Metabolomics in antimicrobial drug discovery

Recent findings on metabolomics and the microbiome of oral bacteria involved in dental caries and periodontal disease

Periodontal disease is characterized by bacterial toxins within the oral biofilm surrounding the teeth, leading to gingivitis and the gradual dissolution of the alveolar bone, which supports the teeth. Notably, symptoms in the early stages of the disease are often absent. Similarly, dental caries occurs when oral bacteria metabolize dietary sugars, producing acids that dissolve tooth enamel and dentin. These bacteria are commonly present in the oral cavity of most individuals. Metabolomics, a relatively recent addition to the "omics" research landscape, involves the comprehensive analysis of metabolites in vivo to elucidate pathological mechanisms and accelerate drug discovery. Meanwhile, the term "microbiome" refers to the collection of microorganisms within a specific environmental niche or their collective genomes. The human microbiome plays a critical role in health and disease, influencing a wide array of physiological and pathological processes. Recent advances in microbiome research have identified numerous bacteria implicated in dental caries and periodontal disease. Additionally, studies have uncovered various pathogenic factors associated with these microorganisms. This review focuses on recent findings in metabolomics and the microbiome, specifically targeting oral bacteria linked to dental caries and periodontal disease. We acknowledge the limitation of relying exclusively on the MEDLINE database via PubMed, while excluding other sources such as gray literature, conference proceedings, and clinical practice guidelines.

Development of membrane-targeting chalcone derivatives as antibacterial agents against multidrug-resistant bacteria

The striking rise of infections caused by multidrug-resistant pathogens has evolved as a serious threat to public health worldwide. To develop new antibacterials to combat multidrug-resistant bacteria, a novel class of amphiphilic chalcone derivatives serving as antimicrobial peptidomimetics was designed and synthesized. Among them, the most promising compound 14b displayed broad-spectrum antimicrobial activity against both Gram-positive bacteria (MICs = 0.5-1 μg/mL) and Gram-negative bacteria (MICs = 1-32 μg/mL), low hemolytic activity, and good membrane selectivity. Moreover, compound 14b exhibited rapid bactericidal action, a low probability of developing resistance, high proteolytic stability, and strong capabilities of inhibiting and destroying bacterial biofilms. Further mechanism investigations revealed that compound 14b possessed strong membrane-disrupting abilities and could disintegrate the integrity of bacterial cell membranes by destroying transmembrane potential and enhancing membrane permeability, and causing the generation of intracellular ROS and the leakage of DNA and proteins, ultimately leading to bacterial death. More importantly, compound 14b also showed excellent in vivo therapeutic potency in a mouse septicemia model infected by both Gram-positive and Gram-negative bacteria, indicating its potential to be an antibacterial agent to confront bacterial infections.

Advance in the application of metabolomics technology in poultry

Metabolomics is a science that takes small molecular metabolites in organisms as the research object and determines the dynamic changes of metabolites at the overall level through a variety of modern analytical techniques. At present, metabolomics technology has been widely used in biological significance interpretation, food safety and quality, breeding, disease diagnosis, functional compound identification, and other fields. Its application in poultry science has also become the focus of widespread attention. With the sustainable development of analytical techniques, metabolomics has great potential in the application of poultry science. In this paper, the research progress of metabolomics in poultry growth and development, genetics and breeding, egg quality, meat quality, and disease is reviewed and concluded, which is expected to provide scientific ideas for the research of metabolomics in poultry.

Progress in the Identification and Design of Novel Antimicrobial Peptides Against Pathogenic Microorganisms

The occurrence and spread of antimicrobial resistance (AMR) pose a looming threat to human health around the world. Novel antibiotics are urgently needed to address the AMR crisis. In recent years, antimicrobial peptides (AMPs) have gained increasing attention as potential alternatives to conventional antibiotics due to their abundant sources, structural diversity, broad-spectrum antimicrobial activity, and ease of production. Given its significance, there has been a tremendous advancement in the research and development of AMPs. Numerous AMPs have been identified from various natural sources (e.g., plant, animal, human, microorganism) based on either well-established isolation or bioinformatic pipelines. Moreover, computer-assisted strategies (e.g., machine learning (ML) and deep learning (DL)) have emerged as a powerful and promising technology for the accurate prediction and design of new AMPs. It may overcome some of the shortcomings of traditional antibiotic discovery and contribute to the rapid development and translation of AMPs. In these cases, this review aims to appraise the latest advances in identifying and designing AMPs and their significant antimicrobial activities against a wide range of bacterial pathogens. The review also highlights the critical challenges in discovering and applying AMPs.

Metabolic Flux Analysis of Xanthomonas oryzae Treated with Bismerthiazol Revealed Glutathione Oxidoreductase in Glutathione Metabolism Serves as an Effective Target

Bacterial blight (BB) of rice caused by Xanthomonas oryzae pathovar oryzae (Xoo) is a serious global rice disease. Due to increasing bactericide resistance, developing new inhibitors is urgent. Drug repositioning offers a potential strategy to address this issue. In this study, we integrated transcriptional data into a genome-scale metabolic model (GSMM) to screen novel anti-Xoo targets. Two RNA-seq datasets (before and after bismerthiazol treatment) were used to constrain the GSMM and simulate metabolic processes. Metabolic fluxes were calculated using parsimonious flux balance analysis (pFBA) identifying reactions with significant changes for target screening. Glutathione oxidoreductase (GSR) was selected as a potential anti-Xoo target and validated through antibacterial experiments. Virtual screening based on the target identified DB12411 as a lead compound with the potential for new antibacterial agents. This approach demonstrates that integrating metabolic networks and transcriptional data can aid in both understanding antibacterial mechanisms and discovering novel drug targets.

Mass spectrometry-based metabolomics for the investigation of antibiotic-bacterial interactions

With the development of analytical technologies especially mass spectrometry, metabolomics is becoming increasingly hot in the field of studying antibiotic-bacterial interactions. On the one hand, metabolomics can reveal metabolic perturbations in bacteria in the presence of antibiotics and expose metabolic mechanisms. On the other hand, through in-depth analysis of bacterial metabolic profiles, biomarkers and bioactive secondary metabolites with great potential as drug precursors can be discovered. This review focuses on the experimental workflow of bacterial metabolomics and its application to study the interaction between bacteria and antibiotics. Metabolomics improves the understanding of antibiotic lethality, reveals metabolic perturbations in antibiotic-resistant bacteria, guides the diagnosis and antibiotic treatment of infectious diseases, and aids in the exploration of antibacterial metabolites in nature. Furthermore, current limitations and directions for future developments in this area are discussed.

Investigation of the antimycobacterial activity of African medicinal plants combined with chemometric analysis to identify potential leads

The emergence of drug-resistant Mycobacterium tuberculosis strains is a threat to global health necessitating the discovery of novel chemotherapeutic agents. Natural products drug discovery, which previously led to the discovery of rifamycins, is a valuable approach in this endeavor. Against this backdrop, we set out to investigate the in vitro antimycobacterial properties of medicinal plants from Ghana and South Africa, evaluating 36 extracts and their 252 corresponding solid phase extraction (SPE) generated fractions primarily against the non-pathogenic Mycobacterium smegmatis and Mycobacterium aurum species. The most potent fraction was further evaluated in vitro against infectious M. tuberculosis strain. Crinum asiaticum (bulb) (Amaryllidaceae) emerged as the most potent plant species with specific fractions showing exceptional, near equipotent activity against the non-pathogenic Mycobacterium species (0.39 µg/ml ≤ MIC ≤ 25 µg/ml) with one fraction being moderately active (MIC = 32.6 µg/ml) against M. tuberculosis. Metabolomic analysis led to the identification of eight compounds predicted to be active against M. smegmatis and M. aurum. In conclusion, from our comprehensive study, we generated data which provided an insight into the antimycobacterial properties of Ghanaian and South African plants. Future work will be focused on the isolation and evaluation of the compounds predicted to be active.

B. Trivella D. NP3 MS Workflow: An Open-Source Software System to Empower Natural Product-Based Drug Discovery Using Untargeted Metabolomics

Natural products (or specialized metabolites) are historically the main source of new drugs. However, the current drug discovery pipelines require miniaturization and speeds that are incompatible with traditional natural product research methods, especially in the early stages of the research. This article introduces the NP3 MS Workflow, a robust open-source software system for liquid chromatography-tandem mass spectrometry (LC-MS/MS) untargeted metabolomic data processing and analysis, designed to rank bioactive natural products directly from complex mixtures of compounds, such as bioactive biota samples. NP3 MS Workflow allows minimal user intervention as well as customization of each step of LC-MS/MS data processing, with diagnostic statistics to allow interpretation and optimization of LC-MS/MS data processing by the user. NP3 MS Workflow adds improved computing of the MS2 spectra in an LC-MS/MS data set and provides tools for automatic [M + H]+ ion deconvolution using fragmentation rules; chemical structural annotation against MS2 databases; and relative quantification of the precursor ions for bioactivity correlation scoring. The software will be presented with case studies and comparisons with equivalent tools currently available. NP3 MS Workflow shows a robust and useful approach to select bioactive natural products from complex mixtures, improving the set of tools available for untargeted metabolomics. It can be easily integrated into natural product-based drug-discovery pipelines and to other fields of research at the interface of chemistry and biology.

Strategy to Empower Nontargeted Metabolomics by Triple-Dimensional Combinatorial Derivatization with MS-TDF Software

Chemical derivatization is a widely employed strategy in metabolomics to enhance metabolite coverage by improving chromatographic behavior and increasing the ionization rates in mass spectroscopy (MS). However, derivatization might complicate MS data, posing challenges for data mining due to the lack of a corresponding benchmark database. To address this issue, we developed a triple-dimensional combinatorial derivatization strategy for nontargeted metabolomics. This strategy utilizes three structurally similar derivatization reagents and is supported by MS-TDF software for accelerated data processing. Notably, simultaneous derivatization of specific metabolite functional groups in biological samples produced compounds with stable but distinct chromatographic retention times and mass numbers, facilitating discrimination by MS-TDF, an in-house MS data processing software. In this study, carbonyl analogues in human plasma were derivatized using a combination of three hydrazide-based derivatization reagents: 2-hydrazinopyridine, 2-hydrazino-5-methylpyridine, and 2-hydrazino-5-cyanopyridine (6-hydrazinonicotinonitrile). This approach was applied to identify potential carbonyl biomarkers in lung cancer. Analysis and validation of human plasma samples demonstrated that our strategy improved the recognition accuracy of metabolites and reduced the risk of false positives, providing a useful method for nontargeted metabolomics studies. The MATLAB code for MS-TDF is available on GitHub at https://github.com/CaixiaYuan/MS-TDF.

β-Lactam potentiators to re-sensitize resistant pathogens: Discovery, development, clinical use and the way forward

β-lactam antibiotics are one of the most widely used and diverse classes of antimicrobial agents for treating both Gram-negative and Gram-positive bacterial infections. The β-lactam antibiotics, which include penicillins, cephalosporins, monobactams and carbapenems, exert their antibacterial activity by inhibiting the bacterial cell wall synthesis and have a global positive impact in treating serious bacterial infections. Today, β-lactam antibiotics are the most frequently prescribed antimicrobial across the globe. However, due to the widespread use and misapplication of β-lactam antibiotics in fields such as human medicine and animal agriculture, resistance to this superlative drug class has emerged in the majority of clinically important bacterial pathogens. This heightened antibiotic resistance prompted researchers to explore novel strategies to restore the activity of β-lactam antibiotics, which led to the discovery of β-lactamase inhibitors (BLIs) and other β-lactam potentiators. Although there are several successful β-lactam-β-lactamase inhibitor combinations in use, the emergence of novel resistance mechanisms and variants of β-lactamases have put the quest of new β-lactam potentiators beyond precedence. This review summarizes the success stories of β-lactamase inhibitors in use, prospective β-lactam potentiators in various phases of clinical trials and the different strategies used to identify novel β-lactam potentiators. Furthermore, this review discusses the various challenges in taking these β-lactam potentiators from bench to bedside and expounds other mechanisms that could be investigated to reduce the global antimicrobial resistance (AMR) burden.

Synergy between Genome Mining, Metabolomics, and Bioinformatics Uncovers Antibacterial Chlorinated Carbazole Alkaloids and Their Biosynthetic Gene Cluster from Streptomyces tubbatahanensis sp. nov., a Novel Actinomycete Isolated from Sulu Sea, Philippines

In this study, a novel actinomycete strain, DSD3025T, isolated from the underexplored marine sediments in Tubbataha Reefs Natural Park, Sulu Sea, Philippines, with the proposed name Streptomyces tubbatahanensis sp. nov., was described using polyphasic approaches and characterized using whole-genome sequencing. Its specialized metabolites were profiled using mass spectrometry and nuclear magnetic resonance analyses, followed by antibacterial, anticancer, and toxicity screening. The S. tubbatahanensis DSD3025T genome was comprised of 7.76 Mbp with a 72.3% G+C content. The average nucleotide identity and digital DNA-DNA hybridization values were 96.5% and 64.1%, respectively, compared with its closest related species, thus delineating the novelty of Streptomyces species. The genome encoded 29 putative biosynthetic gene clusters (BGCs), including a BGC region containing tryptophan halogenase and its associated flavin reductase, which were not found in its close Streptomyces relatives. The metabolite profiling unfolded six rare halogenated carbazole alkaloids, with chlocarbazomycin A as the major compound. A biosynthetic pathway for chlocarbazomycin A was proposed using genome mining, metabolomics, and bioinformatics platforms. Chlocarbazomycin A produced by S. tubbatahanensis DSD3025T has antibacterial activities against Staphylococcus aureus ATCC BAA-44 and Streptococcus pyogenes and showed antiproliferative activity against colon (HCT-116) and ovarian (A2780) human cancer cell lines. Chlocarbazomycin A exhibited no toxicity to liver cells but moderate and high toxicity to kidney and cardiac cell lines, respectively. IMPORTANCE Streptomyces tubbatahanensis DSD3025T is a novel actinomycete with antibiotic and anticancer activities from Tubbataha Reefs Natural Park, a United Nations Educational, Scientific and Cultural Organization World Heritage Site in Sulu Sea and considered one of the Philippines' oldest and most-well-protected marine ecosystems. In silico genome mining tools were used to identify putative BGCs that led to the discovery of genes involved in the production of halogenated carbazole alkaloids and new natural products. By integrating bioinformatics-driven genome mining and metabolomics, we unearthed the hidden biosynthetic richness and mined the associated chemical entities from the novel Streptomyces species. The bioprospecting of novel Streptomyces species from marine sediments of underexplored ecological niches serves as an important source of antibiotic and anticancer drug leads with unique chemical scaffolds.

Serum metabolomics analysis in patients with alcohol dependence

Objective

Alcohol dependence (AD) is a chronic recurrent mental disease caused by long-term drinking. It is one of the most prevalent public health problems. However, AD diagnosis lacks objective biomarkers. This study was aimed to shed some light on potential biomarkers of AD patients by investigating the serum metabolomics profiles of AD patients and the controls.

Methods

Liquid chromatography-mass spectrometry (LC-MS) was used to detect the serum metabolites of 29 AD patients (AD) and 28 controls. Six samples were set aside as the validation set (Control: n = 3; AD group: n = 3), and the remaining were used as the training set (Control: n = 26; AD group: n = 25). Principal component analysis (PCA) and partial least squares discriminant analysis (PCA-DA) were performed to analyze the training set samples. The metabolic pathways were analyzed using the MetPA database. The signal pathways with pathway impact >0.2, value of p <0.05, and FDR < 0.05 were selected. From the screened pathways, the metabolites whose levels changed by at least 3-fold were screened. The metabolites with no numerical overlap in their concentrations in the AD and the control groups were screened out and verified with the validation set.

Results

The serum metabolomic profiles of the control and the AD groups were significantly different. We identified six significantly altered metabolic signal pathways, including protein digestion and absorption; alanine, aspartate, and glutamate metabolism; arginine biosynthesis; linoleic acid metabolism; butanoate metabolism; and GABAergic synapse. In these six signal pathways, the levels of 28 metabolites were found to be significantly altered. Of these, the alterations of 11 metabolites changed by at least 3-fold compared to the control group. Of these 11 metabolites, those with no numerical overlap in their concentrations between the AD and the control groups were GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid and L-glutamine.

Conclusion

The metabolite profile of the AD group was significantly different from that of the control group. GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid, and L-glutamine could be used as potential diagnostic markers for AD.