Image_1_From Function to Metabolome: Metabolomic Analysis Reveals the Effect of Probiotic Fermentation on the Chemical Compositions and Biological Activities of Perilla frutescens Leaves.PNG

This study aimed to investigate the impact of probiotic fermentation on the active components and functions of Perilla frutescens leaves (PFL). PFL was fermented for 7 days using six probiotics (Lacticaseibacillus Paracasei SWFU D16, Lactobacillus Plantarum ATCC 8014, Lactobacillus Rhamnosus ATCC 53013, Streptococcus Thermophilus CICC 6038, Lactobacillus Casei ATCC 334, and Lactobacillus Bulgaricus CICC 6045). The total phenol and flavonoid contents, antioxidant abilities, as well as α-glucosidase and acetylcholinesterase inhibition abilities of PFL during the fermentation process were evaluated, and its bioactive compounds were further quantified by high-performance liquid chromatography (HPLC). Finally, non-targeted ultra-HPLC–tandem mass spectroscopy was used to identify the metabolites affected by fermentation and explore the possible mechanisms of the action of fermentation. The results showed that most of the active component contents and functional activities of PFL exhibited that it first increased and then decreased, and different probiotics had clearly distinguishable effects from each other, of which fermentation with ATCC 53013 for 1 day showed the highest enhancement effect. The same trend was also confirmed by the result of the changes in the contents of 12 phenolic acids and flavonoids by HPLC analysis. Further metabolomic analysis revealed significant metabolite changes under the best fermentation condition, which involved primarily the generation of fatty acids and their conjugates, flavonoids. A total of 574 and 387 metabolites were identified in positive ion and negative ion modes, respectively. Results of Spearman’s analysis indicated that some primary metabolites and secondary metabolites such as flavonoids, phenols, and fatty acids might play an important role in the functional activity of PFL. Differential metabolites were subjected to the KEGG database and 97 metabolites pathways were obtained, of which biosyntheses of unsaturated fatty acids, flavonoid, and isoflavonoid were the most enriched pathways. The above results revealed the potential reason for the differences in metabolic and functional levels of PFL after fermentation. This study could provide a scientific basis for the further study of PFL, as well as novel insights into the action mechanism of probiotic fermentation on the chemical composition and biological activity of food/drug.</p

Image_3_From Function to Metabolome: Metabolomic Analysis Reveals the Effect of Probiotic Fermentation on the Chemical Compositions and Biological Activities of Perilla frutescens Leaves.PNG

This study aimed to investigate the impact of probiotic fermentation on the active components and functions of Perilla frutescens leaves (PFL). PFL was fermented for 7 days using six probiotics (Lacticaseibacillus Paracasei SWFU D16, Lactobacillus Plantarum ATCC 8014, Lactobacillus Rhamnosus ATCC 53013, Streptococcus Thermophilus CICC 6038, Lactobacillus Casei ATCC 334, and Lactobacillus Bulgaricus CICC 6045). The total phenol and flavonoid contents, antioxidant abilities, as well as α-glucosidase and acetylcholinesterase inhibition abilities of PFL during the fermentation process were evaluated, and its bioactive compounds were further quantified by high-performance liquid chromatography (HPLC). Finally, non-targeted ultra-HPLC–tandem mass spectroscopy was used to identify the metabolites affected by fermentation and explore the possible mechanisms of the action of fermentation. The results showed that most of the active component contents and functional activities of PFL exhibited that it first increased and then decreased, and different probiotics had clearly distinguishable effects from each other, of which fermentation with ATCC 53013 for 1 day showed the highest enhancement effect. The same trend was also confirmed by the result of the changes in the contents of 12 phenolic acids and flavonoids by HPLC analysis. Further metabolomic analysis revealed significant metabolite changes under the best fermentation condition, which involved primarily the generation of fatty acids and their conjugates, flavonoids. A total of 574 and 387 metabolites were identified in positive ion and negative ion modes, respectively. Results of Spearman’s analysis indicated that some primary metabolites and secondary metabolites such as flavonoids, phenols, and fatty acids might play an important role in the functional activity of PFL. Differential metabolites were subjected to the KEGG database and 97 metabolites pathways were obtained, of which biosyntheses of unsaturated fatty acids, flavonoid, and isoflavonoid were the most enriched pathways. The above results revealed the potential reason for the differences in metabolic and functional levels of PFL after fermentation. This study could provide a scientific basis for the further study of PFL, as well as novel insights into the action mechanism of probiotic fermentation on the chemical composition and biological activity of food/drug.</p

Table_2_From Function to Metabolome: Metabolomic Analysis Reveals the Effect of Probiotic Fermentation on the Chemical Compositions and Biological Activities of Perilla frutescens Leaves.xlsx

This study aimed to investigate the impact of probiotic fermentation on the active components and functions of Perilla frutescens leaves (PFL). PFL was fermented for 7 days using six probiotics (Lacticaseibacillus Paracasei SWFU D16, Lactobacillus Plantarum ATCC 8014, Lactobacillus Rhamnosus ATCC 53013, Streptococcus Thermophilus CICC 6038, Lactobacillus Casei ATCC 334, and Lactobacillus Bulgaricus CICC 6045). The total phenol and flavonoid contents, antioxidant abilities, as well as α-glucosidase and acetylcholinesterase inhibition abilities of PFL during the fermentation process were evaluated, and its bioactive compounds were further quantified by high-performance liquid chromatography (HPLC). Finally, non-targeted ultra-HPLC–tandem mass spectroscopy was used to identify the metabolites affected by fermentation and explore the possible mechanisms of the action of fermentation. The results showed that most of the active component contents and functional activities of PFL exhibited that it first increased and then decreased, and different probiotics had clearly distinguishable effects from each other, of which fermentation with ATCC 53013 for 1 day showed the highest enhancement effect. The same trend was also confirmed by the result of the changes in the contents of 12 phenolic acids and flavonoids by HPLC analysis. Further metabolomic analysis revealed significant metabolite changes under the best fermentation condition, which involved primarily the generation of fatty acids and their conjugates, flavonoids. A total of 574 and 387 metabolites were identified in positive ion and negative ion modes, respectively. Results of Spearman’s analysis indicated that some primary metabolites and secondary metabolites such as flavonoids, phenols, and fatty acids might play an important role in the functional activity of PFL. Differential metabolites were subjected to the KEGG database and 97 metabolites pathways were obtained, of which biosyntheses of unsaturated fatty acids, flavonoid, and isoflavonoid were the most enriched pathways. The above results revealed the potential reason for the differences in metabolic and functional levels of PFL after fermentation. This study could provide a scientific basis for the further study of PFL, as well as novel insights into the action mechanism of probiotic fermentation on the chemical composition and biological activity of food/drug.</p

Image_2_From Function to Metabolome: Metabolomic Analysis Reveals the Effect of Probiotic Fermentation on the Chemical Compositions and Biological Activities of Perilla frutescens Leaves.PNG

This study aimed to investigate the impact of probiotic fermentation on the active components and functions of Perilla frutescens leaves (PFL). PFL was fermented for 7 days using six probiotics (Lacticaseibacillus Paracasei SWFU D16, Lactobacillus Plantarum ATCC 8014, Lactobacillus Rhamnosus ATCC 53013, Streptococcus Thermophilus CICC 6038, Lactobacillus Casei ATCC 334, and Lactobacillus Bulgaricus CICC 6045). The total phenol and flavonoid contents, antioxidant abilities, as well as α-glucosidase and acetylcholinesterase inhibition abilities of PFL during the fermentation process were evaluated, and its bioactive compounds were further quantified by high-performance liquid chromatography (HPLC). Finally, non-targeted ultra-HPLC–tandem mass spectroscopy was used to identify the metabolites affected by fermentation and explore the possible mechanisms of the action of fermentation. The results showed that most of the active component contents and functional activities of PFL exhibited that it first increased and then decreased, and different probiotics had clearly distinguishable effects from each other, of which fermentation with ATCC 53013 for 1 day showed the highest enhancement effect. The same trend was also confirmed by the result of the changes in the contents of 12 phenolic acids and flavonoids by HPLC analysis. Further metabolomic analysis revealed significant metabolite changes under the best fermentation condition, which involved primarily the generation of fatty acids and their conjugates, flavonoids. A total of 574 and 387 metabolites were identified in positive ion and negative ion modes, respectively. Results of Spearman’s analysis indicated that some primary metabolites and secondary metabolites such as flavonoids, phenols, and fatty acids might play an important role in the functional activity of PFL. Differential metabolites were subjected to the KEGG database and 97 metabolites pathways were obtained, of which biosyntheses of unsaturated fatty acids, flavonoid, and isoflavonoid were the most enriched pathways. The above results revealed the potential reason for the differences in metabolic and functional levels of PFL after fermentation. This study could provide a scientific basis for the further study of PFL, as well as novel insights into the action mechanism of probiotic fermentation on the chemical composition and biological activity of food/drug.</p

Table_1_From Function to Metabolome: Metabolomic Analysis Reveals the Effect of Probiotic Fermentation on the Chemical Compositions and Biological Activities of Perilla frutescens Leaves.xlsx

This study aimed to investigate the impact of probiotic fermentation on the active components and functions of Perilla frutescens leaves (PFL). PFL was fermented for 7 days using six probiotics (Lacticaseibacillus Paracasei SWFU D16, Lactobacillus Plantarum ATCC 8014, Lactobacillus Rhamnosus ATCC 53013, Streptococcus Thermophilus CICC 6038, Lactobacillus Casei ATCC 334, and Lactobacillus Bulgaricus CICC 6045). The total phenol and flavonoid contents, antioxidant abilities, as well as α-glucosidase and acetylcholinesterase inhibition abilities of PFL during the fermentation process were evaluated, and its bioactive compounds were further quantified by high-performance liquid chromatography (HPLC). Finally, non-targeted ultra-HPLC–tandem mass spectroscopy was used to identify the metabolites affected by fermentation and explore the possible mechanisms of the action of fermentation. The results showed that most of the active component contents and functional activities of PFL exhibited that it first increased and then decreased, and different probiotics had clearly distinguishable effects from each other, of which fermentation with ATCC 53013 for 1 day showed the highest enhancement effect. The same trend was also confirmed by the result of the changes in the contents of 12 phenolic acids and flavonoids by HPLC analysis. Further metabolomic analysis revealed significant metabolite changes under the best fermentation condition, which involved primarily the generation of fatty acids and their conjugates, flavonoids. A total of 574 and 387 metabolites were identified in positive ion and negative ion modes, respectively. Results of Spearman’s analysis indicated that some primary metabolites and secondary metabolites such as flavonoids, phenols, and fatty acids might play an important role in the functional activity of PFL. Differential metabolites were subjected to the KEGG database and 97 metabolites pathways were obtained, of which biosyntheses of unsaturated fatty acids, flavonoid, and isoflavonoid were the most enriched pathways. The above results revealed the potential reason for the differences in metabolic and functional levels of PFL after fermentation. This study could provide a scientific basis for the further study of PFL, as well as novel insights into the action mechanism of probiotic fermentation on the chemical composition and biological activity of food/drug.</p

Application of Multicolor Fluorescent Carbon Dots Based on Tea Polyphenols in a White Light-Emitting Diode and Room-Temperature Phosphorescence

Carbon dots (CDs) are new carbon nanomaterials, among which those prepared from biomass are popular due to their excellent optical properties and environmental friendliness. As representative natural phenolic compounds, tea polyphenols are ideal precursors with fluorescent aromatic rings and phenolic hydroxyl structures. Usually, polyphenolic precursors can only be used to produce blue or green fluorescent CDs, and fluorescence in long wavelength domains, such as orange or red, cannot be achieved. Herein, the high reactivity of the phenolic hydroxyl groups in tea polyphenols with o-phthalaldehyde was exploited to modulate the pH during the carbonation process, which led to redshifts of the fluorescence wavelengths. Different pH values during the reaction caused the precursors to take different reaction paths and form fluorescent groups exhibiting different conjugated structures, resulting in carbon dots providing different fluorescent colors. Finally, by utilizing the in situ hydrolysis of ethyl orthosilicate, the tea polyphenol-based carbon dots were embedded into a silica matrix, inducing phosphorescence of the carbon dots. This study provides a new approach for green preparation and application of natural polyphenolic CDs

Proteomic Analysis of the Relationship between Metabolism and Nonhost Resistance in Soybean Exposed to <i>Bipolaris maydis</i>

<div><p>Nonhost resistance (NHR) pertains to the most common form of plant resistance against pathogenic microorganisms of other species. <i>Bipolaris maydis</i> is a non-adapted pathogen affecting soybeans, particularly of maize/soybean intercropping systems. However, no experimental evidence has described the immune response of soybeans against <i>B</i>. <i>maydis</i>. To elucidate the molecular mechanism underlying NHR in soybeans, proteomics analysis based on two-dimensional polyacrylamide gel electrophoresis (2-DE) was performed to identify proteins involved in the soybean response to <i>B</i>. <i>maydis</i>. The spread of <i>B</i>. <i>maydis</i> spores across soybean leaves induced NHR throughout the plant, which mobilized almost all organelles and various metabolic processes in response to <i>B</i>. <i>maydis</i>. Some enzymes, including ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO), mitochondrial processing peptidase (MPP), oxygen evolving enhancer (OEE), and nucleoside diphosphate kinase (NDKs), were found to be related to NHR in soybeans. These enzymes have been identified in previous studies, and STRING analysis showed that most of the protein functions related to major metabolic processes were induced as a response to <i>B</i>. <i>maydis</i>, which suggested an array of complex interactions between soybeans and <i>B</i>. <i>maydis</i>. These findings suggest a systematic NHR against non-adapted pathogens in soybeans. This response was characterized by an overlap between metabolic processes and response to stimulus. Several metabolic processes provide the soybean with innate immunity to the non-adapted pathogen, <i>B</i>. <i>maydis</i>. This research investigation on NHR in soybeans may foster a better understanding of plant innate immunity, as well as the interactions between plant and non-adapted pathogens in intercropping systems.</p></div

Two-DE map of root proteins responding to <i>B</i>. <i>maydis</i>.

<p>S1 and S15 were zoomed in the protein spot 1 and spot 15 differentially expressed under the <i>B</i>. <i>maydis</i> stress; “C” refers to the protein spot excised from the control gel, and “T” refers to the protein spot excised from the treatment gel. The differential abundance of proteins was determined using the PDQuest software and was plotted as the relative intensity enumerated as ES1 and ES15. ES1 and ES15 represent the relative expression between control and treatment of protein spot 1 and spot 15, “C” means control, and “T” indicates treatment. S1/ES1 and S15/ES15 are representative differentially expressed root proteins.</p

<i>Arabidopsis</i> DB-based BLAST analysis of the interaction network of 64 differentially expressed proteins in the roots, stems, and leaves of soybean plants in response to <i>B</i>. <i>maydis</i>.

<p>GO analysis indicated that the 38 red nodes in A might be involved in metabolic processes (P value = 1.070e ⁻¹⁰). Another 35 red nodes in B were involved in stimulus response (P value = 3.970e ⁻¹⁰). Thirty proteins belonged to the both metabolic process and response to stimulus, which suggested that the same protein could perform different functions in soybean plants in response to <i>B</i>. <i>maydis</i> stress.</p

Proteins responsive to <i>B</i>. <i>maydis</i> and its predicted multiple subcellular locations.

<p>A) A conceptual diagram of a systematic NHR of soybean against <i>B</i>. <i>maydis</i>. H₂O₂ production and callose deposition were processed upon the interaction between soybean and <i>B</i>. <i>maydis</i> starting at the cell wall of soybean. The subcellular locations of the differentially expressed proteins were predicted. Changed proteins are shown in italics, and the organelle is written in blue. For instance, Hsp 70 was predicted to exist in chloroplasts and mitochondria. All of the major organelles responded to <i>B</i>. <i>maydis</i>. B) Venn diagram representing the differentially expressed proteins found in the leaves, stems, and roots of soybean plants. An L, S, or R character was placed before the spots (corresponding to the 2-DE pattern) corresponding to leaf, stem, and root proteins. Two pairs of leaf and stem protein spots were attributed to the same protein, L17 and S24, and L34 and S7. There was only one pair of stem and root protein spots that was attributed to the same protein, S15 and R13. However, no protein overlap between leaf and root was detected.</p