Systems Biology

Trypanosoma cruzi, the causative agent of Chagas disease, faces significant metabolic challenges due to fluctuating nutrient availability and oxidative stress within its insect vector. Metabolomic techniques, such as gas chromatography–mass spectrometry (GC–MS), have been widely used to study the adaptive mechanisms of the parasite. This article describes a standardized method for the untargeted metabolomics analysis of T. cruzi epimastigote, covering parasite cultivation, sample deproteinization with methanol, metabolite extraction, derivatization with BSTFA, and GC–MS analysis. To ensure robustness and reproducibility, statistical analysis uses univariate tests, as well as multivariate approaches such as principal component analysis (PCA) and partial least squares (PLS) regression. The protocol offers a reliable and sensitive method to study metabolic responses in T. cruzi under environmental stress, with low biological variability and high reproducibility.

Metabolite modifications play a critical role in enhancing plants’ adaptability to environmental changes and serve as a major source of functional diversity in metabolites. However, current metabolomics approaches are limited to targeted analyses of a small number of known modified metabolites and lack comprehensive, large-scale studies of plant metabolite modifications. Here, we describe a widely targeted metabolite modificomics (WTMM) strategy, developed using ultra-high-performance liquid chromatography–quadrupole linear ion trap (UHPLC-Q-Trap) and ultra-high-performance liquid chromatography–Q-Exactive Orbitrap (UHPLC-QE-Orbitrap) technologies. This strategy enables high-throughput identification and sensitive quantification of modified metabolites. Using tomato as a model, we conducted a metabolite modificomics study and constructed a WTMM database, identifying 165 novel modified metabolites. The WTMM strategy is broadly applicable and can be extended to the study of other plant species.

Acclimation of leaf traits to fluctuating environments is a key mechanism to maximize fitness. One of the most important strategies in acclimation to changing light is to maintain efficient utilization of nitrogen in the photosynthetic apparatus by continuous modifications of between-leaf distribution along the canopy depth and within-leaf partitioning between photosynthetic functions according to local light availability. Between-leaf nitrogen distribution has been intensively studied over the last three decades, where proportional coordination between nitrogen concentration and light gradient was considered optimal in terms of maximizing canopy photosynthesis, without taking other canopy structural and physiological factors into account. We proposed a mechanistic model of protein turnover dynamics in different photosynthetic functions, which can be parameterized using leaves grown under different levels of constant light. By integrating this dynamic model into a multi-layer canopy model, constructed using data collected from a greenhouse experiment, it allowed us to test in silico the degree of optimality in photosynthetic nitrogen use for maximizing canopy carbon assimilation under given light environments.

Short-Chain Fatty Acids (SCFAs) are a product of the fermentation of resistant starches and dietary fibers by the gut microbiota. The most important SCFA are acetate (C2), propionate (C3) and butyrate (C4). These metabolites are formed and absorbed in the colon and then transported through the hepatic vein to the liver. SCFAs are more concentrated in the intestinal lumen than in the serum. Butyrate is largely consumed in the gut epithelium, propionate in the liver and acetate in the periphery. SCFAs act on many cells including components of the immune system and epithelial cells by two main mechanisms: activation of G-protein coupled receptors (GPCRs) and inhibition of histone deacetylase. Considering the association between changes in SCFA concentrations and the development of diseases, methods to quantify these acids in different biological samples are important. In this study, we describe a protocol using gas chromatography to quantify SCFAs in the serum, feces and colonic luminal content. Separation of compounds was performed using a DB-23 column (60 m x 0.25 mm internal diameter [i.d.]) coated with a 0.15 µm thick layer of 80.2% 1-methylnaphatalene. This method has a good linear range (15-10,000 µg/ml). The precision (relative standard deviation [RSD]) is less than 15.0% and the accuracy (error relative [ER]) is within ± 15.0%. The extraction efficiency was higher than 97.0%. Therefore, this is cost effective and reproducible method for SCFA measurement in feces and serum.

Stable-isotope labeled metabolic analysis is an essential methodology to characterize metabolic regulation during biological processes. However, the method using stable-isotope-labeled tracer (e.g., ¹³C-glucose) in live animal is only beginning to be developed. Here, we contribute a qualitative metabolic labeling experiment protocol in Drosophila melanogaster using stable-isotope-labeled ¹³C-glucose tracer followed by liquid chromatography-mass spectrometry (LC-MS) analysis. Detailed experimental setup, data acquisition and analysis are provided to facilitate the application of in vivo metabolic labeling analysis that might be applied in a wide range of biological studies.

Increased antibiotic resistance of plants and human pathogens and continuous use of chemical fertilizers has pushed microbiologists to explore new microbial sources as potential antagonists. In this study, eight strains of Pseudomonas aurantiaca and Pseudomonas chlororaphis, have been isolated from different plant sources and screened for their antagonistic and plant growth promoting potential (Shahid et al., 2017). All strains were compared with reference strain PB-St2 and their secondary metabolites were isolated by the use of solvent partitioning and subjected to LC/ESI/MS for confirmation of compounds. The ESI-mass spectra obtained were used to characterize the surfactants ionization behavior and [M + H]⁺ and [M + Na]⁺ ions were monitored for phenazines, derivatives of lahorenoic acid and cyclic lipopeptide (WLIP). LC-MS and HPLC methods were developed to see the elution of dominant metabolites in a single run to avoid the labor and separate methods of detection for all compounds. The method was found suitable and distinctively separated the compounds at different retention times in gradient flow. This method can be helpful to explore the metabolome of Pseudomonas sp. overall and in identification and quantification of strain specific metabolites.

Metabolomic is an emerging field of system biology. Lipidomic, a branch of metabolomic, aims to characterize lipophilic metabolites in biological systems. Caenorhabditis elegans (C. elegans) is a genetically tractable and versatile animal model for novel discovery of lipid metabolism. In addition, C. elegans embryo is simple and homogeneous. Here, we demonstrate detailed procedures of C. elegans culture, embryo isolation, lipid extraction and metabolomic data analysis.

We made the method for Arabidopsis metabolome analysis based on direct-infusion Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR/MS) (IonSpec). This method was sufficiently applied to metabolic phenotyping of Arabidopsis. This method is simple in that after homogenizing samples, powdered samples are dissolved in extraction solvents (acetone and methanol) to 20% fresh weight/volume. Extracted sample solutions are dried and dissolved in 50% (v/v) acetonitrile. Mass analysis using FT-ICR/MS (IonSpec) is performed in positive and negative ionization operation modes. Mass spectra are acquired over the 100-1,000 m/z range and accumulated to improve the S/N ratio.