Evaluation of the Potential of Corynebacterium glutamicum ATCC 21492 for L-Lysine Production Using Glucose Derived from Textile Waste

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript by Bello et al. explores the production of L-lysine, a high-value-added product, from fabric waste. The authors present and discuss strategies to produce the hydrolysates and C. glutamicum cultivation strategies to increase L-lysine titers and yields. 

General comments

1. The introduction section is quite long and could be condensed.
2. All figures and discussion based on results presented: Please add statistical significance information if adequate and discuss accordingly.

Specific comments

L 22. Please clarify 'cotton', was it the untreated textile or glucose derived from cotton textile waste?

L 131. Please correct the reference manager error. Same for lines 143, 151, 266, 275, 294, 303, 309, 327, 336, 339, etc.

L 168. Please clarify medium composition - 15 g/L refers to which ingredient?

L 230. Please revise this sentence.

L 262-264. Please revise this portion of the manuscript.

L 315-316. I suggest changing the color scheme of Figure 1. The 'blank test (EH4)' sample cannot be identified.

L 328. Please specify the glucose concentration tested.

L 339-343. Was this model used to calculate µmax in the tested carbon sources or culture conditions?

L 353-356 and Fig. 6. Please add statistical significance information if adequate and discuss accordingly.

L 410. Binomial nomenclature must be styled in italics. Please correct the entire text, figures, and reference list.

L 498-526. Please use the presented model to µmax values under the tested conditions.

L 596. Please compare the yields (mg/g) calculated for each condition.

L 636. The authors should do simple Fermi calculations to estimate the amount of L-lysine that can be obtained from the regional/global availability of cotton-derived glucose hydrolysates. Compare these values with the global demand for L-lysine.

Author Response

General comments

1. The introduction section is quite long and could be condensed.

Thank you very much for your comment. The introduction section has been rewritten to reduce it, as has the number of references, and the "References" section has been corrected accordingly. The new "Introduction" section would read as follows (L40-L76):

“The textile industry, driven by the "fast fashion" model, has grown significantly in recent decades, increasing textile waste production and its environmental impact. Ninety-two million tons of textile waste are generated annually, of which only a minimal fraction is recycled [1], [2], [3]. This issue is exacerbated by the use of synthetic fibers, chemical dyes, and processes that consume large amounts of water and energy. In 2016, the textile industry emitted approximately 4 Gt of CO₂, representing 8% of global greenhouse gas emissions [4]. Additionally, washing synthetic garments generates 35% of oceanic microplastics, and an estimated 215 trillion liters of water are consumed annually in this industry [5]

The circular economy emerges as a solution to mitigate this impact through textile recycling strategies. Mechanical recycling, while cost-effective, reduces fiber quality, limiting reuse potential [6]. On the other hand, chemical recycling enables the recovery of high-quality fibers but requires advanced technologies and high operational costs [6], [7]. A promising alternative could be the use of biorefineries processes, using cellulose from textile waste as a carbon source for the biotechnological production of biopolymers, bioethanol, and essential amino acids. This process involves enzymes that hydrolyze cellulose into glucose, which is then fermented by microorganisms such as Saccharomyces cerevisiae and Corynebacterium glutamicum [8], [9].

L-lysine, an essential amino acid for the food and pharmaceutical industries, stands out in this context. It has been demonstrated that lignocellulosic materials can be a viable source for L-lysine production via fermentation, particularly using genetically modified microorganisms like C. glutamicum [10], [11], [12]. As an alternative, cellulose from textile waste could reduce the need for pretreatment processes, i.e. delignification. This approach reduces dependence on agricultural resources and promotes waste reuse.

In this study, two main strategies were evaluated for converting cellulosic textile waste into value-added products: Separate Hydrolysis and Fermentation (SHF) and Simultaneous Saccharification and Fermentation (SSF). The SHF process allows the independent optimization of enzymatic hydrolysis (EH) and fermentation stages to maximize efficiency, while SSF combines the enzymatic hydrolysis of cellulose and the fermentation process into a single step. This integration not only simplifies the overall process by reducing the need for separate optimization and handling of intermediate products but also has the potential to lower operational costs by minimizing equipment requirements, reducing processing time, and improving overall efficiency.

The results demonstrate that converting textile waste into L-lysine through these processes is a sustainable alternative to traditional sources of this amino acid. Moreover, it provides a solution for managing textile waste, contributing to the circular economy and mitigating the environmental impact of this industry [13].”

 

2. All figures and discussion based on results presented: Please add statistical significance information if adequate and discuss accordingly.

Thank you for the suggestion. We included ANOVA for Figures 6 and 8, as we explain in point 9.

Specific comments

1. L 22. Please clarify 'cotton', was it the untreated textile or glucose derived from cotton textile waste?

We agree and a clarification has been added (Abstract, paragraph 2, lines 26-28)

“In SSF, the highest L-lysine yield of 3.10 mg/g untreated cotton was achieved at 14% cotton loading, 7% enzyme dose, 35 °C, and 10% inoculum concentration, corresponding to an L-lysine concentration of 0.5 g/L.”

2. L 131. Please correct the reference manager error. Same for lines 143, 151, 266, 275, 294, 303, 309, 327, 336, 339, etc.

We apologize for the mistake by using the reference manager, which modified the references. To avoid new errors, the references in the manuscript have been introduced manually.

 

3. L 168. Please clarify medium composition - 15 g/L refers to which ingredient?

A clarification has been added to the text – Section 2.4, page 5, paragraph 2, lines 148-151.

“The microorganism was reconstituted from frozen stocks (-80 °C) by inoculating in a medium consisting of 15 g/L of commercial tryptic soy broth (TSB) supplemented with 25 g/L glucose [20], [29], [30]. The commercial TSB was composed of casein, 17 g; soya peptone, 3 g; sodium chloride, 5 g; dipotassium hydrogen phosphate, 2.5 g; and glucose, 2.5 g.”

 

4. L 230. Please revise this sentence.

The sentence has been rewritten (Section 2.7, page 6, paragraph 2, lines 206-212)

“The experimental design considered three variables: initial glucose concentration (24, 33, and 45 g/L), temperature (30 and 35 °C), and inoculum size (2 and 10% v/v). The glucose concentrations tested were based on the optimization of the EH and previous fermentation assays performed in the present research with commercial glucose. Specifically, the 45 g/L glucose concentration was obtained under the conditions of the EH11 assay, the 33 g/L concentration from the EH6 or EH18 assays, and the 24 g/L concentration from the EH19 assay.”

 

5. L 262-264. Please revise this portion of the manuscript.

The mentioned portion of the manuscript has been revised and modified (Section 2.9, page 7, paragraph 1, lines 239-240)

“L-lysine produced by C. glutamicum strains, as well as other amino acids were analyzed by high-performance liquid chromatography (HPLC)”

We have also deleted the explanation of the section, dragged from the template.

 

 

 

6. L 315-316. I suggest changing the color scheme of Figure 1. The 'blank test (EH4)' sample cannot be identified.

We agree with Reviewer 1. Figure 1 has been modified to show correctly the four tests performed.

 

Figure 1. Glucose concentration vs. time obtained with the EH of pretreated and untreated cotton at a 2.5% dose

7. L 328. Please specify the glucose concentration tested.

The glucose concentration tested has been added to the text (Section 3.3, page 10, paragraph 1, lines 314-316)

“The strain growth was determined to standardize the bacterial population in the inoculum, which was carried out in TSB supplemented with 25 g/L of glucose at 30 °C, 120 rpm, for 24 h”.

 

8. L 339-343. Was this model used to calculate µmax in the tested carbon sources or culture conditions?

The bacterial growth was studied in the inoculum preparation step to standardize the bacterial population in the inoculum. It has been added a short explanation in Section 2.4, page 5, paragraph 2, lines 152-154; and in Section 3.3, page 10, paragraph 1, lines 314-317.

Lines 152-154: “Five mL of prepared medium (TSB supplemented with 25 g/L of glucose) was inoculated in 50 mL Erlenmeyer flasks and incubated at 30 °C, 120 rpm, for 24 h in an orbital incubator (LABOLAN Mod 200).”

Lines 314-317: “The strain growth was determined to standardize the bacterial population in the inoculum, which was carried out in TSB supplemented with 25 g/L of glucose at 30 °C, 120 rpm, for 24 h. Figure 1 illustrates the growth dynamics of C. glutamicum ATCC 21492 measured in CFU/ml.”

 

9. L 353-356 and Fig. 6. Please add statistical significance information if adequate and discuss accordingly.

We thank the Reviewer for the suggestion. We have now included statistical significance analysis for lysine production at 35 g/L glucose, where all temperature and inoculum combinations were tested with replicates. An ANOVA revealed statistically significant effects of temperature, inoculum, and their interaction.

“A two-way ANOVA revealed that both temperature and inoculum percentage had a significant effect on L-lysine concentration at 35 g/L glucose, with a highly significant interaction between factors (p < 0.0001). Post-hoc Tukey HSD analysis showed that the combination of 30 °C and 10% inoculum yielded significantly higher L-lysine production compared to other conditions. Conversely, the lowest yields were observed at 37 °C with 10% inoculum”

In addition, we included a clarification of why the initial glucose concentration of 35 g/L was selected to study all cases. Section 2.6, page 6, paragraph 1, L195-200:

“Additional fermentations were performed at varying glucose concentrations (10–100 g/L) to assess substrate inhibition under identical conditions. Additionally, specific tests were conducted by inoculating with a 2% and 10% v/v preculture and increasing the temperature to 35°C and 37°C, selecting the initial glucose concentration in which the SHF assays would be done; i.e., 35 g/L and 50 g/L. At 35 g/L, the central point of SHF study, all the combinations were tested.”

Furthermore, we included an ANOVA for Figure 8, and added the following text (section 3.5, page 13, paragraph 2, lines 377-382)

“An ANOVA was performed, which revealed that glucose, temperature, and inoculum dose significantly influence L-lysine production (p < 0.05). Among these factors, glucose stood out as the most decisive, exerting the greatest direct effect on production. Furthermore, the interactions between factors were also significant, indicating that the relationship among glucose, temperature, and inoculum dose plays an important role in the process.”

 

10. L 410. Binomial nomenclature must be styled in italics. Please correct the entire text, figures, and reference list.

Thank you for the correction. The manuscript has been revised to use the right nomenclature.

 

11. L 498-526. Please use the presented model to µmax values under the tested conditions.

We appreciate the Reviewer’s comment. However, we do not understand it. The value of μ_max was calculated by using modified Gompertz model as explained in Section 2.5, page 5, paragraph 2 (bacterial growth modelling), lines 188-191: “Where N(t) is the CFU value (CFU/mL) for a given time and N0 the CFU value (CFU/mL) at the initial time; A is the asymptote (ln [N∞/N0]) in the stationary phase; μ_max is the maximum specific growth rate (h⁻¹), which comes expressed as (ln(CFU_t) - ln(CFU_t−1))/(t_t − t_t−1); e is the Euler’s number; λ is the lag time (h) and t is the time (h).”

If the Reviewer could explain the comment further, we would be pleased to modify the text accordingly.

 

12. L 596. Please compare the yields (mg/g) calculated for each condition.

Thank you for your observation. We have included the yield (mg lysine/g glucose) of the cited authors and ours (Section 4.2, page 19-20, paragraph 8, Lines 578-588)

“Compared to literature benchmarks, the L-lysine titers achieved in this study were modest (2,38 g Lysine/L and 52.88 mg lysine/g glucose or 2,23 g lysine/L and 67.59 mg lysine/g glucose using 45g glucose /L hydrolysate and 2% inoculum size or 33 g glucose /L hydrolysate and 10% inoculum size respectively, both at 35 ºC). Xu et al. (2019) [22] reported titers up to 121.4 g/L (460 mg lysine/ g glucose) using fed-batch fermentation, 10% inoculum size at 30 ºC with metabolic engineering approaches targeting redox balance, such as GAPDH and IDH modification. Other studies emphasized minimizing flux diversion toward by-products; Mimitsuka et al. (2007) [26] demonstrated the need to regulate cadaverine synthesis, yielding 5.2 g/L L-lysine (104 mg lysine/ g glucose) in 18 h at 30 ºC, while Hussain et al. (2015) [23] highlighted how media optimization can significantly boost L-lysine production (up to 3,5 g/L - 70 mg lysine/ g glucose- in 72 h at 30 ºC).

 

13. L 636. The authors should do simple Fermi calculations to estimate the amount of L-lysine that can be obtained from the regional/global availability of cotton-derived glucose hydrolysates. Compare these values with the global demand for L-lysine.

Thank you for your suggestion. We included a paragraph with Fermi calculations estimating the amount of L-lysine that can be obtained base on our yields from the global availability of cotton:

“To contextualize the feasibility of L-lysine production at scale, we performed a Fermi estimation based on the availability of cotton residues. Assuming an approximate global annual cotton fiber production of 26 million tons [39] and estimating that cotton waste accounts for around 10-20% of this value, this translates to 2.6 to 5.2 million tons of potential feedstock. Applying our experimental yield of 22.30 kg of L-lysine per ton of cotton, the theoretical annual global L-lysine production from cotton residues could range between 58,000 and 116,000 tons. Further refinement of enzymatic hydrolysis and ferm

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

First of all, I would like to congratulate the authors for their work in the manuscript fermentation-3649861. It presents a very promising alternative for the management and valorization of textile waste flows that represent a relevant problem for society.  I would like to share with the authors a number of suggestions and comments to improve the understanding of the results.

* Tables 1, 2, 4: I found it a bit confusing to follow the results and what process (SHF or SSF) and experimental conditions they were associated with. In particular, I think it would be beneficial to compile all the trials into the same summary table (instead of three different ones), where all the key information that is already identified in the tables individually could be clearly compiled. Also, check some minor shortcomings in the nomenclature of the trials (check table 4, it should be EH_xx, right?).

* Figures 6, 7, 8, 9, 10:

• Standardize nomenclature between results figures and trials condition tables (EH_XX). Check those figures in which no mention to EH_XX test name is included, it is difficult to contrast conditions vs results.
• Furthermore and as a general comment: I miss in the text more link between the results and the trials they are related to.

* Line 89-90: could you elaborate a bit more this statement?

* Lines 90-93: this is already mentioned in lines 68-70, right?

* References to Figures and Tables in the text are broken. Some detected are detailed below:

• 127, 139, 147, 262, 271, 290, 299, 305, 323, 332, 335, 343, 345, 421, 429, 437, 456, 470, 483:

*Line 221: authors mentioned full factorial design with 3 parameters. Do you mean 2^3// 2³?

* Lines 350-352: could you provide an explanation? Is there any previous work in which this trend was observed?

* Line 445: include some references to support this statement, please

* Lines 495-497:

• Just to confirm, the physiological factors you mentioned are the ones included in lines 505-511? If so, please, make it clearer in the text these could be reasons for such large variation among replications.
• In this context, I would like to share and overall comment about those trials with greatest variation among replications. It would be of great value to the paper to repeat those trails to confirm these variations. Otherwise, this might be seen as a lack of consistency in the experimental results, due to the great variability. This is an issue when it comes to up-scale and dimension the process.

Author Response

Comments and Suggestions

1. Tables 1, 2, 4: I found it a bit confusing to follow the results and what process (SHF or SSF) and experimental conditions they were associated with. In particular, I think it would be beneficial to compile all the trials into the same summary table (instead of three different ones), where all the key information that is already identified in the tables individually could be clearly compiled. Also, check some minor shortcomings in the nomenclature of the trials (check table 4, it should be EH_xx, right?).

In reference to the compilation of Tables 1, 2, and 4, we appreciate the suggestion. However, it is not possible to do so because these tables represent different assays and treatments, and combining the information would lead to confusion. Even so, we have moved Table 4, now Table 3 to Methods and Materials section, in which we have also added some comments (section 2.3, lines 122-131) and the results have been specified in the corresponding section 3.2, lines 291-299 and in Table 5 (line 308) In this way, we believe the text is clearer.

These tables 3 and 5 includes a test (EH19) that was initially not considered in the manuscript but was conducted to obtain the hydrolysate for the SHF experiments (to obtain the 24 g glucose/L hydrolysates). Adding this data provides a more complete view of the experimental process and its impact on substrate preparation.

The new texts are:

Section 2.3, page 3, lines 122-131:

“During the execution of this study, the Cellic CTec2 cellulase preparation was no longer available, necessitating the optimization of hydrolysis conditions using new commercial enzyme preparations. The last EH tests (EH17-EH24) were performed with the alternative commercial enzyme preparations (Table 3). All experiments were conducted at 20%w/w cotton dose – with the exception of test EH19 which was 14% w/w cotton-, for 72 h under the same temperature (50 °C) and agitation (200 rpm) as those performed with Cellic CTec2. Enzyme concentrations were applied according to the manufacturer’s recommendations, except for experiments EH24 and EH25, where higher and lower concentrations than the recommended dosage were tested for the Fiberlife550 enzyme preparation.”

Section 3.2, page 8, lines 291-299:

“Table 5 presents the hydrolysis results, as well as the doses used with of the alternative enzyme blends under conditions of 20% w/w cotton dose, 50 °C and 200 rpm agitation for 72 hours. Enzyme concentrations followed manufacturer recommendations, except in experiments testing higher and lower doses of Fiberlife550. The findings indicate that only the Saczyme Yield and Fiberlife550 blends (the latter at the recommended con-centration) achieved yields glucose concentrations comparable to Cellic CTec2. Specifical-ly, Saczyme Yield produced 31.06 g/L of glucose, and Fiberlife550 achieved 36.92 g/L after 72 hours. In contrast, deviating from the recommended Fiberlife550 concentration drastically reduced yield, underscoring the importance of adhering to the specified dosage.”

Table 5. Glucose concentration (g/L) after 72h of the EH tests with the alternative enzymatic blends and different cotton doses and pH.

Test Name	Enzymatic blend	Glucose concentration
EH17	Fibercare D	0.31
EH18	Saczyme Yield (20 % w/w cotton)	31.06
EH19	Saczyme Yield (14 % w/w cotton)	24.02
EH20	Flavourzyme	3.82
EH21	Cellic CTec3	4.01
EH22	Fiberlife550	36.92
EH23	Fiberlife500	0.98
EH24	Fiberlife550	0.54
EH25	Fiberlife550	1.50

 

2. Figures 6, 7, 8, 9, 10:

• Standardize nomenclature between results figures and trials condition tables (EH_XX). Check those figures in which no mention to EH_XX test name is included, it is difficult to contrast conditions vs results.
• Furthermore and as a general comment: I miss in the text more link between the results and the trials they are related to.

We understand that there may be confusion regarding the EHXX codes used for enzymatic hydrolysis assays and those shown in Figures 6, 7, 8, 9, and 10. However, Figures 6 and 7 represent fermentation assays using commercial glucose, which are not directly related to the enzymatic hydrolysis experiments. In contrast, Figures 8, 9, and 10 are based on hydrolysates obtained from enzymatic hydrolysis tests. While this is not explicitly stated in the graphs, we have included in Section 2.7, page 6, paragraph 2, lines 206-212 the specific hydrolysis assays that were used to determine the initial glucose concentrations for the SHF experiments:

“The experimental design considered three variables: initial glucose concentration (24, 33, and 45 g/L), temperature (30 and 35 °C), and inoculum size (2 and 10% v/v). The glucose concentrations tested were based on the optimization of the EH and previous fermentation assays performed in the present research with commercial glucose. Specifically, the 45 g/L glucose concentration was obtained under the conditions of the EH11 assay, the 33 g/L concentration from the EH6 or EH18 assays, and the 24 g/L concentration from the EH19 assay.”

 

 

3. Line 89-90: could you elaborate a bit more this statement?

The mentioned text has been modified for a better explanation – Section 1 (Introduction), page 2, paragraph 4, lines 66-72.

“The SHF process allows the independent optimization of enzymatic hydrolysis (EH) and fermentation stages to maximize efficiency, while SSF combines the enzymatic hydrolysis of cellulose and the fermentation process into a single step. This integration not only simplifies the overall process by reducing the need for separate optimization and handling of intermediate products but also has the potential to lower operational costs by minimizing equipment requirements, reducing processing time, and improving overall efficiency.”

4. Lines 90-93: this is already mentioned in lines 68-70, right?

Thank you very much for your comment. The introduction section has been rewritten to reduce it, avoiding repeated or redundant texts. The new "Introduction" section would read as follows (L40-L76):

“The textile industry, driven by the "fast fashion" model, has grown significantly in recent decades, increasing textile waste production and its environmental impact. Ninety-two million tons of textile waste are generated annually, of which only a minimal fraction is recycled [1], [2], [3]. This issue is exacerbated by the use of synthetic fibers, chemical dyes, and processes that consume large amounts of water and energy. In 2016, the textile industry emitted approximately 4 Gt of CO₂, representing 8% of global greenhouse gas emissions [4]. Additionally, washing synthetic garments generates 35% of oceanic microplastics, and an estimated 215 trillion liters of water are consumed annually in this industry [5]

The circular economy emerges as a solution to mitigate this impact through textile recycling strategies. Mechanical recycling, while cost-effective, reduces fiber quality, limiting reuse potential [6]. On the other hand, chemical recycling enables the recovery of high-quality fibers but requires advanced technologies and high operational costs [6], [7]. A promising alternative could be the use of biorefineries processes, using cellulose from textile waste as a carbon source for the biotechnological production of biopolymers, bioethanol, and essential amino acids. This process involves enzymes that hydrolyze cellulose into glucose, which is then fermented by microorganisms such as Saccharomyces cerevisiae and Corynebacterium glutamicum [8], [9].

L-lysine, an essential amino acid for the food and pharmaceutical industries, stands out in this context. It has been demonstrated that lignocellulosic materials can be a viable source for L-lysine production via fermentation, particularly using genetically modified microorganisms like C. glutamicum [10], [11], [12]. As an alternative, cellulose from textile waste could reduce the need for pretreatment processes, i.e. delignification. This approach reduces dependence on agricultural resources and promotes waste reuse.

In this study, two main strategies were evaluated for converting cellulosic textile waste into value-added products: Separate Hydrolysis and Fermentation (SHF) and Simultaneous Saccharification and Fermentation (SSF). The SHF process allows the independent optimization of enzymatic hydrolysis (EH) and fermentation stages to maximize efficiency, while SSF combines the enzymatic hydrolysis of cellulose and the fermentation process into a single step. This integration not only simplifies the overall process by reducing the need for separate optimization and handling of intermediate products but also has the potential to lower operational costs by minimizing equipment requirements, reducing processing time, and improving overall efficiency.

The results demonstrate that converting textile waste into L-lysine through these processes is a sustainable alternative to traditional sources of this amino acid. Moreover, it provides a solution for managing textile waste, contributing to the circular economy and mitigating the environmental impact of this industry [13].”

• References to Figures and Tables in the text are broken. Some detected are detailed:127, 139, 147, 262, 271, 290, 299, 305, 323, 332, 335, 343, 345, 421, 429, 437, 456, 470, 483

We regret this issue. It has already been fixed

5. Line 221: authors mentioned full factorial design with 3 parameters. Do you mean 2^3// 2³?

A better explanation has been added to clarify the full factorial design used – Section 2.7, page 6, lines 206-212:

“The experimental design considered three variables: initial glucose concentration (24, 206 33, and 45 g/L), temperature (30 and 35 °C), and inoculum size (2 and 10% v/v). The glu-207 cose concentrations tested were based on the optimization of the EH and previous fer-208 mentation assays performed in the present research with commercial glucose. Specifically, 209 the 45 g/L glucose concentration was obtained under the conditions of the EH11 assay, the 210 33 g/L concentration from the EH6 or EH18 assays, and the 24 g/L concentration from the 211 EH19 assay.”

6. Lines 350-352: could you provide an explanation? Is there any previous work in which this trend was observed?

 An explanation has been added – Section 3.4, page 12, paragraph 1, lines 340-344.

“Optimal production at 30 °C appears to occur with initial glucose concentrations between 25 and 70 g/L, as moderate glucose levels optimize metabolic efficiency and avoid inhibitory effects observed at extreme concentrations. Similar results have been reported in previous studies [13], [22], [24], [25], [26]”.

7. Line 445: include some references to support this statement, please

 A reference has been included – Section 3.6, page 15, paragraph 5, lines 443-446.

“This is due to a lower liquid-to-solid ratio at higher solid loadings, which may have limited mass transfer and nutrient availability a phenomenon also observed in studies using other substrates for L-lysine production [28].”

 

8. Lines 495-497:

• Just to confirm, the physiological factors you mentioned are the ones included in lines 505-511? If so, please, make it clearer in the text these could be reasons for such large variation among replications.

We thank Reviewer 2 for the comment and would like to clarify that the physiological factors mentioned were provided as examples. In our study, the conditions used to standardize the bacterial population were the same for all experiments. However, dissolved oxygen could not be controlled, as the bacterial growth was conducted in flasks. This parameter is likely responsible for the observed variability among replicates.

It has been added a clarification in section 4.1, page 18 lines 517-519:

“This parameter could not be controlled as the bacterial growth was performed in flasks, being likely the responsible for the variation among replications.”

• In this context, I would like to share and overall comment about those trials with greatest variation among replications. It would be of great value to the paper to repeat those trails to confirm these variations. Otherwise, this might be seen as a lack of consistency in the experimental results, due to the great variability. This is an issue when it comes to up-scale and dimension the process.

Thank you for the observation. We acknowledge the variability observed in certain trials and recognize the importance of repeating these experiments to confirm the observed variations. As part of our ongoing research, we plan to conduct additional trials to address this variability and strengthen the reliability of our findings. These future experiments will provide further insight and contribute to a more robust understanding of the process dynamics.

Author Response File: Author Response.pdf