Critical Review of Selected Analytical Platforms for GC-MS Metabolomics Profiling-Case Study: HS-SPME/GC-MS Analysis of Blackberry's Aroma.

Data processing and data extraction are the first, and most often crucial, steps in metabolomics and multivariate data analysis in general. There are several software solutions for these purposes in GC-MS metabolomics. It becomes unclear which platform offers what kind of data and how that information influences the analysis's conclusions. In this study, selected analytical platforms for GC-MS metabolomics profiling, SpectConnect and XCMS as well as MestReNova software, were used to process the results of the HS-SPME/GC-MS aroma analyses of several blackberry varieties. In addition, a detailed analysis of the identification of the individual components of the blackberry aroma club varieties was performed. In total, 72 components were detected in the XCMS platform, 119 in SpectConnect, and 87 and 167 in MestReNova, with automatic integral and manual correction, respectively, as well as 219 aroma components after manual analysis of GC-MS chromatograms. The obtained datasets were fed, for multivariate data analysis, to SIMCA software, and underwent the creation of PCA, OPLS, and OPLS-DA models. The results of the validation tests and VIP-pred. scores were analyzed in detail.

Clinopodium L. Taxa from the Balkans-Are There Unique Leaf Micromorphological and Phytochemical Patterns?

The concept of the genus Clinopodium L. has changed considerably since its first description. Most of the currently accepted species of the genus have traditionally been treated as separate genera in the group Satureja sensu lato: Clinopodium L., Calamintha sensu Miller or Moench, and Acinos sensu Miller or Moench. This study aimed to gain a better insight into the species diversity of Clinopodium L. from the Balkans by analyzing the taxa that have traditionally been placed in separate genera. The alkane profile and the micromorphological characteristics of the leaves are analyzed. The leaves are visualized using scanning electron microscopy, and alkanes are isolated using n-hexane as a solvent and analyzed using gas chromatography/mass spectrometry. The alkane profile showed the differentiation of the Acinos-group from the other taxa based on the dominant n-C31, while most of the other taxa contained n-C33 as the dominant alkane. The micromorphological features also showed clear differences between the previously recognized genera, especially in the capitate trichomes. The results showed that micromorphological patterns are highly variable in certain groups of the genus Clinopodium.

Modeling and predicting cancer clonal evolution with reinforcement learning.

Cancer results from an evolutionary process that typically yields multiple clones with varying sets of mutations within the same tumor. Accurately modeling this process is key to understanding and predicting cancer evolution. Here, we introduce clone to mutation (CloMu), a flexible and low-parameter tree generative model of cancer evolution. CloMu uses a two-layer neural network trained via reinforcement learning to determine the probability of new mutations based on the existing mutations on a clone. CloMu supports several prediction tasks, including the determination of evolutionary trajectories, tree selection, causality and interchangeability between mutations, and mutation fitness. Importantly, previous methods support only some of these tasks, and many suffer from overfitting on data sets with a large number of mutations. Using simulations, we show that CloMu either matches or outperforms current methods on a wide variety of prediction tasks. In particular, for simulated data with interchangeable mutations, current methods are unable to uncover causal relationships as effectively as CloMu. On breast cancer and leukemia cohorts, we show that CloMu determines similarities and causal relationships between mutations as well as the fitness of mutations. We validate CloMu's inferred mutation fitness values for the leukemia cohort by comparing them to clonal proportion data not used during training, showing high concordance. In summary, CloMu's low-parameter model facilitates a wide range of prediction tasks regarding cancer evolution on increasingly available cohort-level data sets.

UPP2: fast and accurate alignment of datasets with fragmentary sequences.

MOTIVATION: Multiple sequence alignment (MSA) is a basic step in many bioinformatics pipelines. However, achieving highly accurate alignments on large datasets, especially those with sequence length heterogeneity, is a challenging task. Ultra-large multiple sequence alignment using Phylogeny-aware Profiles (UPP) is a method for MSA estimation that builds an ensemble of Hidden Markov Models (eHMM) to represent an estimated alignment on the full-length sequences in the input, and then adds the remaining sequences into the alignment using selected HMMs in the ensemble. Although UPP provides good accuracy, it is computationally intensive on large datasets. RESULTS: We present UPP2, a direct improvement on UPP. The main advance is a fast technique for selecting HMMs in the ensemble that allows us to achieve the same accuracy as UPP but with greatly reduced runtime. We show that UPP2 produces more accurate alignments compared to leading MSA methods on datasets exhibiting substantial sequence length heterogeneity and is among the most accurate otherwise. AVAILABILITY AND IMPLEMENTATION: https://github.com/gillichu/sepp. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Metabolomics as a Potential Chemotaxonomical Tool: Application on the Selected Euphorbia Species Growing Wild in Serbia.

Chemotaxonomy presents various challenges that need to be overcome in order to obtain valid and reliable results. Individual genetic and environmental variations can give a false picture and lead to wrong conclusions. Applying a holistic approach, based on multivariate data analysis, these challenges can be overcome. Thus, a metabolomics approach has to be optimized depending on the subject of research. We used 1H NMR-based metabolomics as a potential chemotaxonomic tool on the selected Euphorbia species growing wild in Serbia. Principal components analysis (PCA), soft independent modeling by class analogy (SIMCA) and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) were used to analyze obtained NMR data in order to reveal chemotaxonomic biomarkers. The standard protocol for plant metabolomics was optimized aiming to extract more specific metabolites, which are characteristic for the Euphorbia genus. The obtained models were validated, which revealed that variables unique for each species were associated with certain classes of molecules according to literature data. In E. salicifolia, acacetin-7-O-glycoside (not found before in the species) was detected, and the structure of the aglycone part was solved based on 2D NMR data. In the presented paper, we have shown that metabolomics can be successfully used in Euphorbia chemotaxonomy.

Charge Transport inside TiO2 Memristors Prepared via FEBID.

We fabricated memristive devices using focused electron beam-induced deposition (FEBID) as a direct-writing technique employing a Pt/TiO2/Pt sandwich layer device configuration. Pinching in the measured current-voltage characteristics (i-v), the characteristic fingerprint of memristive behavior was clearly observed. The temperature dependence was measured for both high and low resistive states in the range from 290 K down to about 2 K, showing a stretched exponential behavior characteristic of Mott-type variable-range hopping. From this observation, a valence change mechanism of the charge transport inside the TiO2 layer can be deduced.

Plant Metabolomics as a Tool for Detecting Adulterants in Edible Plant: A Case Study of Allium ursinum.

Allium ursinum and poisonous adulterants Convallaria majalis and Arum maculatum were used as a model for detection of adulterants in edible plant. A. ursinum samples were spiked with C. majalis and A. maculatum to mimic adulteration. Metabolomic fingerprinting of all samples was performed using 1H NMR spectroscopy, and the resulting data sets were subjected to multivariate data analysis. As a result of this analysis, signals of adulterants were extracted from the data, and the structures of biomarkers of adulteration from partially purified samples were elucidated using 2D NMR and LC-MS techniques. Thus, isovitexin and vicenin II, azetidine-2-carboxylic acid, and trigonelline indicated adulteration of A. ursinum samples with C. majalis. Isovitexin was also recognized to be an indicator of adulteration of A. ursinum with A. maculatum. In conclusion, the case study of A. ursinum suggested that plant metabolomics approach could be utilized for identification of low molecular weight biomarkers of adulteration in edible plants.

Metabolomics study of the desiccation and recovery process in the resurrection plants Ramonda serbica and R. nathaliae.

INTRODUCTION: Ramonda serbica and R. nathaliae are resurrection plants that have the remarkable ability to survive the complete desiccation of their vegetative organs (i.e. leaves, stem, roots) during periods of drought and rapidly revive when rewatered and rehydrated. OBJECTIVE: To investigate metabolic changes in R. serbica and R. nathaliae during their desiccation and recovery process METHODS: Proton nuclear magnetic resonance (1 H-NMR) and gas chromatography-mass spectrometry (GC-MS)-based metabolomics approach coupled with multivariate data analysis was utilised to identify the metabolomes of the plants from 90 biological replicates. RESULTS: Sucrose and the polyphenolic glycoside myconoside were predominant in almost equal amounts in all samples studied, regardless of their water content at sampling. During the dehydration process, a decrease in the relative content of fructose, galactose, and galactinol was observed while the contents of those metabolites were preserved in the partially rehydrated plants. Raffinose and myo-inositol were accumulated in dry samples. CONCLUSION: Using 1 H-NMR and GC-MS as two complementary analytical platforms provided a more complete picture of the metabolite composition for investigation of the desiccation and recovery process in resurrection plants.

Sleep quality and patterns of young West Balkan adults during the third wave of COVID-19 pandemic: a cross-sectional study.

OBJECTIVES: To evaluate the sleep patterns among young West Balkan adults during the third wave of the COVID-19 pandemic. DESIGN AND SETTING: Cross-sectional study conducted using an anonymous online questionnaire based on established sleep questionnaires Insomnia Severity Index (ISI) and Pittsburgh Sleep Quality Index (PSQI) (February-August 2021). PARTICIPANTS: Young adults of Bosnia and Herzegovina, Croatia and Serbia. RESULTS: Of 1058 subjects, mean age was 28.19±9.29 years; majority were women (81.4%) and students (61.9%). Compared with before the pandemic, 528 subjects (49.9%) reported a change in sleeping patterns during the pandemic, with 47.3% subjects reporting sleeping less. Mean sleeping duration during the COVID-19 pandemic was 7.71±2.14 hours with median sleep latency of 20 (10.0-30.0) min. Only 91 (8.6%) subjects reported consuming sleeping medications. Of all, 574 (54.2%) subjects had ISI score >7, with majority (71.2%) having subthreshold insomnia, and 618 (58.4%) PSQI score ≥5, thus indicating poor sleep quality. Of 656 (62.0%) tested subjects, 464 (43.9%) were COVID-19 positive (both symptomatic and asymptomatic) who were 48.8%, next to women (70%), more likely to have insomnia symptoms; and 66.9% were more likely to have poor sleep quality. Subjects using sleep medication were 44 times, and subjects being positive to ISI 15.36 times more likely to have poor sleep quality. In contrast, being a student was a negative independent predictor for both insomnia symptoms and poor sleep quality, and mental labour and not working were negative independent predictors for insomnia symptoms. CONCLUSIONS: During the third wave of the pandemic, sleep patterns were impaired in about half of young West Balkan adults, with COVID-19-positive subjects and being women as positive independent predictors and being a student as negative independent predictor of impaired sleep pattern. Due to its importance in long-term health outcomes, sleep quality in young adults, especially COVID-19-positive ones, should be thoroughly assessed.

GC-FID-MS Based Metabolomics to Access Plum Brandy Quality.

Plum brandy (Slivovitz (en); Sljivovica(sr)) is an alcoholic beverage that is increasingly consumed all over the world. Its quality assessment has become of great importance. In our study, the main volatiles and aroma compounds of 108 non-aged plum brandies originating from three plum cultivars, and fermented using different conditions, were investigated. The chemical profiles obtained after two-step GC-FID-MS analysis were subjected to multivariate data analysis to reveal the peculiarity in different cultivars and fermentation process. Correlation of plum brandy chemical composition with its sensory characteristics obtained by expert commission was also performed. The utilization of PCA and OPLS-DA multivariate analysis methods on GC-FID-MS, enabled discrimination of brandy samples based on differences in plum varieties, pH of plum mash, and addition of selected yeast or enzymes during fermentation. The correlation of brandy GC-FID-MS profiles with their sensory properties was achieved by OPLS multivariate analysis. Proposed workflow confirmed the potential of GC-FID-MS in combination with multivariate data analysis that can be applied to assess the plum brandy quality.

Chemical Characterization of Marrubium vulgare Volatiles from Serbia.

Marrubium vulgare is a cosmopolitan medicinal plant from the Lamiaceae family, which produces structurally highly diverse groups of secondary metabolites. A total of 160 compounds were determined in the volatiles from Serbia during two investigated years (2019 and 2020). The main components were E-caryophyllene, followed by germacrene D, α-humulene and α-copaene. All these compounds are from sesquiterpene hydrocarbons class which was dominant in both investigated years. This variation in volatiles composition could be a consequence of weather conditions, as in the case of other aromatic plants. According to the unrooted cluster tree with 37 samples of Marrubium sp. volatiles from literature and average values from this study, it could be said that there are several chemotypes: E-caryophyllene, ß-bisabolene, α-pinene, ß-farnesene, E-caryophyllene + caryophyllene oxide chemotype, and diverse (unclassified) chemotypes. However, occurring polymorphism could be consequence of adaptation to grow in different environment, especially ecological conditions such as humidity, temperature and altitude, as well as hybridization strongly affected the chemotypes. In addition, this paper aimed to obtain validated models for prediction of retention indices (RIs) of compounds isolated from M. vulgare volatiles. A total of 160 experimentally obtained RIs of volatile compounds was used to build the prediction models. The coefficients of determination were 0.956 and 0.964, demonstrating that these models could be used for predicting RIs, due to low prediction error and high r2.

Chemical Composition, Total Phenols and Flavonoids Contents and Antioxidant Activity as Nutritive Potential of Roasted Hazelnut Skins (Corylus avellana L.).

The present study evaluates natural composition of Serbian roasted hazelnut skins (HS) with potential role in application as functional nutrient of various food products. Total phenols (TPC) and flavonoids contents (TFC) in HS extracts obtained with different ethanol concentrations (10%-I, 50%-II and 96%-III) and their antioxidant activities were investigated. The highest total phenols content (706.0 ± 9.7 mgGAE/gextract) was observed in 96% ethanol HS extract. Ethanol HS extracts showed very high antioxidant activity with effective concentrations (EC50) ranged between 0.052 and 0.066 mg/mL. The phenol and flavonoid content of roasted HS extracts I-III was determined by HPLC-ESI-MS/MS analyses. Contents of lipids, proteins, carbohydrates, metals, and C, H, N, S elements in roasted HS were also determined. Relatively high C/N, C/P and C/N/P ratios, rich metal contents and fatty acids composition indicated that hazelnut skin might be a good candidate for use as either human or fungal functional nutrient. In addition, possible application of phenolic HS extracts as UV booster was studied by recording UV spectra (220-440 nm) of 10 mg/L of HS extracts I-III combined with 10 mg/L of chemical sunscreen agent benzophenone-3 and in vitro sun protection factor (SPF) was calculated.