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. 2021 Jan 11;11(2):57. doi: 10.1007/s13205-020-02588-5

Use of glycerol for the production of actinobacteria with well-known bioremediation abilities

Stefanie B Costa-Gutierrez 1, Juan Daniel Aparicio 1,2, Osvaldo D Delgado 1,3, Claudia S Benimeli 1,4, Marta A Polti 1,5,✉
PMCID: PMC7801532  PMID: 33489676

Abstract

In recent years, there has been an increasing interest in the remediation of contaminated environments, and a suitable solution is in situ bioremediation. To achieve this, large-scale bacterial biomass production should be sustainable, using economic culture media. The main aim of this study was to optimize the physicochemical conditions for the biomass production of an actinobacterium with well-known bioremediation ability using inexpensive substrates and to scale-up its production in a bioreactor. For this, the growth of four strains of actinobacteria were evaluated in minimal medium with glucose and glycerol as carbon and energy sources. In addition, l-asparagine and ammonium sulfate were assayed as alternative nitrogen sources. The strain Streptomyces sp. A5 showed the highest biomass production in shake-flasks culture using glycerol and ammonium sulfate as carbon and nitrogen sources, respectively. Factorial designs with five factors (glycerol concentration, inoculum size, pH, temperature, and agitation) were employed to optimize the biomass production of Streptomyces sp. A5. The maximum biomass production was obtained using 5 g L−1 of glycerol, 0.25 µL of inoculum, pH 7, 30 °C and 200 rpm. Finally, the production was successfully scaled to a 2 L stirred tank bioreactor.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-020-02588-5.

Keywords: Actinobacteria, Glycerol, Biomass production, Bioreactor, Factorial design

Introduction

Bioremediation can broadly be defined as the restoration of contaminated sites using microbial processes to convert polluting compounds into less polluting or harmless ones. This technology has proven to be effective, reliable, and well accepted by society due to its ecological characteristics compared to conventional methods (Kapahi and Sachdeva 2019). Bioremediation strategies can be carried out ex situ or in situ. In situ bioremediation techniques consist of treating the contaminated areas at the site of origin, which makes the process less expensive, avoiding the transport of contaminated samples to be treated elsewhere using ex-situ techniques (Azubuike et al. 2016). Nevertheless, the high cost of production and low scalability make large-scale application of microbial biomass to polluted sites unprofitable. For example, it was estimated that the amount of microbial biomass necessary for in situ treatment of contaminated soils at field scale would be 40 kg ha−1 (Aparicio et al. 2017). Therefore, the production of microbial biomass from low-cost feedstock is an attractive approach to guarantee the sustainability of the biotechnological process.

Biofuels, such as biodiesel and bioethanol, are renewable, environmentally friendly alternative products and represent an alternative to fossil fuels. Biodiesel is produced by transesterification of vegetable oils, animal fats, or microbial oils with alcohol. In this process, the main by-product is glycerol (1,2,3-propanetriol), which represents 10% by weight of the total biodiesel generation (Easterling et al. 2009). Although glycerol is used for different applications—such as emulsifier, softening agent, stabilizer, and wetting agent, for the food, pharmaceutical, and cosmetic industries—the increasing production of biodiesel in the world is causing an excess of this material that surpasses its market. Some biodiesel companies have severe problems removing excess of glycerol because it is quite expensive. Currently, one of the most important concerns is how to dispose of this by-product which is increasing the economic and environmental impact of the industrial biorefineries. Developing processes to convert low-cost glycerol into higher-value products is expected to make biodiesel production more economical and environmentally friendly (Dobson et al. 2012).

The most common carbon source used by microorganisms is glucose via the d-glucose pathway. However, glycerol is widely present in nature, hence several microorganisms can break it down and use it as a carbon and energy source (da Silva et al. 2009). Due to the abundant surplus of crude glycerol from biodiesel production, the use of this substrate could be more convenient (Nakamura and Whited 2003). Unfortunately, crude glycerol can contain a range of 36–96% glycerol and the rest comprises many impurities such as methanol, salts, metals, and matter organic non-glycerol (MONG) that could have a negative influence on microbial growth (Hansen et al. 2009; Ayoub and Abdullah 2012; Chatzifragkou and Papanikolaou 2012). Consequently, only a few microorganisms can utilize crude glycerol due to the large amount and diversity of contaminants (Rumbold et al. 2009; Dobson et al. 2012). Therefore, to minimize the impact of unknown variables introduced by using crude glycerol, it is suggested to use pure glycerol to determine whether it could be appropriate as a substrate for microbial growth (Easterling et al. 2009). From an economic point of view, the price of pure glucose is comparable to that of pure glycerol, which is US$ 0.6 per kg, while the price of crude glycerol is between US$ 0.09 and 0.2 per kg (Mota et al. 2017; Wu and Maravelias 2018). These values highlight the importance of using crude glycerol from biodiesel production as a carbon source for biotechnological processes.

Actinobacteria is a diverse taxonomic phylum, widely distributed in both terrestrial and aquatic environments, where these microorganisms play an important role in the decomposition and recycling of materials (Alvarez et al. 2017). Actinobacteria are important producers of industrially relevant secondary metabolites and exhibit high levels of xerotolerance and halotolerance (Dodd et al. 2018). Additionally, a large and growing body of literature has investigated the role of actinobacteria in the bioremediation of environments impacted by pesticides and heavy metals, an in-deep review on this topic is given by Alvarez et al. (2017) and Briceño et al. (2018).

Four actinobacteria isolated from contaminated sites in the northwestern region of Argentina were studied and its ability to degrade pesticides and reduce/immobilize heavy metals in liquid, sludge, and soil samples was demonstrated (Benimeli et al. 2003; Albarracín et al. 2005; Polti et al. 2007; Fuentes et al. 2010). The bioremediation of contaminated soil samples, at laboratory scale, using these actinobacteria had successful results by reducing the contaminants concentrations and removing pollutants such as chromium and lindane (Polti et al. 2014; Aparicio et al. 2018a, b; Raimondo et al. 2020). Previous research has demonstrated that these actinobacteria are capable of using various carbon sources such as glucose, glycerol, arabinose, sucrose, xylose, inositol, mannitol, fructose, rhamnose, raffinose and cellulose (Benimeli 2004; Polti et al. 2009; Albarracín et al. 2010). Besides, in a previous work, an attempt was made to optimize a vinasse medium to obtain biomass from these actinobacteria (Aparicio et al. 2017).

Several factors are involved during bacterial growth, thus, the cultivation conditions should be optimized to obtain the maximum biomass production. Due to the complex nature of the process, the conventional way of optimizing it (one factor by one experiment) makes research laborious and time-consuming (Mason et al. 2003). Therefore, to save resources and time, factorial experimental design methods were performed; this method allows to determine the significance of the assayed parameters and the interaction between them. Furthermore, the use of statistical tools proved to be useful for optimizing bioremediation parameters, such as environmental conditions and inoculum concentration (Aparicio et al. 2015, 2018a; Raimondo et al. 2020). Generally, the medium composition and the culture conditions are screened in flask-scale, and the optimized culture parameters are tested in a bioreactor-scale fermentation. Whilst some research has been carried out on the use of glycerol for the production of metabolites by actinobacteria (Bankar and Singhal 2010; Viana et al. 2010; Chen et al. 2011a), there is much less information on biomass production.

Based on this background, this study aims to optimize the physicochemical conditions for the production of actinobacteria biomass using pure glycerol as a carbon source.

Materials and methods

Microorganisms and culture media

In this study, four actinobacteria previously isolated from different contaminated environments in Argentina were evaluated. The strains belong to the PROIMI culture collection and useful information about these isolates is provided in Table 1. The strains were maintained on Starch Casein agar (SCA) slants, containing, in g L−1: starch 10.0; casein 1.0; K2HPO4 0.5; agar 12.0. The pH was adjusted to 7.0 before sterilization.

Table 1.

Strains of actinobacteria used in this study

Strains NCBI accession number Isolation location References
Streptomyces sp. M7 AY459531 Sediments from a drainage channel of a copper filter plant from Tucumán, Argentina Benimeli et al. (2003)
Amycolatopsis tucumanensis DSM 45,259 (strain AB0) DQ886938 Sediments from a drainage channel of a copper filter plant from Tucumán, Argentina Albarracín et al. (2005)
Streptomyces sp. MC1 AY741287 Sugar cane Polti et al. (2007)
Streptomyces sp. A5 GQ867055 Soil contaminated with pesticides from Santiago del Estero, Argentina Fuentes et al. (2010)
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Assays were carried out in liquid Minimal Medium (MM), containing in g L−1: K2HPO4 0.5; MgSO4·7H2O 0.20; FeSO4·7H2O 0.01 (Hopwood 1985). MM was supplemented with two different sources of carbon (glucose 10 g L−1; glycerol 3.3 g L−1) and nitrogen [l-asparagine 0.5 g L−1; (NH4)2SO4 4 g L−1]. To determine the best combination of these compounds for achieve maximum microbial growth, combinations of these nutrient sources were performed as follows: MM1 [Glucose + l-asparagine] (control medium), MM2 [Glucose + (NH4)2SO4], MM3 [Glycerol + l-asparagine], and MM4 [Glycerol + (NH4)2SO4]. In all cases, the pH of culture media was adjusted to 7.0 ± 0.2 and they were sterilized by autoclaving at 121 °C for 15 min. All chemicals used in the experiments were analytical grade.

Inocula preparation

Spore suspensions were obtained according to the methodology described by Kieser et al. (2000). Briefly, actinobacterial spores grown on SCA medium were gently removed from the surface of the plates using an inoculation loop and sterile distilled water. The suspension was removed with a sterile pipette and filtered using an appropriate device. The filtrate was centrifuged at 5000×g for 5 min at 4 °C (Eppendorf Centrifuge 5810 R). The collected spores were resuspended in 2 mL of sterile distilled water. To determine the spore concentration of the suspensions, tenfold serial dilutions were made in distilled water and plated on SCA in triplicate. Plates were incubated at 30 °C for 96 h and Colony Forming Units per mL (CFU mL−1) were determined (Polti et al. 2014).

Actinobacteria selection

Spore suspensions (100 μl of 1.109 CFU mL−1) of four actinobacteria were inoculated into each MM and incubated on an orbital shaker (180 rpm) at 30 °C for 96 h. At the end of the assay, the microbial biomass and the residual glycerol concentration were determined. Cell biomass was estimated gravimetrically by centrifuging the media (3000×g, 10 min), washing the pellets twice with distilled water, and drying at 105 °C until constant weight. Biomass was reported as g dry cell weight (DCW) per liter of broth (g DCW L−1) (Polti et al. 2007). The residual glycerol concentration was measured in the culture supernatant using the commercial kit TG Color (Wiener Lab, Argentina), based on an enzymatic method. Enzymatic reactions were performed following the protocol provided in the kits. Absorbance measurements were performed at 505 nm on a microplate reader (Multiskan™ FC Microplate Photometer, Thermo Fisher Scientific, USA). Glycerol concentrations were calculated based on a calibration curve using appropriate standard glycerol solutions. Finally, the strain that showed the highest growth in MM4 was selected for further assays.

Optimization of culture parameters

Screening of significant factors (Plackett–Burman design)

To determine the lower incubation time required to achieve maximum biomass production, the selected actinobacterium was grown in MM4 on an orbital shaker (220 rpm) at 30 °C for 72 h. The Plackett–Burman design was used for screening the variables and their main effects on the response but not their interaction effects (Plackett and Burman 1946). The spore suspensions (25, 50, or 75 μL of 109 CFU mL−1) were inoculated in Erlenmeyer flasks of 100 mL capacity with 30 mL of MM4 (the pH and glycerol concentration used were adjusted according to the Plackett–Burman design). The experimental design is shown in Table 2. Glycerol concentration, inoculum size, pH, temperature, and agitation were evaluated as five independent variables. To each of these variables were assigned two levels, high and low which were denoted as (+ 1) and (− 1), respectively, and a central point (see Table 2). Analysis of the effects of each independent variable was carried out with the help of Minitab®. The R2 coefficient of determination was applied to evaluate the data fit the model. Based on the F test and the p value at a significance level of 95%, significant variables were selected. All assays were run in triplicate.

Table 2.

Experimental levels and codes of the 5 independent variables tested in the Plackett–Burman design

Independent variable Code Low level (− 1) Central point High level (+ 1)
Glycerol (g L−1) A 1.6 3.3 5.0
Inoculum size (µL) B 25 50 75
pH C 6 7 8
Temperature (°C) D 25 30 35
Agitation (rpm) E 180 200 220
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Full factorial design

Based on the above information, a full-factorial design was performed with the Minitab® 17.1.0 software and the process was optimized to obtain the maximum biomass production. For this, the variables which had a significant effect on the responses were evaluated, the codes and the values of the variables were maintained as shown in Table 2. Those variables that did not have a significant effect on the responses were fixed. The growth of the selected actinobacterium was performed with the same methodology described in subsection 2.4. All runs were conducted in triplicate.

Biomass production in a bioreactor

Laboratory-scale bioreactor cultures were performed in a 2 L Inceltech LH 210 series bioreactor equipped with temperature, pH, and dissolved oxygen probes. The agitation consisted of three Rushton type impellers (with six flat-blades each) on one axle, electronically controlled. The aeration of the system was provided by an air inlet through a ring sparger with an air-flow meter (LH), filter, and measurement of dissolved oxygen saturation (Fig. 1).

Fig. 1.

Fig. 1

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Image of the 2 L Inceltech LH 210 series bioreactor during biomass production of the Streptomyces sp. A5 strain. The red arrow indicates the biomass adhered to the surface of the vessel

The inoculum was prepared by the cultivation of spore suspensions in 100 mL flasks with 30 mL of MM4. The culture conditions were defined according to the above results. The cultures were centrifuged (5000×g, 5 min) and the concentrated cells were diluted to a final volume of 100 mL (7%) and used to inoculate the bioreactor vessel containing 1.4 L of MM4. Foaming was controlled by the addition of an antifoam solution (polyol‐base) (0.01%). Actinobacterial cultures were performed in the bioreactor for 48 h under the following conditions: temperature, 30 °C; stirrer speed, 100 rpm; air flow rate, 1 vvm; pH, was not controlled. Samples were withdrawn at 6 h intervals to determine glycerol concentration. Finally, the total biomass was harvested after 48 h of cultivation. The experiments were carried out in duplicate.

Statistical differences were determined using a one-way analysis of variance (ANOVA) followed by a Tukey’s or Fisher’s test at a 95% confidence level (Minitab 17.1.0). All values are mean values with standard deviation.

Results and discussion

Actinobacteria selection

The growth of four actinobacteria with well-known bioremediation abilities was evaluated using different culture medium compositions, in an attempt to reduce the cost of the culture medium for biomass production. Glucose and glycerol were assayed as carbon and energy sources. As it can be seen in Fig. 2, the four strains were able to grow under the four evaluated media. Streptomyces sp. M7 and A. tucumanensis AB0T did not show significant differences in their growth depending on the carbon sources used. However, the biomass production of both strains was strongly influenced by the nitrogen source at the culture medium, which was significantly higher in the presence of l-asparagine than in (NH4)2SO4. On the other hand, biomass production of the strain Streptomyces sp. MC1 was significantly higher in the presence of glucose and (NH4)2SO4. The strain Streptomyces A5 did not show significant differences among all the conditions assayed, indicating that it can use both carbon and nitrogen sources with similar efficiency. The growth of all Streptomyces strains in glycerol-based media (MM3 and MM4) showed comparable rates with those obtained in glucose-based ones (MM1 and MM2), i.e. all the actinobacteria were able to metabolize and grow in a minimal medium with glycerol as a carbon source. These results are similar to those reported for the strain Streptomyces albulus BCRC 11,814 (Dodd et al. 2018).

Fig. 2.

Fig. 2

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Biomass of actinobacteria strains (Streptomyces sp. M7, Amycolaptosis tucumanensis AB0T, Streptomyces sp. MC1 and Streptomyces sp. A5) in minimal medium (MM) with glucose or glycerol as carbon source; and l-asparagine or ammonium sulfate as nitrogen source, after 72 h at 30 °C and 200 rpm. Data are averages and standard deviations from three independent assays. Different letters indicate statistically significant differences (p value < 0.05)

Furthermore, in this study, two different nitrogen sources with the same nitrogen content were evaluated (28 g mol−1). All the strains were able to use this inorganic nitrogen source to grow, however, they showed different efficiencies (Fig. 2). Ammonium sulfate was selected as an alternative nitrogen source because the value of 1 kg of this salt (73.08 USD) is almost twenty times less than 1 kg of l-asparagine (1415.70 USD) (www.sigmaaldrich.com/argentina.html). Considering that it is frequently pursued that alternative substrates—like glycerol and ammonium sulfate—achieve yields comparable to those obtained from more expensive substrates—like glucose and l-asparagine—in industrial-scale processes, glycerol and ammonium sulfate were chosen as alternative substrates of the culture medium for the biomass production of actinobacteria in the following tests. Under this condition the strain Streptomyces sp. A5 achieved the highest biomass production (Fig. 2) and was selected to optimize the culture conditions applying the Plackett–Burman design and scale-up of the process.

Selection and optimization of culture parameters

Using the Plackett–Burman design allows us to evaluate a high number of variables and precisely identify which ones have a significant effect on biomass production. At the same time, the use of experimental factorial designs considerably reduces the number of trials, saving time, energy, and money (Aparicio et al. 2018b). To minimize the number of variables in the model, the optimal culture time was evaluated separately, and no significant differences were observed in the biomass production of the strain Streptomyces sp. A5 after 24 h of incubation (Supp. Figure 1). Therefore, the cultivation time was established at 24 h. Then, a 5-variable 2-level Plackett–Burman method was performed. The variables and levels used were selected according to the data obtained in the laboratory previously (Benimeli et al. 2003; Polti et al. 2011).

Validation of the method was carried out, data normality and constant variance assumptions were confirmed (Supp. Material 1). The biomass production of Streptomyces sp. A5 varied widely, ranged from 0.008 to 0.140 g L−1 in different media and culture conditions (Supp. Table 1). These results demonstrate the importance of the process optimization to achieve maximum biomass production. The relationship between biomass production and the independent variables was determined by multiple-regression statistical analysis and analysis of variance (ANOVA) of the experimental design was performed. The estimated main effect of each variable for biomass production and yield coefficient are summarized in Table 3. Taking into account the five evaluated variables, only glycerol concentration, initial pH of the medium and incubation temperature had a significant effect on biomass production (p < 0.05), at the evaluated levels. The biomass production was minimal (0.008 g L−1) when the variables glycerol concentration, inoculum, temperature, and agitation speed were at their lowest levels. In contrast, the maximum biomass production (0.14 g L−1) was achieved when the variables glycerol concentration, pH, temperature, and agitation speed were at their highest levels. Therefore, the improved cultivation conditions increased 3.2-fold the biomass obtained compared to the non-optimized ones (0.044 g L−1), i.e., all the variables at zero level. Also, the yield coefficient for biomass production by Streptomyces sp. A5 (Y = g biomass formed per g glycerol consumed) are presented in Table 3, and the results were similar to those obtained for the biomass production.

Table 3.

Statistical analysis results according to ANOVA for Plackett–Burman design for biomass production and yield coefficient by Streptomyces sp. A5

Biomass production Yield coefficient
Variable Effect Coefficient p value Effect Coefficient p value
A 0.3285 0.1643 0.005* − 0.0914 − 0.0457 0.011*
B 0.000053 0.000027 0.934 0.000361 0.000181 0.076
C 0.6367 0.3183 0.000* 0.1768 0.0884 0.001*
D 0.04210 0.02105 0.000* 0.01206 0.00603 0.000*
E 0.000225 0.000112 0.596 0.000233 0.000116 0.082
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*Significant effect on biomass production

Based on the results obtained with the Plackett–Burman design, the variables glycerol concentration, pH, and temperature (A, C, and D) were selected for further full factorial design to evaluate its main and interactive effects on biomass production and yield coefficient. The variables B (inoculum concentration) and E (agitation speed) were adjusted since they did not have a significant effect on biomass production. The inoculum concentration was adjusted to 25 µL because it was demonstrated that higher amounts of inoculum did not improve biomass production, and the agitation speed was adjusted to 200 rpm.

The 33 factorial design and the results obtained, and the ANOVA analysis are summarized in Tables 3 and 4, respectively. Validation of the method was carried out, and the normality and constant variance assumptions were confirmed. Based on the analysis, a correlation analysis of predicted versus experimental data was conducted and it showed a correlation coefficient value of 0.74 for biomass production (Supp. Material 2), indicating that the model obtained was useful to predict the biomass production, under different experimental conditions. The biomass production values ranged from 0.022 to 0.161 g L−1 (Supp. Table 2). The lowest biomass concentration was obtained in runs where the variables C (pH) and D (temperature) were at their lowest level. These results suggest that low pH and temperature values might be detrimental to biomass production. On the contrary, the highest biomass production was achieved in runs in which the three evaluated variables were at their medium or highest level (0 or + 1).

Table 4.

Statistical analysis results according to ANOVA for 33 factorial design for biomass production and yield coefficient by Streptomyces sp. A5

Source p value
Biomass production		 p value
Yield coefficient
A 0.053 0.173
C 0.000 0.036
D 0.000 0.487
A*C 0.668 0.233
A*D 0.394 0.669
C*D 0.050 0.829
A*C*D 0.610 0.875
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Significant effect on biomass production marked in bold

An ANOVA test was applied to detect the statistically significant main (individual) and interactive effects of the operational factors on biomass production. As Table 4 shows, two main effects (variables C and D) and one interaction effects (C*D) were significant model terms (p ≤ 0.05). In addition, the yield coefficient was analyzed, but in this case, only the pH (variable C) showed a significant effect. Tables 3 and 4 provide the analysis of variance applied to evaluate the significant differences among the evaluated conditions. Biomass production was higher at high values of temperature and pH, however, no significant differences were found between the temperatures 30 and 35 °C or pH 7 and 8. Taking this into consideration, it was decided to scale the process using a temperature of 30 °C and pH 7 as initial operating conditions, because these environmental parameters were described as the most optimal for the growth of actinobacteria (Alvarez et al. 2017). On the other hand, it was observed that the glycerol concentration (variable A) did not show a significant effect on the growth of Streptomyces sp. A5. Therefore, the highest value of this variable was selected to carry out the following tests, to avoid that the glycerol concentration was limiting for bacterial growth.

Bioreactor evaluation

The culture medium was adjusted and the operational conditions were performed according to the results obtained through factorial design studies. To maintain stable growth, the initial aeration was maintained at 1 vvm (volume/volume/minute) and pH of the culture was not controlled. The mixing was maintained at 100 rpm and the temperature at 30 °C. Dissolved oxygen (DO) in the bioreactor decreased to 30% saturation within 12 h of operation, indicating active microbial growth. When the growth of Streptomyces sp. A5 decreased, the DO started to increase. From 0 to 6 h of incubation, the glycerol consumption by the microbial cells was only 0.56 g L−1 reaching a consumption of 0.72 g L−1 (14.4% v v−1) by the end of the assay. Low glycerol consumption rates were previously reported in Propionibacterium freudenreichii ssp. shermanii 1 and Streptomyces sp. M3004 (Kayali et al. 2011; Pawlicka-Kaczorowska and Czaczyk 2017). Furthermore, a drop in the pH of the culture of nearly 3 points was measured by the end of the cultivation, as was observed for another Streptomyces strain cultivated using glycerol as a carbon source (Chen et al., 2011a, b; Zeng et al., 2017). Because of the heterogeneous nature of the microbial growth of the actinobacteria in the form of pellets, the biomass collected during the sampling would not be representative of the real situation inside the bioreactor; therefore, it was not possible to assess the growth kinetics.

The biomass production reached 0.2 g L−1 after 48 h of batch culture in a 2 L bioreactor under the previously optimized parameters. Twenty-four hours after inoculation, spherical pellets formed became larger during cultivation. By day 2, a mixture of spherical pellets and hyphae of actinobacteria settled at the bottom of the reactor. Some growing cells were separated from the medium and adhered to the walls of the glass vessel above the broth level at a high stirring rate (200 rpm), causing the loss of biomass (See Fig. 1, red arrow). Similar results were recorded by changing the aeration from 1 to 0.5 vvm. These inconveniences were solved when the agitation was reduced to 100 rpm, possibly due to the elimination of the waves produced by high rates. In addition, a polyol-based antifoam was added to the medium to minimize the adhesion of microbial biomass to the vessel. Some reports of a culture of Streptomyces in bioreactor indicated low aeration (0.5–0.7 vvm) and high agitation rates (up to 600 rpm), but surprisingly the authors do not mention problems with the adherence of pellets in the surface of the vessel (Senthil Kumar et al. 2012; El-Naggar et al. 2019).

High aeration and agitation rates in bioreactors are beneficial to achieve higher biomass or product yields, especially under viscous conditions (Bandaiphet and Prasertsan 2006; Juszczyk et al. 2013; Luo et al. 2018). Nevertheless, the results obtained indicate that, in a glycerol-based medium, low rates of aeration and agitation allowed an adequate supply of oxygen and nutrients, and avoided the loss of biomass due to the tendency of the actinobacteria to adhere onto surfaces. Particularly for high biomass production by Streptomyces, some authors proposed an increase in agitation rates until a critical value (Tough and Prosser 1996; El-Enshasy et al. 2000; Mehmood et al. 2010). However, other researchers observed that some strains of Streptomyces develop low biomass production at high agitation rates, which could be due to an inhibition of cell growth or modification of morphology that affected the formation of granules (Okabe et al. 1992; Large et al. 1998; Roubos et al. 2001). Pellets of Streptomyces usually do not form in bioreactors due to high aeration and vigorous agitation, and dispersed mycelial growth is frequently the predominant form (Whitaker 1992). Conversely, in shake-flask cultures, shear levels are lower, promoting the development of pellet morphology. Nevertheless, in the present work, the strain Streptomyces sp. A5 was able to form pellets at the evaluated aeration and agitation rate.

In some cases, the broth is homogeneous and the samples taken from any part of the bioreactor are representative of the entire system, i.e. the culture medium is chemically and physically homogeneous. However, biomass production by actinobacteria in bioreactor raises several complex bioengineering and microbiological challenges related to the formation of pellets or aggregates. This type of microbial morphology leads to a heterogeneous culture which makes the sampling and monitoring of the process difficult. Generally, near the impeller (high shear zone) the broth exhibits low viscosity, whereas in distant regions the culture is more viscous due to reduced mobility (Nienow 1990; Mcneil and Harvey 1993). This phenomenon is more evident when the scale is increased (Thiry and Cingolani 2002).

Although the culture parameters are correctly optimized in flasks, sometimes—for reasons as yet unknown, but possibly due to the oxygen supply or mixing device—the biomass yields in the bioreactor can far differ from those achieved in lower work volume. Therefore, during the production of actinobacteria biomass in a bioreactor, the oxygen is supplied to the medium with the help of a gassing device with sterile filtered air and mechanical agitation to disperse the gas bubbles and nutrients through the liquid. Furthermore, the rheological properties of the broth offer high resistance to mass transfer and oxygen supply to growing cells, limiting the scale-up of the operation. However, other factors affect the aerobic process and its scale-up such as shear stress, nutrient or product concentration, growth of microorganisms, among others (Hsu and Wu 2002).

Scaling-up and scaling-down a fermentation process essentially consist of maintaining physical conditions within the bioreactor since the chemical composition of the broth can be easily kept constant (Hewitt and Nienow 2007). Another aspect to consider, especially for the cultivation of actinobacteria, is the tendency to form filaments and pellets. This behavior avoids the increase of the viscosity in the broth and facilitates the efficient sedimentation and recovery of the actinobacteria biomass; however, it could hinder the correct supply of oxygen and nutrients.

Despite the problems and limitations observed within the use of bioreactors, in the present study, the cultivation of actinobacteria in such devices allowed the production of higher biomass rates compared to those obtained in shake-flask experiments. The biomass production by the strain Streptomyces sp A5 in glycerol-based MM in the bioreactor was 0.2 g L−1, these results were similar to those reported by Polti et al. (2014) in flasks. To date, only a limited number of studies have evaluated, in-depth, the biomass production of Streptomyces strains using glycerol as a carbon source, in a bioreactor.

Conclusions

This study highlighted the ability of the strain Streptomyces sp. A5 to convert pure glycerol into biomass. This approach will prove useful to expand our studies on the use of crude glycerol from biodiesel production as a carbon source for biomass production. This is the first report on the production of biomass of bacteria with well-known bioremediation activity, using glycerol as a substrate. The insights gained from this study may lead to the development of a low-cost process for the production of bacterial biomass, and the high value-added product obtained could act as a solution for contaminated areas. Considerably more work will need to be done to optimize the biomass production of the actinobacteria in a medium using crude glycerol as a carbon source. In addition, since fermentation parameters are valid only for the strain evaluated, a study similar to this one will be carried out to optimize the growth condition of the remaining strains.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 23 KB) (23.1KB, docx)
Supplementary file2 (DOCX 22 KB) (21.7KB, docx)
Supplementary file3 (DOCX 20 KB) (20.2KB, docx)
Supplementary file4 (DOCX 39 KB) (38.6KB, docx)
Supplementary file5 (DOCX 42 KB) (42.1KB, docx)

Acknowledgements

The authors gratefully acknowledge financial support of Consejo de Investigaciones de la Universidad Nacional de Tucumán (PIUNT D626; PIUNT Orientado 503/2019), Agencia Nacional de Promoción Científica y Tecnológica (PICT 2016-0493, PICT 2018-0490), Consejo Nacional de Investigaciones Científicas y Técnicas (PIP 2017-683) and the technical support of Mr. Gonzalo Tapia.

Author contributions

SBC-G: conceptualization, methodology, validation, investigation, formal analysis, writing—original draft. JDA: conceptualization, methodology, validation, investigation, formal analysis, writing—original draft. ODD: methodology, validation, investigation, formal analysis. CSB: conceptualization, validation, supervision, funding acquisition, project administration, writing—review and editing. MAP: conceptualization, validation, supervision, funding acquisition, project administration, writing—review and editing.

Compliance with ethical standards

Conflict of interest

We are declaring that there is no conflict of interests regarding the publication of this article.

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