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17 pages, 3428 KiB  
Article
Heterologous Expression of Ketoreductase ChKRED20 Mutant in Pichia pastoris and Bioreductive Production of (R)-1, 3-Butanediol
by Wanping Chen, Lei Sun, Xinwei Wu, Zhenni Xu, Chin-Yu Chen, Sitong Liu, Haibin Chen, Baoguo Sun and Mingxin Dong
Molecules 2024, 29(18), 4393; https://doi.org/10.3390/molecules29184393 - 16 Sep 2024
Viewed by 775
Abstract
(R)-1, 3-Butanediol (1, 3-BDO) is an important intermediate in the synthesis of aromatics, pheromones, insecticides, and beta-lactam antibiotics. The ChKRED20 is a robust NADH-dependent ketoreductase identified from Chryseobacterium sp. CA49. We obtained a ChKRED20 mutant (M12) through directed [...] Read more.
(R)-1, 3-Butanediol (1, 3-BDO) is an important intermediate in the synthesis of aromatics, pheromones, insecticides, and beta-lactam antibiotics. The ChKRED20 is a robust NADH-dependent ketoreductase identified from Chryseobacterium sp. CA49. We obtained a ChKRED20 mutant (M12) through directed evolutionary screening of ChKRED20, the mutant with significantly improved activity to asymmetrically reduce 4-hydroxy-2-butanone (4H2B) to (R)-1, 3-BDO. So far, both ChKRED20 and its mutants have been expressed in intracellular in E. coli, the process of purification after intracellular expression is complicated, which leads to high cost. Here, we expressed M12 by constructing multicopy expression strains in P. pastoris, and the target protein yield was 302 mg/L in shake-flask fermentation and approximately 3.5 g/L in high-density fermentation. The recombinant M12 showed optimal enzyme activity at 30 °C and had high activity within a broad pH range of 6.0–8.0, and also showed high thermal stability. The recombinant M12 was further used for the reduction of 4H2B to (R)-1, 3-BDO, and 98.9% yield was achieved at 4540 mM 4H2B. The crude M12 enzyme extract was found to catalyze the bioreductive production of (R)-1, 3-BDO with excellent stereoselectivity (ee > 99%) and meet the production requirements. Our research shows that the M12 mutant can be used for the synthesis of (R)-1, 3-BDO, and the P. pastoris expression system is an ideal platform for the large-scale, low-cost preparation of ChKRED20 or its mutants, which may have applications in industrial settings. Full article
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<p>Schematic presentation of the biotransformation of 4H2B to (<span class="html-italic">R</span>)-1, 3-BDO. 4H2B, 4-hydroxy-2- butanone; (<span class="html-italic">R</span>)-1, 3-BDO, <span class="html-italic">R</span>-1, 3-butanediol; M<span class="html-italic">Ch</span>KRED20 (M12), the mutant of <span class="html-italic">Ch</span>KRED20.</p>
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<p>The LigPlot+ analysis results of protein-ligand (4H2B) interactions for the wild-type <span class="html-italic">Ch</span>KRED20 (<b>a</b>) and the mutant M12 (<b>b</b>). The four carbon atoms of 4H2B were represented as ①, ②, ③, and ④ in the figure. The C4 atom of the nicotinamide, where the hydride transfer occurs, makes a close approach to 4H2B, forming van der Waals interactions with 4H2B. The dashed gray lines in the figure represent van der Waals interactions, the yellow dashed lines indicate the hydrogen bonds.</p>
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<p>Overlaying the structures of molecule-docked complexes to compare the interactions between the wild-type (cyan) and mutant M12 (light pink) proteins and the substrate 4H2B. (<b>a</b>) The 12 mutation sites in the proteins are depicted as sticks in the diagram. (<b>b</b>) The amino acid residue of <span class="html-italic">Ch</span>KRED20 (WT in cyan/Mut in light pink) that interacts with the substrate 4H2B is shown in stick form. The coenzyme NAD<sup>+</sup> and the substrate are also represented in stick form, with hydrogen bonds indicated by dashed lines: cyan for WT and yellow for Mut.</p>
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<p>Muti-copy expression of M<span class="html-italic">Ch</span>KRED20 (M12) using gene dosage. (<b>a</b>) Strategy of multi-copy strain construction. (<b>b</b>) The qPCR of the M12 expression cassettes integrated into the host strains carrying 1–4 copies. (<b>c</b>) SDS-PAGE analysis of M12 secreted into the culture supernatant. M: protein marker; lanes 1–4: supernatants from shake-flask fermentation of MChR1c, MChR2c, MChR3c, and MChR4c strains, respectively, collected after 144 h induction with 1% methanol.</p>
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<p>Quantitative analysis of the expression of M12 produced by shake-flask fermentation. Time course of cell density (<b>a</b>) and the yield of the target protein (<b>b</b>) during the induction phase.</p>
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<p>SDS-PAGE analysis of M12 secreted into the supernatant during high-density fermentation. M: protein molecular weight marker (the molecular weight of each band is indicated on the left); cell culture supernatant after induction with 1% methanol for 0, 24, 48, 72, 96, 120,144, and 168 h, respectively, all samples were diluted 10 times.</p>
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<p>The glycosylation staining and deglycosylation of M12. (<b>a</b>) Glycoprotein staining to analyze the expression of M12 expressed in <span class="html-italic">Pichia pastoris</span>, P: the positive control, N: the negative control, M12: the recombinant M12 (<b>b</b>) SDS-PAGE to analyze the M12 expressed in <span class="html-italic">Pichia pastoris</span> after treated with Endo H, lane 1: M12, lane 2: M12 after treated with Endo H, lane 3: the Endo H.</p>
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<p>The optimal concentration of IPA (<b>a</b>) and NAD<sup>+</sup> (<b>b</b>) in the reaction system. (<b>c</b>) Temperature optimization for M12 activity. Enzyme activity at 30 °C was set to 100%. (<b>d</b>) pH optimization for M12 activity. Enzyme activity at pH 5.0 was set to 100%.</p>
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<p>Thermostability of the recombinant M12. The initial enzyme activity was set to 100%.</p>
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<p>Biotransformation of 4H2B to (<span class="html-italic">R</span>)-1, 3-BDO. (<b>a</b>) The conversion rate over the time using the crude enzyme extract of M12. (<b>b</b>) The purity of the production of (<span class="html-italic">R</span>)-1, 3-BDO analyzed with GC.</p>
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15 pages, 5144 KiB  
Article
Insights into the Flavor Profile of Yak Jerky from Different Muscles Based on Electronic Nose, Electronic Tongue, Gas Chromatography–Mass Spectrometry and Gas Chromatography–Ion Mobility Spectrometry
by Bingde Zhou, Xin Zhao, Luca Laghi, Xiaole Jiang, Junni Tang, Xin Du, Chenglin Zhu and Gianfranco Picone
Foods 2024, 13(18), 2911; https://doi.org/10.3390/foods13182911 - 14 Sep 2024
Viewed by 884
Abstract
It is well known that different muscles of yak exhibit distinctive characteristics, such as muscle fibers and metabolomic profiles. We hypothesized that different muscles could alter the flavor profile of yak jerky. Therefore, the objective of this study was to investigate the differences [...] Read more.
It is well known that different muscles of yak exhibit distinctive characteristics, such as muscle fibers and metabolomic profiles. We hypothesized that different muscles could alter the flavor profile of yak jerky. Therefore, the objective of this study was to investigate the differences in flavor profiles of yak jerky produced by longissimus thoracis (LT), triceps brachii (TB) and biceps femoris (BF) through electronic nose (E-nose), electronic tongue (E-tongue), gas chromatography–mass spectrometry (GC-MS) and gas chromatography–ion mobility spectrometry (GC-IMS). The results indicated that different muscles played an important role on the flavor profile of yak jerky. And E-nose and E-tongue could effectively discriminate between yak jerky produced by LT, TB and BF from aroma and taste points of view, respectively. In particular, the LT group exhibited significantly higher response values for ANS (sweetness) and NMS (umami) compared to the BF and TB groups. A total of 65 and 47 volatile compounds were characterized in yak jerky by GC-MS and GC-IMS, respectively. A principal component analysis (PCA) model and robust principal component analysis (rPCA) model could effectively discriminate between the aroma profiles of the LT, TB and BF groups. Ten molecules could be considered potential markers for yak jerky produced by different muscles, filtered based on the criteria of relative odor activity values (ROAV) > 1, p < 0.05, and VIP > 1, namely 1-octen-3-ol, eucalyptol, isovaleraldehyde, 3-carene, D-limonene, γ-terpinene, hexanal-D, hexanal-M, 3-hydroxy-2-butanone-M and ethyl formate. Sensory evaluation demonstrated that the yak jerky produced by LT exhibited superior quality in comparison to that produced by BF and TB, mainly pertaining to lower levels of tenderness and higher color, taste and aroma levels. This study could help to understand the specific contribution of different muscles to the aroma profile of yak jerky and provide a scientific basis for improving the quality of yak jerky. Full article
(This article belongs to the Special Issue Quantitative NMR and MRI Methods Applied for Foodstuffs)
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<p>Sample preparation flowchart. <span class="html-italic">Longissimus thoracis</span> (LT), <span class="html-italic">triceps brachii</span> (TB) and <span class="html-italic">biceps femoris</span> (BF).</p>
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<p>Score plot and loading plot of robust principal component analysis (rPCA) models based on electronic nose (E-nose) (<b>a</b>,<b>b</b>) and electronic tongue (E-tongue) (<b>c</b>,<b>d</b>) response data.</p>
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<p>(<b>a</b>) Venn diagram plot of the number of volatile compounds in yak jerky from different muscles. (<b>b</b>) Bar plot of the percentage of volatile compound species in yak jerky from different muscles. (<b>c</b>) Principal component analysis (PCA) model based on volatile compounds in yak jerky from different muscles. (<b>d</b>) VIP score plots for the partial least-squares discriminant analysis (PLS-DA) model on volatile compounds in yak jerky from different muscles.</p>
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<p>Gas chromatography–ion mobility spectrometry (GC-IMS) observation results of yak jerky from different muscles. (<b>a</b>) 3D topographic plot. (<b>b</b>) Subtraction plot, with spectra from TB group as a reference and the corresponding spectra from LT and BF groups represented as differences from TB group. (<b>c</b>) Gallery plots indicating the variations in volatile compounds’ concentrations among the four groups. Red and blue colors highlight over- and underexpressed components, respectively.</p>
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<p>(<b>a</b>) Bar plot of the relative content of volatile compound species in yak jerky from different muscles characterized by GC-IMS. (<b>b</b>) Venn diagram plot of the number of volatile compounds characterized by GC-MS and GC-IMS.</p>
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<p>The rPCA model was established based on the relative content of GC-IMS differential volatile compounds. (<b>a</b>) The score plot shows the samples from the three groups as follows: squares (LT), circles (TB) and triangles (BF). The median of each group is represented by a wide and empty circle. (<b>b</b>) The loading plot illustrates the significant correlation between the molecule concentration and their importance along PC 1.</p>
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<p>Radar chart for sensory evaluation of yak jerky from different muscles.</p>
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<p>Correlation analysis of E-nose, E-tongue, sensory evaluation and volatile compounds quantified by GC-IMS (<b>a</b>) and GC-MS (<b>b</b>). The size of node is indicative of the number of substances that are significantly correlated with the substance in question. The blue circles represent the E-nose and E-tongue probes; the pink squares represent volatile compounds; and the yellow triangles represent sensory evaluation. In addition, the larger the node, the greater the number of substances with which it is significantly correlated. The thickness of line is representative of the size of the absolute value of the correlation between two substances. In this context, the thicker the line, the greater the absolute value of the correlation between the two substances.</p>
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14 pages, 6673 KiB  
Article
Characterization of Flavor Compounds in Chinese Indigenous Sheep Breeds Using Gas Chromatography–Ion Mobility Spectrometry and Chemometrics
by Fang Wang, Hongbo Wang, Zeyi Liang, Jing Liu, Chen Yang, Huan Zhai, Anle Chen, Zengkui Lu, Yaqin Gao, Xuezhi Ding and Jianbin Liu
Foods 2024, 13(17), 2647; https://doi.org/10.3390/foods13172647 - 23 Aug 2024
Viewed by 863
Abstract
This study analyzed the flavor compounds in the meat of four indigenous breeds of Chinese sheep through the use of gas chromatography–ion mobility spectrometry (GC-IMS). GC-IMS provided information on the characteristics and strength of 71 volatile flavor compounds (monomers and dimers), with aldehydes, [...] Read more.
This study analyzed the flavor compounds in the meat of four indigenous breeds of Chinese sheep through the use of gas chromatography–ion mobility spectrometry (GC-IMS). GC-IMS provided information on the characteristics and strength of 71 volatile flavor compounds (monomers and dimers), with aldehydes, alcohols and ketones being the most abundant in all types of sheep meat. The compounds with higher intensity peaks in the sheep meat were aldehydes (n-nonanal, octanal, heptanal, 3-methylbutanal, and hexanal), alcohols (1-octen-3-ol, hexanol, and pentanol), ketones (3-hydroxy-2-butanon, 2-butanone, and 2-propanone), esters (methyl benzoate), and thiazole (trimethylthiazole). The volatile flavor components in the meat of the different breeds of sheep obtained via GC-IMS were further differentiated using principal component analysis. In addition, orthogonal partial least squares discriminant analysis (OPLS-DA) and variable importance on projection (VIP) were used to determine the characteristic flavor compounds in the meats of different breeds of sheep, and 21 differentially volatile components were screened out based on having a VIP above 1. These results indicate that GC-IMS combined with multivariate analysis is a convenient and powerful method for characterizing and discriminating sheep meat. Full article
(This article belongs to the Section Food Analytical Methods)
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<p>Two-dimensional topographic representation of different breeds’ meat.</p>
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<p>Fingerprint of volatile compounds in the meat of different breeds of sheep (UC: unidentified compound).</p>
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<p>PCA plot of volatile compounds in the meat of different breeds of sheep.</p>
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<p>(<b>A</b>) Score plot of OPLS-DA (R<sup>2</sup>Y = 0.9888; Q2 = 0.974); (<b>B</b>) cross-substitution plot of 200 permutation tests (R<sup>2</sup> = 0.00358; Q<sup>2</sup> = 0.426).</p>
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<p>Screening of differential volatile components in different breeds of sheep meat (<b>A</b>) VIP value. (<b>B</b>) PCA score plot. (<b>C</b>) Clustering heatmap.</p>
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18 pages, 4715 KiB  
Article
Comparison of Different Deodorizing Treatments on the Flavor of Paddy Field Carp, Analyzed by the E-Nose, E-Tongue and Gas Chromatography–Ion Mobility Spectrometry
by Chenying Fu, Yiming Zou, Yixiang Zhang, Mengxiang Liao, Duhuang Chen and Zebin Guo
Foods 2024, 13(16), 2623; https://doi.org/10.3390/foods13162623 - 21 Aug 2024
Viewed by 971
Abstract
Changes in the flavor and taste profiles of Paddy Field Carp after deodorization with perilla juice (PJ), cooking wine (CW) and a mixture of the two (PJ-CW) were analyzed using the E-nose, E-tongue, gas chromatography–ion mobility spectrometry (GC-IMS), free amino acid analysis and [...] Read more.
Changes in the flavor and taste profiles of Paddy Field Carp after deodorization with perilla juice (PJ), cooking wine (CW) and a mixture of the two (PJ-CW) were analyzed using the E-nose, E-tongue, gas chromatography–ion mobility spectrometry (GC-IMS), free amino acid analysis and taste nucleotide analysis. The E-nose and E-tongue revealed that deodorization reduced the content of sulfur-containing compounds, enhanced umami, bitterness, sourness and astringency, and decreased saltiness. PCA and OPLS-DA analysis successfully distinguished between the effects of the treatments. Free amino acids increased from 8777.67 to 11,125.98 mg/100 g and umami amino acids increased from 128.24 to 150.37 mg/100 g after PJ-CW deodorization (p < 0.05). Equivalent umami concentration (EUC) comparisons showed that PJ-CW treatment produced the greatest synergistic umami enhancement (to 3.15 g MSG equiv./100 g). GC-IMS detected 52 aroma compounds; PJ treatment produced the greatest diversity of aldehydes, including heptanal, nonanal, hexanal, 3-methylbutanal, (E)-2-heptenal and (E,E)-2,4-heptadienal. The total content of volatile flavor compounds was the highest after PJ-CW treatment, and the content of many characteristic flavor substances (3-hydroxy-2-butanone, benzaldehyde, 5-methyl-2(3H)-furanone) increased. These findings provided a theoretical basis for the further development of deodorization methods for Paddy Field Carp. Full article
(This article belongs to the Section Food Analytical Methods)
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<p>E-nose radar plot of Paddy Field Carp with different deodorization treatments. Note: B: blank group; PJ: perilla juice; CW: cooking wine; PJ-CW: perilla juice and cooking wine. The scale value (from −5 to 35) represents the response value of the sensor, which is the ratio of the conductivity G of the sample gas passing through the sensor to the conductivity Go of the standard gas filtered by activated carbon passing through the sensor, i.e., G/Go.</p>
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<p>E-nose OPLS-DA score plot of Paddy Field Carp with different deodorization treatments (R<sup>2</sup>X = 0.995; R<sup>2</sup>Y = 0.979; Q<sup>2</sup> = 0.957). Note: B: blank group; PJ: perilla juice; CW: cooking wine; PJ-CW: perilla juice and cooking wine.</p>
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<p>OPLS-DA permutation test.</p>
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<p>E-nose VIP value of Paddy Field Carp with different deodorization treatments.</p>
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<p>E-tongue radar plot of Paddy Field Carp with different deodorization treatments. Note: B: blank group; PJ: perilla juice; CW: cooking wine; PJ-CW: perilla juice and cooking wine. The scale value (from −40 to 20) indicates that the response value of the sensor is equivalent to the level of taste value.</p>
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<p>Saltiness, umami and richness bubble chart of Paddy Field Carp with different deodorization methods. Note: B: blank group; PJ: perilla juice; CW: cooking wine; PJ-CW: perilla juice and cooking wine.</p>
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<p>Bitterness, sourness and astringency bubble chart of Paddy Field Carp with different deodorization methods. Note: B: blank group; PJ: perilla juice; CW: cooking wine; PJ-CW: perilla juice and cooking wine.</p>
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<p>E-tongue PCA score plot of Paddy Field Carp with different deodorization treatments. Note: B: blank group; PJ: perilla juice; CW: cooking wine; PJ-CW: perilla juice and cooking wine.</p>
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<p>Nucleotide content of Paddy Field Carp with different deodorization methods. Note: B: blank group; PJ: perilla juice; CW: cooking wine; PJ-CW: perilla juice and cooking wine. “AMP” is 5′-adenosine monophosphate; “GMP” is 5′-guanosine monophosphate and “CMP” is 5′-cytidine monophosphate. Different letters in the figure indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Comparison of volatile substances in Paddy Field Carp with different deodorization methods. Note: B: blank group; PJ: perilla juice; CW: cooking wine; PJ-CW: perilla juice and cooking wine. The B group serving as the reference, the two-dimensional difference spectra of the other three groups were obtained by deducting the reference, where the background turned white [<a href="#B46-foods-13-02623" class="html-bibr">46</a>]. The red vertical lines represent the reaction ion peak (RIP), and each point on both sides of them represents a volatile substance. The spots with different colors represent different concentrations of each volatile organic compound. The blue area indicates that the concentration in the sample is lower than the B group, while the red area indicates that the concentration is higher than the B group.</p>
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<p>Histogram of the content of some volatile substances in Paddy Field Carp with different deodorization methods. Note: B: blank group; PJ: perilla juice; CW: cooking wine; PJ-CW: perilla juice and cooking wine. Different letters in the figure indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>GC-IMS volatile substance fingerprint. Note: The areas enclosed by blue, yellow, purple and red represent the characteristic flavor substances of Paddy Field Carp under different deodorization methods, respectively. B: blank group; PJ: perilla juice; CW: cooking wine; PJ-CW: perilla juice and cooking wine. “M” is Monomers; “D” is Dimers; “M” and “D” are actually one substance, with the same retention time but different migration times.</p>
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17 pages, 7436 KiB  
Article
Comparative Analysis of Commercially Available Flavor Oil Sausages and Smoked Sausages
by Penghui Zhao, Yongqiang An, Zijie Dong, Xiaoxue Sun, Wanli Zhang, Heng Wang, Bing Yang, Jing Yan, Bing Fang, Fazheng Ren and Lishui Chen
Molecules 2024, 29(16), 3772; https://doi.org/10.3390/molecules29163772 - 9 Aug 2024
Cited by 1 | Viewed by 992
Abstract
This study utilized gas chromatography-ion mobility spectrometry (GC-IMS) to analyze the volatile flavor compounds present in various commercially available sausages. Additionally, it conducted a comparative assessment of the distinctions among different samples by integrating sensory evaluation with textural and physicochemical parameters. The results [...] Read more.
This study utilized gas chromatography-ion mobility spectrometry (GC-IMS) to analyze the volatile flavor compounds present in various commercially available sausages. Additionally, it conducted a comparative assessment of the distinctions among different samples by integrating sensory evaluation with textural and physicochemical parameters. The results of the GC-IMS analysis showed that a total of 65 volatile compounds were detected in the four samples, including 12 hydrocarbons, 11 alcohols, 10 ketones, 9 aldehydes, 12 esters, and 1 acids. Fingerprinting combined with principal component analysis (PCA) showed that the volatiles of different brands of sausages were significantly different (p < 0.05). The volatiles of S1 and S4 were more similar and significantly different from the other two samples (p < 0.05). Among them, there were 14 key volatile substances in the four samples, of which 3-hydroxy-2-butanone and diallyl sulfide were common to all four sausages. Combined textural and sensory evaluations revealed that smoked sausages exhibited superior characteristics in resilience, cohesiveness, springiness, gumminess, and chewiness. Additionally, smoked sausages were found to be more attractive in color, moderately spicy, and salty, while having a lower fat content. In conclusion, smoked sausages are preferred by consumers over flavored oil sausages. Full article
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<p>Three-dimensional GC-IMS spectrum of volatile components in sausages.</p>
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<p>Two-dimensional GC-IMS spectra of volatile components in sausages.</p>
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<p>GC-IMS difference spectrum of volatile components in sausage.</p>
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<p>Fingerprints of volatile components in sausages.</p>
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<p>Plot of PCA scores of different sausage samples.</p>
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13 pages, 2383 KiB  
Article
Use of GC-IMS and Stoichiometry to Characterize Flavor Volatiles in Different Parts of Lueyang Black Chicken during Slaughtering and Cutting
by Linlin He, Hui Yang, Fei Lan, Rui Chen, Pengfei Jiang and Wengang Jin
Foods 2024, 13(12), 1885; https://doi.org/10.3390/foods13121885 - 15 Jun 2024
Cited by 1 | Viewed by 880
Abstract
Chilled and cut chicken is preferred by consumers for its safeness and readiness to cook. To evaluate the quality characteristics of various chilled chicken products, differences in volatile organic components (VOCs) of six different cut parts (breast, back, leg, heart, liver, and gizzard) [...] Read more.
Chilled and cut chicken is preferred by consumers for its safeness and readiness to cook. To evaluate the quality characteristics of various chilled chicken products, differences in volatile organic components (VOCs) of six different cut parts (breast, back, leg, heart, liver, and gizzard) of Lueyang black chicken were characterized through gas chromatography–ion mobility spectroscopy (GC-IMS) combined with stoichiometry. A total of 54 peaks in the signal of VOCs were detected by GC-IMS, and 43 VOCs were identified by qualitative analysis. There were 22 aldehydes (20.66–54.07%), 8 ketones (25.74–62.87%), 9 alcohols (4.17–14.69%), 1 ether (0.18–2.22%), 2 esters (0.43–1.54%), and 1 furan (0.13–0.52%), in which aldehydes, ketones, and alcohols were the main categories. Among the six cut parts, the relative content of aldehydes (54.07%) was the highest in the gizzard, and the relative content of ketones (62.87%) was the highest in the heart. Meanwhile, the relative content of alcohols (14.69%) was the highest in the liver. Based on a stable and reliable predictive model established by orthogonal partial least squares–discriminant analysis (OPLS-DA), 3-hydroxy-2-butanone (monomer and dimer), acetone, 2-butanone monomer, hexanal (monomer and dimer), isopentyl alcohol monomer, and n-hexanol monomer were picked out as characteristic VOCs based on variable importance in projection (VIP value > 1.0, p < 0.05). Principal component analysis (PCA) and the clustering heatmap indicated that the characteristic VOCs could effectively distinguish the six cut parts of Lueyang black chicken. The specific VOCs responsible for flavor differences among six different cut parts of Lueyang black chicken were hexanal (monomer and dimer) for the gizzard, 2-butanone monomer and hexanal dimer for the breast, hexanal monomer for the back, 3-hydroxy-2-butanone monomer for the leg, 3-hydroxy-2-butanone (monomer and dimer) for the heart, and acetone and isopentyl alcohol monomer for the liver. These findings could reveal references for quality assessment and development of chilled products related to different cut parts of Lueyang black chicken in the future. Full article
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<p>The GC−IMS spectra of six different cuts of Lueyang black chicken. (<b>a</b>) Three−dimensional spectra. (<b>b</b>) Two−dimensional top-view spectra. (<b>c</b>) Two−dimensional difference spectra.</p>
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<p>Gallery fingerprint of the VOCs of six different cut parts of Lueyang black chicken. Compounds with suffix D and M represent dimer and monomer, respectively. A, B, and C refer to the region with higher levels of VOCs in the breast, heart, and liver in the gallery fingerprint, respectively. D and E refer to the regions with higher levels of VOCs in the gizzard in the gallery fingerprint.</p>
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<p>The relative content changes of the VOCs of six different cut parts of Lueyang black chicken.</p>
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<p>OPLS−DA scores of VOCs of six different chicken cuts (<b>a</b>) and displacement test (<b>b</b>).</p>
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<p>Screening of characteristic VOCs in different cutting parts of Lueyang black chicken (<b>a</b>) VIP value; (<b>b</b>) principal component score map; (<b>c</b>) clustering heatmap. Compounds with suffix −D and −M represent dimer and monomer, respectively.</p>
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22 pages, 6656 KiB  
Article
Changes in Black Truffle (Tuber melanosporum) Aroma during Storage under Different Conditions
by Ruben Epping, Jan Lisec and Matthias Koch
J. Fungi 2024, 10(5), 354; https://doi.org/10.3390/jof10050354 - 15 May 2024
Viewed by 1153
Abstract
The enticing aroma of truffles is a key factor for their culinary value. Although all truffle species tend to be pricy, the most intensely aromatic species are the most sought after. Research into the aroma of truffles encompasses various disciplines including chemistry, biology, [...] Read more.
The enticing aroma of truffles is a key factor for their culinary value. Although all truffle species tend to be pricy, the most intensely aromatic species are the most sought after. Research into the aroma of truffles encompasses various disciplines including chemistry, biology, and sensory science. This study focusses on the chemical composition of the aroma of black truffles (Tuber melanosporum) and the changes occurring under different storage conditions. For this, truffle samples were stored under different treatments, at different temperatures, and measured over a total storage time of 12 days. Measurements of the truffle aroma profiles were taken with SPME/GC–MS at regular intervals. To handle the ample data collected, a systematic approach utilizing multivariate data analysis techniques was taken. This approach led to a vast amount of data which we made publicly available for future exploration. Results reveal the complexity of aroma changes, with 695 compounds identified, highlighting the need for a comprehensive understanding. Principal component analyses offer initial insights into truffle composition, while individual compounds may serve as markers for age (formic acid, 1-methylpropyl ester), freshness (2-Methyl-1-propanal; 1-(methylthio)-propane), freezing (tetrahydrofuran), salt treatment (1-chloropentane), or heat exposure (4-hydroxy-3-methyl-2-butanone). This research suggests that heat treatment or salt contact significantly affects truffle aroma, while freezing and cutting have less pronounced effects in comparison. The enrichment of compounds showing significant changes during storage was investigated with a metabolomic pathway analysis. The involvement of some of the enriched compounds on the pyruvate/glycolysis and sulfur pathways was shown. Full article
(This article belongs to the Special Issue New Perspectives on Tuber Fungi)
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Graphical abstract

Graphical abstract
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<p>Typical (HS)SPME/GC–MS total ion chromatogram of <span class="html-italic">Tuber melanosporum</span>.</p>
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<p>Retention time vs. retention index plot for measured RI and reference from the literature.</p>
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<p><span class="html-italic">p</span>-value histograms for dependence on time point (TP), temperature, processing type (condition), and both TP and temperature. (<b>Top</b>): linear, (<b>Bottom</b>): logarithmic scale. <span class="html-italic">p</span>-values are multiple-testing-corrected using the method of Benjamini–Hochberg (BH).</p>
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<p>Principal component analysis of stored truffle samples. Storage time (d) is indicated by numbers. Storage temperatures of <span style="color:#EA8B00">room temperature</span>, <span style="color:#5195D3">fridge</span>, and <span style="color:#000099">freezer</span> are indicated by colors. Processing types sliced (●), piece (■), with NaCl (◆), and blanched (▲) are indicated by symbols.</p>
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<p>Progression of peak intensity (logarithmic scale) vs. storage time (in days) for formic acid, 1-methylpropyl ester (<b>A</b>), 2-methylpropanal (<b>B</b>), 1,3-dimethylbenzene (<b>C</b>), 3-methylfuran (<b>D</b>), Tetrahydrofuran (<b>E</b>), and Nonanal (<b>F</b>). Storage temperatures of <span style="color:#EA8B00">room temperature</span>, <span style="color:#5195D3">fridge</span>, and <span style="color:#000099">freezer</span> are indicated by colors. Processing types sliced (●), piece (■), with NaCl (◆), and blanched (▲) are indicated by symbols. To allow easier comparison between groups, lines colored according to temperature levels connect replicate means per time point. Additionally, samples for each time point have been shifted slightly on the <span class="html-italic">x</span>-axis according to the applied processing type. Plot annotations provide information on retention time (RT), ion mass (mz), sum formula, peak ID, and the <span class="html-italic">p</span>-values obtained in an ANOVA with 3 factors.</p>
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<p>Progression of peak intensity (logarithmic scale) vs. storage time (in days) for 4-hydroxy-2-pentanone (<b>A</b>), naphthalene (<b>B</b>), formic acid, butyl ester (<b>C</b>), 2,4-dimethylanisole (<b>D</b>), methanol (<b>E</b>), and 3-phenylfuran (<b>F</b>). Storage temperatures of <span style="color:#EA8B00">room temperature</span>, <span style="color:#5195D3">fridge</span>, and <span style="color:#000099">freezer</span> are indicated by colors. Processing types sliced (●), piece (■), with NaCl (◆), and blanched (▲) are indicated by symbols.</p>
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<p>Progression of peak intensity (logarithmic scale) vs. storage time (in days) for 1-chloropentane (<b>A</b>), 3-methyl-2-butanol (<b>B</b>), 4-hydroxy-3-methyl-2-butanone (<b>C</b>), 1,2,3-trimethoxy-5-methylbenzene (<b>D</b>), 3-methylhexanal (<b>E</b>), and indane (<b>F</b>). Storage temperatures of <span style="color:#EA8B00">room temperature</span>, <span style="color:#5195D3">fridge</span>, and <span style="color:#000099">freezer</span> are indicated by colors. Processing types sliced (●), piece (■), with NaCl (◆), and blanched (▲) are indicated by symbols.</p>
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<p>Progression of peak intensity (logarithmic scale) vs. storage time (in days) for dimethyl sulfide (<b>A</b>), 2-methylthiazole (<b>B</b>), methional (<b>C</b>), dimethyl sulfone (<b>D</b>), and dimethyl trisulfide (<b>E</b>). Storage temperatures of <span style="color:#EA8B00">room temperature</span>, <span style="color:#5195D3">fridge</span>, and <span style="color:#000099">freezer</span> are indicated by colors. Processing types sliced (●), piece (■), with NaCl (◆), and blanched (▲) are indicated by symbols.</p>
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<p>Top enriched metabolites by main chemical class in sliced samples, divided by storage temperature.</p>
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<p>Top enriched metabolites by main chemical class in fridge samples, divided by treatment method.</p>
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<p>Pathway analysis of room temperature sliced samples and selected metabolite pathways that include more than 2 identified compounds.</p>
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<p>Alignment results of the MS-DIAL deconvolution process. All peaks (<b>top</b>) and identified peaks (<b>bottom</b>) in comparison with NIST library.</p>
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12 pages, 6986 KiB  
Article
WO3 Nanoplates Decorated with Au and SnO2 Nanoparticles for Real-Time Detection of Foodborne Pathogens
by Xueyan Li, Zeyi Wu, Xiangyu Song, Denghua Li, Jiajia Liu and Jiatao Zhang
Nanomaterials 2024, 14(8), 719; https://doi.org/10.3390/nano14080719 - 19 Apr 2024
Cited by 2 | Viewed by 1385
Abstract
Nowadays, metal oxide semiconductor gas sensors have diverse applications ranging from human health to smart agriculture with the development of Internet of Things (IoT) technologies. However, high operating temperatures and an unsatisfactory detection capability (high sensitivity, fast response/recovery speed, etc.) hinder their integration [...] Read more.
Nowadays, metal oxide semiconductor gas sensors have diverse applications ranging from human health to smart agriculture with the development of Internet of Things (IoT) technologies. However, high operating temperatures and an unsatisfactory detection capability (high sensitivity, fast response/recovery speed, etc.) hinder their integration into the IoT. Herein, a ternary heterostructure was prepared by decorating WO3 nanoplates with Au and SnO2 nanoparticles through a facial photochemical deposition method. This was employed as a sensing material for 3-hydroxy-2-butanone (3H-2B), a biomarker of Listeria monocytogenes. These Au/SnO2–WO3 nanoplate-based sensors exhibited an excellent response (Ra/Rg = 662) to 25 ppm 3H-2B, which was 24 times higher than that of pure WO3 nanoplates at 140 °C. Moreover, the 3H-2B sensor showed an ultrafast response and recovery speed to 25 ppm 3H-2B as well as high selectivity. These excellent sensing performances could be attributed to the rich Au/SnO2–WO3 active interfaces and the excellent transport of carriers in nanoplates. Furthermore, a wireless portable gas sensor equipped with the Au/SnO2–WO3 nanoplates was assembled, which was tested using 3H-2B with known concentrations to study the possibilities of real-time gas monitoring in food quality and safety. Full article
(This article belongs to the Special Issue The Application of Nanosensors in Energy and Environment)
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<p>(<b>a</b>) The synthesis schematic of XAu/SnO<sub>2</sub>–WO<sub>3</sub> nanoplates. (<b>b</b>,<b>c</b>) HRTEM images. (<b>d</b>) HAADF−STEM image and corresponding EDS elemental mapping results of the 1Au/SnO<sub>2</sub>–WO<sub>3</sub> nanoplates.</p>
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<p>(<b>a</b>) XRD patterns of WO<sub>3</sub> nanoplates, Au–WO<sub>3</sub> nanoplates, SnO<sub>2</sub>–WO<sub>3</sub> nanoplates, and 1Au/SnO<sub>2</sub>–WO<sub>3</sub> nanoplates; XPS spectra of (<b>b</b>) W 4f, (<b>c</b>) Au 4f, (<b>d</b>) Sn 3d, and (<b>e</b>) O 1s; (<b>f</b>) EPR spectra of WO<sub>3</sub> and 1Au/SnO<sub>2</sub>–WO<sub>3</sub> nanoplates.</p>
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<p>(<b>a</b>) Response curves of WO<sub>3</sub> and XAu/SnO<sub>2</sub>–WO<sub>3</sub> nanoplate-based sensors to 25 ppm 3H-2B at different working temperatures. (<b>b</b>) Dynamic response and recovery curves of WO<sub>3</sub> and XAu/SnO<sub>2</sub>–WO<sub>3</sub> nanoplate-based sensors toward different concentrations (1.25, 2.5, 5, 10, 15, and 25 ppm) of 3H-2B at 140 °C. (<b>c</b>) Response curves of WO<sub>3</sub> and XAu/SnO<sub>2</sub>–WO<sub>3</sub> nanoplate-based sensors toward different concentrations of 3H-2B. (<b>d</b>,<b>e</b>) Dynamic response and recovery curves of WO<sub>3</sub> and XAu/SnO<sub>2</sub>–WO<sub>3</sub> nanoplate-based sensors toward 25 ppm 3H-2B. (<b>f</b>) Selectivity tests of WO<sub>3</sub> and XAu/SnO<sub>2</sub>–WO<sub>3</sub> nanoplate-based sensors toward different target gases.</p>
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<p>Schematic of the surface-sensing reaction of 1Au/SnO<sub>2</sub>–WO<sub>3</sub> nanoplates toward 3H-2B and the corresponding band diagram of the sensing mechanism.</p>
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<p>(<b>a</b>) Optical photograph of wireless portable sensor connected to a laptop via ZigBee. (<b>b</b>) Dynamic response and recovery curves displayed on the laptop when the portable sensor was exposed to 25 ppm 3H-2B.</p>
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20 pages, 4758 KiB  
Article
Volatile Organic Compounds Produced by Kosakonia cowanii Cp1 Isolated from the Seeds of Capsicum pubescens R & P Possess Antifungal Activity
by José Luis Hernández Flores, Yomaiko Javier Martínez, Miguel Ángel Ramos López, Carlos Saldaña Gutierrez, Aldo Amaro Reyes, Mariem Monserrat Armendariz Rosales, Maraly Jazmin Cortés Pérez, Mayela Fosado Mendoza, Joanna Ramírez Ramírez, Grecia Ramírez Zavala, Paola Lizeth Tovar Becerra, Laila Valdez Santoyo, Karen Villasana Rodríguez, José Alberto Rodríguez Morales and Juan Campos Guillén
Microorganisms 2023, 11(10), 2491; https://doi.org/10.3390/microorganisms11102491 - 4 Oct 2023
Cited by 4 | Viewed by 2080
Abstract
The Kosakonia cowanii Cp1 strain was isolated from seeds of Capsicum pubescens R. & P. cultivated in Michoacan, Mexico. Genetic and ecological role analyses were conducted for better characterization. The results show that genome has a length of 4.7 Mbp with 56.22% G [...] Read more.
The Kosakonia cowanii Cp1 strain was isolated from seeds of Capsicum pubescens R. & P. cultivated in Michoacan, Mexico. Genetic and ecological role analyses were conducted for better characterization. The results show that genome has a length of 4.7 Mbp with 56.22% G + C and an IncF plasmid of 128 Kbp with 52.51% G + C. Furthermore, pathogenicity test revealed nonpathogenic traits confirmed by the absence of specific virulence-related genes. Interestingly, when fungal inhibitory essays were carried out, the bacterial synthesis of volatile organic compounds (VOCs) with antifungal activity showed that Sclerotinia sp. and Rhizoctonia solani were inhibited by 87.45% and 77.24%, respectively. Meanwhile, Sclerotium rolfsii, Alternaria alternata, and Colletotrichum gloeosporioides demonstrated a mean radial growth inhibition of 52.79%, 40.82%, and 55.40%, respectively. The lowest inhibition was by Fusarium oxysporum, with 10.64%. The VOCs’ characterization by headspace solid–phase microextraction combined with gas chromatography–mass spectrometry (HS-SPME-GC–MS) revealed 65 potential compounds. Some of the compounds identified with high relative abundance were ketones (22.47%), represented by 2-butanone, 3-hydroxy (13.52%), and alcohols (23.5%), represented by ethanol (5.56%) and 1-butanol-3-methyl (4.83%). Our findings revealed, for the first time, that K. cowanii Cp1 associated with C. pubescens seeds possesses potential traits indicating that it could serve as an effective biocontrol. Full article
(This article belongs to the Special Issue Biological Control of the Plant Pathogens)
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<p>Isolation of <span class="html-italic">Kosakonia cowanii</span> Cp1. (<b>A</b>) <span class="html-italic">Capsicum pubescens</span> fruits with no infection symptoms; (<b>B</b>) interior of <span class="html-italic">Capsicum pubescens</span> fruits displaying seeds with no infection symptoms; (<b>C</b>) <span class="html-italic">Capsicum pubescens</span> seeds on TSA medium that was supplemented with 100 μg/mL of ampicillin; (<b>D</b>) a growth of <span class="html-italic">Kosakonia cowanii</span> after 24 h of incubation.</p>
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<p>Pathogenicity test of <span class="html-italic">K. cowanii</span> Cp1 in a serrano pepper (<span class="html-italic">Capsicum annuum</span> L.). (<b>A</b>) Assay of <span class="html-italic">K. cowanii</span> Cp1 that grew on serrano pepper leaves; (<b>B</b>) assay of <span class="html-italic">K. cowanii</span> Cp1 on the external part of pepper fruits; (<b>C</b>) assay of <span class="html-italic">K. cowanii</span> Cp1 on the internal part of pepper fruits. No lesions were observed in any case.</p>
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<p>Graphical circular map of the chromosome and plasmid of <span class="html-italic">K. cowanii</span> Cp1. From the outside to the center rings are the ensembled contigs, CDS on forward, CDS on reverse, non-CDS, AMR genes, VF genes, transporters, drug targets, GC content, and GC skew. The subsystem functional assignments are represented in the figure below.</p>
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<p>Antibiotic resistance genes. The AMR mechanism and its related genes are indicated with a color diagram.</p>
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<p>Phylogenomic analysis of <span class="html-italic">K. cowanii</span> Cp1. Phylogenetic analysis was performed in BV-BRC. The following strains were included: <span class="html-italic">K. cowanii strain 888-76</span>, <span class="html-italic">K. cowanii JCM 10956</span>, <span class="html-italic">K. cowanii Ch1</span>, <span class="html-italic">K. cowanii strain PF-104</span>, <span class="html-italic">K. cowanii Pa82</span>, <span class="html-italic">K. cowanii strain Esp Z</span>, <span class="html-italic">K. pseudosacchari strain NN143</span>, <span class="html-italic">K. sacchari SP1</span>, <span class="html-italic">K. sacchari strain DSM 107661</span>, <span class="html-italic">K. radicincitans strain GXGL-4A</span>, <span class="html-italic">K. oryzae strain D4</span>, <span class="html-italic">K. radicincitans UMEnt01/12</span>, <span class="html-italic">K. arachidis strain KACC 18508</span>, <span class="html-italic">K. oryzendophytica strain REICA 082</span>, and—as an outgroup—<span class="html-italic">Escherichia coli XH989</span>. The label color represents the collection year. The node fill and shape represent the country from which the isolates were gathered, including Mexico, China, Malaysia, Republic of Korea, Sri Lanka, USA, and Zambia.</p>
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<p>Effect of the VOCs produced by <span class="html-italic">K. cowanii</span> Cp1 on mycelial growth. (<b>a</b>–<b>f</b>) show the radial mycelial growth for the untreated controls (indicated by C) and those that were VOC-treated (indicated by Cp1). The lower graph shows the inhibition mycelial rate (%). Statistical differences are represented by letters.</p>
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<p>The VOCs detected in <span class="html-italic">K. cowanii</span> Cp1. Each figure color shows the class family of the compounds and their percentage according to their relative peak-area profile.</p>
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<p>The VOC profiles of <span class="html-italic">K. cowanii</span> Cp1. The relative peak abundance and retention time are shown.</p>
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<p>Inhibitory effect of standard VOCs on the mycelia growth of <span class="html-italic">S. rolfsii</span>. The amount for each compound assayed were, from left to right: 50, 100, and 150 μL/plate of 2-Butanone; 50, 100, and 150 μL/plate of 2-Butanone, 3-hydroxy; 10, 20, and 40 μL/plate of 2-Nonanone; 50, 100, and 150 μL/plate of acetone; 5, 10, and 20 μL/plate of acetic acid; 50, 100, and 150 μL/plate of benzyl alcohol; and 50, 100, and 200 μL/plate of ethanol. Sterile distilled water was used in the control.</p>
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15 pages, 2042 KiB  
Article
Optimization of the Process for Green Jujube Vinegar and Organic Acid and Volatile Compound Analysis during Brewing
by Guifeng Li, Ni Yan, Guoqin Li and Jing Wang
Foods 2023, 12(17), 3168; https://doi.org/10.3390/foods12173168 - 23 Aug 2023
Cited by 1 | Viewed by 1296
Abstract
Healthy fruit vinegar has become very popular recently in China. This study aimed to produce fruit vinegar with a good taste, high nutritional value, and strong functional properties from green jujube. This study investigated the optimization of the process for green jujube vinegar [...] Read more.
Healthy fruit vinegar has become very popular recently in China. This study aimed to produce fruit vinegar with a good taste, high nutritional value, and strong functional properties from green jujube. This study investigated the optimization of the process for green jujube vinegar using response surface methodology. The optimum fermentation parameters for green jujube vinegar were determined as follows: initial alcoholicity 6%, acetobacter 8%, fermentation temperature 32 °C, and time 7 d. The organic acids of the optimized sample were evaluated by HPLC, and the volatile substances were identified and analyzed by HS-SPME and GC-MS during the fermentation and aging of the green jujube vinegar. The results showed that the variation trends of the different organic acids during the making of the green jujube vinegar were significantly different. Organic acids are the key flavor compounds of green jujube vinegar, and their changes were mainly attributed to microbial metabolism. In particular, the green jujube vinegar stood out in terms of volatile aroma compounds, including a total of 61 volatile compounds whose major components were acetic acid, isoamyl acetate, ethyl acetate, 3-hydroxy-2-butanone, methyl palmitate, and ethanol. The results can provide theoretical support for the production of green jujube vinegar. Full article
(This article belongs to the Section Food Engineering and Technology)
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<p>Response surface 3D diagram of the effects of four independent variables on total acidity of green jujube vinegar. A, B, C, and D represent inoculation amount of acetobacter (%, <span class="html-italic">v</span>/<span class="html-italic">v</span>), fermentation temperature (°C), fermentation time (d), and alcohol content (%, <span class="html-italic">v</span>/<span class="html-italic">v</span>), respectively. (<b>a</b>) A and B are two variables, C = 7.00 h, and D = 6.00%; (<b>b</b>) A and C are two variables, B = 32.00 °C, and D = 6.00%; (<b>c</b>) A and D are two variables, B = 32.00 °C, and C = 7.00 h; (<b>d</b>) B and D are two variables, A = 8.00%, and C = 7.00 h; (<b>e</b>) B and C are two variables, A = 8.00%, and D = 6.00%; and (<b>f</b>) C and D are two variables, A = 8.00%, and B = 32.00 °C.</p>
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<p>Analysis of organic acids during the fermentation of green jujube vinegar by HPLC, (1) oxalic acid, (2) tartaric acid, (3) lactic acid, (4) acetic acid, (5) citric acid, (6) malic acid, and (7) succinic acid; (<b>a</b>) fresh jujube juice, (<b>b</b>) alcohol fermented for 7 days, (<b>c</b>) acetic acid fermented for 7 days, (<b>d</b>) green jujube vinegar aged for 1 month, (<b>e</b>) green jujube vinegar aged for 2 months, and (<b>f</b>) analysis of total organic acids in the fermentation of green jujube vinegar.</p>
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<p>Analysis of organic acids during the fermentation of green jujube vinegar by HPLC, (1) oxalic acid, (2) tartaric acid, (3) lactic acid, (4) acetic acid, (5) citric acid, (6) malic acid, and (7) succinic acid; (<b>a</b>) fresh jujube juice, (<b>b</b>) alcohol fermented for 7 days, (<b>c</b>) acetic acid fermented for 7 days, (<b>d</b>) green jujube vinegar aged for 1 month, (<b>e</b>) green jujube vinegar aged for 2 months, and (<b>f</b>) analysis of total organic acids in the fermentation of green jujube vinegar.</p>
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<p>Analysis of flavor compounds during fermentation of green jujube vinegar by HS-SPME-GC-MS, (<b>a</b>) fresh jujube juice, (<b>b</b>) alcohol fermentation for 7 days, (<b>c</b>) acetic acid fermentation for 7 days, (<b>d</b>) green jujube vinegar aged for 1 month, (<b>e</b>) green jujube vinegar aged for 2 months.</p>
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18 pages, 13160 KiB  
Article
Analysis of Volatile Markers and Their Biotransformation in Raw Chicken during Staphylococcus aureus Early Contamination
by Yin Wang, Xian Wang, Yuanyuan Huang, Tianli Yue and Wei Cao
Foods 2023, 12(14), 2782; https://doi.org/10.3390/foods12142782 - 21 Jul 2023
Cited by 4 | Viewed by 1758
Abstract
To address the potential risks to food safety, headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace gas chromatography–ion mobility spectrometry (HS-GC-IMS) were used to analyze the volatile organic compounds (VOCs) generated from chilled chicken contaminated with Staphylococcus aureus during early [...] Read more.
To address the potential risks to food safety, headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace gas chromatography–ion mobility spectrometry (HS-GC-IMS) were used to analyze the volatile organic compounds (VOCs) generated from chilled chicken contaminated with Staphylococcus aureus during early storage. Together with the KEGG database, we analyzed differential metabolites and their possible biotransformation pathways. Orthogonal partial least squares discriminant analysis (OPLS-DA) was applied to characterize VOCs and identify biomarkers associated with the early stage of chicken meat contamination with S. aureus. The results showed 2,6,10,15-tetramethylheptadecane, ethyl acetate, hexanal, 2-methylbutanal, butan-2-one, 3-hydroxy-2-butanone, 3-methylbutanal, and cyclohexanone as characteristic biomarkers, and 1-octen-3-ol, tetradecane, 2-hexanol, 3-methyl-1-butanol, and ethyl 2-methylpropanoate as potential characteristic biomarkers. This provides a theoretical basis for the study of biomarkers of Staphylococcus aureus in poultry meat. Full article
(This article belongs to the Section Food Analytical Methods)
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<p>Venn diagram of VOCs detected at two concentrations using two methods; (<b>a</b>) comparison of M-F and M-S; (<b>b</b>) comparison of I-F and I-S; (<b>c</b>) comparison of HS-SPME-GC-MS and HS-GC-IMS. M-F: substances in 10<sup>−4</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples detected by HS-SPME-GC-MS.; M-S: substances in 10<sup>−6</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples detected by HS-SPME-GC-MS; I-F: substances in 10<sup>−4</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples detected by HS-GC-IMS; I-S: substances in 10<sup>−6</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples detected by HS-GC-IMS.</p>
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<p>Cluster heat map of volatile components of chicken meat at different incubation times by HS-SPME-GC-MS; (<b>A</b>) substances detected at 10<sup>−4</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples; (<b>B</b>) substances detected at 10<sup>−6</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples; “CK” served as a blank control.</p>
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<p>Venn diagram of six time points for volatile components of chicken meat by HS-SPME-GC-MS; (<b>A</b>) 10<sup>−4</sup> concentration bacterial suspension inoculation group; (<b>B</b>) 10<sup>−6</sup> concentration bacterial suspension inoculation group.</p>
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<p>Fingerprint spectra of volatile components in chicken meat at different incubation times (from top to bottom is 0 h, 4 h, 8 h, 12 h, 24 h, 48 h) by HS-GC-IMS; (<b>A</b>) substances detected at 10<sup>−4</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples; (<b>B</b>) substances detected at 10<sup>−6</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples; (M) for monoblock and (D) for dimer.</p>
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<p>KEGG enrichment of all VOCs.</p>
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<p>3-Methylbutanal, 3-Methyl-1-butanol, and 3-Methylbutyric acid (isovaleric acid) are produced by the catabolism of leucine, which has been found to be significantly released by <span class="html-italic">Staphylococcus aureus</span>.</p>
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<p>OPLS-DA of volatile organic compounds in chicken meat contaminated with <span class="html-italic">Staphylococcus aureus</span> at different incubation times by HS-GC-IMS; (<b>A</b>) factor loading diagram at 10<sup>−4</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples; (<b>B</b>) displacement test results at 10<sup>−4</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples; (<b>C</b>) factor loading diagram at 10<sup>−6</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples; (<b>D</b>) displacement test results at 10<sup>−6</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples.</p>
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<p>OPLS-DA of volatile organic compounds in chicken meat contaminated with <span class="html-italic">Staphylococcus aureus</span> at different incubation times by HS-SPME-GC-MS; (<b>A</b>) factor loading diagram at 10<sup>−4</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples; (<b>B</b>) displacement test results at 10<sup>−4</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples; (<b>C</b>) factor loading diagram at 10<sup>−6</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples; (<b>D</b>) displacement test results at 10<sup>−6</sup> concentration of <span class="html-italic">S. aureus</span>-contaminated samples.</p>
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<p>Comparison of the amount of volatile flavor compounds detected by HS-SPME-GC-MS and HS-GC-IMS.</p>
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15 pages, 2752 KiB  
Article
Kosakonia cowanii Ch1 Isolated from Mexican Chili Powder Reveals Growth Inhibition of Phytopathogenic Fungi
by Jacqueline González Espinosa, Yoali Fernanda Hernández Gómez, Yomaiko Javier Martínez, Francisco Javier Flores Gallardo, Juan Ramiro Pacheco Aguilar, Miguel Ángel Ramos López, Jackeline Lizzeta Arvizu Gómez, Carlos Saldaña Gutierrez, José Alberto Rodríguez Morales, María Carlota García Gutiérrez, Aldo Amaro Reyes, Erika Álvarez Hidalgo, Jorge Nuñez Ramírez, José Luis Hernández Flores and Juan Campos Guillén
Microorganisms 2023, 11(7), 1758; https://doi.org/10.3390/microorganisms11071758 - 5 Jul 2023
Cited by 3 | Viewed by 3337
Abstract
Kosakonia cowanii strain Ch1 was isolated from Mexican chili powder, and the genome was sequenced. The genome was 4,765,544 bp in length, with an average G + C content of 56.22%, and a plasmid (pCh1) of 128,063 bp with an average G + [...] Read more.
Kosakonia cowanii strain Ch1 was isolated from Mexican chili powder, and the genome was sequenced. The genome was 4,765,544 bp in length, with an average G + C content of 56.22%, and a plasmid (pCh1) of 128,063 bp with an average G + C content of 52.50%. A phylogenetic analysis revealed a close relation with pathogenic strains; nevertheless, some virulence-related genes were absent, and this genetic characteristic may explain the fact that K. cowanii Ch1 behaved as a non-pathogenic strain when infection assays were performed on the leaves and fruits of Capsicum annuum L. Surprisingly, we observed that this bacterial strain had the ability to spread throughout serrano pepper seeds. Furthermore, K. cowanii Ch1 was evaluated for the production of volatile organic compounds (VOCs) against fungal pathogens, and the results showed that Alternaria alternata and Sclerotium rolfsii were inhibited in a radial mycelial growth assay by a mean rate of 70% and 64%, while Fusarium oxysporum was inhibited by only approximately 10%. Based on the headspace solid-phase microextraction combined with the gas chromatography mass spectrometry (HS-SPME-GC-MS), 67 potential VOCs were identified during the fermentation of K. cowanii Ch1 in TSA medium. From these VOCs, nine main compounds were identified based on relative peak area: dodecanoic acid; 3-hydroxy ethanol; 1-butanol-3-methyl; acetaldehyde; butanoic acid, butyl ester; cyclodecane; 2-butanone, 3-hydroxy; disulfide, dimethyl and pyrazine-2,5-dimethyl. Our findings show the potential of K. cowanii Ch1 for the biocontrol of fungal pathogens through VOCs production and reveal additional abilities and metabolic features as beneficial bacterial specie. Full article
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<p>Circular map of <span class="html-italic">K. cowanii</span> Ch1 chromosome and plasmid. (<b>A</b>) includes, from outer to inner rings, ensembled contigs, CDS on the forward and reverse strand, RNA genes, CDS for antimicrobial resistance genes, CDS for virulence factors, and GC content and skew. (<b>B</b>) indicates the subsystem functional assignments. The numbers provided in parentheses are the count of subsystems and genes associated with the subsystem name.</p>
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<p>Phylogenetic tree analysis of <span class="html-italic">K. cowanii</span> Ch1. The Codon Tree pipeline of BV-BRC was used to generate bacterial phylogenetic trees with <span class="html-italic">Kosakonia</span> genus strains (see methodology). <span class="html-italic">Enterobacter cloacae</span> and <span class="html-italic">Citrobacter freundi</span> were selected as outgroups.</p>
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<p>Pathogenesis test. Infection test with <span class="html-italic">K. cowanii</span> CH1 is shown in leaves (Panel <b>A</b>) and external/internal fruits (Panel <b>B</b>) of serrano pepper (<span class="html-italic">Capsicum annuum</span> L.). These results were similar to the controls. No lesions were detected when <span class="html-italic">K. cowanii</span> was inoculated in plantlets or serrano pepper fruits. Surprisingly, we observed growth of <span class="html-italic">K. cowanii</span> Ch1 on seeds of fruits (Panel <b>C</b>). TSA medium was supplemented with 100 µg/mL of ampicillin.</p>
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<p>Antifungal activity test of <span class="html-italic">K. cowanii</span> Ch1 against fungal pathogens. (<b>A</b>) shows radial mycelial growth for controls (upper) and treatment (lower) at the end of experiments. (<b>B</b>) shows inhibition rate (%) for fungal strains tested. Values by different letters show statistical differences according to Duncan’s multiple range test (<span class="html-italic">p</span> = 0.05).</p>
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<p>VOC detection from 18 h of fermentation culture of <span class="html-italic">K. cowanii</span> Ch1 using HS–SPME–GC–MS. Abundance and retention time are shown for each peak.</p>
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13 pages, 5968 KiB  
Article
Differentiation of Goat Meat Freshness Using Gas Chromatography with Ion Mobility Spectrometry
by Shan He, Bin Zhang, Xuan Dong, Yuqing Wei, Hongtu Li and Bo Tang
Molecules 2023, 28(9), 3874; https://doi.org/10.3390/molecules28093874 - 4 May 2023
Cited by 4 | Viewed by 2161
Abstract
To investigate the flavor changes in goat meat upon storage, the volatile components observed in goat meat after different storage periods were determined using gas chromatography–ion mobility spectrometry (GC–IMS). A total of 38 volatile organic compounds (VOCs) were determined from the goat meat [...] Read more.
To investigate the flavor changes in goat meat upon storage, the volatile components observed in goat meat after different storage periods were determined using gas chromatography–ion mobility spectrometry (GC–IMS). A total of 38 volatile organic compounds (VOCs) were determined from the goat meat samples, including alcohols, ketones, aldehydes, esters, hydrocarbons, ethers, and amine compounds. 1-Hexanol, 3-Hydroxy-2-butanone, and Ethyl Acetate were the main volatile substances in fresh goat meat, and they rapidly decreased with increasing storage time and can be used as biomarkers for identifying fresh meat. When combined with the contents of total volatile basic–nitrogen (TVB-N) and the total numbers of bacterial colonies observed in physical and chemical experiments, the characteristic volatile components of fresh, sub-fresh, and spoiled meat were determined by principal component analysis (PCA). This method will help with the detection of fraudulent production dates in goat meat sales. Full article
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<p>Changes in the TVC and TVB-N content of goat meat upon storage.</p>
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<p>A comparison of the GC-IMS 3D spectra obtained for the fresh, sub-fresh, and spoiled meat samples.</p>
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<p>The two-dimensional top-view comparison of the VOCs for goat samples of different freshness: (<b>a</b>) ion mobility spectrogram; (<b>b</b>) results of comparison with the fresh sample were selected as the reference.</p>
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<p>RI distribution of VOCs in the GC-IMS spectra of goat meat samples.</p>
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<p>Fingerprints of volatile compounds in goat meat samples of different freshness.</p>
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<p>PCA analysis of VOCs found in goat meat samples of different freshness.</p>
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<p>Heat map clustering of volatile substances produced during storage of the goat meat samples.</p>
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<p>Nearest-neighbor Euclidean distance diagram for goat meat samples of different freshness.</p>
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13 pages, 6586 KiB  
Article
Effects of Oat β-Glucan on the Textural and Sensory Properties of Low-Fat Set Type Pea Protein Yogurt
by Peiyao Zhao, Nana Li, Lingyun Chen, Yahong Guo, Yatao Huang, Litao Tong, Lili Wang, Bei Fan, Fengzhong Wang and Liya Liu
Molecules 2023, 28(7), 3067; https://doi.org/10.3390/molecules28073067 - 29 Mar 2023
Cited by 8 | Viewed by 2400
Abstract
This study investigated the effect of oat β-glucan as a fat substitute on the structure formation, texture, and sensory properties of pea protein yogurt. The results showed that the incorporation of 0.5% β-glucan significantly accelerated the lactic acid bacteria-induced fermentation, with the time [...] Read more.
This study investigated the effect of oat β-glucan as a fat substitute on the structure formation, texture, and sensory properties of pea protein yogurt. The results showed that the incorporation of 0.5% β-glucan significantly accelerated the lactic acid bacteria-induced fermentation, with the time for reaching the target pH of 4.6 shortened from 3.5 h to 3 h (p < 0.05); increased the plastic module (G′) from 693 Pa to 764 Pa when fermenting 3 h (p < 0.05); and enhanced the water-holding capacity from 77.29% to 82.15% (p < 0.05). The identification of volatile organic compounds (VOCs) in low-fat pea protein yogurt by GC-IMS revealed a significant decrease in aldehydes and a significant increase in alcohols, ketones and acids in the pea yogurt after fermentation (p < 0.05). Among them, the levels of acetic acid, acetone, 2,3-butanedione, 3-hydroxy-2-butanone, and ethyl acetate all significantly increased with the addition of oat β-glucan (p < 0.05), thereby providing prominent fruity, sweet, and creamy flavors, respectively. Combined with the results of sensory analysis, the quality characteristics of pea protein yogurt with 1% oil by adding 1% oat β-glucan were comparable to the control sample with 3% oil. Therefore, oat β-glucan has a good potential for fat replacement in pea protein yogurt. Full article
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<p>The pH changes of low-fat pea-protein-based yogurt during the fermentation process as affected by oat β-glucan concentration.</p>
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<p>Effects of oat β-glucan concentration on the storage modulus (G′) and loss modulus (G″) of low-fat pea-protein-based yogurt.</p>
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<p>The viscosity of low-fat pea-protein-based yogurt versus shear rate as a function of oat β-glucan concentration.</p>
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<p>Effects of oat β-glucan concentration on the microstructure of pea-protein-based yogurt: (<b>A</b>) yogurt prepared with 3% oil, (<b>B</b>) yogurt prepared with 1% oil, (<b>C</b>) yogurt prepared with 1% oil and 0.25% oat β-glucan, (<b>D</b>) yogurt prepared with 1% oil and 0.5% oat β-glucan, and (<b>E</b>) yogurt prepared with 1% oil and 1% oat β-glucan.</p>
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<p>Effect of oat β-glucan concentration on the two-dimensional difference spectra of VOCs before and after fermentation: A and B represent the samples with or without fermentation, respectively.</p>
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<p>The fingerprints of low-fat pea-protein-based yogurt with different levels of oat β-glucan before and after fermentation: A and B represent the samples with or without fermentation, respectively.</p>
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<p>The relative content of pea-protein-based yogurt with different levels of oat β-glucan before and after fermentation: A and B represent the samples with or without fermentation, respectively.</p>
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18 pages, 1712 KiB  
Article
LC-MS/MS Based Volatile Organic Compound Biomarkers Analysis for Early Detection of Lung Cancer
by Shuaibu Nazifi Sani, Wei Zhou, Balarabe B. Ismail, Yongkui Zhang, Zhijun Chen, Binjie Zhang, Changqian Bao, Houde Zhang and Xiaozhi Wang
Cancers 2023, 15(4), 1186; https://doi.org/10.3390/cancers15041186 - 13 Feb 2023
Cited by 15 | Viewed by 4470
Abstract
(1) Background: lung cancer is the world’s deadliest cancer, but early diagnosis helps to improve the cure rate and thus reduce the mortality rate. Annual low-dose computed tomography (LD-CT) screening is an efficient lung cancer-screening program for a high-risk population. However, LD-CT has [...] Read more.
(1) Background: lung cancer is the world’s deadliest cancer, but early diagnosis helps to improve the cure rate and thus reduce the mortality rate. Annual low-dose computed tomography (LD-CT) screening is an efficient lung cancer-screening program for a high-risk population. However, LD-CT has often been characterized by a higher degree of false-positive results. To meet these challenges, a volatolomic approach, in particular, the breath volatile organic compounds (VOCs) fingerprint analysis, has recently received increased attention for its application in early lung cancer screening thanks to its convenience, non-invasiveness, and being well tolerated by patients. (2) Methods: a LC-MS/MS-based volatolomics analysis was carried out according to P/N 5046800 standard based breath analysis of VOC as novel cancer biomarkers for distinguishing early-stage lung cancer from the healthy control group. The discriminatory accuracy of identified VOCs was assessed using subject work characterization and a random forest risk prediction model. (3) Results: the proposed technique has good performance compared with existing approaches, the differences between the exhaled VOCs of the early lung cancer patients before operation, three to seven days after the operation, as well as four to six weeks after operation under fasting and 1 h after the meal were compared with the healthy controls. The results showed that only 1 h after a meal, the concentration of seven VOCs, including 3-hydroxy-2-butanone (TG-4), glycolaldehyde (TG-7), 2-pentanone (TG-8), acrolein (TG-11), nonaldehyde (TG-19), decanal (TG-20), and crotonaldehyde (TG-22), differ significantly between lung cancer patients and control, with the invasive adenocarcinoma of the lung (IAC) having the most significant difference. (4) Conclusions: this novel, non-invasive approach can improve the detection rate of early lung cancer, and LC-MS/MS-based breath analysis could be a promising method for clinical application. Full article
(This article belongs to the Special Issue Prognostic Biomarkers of Lung Cancer)
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<p>(<b>A</b>–<b>G</b>), 1, control; 2, lung cancer before the operation; 3, lung cancer after the operation after three to seven days; 4, lung cancer after the operation after four to six weeks. Box and whisker plots of the measured concentrations of TG-4, TG-7, TG-8, TG-11, TG-19, TG-20, and TG-22 in the exhaled breath 1 h after meals of the study groups, (least significant difference test) LSD-t analysis of variance. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01. (<b>H</b>), ROC curve analysis was performed on the exhaled air 1 h after the meal in the control group and the lung cancer group before the operation. ROC curves for the TG-4, TG-7, TG-8, TG-11, TG-19, TG-20, and TG-22 breath model in the diagnosis of lung cancer. The area under the curve of TG-4, TG-7, TG-8, TG-11, TG-19, TG-20, and TG-22 were 0.766, 0.611, 0.636, 0.682, 0.604, 0.611, and 0.625, respectively.</p>
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<p>(<b>A</b>–<b>G</b>), 1, control; 2AIS; 3, MIA; 4, IAC. Box and whisker plots of the measured concentrations of TG-4, TG-7, TG-11, TG-13, TG-19, TG-20, and TG-22 in the exhaled breath 1 h after meals of the study groups, (least significant difference test) LSD-t analysis of variance. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01. (NB: All the data from AIS, MIA, and IAC are before surgery).</p>
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<p>Changes in VOC concentration in exhalation after different diets. (<b>A</b>–<b>C</b>). Changes in carbonyl VOCs’ concentration in human exhaled breath after eating some common foods. (<b>D</b>) Changes in the concentration of TG-4 in the exhaled breath after drinking different sugar solutions (<b>E</b>,<b>F</b>). Values and error bars represent mean ± SE.</p>
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<p>Difference between oral and nasal exhalation. Eight healthy volunteers drank the 5% glucose solution and immediately blew into two sampling bags in parallel with each other in the mouth and nose. Values and error bars represent mean ± SE. * nasal cavity compared with the oral cavity, <span class="html-italic">p</span> &lt; 0.05, and # compared fasting after sugar.</p>
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<p>The differences in oral salivary flora between the control group and the lung cancer group. (<b>A</b>) At the phylum level, the human oral salivary flora is mainly <span class="html-italic">Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes, and Fusobacteria</span>, accounting for about 99% of the proportion. Compared with the control group, the proportion of Elusimicrobia in the lung cancer group decreased (<span class="html-italic">p</span> = 0.038). (<b>B</b>) At the genus level, STAMP analyzed the difference in oral saliva between the control group and the lung cancer group.</p>
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