Substantial Extracellular Metabolic Differences Found Between Phylogenetically Closely Related Probiotic and Pathogenic Strains of Escherichia coli

Leaf extracts of eight selected southern African medicinal plants modulate pro-inflammatory cytokine secretion in LPS-stimulated RAW 264.7 macrophages

This study investigates the anti-inflammatory properties of extracts prepared from the leaves of eight southern African medicinal plants used traditionally to treat inflammation and pain. The inhibitory effect of aqueous and ethanol extracts on the release of pro-inflammatory cytokines was determined in lipopolysaccharide (LPS) stimulated and unstimulated RAW 264.7 murine macrophage cells. The levels of interleukin (IL)-1β, IL-6, tumour necrosis factor-α (TNF-α), interferon-gamma (IFN-γ), monocyte chemoattractant protein 1 (MCP-1) and macrophage inflammatory protein (MIP)-2 release were determined using cytokine multiplex-bead assays. The ethanol extracts of Melianthus comosus Vahl (commonly known as honey flower), Tetradenia riparia (Hochst.) Codd (misty plume bush) and Warburgia salutaris (G. Bertol.) Chiov. (pepper-bark tree), demonstrated the most significant inhibitory activity, with over 50-fold inhibition of IL-1β, IL-6 and TNF-α levels in LPS-stimulated RAW 264.7 macrophages. The aqueous extract of M. comosus also significantly inhibited the secretion of all the tested cytokines and chemokines. Phytochemical investigation of M. comosus ethanol leaf extract using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS) led to the detection of crassolide, deoxylimonoic acid D-ring-lactone, 2-hydroxynonanoic acid and 5-noniloxytryptamine. To the best of our knowledge, the cytokine inhibition properties of most of the medicinal plants screened in this study are reported for the first time. Our results support the use of southern African medicinal plants as anti-inflammatory remedies and provide an insight into the immunomodulatory mechanisms of action.

Metabolite diversity among representatives of divergent Prochlorococcus ecotypes

IMPORTANCE

Approximately half of the annual carbon fixation on Earth occurs in the surface ocean through the photosynthetic activities of phytoplankton such as the ubiquitous picocyanobacterium Prochlorococcus. Ecologically distinct subpopulations (or ecotypes) of Prochlorococcus are central conduits of organic substrates into the ocean microbiome, thus playing important roles in surface ocean production. We measured the chemical profile of three cultured ecotype strains, observing striking differences among them that have implications for the likely chemical impact of Prochlorococcus subpopulations on their surroundings in the wild. Subpopulations differ in abundance along gradients of temperature, light, and nutrient concentrations, suggesting that these chemical differences could affect carbon cycling in different ocean strata and should be considered in models of Prochlorococcus physiology and marine carbon dynamics.

High-resolution strain-level microbiome composition analysis from short reads

BACKGROUND

Bacterial strains under the same species can exhibit different biological properties, making strain-level composition analysis an important step in understanding the dynamics of microbial communities. Metagenomic sequencing has become the major means for probing the microbial composition in host-associated or environmental samples. Although there are a plethora of composition analysis tools, they are not optimized to address the challenges in strain-level analysis: highly similar strain genomes and the presence of multiple strains under one species in a sample. Thus, this work aims to provide a high-resolution and more accurate strain-level analysis tool for short reads.

RESULTS

In this work, we present a new strain-level composition analysis tool named StrainScan that employs a novel tree-based k-mers indexing structure to strike a balance between the strain identification accuracy and the computational complexity. We tested StrainScan extensively on a large number of simulated and real sequencing data and benchmarked StrainScan with popular strain-level analysis tools including Krakenuniq, StrainSeeker, Pathoscope2, Sigma, StrainGE, and StrainEst. The results show that StrainScan has higher accuracy and resolution than the state-of-the-art tools on strain-level composition analysis. It improves the F1 score by 20% in identifying multiple strains at the strain level.

CONCLUSIONS

By using a novel k-mer indexing structure, StrainScan is able to provide strain-level analysis with higher resolution than existing tools, enabling it to return more informative strain composition analysis in one sample or across multiple samples. StrainScan takes short reads and a set of reference strains as input and its source codes are freely available at https://github.com/liaoherui/StrainScan . Video Abstract.

Therapeutic Effects of Valeriana jatamansi on Ulcerative Colitis: Insights into Mechanisms of Action through Metabolomics and Microbiome Analysis

Ulcerative colitis (UC), belonging to inflammatory bowel disease (IBD), is a chronic and relapsing inflammatory disorder of the gastrointestinal tract, which has not been completely cured in patients so far. Valeriana jatamansi is a Chinese medicine used clinically to treat "diarrhea," which is closely related to UC. This study was to elucidate the therapeutic effects of V. jatamansi extract (VJE) on dextran sodium sulfate (DSS)-induced UC in mice and its underlying mechanism. In this work, VJE effectively ameliorates the symptoms and histopathological scores and reduces the production of inflammatory factors in UC mice. The colon untargeted metabolomics analysis and 16S rDNA sequencing showed remarkable differences in colon metabolite profiles and intestinal microbiome composition between the control and DSS groups, and VJE intervention can reduce these differences. Thirty-two biomarkers were found and modulated the primary pathways including pyrimidine metabolism, arginine biosynthesis, and glutathione metabolism. Meanwhile, twelve significant taxa of gut microbiota were found. Moreover, there is a close relationship between endogenous metabolites and intestinal flora. These findings suggested that VJE ameliorates UC by inhibiting inflammatory factors, recovering intestinal maladjustment, and regulating the interaction between intestinal microbiota and host metabolites. Therefore, the intervention of V. jatamansi is a potential therapeutic treatment for UC.

Escherichia coli Nissle 1917 Antagonizes Candida albicans Growth and Protects Intestinal Cells from C. albicans-Mediated Damage

Candida albicans is a pathobiont of the gastrointestinal tract. It can contribute to the diversity of the gut microbiome without causing harmful effects. When the immune system is compromised, C. albicans can damage intestinal cells and cause invasive disease. We hypothesize that a therapeutic approach against C. albicans infections can rely on the antimicrobial properties of probiotic bacteria. We investigated the impact of the probiotic strain Escherichia coli Nissle 1917 (EcN) on C. albicans growth and its ability to cause damage to intestinal cells. In co-culture kinetic assays, C. albicans abundance gradually decreased over time compared with C. albicans abundance in the absence of EcN. Quantification of C. albicans survival suggests that EcN exerts a fungicidal activity. Cell-free supernatants (CFS) collected from C. albicans-EcN co-culture mildly altered C. albicans growth, suggesting the involvement of an EcN-released compound. Using a model of co-culture in the presence of human intestinal epithelial cells, we further show that EcN prevents C. albicans from damaging enterocytes both distantly and through direct contact. Consistently, both C. albicans's filamentous growth and microcolony formation were altered by EcN. Taken together, our study proposes that probiotic-strain EcN can be exploited for future therapeutic approaches against C. albicans infections.

Continuous, Nondestructive Detection of Microorganism Growth at Buried Interfaces with Vascularized Polymers

Evaluating surface bacterial growth at buried interfaces can be problematic due to the difficulties associated with obtaining samples. In this work, we present a new method to detect signals from microorganisms at buried interfaces that is nondestructive and can be conducted continuously. Inspired by vascular systems in nature that permit chemical communication between the surface and underlying tissues of an organism, we created a system in which an inert carrier fluid could be introduced into an empty vascular network embedded in a polymer matrix. When a microorganism layer was grown on top, small molecules produced by the growth process would diffuse down into the carrier fluid, which could then be collected and analyzed. We used this system to nondestructively detect signals from a surface layer of Escherichia coli using conductivity, ultraviolet-visible (UV-vis) absorbance spectroscopy, and high-performance liquid chromatography (HPLC) for organic acids, methods that ranged in sensitivity, time-to-result, and cost. Carrier fluid from sample vascularized polymers with surface bacterial growth recorded significantly higher values in both conductivity and absorbance at 350 nm compared to controls with no bacteria after 24 h. HPLC analysis showed three clear peaks that varied between the samples with bacteria and the controls without. Tests tracking the change in signals over 48 h showed clear trends that matched the bacterial growth curves, demonstrating the system's ability to monitor changes over time. A 2D finite element model of the system closely matched the experimental results, confirming the predictability of the system. Finally, tests using clinically relevant Staphylococcus aureus and Pseudomonas aeruginosa yielded differences in conductivity, absorbance, and HPLC peak areas unique to each species. This work lays the foundation for the use of vascularized polymers as an adaptive system for the continuous, nondestructive detection of surface microorganisms at buried interfaces in both industry and medicine.

High-quality genome-scale metabolic network reconstruction of probiotic bacterium Escherichia coli Nissle 1917

BACKGROUND

Escherichia coli Nissle 1917 (EcN) is a probiotic bacterium used to treat various gastrointestinal diseases. EcN is increasingly being used as a chassis for the engineering of advanced microbiome therapeutics. To aid in future engineering efforts, our aim was to construct an updated metabolic model of EcN with extended secondary metabolite representation.

RESULTS

An updated high-quality genome-scale metabolic model of EcN, iHM1533, was developed based on comparison with 55 E. coli/Shigella reference GEMs and manual curation, including expanded secondary metabolite pathways (enterobactin, salmochelins, aerobactin, yersiniabactin, and colibactin). The model was validated and improved using phenotype microarray data, resulting in an 82.3% accuracy in predicting growth phenotypes on various nutrition sources. Flux variability analysis with previously published ¹³C fluxomics data validated prediction of the internal central carbon fluxes. A standardised test suite called Memote assessed the quality of iHM1533 to have an overall score of 89%. The model was applied by using constraint-based flux analysis to predict targets for optimisation of secondary metabolite production. Modelling predicted design targets from across amino acid metabolism, carbon metabolism, and other subsystems that are common or unique for influencing the production of various secondary metabolites.

CONCLUSION

iHM1533 represents a well-annotated metabolic model of EcN with extended secondary metabolite representation. Phenotype characterisation and the iHM1533 model provide a better understanding of the metabolic capabilities of EcN and will help future metabolic engineering efforts.

Integrated Profiling of Gram-Positive and Gram-Negative Probiotic Genomes, Proteomes and Metabolomes Revealed Small Molecules with Differential Growth Inhibition of Antimicrobial-Resistant Pathogens

Probiotics produce small molecules that may serve as alternatives to conventional antibiotics by suppressing growth of antimicrobial resistant (AMR) pathogens. The objective of this study was to identify and examine antimicrobials produced and secreted by probiotics using 'omics' profiling with computer-based metabolic flux analyses. The cell-free supernatant of Gram-positive Lacticaseibacillus rhamnosus GG (LGG) and Gram-negative Escherichia coli Nissle (ECN) probiotics inhibited growth of AMR Salmonella Typhimurium, Escherichia coli, and Klebsiella oxytoca ranging between 28.85 - 41.20% (LGG) and 11.48 - 29.45% (ECN). A dose dependent analysis of probiotic supernatants showed LGG was 6.27% to 20.55% more effective at reducing AMR pathogen growth when compared to ECN. Principal component analysis showed clear separation of ECN and LGG cell free supernatant metabolomes. Among 667 metabolites in the supernatant, 304 were differentially abundant between LGG and ECN probiotics. Proteomics identified 87 proteins, whereby 67 (ECN) and 14 (LGG) showed differential expression as enzymes related to carbohydrate and energy metabolic pathways. The whole genomes and metabolomes were next used for in-silico metabolic network analysis. The model predicted the production of 166 metabolites by LGG and ECN probiotics across amino acid, carbohydrate/energy, and nucleotide metabolism with antimicrobial functions. The predictive accuracy of the metabolic flux analysis highlights the novel utility for profiling probiotic supplements as dietary-based antimicrobial alternatives in the control of AMR pathogen growth.

Integrating in vitro metabolomics with a 96-well high-throughput screening platform

INTRODUCTION

High-throughput screening (HTS) is emerging as an approach to support decision-making in chemical safety assessments. In parallel, in vitro metabolomics is a promising approach that can help accelerate the transition from animal models to high-throughput cell-based models in toxicity testing.

OBJECTIVE

In this study we establish and evaluate a high-throughput metabolomics workflow that is compatible with a 96-well HTS platform employing 50,000 hepatocytes of HepaRG per well.

METHODS

Low biomass cell samples were extracted for metabolomics analyses using a newly established semi-automated protocol, and the intracellular metabolites were analysed using a high-resolution spectral-stitching nanoelectrospray direct infusion mass spectrometry (nESI-DIMS) method that was modified for low sample biomass.

RESULTS

The method was assessed with respect to sensitivity and repeatability of the entire workflow from cell culturing and sampling to measurement of the metabolic phenotype, demonstrating sufficient sensitivity (> 3000 features in hepatocyte extracts) and intra- and inter-plate repeatability for polar nESI-DIMS assays (median relative standard deviation < 30%). The assays were employed for a proof-of-principle toxicological study with a model toxicant, cadmium chloride, revealing changes in the metabolome across five sampling times in the 48-h exposure period. To allow the option for lipidomics analyses, the solvent system was extended by establishing separate extraction methods for polar metabolites and lipids.

CONCLUSIONS

Experimental, analytical and informatics workflows reported here met pre-defined criteria in terms of sensitivity, repeatability and ability to detect metabolome changes induced by a toxicant and are ready for application in metabolomics-driven toxicity testing to complement HTS assays.

Foodborne pathogens in the omics era

Outbreaks and deaths related to Foodborne Diseases (FBD) occur constantly in the world, as a result of the consumption of contaminated foodstuffs with pathogens such as Listeria monocytogenes, Escherichia coli, Staphylococcus aureus, Salmonella spp, Clostridium spp. and Campylobacter spp. The purpose of this review is to discuss the main omic techniques applied in foodborne pathogen and to demonstrate their functionalities through the food chain and to guarantee the food safety. The main techniques presented are genomic, transcriptomic, secretomic, proteomic, and metabolomic, which together, in the field of food and nutrition, are known as "Foodomics." This review had highlighted the potential of omics to integrate variables that contribute to food safety and to enable us to understand their application on foodborne diseases. The appropriate use of these techniques had driven the definition of critical parameters to achieve successful results in the improvement of consumers health, costs and to obtain safe and high-quality products.

Role of Carbon Monoxide in Host-Gut Microbiome Communication

Nature is full of examples of symbiotic relationships. The critical symbiotic relation between host and mutualistic bacteria is attracting increasing attention to the degree that the gut microbiome is proposed by some as a new organ system. The microbiome exerts its systemic effect through a diverse range of metabolites, which include gaseous molecules such as H₂, CO₂, NH₃, CH₄, NO, H₂S, and CO. In turn, the human host can influence the microbiome through these gaseous molecules as well in a reciprocal manner. Among these gaseous molecules, NO, H₂S, and CO occupy a special place because of their widely known physiological functions in the host and their overlap and similarity in both targets and functions. The roles that NO and H₂S play have been extensively examined by others. Herein, the roles of CO in host-gut microbiome communication are examined through a discussion of (1) host production and function of CO, (2) available CO donors as research tools, (3) CO production from diet and bacterial sources, (4) effect of CO on bacteria including CO sensing, and (5) gut microbiome production of CO. There is a large amount of literature suggesting the "messenger" role of CO in host-gut microbiome communication. However, much more work is needed to begin achieving a systematic understanding of this issue.

Metabolomics Study on Pathogenic and Non-pathogenic E. coli with Closely Related Genomes with a Focus on Yersiniabactin and Its Known and Novel Derivatives

The Escherichia coli (E. coli) strains Nissle 1917 (EcN), 83972 and CFT073 are closely related but differ in their phenotypes and pathogenicity. The aim of this study was to compare the metabolome of these strains based on metabolomic data analysis of bacterial samples using liquid chromatography-high resolution mass spectrometry (LC-HRMS). The strains were cultivated in minimum essential medium at 37 °C for 6 h. The sterilized culture supernatant was analyzed, followed by data processing to create feature lists, and statistical analysis to identify discriminating features in the metabolomes of the three strains. Metabolites were identified using the exact masses, isotope patterns, and fragmentation spectra. The results showed that the metabolome of EcN differs significantly from the metabolomes of E. coli 83972 and CFT073. Based on the analysis, yersiniabactin (Ybt), its metal complexes, and its known structural derivatives escherichelin and ulbactin B were identified as discriminating features; the latter has not been described for E. coli before. Additionally, novel Ytb derivatives were found and tentatively identified by LC-MS/HRMS. All these metabolites were determined in significantly higher levels in the metabolome of EcN compared to E. coli 83972, which may explain a large part of the observed differences of the metabolomes.

Bioengineered Escherichia coli Nissle 1917 for tumour-targeting therapy

Bacterial vectors, as microscopic living 'robotic factories', can be reprogrammed into microscopic living 'robotic factories', using a top-down bioengineering approach to produce and deliver anticancer agents. Most of the current research has focused on bacterial species such as Salmonella typhimurium or Clostridium novyi. However, Escherichia coli Nissle 1917 (EcN) is another promising candidate with probiotic properties. EcN offers increased applicability for cancer treatment with the development of new molecular biology and complete genome sequencing techniques. In this review, we discuss the genetics and physical properties of EcN. We also summarize and analyse recent studies regarding tumour therapy mediated by EcN. Many challenges remain in the development of more promising strategies for combatting cancer with EcN.