MG(0:0/20:4(5Z,8Z,11Z,14Z)/0:0)

By writing the four English letters “PNMK” on white paper with a marker pen, and then scanning with a DESI ion source to obtain the scanning result. The signal of the chemical substances on the marker pen used appears on the channel with an m/z value of 322.1918, 323.1953, 546.4010, and etc, from the single cell deconvolution sampling layer class_4. This test data was tested by chuxiaoping from PANOMIX’s R&D laboratory.

1 male adult wild-type rat was obtained from Inserm U1085 - Irset Research Institute (University of Rennes1, France). Animals were age 60 days and were reared under ad-lib conditions. Care and handling of all animals complied with EU directive 2010/63/EU on the protection of animals used for scientific purposes. The whole epididymis was excised from each animal immediately post-mortem, loosely wrapped rapidly in an aluminum foil and a 2.5% (w/v) carboxymethylcellulose (CMC) solution was poured to embed the epididymis to preserve their morphology. To remove air bubbles, the filled aluminum molds was gently freezed by depositing it on isopentane or dry ice, then on the nitrogen vapors and finally by progressively dipping the CMC/sample coated with aluminum foil into liquid nitrogen (or only flush with liquid nitrogen). Frozen tissues were stored at -80 °C until use to avoid degradation.

1 male adult wild-type rat was obtained from Inserm U1085 - Irset Research Institute (University of Rennes1, France). Animals were age 60 days and were reared under ad-lib conditions. Care and handling of all animals complied with EU directive 2010/63/EU on the protection of animals used for scientific purposes. The whole epididymis was excised from each animal immediately post-mortem, loosely wrapped rapidly in an aluminum foil and a 2.5% (w/v) carboxymethylcellulose (CMC) solution was poured to embed the epididymis to preserve their morphology. To remove air bubbles, the filled aluminum molds was gently freezed by depositing it on isopentane or dry ice, then on the nitrogen vapors and finally by progressively dipping the CMC/sample coated with aluminum foil into liquid nitrogen (or only flush with liquid nitrogen). Frozen tissues were stored at -80 °C until use to avoid degradation.

Diseased

Sample information Organism: Macropus giganteus (kangaroo) Organism part: Brain Condition: Wildtype Sample growth conditions: Wild

A more complete and holistic view on host–microbe interactions is needed to understand the physiological and cellular barriers that affect the efficacy of drug treatments and allow the discovery and development of new therapeutics. Here, we developed a multimodal imaging approach combining histopathology with mass spectrometry imaging (MSI) and same section imaging mass cytometry (IMC) to study the effects of Salmonella Typhimurium infection in the liver of a mouse model using the S. Typhimurium strains SL3261 and SL1344. This approach enables correlation of tissue morphology and specific cell phenotypes with molecular images of tissue metabolism. IMC revealed a marked increase in immune cell markers and localization in immune aggregates in infected tissues. A correlative computational method (network analysis) was deployed to find metabolic features associated with infection and revealed metabolic clusters of acetyl carnitines, as well as phosphatidylcholine and phosphatidylethanolamine plasmalogen species, which could be associated with pro-inflammatory immune cell types. By developing an IMC marker for the detection of Salmonella LPS, we were further able to identify and characterize those cell types which contained S. Typhimurium. [dataset] Nicole Strittmatter. Holistic Characterization of a Salmonella Typhimurium Infection Model Using Integrated Molecular Imaging, metabolights_dataset, V1; 2022. https://www.ebi.ac.uk/metabolights/MTBLS2671.

A more complete and holistic view on host–microbe interactions is needed to understand the physiological and cellular barriers that affect the efficacy of drug treatments and allow the discovery and development of new therapeutics. Here, we developed a multimodal imaging approach combining histopathology with mass spectrometry imaging (MSI) and same section imaging mass cytometry (IMC) to study the effects of Salmonella Typhimurium infection in the liver of a mouse model using the S. Typhimurium strains SL3261 and SL1344. This approach enables correlation of tissue morphology and specific cell phenotypes with molecular images of tissue metabolism. IMC revealed a marked increase in immune cell markers and localization in immune aggregates in infected tissues. A correlative computational method (network analysis) was deployed to find metabolic features associated with infection and revealed metabolic clusters of acetyl carnitines, as well as phosphatidylcholine and phosphatidylethanolamine plasmalogen species, which could be associated with pro-inflammatory immune cell types. By developing an IMC marker for the detection of Salmonella LPS, we were further able to identify and characterize those cell types which contained S. Typhimurium. [dataset] Nicole Strittmatter. Holistic Characterization of a Salmonella Typhimurium Infection Model Using Integrated Molecular Imaging, metabolights_dataset, V1; 2022. https://www.ebi.ac.uk/metabolights/MTBLS2671.

A more complete and holistic view on host–microbe interactions is needed to understand the physiological and cellular barriers that affect the efficacy of drug treatments and allow the discovery and development of new therapeutics. Here, we developed a multimodal imaging approach combining histopathology with mass spectrometry imaging (MSI) and same section imaging mass cytometry (IMC) to study the effects of Salmonella Typhimurium infection in the liver of a mouse model using the S. Typhimurium strains SL3261 and SL1344. This approach enables correlation of tissue morphology and specific cell phenotypes with molecular images of tissue metabolism. IMC revealed a marked increase in immune cell markers and localization in immune aggregates in infected tissues. A correlative computational method (network analysis) was deployed to find metabolic features associated with infection and revealed metabolic clusters of acetyl carnitines, as well as phosphatidylcholine and phosphatidylethanolamine plasmalogen species, which could be associated with pro-inflammatory immune cell types. By developing an IMC marker for the detection of Salmonella LPS, we were further able to identify and characterize those cell types which contained S. Typhimurium. [dataset] Nicole Strittmatter. Holistic Characterization of a Salmonella Typhimurium Infection Model Using Integrated Molecular Imaging, metabolights_dataset, V1; 2022. https://www.ebi.ac.uk/metabolights/MTBLS2671.

A more complete and holistic view on host–microbe interactions is needed to understand the physiological and cellular barriers that affect the efficacy of drug treatments and allow the discovery and development of new therapeutics. Here, we developed a multimodal imaging approach combining histopathology with mass spectrometry imaging (MSI) and same section imaging mass cytometry (IMC) to study the effects of Salmonella Typhimurium infection in the liver of a mouse model using the S. Typhimurium strains SL3261 and SL1344. This approach enables correlation of tissue morphology and specific cell phenotypes with molecular images of tissue metabolism. IMC revealed a marked increase in immune cell markers and localization in immune aggregates in infected tissues. A correlative computational method (network analysis) was deployed to find metabolic features associated with infection and revealed metabolic clusters of acetyl carnitines, as well as phosphatidylcholine and phosphatidylethanolamine plasmalogen species, which could be associated with pro-inflammatory immune cell types. By developing an IMC marker for the detection of Salmonella LPS, we were further able to identify and characterize those cell types which contained S. Typhimurium. [dataset] Nicole Strittmatter. Holistic Characterization of a Salmonella Typhimurium Infection Model Using Integrated Molecular Imaging, metabolights_dataset, V1; 2022. https://www.ebi.ac.uk/metabolights/MTBLS2671.