Pseudomonas aeruginosa commonly infects immunocompromised patients, including those with cystic fibrosis (CF). These infections are difficult to treat due to a variety of factors including the ability of Pseudomonas aeruginosa to resist to antibiotic treatment in part due to formation of biofilms. D-amino acids have known biofilm-disruption and antibacterial properties in some bacteria including P. aeruginosa. However, this treatment remains underexplored especially for inhibiting biofilm biomass production under CF environments. We explore the effects of six individual D-amino acids (alanine, aspartic acid, tyrosine, glutamic acid, serine, and proline) on the quorum sensing signaling and biofilm biomass production of two strains: PAO1 and the CF isolate FRD1. The D-amino acid causing the most significant decrease in biofilm mass and a decrease in quorum sensing molecules was D-aspartic acid. Meanwhile D-glutamic acid and D-serine had the opposite effects with an increase in biofilm mass and increase in quorum sensing molecule abundance. D-proline also showed a decrease in quorum sensing signaling with a decrease in biofilm biomass. P. aeruginosa had a lower or delayed quorum sensing response in the presence of D-aspartic acid and the absence of its L- counterpart at 48 h, a potential therapeutic route to explore.

Gestational diabetes mellitus (GDM), a common pregnancy-related metabolic disorder, often goes undiagnosed until the second trimester, limiting early intervention opportunities. Given the higher prevalence of GDM in India, there is a critical need to investigate metabolomic biomarkers among Asian Indians, who exhibit greater insulin resistance and are predisposed to developing type 2 diabetes at an earlier age. This study aimed to identify early pregnancy metabolomic signatures predictive of GDM. Among 2115 pregnant women from the STratification of Risk of Diabetes in Early pregnancy (STRiDE) study, we performed untargeted metabolomic profiling using UPLC-MS/MS at early pregnancy (< 16 weeks) plasma samples from 100 women—comprising 50 with GDM and 50 normal (without GDM) based on oral glucose tolerance test (OGTT) at 24–28 weeks. Statistical and machine learning approaches, including logistic regression and random forest (RF), were applied to identify GDM-associated metabolites and construct predictive models. Pathway enrichment analysis was conducted using KEGG database annotations. A total of 49 metabolites were significantly associated with GDM, primarily involving lipid classes such as phosphatidylcholines, sphingomyelins, and triacylglycerols. RF analysis identified a panel of eight metabolites that achieved best predictive performance (AUC 0.880; 95

Atmospheric pressure matrix-assisted laser desorption/ionization (AP/MALDI) mass spectrometry (MS) allows for highly sensitive and specific detection and relative quantification of metabolites of interest, with the key benefit of minimal sample preparation requirements for complex biological samples such as bacteria. Violacein is a violet-colored pigment produced by the bacterium Chromobacterium violaceum. In this chapter, we detail a high-throughput, high-resolution (HR) MS-based, targeted metabolite profiling protocol for analyzing violacein and its intermediates directly from bacterial colonies. This technique applies to a wide range of metabolites regulated by operon control and is suitable for a molecular phenotyping platform.

BACKGROUND AND AIMS:Obesity has reached epidemic proportions, emphasizing the importance of reliable biomarkers for detecting early metabolic alterations and enabling early preventative interventions. However, our understanding of the molecular mechanisms and specific lipid species associated with childhood obesity remains limited. Therefore, the aim of this study was to investigate plasma lipidomic signatures as potential biomarkers for adolescent obesity. METHODS AND RESULTS:A total of 103 individuals comprising overweight/obese (n = 46) and normal weight (n = 57) were randomly chosen from the baseline ORANGE (Obesity Reduction and Noncommunicable Disease Awareness through Group Education) cohort, having been followed up for a median of 7.1 years. Plasma lipidomic profiling was performed using the UHPLC-HRMS method. We used three different models adjusted for clinical covariates to analyze the data. Clustering methods were used to define metabotypes, which allowed for the stratification of subjects into subgroups with similar clinical and metabolic profiles. We observed that lysophosphatidylcholine (LPC) species like LPC.16.0, LPC.18.3, LPC.18.1, and LPC.20.3 were significantly (p < 0.05) associated with baseline and follow-up BMI in adolescent obesity. The association of LPC species with BMI remained consistently significant even after adjusting for potential confounders. Moreover, applying metabotyping using hierarchical clustering provided insights into the metabolic heterogeneity within the normal and obese groups, distinguishing metabolically healthy individuals from those with unhealthy metabolic profiles. CONCLUSION:The specific LPC levels were found to be altered and increased in childhood obesity, particularly during the follow-up. These findings suggest that LPC species hold promise as potential biomarkers of obesity in adolescents, including healthy and unhealthy metabolic profiles.

Biofilms are dense aggregates of bacterial colonies embedded inside a self-produced polymeric matrix. Biofilms have received increasing attention in medical, industrial, and environmental settings due to their enhanced survival. Their characterization using microscopy techniques has revealed the presence of structural and cellular heterogeneity in many bacterial systems. However, these techniques provide limited chemical detail and lack information about the molecules important for bacterial communication and virulence. Mass spectrometry imaging (MSI) bridges the gap by generating spatial chemical information with unmatched chemical detail, making it an irreplaceable analytical platform in the multi-modal imaging of biofilms. In the last two decades, over 30 species of biofilm-forming bacteria have been studied using MSI in different environments. The literature conveys both analytical advancements and an improved understanding of the effects of environmental variables such as host surface characteristics, antibiotics, and other species of microorganisms on biofilms. This review summarizes the insights from frequently studied model microorganisms. We share a detailed list of organism-wide metabolites, commonly observed mass spectral adducts, culture conditions, strains of bacteria, substrate, broad problem definition, and details of the MS instrumentation, such as ionization sources and matrix, to facilitate future studies. We also compared the spatial characteristics of the secretome under different study designs to highlight changes because of various environmental influences. In addition, we highlight the current limitations of MSI in relation to biofilm characterization to enable cross-comparison between experiments. Overall, MSI has emerged to become an important approach for the spatial/chemical characterization of bacterial biofilms and its use will continue to grow as MSI becomes more accessible.

ABSTRACT The bacterium Pseudomonas aeruginosa is an opportunistic pathogen that can cause lung, skin, wound, joint, urinary tract, and eye infections. While P. aeruginosa is known to exhibit a robust competitive response toward other bacterial species, this bacterium is frequently identified in polymicrobial infections where multiple species survive. For example, in prosthetic joint infections, P. aeruginosa can be identified along with other pathogenic bacteria including Staphylococcus aureus , Enterococcus faecalis , and Corynebacterium striatum . Here, we have explored the survival and behavior of such microbes and find that E. faecalis readily survives culturing with P. aeruginosa while other tested species do not. In each of the tested conditions, E. faecalis growth remained unchanged by the presence of P. aeruginosa , indicating a unique mutualistic interaction between the two species. We find that E. faecalis proximity leads P. aeruginosa to attenuate competitive behaviors as exemplified by reduced production of Pseudomonas quinolone signal and pyocyanin. Reduced alkyl quinolones are important to E. faecalis as these will grow in supernatant from a quinolone mutant but not P. aeruginosa wild-type in planktonic culture. The reduced pyocyanin production of P. aeruginosa is attributable to production of ornithine by E. faecalis , which we recapitulate by adding exogenous ornithine to P. aeruginosa monocultures. Similarly, co-culture with an ornithine-deficient strain of E. faecalis leads P. aeruginosa to yield near monoculture amounts of pyocyanin. Here, we directly demonstrate how notorious pathogens such as P. aeruginosa might persist in polymicrobial infections under the influence of metabolites produced by other bacterial species. IMPORTANCE While we now appreciate that many infections are polymicrobial, we understand little of the specific actions between a given set of microbes to enable combinatorial survival and pathogenesis. The bacteria Pseudomonas aeruginosa and Enterococcus faecalis are both prevalent pathogens in wound, urinary tract, and bacteremic infections. While P. aeruginosa often kills other species in standard laboratory culture conditions, we present here that E. faecalis can be reliably co-cultured with P. aeruginosa . We specifically detail that ornithine produced by E. faecalis reduces the Pseudomonas quinolone signal response of P. aeruginosa . This reduction of the Pseudomonas quinolone signal response aids E. faecalis growth.

Pseudomonas aeruginosa (P. aeruginosa) is commonly implicated in hospital-acquired infections where its capacity to form biofilms on a variety of surfaces and the resulting enhanced antibiotic resistance seriously limit treatment choices. Because surface attachment sensitizes P. aeruginosa to quorum sensing (QS) and induces virulence through both chemical and mechanical cues, we investigate the effect of surface properties through spatially patterned mucin, combined with sub-inhibitory concentrations of tobramycin on QS and virulence factors in both mucoid and non-mucoid P. aeruginosa strains using multi-modal chemical imaging combining confocal Raman microscopy and matrix-assisted laser desorption/ionization-mass spectrometry. Samples comprise surface-adherent static biofilms at a solid-water interface, supernatant liquid, and pellicle biofilms at an air-water interface at various time points. Although the presence of a sub-inhibitory concentration of tobramycin in the supernatant retards growth and development of static biofilms independent of strain and surface mucin patterning, we observe clear differences in the behavior of mucoid and non-mucoid strains. Quinolone signals in a non-mucoid strain are induced earlier and are influenced by mucin surface patterning to a degree not exhibited in the mucoid strain. Additionally, phenazine virulence factors, such as pyocyanin, are observed in the pellicle biofilms of both mucoid and non-mucoid strains but are not detected in the static biofilms from either strain, highlighting the differences in stress response between pellicle and static biofilms. Differences between mucoid and non-mucoid strains are consistent with their strain-specific phenology, in which the mucoid strain develops highly protected biofilms.

Rhamnolipids are surfactants produced by many Pseudomonad bacteria, including the species Pseudomonas aeruginosa. These rhamnolipids are known to aid and enable numerous phenotypic traits that improve the survival of the bacteria that make them. These surfactants are also important for industrial products ranging from pharmaceuticals to cleaning supplies to cosmetics, to name a few. Rhamnolipids have structural diversity that leads to an array of congeners; however, little is known about the localization and distribution of these congeners in two-dimensional space. Differential distribution of congeners can reduce the uniformity of applications in industrial settings and create heterogeneity within biological communities. We examined the distribution patterns of combinations of rhamnolipids in commercially available mixtures, cell-free spent media, and colony biofilms using mass spectrometry. We found that even in the absence of cells, congeners exhibit different distribution patterns, leading to different rhamnolipid congener distributions on a surface. Congeners with shorter fatty acid chains were more centrally located, while longer chains were more heterogeneous and distally located. We found that congeners with similar structures can distribute differently. Within developing colony biofilms, we found rhamnolipid distribution patterns differed from cell-free environments, lacking simple trends noted in cell-free environments. Most strikingly, we found the distribution patterns of individual congeners in the colony biofilms to be diverse. We note that the congener distribution is far from homogeneous but composed of numerous local microenvironments of varied rhamnolipid congener composition.

Metabolic reprogramming and its molecular underpinnings are critical to unravel the duality of cancer cell function and chemo-resistance. Here, we use a constraints-based integrated approach to delineate the interplay between metabolism and epigenetics, hardwired in the genome, to shape temozolomide (TMZ) resistance. Differential metabolism was identified in response to TMZ at varying concentrations in both the resistant neurospheroidal (NSP) and the susceptible (U87MG) glioblastoma cell-lines. The genetic basis of this metabolic adaptation was characterized by whole exome sequencing that identified mutations in signaling pathway regulators of growth and energy metabolism. Remarkably, our integrated approach identified rewiring in glycolysis, TCA cycle, malate aspartate shunt, and oxidative phosphorylation pathways. The differential killing of TMZ resistant NSP by Rotenone at low concentrations with an IC 50 value of 5 nM, three orders of magnitude lower than for U87MG that exhibited an IC 50 value of 1.8 mM was thus identified using our integrated systems-based approach.

There is an increased interest in using high-resolution mass spectrometry (HRMS) in the full scan mode (FS) for simultaneous qualitative and quantitative analysis with accurate mass based extracted ion chromatograms (HRMS-AM) for metabolomic profiling workflows. Herein, the capabilities and features of ‘MQ’, a common platform developed to support quantitative analysis from HRMS data are described. Module for qualitative annotation utilizes peak features that include mass accuracy, peak width, and relative abundance of isotopic distribution that offer reliable metabolic confirmation. Additionally, MQ provides multivariate clustering with Principal Component Analysis and a module for high-throughput database query based on user configurable annotated metabolite lists. MQ is capable of handling system-agnostic data formats from both direct HRMS and LC-HRMS analysis. Data processed using MQ for LC-HRMS-AM quantitation of amino acids benchmarked using a commercial tool is presented that validates the quantitative capabilities of the algorithm developed. Datasets representative of three different HRMS-AM based analysis scenarios have been showcased to demonstrate the utility of MQ. Availability and implementation Freely available on web at, http://www.ldims.com/services/software . MQ is implemented in Java and supported on Linux and Microsoft Windows system having Java runtime environment (JRE) pre-installed.

Altered circulatory asymmetric and symmetric dimethylarginines have been independently reported in patients with end-stage renal failure suggesting their potential role as mediators and early biomarkers of nephropathy. These alterations can also be reflected in urine. Herein, we aimed to evaluate urinary asymmetric to symmetric dimethylarginine ratio (ASR) for early prediction of diabetic nephropathy (DN). In this cross-sectional study, individuals with impaired glucose tolerance (IGT), newly diagnosed diabetes (NDD), diabetic microalbuminuria (MIC), macroalbuminuria (MAC), and normal glucose tolerance (NGT) were recruited from Dr. Mohans’ Diabetes Specialties centre, India. Urinary ASR was measured using a validated high-throughput MALDI-MS/MS method. Significantly lower ASR was observed in MIC (0.909) and MAC (0.741) in comparison to the NGT and NDD groups. On regression models, ASR was associated with MIC [OR: 0.256; 95% CI: 0.158–0.491] and MAC [OR 0.146; 95% CI: 0.071–0.292] controlled for all the available confounding factors. ROC analysis revealed ASR cut-point of 0.95 had C-statistic of 0.691 (95% CI: 0.627-0.755) to discriminate MIC from NDD with 72% sensitivity. Whereas, an ASR cut-point of 0.82 had C-statistic of 0.846 (95% CI: 0.800 - 0.893) had 91% sensitivity for identifying MAC. Our results suggest ASR as a potential early diagnostic biomarker for DN among the Asian Indians.

Passaging and expansion of animal cells in lean maintenance medium could result in periods of limitation of some nutrients. Over time, such stresses could possibly result in selection of cells with metabolic changes and contribute to heterogeneity. Here, we investigate whether selection of Chinese Hamster Ovary (CHO) cells under glutamine limitation results in changes in growth under glutamine-replete conditions. In glutamine-limiting medium, compared to control cells passaged in glutamine-rich medium, the selected cells showed higher glutamine synthetase (GS) activity and attained a higher peak viable cell density (PVCD). Surprisingly, in glutamine-replete conditions, selected cells still showed a higher GS activity but a lower PVCD. We show that in glutamine-replete medium, PVCD of selected cells was restored on (a) inhibition of GS activity with methionine sulfoximine, (b) supplementation of aspartate-without affecting GS activity, and (c) supplementation of serine, which is reported to inhibit GS in vitro. Consistent with the reported effect of serine, inhibition of GS activity was observed upon serine supplementation along with reduced growth of cells under glutamine-limiting conditions. The latter observation is important for the design of glutamine-free culture medium and feed used for GS-CHO and GS-NS0. In summary, we show that CHO cells selected under glutamine limitation have superfluous GS activity in glutamine-replete medium, which negatively affects their PVCD. This may be due to its effect on availability of aspartate which was the limiting nutrient for the growth of selected cells in glutamine-replete conditions.

An authenticated U87MG clonal glioblastoma cell line was investigated to identify a sub-population of neurospheroidal (NSP) cells within the main epithelial population (U87MG). The NSP cells sorted using Fluorescence Assisted Cell Sorting (FACS) showed varied morphology, 30% lower growth rates, 40% higher IC50 values for temozolomide drug and could differentiate into the glial cell type (NDx). Metabolite profiling using HR-LCMS identified glucose, glutamine and serine in both populations and tryptophan only in U87MG as growth limiting substrates. Glycine, alanine, glutamate and proline were secreted by U87MG, however proline and glycine were re-utilized in NSP. Exo-metabolite profiling and phenotypic microarrays identified differential metabolism of primary carbon sources glucose and derived pyruvate for U87MG; glutamine and derived glutamate metabolism in NSP. Differential mRNA abundance of AKT1, PTEN, PIK3CA controlling metabolism, drug efflux, nutrient transport and epigenetic control MDM2 are potentially critical in shaping DNA methylation effects of temozolomide. Our study provides a new insight into the combined effect of these factors leading to temozolomide resistance in NSP.

Inorganic phosphate (Pi) is an essential ion involved in diverse cellular processes including metabolism. Changes in cellular metabolism upon long term adaptation to Pi limitation have been reported in E. coli. Given the essential role of Pi, adaptation to Pi limitation may also result in metabolic changes in animal cells. In this study, we have adapted CHO cells producing recombinant IgG to limiting Pi conditions for 75 days. Not surprisingly, adapted cells showed better survival under Pi limitation. Here, we report the finding that such cells also showed better growth characteristics compared to control in batch culture replete with Pi (higher peak density and integral viable cell density), accompanied by a lower specific oxygen uptake rate and cytochrome oxidase activity towards the end of exponential phase. Surprisingly, the adapted cells grew to a lower peak density under glucose limitation. This suggests long term Pi limitation may lead to selection for an altered metabolism with higher dependence on glucose availability for biomass assimilation compared to control. Steady state U‐13C glucose labeling experiments suggest that adapted cells have a higher pyruvate carboxylase flux. Consistent with this observation, supplementation with aspartate abolished the peak density difference whereas supplementation with serine did not abolish the difference. This supports the hypothesis that cell growth in the adapted culture might be higher due to a higher pyruvate carboxylase flux. Decreased fitness under carbon limitation and mutations in the sucABCD operon has been previously reported in E. coli upon long term adaptation to Pi limitation, suggestive of a similarity in cellular response among such diverse species. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:749–758, 2017

BACKGROUND:The leading edge of the global problem of antibiotic resistance necessitates novel therapeutic strategies. This study develops a novel systems biology driven approach for killing antibiotic resistant pathogens using benign metabolites.RESULTS:Controlled laboratory evolutions established chloramphenicol and streptomycin resistant pathogens of Chromobacterium. These resistant pathogens showed higher growth rates and required higher lethal doses of antibiotic. Growth and viability testing identified malate, maleate, succinate, pyruvate and oxoadipate as resensitising agents for antibiotic therapy. Resistant genes were catalogued through whole genome sequencing. Intracellular metabolomic profiling identified violacein as a potential biomarker for resistance. The temporal variance of metabolites captured the linearized dynamics around the steady state and correlated to growth rate. A constraints-based flux balance model of the core metabolism was used to predict the metabolic basis of antibiotic susceptibility and resistance.CONCLUSIONS:The model predicts electron imbalance and skewed NAD/NADH ratios as a result of antibiotics - chloramphenicol and streptomycin. The resistant pathogen rewired its metabolic networks to compensate for disruption of redox homeostasis. We foresee the utility of such scalable workflows in identifying metabolites for clinical isolates as inevitable solutions to mitigate antibiotic resistance.

Isomeric dimethylarginines are disease markers released from methylated proteins. A method to determine these from urine is described.