An Optimized Synthetic-Bioinformatic Natural Product Antibiotic Sterilizes Multidrug-Resistant Acinetobacter baumannii-Infected Wounds

Natural products from the human microbiome: an emergent frontier in organic synthesis and drug discovery

Often referred to as the "second genome", the human microbiome is at the epicenter of complex inter-habitat biochemical networks like the "gut-brain axis", which has emerged as a significant determinant of cognition, overall health and well-being, as well as resistance to antibiotics and susceptibility to diseases. As part of a broader understanding of the nexus between the human microbiome, diseases and microbial interactions, whether encoded secondary metabolites (natural products) play crucial signalling roles has been the subject of intense scrutiny in the recent past. A major focus of these activities involves harvesting the genomic potential of the human microbiome via bioinformatics guided genome mining and culturomics. Through these efforts, an impressive number of structurally intriguing antibiotics, with enhanced chemical diversity vis-à-vis conventional antibiotics have been isolated from human commensal bacteria, thereby generating considerable interest in their total synthesis and expanding their therapeutic space for drug discovery. These developments augur well for the discovery of new drugs and antibiotics, particularly in the context of challenges posed by mycobacterial resistance and emerging new diseases. The current landscape of various synthetic campaigns and drug discovery initiatives on antibacterial natural products from the human microbiome is captured in this review with an intent to stimulate further activities in this interdisciplinary arena among the new generation.

Combating Antimicrobial Resistance in the Post-Genomic Era: Rapid Antibiotic Discovery

Constantly evolving drug-resistant "superbugs" have caused an urgent demand for novel antimicrobial agents. Natural products and their analogs have been a prolific source of antimicrobial agents, even though a high rediscovery rate and less targeted research has made the field challenging in the pre-genomic era. With recent advancements in technology, natural product research is gaining new life. Genome mining has allowed for more targeted excavation of biosynthetic potential from natural sources that was previously overlooked. Researchers use bioinformatic algorithms to rapidly identify and predict antimicrobial candidates by studying the genome before even entering the lab. In addition, synthetic biology and advanced analytical instruments enable the accelerated identification of novel antibiotics with distinct structures. Here, we reviewed the literature for noteworthy examples of novel antimicrobial agents discovered through various methodologies, highlighting the candidates with potent effectiveness against antimicrobial-resistant pathogens.

Targeted Large-Scale Genome Mining and Candidate Prioritization for Natural Product Discovery

Large-scale genome-mining analyses have identified an enormous number of cryptic biosynthetic gene clusters (BGCs) as a great source of novel bioactive natural products. Given the sheer number of natural product (NP) candidates, effective strategies and computational methods are keys to choosing appropriate BGCs for further NP characterization and production. This review discusses genomics-based approaches for prioritizing candidate BGCs extracted from large-scale genomic data, by highlighting studies that have successfully produced compounds with high chemical novelty, novel biosynthesis pathway, and potent bioactivities. We group these studies based on their BGC-prioritization logics: detecting presence of resistance genes, use of phylogenomics analysis as a guide, and targeting for specific chemical structures. We also briefly comment on the different bioinformatics tools used in the field and examine practical considerations when employing a large-scale genome mining study.

Old and modern antibiotic structures with potential for today's infections

Due to the lack of new antibiotics with efficacy against the ESKAPE and other resistant microbes, coupled to the demise of major pharmaceutical company antibiotic discovery programs, due to a number of factors but mainly ROI calculations and the lack of efficacy of combinatorial chemistry as a substitute, the search for novel antibiotics may well have moved to the utilization of older structures with significant synthetic chemistry input. This short review demonstrates how modern synthetic chemistry, when applied to either modification of current resistant antibiotics such as glycopeptides, or production of novel peptidic agents based on natural product sourced antimicrobial peptides (AMPs) and other potential initial peptide-based agents from genomic searches and baiting techniques, have produced active agents of significant utility. In addition, synthetic chemistry practitioners have now shown that they can produce bioactive molecules of greater than 800 Daltons in kilogram quantities under cGMP conditions.

Synthetic Natural Product Inspired Cyclic Peptides

Natural products are a bountiful source of bioactive molecules. Unfortunately, discovery of novel bioactive natural products is challenging due to cryptic biosynthetic gene clusters, low titers, and arduous purifications. Herein, we describe SNaPP (Synthetic Natural Product Inspired Cyclic Peptides), a method for identifying NP-inspired bioactive peptides. SNaPP expedites bioactive molecule discovery by combining bioinformatics predictions of nonribosomal peptide synthetases with chemical synthesis of the predicted natural products (pNPs). SNaPP utilizes a recently discovered cyclase, the penicillin binding protein-like cyclase, as the lynchpin for the development of a library of head-to-tail cyclic peptide pNPs. Analysis of 500 biosynthetic gene clusters allowed for identification of 131 novel pNPs. Fifty-one diverse pNPs were synthesized using solid phase peptide synthesis and solution-phase cyclization. Antibacterial testing revealed 14 pNPs with antibiotic activity, including activity against multidrug-resistant Gram-negative bacteria. Overall, SNaPP demonstrates the power of combining bioinformatics predictions with chemical synthesis to accelerate the discovery of bioactive molecules.

In Silico/In Vitro Strategies Leading to the Discovery of New Nonribosomal Peptide and Polyketide Antibiotics Active against Human Pathogens

Antibiotics are majorly important molecules for human health. Following the golden age of antibiotic discovery, a period of decline ensued, characterised by the rediscovery of the same molecules. At the same time, new culture techniques and high-throughput sequencing enabled the discovery of new microorganisms that represent a potential source of interesting new antimicrobial substances to explore. The aim of this review is to present recently discovered nonribosomal peptide (NRP) and polyketide (PK) molecules with antimicrobial activity against human pathogens. We highlight the different in silico/in vitro strategies and approaches that led to their discovery. As a result of technological progress and a better understanding of the NRP and PK synthesis mechanisms, these new antibiotic compounds provide an additional option in human medical treatment and a potential way out of the impasse of antibiotic resistance.

Mining and unearthing hidden biosynthetic potential

Genetically encoded small molecules (secondary metabolites) play eminent roles in ecological interactions, as pathogenicity factors and as drug leads. Yet, these chemical mediators often evade detection, and the discovery of novel entities is hampered by low production and high rediscovery rates. These limitations may be addressed by genome mining for biosynthetic gene clusters, thereby unveiling cryptic metabolic potential. The development of sophisticated data mining methods and genetic and analytical tools has enabled the discovery of an impressive array of previously overlooked natural products. This review shows the newest developments in the field, highlighting compound discovery from unconventional sources and microbiomes.

Natural products are an important source of bioactive compounds and have versatile applications in different fields, but their discovery is challenging. Here, the authors review the recent developments in genome mining for discovery of natural products, focusing on compounds from unconventional microorganisms and microbiomes.

Comparative Metabologenomics Analysis of Polar Actinomycetes

Biosynthetic and chemical datasets are the two major pillars for microbial drug discovery in the omics era. Despite the advancement of analysis tools and platforms for multi-strain metabolomics and genomics, linking these information sources remains a considerable bottleneck in strain prioritisation and natural product discovery. In this study, molecular networking of the 100 metabolite extracts derived from applying the OSMAC approach to 25 Polar bacterial strains, showed growth media specificity and potential chemical novelty was suggested. Moreover, the metabolite extracts were screened for antibacterial activity and promising selective bioactivity against drug-persistent pathogens such as Klebsiella pneumoniae and Acinetobacter baumannii was observed. Genome sequencing data were combined with metabolomics experiments in the recently developed computational approach, NPLinker, which was used to link BGC and molecular features to prioritise strains for further investigation based on biosynthetic and chemical information. Herein, we putatively identified the known metabolites ectoine and chrloramphenicol which, through NPLinker, were linked to their associated BGCs. The metabologenomics approach followed in this study can potentially be applied to any large microbial datasets for accelerating the discovery of new (bioactive) specialised metabolites.

Structure Prediction and Synthesis of Pyridine-Based Macrocyclic Peptide Natural Products

The structural and functional characterization of natural products is vastly outpaced by the bioinformatic identification of biosynthetic gene clusters (BGCs) that encode such molecules. Uniting our knowledge of bioinformatics and enzymology to predict and synthetically access natural products is an effective platform for investigating cryptic/silent BGCs. We report the identification, biosynthesis, and total synthesis of a minimalistic class of ribosomally synthesized and post-translationally modified peptides (RiPPs) with the responsible BGCs encoding a subset of enzymes known from thiopeptide biosynthesis. On the basis of the BGC content, these RiPPs were predicted to undergo enzymatic dehydration of serine followed by [4+2]-cycloaddition to produce a trisubstituted, pyridine-based macrocycle. These RiPPs, termed "pyritides", thus contain the same six-membered, nitrogenous heterocycle that defines the thiopeptide RiPP class but lack the ubiquitous thiazole/thiazoline heterocycles, suggesting that thiopeptides should be reclassified as a more elaborate subclass of the pyritides. One pyritide product was obtained using an 11-step synthesis, and the structure verified by an orthogonal chemoenzymatic route using the precursor peptide and cognate pyridine synthase. This work exemplifies complementary bioinformatics, enzymology, and synthesis to characterize a minimalistic yet structurally intriguing scaffold that, unlike most thiopeptides, lacks growth-suppressive activity toward Gram-positive bacteria.

Natural product discovery through microbial genome mining

The advent of the genomic era has opened up enormous possibilities for the discovery of new natural products. Also known as specialized metabolites, these compounds produced by bacteria, fungi, and plants have long been sought for their bioactive properties. Innovations in both DNA sequencing technologies and bioinformatics now allow the wealth of sequence data to be mined at both the genome and metagenome levels for new specialized metabolites. However, a key problem that remains is rapidly and efficiently linking these identified genes to their corresponding compounds. Within this review, we provide specific examples of studies that have used the power of genomic or metagenomic data to overcome these problems and identify new small molecules and their biosynthetic pathways.

Synthetic-Bioinformatic Natural Product Antibiotics with Diverse Modes of Action

Bacterial natural products have inspired the development of numerous antibiotics in use today. As resistance to existing antibiotics has become more prevalent, new antibiotic lead structures and activities are desperately needed. An increasing number of natural product biosynthetic gene clusters, to which no known molecules can be assigned, are found in genome and metagenome sequencing data. Here we access structural information encoded in this underexploited resource using a synthetic-bioinformatic natural product (syn-BNP) approach, which relies on bioinformatic algorithms followed by chemical synthesis to predict and then produce small molecules inspired by biosynthetic gene clusters. In total, 157 syn-BNP cyclic peptides inspired by 96 nonribosomal peptide synthetase gene clusters were synthesized and screened for antibacterial activity. This yielded nine antibiotics with activities against ESKAPE pathogens as well as Mycobacterium tuberculosis. Not only are antibiotic-resistant pathogens susceptible to many of these syn-BNP antibiotics, but they were also unable to develop resistance to these antibiotics in laboratory experiments. Characterized modes of action for these antibiotics include cell lysis, membrane depolarization, inhibition of cell wall biosynthesis, and ClpP protease dysregulation. Increasingly refined syn-BNP-based explorations of biosynthetic gene clusters should allow for more rapid identification of evolutionarily inspired bioactive small molecules, in particular antibiotics with diverse mechanism of actions that could help confront the imminent crisis of antimicrobial resistance.

Reduced ROS-mediated antibiotic resistance and its reverting by glucose in Vibrio alginolyticus

Antibiotic-resistant Vibrio alginolyticus poses a big challenge to human health and food safety. It is urgently needed to understand the mechanisms underlying antibiotic resistance to develop effective approaches for the control. Here we explored the metabolic difference between gentamicin-resistant V. alginolyticus (VA-R_GEN ) and gentamicin-sensitive V. alginolyticus (VA-S), and found that the reactive oxygen species (ROS) generation was altered. Compared with VA-S, the ROS content in VA-R_GEN was reduced due to the decreased generation and increased breakdown of ROS. The decreased production of ROS was attributed to the decreased central carbon metabolism, which is associated with the resistance to gentamicin. As such a mechanism, we exogenously administrated VA-R_GEN with the glucose that activated the central carbon metabolism and promoted the generation of ROS, but decreased the breakdown of ROS in VA-R_GEN . The gentamicin-mediated killing was increased with the elevation of the ROS level by a synergistic effect between gentamicin and exogenous glucose. The synergistic effect was inhibited by thiourea, a scavenger of ROS. These results reveal a reduced ROS-mediated antibiotic resistance mechanism and its reversal by exogenous glucose.

Bioactive Synthetic-Bioinformatic Natural Product Cyclic Peptides Inspired by Nonribosomal Peptide Synthetase Gene Clusters from the Human Microbiome

Bioinformatic analysis of sequenced bacterial genomes has uncovered an increasing number of natural product biosynthetic gene clusters (BGCs) to which no known bacterial metabolite can be ascribed. One emerging method we have investigated for studying these BGCs is the synthetic-Bioinformatic Natural Product (syn-BNP) approach. The syn-BNP approach replaces transcription, translation, and in vivo enzymatic biosynthesis of natural products with bioinformatic algorithms to predict the output of a BGC and in vitro chemical synthesis to produce the predicted structure. Here we report on expanding the syn-BNP approach to the design and synthesis of cyclic peptides inspired by nonribosomal peptide synthetase BGCs associated with the human microbiota. While no syn-BNPs we tested inhibited the growth of bacteria or yeast, five were found to be active in the human cell-based MTT metabolic activity assay. Interestingly, active peptides were mostly inspired by BGCs found in the genomes of opportunistic pathogens that are often more commonly associated with environments outside the human microbiome. The cyclic syn-BNP studies presented here provide further evidence of its potential for identifying bioactive small molecules directly from the instructions encoded in the primary sequences of natural product BGCs.

Next-Generation Drug Discovery to Combat Antimicrobial Resistance

The widespread emergence of antibiotic-resistant pathogens poses a severe threat to public health. This problem becomes even worse with a coincident decline in the supply of new antibiotics. Conventional bioactivity-guided natural product discovery has failed to meet the urgent need for new antibiotics, largely due to limited resources and high rediscovery rates. Recent advances in cultivation techniques, analytical technologies, and genomics-based approaches have greatly expanded our access to previously underexploited microbial sources. These strategies will enable us to access new reservoirs of microorganisms and unleash their chemical potentials, thus opening new opportunities for the discovery of next-generation drugs to address the growing concerns of antimicrobial resistance.

Recent perspectives on the virulent factors and treatment options for multidrug-resistant Acinetobacter baumannii

Acinetobacter baumannii (AB) is one of the most notorious and opportunistic pathogens, which caused high morbidity and mortality rate and World Health Organization (WHO) declared this bacterium as priority-1 pathogen in 2017. The current antibacterial agents, such as colistins, carbapenems, and tigecyclines have limited applications, which necessitate novel and alternative therapeutic remedies. Thus, the understanding of recent perspectives on the virulent factors and antibiotic resistance mechanism exhibited by the bacteria are extremely important. In addition to many combinatorial therapies of antibacterial, there is several natural compounds demonstrated significant antibacterial potential towards these bacteria. The computational systems biology and high throughput screening approaches provide crucial insights in identifying novel drug targets and lead molecules with therapeutics potential. Hence, this review provides profound insight on the recent aspects of the virulent factors associated with AB, role of biofilm formation in drug resistance and the mechanisms of multidrug resistance. This review further illustrates the status of current therapeutic agents, scope, and applications of natural therapeutics, such as herbal medicines and role of computational biology, immunoinformatics and virtual screening in novel lead developments. Thus, this review provides novel insight on latest developments in drug-resistance mechanism of multidrug-resistant A. baumannii (MDRAB) and discovery of probable therapeutic interventions.

Metabolic mechanism of ceftazidime resistance in Vibrio alginolyticus

Background

Microbial metabolism confounds antibiotic efficacy. However, information regarding effect of metabolism on cephalosporin antibiotics-mediated killing and Vibrio spp is largely absence, although the drugs are widely used in clinic and the bacteria are pathogens to both human and aquaculture animals.

Purpose

This study explores the metabolome of cephalosporin antibiotic-resistant Vibrio alginolyticus and analyzes the role of bacterial metabolism in drug and multidrug-resistance.

Results

The metabolomes of isogenic ceftazidime-resistant V. alginolyticus (VA-R_CAZ) and ceftazidime-sensitive V. alginolyticus (VA-S) were analyzed using gas chromatography -mass spectrometry. The metabolome of VA-R_CAZ is characterized by inefficient respiration, an inefficient pyruvate cycle (P cycle), increased biosynthesis of fatty acids and decreased membrane proton motive force. This hypothesis was confirmed by the fact that furfural and malonate, inhibitors of pyruvate dehydrogenase and succinate dehydrogenase (P cycle enzymes), respectively, increased resistance of VA-R_CAZ to antibiotics, while exposure to triclosan, to inhibit biosynthesis of fatty acids, decreased resistance.

Conclusion

These results contribute to our understanding of mechanisms of bacterial antibiotic-resistance and may lead to more effective approaches to treat, manage or prevent infections caused by antibiotic-resistant pathogens including those of the Vibrio species.