Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) elucidates molecular distributions in thin tissue sections. Absolute pixel-to-pixel quantitation has remained a challenge, primarily lacking validation of the appropriate analytical methods. In the present work, isotopically labeled internal standards are applied to tissue sections to maximize quantitative reproducibility and yield accurate quantitative results. We have developed a tissue model for rifampicin (RIF), an antibiotic used to treat tuberculosis, and have tested different methods of applying an isotopically labeled internal standard for MALDI IMS analysis. The application of the standard and subsequently the matrix onto tissue sections resulted in quantitation that was not statistically significantly different from results obtained using HPLC-MS/MS of tissue extracts. Quantitative IMS experiments were performed on liver tissue from an animal dosed in vivo. Each microspot in the quantitative images measures the local concentration of RIF in the thin tissue section. Lower concentrations were detected from the blood vessels and around the portal tracts. The quantitative values obtained from these measurements were comparable (>90% similarity) to HPLC-MS/MS results obtained from extracts of the same tissue.

DB289 [2,5-bis(4-amidinophenyl)furan-bis-O-methylamidoxime] is biotransformed to the potent antiparasitic diamidine DB75 [2,5-bis(4-amidinophenyl) furan] by sequential oxidative O-demethyl-ation and reductive N-dehydroxylation reactions. Previous work demonstrated that the N-dehydroxylation reactions are catalyzed by cytochrome b 5 /NADH-cytochrome b 5 reductase. Enzymes responsible for catalyzing the DB289 O-demethylation pathway have not been identified. We report an in vitro metabolism study to characterize enzymes in human liver microsomes (HLMs) that catalyze the initial O-demethylation of DB289 (M1 formation). Potent inhibition by 1-aminobenzotriazole confirmed that M1 formation is catalyzed by P450 enzymes. M1 formation by HLMs was NADPHdependent, with a K m and V max of 0.5 M and 3.8 nmol/min/mg protein, respectively. Initial screening showed that recombinant CYP1A1, CYP1A2, and CYP1B1 were efficient catalysts of M1 formation. However, none of these three enzymes was responsible for M1 formation by HLMs. Further screening showed that recombinant CYP2J2, CYP4F2, and CYP4F3B could also catalyze M1 formation. An antibody against CYP4F2, which inhibited both CYP4F2 and CYP4F3B, inhibited 91% of M1 formation by HLMs. Two inhibitors of P450-mediated arachidonic acid metabolism, HET0016 (Nhydroxy-N-(4-n-butyl-2-methylphenyl)formamidine) and 17-octadecynoic acid, effectively inhibited M1 formation by HLMs. Inhibition studies with ebastine and antibodies against CYP2J2 suggested that CYP2J2 was not involved in M1 formation by HLMs. Additionally, ketoconazole preferentially inhibited CYP4F2, but not CYP4F3B, and partially inhibited M1 formation by HLMs. We conclude that CYP4F enzymes (e.g., CYP4F2, CYP4F3B) are the major enzymes responsible for M1 formation by HLMs. These findings indicate that, in human liver, members of the CYP4F subfamily biotransform not only endogenous compounds but also xenobiotics.As part of our search for new lead compounds for the treatment of African trypanosomiasis (African sleeping sickness) and other parasitic infections, aromatic dicationic compounds, such as DB75 [2,5-bis(4-amidinophenyl) furan], have been evaluated for efficacy in multiple models of infection. These diamidine-type compounds are effective against a broad range of pathogens in vitro, including Trypanosoma brucei, Leishmania spp., Pneumocystis carinii, and

Small metabolites are essential for normal and diseased biological function but are difficult to study because of their inherent structural complexity. MALDI imaging mass spectrometry (IMS) of small metabolites is particularly challenging as MALDI matrix clusters are often isobaric with metabolite ions, requiring high resolving power instrumentation or derivatization to circumvent this issue. An alternative to this is to perform ion mobility separation before ion detection, enabling the visualization of metabolites without the interference of matrix ions. Here, we use MALDI timsTOF IMS to image small metabolites at high spatial resolution within the human kidney. Through this, we have found metabolites, such as arginic acid, acetylcarnitine, and choline that localize to the cortex, medulla, and renal pelvis, respectively. We have also demonstrated that trapped ion mobility spectrometry (TIMS) can resolve matrix peaks from metabolite signal and separate both isobaric and isomeric metabolites with different localizations within the kidney. The added ion mobility data dimension dramatically increased the peak capacity for molecular imaging experiments. Future work will involve further exploring the small metabolite profiles of human kidneys as a function of age, gender, and ethnicity. File list (3) download file view on ChemRxiv Neumann_AnalChem_LMWmetabolites_SI_Submitted ver... (9.86 MiB) download file view on ChemRxiv Neumann_AnalChem_LMWmetabolites_20200511_Subm... (1.20 MiB) download file view on ChemRxiv Neumann_AnalChem_LMWmetabolites_20200511_Sub... (78.92 MiB)

DB289 is a promising new antimalarial compound that could become an important component of new antimalarial combinations.

To date, proteomic analyses on gastrointestinal cancer tissue samples have been performed using surgical specimens only, which are obtained after a diagnosis is made. To determine if a proteomic signature obtained from endoscopic biopsy samples could be found to assist with diagnosis, frozen endoscopic biopsy samples collected from 63 gastric cancer patients and 43 healthy volunteers were analyzed using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry. A statistical classification model was developed to distinguish tumor from normal tissues using half the samples and validated with the other half. A protein profile was discovered consisting of 73 signals that could classify 32 cancer and 22 normal samples in the validation set with high predictive values (positive and negative predictive values for cancer, 96.8% and 91.3%; sensitivity, 93.8%; specificity, 95.5%). Signals overexpressed in tumors were identified as α-defensin-1, α-defensin-2, calgranulin A, and calgranulin B. A protein profile was also found to distinguish pathologic stage Ia (pT1N0M0) samples (n = 10) from more advanced stage (Ib or higher) tumors (n = 48). Thus, protein profiles obtained from endoscopic biopsy samples may be useful in assisting with the diagnosis of gastric cancer and, possibly, in identifying early stage disease.