From microbial gene essentiality to novel antimicrobial drug targets

Essential genes for Haemophilus parainfluenzae survival and biofilm growth

Haemophilus parainfluenzae (Hp) is a Gram-negative, highly prevalent, and abundant commensal in the human oral cavity, and an infrequent extraoral opportunistic pathogen. Hp occupies multiple niches in the oral cavity, including the supragingival plaque biofilm. Little is known about how Hp interacts with its neighbors in healthy biofilms nor its mechanisms of pathogenesis as an opportunistic pathogen. To address this, we identified the essential genome and conditionally essential genes in in vitro biofilms aerobically and anaerobically. Using transposon insertion sequencing (TnSeq) with a highly saturated mariner transposon library in two strains, the ATCC33392 type-strain (Hp 392) and oral isolate EL1 (Hp EL1), we show that the essential genomes of Hp 392 and Hp EL1 are composed of 395 (20%) and 384 (19%) genes, respectively. The core essential genome, consisting of 341 (17%) essential genes conserved between both strains, was composed of genes associated with genetic information processing, carbohydrate, protein, and energy metabolism. We also identified conditionally essential genes for aerobic and anaerobic biofilm growth, which were associated with carbohydrate and energy metabolism in both strains. RNAseq analysis determined that most genes upregulated during anaerobic growth are not essential for Hp 392 anaerobic survival. The completion of this library and analysis under these conditions gives us a foundational insight into the basic biology of H. parainfluenzae in differing oxygen conditions, similar to its in vivo habitat. This library presents a valuable tool for investigation into conditionally essential genes for an organism that lives in close contact with many microbial species in the human oral habitat.IMPORTANCEHaemophilus parainfluenzae is a highly abundant human commensal microbe, present in most healthy individuals where it colonizes the mouth. H. parainfluenzae correlates with good oral health and may play a role in preservation of healthy host status. Also, H. parainfluenzae can cause opportunistic infections outside of the oral cavity. To date, little is known about how H. parainfluenzae colonizes the human host, despite being such a frequent and abundant part of our human microbiome. Here, we demonstrate the creation and use of a powerful tool, a TnSeq library, used to identify genes necessary for both the outright growth of this organism and also genes conditionally essential for growth in varying oxygen status which it can encounter in the human host. This tool and these data serve as a foundation for further study of this relatively unknown organism that may play a role in preserving human health.

Essential genes for Haemophilus parainfluenzae survival and biofilm growth

Haemophilus parainfluenzae ( Hp ) is a Gram-negative, pleomorphic rod, highly prevalent and abundant as a commensal in the human oral cavity, and an infrequent extraoral opportunistic pathogen. Hp occupies multiple niches in the oral cavity, including the tongue dorsum, keratinized gingiva, and the supragingival plaque biofilm. As a member of the HACEK group, Hp is also known to cause infective endocarditis. Additionally, case reports have identified Hp as the causative agent of meningitis, septic arthritis, chronic osteomyelitis, septicemia, and a variety of other infectious diseases. Little is known about how Hp interacts with its neighbors in the healthy biofilm nor about its mechanisms of pathogenesis as an extraoral opportunistic pathogen. To address these unknowns, we identified the essential genomes of two Hp strains and the conditionally essential genes for their growth in in vitro biofilms aerobically and anaerobically. Using transposon insertion sequencing (TnSeq) with a highly saturated mariner transposon library in two strains, the ATCC33392 type-strain ( Hp 392) and a commensal oral isolate EL1 ( Hp EL1), we show that the essential genome of Hp 392 and Hp EL1 is composed of 395 and 384 genes, respectively. The core essential genome, consisting of 341 essential genes conserved between both strains, was composed of genes associated with genetic information processing, carbohydrate, protein, and energy metabolism. We also identified conditionally essential genes for aerobic and anaerobic biofilm growth, which were associated with carbohydrate and energy metabolism in both strains of Hp . Additionally, RNAseq analysis determined that most genes upregulated during anaerobic growth are not essential for Hp 392 anaerobic biofilm survival. The completion of this library and analysis under these conditions gives us a foundational insight into the basic biology of H. parainfluenzae in differing oxygen conditions, similar to its in vivo oral habitat. Further, the creation of this library presents a valuable tool for further investigation into conditionally essential genes for an organism that lives in close contact with many microbial species in the human oral habitat.

Unrealized targets in the discovery of antibiotics for Gram-negative bacterial infections

Advances in areas that include genomics, systems biology, protein structure determination and artificial intelligence provide new opportunities for target-based antibacterial drug discovery. The selection of a 'good' new target for direct-acting antibacterial compounds is the first decision, for which multiple criteria must be explored, integrated and re-evaluated as drug discovery programmes progress. Criteria include essentiality of the target for bacterial survival, its conservation across different strains of the same species, bacterial species and growth conditions (which determines the spectrum of activity of a potential antibiotic) and the level of homology with human genes (which influences the potential for selective inhibition). Additionally, a bacterial target should have the potential to bind to drug-like molecules, and its subcellular location will govern the need for inhibitors to penetrate one or two bacterial membranes, which is a key challenge in targeting Gram-negative bacteria. The risk of the emergence of target-based drug resistance for drugs with single targets also requires consideration. This Review describes promising but as-yet-unrealized targets for antibacterial drugs against Gram-negative bacteria and examples of cognate inhibitors, and highlights lessons learned from past drug discovery programmes.

Bactabolize is a tool for high-throughput generation of bacterial strain-specific metabolic models

Metabolic capacity can vary substantially within a bacterial species, leading to ecological niche separation, as well as differences in virulence and antimicrobial susceptibility. Genome-scale metabolic models are useful tools for studying the metabolic potential of individuals, and with the rapid expansion of genomic sequencing there is a wealth of data that can be leveraged for comparative analysis. However, there exist few tools to construct strain-specific metabolic models at scale. Here, we describe Bactabolize, a reference-based tool which rapidly produces strain-specific metabolic models and growth phenotype predictions. We describe a pan reference model for the priority antimicrobial-resistant pathogen, Klebsiella pneumoniae, and a quality control framework for using draft genome assemblies as input for Bactabolize. The Bactabolize-derived model for K. pneumoniae reference strain KPPR1 performed comparatively or better than currently available automated approaches CarveMe and gapseq across 507 substrate and 2317 knockout mutant growth predictions. Novel draft genomes passing our systematically defined quality control criteria resulted in models with a high degree of completeness (≥99% genes and reactions captured compared to models derived from matched complete genomes) and high accuracy (mean 0.97, n=10). We anticipate the tools and framework described herein will facilitate large-scale metabolic modelling analyses that broaden our understanding of diversity within bacterial species and inform novel control strategies for priority pathogens.

Can bacteria F. nucleatum be actively involved in colon cancer progression via a radical mediated mechanism?

Outer membrane proteins of Fusobacterium nucleatum, a cancer‑leading bacteria, are considered as the factors responsible for its pathogenicity. Among them, homotrimeric autotransporter protein YadA (Yersinia adhesin A) is an important virulence factor also found in the outer membrane of pathogenic Yersinia species. In this paper, the structure and stability of certain Cu(II) complexes with YadA fragments were investigated using both, experimental and theoretical methods. Potentiometry, UV-Vis, CD, EPR, and calculations at the density functional theory (DFT) level were applied to determine the metal ion coordination sphere. Moreover, the complexes ability to DNA cleavage and reactive oxygen species (ROS) production was studied. We have shown that copper(II) complexes can cleave DNA by 1O2, O2•- and •OH, which are formed in the studied systems. However, the results of electrophoretic experiments revealed that complexes cleave DNA less effectively than free copper(II) ions. Therefore, the presence of studied peptides may prevent DNA from a Cu(II)-induced damage to some extent.

In silico prediction of putative antimicrobial targets in Xanthomonas citri pv. punicae using genome subtraction approach

Xanthomonas citri pv. punicae (Xcp) is the causative agent of bacterial blight disease in pomegranate and severely affects its production. The current control strategies for this disease provide inadequate protection. Identifying novel bactericide target proteins in pathogenic bacteria and formulating selective chemicals against those proteins is an effective approach to containing the disease. In this study, we used the genome subtraction approach and identified 595 Xcp proteins that are non-homologous to the pomegranate proteome, of which 69 are found to be essential proteins. These 69 proteins are considered possible drug target proteins in Xcp. Further, these proteins were subjected to subcellular localization, KEGG pathway, and virulent prediction analysis. Our systematic bioinformatics analysis deciphered 33 virulent proteins, of which two are iron complex outer membrane receptors, and the third is a T4SS PilQ protein localized in the outer membrane. These outer membrane-localized proteins are potential candidate targets for antibacterial agents, and the two iron complex outer membrane receptor proteins show homology with the Drug bank listed drug target sequences. From this study, we inferred that PilQ could be considered a novel antimicrobial target of Xcp, and therefore we deciphered the PilQ protein-protein interacting partners and phylogenetic relatedness. We have also predicted the physiochemical properties, secondary, and tertiary structure of PilQ protein which will be helpful in the design of antimicrobials. The identification of Xcp specific targets is the first step towards the development of a chemical control agent that is more selective with minimum environmental impact.

Transposon insertional mutagenesis of diverse yeast strains suggests coordinated gene essentiality polymorphisms

Due to epistasis, the same mutation can have drastically different phenotypic consequences in different individuals. This phenomenon is pertinent to precision medicine as well as antimicrobial drug development, but its general characteristics are largely unknown. We approach this question by genome-wide assessment of gene essentiality polymorphism in 16 Saccharomyces cerevisiae strains using transposon insertional mutagenesis. Essentiality polymorphism is observed for 9.8% of genes, most of which have had repeated essentiality switches in evolution. Genes exhibiting essentiality polymorphism lean toward having intermediate numbers of genetic and protein interactions. Gene essentiality changes tend to occur concordantly among components of the same protein complex or metabolic pathway and among a group of over 100 mitochondrial proteins, revealing molecular machines or functional modules as units of gene essentiality variation. Most essential genes tolerate transposon insertions consistently among strains in one or more coding segments, delineating nonessential regions within essential genes.

Interrogation of Essentiality in the Reconstructed Haemophilus influenzae Metabolic Network Identifies Lipid Metabolism Antimicrobial Targets: Preclinical Evaluation of a FabH β-Ketoacyl-ACP Synthase Inhibitor

Expediting drug discovery to fight antibacterial resistance requires holistic approaches at system levels. In this study, we focused on the human-adapted pathogen Haemophilus influenzae, and by constructing a high-quality genome-scale metabolic model, we rationally identified new metabolic drug targets in this organism. Contextualization of available gene essentiality data within in silico predictions identified most genes involved in lipid metabolism as promising targets. We focused on the β-ketoacyl-acyl carrier protein synthase III FabH, responsible for catalyzing the first step in the FASII fatty acid synthesis pathway and feedback inhibition. Docking studies provided a plausible three-dimensional model of FabH in complex with the synthetic inhibitor 1-(5-(2-fluoro-5-(hydroxymethyl)phenyl)pyridin-2-yl)piperidine-4-acetic acid (FabHi). Validating our in silico predictions, FabHi reduced H. influenzae viability in a dose- and strain-dependent manner, and this inhibitory effect was independent of fabH gene expression levels. fabH allelic variation was observed among H. influenzae clinical isolates. Many of these polymorphisms, relevant for stabilization of the dimeric active form of FabH and/or activity, may modulate the inhibitory effect as part of a complex multifactorial process with the overall metabolic context emerging as a key factor tuning FabHi activity. Synergies with antibiotics were not observed and bacteria were not prone to develop resistance. Inhibitor administration during H. influenzae infection on a zebrafish septicemia infection model cleared bacteria without signs of host toxicity. Overall, we highlight the potential of H. influenzae metabolism as a source of drug targets, metabolic models as target-screening tools, and FASII targeting suitability to counteract this bacterial infection. IMPORTANCE Antimicrobial resistance drives the need of synergistically combined powerful computational tools and experimental work to accelerate target identification and drug development. Here, we present a high-quality metabolic model of H. influenzae and show its usefulness both as a computational framework for large experimental data set contextualization and as a tool to discover condition-independent drug targets. We focus on β-ketoacyl-acyl carrier protein synthase III FabH chemical inhibition by using a synthetic molecule with good synthetic and antimicrobial profiles that specifically binds to the active site. The mechanistic complexity of FabH inhibition may go beyond allelic variation, and the strain-dependent effect of the inhibitor tested supports the impact of metabolic context as a key factor driving bacterial cell behavior. Therefore, this study highlights the systematic metabolic evaluation of individual strains through computational frameworks to identify secondary metabolic hubs modulating drug response, which will facilitate establishing synergistic and/or more precise and robust antibacterial treatments.

Structural systems pharmacology: A framework for integrating metabolic network and structure-based virtual screening for drug discovery against bacteria

Advances in genome-scale metabolic models (GEMs) and computational drug discovery have caused the identification of drug targets at the system-level and inhibitors to combat bacterial infection and drug resistance. Here we report a structural systems pharmacology framework that integrates the GEM and structure-based virtual screening (SBVS) method to identify drugs effective for Escherichia coli infection. The most complete genome-scale metabolic reconstruction integrated with protein structures (GEM-PRO) of E. coli, iML1515_GP, and FDA-approved drugs have been used. FBA was performed to predict drug targets in silico. The 195 essential genes were predicted in the rich medium. The subsystems in which a significant number of these genes are involved are cofactor, lipopolysaccharide (LPS) biosynthesis that are necessary for cell growth. Therefore, some proteins encoded by these genes are responsible for the biosynthesis and transport of LPS which is the first line of defense against threats. So, these proteins can be potential drug targets. The enzymes with experimental structure and cognate ligands were selected as final drug targets for performing the SBVS method. Finally, we have suggested those drugs that have good interaction with the selected proteins as drug repositioning cases. Also, the suggested molecules could be promising lead compounds. This framework may be helpful to fill the gap between genomics and drug discovery. Results show this framework suggests novel antibacterials that can be subjected to experimental testing soon and it can be suitable for other pathogens.

Innate Host Defense against Klebsiella pneumoniae and the Outlook for Development of Immunotherapies

Klebsiella pneumoniae (K. pneumoniae) is a Gram-negative commensal bacterium and opportunistic pathogen. In healthy individuals, the innate immune system is adept at protecting against K. pneumoniae infection. Notably, the serum complement system and phagocytic leukocytes (e.g., neutrophils) are highly effective at eliminating K. pneumoniae and thereby preventing severe disease. On the other hand, the microbe is a major cause of healthcare-associated infections, especially in individuals with underlying susceptibility factors, such as pre-existing severe illness or immune suppression. The burden of K. pneumoniae infections in hospitals is compounded by antibiotic resistance. Treatment of these infections is often difficult largely because the microbes are usually resistant to multiple antibiotics (multidrug resistant [MDR]). There are a limited number of treatment options for these infections and new therapies, and preventative measures are needed. Here, we review host defense against K. pneumoniae and discuss recent therapeutic measures and vaccine approaches directed to treat and prevent severe disease caused by MDR K. pneumoniae.

Predicting essential genes of 37 prokaryotes by combining information-theoretic features

Essential genes are required for the reproduction and survival of an organism. Rapid identification of essential genes has practical application value in biomedicine. Information theory is a discipline that studies information transmission. Based on the similarity between heredity and information transmission, measures derived from information theory can be applied to genetic sequence analysis on different scales. In this study, we employed 114 features extracted by information theory methods to construct an essential gene prediction model. We applied a backpropagation neural network to construct a classifier and employed it to predict essential genes of 37 prokaryotes. The performance of the classifier was evaluated by applying intra-organism prediction and leave-one-species-out prediction. Among 37 prokaryotes, intra-organism prediction and leave-one-species-out prediction yielded average AUC scores of 0.791 and 0.717, respectively. Considering the potential redundancy in the feature set, we performed feature selection and constructed a key feature subset. In the above two prediction methods, the average AUC scores of 37 organisms obtained by using key features were 0.786 and 0.714, respectively. The results show the potential and universality of information-theoretic features in the study of prokaryotic essential gene prediction.

In Silico Prediction and Prioritization of Novel Selective Antimicrobial Drug Targets in Escherichia coli

Novel antimicrobials interfering with pathogen-specific targets can minimize the risk of perturbations of the gut microbiota (dysbiosis) during therapy. We employed an in silico approach to identify essential proteins in Escherichia coli that are either absent or have low sequence identity in seven beneficial taxa of the gut microbiota: Faecalibacterium, Prevotella, Ruminococcus, Bacteroides, Lactobacillus, Lachnospiraceae and Bifidobacterium. We identified 36 essential proteins that are present in hyper-virulent E. coli ST131 and have low similarity (bitscore < 50 or identity < 30% and alignment length < 25%) to proteins in mammalian hosts and beneficial taxa. Of these, 35 are also present in Klebsiella pneumoniae. None of the proteins are targets of clinically used antibiotics, and 3D structure is available for 23 of them. Four proteins (LptD, LptE, LolB and BamD) are easily accessible as drug targets due to their location in the outer membrane, especially LptD, which contains extracellular domains. Our results indicate that it may be possible to selectively interfere with essential biological processes in Enterobacteriaceae that are absent or mediated by unrelated proteins in beneficial taxa residing in the gut. The identified targets can be used to discover antimicrobial drugs effective against these opportunistic pathogens with a decreased risk of causing dysbiosis.

Learning from -omics strategies applied to uncover Haemophilus influenzae host-pathogen interactions: Current status and perspectives

Haemophilus influenzae has contributed to key bacterial genome sequencing hallmarks, as being not only the first bacterium to be genome-sequenced, but also starring the first genome-wide analysis of chromosomes directly transformed with DNA from a divergent genotype, and pioneering Tn-seq methodologies. Over the years, the phenomenal and constantly evolving development of -omic technologies applied to a whole range of biological questions of clinical relevance in the H. influenzae-host interplay, has greatly moved forward our understanding of this human-adapted pathogen, responsible for multiple acute and chronic infections of the respiratory tract. In this way, essential genes, virulence factors, pathoadaptive traits, and multi-layer gene expression regulatory networks with both genomic and epigenomic complexity levels are being elucidated. Likewise, the unstoppable increasing whole genome sequencing information underpinning H. influenzae great genomic plasticity, mainly when referring to non-capsulated strains, poses major challenges to understand the genomic basis of clinically relevant phenotypes and even more, to clearly highlight potential targets of clinical interest for diagnostic, therapeutic or vaccine development. We review here how genomic, transcriptomic, proteomic and metabolomic-based approaches are great contributors to our current understanding of the interactions between H. influenzae and the human airways, and point possible strategies to maximize their usefulness in the context of biomedical research and clinical needs on this human-adapted bacterial pathogen.

Machine learning approach to gene essentiality prediction: a review

 

Essential genes are critical for the growth and survival of any organism. The machine learning approach complements the experimental methods to minimize the resources required for essentiality assays. Previous studies revealed the need to discover relevant features that significantly classify essential genes, improve on the generalizability of prediction models across organisms, and construct a robust gold standard as the class label for the train data to enhance prediction. Findings also show that a significant limitation of the machine learning approach is predicting conditionally essential genes. The essentiality status of a gene can change due to a specific condition of the organism. This review examines various methods applied to essential gene prediction task, their strengths, limitations and the factors responsible for effective computational prediction of essential genes. We discussed categories of features and how they contribute to the classification performance of essentiality prediction models. Five categories of features, namely, gene sequence, protein sequence, network topology, homology and gene ontology-based features, were generated for Caenorhabditis elegans to perform a comparative analysis of their essentiality prediction capacity. Gene ontology-based feature category outperformed other categories of features majorly due to its high correlation with the genes' biological functions. However, the topology feature category provided the highest discriminatory power making it more suitable for essentiality prediction. The major limiting factor of machine learning to predict essential genes conditionality is the unavailability of labeled data for interest conditions that can train a classifier. Therefore, cooperative machine learning could further exploit models that can perform well in conditional essentiality predictions.

SHORT ABSTRACT

Identification of essential genes is imperative because it provides an understanding of the core structure and function, accelerating drug targets' discovery, among other functions. Recent studies have applied machine learning to complement the experimental identification of essential genes. However, several factors are limiting the performance of machine learning approaches. This review aims to present the standard procedure and resources available for predicting essential genes in organisms, and also highlight the factors responsible for the current limitation in using machine learning for conditional gene essentiality prediction. The choice of features and ML technique was identified as an important factor to predict essential genes effectively.

Novel antimicrobial development using genome-scale metabolic model of Gram-negative pathogens: a review

Antimicrobial resistance (AMR) threatens the effective prevention and treatment of a wide range of infections. Governments around the world are beginning to devote effort for innovative treatment development to treat these resistant bacteria. Systems biology methods have been applied extensively to provide valuable insights into metabolic processes at system level. Genome-scale metabolic models serve as platforms for constraint-based computational techniques which aid in novel drug discovery. Tools for automated reconstruction of metabolic models have been developed to support system level metabolic analysis. We discuss features of such software platforms for potential users to best fit their purpose of research. In this work, we focus to review the development of genome-scale metabolic models of Gram-negative pathogens and also metabolic network approach for identification of antimicrobial drugs targets.

The Laminin Interactome: A Multifactorial Laminin-Binding Strategy by Nontypeable Haemophilus influenzae for Effective Adherence and Colonization

Laminin is a well-defined component of the airway basement membrane (BM). Efficient binding of laminin via multiple interactions is important for nontypeable Haemophilus influenzae (NTHi) colonization in the airway mucosa. In this study, we identified elongation factor thermo-unstable (EF-Tu), l-lactate dehydrogenase (LDH), protein D (PD), and peptidoglycan-associated lipoprotein P6 as novel laminin-binding proteins (Lbps) of NTHi. In parallel with other well-studied Lbps (protein 4 [P4], protein E [PE], protein F [PF], and Haemophilus adhesion and penetration protein [Hap]), EF-Tu, LDH, PD, and P6 exhibited interactions with laminin, and mediated NTHi laminin-dependent adherence to pulmonary epithelial cell lines. More importantly, the NTHi laminin interactome consisting of the well-studied and novel Lbps recognized laminin LG domains from the subunit α chains of laminin-111 and -332, the latter isoform of which is the main laminin in the airway BM. The NTHi interactome mainly targeted multiple heparin-binding domains of laminin. In conclusion, the NTHi interactome exhibited a high plasticity of interactions with different laminin isoforms via multiple heparin-binding sites.

Pharmacodynamics of Ceftiofur Selected by Genomic and Proteomic Approaches of Streptococcus parauberis Isolated from the Flounder, Paralichthys olivaceus

We employed an integrative strategy to present subtractive and comparative metabolic and genomic-based findings of therapeutic targets against Streptococcus parauberis. For the first time, we not only identified potential targets based on genomic and proteomic database analyses but also recommend a new antimicrobial drug for the treatment of olive flounder (Paralichthys olivaceus) infected with S. parauberis. To do that, 102 total annotated metabolic pathways of this bacterial strain were extracted from computational comparative metabolic and genomic databases. Six druggable proteins were identified from these metabolic pathways from the DrugBank database with their respective genes as mtnN, penA, pbp2, murB, murA, coaA, and fni out of 112 essential nonhomologous proteins. Among these hits, 26 transmembrane proteins and 77 cytoplasmic proteins were extracted as potential vaccines and drug targets, respectively. From the FDA DrugBank, ceftiofur was selected to prevent antibiotic resistance as it inhibited our selected identified target. Florfenicol is used for treatment of S. parauberis infection in flounder and was chosen as a comparator drug. All tested strains of fish isolates with S. parauberis were susceptible to ceftiofur and florfenicol with minimum inhibitory concentrations (MIC) of 0.0039-1 μg/mL and 0.5-8 μg/mL, IC50 of 0.001-0.5 μg/mL and 0.7-2.7 μg/mL, and minimum biofilm eradication concentrations (MBEC) of 2-256 μg/mL and 4-64 μg/mL, respectively. Similar susceptibility profiles for ceftiofur and florfenicol were found, with ceftiofur observed as an effective and potent antimicrobial drug against both planktonic and biofilm-forming strains of the fish pathogen Streptococcus parauberis, and it can be applied in the aquaculture industry. Thus, our predictive approach not only showed novel therapeutic agents but also indicated that marketed drugs should also be tested for efficacy against newly identified targets of this important fish pathogen.

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

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

In vitro exploration of the Xanthomonas hortorum pv. vitians genome using transposon insertion sequencing and comparative genomics to discriminate between core and contextual essential genes

The essential genome of a bacterium encompasses core genes associated with basic cellular processes and conditionally essential genes dependent upon environmental conditions or the genetic context. Comprehensive knowledge of those gene sets allows for a better understanding of fundamental bacterial biology and offers new perspectives for antimicrobial drug research against detrimental bacteria such as pathogens. We investigated the essential genome of Xanthomonas hortorum pv. vitians, a gammaproteobacterial plant pathogen of lettuce (Lactuca sativa L.) which belongs to the plant-pathogen reservoir genus Xanthomonas and is affiliated to the family Xanthomonadaceae. No practical means of disease control or prevention against this pathogen is currently available, and its molecular biology is virtually unknown. To reach a comprehensive overview of the essential genome of X. hortorum pv. vitians LM16734, we developed a mixed approach combining high-quality full genome sequencing, saturated transposon insertion sequencing (Tn-Seq) in optimal growth conditions, and coupled computational analyses such as comparative genomics, synteny assessment and phylogenomics. Among the 370 essential loci identified by Tn-Seq, a majority was bound to critical cell processes conserved across bacteria. The remaining genes were either related to specific ecological features of Xanthomonas or Xanthomonadaceae species, or acquired through horizontal gene transfer of mobile genetic elements and associated with ancestral parasitic gene behaviour and bacterial defence systems. Our study sheds new light on our usual concepts about gene essentiality and is pioneering in the molecular and genomic study of X. hortorum pv. vitians.

PynA is a pyrimidine 5'-nucleotidase that functions as an antimutator protein in Streptococcus pneumoniae

Streptococcus pneumoniae is a Gram-positive bacterium that is a major agent of community-acquired bacterial pneumonia, meningitis and sepsis. Although the mismatch repair function of S. pneumoniae has been assigned to the hexA-hexB gene products, an enzyme capable of the direct elimination of noncanonical nucleotides from the cytoplasm has not been described for this bacterium. Our results show that Spr1057, a protein with previously unknown function, is involved in the inactivation of mutagenic pyrimidine nucleotides and was accordingly designated PynA (pyrimidine nucleotidase A). Biochemical assays confirmed the phosphatase activity of the recombinant enzyme and revealed its metal ion dependence for optimal enzyme activity. We demonstrated that PynA forms a homodimer with higher in vitro activity towards noncanonical 5-fluoro-2'-deoxyuridine monophosphate than towards canonical thymidine monophosphate. Furthermore, we showed via in vivo assays that PynA protects cells against noncanonical pyrimidine derivatives such as 5-fluoro-2'-deoxyuridine and prevents the incorporation of the potentially mutagenic 5-bromo-2'-deoxyuridine (5-BrdU) into DNA. Fluctuation analysis performed under S. pneumoniae exposure to 5-BrdU revealed that the pynA null strain accumulates random mutations with high frequency, resulting in a 30-fold increase in the mutation rate. The data support a model in which PynA, a protein conserved in other Gram-positive bacteria, functions as a house-cleaning enzyme by selectively eliminating noncanonical nucleotides and maintaining the purity of dNTP pools, similar to the YjjG protein described for Escherichia coli.

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.

Comparative analysis of the Burkholderia cenocepacia K56-2 essential genome reveals cell envelope functions that are uniquely required for survival in species of the genus Burkholderia

Burkholderia cenocepacia K56-2 belongs to the Burkholderia cepacia complex, a group of Gram-negative opportunistic pathogens that have large and dynamic genomes. In this work, we identified the essential genome of B. cenocepacia K56-2 using high-density transposon mutagenesis and insertion site sequencing (Tn-seq circle). We constructed a library of one million transposon mutants and identified the transposon insertions at an average of one insertion per 27 bp. The probability of gene essentiality was determined by comparing of the insertion density per gene with the variance of neutral datasets generated by Monte Carlo simulations. Five hundred and eight genes were not significantly disrupted, suggesting that these genes are essential for survival in rich, undefined medium. Comparison of the B. cenocepacia K56-2 essential genome with that of the closely related B. cenocepacia J2315 revealed partial overlapping, suggesting that some essential genes are strain-specific. Furthermore, 158 essential genes were conserved in B. cenocepacia and two species belonging to the Burkholderia pseudomallei complex, B. pseudomallei K96243 and Burkholderia thailandensis E264. Porins, including OpcC, a lysophospholipid transporter, LplT, and a protein involved in the modification of lipid A with aminoarabinose were found to be essential in Burkholderia genomes but not in other bacterial essential genomes identified so far. Our results highlight the existence of cell envelope processes that are uniquely essential in species of the genus Burkholderia for which the essential genomes have been identified by Tn-seq.

In silico analysis of putative drug and vaccine targets of the metabolic pathways of Actinobacillus pleuropneumoniae using a subtractive/comparative genomics approach

Actinobacillus pleuropneumoniae is a Gram-negative bacterium that resides in the respiratory tract of pigs and causes porcine respiratory disease complex, which leads to significant losses in the pig industry worldwide. The incidence of drug resistance in this bacterium is increasing; thus, identifying new protein/gene targets for drug and vaccine development is critical. In this study, we used an in silico approach, utilizing several databases including the Kyoto Encyclopedia of Genes and Genomes (KEGG), the Database of Essential Genes (DEG), DrugBank, and Swiss-Prot to identify non-homologous essential genes and prioritize these proteins for their druggability. The results showed 20 metabolic pathways that were unique and contained 273 non-homologous proteins, of which 122 were essential. Of the 122 essential proteins, there were 95 cytoplasmic proteins and 11 transmembrane proteins, which are potentially suitable for drug and vaccine targets, respectively. Among these, 25 had at least one hit in DrugBank, and three had similarity to metabolic proteins from Mycoplasma hyopneumoniae, another pathogen causing porcine respiratory disease complex; thus, they could serve as common therapeutic targets. In conclusion, we identified glyoxylate and dicarboxylate pathways as potential targets for antimicrobial therapy and tetra-acyldisaccharide 4'-kinase and 3-deoxy-D-manno-octulosonic-acid transferase as vaccine candidates against A. pleuropneumoniae.

High-throughput analysis of Yersinia pseudotuberculosis gene essentiality in optimised in vitro conditions, and implications for the speciation of Yersinia pestis

Background

Yersinia pseudotuberculosis is a zoonotic pathogen, causing mild gastrointestinal infection in humans. From this comparatively benign pathogenic species emerged the highly virulent plague bacillus, Yersinia pestis, which has experienced significant genetic divergence in a relatively short time span. Much of our knowledge of Yersinia spp. evolution stems from genomic comparison and gene expression studies. Here we apply transposon-directed insertion site sequencing (TraDIS) to describe the essential gene set of Y. pseudotuberculosis IP32953 in optimised in vitro growth conditions, and contrast these with the published essential genes of Y. pestis.

Results

The essential genes of an organism are the core genetic elements required for basic survival processes in a given growth condition, and are therefore attractive targets for antimicrobials. One such gene we identified is yptb3665, which encodes a peptide deformylase, and here we report for the first time, the sensitivity of Y. pseudotuberculosis to actinonin, a deformylase inhibitor. Comparison of the essential genes of Y. pseudotuberculosis with those of Y. pestis revealed the genes whose importance are shared by both species, as well as genes that were differentially required for growth. In particular, we find that the two species uniquely rely upon different iron acquisition and respiratory metabolic pathways under similar in vitro conditions.

Conclusions

The discovery of uniquely essential genes between the closely related Yersinia spp. represent some of the fundamental, species-defining points of divergence that arose during the evolution of Y. pestis from its ancestor. Furthermore, the shared essential genes represent ideal candidates for the development of novel antimicrobials against both species.

Electronic supplementary material

The online version of this article (10.1186/s12866-018-1189-5) contains supplementary material, which is available to authorized users.

HU of Streptococcus pneumoniae Is Essential for the Preservation of DNA Supercoiling

The histone-like protein HU is a conserved nucleoid-associated protein that is involved in the maintenance of the bacterial chromosome architecture. It is the only known nucleoid-associated protein in Streptococcus pneumoniae, but it has not been studied. The pneumococcal gene encoding this protein, hlp, is shown herein to be essential for cell viability. Its disruption was only possible either when it was duplicated in the chromosome and its expression induced from the P _Zn promoter, or when hlp was cloned into a plasmid under the control of the inducible P _mal promoter. In vitro assays indicated that pneumococcal HU shows a preference for binding to supercoiled DNA rather than to linear or nicked DNA. In vivo experiments in which the amount of HU was manipulated showed a relationship between the amount of HU and the level of DNA supercoiling. A twofold reduction in the amount of HU triggered a 21% increase in DNA relaxation in untreated cells. However, in cells treated with novobiocin, a drug that relaxes DNA by inhibiting DNA gyrase, a 35% increase in DNA relaxation was observed, instead of the expected 20% in cells with a constitutive HU amount. Conversely, a fourfold HU increase caused only 14% of DNA relaxation in the presence of novobiocin. Taken together, these results support an essential role for HU in the maintenance of DNA supercoiling in S. pneumoniae.

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

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

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

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

Advances and perspectives in computational prediction of microbial gene essentiality

The minimal subset of genes required for cellular growth, survival and viability of an organism are classified as essential genes. Knowledge of essential genes gives insight into the core structure and functioning of a cell. This might lead to more efficient antimicrobial drug discovery, to elucidation of the correlations between genotype and phenotype, and a better understanding of the minimal requirements for a (synthetic) cell. Traditionally, constructing a catalog of essential genes for a given microbe involved costly and time-consuming laboratory experiments. While experimental methods have produced abundant gene essentiality data for model organisms like Escherichia coli and Bacillus subtilis, the knowledge generated cannot automatically be extrapolated to predict essential genes in all bacteria. In addition, essential genes identified in the laboratory are by definition 'conditionally essential', as they are essential under the specified experimental conditions: these might not resemble conditions in the microorganisms' natural habitat(s). Also, large-scale experimental assaying for essential genes is not always feasible because of the time investment required to setup these assays. The ability to rapidly and precisely identify essential genes in silico is therefore important and has great potential for applications in medicine, biotechnology and basic biological research. Here, we review the advances made in the use of computational methods to predict microbial gene essentiality, perspectives for the future of these techniques and the possible practical applications of essential genes.

An integrated computational-experimental approach reveals Yersinia pestis genes essential across a narrow or a broad range of environmental conditions

Background

The World Health Organization has categorized plague as a re-emerging disease and the potential for Yersinia pestis to also be used as a bioweapon makes the identification of new drug targets against this pathogen a priority. Environmental temperature is a key signal which regulates virulence of the bacterium. The bacterium normally grows outside the human host at 28 °C. Therefore, understanding the mechanisms that the bacterium used to adapt to a mammalian host at 37 °C is central to the development of vaccines or drugs for the prevention or treatment of human disease.

Results

Using a library of over 1 million Y. pestis CO92 random mutants and transposon-directed insertion site sequencing, we identified 530 essential genes when the bacteria were cultured at 28 °C. When the library of mutants was subsequently cultured at 37 °C we identified 19 genes that were essential at 37 °C but not at 28 °C, including genes which encode proteins that play a role in enabling functioning of the type III secretion and in DNA replication and maintenance. Using genome-scale metabolic network reconstruction we showed that growth conditions profoundly influence the physiology of the bacterium, and by combining computational and experimental approaches we were able to identify 54 genes that are essential under a broad range of conditions.

Conclusions

Using an integrated computational-experimental approach we identify genes which are required for growth at 37 °C and under a broad range of environments may be the best targets for the development of new interventions to prevent or treat plague in humans.

Electronic supplementary material

The online version of this article (doi:10.1186/s12866-017-1073-8) contains supplementary material, which is available to authorized users.

Defining Genetic Fitness Determinants and Creating Genomic Resources for an Oral Pathogen

Periodontitis is a microbial infection that destroys the structures that support the teeth. Although it is typically a chronic condition, rapidly progressing, aggressive forms are associated with the oral pathogen Aggregatibacter actinomycetemcomitans One of this bacterium's key virulence traits is its ability to attach to surfaces and form robust biofilms that resist killing by the host and antibiotics. Though much has been learned about A. actinomycetemcomitans since its initial discovery, we lack insight into a fundamental aspect of its basic biology, as we do not know the full set of genes that it requires for viability (the essential genome). Furthermore, research on A. actinomycetemcomitans is hampered by the field's lack of a mutant collection. To address these gaps, we used rapid transposon mutant sequencing (Tn-seq) to define the essential genomes of two strains of A. actinomycetemcomitans, revealing a core set of 319 genes. We then generated an arrayed mutant library comprising >1,500 unique insertions and used a sequencing-based approach to define each mutant's position (well and plate) in the library. To demonstrate its utility, we screened the library for mutants with weakened resistance to subinhibitory erythromycin, revealing the multidrug efflux pump AcrAB as a critical resistance factor. During the screen, we discovered that erythromycin induces A. actinomycetemcomitans to form biofilms. We therefore devised a novel Tn-seq-based screen to identify specific factors that mediate this phenotype and in follow-up experiments confirmed 4 mutants. Together, these studies present new insights and resources for investigating the basic biology and disease mechanisms of a human pathogen.IMPORTANCE Millions suffer from gum disease, which often is caused by Aggregatibacter actinomycetemcomitans, a bacterium that forms antibiotic-resistant biofilms. To fully understand any organism, we should be able to answer: what genes does it require for life? Here, we address this question for A. actinomycetemcomitans by determining the genes in its genome that cannot be mutated. As for the genes that can be mutated, we archived these mutants into a library, which we used to find genes that contribute to antibiotic resistance, leading us to discover that antibiotics cause A. actinomycetemcomitans to form biofilms. We then devised an approach to find genes that mediate this process and confirmed 4 genes. These results illuminate new fundamental traits of a human pathogen.

High-throughput CRISPRi phenotyping identifies new essential genes in Streptococcus pneumoniae

Genome‐wide screens have discovered a large set of essential genes in the opportunistic human pathogen Streptococcus pneumoniae. However, the functions of many essential genes are still unknown, hampering vaccine development and drug discovery. Based on results from transposon sequencing (Tn‐seq), we refined the list of essential genes in S. pneumoniae serotype 2 strain D39. Next, we created a knockdown library targeting 348 potentially essential genes by CRISPR interference (CRISPRi) and show a growth phenotype for 254 of them (73%). Using high‐content microscopy screening, we searched for essential genes of unknown function with clear phenotypes in cell morphology upon CRISPRi‐based depletion. We show that SPD_1416 and SPD_1417 (renamed to MurT and GatD, respectively) are essential for peptidoglycan synthesis, and that SPD_1198 and SPD_1197 (renamed to TarP and TarQ, respectively) are responsible for the polymerization of teichoic acid (TA) precursors. This knowledge enabled us to reconstruct the unique pneumococcal TA biosynthetic pathway. CRISPRi was also employed to unravel the role of the essential Clp‐proteolytic system in regulation of competence development, and we show that ClpX is the essential ATPase responsible for ClpP‐dependent repression of competence. The CRISPRi library provides a valuable tool for characterization of pneumococcal genes and pathways and revealed several promising antibiotic targets.

Genome-wide fitness analyses of the foodborne pathogen Campylobacter jejuni in in vitro and in vivo models

Campylobacter is the most common cause of foodborne bacterial illness worldwide. Faecal contamination of meat, especially chicken, during processing represents a key route of transmission to humans. There is a lack of insight into the mechanisms driving C. jejuni growth and survival within hosts and the environment. Here, we report a detailed analysis of C. jejuni fitness across models reflecting stages in its life cycle. Transposon (Tn) gene-inactivation libraries were generated in three C. jejuni strains and the impact on fitness during chicken colonisation, survival in houseflies and under nutrient-rich and -poor conditions at 4 °C and infection of human gut epithelial cells was assessed by Tn-insertion site sequencing (Tn-seq). A total of 331 homologous gene clusters were essential for fitness during in vitro growth in three C. jejuni strains, revealing that a large part of its genome is dedicated to growth. We report novel C. jejuni factors essential throughout its life cycle. Importantly, we identified genes that fulfil important roles across multiple conditions. Our comprehensive screens showed which flagella elements are essential for growth and which are vital to the interaction with host organisms. Future efforts should focus on how to exploit this knowledge to effectively control infections caused by C. jejuni.

Panel 4: Report of the Microbiology Panel

Objective To perform a comprehensive review of the literature from July 2011 until June 2015 on the virology and bacteriology of otitis media in children. Data Sources PubMed database of the National Library of Medicine. Review Methods Two subpanels comprising experts in the virology and bacteriology of otitis media were created. Each panel reviewed the relevant literature in the fields of virology and bacteriology and generated draft reviews. These initial reviews were distributed to all panel members prior to meeting together at the Post-symposium Research Conference of the 18th International Symposium on Recent Advances in Otitis Media, National Harbor, Maryland, in June 2015. A final draft was created, circulated, and approved by all panel members. Conclusions Excellent progress has been made in the past 4 years in advancing our understanding of the microbiology of otitis media. Numerous advances were made in basic laboratory studies, in animal models of otitis media, in better understanding the epidemiology of disease, and in clinical practice. Implications for Practice (1) Many viruses cause acute otitis media without bacterial coinfection, and such cases do not require antibiotic treatment. (2) When respiratory syncytial virus, metapneumovirus, and influenza virus peak in the community, practitioners can expect to see an increase in clinical otitis media cases. (3) Biomarkers that predict which children with upper respiratory tract infections will develop otitis media may be available in the future. (4) Compounds that target newly identified bacterial virulence determinants may be available as future treatment options for children with otitis media.

The secondary resistome of multidrug-resistant Klebsiella pneumoniae

Klebsiella pneumoniae causes severe lung and bloodstream infections that are difficult to treat due to multidrug resistance. We hypothesized that antimicrobial resistance can be reversed by targeting chromosomal non-essential genes that are not responsible for acquired resistance but essential for resistant bacteria under therapeutic concentrations of antimicrobials. Conditional essentiality of individual genes to antimicrobial resistance was evaluated in an epidemic multidrug-resistant clone of K. pneumoniae (ST258). We constructed a high-density transposon mutant library of >430,000 unique Tn5 insertions and measured mutant depletion upon exposure to three clinically relevant antimicrobials (colistin, imipenem or ciprofloxacin) by Transposon Directed Insertion-site Sequencing (TraDIS). Using this high-throughput approach, we defined three sets of chromosomal non-essential genes essential for growth during exposure to colistin (n = 35), imipenem (n = 1) or ciprofloxacin (n = 1) in addition to known resistance determinants, collectively termed the "secondary resistome". As proof of principle, we demonstrated that inactivation of a non-essential gene not previously found linked to colistin resistance (dedA) restored colistin susceptibility by reducing the minimum inhibitory concentration from 8 to 0.5 μg/ml, 4-fold below the susceptibility breakpoint (S ≤ 2 μg/ml). This finding suggests that the secondary resistome is a potential target for developing antimicrobial "helper" drugs that restore the efficacy of existing antimicrobials.

Bypass of Candida albicans Filamentation/Biofilm Regulators through Diminished Expression of Protein Kinase Cak1

Biofilm formation on implanted medical devices is a major source of lethal invasive infection by Candida albicans. Filamentous growth of this fungus is tied to biofilm formation because many filamentation-associated genes are required for surface adherence. Cell cycle or cell growth defects can induce filamentation, but we have limited information about the coupling between filamentation and filamentation-associated gene expression after cell cycle/cell growth inhibition. Here we identified the CDK activating protein kinase Cak1 as a determinant of filamentation and filamentation-associated gene expression through a screen of mutations that diminish expression of protein kinase-related genes implicated in cell cycle/cell growth control. A cak1diminished expression (DX) strain displays filamentous growth and expresses filamentation-associated genes in the absence of typical inducing signals. In a wild-type background, expression of filamentation-associated genes depends upon the transcription factors Bcr1, Brg1, Efg1, Tec1, and Ume6. In the cak1 DX background, the dependence of filamentation-associated gene expression on each transcription factor is substantially relieved. The unexpected bypass of filamentation-associated gene expression activators has the functional consequence of enabling biofilm formation in the absence of Bcr1, Brg1, Tec1, Ume6, or in the absence of both Brg1 and Ume6. It also enables filamentous cell morphogenesis, though not biofilm formation, in the absence of Efg1. Because these transcription factors are known to have shared target genes, we suggest that cell cycle/cell growth limitation leads to activation of several transcription factors, thus relieving dependence on any one.

The ability of the pathogen Candida albicans to grow on surfaces as biofilms is a determinant of infection ability, because biofilms on implanted medical devices seed infections. Biofilm formation by this organism requires growth in the form of filamentous cells and the expression of filamentation-associated genes. Inhibition of cell proliferation can induce filamentous cell formation, as we find here for strains that express greatly reduced levels of the cell cycle regulator Cak1. Surprisingly, biofilm formation occurs independently of many central biofilm regulatory genes when Cak1 levels are reduced. This response to proliferation inhibition may reflect the activation of numerous biofilm regulators, thus relieving the dependence on any one regulator. The stimulation of biofilm formation by proliferation inhibition, a property of many bacterial pathogens as well, may contribute to the limited effectiveness of antimicrobials against biofilms.

Impact of gut microbiota on diabetes mellitus

Various functions of the gut are regulated by sophisticated interactions among its functional elements, including the gut microbiota. These microorganisms play a crucial role in gastrointestinal mucosa permeability. They control the fermentation and absorption of dietary polysaccharides to produce short-chain fatty acids, which may explain their importance in the regulation of fat accumulation and the subsequent development of obesity-related diseases, suggesting that they are a crucial mediator of obesity and its consequences. In addition, gut bacteria play a crucial role in the host immune system, modulation of inflammatory processes, extraction of energy from the host diet and alterations of human gene expression. Dietary modulation of the human colonic microbiota has been shown to confer a number of health benefits to the host. Simple therapeutic strategies targeted at attenuating the progression of chronic low-grade inflammation and insulin resistance are urgently required to prevent or slow the development of diabetes in susceptible individuals. The main objective of this review is to address the pathogenic association between gut microbiota and diabetes, and to explore any novel related therapeutic targets. New insights into the role of the gut microbiota in diabetes could lead to the development of integrated strategies using probiotics to prevent and treat these metabolic disorders.

Cell-based screens and phenomics with fission yeast

Next-generation sequencing approaches have considerably advanced our understanding of genome function and regulation. However, the knowledge of gene function and complex cellular processes remains a challenge and bottleneck in biological research. Phenomics is a rapidly emerging area, which seeks to rigorously characterize all phenotypes associated with genes or gene variants. Such high-throughput phenotyping under different conditions can be a potent approach toward gene function. The fission yeast Schizosaccharomyces pombe (S. pombe) is a proven eukaryotic model organism that is increasingly used for genomewide screens and phenomic assays. In this review, we highlight current large-scale, cell-based approaches used with S. pombe, including computational colony-growth measurements, genetic interaction screens, parallel profiling using barcodes, microscopy-based cell profiling, metabolomic methods and transposon mutagenesis. These diverse methods are starting to offer rich insights into the relationship between genotypes and phenotypes.

Human microbiomes and their roles in dysbiosis, common diseases, and novel therapeutic approaches

The human body is the residence of a large number of commensal (non-pathogenic) and pathogenic microbial species that have co-evolved with the human genome, adaptive immune system, and diet. With recent advances in DNA-based technologies, we initiated the exploration of bacterial gene functions and their role in human health. The main goal of the human microbiome project is to characterize the abundance, diversity and functionality of the genes present in all microorganisms that permanently live in different sites of the human body. The gut microbiota expresses over 3.3 million bacterial genes, while the human genome expresses only 20 thousand genes. Microbe gene-products exert pivotal functions via the regulation of food digestion and immune system development. Studies are confirming that manipulation of non-pathogenic bacterial strains in the host can stimulate the recovery of the immune response to pathogenic bacteria causing diseases. Different approaches, including the use of nutraceutics (prebiotics and probiotics) as well as phages engineered with CRISPR/Cas systems and quorum sensing systems have been developed as new therapies for controlling dysbiosis (alterations in microbial community) and common diseases (e.g., diabetes and obesity). The designing and production of pharmaceuticals based on our own body’s microbiome is an emerging field and is rapidly growing to be fully explored in the near future. This review provides an outlook on recent findings on the human microbiomes, their impact on health and diseases, and on the development of targeted therapies.

Whole-genome sequencing targets drug-resistant bacterial infections

During the past two decades, the technological progress of whole-genome sequencing (WGS) had changed the fields of Environmental Microbiology and Biotechnology, and, currently, is changing the underlying principles, approaches, and fundamentals of Public Health, Epidemiology, Health Economics, and national productivity. Today’s WGS technologies are able to compete with conventional techniques in cost, speed, accuracy, and resolution for day-to-day control of infectious diseases and outbreaks in clinical laboratories and in long-term epidemiological investigations. WGS gives rise to an exciting future direction for personalized Genomic Epidemiology. One of the most vital and growing public health problems is the emerging and re-emerging of multidrug-resistant (MDR) bacterial infections in the communities and healthcare settings, reinforced by a decline in antimicrobial drug discovery. In recent years, retrospective analysis provided by WGS has had a great impact on the identification and tracking of MDR microorganisms in hospitals and communities. The obtained genomic data are also important for developing novel easy-to-use diagnostic assays for clinics, as well as for antibiotic and therapeutic development at both the personal and population levels. At present, this technology has been successfully applied as an addendum to the real-time diagnostic methods currently used in clinical laboratories. However, the significance of WGS for public health may increase if: (a) unified and user-friendly bioinformatics toolsets for easy data interpretation and management are established, and (b) standards for data validation and verification are developed. Herein, we review the current and future impact of this technology on diagnosis, prevention, treatment, and control of MDR infectious bacteria in clinics and on the global scale.

Essential Genes in the Core Genome of the Human Pathogen Streptococcus pyogenes

Streptococcus pyogenes (Group A Streptococcus, GAS) remains a major public health burden worldwide, infecting over 750 million people leading to over 500,000 deaths annually. GAS pathogenesis is complex, involving genetically distinct GAS strains and multiple infection sites. To overcome fastidious genetic manipulations and accelerate pathogenesis investigations in GAS, we developed a mariner-based system (Krmit) for en masse monitoring of complex mutant pools by transposon sequencing (Tn-seq). Highly saturated transposant libraries (Krmit insertions in ca. every 25 nucleotides) were generated in two distinct GAS clinical isolates, a serotype M1T1 invasive strain 5448 and a nephritogenic serotype M49 strain NZ131, and analyzed using a Bayesian statistical model to predict GAS essential genes, identifying sets of 227 and 241 of those genes in 5448 and NZ131, respectively. A large proportion of GAS essential genes corresponded to key cellular processes and metabolic pathways, and 177 were found conserved within the GAS core genome established from 20 available GAS genomes. Selected essential genes were validated using conditional-expression mutants. Finally, comparison to previous essentiality analyses in S. sanguinis and S. pneumoniae revealed significant overlaps, providing valuable insights for the development of new antimicrobials to treat infections by GAS and other pathogenic streptococci.