Identification of Antibacterial Components in the Methanol-Phase Extract from Edible Herbaceous Plant Rumex madaio Makino and Their Antibacterial Action Modes

Abstract

Outbreaks and prevalence of infectious diseases worldwide are some of the major contributors to morbidity and morbidity in humans. Pharmacophageous plants are the best source for searching antibacterial compounds with low toxicity to humans. In this study, we identified, for the first time, antibacterial components and action modes of methanol-phase extract from such one edible herbaceous plant Rumex madaio Makino. The bacteriostatic rate of the extract was 75% against 23 species of common pathogenic bacteria. The extract was further purified using the preparative high-performance liquid chromatography (Prep-HPLC) technique, and five separated componential complexes (CC) were obtained. Among these, the CC 1 significantly increased cell surface hydrophobicity and membrane permeability and decreased membrane fluidity, which damaged cell structure integrity of Gram-positive and -negative pathogens tested. A total of 58 different compounds in the extract were identified using ultra-HPLC and mass spectrometry (UHPLC-MS) techniques. Comparative transcriptomic analyses revealed a number of differentially expressed genes and various changed metabolic pathways mediated by the CC1 action, such as down-regulated carbohydrate transport and/or utilization and energy metabolism in four pathogenic strains tested. Overall, the results in this study demonstrated that the CC1 from R. madaio Makino are promising candidates for antibacterial medicine and human health care products.

1. Introduction

China is one of the richest countries in biodiversity, with very high levels of plant endemism [1]. Pharmacopoeia of the Peoples’ Republic of China (2020 Edition) contains 2711 species of Chinese herbal plants, which constitute a gold mine for exploiting medicine candidates and health care products [2]. For instance, R. madaio Makino is an edible, perennial and herbaceous plant that belongs to the Dicotyledoneae class, Polygonaceae family, and Rumex genus. According to the National Compilation of Chinese Herbal Medicine (1996 Edition), leaf and root tissues of R. madaio Makino can be used as medicine such as clearing heat and detoxification, removing blood stasis, and defecating and killing insects. Nevertheless, current studies on the antibacterial activity of R. madaio Makino are rare.

In this study, antibacterial components and action modes of methanol-phase extract from R. madaio Makino were for the first time identified. The objectives of this study were: (1) to extract bioactive substances from R. madaio Makino using the methanol and chloroform extraction (MCE) method, and determine their inhibition activity against 23 species of pathogenic bacteria; (2) to purify the methanol-phase extract from R. madaio Makino by preparation high-performance liquid chromatography (Prep-HPLC) analysis, and identify bioactive compounds in componential complex 1 (CC 1) using an ultra-HPLC and mass spectrometry (UHPLC-MS) technique; (3) to determine cell surface hydrophobicity, cell membrane permeability, fluidity, and the damage of four representative pathogenic strains treated with the CC 1; (4) to decipher possible molecular mechanisms underlying antibacterial activity by comparative transcriptomic analysis. The results of this study meet the increasing need for novel antibacterial agent candidates against common pathogenic bacteria.

2. Results and Discussion

2.1. Antibacterial Activity of Crude Extracts from R. madaio Makino

Antibacterial substances in fresh leaf and stem tissues of R. madaio Makino were extracted using the MCE method. The results showed that the water loss rate of the plant material was 93.32%, and extraction rates of the methanol phase and chloroform phase were 32.10% and 29.60%, respectively. Antibacterial activity of the crude extracts against 23 species of pathogenic bacteria was determined, most of which are common foodborne pathogens, and the results are presented in

Table 1. Antibacterial activity of crude extracts from R. madaio Makino.

pStrain	Inhibition Zone (Diameter, mm)		MIC (μg/mL)
	CPE	MPE	CPE	MPE
Aeromonas hydrophila ATCC35654	—	11.30 ± 0.47	—	126
Bacillus cereus A1-1	—	14.70 ± 1.25	—	32
Enterobacter cloacae ATCC13047	7.90 ± 0.05	13.00 ± 0.86	512	64
Enterobacter cloacae	—	8.30 ± 0.24	—	512
Escherichia coli ATCC8739	—	—	—	—
Escherichia coli ATCC25922	—	—	—	—
Escherichia coli K12	—	9.30 ± 1.25	—	128
Enterobacter sakazakii CMCC45401	8.90 ± 0.14	8.70 ± 0.47	256	512
Listeria monocytogenes ATCC19115	9.80 ± 0.17	—	256	—
Pseudomonas aeruginosa ATCC9027	—	9.30 ± 0.94	—	256
Pseudomonas aeruginosa ATCC27853	—	9.00 ± 0.21	—	256
Salmonella choleraesuis ATCC13312	—	9.70 ± 0.94	—	256
Salmonella paratyphi-A CMCC50093	8.70 ± 0.94	9.40 ± 0.43	512	256
Salmonella typhimurium ATCC15611	8.90 ± 0.17	14.00 ± 0.82	256	32
Salmonella	8.20 ± 0.17	20.30 ± 0.47	512	8
Shigella dysenteriae CMCC51252	—	—	—	—
Shigella flexneri CMCC51572	—	10.00 ± 0.00	—	128
Shigella flexneri ATCC12022	—	—	—	—
Shigella flexneri CMCC51574	—	—	—	—
Shigella sonnei ATCC25931	—	—	—	—
Shigella sonnet CMCC51592	9.40 ± 0.29	8.10 ± 0.05	256	512
Staphylococcus aureus ATCC25923	10.60 ± 0.42	8.10 ± 0.29	128	512
Staphylococcus aureus ATCC8095	8.00 ± 0.05	7.30 ± 0.21	512	1024
Staphylococcus aureus ATCC29213	—	7.20 ± 0.08	—	1024
Staphylococcus aureus ATCC6538	10.00 ± 0.82	10.00 ± 2.16	256	256
Staphylococcus aureus ATCC6538P	—	10.50 ± 0.41	—	128
Staphylococcus aureus	7.00 ± 0.00	8.50 ± 0.41	1024	512
Vibrio alginolyticus ATCC17749	—	24.30 ± 1.25	—	4
Vibrio alginolyticus ATCC33787	—	—	—	—
Vibrio cholerae Q10-54	—	—	—	—
Vibrio cholerae b10-49	—	9.00 ± 0.24	—	256
Vibrio cholerae GIM1.449	10.30 ± 0.36	10.50 ± 0.41	256	128
Vibrio fluvialis ATCC33809	11.30 ± 0.47	7.90 ± 0.09	128	512
Vibrio harvey ATCC BAA-1117	—	8.00 ± 0.05	—	512
Vibrio harveyi ATCC33842	—	—	—	—
Vibrio metschnikovii ATCC700040	8.40 ± 0.42	—	512	—
Vibrio mimicus bio-56759	9.20 ± 0.12	13.00 ± 0.82	512	64
Vibrio parahaemolyticus B3-13	10.50 ± 0.41	9.10 ± 0.12	128	256
Vibrio parahaemolyticus B4-10	—	10.30 ± 0.47	—	128
Vibrio parahaemolyticus B5-29	—	12.30 ± 0.94	—	64
Vibrio parahaemolyticus B9-35	—	8.30 ± 0.21	—	512
Vibrio parahaemolyticus ATCC17802	—	13.70 ± 0.94	—	128
Vibrio parahaemolyticus ATCC33847	—	13.00 ± 0.00	—	64
Vibrio vulnificus ATCC27562	11.70 ± 1.25	8.70 ± 0.47	128	256

Note: CPE: chloroform phase extract. MPE: methanol phase extract. —: no bacteriostasis activity. Inhibition zone: diameter includes the disk diameter (6 mm). MIC: minimum inhibitory concentration. Values are means ± S.D. of three parallel measurements.

. The chloroform-phase crude extract from R. madaio Makino showed a bacteriostatic rate of 39%, inhibiting 2 species of Gram-positive and 11 species of Gram-negative pathogens (Table 1, Figure 1). Remarkably, the methanol-phase crude extract from R. madaio Makino inhibited the growth of 33 bacteria strains tested with a bacteriostatic rate of 75%, including 2 species of Gram-positive and 18 species of Gram-negative pathogens (Table 1). Based on the higher bacteriostatic rate (75%), the methanol-phase crude extract from R. madaio Makino was chosen for further analysis in this study.

2.2. Purification of the Methanol-Phase Crude Extract from R. madaio Makino

Large amounts of the methanol-phase crude extract from R. madaio Makino were further purified by the Prep-HPLC analysis. As shown in Figure 2, five obviously separated peaks (designated as componential complex, CCs 1 to 5) were observed by scanning at OD_{280 nm} for 15 min.

These five single peaks were individually collected for antibacterial activity analysis. The results revealed that the CC 1 had strong inhibitory effects on Vibrio parahaemolyticus ATCC17802, Vibrio alginolyticus ATCC17749, Bacillus cereus A1-1, and V. parahaemolyticus B4-10. Moreover, the growth of the other four strains was also depressed, including V. parahaemolyticus ATCC33847, V. parahaemolyticus B3-13, V. parahaemolyticus B5-29, and Staphylococcus aureus ATCC6538 (

Table 2. Antibacterial activity of the CC 1 from R. madaio Makino.

Strain	Inhibition Zone (Diameter, mm)	MIC (μg/mL)
B. cereus A1-1	10.30 ± 0.24	128
S. typhimurium ATCC15611	7.90 ± 0.22	512
S. aureus ATCC6538	7.00 ± 0.05	1024
V. alginolyticus ATCC17749	11.20 ± 0.21	64
V. parahaemolyticus ATCC17802	11.10 ± 0.08	64
V. parahaemolyticus ATCC33847	7.90 ± 0.25	256
V. parahaemolyticus B3-13	7.10 ± 0.09	512
V. parahaemolyticus B4-10	9.40 ± 0.26	256
V. parahaemolyticus B5-29	8.10 ± 0.12	512

Note: MIC: minimum inhibitory concentration.

). Among these, V. alginolyticus is an opportunistic pathogenic bacterium that can infect a broad range of marine host animals, including fish, crab and pearl oysters, and can also infect the human ear, soft tissue and wounded sites [3,4], while V. parahaemolyticus is a leading seafood-borne pathogen worldwide and can cause acute gastroenteritis and septicemia in humans [5]. B. cereus is a Gram-positive bacterium for food poisoning. This bacterium has been incriminated in clinical conditions such as anthrax-like progressive pneumonia, fulminant sepsis, and devastating central nervous system infections, particularly in immunosuppressed individuals, intravenous drug abusers, and neonates [6].

Conversely, the other four peaks (CCs 2 to 4) showed weak or no antibacterial activity, indicating that bioactive compounds in the methanol-phase extract from R. madaio Makino existed in the CC 1.

MIC values of the CC 1 were also determined, which was 64 μg/mL against V. alginolyticus ATCC17749 and V. parahaemolyticus ATCC17802; 128 μg/mL against B. cereus A1-1; and 256 μg/mL against V. parahaemolyticus B4-10.

2.3. Changed Bacterial Cell Surface Structure by the CC 1 Extract

To decipher possible mechanisms underlying bacteriostatic activity of the CC 1, the cell structure of the four highly inhibited strains were observed by the transmission electron microscope (TEM) analysis. As shown in Figure 3, in remarkable contrast to control groups whose cell surface structure was intact, showing rod cells, a flat surface, and a clear structure, bacterial cells in the treatment groups showed different degrees of contraction and rupture, some of which were deformed with obvious depressions, folds or cavities on the surface. For example, for the Gram-positive B. cereus A1-1, the 2 h treatment by the CC 1 resulted in the bacterial cell surface shrinking seriously, the flagella breaking, and some contents leaking. After being treated for 4 h, cell surface shrinkage was intensified, and more cells were ruptured. After being treated for 6 h, the cell structure was seriously damaged, a large number of contents exuded, and only a few cells still maintained rod shape (Figure 3A). For the Gram-negative V. parahaemolyticus ATCC17802, after being treated with the CC 1 for 2 h, its cell surface shrunk slightly, and pili structure was still visible. However, after being treated for 4 h, the cell surface shrinkage increased and the cell membrane folded. V. parahaemolyticus ATCC17802 cells were destroyed, seriously shrunk and deformed after being treated for 6 h (Figure 3C). These results indicated that the CC 1 from R. madaio Makino damaged the cell surface structure of the Gram-negative and Gram-positive pathogens.

2.4. Changed Bacterial Cell Surface Hydrophobicity, Cell Membrane Fluidity, Permeability, and Damage by the CC 1 from R. madaio Makino

Cell surface hydrophobicity plays an important role in the adhesion to abiotic and biological surfaces and infiltration of host tissue [7]. In this study, bacterial cell surface hydrophobicity of all four experimental groups was significantly increased (p < 0.05) when compared with the control groups (Figure 4A). The effect was highly enhanced with the increase in treatment time. For example, cell surface hydrophobicity was significantly increased in V. parahaemolyticus ATCC17802 (1.47-fold), V. parahaemolyticus B4-10 (1.62-fold) and B. cereus A1-1 (1.42-fold) after being treated with the CC1 for 2 h (p < 0.05), whereas a similar change was observed in the treatment group of V. alginolyticus ATCC17749 (1.48-fold) after being treated for 4 h. Moreover, the highest increase in cell surface hydrophobicity was observed in B. cereus A1-1 (3.75-fold) after being treated with the CC1 for 6 h (Figure 4A).

Membrane fluidity is also a key parameter of the bacterial cell membrane that undergoes quick adaptation in response to environmental challenges [8]. It has recently been regarded as an important factor in the antibacterial mechanism of membrane-targeting antibiotics [9]. In this study, compared with the control groups, there was no significant difference in cell membrane fluidity of V. parahaemolyticus ATCC17802 and B4-10, as well as V. alginolyticus ATCC17749 after being treated with the CC 1 for 2 h (p > 0.05). However, a significant decrease in membrane fluidity of these three strains was observed after the treatment for 4 h. Additionally, cell membrane fluidity significantly declined in B. cereus A1-1 (1.20-fold) treated with the CC 1 for 2 h, and sharply lost for 6 h (8.11-fold) (Figure 4B). The change of membrane lipid composition likely contributed to the observed membrane fluidity change to resist the lipid disorder effect by therapeutic agents [10].

The o-nitrophenyl-β-d-galactopyranoside (o-nitrophenyl)-β-d-galactopyranoside (ONPG) was used as a probe to monitor the inner cell membrane permeability of the four bacterial strains, and the results were illustrated in Figure 5. Different influence of the CC 1 from R. madaio Makino on inner cell membrane permeability was observed among the four treatment groups. For example, V. alginolyticus ATCC17749 did not change significantly in the inner cell membrane permeability after the treatment for 2 h (p > 0.05), whereas a significant increase was observed after being treated for 4 h (1.15-fold) and 6 h (1.18-fold), respectively (p < 0.05) (Figure 5).

N-Phenyl-1-naphthylamine (NPN) was used as a probe to monitor the bacterial outer membrane permeability. As shown in Figure 6, the outer membrane permeability in the four experimental groups were all highly increased after the treatment with the CC 1 for 2 h (p < 0.01). The highest increase was found in B. cereus A1-1 (6.06-fold) after being treated for 6 h, whereas an opposite pattern was observed in V. parahaemolyticus ATCC17802 (1.77-fold).

As shown in Figure 4C, when compared with the control groups, cell membrane damage rates of all four experimental groups significantly increased (p < 0.05), which raised with the increase in treatment time. Significant damage was observed in B. cereus A1-1 (2.95-fold) and V. parahaemolyticus B4-10 (2.21-fold) after being treated for 2 h, whereas a similar change was found in the other two strains treated for 4 h. Moreover, cell membrane damage of B. cereus A1-1 was the most severe among the four strains after being treated for 6 h (8.54-fold).

Taken together, these results demonstrated that the CC 1 from R. madaio Makino significantly increased bacterial cell surface hydrophobicity and membrane permeability and decreased membrane fluidity of V. parahaemolyticus ATCC17802, V. parahaemolyticus B4-10, V. alginolyticus ATCC17749, and B. cereus A1-1, consistent with the observed bacterial surface structure by the TEM analysis. The damaged cell surface and membrane structure integrity were beneficial for the CC1 to penetrate bacterial cell envelope to target intracellular processes.

2.5. Identification of Potential Antibacterial Compounds in the CC 1 from R. madaio Makino

The obtained CC 1 resolved in H₂O was subjected to UHPLC-MS analysis. As shown in

Table 3. Compounds identified in the CC 1 from R. madaio Makino by the UHPLC–MS analysis.

Peak No.	Identified Compound	Compound Nature	Rt (min)	Formula	Exact Mass	Peak Area (%)
1	p-Octopamine	Biogenic amine	3.84	C8H11NO2	153.08	18.62
2	D-alpha-Aminobutyric acid	Amino acids and derivatives	0.65	C4H9NO2	103.06	9.46
3	Sucrose	Carbohydrates	0.89	C12H22O11	342.12	7.01
4	Turanose	Carbohydrates	0.79	C12H22O11	342.12	7.01
5	Lactulose	Organooxygen compounds	0.77	C12H22O11	342.12	7.01
6	L-Arginine	Amino acids and derivatives	0.60	C6H14N4O2	174.11	4.98
7	L-Lysine; L-Glutamine	Amino acids and derivatives	0.64	C6H14N2O2	146.11	4.68
8	D-Glutamine	Amino acids and derivatives	0.66	C5H10N2O3	146.07	4.68
9	(2E)-Decenoyl-ACP	Carboxylic acids and derivatives	1.47	C6H11NO2	129.08	3.14
10	O-Acetylethanolamine	Alkaloids	0.67	C4H9NO2	103.06	3.00
11	L-Pipecolic acid	Amino acids and derivatives	0.69	C6H11NO2	129.08	2.48
12	Pyrrolidonecarboxylic acid	Amino acids and derivatives	0.67	C5H7NO3	129.04	2.48
13	D-Maltose	Carbohydrates	0.76	C12H22O11	342.12	1.86
14	Trigonelline	Alkaloids	0.82	C7H7NO2	137.05	1.74
15	Indole	Alkaloids	3.82	C8H7N	117.06	1.66
16	Uridine 5’-diphospho-d-glucose	Carbohydrates	0.71	C15H24N2O17P2	566.06	1.65
17	Proline; L-Proline	Amino acids and derivatives;	0.73	C5H9NO2	115.06	1.53
18	D-Proline	Amino acids and derivatives	0.76	C5H9NO2	115.06	1.53
19	Lubiprostone	Fatty acyls	12.75	C20H32F2O5	390.22	1.40
20	Phosphoric acid	Inganic acids	0.65	H3O4P	97.98	1.29
21	Sarracine	Alkaloids	13.14	C18H27NO5	337.19	0.83
22	Galactose 1-phosphate	Organooxygen compounds	0.65	C6H13O9P	260.03	0.75
23	L-Glutamic acid	Amino acids and derivatives	0.66	C5H9NO4	147.05	0.67
24	Kojibiose	Carbohydrates	0.72	C12H22O11	342.12	0.50
25	Glucose 6-phosphate	Carbohydrates	0.65	C6H13O9P	260.03	0.49
26	p-Aminobenzoate	Benzoic acid derivatives	0.74	C7H7NO2	137.05	0.47
27	Betaine	Alkaloids	1.06	C5H11NO2	117.08	0.47
28	L-Histidine	Amino acids and derivatives	0.59	C6H9N3O2	155.07	0.44
29	8,9-DiHETrE	Fatty Acyls	13.03	C20H34O4	338.25	0.43
30	Gluconic acid	Organic acids	0.69	C6H12O7	196.06	0.43
31	N,N-Dimethylglycine	Amino acids and derivatives	1.04	C4H9NO2	103.05	0.40
32	2-Aminoisobutyric acid	Amino acids and derivatives	0.98	C4H9NO2	103.06	0.37
33	Diallyl disulfide	Organic disulfide	0.68	C6H10S2	146.02	0.37
34	2-Hydroxybutanoic acid	Organic acids	0.64	C4H8O3	104.05	0.35
35	Beta-Sitosterol	Steroids	12.93	C29H50O	414.39	0.33
36	Phosphorylcholine	Cholines	0.67	C5H14NO4P	183.07	0.31
37	Campesterol	Steroids and steroid derivatives	12.18	C28H48O	400.37	0.31
38	Gemcitabine	Pyrimidine nucleosides	0.75	C9H11F2N3O4	263.07	0.30
39	L-Threonine	Amino acids and derivatives	0.64	C4H9NO3	119.06	0.29
40	L-Homoserine	Amino acids and derivatives	0.67	C4H9NO3	119.05	0.29
41	3-Ethyl-1,2-benzenediol	Phenols	0.74	C8H10O2	138.07	0.29
42	Diacylglycerol	Glycerolipids	13.42	C37H70O5	568.51	0.28
43	Rutin	Flavonoids	5.85	C27H30O16	610.15	0.27
44	cis-Aconitic acid	Organic acids and derivatives	1.46	C6H6O6	174.02	0.25
45	L-Citruline	Amino acids and derivatives	0.66	C6H13N3O3	175.09	0.25
46	Wighteone	Flavonoids	13.01	C20H18O5	338.11	0.24
47	Beta-d-Fructose 2-phosphate	Carbohydrates	0.75	C6H13O9P	260.03	0.22
48	Maltol	Flavonoids	0.90	C6H6O3	126.03	0.21
49	Itaconic acid	Organic acids	0.52	C5H6O4	130.03	0.21
50	Safrole	Benzodioxoles	12.26	C10H10O2	162.07	0.20
51	22-Dehydroclerosterol	Steroids	12.59	C29H46O	410.35	0.18
52	8-Hydroxybergapten	Coumarins	10.56	C12H8O5	232.04	0.17
53	Isoquercitrin	Flavonoids	6.06	C21H20O12	464.10	0.14
54	Miltirone	Diterpenoids	12.98	C19H22O2	282.16	0.11
55	Puerarin	Flavonoids	4.89	C21H20O9	416.11	0.11
56	Cinchonine	Alkaloids	11.99	C19H22N2O	294.17	0.09
57	3-Ethoxy-4-hydroxybenzaldehyde	Phenols	5.72	C9H10O3	166.06	0.07
58	Lumichrome	Alkaloids	6.69	C12H10N4O2	242.08	0.07

, a total of 58 different compounds were identified. The highest percentage of these compounds in the CC 1 was p-phenol ethanolamine (18.62%), followed by D-2-aminobutyric acid (9.46%), sucrose (7.01%), turanose (7.01%), and lactulose (7.01%). Some compounds with lower concentrations were also identified from the extract (0.83–0.07%), including a galactose 1-phosphate, L-glutamic acid, and kojibiose (Table 3). Phenols and organic acids have good antioxidant and antibacterial activities [11], while alkaloids can inhibit the formation of and/or disperse bacterial biofilms [12]. For example, the indole of alkaloids is a versatile heterocyclic compound with various pharmacological activities such as anticancer, anticonvulsant, antimicrobial, antitubercular, antimalarial, antiviral, antidiabetic and other miscellaneous activities. Indole also regulates various aspects of bacterial physiology, including spore formation, plasmid stability, resistance to drugs, biofilm formation and virulence [13]. Saccharides have been used to preserve foods for a long history by changing cell osmolarity to inhibit harmful bacterial growth. Kojibiose is a natural disaccharide comprising two glucose moieties linked by an α-1,2 glycosidic bond. It has been reported that Kojibiose can inhibit bacterial proliferation and have anti-inflammatory and antiviral activities [14,15]. In contrast, the certain content of the identified amino acids may not contribute to the observed antibacterial activity by the CC 1 from R. madaio Makino.

2.6. Differential Transcriptomes Mediated by the CC 1 from R. madaio Makino

To gain insights into the genome-wide gene expression changes mediated by the CC 1 from R. madaio Makino, we determined transcriptomes of the four bacterial strains treated for 6 h using Illumina RNA sequencing technology. A complete list of DEGs in the four strains was available in the NCBI SRA database (https://submit.ncbi.nlm.nih.gov/subs/bioproject/, accessed on 17 October 2021) under the accession number PRJNA767551. To validate the transcriptome data, we examined 32 representative DEGs (Table S2) by RT-qPCR analysis, and the resulting data were correlated with those yielded from the transcriptome analysis (Table S2).

2.6.1. The Major Altered Metabolic Pathways in V. alginolyticus ATCC17749

Approximately 6.73% (316/4698) of V. alginolyticus ATCC17749 genes were expressed differently in the experimental group compared with the control group. Among these, 238 genes showed higher transcription levels (FC ≥ 2.0), and 78 genes were down-regulated (FC ≤ 0.5). Based on the comparative transcriptomic analyses, 11 significantly changed metabolic pathways were identified, including valine, leucine and isoleucine degradation; nitrogen, histidine, tryptophan, glyoxylate and dicarboxylate metabolisms; quorum sensing (QS); lysine degradation; fatty acid degradation; amino sugar and nucleotide sugar metabolism; ABC transporters; and mitogen-activated protein kinase (MAPK) signal pathway (Figure 7).

Remarkably, approximately 60 DEGs involved in 10 changed metabolic pathways were significantly up-regulated in V. alginolyticus ATCC17749 (2.002- to 87.807-fold) (p < 0.05) (

Table 4. Major altered metabolic pathways in V. alginolyticus ATCC17749 treated by the CC1 from R. madaio Makino.

Metabolic Pathway	Gene ID	Fold Change	Gene Description
Valine, leucine and isoleucine degradation	N646_4585	2.117	Acetoacetyl-coenzyme A synthetase
	N646_4506	2.127	Putative 3-hydroxyisobutyrate dehydrogenase
	N646_4019	2.293	Acetoacetyl-coenzyme A synthetase
	N646_4049	2.793	Putative acyl-CoA carboxyltransferase beta chain
	N646_4047	3.123	Putative acyl-CoA carboxylase alpha chain
	N646_4057	3.302	3-hydroxyisobutyrate dehydrogenase
	N646_4048	4.128	Putative enoyl-CoA hydratase/isomerase
	N646_4053	4.602	Putative aldehyde dehydrogenase
	N646_4050	4.619	Putative acyl-CoA dehydrogenase
Nitrogen metabolism	N646_3727	2.193	Putative oxidoreductase protein
	N646_4426	2.656	Hypothetical protein
	N646_3915	5.506	Periplasmic nitrate reductase
	N646_4365	5.657	Hypothetical protein
	N646_3914	6.137	Periplasmic nitrate reductase%2C cytochrome c-type protein
	N646_4364	11.868	Nitrite reductase [NAD(P)H]%2C small subunit
	N646_1010	29.988	Nitrite reductase periplasmic cytochrome c552
	N646_0236	87.807	Hydroxylamine reductase
Quorum sensing	N646_0372	2.104	ABC-type spermidine/putrescine transport system%2C permease component II
	N646_2230	2.108	Peptide ABC transporter%2C permease protein
	N646_4026	2.258	Putative ABC transporter%2C membrane spanning protein
	N646_1576	2.315	Peptide ABC transporter%2C periplasmic peptide-binding protein
	N646_0379	2.493	Oligopeptide ABC transporter%2C permease protein
	N646_2228	2.531	Peptide ABC transporter%2C periplasmic peptide-binding protein
	N646_4027	2.666	Putative high-affinity branched-chain amino acid transport permease protein
	N646_0377	2.688	Oligopeptide ABC transporter%2C ATP-binding protein
	N646_1580	2.821	Peptide ABC transporter%2C ATP-binding protein
	N646_0378	2.836	Oligopeptide ABC transporter%2C ATP-binding protein
	N646_4024	2.850	Putative high-affinity branched-chain amino acid transport ATP-binding protein
	N646_0380	2.854	Oligopeptide ABC transporter%2C permease protein
	N646_4025	2.951	Putative long-chain-fatty-acid-CoA ligase
	N646_0381	3.075	Oligopeptide ABC transporter%2C periplasmic oligopeptide-binding protein
	N646_0370	3.909	Putative ATP-binding component of ABC transporter
	N646_4029	4.034	Putative high-affinity branched-chain amino acid transport ATP-binding protein
	N646_0371	4.049	Putative permease of ABC transporter
	N646_0367	4.112	Putative binding protein component of ABC transporter
Histidine metabolism	N646_0312	2.001	Formimidoylglutamase
	N646_0189	2.072	Imidazoleglycerol-phosphate dehydratase/histidinol-phosphatase
	N646_0190	2.090	Imidazole glycerol phosphate synthase subunit HisH
	N646_0313	3.141	Imidazolonepropionase
	N646_0311	3.168	Urocanate hydratase
	N646_0310	3.187	Histidine ammonia-lyase
Fatty acid degradation	N646_1753	0.344	Hypothetical protein
	N646_0066	2.033	Amino acid ABC transporter%2C permease protein
	N646_3145	2.064	Rubredoxin/rubredoxin reductase
	N646_2209	2.122	Acetyl-CoA C-acyltransferase FadA
	N646_3116	2.163	Maltose ABC transporter periplasmic protein
	N646_3117	2.319	Maltose/maltodextrin ABC transporter%2C ATP-binding protein
	N646_3389	2.793	Putative ferrichrome ABC transporter (permease)
	N646_1395	2.879	Acyl-CoA dehydrogenase
	N646_4429	3.400	Nitrate ABC transporter nitrate-binding protein
	N646_4028	5.585	Hypothetical protein
	N646_4427	6.398	Hypothetical protein
	N646_3568	14.448	Putative ABC transporter%2C ATP-binding protein
ABC transporters	N646_4485	2.173	Arginine ABC transporter%2C permease protein
	N646_4527	3.899	Putative inner-membrane permease
	N646_4487	4.958	Arginine ABC transporter%2C periplasmic arginine-binding protein
	N646_4488	5.676	Arginine ABC transporter%2C ATP-binding protein
	N646_4486	7.585	ABC-type arginine transport system%2C permease component
Tryptophan metabolism	N646_2210	2.123	Fatty oxidation complex%2C alpha subunit
	N646_3629	2.155	Tryptophanase
	N646_4052	5.154	Putative acyl-CoA thiolase
Lysine degradation	N646_3623	2.972	Transcriptional regulator
	N646_1979	3.332	Arginine/lysine/ornithine decarboxylase
MAPK signaling pathway	N646_2909	0.123	Cation transport ATPase%2C E1-E2 family protein
	N646_3134	0.369	Catalase
Glyoxylate and dicarboxylate metabolism	N646_1965	2.122	Acetyl-coenzyme A synthetase
	N646_2741	2.135	Isocitrate lyase
	N646_2740	2.88	Malate synthase
	N646_3637	3.006	Malate synthase
Amino sugar and nucleotide sugar metabolism	N646_4226	0.400	Glucose-1-phosphate adenylyltransferase
	N646_1583	2.322	Beta-N-hexosaminidase
	N646_3834	2.610	Hypothetical protein
	N646_1582	3.440	Ptative N-acetylglucosamine kinase
	N646_4346	4.386	Ptative mannose-6-phosphate isomerase
	N646_3455	5.366	Hpothetical protein

). For example, in the valine, leucine and isoleucine degradation, expression of nine DEGs were significantly up-regulated at the transcription level (2.117- to 4.619-fold) (p < 0.05); six DEGs encoding key enzymes in the histidine metabolism were also significantly up-regulated (2.001- to 3.187-fold) (p < 0.05); similarly, in the tryptophan metabolism, expression of three DEGs were significantly enhanced (2.123- to 5.154-fold) (p < 0.05); additionally, in the lysine degradation, expression of a transcriptional regulator (N646_3623) and an arginine/lysine/ornithine decarboxylase (N646_1979) were significantly up-regulated (2.972- to 3.332-fold) (p < 0.05). These four pathways are related to amino acid degradation metabolisms.

Meanwhile, eight DEGs in the nitrogen metabolism were also significantly up-regulated (2.193- to 87.807-fold) (p < 0.05), in which, specifically, one DEG encoding a hydroxylamine reductase (N646_0236) was greatly enhanced to express (87.807-fold).

ABC transporters are ATP-dependent efflux transporters to transport lipids, metabolites, exogenous substances and other small molecules out of the cell [16]. They are also the main type of transporters associated with bacterial multidrug resistance [17]. In this study, comparative transcriptome analysis revealed 23 DEGs in ABC transporters and QS that were significantly up-regulated in V. alginolyticus ATCC17749 (2.104- to 7.585-fold) (p < 0.05) (Table 4). ABC transporter can also catalyze the turnover of lipids in the lipid bilayer that play a critical role in the occurrence and functional maintenance of the cell membrane [18]. In this study, the up-regulated expression of these DEGs suggested that the treatment with the CC 1 from R. madaio Makino enhanced the bacterial pumping of exogenous and endogenous metabolites to eliminate cell damage.

In contrast, all DEGs in the MAPK signaling pathway were significantly inhibited (0.123- to 0.369-fold) (p < 0.05) (Table 4), which likely led to a highly toxic reactive oxygen species (ROS) accumulation and cell damage.

2.6.2. The Major Altered Metabolic Pathways in V. parahaemolyticus ATCC17802

Approximately 19.62% (917/4,674) of V. parahaemolyticus ATCC17802 genes were expressed differently in the experimental group compared with the control group. Among these, 128 genes showed higher transcription levels (FC ≥ 2.0), and 789 genes were down-regulated (FC ≤ 0.5). Comparative transcriptome analyses revealed 20 significantly changed metabolic pathways, including methane, nitrogen, glycerolipid, propanoate, sulfur, starch and sucrose, taurine and hypotaurine, phosphonate and phosphinate, and biotin metabolisms; glucagon, and hypoxia inducible factor-1 (HIF-1) signaling pathway; benzoate and ethylbenzene degradation; glycolysis/gluconeogenesis; flagellar assembly; apoptosis; bacterial chemotaxis; cationic antimicrobial peptide (CAMP) resistance; necroptosis, and RNA transport (Figure 8).

Notably, approximately 77 DEGs involved in 12 changed metabolic pathways were significantly down-regulated (0.05- to 0.491-fold) (p < 0.05) (

Table 5. Major altered metabolic pathways in V. parahaemolyticus ATCC17802 treated by the CC1 from R. madaio Makino.

Metabolic Pathway	Gene ID	Fold Change	Gene Description
Methane metabolism	VP_RS15865	0.091	NapC/NirT family cytochrome c
	VP_RS15860	0.067	Trimethylamine-N-oxide reductase 2
	VP_RS07325	0.224	Acetate kinase
	VP_RS13930	0.206	2%2C3-bisphosphoglycerate-independent phosphoglycerate mutase
	VP_RS18135	0.104	Formate dehydrogenase subunit gamma
	VP_RS12615	0.320	Phosphate acetyltransferase
	VP_RS07335	0.227	Trimethylamine-N-oxide reductase TorA
	VP_RS15585	0.304	S-(hydroxymethyl)glutathione dehydrogenase/class III alcohol dehydrogenase
	VP_RS05645	0.302	Phosphoglycerate dehydrogenase
	VP_RS07330	0.338	Pentaheme c-type cytochrome TorC
	VP_RS05030	0.381	Molecular chaperone TorD
	VP_RS15580	0.412	S-formylglutathione hydrolase
	VP_RS05640	0.342	6-phosphofructokinase
Glycolysis/Gluconeogenesis	VP_RS23260	0.087	6-phospho-beta-glucosidase
	VP_RS12915	0.272	6-phospho-beta-glucosidase
	VP_RS12215	0.310	Pyruvate dehydrogenase (acetyl-transferring)
	VP_RS12210	0.331	Pyruvate dehydrogenase complex dihydrolipoyllysine-residue acetyltransferase
	VP_RS13410	0.406	Glucose-6-phosphate isomerase
	VP_RS10485	0.416	D-hexose-6-phosphate mutarotase
	VP_RS09910	0.433	Pyruvate kinase
	VP_RS18295	2.558	2-oxo acid dehydrogenase subunit E2
Flagellar assembly	VP_RS22540	0.055	Flagellar biosynthesis protein FliQ
	VP_RS16540	0.064	Flagellar basal body rod protein FlgB
	VP_RS16565	0.086	Flagellar basal-body rod protein FlgG
	VP_RS22520	0.091	OmpA family protein
	VP_RS16550	0.129	Flagellar hook assembly protein FlgD
	VP_RS22605	0.193	Flagellar motor stator protein MotA
	VP_RS22545	0.210	Flagellar biosynthetic protein FliR
	VP_RS22575	0.225	Flagellar filament capping protein FliD
	VP_RS22535	0.237	Flagellar type III secretion system pore protein FliP
	VP_RS22490	0.265	Flagellar protein export ATPase FliI
	VP_RS16555	0.272	Flagellar basal body protein FlgE
	VP_RS22590	0.281	Flagellar hook-length control protein FliK
	VP_RS16575	0.327	Flagellar basal body P-ring protein FlgI
	VP_RS10920	0.363	Flagellar M-ring protein FliF
	VP_RS22495	0.366	Flagellar assembly protein H
	VP_RS10900	0.386	Flagella biosynthesis chaperone FliJ
	VP_RS16585	0.396	Flagellar hook-associated protein FlgK
	VP_RS16590	0.412	Flagellar hook-associated protein FlgL
	VP_RS13775	0.416	Sel1 repeat family protein
	VP_RS10835	0.429	RNA polymerase sigma factor FliA
	VP_RS10895	0.452	Flagellar hook-length control protein FliK
	VP_RS03835	0.462	Flagellar hook protein FlgE
	VP_RS03855	0.490	Flagellar basal body P-ring protein FlgI
Glucagon signaling pathway	VP_RS01720	0.369	Pyruvate kinase PykF
	VP_RS18300	3.294	Alpha-ketoacid dehydrogenase subunit beta
	VP_RS22915	5.913	Glycogen/starch/alpha-glucan phosphorylase
HIF-1 signaling pathway	VP_RS10480	0.168	Type I glyceraldehyde-3-phosphate dehydrogenase
	VP_RS14700	0.301	ArsJ-associated glyceraldehyde-3-phosphate dehydrogenase
	VP_RS12650	0.479	Phosphoglycerate kinase
Nitrogen metabolism	VP_RS20240	0.126	Nitrite reductase large subunit NirB
	VP_RS02310	0.158	Glutamate synthase subunit beta
	VP_RS20280	0.226	Nitrate reductase
	VP_RS02315	0.236	Glutamate synthase large subunit
	VP_RS20255	0.270	ABC transporter substrate-binding protein
	VP_RS12190	0.418	Carbonate dehydratase
	VP_RS20915	2.061	Nitrate reductase cytochrome c-type subunit
	VP_RS20910	2.197	Periplasmic nitrate reductase subunit alpha
	VP_RS05780	14.974	Hydroxylamine reductase
	VP_RS09370	19.809	Ammonia-forming nitrite reductase cytochrome c552 subunit
Glycerolipid metabolism	VP_RS01760	0.040	Dihydroxyacetone kinase ADP-binding subunit DhaL
	VP_RS01755	0.067	Dihydroxyacetone kinase subunit DhaK
	VP_RS21295	0.193	Diacylglycerol kinase
	VP_RS11580	0.239	Glycerol kinase GlpK
	VP_RS15810	0.431	Glycerate kinase
	VP_RS05740	2.015	Triacylglycerol lipase
Apoptosis	VP_RS23210	0.086	Alkyl hydroperoxide reductase subunit C
	VP_RS20650	0.282	C-type cytochrome
	VP_RS02795	0.415	Peroxiredoxin C
Bacterial chemotaxis	VP_RS22610	0.101	OmpA family protein
	VP_RS22160	0.243	Methyl-accepting chemotaxis protein
	VP_RS03815	0.255	Protein-glutamate O-methyltransferase
	VP_RS17585	0.267	Methyl-accepting chemotaxis protein
	VP_RS22500	0.294	Flagellar motor switch protein FliG
	VP_RS22100	0.337	Methyl-accepting chemotaxis protein
	VP_RS10915	0.356	Flagellar motor switch protein FliG
	VP_RS05760	0.374	Methyl-accepting chemotaxis protein
	VP_RS10820	0.386	Chemotaxis protein CheA
	VP_RS10825	0.389	Protein phosphatase CheZ
	VP_RS10880	0.411	Flagellar motor switch protein FliN
	VP_RS03810	0.415	Chemotaxis protein CheV
	VP_RS03305	0.433	Flagellar motor protein PomA
	VP_RS10815	0.471	Chemotaxis response regulator protein-glutamate methylesterase
	VP_RS10830	0.473	Chemotaxis response regulator CheY
	VP_RS05310	0.486	Methyl-accepting chemotaxis protein
	VP_RS10800	0.491	Chemotaxis protein CheW
Propanoate metabolism	VP_RS01750	0.051	Glycerol dehydrogenase
	VP_RS04855	0.072	Formate C-acetyltransferase
	VP_RS18985	0.119	Acetyl-CoA carboxylase%2C carboxyltransferase subunit beta
	VP_RS16405	0.240	Aspartate aminotransferase family protein
	VP_RS07930	2.084	2-methylcitrate synthase
	VP_RS07925	2.094	Fe/S-dependent 2-methylisocitrate dehydratase AcnD
	VP_RS20545	2.450	CoA-acylating methylmalonate-semialdehyde dehydrogenase
Cationic antimicrobial peptide (CAMP) resistance	VP_RS00200	0.120	Multidrug efflux RND transporter permease subunit VmeD
	VP_RS00205	0.159	Multidrug efflux RND transporter periplasmic adaptor subunit VmeC
	VP_RS21260	0.344	Thiol: disuLfide interchange protein DsbA/DsbL
	VP_RS05670	0.456	ATP-binding cassette domain-containing protein
	VP_RS21300	0.489	Phosphoethanolamine-lipid A transferase
	VP_RS05315	2.030	Multidrug efflux RND transporter periplasmic adaptor subunit VmeA
	VP_RS20865	2.560	Multidrug efflux RND transporter periplasmic adaptor subunit VmeY
	VP_RS14065	4.124	Envelope stress sensor histidine kinase CpxA
	VP_RS14060	4.705	Response regulator
Sulfur metabolism	VP_RS07020	0.050	Dimethyl sulfoxide reductase subunit A
	VP_RS07030	0.052	Dimethyl sulfoxide reductase anchor subunit
	VP_RS07025	0.058	Dimethyl sulfoxide reductase subunit B
	VP_RS05930	0.110	Cytochrome subunit of suLfide dehydrogenase
	VP_RS03905	0.337	Cysteine synthase A
	VP_RS13370	0.417	Assimilatory suLfite reductase (NADPH) hemoprotein subunit
	VP_RS13375	0.440	Assimilatory sulfite reductase (NADPH) flavoprotein subunit
	VP_RS01435	0.442	Sulfate adenylyltransferase subunit CysN
	VP_RS01430	0.450	Sulfate adenylyltransferase subunit CysD
Starch and sucrose metabolism	VP_RS12920	0.206	PTS lactose/cellobiose transporter subunit IIA
	VP_RS19165	0.393	Glucose-1-phosphate adenylyltransferase
	VP_RS03410	0.474	Alpha%2Calpha-phosphotrehalase
	VP_RS23025	0.498	Glycogen debranching protein GlgX
	VP_RS03405	0.499	PTS trehalose transporter subunit IIBC
	VP_RS22910	4.693	4-alpha-glucanotransferase
Necroptosis	VP_RS04005	0.261	Molecular chaperone HtpG
	VP_RS00595	0.363	Glutamate-ammonia ligase
Taurine and hypotaurine metabolism	VP_RS10125	0.167	Acetate kinase
	VP_RS05370	0.219	Alanine dehydrogenase
	VP_RS10130	0.244	Phosphate acetyltransferase
Benzoate degradation	VP_RS20635	0.295	Carboxymuconolactone decarboxylase family protein
	VP_RS20550	2.679	Thiolase family protein
	VP_RS00135	2.713	Fatty acid oxidation complex subunit alpha FadB
RNA transport	VP_RS19430	0.440	Stress response translation initiation inhibitor YciH
	VP_RS01980	0.485	Multifunctional CCA addition/repair protein
Phosphonate and phosphinate metabolism	VP_RS16410	0.206	2-aminoethylphosphonate--pyruvate Transaminase
	VP_RS16400	0.491	Phosphonoacetaldehyde hydrolase
Ethylbenzene degradation	VP_RS10720	2.111	Acetyl-CoA C-acyltransferase FadI
	VP_RS00130	2.465	Acetyl-CoA C-acyltransferase FadA
Biotin metabolism	VP_RS05435	0.057	Dethiobiotin synthase
	VP_RS21415	0.265	Beta-ketoacyl-ACP reductase
	VP_RS05415	0.376	Adenosylmethionine-8-amino-7-oxononanoate transaminase
	VP_RS05425	0.454	8-amino-7-oxononanoate synthase
	VP_RS05420	0.479	Biotin synthase BioB
	VP_RS05430	0.492	Malonyl-ACP O-methyltransferase BioC
	VP_RS20520	2.061	SDR family oxidoreductase

). For example, in the glycolysis/gluconeogenesis, except for an up-regulated 2-oxo acid dehydrogenase subunit E2 (VP_RS18295), the other seven DEGs were significantly down-regulation (0.087- to 0.433-fold) (p < 0.05); in the propanoate metabolic pathway, express of four DEGs were significantly depressed (0.051- to 0.240-fold) (p < 0.05); in the starch and sucrose metabolisms, except for a 4-alpha-glucono transfer (VP_RS22910), the other five DEGs were significantly down-regulated (0.206- to 0.499-fold) (p < 0.05). These three metabolic pathways were related to carbohydrate metabolisms. Their overall down-regulation trend indicated inactive carbon source transportation and/or utilization, which likely resulted in insufficient energy supply.

Approximately 44 DEGs involved in six energy metabolism pathways in V. parahaemolyticus ATCC17802 were also significantly inhibited (p < 0.05). For example, the DEG encoding a pyruvate dehydrogenase complex dihydrolipoyllysine-residue acetyltransferase (VP_RS12210) was significantly down-regulated (0.331-fold), which connects glycolysis with tricarboxylic acid cycle (TCA) and plays a key role in glucose metabolism [19]. The down-regulation of this enzyme led to a decrease in ATP production and insufficient energy supply [20], which consequently affected bacterial growth and mobility.

The bacterial flagellum is a complex mobility machine with a diversity of roles in pathogenesis, including attachment, colonization, invasion, maintenance and post-infection dispersal in the host [21,22]. In this study, expression of 23 DEGs involved in three substructures of the flagellum, including the filament, hook and basal body [23], were significantly down-regulated at the transcriptional level in V. parahaemolyticus ATCC17802 (0.055- to 0.49-fold) (p < 0.05), which indicated the depressed flagellum assembly that led to inactive motility of V. parahaemolyticus ATCC17802. The 17 down-regulated DEGs in the bacterial chemotaxis [24] (0.101- to 0.491-fold) (p < 0.05) provided indirect evidence for this result.

Interestingly, 23 DEGs encoding type III secretory system (T3SS) components were also significantly down-regulated (0.055- to 0.490 -fold) (p < 0.05). T3SS enables pathogenic bacteria to directly inject effector proteins into host cells, facilitating bacterial colonization in the host [25]. This result suggested that the cytotoxicity of V. parahaemolyticus ATCC17802 was significantly reduced after being treated with the CC 1 from R. madaio Makino.

Additionally, in the cationic antimicrobial peptide (CAMP) resistance system, five DEGs were significantly inhibited (0.120- to 0.489-fold), including a multidrug efflux RND transporter permease subunit VmeD (VP_RS00200), a thiol: disulfide interchange protein DsbA/DsbL (VP_RS21260), an ATP-binding cassette domain-containing protein (VP_RS05670), a multidrug efflux RND transporter periplasmic adaptor subunit VmeC (VP_RS00205), and a phosphoethanolamine-lipid A transferase (VP_RS21300) (Table 5). These results indicated poor efficiency of multidrug efflux transport in V. parahaemolyticus ATCC17802 after being treated by the CC 1.

In contrast, five DEGs were significantly up-regulated (2.030- to 4.705-fold), e.g., a response regulator (VP_RS14060) and an envelope stress sensor histidine kinase CpxA (VP_RS14065) (Table 5).

2.6.3. The Major Altered Metabolic Pathways in V. parahaemolyticus B4-10

Approximately 16.75% (783/4674) of V. parahaemolyticus B4-10 genes were expressed differently in the experimental group when compared with the control group. Among these genes, 204 showed higher transcription levels (FC ≥ 2.0), and 579 genes were down-regulated (FC ≤ 0.5). Based on the comparative transcriptome analysis, five significantly changed metabolic pathways were identified, including styrene degradation, nitrogen metabolism, QS, folate biosynthesis, and histidine metabolism (Figure 9).

Similar to V. alginolyticus ATCC17749, the expression of 10 DEGs in the nitrogen metabolism were significantly up-regulated (2.129- to 107.754-fold) (p < 0.05) (

Table 6. Major altered metabolic pathways in V. parahaemolyticus B4-10 treated by the CC1 from R. madaio Makino.

Metabolic Pathway	Gene ID	Fold Change	Gene Description
Styrene degradation	VP_RS06550	0.394	Homogentisate 1%2C2-dioxygenase
	VP_RS06560	0.408	Maleylacetoacetate isomerase
	VP_RS06555	0.471	Fumarylacetoacetate hydrolase family protein
Nitrogen metabolism	VP_RS20240	2.129	Nitrite reductase large subunit NirB
	VP_RS19890	2.518	Nitrite reductase small subunit NirD
	VP_RS20235	2.823	Nitrite reductase small subunit NirD
	VP_RS20280	3.753	Nitrate reductase
	VP_RS20915	3.759	Nitrate reductase cytochrome c-type subunit
	VP_RS19895	3.988	Nitrite reductase large subunit NirB
	VP_RS20910	4.186	Periplasmic nitrate reductase subunit alpha
	VP_RS20250	10.250	ABC transporter permease
	VP_RS09370	29.586	Ammonia-forming nitrite reductase cytochrome c552 subunit
	VP_RS05780	107.754	Hydroxylamine reductase
Quorum sensing	VP_RS06530	0.241	Oligopeptide ABC transporter permease OppB
	VP_RS06520	0.256	ATP-binding cassette domain-containing protein
	VP_RS06525	0.265	ABC transporter permease subunit
	VP_RS06515	0.297	ATP-binding cassette domain-containing protein
	VP_RS06485	0.310	ABC transporter ATP-binding protein
	VP_RS06495	0.346	ABC transporter permease
	VP_RS06535	0.362	Peptide ABC transporter substrate-binding protein
	VP_RS20670	0.368	ABC transporter ATP-binding protein
	VP_RS06490	0.370	ABC transporter permease
	VP_RS20680	0.381	Branched-chain amino acid ABC transporter permease
	VP_RS06470	0.388	Polyamine ABC transporter substrate-binding protein
	VP_RS21025	0.416	Autoinducer 2-binding periplasmic protein LuxP
	VP_RS20695	0.455	ABC transporter ATP-binding protein
	VP_RS01695	0.468	Long-chain fatty acid--CoA ligase
	VP_RS20675	0.475	ABC transporter substrate-binding protein
	VP_RS00850	0.495	ABC transporter ATP-binding protein
	VP_RS12050	2.098	ABC transporter ATP-binding protein
	VP_RS15305	2.117	GTP cyclohydrolase II
	VP_RS22315	2.159	ABC transporter ATP-binding protein
	VP_RS12040	2.232	ABC transporter permease
	VP_RS08360	2.551	Two-component sensor histidine kinase
	VP_RS22015	2.976	Response regulator transcription factor
	VP_RS08355	3.014	Response regulator
	VP_RS16930	3.141	Permease
Folate biosynthesis	VP_RS17975	0.476	Phenylalanine 4-monooxygenase
	VP_RS09130	0.494	Aminodeoxychorismate synthase component I
	VP_RS03365	0.491	NADPH-dependent 7-cyano-7-deazaguanine reductase QueF
	VP_RS07885	0.497	7-cyano-7-deazaguanine synthase QueC
	VP_RS09170	0.389	6-carboxytetrahydropterin synthase QueD
	VP_RS13730	0.433	Aminodeoxychorismate/anthranilate synthase component II
	VP_RS07890	0.484	7-carboxy-7-deazaguanine synthase QueE
	VP_RS17980	0.432	4a-hydroxytetrahydrobiopterin dehydratase
	VP_RS01970	0.431	2-amino-4-hydroxy-6-hydroxymethyldihydropteridine diphosphokinase
Histidine metabolism	VP_RS06185	10.231	Urocanate hydratase
	VP_RS06180	6.284	Histidine ammonia-lyase
	VP_RS06195	6.998	Imidazolonepropionase
	VP_RS06190	5.106	Formimidoylglutamase
	VP_RS05565	0.496	Bifunctional phosphoribosyl-AMP cyclohydrolase/phosphoribosyl-ATP diphosphatase HisIE

). Notably, one DEG encoding a hydroxylamine reductase (VP_RS05780) was greatly up-regulated (107.754-fold). This enzyme can reduce hydroxylamine analogs such as methylhydroxylamine and hydroxyquinone as a scavenger of potentially toxic by-products of nitrate metabolism [26]. Moreover, in the histidine metabolism, four DEGs were highly up-regulated (5.106- to 10.231-fold) (Table 6). The enhanced nitrogen metabolism may have supplemented the energy supply in V. parahaemolyticus B4-10 after being treated by the CC 1.

2.6.4. The Major Altered Metabolic Pathways in B. cereus A1-1

Approximately 12.57% (720/5730) of B. cereus A1-1 genes were expressed differently in the experimental group. Among these genes, 178 showed higher transcription levels (FC ≥ 2.0), and 542 genes were down-regulated (FC ≤ 0.5). The comparative transcriptome analysis revealed 17 significantly changed metabolic pathways, including flagellar assembly; bacterial chemotaxis; two-component system (TCS); thiamine and nitrogen metabolisms; ABC transporters; arginine biosynthesis; fatty acid degradation; alanine, aspartate and glutamate metabolism; riboflavin metabolism; HIF-1 signaling pathway; glycolysis/gluconeogenesis; butanoate, pyrimidine, and propanoate metabolisms; benzoate degradation; and inositol phosphate metabolism (Figure 10).

Similar to the other bacterial strains tested, expression of 12 DEGs involved in the nitrogen metabolism and riboflavin metabolism were significantly up-regulated in B. cereus A1-1 (3.325- to 150.780-fold) (p < 0.05) (

Table 7. Major altered metabolic pathways in B. cereus A1-1 treated by the CC1 from R. madaio Makino.

Metabolic Pathway	Gene ID	Fold Change	Gene Description
Flagellar assembly	BCN_RS08555	0.038	Flagellar assembly protein FliH
	BCN_RS08605	0.045	Flagellin
	BCN_RS08610	0.072	Flagellin
	BCN_RS08640	0.108	Flagellar type III secretion system pore protein FliP
	BCN_RS08550	0.113	Flagellar motor switch protein FliG
	BCN_RS22265	0.115	Flagellar motor stator protein MotA
	BCN_RS22260	0.143	Flagellar motor protein MotB
	BCN_RS08545	0.154	Flagellar M-ring protein FliF
	BCN_RS08470	0.158	Flagellar motor switch protein
	BCN_RS08560	0.158	Flagellar protein export ATPase FliI
	BCN_RS08535	0.173	Flagellar basal body rod protein FlgC
	BCN_RS08670	0.188	Flagellar basal-body rod protein FlgG
	BCN_RS08520	0.196	Flagellar protein FliS
	BCN_RS08530	0.197	Flagellar basal body rod protein FlgB
	BCN_RS08625	0.200	Flagellar motor switch protein FliM
	BCN_RS08660	0.230	Flagellar biosynthesis protein FlhA
	BCN_RS08510	0.241	Flagellar hook-associated protein 3
	BCN_RS08655	0.392	Flagellar type III secretion system protein FlhB
	BCN_RS08650	0.438	Flagellar type III secretion system protein FliR
Bacterial chemotaxis	BCN_RS10010	0.063	Methyl-accepting chemotaxis protein
	BCN_RS03675	0.088	Methyl-accepting chemotaxis protein
	BCN_RS02280	0.185	Methyl-accepting chemotaxis protein
	BCN_RS08460	0.186	Response regulator
	BCN_RS08625	0.200	Flagellar motor switch protein FliM
	BCN_RS25160	0.265	DUF4077 domain-containing protein
	BCN_RS24975	0.321	Methyl-accepting chemotaxis protein
	BCN_RS08595	0.357	Chemotaxis protein
	BCN_RS08455	0.474	OmpA family protein
Two-component system	BCN_RS27005	0.136	Respiratory nitrate reductase subunit gamma
	BCN_RS26190	0.152	Cytochrome d ubiquinol oxidase subunit II
	BCN_RS23710	0.219	Potassium-transporting ATPase subunit KdpA
	BCN_RS27000	0.231	Acetyl-CoA C-acyltransferase
	BCN_RS23715	0.258	Methyl-accepting chemotaxis protein
	BCN_RS04080	0.385	Nitrate reductase molybdenum cofactor assembly chaperone
	BCN_RS15080	0.401	Response regulator
	BCN_RS04090	0.419	Methyl-accepting chemotaxis protein
	BCN_RS07505	2.006	Phosphate ABC transporter substrate-binding protein PstS
	BCN_RS26540	2.297	Cytochrome ubiquinol oxidase subunit I
	BCN_RS17290	2.348	Chemotaxis protein CheA
	BCN_RS02700	3.703	Antiholin-like murein hydrolase modulator LrgA
	BCN_RS10795	4.600	Acetyl-CoA C-acetyltransferase
	BCN_RS07495	5.804	Hypothetical protein
Thiamine metabolism	BCN_RS29465	0.031	TenA family transcriptional regulator
	BCN_RS02365	0.205	Thiamine phosphate synthase
	BCN_RS04005	0.224	Thiaminase II
	BCN_RS04040	0.274	Thiazole synthase
	BCN_RS04030	0.282	Glycine oxidase ThiO
	BCN_RS04050	0.304	Bifunctional hydroxymethylpyrimidine kinase/phosphomethylpyrimidine kinase
	BCN_RS04025	0.310	Thiazole tautomerase TenI
	BCN_RS25935	0.320	Phosphomethylpyrimidine synthase ThiC
	BCN_RS21485	0.342	Alkaline phosphatase
	BCN_RS12695	0.397	Thiaminase II
	BCN_RS02360	0.407	Hydroxyethylthiazole kinase
	BCN_RS10005	0.407	Ribosome small subunit-dependent GTPase A
	BCN_RS22955	0.433	Cysteine desulfurase
	BCN_RS02660	0.457	Acetylornithine deacetylase
ABC transporters	BCN_RS03130	0.051	Amino acid ABC transporter permease
	BCN_RS14125	0.051	Glycine betaine ABC transporter substrate-binding protein
	BCN_RS15895	0.056	Substrate-binding domain-containing protein
	BCN_RS06920	0.179	ABC transporter ATP-binding protein
	BCN_RS17880	0.205	Ribose ABC transporter ATP-binding protein RbsA
	BCN_RS01110	0.221	Amino acid ABC transporter ATP-binding protein
	BCN_RS06915	0.225	Peptide ABC transporter substrate-binding protein
	BCN_RS01100	0.258	Amino acid ABC transporter ATP-binding protein
	BCN_RS04010	0.263	Phosphate ABC transporter permease PstA
	BCN_RS08770	0.268	Peptide ABC transporter substrate-binding protein
	BCN_RS14120	0.268	BMP family protein
	BCN_RS20515	0.272	ABC transporter ATP-binding protein
	BCN_RS03855	0.278	Phosphonate ABC transporter ATP-binding protein
	BCN_RS01165	0.282	Molybdate ABC transporter permease subunit
	BCN_RS20525	0.283	ABC transporter ATP-binding protein
	BCN_RS21100	0.320	Metal ABC transporter substrate-binding protein
	BCN_RS04020	0.322	ABC transporter substrate-binding protein
	BCN_RS04015	0.326	Phosphate ABC transporter permease subunit PstC
	BCN_RS03845	0.330	ATP-binding cassette domain-containing protein
	BCN_RS03850	0.347	Phosphate ABC transporter ATP-binding protein
	BCN_RS24655	0.347	Transporter substrate-binding domain-containing protein
	BCN_RS01125	0.351	Putative 2-aminoethylphosphonate ABC transporter ATP-binding protein
	BCN_RS20520	0.355	Aliphatic sulfonate ABC transporter substrate-binding protein
	BCN_RS18335	0.379	Iron ABC transporter permease
	BCN_RS09350	0.405	Energy-coupling factor transporter transmembrane protein EcfT
	BCN_RS24665	0.405	Putative 2-aminoethylphosphonate ABC transporter substrate-binding protein
	BCN_RS01160	0.413	Molybdate ABC transporter substrate-binding protein
	BCN_RS04750	0.458	ABC transporter permease
	BCN_RS01870	0.465	ABC transporter permease
	BCN_RS17755	0.470	Methionine ABC transporter substrate-binding lipoprotein MetQ
	BCN_RS03600	0.487	Phosphate ABC transporter substrate-binding protein PstS
	BCN_RS09570	0.487	Peptide ABC transporter substrate-binding protein
	BCN_RS10085	0.487	Sugar ABC transporter permease
	BCN_RS09640	4.508	Thiol reductant ABC exporter subunit CydC
	BCN_RS26090	14.65	ABC transporter substrate-binding protein
	BCN_RS13495	20.285	MetQ/NlpA family ABC transporter substrate-binding protein
Arginine biosynthesis	BCN_RS20420	0.070	N-acetyl-gamma-glutamyl-phosphate reductase
	BCN_RS20400	0.117	Ornithine carbamoyltransferase
	BCN_RS20410	0.159	Acetylglutamate kinase
	BCN_RS20405	0.171	Acetylornithine transaminase
	BCN_RS20415	0.271	Bifunctional glutamate N-acetyltransferase/amino-acid acetyltransferase ArgJ
	BCN_RS00945	0.281	Arginase
	BCN_RS22860	0.292	Argininosuccinate lyase
	BCN_RS22865	0.486	Argininosuccinate synthase
Nitrogen metabolism	BCN_RS07150	0.365	Nitronate monooxygenase
	BCN_RS10835	5.001	Nitrate transporter NarK
	BCN_RS10790	6.281	Nitrate reductase subunit beta
	BCN_RS10800	7.880	Respiratory nitrate reductase subunit gamma
	BCN_RS10785	8.675	Nitrate reductase subunit alpha
	BCN_RS10870	8.912	Nitrite reductase small subunit NirD
	BCN_RS10875	15.156	NADPH-nitrite reductase large subunit
	BCN_RS16540	150.780	Hydroxylamine reductase
Riboflavin metabolism	BCN_RS20310	3.325	Bifunctional diaminohydroxyphosphoribosylaminopyrimidine deaminase/5-Amino-6-(5-phosphoribosylamino) uracil reductase RibD
	BCN_RS20320	4.247	Bifunctional 3%2C4-dihydroxy-2-butanone 4-phosphate synthase/GTP Cyclohydrolase II
	BCN_RS20325	4.361	6%2C7-dimethyl-8-ribityllumazine synthase
	BCN_RS20315	4.769	Riboflavin synthase subunit alpha
Pyrimidine metabolism	BCN_RS15125	0.304	5’-nucleotidase C-terminal domain-containing protein
	BCN_RS24625	0.355	Bifunctional metallophosphatase/5’-nucleotidase
	BCN_RS18815	0.381	Carbamoyl-phosphate synthase large subunit
	BCN_RS18820	0.406	Carbamoyl phosphate synthase small subunit
	BCN_RS18795	0.419	Orotate phosphoribosyltransferase
	BCN_RS18805	0.430	Dihydroorotate oxidase B catalytic subunit
	BCN_RS18800	0.438	Orotidine-5’-phosphate decarboxylase
	BCN_RS18810	0.441	Dihydroorotate oxidase B electron transfer subunit
	BCN_RS20265	0.445	5’-nucleotidase C-terminal domain-containing protein
	BCN_RS18825	0.449	Dihydroorotase
	BCN_RS07895	0.462	Nucleoside-diphosphate kinase
	BCN_RS09440	0.473	Pyrimidine-nucleoside phosphorylase
HIF-1 signaling pathway	BCN_RS24725	0.191	L-lactate dehydrogenase
	BCN_RS25405	2.598	Phosphoglycerate kinase
	BCN_RS25410	2.736	Type I glyceraldehyde-3-phosphate dehydrogenase
	BCN_RS25390	3.143	phosphopyruvate hydratase
	BCN_RS24095	5.531	L-lactate dehydrogenase
Fatty acid degradation	BCN_RS17445	0.340	Acetyl-CoA C-acetyltransferase
	BCN_RS17450	0.456	Acyl-CoA synthetase
Alanine, aspartate and glutamate metabolism	BCN_RS08845	0.353	Glutaminase A
	BCN_RS08855	0.361	Hypothetical protein
	BCN_RS19905	0.420	Carbon-nitrogen family hydrolase
	BCN_RS15030	0.486	Asparaginase
	BCN_RS03305	0.498	Aspartate ammonia-lyase
	BCN_RS00970	2.986	Glutamine--fructose-6-phosphate transaminase (isomerizing)
	BCN_RS03230	7.200	Alanine dehydrogenase
Benzoate degradation	BCN_RS26535	2.191	3-hydroxybutyryl-CoA dehydrogenase
	BCN_RS24780	2.199	Acetyl-CoA C-acetyltransferase
	BCN_RS24785	2.285	3-hydroxyacyl-CoA dehydrogenase/enoyl-CoA hydratase family protein
Glycolysis/Gluconeogenesis	BCN_RS08815	0.225	Histidine phosphatase family protein
	BCN_RS21600	0.299	Bifunctional acetaldehyde-CoA/alcohol dehydrogenase
	BCN_RS11285	0.411	Alcohol dehydrogenase AdhP
	BCN_RS28275	0.413	S-(hydroxymethyl)glutathione dehydrogenase/class III alcohol dehydrogenase
	BCN_RS22940	0.489	Acyl-CoA ligase
	BCN_RS26420	2.666	PTS glucose transporter subunit IIA
	BCN_RS25395	2.901	2%2C3-bisphosphoglycerate-independent phosphoglycerate mutase
	BCN_RS25815	5.561	6-phospho-beta-glucosidase
Inositol phosphate metabolism	BCN_RS18155	0.186	Phosphatidylinositol diacylglycerol-lyase
	BCN_RS03640	0.245	Phospholipase C
	BCN_RS25400	2.616	Triose-phosphate isomerase
Butanoate metabolism	BCN_RS02750	0.158	Formate C-acetyltransferase
	BCN_RS07305	0.199	Acetolactate synthase large subunit
	BCN_RS11410	0.359	Acetate CoA-transferase subunit alpha
	BCN_RS11415	0.382	CoA transferase subunit B
	BCN_RS04800	2.474	Alpha-acetolactate decarboxylase
Propanoate metabolism	BCN_RS18555	0.407	ADP-forming succinate--CoA ligase subunit beta
	BCN_RS07995	0.451	Methylglyoxal synthase
	BCN_RS18550	0.467	Succinate-CoA ligase subunit alpha

). Specifically, the DEG encoding a hydroxylamine reductase (BCN_RS16540) was also greatly enhanced to express in B. cereus A1-1 (150.780-fold).

Conversely, 69 DEGs involved in the flagellar assembly, bacterial chemotaxis, ABC transporters, and TCS were significantly down-regulated at the transcription level in B. cereus A1-1 (0.038- to 0.487-fold) (p < 0.05) (Table 7), similar to the other bacterial strains treated with the CC1. For example, in the flagellar assembly, expression of 19 DEGs were significantly depressed (0.038- to 0.438-fold) (p < 0.05); 9 DEGs in bacterial chemotaxis were significantly down-regulated (0.063- to 0.474-fold); and expression of 33 DEGs in ABC transporters were significantly inhibited (0.051- to 0.487-fold).

Approximately eight DEGs in the TCSs were significantly down-regulated. TCSs are widespread regulatory systems that can help bacteria to control their cellular functions and respond to a diverse range of stimuli [27]. In this study, in the HIF-1 signaling pathway, the expression of a L-lactate dehydrogenase (BCN_RS24725) was also significantly down-regulated (0.191-fold). These results indicated the inhibited signal transduction systems in B. cereus A1-1.

Additionally, 17 DEGs in the arginine biosynthesis, thiamine metabolism, and alanine, aspartate and glutamate metabolism were all significantly down-regulated (0.031- to 0.498-fold) (p < 0.05) (Table 7), which suggested the inhibited energy metabolism in B. cereus A1-1 after being treated by the CC 1 from R. madaio Makino.

3. Materials and Methods

3.1. Bacterial Strains and Culture Conditions

Bacterial strains and culture media used in this study are listed in Table S1. Bacterial culture media were purchased as described previously [28]. Vibrio strains were inoculated in media (pH 8.4–8.5) with 3.0% NaCl, while non-Vibrios in media (pH 7.0–7.2) with 1% NaCl [28].

3.2. Extraction of Bioactive Substances from R. madaio Makino

R. madaio Makino was collected in Lishui City (27°25′37″ N, 118°41′28″ E), Zhejiang Province, China in September of 2020. A 500 g of fresh leaf and stem tissues of R. madaio Makino was washed clean, dried at room temperature, and then freeze-dried using ALPHA 2-4 LD Plus Freeze Dryer (Martin Christ, Osterode, Germany) at −80 °C for 48 h. The freeze-dried material was crushed using FW-135 High-Speed Crusher (Beijing Kangtuo Medical Instruments Co., Ltd., Beijing, China) and passed through 300 mesh screen. Then, 10.0 g of the powder was mixed with 99-mL chloroform: methanol (2:1, v/v, analytical grade, Merck KGaA, Darmstadt, Germany) at a solid to liquid ratio of 1.10 (m/v) for 5 h [29]. A 60 mL of H₂O (Analytical grade, Merck KGaA, Darmstadt,,Germany) was then added, fully mixed, and then sonicated using Scientz IID ULtrasonic Cell Crusher (SCIENT Z, Ningbo, China) at the following parameters: power: 300 W; ultrasonic on time: 1 s; ultrasonic off time: 1 s; working time: 20 min; and probe size: 6 mm. The sonicated mixture was filtered through 20–25 μm membrane (Shanghai Sangon Biological Engineeing Technology and Service Co., Ltd., Shanghai, China), and the filtration was collected for the secondary extraction. The methanol phase was separated from the chloroform phase and then individually evaporated, concentrated on pasting using Rotary Evaporator (IKA, Staufen, Germany).

3.3. Antimicrobial Susceptibility Assay

Susceptibility of bacterial strains (Table S1) to the extracts from R. madaio Makino was determined according to the method issued by Clinical and Laboratory Standards Institute (CLSI) (2018, CLSI, M100-S23) using Mueller-Hinton (M-H) agar (CM337) and Mueller-Hinton broth (M391) (OXOID, Basingstoke, UK). Briefly, a 10 μL of crude extracts (500 μg/mL) was added onto each blank disc (6 mm, OXOID, Basingstoke, UK) on MH ager plates. The gentamicin disc (10 μg, OXOID, Basingstoke, UK) was used as a positive control, while the methanol-phase with water and chloroform-phase with ethanol was a negative control, respectively. The plates were incubated at 37 °C for 12 h. Bacteriostatic activity was evaluated by measuring diameters of bacteriostatic circles.

Broth dilution testing (microdilution) (2018, CLSI, M100-S18) was used to determine MICs of the extracts. Briefly, a 100 μL/well of the extracts (1024 μg/mL) was serially diluted, mixed with 100 μL/well of Mueller-Hinton broth (CM337) and 10 μL/well of bacteria strain (1.5 × 10⁶ colony-forming unit (CFU)/mL), and then incubated at 37 °C for 12 h [30]. The MIC was defined as the lowest concentration of a particular antibacterial agent that inhibits bacterial growth (2018, CLSI, M100-S18). The standard solution of gentamicin (100 μg/mL) was purchased from National Standard Material Information Center, Beijing, China.

3.4. Prep-HPLC Analysis

Aliquots (10 mg/mL) of freeze-dried samples resolved in H₂O (Analytical grade, Merck KGaA, Darmstadt, Germany) were centrifuged at 12,000 rpm for 20 min. The supernatant was filtered through 0.22 µm membrane (Sangon, Shanghai, China), and the filtration was collected for further analysis. Prep-HPLC was run using Waters 2707 (Waters, Milford, Massachusetts, USA) linked with UPLC Sunfire C18 column (5 μm, 10 × 250 mm) (Waters, Massachusetts, USA) at the following parameters: column temperature, 40 °C; injection volume, 100 μL; and mobile phase of methanol (eluent A) and water (eluent B) at a flow rate of 4 mL/min (isocratic elution: 0–15 min, 20% eluent A and 80% eluent B). Photo-diode array (PDA) spectra were measured in the wavelength ranging from 200 to 600 nm.

3.5. UHPLC–MS Analysis

The UHPLC–MS analysis was carried out using EXIONLC System (Sciex, Framingham, MA, USA) by Shanghai Hoogen Biotech, Shanghai, China using the parameters as described previously [31]. The mobile phase A contained 0.1% formic acid in H₂O (v/v), and mobile phase B was acetonitrile (Merck KGaA, Darmstadt, Germany); column temperature: 40 °C; auto-sampler temperature: 4 °C; injection volume: 2 μL. Typical ion source parameters were: IonSpray voltage: +5500/−4500 V; curtain gas: 35 psi; temperature: 400 °C; ion source Gas 1:60 psi; ion source Gas 2: 60 psi; and declustering potential (DP): ±100 V. The SCIEX Analyst Work Station Software (Version 1.6.3) was employed for multiple reaction monitoring (MRM) data acquisition and processing. In-house R program and database were applied for peak detection and annotation (Shanghai Hoogen Biotech, Shanghai, China).

3.6. Transmission Electron Microscope (TEM) Assay

Samples for TEM analysis were prepared according to the method described previously [32]. Briefly, 1 × MIC concentration of CC 1 from R. madaio Makino was added in bacterial culture (5 mL) at middle logarithmic growth phase (mid-LQP), and incubated at 37 °C for 2 h, 4 h and 6 h, respectively. A 1.5 mL of the cell suspension were collected, washed, fixed, and observed using SU5000 transmission electron microscope (Hitachi, Tokyo, Japan, 5.0 kV, ×30,000) [32].

3.7. Bacterial Cell Surface Hydrophobicity, Membrane Fluidity and Damage Assays

Bacterial cell surface hydrophobicity and membrane fluidity were measured according to the methods by Krausova et al. [33] and Kuhry et al. [34], respectively. In the former method, 1 mL of 98% cetane (Sangon, Shanghai, China) was added into 1 mL of bacterial cell suspension (OD_{600 nm} values of 0.55 to 0.60) and rotated for 1 min and then stood at room temperature for 30 min. The absorbance of the aqueous phase was measured at OD_{600 nm} using BioTek Synergy 2 (BioTek, Burlington, VT, USA). To measure the membrane fluidity, a 200 μL/well of bacterial suspension was mixed with 2 μL of 10 mM 1,6-diphenyl-1,3,5-hexatriene (DPH) (Sangon, China), and the change of fluorescence intensity of each well was measured at excitation light wavelength of 362 nm and emission light wavelength of 427 nm using BioTek Synergy 2 (BioTek, Burlington, VT, USA).

Cell membrane damage was examined according to the method described previously [32]. Briefly, the bacterial cell suspension was double-dyed using propidium iodide (PI, 10 mM final concentration) (Sangon, China), and 5(6)-carboxydiacetate fluorescein succinimidyl ester (CFDA, 10 mM final concentration) (Beijing Solarbio Science & Technology Co. Ltd., Beijing, China), and determined using Flow Cytometer BD FACSVerse™ (Becton, Dickinson and Company, Franklin Lakes, NJ, USA) [32].

3.8. Cell Membrane Permeability Analysis

Bacterial culture at the mid-LGS was mixed with 1 × MIC concentration of the CC 1 from R. madaio Makino and then incubated at 37 °C for 2 h, 4 h and 6 h. Outer membrane permeability was measured according to the method described previously [35]. Briefly, a 200 μL/well of bacterial cell suspension was mixed with 2 μL/well of 10 mm NPN solution (Sangon, Shanghai, China). The excitation and emission wavelengths were set at 350 nm and 420 nm, respectively, and recorded using BioTek Synergy 2 (BioTek, Burlington, VT, USA) [35].

Inner membrane permeability was measured according to the method described previously [36]. Briefly, a 200 μL/well of bacterial cell suspension was mixed with 2.5 μL/well of 10 mm ONPG solution (Sangon, Shanghai, China). The cell mixture was incubated at 37 °C and measured for each well at OD_{415 nm} using BioTek Synergy 2 (BioTek, Burlington, VT, USA) every 30 min for 5 h, which was marked as OD₁, while OD₂ generated from the untreated bacterial suspension was used as a negative control [36].

3.9. Illumina RNA Sequencing

Bacterial culture at the mid-LGP was treated with 1 × MIC concentration of the CC 1 from R. madaio Makino for 6 h. Total RNA was prepared using RNeasy Protect Bacteria Mini Kit (QIAGEN Biotech Co. Ltd., Frankfurt, Germany) and QIAGEN RNeasy Mini Kit (QIAGEN). DNA was removed from the samples using RNase-Free DNase Set (QIAGEN). Three independently prepared RNA samples were used for each Illumina RNA-sequencing analysis. Illumina sequencing was conducted by Shanghai Majorbio Bio-pharm Technology Co. Ltd. (Shanghai, China) using Illumina HiSeq 2500 platform (Illumina, Santiago, CA, USA). High quality reads that passed the Illumina quality filters were used for sequence analyses [32].

3.10. Reverse Transcription Real Time-Quantitative PCR (RT-qPCR) Assay

Total RNA extraction, reverse transcription reactions, and relative quantitative PCR reactions were performed using the same kits and instrument according to the method described previously [31]. The 16S rRNA gene was used as the internal reference gene, and 2^−ΔΔCt method was used to calculate relative expression of genes. Oligonucleotide primers used for the RT-qPCR were synthesized by Sangon, Shanghai, China.

3.11. Data Analysis

Expression of each gene was calculated using RNA-Seq by Expectation-Maximization (RSEM, http://deweylab.github.io/RSEM/, accessed on 17 October 2021). Genes with the criteria, fold-changes ≥ 2.0 or ≤0.5, and p-values < 0.05 relative to the control were defined as DEGs. These DEGs were used for gene set enrichment analysis (GSEA) against the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (https://www.genome.jp/kegg/, accessed on 17 October 2021). Significantly changed GSEA were identified when the enrichment test p-value fell below 0.05 [32]. All tests were performed in triplicates. The data were analyzed using SPSS statistical analysis software version 17.0 (SPSS Inc., Armonk, NY, USA).

4. Conclusions

In this study, we identified, for the first time, antibacterial components and action modes of methanol-phase extract from one edible herbaceous plant R. madaio Makino. The bacteriostatic rate of the extract was 75% against 23 species of common pathogenic bacteria, which was higher than that of the chloroform-phase extract (39%). The methanol-phase extract was further purified using the Prep-HPLC technique, and five separated CCs were obtained. Among these, the CC 1 from R. madaio Makino significantly increased bacterial cell surface hydrophobicity and membrane permeability and decreased membrane fluidity of Gram-positive and Gram-negative pathogens, such as V. parahaemolyticus ATCC17802, V. parahaemolyticus B4-10, V. alginolyticus ATCC17749, and B. cereus A1-1. The damaged cell surface and membrane structure integrity facilitated the CC1 to penetrate bacterial cell envelope to target intracellular processes. A total of 58 different compounds in the extract were identified using UHPLC–MS technique. Comparative transcriptomic analyses revealed a number of differentially expressed genes (DGEs) and various changed metabolic pathways mediated by the CC1 action, such as down-regulation of carbohydrate transport and/or utilization, and energy metabolism; upward regulation of amino acid and fatty acid degradation, and nitrogen metabolism; and inactive flagellar assembly and mobility in the four bacterial strains. Taken, the results in this study demonstrated that the CC1 from R. madaio Makino are promising candidates for antibacterial medicine and human health care products.