Volatolomics approach by HS-SPME-GC-MS and multivariate analysis to discriminate olive tree varieties infected by Xylella fastidiosa

Metabolome classification of olive by-products from different oil presses providing insights into its potential health benefits and valorization as analyzed via multiplex MS-based techniques coupled to chemometrics

INTRODUCTION

The Olive (Olea europaea L.) is one of the most popular edible oil-producing fruits, consumed worldwide for its myriad nutritional and health benefits. Olive oil production generates huge quantities of by-products from the fruit, which are considered environmental hazards. Recently, more and more efforts have been made to valorize olive by-products as a source of low-cost, value-added food applications.

OBJECTIVE

The main objective of this study was to globally assess the metabolome of olive fruit by-products, including olive mill wastewater, olive pomace, and olive seeds from fruits from two areas, Siwa and Anshas, Egypt.

METHODS

Gas chromatography-mass spectrometry (GC-MS) and ultra-high-performance liquid chromatography with mass spectrometry (UPLC-MS) were used for profiling primary and secondary metabolites in olive by-products. Also, multivariate data analyses were used to assess variations between olive by-product samples.

RESULTS

A total of 103 primary metabolites and 105 secondary metabolites were identified by GC-MS and UPLC-MS, respectively. Fatty acids amounted to a major class in the olive by-products at 53-91%, with oleic acid dominating, especially in the pomace of Siwa. Mill wastewater was discriminated from other by-products by the presence of phenolics mainly tyrosol, hydroxyl tyrosol, and α-tocopherol as analyzed by UPLC-MS indicating their potential antioxidant activity. Pomace and seeds were rich in fatty acids/esters and hydroxy fatty acids and not readily distinguishable from each other.

CONCLUSION

The current work discusses the metabolome profile of olive waste products for valorization purposes. Pomace and seeds were enriched in fatty acids/esters, though not readily distinguishable from each other.

Decoding Metabolic Reprogramming in Plants under Pathogen Attacks, a Comprehensive Review of Emerging Metabolomics Technologies to Maximize Their Applications

In their environment, plants interact with a multitude of living organisms and have to cope with a large variety of aggressions of biotic or abiotic origin. What has been known for several decades is that the extraordinary variety of chemical compounds the plants are capable of synthesizing may be estimated in the range of hundreds of thousands, but only a fraction has been fully characterized to be implicated in defense responses. Despite the vast importance of these metabolites for plants and also for human health, our knowledge about their biosynthetic pathways and functions is still fragmentary. Recent progress has been made particularly for the phenylpropanoids and oxylipids metabolism, which is more emphasized in this review. With an increasing interest in monitoring plant metabolic reprogramming, the development of advanced analysis methods should now follow. This review capitalizes on the advanced technologies used in metabolome mapping in planta, including different metabolomics approaches, imaging, flux analysis, and interpretation using bioinformatics tools. Advantages and limitations with regards to the application of each technique towards monitoring which metabolite class or type are highlighted, with special emphasis on the necessary future developments to better mirror such intricate metabolic interactions in planta.

Selection of Elms Tolerant to Dutch Elm Disease in South-West Romania

Ophoiostoma novo- ulmi continues to be one of the most dangerous invasive fungi, destroying many autochthonous elm forests and cultures throughout the world. Searching for natural genotypes tolerant to Dutch Elm Disease (DED) is one of the main objectives of silviculturists all over the northern hemisphere in order to save the susceptible elms and to restore their ecosystem biodiversity. In this regard, the first trial was established between 1991 and 1994, in south-west Romania (Pădurea Verde, Timișoara), using three elm species (Ulmus minor, U. glabra, and U. laevis) with 38 provenances. A local strain of Ophiostoma novo-ulmi was used to artificially inoculate all elm variants and the DED evolution was observed. Furthermore, in 2018–2021 the trial was inventoried to understand the local genotype reaction to DED in the local environmental conditions after almost 30 years. The outcomes of the present study proved the continuous presence of the infections in the comparative culture and its proximity, but the identified pathogen had a new hybrid form (found for the first time in Romania) between O. novo-ulmi ssp. Americana x O. novo-ulmi ssp. novo-ulmi. Wych elm (U. glabra) was extremely sensitive to DED: only 12 trees (out of 69 found in 2018) survived in 2021, and only one tree could be selected according to the adopted health criteria (resistance and vigour). The field elm (U. minor) was sensitive to the pathogen, but there were still individuals that showed good health status and growth. In contrast, the European white elm (U. laevis) proved constant tolerance to DED: only 15% had been found dead or presented severe symptoms of dieback. Overall, the results of this study report the diverse reactions of the Romanian regional elm genotypes to DED over the last three decades, providing promising perspectives for improving the presence of elms in the forest ecosystems of the Carpathian basin.

Exploration on Varying Patterns of Morphological Features and Quality of Armeniacae Semen Amarum in Rancid Process Based on Colorimeter, Electronic Nose, and GC/MS Coupled With Human Panel

In recent years, the domestic and international trade volumes of Chinese medicinal materials (CMMs) keep increasing. By the end of 2019, the total amount of exported CMMs reached as high as US $1.137 billion, while imported was US $2.155 billion. A stable and controllable quality system of CMMs apparently becomes the most important issue, which needs multifaceted collaboration from harvesting CMMs at a proper season to storing CMMs at a proper temperature. However, due to imperfect storage conditions, different kinds of deteriorations are prone to occur, for instance, get moldy or rancid, which not only causes a huge waste of CMM resources but also poses a great threat to clinical medication safety and public health. The key issue is to quickly and accurately distinguish deteriorated CMM samples so as to avoid consuming low-quality or even harmful CMMs. However, some attention has been paid to study the changing quality of deteriorated CMMs and a suitable method for identifying them. In this study, as a medicine and food material which easily becomes rancid, armeniacae semen amarum (ASA) was chosen as a research objective, and experimental ASA samples of different rancidness degrees were collected. Then, various kinds of analytical methods and technologies were applied to explore the changing rules of ASA quality and figure out the key indicators for the quality evaluation of ASA in the rancid process, including the human panel, colorimeter, electronic nose, and GC/MS. This study aims to analyze the correlation between the external morphological features and the inner chemical compounds, to find out the specific components from "quantitative change" to "qualitative change" in the process of "getting rancid," and to discover the dynamic changes in the aforementioned key indicators at different stages of rancidness. The results showed since ASA samples began to get rancid with the extension of storage time, morphological features, namely, surface color and smell, changed significantly, and the degree of rancidness further deepened at the same time. Based on macroscopic identification accomplished via the human panel, ASA samples with varying degrees of rancidness were divided into four groups. The result of colorimeter analysis was in agreement with that of the human panel, as well as the determination of the amygdalin content and peroxide value. Moreover, there were obvious differences in the amygdalin content and peroxide value among ASA samples with different rancidness degrees. With a higher degree of rancidness, the content of amygdalin decreased, while the peroxide value increased significantly. The rancidness degree of ASA has a negative correlation with the amygdalin content and a positive correlation with the peroxide value. The newly discovered nonanal and 2-bromopropiophenone in rancid ASA samples may be the key components of "rancidity smell," and these two components would be the exclusive components that trigger "quantitative change" to "qualitative change" in the process of rancidness of ASA. This study sheds light on studying the internal mechanism of "rancidness" of CMMs and provides an important basis for the effective storage and safe medication of easy-to-get rancid herbs, and it also plays an important foundation for the establishment of a stable and controllable quality system for CMMs.

Volatolomics in healthcare and its advanced detection technology

Various diseases increasingly challenge the health status and life quality of human beings. Volatolome emitted from patients has been considered as a potential family of markers, volatolomics, for diagnosis/screening. There are two fundamental issues of volatolomics in healthcare. On one hand, the solid relationship between the volatolome and specific diseases needs to be clarified and verified. On the other hand, effective methods should be explored for the precise detection of volatolome. Several comprehensive review articles had been published in this field. However, a timely and systematical summary and elaboration is still desired. In this review article, the research methodology of volatolomics in healthcare is critically considered and given out, at first. Then, the sets of volatolome according to specific diseases through different body sources and the analytical instruments for their identifications are systematically summarized. Thirdly, the advanced electronic nose and photonic nose technologies for volatile organic compounds (VOCs) detection are well introduced. The existed obstacles and future perspectives are deeply thought and discussed. This article could give a good guidance to researchers in this interdisciplinary field, not only understanding the cutting-edge detection technologies for doctors (medicinal background), but also making reference to clarify the choice of aimed VOCs during the sensor research for chemists, materials scientists, electronics engineers, etc.

THE IMPROVEMENT OF PCA ALGORITHM AND ITS APPLICATION IN THE PREDICTION OF ELBOW KNEE JOINT INJURY

ABSTRACT Objective: There were many constraints produced by training time and joint injury to analyze the influence of the training intensity on the elbow and knee joints of athletes during the training process. Methods: An improved algorithm-based master component analysis (PCA) modeling method is proposed .1 4 4 athletes were selected in xxx and compared in three groups. Results: The improved PCA models for injury prediction were applied to athletes from group A, the traditional injury models for prediction were adopted for athletes from group B, and athletes from group C received the hospital physical examinations. The results showed that the accuracy of elbow injury in group A due to excessive exercise was 66.86%, the accuracy of hospital physical examination in group C was 67%, and the accuracy of the traditional algorithm in group B was 50%, finding that the accuracy of group A was obviously different from group B (P < 0.05). Compared with other injuries caused by excessive friction, the detection accuracy of knee injuries caused by excessive friction in group A was 62%, that in group B was 44%, and that in group C was 63%. There was a statistically marked difference between groups A and B (P < 0.05). Conclusions: A PCA - based model of athletes’ overtraining injury has high accuracy and adaptability, predicting elbow injury. Level of evidence II; Therapeutic studies - investigation of treatment results.

HPLC-MS/MS method applied to an untargeted metabolomics approach for the diagnosis of "olive quick decline syndrome"

Olive quick decline syndrome (OQDS) is a disorder associated with bacterial infections caused by Xylella fastidiosa subsp. pauca ST53 in olive trees. Metabolic profile changes occurring in infected olive trees are still poorly investigated, but have the potential to unravel reliable biomarkers to be exploited for early diagnosis of infections. In this study, an untargeted metabolomic method using high-performance liquid chromatography coupled to quadrupole-time-of-flight high-resolution mass spectrometry (HPLC-ESI-Q-TOF-MS) was used to detect differences in samples (leaves) from healthy (Ctrl) and infected (Xf) olive trees. Both unsupervised and supervised data analysis clearly differentiated the groups. Different metabolites have been identified as potential specific biomarkers, and their characterization strongly suggests that metabolism of flavonoids and long-chain fatty acids is perturbed in Xf samples. In particular, a decrease in the defence capabilities of the host after Xf infection is proposed because of a significant dysregulation of some metabolites belonging to flavonoid family. Moreover, oleic acid is confirmed as a putative diffusible signal factor (DSF). This study provides new insights into the host-pathogen interactions and confirms LC-HRMS-based metabolomics as a powerful approach for disease-associated biomarkers discovery in plants.

A non-targeted metabolomics study on Xylella fastidiosa infected olive plants grown under controlled conditions

In the last decade, the bacterial pathogen Xylella fastidiosa has devastated olive trees throughout Apulia region (Southern Italy) in the form of the disease called "Olive Quick Decline Syndrome" (OQDS). This study describes changes in the metabolic profile due to the infection by X. fastidiosa subsp. pauca ST53 in artificially inoculated young olive plants of the susceptible variety Cellina di Nardò. The test plants, grown in a thermo-conditioned greenhouse, were also co-inoculated with some xylem-inhabiting fungi known to largely occur in OQDS-affected trees, in order to partially reproduce field conditions in terms of biotic stress. The investigations were performed by combining NMR spectroscopy and MS spectrometry with a non-targeted approach for the analysis of leaf extracts. Statistical analysis revealed that Xylella-infected plants were characterized by higher amounts of malic acid, formic acid, mannitol, and sucrose than in Xylella-non-infected ones, whereas it revealed slightly lower amounts of oleuropein. Attention was paid to mannitol which may play a central role in sustaining the survival of the olive tree against bacterial infection. This study contributes to describe a set of metabolites playing a possible role as markers in the infections by X. fastidiosa in olive.