Analysis of Intracellular Metabolites from Microorganisms: Quenching and Extraction Protocols

Revealing the hidden world of soil microbes: Metagenomic insights into plant, bacteria, and fungi interactions for sustainable agriculture and ecosystem restoration

The future of agriculture is questionable under the current climate change scenario. Climate change and climate-related calamities directly influence biotic and abiotic factors that control agroecosystems, endangering the safety of the world's food supply. The intricate interactions between soil microorganisms, including plants, bacteria, and fungi, play a pivotal role in promoting sustainable agriculture and ecosystem restoration. Soil microbes play a major part in nutrient cycling, including soil organic carbon (SOC), and play a pivotal function in the emission and depletion of greenhouse gases, including CH4, CO2, and N2O, which can impact the climate. At this juncture, developing a triumphant metagenomics approach has greatly increased our knowledge of the makeup, functionality, and dynamics of the soil microbiome. Currently, the involvement of plants in climate change indicates that they can interact with the microbial communities in their environment to relieve various stresses through the innate microbiome assortment of focused strains, a phenomenon dubbed "Cry for Help." The metagenomics method has lately appeared as a new platform to adjust and encourage beneficial communications between plants and microbes and improve plant fitness. The metagenomics of soil microbes can provide a powerful tool for designing and evaluating ecosystem restoration strategies that promote sustainable agriculture under a changing climate. By identifying the specific functions and activities of soil microbes, we can develop restoration programs that support these critical components of healthy ecosystems while providing economic benefits through ecosystem services. In the current review, we highlight the innate functions of microbiomes to maintain the sustainability of agriculture and ecosystem restoration. Through this insight study of soil microbe metagenomics, we pave the way for innovative strategies to address the pressing challenges of food security and environmental conservation. The present article elucidates the mechanisms through which plants and microbes communicate to enhance plant resilience and ecosystem restoration and to leverage metagenomics to identify and promote beneficial plant-microbe interactions. Key findings reveal that soil microbes are pivotal in nutrient cycling, greenhouse gas modulation, and overall ecosystem health, offering novel insights into designing ecosystem restoration strategies that bolster sustainable agriculture. As this is a topic many are grappling with, hope these musings will provide people alike with some food for thought.

Evolution-aided improvement of the acid tolerance of Levilactobacillus brevis and its application in sourdough fermentation

Levilactobacillus brevis is crucial in food fermentation, particularly in sourdough production. However, the cultivation of L. brevis faces a challenge with accumulation of lactic acid, a major inhibitor. We aimed to increase the acid tolerance of L. brevis, an industrial strain for sourdough fermentation. We used the adaptive laboratory evolution (ALE) to obtain lactic acid tolerant strains. The evolved strain's fermentation and metabolite profiles, alongside sensory evaluation, were compared with the parental strain by using various analytical techniques. The ALE approach increased lactic acid tolerance in the evolved strain showing an increased growth rate by 1.1 and 1.9 times higher than the parental strain at pH 4.1 and 6.5, respectively. Comprehensive analyses demonstrated its potential application in sourdough fermentation, promising reduced downstream costs. The evolved strain, free from genetically modified organisms concerns, has great potential for industrial use by exhibiting enhanced growth in acidic conditions without affecting consumers' bread preferences.

Bacterial metabolomics: current applications for human welfare and future aspects

An imbalanced microbiome is linked to several diseases, such as cancer, inflammatory bowel disease, obesity, and even neurological disorders. Bacteria and their by-products are used for various industrial and clinical purposes. The metabolites under discussion were chosen based on their biological impacts on host and gut microbiota interactions as established by metabolome research. The separation of bacterial metabolites by using statistics and machine learning analysis creates new opportunities for applications of bacteria and their metabolites in the environmental and medical sciences. Thus, the metabolite production strategies, methodologies, and importance of bacterial metabolites for human well-being are discussed in this review.

Investigation of different cold adaptation abilities in Salmonella enterica serotype Typhimurium strains using extracellular metabolomic approach

This study explored the extracellular metabolomic responses of three different Salmonella enterica serotype Typhimurium (S. Typhimurium) strains-ATCC 13311 (STy1), NCCP 16964 (STy4), and NCCP 16958 (STy8)-cultured at refrigeration temperatures. The objective was to identify the survival mechanisms of S. Typhimurium under cold stress by analyzing variations in their metabolomic profiles. Qualitative and quantitative assessments identified significant metabolite alterations on day 6, marking a critical inflection point. Key metabolites such as trehalose, proline, glycerol, and tryptophan were notably upregulated in response to cold stress. Through multivariate analyses, the strains were distinguished using three metabolites-4-aminobutyrate, ethanol, and uridine-as potential biomarkers, underscoring distinct metabolic responses to refrigeration. Specifically, STy1 exhibited unique adaptive capabilities through enhanced metabolism of betaine and 4-aminobutyrate. These findings highlight the variability in adaptive strategies among S. Typhimurium strains, suggesting that certain strains may possess more robust metabolic pathways for enhancing survival in refrigerated conditions.

Biobased short chain fatty acid production - Exploring microbial community dynamics and metabolic networks through kinetic and microbial modeling approaches

In recent years, there has been growing interest in harnessing anaerobic digestion technology for resource recovery from waste streams. This approach has evolved beyond its traditional role in energy generation to encompass the production of valuable carboxylic acids, especially volatile fatty acids (VFAs) like acetic acid, propionic acid, and butyric acid. VFAs hold great potential for various industries and biobased applications due to their versatile properties. Despite increasing global demand, over 90% of VFAs are currently produced synthetically from petrochemicals. Realizing the potential of large-scale biobased VFA production from waste streams offers significant eco-friendly opportunities but comes with several key challenges. These include low VFA production yields, unstable acid compositions, complex and expensive purification methods, and post-processing needs. Among these, production yield and acid composition stand out as the most critical obstacles impacting economic viability and competitiveness. This paper seeks to offer a comprehensive view of combining complementary modeling approaches, including kinetic and microbial modeling, to understand the workings of microbial communities and metabolic pathways in VFA production, enhance production efficiency, and regulate acid profiles through the integration of omics and bioreactor data.

Transcriptomic and metabolomic analysis of prebiotics utilization by Bifidobacterium animalis

In this study, the utilization mechanism of oligosaccharides by Bifidobacterium was investigated through the transcriptome sequencing and non-targeted metabolomics technology of Bifidobacterium animalis cultured with fructo-oligosaccharides (FOS) and galacto-oligosaccharides (GOS). The results showed that FOS affected the synthesis of adenosine triphosphate binding transporters (ABC transporters) by increasing the expression levels of msmE, msmG, and gluA. Similarly, GOS improved aminoacyl-tRNA synthases by upregulating the expression of tRNA-Ala, tRNA-Pro, and tRNA-Met. Bifidobacterium animalis cultured with FOS and GOS produced different metabolites, such as histamine, tartaric acid, and norepinephrine, with the functions of inhibiting inflammation, alleviating depression and diseases related to brain and nervous system and maintaining body health. Furthermore, the transcriptome and metabolome analysis results revealed that FOS and GOS promoted the growth and metabolism of Bifidobacterium animalis by regulating the related pathways of carbohydrate, energy, and amino acid metabolism. Overall, the experimental results provided significant insights into the prebiotic effects of FOS and GOS.

Comparison of Three Widely Employed Extraction Methods for Metabolomic Analysis of Trypanosoma brucei

Trypanosoma brucei (Tb) is the causative agent of human African trypanosomiasis (HAT), also known as sleeping sickness, which can be fatal if left untreated. An understanding of the parasite's cellular metabolism is vital for the discovery of new antitrypanosomal drugs and for disease eradication. Metabolomics can be used to analyze numerous metabolic pathways described as essential to Tb. brucei but has some limitations linked to the metabolites' physicochemical properties and the extraction process. To develop an optimized method for extracting and analyzing Tb. brucei metabolites, we tested the three most commonly used extraction methods, analyzed the extracts by hydrophilic interaction liquid chromatography high-resolution mass spectrometry (HILIC LC-HRMS), and further evaluated the results using quantitative criteria including the number, intensity, reproducibility, and variability of features, as well as qualitative criteria such as the specific coverage of relevant metabolites. Here, we present the resulting protocols for untargeted metabolomic analysis of Tb. brucei using (HILIC LC-HRMS). © 2024 Wiley Periodicals LLC. Basic Protocol 1: Culture of Trypanosoma brucei brucei parasites Basic Protocol 2: Preparation of samples for metabolomic analysis of Trypanosoma brucei brucei Basic Protocol 3: LC-HRMS-based metabolomic data analysis of Trypanosoma brucei brucei.

SCALiR: A Web Application for Automating Absolute Quantification of Mass Spectrometry-Based Metabolomics Data

Quantitative liquid chromatography-mass spectrometry (LC-MS)-based metabolomics is becoming an important approach for studying complex biological systems but presents several technical challenges that limit its widespread use. Computing metabolite concentrations using standard curves generated from standard mixtures of known concentrations is a labor-intensive process that is often performed manually. Currently, there are few options for open-source software tools that can automatically calculate metabolite concentrations. Herein, we introduce SCALiR (standard curve application for determining linear ranges), a new web-based software tool specifically built for this task, which allows users to automatically transform LC-MS signals into absolute quantitative data (https://www.lewisresearchgroup.org/software). SCALiR uses an algorithm that automatically finds the equation of the line of best fit for each standard curve and uses this equation to calculate compound concentrations from the LC-MS signal. Using a standard mix containing 77 metabolites, we show a close correlation between the concentrations calculated by SCALiR and the expected concentrations of each compound (R2 = 0.99 for a y = x curve fitting). Moreover, we demonstrate that SCALiR reproducibly calculates concentrations of midrange standards across ten analytical batches (average coefficient of variation 0.091). SCALiR can be used to calculate metabolite concentrations either using external calibration curves or by using internal standards to correct for matrix effects. This open-source and vendor agnostic software offers users several advantages in that (1) it requires only 10 s of analysis time to compute concentrations of >75 compounds, (2) it facilitates automation of quantitative workflows, and (3) it performs deterministic evaluations of compound quantification limits. SCALiR therefore provides the metabolomics community with a simple and rapid tool that enables rigorous and reproducible quantitative metabolomics studies.

Restricted glycolysis is a primary cause of the reduced growth rate of zinc-deficient yeast cells

Zinc is required for many critical processes, including intermediary metabolism. In Saccharomyces cerevisiae, the Zap1 activator regulates the transcription of ∼80 genes in response to Zn supply. Some Zap1-regulated genes are Zn transporters that maintain Zn homeostasis, while others mediate adaptive responses that enhance fitness. One adaptive response gene encodes the 2-cysteine peroxiredoxin Tsa1, which is critical to Zn-deficient (ZnD) growth. Depending on its redox state, Tsa1 can function as a peroxidase, a protein chaperone, or a regulatory redox sensor. In a screen for possible Tsa1 regulatory targets, we identified a mutation (cdc19S492A) that partially suppressed the tsa1Δ growth defect. The cdc19S492A mutation reduced activity of its protein product, pyruvate kinase isozyme 1 (Pyk1), implicating Tsa1 in adapting glycolysis to ZnD conditions. Glycolysis requires activity of the Zn-dependent enzyme fructose-bisphosphate aldolase 1, which was substantially decreased in ZnD cells. We hypothesized that in ZnD tsa1Δ cells, the loss of a compensatory Tsa1 regulatory function causes depletion of glycolytic intermediates and restricts dependent amino acid synthesis pathways, and that the decreased activity of Pyk1S492A counteracted this depletion by slowing the irreversible conversion of phosphoenolpyruvate to pyruvate. In support of this model, supplementing ZnD tsa1Δ cells with aromatic amino acids improved their growth. Phosphoenolpyruvate supplementation, in contrast, had a much greater effect on growth rate of WT and tsa1Δ ZnD cells, indicating that inefficient glycolysis is a major factor limiting yeast growth. Surprisingly however, this restriction was not primarily due to low fructose-bisphosphate aldolase 1 activity, but instead occurs earlier in glycolysis.

Metabolomics-based development of bioproduction processes toward industrial-scale production

Microbial biomanufacturing offers a promising, environment-friendly platform for next-generation chemical production. However, its limited industrial implementation is attributed to the slow production rates of target compounds and the time-intensive engineering of high-yield strains. This review highlights how metabolomics expedites bioproduction development, as demonstrated through case studies of its integration into microbial strain engineering, culture optimization, and model construction. The Design-Build-Test-Learn (DBTL) cycle serves as a standard workflow for strain engineering. Process development, including the optimization of culture conditions and scale-up, is crucial for industrial production. In silico models facilitate the development of strains and processes. Metabolomics is a powerful driver of the DBTL framework, process development, and model construction.

Endo metabolomic profiling of flor and wine yeasts reveals a positive correlation between intracellular metabolite load and the specific glycolytic flux during wine fermentation

This study explored the intracellular metabolic variations between 17 strains of Saccharomyces cerevisiae belonging to two different genetic populations: flor and wine yeasts, in the context of alcoholic fermentation. These two populations are closely related as they share the same ecological niche but display distinct genetic characteristics. A protocol was developed for intracellular metabolites extraction and 1H-NMR analysis. This methodology allowed us to identify and quantify 21 intracellular metabolites at two different fermentation steps: the exponential and stationary phases. This work provided evidence of significant differences in the abundance of intracellular metabolites, which are strain- and time-dependent, thus revealing complex interactions. Moreover, the differences in abundance appeared to be correlated with life-history traits such as average cell size and specific glycolytic flux, which revealed unsuspected phenotypic correlations between metabolite load and fermentation activity.

Precision fermentation with mass spectrometry-based spent media analysis

Optimization and monitoring of bioprocesses requires the measurement of several process parameters and quality attributes. Mass spectrometry (MS)-based techniques such as those coupled to gas chromatography (GCMS) and liquid Chromatography (LCMS) enable the simultaneous measurement of hundreds of metabolites with high sensitivity. When applied to spent media, such metabolome analysis can help determine the sequence of substrate uptake and metabolite secretion, consequently facilitating better design of initial media and feeding strategy. Furthermore, the analysis of metabolite diversity and abundance from spent media will aid the determination of metabolic phases of the culture and the identification of metabolites as surrogate markers for product titer and quality. This review covers the recent advances in metabolomics analysis applied to the development and monitoring of bioprocesses. In this regard, we recommend a stepwise workflow and guidelines that a bioprocesses engineer can adopt to develop and optimize a fermentation process using spent media analysis. Finally, we show examples of how the use of MS can revolutionize the design and monitoring of bioprocesses.

Mass spectrometry-based analysis of gut microbial metabolites of aromatic amino acids

Small molecules derived from gut microbiota have been increasingly investigated to better understand the functional roles of the human gut microbiome. Microbial metabolites of aromatic amino acids (AAA) have been linked to many diseases, such as metabolic disorders, chronic kidney diseases, inflammatory bowel disease, diabetes, and cancer. Important microbial AAA metabolites are often discovered via global metabolite profiling of biological specimens collected from humans or animal models. Subsequent metabolite identity confirmation and absolute quantification using targeted analysis enable comparisons across different studies, which can lead to the establishment of threshold concentrations of potential metabolite biomarkers. Owing to their excellent selectivity and sensitivity, hyphenated mass spectrometry (MS) techniques are often employed to identify and quantify AAA metabolites in various biological matrices. Here, we summarize the developments over the past five years in MS-based methodology for analyzing gut microbiota-derived AAA. Sample preparation, method validation, analytical performance, and statistical methods for correlation analysis are discussed, along with future perspectives.

In Search of Complementary Extraction Methods for Comprehensive Coverage of the Escherichia coli Metabolome

Escherichia coli is an invaluable research tool for many fields of biology, in particular for the production of recombinant enzymes. However, the activity of many such recombinant enzymes cannot be determined using standard biochemical assays, as often, the relevant substrates are not known, or the products produced are not detectable. Today, the biochemical footprints of such unknown enzyme activities can be revealed via the analysis of the metabolomes of the recombinant E. coli clones in which they are expressed, using sensitive technologies such as mass spectrometry. However, before any metabolites can be identified, it is necessary to achieve as high a coverage of the potential metabolites present within E. coli as possible. We have therefore analyzed a wide range of different extraction methods against the cell free extracts of various recombinant E. coli clones. The results were analyzed to determine the minimum number of extractions that achieved high recovery and coverage of metabolites. Two methods were selected for further analysis due to their ability to produce not only high numbers of ions, but also wide mass coverage and a high degree of complementarity. One extraction method uses acetonitrile and water, in a 4:1 ratio, which is then dried down and reconstituted in the chromatography running buffer prior to injection onto the chromatography column, and the other extraction method uses a combination of methanol, water and chloroform, in a 3:1:1 ratio, which is injected directly onto the chromatography column. These two extraction methods were shown to be complementary to each other, as regards the respective metabolites extracted, and to cover a large range of metabolites.

Intracellular Dynamics-Resolved Label-Free Scattering Reveals Real-Time Metabolism of Single Bacteria

Nanoscopic investigation of bacterial cells is essential to reveal their physiological status, impacting all cellular functions. Currently, this requires labeled probes or targeted staining procedures. Herein, we report a new bacterial feature, intracellular dynamics-resolved Rayleigh scattering (IDRS), that visualizes spatiotemporal cytoplasmic transitions in unlabeled bacteria and characterizes their real-time physiological status in 10 s. From single-bacterium IDRS signals, we discovered unique spatial patterns and their multiple transitions in Gram-negative and Gram-positive bacteria. The magnitude of IDRS signal variation highly correlated with the metabolic status of bacteria, differentiating persistent subpopulations. This is also the first report demonstrating distinct real-time metabolic conditions of unlabeled drug-resistant bacteria that are exposed to different doses of antibiotics. Our strategy opens up a way to simultaneously trace in situ metabolic and antibiotic resistance statuses, which can be applied in single-cell level control of bacterial metabolism and efficacy with a heterogeneous nature.

Characterization of phenyl propiolic acid from Proteus mirabilis DMTMMR-11 and Evaluation of its mode of action against Yersinia enterocolitica (MTCC-840) an in-Vitro and in-Vivo based approach

Foodborne illnesses are pervasive in raising public health concerns in both developed and developing nations. Yersinia enterocolitica a zoonotic bacterial species that causes food-transmitted infections, and gastroenteritis, is its most prevalent clinical manifestation. This study aims to investigate the differences, dependencies, and inhibitory mechanisms between the host and the microbiome. Proteus mirabilis DMTMMR-11, the bacterium found in the human gastrointestinal tract was used for the extraction of intracellular metabolite, because of its beneficial effects on the normal flora of the human gut. Phenyl propiolic acid was identified as the dominant compound in the metabolite after characterization using FT-IR, NMR, and LC-MS-MS. To assess its inhibitory mechanism against Yersinia enterocolitica, the pathogen was subjected to biological characterization by MBC and MIC, resulting in the rate of inhibition at 50 μg/ml. Anti-bacterial curve supports the inhibited growth of Y. enterocolitica. Mechanism of inhibition at its cellular level was indicated by the increase in alkaline phosphate content, which drastically reduced the cell membrane and cell wall potential expanding its permeability by intruding the membrane proteins, which was observed in SEM Imaging. Phenyl propiolic acid efficiently disrupts the biofilm formation by reducing the adherence and increasing the eradication property of the pathogen by exhibiting 65% of inhibition at the minimal duration of 12h. In-vivo study was carried out through host-pathogen interaction in C. elegans, an efficient model organism assessed for its life-span, physiological, and behavioral assays.

Anomalous Dynamics of Labile Metabolites in Cold Human Blood Detected Using 1H NMR Spectroscopy

Recent efforts in our laboratory have enabled access to an unprecedented number (∼90) of quantifiable metabolites in human blood by a simple nuclear magnetic resonance (NMR) spectroscopy method, which includes energy coenzymes, redox coenzymes, and antioxidants that are fundamental to cellular functions [ J. Magn. Reson. Open 2022, 12-13, 100082]. The coenzymes and antioxidants, however, are notoriously labile and are extremely sensitive to specimen harvesting, extraction, and measurement conditions. This problem is largely underappreciated and carries the risk of grossly inaccurate measurements and incorrect study outcomes. As a part of addressing this challenge, in this study, human blood specimens were comprehensively and quantitatively investigated using 1H NMR spectroscopy. Freshly drawn human blood specimens were treated or not treated with methanol, ethanol, or a mixture of methanol and chloroform, and stored on ice or on bench, at room temperature for different time periods from 0 to 24 h, prior to storing at -80 °C. Interestingly, the labile metabolite levels were stable in blood treated with an organic solvent. However, their levels in blood in untreated samples increased or decreased by factors of up to 5 or more within 3 h. Further, surprisingly, and contrary to the current knowledge about metabolite stability, the variation of coenzyme levels was more dramatic in blood stored on ice than on bench, at room temperature. In addition, unlike the generally observed phenomenon of oxidation of redox coenzymes, reduction was observed in untreated blood. Such preanalytical dynamics of the labile metabolites potentially arises from the active cellular metabolism. From the metabolomics perspective, the massive variation of the labile metabolite levels even in blood stored on ice is alarming and stresses the critical need to immediately quench the cellular metabolism for reliable analyses. Overall, the results provide compelling evidence that warrants a paradigm shift in the sample collection protocol for blood metabolomics involving labile metabolites.

SCALiR: a web application for automating absolute quantification of mass spectrometry-based metabolomics data

Metabolomics is an important approach for studying complex biological systems. Quantitative liquid chromatography-mass spectrometry (LC-MS)-based metabolomics is becoming a mainstream strategy but presents several technical challenges that limit its widespread use. Computing metabolite concentrations using standard curves generated from standard mixtures of known concentrations is a labor-intensive process which is often performed manually. Currently, there are few options for open-source software tools that can automatically calculate metabolite concentrations. Herein, we introduce SCALiR (Standard Curve Application for determining Linear Ranges), a new web-based software tool specifically built for this task, which allows users to automatically transform LC-MS signal data into absolute quantitative data (https://www.lewisresearchgroup.org/software). The algorithm used in SCALiR automatically finds the equation of the line of best fit for each standard curve and uses this equation to calculate compound concentrations from their LC-MS signal. Using a standard mix containing 77 metabolites, we found excellent correlation between the concentrations calculated by SCALiR and the expected concentrations of each compound (R2 = 0.99) and that SCALiR reproducibly calculated concentrations of mid-range standards across ten analytical batches (average coefficient of variation 0.091). SCALiR offers users several advantages, including that it (1) is open-source and vendor agnostic; (2) requires only 10 seconds of analysis time to compute concentrations of >75 compounds; (3) facilitates automation of quantitative workflows; and (4) performs deterministic evaluation of compound quantification limits. SCALiR provides the metabolomics community with a simple and rapid tool that enables rigorous and reproducible quantitative metabolomics studies.

Molecular responses during bacterial filamentation reveal inhibition methods of drug-resistant bacteria

Bacterial antimicrobial resistance (AMR) is among the most significant challenges to current human society. Exposing bacteria to antibiotics can activate their self-saving responses, e.g., filamentation, leading to the development of bacterial AMR. Understanding the molecular changes during the self-saving responses can reveal new inhibition methods of drug-resistant bacteria. Herein, we used an online microfluidics mass spectrometry system for real-time characterization of metabolic changes of bacteria during filamentation under the stimulus of antibiotics. Significant pathways, e.g., nucleotide metabolism and coenzyme A biosynthesis, correlated to the filamentation of extended-spectrum beta-lactamase-producing Escherichia coli (ESBL-E. coli) were identified. A cyclic dinucleotide, c-di-GMP, which is derived from nucleotide metabolism and reported closely related to bacterial resistance and tolerance, was observed significantly up-regulated during the bacterial filamentation. By using a chemical inhibitor, ebselen, to inhibit diguanylate cyclases which catalyzes the synthesis of c-di-GMP, the minimum inhibitory concentration of ceftriaxone against ESBL-E. coli was significantly decreased. This inhibitory effect was also verified with other ESBL-E. coli strains and other beta-lactam antibiotics, i.e., ampicillin. A mutant strain of ESBL-E. coli by knocking out the dgcM gene was used to demonstrate that the inhibition of the antibiotic resistance to beta-lactams by ebselen was mediated through the inhibition of the diguanylate cyclase DgcM and the modulation of c-di-GMP levels. Our study uncovers the molecular changes during bacterial filamentation and proposes a method to inhibit antibiotic-resistant bacteria by combining traditional antibiotics and chemical inhibitors against the enzymes involved in bacterial self-saving responses.

Metabolomic profiling of bacterial biofilm: trends, challenges, and an emerging antibiofilm target

Biofilm-related infections substantially contribute to bacterial illnesses, with estimates indicating that at least 80% of such diseases are linked to biofilms. Biofilms exhibit unique metabolic patterns that set them apart from their planktonic counterparts, resulting in significant metabolic reprogramming during biofilm formation. Differential glycolytic enzymes suggest that central metabolic processes are markedly different in biofilms and planktonic cells. The glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is highly expressed in Staphylococcus aureus biofilm progenitors, indicating that changes in glycolysis activity play a role in biofilm development. Notably, an important consideration is a correlation between elevated cyclic di-guanylate monophosphate (c-di-GMP) activity and biofilm formation in various bacteria. C-di-GMP plays a critical role in maintaining the persistence of Pseudomonas aeruginosa biofilms by regulating alginate production, a significant biofilm matrix component. Furthermore, it has been demonstrated that S. aureus biofilm development is initiated by several tricarboxylic acid (TCA) intermediates in a FnbA-dependent manner. Finally, Glucose 6-phosphatase (G6P) boosts the phosphorylation of histidine-containing protein (HPr) by increasing the activity of HPr kinase, enhancing its interaction with CcpA, and resulting in biofilm development through polysaccharide intercellular adhesion (PIA) accumulation and icaADBC transcription. Therefore, studying the metabolic changes associated with biofilm development is crucial for understanding the complex mechanisms involved in biofilm formation and identifying potential targets for intervention. Accordingly, this review aims to provide a comprehensive overview of recent advances in metabolomic profiling of biofilms, including emerging trends, prevailing challenges, and the identification of potential targets for anti-biofilm strategies.

Characterization and Amelioration of Filtration Difficulties Encountered in Metabolomic Studies of Clostridium thermocellum at Elevated Sugar Concentrations

Clostridium thermocellum, a promising candidate for consolidated bioprocessing, has been subjected to numerous engineering strategies for enhanced bioethanol production. Measurements of intracellular metabolites at substrate concentrations high enough (>50 g/L) to allow the production of industrially relevant titers of ethanol would inform efforts toward this end but have been difficult due to the production of a viscous substance that interferes with the filtration and quenching steps during metabolite extraction. To determine whether this problem is unique to C. thermocellum, we performed filtration experiments with other organisms that have been engineered for high-titer ethanol production, including Escherichia coli and Thermoanaerobacterium saccharolyticum. We addressed the problem through a series of improvements, including active pH control (to reduce problems with viscosity), investigation of different filter materials and pore sizes (to increase the filtration capacity), and correction for extracellular metabolite concentrations, and we developed a technique for more accurate intracellular metabolite measurements at elevated substrate concentrations. IMPORTANCE The accurate measurement of intracellular metabolites (metabolomics) is an integral part of metabolic engineering for the enhanced production of industrially important compounds and a useful technique to understand microbial physiology. Previous work tended to focus on model organisms under laboratory conditions. As we try to perform metabolomic studies with a wider range of organisms under conditions that more closely represent those found in nature or industry, we have found limitations in existing techniques. For example, fast filtration is an important step in quenching metabolism in preparation for metabolite extraction; however, it does not work for cultures of C. thermocellum at high substrate concentrations. In this work, we characterize the extent of the problem and develop techniques to overcome it.

Dark accumulation of downstream glycolytic intermediates initiates robust photosynthesis in cyanobacteria

Photosynthesis must maintain stability and robustness throughout fluctuating natural environments. In cyanobacteria, dark-to-light transition leads to drastic metabolic changes from dark respiratory metabolism to CO2 fixation through the Calvin-Benson-Bassham (CBB) cycle using energy and redox equivalents provided by photosynthetic electron transfer. Previous studies have shown that catabolic metabolism supports the smooth transition into CBB cycle metabolism. However, metabolic mechanisms for robust initiation of photosynthesis are poorly understood due to lack of dynamic metabolic characterizations of dark-to-light transitions. Here, we show rapid dynamic changes (on a time scale of seconds) in absolute metabolite concentrations and 13C tracer incorporation after strong or weak light irradiation in the cyanobacterium Synechocystis sp. PCC 6803. Integration of this data enabled estimation of time-resolved nonstationary metabolic flux underlying CBB cycle activation. This dynamic metabolic analysis indicated that downstream glycolytic intermediates, including phosphoglycerate and phosphoenolpyruvate, accumulate under dark conditions as major substrates for initial CO2 fixation. Compared with wild-type Synechocystis, significant decreases in the initial oxygen evolution rate were observed in 12 h dark preincubated mutants deficient in glycogen degradation or oxidative pentose phosphate pathways. Accordingly, the degree of decrease in the initial oxygen evolution rate was proportional to the accumulated pool size of glycolytic intermediates. These observations indicate that the accumulation of glycolytic intermediates is essential for efficient metabolism switching under fluctuating light environments.

Multi-omics approach reveals elevated potential of bacteria for biodegradation of imidacloprid

The residual imidacloprid, a widely used insecticide is causing serious environmental concerns. Knowledge of its biodegradation will help in assessing its residual mass in soil. In view of this, a soil microcosm-based study was performed to test the biodegradation potential of Agrobacterium sp. InxBP2. It achieved ∼88% degradation in 20 days and followed the pseudo-first-order kinetics (k = 0.0511 day^-1 and t_1/2=7 days). Whole genome sequencing of Agrobacterium sp. InxBP2 revealed a genome size of 5.44 Mbp with 5179 genes. Imidacloprid degrading genes at loci K7A42_07110 (ABC transporter substrate-binding protein), K7A42_07270 (amidohydrolase family protein), K7A42_07385 (ABC transporter ATP-binding protein), K7A42_16,845 (nitronate monooxygenase family protein), and K7A42_20,660 (FAD-dependent monooxygenase) having sequence and functional similarity with known counterparts were identified. Molecular docking of proteins encoded by identified genes with their respective degradation pathway intermediates exhibited significant binding energies (-6.56 to -4.14 kcal/mol). Molecular dynamic simulation discovered consistent interactions and binding depicting high stability of docked complexes. Proteome analysis revealed differential protein expression in imidacloprid treated versus untreated samples which corroborated with the in-silico findings. Further, the detection of metabolites proved the bacterial degradation of imidacloprid. Thus, results provided a mechanistic link between imidacloprid and associated degradative genes/enzymes of Agrobacterium sp. InxBP2. These findings will be of immense significance in carrying out the lifecycle analysis and formulating strategies for the bioremediation of soils contaminated with insecticides like imidacloprid.

Comparative metabolomic analysis of exudates of microcystin-producing and microcystin-free Microcystis aeruginosa strains

Cyanobacterial harmful algal blooms (cHABs) dominated by Microcystis aeruginosa threaten the ecological integrity and beneficial uses of lakes globally. In addition to producing hepatotoxic microcystins (MC), M. aeruginosa exudates (MaE) contain various compounds with demonstrated toxicity to aquatic biota. Previously, we found that the ecotoxicity of MaE differed between MC-producing and MC-free strains at exponential (E-phase) and stationary (S-phase) growth phases. However, the components in these exudates and their specific harmful effects were unclear. In this study, we performed untargeted metabolomics based on liquid chromatography-mass spectrometry to reveal the constituents in MaE of a MC-producing and a MC-free strain at both E-phase and S-phase. A total of 409 metabolites were identified and quantified based on their relative abundance. These compounds included lipids, organoheterocyclic compounds, organic acid, benzenoids and organic oxygen compounds. Multivariate analysis revealed that strains and growth phases significantly influenced the metabolite profile. The MC-producing strain had greater total metabolites abundance than the MC-free strain at S-phase, whereas the MC-free strain released higher concentrations of benzenoids, lipids, organic oxygen, organic nitrogen and organoheterocyclic compounds than the MC-producing strain at E-phase. Total metabolites had higher abundance in S-phase than in E- phase in both strains. Analysis of differential metabolites (DMs) and pathways suggest that lipids metabolism and biosynthesis of secondary metabolites were more tightly coupled to growth phases than to strains. Abundance of some toxic lipids and benzenoids DMs were significantly higher in the MC-free strain than the MC-producing one. This study builds on the understanding of MaE chemicals and their biotoxicity, and adds to evidence that non-MC-producing strains of cyanobacteria may also pose a threat to ecosystem health.

Optimized Fast Filtration-Based Sampling and Extraction Enables Precise and Absolute Quantification of the Escherichia coli Central Carbon Metabolome

Precise and accurate quantification is a prerequisite for interpretation of targeted metabolomics data, but this task is challenged by the inherent instability of the analytes. The sampling, quenching, extraction, and sample purification conditions required to recover and stabilize metabolites in representative extracts have also been proven highly dependent on species-specific properties. For Escherichia coli, unspecific leakage has been demonstrated for conventional microbial metabolomics sampling protocols. We herein present a fast filtration-based sampling protocol for this widely applied model organism, focusing on pitfalls such as inefficient filtration, selective loss of biomass, matrix contamination, and membrane permeabilization and leakage. We evaluate the effect of and need for removal of extracellular components and demonstrate how residual salts can challenge analytical accuracy of hyphenated mass spectrometric analyses, even when sophisticated correction strategies are applied. Laborious extraction procedures are bypassed by direct extraction in cold acetonitrile:water:methanol (3:5:2, v/v%), ensuring compatibility with sample concentration and thus, any downstream analysis. By applying this protocol, we achieve and demonstrate high precision and low metabolite turnover, and, followingly, minimal perturbation of the inherent metabolic state. This allows us to herein report absolute intracellular concentrations in E. coli and explore its central carbon metabolome at several commonly applied cultivation conditions.

Tool and techniques study to plant microbiome current understanding and future needs: an overview

Microorganisms are present in the universe and they play role in beneficial and harmful to human life, society, and environments. Plant microbiome is a broad term in which microbes are present in the rhizo, phyllo, or endophytic region and play several beneficial and harmful roles with the plant. To know of these microorganisms, it is essential to be able to isolate purification and identify them quickly under laboratory conditions. So, to improve the microbial study, several tools and techniques such as microscopy, rRNA, or rDNA sequencing, fingerprinting, probing, clone libraries, chips, and metagenomics have been developed. The major benefits of these techniques are the identification of microbial community through direct analysis as well as it can apply in situ. Without tools and techniques, we cannot understand the roles of microbiomes. This review explains the tools and their roles in the understanding of microbiomes and their ecological diversity in environments.

Cronobacter sakazakii Cue for the Attraction and Its Impact on the Immunity of Caenorhabditis elegans

Cronobacter sakazakii, an opportunistic foodborne pathogen prevalently detected in contaminated powdered infant formula, is associated with different diseases, including meningitis. It can cross the blood-brain barrier and affects the CNS. The impact of C. sakazakii on host neuronal cells and behavior is largely unknown. Hence, detailed molecular data are required to understand its severity. Caenorhabditis elegans is a unique model for studying chemical communication, as it relies on chemosensation for searching nutritional supplements. Although, C. sakazakii is pathogenic to C. elegans, our analysis indicated that C. elegans was highly attracted toward C. sakazakii compared to its food source, E. coli OP50. To study the cue for the attraction, bioactive components (RNA/Protein/Lipopolysaccharides/Metabolites) of C. sakazakii were isolated and used for observing the chemotaxis behavior of C. elegans. The results signified that C. elegans was more attracted toward acid extracted metabolites than those of the other extraction methods. The combined action of acid extracted metabolites of C. sakazakii and a candidate pathogen drastically reduced the survival of C. elegans. In addition, qPCR analysis suggested that the exposure of isolated metabolites through acid extraction to C. elegans for 24 h modified the candidate immune regulatory genes involved in pathogen recognition and kinase activity such as clec-60, clec-87, lys-7, akt-2, pkc-1, and jnk-1.

Metabolomics and modelling approaches for systems metabolic engineering

Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts.

Striving for sustainable biosynthesis: discovery, diversification, and production of antimicrobial drugs in Escherichia coli

New antimicrobials need to be discovered to fight the advance of multidrug-resistant pathogens. A promising approach is the screening for antimicrobial agents naturally produced by living organisms. As an alternative to studying the native producer, it is possible to use genetically tractable microbes as heterologous hosts to aid the discovery process, facilitate product diversification through genetic engineering, and ultimately enable environmentally friendly production. In this mini-review, we summarize the literature from 2017 to 2022 on the application of Escherichia coli and E. coli-based platforms as versatile and powerful systems for the discovery, characterization, and sustainable production of antimicrobials. We highlight recent developments in high-throughput screening methods and genetic engineering approaches that build on the strengths of E. coli as an expression host and that led to the production of antimicrobial compounds. In the last section, we briefly discuss new techniques that have not been applied to discover or engineer antimicrobials yet, but that may be useful for this application in the future.

Overexpression of bacteriophage T4 and T7 endolysins differentially regulate the metabolic fingerprint of host Escherichia coli

Bioactive proteins are often overexpressed in different host systems for biotechnological/biomedical applications. Endolysins are natural bactericidal proteins that cleave the bacterial peptidoglycan membrane, and have the potential to be the next-generation enzybiotics. Therefore, the present study aims to elucidate the impact of two endolysins (T4L, T7L) overexpression on metabolic fingerprint of E. coli using NMR spectroscopy. The ¹H NMR-based metabolomics analysis revealed global metabolite profiles of E. coli in response to endolysins. The study has identified nearly 75 metabolites, including organic acids, amino acids, sugars and nucleic acids. RNA Polymerase (RNAP) has been considered as reference protein for marking the specific alterations in metabolic pathways. The data suggested downregulation of central carbon metabolic pathway in both endolysins overexpression, but to a different extent. Also, the endolysin overexpression have highlighted the enhanced metabolic load and stress generation in the host cells, thus leading to the activation of osmoregulatory pathways. The overall changes in metabolic fingerprint of E. coli highlights the enhanced perturbations during the overexpression of T4L as compared to T7L. These untargeted metabolic studies shed light on the regulation of molecular pathways during the heterologous overexpression of these lytic enzymes that are lethal to the host.

Evaluation and optimization of analytical procedure and sample preparation for polar Streptomyces albus J1074 metabolome profiling

Metabolomics is an essential discipline in omics technology that promotes research on the biology of microbial systems. Streptomyces albus J1074 is a model organism used in fundamental research and industrial microbiology. Nevertheless, a comprehensive and standardized method for analyzing the metabolome of S. albus J1074 is yet to be developed. Thus, we comprehensively evaluated and optimized the analytical procedure and sample preparation for profiling polar metabolites using hydrophilic interaction liquid chromatography (HILIC) coupled with high-resolution mass spectrometry (HRMS). We systematically examined the HILIC columns, quenching solutions, sample-to-quenching ratios, and extraction methods. Then, the optimal protocol was used to investigate the dynamic intracellular polar metabolite profile of the engineered S. albus J1074 strains during spinosad (spinosyn A and spinosyn D) fermentation. A total of 3648 compounds were detected, and 83 metabolites were matched to the standards. The intracellular metabolomic profiles of engineered S. albus J1074 strains (ADE-AP and OE3) were detected; furthermore, their metabolomes in different stages were analyzed to reveal the reasons for their differences in their spinosad production, as well as the current metabolic limitation of heterologous spinosad production in S. albus J1074. The HILIC-HRMS method is a valuable tool for investigating polar metabolomes, and provides a reference methodology to study other Streptomyces metabolomes.

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A HILIC-HRMS method was developed for polar metabolome profiling.

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Sample preparation protocol for Streptomyces albus J1074 intracellular metabolites was studied for the first time.

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This study revealed the possible reasons for different production of spinosad of engineered S. albus J1074 strains.

A targeted metabolomics method for extra- and intracellular metabolite quantification covering the complete monolignol and lignan synthesis pathway

Microbial synthesis of monolignols and lignans from simple substrates is a promising alternative to plant extraction. Bottlenecks and byproduct formation during heterologous production require targeted metabolomics tools for pathway optimization.

In contrast to available fractional methods, we established a comprehensive targeted metabolomics method. It enables the quantification of 17 extra- and intracellular metabolites of the monolignol and lignan pathway, ranging from amino acids to pluviatolide. Several cell disruption methods were compared. Hot water extraction was best suited regarding monolignol and lignan stability as well as extraction efficacy. The method was applied to compare enzymes for alleviating bottlenecks during heterologous monolignol and lignan production in E. coli. Variants of tyrosine ammonia-lyase had a considerable influence on titers of subsequent metabolites. The choice of multicopper oxidase greatly affected the accumulation of lignans. Metabolite titers were monitored during batch fermentation of either monolignol or lignan-producing recombinant E. coli strains, demonstrating the dynamic accumulation of metabolites.

The new method enables efficient time-resolved targeted metabolomics of monolignol- and lignan-producing E. coli. It facilitates bottleneck identification and byproduct quantification, making it a valuable tool for further pathway engineering studies. This method will benefit the bioprocess development of biotransformation or fermentation approaches for microbial lignan production.

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Monolignols and lignans were heterologously produced in Escherichia coli

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A targeted metabolomics method was developed covering 17 out of 20 metabolites.

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Hot water extraction is well suited for intracellular monolignol & lignan analysis.

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Metabolite accumulation identifies bottlenecks and dynamic activity.

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Assessment of pathway activity enables efficient cell factory engineering.

Recent Advances in Microscale Electroporation

Electroporation (EP) is a commonly used strategy to increase cell permeability for intracellular cargo delivery or irreversible cell membrane disruption using electric fields. In recent years, EP performance has been improved by shrinking electrodes and device structures to the microscale. Integration with microfluidics has led to the design of devices performing static EP, where cells are fixed in a defined region, or continuous EP, where cells constantly pass through the device. Each device type performs superior to conventional, macroscale EP devices while providing additional advantages in precision manipulation (static EP) and increased throughput (continuous EP). Microscale EP is gentle on cells and has enabled more sensitive assaying of cells with novel applications. In this Review, we present the physical principles of microscale EP devices and examine design trends in recent years. In addition, we discuss the use of reversible and irreversible EP in the development of therapeutics and analysis of intracellular contents, among other noteworthy applications. This Review aims to inform and encourage scientists and engineers to expand the use of efficient and versatile microscale EP technologies.

Combined roles of exporters in acetic acid tolerance in Saccharomyces cerevisiae

Acetic acid is a growth inhibitor generated during alcoholic fermentation and pretreatment of lignocellulosic biomass, a major feedstock to produce bioethanol. An understanding of the acetic acid tolerance mechanisms is pivotal for the industrial production of bioethanol. One of the mechanisms for acetic acid tolerance is transporter-mediated secretion where individual transporters have been implicated. Here, we deleted the transporters Aqr1, Tpo2, and Tpo3, in various combinations, to investigate their combined role in acetic acid tolerance. Single transporter deletions did not impact the tolerance at mild acetic acid stress (20 mM), but at severe stress (50 mM) growth was decreased or impaired. Tpo2 plays a crucial role in acetic acid tolerance, while the AQR1 deletion has a least effect on growth and acetate efflux. Deletion of both Tpo2 and Tpo3 enhanced the severe growth defects at 20 mM acetic acid concomitantly with a reduced rate of acetate secretion, while TPO2 and/or TPO3 overexpression in ∆tpo2∆tpo3∆ restored the tolerance. In the deletion strains, the acetate derived from sugar metabolism accumulated intracellularly, while gene transcription analysis suggests that under these conditions, ethanol metabolism is activated while acetic acid production is reduced. The data demonstrate that Tpo2 and Tpo3 together fulfill an important role in acetate efflux and the acetic acid response.

Metagenomics: A Tool for Exploring Key Microbiome With the Potentials for Improving Sustainable Agriculture

Microorganisms are immense in nature and exist in every imaginable ecological niche, performing a wide range of metabolic processes. Unfortunately, using traditional microbiological methods, most microorganisms remain unculturable. The emergence of metagenomics has resolved the challenge of capturing the entire microbial community in an environmental sample by enabling the analysis of whole genomes without requiring culturing. Metagenomics as a non-culture approach encompasses a greater amount of genetic information than traditional approaches. The plant root-associated microbial community is essential for plant growth and development, hence the interactions between microorganisms, soil, and plants is essential to understand and improve crop yields in rural and urban agriculture. Although some of these microorganisms are currently unculturable in the laboratory, metagenomic techniques may nevertheless be used to identify the microorganisms and their functional traits. A detailed understanding of these organisms and their interactions should facilitate an improvement of plant growth and sustainable crop production in soil and soilless agriculture. Therefore, the objective of this review is to provide insights into metagenomic techniques to study plant root-associated microbiota and microbial ecology. In addition, the different DNA-based techniques and their role in elaborating plant microbiomes are discussed. As an understanding of these microorganisms and their biotechnological potentials are unlocked through metagenomics, they can be used to develop new, useful and unique bio-fertilizers and bio-pesticides that are not harmful to the environment.

Hot isopropanol quenching procedure for automated microtiter plate scale 13C-labeling experiments

Background

Currently, the generation of genetic diversity for microbial cell factories outpaces the screening of strain variants with omics-based phenotyping methods. Especially isotopic labeling experiments, which constitute techniques aimed at elucidating cellular phenotypes and supporting rational strain design by growing microorganisms on substrates enriched with heavy isotopes, suffer from comparably low throughput and the high cost of labeled substrates.

Results

We present a miniaturized, parallelized, and automated approach to ¹³C-isotopic labeling experiments by establishing and validating a hot isopropanol quenching method on a robotic platform coupled with a microbioreactor cultivation system. This allows for the first time to conduct automated labeling experiments at a microtiter plate scale in up to 48 parallel batches. A further innovation enabled by the automated quenching method is the analysis of free amino acids instead of proteinogenic ones on said microliter scale. Capitalizing on the latter point and as a proof of concept, we present an isotopically instationary labeling experiment in Corynebacterium glutamicum ATCC 13032, generating dynamic labeling data of free amino acids in the process.

Conclusions

Our results show that a robotic liquid handler is sufficiently fast to generate informative isotopically transient labeling data. Furthermore, the amount of biomass obtained from a sub-milliliter cultivation in a microbioreactor is adequate for the detection of labeling patterns of free amino acids. Combining the innovations presented in this study, isotopically stationary and instationary automated labeling experiments can be conducted, thus fulfilling the prerequisites for ¹³C-metabolic flux analyses in high-throughput.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01806-4.

Bacterial Metabolomics: Sample Preparation Methods

Metabolomics is a comprehensive analysis of metabolites existing in biological systems. As one of the important "omics" tools, the approach has been widely employed in various fields in helping to better understand the complex cellular metabolic states and changes. Bacterial metabolomics has gained a significant interest as bacteria serve to provide a better subject or model at systems level. The approach in metabolomics is categorized into untargeted and targeted which serves different paradigms of interest. Nevertheless, the bottleneck in metabolomics has been the sample or metabolite preparation method. A custom-made method and design for a particular species or strain of bacteria might be necessary as most studies generally refer to other bacteria or even yeast and fungi that may lead to unreliable analysis. The paramount aspect of metabolomics design comprises sample harvesting, quenching, and metabolite extraction procedures. Depending on the type of samples and research objective, each step must be at optimal conditions which are significantly important in determining the final output. To date, there are no standardized nor single designated protocols that have been established for a specific bacteria strain for untargeted and targeted approaches. In this paper, the existing and current developments of sample preparation methods of bacterial metabolomics used in both approaches are reviewed. The review also highlights previous literature of optimized conditions used to propose the most ideal methods for metabolite preparation, particularly for bacterial cells. Advantages and limitations of methods are discussed for future improvement of bacterial metabolomics.

Luciferase-Based Determination of ATP/NAD(H) Pools in a Marine (Environmental) Bacterium

In all living organisms, adenosine triphosphate (ATP) and NAD(H) represent universal molecular currencies for energy and redox state, respectively, and are thus widely applicable molecular proxies for an organism's viability and activity. To this end, corresponding luciferase-based assays in combination with a microplate reader were established with the marine model bacterium Phaeobacter inhibens DSM 17395 (Escherichia coli K12 served as reference). Grey multiwell plates best balanced sensitivity and crosstalk, and optimal incubation times were 5 min and 30 min for the ATP and NAD(H) assay, respectively, together allowing limits of detection of 0.042, 0.470 and 0.710 nM for ATP, NAD+, and NADH, respectively. Quenching of bacterial cell samples involved Tris-EDTA-DTAB and bicarbonate base-DTAB for ATP and NAD(H) assays, respectively. The ATP and NAD(H) yields determined for P. inhibens DSM 17395 at ¼ ODmax were found to reside well within the range previously reported for E. coli and other bacteria, e.g., 3.28 µmol ATP (g cellsdry)-1. Thus, the here described methods for luciferase-based determination of ATP/NAD(H) pools open a promising approach to investigate energy and redox states in marine (environmental) bacteria.

Unraveling antimicrobial resistance using metabolomics

The emergence of antimicrobial resistance (AMR) in bacterial pathogens represents a global health threat. The metabolic state of bacteria is associated with a range of genetic and phenotypic resistance mechanisms. This review provides an overview of the roles of metabolic processes that are associated with AMR mechanisms, including energy production, cell wall synthesis, cell-cell communication, and bacterial growth. These metabolic processes can be targeted with the aim of re-sensitizing resistant pathogens to antibiotic treatments. We discuss how state-of-the-art metabolomics approaches can be used for comprehensive analysis of microbial AMR-related metabolism, which may facilitate the discovery of novel drug targets and treatment strategies. TEASER: Novel treatment strategies are needed to address the emerging threat of antimicrobial resistance (AMR) in bacterial pathogens. Metabolomics approaches may help to unravel the biochemical underpinnings of AMR, thereby facilitating the discovery of metabolism-associated drug targets and treatment strategies.

Trypanosoma brucei: Metabolomics for analysis of cellular metabolism and drug discovery

BACKGROUND

Trypanosoma brucei is the causative agent of Human African Trypanosomiasis (also known as sleeping sickness), a disease causing serious neurological disorders and fatal if left untreated. Due to its lethal pathogenicity, a variety of treatments have been developed over the years, but which have some important limitations such as acute toxicity and parasite resistance. Metabolomics is an innovative tool used to better understand the parasite's cellular metabolism, and identify new potential targets, modes of action and resistance mechanisms. The metabolomic approach is mainly associated with robust analytical techniques, such as NMR and Mass Spectrometry. Applying these tools to the trypanosome parasite is, thus, useful for providing new insights into the sleeping sickness pathology and guidance towards innovative treatments.

AIM OF REVIEW

The present review aims to comprehensively describe the T. brucei biology and identify targets for new or commercialized antitrypanosomal drugs. Recent metabolomic applications to provide a deeper knowledge about the mechanisms of action of drugs or potential drugs against T. brucei are highlighted. Additionally, the advantages of metabolomics, alone or combined with other methods, are discussed.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Compared to other parasites, only few studies employing metabolomics have to date been reported on Trypanosoma brucei. Published metabolic studies, treatments and modes of action are discussed. The main interest is to evaluate the metabolomics contribution to the understanding of T. brucei's metabolism.

Metabolic Responses of "Big Six" Escherichia coli in Wheat Flour to Thermal Treatment Revealed by Nuclear Magnetic Resonance Spectroscopy

Escherichia coli outbreaks linked to wheat flour consumption have kept emerging in recent years, which necessitated an antimicrobial step being incorporated into the flour production process. The objectives of this in vivo study were to holistically evaluate the sanitizing efficacy of thermal treatment at 60 and 70°C against the "big six" E. coli strains (O26:H11, O45:H2, O103:H11, O111, O121:H19, and O145) in wheat flour and to assess the strain-specific metabolic responses using nuclear magnetic resonance (NMR) spectroscopy. The 70°C treatment temperature indiscriminatingly inactivated all strains by over 4.3-log CFU/g within 20 min, suggesting the high sanitization effectiveness of this treatment temperature, whereas the treatment at 60°C inactivated the strains to various degrees during the 1-h process. The most resistant strains at 60°C, O26 and O45, were characterized by amino acid and sugar depletion, and their high resistance was attributed to the dual effects of activated heat shock protein (HSP) synthesis and promoted glycolysis. O121 also demonstrated these metabolic changes, yet its thermal resistance was largely impaired by the weakened membrane structure and diminished osmotic protection due to phosphorylcholine exhaustion. In contrast, O111, O145, and O103 presented a substantial elevation of metabolites after stress at 60°C; their moderate thermal resistance was mainly explained by the accumulation of amino acids as osmolytes. Overall, the study enhanced our understanding of the metabolic responses of big six E. coli to heat stress and provided a model for conducting NMR-based metabolomic studies in powdered food matrices. IMPORTANCE "Big six" Escherichia coli strains have caused several outbreaks linked to wheat flour consumption in the last decade, revealing the vital importance of adopting an antimicrobial treatment during the flour production process. Therefore, the present study was carried out to evaluate the efficacy of a typical sanitizing approach, thermal treatment, against the big six strains in wheat flour along with the underlying antimicrobial mechanisms. Findings showed that thermal treatment at 60 and 70°C could markedly mitigate the loads of all strains in wheat flour. Moreover, activated heat shock protein synthesis combined with expedited glycolysis and enhanced osmotic protection were identified as two major metabolic alteration patterns in the E. coli strains to cope with the heat stress. With the responses of big six in wheat flour to thermal treatment elucidated, scientific basis for incorporating a thermal inactivation step in wheat flour production was provided.

Precursor Quantitation Methods for Next Generation Food Production

Food is essential for human survival. Nowadays, traditional agriculture faces challenges in balancing the need of sustainable environmental development and the rising food demand caused by an increasing population. In addition, in the emerging of consumers' awareness of health related issues bring a growing trend towards novel nature-based food additives. Synthetic biology, using engineered microbial cell factories for production of various molecules, shows great advantages for generating food alternatives and additives, which not only relieve the pressure laid on tradition agriculture, but also create a new stage in healthy and sustainable food supplement. The biosynthesis of food components (protein, fats, carbohydrates or vitamins) in engineered microbial cells often involves cellular central metabolic pathways, where common precursors are processed into different proteins and products. Quantitation of the precursors provides information of the metabolic flux and intracellular metabolic state, giving guidance for precise pathway engineering. In this review, we summarized the quantitation methods for most cellular biosynthetic precursors, including energy molecules and co-factors involved in redox-reactions. It will also be useful for studies worked on pathway engineering of other microbial-derived metabolites. Finally, advantages and limitations of each method are discussed.

Antimicrobial, Antibiofilm, and Antioxidant Properties of Boletus edulis and Neoboletus luridiformis Against Multidrug-Resistant ESKAPE Pathogens

Multidrug-resistant ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) has become the most recurrent global cause of skin and soft-tissue infections, belonging to the WHO priority pathogens list. Successful therapy remains challenging and entails the assessment of novel and successful antibiotics. In this study, mushrooms are considered a valuable and unique source of natural antimicrobial compounds. Therefore, this study aimed to evaluate the antimicrobial and antibiofilm properties of Boletus edulis (B. edulis) and Neoboletus luridiformis (N. luridiformis) aqueous and methanolic extracts against ESKAPE isolates from clinical wound infections. Disk diffusion and microdilution methods were used to assess the antimicrobial activity. Phytochemical characterization was achieved by analysis of total phenols, orthodiphenols content, and antioxidant activity as well as by high-performance liquid chromatography-diode array detector (HPLC-DAD). Human foreskin fibroblasts-1 (HFF-1) cell viability was performed by the MTT assay. Aqueous and methanolic extracts of B. edulis and N. luridiformis showed antimicrobial and antibiofilm properties against multidrug-resistant bacteria, although with different efficacy rates. The results showed that there is a convincing relation between the content of phenolic compounds, antioxidant activity, and antimicrobial activity suggesting that the presence of phenolic compounds may explain the biological effects. HPLC analysis revealed high levels of protocatechuic acid, homogentisic acid, pyrogallol, gallic acid, p-catechin, and dihydroxybenzoic acid in the aqueous extract of B. edulis, explaining the highest antimicrobial and antibiofilm properties. Importantly, the mushrooms extracts were non-cytotoxic at all the tested concentrations. Overall, the tested mushrooms extracts are good candidates to further explore its use in the prevention of wound infection, particularly by multidrug-resistant pathogens.

Metabolic Potential of Epichloë Endophytes for Host Grass Fungal Disease Resistance

Asexual species of the genus Epichloë (Clavicipitaceae, Ascomycota) form endosymbiotic associations with Pooidae grasses. This association is important both ecologically and to the pasture and turf industries, as the endophytic fungi confer a multitude of benefits to their host plant that improve competitive ability and performance such as growth promotion, abiotic stress tolerance, pest deterrence and increased host disease resistance. Biotic stress tolerance conferred by the production of bioprotective metabolites has a critical role in an industry context. While the known antimammalian and insecticidal toxins are well characterized due to their impact on livestock welfare, antimicrobial metabolites are less studied. Both pasture and turf grasses are challenged by many phytopathogenic diseases that result in significant economic losses and impact livestock health. Further investigations of Epichloë endophytes as natural biocontrol agents can be conducted on strains that are safe for animals. With the additional benefits of possessing host disease resistance, these strains would increase their commercial importance. Field reports have indicated that pasture grasses associated with Epichloë endophytes are superior in resisting fungal pathogens. However, only a few antifungal compounds have been identified and chemically characterized, and these from sexual (pathogenic) Epichloë species, rather than those utilized to enhance performance in turf and pasture industries. This review provides insight into the various strategies reported in identifying antifungal activity from Epichloë endophytes and, where described, the associated antifungal metabolites responsible for the activity.

Untargeted Microbial Exometabolomics and Metabolomics Analysis of Helicobacter pylori J99 and jhp0106 Mutant

Untargeted metabolomic profiling provides the opportunity to comprehensively explore metabolites of interest. Herein, we investigated the metabolic pathways associated with Jhp0106, a glycosyltransferase enzyme in Helicobacter pylori. Through untargeted exometabolomic and metabolomic profiling, we identified 9 and 10 features with significant differences in the culture media and pellets of the wild-type (WT) J99 and jhp0106 mutant (Δjhp0106). After tentative identification, several phosphatidylethanolamines (PEs) were identified in the culture medium, the levels of which were significantly higher in WT J99 than in Δjhp0106. Moreover, the reduced lysophosphatidic acid absorption from the culture medium and the reduced intrinsic diacylglycerol levels observed in Δjhp0106 indicate the possibility of reduced PE synthesis in Δjhp0106. The results suggest an association of the PE synthesis pathway with flagellar formation in H. pylori. Further investigations should be conducted to confirm this finding and the roles of the PE synthesis pathway in flagellar formation. This study successfully demonstrates the feasibility of the proposed extraction procedure and untargeted exometabolomic and metabolomic profiling strategies for microbial metabolomics. They may also extend our understanding of metabolic pathways associated with flagellar formation in H. pylori.

Qualitative and Quantitative Comparison of Liquid–Liquid Phase Extraction Using Ethyl Acetate and Liquid–Solid Phase Extraction Using Poly-Benzyl-Resin for Natural Products

A key step in the process of isolating microbial natural products is the preparation of an extract from a culture. This step determines which molecules will be available for detection in the subsequent chemical and biological analysis of a biodiscovery pipeline. In the present study we wanted to document potential differences in performance between liquid–liquid extraction using ethyl acetate and liquid–solid extraction using a poly-benzyl-resin. For the comparison of the two extraction protocols, we spiked a culture of Flavobacterium sp. with a diverse selection of natural products of microbial and plant origin to investigate whether the methods were comparable with respect to selectivity. We also investigated the efficiency of the two extraction methods quantitatively, using water spiked with a selection of natural products, and studied the quantitative effect of different pH levels of the aqueous solutions on the extraction yields of the two methods. The same compounds were extracted by the two methods, but the solid-phase extract contained more media components compared with the liquid-phase extract. Quantitatively, the two extraction methods varied in their recovery rates. We conclude that practical aspects could be more important when selecting one of the extraction protocols, as their efficiencies in extracting specific compounds were quite similar.