Quantitative structure-retention relationships applied to liquid chromatography gradient elution method for the determination of carbonyl-2,4-dinitrophenylhydrazone compounds

Facilitating structural elucidation of small environmental solutes in RPLC-HRMS by retention index prediction

Implementing effective environmental management strategies requires a comprehensive understanding of the chemical composition of environmental pollutants, particularly in complex mixtures. Utilizing innovative analytical techniques, such as high-resolution mass spectrometry and predictive retention index models, can provide valuable insights into the molecular structures of environmental contaminants. Liquid Chromatography-High-Resolution Mass Spectrometry is a powerful tool for the identification of isomeric structures in complex samples. However, there are some limitations that can prevent accurate isomeric structure identification, particularly in cases where the isomers have similar mass and fragmentation patterns. Liquid chromatographic retention, determined by the size, shape, and polarity of the analyte and its interactions with the stationary phase, contains valuable 3D structural information that is vastly underutilized. Therefore, a predictive retention index model is developed which is transferrable to LC-HRMS systems and can assist in the structural elucidation of unknowns. The approach is currently restricted to carbon, hydrogen, and oxygen-based molecules <500 g mol-1. The methodology facilitates the acceptance of accurate structural formulas and the exclusion of erroneous hypothetical structural representations by leveraging retention time estimations, thereby providing a permissible tolerance range for a given elemental composition and experimental retention time. This approach serves as a proof of concept for the development of a Quantitative Structure-Retention Relationship model using a generic gradient LC approach. The use of a widely used reversed-phase (U)HPLC column and a relatively large set of training (101) and test compounds (14) demonstrates the feasibility and potential applicability of this approach for predicting the retention behaviour of compounds in complex mixtures. By providing a standard operating procedure, this approach can be easily replicated and applied to various analytical challenges, further supporting its potential for broader implementation.

Quantitative Structure–Retention Relationship Analysis of Polycyclic Aromatic Compounds in Ultra-High Performance Chromatography

A comparative quantitative structure–retention relationship (QSRR) study was carried out to predict the retention time of polycyclic aromatic hydrocarbons (PAHs) using molecular descriptors. The molecular descriptors were generated by the software Dragon and employed to build QSRR models. The effect of chromatographic parameters, such as flow rate, temperature, and gradient time, was also considered. An artificial neural network (ANN) and Partial Least Squares Regression (PLS-R) were used to investigate the correlation between the retention time, taken as the response, and the predictors. Six descriptors were selected by the genetic algorithm for the development of the ANN model: the molecular weight (MW); ring descriptor types nCIR and nR10; radial distribution functions RDF090u and RDF030m; and the 3D-MoRSE descriptor Mor07u. The most significant descriptors in the PLS-R model were MW, RDF110u, Mor20u, Mor26u, and Mor30u; edge adjacency indice SM09_AEA (dm); 3D matrix-based descriptor SpPosA_RG; and the GETAWAY descriptor H7u. The built models were used to predict the retention of three analytes not included in the calibration set. Taking into account the statistical parameter RMSE for the prediction set (0.433 and 0.077 for the PLS-R and ANN models, respectively), the study confirmed that QSRR models, associated with chromatographic parameters, are better described by nonlinear methods.

Phytohormone treatment induces generation of cryptic peptides with antimicrobial activity in the Moss Physcomitrella patens

BACKGROUND

Cryptic peptides (cryptides) are small bioactive molecules generated via degradation of functionally active proteins. Only a few examples of plant cryptides playing an important role in plant defense have been reported to date, hence our knowledge about cryptic signals hidden in protein structure remains very limited. Moreover, little is known about how stress conditions influence the size of endogenous peptide pools, and which of these peptides themselves have biological functions is currently unclear.

RESULTS

Here, we used mass spectrometry to comprehensively analyze the endogenous peptide pools generated from functionally active proteins inside the cell and in the secretome from the model plant Physcomitrella patens. Overall, we identified approximately 4,000 intracellular and approximately 500 secreted peptides. We found that the secretome and cellular peptidomes did not show significant overlap and that respective protein precursors have very different protein degradation patterns. We showed that treatment with the plant stress hormone methyl jasmonate induced specific proteolysis of new functional proteins and the release of bioactive peptides having an antimicrobial activity and capable to elicit the expression of plant defense genes. Finally, we showed that the inhibition of protease activity during methyl jasmonate treatment decreased the secretome antimicrobial potential, suggesting an important role of peptides released from proteins in immune response.

CONCLUSIONS

Using mass-spectrometry, in vitro experiments and bioinformatics analysis, we found that methyl jasmonate acid induces significant changes in the peptide pools and that some of the resulting peptides possess antimicrobial and regulatory activities. Moreover, our study provides a list of peptides for further study of potential plant cryptides.

UHPLC Analysis of Saffron (Crocus sativus L.): Optimization of Separation Using Chemometrics and Detection of Minor Crocetin Esters

Ultra-high performance liquid chromatography (UHPLC) coupled with diode array detection (DAD) was applied to improve separation and detection of mono- and bis-glucosyl esters of crocetin (crocins), the main red-colored constituents of saffron (Crocus sativus L.), and other polar components. Response surface methodology (RSM) was used to optimise the chromatographic resolution on the Kinetex C18 (Phenomenex) column taking into account of the combined effect of the column temperature, the eluent flow rate and the slope of a linear eluent concentration gradient. A three-level full-factorial design of experiments was adopted to identify suitable combinations of the above factors. The influence of the separation conditions on the resolutions of 22 adjacent peaks was simultaneously modelled by a multi-layer artificial neural network (ANN) in which a bit string representation was used to identify the target analytes. The chromatogram collected under the optimal separation conditions revealed a higher number of crocetin esters than those already characterised by means of mass-spectrometry data and usually detected by HPLC. Ultra-high performance liquid chromatography analyses carried out on the novel Luna Omega Polar C18 (Phenomenex) column confirmed the large number of crocetin derivatives. Further work is in progress to acquire mass-spectrometry data and to clarify the chemical structure to the newly found saffron components.

QSRR Modeling for Metabolite Standards Analyzed by Two Different Chromatographic Columns Using Multiple Linear Regression

Modified quantitative structure retention relationships (QSRRs) are proposed and applied to describe two retention data sets: A set of 94 metabolites studied by a hydrophilic interaction chromatography system under organic content gradient conditions and a set of tryptophan and its major metabolites analyzed by a reversed-phase chromatographic system under isocratic as well as pH and/or simultaneous pH and organic content gradient conditions. According to the proposed modification, an additional descriptor is added to a conventional QSRR expression, which is the analyte retention time, tR(R), measured under the same elution conditions, but in a second chromatographic column considered as a reference one. The 94 metabolites were studied on an Amide column using a Bare Silica column as a reference. For the second dataset, a Kinetex EVO C18 and a Gemini-NX column were used, where each of them was served as a reference column of the other. We found in all cases a significant improvement of the performance of the QSRR models when the descriptor tR(R) was considered.

A new agent for derivatizing carbonyl species used to investigate limonene ozonolysis

A new method for derivatizing carbonyl compounds is presented. The conversion of a series of dicarbonyls to oximes in aqueous solution and from gas-phase sampling was achieved using O-tert-butyl-hydroxylamine hydrochloride (TBOX). Some advantages of using this derivatization agent include: aqueous reactions, lower molecular weight oximes, and shortened oxime-formation reaction time. Additionally, the TBOX derivatization technique was used to investigate the carbonyl reaction products from limonene ozonolysis. With ozone (O3) as the limiting reagent, four carbonyl compounds were detected: 7-hydroxy-6-oxo-3-(prop-1-en-2-yl)heptanal; 3-Isopropenyl-6-oxoheptanal (IPOH), 3-acetyl-6-oxoheptanal (3A6O) and one carbonyl of unknown structure. Using cyclohexane as a hydroxyl (OH•) radical scavenger, the relative yields (peak area) of the unknown carbonyl, IPOH, and 3A6O were reduced indicating the influence secondary OH radicals have on limonene ozonolysis products. The relative yield of the hydroxy-dicarbonyl based on the chromatogram was unchanged suggesting it is only made by the limonene + O3 reaction. The detection of 3A6O using TBOX highlights the advantages of a smaller molecular weight derivatization agent for the detection of multi-carbonyl compounds. The use of TBOX derivatization if combined with other derivatization agents may address a recurring need to simply and accurately detect multi-functional oxygenated species in air.

Carbonylation as a key reaction in anaerobic acetone activation by Desulfococcus biacutus

Acetone is activated by aerobic and nitrate-reducing bacteria via an ATP-dependent carboxylation reaction to form acetoacetate as the first reaction product. In the activation of acetone by sulfate-reducing bacteria, acetoacetate has not been found to be an intermediate. Here, we present evidence of a carbonylation reaction as the initial step in the activation of acetone by the strictly anaerobic sulfate reducer Desulfococcus biacutus. In cell suspension experiments, CO was found to be a far better cosubstrate for acetone activation than CO2. The hypothetical reaction product, acetoacetaldehyde, is extremely reactive and could not be identified as a free intermediate. However, acetoacetaldehyde dinitrophenylhydrazone was detected by mass spectrometry in cell extract experiments as a reaction product of acetone, CO, and dinitrophenylhydrazine. In a similar assay, 2-amino-4-methylpyrimidine was formed as the product of a reaction between acetoacetaldehyde and guanidine. The reaction depended on ATP as a cosubstrate. Moreover, the specific activity of aldehyde dehydrogenase (coenzyme A [CoA] acylating) tested with the putative physiological substrate was found to be 153 ± 36 mU mg(-1) protein, and its activity was specifically induced in extracts of acetone-grown cells. Moreover, acetoacetyl-CoA was detected (by mass spectrometry) after the carbonylation reaction as the subsequent intermediate after acetoacetaldehyde was formed. These results together provide evidence that acetoacetaldehyde is an intermediate in the activation of acetone by sulfate-reducing bacteria.