Siderophore from Talaromyces trachyspermus: augmentation and characterization

In the present study, a siderophore compound produced by an endophytic fungus, Talaromyces trachyspermus was optimized for maximum production, 88.9 % SU by applying Plackett-Burman design and Response Surface Methodology through Central Composite Design that showed the succinic acid (1.141 g/L), sucrose (31.028 g/L) and temperature (27.475 °C) as significant factors. On scale up, a further increase in siderophore yield was obtained (by 3%) The compound was extracted, purified and detected chemically as catecholate siderophore showing max. λ absorbance at 279nm. Contained of hydroxy benzene as shown by GC-MS analysis and further identified as berberine by HRLC-MS studies. The compound berberine is clinically a very important drug with several ethnobotanical properties. This is rare to report fungal catecholate and first to report the production of berberine from Talaromyces species.


Introduction
Burman (PB) design and response surface methodology (RSM) by central composite design (CCD), for enhanced production of siderophore by using Czapek's Dox broth medium supplemented with leucine, biotin, and succinic acid. Scale-up of optimized shake flask protocol to laboratory-scale bioreactor and characterization of compound was also studied.

Materials and Methods
Optimizationofphysicalandchemicalparametersforsiderophoreproduction:

Statistical approach & Designs of experiment
In the first phase, Plackett-Burman design was used to find the significant variable(s) or factor(s) to optimize the siderophore production. In the next phase, Response Surface Methodology through Central Composite Design was used to find the optimum concentration of the selected variable. According to Murugappan et al. the selected variables on the responses was analyzed to maximize the siderophore production [9].

Plackett-Burman design
At first stage of the optimization, 13 variable Plackett-Burman experimental design was used to find the significant ingredients of the basal medium, Czapek's Dox broth for the maximum production of siderophore. This experimental design was two-factorial design, and was used to identify the critical parameters required for optimum siderophore production by screening n variables in n + 1 experiment [10]. Optimum values for physical parameters such as pH, temperature, RPM and incubation days were obtained by screening one variable at a time method (OVAT) ( Table 1). These variables were coded as A, B, C, D, E, F, H, J, K, L, M, and N respectively, while O, P, Q, R, S and T were considered as dummy variables. Experiments of PB design were carried out in triplicates, and the average mean of siderophore unit percentage (SU%) was considered as the final response. The quantification of siderophore production was carried out by Chrome Azurole Shuttle assay [11]. Each of these variables was represented at two different levels-high concentration (H) and low concentration (L) ( Table 1). The effect of individual variable was determined by calculating the difference between the average of measure at the H value and the L value. The full experimental design consisting of 13 variables with six dummy variables and 20 trials is depicted in table 2. The effect of each variable on siderophore production in the form of SU% was calculated, and the highest confidence level and F-test was used to determine the significant component [12].

Response surface methodology (RSM)
The second phase in optimization of the medium-composition was to find the optimum concentration of the significant components by RSM through CCD. It involved steps such as procedures to find the optimum region, the responses in the optimum region of variables, estimation of the optimal conditions and verification of the data. The variables obtained from PB design to enhance the siderophore production were selected for CCD to study the interaction between the various medium constituents, which influence the siderophore production.
In the present work, experiments were planned to obtain a quadratic model.
Where Yi is the predicted response, XiXj are input variables, which influence the response variable Y, β 0 is the offset term, βi is the ith linear coefficient, β ii is the quadratic coefficient, β ij is the ijth interaction coefficient. After the analysis of data, the experimental run with optimum values of variable was done to check the validity of the model.

Scale-up and validation on bioreactor
The shake flask process was scaled-up to 5L capacity fully automated laboratory-scale bioreactor (Murhotpye Scientific Co., India, Model LF-5) equipped with monitoring & control of physiochemical variables, namely, pH temperature, dissolved Oxygen, air flow rate & agitation.
The fermenter was operated at 3 L working volume. The fermenter was autoclaved and sterilized at 121°C for 20 minutes. Thereafter, separately autoclaved/ filter-sterilized components of medium were added to bioreactor. Initial value of the physicochemical parameters was adjusted (aeration rate of 0.1vvm, pH at 6.8, temperature 28°C, agitation 140 rpm). Following inoculation of the medium, the DO was automatically controlled with respect to aeration and agitation. The pH was adjusted by automatic addition of 2N KOH/2N H 3 PO 4 . The performance of siderophore producing isolate was tested out and the validity of optimization studies carried out at shakeflask level was confirmed.

Characterization of siderophore
Chemical detection of type of siderophore Detection of hydroxamate type of siderophores was carried out using the Csaky Assay [13]. The assay detects the presence of secondary hydroxamate and depends on the oxidation to nitrite and formation of a colored complex via diazonium coupling. The reaction mixture after incubation of 30 minutes, a cherry color indicated the presence of hydroxamate type of siderophore. And to check the presence of catechol type siderophore, Arnow assay was performed [14].

Extraction and purification of siderophore
Cell free supernatant was harvested and CAS positive supernatant of the fungi was concentrated (10X) on rotatory vacuum evaporator (Model) at 100 rpm at 50º C (pH 6.0 adjusted with 12 N HCl). Then it was subjected to Amberlite XAD column prepared with AmberliteXAD-16 resin (Sigma, USA) dissolved in distilled water and kept overnight at 8°C for soaking. Before use, the resin was activated by treating with 0.1% NaNO 3 and loaded in a sintered glass column of 40x6cm size; the loaded column was pre-washed twice with water, methanol and water.
The aqueous concentrated supernatant containing ferric siderophore was allowed to slowly pass through the column at the rate of 5ml/min. using a peristaltic pump. Loading of supernatant was continued until the saturation of column, as indicated by reddish-browning of column. The column was then washed with five to ten bed volume of distilled water to remove all unbound components of the medium. Solvent was then changed to 50% methanol and the column was left to equilibrate for the extraction of siderophores. Different fractions were separately collected; filtrate, water and eluted fractions were checked for CAS test. CAS positive fractions were used for characterization of siderophore.

Detection Using Thin Layer Chromatography (TLC)
CAS positive fraction or concentrated samples of siderophore were spotted on HiMedia 5X10 silica gel plates and spots were allowed to dry. The plates were then run in an n-butanol: acetic acid: DH2O (12:3:5) solvent system until the solvent front reached the top of the plate.
Plates were then dried and sprayed with 0.1 M FeCl 3 in 0.1 N HCl. The formation of a winecolored spot indicated a hydroxamate-type siderophore, while a dark gray spot indicated production of a catechol-type siderophore. Siderophores were separated on the basis of hydrophobicity using these plates.

Spectrophotometric assay
CAS positive fraction was subjected to double beam UV-Visible Spectrophotometric scan (200-800 nm) and the absorption maxima were recorded.

Fourier Transform Infrared (FTIR) spectroscopy
The extracted siderophores were characterized by collecting the FT-IR spectra in the transmission mode (4000-450/cm) using Shimadzu FT-IR spectrophotometer (Model-8400S and IR solution version 1 .40 software).

GC-MS analysis
The

Results and Discussion
To allow an economical use of siderophore sand metabolic resources, the need of chemical stability and regulation of fungal siderophore biosynthesis is an essential aspect of microbial life in the soil and in the rhizosphere for determination of significant variables affecting the response of siderophore production. Statistical optimization of these variables for maximum production was carried out.
Medium selected for analysis of T. trachyspermus was Czapek's Dox Broth, which contains sucrose, sodium nitrate, dipotassium phosphate, magnesium sulfate, potassium chloride and Iron sulfate in the media. FeSO 4 is already present as iron source, so there was no requirement of putting the external iron source for the study. Along with these variables and external variables, a total of 13 factors were considered for Placket-Burman analysis, which have been listed in table 2 with their high and low value for Placket Burman design. The results of the PBD analysis have been depicted in table 3. The three significant variables having a major effect on siderophore production with T. trachyspermus were found to be succinic acid, sucrose and temperature as deduced from F value and Pareto chart (Figure 1) of the effect of a variable on siderophore production. The model F-value of 289079.82 implies that model is significant. There remains merely 0.14% chance for F-value to be large occurring due to noise.       2 and fig 3 show the contour plot and surface plot respectively of the RSM analysis (Table   6), each considering one variable being at zero value. 13 The maximum value of siderophore production of 88.894 obtained by maximization analysis through RSM was observed for succinic acid at a level of 1.141 g/L, sucrose concentration of 31.028 g/L and temperature of 27.475ºC (Table 8)     The statistical optimization confers an effective and practical approach for obtaining maximum production of metabolites, Dewedar et al. [15] reported 89.33% siderophore production by Azotobacter chrococcum through two-steps statistical optimization method and found pH, incubation period and K 2 HPO 4 as three significant variables. Whereas, Abo-Zaid et al. [16] reported glycerol, glucose and K 2 HPO 4 being significant variables for Pseudomonas aeruginosa (6.0235%) and glutamic acid, sodium succinate and FeCl 3 for Pseudomonas fluorescens (6.258%). 90.52% siderophore unit was achieved by using response surface methodology optimization at the glucose concentration of 21.84 g/l, pH 6.18, and Pb (NO 3 ) 2 concentration of 245.04 µmol/ by Bacillus sp. [17]. It was also found by Shaikh et al. that

Run A B C D E F G H J K L M N O P Q R S T Yield 1 H H H H H H H H H H H H H H H H H
Pseudomonas aeruginosa produced maximum siderophore (68.41 % SU) with the optimized factors, succinic acid (0.49 g/100 ml), pH (7.08) and temperature 27.8ºC [7].
In interest to our study, it is first to capitalize on the siderophore production from endophytic fungi by using the two-way statistical approach.

Scale-up of process on bioreactor
After optimization of culture condition for siderophore production, we used fermenter and Penicillium digitatum (84.26%) [18].

Extraction and purification of siderophore
Concentrated supernatant from incubated optimized medium broth (pH 6.8) when passed through amberlite XAD-16 resin and when eluted with (1:1) methanol: water, yielded three different fractions. Out of these three fractions, only one fraction was CAS positive. This CAS positive fraction upon vacuum drying on rotatory vacuum evaporator yielded dry powder weighing 998mg/L from T. trachyspermus culture. This extract was further processed for characterization.

Characterization of siderophore Detection of type of siderophores
Eluted sample of siderophore and reagent mixture were kept for 20-30 min and it was noted that pink red color in test solution appeared while no change in color was observed in control. This indicated the hydroxamate nature of siderophore compound [13] by T.
trachyspermus. And change in the color of Arnow's test from yellow to pink-red color indicated the presence of catecholate type of siderophore [14]. Thus, the extract contained a mixed type of siderophore as it showed presence of hydroxamate as well as catecholate type of siderophore by T. trachyspermus.

Detection by Thin Layer Chromatography
When lyophilized and concentrated culture supernatant was subjected to thin layer chromatography, results were found similar to Clark and Lee [19] and Memon [20]. Thus T.

Spectrophotometric assay
Further, to confirm the presence of the type of siderophore in the eluted sample, spectrophotometric analysis of CAS positive fraction was carried out and found λ max at 279.66 nm (Fig 6). The compound belongs to methoxybenzene hence, the peak indicated the presence of catecholate type of siderophore [20].  (Fig 7). This value matched with the standard values of IR frequencies. Similar results have also been reported in P. putida and another Pseudomonas sp. [8,21].

LC-MS Analysis
For determination of the identity of siderophore compound, LC-MS/MS was performed by positive electrospray ionization and with TOF acquisition SW. At physiologically relevant concentrations, by chromatogram peaks (Fig 9A) (Fig 9B), belongs to a class of alkaloid structurally related to the benzyl isoquinolines (Fig 9C), containing a second aromatic ring beside the isoquinolines as a heteropentacyclic acidic compound. This compound has been found in many plants and microbes, most notably in goldenseal (Hydrastiscanadensis), barberry (Berberisvulgaris), Oregon grape (Berberisaquifolium), and goldthread (Coptischinensis). This efficiently chelates with metal ion [22].
Gholampour and Keikha [23] found that berberine protects the liver and kidneys against ferrous sulfate-induced toxicity by reduction in lipid peroxidation and shows ability to chelate iron. Berberine can be categorized as one of major but rare groups of siderophores, the catecholates (phenolates) [24]. Fe 3+ is a strong Lewis acid, preferring strong Lewis bases such as anionic or neutral oxygen atoms to coordinate with (Fig 9D) [25]. The catecholate, or catechol type, siderophores are the second most common siderophore class beside the fact that they have thus far only been found to be produced by bacteria [26]. They have been found to contain either a mono or di hydroxy benzoic acid residue that is used to chelate ferric iron and derived from di hydroxy benzoic acid [27]. The best-studied example of a catechol type siderophore is enterobactin by E. coli [28].
Berberine has a yellow color, and has often been used as a dye being a bioactive and very remarkable health profit phytochemical drug affecting the body at the molecular level. Berberine has been shown to reduce blood sugar [29]. Berberine has a long history of use in traditional Chinese medicine, where it was used to treat various ailments as it reduces cholesterol and triglyceride levels, while raising HDL, acts against depression, cancer, fatty liver and heart failure.
It also has potent antioxidant and anti-inflammatory effects [30]. Studies have shown that it activates "metabolic master switch" an enzyme inside cells called AMP-activated protein kinase (AMPK) [31]. It has been shown to fight harmful microorganisms, including bacteria, viruses, fungi and parasites such as Staphylococcus aureus and Microcystis aeruginosa [ 32,33,34]. The endophytic fungi Alternaria sp., which was isolated from the healthy leaves of Coptis chinensis was also reported to produce 9.313 μ g• g⁻¹berberine when grown in the PDA culture medium [35]. Vinodhini and Agastian reported 196 µg/L of berberine production from Fusarium solani, isolated from Coscinium fenestratum (Gaertn.) Colebr an endangered medicinal plant [36].
Galanie and Smolke reported fermentative production of protoberberine alkaloids by engineering the biosynthetic pathways in Saccharomyces cerevisiae [37]. Moreover, endophytic fungi can benefit the plant host by providing nutrients and competing with pathogenic organisms resulting in the reduction of chemical use in the agriculture, protection of agro-ecosystems and biological resources thus supporting sustainable agricultural system.

Conflict of interest
All authors declare no conflict of interest.