Software Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics.

The annotation of small molecules remains a major challenge in untargeted mass spectrometry-based metabolomics. We here critically discuss structured elucidation approaches and software that are designed to help during the annotation of unknown compounds. Only by elucidating unknown metabolites first is it possible to biologically interpret complex systems, to map compounds to pathways and to create reliable predictive metabolic models for translational and clinical research. These strategies include the construction and quality of tandem mass spectral databases such as the coalition of MassBank repositories and investigations of MS/MS matching confidence. We present in silico fragmentation tools such as MS-FINDER, CFM-ID, MetFrag, ChemDistiller and CSI:FingerID that can annotate compounds from existing structure databases and that have been used in the CASMI (critical assessment of small molecule identification) contests. Furthermore, the use of retention time models from liquid chromatography and the utility of collision cross-section modelling from ion mobility experiments are covered. Workflows and published examples of successfully annotated unknown compounds are included

Comprehensive comparison of in silico MS/MS fragmentation tools of the CASMI contest: database boosting is needed to achieve 93% accuracy.

In mass spectrometry-based untargeted metabolomics, rarely more than 30% of the compounds are identified. Without the true identity of these molecules it is impossible to draw conclusions about the biological mechanisms, pathway relationships and provenance of compounds. The only way at present to address this discrepancy is to use in silico fragmentation software to identify unknown compounds by comparing and ranking theoretical MS/MS fragmentations from target structures to experimental tandem mass spectra (MS/MS). We compared the performance of four publicly available in silico fragmentation algorithms (MetFragCL, CFM-ID, MAGMa+ and MS-FINDER) that participated in the 2016 CASMI challenge. We found that optimizing the use of metadata, weighting factors and the manner of combining different tools eventually defined the ultimate outcomes of each method. We comprehensively analysed how outcomes of different tools could be combined and reached a final success rate of 93% for the training data, and 87% for the challenge data, using a combination of MAGMa+, CFM-ID and compound importance information along with MS/MS matching. Matching MS/MS spectra against the MS/MS libraries without using any in silico tool yielded 60% correct hits, showing that the use of in silico methods is still important

Optimization of the laboratory brewery vessel washing conditions

U ovom istraživanju praćene su različite koncentracije metalnih iona (aluminija, bakra, željeza, molibdena i kositra) u vodi za ispiranje kotla za kominu laboratorijske minipivovare. Proces ispiranja optimiran je obzirom na vrijeme ispiranja te na koncentraciju nitratne kiseline u vodi za ispiranje kotla za kominu. Postupak dizajniranja eksperimenta, optimiranja procesa ispiranja i predviđanja ponašanja sustava provedeno je pomoću računalnog programa Design Expert (verzija 7, kompanije State-Ease, USA). Određeni su optimalni uvjeti ispiranja (idealno vrijeme ispiranja i koncentracija nitratne kiseline u vodi za ispiranje) korištenjem dva kriterija: minimalno dopuštenoj koncentraciji nitratne kiseline za ostvarivanje zadovoljavajućeg ispiranja (prema protokolu o sanitaciji pivovara) i maksimalno dopuštenim koncentracijama teških metala (prema Zakonu o vodama NN 107/95, 150/05). Optimirane vrijednosti zadovoljavaju navedene kriterije te se mogu primijeniti u sanitaciji industrijskih pivovara.In this research different concentrations of heavy metal ions (Al, Cu, Fe, Mo and Sn) were monitored in the waste water used to rinse the laboratory brewery vessel. The rinsing process was optimized considering the time of rinsing and the nitric acid concentration in the solution prepared for rinsing the vessel. Experiment design, rinsing optimization and system prediction was made using computer program Design Expert (version 7, State-Ease Company, USA). Optimization conditions were determined (optimal rinsing time and concentration of nitric acid in the solution prepared for vessel rinsing) using two criteria: minimum concentration of nitric acid allowed for satisfying vessel rinsing (according to brewery sanitation protocol) and maximum concentration of nitric acid allowed (according to Water Act NN 107/95, 150/05). Optimized values satisfy the criteria and could be used in sanitation of industrial breweries

Optimization of the laboratory brewery vessel washing conditions

U ovom istraživanju praćene su različite koncentracije metalnih iona (aluminija, bakra, željeza, molibdena i kositra) u vodi za ispiranje kotla za kominu laboratorijske minipivovare. Proces ispiranja optimiran je obzirom na vrijeme ispiranja te na koncentraciju nitratne kiseline u vodi za ispiranje kotla za kominu. Postupak dizajniranja eksperimenta, optimiranja procesa ispiranja i predviđanja ponašanja sustava provedeno je pomoću računalnog programa Design Expert (verzija 7, kompanije State-Ease, USA). Određeni su optimalni uvjeti ispiranja (idealno vrijeme ispiranja i koncentracija nitratne kiseline u vodi za ispiranje) korištenjem dva kriterija: minimalno dopuštenoj koncentraciji nitratne kiseline za ostvarivanje zadovoljavajućeg ispiranja (prema protokolu o sanitaciji pivovara) i maksimalno dopuštenim koncentracijama teških metala (prema Zakonu o vodama NN 107/95, 150/05). Optimirane vrijednosti zadovoljavaju navedene kriterije te se mogu primijeniti u sanitaciji industrijskih pivovara.In this research different concentrations of heavy metal ions (Al, Cu, Fe, Mo and Sn) were monitored in the waste water used to rinse the laboratory brewery vessel. The rinsing process was optimized considering the time of rinsing and the nitric acid concentration in the solution prepared for rinsing the vessel. Experiment design, rinsing optimization and system prediction was made using computer program Design Expert (version 7, State-Ease Company, USA). Optimization conditions were determined (optimal rinsing time and concentration of nitric acid in the solution prepared for vessel rinsing) using two criteria: minimum concentration of nitric acid allowed for satisfying vessel rinsing (according to brewery sanitation protocol) and maximum concentration of nitric acid allowed (according to Water Act NN 107/95, 150/05). Optimized values satisfy the criteria and could be used in sanitation of industrial breweries

Software Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics

The annotation of small molecules remains a major challenge in untargeted mass spectrometry-based metabolomics. We here critically discuss structured elucidation approaches and software that are designed to help during the annotation of unknown compounds. Only by elucidating unknown metabolites first is it possible to biologically interpret complex systems, to map compounds to pathways and to create reliable predictive metabolic models for translational and clinical research. These strategies include the construction and quality of tandem mass spectral databases such as the coalition of MassBank repositories and investigations of MS/MS matching confidence. We present in silico fragmentation tools such as MS-FINDER, CFM-ID, MetFrag, ChemDistiller and CSI:FingerID that can annotate compounds from existing structure databases and that have been used in the CASMI (critical assessment of small molecule identification) contests. Furthermore, the use of retention time models from liquid chromatography and the utility of collision cross-section modelling from ion mobility experiments are covered. Workflows and published examples of successfully annotated unknown compounds are included

Investigation into Cellular Glycolysis for the Mechanism Study of Energy Metabolism Disorder Triggered by Lipopolysaccharide

Lipopolysaccharide (LPS) is the main virulence factor of Gram-negative bacteria, which can incite inflammation in tissues by inducing cells to secrete a variety of proinflammatory mediators, including cytokines, chemokines, interleukins, and prostaglandins. Herein, we chose LPS as an inducer to establish an inflammatory model of HeLa cells, and explored the effects of LPS on energy metabolism. We treated HeLa cells with different concentrations (0, 0.4, 1.0, 2.0, 4.0, and 6.0 μg/mL) of LPS for 24 h, and explored its effects on intercellular adenosine triphosphate (ATP) levels, intercellular nitrous oxide (NO) content, mitochondrial functions, and enzyme activities related to energy metabolism. Furthermore, we used metabonomics to study the metabolites that participated in energy metabolism. We found a positive correlation between LPS concentrations and intracellular ATP levels. In addition, LPS increased intracellular NO production, altered mitochondrial functions, strengthened glycolytic enzyme activities, and changed metabolites related to energy metabolism. Hence, in this study, we showed that LPS can strengthen energy metabolism by enhancing glycolysis, which could be used as an early diagnostic biomarker or a novel therapeutic target for inflammation-associated cancers

Hexosamine biosynthetic pathway and O-GlcNAc-processing enzymes regulate daily rhythms in protein O-GlcNAcylation.

The integration of circadian and metabolic signals is essential for maintaining robust circadian rhythms and ensuring efficient metabolism and energy use. Using Drosophila as an animal model, we show that cellular protein O-GlcNAcylation exhibits robust 24-hour rhythm and represents a key post-translational mechanism that regulates circadian physiology. We observe strong correlation between protein O-GlcNAcylation rhythms and clock-controlled feeding-fasting cycles, suggesting that O-GlcNAcylation rhythms are primarily driven by nutrient input. Interestingly, daily O-GlcNAcylation rhythms are severely dampened when we subject flies to time-restricted feeding at unnatural feeding time. This suggests the presence of clock-regulated buffering mechanisms that prevent excessive O-GlcNAcylation at non-optimal times of the day-night cycle. We show that this buffering mechanism is mediated by the expression and activity of GFAT, OGT, and OGA, which are regulated through integration of circadian and metabolic signals. Finally, we generate a mathematical model to describe the key factors that regulate daily O-GlcNAcylation rhythm

Hexosamine biosynthetic pathway and O-GlcNAc-processing enzymes regulate daily rhythms in protein O-GlcNAcylation.

The integration of circadian and metabolic signals is essential for maintaining robust circadian rhythms and ensuring efficient metabolism and energy use. Using Drosophila as an animal model, we show that cellular protein O-GlcNAcylation exhibits robust 24-hour rhythm and represents a key post-translational mechanism that regulates circadian physiology. We observe strong correlation between protein O-GlcNAcylation rhythms and clock-controlled feeding-fasting cycles, suggesting that O-GlcNAcylation rhythms are primarily driven by nutrient input. Interestingly, daily O-GlcNAcylation rhythms are severely dampened when we subject flies to time-restricted feeding at unnatural feeding time. This suggests the presence of clock-regulated buffering mechanisms that prevent excessive O-GlcNAcylation at non-optimal times of the day-night cycle. We show that this buffering mechanism is mediated by the expression and activity of GFAT, OGT, and OGA, which are regulated through integration of circadian and metabolic signals. Finally, we generate a mathematical model to describe the key factors that regulate daily O-GlcNAcylation rhythm