Essential genes as antimicrobial targets and cornerstones of synthetic biology

Functional characterization of GAPDH2 through overexpression and dsRNA-mediated RNA interference in Synechocystis

Glyceraldehyde-3-phosphate dehydrogenase 2 (GAPDH2) plays a vital role in cell growth, stress responses, and various cellular processes in organisms. However, its functional characterization in cyanobacteria, particularly in Synechocystis sp. PCC 6803, remains largely unexplored, especially concerning its overexpression and RNA interference (RNAi) via double-stranded RNA (dsRNA). This study aimed to investigate the biological role of GAPDH2 in Synechocystis sp. PCC 6803 by cloning its complete coding sequence (SyGAPDH2). The SyGAPDH2 protein comprises 350 amino acids with a molecular weight of 86.480 kDa and an isoelectric point of 5.03. The sequence alignment analysis revealed two conserved domains: NADH (Nicotinamide Adenine Dinucleotide)-quinone oxidoreductase subunit NuoI and NADH-ubiquinone/plastoquinone oxidoreductase chain 6. Similarly, Phylogenetic analysis demonstrated high sequence similarity of 96 % and 94 % with Coliform (Gammaproteobacteria bacterium), respectively. We further explored the functional significance of SyGAPDH2 through overexpression using the PpsbAII+SyGAPDH2 vector and double stranded RNA (dsRNA)-mediated silencing with dsGAPDH2. Overexpression significantly enhanced cell growth, while dsRNA-mediated suppression resulted in reduced cell proliferation, with effects observed 12 h post-treatment and persisting up to 36 h. These findings emphasize the essential regulatory role of SyGAPDH2 in cellular development and stress response. This study contributes to our understanding of GAPDH2 functional importance in cyanobacteria, providing a foundation for future investigations into its subcellular localization, additional functional roles, and broader regulatory mechanisms within cyanobacterial cellular processes.

Experimental evolution of gene essentiality in bacteria

Essential gene products carry out fundamental cellular activities in interaction with other components. However, the lack of essential gene mutants and appropriate methodologies to link essential gene functions with their partners poses significant challenges. Here, we have generated deletion mutants in 32 genes previously identified as essential, with 23 mutants showing extremely slow growth in the SK36 strain of Streptococcus sanguinis. The 23 genes corresponding to these mutants encode components of diverse pathways, are widely conserved among bacteria, and are essential in many other bacterial species. Whole-genome sequencing of 243 independently evolved populations of these mutants has identified >1000 spontaneous suppressor mutations in experimental evolution. Many of these mutations define new gene and pathway relationships, such as F1Fo-ATPase/V1Vo-ATPase/TrkA1-H1 that were demonstrated across multiple Streptococcus species. Patterns of spontaneous mutations occurring in essential gene mutants differed from those found in wildtype. While gene duplications occurred rarely and appeared most often at later stages of evolution, substitutions, deletions, and insertions were prevalent in evolved populations. These essential gene deletion mutants and spontaneous mutations fixed in the mutant populations during evolution establish a foundation for understanding gene essentiality and the interaction of essential genes in networks.

Human essential gene identification based on feature fusion and feature screening

Essential genes are necessary to sustain the life of a species under adequate nutritional conditions. These genes have attracted significant attention for their potential as drug targets, especially in developing broad-spectrum antibacterial drugs. However, studying essential genes remains challenging due to their variability in specific environmental conditions. In this study, the authors aim to develop a powerful prediction model for identifying essential genes in humans. The authors first obtained the essential gene data from human cancer cell lines and characterised gene sequences using 7 feature encoding methods such as Kmer, the Composition of K-spaced Nucleic Acid Pairs, and Z-curve. Subsequently, feature fusion and feature optimisation strategies were employed to select the impactful features. Finally, machine learning algorithms were applied to construct the prediction models and evaluate their performance. The single-feature-based model achieved the highest area under the Receiver Operating Characteristic curve (AUC) of 0.830. After fusing and filtering these features, the classical machine learning models achieved the highest AUC at 0.823 while the deep learning model reached 0.860. Results obtained by the authors show that compared to using individual features, feature fusion and feature optimisation strategies significantly improved model performance. Moreover, the study provided an advantageous method for essential gene identification compared to other methods.

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 model organism Escherichia coli, as well as major human pathogens including Salmonella enterica and Klebsiella pneumoniae. Essential gene sets have been determined for several members of the Enterobacteriaceae, with the Keio E. coli single-gene deletion library often regarded as a gold standard. However, it remains unclear how gene essentiality varies between related strains and species. To investigate this, we have assembled a collection of 13 sequenced high-density transposon mutant libraries from five genera within the Enterobacteriaceae. We first assess several 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. Despite the presence of a large cohort of variably essential genes, 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 σE extracytoplasmic stress response, which appears to have independently acquired essentiality 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 identifies several instances of essential stress responses masked by redundancy in free-living bacteria.IMPORTANCEThe essential genome, that is the set of genes absolutely required to sustain life, is a core concept in genetics. Essential genes in bacteria serve as drug targets, put constraints on the engineering of biological chassis for technological or industrial purposes, and are key to constructing synthetic life. Despite decades of study, relatively little is known about how gene essentiality varies across related bacteria. In this study, we have collected gene essentiality data for 13 bacteria related to the model organism Escherichia coli, including several human pathogens, and investigated the conservation of essentiality. We find that approximately a third of the genes essential in any particular strain are non-essential in another related strain. Surprisingly, we do not find evidence for essential genes unique to specific genera; rather it appears a substantial fraction of the essential genome rapidly gains or loses essentiality during evolution. This suggests that essentiality is not an immutable characteristic but depends crucially on the genomic context. We illustrate this through a comparison of our essential genes in free-living bacteria to genes conserved in 34 insect endosymbionts with naturally reduced genomes, finding several cases where genes generally regarded as being important for specific stress responses appear to have become essential in endosymbionts due to a loss of functional redundancy in the genome.

Differentially used codons among essential genes in bacteria identified by machine learning-based analysis

Codon usage bias (CUB), the uneven usage of synonymous codons encoding the same amino acid, differs among genes within and across bacteria genomes. CUB is known to be influenced by gene expression and accordingly, CUB differs between the high-expression and low-expression genes in several bacteria. In this article, we have extended codon usage study considering gene essentiality as a feature. Using machine learning (ML) based approaches, we have analysed Relative Synonymous Codon Usage (RSCU) values between essential and non-essential genes in Escherichia coli and thirty-four other bacterial genomes whose gene essentiality features were available in public databases. We observed significant differences in codon usage patterns between essential and non-essential genes for majority of the bacterial genomes and accordingly, ML based classifiers achieved high area under curve (AUC) scores, with a minimum score of 70.0 across twenty-eight organisms. Further, importance of the codons towards classifying genes found to differ among the codons in each genome. Arg codon CGT and Gly codon GGT were observed to be the most preferred codons among essential genes in Escherichia coli. Interestingly, some of the codons like CGT, ATA, GGT and GGG observed to be contributing consistently towards classifying essential genes across thirty-five bacteria genomes studied. In other hand, codons TGY and CAY encoding amino acids Cys and His respectively were among the least contributing codons towards classification among all these bacteria. This study demonstrates the gene essentiality based differences in synonymous codon usage in bacteria genomes and presents a common codon usage pattern across bacteria.

CRISPRi functional genomics in bacteria and its application to medical and industrial research

SUMMARYFunctional genomics is the use of systematic gene perturbation approaches to determine the contributions of genes under conditions of interest. Although functional genomic strategies have been used in bacteria for decades, recent studies have taken advantage of CRISPR (clustered regularly interspaced short palindromic repeats) technologies, such as CRISPRi (CRISPR interference), that are capable of precisely modulating expression of all genes in the genome. Here, we discuss and review the use of CRISPRi and related technologies for bacterial functional genomics. We discuss the strengths and weaknesses of CRISPRi as well as design considerations for CRISPRi genetic screens. We also review examples of how CRISPRi screens have defined relevant genetic targets for medical and industrial applications. Finally, we outline a few of the many possible directions that could be pursued using CRISPR-based functional genomics in bacteria. Our view is that the most exciting screens and discoveries are yet to come.

A mobile CRISPRi collection enables genetic interaction studies for the essential genes of Escherichia coli

Advances in gene editing, in particular CRISPR interference (CRISPRi), have enabled depletion of essential cellular machinery to study the downstream effects on bacterial physiology. Here, we describe the construction of an ordered E. coli CRISPRi collection, designed to knock down the expression of 356 essential genes with the induction of a catalytically inactive Cas9, harbored on the conjugative plasmid pFD152. This mobile CRISPRi library can be conjugated into other ordered genetic libraries to assess combined effects of essential gene knockdowns with non-essential gene deletions. As proof of concept, we probed cell envelope synthesis with two complementary crosses: (1) an Lpp deletion into every CRISPRi knockdown strain and (2) the lolA knockdown plasmid into the Keio collection. These experiments revealed a number of notable genetic interactions for the essential phenotype probed and, in particular, showed suppressing interactions for the loci in question.

High-throughput functional genomics: A (myco)bacterial perspective

Advances in sequencing technologies have enabled unprecedented insights into bacterial genome composition and dynamics. However, the disconnect between the rapid acquisition of genomic data and the (much slower) confirmation of inferred genetic function threatens to widen unless techniques for fast, high-throughput functional validation can be applied at scale. This applies equally to Mycobacterium tuberculosis, the leading infectious cause of death globally and a pathogen whose genome, despite being among the first to be sequenced two decades ago, still contains many genes of unknown function. Here, we summarize the evolution of bacterial high-throughput functional genomics, focusing primarily on transposon (Tn)-based mutagenesis and the construction of arrayed mutant libraries in diverse bacterial systems. We also consider the contributions of CRISPR interference as a transformative technique for probing bacterial gene function at scale. Throughout, we situate our analysis within the context of functional genomics of mycobacteria, focusing specifically on the potential to yield insights into M. tuberculosis pathogenicity and vulnerabilities for new drug and regimen development. Finally, we offer suggestions for future approaches that might be usefully applied in elucidating the complex cellular biology of this major human pathogen.

PHF5A as a new OncoTarget and therapeutic prospects

PHF5A (PHD-finger domain protein 5A) is a highly conserved protein comprised of 110 amino acids that belong to PHD zinc finger proteins and is ubiquitously expressed in entire eukaryotic nuclei from yeast to man. PHF5A is an essential component of the SF3B splicing complex regulating protein-protein or protein-DNA interactions; particularly involved in pre-mRNA splicing. Besides its basic spliceosome-associated attributes encompassing the regulation of alternative splicing of specific genes, PHF5A also plays a pivotal role in cell cycle regulation and morphological development of cells along with their differentiation into particular tissues/organs, DNA damage repair, maintenance of pluripotent embryonic stem cells (CSCs) embryogenesis and regulation of chromatin-mediated transcription. Presently identification of spliceosome and non-spliceosome-associated attributes of PHF5A needs great attention based on its key involvement in the pathogenesis of cancer malignancies including the prognosis of lung adenocarcinoma, endometrial adenocarcinoma, breast, and colorectal cancer. PHF5A is an essential splicing factor or cofactor actively participating as an oncogenic protein in tumorigenesis via activation of downstream signaling pathway attributed to its regulation of dysregulated splicing or abnormal alternative splicing of targeted genes. Further, the participation of PHF5A in regulating the growth of cancer stem cells might not be ignored. The current review briefly overviews the structural and functional attributes of PHF5A along with its hitherto described role in the propagation of cancer malignancies and its future concern as a potential therapeutic target for cancer management/treatment.

Identify essential genes based on clustering based synthetic minority oversampling technique

Prediction of essential genes in a life organism is one of the central tasks in synthetic biology. Computational predictors are desired because experimental data is often unavailable. Recently, some sequence-based predictors have been constructed to identify essential genes. However, their predictive performance should be further improved. One key problem is how to effectively extract the sequence-based features, which are able to discriminate the essential genes. Another problem is the imbalanced training set. The amount of essential genes in human cell lines is lower than that of non-essential genes. Therefore, predictors trained with such imbalanced training set tend to identify an unseen sequence as a non-essential gene. Here, a new over-sampling strategy was proposed called Clustering based Synthetic Minority Oversampling Technique (CSMOTE) to overcome the imbalanced data issue. Combining CSMOTE with the Z curve, the global features, and Support Vector Machines, a new protocol called iEsGene-CSMOTE was proposed to identify essential genes. The rigorous jackknife cross validation results indicated that iEsGene-CSMOTE is better than the other competing methods. The proposed method outperformed λ-interval Z curve by 35.48% and 11.25% in terms of Sn and BACC, respectively.

A bacterial pan-genome makes gene essentiality strain-dependent and evolvable

Many bacterial species are represented by a pan-genome, whose genetic repertoire far outstrips that of any single bacterial genome. Here we investigate how a bacterial pan-genome might influence gene essentiality and whether essential genes that are initially critical for the survival of an organism can evolve to become non-essential. By using Transposon insertion sequencing (Tn-seq), whole-genome sequencing and RNA-seq on a set of 36 clinical Streptococcus pneumoniae strains representative of >68% of the species' pan-genome, we identify a species-wide 'essentialome' that can be subdivided into universal, core strain-specific and accessory essential genes. By employing 'forced-evolution experiments', we show that specific genetic changes allow bacteria to bypass essentiality. Moreover, by untangling several genetic mechanisms, we show that gene essentiality can be highly influenced by and/or be dependent on: (1) the composition of the accessory genome, (2) the accumulation of toxic intermediates, (3) functional redundancy, (4) efficient recycling of critical metabolites and (5) pathway rewiring. While this functional characterization underscores the evolvability potential of many essential genes, we also show that genes with differential essentiality remain important antimicrobial drug target candidates, as their inactivation almost always has a severe fitness cost in vivo.

Bacterial genome reductions: Tools, applications, and challenges

Bacterial cells are widely used to produce value-added products due to their versatility, ease of manipulation, and the abundance of genome engineering tools. However, the efficiency of producing these desired biomolecules is often hindered by the cells’ own metabolism, genetic instability, and the toxicity of the product. To overcome these challenges, genome reductions have been performed, making strains with the potential of serving as chassis for downstream applications. Here we review the current technologies that enable the design and construction of such reduced-genome bacteria as well as the challenges that limit their assembly and applicability. While genomic reductions have shown improvement of many cellular characteristics, a major challenge still exists in constructing these cells efficiently and rapidly. Computational tools have been created in attempts at minimizing the time needed to design these organisms, but gaps still exist in modelling these reductions in silico. Genomic reductions are a promising avenue for improving the production of value-added products, constructing chassis cells, and for uncovering cellular function but are currently limited by their time-consuming construction methods. With improvements to and the creation of novel genome editing tools and in silico models, these approaches could be combined to expedite this process and create more streamlined and efficient cell factories.

Gradients in gene essentiality reshape antibacterial research

Essential genes encode the processes that are necessary for life. Until recently, commonly applied binary classifications left no space between essential and non-essential genes. In this review, we frame bacterial gene essentiality in the context of genetic networks. We explore how the quantitative properties of gene essentiality are influenced by the nature of the encoded process, environmental conditions and genetic background, including a strain's distinct evolutionary history. The covered topics have important consequences for antibacterials, which inhibit essential processes. We argue that the quantitative properties of essentiality can thus be used to prioritize antibacterial cellular targets and desired spectrum of activity in specific infection settings. We summarize our points with a case study on the core essential genome of the cystic fibrosis pathobiome and highlight avenues for targeted antibacterial development.

Advances and prospects in metabolic engineering of Escherichia coli for L-tryptophan production

As an important raw material for pharmaceutical, food and feed industry, highly efficient production of L-tryptophan by Escherichia coli has attracted a considerable attention. However, there are complicated and multiple layers of regulation networks in L-tryptophan biosynthetic pathway and thus have difficulty to rewrite the biosynthetic pathway for producing L-tryptophan with high efficiency in E. coli. This review summarizes the biosynthetic pathway of L-tryptophan and highlights the main regulatory mechanisms in E. coli. In addition, we discussed the latest metabolic engineering strategies achieved in E. coli to reconstruct the L-tryptophan biosynthetic pathway. Moreover, we also review a few strategies that can be used in E. coli to improve robustness and streamline of L-tryptophan high-producing strains. Lastly, we also propose the potential strategies to further increase L-tryptophan production by systematic metabolic engineering and synthetic biology techniques.

Analyzing the Function of Essential Genes by Plasmid Shuffling

Investigations on gene essentiality have important implications in several fields of basic and applied research. A variety of strategies have been developed over the years to identify essential genes. Here, we describe an implemented plasmid shuffling method useful to assess the essentiality of overlapped genes under very stringent conditions. A host strain harboring the chromosomal deletion of the genes of interest is complemented by a thermosensitive plasmid carrying the copy of gene 1, gene 2, and rpsL allele, conferring streptomycin sensitivity to an otherwise resistant strain. A compatible plasmid harboring a different selectable marker and the copy of gene 2 only is transformed into the host strain, resulting in the coexistence of two plasmids. These cells are grown at high temperatures in a medium containing streptomycin. Under such conditions, viable cells are expected to contain only the incoming plasmid and to carry suppressor mutation(s) that bypass the loss of the essential gene 1. The system may thus represent a valuable tool to identify interactions between essential proteins and cell pathways.

A large-scale whole-genome sequencing analysis reveals false positives of bacterial essential genes

Essential genes are crucial for bacterial viability and represent attractive targets for novel anti-pathogen drug discovery. However, essential genes determined by the transposon insertion sequencing (Tn-seq) approach often contain many false positives. We hypothesized that some of those false positives are genes that are actually deleted from the genome, so they do not present any transposon insertion in the course of Tn-seq analysis. Based on this assumption, we performed a large-scale whole-genome sequencing analysis for the bacterium of interest. Our analysis revealed that some "essential genes" are indeed removed from the analyzed bacterial genomes. Since these genes were kicked out by bacteria, they should not be defined as essential. Our work showed that gene deletion is one of the false positive sources of essentiality determination, which is apparently underestimated in previous studies. We suggest subtracting the genome backgrounds before the evaluation of Tn-seq, and created a list of false positive gene essentiality as a reference for the downstream application. KEY POINTS: • Discovery of false positives of essential genes defined previously through the analyses of a large scale of whole-genome sequencing data • These false positives are the results of gene deletions in the studied genomes • Sequencing the target genome before Tn-seq analysis is of importance while some studies neglected it.

Geptop 2.0: Accurately Select Essential Genes from the List of Protein-Coding Genes in Prokaryotic Genomes

Computational tool composites alternative way to identify essential genes and it is low-cost and time-efficient. Based on experimental essentiality sets deposited in the databases DEG and OGEE as reference, we developed an automatically computational tool named Geptop to select essential genes from the set of protein-coding genes in a prokaryotic genome, which utilizes the strategy of reciprocally best hit for homology search and evolutionary distance for weight assigning. The latest version of Geptop is 2.0 ( http://guolab.whu.edu.cn/geptop ), which can predict gene essentiality with the mean AUC 0f 0.84 in prokaryotes and is more stable. The chapter is to briefly introduce the tool and tell how to use it.

DELEAT: gene essentiality prediction and deletion design for bacterial genome reduction

Background

The study of gene essentiality is fundamental to understand the basic principles of life, as well as for applications in many fields. In recent decades, dozens of sets of essential genes have been determined using different experimental and bioinformatics approaches, and this information has been useful for genome reduction of model organisms. Multiple in silico strategies have been developed to predict gene essentiality, but no optimal algorithm or set of gene features has been found yet, especially for non-model organisms with incomplete functional annotation.

Results

We have developed DELEAT v0.1 (DELetion design by Essentiality Analysis Tool), an easy-to-use bioinformatic tool which integrates an in silico gene essentiality classifier in a pipeline allowing automatic design of large-scale deletions in any bacterial genome. The essentiality classifier consists of a novel logistic regression model based on only six gene features which are not dependent on experimental data or functional annotation. As a proof of concept, we have applied this pipeline to the determination of dispensable regions in the genome of Bartonella quintana str. Toulouse. In this already reduced genome, 35 possible deletions have been delimited, spanning 29% of the genome.

Conclusions

Built on in silico gene essentiality predictions, we have developed an analysis pipeline which assists researchers throughout multiple stages of bacterial genome reduction projects, and created a novel classifier which is simple, fast, and universally applicable to any bacterial organism with a GenBank annotation file.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04348-5.

An overview and future prospects of recombinant protein production in Bacillus subtilis

Bacillus subtilis is a well-characterized Gram-positive bacterium and a valuable host for recombinant protein production because of its efficient secretion ability, high yield, and non-toxicity. Here, we comprehensively review the recent studies on recombinant protein production in B. subtilis to update and supplement other previous reviews. We have focused on several aspects, including optimization of B. subtilis strains, enhancement and regulation of expression, improvement of secretion level, surface display of proteins, and fermentation optimization. Among them, optimization of B. subtilis strains mainly involves undirected chemical/physical mutagenesis and selection and genetic manipulation; enhancement and regulation of expression comprises autonomous plasmid and integrated expression, promoter regulation and engineering, and fine-tuning gene expression based on proteases and molecular chaperones; improvement of secretion level predominantly involves secretion pathway and signal peptide screening and optimization; surface display of proteins includes surface display of proteins on spores or vegetative cells; and fermentation optimization incorporates medium optimization, process condition optimization, and feeding strategy optimization. Furthermore, we propose some novel methods and future challenges for recombinant protein production in B. subtilis.Key points• A comprehensive review on recombinant protein production in Bacillus subtilis.• Novel techniques facilitate recombinant protein expression and secretion.• Surface display of proteins has significant potential for different applications.

Genome-wide comparison of four MRSA clinical isolates from Germany and Hungary

Staphylococcus aureus is a drug-resistant pathogen, capable of colonizing diverse ecological niches and causing a broad spectrum of infections related to a community and healthcare. In this study, we choose four methicillin-resistant S. aureus (MRSA) clinical isolates from Germany and Hungary based on our previous polyphasic characterization finding. We assumed that the selected strains have a different genetic background in terms of the presence of resistance and virulence genes, prophages, plasmids, and secondary metabolite biosynthesis genes that may play a crucial role in niche adaptation and pathogenesis. To clarify these assumptions, we performed a comparative genome analysis of these strains and observed many differences in their genomic compositions. The Hungarian isolates (SA H27 and SA H32) with ST22-SCCmec type IVa have fewer genes for multiple-drug resistance, virulence, and prophages reported in Germany isolates. Germany isolate, SA G6 acquires aminoglycoside (ant(6)-Ia and aph(3’)-III) and nucleoside (sat-4) resistance genes via phage transduction and may determine its pathogenic potential. The comparative genome study allowed the segregation of isolates of geographical origin and differentiation of the clinical isolates from the commensal isolates. This study suggested that Germany and Hungarian isolates are genetically diverse and showing variation among them due to the gain or loss of mobile genetic elements (MGEs). An interesting finding is the addition of SA G6 genome responsible for the drastic decline of the core/pan-genome ratio curve and causing the pan-genome to open wider. Functional characterizations revealed that S. aureus isolates survival are maintained by the amino acids catabolism and favor adaptation to growing in a protein-rich medium. The dispersible and singleton genes content of S. aureus genomes allows us to understand the genetic variation among the CC5 and CC22 groups. The strains with the same genetic background were clustered together, which suggests that these strains are highly alike; however, comparative genome analysis exposed that the acquisition of phage elements, and plasmids through the events of MGEs transfer contribute to differences in their phenotypic characters. This comparative genome analysis would improve the knowledge about the pathogenic S. aureus strain’s characterization, and responsible for clinically important phenotypic differences among the S. aureus strains.

Essential Genes of the Parasitic Apicomplexa

Genome-scale mutagenesis screens for genes essential for apicomplexan parasite survival have been completed in three species: Plasmodium falciparum, the major human malaria parasite, Plasmodium berghei, a model rodent malaria parasite, and the more distantly related Toxoplasma gondii, the causative agent of toxoplasmosis. These three species share 2606 single-copy orthologs, 1500 of which have essentiality data in all three screens. In this review, we explore the overlap between these datasets to define the core essential genes of the phylum Apicomplexa. We further discuss the implications of these groundbreaking studies for understanding apicomplexan parasite biology, and we identify promising areas of focus for developing new pan-apicomplexan parasite interventions.

DeeplyEssential: a deep neural network for predicting essential genes in microbes

BACKGROUND

Essential genes are those genes that are critical for the survival of an organism. The prediction of essential genes in bacteria can provide targets for the design of novel antibiotic compounds or antimicrobial strategies.

RESULTS

We propose a deep neural network for predicting essential genes in microbes. Our architecture called DEEPLYESSENTIAL makes minimal assumptions about the input data (i.e., it only uses gene primary sequence and the corresponding protein sequence) to carry out the prediction thus maximizing its practical application compared to existing predictors that require structural or topological features which might not be readily available. We also expose and study a hidden performance bias that effected previous classifiers. Extensive results show that DEEPLYESSENTIAL outperform existing classifiers that either employ down-sampling to balance the training set or use clustering to exclude multiple copies of orthologous genes.

CONCLUSION

Deep neural network architectures can efficiently predict whether a microbial gene is essential (or not) using only its sequence information.

Analyses of Livestock-Associated Staphylococcus aureus Pan-Genomes Suggest Virulence Is Not Primary Interest in Evolution of Its Genome

Staphylococcus aureus is not only part of normal flora but also an opportunistic pathogen relevant to microbial genomics, public health, and veterinary medicine. In addition to being a well-known human pathogen, S. aureus causes various infections in economically important livestock animals such as cows, sheep, goats, and pigs. There are very few studies that have examined the pan-genome of S. aureus or the host-specific strains' pan-genomes. We report on livestock-associated S. aureus' (LA-SA) pan-genome and suggest that virulence is not the primary interest in evolution of its genome. LA-SA' complete genomes were retrieved from the NCBI and pan-genome was constructed by high-speed Roary pipeline. The pan-genome size was 4637 clusters, whereas 42.46% of the pan-genome was associated with the core genome. We found 1268 genes were associated with the strain-unique genome, and the remaining 1432 cluster with the accessory genome. COG (clusters of orthologous group of proteins) analysis of the core genes revealed 34% of clusters related to metabolism responsible for amino acid and inorganic ion transport (COG categories E and P), followed by carbohydrate metabolism (category G). Virulent gene analysis revealed the core genes responsible for antiphagocytosis and iron uptake. The fluidity of pan-genome was calculated as 0.082 ± 0.025. Importantly, the positive selection analysis suggested a slower rate of evolution among the LA-SA genomes. We call for comparative microbial and pan-genome research between human and LA-SA that can help further understand the evolution of virulence and thus inform future microbial diagnostics and drug discovery.

Repurposing the Streptococcus mutans CRISPR-Cas9 System to Understand Essential Gene Function

A recent genome-wide screen identified ~300 essential or growth-supporting genes in the dental caries pathogen Streptococcus mutans. To be able to study these genes, we built a CRISPR interference tool around the Cas9 nuclease (Cas9Smu) encoded in the S. mutans UA159 genome. Using a xylose-inducible dead Cas9Smu with a constitutively active single-guide RNA (sgRNA), we observed titratable repression of GFP fluorescence that compared favorably to that of Streptococcus pyogenes dCas9 (Cas9Spy). We then investigated sgRNA specificity and proto-spacer adjacent motif (PAM) requirements. Interference by sgRNAs did not occur with double or triple base-pair mutations, or if single base-pair mutations were in the 3' end of the sgRNA. Bioinformatic analysis of >450 S. mutans genomes allied with in vivo assays revealed a similar PAM recognition sequence as Cas9Spy. Next, we created a comprehensive library of sgRNA plasmids that were directed at essential and growth-supporting genes. We discovered growth defects for 77% of the CRISPRi strains expressing sgRNAs. Phenotypes of CRISPRi strains, across several biological pathways, were assessed using fluorescence microscopy. A variety of cell structure anomalies were observed, including segregational instability of the chromosome, enlarged cells, and ovococci-to-rod shape transitions. CRISPRi was also employed to observe how silencing of cell wall glycopolysaccharide biosynthesis (rhamnose-glucose polysaccharide, RGP) affected both cell division and pathogenesis in a wax worm model. The CRISPRi tool and sgRNA library are valuable resources for characterizing essential genes in S. mutans, some of which could prove to be promising therapeutic targets.

Auranofin is an effective agent against clinical isolates of Staphylococcus aureus

Aim: The orphan drug auranofin was recently found to exhibit antimicrobial properties. Materials & methods: We explored the efficacy of auranofin by evaluating the minimal inhibitory concentration against a collection of over 500 clinical isolates derived from multiple institutions, inclusive of drug resistant strains. Our evaluation also included continuous exposure of bacteria to auranofin. Results & conclusion: We found that minimal inhibitory concentrations ranged between 0.125 and 1 mg/l, exerting robust antimicrobial activity against a sizeable clinical collection of the bacteria. Further, we evaluated the propensity of the methicillin-resistant Staphylococcus aureus strain MW2 to develop resistance through extended exposure to auranofin. After 25 days, the bacteria remained susceptible. Our data suggest that resistance mechanisms do not currently exist to block auranofin antimicrobial activity.

Identifying Bacterial Essential Genes Based on a Feature-Integrated Method

Essential genes are those genes of an organism that are considered to be crucial for its survival. Identification of essential genes is therefore of great significance to advance our understanding of the principles of cellular life. We have developed a novel computational method, which can effectively predict bacterial essential genes by extracting and integrating homologous features, protein domain feature, gene intrinsic features, and network topological features. By performing the principal component regression (PCR) analysis for Escherichia coli MG1655, we established a classification model with the average area under curve (AUC) value of 0.992 in ten times 5-fold cross-validation tests. Furthermore, when employing this new model to a distantly related organism-Streptococcus pneumoniae TIGR4, we still got a reliable AUC value of 0.788. These results indicate that our feature-integrated approach could have practical applications in accurately investigating essential genes from broad bacterial species, and also provide helpful guidelines for the minimal cell.

Comparative assessment of the therapeutic drug targets of C. botulinum ATCC 3502 and C. difficile str. 630 using in silico subtractive proteomics approach

Growing antimicrobial resistance of the pathogens against multiple drugs posed a serious threat to the human health worldwide. This fueled the need of identifying the novel therapeutic targets that can be used for developing new class of the drugs. Recently, there is a substantial rise in the rate of Clostridium infections as well as in the emergence of virulent and antibiotic resistant strains. Hence, there is an urgent need for the identification of potential therapeutic targets and the development of new drugs for the treatment and prevention of Clostridium infections. In the present study, a combinatorial approach involving systems biology and comparative genomics strategy was tested against Clostridium botulinum ATCC 3502 and Clostridium difficile str. 630 pathogens, to render potential therapeutic target at qualitative and quantitative level. This resulted in the identification of five common (present in both the pathogens, 34 in C. botulinum ATCC 3502 and 42 in C. difficile str. 630) drug targets followed by virtual screening-based identification of potential inhibitors employing molecular docking and molecular dynamics simulations. The identified targets will provide a solid platform for the designing of novel wide-spectrum lead compounds capable of inhibiting their catalytic activities against multidrug-resistant Clostridium in the near future.

Systematic analysis reveals the prevalence and principles of bypassable gene essentiality

Gene essentiality is a variable phenotypic trait, but to what extent and how essential genes can become dispensable for viability remain unclear. Here, we investigate 'bypass of essentiality (BOE)' - an underexplored type of digenic genetic interaction that renders essential genes dispensable. Through analyzing essential genes on one of the six chromosome arms of the fission yeast Schizosaccharomyces pombe, we find that, remarkably, as many as 27% of them can be converted to non-essential genes by BOE interactions. Using this dataset we identify three principles of essentiality bypass: bypassable essential genes tend to have lower importance, tend to exhibit differential essentiality between species, and tend to act with other bypassable genes. In addition, we delineate mechanisms underlying bypassable essentiality, including the previously unappreciated mechanism of dormant redundancy between paralogs. The new insights gained on bypassable essentiality deepen our understanding of genotype-phenotype relationships and will facilitate drug development related to essential genes.

The bare necessities: Uncovering essential and condition-critical genes with transposon sequencing

Querying gene function in bacteria has been greatly accelerated by the advent of transposon sequencing (Tn-seq) technologies (related Tn-seq strategies are known as TraDIS, INSeq, RB-TnSeq, and HITS). Pooled populations of transposon mutants are cultured in an environment and next-generation sequencing tools are used to determine areas of the genome that are important for bacterial fitness. In this review we provide an overview of Tn-seq methodologies and discuss how Tn-seq has been applied, or could be applied, to the study of oral microbiology. These applications include studying the essential genome as a means to rationally design therapeutic agents. Tn-seq has also contributed to our understanding of well-studied biological processes in oral bacteria. Other important applications include in vivo pathogenesis studies and use of Tn-seq to probe the molecular basis of microbial interactions. We also highlight recent advancements in techniques that act in synergy with Tn-seq such as clustered regularly interspaced short palindromic repeats (CRISPR) interference and microfluidic chip platforms.

Restoration of biofuel production levels and increased tolerance under ionic liquid stress is enabled by a mutation in the essential Escherichia coli gene cydC

BACKGROUND

Microbial production of chemicals from renewable carbon sources enables a sustainable route to many bioproducts. Sugar streams, such as those derived from biomass pretreated with ionic liquids (IL), provide efficiently derived and cost-competitive starting materials. A limitation to this approach is that residual ILs in the pretreated sugar source can be inhibitory to microbial growth and impair expression of the desired biosynthetic pathway.

RESULTS

We utilized laboratory evolution to select Escherichia coli strains capable of robust growth in the presence of the IL, 1-ethyl-3-methyl-imidizolium acetate ([EMIM]OAc). Whole genome sequencing of the evolved strain identified a point mutation in an essential gene, cydC, which confers tolerance to two different classes of ILs at concentrations that are otherwise growth inhibitory. This mutation, cydC-D86G, fully restores the specific production of the bio-jet fuel candidate D-limonene, as well as the biogasoline and platform chemical isopentenol, in growth medium containing ILs. Similar amino acids at this position in cydC, such as cydC-D86V, also confer tolerance to [EMIM]OAc. We show that this [EMIM]OAc tolerance phenotype of cydC-D86G strains is independent of its wild-type function in activating the cytochrome bd-I respiratory complex. Using shotgun proteomics, we characterized the underlying differential cellular responses altered in this mutant. While wild-type E. coli cannot produce detectable amounts of either product in the presence of ILs at levels expected to be residual in sugars from pretreated biomass, the engineered cydC-D86G strains produce over 200 mg/L D-limonene and 350 mg/L isopentenol, which are among the highest reported titers in the presence of [EMIM]OAc.

CONCLUSIONS

The optimized strains in this study produce high titers of two candidate biofuels and bioproducts under IL stress. Both sets of production strains surpass production titers from other IL tolerant mutants in the literature. Our application of laboratory evolution identified a gain of function mutation in an essential gene, which is unusual in comparison to other published IL tolerant mutants.

Variability of Bacterial Essential Genes Among Closely Related Bacteria: The Case of Escherichia coli

The definition of bacterial essential genes has been widely pursued using different approaches. Their study has impacted several fields of research such as synthetic biology, the construction of bacteria with minimal chromosomes, the search for new antibiotic targets, or the design of strains with biotechnological applications. Bacterial genomes are mosaics that only share a small subset of gene-sequences (core genome) even among members of the same species. It has been reported that the presence of essential genes is highly variable between closely related bacteria and even among members of the same species, due to the phenomenon known as “non-orthologous gene displacement” that refers to the coding for an essential function by genes with no sequence homology due to horizontal gene transfer (HGT). The existence of dormant forms among bacteria and the high incidence of HGT have been proposed to be driving forces of bacterial evolution, and they might have a role in the low level of conservation of essential genes among related bacteria by non-orthologous gene displacement, but this correlation has not been recognized. The aim of this mini-review is to give a brief overview of the approaches that have been taken to define and study essential genes, and the implications of non-orthologous gene displacement in bacterial evolution, focusing mainly in the case of Escherichia coli. To this end, we reviewed the available literature, and we searched for the presence of the essential genes defined by mutagenesis in the genomes of the 63 best-sequenced E. coli genomes that are available in NCBI database. We could not document specific cases of non-orthologous gene displacement among the E. coli strains analyzed, but we found that the quality of the genome-sequences in the database is not enough to make accurate predictions about the conservation of essential-genes among members of this bacterial species.

Identification of novel drug targets in bovine respiratory disease: an essential step in applying biotechnologic techniques to develop more effective therapeutic treatments

BACKGROUND

Bovine Respiratory Disease (BRD) is a major problem in cattle production which causes substantial economic loss. BRD has multifactorial aetiologies, is multi-microbial, and several of the causative pathogens are unknown. Consequently, primary management practices such as metaphylactic antimicrobial injections for BRD prevention are used to reduce the incidence of BRD in feedlot cattle. However, this poses a serious threat in the form of development of antimicrobial resistance and demands an urgent need to find novel interventions that could reduce the effects of BRD drastically and also delay/prevent bacterial resistance.

MATERIALS AND METHODS

We have employed a subtractive genomics approach that helps delineate essential, host-specific, and druggable targets in pathogens responsible for BRD. We also proposed antimicrobials from FDA green and orange book that could be repositioned for BRD.

RESULTS

We have identified 107 putative targets that are essential, selective and druggable. We have also confirmed the susceptibility of two BRD pathogens to one of the proposed antimicrobials - oxytetracycline.

CONCLUSION

This approach allows for repositioning drugs known for other infections to BRD, predicting novel druggable targets for BRD infection, and providing a new direction in developing more effective therapeutic treatments for BRD.

CRISPR-Cas9 technology: applications in genome engineering, development of sequence-specific antimicrobials, and future prospects

The development of CRISPR-Cas9 technology has revolutionized our ability to edit DNA and to modulate expression levels of genes of interest, thus providing powerful tools to accelerate the precise engineering of a wide range of organisms. In addition, the CRISPR-Cas system can be harnessed to design "precision" antimicrobials that target bacterial pathogens in a DNA sequence-specific manner. This capability will enable killing of drug-resistant microbes by selectively targeting genes involved in antibiotic resistance, biofilm formation and virulence. Here, we review the origins and mechanistic basis of CRISPR-Cas systems, discuss how this technology can be leveraged to provide a range of applications in both eukaryotic and prokaryotic systems, and finish by outlining limitations and future prospects.

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.

The Essential Genome of Burkholderia cenocepacia H111

The study of the minimum set of genes required to sustain life is a fundamental question in biological research. Recent studies on bacterial essential genes suggested that between 350 and 700 genes are essential to support autonomous bacterial cell growth. Essential genes are of interest as potential new antimicrobial drug targets; hence, our aim was to identify the essential genome of the cystic fibrosis (CF) isolate Burkholderia cenocepacia H111. Using a transposon sequencing (Tn-Seq) approach, we identified essential genes required for growth in rich medium under aerobic and microoxic conditions as well as in a defined minimal medium with citrate as a sole carbon source. Our analysis suggests that 398 genes are required for autonomous growth in rich medium, a number that represents only around 5% of the predicted genes of this bacterium. Five hundred twenty-six genes were required to support growth in minimal medium, and 434 genes were essential under microoxic conditions (0.5% O₂). A comparison of these data sets identified 339 genes that represent the minimal set of essential genes required for growth under all conditions tested and can be considered the core essential genome of B. cenocepacia H111. The majority of essential genes were found to be located on chromosome 1, and few such genes were located on chromosome 2, where most of them were clustered in one region. This gene cluster is fully conserved in all Burkholderia species but is present on chromosome 1 in members of the closely related genus Ralstonia, suggesting that the transfer of these essential genes to chromosome 2 in a common ancestor contributed toward the separation of the two genera.IMPORTANCE Transposon sequencing (Tn-Seq) is a powerful method used to identify genes that are essential for autonomous growth under various conditions. In this study, we have identified a set of "core essential genes" that are required for growth under multiple conditions, and these genes represent potential antimicrobial targets. We also identified genes specifically required for growth under low-oxygen and nutrient-limited environments. We generated conditional mutants to verify the results of our Tn-Seq analysis and demonstrate that one of the identified genes was not essential per se but was an artifact of the construction of the mutant library. We also present verified examples of genes that were not truly essential but, when inactivated, showed a growth defect. These examples have identified so-far-underestimated shortcomings of this powerful method.

Cas9 Nickase-Assisted RNA Repression Enables Stable and Efficient Manipulation of Essential Metabolic Genes in Clostridium cellulolyticum

Essential gene functions remain largely underexplored in bacteria. Clostridium cellulolyticum is a promising candidate for consolidated bioprocessing; however, its genetic manipulation to reduce the formation of less-valuable acetate is technically challenging due to the essentiality of acetate-producing genes. Here we developed a Cas9 nickase-assisted chromosome-based RNA repression to stably manipulate essential genes in C. cellulolyticum. Our plasmid-based expression of antisense RNA (asRNA) molecules targeting the phosphotransacetylase (pta) gene successfully reduced the enzymatic activity by 35% in cellobiose-grown cells, metabolically decreased the acetate titer by 15 and 52% in wildtype transformants on cellulose and xylan, respectively. To control both acetate and lactate simultaneously, we transformed the repression plasmid into lactate production-deficient mutant and found the plasmid delivery reduced acetate titer by more than 33%, concomitant with negligible lactate formation. The strains with pta gene repression generally diverted more carbon into ethanol. However, further testing on chromosomal integrants that were created by double-crossover recombination exhibited only very weak repression because DNA integration dramatically lessened gene dosage. With the design of a tandem repetitive promoter-driven asRNA module and the use of a new Cas9 nickase genome editing tool, a chromosomal integrant (LM3P) was generated in a single step and successfully enhanced RNA repression, with a 27% decrease in acetate titer on cellulose in antibiotic-free medium. These results indicate the effectiveness of tandem promoter-driven RNA repression modules in promoting gene repression in chromosomal integrants. Our combinatorial method using a Cas9 nickase genome editing tool to integrate the gene repression module demonstrates easy-to-use and high-efficiency advantages, paving the way for stably manipulating genes, even essential ones, for functional characterization and microbial engineering.

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.

Essential genome of Campylobacter jejuni

BACKGROUND

Campylobacter species are a leading cause of bacterial foodborne illness worldwide. Despite the global efforts to curb them, Campylobacter infections have increased continuously in both developed and developing countries. The development of effective strategies to control the infection by this pathogen is warranted. The essential genes of bacteria are the most prominent targets for this purpose. In this study, we used transposon sequencing (Tn-seq) of a genome-saturating library of Tn5 insertion mutants to define the essential genome of C. jejuni at a high resolution.

RESULT

We constructed a Tn5 mutant library of unprecedented complexity in C. jejuni NCTC 11168 with 95,929 unique insertions throughout the genome and used the genomic DNA of the library for the reconstruction of Tn5 libraries in the same (C. jejuni NCTC 11168) and different strain background (C. jejuni 81-176) through natural transformation. We identified 166 essential protein-coding genes and 20 essential transfer RNAs (tRNA) in C. jejuni NCTC 11168 which were intolerant to Tn5 insertions during in vitro growth. The reconstructed C. jejuni 81-176 library had 384 protein coding genes with no Tn5 insertions. Essential genes in both strain backgrounds were highly enriched in the cluster of orthologous group (COG) categories of 'Translation, ribosomal structure and biogenesis (J)', 'Energy production and conversion (C)', and 'Coenzyme transport and metabolism (H)'.

CONCLUSION

Comparative analysis among this and previous studies identified 50 core essential genes of C. jejuni, which can be further investigated for the development of novel strategies to control the spread of this notorious foodborne bacterial pathogen.

Synthetic Biology-The Synthesis of Biology

Synthetic biology concerns the engineering of man-made living biomachines from standardized components that can perform predefined functions in a (self-)controlled manner. Different research strategies and interdisciplinary efforts are pursued to implement engineering principles to biology. The "top-down" strategy exploits nature's incredible diversity of existing, natural parts to construct synthetic compositions of genetic, metabolic, or signaling networks with predictable and controllable properties. This mainly application-driven approach results in living factories that produce drugs, biofuels, biomaterials, and fine chemicals, and results in living pills that are based on engineered cells with the capacity to autonomously detect and treat disease states in vivo. In contrast, the "bottom-up" strategy seeks to be independent of existing living systems by designing biological systems from scratch and synthesizing artificial biological entities not found in nature. This more knowledge-driven approach investigates the reconstruction of minimal biological systems that are capable of performing basic biological phenomena, such as self-organization, self-replication, and self-sustainability. Moreover, the syntheses of artificial biological units, such as synthetic nucleotides or amino acids, and their implementation into polymers inside living cells currently set the boundaries between natural and artificial biological systems. In particular, the in vitro design, synthesis, and transfer of complete genomes into host cells point to the future of synthetic biology: the creation of designer cells with tailored desirable properties for biomedicine and biotechnology.

Selection of key sequence-based features for prediction of essential genes in 31 diverse bacterial species

Genes that are indispensable for survival are essential genes. Many features have been proposed for computational prediction of essential genes. In this paper, the least absolute shrinkage and selection operator method was used to screen key sequence-based features related to gene essentiality. To assess the effects, the selected features were used to predict the essential genes from 31 bacterial species based on a support vector machine classifier. For all 31 bacterial objects (21 Gram-negative objects and ten Gram-positive objects), the features in the three datasets were reduced from 57, 59, and 58, to 40, 37, and 38, respectively, without loss of prediction accuracy. Results showed that some features were redundant for gene essentiality, so could be eliminated from future analyses. The selected features contained more complex (or key) biological information for gene essentiality, and could be of use in related research projects, such as gene prediction, synthetic biology, and drug design.

Making life difficult for Clostridium difficile: augmenting the pathogen's metabolic model with transcriptomic and codon usage data for better therapeutic target characterization

BACKGROUND

Clostridium difficile is a bacterium which can infect various animal species, including humans. Infection with this bacterium is a leading healthcare-associated illness. A better understanding of this organism and the relationship between its genotype and phenotype is essential to the search for an effective treatment. Genome-scale metabolic models contain all known biochemical reactions of a microorganism and can be used to investigate this relationship.

RESULTS

We present icdf834, an updated metabolic network of C. difficile that builds on iMLTC806cdf and features 1227 reactions, 834 genes, and 807 metabolites. We used this metabolic network to reconstruct the metabolic landscape of this bacterium. The standard metabolic model cannot account for changes in the bacterial metabolism in response to different environmental conditions. To account for this limitation, we also integrated transcriptomic data, which details the gene expression of the bacterium in a wide array of environments. Importantly, to bridge the gap between gene expression levels and protein abundance, we accounted for the synonymous codon usage bias of the bacterium in the model. To our knowledge, this is the first time codon usage has been quantified and integrated into a metabolic model. The metabolic fluxes were defined as a function of protein abundance. To determine potential therapeutic targets using the model, we conducted gene essentiality and metabolic pathway sensitivity analyses and calculated flux control coefficients. We obtained 92.3% accuracy in predicting gene essentiality when compared to experimental data for C. difficile R20291 (ribotype 027) homologs. We validated our context-specific metabolic models using sensitivity and robustness analyses and compared model predictions with literature on C. difficile. The model predicts interesting facets of the bacterium's metabolism, such as changes in the bacterium's growth in response to different environmental conditions.

CONCLUSIONS

After an extensive validation process, we used icdf834 to obtain state-of-the-art predictions of therapeutic targets for C. difficile. We show how context-specific metabolic models augmented with codon usage information can be a beneficial resource for better understanding C. difficile and for identifying novel therapeutic targets. We remark that our approach can be applied to investigate and treat against other pathogens.

An integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features

We propose an integrated machine learning process to predict gene essentiality in Escherichia coli K-12 MG1655 metabolism that outperforms known methods.

Synthetic Chemical Inducers and Genetic Decoupling Enable Orthogonal Control of the rhaBAD Promoter

External control of gene expression is crucial in synthetic biology and biotechnology research and applications, and is commonly achieved using inducible promoter systems. The E. coli rhamnose-inducible rhaBAD promoter has properties superior to more commonly used inducible expression systems, but is marred by transient expression caused by degradation of the native inducer, l-rhamnose. To address this problem, 35 analogues of l-rhamnose were screened for induction of the rhaBAD promoter, but no strong inducers were identified. In the native configuration, an inducer must bind and activate two transcriptional activators, RhaR and RhaS. Therefore, the expression system was reconfigured to decouple the rhaBAD promoter from the native rhaSR regulatory cascade so that candidate inducers need only activate the terminal transcription factor RhaS. Rescreening the 35 compounds using the modified rhaBAD expression system revealed several promising inducers. These were characterized further to determine the strength, kinetics, and concentration-dependence of induction; whether the inducer was used as a carbon source by E. coli; and the modality (distribution) of induction among populations of cells. l-Mannose was found to be the most useful orthogonal inducer, providing an even greater range of induction than the native inducer l-rhamnose, and crucially, allowing sustained induction instead of transient induction. These findings address the key limitation of the rhaBAD expression system and suggest it may now be the most suitable system for many applications.

A novel proposal of a simplified bacterial gene set and the neo-construction of a general minimized metabolic network

A minimal gene set (MGS) is critical for the assembly of a minimal artificial cell. We have developed a proposal of simplifying bacterial gene set to approximate a bacterial MGS by the following procedure. First, we base our simplified bacterial gene set (SBGS) on experimentally determined essential genes to ensure that the genes included in the SBGS are critical. Second, we introduced a half-retaining strategy to extract persistent essential genes to ensure stability. Third, we constructed a viable metabolic network to supplement SBGS. The proposed SBGS includes 327 genes and required 431 reactions. This report describes an SBGS that preserves both self-replication and self-maintenance systems. In the minimized metabolic network, we identified five novel hub metabolites and confirmed 20 known hubs. Highly essential genes were found to distribute the connecting metabolites into more reactions. Based on our SBGS, we expanded the pool of targets for designing broad-spectrum antibacterial drugs to reduce pathogen resistance. We also suggested a rough semi-de novo strategy to synthesize an artificial cell, with potential applications in industry.

Evidence of horizontal gene transfer between obligate leaf nodule symbionts

Bacteria of the genus Burkholderia establish an obligate symbiosis with plant species of the Rubiaceae and Primulaceae families. The bacteria, housed within the leaves, are transmitted hereditarily and have not yet been cultured. We have sequenced and compared the genomes of eight bacterial leaf nodule symbionts of the Rubiaceae plant family. All of the genomes exhibit features consistent with genome erosion. Genes potentially involved in the biosynthesis of kirkamide, an insecticidal C7N aminocyclitol, are conserved in most Rubiaceae symbionts. However, some have partially lost the kirkamide pathway due to genome erosion and are unable to synthesize the compound. Kirkamide synthesis is therefore not responsible for the obligate nature of the symbiosis. More importantly, we find evidence of intra-clade horizontal gene transfer (HGT) events affecting genes of the secondary metabolism. This indicates that substantial gene flow can occur at the early stages following host restriction in leaf nodule symbioses. We propose that host-switching events and plasmid conjugative transfers could have promoted these HGTs. This genomic analysis of leaf nodule symbionts gives, for the first time, new insights in the genome evolution of obligate symbionts in their early stages of the association with plants.