Identifying targets for antibiotic development using omics technologies

Recent Advances and Techniques for Identifying Novel Antibacterial Targets

BACKGROUND

With the emergence of drug-resistant bacteria, the development of new antibiotics is urgently required. Target-based drug discovery is the most frequently employed approach for the drug development process. However, traditional drug target identification techniques are costly and time-consuming. As research continues, innovative approaches for antibacterial target identification have been developed which enabled us to discover drug targets more easily and quickly.

METHODS

In this review, methods for finding drug targets from omics databases have been discussed in detail including principles, procedures, advantages, and potential limitations. The role of phage-driven and bacterial cytological profiling approaches is also discussed. Moreover, current article demonstrates the advancements being made in the establishment of computational tools, machine learning algorithms, and databases for antibacterial target identification.

RESULTS

Bacterial drug targets successfully identified by employing these aforementioned techniques are described as well.

CONCLUSION

The goal of this review is to attract the interest of synthetic chemists, biologists, and computational researchers to discuss and improve these methods for easier and quicker development of new drugs.

Classification of antimicrobial mechanism of action using dynamic bacterial morphology imaging

Antimicrobial resistance is a major threat to human health. Basic knowledge of antimicrobial mechanism of action (MoA) is imperative for patient care and for identification of novel antimicrobials. However, the process of antimicrobial MoA identification is relatively laborious. Here, we developed a simple, quantitative time-lapse fluorescence imaging method, Dynamic Bacterial Morphology Imaging (DBMI), to facilitate this process. It uses a membrane dye and a nucleoid dye to track the morphological changes of single Bacillus subtilis cells in response to antimicrobials for up to 60 min. DBMI of bacterial cells facilitated assignment of the MoAs of 14 distinct, known antimicrobial compounds to the five main classes. We conclude that DBMI is a simple method, which facilitates rapid classification of the MoA of antimicrobials in functionally distinct classes.

Optimizing Antimicrobial Therapy by Integrating Multi-Omics With Pharmacokinetic/Pharmacodynamic Models and Precision Dosing

In the era of “Bad Bugs, No Drugs,” optimizing antibiotic therapy against multi-drug resistant (MDR) pathogens is crucial. Mathematical modelling has been employed to further optimize dosing regimens. These models include mechanism-based PK/PD models, systems-based models, quantitative systems pharmacology (QSP) and population PK models. Quantitative systems pharmacology has significant potential in precision antimicrobial chemotherapy in the clinic. Population PK models have been employed in model-informed precision dosing (MIPD). Several antibiotics require close monitoring and dose adjustments in order to ensure optimal outcomes in patients with infectious diseases. Success or failure of antibiotic therapy is dependent on the patient, antibiotic and bacterium. For some drugs, treatment responses vary greatly between individuals due to genotype and disease characteristics. Thus, for these drugs, tailored dosing is required for successful therapy. With antibiotics, inappropriate dosing such as insufficient dosing may put patients at risk of therapeutic failure which could lead to mortality. Conversely, doses that are too high could lead to toxicities. Hence, precision dosing which customizes doses to individual patients is crucial for antibiotics especially those with a narrow therapeutic index. In this review, we discuss the various strategies in optimizing antimicrobial therapy to address the challenges in the management of infectious diseases and delivering personalized therapy.

Guided extraction of genome-scale metabolic models for the integration and analysis of omics data

Omics data can be integrated into a reference model using various model extraction methods (MEMs) to yield context-specific genome-scale metabolic models (GEMs). How to chose the appropriate MEM, thresholding rule and threshold remains a challenge. We integrated mouse transcriptomic data from a Cyp51 knockout mice diet experiment (GSE58271) using five MEMs (GIMME, iMAT, FASTCORE, INIT an tINIT) in a combination with a recently published mouse GEM iMM1865. Except for INIT and tINIT, the size of extracted models varied with the MEM used (t-test: p-value < 0.001). The Jaccard index of iMAT models ranged from 0.27 to 1.0. Out of the three factors under study in the experiment (diet, gender and genotype), gender explained most of the variability ( > 90%) in PC1 for FASTCORE. In iMAT, each of the three factors explained less than 40% of the variability within PC1, PC2 and PC3. Among all the MEMs, FASTCORE captured the most of the true variability in the data by clustering samples by gender. Our results show that for the efficient use of MEMs in the context of omics data integration and analysis, one should apply various MEMs, thresholding rules, and thresholding values to select the MEM and its configuration that best captures the true variability in the data. This selection can be guided by the methodology as proposed and used in this paper. Moreover, we describe certain approaches that can be used to analyse the results obtained with the selected MEM and to put these results in a biological context.

Technologies for High-Throughput Identification of Antibiotic Mechanism of Action

There are two main strategies for antibiotic discovery: target-based and phenotypic screening. The latter has been much more successful in delivering first-in-class antibiotics, despite the major bottleneck of delayed Mechanism-of-Action (MOA) identification. Although finding new antimicrobial compounds is a very challenging task, identifying their MOA has proven equally challenging. MOA identification is important because it is a great facilitator of lead optimization and improves the chances of commercialization. Moreover, the ability to rapidly detect MOA could enable a shift from an activity-based discovery paradigm towards a mechanism-based approach. This would allow to probe the grey chemical matter, an underexplored source of structural novelty. In this study we review techniques with throughput suitable to screen large libraries and sufficient sensitivity to distinguish MOA. In particular, the techniques used in chemical genetics (e.g., based on overexpression and knockout/knockdown collections), promoter-reporter libraries, transcriptomics (e.g., using microarrays and RNA sequencing), proteomics (e.g., either gel-based or gel-free techniques), metabolomics (e.g., resourcing to nuclear magnetic resonance or mass spectrometry techniques), bacterial cytological profiling, and vibrational spectroscopy (e.g., Fourier-transform infrared or Raman scattering spectroscopy) were discussed. Ultimately, new and reinvigorated phenotypic assays bring renewed hope in the discovery of a new generation of antibiotics.

Vaccines for multidrug resistant Gram negative bacteria: lessons from the past for guiding future success

Antimicrobial resistance is a major threat to global public health. Vaccination is an effective approach for preventing bacterial infections, however it has not been successfully applied to infections caused by some of the most problematic multidrug resistant pathogens. In this review, the potential for vaccines to contribute to reducing the burden of disease of infections caused by multidrug resistant Gram negative bacteria is presented. Technical, logistical and societal hurdles that have limited successful vaccine development for these infections in the past are identified, and recent advances that can contribute to overcoming these challenges are assessed. A synthesis of vaccine technologies that have been employed in the development of vaccines for key multidrug resistant Gram negative bacteria is included, and emerging technologies that may contribute to future successes are discussed. Finally, a comprehensive review of vaccine development efforts over the last 40 years for three of the most worrisome multidrug resistant Gram negative pathogens, Acinetobacter baumannii, Klebsiella pneumoniae and Pseudomonas aeruginosa is presented, with a focus on recent and ongoing studies. Finally, future directions for the vaccine development field are highlighted.

Interactions with Microbial Proteins Driving the Antibacterial Activity of Flavonoids

Flavonoids are among the most abundant natural bioactive compounds produced by plants. Many different activities have been reported for these secondary metabolites against numerous cells and systems. One of the most interesting is certainly the antimicrobial, which is stimulated through various molecular mechanisms. In fact, flavonoids are effective both in directly damaging the envelope of Gram-negative and Gram-positive bacteria but also by acting toward specific molecular targets essential for the survival of these microorganisms. The purpose of this paper is to present an overview of the most interesting results obtained in the research focused on the study of the interactions between flavonoids and bacterial proteins. Despite the great structural heterogeneity of these plant metabolites, it is interesting to observe that many flavonoids affect the same cellular pathways. Furthermore, it is evident that some of these compounds interact with more than one target, producing multiple effects. Taken together, the reported data demonstrate the great potential of flavonoids in developing innovative systems, which can help address the increasingly serious problem of antibiotic resistance.

Proteomic interrogation of antibiotic resistance and persistence in Escherichia coli - progress and potential for medical research

Introduction Escherichia coli strains possess two survival strategies to endure lethal antibiotic exposure including antibiotic resistance and persistence, in which persistence can contribute to the emergence of antibiotic resistance and increasing the risk of multidrug resistance. Using high-throughput proteomics for the comprehensive understanding of mechanisms of antibiotic resistance and persistence is an effective strategy for development of target-based anti-bacterial therapies. Areas covered In this review, we summarize a comprehensive proteomic perspective of antibiotic resistance and persistence in E. coli, and overview of anti-antibiotic resistance and anti-persister molecules and strategies for the development of potential therapies. Expert opinion Proteomics allows us to globally identify the critical proteins and pathways involved in antibiotic resistance and persistence. Advancements in methodologies of proteomics and multi-omic strategies are required to overcome the limitations of proteomics and better understand mechanisms of antibiotic resistance and persistence in E. coli, and to open the possibility for identification of new targets for alternative strategies in therapeutics.

Analysis of the Extracellular Proteome of Colistin-Resistant Korean Acinetobacter baumannii Strains

We analyzed the extracellular proteome of colistin-resistant Korean Acinetobacter baumannii (KAB) strains to identify proteome profiles that can be used to characterize extensively drug-resistant KAB strains. Four colistin-resistant KAB strains with colistin resistance associated with point mutations in pmrB and pmrC genes were analyzed. Analysis of the extracellular proteome of these strains revealed the presence of 506 induced common proteins, which were hence considered as the core extracellular proteome. Class C ADC-30 and class D OXA-23 β-lactamases were abundantly induced in these strains. Porins (CarO and CarO-like porin), outer membrane proteins (OmpH and BamABDE), transport protein (AdeK), receptor (TonB), and several proteins of unknown function were among the specifically induced proteins. Based on the sequence homology analysis of proteins from the core proteome and those of other A. baumannii strains and pathogenic bacterial species as well as further in silico screening, we propose that CarO-like porin is an A. baumannii-specific protein and that two tryptic peptides that originate from CarO-like porin detected by tandem mass spectrometry are peptide makers of this protein.

Antibiotic Discovery: Where Have We Come from, Where Do We Go?

Given the increase in antibiotic-resistant bacteria, alongside the alarmingly low rate of newly approved antibiotics for clinical usage, we are on the verge of not having effective treatments for many common infectious diseases. Historically, antibiotic discovery has been crucial in outpacing resistance and success is closely related to systematic procedures—platforms—that have catalyzed the antibiotic golden age, namely the Waksman platform, followed by the platforms of semi-synthesis and fully synthetic antibiotics. Said platforms resulted in the major antibiotic classes: aminoglycosides, amphenicols, ansamycins, beta-lactams, lipopeptides, diaminopyrimidines, fosfomycins, imidazoles, macrolides, oxazolidinones, streptogramins, polymyxins, sulphonamides, glycopeptides, quinolones and tetracyclines. During the genomics era came the target-based platform, mostly considered a failure due to limitations in translating drugs to the clinic. Therefore, cell-based platforms were re-instituted, and are still of the utmost importance in the fight against infectious diseases. Although the antibiotic pipeline is still lackluster, especially of new classes and novel mechanisms of action, in the post-genomic era, there is an increasingly large set of information available on microbial metabolism. The translation of such knowledge into novel platforms will hopefully result in the discovery of new and better therapeutics, which can sway the war on infectious diseases back in our favor.

Tachyplesin Causes Membrane Instability That Kills Multidrug-Resistant Bacteria by Inhibiting the 3-Ketoacyl Carrier Protein Reductase FabG

Tachyplesin is a type of cationic β-hairpin antimicrobial peptide discovered in horseshoe crab approximately 30 years ago that is well known for both its potential antimicrobial activities against multidrug-resistant bacteria and its cytotoxicity to mammalian cells. Though its physical interactions with artificial membranes have been well studied, details of its physiological mechanism of action the physiological consequences of its action remain limited. By using the DNA-binding fluorescent dye propidium iodide to monitor membrane integrity, confocal microscopy to assess the intracellular location of FITC-tagged tachyplesin, and RNA sequencing of the differentially expressed genes in four Gram-negative bacteria (Escherichia coli, Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa) treated with lethal or sublethal concentrations of tachyplesin, we found that compared with levofloxacin-treated bacteria, tachyplesin-treated bacteria showed significant effects on the pathways underlying unsaturated fatty acid biosynthesis. Notably, RNA levels of the conserved and essential 3-ketoacyl carrier protein reductase in this pathway (gene FabG) were elevated in all of the four bacteria after tachyplesin treatment. In vitro tests including surface plasmon resonance and enzyme activity assays showed that tachyplesin could bind and inhibit 3-ketoacyl carrier protein reductase, which was consistent with molecular docking prediction results. As unsaturated fatty acids are important for membrane fluidity, our results provided one possible mechanism to explain how tachyplesin kills bacteria and causes cytotoxicity by targeting membranes, which may be helpful for designing more specific and safer antibiotics based on the function of tachyplesin.

Systemic Responses of Multidrug-Resistant Pseudomonas aeruginosa and Acinetobacter baumannii Following Exposure to the Antimicrobial Peptide Cathelicidin-BF Imply Multiple Intracellular Targets

Cathelicidin-BF, derived from the banded krait (Bungarus fasciatus), is a typically cationic, amphiphilic and α-helical antimicrobial peptide (AMP) with 30 amino acids that exerts powerful effects on multidrug-resistant (MDR) clinical isolates, including Pseudomonas aeruginosa, Acinetobacter baumannii, and Klebsiella pneumoniae, but whether it targets plasma membranes or intracellular targets to kill bacteria is still controversial. In the present study, we demonstrated that the disruption of bacterial membranes with high concentrations of cathelicidin-BF was the cause of bacterial death, as with conventional antibiotics at high concentrations. At lower concentrations, cathelicidin-BF did not cause bacterial plasma membrane disruption, but it was able to cross the membrane and aggregate at the nucleoid regions. Functional proteins of the transcription processes of P. aeruginosa and A. baumannii were affected by sublethal doses of cathelicidin-BF, as demonstrated by comparative proteomics using isobaric tags for relative and absolute quantification and subsequent gene ontology (GO) analysis. Analysis using the Kyoto Encyclopedia of Genes and Genomes showed that cathelicidin-BF mainly interferes with metabolic pathways related to amino acid synthesis, metabolism of cofactors and vitamins, metabolism of purine and energy supply, and other processes. Although specific targets of cathelicidin-BF must still be validated, our study offers strong evidence that cathelicidin-BF may act upon intracellular targets to kill superbugs, which may be helpful for further efforts to discover novel antibiotics to fight against them.

Integrated proteomic and metabolomic analysis reveals that rhodomyrtone reduces the capsule in Streptococcus pneumoniae

The emergence of antibiotic-resistant pathogenic bacteria is a healthcare problem worldwide. We evaluated the antimicrobial activity of rhodomyrtone, an acylphloroglucinol present in Rhodomyrtus tomentosa leaves, against the human Gram-positive pathogen Streptococcus pneumoniae. The compound exhibited pronounced anti-pneumococcal activity against a broad collection of clinical isolates. We studied the effects at the molecular level by integrated proteomic and metabolomic analysis. The results revealed alterations in enzymes and metabolites involved in several metabolic pathways including amino acid biosynthesis, nucleic acid biosynthesis, glucid, and lipid metabolism. Notably, the levels of two enzymes (glycosyltransferase and UTP-glucose-1-phosphate uridylyltransferase) and three metabolites (UDP-glucose, UDP-glucuronic acid and UDP-N-acetyl-D-galactosamine) participating in the synthesis of the pneumococcal capsule clearly diminished in the bacterial cells exposed to rhodomyrtone. Rhodomyrtone-treated pneumococci significantly possessed less amount of capsule, as measured by a colorimetric assay and visualized by electron microscopy. These findings reveal the utility of combining proteomic and metabolomic analyses to provide insight into phenotypic features of S. pneumoniae treated with this potential novel antibiotic. This can lead to an alternative antibiotic for the treatment of S. pneumoniae infections, because of the growing concern regarding antimicrobial resistance.

Roles of Regulatory RNAs for Antibiotic Resistance in Bacteria and Their Potential Value as Novel Drug Targets

The emergence of antibiotic resistance mechanisms among bacterial pathogens increases the demand for novel treatment strategies. Lately, the contribution of non-coding RNAs to antibiotic resistance and their potential value as drug targets became evident. RNA attenuator elements in mRNA leader regions couple expression of resistance genes to the presence of the cognate antibiotic. Trans-encoded small RNAs (sRNAs) modulate antibiotic tolerance by base-pairing with mRNAs encoding functions important for resistance such as metabolic enzymes, drug efflux pumps, or transport proteins. Bacteria respond with extensive changes of their sRNA repertoire to antibiotics. Each antibiotic generates a unique sRNA profile possibly causing downstream effects that may help to overcome the antibiotic challenge. In consequence, regulatory RNAs including sRNAs and their protein interaction partners such as Hfq may prove useful as targets for antimicrobial chemotherapy. Indeed, several compounds have been developed that kill bacteria by mimicking ligands for riboswitches controlling essential genes, demonstrating that regulatory RNA elements are druggable targets. Drugs acting on sRNAs are considered for combined therapies to treat infections. In this review, we address how regulatory RNAs respond to and establish resistance to antibiotics in bacteria. Approaches to target RNAs involved in intrinsic antibiotic resistance or virulence for chemotherapy will be discussed.

Using bacterial genomes and essential genes for the development of new antibiotics

The shrinking antibiotic development pipeline together with the global increase in antibiotic resistant infections requires that new molecules with antimicrobial activity are developed. Traditional empirical screening approaches of natural and non-natural compounds have identified the majority of antibiotics that are currently available, however this approach has produced relatively few new antibiotics over the last few decades. The vast amount of bacterial genome sequence information that has become available since the sequencing of the first bacterial genome more than 20years ago holds potential for contributing to the discovery of novel antimicrobial compounds. Comparative genomic approaches can identify genes that are highly conserved within and between bacterial species, and thus may represent genes that participate in key bacterial processes. Whole genome mutagenesis studies can also identify genes necessary for bacterial growth and survival under different environmental conditions, making them attractive targets for the development of novel inhibitory compounds. In addition, transcriptomic and proteomic approaches can be used to characterize RNA and protein levels on a cellular scale, providing information on bacterial physiology that can be applied to antibiotic target identification. Finally, bacterial genomes can be mined to identify biosynthetic pathways that produce many intrinsic antimicrobial compounds and peptides. In this review, we provide an overview of past and current efforts aimed at using bacterial genomic data in the discovery and development of novel antibiotics.

The analysis of the antibiotic resistome offers new opportunities for therapeutic intervention

Most efforts in the development of antimicrobials have focused on the screening of lethal targets. Nevertheless, the constant expansion of antimicrobial resistance makes the antibiotic resistance determinants themselves suitable targets for finding inhibitors to be used in combination with antibiotics. Among them, inhibitors of antibiotic inactivating enzymes and of multidrug efflux pumps are suitable candidates for improving the efficacy of antibiotics. In addition, the application of systems biology tools is helping to understand the changes in bacterial physiology associated to the acquisition of resistance, including the increased susceptibility to other antibiotics displayed by some antibiotic-resistant mutants. This information is useful for implementing novel strategies based in metabolic interventions or combination of antibiotics for improving the efficacy of antibacterial therapy.