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# New Insights on Carotenoid Production by Gordonia alkanivorans Strain 1B

Written By

Tiago P. Silva, Susana M. Paixão, Ana S. Fernandes, José C. Roseiro and Luís Alves

Submitted: February 14th, 2022Reviewed: February 24th, 2022Published: April 18th, 2022

DOI: 10.5772/intechopen.103919

From the Edited Volume

## Carotenoids - New Perspectives and Application [Working Title]

Dr. Rosa María Martínez-Espinosa

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## Abstract

Gordonia alkanivorans strain 1B is a desulfurizing bacterium and a hyper-pigment producer. Most carotenoid optimization studies have been performed with light, but little is still known on how carbon/sulfur-source concentrations influence carotenoid production under darkness. In this work, a surface response methodology based on a two-factor Doehlert distribution (% glucose in a glucose/fructose 10 g/L mixture; sulfate concentration) was used to study carotenoid and biomass production without light. These responses were then compared to those previously obtained under light. Moreover, carbon consumption was also monitored, and different metabolic parameters were further calculated. The results indicate that both light and glucose promote slower growth rates, but stimulate carotenoid production and carbon conversion to carotenoids and biomass. Fructose induces higher growth rates, and greater biomass production at 72 h; however, its presence seems to inhibit carotenoid production. Moreover, although at a much lower yield than under light, results demonstrate that under darkness the highest carotenoid production can be achieved with 100% glucose (10 g/L), ≥27 mg/L sulfate, and high growth time (>216 h). These results give a novel insight into the metabolism of strain 1B, highlighting the importance of culture conditions optimization to increase the process efficiency for carotenoid and/or biomass production.

### Keywords

• Gordonia alkanivorans strain 1B
• biomass
• carotenoids
• dark/light
• glucose/fructose

## 1. Introduction

Carotenoids are bioactive molecules characterized by their intense coloration, which varies between red, yellow, orange, and pink, depending on their molecular structure. These molecules serve several biological purposes, aiding in photosynthesis in autotrophic organisms, protecting cells from excess light, have high antioxidant properties, and help in regulating membrane fluidity [1]. Due to these characteristics, carotenoids have garnered the interest of the health, cosmetic, pharmaceutical, and food industries, amongst others, giving them a high market value [2]. Indeed, the global carotenoids market was valued to grow from $1.5 billion in 2019 to$2.0 billion by 2026, recording an annual growth rate of 4.2% during the forecast period [3].

Carotenoids can be obtained from many sources, they can be chemically synthesized, extracted from plants and animals, or extracted from microorganisms. The latter option is becoming increasingly more appealing since microorganisms can be cultivated to higher densities, do not depend on seasonality, and can still be considered a natural source and a safe alternative to the synthetically derived pigments, which has become a deciding factor for consumers [4, 5].

Many microorganisms depend on light as a fundamental factor for carotenoid production. In the case of photosynthetic microorganisms, such as microalgae, known amongst the highest carotenoid producers, light is necessary for autotrophic growth and subsequent carotenoid production. Through photosynthesis, these microorganisms, consume CO2 in the presence of light and use it to grow and produce byproducts. This dependence on light, however, leads to some constraints, since higher biomass concentrations will result in lower light penetration, which can hinder culture growth and reduce production yields [6]. As well, for heterotrophic growth, in microalgae, yeast, or bacteria, light can be fundamental as a powerful inducer, or necessary factor, for carotenoid production [7]. To overcome this problem, reactor designs had to be adjusted to increase surface area and light exposure, resulting in larger, more complex biorefineries, which demand higher extents of land use and/or greater initial costs [8].

When producing microbial biomass in an industrial setting, operation conditions can greatly impact production costs and process efficiency [9]. Many microbial-based industries struggle to optimize culture conditions to increase process efficiency [10]. In a biorefinery, carotenoid production could be viewed as a high-added-value byproduct and not as the focus of the process. In this perspective, the ability to produce carotenoids without a light source would make the process much easier, allowing the use of more conventional installations, and bioreactors, reducing the need for space, or complex infrastructures, leading to a reduction in installation costs [11].

The genus Gordoniais known for its carotenoid producers, such as strains of Gordonia alkanivorans, Gordonia jacobea, Gordonia terrae, Gordonia ajoucoccusand Gordonia amicalis[7, 12, 13, 14, 15]. Gordonia alkanivoransstrain 1B is a bacterium with high biotechnological interest. It has been extensively studied for its biodesulfurization (BDS) abilities, as a biocatalyst to substitute/complement the conventional fuel desulfurization methods. Using the 4S pathway, strain 1B can remove sulfur from complex organo-sulfur molecules, at ambient temperatures and pressures, without the need for additional treatments, potentially making the process more efficient and less pollutant [16, 17, 18, 19, 20]. However, one of the drawbacks that may hinder the BDS scale-up is the lack of economic viability, thus measures to reduce the overall process costs to make BDS with strain 1B economically competitive include the use of cost-effective feedstocks [21, 22, 23, 24], culture medium minimization [10] and the exploitation of high-added value byproducts, such as biosurfactants and carotenoids [25, 26].

Carotenoid production is an attribute seldomly valorized in the literature related to biodesulfurizing microorganisms; however, it is commonly found in isolates from oil and oil-contaminated environments [27, 28, 29, 30, 31].

G. alkanivoransstrain 1B was repeatedly described as a good carotenoid producer, presenting different concentrations and production profiles depending on its growth conditions [7, 25, 32]. Of the different carotenoids produced, three have been identified as canthaxanthin, astaxanthin, and lutein, by comparing with their respective standards through HPLC [7, 25]. Several carbon and sulfur sources have been tested as inducers, to increase carotenoid production with this strain, and initial studies have revealed that glucose and sulfate in abundance, in the presence of light, promote the highest accumulation of carotenoids [7, 32]. However, Gordonia alkanivoransstrain 1B is one of the few described fructophilic bacteria [17], meaning it presents higher growth rates with fructose, producing biomass at faster rates, but also fewer carotenoids [32]. Furthermore, the presence of sulfate causes the inhibition of the biodesulfurization pathways. Concentrations as low as 30 mg/L almost completely inhibit desulfurization, even in the presence of organosulfur inducers [23].

Some work has already been performed to better understand how these factors (carbon-source/sulfur-source) correlate to generate the highest biomass and carotenoid productivity [32], however, it was mostly performed under the influence of light. Indeed, up to now, little is still known on how factors, such as carbon source and sulfur source concentrations, influence carotenoid production by G. alkanivoransstrain 1B without the stimulus of light. Moreover, there is also a need to better understand the correlation between carotenoid accumulation, biomass production, and carbon consumption, with and without light. The correct balance between these responses is fundamental to better understand the metabolism of strain 1B and efficiently drive the process toward the production of either biomass (i.e., biocatalysts for desulfurization) or carotenoids, depending on the purpose of the biorefinery in consideration (bioproduct versusbioprocess).

This work initially focuses on the optimization of culture conditions toward carotenoid production by G. alkanivoransstrain 1B without the stimulus of light. In this context, a surface response methodology (SRM) based on the Doehlert [33] distribution for two factors (% of glucose in a mixture of glucose + fructose (10 g/L total sugars); and sulfate concentration) was performed in the absence of light. Moreover, these SMR results (total biomass; total carotenoid production) were compared with the SRM results previously obtained by Fernandes et al. [32] for the carotenoids production in the presence of light (400 lux). In addition to biomass and carotenoids, specific carotenoid production (μg of carotenoids/g of dry cell weight), carbon consumption, and carotenoid and biomass production per carbon consumed were also evaluated as responses, both in absence/presence of light.

## 2. Materials and methods

### 2.1 Chemicals

Sodium sulfate anhydrous (>99%) was from Merck (New Jersey, USA). Dimethyl sulfoxide (DMSO) (99.9%), acetone (99.9%), ethyl acetate (99.8%), and methanol (99.9%) were obtained from Carlo Erba Reagents (Val de Reuil, France). The remaining reagents were of the highest grade commercially available. Stock solutions of glucose (glu) and fructose (fru) were prepared at 50% (w/v), filter sterilized, and stored for further use as a carbon source (C-source) in culture media. In the same way, a stock solution of 20 g/L Na2SO4 was also prepared and autoclaved (121°C, 1.03 bar, 15 min) to be further used as the sulfur source (S-source).

### 2.2 Microorganism and culture conditions

The microorganism used in this study was G. alkanivoransstrain 1B, a bacterium isolated in our laboratory [16], and kept at a culture collection of microorganisms (CCM at LNEG, Portugal, Lisbon). The basal salts medium used for cultivation, maintenance, and for all the growth/carotenoid production assays was described in Ref. [32]. The final pH was adjusted to 7.5 prior to sterilization by autoclave (121°C, 1.03 bar, 15 min). Afterward, the C-source (fructose and/or glucose) was added to the culture medium, in aseptic conditions, to an initial concentration of 10 g/L of total sugar(s). Similarly, the stock solution of S-source (Na2SO4) was also added to obtain the desired final concentrations of 9.04 mg/L, 22 mg/L, and 34.99 mg/L, depending on the assay.

The bacterial cultures were performed in 500 mL Erlenmeyer shake-flasks containing 150 mL culture medium, covered in tin foil to avoid light exposure, incubated in an orbital shaker (≈150 rpm) within an acclimatization chamber (Fitoclima 14000E Walk-In, Aralab, Portugal), at 30°C. All the assays were performed at least in duplicate. Sampling was carried out at 72 h and 216 h for immediate biomass determination (DCW = dry cell weight in g/L), while the remainder of each sample was centrifuged (8600 g at 4–5°C, 20 min in a refrigerated Sigma 2–16 K centrifuge) and the respective cells stored at −20°C until further pigment extraction and analysis. The supernatant was evaluated for sugar concentration through HPLC, using a Sugar-Pak 1 column (6.5 × 300 mm, 10 μm, Waters™, MA, USA) [32].

### 2.3 Experimental design methodology

A Doehlert distribution for two factors was used as the base for a surface response methodology (SRM) [33] to study carotenoid and biomass production by G. alkanivoransstrain 1B in the absence of light (L0). The two factors studied were: X1 – % of glucose in mixture glucose + fructose of 10 g/L of total sugars (0–100% glucose in the mix) and X2 – sulfate concentration (7–37 mg/L of sulfate). Fourteen experiments (seven conditions in duplicate) were carried out. The results were evaluated in terms of responses (Yi): biomass and total carotenoids production by strain 1B, at 72 h and 216 h. The model used to express the responses was a second-order polynomial model:

Yi=β0+β1X1+β2X2+β12X12+β11X12+β22X22E1

where: Yi– response from experiment i; β– parameters of the polynomial model; and X– experimental factor level [7, 23, 32].

In addition, specific carotenoid production (μg of carotenoids/g of DCW) was also evaluated as another response, both with and without a light source. The same polynomial model was applied to these results to generate the corresponding response surfaces. Model validation was performed through the Fischer test, for the effectiveness of the factors and the lack of fit, and R2 (coefficient of multiple determination).

### 2.4 Carotenoid extraction and analysis

Carotenoid extraction and further characterization were performed following the procedure described in Ref. [7, 32]. The pigment results are presented as μg of total carotenoid produced (μg carotenoids per 150 mL) or as specific carotenoid production (μg of carotenoids/g of DCW).

## 3. Results and discussion

### 3.1 Experimental design (ED-L0)

Table 1 shows the set of tests performed within the experimental design (ED), to study carotenoid and biomass production by strain 1B in the absence of light (L0), and the responses obtained (biomass and total carotenoid production, both after 72 h and 216 h). Figure 1 shows the response surfaces for the variation of biomass (Figure 1A and B) and total carotenoid production (Figure 1C and D), within the experimental domain, based on the responses observed.

In terms of biomass production, it is possible to see that at 72 h both factors influenced the response. The highest results were obtained with glucose ≤50% and sulfate at 22 mg/L. Further increases in glucose % resulted in a significant reduction of biomass regardless of sulfate concentration, with the lowest value being registered with 100% glucose, having a difference of more than six-fold when compared to the best results (0.72 vs. 4.66 g/L). This indicates that, at this time, when glucose % is above 50% it becomes the most influential factor, as corroborated by the more vertical lines of the left quadrants of the response surfaces (Figure 1A). Sulfate concentrations below and above 22 mg/L also resulted in lower biomass production, even with glucose at 25%. This was especially evident with 9.01 mg/L of sulfate, as biomass never reached 3 g/L regardless of glucose concentration. In fact, sulfate was the most influential factor up to 20 mg/L, when glucose was below 50%, clearly demonstrated by the horizontal lines in the lower left quadrants of the response surfaces.

After 216 h, both factors continue to influence biomass production. However, contrary to what was observed at 72 h, an increase of glucose % was shown to have a positive effect on biomass, especially for values above 25%, regardless of sulfate concentration. The highest biomass concentration was observed with 100% glucose and 22 mg/L of sulfate (Table 1; tests 3–4: 3.98 g/L DCW), while the lowest results were registered with 9.01 mg/L of sulfate (Table 1; tests 9–10: 2.16 g/L DCW and tests 11–12: 2.38 g/L DCW). Increasing sulfate concentration resulted in a significant increase of biomass up to 22 mg/L, after which its influence is greatly reduced, regardless of glucose %, as seen in the lower half of Figure 1B.

The results obtained at both times (72 h and 216 h) are in accordance with the fructophilic nature of this strain, as described by Alves and Paixão [17]. Up to 72 h, when glucose and fructose are at a 50:50 ratio in a 10 g/L mix, there is no significant difference from growth with 0% glucose (100% fructose); therefore, by this time and within this range of glucose %, the growth is mostly finished, achieving the highest results. Further increases of glucose % result in lower biomass production, confirming that fructose has a stimulant effect on growth rates. When glucose represents 100% of the 10 g/L mix, and there is no fructose to induce biomass formation, the lag phase becomes longer, and the culture presents its lowest results. At 216 h, glucose seems to have a stimulant effect toward biomass production, however, this is also the result of its fructophilic nature. Between 72 h and 216 h, cultures with higher glucose % were at an earlier stage of their growth, and as such continued to increase biomass production. On the other hand, cultures with lower glucose %, which had already finished their development at 72 h, entered the stationary, or even cell death phase of the growth, resulting in stagnation, and/or reduction of biomass production, thus explaining this apparent contradiction.

Finally, it becomes evident that, under these conditions, a minimum sulfate concentration between 20 and 22 mg/L is needed to achieve significant biomass production. When sulfate was at 9.01 mg/L, biomass never reached a concentration of 3 g/L regardless of time or glucose %. On the other hand, an increase to 34.99 mg/L was mostly shown to have a small effect on biomass, thus reinforcing the notion that 22 mg/L of sulfate is sufficient for the consumption of 10 g/L of glucose/fructose.

In terms of total carotenoid production (μg of carotenoids per shake-flask), at 72 h, it is clear that both factors equally influence the response. In fact, at this time the optimum conditions were found at the center of the experimental domain. As seen in both Table 1 and Figure 1C, this response is at its highest (65.4 μg) when glucose % is at 50%, and sulfate is of about 22 mg/L. Any significant deviation from these values results in a reduction of total carotenoid production.

At 216 h, total carotenoid production was positively influenced by both factors. Glucose % is shown to have the highest influence, increasing its impact for higher values of this parameter. This is especially true above 75%, since an increase to 100% glucose in the sugar mix resulted in an increase of 75% of total carotenoid production, from 178.2 to 311.1 μg, the highest observed in this ED. The lowest values were observed for conditions with sulfate at 9.01 mg/L (Table 1; tests 9-10: 32.8 μg and tests 11-12: 52.2 μg). As seen with biomass, increasing sulfate up to 22 mg/L resulted in an increase in response to more than double. Further increases in sulfate concentration have a smaller but positive impact. Figure 1D indicates that this production could be further increased by combining the maximum of both factors with glucose % at 100% and sulfate at 37.0 mg/L reaching a value close to 350 μg per culture flask.

At 72 h, it is possible to see equilibrium between biomass production and carotenoid induction, guaranteed by the presence of both sugars and enough sulfate to ensure complete carbon consumption. While glucose stimulates pigment production, it induces slower biomass formation, so if there is no fructose in the sugar mix, there will be fewer cells, resulting in less carotenoids.

Changing any of these conditions would result in a reduction of response, as demonstrated by the concentric lines of the response surface (Figure 1C). After 216 h of growth, the response changes and both factors presented a positive influence on the total carotenoid concentration, reaching a theoretical maximum at 100% glucose and 37 mg/L of sulfate. Overall, for lower glucose % in mix and/or lower sulfate concentration, sulfate concentration appeared to have greater influence, as seen in horizontal and diagonal lines in the lower quadrants. As for higher sulfate and glucose concentrations, the percentage of glucose/total sugars presented the highest influence, evidenced by the much more vertical lines in the upper quadrants.

#### 3.1.1 Analysis of ED factors

The data obtained from the ED-L0 was further used for regression analysis, and the polynomial model-derived parameters (β0β22) are shown in Table 2. The β parameters of this polynomial model used to estimate the responses have the following meanings: β0 represents the center of the experimental domain; β1 and β2 indicate the importance of the respective factors (factor 1: % glucose in a mixture glu + fru or glucose ratio, and factor 2: sulfate concentration, respectively) on the responses. The interaction parameter, β12, indicates how the effect of one factor is dependent on the level of the other factor. β11 and β12 values determine how the response surface folds downward (negative values) or upward (positive values) quadratically, more or less rapidly in accordance with the magnitude of the absolute value [23].

Test (#)Responses
DarkLight*
FactorsBiomass (g/L)Carotenoids (μg)Biomass (g/L)Carotenoids (μg)
Glucose (%)Sulfate (mg/L)72 h216 h72 h216 h72 h216 h72 h216 h
150223.873.5374.6110.22.424.2230.8400.5
250224.173.7656.2125.52.304.65215.4435.8
3100220.814.0640.6336.80.324.17103.7912.7
4100220.633.9039.7285.30.403.2782.6675.6
50224.063.2531.892.62.864.55290.2462.0
60225.253.0540.369.02.844.63303.1493.8
77534.993.393.7952.81852.425.00286.8592.5
87534.993.113.5961.3171.42.804.57315.4514.4
9259.011.992.195.134.01.832.39104.0136.3
10259.012.872.1311.031.61.752.30195.2257.0
11759.012.552.4519.458.71.812.43151.6204.2
12759.012.932.3031.645.71.792.27155.8197.7
132534.993.523.2320.384.42.484.71225.0427.0
142534.993.992.9921.187.11.994.71235.3427.0

### Table 1.

Doehlert distribution for two factors: % of glucose in mixture glucose + fructose (0–100%) and sulfate concentration (7–37 mg/L), and the responses evaluated (biomass and total carotenoids) in absence of light (ED-L0) versuswith light (400 lux, ED-L400). Seven conditions were tested in duplicates (14 tests), for statistical analysis.

Environmental conditionsDark (L0)Light (L400)*
ResponsesBiomassCarotenoidsBiomassCarotenoids
Time72 h216 h72 h216 h72 h216 h72 h216 h
Model parametersβ04.023.6565.4117.872.364.43223.14418.21
β1−1.340.4110.3395.39−0.77−0.1−55.33137.27
β20.530.6512.7651.660.361.0865.8150.83
β12−0.470.2110.9142.170.210.6538.59105.36
β11−1.33−0.08−27.378.06−0.76−0.27−28.23217.83
β22−0.86−1.06−41.01−66.86−0.08−1.43−9.94−191.0
Model validation (Fischer test)Effectiveness of parameters4.0473.955.6425.52.894.172.4715.88
Significance level (α), F (5,8)0.040.0010.020.0010.090.040.120.001
Lack of fit23.680.0217.2517.1793.513.2935.820.78
Significance level (α), F (1,7)0.001>0.1000.0040.0040.001>0.10.0005>0.1
R2Coefficient of multiple determination0.720.980.780.940.640.720.610.91

### Table 2.

Parameters of the polynomial model representing the responses studied (biomass production; total carotenoid production), with and without light (L400vs L0), at 72 h and 216 h. β0, response at the center of the experimental domain; β1 and β2, parameters of the factors 1 (% glucose in a mix glu + fru) and 2 (sulfate concentration, mg/L), respectively; β12, parameter of the interaction of the factors 1 and 2; β11 and β22, self-interaction parameters of the factors 1 and 2, respectively.

At 72 h, β1 and β2 have opposite influences. β1 presents the greatest value, indicating that glucose % has the highest influence on biomass production. However, being negative, β1 also indicates that increasing this factor leads to a decrease in response, meaning that an increase of glucose % leads to a decrease in biomass. On the other hand, β2 has a smaller, positive value indicating that an increase in sulfate concentration leads to an increase in biomass production. Analyzing pigment production at 72 h, β1, β2, and β12 presented positive values, indicating that the increase of each factor, individually or simultaneously, results in an increase of the response. Sulfate concentration was the factor with the greatest influence on pigment production.

At 216 h, there was a change in the response, as illustrated by the βparameters. Increasing each factor led to an increase in both biomass and pigment production. As shown in Table 2, for these conditions, sulfate concentration had a greater influence on biomass production (β2 was 1.5-fold higher than β1), however, pigment production was mostly influenced by glucose ratio (β1 almost two-fold higher than β2).

#### 3.1.2 Comparing light and dark influence on carotenoid production

In a previous work [32], a similar experimental design was performed to evaluate the influence of light (400 lux). The results from that work, referred to as ED-L400, are presented in Table 1 and Figure 2AD. From the comparison of ED-L0 and ED-L400 results (Figure 1versusFigure 2), several differences become evident. In terms of biomass production, at 72 h optimum conditions do not differ substantially; however, the average results obtained under dark conditions were higher for every condition tested. This seems to indicate an inhibitory effect of the light source on growth rates, possibly resulting from the allocation of nutrients toward carotenoid production.

At 216 h, when sulfate concentration was 9.01 mg/L (Table 1: tests 9–12), there was no difference between light and dark cultures, and biomass did not surpass 3 g/L, reinforcing the observation that sulfate, at this concentration, was limiting. For the remaining conditions, there seemed to be a response in which cultures were grown with lower glucose %, and consequently with higher fructose concentrations, have lower biomass under dark conditions (Table 1: tests 5-6 and 13-14). As suggested above, this can be explained by the faster growth of these cultures under dark conditions, that by 216 h were already undergoing the cellular death phase. The inhibitory effect of the light source lowered the overall growth rates, to the point that, under light conditions, at 216 h these cultures were at an earlier stage of the growth, explaining the increased absorbance. For cultures with higher levels of glucose, since the growth rate is already slower, the inhibitory effects of light were not so evident with this two-point sampling (72 h and 216 h).

In terms of total carotenoid production, in both cases, the best results were obtained after 216 h with 100% glucose and 22 mg/L sulfate. However, the best average results obtained under light (∼794 μg) were more than two-fold higher than those obtained in the dark conditions (∼311 μg). Regardless of the presence of a light source, there was an increase of total carotenoid production from 72 h to 216 h for every condition tested. In both studies, at 72 h, this response was negatively influenced by higher glucose percentages in the mix. This effect, which is especially evident under light, seems to be mitigated, in both cases, by a higher concentration of sulfates. At 216 h this effect is reversed, and response is stimulated by glucose, since, as explained above, glucose induces slower growth rates, and longer division times would benefit such cultures.

Analyzing the beta parameters for both EDs (Table 2), the differences are again evident. At 72 h, in terms of biomass, each factor individually influences the response in a similar manner (β1 and β2). However, when both factors were increased simultaneously (β12), the responses observed were opposite. Under dark conditions, this led to a decrease in biomass, while with light, it increased biomass production. This could indicate that, in the presence of light, the inhibitory effect that glucose has on biomass production can be partially reversed by increasing sulfate concentration, while under dark conditions, it can only be mitigated, maintaining the negative effect. The existence of this inhibitory effect was not previously observed, since, up to now, the works performed with sugar mixtures, did not take into account the conjugation of a lack of sulfur and light sources [17]. Nevertheless, Silva et al. [7] have already referred that strain 1B showed lower growth rates under the light. At 216 h the concentration of glucose has opposite effects depending on the presence of the light source. In the dark, it has a positive effect, while with light, it has a slightly negative influence. Furthermore, the relative influence of sulfate (β2) was higher with light, while glucose (β1) was higher without.

In terms of total carotenoid production, at 72 h, comparing β1, β2, and β12 to their respective β0, it becomes clear that the studied factors presented a greater relative influence under light. Moreover, the increase of the glucose % (β1) led to opposite responses. In the absence of light, an increase of glucose % resulted in an increase of total carotenoids, while in its presence, it greatly reduced total carotenoid production. At 216 h, total carotenoid production was positively influenced by all factors in both cases. However, all factors, especially glucose concentration, have greater relative importance under dark conditions. This indicates that in the absence of the stimulus of light, sulfate concentration, % of glucose in the sugar mix, and even time have greater importance for this response.

### 3.2 Specific carotenoid production

Total carotenoid production is an important parameter for the industrial process. Since it indicates the amount of carotenoids obtained in a certain volume of culture, it is deeply influenced by biomass production. The best conditions for total carotenoid production are obtained when there is a compromise between the highest carotenoid and highest biomass production. However, to better understand the mechanisms that influence carotenoid synthesis, it is fundamental to analyze specific carotenoid production (μg of carotenoids per g of dry cell weight - μg(Carotenoids)/g(DCW) or μg/g(DCW)). By evaluating the concentration of carotenoids per g of cells, it is possible to determine, which conditions induce greater cellular accumulation.

Using the results obtained in terms of biomass and total carotenoids, for each condition tested, the specific carotenoid concentrations were calculated, for both EDs, at dark and light conditions, at 72 h and 216 h and are presented in Table 3, with the corresponding response surfaces represented in Figure 3AD.

Test (#)Response
FactorsDark (L0)Light (L400)
Glucose (%)Sulfate
(mg/L)
72 h216 h72 h216 h
μg/g(DCW)μg/g(DCW)μg/g(DCW)μg/g(DCW)
15022128.51208.12635.81635.71
2502289.85222.52624.35624.80
310022334.16553.042160.421459.15
410022420.11487.691376.671377.37
502252.22189.95676.46676.92
602251.17150.82711.50711.02
77534.99103.83325.42790.08790.00
87534.99131.40318.29750.95750.40
9259.0117.09103.50378.87380.20
10259.0125.5598.90743.62744.93
11759.0150.72159.73558.38560.22
12759.0171.90132.46580.26580.62
132534.9938.45174.20604.84604.39
142534.9935.25194.20788.27604.39

### Table 3.

Doehlert distribution for two factors: % of glucose in mixture glucose + fructose (0–100%) and sulfate concentration (7–37 mg/L), and the response in terms of specific carotenoid production (μg/g(DCW)), with and without light (L400vs L0), at 72 h and 216 h. seven conditions were tested in duplicates (14 tests), for statistical analysis.

Observing these results, it is possible to see that there are two very different behaviors in relation to time. Under the effects of light, the specific production of carotenoids is almost unchanged throughout the time period, from 72 h to 216 h (Table 3; Figure 3A and B). However, when the culture is grown in the darkness, time clearly has a significant influence, leading to a considerable increase of the carotenoids concentration present in the bacterial biomass, as well as to different influences of the studied factors, easily seen in the response surfaces in Figure 3C and D. In previous works, this feature had gone unnoticed since it is not observable when analyzing only the total carotenoid production.

From Table 3, it is also possible to determine that, for the same tests, specific carotenoid production was always greater in the presence of light, although this difference was more evident at 72 h. Tests 3 and 4, with glucose at 100% of the sugar mix and 22 mg/L of sulfates, always presented the highest response in each set of assays (L400/L0).

Further analyzing the results obtained in the presence of light, it is possible to see that, at both times, the two factors had a positive influence on specific carotenoid production. Maximum values were observed with 100% glucose and 22 mg/L of sulfate, while the lowest was registered with 9.01 mg/L of sulfates regardless of glucose percentage. As shown in Figure 3A and B, glucose % is the most influential factor, evidenced by the almost vertical lines, with sulfate having a smaller influence, mostly for values below 22 mg/L. Optimum conditions for maximum specific carotenoid production are glucose at 100% of the sugar mix and sulfate concentration of at least 22 mg/L. These results also seem to reinforce the idea that the presence of fructose interferes with the cellular accumulation of carotenoids. Even at lower fructose concentrations (2.5 g/L in 10 g/L mix), specific carotenoid concentration only reaches 770 μg/g(DCW); however, when glucose represents 100% of 10 g/L mix, cellular accumulation of carotenoids has an increase of 140% and 94% at 72 h and 216 h, respectively, showing that a small concentration of fructose can have significant negative impacts on carotenoid production.

Under dark conditions, the responses obtained at both times were similar, but differences between tests were more pronounced at 72 h. As in previous results, the highest responses were obtained with glucose at 100% and 22 mg/L of sulfate (377 μg/g(DCW)). While the lowest results were observed with glucose at 25% at either sulfate concentrations (21.3 and 36.9 μg/g(DCW)), followed by glucose at 0% (51.7 μg/g(DCW)). This indicates a lower influence of the factors, when fructose is the dominant sugar, as demonstrated by the left quadrants of Figure 3C, which show a reduced variation of the response, regardless of glucose % and sulfate concentration. When glucose % is above 50%, both factors influence the response, with glucose showing the highest influence, as shown by the almost vertical lines on the right quadrants. Sulfate concentration is mostly important up to 22 mg/L, with higher values showing reduced or even negative impact on specific carotenoid production. So, Figure 3C shows that maximum cellular carotenoids would be obtained with 100% glucose and 22 mg/L, as it was tested (Table 3, tests 3 and 4).

At 216 h, carotenoid concentrations were higher for every condition tested. The highest value was recorded with 100% glucose and 22 mg/L of sulfate (520 μg/g DCW). The lowest values were observed when sulfate was at 9.01 mg/L with glucose at 25% (101 μg/g(DCW)) and 75% (146.10 μg/g(DCW)). Both factors have a positive influence on the cellular accumulation of carotenoids; however, when sulfate is 22 mg/L or higher, glucose has the highest influence, shown by the vertical lines in the upper right corner of Figure 3D. Results indicate that the highest specific carotenoid production could be achieved with glucose 100% and sulfate >35 mg/L.

These results also indicate that a concentration of 9.01 mg/L of sulfate hinders specific carotenoid production, not only biomass production, and 22 mg/L of sulfate are sufficient for high carotenoid production, at earlier stages of the growth (72 h), with further increases having minimal impact. At later times of growth, increasing sulfate concentration to 34.99 mg/L leads to increases in cellular accumulation of carotenoids, most likely because cellular needs for growth are met and it can be diverted toward secondary metabolite production.

Most importantly, fructose seems to have an inhibitory effect on carotenogenesis. Under these conditions, since the tests were performed with a mix of fructose and glucose, with different percentages while maintaining 10 g/L of total sugars, when glucose % was increased, there was a proportional decrease in fructose. So, when glucose was increased from 25 to 50% (and sulfate from 9.01 to 22 mg/L) there was a 25% reduction in fructose, which caused a very significant increase in the accumulation of carotenoids (five-fold at 72 h and two-fold at 216 h). A further increase of both glucose and sulfate values to 75% and 34.99 mg/L, respectively, resulted in a much lower or nonexistent increase in the response, especially at 72 h. However, by completely removing fructose from the mix, from 50–0% fructose (Table 3; tests 1-2 and 5-6), even without increasing sulfate concentration, there was an increase in response (μg(Carotenoids)/g(DCW)) of more than three-fold at 72 h and more than two-fold at 216 h. This seems to indicate an inhibitory effect, which is slightly lower at 216 h, since most fructose has been completely consumed within 72 h to 76 h, possibly attenuating its inhibitory effects. Furthermore, cells grown with glucose at 25% were those that had the highest increase over time, raising cellular concentration of carotenoids 4.75- and five-fold; while for higher glucose %, the increase was under three-fold, further reinforcing the theory that carotenoid production is increased after fructose disappears, especially when glucose is present.

Sugars having inhibitory effects on carotenoid synthesis is a known phenomenon, mostly observed for glucose. Some researchers proposed the use of alternative sugars, or alcohols, as C-sources, to achieve higher carotenoid concentrations. In fact, a similar phenomenon was described for Xanthophyllomyces dendrorhous, a yeast that produces astaxanthin. This microorganism starts to produce carotenoids at the stationary phase of the growth if grown with glucose but starts the production at the beginning of the growth if cultivated with succinate [34]. Since G. alkanivoransstrain 1B is a fructophilic bacterium [17], it could be the case that similar mechanisms are being applied to its preferred C-source, explaining the reduced carotenoid production in the presence of this sugar.

Table 4 presents the beta parameters for the polynomial model used for the specific carotenoid production, showing the influence of each factor studied (% glucose in a mix glu + fru; sulfate concentration). It is possible to note that both factors have a positive influence on the response. It is also clear that glucose percentage is the most influential factor on the conditions tested (Figure 3), being several times more influential than sulfate concentration in all cases.

 Response μg(Carotenoids)/g(DCW) Environmental conditions Dark (L0) Light (L400) Time 72 h 216 h 72 h 216 h Model parameters β0 109.19 215.35 630.19 630.37 β1 128.61 147.08 371.86 270.38 β2 20.74 74.69 97.14 69.74 β12 23.54 53.55 38.04 91.19 β11 105.23 130.03 601.09 424.76 β22 −101.63 −79.38 −174.79 −146.61 Model validation (Fischer test) Effectiveness of parameters 14.01 28.95 4.15 9.32 Significance level (α), F(5,8) 0.001 0.001 0.05 0.01 Lack of fit 19.22 18.11 5.86 9.9 Significance level (α), F(1,7) 0.01 0.01 0.05 0.05 R2 Coefficient of multiple determination 0.9 0.95 0.72 0.85

### Table 4.

Parameters of the polynomial model representing specific carotenoid production (μg/g(DCW)), with and without light, at 72 h and 216 h. β0, response at the center of the experimental domain; β1 and β2, parameters of the factors 1 (% glucose in a mix glu + fru) and 2 (sulfate concentration, mg/L), respectively; β12, parameter of the interaction of the factors 1 and 2; β11 and β22, self-interaction parameters of the factors 1 and 2, respectively.

Considering the responses at the center of the domain (β0), it becomes clear that both factors have a greater relative influence under dark conditions, despite having significantly lower responses. Glucose concentration is especially influential at 72 h, as β1 is greater than β0. Moreover, under light, the relative importance of the individual factors reduces with time, while under dark conditions, the relative influence of sulfate increases, and that of the glucose percentage is reduced.

Comparing the overall results for specific carotenoid production (Table 3; Figure 3) with those obtained for total carotenoid production (Table 1, Figure 2), it becomes visible that, under light, cellular carotenoid production is not influenced by time above 72 h, meaning that total carotenoid production increased due to an increase in biomass concentration and not in the cellular carotenoid concentration. In the same way, the sulfate concentration had a greater influence on total carotenoid production, due to its importance for biomass production. Values above 22 mg/L had little effect on cellular carotenoid production, despite increasing total carotenoid production. Under dark conditions, by comparing the response surfaces obtained for specific carotenoid production (Figure 3C and D) with those obtained for total carotenoids (Figure 1C and D), it is possible to observe that there are significant differences at 72 h since at this time the biomass produced is very different depending on the conditions tested. So, the conditions for the highest total carotenoid production will lead to more biomass, but not the cells at the highest pigmentation. At 216 h, the figures are much similar, since the differences between biomass were much smaller.

### 3.3 Influence of the carbon source

#### 3.3.1 Carbon consumption

Sugar consumption was greatly affected by the influence of light, under some conditions, sugars were fully consumed, while in others sugar consumption was residual. Due to this range of results, carbon consumption could not be properly represented by the models previously applied. However, given their importance to understanding the metabolic response, total sugar consumption results were displayed in Figure 4AD, to better illustrate how they were influenced by the factors studied in EDs (L0 and L400).

Under dark conditions, at 72 h (Figure 4C), it is possible to see that the tests with more glucose and less sulfate were those in which sugar consumption was the lowest. Except for the conditions when glucose was at 75%, fructose was always completely consumed, which seems to indicate a slower consumption of glucose, expected from this fructophilic strain. At 216 h (Figure 4D), sugars were completely consumed, apart from the tests with lower sulfate concentration, which maintained the same concentration values presented at 72 h, and one of the replicates with 100% glucose. This reinforces the concept that sulfate levels were limiting the growth of the culture, and that a value higher than 9.01 mg/L is needed to consume 10 g/L of sugars.

Under light, at 72 h, none of the tests resulted in the complete consumption of sugars. The highest result (8.81 g/L) was observed when glucose was at 0% and fructose was the sole C-source. As shown in Figure 4A, increasing glucose % resulted in a decrease in sugar consumption that was especially evident above 50% glucose with 22–34.99 mg/L of sulfate. The lowest sugar consumption was observed when glucose was 100% of the 10 g/L sugar mix, where the culture was still in its lag phase, and sugar consumption was residual (0.0042 g/L). At 216 h (Figure 4B), sugars were fully consumed when glucose percentage was up to 50% and sulfate concentration was ≥22 mg/L. At 75% glucose with 34.99 mg/L sulfate, less than 2.2 g/L were left as residual, and at 100% glucose, less than 5 of the 10 g/L of initial glucose were consumed.

Comparing both light and dark results, there was a clear inhibitory effect of the light source, in terms of consumption of both sugars, this had only been described for glucose, mostly because assays with fructose ended before 72 h. Moreover, these results also point out that, with sufficient sulfur source, carbon source consumption is reduced, there is an accentuated fructophilic behavior and a significant effect of the glucose concentration under light conditions. The presence of fructose, greatly accelerated sugar consumption, as seen when comparing the results of 75% glucose and 100% glucose on every assay.

#### 3.3.2 Carbon conversion to biomass

To better understand and prepare a future biorefinery it is important to evaluate how carbon is diverted toward biomass production. As such, based on the results for biomass production and carbon consumption, Figure 5AD was created, illustrating biomass produced (g/L DCW) per total sugar consumed (g/L), that is, (g/g), for the different conditions tested.

At 72 h, with light (Figure 5A), the highest result was achieved with 75% glucose and 34.99 mg/L of sulfate (0.52 g/g), any reduction in glucose % or sulfate concentration resulted in a decrease in response. The remaining conditions had values between 0.33 and 0.25 g/g. Results with glucose at 100% of the mix were disregarded, since as previously stated, under these conditions the culture was still in its lag phase, there was residual carbon consumption and residual biomass production. At 216 h (Figure 5B), carbon conversion to biomass increased on every condition tested, nonetheless, the general trends remained similar. The highest result was registered with 100% glucose (0.76 g/g), followed by 75% glucose with 34.99 mg/L of sulfate (0.65 g/g), the lowest was also observed with 75% glucose but with 9.01 mg/L (0.3 g/g). The remaining results varied between 0.44 g/g and 0.51 g/g.

This shows that higher concentrations of glucose and sulfate result in a higher carbon conversion to biomass. However, since fructose is needed to induce faster biomass production, 100% glucose leads to lower initial results, this can be surpassed by maintaining a small concentration of fructose, no more than 25% of total sugars. Furthermore, it also seems to indicate that carbon conversion to biomass increases with time. This could result from the accumulation of reserve substances at later times, in response to the stimulus of light, coupled with a slower metabolic activity which results in less carbon being converted to CO2.

Under dark conditions, at 72 h (Figure 5C), significant differences were mostly observed at both extremes of glucose %, with 22 mg/L of sulfate. The highest result occurred with 0% glucose (0.47 g/g) and the lowest with 100% glucose (0.22 g/g). The remaining conditions resulted in values between 0.32 g/g and 0.43 g/g without a defined tendency. At 72 h sulfate appears to be less influential to how cells allocate carbon, most influence is centered on the presence/absence of fructose and glucose. Indicating that the nature of carbon source leads to different metabolic responses, which could be related to the fructophilic behavior of G. alkanivoransstrain 1B. After 216 h (Figure 5D), the lowest results were observed with glucose <50% or sulfate <22 mg/L (0.27–0.32 g/g). The highest result was achieved with 100% glucose and 22 mg/L of sulfates (0.48 g/g). Overall, carbon conversion to biomass appears to be stimulated by higher glucose %. Sulfate concentration also stimulates this response, up to 22 mg/L, greater increases seem to have no influence. This could indicate that fructose stimulates the production of extracellular compounds, such as biosurfactants [26], and glucose the accumulation of reserve substances, such as lipids [35], thus diverting carbon to different pathways.

Comparing the results obtained, at 72 h, carbon conversion to biomass was mostly higher under dark conditions, however, at 216 h this is reversed. Moreover, higher glucose and sulfate concentrations at later times, also present higher carbon conversion rates to biomass, with the highest results being obtained at 216 h, with light, 100% glucose, and 22 mg/L of sulfate.

Without light, when there was lower glucose %, time led to a reduction in carbon conversion to biomass, even if there was very few or no carbon left at 72 h. With greater glucose percentages, there was an increase of carbon conversion to biomass from 72 h to 216 h, even when sugar was already consumed at 72 h. Comparing each individual value obtained at 216 h and 72 h (Figure 5C and D), it becomes clear that, over time, carbon conversion to biomass increases with the increase in glucose % (0 < 25 < 50 < 75 < 100%). This increase with time could be the result of the accumulation of reserve substances, such as lipids, sugars, or PHA’s, induced by light and/or glucose, resulting in slower growth rates, and higher carbon conversion yields. Conversely, without the stimulus of light, especially at greater fructose concentrations, growth rates are higher, but there is a loss of biomass over time, which could indicate that cells produce fewer reserve substances, or that these are converted, or released into the medium in the form of biosurfactants or other exopolysaccharides, resulting in loss of dry weight. Alternatively, this could be the result of a higher metabolic activity induced by fructose, as highlighted by Alves and Paixão [17], which could result in cells with lower abundance of reserve substances, leading to greater cellular lysis over time.

Other fructophilic bacteria and yeast have been shown to convert fructose to mannitol, which is accumulated and used as an osmolyte, a carbon reserve, or an antioxidant, substituting carotenoids in the latter function. However, the same phenomenon is not observed when glucose is the C-source [36, 37]. A similar mechanism could be occurring here, in which fructose is converted into mannitol or another intermediary and then consumed for the cell metabolism, while glucose is consumed at a slower speed, and further converted to carotenoids and other reserve substances, which would be consumed after the 216 h evaluated in this work (Figure 4).

#### 3.3.3 Specific carotenoid production per gram of sugar consumed

A final response was still obtained by combining the responses in terms of specific carotenoid production (μg(Carotenoids)/g(DCW)) per total sugar consumed (g/L), that is, specific carotenoid production per sugar consumed (μg(Carotenoids)/g(DCW)/g(Sugars)/L). This combined response indicates how efficiently sugars are converted into carotenoids in each cell. The results obtained are illustrated in Figure 6AD.

After 72 h under light, the lowest results were registered when glucose was at 0% or sulfate was 9.01 mg/L (72.31–84.17 μg(Carotenoids)/g(DCW)/g(Sugars)/L). Increases in glucose % or sulfate concentration always resulted in an increased response. The highest result calculated was obtained for 75% glucose and 34.99 mg/L of sulfate (165.71 μg(Carotenoids)/g(DCW)/g(Sugars)/L). It should be noted that cells grown on 100% glucose and 22 mg/L of sulfate revealed much greater specific carotenoid production, and since carbon consumption at this point was still residual, the calculated result was several thousand times greater than any other, losing most of its comparative meaning (Figure 6A). However, this is not devoid of biological meaning, since it indicates that under these conditions, before biomass production begins, or sugar consumption starts, carotenoid production is already occurring, and as seen above at the same specific concentration, as later times.

After 216 h, as demonstrated in Figure 6B, the highest values were achieved when glucose was at 100% of the 10 g/L sugar mix and sulfate at 22 mg/L (293 μg(Carotenoids)/g(DCW)/g(Sugars)/L). The lowest values were obtained when glucose % was between 25 and 50% with sulfate ≥22 mg/L (60.4–63 μg(Carotenoids)/g(DCW)/g(Sugars)/L).

These results show that, at both times, glucose is the factor with most influence. At 72 h, the factors studied had a greater influence at higher concentrations of sulfate and glucose %, and both glucose and sulfate have a positive effect. At 216 h, the response presented two behaviors. For lower concentrations of sulfate, lower glucose % benefits the response, while for higher concentrations of sulfates, greater glucose % benefits the response. This could be due to the fact that lower concentrations of sulfate result in less biomass, leading to an excess carbon source, which could help induce the synthesis of carotenoids, as a response to the light. But, with greater sulfate concentration glucose acts as the inducer. Moreover, both at 72 h and 216 h, 100% glucose proved to be the best condition, even at lower sulfate concentration.

In the absence of light, at 72 h (Figure 6C), the highest results were obtained with glucose at 100% and 22 mg/L of sulfate, while the lowest were observed with glucose at 25% and sulfate at 9.01 mg/L (130 and 2.82 μg(Carotenoids)/g(DCW)/g(Sugars)/L, respectively). At 216 h (Figure 6D), the maximum and minimum values were registered at the same conditions (62.7 and 12.6 μg(Carotenoids)/g(DCW)/g(Sugars)/L, respectively). This clearly demonstrates that both factors have a positive effect on the response, also showing that under dark conditions, especially at 72 h, glucose is the most influential factor. At 216 h response values were higher, apart from the tests with 100% glucose; however, the relative importance of glucose % was lower, as shown by the closer response values, and sulfate gained influence, when glucose % was <100%. Furthermore, as previously stated, fructose seems to have an inhibitory effect on the carotenoid production, and on the efficiency of converting carbon into carotenoids, as evidenced by the difference in response values between 75% and 100% glucose, especially significant at 72 h (Figure 6C).

Comparing the results obtained for specific carotenoid production per sugar consumed (μg(Carotenoids)/g(DCW)/g(Sugars)/L) at both times, with and without light (Figure 6), it becomes clear that time, for most conditions, had opposite influences on the response. With light, carbon conversion to carotenoids mostly decreased over time, while without light, it seems to increase, except when glucose is used at 100% of the sugar mix. This fact could be a conjugation of several different factors. At earlier stages of the growth, the cells were fewer in number and had greater exposure to light, due to a lower cell density. As the cultures progressed, the number of cells increased and there was an increase in shade effect. Since under dark conditions the stimulus of light is not present, the values are lower, but increase over time. Other factors, such as oxygen and nutrient concentration vary in a similar fashion in both assays, and as such, should play a smaller role in this difference. The result observed for 100% glucose at 72 h under light is an extreme example, where the culture was only starting to grow at that point, however, the cells were heavily stimulated to produce carotenoids. The cells present at this time were mostly from the initial inoculum, and they were induced to produce carotenoids, by the presence of light, and high concentrations of glucose (100% of the 10 g/L mix) and sulfate (22 mg/L), before starting to grow and consume sugar in a significant manner.

The presence of light enhances the conversion of carbon into carotenoids in each cell, as demonstrated by the smaller response under dark conditions. Moreover, carotenoid production seems to be induced by sugar but is not dependent on it. As stated above, with light, at 72 h and 100% glucose (10 g/L), the cells were extremely rich in carotenoids, but sugar consumption was minimal. This indicates that strain 1B could be producing the carotenoids based on cellular reserve substances present in the cells of the inoculum. This is reinforced by the fact that, in the dark, with 0% glucose, and 25% glucose, there is a complete sugar consumption by 72 h (Figure 4C and D), and the specific carotenoid production increases at 216 h (Figure 6C and D). This evidence confirms what had already been reported in the work by Silva et al. [7], in which strain 1B cells grown in the dark with fructose and DBT were placed in the light after the end of the growth and have developed coloration, without additional extracellular sugar.

## 4. Conclusion

This work reinforces the importance of the sulfate concentration, the nature and ratio of the sugars used as C-source, the presence of light, and the growth time for the production of biomass and carotenoids by G. alkanivoransstrain 1B, leading to a better understanding of how these factors interact with each other to influence different metabolic responses.

In terms of sulfate, it shows that >20 mg/L are needed to consume 10 g/L C-source (glucose/fructose), while guarantying efficient biomass and carotenoid production. However, this concentration is enough to cause significant biodesulfurization inhibition, making it difficult to conjugate high carotenoid production with high desulfurization ability, without adapting the biocatalyst production method.

In terms of carbon, as expected, the presence of fructose leads to faster growth rates and greater biomass production. However, at later times, after growth has ended, it also led to a loss of biomass, especially in the absence of light, probably due to the production of extracellular compounds, such as biosurfactants. Moreover, fructose seems to inhibit carotenoid production to some extent, since even 25% of fructose can result in a great loss in carotenoid production. Glucose, on the other hand, hinders growth rates and stimulates carotenoid production and conversion of carbon to carotenoids and biomass, possibly indicating the accumulation of reserve substances, thus justifying the longer growth rates. The presence of light also seems to reduce growth rates, and stimulate carotenoid production, while making the fructophilic behavior more evident. In addition, the growth time period is especially important to generate specific carotenoids without light, and biomass in the presence of either light or greater glucose concentrations. All these responses seem to indicate that the fructophilic behavior of this strain is not simply a matter of sugar transport, since there are different metabolic behaviors in the presence/absence of both sugars.

The overall results indicate that higher glucose concentrations combined with more light, or a better-adapted system, with a higher surface to volume ratio, could drastically increase carotenoid production. In addition, this study confirms that is possible to produce carotenoids under dark conditions, and that production can be greatly stimulated by culture medium conditions. Moreover, it also reinforces that even without sugar consumption it is possible to induce carotenoid production in cells of strain 1B, opening the possibility of developing two-phase systems of biomass production based on fructose without light, and further carotenogenesis induction with light exposure, under optimal conditions.

Ultimately, these results may help in the development of a future biorefinery, either pointing the way to generate carotenoids under dark conditions, as an added value byproduct, or further increment carotenoid production in the light, as the main bioproduct.

## Acknowledgments

This work was financed by national funds through FCT (Fundação para a Ciência e a Tecnologia) in the scope of the project GreenFuel (PTDC/EAM-AMB/30975/2017). Tiago P. Silva also acknowledges FCT for his PhD financial support (SFRH/BD/104977/2014).

## References

1. 1.Ram S, Mitra M, Shah F, Tirkey SR, Mishra S. Bacteria as an alternate biofactory for carotenoid production: A review of its applications, opportunities and challenges. Journal of Functional Foods. 2020;67:103867. DOI: 10.1016/j.jff.2020.103867
2. 2.Amengual J. Bioactive properties of carotenoids in human health. Nutrients. 2019;11:1-6. DOI: 10.3390/nu11102388
3. 3.McWilliams A. The Global Market for Carotenoids. Wellesley, Massachusetts, United States: BCC Research; 2018. Report ID: FOD025F
4. 4.Gong M, Bassi A. Carotenoids from microalgae: A review of recent developments. Biotechnology Advances. 2016;34:1396-1412. DOI: 10.1016/j.biotechadv.2016.10.005
5. 5.Barreiro C, Barredo J-L. Carotenoids Production: A Healthy and Profitable Industry. Berlin/Heidelberg, Germany: Springer; 2018. pp. 45-55. DOI: 10.1007/978-1-4939-8742-9_2
6. 6.Khan MI, Shin JH, Kim JD. The promising future of microalgae: Current status, challenges, and optimization of a sustainable and renewable industry for biofuels, feed, and other products. Microbial Cell Factories. 2018;17:1-21. DOI: 10.1186/s12934-018-0879-x
7. 7.Silva TP, Paixão SM, Alves L. Ability ofGordonia alkanivoransstrain 1B for high added value carotenoids production. RSC Advances. 2016;6:58055-58063. DOI: 10.1039/c6ra08126f
8. 8.Gifuni I, Pollio A, Safi C, Marzocchella A, Olivieri G. Current bottlenecks and challenges of the microalgal biorefinery. Trends in Biotechnology. 2019;37:242-252. DOI: 10.1016/j.tibtech.2018.09.006
9. 9.Alves L, Paixão SM, Pacheco R, Ferreira AF, Silva CM. Biodesulphurization of fossil fuels: Energy, emissions and cost analysis. RSC Advances. 2015;5:34047-34057. DOI: 10.1039/C4RA14216K
10. 10.Pacheco M, Paixão SM, Silva TP, Alves L. On the road to cost-effective fossil fuel desulfurization by:Gordonia alkanivoransstrain 1B. RSC Advances. 2019;9(44):25405-25413. DOI: 10.1039/c9ra03601f
11. 11.Hu J, Nagarajan D, Zhang Q, Chang JS, Lee DJ. Heterotrophic cultivation of microalgae for pigment production: A review. Biotechnology Advances. 2018;36:54-67. DOI: 10.1016/j.biotechadv.2017.09.009
12. 12.Kim JH, Kim SH, Yoon JH, Lee PC. Carotenoid production from n-alkanes with a broad range of chain lengths by the novel speciesGordonia ajoucoccusA2T. Applied Microbiology and Biotechnology. 2014;98:3759-3768. DOI: 10.1007/s00253-014-5516-y
13. 13.Lee K-W, How CW, Chen L, Chen PT, Lan JC-W, Ng H-S. Integrated extractive disruption ofGordonia terraecells with direct recovery of carotenoids using alcohol/salt aqueous biphasic system. Separation and Purification Technology. 2019;223:107-112. DOI: 10.1016/j.seppur.2019.04.031
14. 14.Veiga-Crespo P, Blasco L, do Santos FR, Poza M, Villa TG. Influence of culture conditions ofGordonia jacobaeaMV-26 on canthaxanthin production. International Microbiology. 2005;8:55-58
15. 15.Sowani H, Deshpande A, Gupta V, Kulkarni M, Zinjarde S. Biodegradation of squalene and n-hexadecane byGordonia amicalisHS-11 with concomitant formation of biosurfactant and carotenoids. International Biodeterioration and Biodegradation. 2019;142:172-181. DOI: 10.1016/j.ibiod.2019.05.005
16. 16.Alves L, Salgueiro R, Rodrigues C, Mesquita E, Matos J, Gírio FM. Desulfurization of dibenzothiophene, benzothiophene, and other thiophene analogs by a newly isolated bacterium,Gordonia alkanivoransstrain 1B. Applied Biochemistry and Biotechnology. 2005;120(3):199-208. DOI: 10.1385/ABAB:120:3:199
17. 17.Alves L, Paixão SM. Fructophilic behaviour ofGordonia alkanivoransstrain 1B during dibenzothiophene desulfurization process. New Biotechnology. 2014;31:73-79. DOI: 10.1016/J.NBT.2013.08.007
18. 18.Paixão SM, Arez BF, Roseiro JC, Alves L. Simultaneously saccharification and fermentation approach as a tool for enhanced fossil fuels biodesulfurization. Journal of Environmental Management. 2016;182:397-405. DOI: 10.1016/j.jenvman.2016.07.099
19. 19.Paixão SM, Silva TP, Arez BF, Alves L. Advances in the reduction of the costs inherent to fossil fuels’ biodesulfurization towards its potential industrial application. Biotechnology. 2019;22:390-425. DOI: 10.4018/978-1-5225-8903-7.ch081
20. 20.Alves L, Melo M, Mendonça D, Simões F, Matos J, Tenreiro R, et al. Sequencing, cloning and expression of the dsz genes required for dibenzothiophene sulfone desulfurization fromGordonia alkanivoransstrain 1B. Enzyme and Microbial Technology. 2007;40:1598-1603. DOI: 10.1016/J.ENZMICTEC.2006.11.008
21. 21.Alves L, Paixão SM. Enhancement of dibenzothiophene desulfurization byGordonia alkanivoransstrain 1B using sugar beet molasses as alternative carbon source. Applied Biochemistry and Biotechnology. 2014;172(6):3297-3305. DOI: 10.1007/S12010-014-0763-Z
22. 22.Silva TP, Paixão SM, Roseiro JC, Alves L. Jerusalem artichoke as low-cost fructose-rich feedstock for fossil fuels desulphurization by a fructophilic bacterium. Journal of Applied Microbiology. 2015;118:609-618. DOI: 10.1111/JAM.12721
23. 23.Silva TP, Paixão SM, Teixeira AV, Roseiro JC, Alves L. Optimization of low sulfur carob pulp liquor as carbon source for fossil fuels biodesulfurization. Journal of Chemical Technology & Biotechnology. 2013;88:919-923. DOI: 10.1002/JCTB.3921
24. 24.Alves L, Marques S, Matos J, Tenreiro R, Gírio FM. Dibenzothiophene desulfurization byGordonia alkanivoransstrain 1B using recycled paper sludge hydrolyzate. Chemosphere. 2008;70:967-973. DOI: 10.1016/j.chemosphere.2007.08.016
25. 25.Silva TP, Alves L, Paixão SM. Effect of dibenzothiophene and its alkylated derivatives on coupled desulfurization and carotenoid production byGordonia alkanivoransstrain 1B. Journal of Environmental Management. 2020;270:110825. DOI: 10.1016/J.JENVMAN.2020.110825
26. 26.Tavares J, Alves L, Silva TP, Paixão SM. Design and validation of an expeditious analytical method to quantify the emulsifying activity during biosurfactants/bioemulsifiers production. Colloids and Surfaces B: Biointerfaces. 2021;208:112111. DOI: 10.1016/j.colsurfb.2021.112111
27. 27.Lee DW, Lee H, Lee AH, Kwon BO, Khim JS, Yim UH, et al. Microbial community composition and PAHs removal potential of indigenous bacteria in oil contaminated sediment of Taean coast, Korea. Environmental Pollution. 2018;234:503-512. DOI: 10.1016/J.ENVPOL.2017.11.097
28. 28.Salehi Bakhtiyari A, Etemadifar Z, Borhani MS. Use of response surface methodology to enhance carotenoid pigment production fromCellulosimicrobiumstrain AZ. SN Applied Sciences. 2020;2:1-9. DOI: 10.1007/S42452-020-03549-6/TABLES/4
29. 29.Subhash Y, Lee SS. Roseomonas deserti sp. nov., isolated from crude oil contaminated desert sand. International Journal of Systematic and Evolutionary Microbiology. 2018;68:675-680. DOI: 10.1099/IJSEM.0.002565/CITE/REFWORKS
30. 30.Venil CK, Malathi M, Devi PR. Characterization of Dietzia maris AURCCBT01 from oil-contaminated soil for biodegradation of crude oil. Biotechnology. 2021;11:1-13. DOI: 10.1007/S13205-021-02807-7/TABLES/3
31. 31.Matsui T, Maruhashi K. Isolation of Carotenoid-deficient Mutant from Alkylated Dibenzothiophene Desulfurizing Nocardioform Bacteria,Gordoniasp. TM414. Current Microbiology. 2004;48(2):130-134. DOI: 10.1007/S00284-003-4141-2
32. 32.Fernandes AS, Paixão SM, Silva TP, Roseiro JC, Alves L. Influence of culture conditions towards optimal carotenoid production byGordonia alkanivoransstrain 1B. Bioprocess and Biosystems Engineering. 2018;41:143-155. DOI: 10.1007/s00449-017-1853-4
33. 33.Doehlert DH. Uniform Shell designs. Applied Statistics. 1970;19:231. DOI: 10.2307/2346327
34. 34.Wozniak A, Lozano C, Barahona S, Niklitschek M, Marcoleta A, Alcaíno J, et al. Differential carotenoid production and gene expression inXanthophyllomyces dendrorhousgrown in a nonfermentable carbon source. FEMS Yeast Research. 2011;11:252-262. DOI: 10.1111/j.1567-1364.2010.00711.x
35. 35.Gouda MK, Omar SH, Aouad LM. Single cell oil production byGordoniasp. DG using agro-industrial wastes. World Journal of Microbiology and Biotechnology. 2008;24:1703-1711. DOI: 10.1007/s11274-008-9664-z
36. 36.Meena M, Prasad V, Zehra A, Gupta VK, Upadhyay RS. Mannitol metabolism during pathogenic fungal–host interactions under stressed conditions. Frontiers in Microbiology. 2015;6. Article 1019, (12 pages). DOI: 10.3389/fmicb.2015.01019
37. 37.Filannino P, di Cagno R, Tlais AZA, Cantatore V, Gobbetti M. Fructose-rich niches traced the evolution of lactic acid bacteria toward fructophilic species. Critical Reviews in Microbiology. 2019;45:65-81. DOI: 10.1080/1040841X.2018.1543649

Written By

Tiago P. Silva, Susana M. Paixão, Ana S. Fernandes, José C. Roseiro and Luís Alves

Submitted: February 14th, 2022Reviewed: February 24th, 2022Published: April 18th, 2022