This protocol describes the steps to generate a 3D model of metabolite distribution during trypanosomatid infection, including sample collection, metabolite extraction, an overview of liquid chromatography-tandem mass spectrometry data acquisition, 3D model generation, and finally, data visualization.
Pathogen tropism and disease tropism refer to the tissue locations selectively colonized or damaged by pathogens, leading to localized disease symptoms. Human-infective trypanosomatid parasites include Trypanosoma cruzi, the causative agent of Chagas disease; Trypanosoma brucei, the causative agent of sleeping sickness; and Leishmania species, causative agents of leishmaniasis. Jointly, they affect 20 million people across the globe. These parasites show specific tropism: heart, esophagus, colon for T. cruzi, adipose tissue, pancreas, skin, circulatory system and central nervous system for T. brucei, skin for dermotropic Leishmania strains, and liver, spleen, and bone marrow for viscerotropic Leishmania strains. A spatial perspective is therefore essential to understand trypanosomatid disease pathogenesis. Chemical cartography generates 3D visualizations of small molecule abundance generated via liquid chromatography-mass spectrometry, in comparison to microbiological and immunological parameters. This protocol demonstrates how chemical cartography can be applied to study pathogenic processes during trypanosomatid infection, beginning from systematic tissue sampling and metabolite extraction, followed by liquid chromatography-tandem mass spectrometry data acquisition, and concluding with the generation of 3D maps of metabolite distribution. This method can be used for multiple research questions, such as nutrient requirements for tissue colonization by T. cruzi, T. brucei, or Leishmania, immunometabolism at sites of infection, and the relationship between local tissue metabolic perturbation and clinical disease symptoms, leading to comprehensive insight into trypanosomatid disease pathogenesis.
Trypanosomatid parasites consist of Leishmania species, African trypanosomes (Trypanosoma brucei), and American trypanosomes (Trypanosoma cruzi). Leishmania protozoa cause leishmaniasis, which includes self-healing and self-limited localized cutaneous leishmaniasis, mucocutaneous leishmaniasis in which the mucosal tissues of the mouth, nose, and throat become damaged, and visceral leishmaniasis with parasite tropism to the visceral organs causing fever and hepatosplenomegaly1,2. T. brucei causes Human African trypanosomiasis (HAT), also known as sleeping sickness, mainly reported in African countries3. The clinical signs and symptoms include hepatosplenomegaly, fever, headache, musculoskeletal pains, lymphadenopathies, and anemia in the hemo-lymphatic stage when parasites localize to the bloodstream and lymphatics. This is followed by the meningo-encephalitic stage, where parasites localize to the central nervous system and cause sleep disturbance, behavioral alteration, and eventually fatal comas4. T. cruzi causes Chagas disease, endemic in the Americas. Infected individuals experience an initial acute stage, usually asymptomatic, with broad parasite tropism. About 10%-30% of infected individuals experience chronic stage symptoms after decades of infection, characterized by megaoesophagus, megacolon, and cardiovascular complications5,6.
Metabolomics studies small molecular species (50-1,500 Da), including biological compounds from primary or secondary metabolism and externally-derived compounds such as drugs or food-derived molecules. In the context of host-pathogen interactions, metabolomics can explore the impact of infection on host metabolite environments, crucial in accessing the effect of the pathogen on the host. It can also assess pathogen adaptations to the host nutritional and immunological environment7,8,9. Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are common metabolomics tools used to identify, quantify, and characterize metabolites. This "omics" approach can also be applied to biomarker discovery and drug development10,11.
Given the specific tissue tropism of trypanosomatid parasites, spatial metabolomics analyses can enable significant insight into the pathogenesis of the diseases they cause. Mapping the spatial distribution of metabolites revealed metabolites locally affected by chronic Trypanosoma cruzi infection in mouse heart tissue and acute and long-term Trypanosoma cruzi infection in the mouse gastrointestinal tract6,12,13. Specifically, 3D chemical cartography demonstrated a disconnect between parasite persistence and metabolic alterations in the heart tissue of chronically Trypanosoma cruzi-infected mice. Metabolism was most perturbed in lower and apical segments of the heart, matching with sites of Chagas disease symptoms (cardiac apical aneurysms). Metabolite families perturbed by infection at specific cardiac sites and correlated to disease severity include acylcarnitines and glycerophosphocholines12,13,14. In the gastrointestinal tract, persistent metabolic alterations concurred with sites of Chagas disease symptoms: esophagus and colon. In contrast, metabolism is re-normalized at sites not associated with Chagas disease symptoms, such as the small intestine. Metabolites locally perturbed by infection in the gastrointestinal tract include acylcarnitines, glycerophosphocholines, kynurenine, tryptophan, and cholic acid. In addition, these analyses enabled the identification of a new metabolic mechanism of tolerance to Chagas disease6. Applying these methods to the study of cutaneous leishmaniasis revealed significant metabolic perturbations at the site of the lesion, but also specific metabolic changes in lesion-adjacent, macroscopically healthy tissue. For example, glutamine was depleted at the lesion site, whereas glycerophosphocholines in the m/z (mass to charge ratio) 200-299, 400-499, 500-599, and 600-699 were significantly increased at the lesion site. PC (O-34:1) was only increased at lesion-adjacent sites15.
The goal of this manuscript is to demonstrate the steps necessary to generate 3D models of metabolite distribution ("chemical cartography") as applied to trypanosomatid parasite infection models (Figure 1). This approach builds on several critical advances in the context of metabolomics and metabolomics data processing, particularly the development of 'ili software to plot metabolomics data onto 3D models easily16.
All animal experiments described were approved by the University of Oklahoma or the University of California San Diego Institutional Animal Care and Use Committee. All steps handling infectious material were performed inside a biosafety cabinet (class II, type A2) and according to local regulations.
1. Tissue collection
2. Metabolite extraction
NOTE: Only LC-MS grade liquids and reagents must be used throughout. This method was adapted from Reference20.
3. LC-MS data acquisition
4. LC-MS data processing
5. 3D model generation
6. 'ili plot generation
The number of metabolite features obtained depends on the tissue type analyzed and data processing parameters. For example, this protocol has been used to analyze the spatial impact of T. cruzi infection on the gastrointestinal tract metabolome in a mouse model of T. cruzi infection. In prior work, male C3H/HeJ were injected intraperitoneally with 1,000 CL + luc T. cruzi parasites32,6. Animals were euthanized 12 or 89 days post-infection, and a chemical cartography analysis of 13 contiguous segments of the gastrointestinal tract was performed as described in this protocol. This analysis led to a feature table of 5,502 features, which were then visualized into 3D using the steps described in this protocol. This approach enables the visualization of metabolite features in individual animals that are high at the site of high parasite load (kynurenine, Figure 2B vs. parasite load, Figure 2A), of metabolites with differential distribution across tissue regions (glutamine, Figure 2C) and metabolite features that are found at comparable levels across small and large intestines (LPE 16:0 Figure 2D). Kynurenine was selected for visualization because of its known relationship to inflammation and prior publications on the ability of kynurenine-derived metabolites to regulate T. cruzi load33. Random forest-based machine learning models had previously revealed an association between kynurenine levels and infection status6. Glutamine was selected for a visualization based on previous publications demonstrating a relationship between in vitro glutamine availability and T. cruzi drug sensitivity34. Differential distribution was confirmed using logistic regression, p < 0.05. LPE 16:0 was selected after visual inspection of the data to discover metabolite features found at comparable levels across tissue sites.
Figure 1: Protocol overview. The illustration was created with BioRender.com. Please click here to view a larger version of this figure.
Figure 2: Chemical cartography analysis. Male C3H/HeJ mice were injected intraperitoneally with 1,000 CL+luc T. cruzi parasites32. Animals were euthanized 12 or 89 days post-infection, and the gastrointestinal tract was collected and sectioned systematically (step 1)6. Metabolites were extracted as in step 2 and analyzed by LC-MS/MS. 3D model generation was performed using the SketchUp software (step 5), and data were plotted in 3D as in step 6. (A) Parasite distribution in a specific mouse, 12 days post-infection. (B) Kynurenine metabolite distribution in the same mouse, 12 days post-infection. (C) Mean glutamine distribution across infected mice, 89 days post-infection. (D) Comparable levels of m/z 454.292 retention time 2.929 min, annotated as 2-hexadecanoyl-sn-glycero-3-phosphoethanolamine (LPE 16:0), in the same mouse as in A and B in the small intestine and colon. Samples and data were generated in6. Please click here to view a larger version of this figure.
Understanding trypanosomatid infections is essential to guide novel drug development and treatment approaches. This chemical cartography method is uniquely poised to provide actionable insights into the relationship between metabolism and trypanosomatid disease pathogenesis, thus addressing this translational need.
Only LC-MS grade solvents are recommended during metabolite extraction and MS analyses, to lessen background contamination. Polymeric contamination35, commonly derived from paraffin film and/or other plastics36,37,38, must be avoided where possible. Parafilm, in particular, must never be used. These aspects are crucial since LC-MS data quality depends on the materials used during sample preparation and metabolite extraction. Data quality should be ensured before generating 'ili plots. In addition, generating these comprehensive spatial metabolomics maps requires the collection of all adjacent tissue samples and metabolite extraction from all collected samples to avoid gaps in these maps. Collection procedures, logistics of metabolite extraction and LC-MS analysis, and costs should thus be considered and planned accordingly.
This protocol can be modified to meet user needs in multiple ways. For example, the polarity and solubility of solvents used during metabolite extraction will influence what metabolites are detected39. To maximize the diversity of detected metabolite features for untargeted chemical cartography analyses, combining multiple extraction steps and solvents is recommended. For example, this method utilizes dichloromethane, methanol, and water as extraction solvents because they enable accurate detection of nonpolar and polar molecules20,40. However, these solvents are not universally suitable for every MS experiment, and researchers should select extraction solvents based on the goals of their project. Likewise, different LC-MS/MS conditions can be used, such as replacing reversed-phase chromatography with normal phase chromatography. Alternative columns can also be used for reversed-phase data collection instead of C8 chromatography, though empirically, C8 chromatography is more robust to tissue lipids and has a lower clogging frequency. Conceptually, these protocols can also be applied to other mass spectrometry methods such as gas chromatography-mass spectrometry, etc.
An alternative approach is mass spectrometry imaging. Indeed, unlike mass spectrometry imaging approaches, liquid chromatography-mass spectrometry does not inherently preserve spatial information10. Chemical cartography approaches bridge this gap by including sampling location at the time of project conceptualization, in the sample metadata, and at data processing steps. A strength of this chemical cartography approach, unlike mass spectrometry imaging, is the ability to provide confident annotations (Metabolomics Standards Initiative level 1 or level 2 annotation confidence41), unlike mass spectrometry imaging where the bulk of applications rely on accurate mass only for annotation. Mass spectrometry imaging will enable fine-grained spatial mapping, sometimes down to the single-cell level, e.g.,42,43. In contrast, chemical cartography approaches enable large-scale cross-organ mapping of metabolite distribution without requiring highly specialized whole-animal cryosectioning skills. Chemical cartography provides complementary evidence to the many spatial transcriptomic approaches being developed, e.g.,44, with the advantage of focusing on the 'omics layer closest to the phenotype'45. Alternative methods for parasite load quantification include measuring bioluminescence at the time of sample collection6. Fine segments could also be collected to enable confocal or electron microscopy to assess localized parasite burden and tissue damage. The water homogenate, which is used for cytokine quantification in this protocol and prior publications13, could also be used to quantify protein-based markers of tissue damage.
There are also multiple ways to obtain 3D models suitable to plot the resulting LC-MS data. In addition to the method suggested here, models can be purchased pre-made from various online vendors. Ensure that the terms of use match with the intended usage, especially concerning publication. Models for large organs can be generated de novo using 3D scanners according to scanner instructions. Alternatives such as MATLAB exist for generating and visualizing 3D models for chemical cartography46, but they were primarily implemented before the development of 'ili16. MATLAB is a data analysis and programming tool suite offering a wide variety of applications across many fields. However, MATLAB is neither free nor open-source, and it requires familiarity with MATLAB interfaces, especially considering MATLAB was not developed for processing mass spectrometry data. This proposed method's alternatives, namely, SketchUp, Meshlab, and 'ili, are freely accessible, user-friendly, and offer similar functions as MATLAB for chemical cartography purposes.
This method is robust concerning sample preparation and metabolite extraction. Troubleshooting is most often necessary at the LC-MS data acquisition step. This is beyond the scope of this article. Readers are directed to excellent publications on LC-MS data acquisition troubleshooting, including20,47. Likewise, the complexities of metabolite annotation are beyond the scope of this method's focus on 3D model generation. Useful references on this topic include24,25,48,49.
While this method effectively explores disease pathogenesis, there are limitations to this approach, some of which are common across any metabolomics experiment. One such limitation is the low annotation rate of LC-MS features50, which is contingent upon reference spectral libraries' availability and quality. A further limitation is that this protocol does not preserve mRNA due to the incompatibility of RNA preservation reagents such as RNAlater with LC-MS/MS analysis. However, the protein quality is adequate for downstream analyses and thus can replace mRNA-based analyses.
A chemical cartography approach to infection pathogenesis directly reflects how bacterial, viral, or parasitic infections develop in organ systems and cause localized disease. Analyzing these regional subsamples and generating 3D models ultimately conveys how metabolites function across three-dimensional space, shedding light on these previously unrecognized spatial dimensions of molecular biology. Using this protocol, for example, metabolite localization was compared to Trypanosoma cruzi parasite load. Results clarified the relationship between the pathogen and host tissue and also demonstrated the metabolic dynamics of Chagas disease symptom progression6. Chemical cartography methods have also been applied to various topics, such as human-built environment interaction51,52,53, the chemical makeup of organ systems like human skin46 and lungs54, and plant metabolism and environment interactions55. Future applications can involve assessing localized disease tolerance and resilience, or the relationship between local metabolite levels, pathogen tropism, and disease tropism in models beyond trypanosomatid infection. This approach should also have broad applicability to expand current pharmacokinetics protocols, to assess the relationship between local tissue drug levels and drug metabolism vs. overall metabolic context, tissue damage, and pathogen clearance. Overall, chemical cartography allows unique explorations of metabolite distributions in various sample types, with applications including disease pathogenesis, human health, human-environment interactions, and microbial dynamics.
The authors have nothing to disclose.
Laura-Isobel McCall, PhD, holds an Investigators in the Pathogenesis of Infectious Disease Award from the Burroughs Wellcome Fund. The authors further wish to acknowledge support from NIH award number R21AI148886, a pilot grant from the Oklahoma Center for Respiratory and Infectious Diseases (OCRID) under NIH award number P20GM103648, and start-up funds from the University of Oklahoma (to LIM). The content is solely the authors' responsibility and does not necessarily represent the official views of the funders. The authors also wish to thank the developers of the tools used in this protocol. All relevant publications have been cited, where applicable.
1.5 mL Eppendorf tubes | NA | NA | any brand, as available |
1 L bottle, pyrex | NA | NA | any brand, as available |
1 L graduated cylinder, pyrex | NA | NA | any brand, as available |
2 mL SafeLock Eppendorf tubes | VWR | 20901-540 | use the appropriate tube model for the available tissue homogenizer |
3D model (de-novo generated according to protocol steps, or purchased) | NA | NA | as appropriate for system under investigation |
5 mm stainless steel bead | Qiagen | 69989 | |
96 well plate | Fisher | 3252449 | |
AATTCCTCCAAGCAGCGGATA primer | NA | NA | any brand, as available; published in Piron, M. et al. Development of a real-time PCR assay for Trypanosoma cruzi detection in blood samples. Acta tropica. 103 (3), 195–200 (2007). |
analytical balance | NA | NA | any brand, as available |
ASTCGGCTGATCGTTTTCGA primer | NA | NA | any brand, as available; published in Piron, M. et al. Development of a real-time PCR assay for Trypanosoma cruzi detection in blood samples. Acta tropica. 103 (3), 195–200 (2007). |
benchtop centrifuge with microcentrifuge, falcon tube and 96-well-plate capacity | NA | NA | any brand, as available |
biosafety cabinet | NA | NA | class II, type A2; any brand, as available |
CAGCAAGCATCTATGCACTTAG ACCCC primer |
NA | NA | any brand, as available; published in Cummings, K.L., Tarleton, R.L. Rapid quantitation of Trypanosoma cruzi in host tissue by real-time PCR. Molecular and biochemical parasitology. 129 (1), 53–59 (2003). |
camera | NA | NA | any brand, as available. A cellphone camera is adequate for this protocol |
chemiluminescent-capable imaging system | NA | NA | any system, as available |
cotton balls | NA | NA | any brand, as available |
cryogloves | VWR | 97008-208 | replace with any brand, as available |
dissection scissors | NA | NA | any brand, as available |
dry ice | NA | NA | any brand, as available |
extra-length forceps | NA | NA | any brand, as available |
flammable-grade refrigerator | NA | NA | any brand, as available |
freezer storage boxes for microcentrifuge tubes | NA | NA | any brand, as available |
fume hood | NA | NA | any brand, as available |
high-resolution mass spectrometer | NA | NA | any brand, as available, such as ThermoFisher Q-Exactive Plus (catalog number 0726030) |
ice bucket | NA | NA | any brand, as available |
ili software | ili.embl.de | NA | |
isoflurane | Covetrus | 29405 | |
large tupperware | NA | NA | any brand, as available; large enough to comfortably contain mouse, cotton ball |
LC-MS grade acetonitrile | Fisher Optima | A955-4 | |
LC-MS grade dicholoromethane | Fisher Optima | D151-4 | |
LC-MS grade formic acid | Fisher Optima | A11750 | |
LC-MS grade methanol | Fisher Optima | A456-4 | |
LC-MS grade water | Fisher Optima | W64 | |
liquid chromatography column | Phenomenex | 00B-4499-AN | may be changed to other brands and models as appropriate for the metabolites of interest |
liquid chromatography column guard cartridge | Phenomenex | AJ0-8784 | may be changed to other brands and models as appropriate for the metabolites of interest |
liquid chromatography column guard cartridge holder | Phenomenex | AJ0-9000 | may be changed to other brands and models as appropriate for the metabolites of interest |
liquid nitrogen | NA | NA | any brand, as available |
luciferin | Goldbio | LUCK-1G | |
MeshLab software | https://www.meshlab.net/ | NA | |
Meshmixer software | https://www.meshmixer.com/ | NA | |
MS calibrant | NA | NA | appropriate one for available instrument |
MS data processing software | NA | NA | multiple options available; authors recommend MZmine |
MSConvert software | http://proteowizard.sourceforge.net/ | NA | |
Nanodrop | ThermoFisher | ND-ONE-W | other nanodrop models are also suitable |
p1000 pipet tips | NA | NA | use the appropriate brand to fit available pipettors |
p1000 pipettor | NA | NA | any brand, as available |
p20 pipette tips | NA | NA | use the appropriate brand to fit available pipettors |
p20 pipettor | NA | NA | any brand, as available |
p200 pipette tips | NA | NA | use the appropriate brand to fit available pipettors |
p200 pipettor | NA | NA | any brand, as available |
personal protective equipment (gloves, lab coat, safety glasses/goggles; faceshield) | NA | NA | any brand, as available |
Q-Plex Mouse Cytokine – Screen (16-Plex) | Quansys biosciences | 110949MS | can replace with other protein-based cytokine assays such as other commercial cytokine ELISA kits |
Quick-DNA Miniprep Plus Kit (200 preps) | Zymo | D4069 | replace with any brand of mammalian DNA extraction kit, as available |
real-time thermocycler | NA | NA | any brand, as available |
salt shaker or tea infuser | NA | NA | any brand; to contain isoflurane-soaked cotton ball and prevent contact with mouse skin |
SketchUp software | https://www.sketchup.com/ | NA | |
specimen forceps | NA | NA | any brand, as available |
speedvac with microcentrifuge tube and 96-well-plate capacity | NA | NA | any brand, as available |
spreadsheet software | https://www.microsoft.com/en-us/microsoft-365/excel | NA | can replace with other spreadsheet management software, as applicable |
sulfachloropyridazine | Sigma | S9882-100G | |
sulfadimethoxine | Sigma | S7007-10G | |
Sybr green qPCR reaction mix | Fisher | A25780 | can replace with other Sybr green qPCR reaction mixes, as desired |
TCCCTCTCATCAGTTCTAT GGCCCA primer |
NA | NA | any brand, as available; published in Cummings, K.L., Tarleton, R.L. Rapid quantitation of Trypanosoma cruzi in host tissue by real-time PCR. Molecular and biochemical parasitology. 129 (1), 53–59 (2003). |
tissue homogenizer | NA | NA | any brand, as available; for example, Qiagen TissueLyser II, catalog number 85300, with TissueLyser Adapter Set (2 x 24), catalog number 69982 |
tissue samples | NA | NA | from appropriate infection model |
TissueLyser single-bead dispenser | Qiagen | 69965 | |
UHPLC | NA | NA | any brand, as available, such as ThermoFisher Vanquish (catalog number IQLAAAGABHFAPUMBHV) |
ultra-low temperature freezer (-80) | NA | NA | any brand, as available |
ultrasonic bath | NA | NA | any system, as available |
wet ice | NA | NA | any brand, as available |
zone-free sealing film | VWR | 490007-390 |