction results of over 4,000 prokaryotes (https://www.pubapps.vcu.edu/epath/). In ePath, gene essentiality is linked to biological functions annotated by KEGG Ortholog (KO). Two new scoring systems, namely, E_score and P_score, are proposed for each KO as the EG evaluation criteria. E_score represents appearance and essentiality of a given KO in existing experimental results of gene essentiality, while P_score denotes gene essentiality based on the principle that a gene is essential if it plays a role in genetic information processing, cell envelope maintenance or energy production. The new EG prediction algorithm shows prediction accuracy ranging from 75% to 91% based on validation from five new experimental studies on EG identification. Our overall goal with ePath is to provide a comprehensive and reliable reference for gene essentiality annotation, facilitating the study of those prokaryotes without experimentally derived gene essentiality information.

A new inducible CRISPR-Cas9 system useful for genome editing and study of double-strand break repair in Candida glabrata.

In recent years, the CRISPR-Cas9 system has proven extremely useful for genome editing in many species, including the model yeast Saccharomyces cerevisiae and other yeast species such as Candida glabrata. Inducible CRISPR-Cas9 systems have the additional advantage of allowing to separate the transformation step of the organism by the CRISPR-Cas9 system, from the cutting and repair steps. This has indeed been developed in S.cerevisiae, where most inducible expression systems rely on the GAL promoters. Unfortunately, C.glabrata is gal- and lacks the GAL genes, like many other yeast species. We report here the use of a vector expressing cas9 under the control of the MET3 promoter, with the guide RNA cloned into the same plasmid. We show that it can be used efficiently in C.glabrata, for both described outcomes of CRISPR-Cas9-induced chromosome breaks; nonhomologous end joining in the absence of a homologous repair template; and homologous recombination in the presence of such a template. This system therefore allows easy editing of the genome of C.glabrata, and its inducibility may allow identification of essential genes in this asexual yeast, where spore lethality cannot be observed, as well as the study of double-strand break repair.

Defining Human Pluripotency.

Human pluripotent stem cells harbor the capacity to differentiate into cells from the three embryonic germ layers, and this ability grants them a central role in modeling human disorders and in the field of regenerative medicine. Here, we review pluripotency in human cells with respect to four different aspects: (1) embryonic development, (2) transcriptomes of pluripotent cell stages, (3) genes and pathways that reprogram somatic cells into pluripotent stem cells, and finally (4) the recent identification of the human pluripotent stem cell essentialome. These four aspects of pluripotency collectively culminate in a broader understanding of what makes a cell pluripotent.

A large-scale CRISPR screen and identification of essential genes in cellular senescence bypass.

Cellular senescence is an important mechanism of autonomous tumor suppression, while its consequence such as the senescence-associated secretory phenotype (SASP) may drive tumorigenesis and age-related diseases. Therefore, controlling the cell fate optimally when encountering senescence stress is helpful for anti-cancer or anti-aging treatments. To identify genes essential for senescence establishment or maintenance, we carried out a CRISPR-based screen with a deliberately designed single-guide RNA (sgRNA) library. The library comprised of about 12,000 kinds of sgRNAs targeting 1378 senescence-associated genes selected by integrating the information of literature mining, protein-protein interaction network, and differential gene expression. We successfully detected a dozen gene deficiencies potentially causing senescence bypass, and their phenotypes were further validated with a high true positive rate. RNA-seq analysis showed distinct transcriptome patterns of these bypass cells. Interestingly, in the bypass cells, the expression of SASP genes was maintained or elevated with CHEK2, HAS1, or MDK deficiency; but neutralized with MTOR, CRISPLD2, or MORF4L1 deficiency. Pathways of some age-related neurodegenerative disorders were also downregulated with MTOR, CRISPLD2, or MORF4L1 deficiency. The results demonstrated that disturbing these genes could lead to distinct cell fates as a consequence of senescence bypass, suggesting that they may play essential roles in cellular senescence.

A Novel Method for Identifying Essential Genes by Fusing Dynamic Protein⁻Protein Interactive Networks.

Essential genes play an indispensable role in supporting the life of an organism. Identification of essential genes helps us to understand the underlying mechanism of cell life. The essential genes of bacteria are potential drug targets of some diseases genes. Recently, several computational methods have been proposed to detect essential genes based on the static protein–protein interactive (PPI) networks. However, these methods have ignored the fact that essential genes play essential roles under certain conditions. In this work, a novel method was proposed for the identification of essential proteins by fusing the dynamic PPI networks of different time points (called by FDP). Firstly, the active PPI networks of each time point were constructed and then they were fused into a final network according to the networks’ similarities. Finally, a novel centrality method was designed to assign each gene in the final network a ranking score, whilst considering its orthologous property and its global and local topological properties in the network. This model was applied on two different yeast data sets. The results showed that the FDP achieved a better performance in essential gene prediction as compared to other existing methods that are based on the static PPI network or that are based on dynamic networks.

IEsGene-ZCPseKNC: Identify Essential Genes Based on Z Curve Pseudo $k$ -Tuple Nucleotide Composition

As an important technique for synthetic biology, computational identification of essential genes will facilitate the development of the related fields, such as genome analysis, drug design, etc. The identification of prokaryotic essential genes has been extensively studied, especially focusing on the essential genes in bacteria. Archaea as an important domain in prokaryote exists high variance of genome sizes. However, there is no predictor available for predicting essential genes in archaea. In this paper, we developed the first computational predictor for predicting essential genes in archaea called iEsGene-ZCPseKNC. With the purpose of capturing sequence patterns of the essential genes, a new feature called Z curve pseudo $k$ -tuple nucleotide composition (ZCPseKNC) was proposed, which incorporates the advantages of both Z curve and pseudo $k$ -tuple nucleotide composition (PseKNC). In order to overcome the problems caused by the imbalanced training set, the SMOTE algorithm was employed to further improve the predictive performance of iEsGene-ZCPseKNC. Evaluated by the rigorous jackknife test on a benchmark dataset, the experimental results showed that the iEsGene-ZCPseKNC predictor outperformed the predictors based on Z curve and PseKNC, indicating that iEsGene-ZCPseKNC is useful for identification of essential genes in archaea, and would be a powerful tool for genome analysis. A user friendly web server of the iEsGene-ZCPseKNC predictor was established and can be easily accessed from http://bliulab.net/iEsGene-ZCPseKNC/ .

Comprehensive review of the identification of essential genes using computational methods: focusing on feature implementation and assessment.

Essential genes have attracted increasing attention in recent years due to the important functions of these genes in organisms. Among the methods used to identify the essential genes, accurate and efficient computational methods can make up for the deficiencies of expensive and time-consuming experimental technologies. In this review, we have collected researches on essential gene predictions in prokaryotes and eukaryotes and summarized the five predominant types of features used in these studies. The five types of features include evolutionary conservation, domain information, network topology, sequence component and expression level. We have described how to implement the useful forms of these features and evaluated their performance based on the data of Escherichia coli MG1655, Bacillus subtilis 168 and human. The prerequisite and applicable range of these features is described. In addition, we have investigated the techniques used to weight features in various models. To facilitate researchers in the field, two available online tools, which are accessible for free and can be directly used to predict gene essentiality in prokaryotes and humans, were referred. This article provides a simple guide for the identification of essential genes in prokaryotes and eukaryotes.

The Escherichia coli bcsB gene is a conditional essential gene in the context of functional cellulose synthesis.

The understanding of why a gene is essential for a bacterium has implications in different research areas, such as bacterial evolution, synthetic biology and biotechnology, making the identification of essential genes a very active research field. Bacterial essential genes have been defined, among other criteria, by the inability to obtain viable mutants in such genes. In the case of Escherichia coli this approach led to the construction of the Keio collection of single-gene knockout mutants that contains deletions of all the open reading frames present in the genome with the exception of 303 genes that were found to be essential for the growth of this bacterium. One of the genes that was identified as essential is bcsB, which is involved in synthesis of extracellular cellulose. However, the reason for the essential nature of BcsB for E. coli viability has not been determined. In this work we show that bcsB is essential only in strains that have a functional capacity to synthesize cellulose, presumably due to the activity of BcsB in the translocation of this polymer across the periplasm. Thus, we propose that bcsB is a conditionally essential gene in E. coli.

Abstract IA25: Identification of essential genes for cancer immunotherapy

Abstract Cancer immunotherapies can trigger dramatic responses in a subset of patients, but many patients with common types of cancer (e.g., breast, ovary, pancreatic, brain and colon) do not experience significant benefit from immunotherapy. The priority now must be determining what makes some cancers resist the immune system, even after treatments designed to fortify the body’s natural antitumor capabilities. Understanding the mechanisms of immune resistance and tumor escape could help enhance tumor immunotherapy. Virtually every cancer contains mutations within protein-encoding genes. These mutations can create targets that can be recognized by immune cells, but mutations may also impair immune recognition and enable immune escape. We have previously observed that cancer cells can escape immune recognition via loss of heterozygosity (LOH) and mutations in β2 microglobulin, which are common in human tumors. These historical findings are important because current cancer immunotherapies mostly rely on T cells, which are adept at recognizing cells in which genetic disruptions have generated aberrant proteins. Anti-CTLA-4 or PD1/PDL1 work in large part by releasing natural checkpoints that constrain T-cell activity. Chimeric antigen receptor T-cell therapies (CAR-T), generated by genetically altering a patient’s T cells, can trigger long-lasting remissions in some patients with blood cancers, but have not yet been definitively found to be effective in solid cancers. These therapies build on a deep understanding of T-cell biology gleaned from decades of basic research. To obtain a more complete, whole-genome visualization of why immunotherapies sometimes fail, we explored the factors that influence tumor cells’ vulnerability to T-cell killing. Using a library of 123,000 guide RNAs, we employed a CRISPR-Cas9 system to systematically eliminate the function of every protein-encoding gene. Surprisingly, this genome-wide screen identified dozens of new genes that potentially influence tumor cells’ susceptibility to T-cell attack. When these genes were knocked-out, tumor cells were significantly more likely to survive and continue to multiply after exposure to T cells that we had genetically engineered to recognize tumor-associated antigens. Many of the genes identified in our screen were previously known to be involved in T cell-tumor cell interactions, including those mediating antigen processing and presentation and responses to cytokines. However, dozens of unique “hits” from the CRISPR screen had not previously been linked to T cells’ ability to eliminate their targets. Loss-of-function mutations in these novel resistance genes were found at high rates in patients for whom immunotherapies failed. Given the diverse gene set revealed by our CRISPR screens and the complexity of the tumor microenvironment, which can include high levels of immunosuppressive potassium, it seems unlikely that a single “fix” will enhance immunotherapy. Instead, we must develop a new category of drugs that circumvent these escape mechanisms. We hope our findings will serve as a blueprint to guide comprehensive studies of what makes some tumors resist T-cell control. Ultimately, novel combination immunotherapies based on individual gene mutations may enable the expansion of curative immunotherapy. Selected

Genome-Wide Determination of Gene Essentiality by Transposon Insertion Sequencing in Yeast Pichia pastoris

In many prokaryotes but limited eukaryotic species, the combination of transposon mutagenesis and high-throughput sequencing has greatly accelerated the identification of essential genes. Here we successfully applied this technique to the methylotrophic yeast Pichia pastoris and classified its conditionally essential/non-essential gene sets. Firstly, we showed that two DNA transposons, TcBuster and Sleeping beauty, had high transposition activities in P. pastoris. By merging their insertion libraries and performing Tn-seq, we identified a total of 202,858 unique insertions under glucose supported growth condition. We then developed a machine learning method to classify the 5,040 annotated genes into putatively essential, putatively non-essential, ambig1 and ambig2 groups, and validated the accuracy of this classification model. Besides, Tn-seq was also performed under methanol supported growth condition and methanol specific essential genes were identified. The comparison of conditionally essential genes between glucose and methanol supported growth conditions helped to reveal potential novel targets involved in methanol metabolism and signaling. Our findings suggest that transposon mutagenesis and Tn-seq could be applied in the methylotrophic yeast Pichia pastoris to classify conditionally essential/non-essential gene sets. Our work also shows that determining gene essentiality under different culture conditions could help to screen for novel functional components specifically involved in methanol metabolism.

The Essential Genome of Escherichia coli K-12.

ABSTRACTTransposon-directed insertion site sequencing (TraDIS) is a high-throughput method coupling transposon mutagenesis with short-fragment DNA sequencing. It is commonly used to identify essential genes. Single gene deletion libraries are considered the gold standard for identifying essential genes. Currently, the TraDIS method has not been benchmarked against such libraries, and therefore, it remains unclear whether the two methodologies are comparable. To address this, a high-density transposon library was constructed in Escherichia coli K-12. Essential genes predicted from sequencing of this library were compared to existing essential gene databases. To decrease false-positive identification of essential genes, statistical data analysis included corrections for both gene length and genome length. Through this analysis, new essential genes and genes previously incorrectly designated essential were identified. We show that manual analysis of TraDIS data reveals novel features that would not have been detected by statistical analysis alone. Examples include short essential regions within genes, orientation-dependent effects, and fine-resolution identification of genome and protein features. Recognition of these insertion profiles in transposon mutagenesis data sets will assist genome annotation of less well characterized genomes and provides new insights into bacterial physiology and biochemistry.

Genomewide Identification of Essential Genes and Fitness Determinants of Streptococcus mutans UA159.

Transposon mutagenesis coupled with next-generation DNA sequencing (Tn-seq) is a powerful tool for discovering regions of the genome that are required for the survival of bacteria in different environments. We adapted this technique to the dental caries pathogen Streptococcus mutans UA159 and identified 11% of the genome as essential, with many genes encoding products required for replication, translation, lipid metabolism, and cell wall biogenesis. Comparison of the essential genome of S.mutans UA159 with those of selected other streptococci for which such information is available revealed several metabolic pathways and genes that are required in S.mutans, but not in some Streptococcus spp. We further identified genes that are essential for sustained growth in rich or defined medium, as well as for persistence in vivo in a rodent model of oral infection. Collectively, our results provide a novel and comprehensive view of the genes required for essential processes of S.mutans, many of which could represent potential targets for therapeutics. IMPORTANCE Tooth decay (dental caries) is a common cause of pain, impaired quality of life, and tooth loss in children and adults. It begins because of a compositional change in the microorganisms that colonize the tooth surface driven by repeated and sustained carbohydrate intake. Although several bacterial species are associated with tooth decay, Streptococcus mutans is the most common cause. Therefore, it is important to identify biological processes that contribute to the survival of S.mutans in the human mouth, with the aim of disrupting the processes with antimicrobial agents. We successfully applied Tn-seq to S.mutans, discovering genes that are required for survival, growth, and persistence, both in laboratory environments and in a mouse model of tooth decay. This work highlights new avenues for the control of an important human pathogen.

A Comprehensive Overview of Online Resources to Identify and Predict Bacterial Essential Genes.

Genes critical for the survival or reproduction of an organism in certain circumstances are classified as essential genes. Essential genes play a significant role in deciphering the survival mechanism of life. They may be greatly applied to pharmaceutics and synthetic biology. The continuous progress of experimental method for essential gene identification has accelerated the accumulation of gene essentiality data which facilitates the study of essential genes in silico. In this article, we present some available online resources related to gene essentiality, including bioinformatic software tools for transposon sequencing (Tn-seq) analysis, essential gene databases and online services to predict bacterial essential genes. We review several computational approaches that have been used to predict essential genes, and summarize the features used for gene essentiality prediction. In addition, we evaluate the available online bacterial essential gene prediction servers based on the experimentally validated essential gene sets of 30 bacteria from DEG. This article is intended to be a quick reference guide for the microbiologists interested in the essential genes.

Sequence-based information-theoretic features for gene essentiality prediction

BackgroundIdentification of essential genes is not only useful for our understanding of the minimal gene set required for cellular life but also aids the identification of novel drug targets in pathogens. In this work, we present a simple and effective gene essentiality prediction method using information-theoretic features that are derived exclusively from the gene sequences.ResultsWe developed a Random Forest classifier and performed an extensive model performance evaluation among and within 15 selected bacteria. In intra-organism predictions, where training and testing sets are taken from the same organism, AUC (Area Under the Curve) scores ranging from 0.73 to 0.90, 0.84 on average, were obtained. Cross-organism predictions using 5-fold cross-validation, pairwise, leave-one-species-out, leave-one-taxon-out, and cross-taxon yielded average AUC scores of 0.88, 0.75, 0.80, 0.82, and 0.78, respectively. To further show the applicability of our method in other domains of life, we predicted the essential genes of the yeast Schizosaccharomyces pombe and obtained a similar accuracy (AUC 0.84).ConclusionsThe proposed method enables a simple and reliable identification of essential genes without searching in databases for orthologs and demanding further experimental data such as network topology and gene-expression.

Human gene essentiality.

A gene can be defined as essential when loss of its function compromises viability of the individual (for example, embryonic lethality) or results in profound loss of fitness. At the population level, identification of essential genes is accomplished by observing intolerance to loss-of-function variants. Several computational methods are available to score gene essentiality, and recent progress has been made in defining essentiality in the non-coding genome. Haploinsufficiency is emerging as a critical aspect of gene essentiality: approximately 3,000 human genes cannot tolerate loss of one of the two alleles. Genes identified as essential in human cell lines or knockout mice may be distinct from those in living humans. Reconciling these discrepancies in how we evaluate gene essentiality has applications in clinical genetics and may offer insights for drug development.

Genome-wide sequence transposon insertion sites and analyze the essential genes of Brucella melitensis

A transposon mutant library of B. melitensis NI including 32,640 transposon mutants was established. By sequencing the transposon insertion sites, 10,832 mutants were successfully defined for their insertion sites. Analysis of the mutants with defined transposon insertion sites (DTIS) indicated that the insertions were well spread through the two genomes. In addition, 948 genes with no detectable transposon insertions were taken as the candidate for identification of essential genes. In comparison with the Bacterial Database of Essential Genes and by using comparative genomics analysis, 183 potential essential genes of B. melitensis NI cultured in vitro were found and they were conserved in the common bacteria. This work was focused on screening of the essential genes of B. melitensis NI, which may provide a foundation for identification of the novel drug targets against brucellosis. Besides, the sequence-defined transposon library should serve as a resource for screening of different function genes of Brucella.