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MAP  >  Food Materials Research
2022 Volume 2
Article Contents
Abstract
Introduction
Materials and methods
Plant material collection and identification
Materials, reagents, and instrumentation
Qualitative determination of the phytochemical constituents
Extraction and isolation
Anti-bacterial and anti-fungal assays
Identification and selection of target protein
Selection of ligand molecules
Preparation of protein molecule
Virtual screening of ligands
Docking
Autodock vina
Biovia discovery studio client 2021
Structure visualization through pymol
Drug likeliness property analysis
Statistical data analysis
Results
Phytochemical test
Characterization of isolated compounds
Antimicrobial activities assay
Binding mode of isolated compounds docked against dnmt1 enzyme
Binding mode of isolated compounds docked against hpv type 16 e6
Admet profiling in grug-likeness and toxicity analysis
Discussion
Conclusions
Author contributions
Data availability
Acknowledgments
Conflict of interest
Supplementary information
Rights and permissions
References
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ARTICLE   Open Access    

A multi-layer genome mining and phylogenomic analysis to construct efficient and autonomous efflux system for medium chain fatty acids

  • 1.

    College of Food Science and Technology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China

  • 2.

    Department of Food Science and Technology, College of Light Industry and Food Engineering, Nanjing Forestry University, Nanjing 210037, China

  • 3.

    School of Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi 214122, China

More Information
  • Medium-chain fatty acids (MCFAs) are important components for food, pharmaceutical and fuel industries. Nevertheless, engineering microorganisms to produce MCFAs often induces toxicity and stresses towards host strains, which could be alleviated via accelerating the export of MCFAs from cells. However, current secretory systems are inefficient and require inducible promoters. Here, a multi-layer genome mining and phylogenomic analysis was developed to identify efficient efflux transporters. Firstly, based on the genomic mining of 397 strains throughout various representative species, the evolutionary history of efflux transporters was recapitulated, and further experimental analysis revealed that acrE from Citrobacter exhibited the best performance. Secondly, according to the further mining of 797 Citrobacter genomes and 1084 Escherichia genomes, a detailed phylogenomic analysis of efflux transporter-centric genomic vicinities was performed. This led to the identification of efficient efflux pump combination acrE and acrF. These efflux pumps were then combined with the quorum-sensing circuit from Enterococcus faecalis to regulate MCFA efflux in an autonomous manner, which achieved a 4.9-fold boost in MCFA production and firstly demonstrated the efficient and autonomous efflux pump specially for MCFAs. The integrative omics technologies described here are enabling the utilization of the increasingly large database and the effective mining of target gene diversities.

  • Introduction

    Salvia rosmarinus L. (old name Rosmarinus officinalis), common name Rosemary thrives well in dry regions, hills and low mountains, calcareous, shale, clay, and rocky substrates[1]. Salvia rosmarinus used since ancient times in traditional medicine is justified by its antiseptic, antimicrobial, anti-inflammatory, antioxidant, and antitumorigenic activity[1,2]. The main objective of the study is to evaluate the antimicrobial activity of different extracts of Salvia rosmarinus in vitro, and its compounds related to in silico targeting of enzymes involved in cervical cancer. Since the start of the 20th century, some studies have shown that microbial infections can cause cervical cancers worldwide, infections are linked to about 15% to 20% of cancers[3]. More recently, infections with certain viruses like Human papillomaviruses (HPV) and Human immunodeficiency virus (HIV), bacteria like Chlamydia trachomatis, and parasites like schistosomiasis have been recognized as risk factors for cancer in humans[3]. Then again, cancer cells are a group of diseases characterized by uncontrolled growth and spread of abnormal cells. Many things are known to increase the risk of cancer, including dietary factors, certain infections, lack of physical activity, obesity, and environmental pollutants[4]. Some studies have found that unbalanced common flora Lactobacillus bacteria around the reproductive organ of females increases the growth of yeast species (like Candida albicans) and some studies have found that women whose blood tests showed past or current Chlamydia trachomatis infection may be at greater risk of cervical cancer. It could therefore be that human papillomavirus (HPV) promotes cervical cancer growth[3]. Salvia rosmarinus is traditionally a healer chosen as a muscle relaxant and treatment for cutaneous allergy, tumors, increases digestion, and the ability to treat depressive behavior; mothers wash their bodies to remove bacterial and fungal infections, promote hair growth, and fight bad smells[5] .

    The study of plant-based chemicals, known as phytochemicals, in medicinal plants is gaining popularity due to their numerous pharmacological effects[6] against drug resistance pathogens and cancers. The causes of drug resistance to bacteria, fungi, and cancer are diverse, complex, and only partially understood. The factors may act together to initiate or promote infections and carcinogenesis in the human body is the leading cause of death[7]. Antimicrobial medicines are the cornerstone of modern medicine. The emergence and spread of drug-resistant pathogens like bacteria and fungi threaten our ability to treat common infections and to perform life-saving procedures including cancer chemotherapy and cesarean sections, hip replacements, organ transplantation, and other surgeries[7]. On the other hand, information about the current magnitude of the burden of bacterial and fungal drug resistance, trends in different parts of the world, and the leading pathogen–drug combinations contributing to the microbial burden is crucial. If left unchecked, the spread of drug resistance could make many microbial pathogens much more lethal in the future than they are today. In addition to these, cancers can affect almost any part of the body and have many anatomies and molecular subtypes that each require specific management strategies to avoid or inhibit them. There are more than 200 different types of cancer that have been detected. The world's most common cancers affecting men are lung, prostate, colorectal, stomach, and liver cancers[8]. While breast, cervix, colorectal, lung, and stomach cancers are the most commonly diagnosed among women[8]. Although some cancers said to be preventable they seem to still be one of the causes of death to humans, for example cervical cancer. The need to fill the gap to overcome the problem of searching for antimicrobials and anticancers from one source of Salvia rosmarinus is of importance.

    Cervical cancer is a common cancer in women and a prominent cause of death[9]. In Ethiopia, cervical cancer is a big deal for women aged 15 to 44, coming in as the second most common cancer[9]. Globally, it's the fourth most common prevalent disease for women[10]. Aberrant methylation of tumor-suppressor genes' promoters can shut down their important functions and play a big role in causing cervical tumors[10]. There are various cervical cancer repressor genes (proteins turn off or reduce gene expression from the affected gene), such as CCNA1, CHF, HIT, PAX1, PTEN, SFRP4, and TSC1. The genes play a crucial role in causing cervical cancer by regulating transcription and expression through promoter hypermethylation, leading to precursor lesions during cervical development and malignant transformation[11]. The process of DNA methylation is primarily carried out by a group of enzymes known as DNA methyltransferases (DNMT1). It has been reported that DNMT1 (PDB ID: 4WXX), a protein responsible for DNA methylation can contribute to the development of cervical cancer. DNMT1 inhibits the transcription of tumor suppressor genes, facilitating tumorigenesis, which finally develops into cervical cancer. Tumor suppressor gene transcription is inhibited by DNMT1, which helps cancer grow and eventually leads to cervical cancer. Repressive genes' hypermethylation may be decreased, their expression can be increased, and the phenotype of malignant tumors can be reversed by inhibiting the DNMT1 enzyme.

    On the other hand, infection by the human papilloma virus (HPV) phenotype 16, enzyme 6 (PDB ID: 4XR8) has been correlated with a greatly increased risk of cervical cancer worldwide[12]. Based on variations in the nucleotide sequences of the virus genome, over 100 distinct varieties of the human papilloma virus (HPV) have been identified (e.g. type 1, 2 etc.). Genital warts can result from certain types 6 and 11 of sexually transmitted HPVs. Other HPV strains, still, that can infect the genitalia, do not show any symptoms of infection[8]. Persistent infection with a subset of approximately 13 so-called 'high-risk' sexually transmitted HPVs, including such as types 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, and 68 different from the ones that cause warts may lead to the development of cervical intraepithelial neoplasia (CIN), vulvar intraepithelial neoplasia (VIN), penile intraepithelial neoplasia (PIN), and/or anal intraepithelial neoplasia (AIN). These are precancerous lesions and can progress to invasive cancer. Almost all occurrences of cervical cancer have HPV infection as a required component[13]. Superfluous infection by HPV type 16 E6 (PDB ID: 4XR8) has been correlated with a greatly increased genital risk of precursor cervical cancer worldwide[11]. Scholars more defined in major biochemical and biological activities of HPV type 16 E6 (PDB ID: 4XR8) in high-risk HPV oncogenes and how they may work together in the development of cervical disease and cancer[13].

    One potential approach to treat cervical cancer is to inhibit the activity of the DNMT1 and HPV type 16 E6 enzymes specifically[13−16]. Over 50% of clinical drug forms worldwide originate from plant compounds[17]. In the past, developing new drugs was a lengthy and costly process. However, with the emergence of bioinformatics, the use of computer-based tools and methods have become increasingly important in drug discovery. One such method is molecular docking and ADMET profiling which involves using the structure of a drug to screen for potential candidates. This approach is known as structure-based drug design and can save both time and resources during the research process[15]. Structural-based drug designing addresses ligand binding sites with a known protein structure[15]. Using free binding energies, a computational method known as docking examines a large number of molecules and suggests structural theories for impeding the target molecule[17]. Nowadays, due to increasing antibiotic resistance like bacteria, fungi, and cancer cells, natural products remain an important source for discovering antimicrobial compounds and novel drugs for anti-cancers like cervical cancers. Therefore, the purpose of this research is to assess the antimicrobial activity of extracts, molecular docking, ADMET profiling in anticancer properties of compounds isolated from Salvia rosmarinus, on a targeting DNMT1 and HPV type 16 E6 in human cervical cancer. In the present study, various solvent crude extracts obtained from Salvia rosmarinus were used for antimicrobial activity and the isolated compounds 1 and 2 were submitted for in silico study to target the DNMT1 and HPV type 16 E6 enzymes to inhibit the growth of human cervical cancer cells.

    Materials and methods

    Plant material collection and identification

    Healthy Salvia rosmarinus leaves were collected in Bacho district, Southwest Showa, Oromia, Ethiopia, during the dry season of November 2022. The plant materials were authenticated by Melaku Wondafrish, Natural Science Department, Addis Ababa University and deposited with a voucher number 3/2-2/MD003-80/8060/15 in Addis Ababa University's National Herbarium.

    Materials, reagents, and instrumentation

    The most common organic solvent used in extractions of medicinal plants is 2.5 L of petroleum ether, chloroform/methanol (1:1), and methanol. The test culture medium for microbes was used and performed in sterile Petri dishes (100 mm diameter) containing sterile Muller–Hinton Agar medium (25 mL, pH 7) and Sabouraud Dextrose Agar (SDA) for bacteria and fungi, respectively. A sterile Whatman filter paper (No. 1) disc of 6 mm diameter was used to determine which antibiotics an infective organism is sensitive to prescribed by a minimum zone of inhibition (MZI). Ciprofloxacin antibiotic reference (manufactured by Wellona Pharma Ciprofloxacin tablet made in India) and Ketoconazole 2% (made in Bangladesh) were used as a positive controls for antibacterial and antifungal, respectively and Dimethyl sulfoxide (DMSO) 98.9% was used as a negative control for antimicrobial tests. In the present study, the height of the column was 650 mm and the width was 80 mm. Several studies by previous researchers showed the acceptable efficiency of column chromatography (up to 43.0% w/w recovery) in the fractionation and separation of phenolic compounds from plant samples[18]. In column chromatography, the ideal stationary phase used silica gel 60 (0.200 mm) particles. The 1H-NMR spectrums of the compounds were analyzed using a 600 MHz NMR machine and 150 MHz for 13C NMR. The compounds were dissolved in MeOD for compound 1 and in DMSO for compound 2 for NMR analysis. On the other hand, UV spectroscopy (made in China) used 570 nm ultraviolet light to determine the absorbency of flavonoids (mg·g−1) phytochemicals.

    Qualitative determination of the phytochemical constituents

    The samples (extracts) were analyzed to detect the presence of certain chemical compounds such as alkaloids (tested using Wagner's reagents), saponins (tested using the froth test), steroids (tested with Liebermann Burchard's tests), terpenoids (tested with Lidaebermann Burchard's tests), quinones, and flavonoids (tested using Shinoda tests)[19].

    Extraction and isolation

    The leaves of Salvia rosmarinus (500 g) were successively extracted using maceration using petroleum ether, chloroform/methanol (1:1), and methanol, every one 2.5 L for 72 h to afford 3.6, 6, and 53 g crude extracts, respectively. The methanol/chloroform (1:1) extract (6 g) was loaded to silica gel (150 g) column chromatography using the increasing polarity of petroleum ether, methanol/chloroform (1:1) solvent system to afford 80 fractions (100 mL each). The fraction obtained from chloroform/methanol 1:1 (3:2) after repeated column chromatography yielded compound 1 (18 mg). Fractions 56-65, eluted with chloroform/methanol (1:1) were combined and purified with column chromatography to give compound 2 (10 mg).

    Anti-bacterial and anti-fungal assays

    The microorganisms were obtained from the Ethiopia Biodiversity Institution (EBI). Two gram-positive bacteria namely Staphylococcus aureus serotype (ATCC 25923) and Streptococcus epidermidis (ATCC14990); and three gram-negative bacteria, namely Escherichia coli (ATCC 25922), Pseudomonas aeruginosa (ATCC 5702), and Klebsiella pneumonia (ATCC e13883) were inoculated overnight at 37 °C in Muller–Hinton Agar/MHA culture medium and two fungus strains of Candida albicans (ATCC 16404) and Aspergillus niger (ATCC 11414) were inoculated overnight at 27−30 °C in Sabouraud Dextrose Agar/SDA culture medium[20].

    The antibacterial and antifungal activities of different crude extracts obtained from Salvia rosmarinus plant leaves were evaluated by the disk diffusion method (in accordance with the 13th edition of the CLSI M02 document on hardydiagnostics.com/disk-diffusion). Briefly, the test was performed in sterile Petri dishes (100 mm diameter) containing solid and sterile Muller–Hinton Agar medium (25 mL, pH 7) and Sabouraud Dextrose Agar (SDA) for bacteria and fungi, respectively. The extracts were placed on the surface of the media that had previously been injected with a sterile microbial suspension (one microbe per petri dish) after being adsorbed on sterile paper discs (5 μL per Whatman disc of 6 mm diameter). To prevent test samples from eventually evaporating, all Petri dishes were sealed with sterile laboratory films. They were then incubated at 37 °C for 24 h, and the zone diameter of the inhibition was measured and represented in millimeters. Ciprofloxacin antibiotic reference (manufactured by Wellona Pharma Ciprofloxacin tablet, India) was used as a positive control and DMSO was used as a negative control for antibacterial activity test while Ketoconazole 2% (Bangladesh) was used as a positive control and 10 μL of 0.2% agar as a negative control for antifungal activity tests[20]. The term 'inhibitory concentration' refers to the minimum sample concentration required to kill 99.9% of the microorganisms present[21]. Three repetitions of the crude extract sample were used to precisely measure the inhibitory halo diameter (in mm), which was then expressed as mean ± standard deviation to assess the anti-microbial activity.

    Identification and selection of target protein

    Cervical cancer-causing protein was identified through relevant literature. The protein molecule structure of DNA (cytosine-5)-methyltransferase 1 (DNMT1) (PDB ID: 4WXX)[21] and HPV type 16 E6 (PDB ID: 4XR8)[21] - a protein known to cause cervical cancer - were downloaded from the Protein Data Bank[22]. The stability of the protein molecule was assessed using Rampage[23].

    Selection of ligand molecules

    Phytochemical constituents of Salvia rosmarinus plant leaves were used to select a source of secondary metabolites (ligands). Ligand molecules were obtained through plant extraction, and isolation, and realized with PubChem (https://pubchem.ncbi.nlm.nih.gov/). The ligands were downloaded in Silver diamine fluoride format (SDF) and then converted to PDB format using an online SMILES translator (https://cactus.nci.nih.gov/translate/). The downloaded files were in PDB format, which was utilized for running various tools and software[24].

    Preparation of protein molecule

    The Biovia Discovery Studio Visualizer software was used to analyze the protein molecule. The protein molecule was converted into PDB format and its hierarchy was analyzed by selecting ligands and water molecules. Both the protein molecule and the water molecules lost their attached ligands during the analysis. Finally, the protein's crystal structure was saved in a PDB file[25].

    Virtual screening of ligands

    PyRx software was utilized to screen secondary metabolites and identify those ligands with the lowest binding energy to the protein target. The ligands with the lowest binding energy were further screened for their drug-likeliness property through analysis. It is worth noting that PyRx runs on PDBQT format. To begin using PyRx, it needs to load a protein molecule. This molecule should be converted from PDB to the protein data bank, partial charge (Q), and Atom Type (PDBQT) format. Once the protein molecule is loaded, it can import ligands from a specific folder in Silver diamine fluoride format. The ligand energy was minimized and changed to PDBQT format. The protein was docked with the ligand and screened based on minimum binding energy (https://cactus.nci.nih.gov/translate/).

    Docking

    The optimal ligand was selected for final docking using AutoDock Vina and Biovia by modifying the reference of Discovery Studio Client 2021 (https://cactus.nci.nih.gov/translate/).

    AutoDock Vina

    The protein target from the Protein Data Bank (PDB) was loaded onto the graphical interface of AutoDock Vina. To prepare the protein for docking, water molecules were removed, hydrogen polar atoms were added, and Kollman charges were assigned to the protein molecule. Ultimately, PDBQT format was used to store the protein. After being imported in PDB format, the Ligand molecule was transformed to PDBQT format. Next, a grid box was chosen to represent the docked region. The command prompt was used to run AutoDock Vina and the outcomes were examined (https://cactus.nci.nih.gov/translate/).

    Biovia Discovery Studio Client 2021

    Docking the ligand with the protein target DNMT1(PDB ID: 4WXX)[22] and HPV type 16 E6 (PDB ID: 4XR8)[21] enzymes were performed using Biovia Discovery Studio Client 2021 by loading the protein target first followed by the ligand in PDB format. The charges were attached to the protein molecule, and the energy was minimized for the ligands. Both the protein and ligand molecules were prepared for docking. Once the docking process was complete, the results were analyzed based on several parameters, including absolute energy, clean energy, conf number, mol number, relative energy, and pose number. The interaction between the protein and ligand was analyzed using structure visualization tools, such as Biovia Discovery Studio Visualizer and PyMol (https://cactus.nci.nih.gov/translate/).

    Structure visualization through PyMol

    The process of visualizing the structure was carried out using the PyMol tool. PyMol is a freely available software. Firstly, the protein molecule in PDBQT form was loaded on the PyMol graphical screen. Then, the output PDBQT file was added. The docked structure was visualized and the 'molecule' option was changed to 'molecular surface' under the 'shown as' menu (https://cactus.nci.nih.gov/translate/).

    Drug likeliness property analysis

    Drug likeliness properties of the screened ligands were evaluated using the SwissADME online server. SMILE notations were obtained from PubChem and submitted to the SwissADME web server for analysis. The drugs were subjected to Lipinski's rule of five[20] for analysis. Lipinski's rules of five were selected for final docking through AutoDock Vina and Biovia Discovery Studio Client 2021. Ligands 1 and 2 were analyzed using Lipinski's rule of five for docking with AutoDock Vina and Biovia Discovery Studio Client 2021.

    Statistical data analysis

    The antimicrobial analysis data generated by triplicate measurements reported as mean ± standard deviation, and a bar graph also generated by GraphPad Prism version 8.0.1 (244) for Windows were used to perform the analysis. GraphPad Prism was used and combined with scientific graphing, comprehensive bar graph fitting (nonlinear regression), understandable statistics, and data organization. Prism allows the performance and modification of basic statistical tests commonly used and determined through the statistical applications in microbiology labs (https://graphpad-prism.software.informer.com/8.0/).

    Results

    Phytochemical test

    Phytochemical screening of the different extracts for the presence (+) and absence (−) of alkaloids, steroids, glycosides, coumarins, terpenoids, flavonoids, carbohydrates, tannins, and saponins were done. The present study showed that alkaloids, terpenoids, flavonoids, and tannins tests in S. rosmarinus leaves of petroleum ether, chloroform/methanol (1:1), and methanol extracts were high whereas glycoside, coumarins, and carbohydrates had a moderate presence. The extract of S. rosmarinus leaves contain commonly bioactive constituents such as alkaloids, steroids, terpenoids, flavonoids, tannins, and saponins. These bioactive chemicals have active medicinal properties. Phytochemical compounds found in S. rosmarinus leaves have the potential to treat cancer cells and pathogens. The study also found that these flavonoids are related to natural phenolic compounds with anticancer and antimicrobial properties in the human diet (Table 1).

    Table 1.  Phytochemical screening tests result of petroleum ether, chloroform/methanol (1:1) and methanol extracts of Salvia rosmarinus leaves.
    Botanical name Phytochemicals Phytochemical screening tests Different extracts
    Petroleum ether Chloroform/methanol (1:1) Mehanol
    Salvia rosmarinus Alkaloids Wagner's test ++ ++ ++
    Steroids Libermann Burchard test ++ + ++
    Glycoside Keller-Killiani test − + −
    Coumarins Appirade test − + +
    Terpenoids Libermann Burchard test ++ ++ ++
    Flavonoids Shinoda test ++ ++ ++
    Carbohydrate Fehling's test − ++ ++
    Tannins Lead acetate test ++ ++ ++
    Saponins Foam test + + +
    + indicates moderate presence, ++ indicates highly present, − indicates absence.
     | Show Table
    DownLoad: CSV

    Characterization of isolated compounds

    Two compounds were isolated and characterized using NMR spectroscopic methods (Fig. 1 & Supplementary Fig. S1a−c). Compound 1 (10 mg) was isolated as yellow crystals from the methanol/chloroform (1:1) leaf extract of Salvia rosmarinus. The TLC profile showed a spot at Rf 0.42 with methanol/chloroform (3:2) as a mobile phase. The 1H-NMR spectrum (600 MHz, MeOD, Table 2, Supplementary Fig. S1a) of compound 1 showed the presence of one olefinic proton signal at δ 5.3 (t, J = 3.7 Hz, 1H), two deshielded protons at δ 4.7 (m, 1H), and 4.1 (m, 1H) associated with the C-30 exocyclic methylene group, and one O-bearing methine proton at δH 3.2 (m, 1H), and six methyl protons at δ 1.14 (s, 3H), 1.03 (d, J = 6.3 Hz, 3H), 1.00 (s, 3H), 0.98 (s, 3H), 0.87 (s, 3H), and 0.80 (s, 3H). A proton signal at δ 2.22 (d, J = 13.5 Hz, 1H) was attributed to methine proton for H-18. Other proton signals integrate for 20 protons were observed in the range δ 2.2 to 1.2. The proton decoupled 13C-NMR and DEPT-135 spectra (151 MHz, MeOD, Supplementary Fig. S1b & c) of compound 1 revealed the presence of 30 well-resolved carbon signals, suggesting a triterpene skeleton. The analysis of the 13C NMR spectrum displayed signals corresponding to six methyl, nine methylene, seven methine, and eight quaternary carbons. Among them, the signal observed at δ 125.5 (C-12) belongs to olefinic carbons. The methylene carbon showed signals at δC 39.9, 28.5, 18.1, 36.7, 23.9, 30.4, 26.5, 32.9, and 38.6. The quaternary carbons showed a signal at δC 39.4, 41.9, 38.4, 138.2, 41.8, and 47.8. The signals of exocyclic methylene carbon signals appeared at δ 153.1 and 103.9. The spectrum also showed sp3 oxygenated methine carbon at δ 78.3 and carboxyl carbon at δ 180.2. The spectrum revealed signals due to methyl groups at δC 27.4, 16.3, 15.0, 20.2, 22.7, and 16.4. The remaining carbon signals for aliphatic methines were shown at δC 55.3, 55.2, 53.0, and 37.1. The NMR spectral data of compound 1 is in good agreement with data reported for micromeric acid, previously reported from the same species by Abdel-Monem et al.[26]. (Fig. 1, Table 2).

    Figure 1.  Structure of isolated compounds from the leaves of Salvia rosmarinus.
    DownLoad: Full-Size Img PowerPoint
    Table 2.  Comparison of the 13C-NMR spectral data of compound 1 and micromeric acid (MeOD, δ in ppm).
    Position NMR data of compound 1 Abdel-Monem
    et al.[26]
    1H-NMR 13C-NMR 13C-NMR
    1 38.60 39.9
    2 27.8 28.5
    3 3.2 (m, 1H) 78.3 80.3
    4 − 39.4 39.9
    5 55.3 56.7
    6 18.1 18.3
    7 36.7 34.2
    8 − 41.9 40.7
    9 53 48.8
    10 − 38.4 38.2
    11 23.9 24.6
    12 5.3 (t, J = 3.7 Hz, 1H) 125.5 127.7
    13 − 138.2 138
    14 − 41.8 43.3
    15 30.4 29.1
    16 26.5 25.6
    17 − 47.8 48
    18 δ 2.22 (d, J = 13.5 Hz, 1H) 55.2 56.1
    19 37.1 38.7
    20 − 153.1 152.8
    21 32.9 33.5
    22 39.0 40.1
    23 27.4 29.4
    24 16.3 16.9
    25 15.0 16.6
    26 20.2 18.3
    27 22.7 24.6
    28 − 180.2 177.8
    29 16.4 17.3
    30 4.7 (m, 1H), and 4.1 (m, 1H) 103.9 106.5
     | Show Table
    DownLoad: CSV

    Compound 2 (18 mg) was obtained as a white amorphous isolated from 40% methanol/chloroform (1:1) in petroleum ether fraction with an Rf value of 0.49. The 1H NMR (600 MHz, DMSO, Supplementary Fig. S2a) spectral-data showed two doublets at 7.79 (d, J = 8.7 Hz, 2H), and 6.90 (d, J = 8.7 Hz, 2H) which are evident for the presence of 1,4-disubstituted aromatic group. The oxygenated methylene and terminal methyl protons were shown at δ 4.25 (q, J = 7.1 Hz, 2H) and 1.29 (t, J = 7.1 Hz, 3H), respectively. The13C-NMR spectrum, with the aid of DEPT-135 (151 MHz, DMSO, Table 3, Supplementary Fig. S2b & c) spectra of compound 2 confirmed the presence of well-resolved seven carbon peaks corresponding to nine carbons including threee quaternary carbons, one oxygenated methylene carbon, one terminal methyl carbon, and two symmetrical aromatic methine carbons. The presence of quaternary carbon signals was shown at δ 120.9 (C-1), 148.2 (C-4), and ester carbonyl at δ 166.0 (C-7). The symmetry aromatic carbons signal was observed at δ 131.4 (C-2, 6), and 116.8 (C-3, 5). The oxygenated methylene and terminal methyl carbons appeared at δC 60.4 (C-8) and 14.7 (C-9), respectively. The spectral results provided above were in good agreement with those for benzocaine in the study by Alotaibi et al.[27]. Accordingly, compound 2 was elucidated to be benzocaine (4-Aminobenzoic acid-ethyl ester) (Table 3, Fig. 1, Supplementary Fig. S2a−c), this compound has never been reported before from the leaves of Salvia rosmarinus.

    Table 3.  Comparison of the 1H-NMR, and 13C-NMR spectral data of compound 2 and benzocaine (DMSO, δ in ppm).
    Position NMR data of compound 2 Alotaibi et al.[27]
    1H-NMR 13C-NMR 1H-NMR 13C-NMR
    1 − 120.9 − 119
    2 7.79 (d, J = 8.7 Hz, 2H) 131.4 7.86 (d, J = 7.6 Hz) 132
    3 6.90 (d, J = 8.7 Hz, 2H) 116.8 6.83 (d, J = 7.6 Hz) 114
    4 − 148.2 − 151
    5 6.90 (d, J = 8.7 Hz, 2H) 116.8 6.83 (d, J = 7.6 Hz) 114
    6 7.79 (d, J = 8.7 Hz, 2H) 131.4 7.86 (d, J = 7.6 Hz) 132
    7 − 166.0 − 169
    8 4.3 (q, J = 7.1 Hz, 2H) 60.4 4.3 (q, J = 7.0 Hz) 61
    9 1.3 (t, J = 7.1 Hz, 3H) 14.7 1.36 (t, J = 7.0 Hz) 15
     | Show Table
    DownLoad: CSV

    Antimicrobial activities assay

    The extracts and isolated compounds from Salvia rosmarinus were evaluated in vitro against microbes from gram-positive bacteria (S. aureus and S. epidermidis), gram-negative bacteria (E. coli, P. aeruginosa, and K. pneumoniae) and fungi (C. albicans and A. Niger) (Table 4). The petroleum ether extracts exhibited significant activity against all the present study-tested microbes at 100 μg·mL−1, resulting in an inhibition zone ranging from 7 to 21 mm. Chloroform/methanol (1:1) and methanol extracts demonstrated significant activity against all the present study-tested microbes at 100 μg·mL−1 exhibiting inhibition zones from 6 to 14 mm and 6 to 13 mm, respectively (Table 4). The chloroform/methanol (1:1) extracts were significantly active against bacteria of E. coli and K. pneumonia, and A. Niger fungi at 100 μg·mL−1. On the other hand, chloroform/methanol (1:1) extracts were significantly inactive against the S. rosmarinus and P. aeruginosa of bacteria and C. albicans of fungi, and again chloroform/methanol (1:1) extracts overall significantly active produced an inhibition zone of 12 to 14 mm (Table 4). Methanol extracts exhibited significant activity against S. aureus, E. coli bacteria, and A. Niger fungi at 100 μg·mL−1. The inhibition zone was recorded to be 11 to 13 mm. However, methanol extracts exhibited significant inactivity against K. pneumoniae (Table 4). The overall result of our studies shows that Salvia rosmarinus was extracted and evaluated in vitro, exhibiting significant antibacterial and antifungal activity, with inhibition zones recorded between 6 to 21 mm for bacteria and 5 to 21 mm for fungi. In our study, the positive control for ciprofloxacin exhibited antibacterial activity measured at 21.33 ± 1.15 mm, 15.00 ± 0.00 mm, and 14.20 ± 0.50 mm for petroleum ether, chloroform/methanol (1:1), and methanol extracts, respectively. Similarly, the positive control for ketoconazole demonstrated antifungal activity of 22.00 ± 1.00 mm, 13.67 ± 0.58 mm, and 15.00 ± 0.58 mm for petroleum ether, chloroform/methanol (1:1), and methanol extracts, respectively. Additionally, our findings indicated that the mean values of flavonoids (mg/g) tested were 92.2%, 90.4%, and 94.0% for petroleum ether, chloroform/methanol (1:1), and methanol extracts, respectively. This suggests that the groups of phenolic compounds evaluated play a significant role in antimicrobial activities, particularly against antibiotic-resistant strains.

    Table 4.  Comparison of mean zone of inhibition (MZI) leaf extracts of Salvia rosmarinus.
    Type of specimen, and standard antibiotics for
    each sample    		 Concentration (μg·mL−1) of extract
    in 99.8% DMSO    		 Average values of the zone of inhibition (mm)
    Gram-positive (+) bacteria Gram-negative (−) bacteria Fungai
    S. aurous S. epidermidis E. coli P. aeruginosa K. pneumoniae C. albicans A. niger
    Petroleum ether extracts
    S. rosmarinus 50 18.50 ± 0.50 15.33 ± 0.58 0.00 ± 0.00 0.00 ± 0.00 10.00 ± 0.00 15.93 ± 0.12 4.47 ± 0.50
    75 19.87 ± 0.06 17.00 ± 0.00 9.33 ± 0.29 10.53 ± 0.50 10.93 ± 0.12 18.87 ± 0.23 5.47 ± 0.50
    100 21.37 ± 0.78 17.50 ± 0.50 11.47 ± 0.50 13.17 ± 0.29 12.43 ± 0.51 20.83 ± 0.76 6.70 ± 0.10
    Standard antibiotics Cipro. 21.33 ± 1.15 18.33 ± 0.58 9.33 ± 0.58 12.30 ± 0.52 15.00 ± 0.00
    Ketocon. 22.00 ± 1.00 10.67 ± 0.58
    Chloroform/methanol (1:1) extracts
    50 5.47 ± 0.42 0.00 ± 0.00 10.33 ± 0.00 0.00 ± 0.00 9.70 ± 0.00 0.00 ± 0.12 8.47 ± 0.50
    S. rosmarinus
    		 75 5.93 ± 0.06 0.00 ± 0.00 11.33 ± 0.29 0.00 ± 0.50 12.50 ± 0.12 0.00 ± 0.23 10.67 ± 0.50
    100 6.47 ± 0.06 0.00 ± 0.00 14.17 ± 0.50 7.33 ± 0.29 14.17 ± 0.51 0.00 ± 0.76 12.67 ± 0.10
    Standard antibiotics Cipro. 15.00 ± 0.00 11.00 ± 1.00 11.33 ± 0.58 10.00 ± 0.52 12.67 ± 0.00
    Ketocon. 7.00 ± 1.00 13.67 ± 0.58
    Methanol extracts
    50 9.17 ± 0.29 5.50 ± 0.50 0.00 ± 0.00 7.50 ± 0.00 0.00 ± 0.00 6.57 ± 0.12 0.00 ± 0.50
    S. rosmarinus
    		 75 9.90 ± 0.10 6.93 ± 0.12 9.33 ± 0.29 8.50 ± 0.50 0.00 ± 0.00 8.70 ± 0.23 0.00 ± 0.50
    100 11.63 ± 0.55 7.97 ± 0.06 11.47 ± 0.50 9.90 ± 0.10 0.00 ± 0.00 10.83 ± 0.76 13.13 ± 0.10
    Standard antibiotics Cipro. 13.00 ± 0.00 11.50 ± 0.50 14.20 ± 0.58 13.33 ± 0.29 10.00 ± 0.00
    Ketocon. 12.00 ± 1.00 15.00 ± 0.58
    Mean values of flavonoids (mg·g−1) by 570 nm
    S. rosmarinus
    		 Petroleum ether extracts Chloroform/methanol (1:1) extracts Methanol extracts
    50 0.736 0.797 0.862
    75 0.902 0.881 0.890
    100 0.922 0.904 0.940
    Samples: Antibiotics: Cipro., Ciprofloxacin; Ketocon., ketoconazole (Nizoral); DMSO 99.8%, Dimethyl sulfoxide.
     | Show Table
    DownLoad: CSV

    Determining the three solvent extracts in S. rosmarinus plants resulted in relatively high comparable with positive (+) control. Especially, the S. rosmarinus petroleum ether leaf extracts against drug resistance human pathogenic bacteria S. aureus, S. epidermidis, E. coli, P. aeruginosa, and K. pneumoniae were minimum zone of inhibition (MZI) recorded that 21.37 ± 0.78, 17.50 ± 0.50, 11.47 ± 0.50, 13.17 ± 0.29, and 12.43 ± 0.51 mm, respectively and against human pathogenic fungi C. albicans and A. niger were minimum zone of inhibition (MZI) recorded that 20.83 ± 0.76 and 6.70 ± 0.10 mm, respectively which was used from bacteria against S. aureus MZI recorded that 21.37 ± 0.78 mm higher than the positive control (21.33 ± 1.15 mm). The S. rosmarinus of chloroform/methanol (1:1) extracts were found to be against E. coli (14.17 ± 0.50 mm) and K. pneumoniae (14.17 ± 0.51 mm) higher than the positive control 11.33 ± 0.58 and 12.67 ± 0.00 mm, respectively. The methanol extracts of leaves in the present study plants were found to have overall MZI recorded less than the positive control. The Salvia rosmarinus crude extracts showed better antifungal activities than the gram-negative (−) bacteria (Table 4, Fig 2, Supplementary Fig. S3). Therefore, the three extracts, using various solvents of different polarity indexes, have been attributed to specific biological activities. For example, the antimicrobial activities of Salvia rosmarinus extracts may be due to the presence of alkaloids, terpenoids, flavonoids, tannins, and saponins in natural products (Table 1).

    Figure 2.  Microbes' resistance with drugs relative to standard antibiotics in extracts of Salvia rosmarinus. The figures represent understudy of three extracts derived from Salvia rosmarinus. (a) Petroleum ether, (b) chloroform/methanol (1:1), and (c) methanol extracts tested in Salvia rosmarinus.
    DownLoad: Full-Size Img PowerPoint

    Compounds 1 and 2 were isolated from chloroform/methanol (1:1) extract of Salvia rosmarinus (Fig. 1, Tables 2 & 3). The plant extract exhibited highest antibacterial results recorded a mean inhibition with diameters of 21 and 14 mm at a concentration of 100 mg·mL−1 against S. aureus and E. coli/K. pneumoniae, respectively. After testing, overall it was found that the highly active petroleum ether extract of Salvia rosmarinus was able to inhibit the growth of S. aureus and C. albicans, with inhibition zones of 21 and 20 mm, respectively. The petroleum ether extracts showed good efficacy against all tested microbes, particularly gram-positive bacteria and fungi (Table 4). This is noteworthy because gram-negative bacteria generally exhibit greater resistance to antimicrobial agents. Petroleum ether and chloroform/methanol (1:1) extracts of the leaves were used at a concentration of 100 mg·mL−1, resulting in impressive inhibition zone diameters of 11 and 14 mm for E. coli, 13 and 7 mm for P. aeruginosa, and 12 and 14 mm for K. pneumoniae, respectively.

    The present study found that at a concentration of 50 μg·mL−1, petroleum ether, chloroform/methanol (1:1), and MeOH extracts did not display any significant inhibition zone effects against the tested microbes. This implies that the samples have a dose-dependent inhibitory effect on the pathogens. The leaves of Salvia rosmarinus have been found to possess remarkable antimicrobial properties against gram-negative bacteria in different extracts such as E. coli, P. aeruginosa, and K. pneumoniae with 14.17 ± 0.50 in chloroform/methanol (1:1), 13.17 ± 0.29 in petroleum ether and 14.17 ± 0.51 in chloroform/methanol (1:1), respectively. However, in the present study, Salvia rosmarinus was found to possess remarkable high zones of inhibition with diameters of 21.37 ± 0.78 and 17.50 ± 0.50 mm antimicrobial properties against S. aureus, and S. epidermidis of gram-positive bacteria, respectively (Supplementary Fig. S3). The results are summarized in Fig. 2a−c.

    Binding mode of isolated compounds docked against DNMT1 enzyme

    The crystal structure of human DNMT1 (351-1600), classification transferase, resolution: 2.62 Å, PDB ID: 4WXX. Active site dimensions were set as grid size of center X = −12.800500 Å, center Y = 34.654981 Å, center Z = −24.870231 Å (XYZ axis) and radius 59.081291. A study was conducted to investigate the binding interaction of the isolated compounds 1 and 2 of the leaves of Salvia rosmarinus with the binding sites of the DNMT1 enzyme in human cervical cancer (PDB ID: 4WXX), using molecular docking analysis.

    The study also compared the results with those of standard anti-cancer agents Jaceosidin (Table 5 & Fig. 3). The compounds isolated had a final fixing energy extending from −5.3 to −8.4 kcal·mol−1, as shown in Table 4. It was compared to jaceosidin (–7.8 kcal·mol−1). The results of the molecular docking analysis showed that, compound 1 (−8.4 kcal·mol−1) showed the highest binding energy values compared with the standard drugs jaceosidin (–7.8 kcal·mol−1). Compound 2 has shown lower docking affinity (–5.3 kcal·mol−1) but good matching amino acid residue interactions compared to jaceosidin. After analyzing the results, it was found that the isolated compounds had similar residual interactions and docking scores with jaceosidin.

    Table 5.  Molecular docking results of ligand compounds 1 and 2 against DNMT1 enzyme (PDB ID: 4WXX).
    Ligands Binding affinity

    ( kcal·mol−1)    		 H-bond Residual interactions
    Hydrophobic/electrostatic Van der Waals
    1 −8.4 ARG778 (2.85249), ARG778 (2.97417), VAL894 (2.42832) − Lys-889, Pro-879, Tyr-865, His-795, Cys-893, Gly-760, Val-759, Phe-892, Phe-890, Pro-884, Lys-749
    2 −5.3 ARG596 (2.73996), ALA597 (1.84126), ILE422 (2.99493), THR424 (2.1965), ILE422 (2.93653) Electrostatic Pi-Cation-ARG595 (3.56619), Hydrophobic Alkyl-ARG595 (4.15839), Hydrophobic Pi-Alkyl-ARG595 (5.14967) Asp-423, Glu-428, Gly-425, Ile-427, Trp-464, Phe-556, Gln-560, Gln-594, Glu-559, Gln-598, Ser-563
    Jaceosidin −7.8 ASP571 (2.93566), GLN573 (2.02126), GLU562 (2.42376), GLN573 (3.49555), GLU562 (3.46629) Hydrophobic Alkyl-PRO574 (4.59409), Hydrophobic Alkyl-ARG690 (5.09748), Hydrophobic Pi-Alkyl-PHE576 (5.1314), Hydrophobic Pi-Alkyl-PRO574 (4.97072), Hydrophobic Pi-Alkyl-ARG690 (5.07356) Glu-698, Cys-691, Ala-695, Pro-692, Val-658, Glu-566, Asp-565
     | Show Table
    DownLoad: CSV
    Figure 3.  The 2D and 3D binding interactions of compounds against DNMT1 enzyme (PDB ID: 4WXX). The 2D and 3D binding interactions of compound 1 and 2 represent against DNMT1 enzyme, and jaceosidin (standard) against DNMT1 enzyme.
    DownLoad: Full-Size Img PowerPoint

    Hence, compound 1 might have potential anti-cancer agents. However, anti-cancer in vitro analysis has not yet been performed. Promising in silico results indicate that further research could be beneficial. The 2D and 3D binding interactions of compounds 1 and 2 against human cervical cancer of DNMT1 enzyme (PDB ID: 4WXX) are presented in Fig. 3. The binding interactions between the DNMT1 enzyme (PDB ID: 4WXX), and compound 1 (Fig. 3) and compound 2 (Fig. 3) were displayed in 3D. Compounds and amino acids are connected by hydrogen bonds (green dash lines) and hydrophobic interactions (non-green lines).

    Binding mode of isolated compounds docked against HPV type 16 E6

    Crystal structure of the HPV16 E6/E6AP/p53 ternary complex at 2.25 Å resolution, classification viral protein, PDB ID: 4XR8. Active site dimensions were set as grid size of center X = −43.202782 Å, center Y = −39.085513 Å, center Z = −29.194115 Å (XYZ axis), R-value observed 0.196, and Radius 65.584122. A study was conducted to investigate the binding interaction of the isolated compounds 1 and 2 of the leaves of Salvia rosmarinus with the binding sites of the enzyme of human papilloma virus (HPV) type 16 E6 (PDB ID: 4XR8), using molecular docking analysis software. The study also compared the results with those of standard anti-cancer agents jaceosidin (Table 6 & Fig. 4). The compounds isolated had a bottom most fixing energy extending from −6.3 to −10.1 kcal·mol−1, as shown in Table 6. It was compared to jaceosidin (–8.8 kcal·mol−1). The results of the molecular docking analysis showed that, compound 1 (−10.1 kcal·mol−1) showed the highest binding energy values compared with the standard drugs jaceosidin (–8.8 kcal·mol−1). Compound 2 has shown lower docking affinity (–6.3 kcal·mol−1) but good matching amino acid residue interactions compared to jaceosidin. After analyzing the results, it was found that the isolated compounds had similar residual interactions and docking scores with jaceosidin.

    Table 6.  Molecular docking results of ligand compounds 1 and 2 against HPV type 16 E6 (PDB ID: 4XR8).
    Ligands Binding affinity
    (kcal·mol−1)    		 H-bond Residual interactions
    Hydrophobic/electrostatic Van der Waals
    1 −10.1 ASN101 (2.25622), ASP228 (2.88341) − Asp-148, Lys-176, Lys-180, Asp-178, Ile-179, Tyr-177, Ile-334, Glu-382, Gln-336, Pro-335, Gln-73, Arg-383, Tyr-100
    2 −6.5 TRP63 (1.90011), ARG67 (2.16075), ARG67 (2.8181) Hydrophobic Pi-Sigma-TRP341 (3.76182), Hydrophobic Pi-Pi Stacked-TYR156 (4.36581), Hydrophobic Pi-Pi T-shaped-TRP63 (5.16561), Hydrophobic Pi-Pi T-shaped-TRP63 (5.44632), Hydrophobic Alkyl-PRO155 (4.34691), Hydrophobic Pi-Alkyl-TRP341 (4.11391), Hydrophobic Pi-Alkyl-ALA64 (4.61525) Glu-154, Arg-345, Asp-66, Met-331, Glu-112, Lys-16, Trp-231
    Jaceosidin −8.8 ARG146 (2.06941), GLY70 (3.49991), GLN73 (3.38801) Electrostatic Pi-Cation-ARG67 (3.93442), Hydrophobic Pi-Alkyl-PRO49 (5.40012) Tyr-342, Tyr-79, Ser-338, Arg-129, Pro-335, Leu-76, Tyr-81, Ser-74, Tyr-71, Ser-80, Glu-46
     | Show Table
    DownLoad: CSV
    Figure 4.  The 2D and 3D binding interactions of compounds against HPV type 16 E6 (PDB ID: 4XR8). The 2D and 3D binding interactions of compound 1 and 2 represent against HPV type 16 E6 enzyme, and jaceosidin (standard) against HPV type 16 E6 enzyme.
    DownLoad: Full-Size Img PowerPoint

    Hence, compounds 1 and 2 might have potential anti-cancer agents of HPV as good inhibitors. However, anti-cancer in vitro analysis has not been performed yet on HPV that causes cervical cancer agents. Promising in silico results indicate that further research could be beneficial. The 2D and 3D binding interactions of compounds 1 and 2 against human papilloma virus (HPV) type 16 E6 enzyme (PDB ID: 4XR8) are presented in Fig. 4. The binding interactions between the HPV type 16 E6 enzyme (PDB ID: 4XR8) and compound 1 (Fig. 4) and compound 2 (Fig. 4) were displayed in 3D. Compounds and amino acids are connected by hydrogen bonds (magenta lines) and hydrophobic interactions (non-green lines).

    ADMET profiling in grug-likeness and toxicity analysis

    In silico bioactivities of a drug, including drug-likeness and toxicity, predict its oral activity based on the document of Lipinski's Rule[25] was stated and the results of the current study showed that the compounds displayed conform to Lipinski's rule of five (Table 7). Therefore, both compounds 1 and 2 should undergo further investigation as potential anti-cancer agents. Table 8 shows the acute toxicity predictions, such as LD50 values and toxicity class classification (ranging from 1 for toxic, to 6 for non-toxic), for each ligand, revealing that none of them were acutely toxic. Furthermore, they were found to be similar to standard drugs. Isolated compound 1 has shown toxicity class classification 4 (harmful if swallowed), while 2 showed even better toxicity prediction giving results of endpoints such as hepatotoxicity, mutagenicity, cytotoxicity, and irritant (Table 8). All the isolated compounds were predicted to be non-hepatotoxic, non-irritant, and non-cytotoxic. However, compound 1 has shown carcinogenicity and immunotoxicity (Table 9). Hence, based on ADMET prediction analysis, none of the compounds have shown acute toxicity, so they might be proven as good drug candidates.

    Table 7.  Drug-likeness predictions of compounds computed by Swiss ADME.
    Ligands Formula Mol. Wt. (g·mol−1) NRB NHA NHD TPSA (A°2) Log P (iLOGP) Log S (ESOL) Lipinski's rule of five
    1 C30H46O3 454.68 1 3 2 57.53 3.56 −6.21 1
    2 C 9H11NO2 165.19 3 2 1 52.32 1.89 −2.21 0
    Jaceosidin C17H14O7 330.3 3 7 3 105 1.7 1 0
    NHD, number of hydrogen donors; NHA, number of hydrogen acceptors; NRB, number of rotatable bonds; TPSA, total polar surface area; and log P, octanol-water partition coefficients; Log S, turbid metric of solubility.
     | Show Table
    DownLoad: CSV
    Table 8.  Pre ADMET predictions of compounds, computed by Swiss ADME.
    Ligands Formula Skin permeation value
    (logKp - cm·s−1)    		 GI
    absorption    		 Inhibitor interaction
    BBB permeability Pgp substrate CYP1A2 inhibitor CYP2C19 inhibitor CYP2C9 inhibitor CYP2D6 inhibitor
    1 C30H46O3 −4.44 Low No No No No No No
    2 C 9H11NO2 −5.99 High Yes No No No No No
    Jaceosidin C17H14O7 −6.13 High No No Yes No Yes Yes
    GI, gastrointestinal; BBB, blood brain barrier; Pgp, P-glycoprotein; and CYP, cytochrome-P.
     | Show Table
    DownLoad: CSV
    Table 9.  Toxicity prediction of compounds, computed by ProTox-II and OSIRIS property explorer.
    Ligands Formula LD50
    (mg·kg−1)    		 Toxicity
    class    		 Organ toxicity
    Hepatotoxicity Carcinogenicity Immunotoxicity Mutagenicity Cytotoxicity Irritant
    1 C30H46O3 2,000 4 Inactive Active Active Inactive Inactive Inactive
    2 C 9H11NO2 NA NA Inactive Inactive Inactive Inactive Inactive Inactive
    Jaceosidin C17H14O7 69 3 Inactive Inactive Inactive Inactive Inactive Inactive
    NA, not available.
     | Show Table
    DownLoad: CSV

    Discussion

    Rosemary is an evergreen perennial plant that belongs to the family Lamiaceae, previously known as Rosmarinus officinalis. Recently, the genus Rosmarinus was combined with the genus Salvia in a phylogenetic study and became known as Salvia rosmarinus[28,29] and it has been used since ancient times for various medicinal, culinary, and ornamental purposes. In the field of food science, rosemary is well known as its essential oil is used as a food preservative, thanks to its antimicrobial and antioxidant properties, rosemary has many other food applications such as cooking, medicinal, and pharmacology uses[30]. According to the study, certain phytochemical compounds found in Salvia rosmarinus leaves have the potential to halt the growth of cancer cells, and pathogens or even kill them[31]. In literature, alkaloids are found mostly in fungi and are known for their strong antimicrobial properties, which make them valuable in traditional medicine[32,33]. However, in the present study, S. rosmarinus species have been shown to possess alkaloids. Most alkaloids have a bitter taste and are used to protect against antimalarial, antiasthma, anticancer, antiarrhythmic, analgesic, and antibacterial[33] also some alkaloids containing nitrogen such as vincristine, are used to treat cancer.

    Steroids occur naturally in the human body. They are hormones that help regulate our body's reaction to infection or injury, the speed of metabolism, and more. On the other hand, steroids are reported to have various biological activities such as chronic obstructive pulmonary disease (COPD), multiple sclerosis, and imitate male sex hormones[34]. It is a natural steroid compound occurring both in plants and animals[35]. Thus, were found in the present study. Terpenoids are derived from mevalonic acid (MVA) which is composed of a plurality of isoprene (C5) structural units. Terpenoids, like mono-terpenes and sesquiterpenes, are widely found in nature and more than 50,000 have been found in plants that reduce tumors and cancers. Many volatile terpenoids, such as menthol and perillyl alcohol, are used as raw materials for spices, flavorings, and cosmetics[36]. In the present study, high levels of these compounds were found in Salvia rosmarinus leaves.

    Flavonoids are a class of phenolic compounds commonly found in fruits and vegetables and are considered excellent antioxidants[37]. Similarly, the results of this study revealed that S. rosmarinus contain flavonoids. According to the literature, these flavonoids, terpenoids, and steroid activities include anti-diabetic, anti-inflammatory, anti-cancer, anti-bacterial, hepatic-protective, and antioxidant effects[36]. Tannins are commonly found in most terrestrial plants[38] and have the potential to treat cancer, and HIV/AIDS as well as to treat inflamed or ulcerated tissues. Similarly, in the present study, tannins were highly found in the presented plant. On the other hand, due to a sudden rise in the number of contagious diseases and the development of antimicrobial resistance against current drugs, drug development studies are vital to discovering novel medicinal compounds[30] and add to these cancer is a complex multi-gene disease[39] as in various cervical cancer repressor genes[11] that by proteins turn off or reduce gene expression from the affected gene to cause cervical cancer by regulating transcription and expression through promoter hypermethylation (DNMT1), leading to precursor lesions during cervical development and malignant transformation.

    In a previous study[40], a good antibacterial result was recorded at a median concentration (65 μg·mL−1). Methanol extract showed a maximum and minimum zone antibacterial result against negative bacteria E. coli 14 + 0.71 and most of the petroleum ether tests show null zone of inhibition. However, in the present study at a concentration of 100 μg·mL−1, the methanol extract demonstrated both maximum and minimum antibacterial zones against E. coli 11.47 ± 0.50. Conversely, the test conducted with petroleum ether exhibited a good zone of inhibition by increasing concentration. Further research may be necessary to determine the optimal concentration for this extract to maximize its efficacy. The results obtained in gram-negative bacteria such as E. coli, P. aeruginosa, and K. pneumoniae are consistent with previous research findings[41]. However, in the present study, Salvia rosmarinus has been found to possess high zones of inhibition with diameters of 21.37 ± 0.78 and 17.50 ± 0.50 mm antimicrobial properties against S. aureus, and S.epidermidis of gram-positive bacteria, respectively (Table 4 & Fig. 2, Supplementary Fig. S3). According to a previous study[42], the ethanolic leaf extract of Salvia rosmarinus did exhibit activity against C. albicans strains. In the present study, the antifungal activity of petroleum ether extracts from Salvia rosmarinus were evaluated against two human pathogenic fungi, namely C. albicans and A. niger. The findings showed that at a concentration of 100 μg·mL−1, the extracts were able to inhibit the growth of C. albicans 20.83 ± 0.76 resulting in a minimum zone of inhibition.

    Antimicrobial agents can be divided into groups based on the mechanism of antimicrobial activity. The main groups are: agents that inhibit cell wall synthesis, depolarize the cell membrane, inhibit protein synthesis, inhibit nucleic acid synthesis, and inhibit metabolic pathways in bacteria. On the other hand, antimicrobial resistance mechanisms fall into four main categories: limiting the uptake of a drug; modifying a drug target; inactivating a drug; and active drug efflux. Because of differences in structure, etc., there is a variation in the types of mechanisms used by gram-negative bacteria vs gram-positive bacteria. Gram-negative bacteria make use of all four main mechanisms, whereas gram-positive bacteria less commonly use limiting the uptake of a drug[43]. The present findings showed similar activity in chloroform/methanol (1:1) and methanol extracts of leaves of Salvia rosmarinus than gram-negative bacteria like P. aeruginosa and Klebsiella pneumoniae. However, Staphylococcus epidermidis of gram-positive bacteria under chloroform/methanol (1:1) extracts have similarly shown antimicrobial résistance. This occurred due to intrinsic resistance that may make use of limiting uptake, drug inactivation, and drug efflux that need further study. The structure of the cell wall thickness and thinners of gram-negative and gram-positive bacteria cells, respectively when exposed to an antimicrobial agent, there happen two main scenarios may occur regarding resistance and persistence. In the first scenario, resistant cells survive after non-resistant ones are killed. When these resistant cells regrow, the culture consists entirely of resistant bacteria. In the second scenario, dormant persistent cells survive. While the non-persistent cells are killed, the persistent cells remain. When regrown, any active cells from this group will still be susceptible to the antimicrobial agent.

    Ferreira et al.[44] explained that with molecular docking, the interaction energy of small molecular weight compounds with macromolecules such as target protein (enzymes), and hydrophobic interactions and hydrogen bonds at the atomic level can be calculated as energy. Several studies have been conducted showing natural products such as epigallocatechin-3-gallate-3-gallate (EGCG), curcumin, and genistein can be used as an inhibitor of DNMT1[45−47] . In the literature micromenic (1) is used for antimicrobial activities and for antibiotic-resistance like methicillin-resistant Staphylococcus aureus (MRSA)[48], and benzocaine (2) is used to relieve pain and itching caused by conditions such as sunburn or other minor burns, insect bites or stings, poison ivy, poison oak, poison sumac, minor cuts, or scratches[49]. However, in the present study, Salvia rosmarinus was used as a source of secondary metabolites (ligands) by using chloroform/methanol (1:1) extract of the plant leaves yielded to isolate micromeric (1) and benzocaine (2) in design structure as a candidate for drugs as inhibitors of the DNMT1 enzyme by inhibiting the activity of DNMT1 that prevent the formation of cervical cancer cells.

    Cervical cancer is one of the most dangerous and deadly cancers in women caused by Human papillomaviruses (HPV). Some sexually transmitted HPVs (type 6 owner of E6) may cause genital warts. There are several options for the treatment of early-stage cervical cancer such as surgery, nonspecific chemotherapy, radiation therapy, laser therapy, hormonal therapy, targeted therapy, and immunotherapy, but there is no effective cure for an ongoing HPV infection. In the present study, Salvia rosmarinus leaves extracted and isolated compounds 1 and 2 are one of the therapeutic drugs design structure as a candidate drug for inhibiting HPV type 16 E6 enzyme. Similarly, numerous researchers have conducted studies on the impact of plant metabolites on the treatment of cervical cancer. Their research has demonstrated that several compounds such as jaceosidin, resveratrol, berberin, gingerol, and silymarin may be active in treating the growth of cells[47].

    Small-molecule drugs are still most commonly used in the treatment of cancer[50]. Molecular docking in in silico looks for novel small-molecule (ligands) interacting with genes or DNA or protein structure agents which are still in demand, newly designed compounds are required to have a specific even multi-targeted mechanism of action to anticancer and good selectivity over normal cells. In addition to these, in the literature, anti-cancer drugs are not easily classified into different groups[51]. Thus, drugs have been grouped according to their chemical structure, presumed mechanism of action, and cytotoxic activity related to cell cycle arrest, transcription regulation, modulating autophagy, inhibition of signaling pathways, suppression of metabolic enzymes, and membrane disruption[52]. Another problem for grouping anticancers often encountered is the resistance that may emerge after a brief period of a positive reaction to the therapy or may even occur in drug-naïve patients[50]. In recent years, many studies have investigated the molecular mechanism of compounds affecting cancer cells and results suggest that compounds exert their anticancer effects by providing free electron charge inhibiting some of the signaling pathways that are effective in the progression of cancer cells[53] and numerous studies have shown that plant-based compounds such as phenolic acids and sesquiterpene act as anticancer agents by affecting a wide range of molecular mechanisms related to cancer[53]. The present investigations may similarly support molecular mechanisms provided for the suppression of metabolic enzymes of cervical cancer.

    Conclusions

    The main aim of the study was to evaluate the antimicrobial activity of different extracts of Salvia rosmarinus in vitro, and its compounds related to in silico targeting of enzymes involved in cervical cancer. The phytochemical screening tests indicated the presence of phytochemicals such as alkaloids, terpenoids, flavonoids, and tannins in its extracts. The plant also exhibited high antimicrobial activity, with varying efficacy in inhibiting pathogens in a dose-dependent manner (50−100 μg·mL−1). However, this extract exhibited a comparatively high inhibition zone in gram-positive and gram-negative bacteria had lower inhibition zones against E. coli, P. aeruginosa, and K. pneumoniae, respectively, and stronger antifungal activity 20.83 ± 0.76 mm inhibition zone against C. albicans fungi. Molecular docking is a promising approach to developing effective drugs through a structure-based drug design process. Based on the docking results, the in silico study predicts the best interaction between the ligand molecule and the protein target DNMT1 and HPV type 16 E6. Compound 1 (–8.3 kcal·mol−1) and 2 (–5.3 kcal·mol−1) interacted with DNMT1 (PDB ID: 4WXX) and the same compound 1 (–10.1 kcal·mol−1) and 2 (–6.5 kcal·mol−1) interacted with HPV type 16 E6 (PDB ID: 4XR8). Compounds 1 and 2 may have potential as a medicine for treating agents of cancer by inhibiting enzymes DNMT1 and HPV type 16 E6 sites, as well as for antimicrobial activities. None of the compounds exhibited acute toxicity in ADMET prediction analysis, indicating their potential as drug candidates. Further studies are required using the in silico approach to generate a potential drug through a structure-based drug-designing approach.

  • The authors confirm contribution to the paper as follows: all authors designed and comprehended the research work; plant materials collection, experiments performing, data evaluation and manuscript draft: Dejene M; research supervision and manuscript revision: Dekebo A, Jemal K; NMR results generation: Tufa LT; NMR data analysis: Dekebo A, Tegegn G; molecular docking analysis: Aliye M. All authors reviewed the results and approved the final version of the manuscript.

  • All data generated or analyzed during this study are included in this published article.

    • Acknowledgments

    This work was partially supported by Adama Science and Technology University under Grant (ASTU/SP-R/171/2022). We are grateful for the fellowship support from Adama Science and Technology University (ASTU), the identification of plants by Mr. Melaku Wendafrash, and pathogenic strain support from the Ethiopian Biodiversity Institute (EBI). We also thank the technical assistants of the Applied Biology and Chemistry departments of Haramaya University (HU) for their help.

  • The authors declare that they have no conflict of interest.

  • Supplemental Table S1 Nucleotide sequences of primers used in this study.
    Supplemental Table S2 Plasmids used in this study.
    Supplemental Table S3 DNA sequences of modified genes.
    Supplemental Fig. S1 Fusing predicted efflux pumps with GFP to confirm their expression.
    Supplemental Fig. S2 The impact of deletion of envR on cell growth (final OD600).
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  • Cite this article

    Peng H, Zhou L, Duan X, Wang Z, Wang Z, et al. 2022. A multi-layer genome mining and phylogenomic analysis to construct efficient and autonomous efflux system for medium chain fatty acids. Food Materials Research 2:15 doi: 10.48130/FMR-2022-0015
    Peng H, Zhou L, Duan X, Wang Z, Wang Z, et al. 2022. A multi-layer genome mining and phylogenomic analysis to construct efficient and autonomous efflux system for medium chain fatty acids. Food Materials Research 2:15 doi: 10.48130/FMR-2022-0015
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A multi-layer genome mining and phylogenomic analysis to construct efficient and autonomous efflux system for medium chain fatty acids

  • 1.

    College of Food Science and Technology, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China

  • 2.

    Department of Food Science and Technology, College of Light Industry and Food Engineering, Nanjing Forestry University, Nanjing 210037, China

  • 3.

    School of Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi 214122, China

  • Received: 08 August 2022
  • Accepted: 07 September 2022
  • Published online: 21 September 2022
Food Materials Research  2,  Article number: 15  (2022)  |  Cite this article

Abstract: Medium-chain fatty acids (MCFAs) are important components for food, pharmaceutical and fuel industries. Nevertheless, engineering microorganisms to produce MCFAs often induces toxicity and stresses towards host strains, which could be alleviated via accelerating the export of MCFAs from cells. However, current secretory systems are inefficient and require inducible promoters. Here, a multi-layer genome mining and phylogenomic analysis was developed to identify efficient efflux transporters. Firstly, based on the genomic mining of 397 strains throughout various representative species, the evolutionary history of efflux transporters was recapitulated, and further experimental analysis revealed that acrE from Citrobacter exhibited the best performance. Secondly, according to the further mining of 797 Citrobacter genomes and 1084 Escherichia genomes, a detailed phylogenomic analysis of efflux transporter-centric genomic vicinities was performed. This led to the identification of efficient efflux pump combination acrE and acrF. These efflux pumps were then combined with the quorum-sensing circuit from Enterococcus faecalis to regulate MCFA efflux in an autonomous manner, which achieved a 4.9-fold boost in MCFA production and firstly demonstrated the efficient and autonomous efflux pump specially for MCFAs. The integrative omics technologies described here are enabling the utilization of the increasingly large database and the effective mining of target gene diversities.

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    INTRODUCTION

    • Medium chain fatty acids (MCFAs) represent molecules with one carboxylic acid bound to a medium alkyl chain (C6-C10), constituting important food constituents and essential feedstocks of biofuels or oleo-chemical industries. Compared to their long-chain counterparts with a long alkyl chain (C12 or more), the shorter chain lengths confer MCFAs with significant characters such as higher carbon conversion yield and lower freezing/cloudy point, suggesting their potential as substitutes for fossil fuels[1,2]. Furthermore, MCFAs exhibit other unique physicochemical properties, for instance, little tendency to deposit as body fat, weight control benefits, antimicrobial effects, immune-modulating effects, and improving clinical symptoms, constituting their unique advantages as food constituents or even chemotherapeutic agents[3,4].

      Currently, natural source extraction or petrol-based synthesis are the main processes by which to obtain MCFAs. In nature, MCFAs present only in coconut and palm kernel with low concentrations, ranging from 7.9% to 15% of total fatty acids. Due to the seasonal/regional limitations, long breeding cycles and low concentrations, plant extraction is not amendable for industrialization[2,5,6]. Besides, the growing scarcity of fossil fuels and environmental anxiety of rising petrol-based manufacturing costs, and owing to food safety considerations, this manner is unfavorable in the food and pharmaceutical industries[1]. Accordingly, efficient, scalable and sustainable procedures to obtain MCFAs from cheap and renewable resources are required as an impetus towards MCFAs more widespread adoption.

      Numerous advantages inherent to microbial conversion procedures, for instances, rapid replication speeds, the capability of utilizing renewable feedstocks or acting during mile pressures and temperatures, and easy realization of large-scale fermentation[2,5,7−9], means it is an attractive alternative for fatty acid production. Previous pioneering studies have firstly demonstrated efficient MCFA production at 1.1−1.3 g/L via utilizing reversal of β-oxidation cycle (r-BOX) associate with leveraging thioesterases[10−12]. A series of our studies achieved the highest titer (3.8−15.6 g/L) reported to date through identifying pathway bottlenecks[13], satisfying redox cofactor requirement[14], or constructing artificial micro-aerobic metabolism[15]. All of these results have illustrated that E. coli-based bioconversion so far presents a good chassis to produce MCFAs.

      Despite the apparent capability for microbial production of MCFAs, product toxicity is a common issue in strain engineering, which would result in physiological perturbations including reducing cell viability and membrane integrity, inducing membrane stress responses and losing proton motive force[16−18]. One promising strategy to abate this problem is improving the transport speed of MCFAs from cells, and our previous study has demonstrated that expressing transporter from E. coli responsible for accelerating MCFA export could improve the production of MCFAs[19]. However, current secreting system is constructed based on the endogenous transporters derived from E. coli, which is inefficient and requires inducible promoters for conducting the transport function. This is still incompatible with large-scale production.

      The rapid buildup of genomic information has revealed that metabolic abilities of virtually all organisms are vastly underappreciated[20,21], and sequenced microbial genomes may contain numerous efflux pumps and offer a vastly unexplored resource for mining novel pumps. Here, in order to efficiently mine genomes during large genomic datasets, a multi-layer genome mining and phylogenomic analysis was developed to screen a library of uncharacterized heterologous pumps among over 2000 microbial genomes. This led to the identification of efficient efflux pump combination acrE and acrF from Citrobacter tructae. When combining with the quorum-sensing (QS) circuit from Enterococcus faecalis, MCFA efflux presented as an autonomous behavior without inducer supplementation or human supervision, and this achieved a 4.9-fold boost in MCFA production.

    MATERIALS AND METHODS

      General procedures

    • E. coli JM109 and BL21 (DE3) were used for all molecular experiments and bio-catalysis, respectively. The plasmids of pACYCDuet-1, pCDFDuet-1, and pETDuet-1 (Novagen, Darmstadt, Germany) used in this study required the supplementation of 20 μg/mL of chloramphenicol, 40 μg/mL of streptomycin, 100 μg/mL of ampicillin, respectively, to maintain in the same cell. T4 DNA ligase, FastDigest restriction enzymes, and Phusion DHA polymerase (Novagen, Darmstadt, Germany) were employed to perform standard molecular manipulations. UV/vis spectrophotometer (UVmini-1240, Shimadzu, kyoto, Japan) was utilized to measure cell growth (OD600).

      General phylogenomic reconstruction of MCFA transporter families

    • Genomes for general phylogenomic analysis of MCFA transporter families such as AcrE, MdtE, and MdtC, were selected from 397 representative species of prokaryotic microorganisms. These genome assemblies, which were obtained from NCBI FTP site based on the screening parameters such as completeness (≥ 80%), contig numbers (cut-off ≤ 400), N50 (≥ 20,000 bases)[22], were annotated through Rapid Annotation using Subsystem Technology[23]. The blast database was created based on these annotated genome assemblies via the makeblastdb program in Linux, and the executing parameters were set as dbtype prot, and parse_seqids, respectively. The amino acid sequences of AcrE, MdtE, and MdtC from E. coli were utilized as queries for bioinformatics screening to predict target regions responsible for MCFA efflux within the constructed blast database associated with the parameters such as E-value cutoff of 1E-12 and bit score cutoff of 200. MUSCLE v3.8.31 was then used to align, trim and concatenate the obtained homologs[24], and IQ-TREE was utilized for phylogenomic reconstruction based on the resulting matrix[25]. During phylogenomic reconstruction, ModelFinder was used to identify the suitable model of substitution, and ultrafast bootstrap was set as 10,000 replicates.

      Analysis of detailed evolutionary divergence in Citrobacter and Escherichia species

    • In order to comprehensively analyze transporter-centric phylogenies which contained the genomic context surrounding the target gene acrE, genomes deposited as Citrobacteria or Escherichia were retrieved from the NCBI FTP site with the appropriate filter parameters such as contig number (cut-off ≤ 400), N50 (≥ 20,000 bases), and completeness (≥ 80%), resulting in 797 genomes of Citrobacteria and 1,084 genomes of Escherichia. Based on this, the evolutionary relationships focusing on the genomic context encompassing acrE gene among different organisms were analyzed through CORASON[21,26] via retrieving gene neighborhood of acrE up to 20 genes upstream and downstream from genomes.

      Construction of MCFA efflux pump library

    • Primers and plasmids utilized here are shown in Supplemental Tables S1 and S2, respectively. In order to clearly annotate each primer or gene, all the names of these genetic parts contained both abbreviated species and gene names. The plasmid of pCDFD-T7-bktB-T7-fadB-T7-ter-T7-ydiI-T7-acs, which was used for MCFA production, was derived from our previous study[19]. All the predicted efflux pumps were amplified from the genomic DNA prepared by Ezup Column Bacteria Genomic DNA Purification Kit (Sangon Biotech, Shanghai, China), or synthesized by GenScript (Nanjing, China). Primers Pf_PA-others(NdeI) and Pr_PA-others(XhoI), Pf_PA-mdtC(NdeI) and Pr_PA-mdtC(XhoI), Pf_SC-mdtC(NdeI) and Pr_SC-mdtC(XhoI), Pf_SE-mdtC(NdeI) and Pr_SE-mdtC(XhoI), Pf_SE-acrE(NdeI) and Pr_SE-acrE(XhoI), Pf_SE-acrA(NdeI) and Pr_SE-acrA(XhoI) were used to amplify other efflux RND transporter periplasmic adaptor subunit families of Pseudomonas aeruginosa, mdtC of Pseudomonas aeruginosa, mdtC of Streptomyces coelicolor, and mdtC of Salmonella enterica, acrE of Salmonella enterica, acrA of Salmonella enterica from corresponding genomic DNA into NdeI/XhoI site of pETDuet-1 through Gibson assembly kit (New England Biolabs), resulting in plasmids of pETD-PA-others, pETD-PA-mdtC, pETD-SC-mdtC, pETD-SE-mdtC, pETD-SE-acrE, pETD-SE-acrA, respectively.

      Primers Pf_CTR-acrE(NdeI) and Pr_CTR-acrE(XhoI), Pf_CTR-acrA(NdeI) and Pr_CTR-acrA(XhoI), Pf_CTR-mdtE(NdeI) and Pr_CTR-mdtE(XhoI), Pf_CTE-acrE(NdeI) and Pr_CTE-acrE(XhoI), Pf_CTE-acrA(NdeI) and Pr_CTE-acrA(XhoI), Pf_ES-acrE(NdeI) and Pr_ES-acrE(XhoI), Pf_ES-acrA(NdeI) and Pr_ES-acrA(XhoI), Pf_BA-acrE(NdeI) and Pr_BA-acrE(XhoI), Pf_BA-acrA(NdeI) and Pr_BA-acrA(XhoI), Pf_CU-acrE(NdeI) and Pr_CU-acrE(XhoI), Pf_CU-acrA(NdeI) and Pr_CU-acrA(XhoI), Pf_KV-acrE(NdeI) and Pr_KV-acrE(XhoI), Pf_KV-acrA(NdeI) and Pr_KV-acrA(XhoI), Pf_KV-others(NdeI) and Pr_KV-others(XhoI), Pf_RT-acrA(NdeI) and Pr_RT-acrA(XhoI), Pf_RT-others(NdeI) and Pr_RT-others(XhoI), Pf_AG-others(NdeI) and Pr_AG-others(XhoI), Pf_SF-others(NdeI) and Pr_SF-others(XhoI), Pf_CR-others(NdeI) and Pr_CR-others(XhoI), Pf_MP-others(NdeI) and Pr_MP-others(XhoI), Pf_ZA-acrA(NdeI) and Pr_ZA-acrA(XhoI) were used to amplify acrE of Citrobacter tructae, acrA of Citrobacter tructae, mdtE of Citrobacter tructae, acrE of Citrobacter telavivum, acrA of Citrobacter telavivum, acrE of Enterobacter soli, acrA of Enterobacter soli, acrE of Buttiauxella agrestis, acrA of Buttiauxella agrestis, acrE of Cronobacter universalis, acrA of Cronobacter universalis, acrE of Klebsiella variicola, acrA of Klebsiella variicola, other efflux RND transporter periplasmic adaptor subunit families of Klebsiella variicola, acrA of Raoultera terrigena, other efflux RND transporter periplasmic adaptor subunit families of Raoultera terrigena, other efflux RND transporter periplasmic adaptor subunit families of Acetobacter ghanensis, other efflux RND transporter periplasmic adaptor subunit families of Solimonas flava, other efflux RND transporter periplasmic adaptor subunit families of Caulobacter rhizosphaerae, other efflux RND transporter periplasmic adaptor subunit families of Methylibium petroleiphilum, acrA of Zavarzinia aquatilis from corresponding pUC57 derived plasmids (GenScript, Nanjing, China) into NdeI/XhoI site of pETDuet-1 through Gibson assembly kit (New England Biolabs, Ipswich, UK), resulting in plasmids of pETD-CTR-acrE, pETD-CTR-acrA, pETD-CTR-mdtE, pETD-CTE-acrE, pETD-CTE-acrA, pETD-ES-acrE, pETD-ES-acrA, pETD-BA-acrE, pETD-BA-acrA, pETD-CU-acrE, pETD-CU-acrA, pETD-KV-acrE, pETD-KV-acrA, pETD-KV-others, pETD-RT-acrA, pETD-RT-others, pETD-AG-others, pETD-SF-others, pETD-CR-others, pETD-MP-others, pETD-ZA-acrA, respectively.

      To fuse each predicted efflux pump to GFP individually, the stop codon of each predicted efflux pump was removed and two rounds of PCR was used to introduce a Gly-Ser-Gly linker between these two genes[27]. During the first round, two sets of primers such as Pf_PA-others-GSG-GFP(EcoNI) and Pr_PA-others-GSG-GFP, Pf_PA-others-GSG-GFP and Pr_PA-others-GSG-GFP(XhoI) were used. Secondly, primers Pf_PA-others-GSG-GFP(EcoNI)/Pr_fused-GFP(XhoI) were used to connect two above PCR products via overlapping extension PCR, resulted in pACYC-PA-others-GSG-GFP harboring fused gene construct encoding PA_others, three amino acid linker, and GFP. Similarly, Pf_PA-mdtC-GSG-GFP(EcoNI)/Pr_PA-mdtC-GSG-GFP and Pf_PA-mdtC-GSG-GFP/Pr_fused-GFP(XhoI), Pf_SC-mdtC-GSG-GFP(EcoNI)/Pr_SC-mdtC-GSG-GFP and Pf_SC-mdtC-GSG-GFP/Pr_fused-GFP(XhoI), Pf_SE-mdtC-GSG-GFP(EcoNI)/Pr_SE-mdtC-GSG-GFP and Pf_SE-mdtC-GSG-GFP/Pr_fused-GFP(XhoI), Pf_SE-acrE-GSG-GFP(EcoNI)/Pr_SE-acrE-GSG-GFP and Pf_SE-acrE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_SE-acrA-GSG-GFP(EcoNI)/Pr_SE-acrA-GSG-GFP and Pf_SE-acrA-GSG-GFP/Pr_fused-GFP(XhoI), Pf_CTR-acrE-GSG-GFP(EcoNI)/Pr_CTR-acrE-GSG-GFP and Pf_CTR-acrE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_CTR-acrA-GSG-GFP(EcoNI)/Pr_CTR-acrA-GSG-GFP and Pf_CTR-acrA-GSG-GFP/Pr_fused-GFP(XhoI), Pf_CTR-mdtE-GSG-GFP(EcoNI)/Pr_CTR-mdtE-GSG-GFP and Pf_CTR-mdtE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_CTE-acrE-GSG-GFP(EcoNI)/Pr_CTE-acrE-GSG-GFP and Pf_CTE-acrE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_ES-acrE-GSG-GFP(EcoNI)/Pr_ES-acrE-GSG-GFP and Pf_ES-acrE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_ES-acrA-GSG-GFP(EcoNI)/Pr_ES-acrA-GSG-GFP and Pf_ES-acrA-GSG-GFP/Pr_fused-GFP(XhoI), Pf_BA-acrE-GSG-GFP(EcoNI)/Pr_BA-acrE-GSG-GFP and Pf_BA-acrE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_BA-acrA-GSG-GFP(EcoNI)/Pr_BA-acrA-GSG-GFP and Pf_BA-acrA-GSG-GFP/Pr_fused-GFP(XhoI), Pf_CU-acrE-GSG-GFP(EcoNI)/Pr_CU-acrE-GSG-GFP and Pf_CU-acrE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_CU-acrA-GSG-GFP(EcoNI)/Pr_CU-acrA-GSG-GFP and Pf_CU-acrA-GSG-GFP/Pr_fused-GFP(XhoI), Pf_KV-acrE-GSG-GFP(EcoNI)/Pr_KV-acrE-GSG-GFP and Pf_KV-acrE-GSG-GFP/Pr_fused-GFP(XhoI), Pf_KV-acrA-GSG-GFP(EcoNI)/Pr_KV-acrA-GSG-GFP and Pf_KV-acrA-GSG-GFP/Pr_fused-GFP(XhoI), Pf_KV-others-GSG-GFP(EcoNI)/Pr_KV-others-GSG-GFP and Pf_KV-others-GSG-GFP/Pr_fused-GFP(XhoI), Pf_RT-acrA-GSG-GFP(EcoNI)/Pr_RT-acrA-GSG-GFP and Pf_RT-acrA-GSG-GFP/Pr_fused-GFP(XhoI), Pf_RT-others-GSG-GFP(EcoNI)/Pr_RT-others-GSG-GFP and Pf_RT-others-GSG-GFP/Pr_fused-GFP(XhoI), Pf_AG-others-GSG-GFP(EcoNI)/Pr_AG-others-GSG-GFP and Pf_AG-others-GSG-GFP/Pr_fused-GFP(XhoI), Pf_SF-others-GSG-GFP(EcoNI)/Pr_SF-others-GSG-GFP and Pf_SF-others-GSG-GFP/Pr_fused-GFP(XhoI), Pf_CR-others-GSG-GFP(EcoNI)/Pr_CR-others-GSG-GFP and Pf_CR-others-GSG-GFP/Pr_fused-GFP(XhoI), Pf_MP-others-GSG-GFP(EcoNI)/Pr_MP-others-GSG-GFP and Pf_MP-others-GSG-GFP/Pr_fused-GFP(XhoI), Pf_ZA-acrA-GSG-GFP(EcoNI)/Pr_ZA-acrA-GSG-GFP and Pf_ZA-acrA-GSG-GFP/Pr_fused-GFP(XhoI) were used to fuse other predicted efflux pumps to GFP, this resulted in pACYC-PA-mdtC-GSG-GFP, pACYC-SC-mdtC-GSG-GFP, pACYC-SE-mdtC-GSG-GFP, pACYC-SE-acrE-GSG-GFP, pACYC-SE-acrA-GSG-GFP, pACYC-CTR-acrE-GSG-GFP, pACYC-CTR-acrA-GSG-GFP, pACYC-CTR-mdtE-GSG-GFP, pACYC-CTR-acrE-GSG-GFP, pACYC-ES-acrE-GSG-GFP, pACYC-ES-acrA-GSG-GFP, pACYC-BA-acrE-GSG-GFP, pACYC-BA-acrA-GSG-GFP, pACYC-CU-acrE-GSG-GFP, pACYC-CU-acrA-GSG-GFP, pACYC-KV-acrE-GSG-GFP, pACYC-KV-acrA-GSG-GFP, pACYC-KV-others-GSG-GFP, pACYC-RT-acrA-GSG-GFP, pACYC-RT-others-GSG-GFP, pACYC-AG-others-GSG-GFP, pACYC-SF-others-GSG-GFP, pACYC-CR-others-GSG-GFP, pACYC-MP-others-GSG-GFP, pACYC-ZA-acrA-GSG-GFP, respectively.

      Primers Pf_CTR-envR(NdeI) and Pr_CTR-envR(XhoI) were used to amplify envR of Citrobacter tructae from corresponding pUC57 derived plasmids (GenScript, Nanjing, China) into NdeI/XhoI site of pETDuet-1 through Gibson assembly kit (New England Biolabs), resulting in plasmids of pETD-CTR-envR. Primers Pf_EC-envR(NdeI) and Pr_EC-envR(XhoI) were used to amplify envR of E. coli from genomic DNA into NdeI/XhoI site of pETDuet-1 through Gibson assembly kit (New England Biolabs), resulting in plasmids of pETD-EC-envR. The lambda-red recombination-based method[28] was used to construct the EC_envR knockout mutant. Briefly, primers Pf_KanFRT-EC-envR and Pr_ KanFRT-EC-envR were used to amplify the FRT-flanked kanamycin resistance gene (KanFRT) from the plasmid pKD13[28], which included 40 bp of homology with the ends of EC-envR in both sides. This design would facilitate integration of this cassette into the corresponding sites. After transforming these cassettes, proper colonies were verified via colony PCR and following sequencing. The FRT-flanked Kan would be excised by FLP recombinase via pCP20 plasmid[28]. Primers Pf_CTR-acrF(G)/Pr_CTR-acrF(G), and Pf_pETD-CTR-acrE(G)/ Pr_pETD-CTR-acrE(G) were used to amplify CTR-acrF of Citrobacter tructae from corresponding pUC57 derived plasmids (GenScript, Nanjing, China) into pETD-CTR-acrE through Gibson assembly kit (New England Biolabs), resulting in plasmids of pETD-CTR-acrE-CTR-acrF.

      Construction of autonomous MCFA secreting systems

    • Primers and plasmids utilized here were shown in Supplemental Tables S1 and S2, respectively. Primer sets of Pf_Ptrc-PrgX(PETD)/Pr_Ptrc-PrgX(Pi), Pf_Pi-ccfA(G)/Pr_ccfA(G), Pf_prgZ(G)/Pr_prgZ(G), Pf_PprgQ-CTR-acrE(G)/Pr_PprgQ-CTR-acrE(G), and Pf_PprgQ-CTR-acrF(G)/Pr_PprgQ-CTR-acrF(PETD) were used to amplify prgX under Ptrc promoter, ccfA under Pi promoter, prgZ under P1 promoter, CTR_acrE under PprgQ promoter, and CTR_acrF under PprgQ promoter from pACYC-Ptrc-prgX, pETD-Ptrc-ccfA-Ptrc-prgZ, and corresponding pUC57 derived plasmids (GenScript, Nanjing, China) into EcoNI/XhoI site of pETDuet-1 through Gibson assembly kit (New England Biolabs) (i = 1−6). This would result in the plasmid of pETD-Ptrc-prgX-Pi-ccfA-PprgQ-CTR-acrE-PprgQ-CTR-acrF (i = 1−6).

      Fluorescence intensity measurement

    • During the shake flask culture, LB medium associate with corresponding antibiotics was firstly utilized to culture engineered strains overnight (37 °C, 220 rpm orbital shaking). MOPS minimal medium supplemented with 10 g/L D-glucose was then used for re-culture with OD600 of 0.1, and the culture condition was then altered to 30 °C when OD600 reached 0.6[29]. At this time, 1 mM IPTG was added to induce the expression. Cell fluorescence and cell density were measured after 30 h of culture using Cytation 3 imaging reader system (BioTek, Winooski, USA).

      Analytical methods

    • Each experiment was conducted in triplicate and the deviation was represented by the error bar. The extracellular and intracellular MCFA measurement was conducted based on our previous study[19]. Briefly, the supernatant of 1 mL cell culture was obtained (10,000 g, 5 min) for extracellular MCFA measurement, whereas the cell pellet of 1 mL cell culture was recovered (10,000 g, 5 min) with 1 mL deionized water for intracellular MCFA measurement. Based on our previous studies[13,14], gas chromatograph mass spectrometer (GC-MS) QP2010 Plus (Shimadzu) equipped with GC-MS column (Rtx-5 MS capillary with length of 30 m, film thickness of 0.25 μm, diameter of 0.25 mm) was utilized for the following free fatty acid extraction and quantification.

      Culture conditions

    • MOPS minimal medium supplemented with 15 g/L D-glucose was used to perform the fermentations as demonstrated in our previous studies[13,14]. The overnight incubation in LB medium was firstly conducted to prepare the pre-inocula, which were then diluted into 50 mL MOPS minimal medium with an initial OD600 of 0.1 in 500-mL flasks. The parameters of 37 °C and 220 rpm orbital shaking were used to conduct the fermentation. The culture temperature was then altered to 30 °C with the supplementation of 1 mM IPTG when the OD600 reached 0.5−0.6. The concentration of MCFAs, including both extracellular and intracellular levels, was measured after a fermentation time of 48 h.

      Batch culture

    • Seed culture, which was performed on rotary shakers overnight (37 °C, 220 rpm), was then diluted into 3-L BioFlo 115 fermentor (New Brunswick Scientific Co, Edison, NJ, USA) as an OD600 of 0.1. This fermentor included 1.5 L MOPS minimal medium associate with corresponding antibiotics and 10 g/L D-glucose. During the fermentation, concentrated D-glucose (800 g/L) was used to maintain D-glucose concentration at 5 g/L. The cultivation temperature was changed to 30 °C when OD600 reached 0.5−0.6 associoate with the supplementation of 1 mM IPTG. 12.5% NH4OH solution or phosphoric acid solution was used to keep the pH at 6.5, and the agitation cascade (200−500 rpm) was utilized to keep the dissolved oxygen concentration at 30% saturation. Each MCFA fermentation was conducted in triplicate, and the deviation was represented via the error bar.

    RESULTS

      General evolutionary recapitulation of MCFA transporter families

    • Our previous secreting system screened numerous endogenous transporters including famous AcrAB-TolC system and other triphosphate (ATP)-binding cassette superfamily or annotated multidrug efflux superfamily, and found that the overexpression of resistance nodulation cell division family transporter acrE, mdtE and mdtC together with the deletion of multidrug efflux pump cmr from E. coli achieved the best performance[19]. However, owing to the rapid accumulation of genomic information, other sequenced microbial genomes may contain numerous efflux pumps and present a greatly unexplored resource for mining novel pumps. In order to screen the most favorable candidates during large genomic datasets, a multi-layer genome mining and phylogenomic analysis was developed. Firstly, the general evolutionary recapitulation of MCFA transporter families was investigated by comprehensive and systematic phylogenomics, and the input of the customized blast database for this analysis was constructed with 397 genomes belonging to different representative prokaryotic species.

      Our previous study identified that acrE, mdtE and mdtC from E. coli were responsible for accelerating MCFA export[19]. Hence, the amino acid sequences of AcrE, MdtE, and MdtC from E. coli were utilized as queries for the bioinformatics screen to predict target regions responsible for MCFA efflux within the constructed blast database. This screen was performed under E-value cutoff of 1E-12 and bit score cutoff of 200. The homology hits for AcrE, MdtE, and MdtC were 287, 284, 1446, respectively, among the constructed blast database, and the evolutionary relationships of AcrE, MdtE, and MdtC homology hits are presented in Figs 1, 2 & 3, respectively.

      Figure 1. 

      The evolutionary relationships of AcrE homology hits. When using AcrE as a query, the evolutionary relationships of 287 homology hits were analyzed and each homolog information was confirmed with BLASTp. It was found that the homology hits of AcrE mainly included AcrE families, AcrA families, MdtE families, and other efflux RND transporter periplasmic adaptor subunits. The violet and red indicated the selected predicted efflux pumps for further analysis.

      Figure 2. 

      The evolutionary relationships of MdtE homology hits. When using MdtE as a query, the evolutionary relationships of 284 homology hits were analyzed and each homolog information was confirmed with BLASTp. It was found that the homology hits of MdtE also mainly comprised AcrE families, AcrA families, MdtE families, and other efflux RND transporter periplasmic adaptor subunits. The colored areas indicate the relationships between Citrobacteria and E. coli species.

      Figure 3. 

      The evolutionary relationships of MdtC homology hits. (a) When using MdtC as a query, the evolutionary relationships of 1,446 homology hits were analyzed and each homolog information was confirmed with BLASTp. These homology hits could be divided into seven different enzyme families such as MdtC, MdtB, AcrD, AcrF, MdtF, AcrB, and CusA families. (b) The evolutionary history of MdtC families was further recapitulated. The colored areas indicate the selected predicted efflux pumps for further analysis.

      As seen in Fig. 1, the homologues of AcrE were distributed in 134 genomes, and most genomes contained more than one homology hit, indicating the deep genomic mining for the target gene. The information of these homologues was then confirmed via BLASTp. It was found that the homology hits of AcrE mainly included AcrE families, AcrA families, MdtE families, and other efflux RND transporter periplasmic adaptor subunits such as MexX, MexA. Whereas the homologues of MdtE were also distributed in 134 genomes, and most genomes also contained multiple homology hits (Fig. 2). Similarly, the homology hits of MdtE also mainly comprised AcrE families, AcrA families, MdtE families, and other efflux RND transporter periplasmic adaptor subunits, indicating the analogous evolutionary relationships between AcrE and MdtE. MdtC presented totally different evolutionary history compared with AcrE and MdtE, and the 1446 homology hits were distributed in 236 genomes (Fig. 3a). These homology hits could be divided into seven different enzyme families such as MdtC, MdtB, AcrD, AcrF, MdtF, AcrB, and CusA families, and the evolutionary history of MdtC was further recapitulated (Fig. 3b).

      When utilizing AcrE (Fig. 1) or MdtE (Fig. 2) as a query to mining genomes, homologues from Citrobacteria, Salmonella, and Enterobacteria species presented the closest evolutionary relationships with Escherichia species among both AcrE and AcrA families; Among the MdtE families, only the homologue from Citrobacteria tructae and Escherichia species existed; Whereas among efflux RND transporter periplasmic adaptor subunit families, merely homologues from partial Escherichia species were existing along with other species such as Pseudomonas, Acetobacteria species.

      When using MdtC as a query to mining genomes, homologues from Citrobacteria, Enterobacteria, and Salmonella species presented the closest evolutionary relationships with Escherichia species, and Enterobacteria species exhibited closer evolutionary relationships than Salmonella species among MdtC families (Fig. 3b), whereas these two species bestowed different evolutionary behaviors when using AcrE or MdtE as queries. Furthermore, the taxonomic relationship of each species was defined via constructing a species tree with the amino acid sequences of their RNA polymerase beta subunits (RpoB) (Fig. 4). It was found that Salmonella species exhibited closer evolutionary relationship with Escherichia species than Citrobacteria species, which was different when using AcrE, MdtE, or MdtC as queries, suggesting the interesting engineering targets of homologues from Citrobacteria species.

      Figure 4. 

      The taxonomic relationship of each species used for general evolutionary recapitulation. The taxonomic relationship of each species was defined via constructing a species tree with the amino acid sequences of their RNA polymerase beta subunits (RpoB). It was found that Salmonella species exhibited closer evolutionary relationship with Escherichia species than Citrobacteria species, which was different when using AcrE, MdtE, or MdtC as queries.

      Construction of MCFA efflux pump library

    • The above bioinformatic metric rendered the ability to rank the entire set of pumps and pick a portion that manifested a uniform distribution of candidates. To construct the library, the predicted efflux pumps were amplified from the genomic DNA or synthesized by GenScript (Nanjing, China), and this library harbored 29 predicted efflux pumps, all of which had not been previously characterized for MCFA transport. This library mainly focused on AcrE or MdtE homologues, as in our previous study[19] demonstrated that these two transporters derived from E. coli exhibited better performance than MdtC. Besides, due to the large size of MdtC (> 3,000 bp), it is costly and not convenient to amplify or synthesize numerous MdtC homologues.

      AcrE or mdtE homologues from Citrobacter tructae and Citrobacter telavivum among AcrE families, AcrA families, and MdtE families were selected, as we observed that these species presented different evolutionary trajectories. For instance, under the same search parameters, when using AcrE as a query, suitable hits were obtained and occurred in similar evolutionary positions among the AcrE families (Fig. 1); Whereas only suitable hits from Citrobacter tructae were observed when using MdtE as a query among the MdtE family; When using MdtC as a query, suitable hits were obtained in both species, yet they occurred in different evolutionary positions among the MdtC families (Fig. 3). Other AcrE/MdtE homologues were selected from Salmonella enterica, Enterobacter soli, Buttiauxella agrestis and Cronobacter universalis among AcrE or AcrA families, Klebsiella variicola among AcrE families, AcrA families, or other efflux RND transporter periplasmic adaptor subunit families, Raoultera terrigena among AcrA families or other efflux RND transporter periplasmic adaptor subunit families, Pseudomonas aeruginosa, Acetobacter ghanensis, Solimonas flava, Caulobacter rhizosphaerae, and Methylibium petroleiphilum among other efflux RND transporter periplasmic adaptor subunit families, Zavarzinia aquatilis among AcrA families. Several MdtC homologues from Citrobacter tructae, Citrobacter telavivum, Pseudomonas aeruginosa, Streptomyces coelicolor, and Salmonella enterica were also selected for further investigation.

      To efficiently identify suitable transporters with the capability to export MCFAs from cells, a simple test system constructed in our previous study[19], was utilized. This test system consisted of two individual plasmids (Fig. 5b), which could stably maintain in one cell owing to their distinct replication origins and antibiotic resistance markers. The first plasmid pCDFD-T7-bktB-T7-fadB-T7-ter-T7-ydiI-t7-acs carrying thiolase (BktB) of Ralstonia eutropha, 3-hydroxyacyl-CoA dehydrogenase/enoyl-CoA hydratase (FadB) of E. coli, transenoyl-CoA reductase (Ter) of Euglena gracilis, thioesterase (YdiI) of E. coli, and acetyl-CoA synthetase (Acs) of E. coli, was responsible for MCFA production (Fig. 5a), whereas the other pETDuet-1 derived plasmid was utilized for the expression of various bacterial transporters.

      Figure 5. 

      Construction of MCFA efflux pump library. (a) Microbial production of MCFAs from D-glucose via the reversal of β-oxidation cycle and transporter engineering. (b) Illustration of the test system. This test system consisted of two individual plasmids. The first plasmid pCDFD-T7-bktB-T7-fadB-T7-ter-T7-ydiI-t7-acs was responsible for MCFA production, whereas the other pETDuet-1 derived plasmid was utilized for the expression of various bacterial transporters. (c) Effect of predicted efflux pump engineering on extracellular, intracellular and total MCFA production. Each experiment in this study was conducted in triplicate and error bars signify standard deviation (SD) with 95% confidence interval (CI).

      A set of 29 predicted efflux pumps were then overexpressed individually, and three different measurements including the extracellular MCFA concentration, the intracellular MCFA concentration, and the total MCFA concentration, were used to screen each target pump. Firstly, as these candidates have not been characterized previously, to assure their reliable gene expression, GFP was tagged to each candidate to measure translational output and normalized fluorescence measurements were conducted for each one by dividing measured fluorescence values to the OD600 of that well (Supplemental Fig. S1). As seen from Fig. 5c, it was found that homologues among AcrE/MdtE families exhibited better performance than among MdtC families and AcrA families, and the top-performing candidate pumps existed in Citrobacteria species.

      Detailed evolutionary divergence of MCFA transporter families in Citrobacter species

    • Although the top-performing efflux pumps exist in Citrobacteria species, AcrE homologues from different Citrobacteria species exhibited dissimilar behaviors. Besides, MCFA transporter homologues from Citrobacteria species occurred in divergent evolutionary positions, suggesting the necessity for future engineering efforts. Hence, genomes deposited as Citrobacteria were retrieved from the NCBI FTP site with the appropriate filter parameters such as contig number (cut-off ≤ 400), N50 (≥ 20,000 bases), and completeness (≥ 80%) to remove low-quality genomes and eliminate redundancy at the strain level. This resulted in a subset of 797 genomes used hereafter, to comprehensively analyze transporter-centric phylogenies which contained the genomic context surrounding target genes.

      Analysis of this AcrE-centric phylogenetic tree exhibited in Fig. 6a revealed that EnvR homologues, a predicted AcrEF/EnvCD operon regulator, were present in most Citrobacteria species. Hence, we then asked whether this transcriptional regulator could further affect MCFA production. It was found that overexpression of EnvR from Citrobacter tructae decreased extracellular MCFA production by 32% (Fig. 6b), suggesting that EnvR might act as a repressor. The AcrE-centric phylogenetic tree based on genomes of Escherichia species were then constructed, and 1084 genomes deposited as Escherichia were retrieved from the NCBI FTP site. This phylogenetic tree also manifested that EnvR homologues were existing in most Escherichia species (Fig. 7a), and it was observed that overexpression of EnvR from E. coli decreased extracellular MCFA production by 39%, whereas the deletion of endogenous EnvR further increased extracellular MCFA production by 168% associated with the overexpression of EnvR from Citrobacter tructae (Fig. 7b).

      Figure 6. 

      Detailed evolutionary divergence of MCFA transporter families in Citrobacter species. (a) Analysis of this AcrE-centric phylogenetic tree based on genomes from Citrobacter species. This revealed that EnvR homologues, a predicted AcrEF/EnvCD operon regulator, were present in most Citrobacteria species. (b) Effect of transcriptional regulator EnvR engineering on MCFA production. CT_EnvR indicated envR of Citrobacter tructae. Experiments in this study were conducted in triplicate and error bars signify SD with 95% CI.

      Figure 7. 

      Detailed evolutionary divergence of MCFA transporter families in Escherichia species. (a) Analysis of the AcrE-centric phylogenetic tree based on genomes of Escherichia species. This phylogenetic tree also manifested that EnvR homologues were existing in most Escherichia species. (b) Effect of transcriptional regulator EnvR engineering on MCFA production. EC_EnvR indicated envR of E. coli; CT_EnvR indicated envR of Citrobacter tructae; CT_AcrE indicated acrE of Citrobacter tructae; CT_AcrF indicated acrF of Citrobacter tructae. Experiments in this study were conducted in triplicate and error bars signify SD with 95% CI.

      Although the deletion of endogenous EnvR rendered the increase of extracellular MCFA production, we also observed the decrease of the cell growth (Supplemental Fig. S2). This would exert a negative influence on the total MCFA production and indicated that EnvR was not only involved in MCFA export, but also possessed unknown essential functions. In order to prevent the deactivation of the entire regulon by deleting EnvR, we sought to investigate whether there was a new protein potentially involved in MCFA export. As EnvR was a predicted AcrEF operon regulator, AcrF from Citrobacter tructae was then overexpressed associated with AcrE. It was found that overexpression of both AcrE and AcrF exhibited the best performance (2.5-fold) among all the candidates (Fig. 7b), demonstrating that AcrE and AcrF were responsible for MCFA export.

      Construction of autonomous MCFA secreting systems

    • In order to convert MCFA efflux to an autonomous behavior without inducer supplementation and human supervision, we turned to combining quorum-sensing (QS) circuitry with the efflux pumps. Our previous studies described two robust and autonomous QS-based circuits deriving from peptide pheromone responsive QS system of Enterococcus faecalis (QEX), and optimized acyl-homoserine lactone responsive QS system of Vibrio fisheri (QVX) by introducing T7 RNA polymerase as a genetic amplifier[26,30]. As the optimized QVX circuity needs the expression of T7 RNA polymerase, this would affect the utilization of T7 promoter for driving other pathway genes. Hence, in this study, T7 promoter driving the expression of efflux pumps was replaced by QEX circuity.

      During the QEX circuity, the operator sequence of the response promoter PprgQ was repressed by the master protein regulator PrgX, and the activation of this response promoter only occurred when heptapeptide cCF10 synthesized by heptapeptide CcfA bound to protein regulator PrgX (Fig. 8a)[30]. Our previous studies demonstrated that the components of functional QEX circuity must contain protein regulator PrgX and surface cCF10-binding protein PrgZ driven by constitutive Ptrc and P1 promoters, respectively, to assure both the low leakiness and robust response behavior of QEX circuity[30], whereas signal synthase CcfA was driven by constitutive promoters with different strength ranging from high strength P1 to low strength P6, to trigger QEX circuity at various times.

      Figure 8. 

      Construction of autonomous MCFA secreting systems. (a) Schematic of QEX circuity. (b) The effect of replacing T7 promoter with QEX circuity on MCFA production. The signal synthase CcfA was driven by constitutive promoters with different strength ranging from high strength P1 to low strength P6, to trigger QEX circuity at various times. (c) The evaluation of the performance of this autonomous MCFA secreting system in scaled-up bioreactors. Experiments in this study were conducted in triplicate and error bars signify SD with 95% CI.

      As seen in Fig. 8b, it was observed that different triggering times of QEX circuity driving the efflux pumps exerted different impact on extracellular MCFA concentrations and total MCFA concentrations. We found that an early or delayed triggering of efflux pumps led to the decrease of extracellular or total MCFA concentrations compared to the suitable triggering time (i = 2), further demonstrating the importance of examining the impact of different triggering times on efflux efficiency. It was presumed that during the early fermentation time, product toxicity did not present as an issue in strain engineering, and the early expression of efflux pumps would exert an extra metabolic burden on host strains; whereas the delay triggering of efflux pumps would not efficiently alleviate the product toxicity.

      We also evaluated the performance of this autonomous MCFA secreting system in scaled-up bioreactors (Fig. 8c), which presented as more industrially relevant procedures. The autonomous secreting system was then evaluated in a 5-L fermenter with the conduction of dissolved oxygen (30%), glucose (5 g/L) and pH control (6.5). It was observed that engineered strains in bioreactors exhibited better performance than in shake flasks, and a nearly 4.9-fold increase in MCFA titers (6.9 g/L) was observed. It was presumed that engineered strains in bioreactors produced higher concentration of MCFAs than shake flasks, and this would render more product toxicity to host strains, thus limiting their performance in bioreactors, whereas our autonomous secreting system would unleash their potential in target product synthesis.

    DISCUSSION

    • Most bio-chemicals present toxic effects and stresses towards host strains during high concentrations, which are essential for developing an economically viable and scalable bio-process[1,16,31]. Furthermore, extracting MCFAs through harvesting engineered organisms also exhibits energy- and cost-intensive characteristics. Numerous studies found that microbial efflux pumps could provide host strains the ability of resistance to high target product concentrations in fermentation broth via improving the secretion of endogenous compounds. More importantly, expediting product secretion could decrease product inhibition and improve target flux through reversible reactions due to the maintainence of low intracellular target product levels[16,17]. However, the information of efflux pumps specially responsible for MCFA transport is limited. Here, a multi-layer genome mining analysis combining with quorum-sensing circuit was developed to screen a library of uncharacterized heterologous pumps among over 2000 microbial genomes, and these efforts rewired the MCFA efflux to a robust and autonomous behavior without inducer supplementation or human supervision, paving the way to develop economically feasible bioprocesses.

      The current MCFA secreting system is built on the basis of endogenous transporters, which require both over-expression of acrE, mdtE, mdtC and deletion of cmr from E. coli[19]. However, fueled by rapid developments in high-throughput sequencing, numerous other sequenced microbial genomes contain abundant efflux pumps and present a largely unexplored resource for mining novel pumps[20,21]. In order to efficiently mine genomes during large genomic datasets, a multi-layer genome mining and phylogenomic analysis was developed. In the first layer, the general evolutionary recapitulation of target gene families was performed by comprehensive and systematic phylogenomics based on 397 genomes belonging to different representative prokaryotic species. In the second layer, special species which exhibited great potential after experimental verification were selected for future engineering efforts, and target gene-centric phylogenies, which contained the genomic context surrounding target genes based on all the genomes derived from these species, was conducted. This allowed us to perform detailed analyses of how gene cluster architectures evolved from their constituent independent enzymes or sub-clusters. This multi-layer analysis would enable us to identify hidden regulons related to target genes. Hence, this multi-layer bioinformatic framework could help us to effectively screen uncharacterized heterologous target genes or pathways across large strain collections during genome mining.

      MCFA efflux in organisms by nature could sense environmental changes in real time, and self-regulate cellular pathway fluxes, which would maximize product yields and minimize human supervision over the fermentation process control. Whereas current MCFA efflux systems required inducible promoters to conduct the transport function[19], and this was still incompatible with large-scale production[30,32,33]. In order to transform current MCFA efflux systems to an autonomous behavior eliminating inducer supplementation and human supervision, peptide pheromone responsive QS system of Enterococcus faecalis was combined with the efflux pumps. It was found that suitable triggering times of QEX circuity driving the efflux pumps yielded the best effect, and an early or delayed triggering of efflux pumps led to the decrease of extracellular or total MCFA concentrations, demonstrating the importance of examining the impact of different triggering times on efflux efficiency (Fig. 8b). This is, to our knowledge, the first report of autonomous and robust MCFA efflux system, and our autonomous secreting system would unleash microbial potential in target product synthesis, providing a valuable tool for advancing the field of high-value oleochemical research.

      Supporting information

    • Detailed information regarding the construction of MCFA efflux pump library and autonomous MCFA secreting systems, experimental details on the quantitation of MCFAs, culture conditions and batch culture are shown. The results regarding the confirmation of expressing each predicted efflux pump, cell growth of engineered strains, DNA sequences of modified genes (Supplemental Table S3) are also presented.

      Acknowledgments

      • Thanks to Pablo Cruz-Morales (Senior researcher, DTU Biosustain) to help us with the phylogenomics analysis for mining the efflux pumps. This work was financially supported by Natural Science Foundation of Jiangsu Province (BK20202002), Excellent Youth Foundation of Jiangsu Scientific Committee (BK20211526), Jiangsu Agricultural Science and Technology Innovation Fund (SCX(20)3332), National Natural Science Foundation of China (No. 31972060), Fellowship of China Postdoctoral Science Foundation (2020T130305), Fundamental Research Funds for the Central Universities (KYGD202003), China Postdoctoral Science Foundation (2018M640491), Postdoctoral Research Funding of Jiangsu Province (2018K030B), the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).

      Conflict of interest

      • The authors declare that they have no conflict of interest.

      Supplementary information
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      • Copyright: © 2022 by the author(s). Published by Maximum Academic Press on behalf of Nanjing Agricultural University. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (8)  References (33)
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    Cite this article
    Peng H, Zhou L, Duan X, Wang Z, Wang Z, et al. 2022. A multi-layer genome mining and phylogenomic analysis to construct efficient and autonomous efflux system for medium chain fatty acids. Food Materials Research 2:15 doi: 10.48130/FMR-2022-0015
    Peng H, Zhou L, Duan X, Wang Z, Wang Z, et al. 2022. A multi-layer genome mining and phylogenomic analysis to construct efficient and autonomous efflux system for medium chain fatty acids. Food Materials Research 2:15 doi: 10.48130/FMR-2022-0015
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  • Introduction
  • Materials and methods

  • General procedures

  • General phylogenomic reconstruction of mcfa transporter families

  • Analysis of detailed evolutionary divergence in citrobacter and escherichia species

  • Construction of mcfa efflux pump library

  • Construction of autonomous mcfa secreting systems

  • Fluorescence intensity measurement

  • Analytical methods

  • Culture conditions

  • Batch culture

  • Results

  • General evolutionary recapitulation of mcfa transporter families

  • Construction of mcfa efflux pump library

  • Detailed evolutionary divergence of mcfa transporter families in citrobacter species

  • Construction of autonomous mcfa secreting systems

  • Discussion

  • Supporting information

  • Acknowledgments
  • Conflict of interest
  • Supplementary information
  • Rights and permissions
  • About this article
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