Are essential genes really essential?

The evolutionary rate of antibacterial drug targets

Background

One of the major issues in the fight against infectious diseases is the notable increase in multiple drug resistance in pathogenic species. For that reason, newly acquired high-throughput data on virulent microbial agents attract the attention of many researchers seeking potential new drug targets. Many approaches have been used to evaluate proteins from infectious pathogens, including, but not limited to, similarity analysis, reverse docking, statistical 3D structure analysis, machine learning, topological properties of interaction networks or a combination of the aforementioned methods. From a biological perspective, most essential proteins (knockout lethal for bacteria) or highly conserved proteins (broad spectrum activity) are potential drug targets. Ribosomal proteins comprise such an example. Many of them are well-known drug targets in bacteria. It is intuitive that we should learn from nature how to design good drugs. Firstly, known antibiotics are mainly originating from natural products of microorganisms targeting other microorganisms. Secondly, paleontological data suggests that antibiotics have been used by microorganisms for million years. Thus, we have hypothesized that good drug targets are evolutionary constrained and are subject of evolutionary selection. This means that mutations in such proteins are deleterious and removed by selection, which makes them less susceptible to random development of resistance. Analysis of the speed of evolution seems to be good approach to test this hypothesis.

Results

In this study we show that pN/pS ratio of genes coding for known drug targets is significantly lower than the genome average and also lower than that for essential genes identified by experimental methods. Similar results are observed in the case of dN/dS analysis. Both analyzes suggest that drug targets tend to evolve slowly and that the rate of evolution is a better predictor of drugability than essentiality.

Conclusions

Evolutionary rate can be used to score and find potential drug targets. The results presented here may become a useful addition to a repertoire of drug target prediction methods. As a proof of concept, we analyzed GO enrichment among the slowest evolving genes. These may become the starting point in the search for antibiotics with a novel mechanism.

From essential to persistent genes: a functional approach to constructing synthetic life

A central undertaking in synthetic biology (SB) is the quest for the 'minimal genome'. However, 'minimal sets' of essential genes are strongly context-dependent and, in all prokaryotic genomes sequenced to date, not a single protein-coding gene is entirely conserved. Furthermore, a lack of consensus in the field as to what attributes make a gene truly essential adds another aspect of variation. Thus, a universal minimal genome remains elusive. Here, as an alternative to defining a minimal genome, we propose that the concept of gene persistence can be used to classify genes needed for robust long-term survival. Persistent genes, although not ubiquitous, are conserved in a majority of genomes, tend to be expressed at high levels, and are frequently located on the leading DNA strand. These criteria impose constraints on genome organization, and these are important considerations for engineering cells and for creating cellular life-like forms in SB.

In vivo-validated essential genes identified in Acinetobacter baumannii by using human ascites overlap poorly with essential genes detected on laboratory media

A critical feature of a potential antimicrobial target is the characteristic of being essential for growth and survival during host infection. For bacteria, genome-wide essentiality screens are usually performed on rich laboratory media. This study addressed whether genes detected in that manner were optimal for the identification of antimicrobial targets since the in vivo milieu is fundamentally different. Mutant derivatives of a clinical isolate of Acinetobacter baumannii were screened for growth on human ascites, an ex vivo medium that reflects the infection environment. A subset of 34 mutants with unique gene disruptions that demonstrated little to no growth on ascites underwent evaluation in a rat subcutaneous abscess model, establishing 18 (53%) of these genes as in vivo essential. The putative gene products all had annotated biological functions, represented unrecognized or underexploited antimicrobial targets, and could be grouped into five functional categories: metabolic, two-component signaling systems, DNA/RNA synthesis and regulation, protein transport, and structural. These A. baumannii in vivo essential genes overlapped poorly with the sets of essential genes from other Gram-negative bacteria catalogued in the Database of Essential Genes (DEG), including those of Acinetobacter baylyi, a closely related species. However, this finding was not due to the absence of orthologs. None of the 18 in vivo essential genes identified in this study, or their putative gene products, were targets of FDA-approved drugs or drugs in the developmental pipeline, indicating that a significant portion of the available target space within pathogenic Gram-negative bacteria is currently neglected.

The human pathogen Acinetobacter baumannii is of increasing clinical importance, and a growing proportion of isolates are multiantimicrobial-resistant, pan-antimicrobial-resistant, or extremely resistant strains. This scenario is reflective of the general problem of a critical lack of antimicrobials effective against antimicrobial-resistant Gram-negative bacteria, such as Pseudomonas aeruginosa, Klebsiella pneumoniae, Enterobacter sp., and Escherichia coli. This study identified a set of A. baumannii genes that are essential for growth and survival during infection and demonstrated the importance of using clinically relevant media and in vivo validation while screening for essential genes for the purpose of developing new antimicrobials. Furthermore, it established that if a gene is absent from the Database of Essential Genes, it should not be excluded as a potential antimicrobial target. Lastly, a new set of high-value potential antimicrobial targets for pathogenic Gram-negative bacteria has been identified.

Bugs, drugs and chemical genomics

The serendipitous discovery of penicillin inspired intensive research into how small molecules affect basic cellular processes and their potential to treat disease. Biochemical and genetic approaches have been fundamental for clarifying small-molecule modes of action. Genomic technologies have permitted the use of chemical-genetic strategies that comprehensively study compound-target relationships in the context of a living cell, providing a systems biology view of both the cellular targets and the interdependent networks that respond to chemical stress. These studies highlight the fact that in vitro determinations of mechanism rarely translate into a complete understanding of drug behavior in the cell. Here, we review key discoveries that gave rise to the field of chemical genetics, with particular attention to chemical-genetic strategies developed for bakers' yeast, their extension to clinically relevant microbial pathogens, and the potential of these approaches to affect antimicrobial drug discovery.

OGEE: an online gene essentiality database

OGEE is an Online GEne Essentiality database. Its main purpose is to enhance our understanding of the essentiality of genes. This is achieved by collecting not only experimentally tested essential and non-essential genes, but also associated gene features such as expression profiles, duplication status, conservation across species, evolutionary origins and involvement in embryonic development. We focus on large-scale experiments and complement our data with text-mining results. Genes are organized into data sets according to their sources. Genes with variable essentiality status across data sets are tagged as conditionally essential, highlighting the complex interplay between gene functions and environments. Linked tools allow the user to compare gene essentiality among different gene groups, or compare features of essential genes to non-essential genes, and visualize the results. OGEE is freely available at http://ogeedb.embl.de.

Genomes of the most dangerous epidemic bacteria have a virulence repertoire characterized by fewer genes but more toxin-antitoxin modules

BACKGROUND

We conducted a comparative genomic study based on a neutral approach to identify genome specificities associated with the virulence capacity of pathogenic bacteria. We also determined whether virulence is dictated by rules, or if it is the result of individual evolutionary histories. We systematically compared the genomes of the 12 most dangerous pandemic bacteria for humans ("bad bugs") to their closest non-epidemic related species ("controls").

METHODOLOGY/PRINCIPAL FINDINGS

We found several significantly different features in the "bad bugs", one of which was a smaller genome that likely resulted from a degraded recombination and repair system. The 10 Cluster of Orthologous Group (COG) functional categories revealed a significantly smaller number of genes in the "bad bugs", which lacked mostly transcription, signal transduction mechanisms, cell motility, energy production and conversion, and metabolic and regulatory functions. A few genes were identified as virulence factors, including secretion system proteins. Five "bad bugs" showed a greater number of poly (A) tails compared to the controls, whereas an elevated number of poly (A) tails was found to be strongly correlated to a low GC% content. The "bad bugs" had fewer tandem repeat sequences compared to controls. Moreover, the results obtained from a principal component analysis (PCA) showed that the "bad bugs" had surprisingly more toxin-antitoxin modules than did the controls.

CONCLUSIONS/SIGNIFICANCE

We conclude that pathogenic capacity is not the result of "virulence factors" but is the outcome of a virulent gene repertoire resulting from reduced genome repertoires. Toxin-antitoxin systems could participate in the virulence repertoire, but they may have developed independently of selfish evolution.

The systematic functional analysis of Plasmodium protein kinases identifies essential regulators of mosquito transmission

Although eukaryotic protein kinases (ePKs) contribute to many cellular processes, only three Plasmodium falciparum ePKs have thus far been identified as essential for parasite asexual blood stage development. To identify pathways essential for parasite transmission between their mammalian host and mosquito vector, we undertook a systematic functional analysis of ePKs in the genetically tractable rodent parasite Plasmodium berghei. Modeling domain signatures of conventional ePKs identified 66 putative Plasmodium ePKs. Kinomes are highly conserved between Plasmodium species. Using reverse genetics, we show that 23 ePKs are redundant for asexual erythrocytic parasite development in mice. Phenotyping mutants at four life cycle stages in Anopheles stephensi mosquitoes revealed functional clusters of kinases required for sexual development and sporogony. Roles for a putative SR protein kinase (SRPK) in microgamete formation, a conserved regulator of clathrin uncoating (GAK) in ookinete formation, and a likely regulator of energy metabolism (SNF1/KIN) in sporozoite development were identified.

Identification of essential genes in C. jejuni genome highlights hyper-variable plasticity regions

A microarray transposon-based tracking approach was used to identify Campylobacter jejuni genes which are required for cell growth at 37°C, under a microaerophilic atmosphere and on a rich Mueller-Hinton medium. A transposon-based mutant library, comprised of 7,201 individual mutants was constructed, representing 4.48× coverage of the genome. An analysis of genes lacking a transposon insertion revealed 195 essential gene candidates. The function of these genes represent many of the expected core functions of the cell, such as energy metabolism, macromolecule and cofactor biosynthesis, cell structural proteins as well as basic cell processes. Forty-nine hypothetical proteins were also identified, further underlining the importance of currently unknown proteins and pathways within C. jejuni. Unlike other bacteria, the essential genes were not uniformly distributed along the chromosome with three main regions lacking essential genes. These particular regions corresponded to known hyper-variable plasticity regions of C. jejuni genome indicating, as expected, that these regions are dispensable in any given C. jejuni strain. Overall, this work identified dispensable and essential genes in C. jejuni that will ultimately lead to a better understanding of Campylobacter physiology.

Dispensability of Escherichia coli's latent pathways

Gene-knockout experiments on single-cell organisms have established that expression of a substantial fraction of genes is not needed for optimal growth. This problem acquired a new dimension with the recent discovery that environmental and genetic perturbations of the bacterium Escherichia coli are followed by the temporary activation of a large number of latent metabolic pathways, which suggests the hypothesis that temporarily activated reactions impact growth and hence facilitate adaptation in the presence of perturbations. Here, we test this hypothesis computationally and find, surprisingly, that the availability of latent pathways consistently offers no growth advantage and tends, in fact, to inhibit growth after genetic perturbations. This is shown to be true even for latent pathways with a known function in alternate conditions, thus extending the significance of this adverse effect beyond apparently nonessential genes. These findings raise the possibility that latent pathway activation is in fact derivative of another, potentially suboptimal, adaptive response.

Phenotypic landscape of a bacterial cell

The explosion of sequence information in bacteria makes developing high-throughput, cost-effective approaches to matching genes with phenotypes imperative. Using E. coli as proof of principle, we show that combining large-scale chemical genomics with quantitative fitness measurements provides a high-quality data set rich in discovery. Probing growth profiles of a mutant library in hundreds of conditions in parallel yielded > 10,000 phenotypes that allowed us to study gene essentiality, discover leads for gene function and drug action, and understand higher-order organization of the bacterial chromosome. We highlight new information derived from the study, including insights into a gene involved in multiple antibiotic resistance and the synergy between a broadly used combinatory antibiotic therapy, trimethoprim and sulfonamides. This data set, publicly available at http://ecoliwiki.net/tools/chemgen/, is a valuable resource for both the microbiological and bioinformatic communities, as it provides high-confidence associations between hundreds of annotated and uncharacterized genes as well as inferences about the mode of action of several poorly understood drugs.

Investigating the predictability of essential genes across distantly related organisms using an integrative approach

Rapid and accurate identification of new essential genes in under-studied microorganisms will significantly improve our understanding of how a cell works and the ability to re-engineer microorganisms. However, predicting essential genes across distantly related organisms remains a challenge. Here, we present a machine learning-based integrative approach that reliably transfers essential gene annotations between distantly related bacteria. We focused on four bacterial species that have well-characterized essential genes, and tested the transferability between three pairs among them. For each pair, we trained our classifier to learn traits associated with essential genes in one organism, and applied it to make predictions in the other. The predictions were then evaluated by examining the agreements with the known essential genes in the target organism. Ten-fold cross-validation in the same organism yielded AUC scores between 0.86 and 0.93. Cross-organism predictions yielded AUC scores between 0.69 and 0.89. The transferability is likely affected by growth conditions, quality of the training data set and the evolutionary distance. We are thus the first to report that gene essentiality can be reliably predicted using features trained and tested in a distantly related organism. Our approach proves more robust and portable than existing approaches, significantly extending our ability to predict essential genes beyond orthologs.

The twin arginine transport system appears to be essential for viability in Sinorhizobium meliloti

The twin arginine transport (Tat) system is responsible for transporting prefolded proteins to the periplasmic space. The Tat pathway has been implicated in many bacterial cellular functions, including motility, biofilm formation, and pathogenesis and symbiosis. Since the annotation of Sinorhizobium meliloti Rm1021 genome suggests that there may be up to 94 putative Tat substrates, we hypothesized that characterizing the twin arginine transport system in this organism might yield unique data that could help in the understanding of twin arginine transport. To initiate this work we attempted a targeted mutagenesis of the tat locus. Despite repeated attempts using a number of different types of media, the attempts at mutation construction were unsuccessful unless the experiment was carried out in a strain that was merodiploid for tatABC. In addition, it was shown that a plasmid carrying tatABC was stable in the absence of antibiotic selection in a tat deletion background. Finally, fluorescence microscopy and live/dead assays of these cultures show a high proportion of dead and irregularly shaped cells, suggesting that the loss of tatABC is inversely correlated with viability. Taken together, the results of this work provide evidence that the twin arginine transport system of S. meliloti appears to be essential for viability under all the conditions that we had tested.

Introducing the bacterial 'chromid': not a chromosome, not a plasmid

In addition to the main chromosome, approximately one in ten bacterial genomes have a 'second chromosome' or 'megaplasmid'. Here, we propose that these represent a single class of elements that have a distinct and consistent set of properties, and suggest the term 'chromid' to distinguish them from both chromosomes and plasmids. Chromids carry some core genes, and their nucleotide composition and codon usage are very similar to those of the chromosomes they are associated with. By contrast, they have plasmid replication and partitioning systems and the majority of their genes confer accessory functions. Chromids seem particularly rich in genus-specific genes and appear to be 'reinvented' at the origin of a new genus.