Uncovering major genomic features of essential genes in Bacteria and a methanogenic Archaea

The identification of essential cellular genes is critical for validating drug targets

Accurately identifying biological targets is crucial for advancing treatment options. Essential genes, vital for cell or organism survival, hold promise as potential drug targets in disease treatment. Although many studies have sought to identify essential genes as therapeutic targets in medicine and bioinformatics, systematic reviews on their relationship with drug targets are relatively rare. This work presents a comprehensive analysis to aid in identifying essential genes as potential targets for drug discovery, encompassing their relevance, identification methods, successful case studies, and challenges. This work will facilitate the identification of essential genes as therapeutic targets, thereby boosting new drug development.

Transposon mutagenesis screen in Klebsiella pneumoniae identifies genetic determinants required for growth in human urine and serum

Klebsiella pneumoniae is a global public health concern due to the rising myriad of hypervirulent and multidrug-resistant clones both alarmingly associated with high mortality. The molecular mechanisms underpinning these recalcitrant K. pneumoniae infection, and how virulence is coupled with the emergence of lineages resistant to nearly all present-day clinically important antimicrobials, are unclear. In this study, we performed a genome-wide screen in K. pneumoniae ECL8, a member of the endemic K2-ST375 pathotype most often reported in Asia, to define genes essential for growth in a nutrient-rich laboratory medium (Luria-Bertani [LB] medium), human urine, and serum. Through transposon directed insertion-site sequencing (TraDIS), a total of 427 genes were identified as essential for growth on LB agar, whereas transposon insertions in 11 and 144 genes decreased fitness for growth in either urine or serum, respectively. These studies not only provide further knowledge on the genetics of this pathogen but also provide a strong impetus for discovering new antimicrobial targets to improve current therapeutic options for K. pneumoniae infections.

Transposon sequencing reveals the essential gene set and genes enabling gut symbiosis in the insect symbiont Caballeronia insecticola

Caballeronia insecticola is a bacterium belonging to the Burkholderia genus sensu lato, which is able to colonize multiple environments like soils and the gut of the bean bug Riptortus pedestris. We constructed a saturated Himar1 mariner transposon library and revealed by transposon-sequencing that 498 protein-coding genes constitute the essential genome of Caballeronia insecticola for growth in free-living conditions. By comparing essential gene sets of Caballeronia insecticola and seven related Burkholderia s.l. strains, only 120 common genes were identified, indicating that a large part of the essential genome is strain-specific. In order to reproduce specific nutritional conditions that are present in the gut of Riptortus pedestris, we grew the mutant library in minimal media supplemented with candidate gut nutrients and identified several condition-dependent fitness-defect genes by transposon-sequencing. To validate the robustness of the approach, insertion mutants in six fitness genes were constructed and their growth deficiency in media supplemented with the corresponding nutrient was confirmed. The mutants were further tested for their efficiency in Riptortus pedestris gut colonization, confirming that gluconeogenic carbon sources, taurine and inositol, are nutrients consumed by the symbiont in the gut. Thus, our study provides insights about specific contributions provided by the insect host to the bacterial symbiont.

Immunoinformatics aided designing of a next generation poly-epitope vaccine against uropathogenic Escherichia coli to combat urinary tract infections

Urinary tract infections (UTIs) are the second most prevalent bacterial infections and uropathogenic Escherichia coli (UPEC) stands among the primary causative agents of UTIs. The usage of antibiotics is the routine therapy being used in various countries to treat UTIs but becoming ineffective because of increasing antibiotic resistance among UPEC strains. Thus, there must be the development of some alternative treatment strategies such as vaccine development against UPEC. In the following study, pan-genomics along with reverse vaccinology approaches is used under the framework of bioinformatics for the identification of core putative vaccine candidates, employing 307 UPEC genomes (complete and draft), available publicly. A total of nine T-cell epitopes (derived from B-cells) of both MHC classes (I and II), were prioritized among three potential protein candidates. These epitopes were then docked together by using linkers (GPGPG and AAY) and an adjuvant (Cholera Toxin B) to form a poly-valent vaccine construct. The chimeric vaccine construct was undergone by molecular modelling, further refinement and energy minimization. We predicted positive results of the vaccine construct in immune simulations with significantly high levels of immune cells. The protein-protein docking analysis of vaccine construct with toll-like receptors predicted efficient binding, which was further validated by molecular dynamics simulation of vaccine construct with TLR-2 and TLR-4 at 120 ns, resulting in stable complexes' conformation throughout the simulation run. Overall, the vaccine construct demonstrated positive antigenic response. In future, this chimeric vaccine construct or the identified epitopes could be experimentally validated for the development of UPEC vaccines against UTIs.Communicated by Ramaswamy H. Sarma.

Mesomycoplasma ovipneumoniae from goats with respiratory infection: pathogenic characteristics, population structure, and genomic features

BACKGROUND

Mycoplasma ovipneumoniae is a critical pathogen that causes respiratory diseases that threaten Caprini health and cause economic damage. A genome-wide study of M. ovipneumoniae will help understand the pathogenic characteristics of this microorganism.

RESULTS

Toxicological pathology and whole-genome sequencing of nine M. ovipneumoniae strains isolated from goats were performed using an epidemiological survey. These strains exhibited anterior ventral lung consolidation, typical of bronchopneumonia in goats. Average nucleotide identity and phylogenetic analysis based on whole-genome sequences showed that all M. ovipneumoniae strains clustered into two clades, largely in accordance with their geographical origins. The pan-genome of the 23 M. ovipneumoniae strains contained 5,596 genes, including 385 core, 210 soft core, and 5,001 accessory genes. Among these genes, two protein-coding genes were annotated as cilium adhesion and eight as paralog surface adhesins when annotated to VFDB, and no antibiotic resistance-related genes were predicted. Additionally, 23 strains carried glucosidase-related genes (ycjT and group_1595) and glucosidase-related genes (atpD_2), indicating that M. ovipneumoniae possesses a wide range of glycoside hydrolase activities.

CONCLUSIONS

The population structure and genomic features identified in this study will facilitate further investigations into the pathogenesis of M. ovipneumoniae and lay the foundation for the development of preventive and therapeutic methods.

Genome-wide fitness analysis identifies genes required for in vitro growth and macrophage infection by African and global epidemic pathovariants of Salmonella enterica Enteritidis

Salmonella enterica Enteritidis is the second most common serovar associated with invasive non-typhoidal Salmonella (iNTS) disease in sub-Saharan Africa. Previously, genomic and phylogenetic characterization of S . enterica Enteritidis isolates from the human bloodstream led to the discovery of the Central/Eastern African clade (CEAC) and West African clade, which were distinct from the gastroenteritis-associated global epidemic clade (GEC). The African S . enterica Enteritidis clades have unique genetic signatures that include genomic degradation, novel prophage repertoires and multi-drug resistance, but the molecular basis for the enhanced propensity of African S . enterica Enteritidis to cause bloodstream infection is poorly understood. We used transposon insertion sequencing (TIS) to identify the genetic determinants of the GEC representative strain P125109 and the CEAC representative strain D7795 for growth in three in vitro conditions (LB or minimal NonSPI2 and InSPI2 growth media), and for survival and replication in RAW 264.7 murine macrophages. We identified 207 in vitro -required genes that were common to both S . enterica Enteritidis strains and also required by S . enterica Typhimurium, S . enterica Typhi and Escherichia coli , and 63 genes that were only required by individual S . enterica Enteritidis strains. Similar types of genes were required by both P125109 and D7795 for optimal growth in particular media. Screening the transposon libraries during macrophage infection identified 177 P125109 and 201 D7795 genes that contribute to bacterial survival and replication in mammalian cells. The majority of these genes have proven roles in Salmonella virulence. Our analysis uncovered candidate strain-specific macrophage fitness genes that could encode novel Salmonella virulence factors.

Application of TraDIS to define the core essential genome of Campylobacter jejuni and Campylobacter coli

Campylobacter species are the major cause of bacterial gastroenteritis. As there is no effective vaccine, combined with the rapid increase in antimicrobial resistant strains, there is a need to identify new targets for intervention. Essential genes are those that are necessary for growth and/or survival, making these attractive targets. In this study, comprehensive transposon mutant libraries were created in six C. jejuni strains, four C. coli strains and one C. lari and C. hyointestinalis strain, allowing for those genes that cannot tolerate a transposon insertion being called as essential. Comparison of essential gene lists using core genome analysis can highlight those genes which are common across multiple strains and/or species. Comparison of C. jejuni and C. coli, the two species that cause the most disease, identified 316 essential genes. Genes of interest highlighted members of the purine pathway being essential for C. jejuni whilst also finding that a functional potassium uptake system is essential. Protein-protein interaction networks using these essential gene lists also highlighted proteins in the purine pathway being major 'hub' proteins which have a large number of interactors across the network. When adding in two more species (C. lari and C. hyointestinalis) the essential gene list reduces to 261. Within these 261 essential genes, there are many genes that have been found to be essential in other bacteria. These include htrB and PEB4, which have previously been found as core virulence genes across Campylobacter species in other studies. There were 21 genes which have no known function with eight of these being associated with the membrane. These surface-associated essential genes may provide attractive targets. The essential gene lists presented will help to prioritise targets for the development of novel therapeutic and preventative interventions.

Identification of essential genes in Coxiella burnetii

Coxiella burnetii is an intracellular pathogen responsible for causing Q fever in humans, a disease with varied presentations ranging from a mild flu-like sickness to a debilitating illness that can result in endocarditis. The intracellular lifestyle of C. burnetii is unique, residing in an acidic phagolysosome-like compartment within host cells. An understanding of the core molecular biology of C. burnetii will greatly increase our understanding of C. burnetii growth, survival and pathogenesis. We used transposon-directed insertion site sequencing (TraDIS) to reveal C. burnetii Nine Mile Phase II genes fundamental for growth and in vitro survival. Screening a transposon library containing >10 000 unique transposon mutants revealed 512 predicted essential genes. Essential routes of synthesis were identified for the mevalonate pathway, as well as peptidoglycan and biotin synthesis. Some essential genes identified (e.g. predicted type IV secretion system effector genes) are typically considered to be associated with C. burnetii virulence, a caveat concerning the axenic media used in the study. Investigation into the conservation of the essential genes identified revealed that 78 % are conserved across all C. burnetii strains sequenced to date, which probably play critical functions. This is the first report of a whole genome transposon screen in C. burnetii that has been undertaken for the identification of essential genes.

Microbiome-driven breeding strategy potentially improves beef fatty acid profile benefiting human health and reduces methane emissions

BACKGROUND

Healthier ruminant products can be achieved by adequate manipulation of the rumen microbiota to increase the flux of beneficial fatty acids reaching host tissues. Genomic selection to modify the microbiome function provides a permanent and accumulative solution, which may have also favourable consequences in other traits of interest (e.g. methane emissions). Possibly due to a lack of data, this strategy has never been explored.

RESULTS

This study provides a comprehensive identification of ruminal microbial mechanisms under host genomic influence that directly or indirectly affect the content of unsaturated fatty acids in beef associated with human dietary health benefits C18:3n-3, C20:5n-3, C22:5n-3, C22:6n-3 or cis-9, trans-11 C18:2 and trans-11 C18:1 in relation to hypercholesterolemic saturated fatty acids C12:0, C14:0 and C16:0, referred to as N3 and CLA indices. We first identified that ~27.6% (1002/3633) of the functional core additive log-ratio transformed microbial gene abundances (alr-MG) in the rumen were at least moderately host-genomically influenced (HGFC). Of these, 372 alr-MG were host-genomically correlated with the N3 index (n=290), CLA index (n=66) or with both (n=16), indicating that the HGFC influence on beef fatty acid composition is much more complex than the direct regulation of microbial lipolysis and biohydrogenation of dietary lipids and that N3 index variation is more strongly subjected to variations in the HGFC than CLA. Of these 372 alr-MG, 110 were correlated with the N3 and/or CLA index in the same direction, suggesting the opportunity for enhancement of both indices simultaneously through a microbiome-driven breeding strategy. These microbial genes were involved in microbial protein synthesis (aroF and serA), carbohydrate metabolism and transport (galT, msmX), lipopolysaccharide biosynthesis (kdsA, lpxD, lpxB), or flagellar synthesis (flgB, fliN) in certain genera within the Proteobacteria phyla (e.g. Serratia, Aeromonas). A microbiome-driven breeding strategy based on these microbial mechanisms as sole information criteria resulted in a positive selection response for both indices (1.36±0.24 and 0.79±0.21 sd of N3 and CLA indices, at 2.06 selection intensity). When evaluating the impact of our microbiome-driven breeding strategy to increase N3 and CLA indices on the environmental trait methane emissions (g/kg of dry matter intake), we obtained a correlated mitigation response of -0.41±0.12 sd.

CONCLUSION

This research provides insight on the possibility of using the ruminal functional microbiome as information for host genomic selection, which could simultaneously improve several microbiome-driven traits of interest, in this study exemplified with meat quality traits and methane emissions. Video Abstract.

Differential Genetic Strategies of Burkholderia vietnamiensis and Paraburkholderia kururiensis for Root Colonization of Oryza sativa subsp. japonica and O. sativa subsp. indica , as Revealed by Transposon Mutagenesis Sequencing

Burkholderiaceae are frequent and abundant colonizers of the rice rhizosphere and interesting candidates to investigate for growth promotion. Species of Paraburkholderia have repeatedly been described to stimulate plant growth.

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.

Research on the Computational Prediction of Essential Genes

Genes, the nucleotide sequences that encode a polypeptide chain or functional RNA, are the basic genetic unit controlling biological traits. They are the guarantee of the basic structures and functions in organisms, and they store information related to biological factors and processes such as blood type, gestation, growth, and apoptosis. The environment and genetics jointly affect important physiological processes such as reproduction, cell division, and protein synthesis. Genes are related to a wide range of phenomena including growth, decline, illness, aging, and death. During the evolution of organisms, there is a class of genes that exist in a conserved form in multiple species. These genes are often located on the dominant strand of DNA and tend to have higher expression levels. The protein encoded by it usually either performs very important functions or is responsible for maintaining and repairing these essential functions. Such genes are called persistent genes. Among them, the irreplaceable part of the body’s life activities is the essential gene. For example, when starch is the only source of energy, the genes related to starch digestion are essential genes. Without them, the organism will die because it cannot obtain enough energy to maintain basic functions. The function of the proteins encoded by these genes is thought to be fundamental to life. Nowadays, DNA can be extracted from blood, saliva, or tissue cells for genetic testing, and detailed genetic information can be obtained using the most advanced scientific instruments and technologies. The information gained from genetic testing is useful to assess the potential risks of disease, and to help determine the prognosis and development of diseases. Such information is also useful for developing personalized medication and providing targeted health guidance to improve the quality of life. Therefore, it is of great theoretical and practical significance to identify important and essential genes. In this paper, the research status of essential genes and the essential genome database of bacteria are reviewed, the computational prediction method of essential genes based on communication coding theory is expounded, and the significance and practical application value of essential genes are discussed.

Prediction of Genes That Function in Methanogenesis and CO2 Pathways in Extremophiles

Gaet’ale (GAL) and Mud’ara (MUP) are two hypersaline ponds located in the Danakil Depression recharged by underground water from the surrounding highlands. These two ponds have different pH, salinity, and show variation in the concentration of many ionic components. Metagenomic analysis concludes that GAL is dominated by bacteria as in the case of the other hypersaline and acidic ponds in the Danakil Depression. However, Archaea dominated the ponds of MUP. In the current study, the application of SEED and KEGG helped to map the ordered steps of specific enzyme catalyzed reaction in converting CO₂ into cell products. We predict that highly efficient and light-independent carbon fixation involving phosphoenolpyruvate carboxylase takes place in MUP. On the contrary, genes encoding enzymes involved in hydrogenotrophic and acetoclastic methanogenesis appeared solely in ponds of GAL, implying the biological source of the hazardous methane gas in that environment. Based on the investigation of the sources of the genes of interest, it is clear that cooperative interactions between members of the two communities and syntrophic metabolism is the main strategy adapted to utilize inorganic carbon as a carbon source in both MUP and GAL. This insight can be used to design biotechnological applications of microbial communities in production of methane biogas or to minimize CO₂ emissions.

Harnessing model organism genomics to underpin the machine learning-based prediction of essential genes in eukaryotes - Biotechnological implications

The availability of high-quality genomes and advances in functional genomics have enabled large-scale studies of essential genes in model eukaryotes, including the 'elegant worm' (Caenorhabditis elegans; Nematoda) and the 'vinegar fly' (Drosophila melanogaster; Arthropoda). However, this is not the case for other, much less-studied organisms, such as socioeconomically important parasites, for which functional genomic platforms usually do not exist. Thus, there is a need to develop innovative techniques or approaches for the prediction, identification and investigation of essential genes. A key approach that could enable the prediction of such genes is machine learning (ML). Here, we undertake an historical review of experimental and computational approaches employed for the characterisation of essential genes in eukaryotes, with a particular focus on model ecdysozoans (C. elegans and D. melanogaster), and discuss the possible applicability of ML-approaches to organisms such as socioeconomically important parasites. We highlight some recent results showing that high-performance ML, combined with feature engineering, allows a reliable prediction of essential genes from extensive, publicly available 'omic data sets, with major potential to prioritise such genes (with statistical confidence) for subsequent functional genomic validation. These findings could 'open the door' to fundamental and applied research areas. Evidence of some commonality in the essential gene-complement between these two organisms indicates that an ML-engineering approach could find broader applicability to ecdysozoans such as parasitic nematodes or arthropods, provided that suitably large and informative data sets become/are available for proper feature engineering, and for the robust training and validation of algorithms. This area warrants detailed exploration to, for example, facilitate the identification and characterisation of essential molecules as novel targets for drugs and vaccines against parasitic diseases. This focus is particularly important, given the substantial impact that such diseases have worldwide, and the current challenges associated with their prevention and control and with drug resistance in parasite populations.

At the Crossroads of Bioenergetics and Antibiotic Discovery

Dr. Vladimir Skulachev was my mentor, and his pioneering work in the field of bioenergetics inspired the discoveries described in this review, written in the form of a personal account of events. Examining basic mechanisms of chemiosmotic coupling unexpectedly led us to transenvelope multidrug resistance pumps (MDR pumps) that severely limit development of novel antibiotics. One of the major advances of Skulachev and his group was the discovery of the mitochondrial membrane potential with the use of permeant cations such as TPP⁺, which served as electric probes. We describe our finding of their natural counterparts in plants, where they act as antimicrobials. The most challenging problems in antimicrobial drug discovery are antibiotic tolerance of chronic infections caused by dormant persister cells; antibiotic resistance, responsible for the current antimicrobial resistance crisis (AMR); and finding novel compounds acting against Gram-negative bacteria, protected by their powerful multidrug resistance pumps. Our study of persisters shows that these are rare cells formed by stochastic fluctuation in expression of Krebs cycle enzymes, leading to a drop in ATP, target shutdown, and antibiotic tolerance. Searching for compounds that can corrupt targets in the absence of ATP, we identified acyldepsipeptide (ADEP) that activates the ClpP protease, forcing cells to self-digest. Growing previously uncultured bacteria led us to teixobactin, a novel cell wall acting antibiotic. Teixobactin avoids efflux by targeting lipid II and lipid III, precursors of peptidoglycan and wall teichoic acid, located on the surface. The targets are immutable, and teixobactin is the first antibiotic with no detectable resistance. Our search for compounds acting against Gram-negative bacteria led to the discovery of darobactins, which also hit a surface target, the essential chaperone BamA.

Position preference of essential genes in prokaryotic operons

Essential genes, which form the basis of life activities, are crucial for the survival of organisms. Essential genes tend to be located in operons, but how they are distributed in operons is still unclear for most prokaryotes. In order to clarify the general rule of position preference of essential genes in operons, an index of the average position of genes in an operon was proposed, and the distributions of essential and non-essential genes in operons in 51 bacterial genomes and two archaeal genomes were analyzed based on this new index. Consequently, essential genes were found to preferentially occupy the front positions of the operons, which tend to be expressed at higher levels.

Elucidating Essential Genes in Plant-Associated Pseudomonas protegens Pf-5 Using Transposon Insertion Sequencing

Gene essentiality studies have been performed on numerous bacterial pathogens, but essential gene sets have been determined for only a few plant-associated bacteria. Pseudomonas protegens Pf-5 is a plant-commensal, biocontrol bacterium that can control disease-causing pathogens on a wide range of crops. Work on Pf-5 has mostly focused on secondary metabolism and biocontrol genes, but genome-wide approaches such as high-throughput transposon mutagenesis have not yet been used for this species. In this study, we generated a dense P. protegens Pf-5 transposon mutant library and used transposon-directed insertion site sequencing (TraDIS) to identify 446 genes essential for growth on rich media. Genes required for fundamental cellular machinery were enriched in the essential gene set, while genes related to nutrient biosynthesis, stress responses, and transport were underrepresented. The majority of Pf-5 essential genes were part of the P. protegens core genome. Comparison of the essential gene set of Pf-5 with those of two plant-associated pseudomonads, P. simiae and P. syringae, and the well-studied opportunistic human pathogen P. aeruginosa PA14 showed that the four species share a large number of essential genes, but each species also had uniquely essential genes. Comparison of the Pf-5 in silico-predicted and in vitro-determined essential gene sets highlighted the essential cellular functions that are over- and underestimated by each method. Expanding essentiality studies into bacteria with a range of lifestyles may improve our understanding of the biological processes important for bacterial survival and growth.IMPORTANCE Essential genes are those crucial for survival or normal growth rates in an organism. Essential gene sets have been identified in numerous bacterial pathogens but only a few plant-associated bacteria. Employing genome-wide approaches, such as transposon insertion sequencing, allows for the concurrent analyses of all genes of a bacterial species and rapid determination of essential gene sets. We have used transposon insertion sequencing to systematically analyze thousands of Pseudomonas protegens Pf-5 genes and gain insights into gene functions and interactions that are not readily available using traditional methods. Comparing Pf-5 essential genes with those of three other pseudomonads highlights how gene essentiality varies between closely related species.

A Computational Framework Based on Ensemble Deep Neural Networks for Essential Genes Identification

Essential genes contain key information of genomes that could be the key to a comprehensive understanding of life and evolution. Because of their importance, studies of essential genes have been considered a crucial problem in computational biology. Computational methods for identifying essential genes have become increasingly popular to reduce the cost and time-consumption of traditional experiments. A few models have addressed this problem, but performance is still not satisfactory because of high dimensional features and the use of traditional machine learning algorithms. Thus, there is a need to create a novel model to improve the predictive performance of this problem from DNA sequence features. This study took advantage of a natural language processing (NLP) model in learning biological sequences by treating them as natural language words. To learn the NLP features, a supervised learning model was consequentially employed by an ensemble deep neural network. Our proposed method could identify essential genes with sensitivity, specificity, accuracy, Matthews correlation coefficient (MCC), and area under the receiver operating characteristic curve (AUC) values of 60.2%, 84.6%, 76.3%, 0.449, and 0.814, respectively. The overall performance outperformed the single models without ensemble, as well as the state-of-the-art predictors on the same benchmark dataset. This indicated the effectiveness of the proposed method in determining essential genes, in particular, and other sequencing problems, in general.

Redefining genetic essentiality in Mycobacterium tuberculosis

Sequencing transposon mutant libraries have been pivotal in annotating essential and non-essential genes in bacteria. This is particularly very helpful in the case of Mycobacterium tuberculosis with a large part of its genome without known function. It is not known whether there are any variations in the essentiality states as a function of optimal growth in the absence of any selection pressure. We here grow a high-density mutant library of M. tuberculosis through serial cultures and monitor the temporal fluctuations in insertion frequencies across all TA dinucleotides in the genome. Genes that cause morphological and physiological heterogeneity or enable metabolic bypass were found to gradually lose insertions, while genes comprising the toxin-antitoxin systems were found to get enriched with insertions during growth in nutrient replete conditions. High levels of fluctuations were observed in genes involved in cell wall and cell processes, intermediary metabolism, and genes involved in virulence, suggesting new modes of adaptation undertaken by the mutants. We also report the essentiality status of several newly annotated genetic features.

Comparative genomic analysis reveals starvation survival systems in Methanothermobacter thermautotrophicus ΔH

Methanothermobacter thermautotrophicus ΔH (MTH) is a thermophilic hydrogenotrophic methanogenic archaeon capable of reducing CO₂ with H₂ to produce methane gas. It is the potential candidate in the biomethanation of CO₂ and CO in anaerobic reactors and biogas upgrading process. However, systematic studies addressing its genome conservation and function remain scant in this genome. In this study, we have evaluated its evolutionary resemblance and metabolic discrepancy, particularly in starvation survival systems by comparing the genomic contexts with Methanothermobacter marburgensis str. Marburg (MMG) and Methanobacterium formicicum DSM 1535 (MFO). The phylogenomic analysis of this study indicated that there was a strong phylogenomic signal among MTH, MMG, and MFO in the whole-genome tree. DNA replication machinery was conserved in the MTH genome and might have evolved at different evolution rates. Genome synteny analysis observed collinearity of either gene orders or gene families has to be maintained with syntenic blocks located in the syntenic out-paralogs. A genome-wide metabolic analysis identified some unique putative metabolic subsystems in MTH, which are proposed to determine its growth characteristics in diverse environments. MTH genome comprised of 93 unique genes-coding for starvation survival and stress-response proteins. These proteins confer its adaptation to nutritional deprivation and other abiotic stresses. MTH has a typical system to withstand its growth and cell viability during stable operation and recovery after prolonged starvation. Thus, the present work will provide an insight to improve the genome refinement and metabolic reconstruction in parallel to other closely related species.

Large-Scale Analysis of the Mycoplasma bovis Genome Identified Non-essential, Adhesion- and Virulence-Related Genes

Mycoplasma bovis is an important pathogen of cattle causing bovine mycoplasmosis. Clinical manifestations are numerous, but pneumonia, mastitis, and arthritis cases are mainly reported. Currently, no efficient vaccine is available and antibiotic treatments are not always satisfactory. The design of new, efficient prophylactic and therapeutic approaches requires a better understanding of the molecular mechanisms responsible for M. bovis pathogenicity. Random transposon mutagenesis has been widely used in Mycoplasma species to identify potential gene functions. Such an approach can also be used to screen genomes and search for essential and non-essential genes for growth. Here, we generated a random transposon mutant library of M. bovis strain JF4278 containing approximately 4000 independent insertion sites. We then coupled high-throughput screening of this mutant library to transposon sequencing and bioinformatic analysis to identify M. bovis non-essential, adhesion- and virulence-related genes. Three hundred and fifty-two genes of M. bovis were assigned as essential for growth in rich medium. Among the remaining non-essential genes, putative virulence-related factors were subsequently identified. The complete mutant library was screened for adhesion using primary bovine mammary gland epithelial cells. Data from this assay resulted in a list of conditional-essential genes with putative adhesion-related functions by identifying non-essential genes for growth that are essential for host cell-adhesion. By individually assessing the adhesion capacity of six selected mutants, two previously unknown factors and the adhesin TrmFO were associated with a reduced adhesion phenotype. Overall, our study (i) uncovers new, putative virulence-related genes; (ii) offers a list of putative adhesion-related factors; and (iii) provides valuable information for vaccine design and for exploring M. bovis biology, pathogenesis, and host-interaction.

Immunoinformatics-Aided Design and Evaluation of a Potential Multi-Epitope Vaccine against Klebsiella Pneumoniae

Klebsiella pneumoniae is an opportunistic gram-negative bacterium that causes nosocomial infection in healthcare settings. Despite the high morbidity and mortality rate associated with these bacterial infections, no effective vaccine is available to counter the pathogen. In this study, the pangenome of a total of 222 available complete genomes of K. pneumoniae was explored to obtain the core proteome. A reverse vaccinology strategy was applied to the core proteins to identify four antigenic proteins. These proteins were then subjected to epitope mapping and prioritization steps to shortlist nine B-cell derived T-cell epitopes which were linked together using GPGPG linkers. An adjuvant (Cholera Toxin B) was also added at the N-terminal of the vaccine construct to improve its immunogenicity and a stabilized multi-epitope protein structure was obtained using molecular dynamics simulation. The designed vaccine exhibited sustainable and strong bonding interactions with Toll-like receptor 2 and Toll-like receptor 4. In silico reverse translation and codon optimization also confirmed its high expression in E. coli K12 strain. The computer-aided analyses performed in this study imply that the designed multi-epitope vaccine can elicit specific immune responses against K. pneumoniae. However, wet lab validation is necessary to further verify the effectiveness of this proposed vaccine candidate.

Genomic analysis unveils important aspects of population structure, virulence, and antimicrobial resistance in Klebsiella aerogenes

Klebsiella aerogenes is an important pathogen in healthcare-associated infections. Nevertheless, in comparison to other clinically important pathogens, K. aerogenes population structure, genetic diversity, and pathogenicity remain poorly understood. Here, we elucidate K. aerogenes clonal complexes (CCs) and genomic features associated with resistance and virulence. We present a detailed description of the population structure of K. aerogenes based on 97 publicly available genomes by using both multilocus sequence typing and single-nucleotide polymorphisms extracted from the core genome. We also assessed virulence and resistance profiles using Virulence Finder Database and Comprehensive Antibiotic Resistance Database, respectively. We show that K. aerogenes has an open pangenome and a large effective population size, which account for its high genomic diversity and support that negative selection prevents fixation of most deleterious alleles. The population is structured in at least 10 CCs, including two novel ones identified here, CC9 and CC10. The repertoires of resistance genes comprise a high number of antibiotic efflux proteins as well as narrow- and extended-spectrum β-lactamases. Regarding the population structure, we identified two clusters based on virulence profiles because of the presence of the toxin-encoding clb operon and the siderophore production genes, irp and ybt. Notably, CC3 comprises the majority of K. aerogenes isolates associated with hospital outbreaks, emphasizing the importance of constant monitoring of this pathogen. Collectively, our results may provide a foundation for the development of new therapeutic and surveillance strategies worldwide.

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.

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.

Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways

Identifying essential genes in a given organism is important for research on their fundamental roles in organism survival. Furthermore, if possible, uncovering the links between core functions or pathways with these essential genes will further help us obtain deep insight into the key roles of these genes. In this study, we investigated the essential and non-essential genes reported in a previous study and extracted gene ontology (GO) terms and biological pathways that are important for the determination of essential genes. Through the enrichment theory of GO and KEGG pathways, we encoded each essential/non-essential gene into a vector in which each component represented the relationship between the gene and one GO term or KEGG pathway. To analyze these relationships, the maximum relevance minimum redundancy (mRMR) was adopted. Then, the incremental feature selection (IFS) and support vector machine (SVM) were employed to extract important GO terms and KEGG pathways. A prediction model was built simultaneously using the extracted GO terms and KEGG pathways, which yielded nearly perfect performance, with a Matthews correlation coefficient of 0.951, for distinguishing essential and non-essential genes. To fully investigate the key factors influencing the fundamental roles of essential genes, the 21 most important GO terms and three KEGG pathways were analyzed in detail. In addition, several genes was provided in this study, which were predicted to be essential genes by our prediction model. We suggest that this study provides more functional and pathway information on the essential genes and provides a new way to investigate related problems.

Construction and Analysis of Two Genome-Scale Deletion Libraries for Bacillus subtilis

A systems-level understanding of Gram-positive bacteria is important from both an environmental and health perspective and is most easily obtained when high-quality, validated genomic resources are available. To this end, we constructed two ordered, barcoded, erythromycin-resistance- and kanamycin-resistance-marked single-gene deletion libraries of the Gram-positive model organism, Bacillus subtilis. The libraries comprise 3,968 and 3,970 genes, respectively, and overlap in all but four genes. Using these libraries, we update the set of essential genes known for this organism, provide a comprehensive compendium of B. subtilis auxotrophic genes, and identify genes required for utilizing specific carbon and nitrogen sources, as well as those required for growth at low temperature. We report the identification of enzymes catalyzing several missing steps in amino acid biosynthesis. Finally, we describe a suite of high-throughput phenotyping methodologies and apply them to provide a genome-wide analysis of competence and sporulation. Altogether, we provide versatile resources for studying gene function and pathway and network architecture in Gram-positive bacteria.

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.

Impact of genomics on the understanding of microbial evolution and classification: the importance of Darwin's views on classification

Analyses of genome sequences, by some approaches, suggest that the widespread occurrence of horizontal gene transfers (HGTs) in prokaryotes disguises their evolutionary relationships and have led to questioning of the Darwinian model of evolution for prokaryotes. These inferences are critically examined in the light of comparative genome analysis, characteristic synapomorphies, phylogenetic trees and Darwin's views on examining evolutionary relationships. Genome sequences are enabling discovery of numerous molecular markers (synapomorphies) such as conserved signature indels (CSIs) and conserved signature proteins (CSPs), which are distinctive characteristics of different prokaryotic taxa. Based on these molecular markers, exhibiting high degree of specificity and predictive ability, numerous prokaryotic taxa of different ranks, currently identified based on the 16S rRNA gene trees, can now be reliably demarcated in molecular terms. Within all studied groups, multiple CSIs and CSPs have been identified for successive nested clades providing reliable information regarding their hierarchical relationships and these inferences are not affected by HGTs. These results strongly support Darwin's views on evolution and classification and supplement the current phylogenetic framework based on 16S rRNA in important respects. The identified molecular markers provide important means for developing novel diagnostics, therapeutics and for functional studies providing important insights regarding prokaryotic taxa.