Molecular cartography in acute Chlamydia pneumoniae infections—a non-targeted metabolomics approach

An Overview of the Latest Metabolomics Studies on Atopic Eczema with New Directions for Study

Atopic eczema (AE) is an inflammatory skin disorder affecting approximately 20% of children worldwide and early onset can lead to asthma and allergies. Currently, the mechanisms of the disease are not fully understood. Metabolomics, the analysis of small molecules in the skin produced by the host and microbes, opens a window to observe the mechanisms of the disease which then may lead to new drug targets for AE treatment. Here, we review the latest advances in AE metabolomics, highlighting both the lipid and non-lipid molecules, along with reviewing the metabolites currently known to reside in the skin.

MS4A15 drives ferroptosis resistance through calcium-restricted lipid remodeling

Ferroptosis is an iron-dependent form of cell death driven by biochemical processes that promote oxidation within the lipid compartment. Calcium (Ca²⁺) is a signaling molecule in diverse cellular processes such as migration, neurotransmission, and cell death. Here, we uncover a crucial link between ferroptosis and Ca²⁺ through the identification of the novel tetraspanin MS4A15. MS4A15 localizes to the endoplasmic reticulum, where it blocks ferroptosis by depleting luminal Ca²⁺ stores and reprogramming membrane phospholipids to ferroptosis-resistant species. Specifically, prolonged Ca²⁺ depletion inhibits lipid elongation and desaturation, driving lipid droplet dispersion and formation of shorter, more saturated ether lipids that protect phospholipids from ferroptotic reactive species. We further demonstrate that increasing luminal Ca²⁺ levels can preferentially sensitize refractory cancer cell lines. In summary, MS4A15 regulation of anti-ferroptotic lipid reservoirs provides a key resistance mechanism that is distinct from antioxidant and lipid detoxification pathways. Manipulating Ca²⁺ homeostasis offers a compelling strategy to balance cellular lipids and cell survival in ferroptosis-associated diseases.

Bio- and Chemoinformatics Approaches for Metabolomics Data Analysis

Metabolomics data analysis includes several repetitive tasks, including data sorting, calculation of exact masses or other physicochemical properties, or searching for identifiers in different databases. Several of these tasks can be automated using command line tools or short scripts in different scripting languages like Perl, Python, or R. This chapter presents simple solutions and short scripts written in R that can be used for the interaction with specific web services or for the calculation of physicochemical properties or molecular formulae.

Growth of Chlamydia pneumoniae Is Enhanced in Cells with Impaired Mitochondrial Function

Effective growth and replication of obligate intracellular pathogens depend on host cell metabolism. How this is connected to host cell mitochondrial function has not been studied so far. Recent studies suggest that growth of intracellular bacteria such as Chlamydia pneumoniae is enhanced in a low oxygen environment, arguing for a particular mechanistic role of the mitochondrial respiration in controlling intracellular progeny. Metabolic changes in C. pneumoniae infected epithelial cells were analyzed under normoxic (O₂ ≈ 20%) and hypoxic conditions (O₂ < 3%). We observed that infection of epithelial cells with C. pneumoniae under normoxia impaired mitochondrial function characterized by an enhanced mitochondrial membrane potential and ROS generation. Knockdown and mutation of the host cell ATP synthase resulted in an increased chlamydial replication already under normoxic conditions. As expected, mitochondrial hyperpolarization was observed in non-infected control cells cultured under hypoxic conditions, which was beneficial for C. pneumoniae growth. Taken together, functional and genetically encoded mitochondrial dysfunction strongly promotes intracellular growth of C. pneumoniae.

Characterization of poplar metabotypes via mass difference enrichment analysis

Instrumentation technology for metabolomics has advanced drastically in recent years in terms of sensitivity and specificity. Despite these technical advances, data analytical strategies are still in their infancy in comparison with other 'omics'. Plants are known to possess an immense diversity of secondary metabolites. Typically, more than 70% of metabolomics data are not amenable to systems biological interpretation because of poor database coverage. Here, we propose a new general strategy for mass-spectrometry-based metabolomics that incorporates all exact mass features with known sum formulas into the evaluation and interpretation of metabolomics studies. We extend the use of mass differences, commonly used for feature annotation, by redefining them as variables that reflect the remaining 'omic' domains. The strategy uses exact mass difference network analyses exemplified for the metabolomic description of two grey poplar (Populus × canescens) genotypes that differ in their capability to emit isoprene. This strategy established a direct connection between the metabotype and the non-isoprene-emitting phenotype, as mass differences pertaining to prenylation reactions were over-represented in non-isoprene-emitting poplars. Not only was the analysis of mass differences able to grasp the known chemical biology of poplar, but it also improved the interpretability of yet unknown biochemical relationships.

Bioactive Potential of Marine Macroalgae from the Central Red Sea (Saudi Arabia) Assessed by High-Throughput Imaging-Based Phenotypic Profiling

Marine algae represent an important source of novel natural products. While their bioactive potential has been studied to some extent, limited information is available on marine algae from the Red Sea. This study aimed at the broad discovery of new bioactivities from a collection of twelve macroalgal species from the Central Red Sea. We used imaging-based High-Content Screening (HCS) with a diverse spectrum of cellular markers for detailed cytological profiling of fractionated algal extracts. The cytological profiles for 3 out of 60 algal fractions clustered closely to reference inhibitors and showed strong inhibitory activities on the HIV-1 reverse transcriptase in a single-enzyme biochemical assay, validating the suggested biological target. Subsequent chemical profiling of the active fractions of two brown algal species by ultra-high resolution mass spectrometry (FT-ICR-MS) revealed possible candidate molecules. A database query of these molecules led us to groups of compounds with structural similarities, which are suggested to be responsible for the observed activity. Our work demonstrates the versatility and power of cytological profiling for the bioprospecting of unknown biological resources and highlights Red Sea algae as a source of bioactives that may serve as a starting point for further studies.

Guinea pig genital tract lipidome reveals in vivo and in vitro regulation of phosphatidylcholine 16:0/18:1 and contribution to Chlamydia trachomatis serovar D infectivity

INTRODUCTION

Chlamydia trachomatis (Ct), is the leading cause of sexually transmitted infections worldwide. Host transcriptomic- or proteomic profiling studies have identified key molecules involved in establishment of Ct infection or the generation of anti Ct-immunity. However, the contribution of the host metabolome is not known.

OBJECTIVES

The objective of this study was to determine the contribution of host metabolites in genital Ct infection.

METHODS

We used high-performance liquid chromatography-mass spectrometry, and mapped lipid profiles in genital swabs obtained from female guinea pigs at days 3, 9, 15, 30 and 65 post Ct serovar D intravaginal infection.

RESULTS

Across all time points assessed, 13 distinct lipid species including choline, ethanolamine and glycerol were detected. Amongst these metabolites, phosphatidylcholine (PC) was the predominant phospholipid detected from animals actively shedding bacteria i.e., at 3, 9, and 15 days post infection. However, at days 30 and 65 when the animals had cleared the infection, PC was observed to be decreased compared to previous time points. Mass spectrometry analyses of PC produced in guinea pigs (in vivo) and 104C1 guinea pig cell line (in vitro) revealed distinct PC species following Ct D infection. Amongst these, PC 16:0/18:1 was significantly upregulated following Ct D infection (p < 0.05, >twofold change) in vivo and in vitro infection models investigated in this report. Exogenous addition of PC 16:0/18:1 resulted in significant increase in Ct D in Hela 229 cells.

CONCLUSION

This study demonstrates a role for host metabolite, PC 16:0/18:1 in regulating genital Ct infection in vivo and in vitro.

MetICA: independent component analysis for high-resolution mass-spectrometry based non-targeted metabolomics

BACKGROUND

Interpreting non-targeted metabolomics data remains a challenging task. Signals from non-targeted metabolomics studies stem from a combination of biological causes, complex interactions between them and experimental bias/noise. The resulting data matrix usually contain huge number of variables and only few samples, and classical techniques using nonlinear mapping could result in computational complexity and overfitting. Independent Component Analysis (ICA) as a linear method could potentially bring more meaningful results than Principal Component Analysis (PCA). However, a major problem with most ICA algorithms is the output variations between different runs and the result of a single ICA run should be interpreted with reserve.

RESULTS

ICA was applied to simulated and experimental mass spectrometry (MS)-based non-targeted metabolomics data, under the hypothesis that underlying sources are mutually independent. Inspired from the Icasso algorithm, a new ICA method, MetICA was developed to handle the instability of ICA on complex datasets. Like the original Icasso algorithm, MetICA evaluated the algorithmic and statistical reliability of ICA runs. In addition, MetICA suggests two ways to select the optimal number of model components and gives an order of interpretation for the components obtained.

CONCLUSIONS

Correlating the components obtained with prior biological knowledge allows understanding how non-targeted metabolomics data reflect biological nature and technical phenomena. We could also extract mass signals related to this information. This novel approach provides meaningful components due to their independent nature. Furthermore, it provides an innovative concept on which to base model selection: that of optimizing the number of reliable components instead of trying to fit the data. The current version of MetICA is available at https://github.com/daniellyz/MetICA.

Global metabolomic analysis of a mammalian host infected with Bacillus anthracis

Whereas DNA provides the information to design life and proteins provide the materials to construct it, the metabolome can be viewed as the physiology that powers it. As such, metabolomics, the field charged with the study of the dynamic small-molecule fluctuations that occur in response to changing biology, is now being used to study the basis of disease. Here, we describe a comprehensive metabolomic analysis of a systemic bacterial infection using Bacillus anthracis, the etiological agent of anthrax disease, as the model pathogen. An organ and blood analysis identified approximately 400 metabolites, including several key classes of lipids involved in inflammation, as being suppressed by B. anthracis. Metabolite changes were detected as early as 1 day postinfection, well before the onset of disease or the spread of bacteria to organs, which testifies to the sensitivity of this methodology. Functional studies using pharmacologic inhibition of host phospholipases support the idea of a role of these key enzymes and lipid mediators in host survival during anthrax disease. Finally, the results are integrated to provide a comprehensive picture of how B. anthracis alters host physiology. Collectively, the results of this study provide a blueprint for using metabolomics as a platform to identify and study novel host-pathogen interactions that shape the outcome of an infection.

Changes in Brain Metallome/Metabolome Pattern due to a Single i.v. Injection of Manganese in Rats

Exposure to high concentrations of Manganese (Mn) is known to potentially induce an accumulation in the brain, leading to a Parkinson related disease, called manganism. Versatile mechanisms of Mn-induced brain injury are discussed, with inactivation of mitochondrial defense against oxidative stress being a major one. So far, studies indicate that the main Mn-species entering the brain are low molecular mass (LMM) compounds such as Mn-citrate. Applying a single low dose MnCl₂ injection in rats, we observed alterations in Mn-species pattern within the brain by analysis of aqueous brain extracts by size-exclusion chromatography—inductively coupled plasma mass spectrometry (SEC-ICP-MS). Additionally, electrospray ionization—ion cyclotron resonance-Fourier transform-mass spectrometry (ESI-ICR/FT-MS) measurement of methanolic brain extracts revealed a comprehensive analysis of changes in brain metabolisms after the single MnCl₂ injection. Major alterations were observed for amino acid, fatty acid, glutathione, glucose and purine/pyrimidine metabolism. The power of this metabolomic approach is the broad and detailed overview of affected brain metabolisms. We also correlated results from the metallomic investigations (Mn concentrations and Mn-species in brain) with the findings from metabolomics. This strategy might help to unravel the role of different Mn-species during Mn-induced alterations in brain metabolism.

DI-ICR-FT-MS-based high-throughput deep metabotyping: a case study of the Caenorhabditis elegans-Pseudomonas aeruginosa infection model

In metabolomics there is an ever-growing need for faster and more comprehensive analysis methods to cope with the increasing size of biological studies. Direct-infusion ion-cyclotron-resonance Fourier-transform spectrometry (DI-ICR-FT-MS) is used in non-targeted metabolomics to obtain high-resolution snapshots of the metabolic state of a system. We applied this technology to a Caenorhabditis elegans-Pseudomonas aeruginosa infection model and optimized times needed for cultivation and mass-spectrometric analysis. Our results reveal that DI-ICR-FT-MS is a promising tool for high-throughput in-depth non-targeted metabolomics. We performed whole-worm metabolomics and recovered markers of the induced metabolic changes in C. elegans brought about by interaction with pathogens. In this investigation, we reveal complex metabolic phenotypes enabling clustering based upon challenge. Specifically, we observed a marked decrease in amino-acid metabolism with infection by P. aeruginosa and a marked increase in sugar metabolism with infection by Salmonella enterica. We were also able to discriminate between infection with a virulent wild-type Pseudomonas and with an attenuated mutant, making it possible to use this method in larger genetic screens to identify host and pathogen effectors affecting the metabolic phenotype of infection.

High precision mass measurements for wine metabolomics

An overview of the critical steps for the non-targeted Ultra-High Performance Liquid Chromatography coupled with Quadrupole Time-of-Flight Mass Spectrometry (UPLC-Q-ToF-MS) analysis of wine chemistry is given, ranging from the study design, data preprocessing and statistical analyses, to markers identification. UPLC-Q-ToF-MS data was enhanced by the alignment of exact mass data from FTICR-MS, and marker peaks were identified using UPLC-Q-ToF-MS(2). In combination with multivariate statistical tools and the annotation of peaks with metabolites from relevant databases, this analytical process provides a fine description of the chemical complexity of wines, as exemplified in the case of red (Pinot noir) and white (Chardonnay) wines from various geographic origins in Burgundy.

How subtle is the "terroir" effect? Chemistry-related signatures of two "climats de Bourgogne"

The chemical composition of grape berries is influenced by various environmental conditions often considered to be representative of a “terroir”. If grapes from a given terroir are assumed to reflect this origin in their chemical compositions, the corresponding wine should also reflect it. The aim of this work was therefore to reveal the “terroir” expression within the chemodiversity of grapes and related wines, using ultrahigh-resolution mass spectrometry. Grapes and corresponding wines, from two distinct – though very proximate – terroirs of Burgundy were analyzed over three vintages (2010, 2011 and 2012). Ultrahigh-resolution mass spectrometry and ultra-high performance liquid chromatography were used as untargeted and targeted approaches to discriminate complex chemical fingerprints for vintages, classes (wines, skins or musts), and terroirs. Statistical analyses revealed that even if vintages have the most significant impact on fingerprints, the most significant terroir differences are seen in the grapes of a given vintage.

Imaging of Chlamydia and host cell metabolism

ABSTRACT: 

Chlamydial infections cause a wide range of acute and chronic diseases. Chlamydia trachomatis is the most common sexually transmitted bacterium while Chlamydia pneumoniae causes infections of the upper and lower respiratory tract. Chlamydia are obligate, intracellular bacteria with a biphasic developmental cycle that involves unique metabolic changes. Aside from entering an actively replicating state, Chlamydia may also implement persistent infections depending on different microenvironmental factors. In addition, changes in local oxygen availability and the composition of surrounding host microbiota are suggested to affect chlamydial growth and metabolism. Both bacteria and host cells endure characteristic metabolic changes during infection. Technical developments in recent years enable us to separately characterize chlamydial and host cell metabolism in living cells. This article focuses on novel approaches to analyze chlamydial metabolism such as NAD(P)H fluorescence lifetime imaging by two-photon microscopy. In addition, we provide an overview regarding promising future possibilities to further elucidate host–pathogen metabolic interactions.

Chlamydial metabolism revisited: interspecies metabolic variability and developmental stage-specific physiologic activities

Chlamydiae are a group of obligate intracellular bacteria comprising important human and animal pathogens as well as symbionts of ubiquitous protists. They are characterized by a developmental cycle including two main morphologically and physiologically distinct stages, the replicating reticulate body and the infectious nondividing elementary body. In this review, we reconstruct the history of studies that have led to our current perception of chlamydial physiology, focusing on their energy and central carbon metabolism. We then compare the metabolic capabilities of pathogenic and environmental chlamydiae highlighting interspecies variability among the metabolically more flexible environmental strains. We discuss recent findings suggesting that chlamydiae may not live as energy parasites throughout the developmental cycle and that elementary bodies are not metabolically inert but exhibit metabolic activity under appropriate axenic conditions. The observed host-free metabolic activity of elementary bodies may reflect adequate recapitulation of the intracellular environment, but there is evidence that this activity is biologically relevant and required for extracellular survival and maintenance of infectivity. The recent discoveries call for a reconsideration of chlamydial metabolism and future in-depth analyses to better understand how species- and stage-specific differences in chlamydial physiology may affect virulence, tissue tropism, and host adaptation.