Considering the physicochemical diversity of the metabolome, untargeted metabolomics will inevitably discriminate against certain compound classes. Efforts are nevertheless made to maximize the metabolome coverage. Contrary to the main steps of a typical liquid chromatography–mass spectrometry (LC–MS) metabolomics workflow, such as metabolite extraction, the sample reconstitution step has not been optimized for maximal metabolome coverage. This sample concentration step typically occurs after metabolite extraction, when dried samples are reconstituted in a solvent for injection on column. The aim of this study was to evaluate the impact of the sample reconstitution solvent composition on metabolome coverage in untargeted LC–MS metabolomics. Lysogeny Broth medium samples reconstituted in MeOH/H₂O ratios ranging from 0 to 100% MeOH and analyzed with untargeted reversed phase LC–MS showed that the highest number of metabolite features (n = 1500) was detected in samples reconstituted in 100% H₂O. As compared to a commonly used reconstitution solvent mixture of 50/50 MeOH/H₂O, our results indicate that the small fraction of compounds increasing in peak area response by the addition of MeOH to H₂O, 5%, is outweighed by the fraction of compounds with decreased response, 57%. We evaluated our results on human serum samples from lymphoma patients and healthy control subjects. Reconstitution in 100% H₂O resulted in a higher number of significant metabolites discriminating between these two groups than both 50% and 100% MeOH. These findings show that the sample reconstitution step has a clear impact on the metabolome coverage of MeOH extracted biological samples, highlighting the importance of the reconstitution solvent composition for untargeted discovery metabolomics.

Introduction Pancreatic ductal adenocarcinoma (PDAC) is the fifth most common cause of cancer-related death in Europe with a 5-year survival rate of <5%. Chronic pancreatitis (CP) is a risk factor for PDAC development, but in the majority of cases malignancy is discovered too late for curative treatment. There is at present no reliable diagnostic marker for PDAC available. Objectives The aim of the study was to identify single blood-based metabolites or a panel of metabolites discriminating PDAC and CP using liquid chromatography-mass spectrometry (LC-MS). Methods A discovery cohort comprising PDAC (n = 44) and CP (n = 23) samples was analyzed by LC-MS followed by univariate (Student’s t test) and multivariate (orthogonal partial least squares-discriminant analysis (OPLS-DA)) statistics. Discriminative metabolite features were subject to raw data examination and identification to ensure high feature quality. Their discriminatory power was then confirmed in an independent validation cohort including PDAC (n = 20) and CP (n = 31) samples. Results Glycocholic acid, N-palmitoyl glutamic acid and hexanoylcarnitine were identified as single markers discriminating PDAC and CP by univariate analysis. OPLS-DA resulted in a panel of five metabolites including the aforementioned three metabolites as well as phenylacetylglutamine (PAGN) and chenodeoxyglycocholate. Conclusion Using LC-MS-based metabolomics we identified three single metabolites and a five-metabolite panel discriminating PDAC and CP in two independent cohorts. Although further study is needed in larger cohorts, the metabolites identified are potentially of use in PDAC diagnostics.

Two recently discovered groups of prokaryotic di-metal carboxylate proteins harbor a heterodinuclear Mn/Fe cofactor. These are the class Ic ribonucleotide reductase R2 proteins and a group of oxidases that are found predominantly in pathogens and extremophiles, called R2-like ligand-binding oxidases (R2lox). We have recently shown that the Mn/Fe cofactor of R2lox self-assembles from Mn^II and Fe^II in vitro and catalyzes formation of a tyrosine-valine ether cross-link in the protein scaffold (Griese, J. J., Roos, K., Cox, N., Shafaat, H. S., Branca, R. M., Lehtiö, J., Gräslund, A., Lubitz, W., Siegbahn, P. E., and Högbom, M. (2013) Proc. Natl. Acad. Sci. U.S.A. 110, 17189–17194). Here, we present a detailed structural analysis of R2lox in the nonactivated, reduced, and oxidized resting Mn/Fe- and Fe/Fe-bound states, as well as the nonactivated Mn/Mn-bound state. X-ray crystallography and x-ray absorption spectroscopy demonstrate that the active site ligand configuration of R2lox is essentially the same regardless of cofactor composition. Both the Mn/Fe and the diiron cofactor activate oxygen and catalyze formation of the ether cross-link, whereas the dimanganese cluster does not. The structures delineate likely routes for gated oxygen and substrate access to the active site that are controlled by the redox state of the cofactor. These results suggest that oxygen activation proceeds via similar mechanisms at the Mn/Fe and Fe/Fe center and that R2lox proteins might utilize either cofactor in vivo based on metal availability.

Untargeted metabolic profiling has generated large activity in the field of clinical biomarker discovery. Yet, no clinically approved metabolite biomarkers have emerged with failure in validation phases often being a reason. To investigate why, we have applied untargeted metabolic profiling in a retrospective cohort of serum samples representing non-related diseases. Age and gender matched samples from patients diagnosed with pneumonia, congestive heart failure, lymphoma and healthy controls were subject to comprehensive metabolic profiling using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). The metabolic profile of each diagnosis was compared to the healthy control group and significant metabolites were filtered out using t-test with FDR correction. Metabolites found to be significant between each disease and healthy controls were compared and analyzed for overlap. Results show that despite differences in etiology and clinical disease presentation, the fraction of metabolites with an overlap between two or more diseases was 61%. A majority of these metabolites can be associated with immune responses thus representing non-disease specific events. We show that metabolic serum profiles from patients representing non-related diseases display very similar metabolic differences when compared to healthy controls. Many of the metabolites discovered as disease specific in this study have further been associated with other diseases in the literature. Based on our findings we suggest non-related disease controls in metabolomics biomarker discovery studies to increase the chances of a successful validation and future clinical applications.

Glutamate-ammonia ligase (GLUL) is important for acid-base homeostasis, ammonia detoxification, cell signaling, and proliferation. Here, we reported that GLUL ablation conferred resistance to several anticancer drugs in specific cancer cell lines while leaving other cell lines non-resistant to the same drugs. To understand the biochemical mechanics supporting this drug resistance, we compared drug-resistant GLUL knockout (KO) A549 non-small-cell lung carcinoma (NSCLC) cells with non-resistant GLUL KO H1299 NSCLC cells and found that the resistant A549 cells, to a larger extent, depended on exogenous glucose for proliferation. As GLUL activity is linked to the tricarboxylic acid (TCA) cycle via reversed glutaminolysis, we probed carbon flux through both glycolysis and TCA pathways by means of ¹³C5 glutamine, ¹³C5 glutamate, and ¹³C6 glucose tracing. We observed increased labeling of malate and aspartate in A549 GLUL KO cells, whereas the non-resistant GLUL KO H1299 cells displayed decreased ¹³C-labeling. The malate and aspartate shuttle supported cellular NADH production and was associated with cellular metabolic fitness. Inhibition of the malate-aspartate shuttle with aminooxyacetic acid significantly impacted upon cell viability with an IC₅₀ of 11.5 μM in resistant GLUL KO A549 cells compared to 28 μM in control A549 cells, linking resistance to the malate-aspartate shuttle. Additionally, rescuing GLUL expression in A549 KO cells increased drug sensitivity. We proposed a novel metabolic mechanism in cancer drug resistance where the increased capacity of the malate-aspartate shuttle increased metabolic fitness, thereby facilitating cancer cells to escape drug pressure.

The cholesterol metabolism is essential for cancer cell proliferation. We found the expression of genes involved in the cholesterol biosynthesis pathway up-regulated in the daunorubicin-resistant leukemia cell line CEM/R2, which is a daughter cell line to the leukemia cell line CCRF-CEM (CEM). Cellular ²H₂O labelling, mass spectrometry, and isotopomer analysis revealed an increase in lanosterol synthesis which was not accompanied by an increase in cholesterol flux or pool size in CEM/R2 cells. Exogenous addition of lanosterol had a negative effect on CEM/R2 and a positive effect on sensitive CEM cell viability. Treatment of CEM and CEM/R2 cells with cholesterol biosynthesis inhibitors acting on the enzymes squalene epoxidase and lanosterol synthase, both also involved in the 24,25-epoxycholesterol shunt pathway, revealed a connection of this pathway to lanosterol turnover. Our data highlight that an increased lanosterol flux poses a metabolic weakness of resistant cells that potentially could be therapeutically exploited.