Metabolic Changes in Lung Tissue of Tuberculosis-Infected Mice Using GC/Q-TOF with Low Energy EI

Significance of the Topic

Metabolomic profiling of lung tissue in tuberculosis (TB) provides critical insights into host–pathogen interactions and may reveal novel biomarkers for diagnosis or treatment monitoring. By capturing global metabolic alterations induced by Mycobacterium tuberculosis, researchers can uncover new pathophysiological pathways, guide therapeutic strategies, and improve understanding of immune responses in infected hosts.

Objectives and Study Overview

This study aimed to compare the metabolic profiles of uninfected and TB-infected mouse lung tissues nine weeks post-infection using an untargeted gas chromatography–quadrupole time-of-flight mass spectrometry (GC/Q-TOF MS) approach with low-energy electron ionization (EI). Key goals included identifying differential metabolites, confirming molecular formulas of known and unknown compounds, and mapping perturbed biochemical pathways associated with TB infection.

Methodology and Instrumentation

Lung tissues from mice infected intratracheally with 5×10^4 CFU of M. tuberculosis H37Rv and from uninfected controls were extracted and derivatized by O-methoximation followed by trimethylsilylation.

• Instrument setup:
  • Gas chromatograph: Agilent 7890B GC system
  • Mass spectrometer: Agilent 7250 GC/Q-TOF with standard EI at 70 eV and low-energy EI at 17, 15, and 12 eV
  • Column: Agilent DB-5MS (30 m×0.25 mm, 0.25 µm, DuraGuard) with retention time locking via the Fiehn method
  • Carrier gas: Helium at 1 mL/min
  • Transfer line temperature: 290 °C; ion source: 200 °C; quadrupole: 150 °C
  • Mass range: 50–950 m/z; acquisition rate: 5 Hz
• Data processing:
  • Initial compound annotation using Fiehn retention index library, NIST library, and accurate-mass Metabolomics PCDL
  • Feature detection with SureMass in MassHunter Unknowns Analysis B.08.00
  • Statistical analysis, principal component analysis (PCA), fold-change, and heatmap generation in Mass Profiler Professional (MPP) v13.0
  • Pathway mapping using Pathway Architect extension for MPP
  • Molecular ion confirmation and structural elucidation of unknowns via low-energy EI and targeted MS/MS in Qualitative Analysis with Molecular Structure Correlator (MSC)

Main Results and Discussion

PCA revealed clear separation between infected and control lung samples, indicating profound metabolic reprogramming upon TB infection. Volcano plot and heatmap analyses highlighted significant fold changes in amino acids, nucleobases, and other small molecules.

Notable findings:

• Increased levels of itaconic acid and kynurenine, metabolites linked to macrophage activation and immune modulation
• Altered amino acid profiles, suggesting shifts in nitrogen metabolism and host defense mechanisms
• Differential regulation of purine and pyrimidine pathways and NAD biosynthesis II, implicating energy metabolism and redox balance in TB pathology

Pathway Architect identified purine/pyrimidine metabolism and NAD biosynthesis as highly impacted, pointing to disrupted nucleotide turnover and cofactor generation in infected tissue.

Unknown compound analysis using low-energy EI enabled reliable detection of molecular ions. Subsequent MS/MS fragmentation and MSC correlation provided plausible molecular formulas and structural hypotheses for previously unannotated features.

Benefits and Practical Applications

This untargeted metabolomics approach allows comprehensive detection of host metabolic responses to TB, facilitating:

• Discovery of metabolic biomarkers for early TB diagnosis or treatment monitoring
• Elucidation of novel host defense pathways, such as the itaconate axis
• Development of targeted assays for clinical or preclinical research

Future Trends and Possibilities for Use

Emerging directions in TB metabolomics include:

• Integration with transcriptomic and proteomic data for systems-level insights
• Expansion of high-resolution libraries tailored to low-energy EI spectra
• Translation of animal model findings to human clinical samples
• Application of machine learning for biomarker validation and predictive modeling
• Advancements in ionization techniques to improve sensitivity for trace metabolites

Conclusion

This study demonstrates that low-energy EI GC/Q-TOF MS combined with comprehensive data analysis can robustly profile metabolic alterations in TB-infected lung tissue. Key metabolic pathways disrupted by infection were identified, and unknown compounds were structurally characterized, paving the way for novel biomarker discovery and deeper understanding of TB pathophysiology.

References

1. World Health Organization. Tuberculosis fact sheet FS104. 2014.
2. Strelko CL, et al. Itaconic Acid Is a Mammalian Metabolite Induced during Macrophage Activation. Journal of the American Chemical Society. 2011;133(41):16386–16389.