Evaluation of Different Amino Acids on Growth and Cyanide Production by Bacillus megaterium for Gold Recovery

: Bio-cyanidation, as a sustainable and effective method to extract gold from primary and secondary resources, has attracted attention because of its environmental friendliness and economic beneﬁts. The effect of amino acids on bio-cyanide production using Bacillus megaterium ( B. megaterium ) is a less explored area in this ﬁeld and is the main interest of this study. Here, the effect of glycine, threonine, and glutamine over a concentration range of 0 to 10 g/L was investigated. The results showed at equal concentration of amino acids (5 g/L), glycine yields (maximum ca. 110 mg/L) a higher concentration of biogenic cyanide (bio-CN), while glutamine and threonine produce less (maximum ca. 74 mg/L and ca. 64 mg/L, respectively). For the ﬁrst time, optimization of mixing the three amino acids was investigated and revealed more signiﬁcant roles for glycine and glutamine in stimulation of bio-CN by B. megaterium . The interactions involved in the biosynthesis of bio-CN were explained with a reference to metabolic pathways and the cycle of the bacteria. In mixed amino acids, the optimum medium for bio-CN production was identiﬁed to be 2.84 g/L glycine, 3.0 g/L glutamine in the absence of threonine, which could produce a high concentration of ca. 86 mg/L bio-CN, resulting in gold leaching efﬁciency comparable to chemical cyanide.


Introduction
Cyanidation is the most common process for the extraction of gold and many other precious metals from their resources [1,2].With the decrease in the assay of gold in primary resources, complication of the secondary resources, and increase in the environmental concerns of applying concentrated cyanide for gold extraction, there has been extensive research to find a suitable alternative to replace the conventional procedure [3].Comparing microbiological methods of metal production to the thermal and chemical routes, microbiological processes release significantly lower CO 2 and consume less water [4].
Bio-cyanidation for gold leaching is a promising option with many environmental and economic benefits [5,6].Some benefits are related to its cleaner production, safer handling, and the simplicity of its remediation.Bio-CN is produced as a result of natural metabolic activities of certain microorganisms from non-toxic chemicals, whereas chem-CN is produced through some non-clean processes (e.g., reacting methane and ammonia at high temperature).In bio-cyanidation, concentration of bio-CN is usually lower than Chem-CN and it makes it slightly safer to handle.In addition, production of bio-CN is associated with some other organic chemicals that are produced by the microorganism and they can remediate the extra cyanide after the leaching process [5].Furthermore, the leached metals in bio-CN solution can be easily purified by conventional processes, such as solvent extraction and the use of activated carbon [7].
Figure 1 shows the main sequences of transformation of glycine (C 2 H 5 NO 2 ) to cyanide in biological systems, where the presence of HCN-synthase enzyme is responsible for degradation of glycine to iminoacetic acid (C 2 H 3 NO 2 ) and, then, to hydrogen cyanide [8].
Figure 1 shows the main sequences of transformation of glycine (C2H5NO2) to cyanide in biological systems, where the presence of HCN-synthase enzyme is responsible for degradation of glycine to iminoacetic acid (C2H3NO2) and, then, to hydrogen cyanide [8].Since glycine is an important compound in the biological formation of cyanide, its concentration can substantially influence bacterial growth and activity.There are several studies on finding the best concentration of glycine; Shin et al. (2013) [9] investigated concentrations of 0.5 to 20 g/L glycine on growth and cyanide production by Chromobacterium violaceum.They found that at pH 9 and in YP medium (5 g/L yeast extract, 10 g/L polypeptone), the concentration of 5 g/L glycine is the best for cyanide production and 0.5 g/L is the best for bacterial growth.Likewise, Motaghed et al. (2014) [8] examined the functionality of B. megaterium for leaching platinum and rhenium from spent refinery catalyst at various glycine concentrations (0 to 15 g/L) and pulp densities (1 to 10% w/v spent refinery catalyst).Their results revealed there is not a significant interaction between these two parameters and each parameter influences separately.Optimum concentration of glycine for maximum metal recovery (16% platinum and 98% rhenium) was reached at 12.8 g/L and the best pulp density was 2.5% w/v.
To recover gold from printed circuit boards, Işıldar et al. (2016) [10] employed Pseudomonas fluorescens (P.fluorescens) and Pseudomonas putida (P.putida) in 5, 7.5, and 10 g/L concentrations of glycine.Their results showed that an increase in the concentration of glycine causes a negative effect on both growth and cyanide production of P. fluorescens.On the other hand, for P. putida, glycine, at this range of concentration, has an insignificant influence on bacterial growth.Here, cyanide production rose with an increase in the concentration of glycine.Arshadi et al. (2016) [11] optimized parameters of pulp density, initial pH, and glycine concentration for bioleaching of gold and copper from cell-phone printed circuit boards using B. megaterium.For a range of 0.5 g/L to 10 g/L glycine, their findings demonstrated the maximum cyanide could be generated at the highest level of glycine.They suggested the best bacterial growth could be achieved at pH 8 and the maximum gold recovery at pH 10. Kumar et al. (2018) [12] showed that glycine higher than a certain concentration is not tolerable by bacteria and can lead to their death depending on other medium conditions (such as pH and metallic contaminations).
There are different amino acids that could be potential candidates to replace glycine.Alanine, threonine, lysine, proline, serine, valine, methionine, isoleucine, tyrosine, asparatic acid, phenylalanine, glutamine, histidine, glutamic acid, and cysteine are some options that contain nitrogen and carbon branches in their structure and are viable options to explore for cyanogenic bacteria [13][14][15].Applying different amino acids means they contribute differently to the growth of bacteria and its performance in biogenic cyanide (bio-CN) production.Threonine and glutamine are two promising amino acids, capable Since glycine is an important compound in the biological formation of cyanide, its concentration can substantially influence bacterial growth and activity.There are several studies on finding the best concentration of glycine; Shin et al. (2013) [9] investigated concentrations of 0.5 to 20 g/L glycine on growth and cyanide production by Chromobacterium violaceum.They found that at pH 9 and in YP medium (5 g/L yeast extract, 10 g/L polypeptone), the concentration of 5 g/L glycine is the best for cyanide production and 0.5 g/L is the best for bacterial growth.Likewise, Motaghed et al. (2014) [8] examined the functionality of B. megaterium for leaching platinum and rhenium from spent refinery catalyst at various glycine concentrations (0 to 15 g/L) and pulp densities (1 to 10% w/v spent refinery catalyst).Their results revealed there is not a significant interaction between these two parameters and each parameter influences separately.Optimum concentration of glycine for maximum metal recovery (16% platinum and 98% rhenium) was reached at 12.8 g/L and the best pulp density was 2.5% w/v.
To recover gold from printed circuit boards, Işıldar et al. (2016) [10] employed Pseudomonas fluorescens (P.fluorescens) and Pseudomonas putida (P.putida) in 5, 7.5, and 10 g/L concentrations of glycine.Their results showed that an increase in the concentration of glycine causes a negative effect on both growth and cyanide production of P. fluorescens.On the other hand, for P. putida, glycine, at this range of concentration, has an insignificant influence on bacterial growth.Here, cyanide production rose with an increase in the concentration of glycine.Arshadi et al. (2016) [11] optimized parameters of pulp density, initial pH, and glycine concentration for bioleaching of gold and copper from cell-phone printed circuit boards using B. megaterium.For a range of 0.5 g/L to 10 g/L glycine, their findings demonstrated the maximum cyanide could be generated at the highest level of glycine.They suggested the best bacterial growth could be achieved at pH 8 and the maximum gold recovery at pH 10. Kumar et al. (2018) [12] showed that glycine higher than a certain concentration is not tolerable by bacteria and can lead to their death depending on other medium conditions (such as pH and metallic contaminations).
There are different amino acids that could be potential candidates to replace glycine.Alanine, threonine, lysine, proline, serine, valine, methionine, isoleucine, tyrosine, asparatic acid, phenylalanine, glutamine, histidine, glutamic acid, and cysteine are some options that contain nitrogen and carbon branches in their structure and are viable options to explore for cyanogenic bacteria [13][14][15].Applying different amino acids means they contribute differently to the growth of bacteria and its performance in biogenic cyanide (bio-CN) production.Threonine and glutamine are two promising amino acids, capable of producing a high concentration of cyanide and maintaining satisfactory bacterial growth [15].
To date, there is a scarcity of reports about the application of amino acids (including threonine and glutamine), other than glycine, for bio-cyanidation of gold.Moreover, there is no study about mixing the amino acids to study the growth and cyanide production of cyanogenic bacteria.Based on these statements, the main goal of this study was to investigate the influence of threonine and glutamine in bio-cyanidation and compare them with glycine.Herein, growth of B. megaterium, and its ability to produce bio-CN, are studied at different concentration of the amino acids.Moreover, different ratios of glycine, threonine, and glutamine are explored and the optimum condition for maximum cyanide production is determined, based on D-optimal design in response surface methodology (RSM), by using Design Expert (version 7; State-Ease Inc., Minneapolis, MN, USA) software.At the end, the results were explained by referring to the metabolic pathways of the bacteria and the optimum condition for maximum gold leaching efficiency was verified.

Bacteria and Growth Medium
B. megaterium (ATCC 14581), a bio-safety level one bacterium, was used in this study.The main culture medium for all the experiments was a standard Luria−Bertani (LB) medium containing 10 g/L tryptone, 5 g/L yeast extract, and 10 g/L NaCl.Initial pH for all the experiments was 10 (adjusted by concentrated NaOH solution) and tests started by supplying bacteria at 5% (v/v) inoculation ratio.For all steps of bacterial growth and culturing, a shaker-incubator at 30 • C and 150 rpm rotation speed was employed.For cyanide stimulation by the bacteria, amino acids of glycine, threonine, and glutamine were chosen as the precursors.All chemicals used in this study were from Fisher Scientific and were of analytical grade.The choice of fixed parameters, such as temperature, pH, and time, were based on our preliminary experiments and our earlier investigations [6,16,17].

Experimental Design
This study had three main phases; it started by analyzing the changes in the bacterial population and bio-CN concentration over time for different types of individual amino acids, including glycine, threonine, and glutamine.The second step was an investigation of the effect of different concentrations of amino acids on bacterial growth and concentration of bio-CN.In the following step, amino acids were mixed at different ratios and their effects on bacterial growth were monitored.Here, the medium was optimized for maximum concentration of bio-CN.At the end, the optimum medium with maximum concentration of produced bio-CN was verified by leaching pure gold powder (99.995% pure at <45 µm particle size).Experiments were performed in 100 mL flasks with 5% (v/v) inoculation ratio of pre-cultured B. megaterium.
Changes in the bacterial population and bio-CN concentration were monitored over a 48-h period.A concentration of 5 g/L glycine in standard LB medium is common in bio-cyanidation investigations [6], and since there is no report of using threonine and glutamine for cyanide production by cyanogenic microorganisms, these media were also prepared at the same concentration.In the second phase, bacterial growth and bio-CN production were studied by changing the concentration of each amino acid from 0 to 10 g/L and samples were measured after 48 h.This led to designing a comprehensive test plan for the next stage which was analyzing the effect of mixing amino acids.The experimental design was prepared by using Design Expert (version 7) and was based on D-optimal response surface methodology (RSM).Herein, the type of amino acids (glycine, threonine, and glutamine) and concentrations of them were studied, bacterial growth was monitored, and bio-CN production in a mixed amino acid system was optimized (design in Supplementary Materials Table S1).In this step of the experiment, bacterial growth and concentration of bio-CN were measured after 48 h.The experiments were performed in sterilized conditions by autoclaving all solutions and glassware at 121 • C for longer than 20 min.
Finally, the optimum medium condition suggested by the software for maximum concentration of bio-CN was verified after three times replicates.In addition, the optimum solution was used for leaching gold and was compared with control (just sterilized medium without bacteria), and chemical cyanide (Chem-CN prepared by NaCN at equivalent cyanide concentration that was achieved from the optimum biological solution).The leaching test was performed at a starting pH of 10, by adding 1 mg gold powder, on a magnetic stirrer at 400 rpm, 25 • C, for 24 h, in triplicates.Before leaching, all the solutions achieved after biological activities were initially centrifuged at 5500 rpm for 5 min and filtered by sterilized filter with 0.45 µm porosity.All the chemicals were prepared from analytical grade reagents procured from Fisher Scientific.

Analytical Techniques
Bacterial growth was quantified using a UV-visible spectrometer (Thermo Scientific GENESYS 10S) at an optical density of 600 nm (OD 600 ).The concentration of cyanide was measured, based on potentiometry titration, using an auto titrator (Metrohm, 916 Ti-Touch titrator with a silver electrode) and silver nitrate solution (0.0192 N, Fisher Scientific, Waltham, MA, USA).Over different stages of the experiment, pH and dissolved oxygen of the solutions were monitored using a pH probe (OAKTON 35805-67 Accumet Fast Response) and an optical dissolved oxygen sensor (Thermo Scientific™ Orion™ Star A213 RDO/DO Benchtop Meter).Gold concentration in the solution was analyzed by atomic absorption spectroscopy (AAS, Thermo Scientific, Waltham, MA, USA).To have clean samples for accurate measurement, all solutions were primarily filtered using sterilized filter with 0.45 µm porosity.

Bacterial Growth and Cyanide Production
Figure 2 shows the kinetics of bacterial growth by B. megaterium (as OD 600 ) and changes in the concentration of the produced bio-CN over a 48-h period and as a result of using different types of amino acids.From Figure 2a the best growth could be seen to happen in the medium containing glycine, which reached OD 600 = 0.127 in 1 h, then gradually decreased to about 0.020 over the first 24 h and stabilized until the end of the investigation.The decreasing trend for the other amino acids was immediate and sharper.The OD 600 in threonine and glutamine medium rapidly decreased to about 0.020 in the first 10 h and ended up at 0.013 after 48 h.However, it should be noted that OD 600 was slightly higher most of the times in the glutamine medium compared to threonine.This behavior could be related to the simpler structure of glycine which makes it easier for the bacteria to grow.
The trend of bio-CN production by B. megaterium in Figure 2b shows a similar pattern for all the amino acids; an early increase and decrease in the concentration within the first few hours, followed by another increase and decrease, which stabilizes for threonine and glutamine, at the end of 48 h.The pattern of the first peak was observed in other studies too [15,16]; the first increase is related to the faster metabolizing of the amino acids in the beginning of the process, and the first decrease is due to the consumption of a fraction of the produced cyanide by the same bacteria before the system stabilizes [15,16,18].In terms of glycine, bio-CN concentration increased to ca. 85 mg/L in the first 6 h, dropped to less than 63 mg/L after 10 h, scored a maximum concentration of ca.110 mg/L in 24 h, and ended up to about 66 mg/L after 48 h.For threonine and glutamine, ca.54 mg/L and ca.74 mg/L (respectively) were their first peaks, which appeared in the first hour.Bio-CN concentrations of ca.65 mg/L in threonine medium and ca.74 mg/L in glutamine medium were the second peaks that appeared after 10 h for both amino acids and levels then remained constant until the end of 48 h.Glycine was the simplest amino acid, and it was reasonable to observe a better growth and higher concentration of bio-CN in the medium containing this amino acid.

Effect of Concentration of Amino Acids
The results of bacterial growth (OD 600 ), bio-CN production, changes in pH, and level of DO after 48 h bacteria activity in LB medium containing different concentrations of glycine threonine, and glutamine are presented in Figure 3. Based on the results of bacterial growth (Figure 3a), the medium with no amino acid OD 600 reached approximately 2.5.Adding 1 g/L of amino acids reduced OD 600 to 2.187 for glycine, 1.677 for threonine, and 0.864 for glutamine.From 1 g/L to 5 g/L amino acids the decreasing trend of OD 600 continued at which the slowest rate was for glycine and the most sudden decrease was observed for threonine.For all the samples, OD 600 remained negligible after 5 g/L amino acid.The results indicated that, although amino acids are necessary for production of a high concentration of bio-CN, they are not the favorable food for bacteria, which agrees with the findings in other reports [8,10].Based on the results, increase in the concentration of amino acids caused a decrease in the population of bacteria.At the same time, amino acids had a positive (but less significant) influence on the concentration of bio-CN.Results suggested that the concentration of bio-CN is rather influenced by the presence of enzymes in the medium than being directly affected by the bacterial population (similar effect was seen elsewhere too [19]).Meaning, the enzymes generated by the bacteria are mainly responsible for bio-CN production.The trend of bio-CN production by B. megaterium in Figure 2b shows a similar pattern for all the amino acids; an early increase and decrease in the concentration within the first few hours, followed by another increase and decrease, which stabilizes for threonine and glutamine, at the end of 48 h.The pattern of the first peak was observed in other studies too [15,16]; the first increase is related to the faster metabolizing of the amino acids in the beginning of the process, and the first decrease is due to the consumption of a fraction of the produced cyanide by the same bacteria before the system stabilizes [15,16,18].In terms of glycine, bio-CN concentration increased to ca. 85 mg/L in the first 6 h, dropped to less than 63 mg/L after 10 h, scored a maximum concentration of ca.110 mg/L in 24 h, and ended up to about 66 mg/L after 48 h.For threonine and glutamine, ca.54 mg/L and ca.which agrees with the findings in other reports [8,10].Based on the results, increase in the concentration of amino acids caused a decrease in the population of bacteria.At the same time, amino acids had a positive (but less significant) influence on the concentration of bio-CN.Results suggested that the concentration of bio-CN is rather influenced by the presence of enzymes in the medium than being directly affected by the bacterial population (similar effect was seen elsewhere too [19]).Meaning, the enzymes generated by the bacteria are mainly responsible for bio-CN production.As shown in Figure 3b, bio-CN production gradually increased as the concentration of amino acids rose.From the test with 0 g/L amino acid to 10 g/L glycine, threonine, and glutamine, bio-CN concentration increased from ca. 33 mg/L to about 106 mg/L, 81 mg/L, and 73 mg/L, respectively.This was a result of the conversion of nitrogen and carbon in the amino acids to bio-CN by the bacteria through certain metabolic pathways.Synchronized with the changes in the bacterial population (OD600) and concentrations of bio-CN, there was a change for pH and DO of the solutions (Figure 3c,d).It was clear that with the increase in concentration of amino acids, the drop in pH level became less significant.There were two main contributing factors to describe the changes in the pH level; one was bacterial activity and second was the buffering property of the amino acids.All the experiments started at pH 10 and the drop in the pH level was related to the production of bio-CN which was associated with the release of some protons (Figure 1).It was also related to the buffering property of the amino acids, which prevented any significant change in the pH level.In a medium with a higher concentration of amino acids (greater than 7.5 g/L), the buffering property of the amino acids over weighs the acid production by the microorganisms [20].The oxygen consumption was a result of bacterial growth and metabolism, which was higher in the solution with a higher concentration of amino acids and a lower level of OD600.
The production of bio-CN from glycine was greater than either threonine or glutamine.A comparison of the structure and mass percentage of carbon-nitrogen (C-N) in glycine, threonine, and glutamine is shown in Table 1.Here, glutamine had the highest percentage of C-N and could theoretically produce more cyanide compared to the others; however, its structure is more complicated, and it is more difficult for bacteria to metabolize it.At the same time, glycine has the simplest structure and the second highest percentage of C-N in the list, which makes it the best precursor for cyanide.As shown in Figure 3b, bio-CN production gradually increased as the concentration of amino acids rose.From the test with 0 g/L amino acid to 10 g/L glycine, threonine, and glutamine, bio-CN concentration increased from ca. 33 mg/L to about 106 mg/L, 81 mg/L, and 73 mg/L, respectively.This was a result of the conversion of nitrogen and carbon in the amino acids to bio-CN by the bacteria through certain metabolic pathways.Synchronized with the changes in the bacterial population (OD 600 ) and concentrations of bio-CN, there was a change for pH and DO of the solutions (Figure 3c,d).It was clear that with the increase in concentration of amino acids, the drop in pH level became less significant.There were two main contributing factors to describe the changes in the pH level; one was bacterial activity and second was the buffering property of the amino acids.All the experiments started at pH 10 and the drop in the pH level was related to the production of bio-CN which was associated with the release of some protons (Figure 1).It was also related to the buffering property of the amino acids, which prevented any significant change in the pH level.In a medium with a higher concentration of amino acids (greater than 7.5 g/L), the buffering property of the amino acids over weighs the acid production by the microorganisms [20].The oxygen consumption was a result of bacterial growth and metabolism, which was higher in the solution with a higher concentration of amino acids and a lower level of OD 600 .
The production of bio-CN from glycine was greater than either threonine or glutamine.A comparison of the structure and mass percentage of carbon-nitrogen (C-N) in glycine, threonine, and glutamine is shown in Table 1.Here, glutamine had the highest percentage of C-N and could theoretically produce more cyanide compared to the others; however, its structure is more complicated, and it is more difficult for bacteria to metabolize it.At the same time, glycine has the simplest structure and the second highest percentage of C-N in the list, which makes it the best precursor for cyanide.

Mixing of Amino Acids
Based on the results in the previous section, 3 g/L of each amino acid was the maximum level that bacteria could survive and produce reasonable concentrations of bio-CN.Therefore, 3 g/L was considered as the maximum limit for the amino acids in designing the next phase of experiments to optimize the ratios of glycine, threonine, and glutamine for maximum bacterial growth (OD 600 ), and bio-CN production (Table S1 in the Supplementary Materials).

Mixing of Amino Acids
Based on the results in the previous section, 3 g/L of each amino acid was maximum level that bacteria could survive and produce reasonable concentrations of b CN.Therefore, 3 g/L was considered as the maximum limit for the amino acids designing the next phase of experiments to optimize the ratios of glycine, threonine, a glutamine for maximum bacterial growth (OD600), and bio-CN production (Table S1 in supplementary materials).

Monitor of Bacterial growth
The analysis of variance (ANOVA) for bacterial growth (OD600) was made based the results of mixing amino acids at different ratios.As shown in the ANOVA ta (supplementary information Table S2), all three amino acids showed significant effects the growth of bacteria (p-value smaller than 0.005 model was valid within 95% confide interval [21]).In addition, threonine-glutamine and glycine-glutamine were interactions with the highest level of influence on bacterial growth in mixed amino a conditions.The model suggested the medium with no amino acid (0 g/L of any of amino acid) was the best condition for maximum growth of bacteria and results shown Figure 3 agree with this outcome.This is mainly because of the inhibitory effect of am acids which prevent formation of certain enzymes by the bacteria responsible biosynthesis of the bacteria cell walls [22,23].
In terms of parameter interactions, Figure 4 shows the effect of changing concentration of two of the amino acids at a time (the graphs are results of simulation the Design Expert software, based on 20 experiments including replicates and cen points).Here, medium with 0 g/L amino acid showed the highest level of OD600 (ca. 2 and the medium with threonine and either glycine or glutamine had the lowest bacte growth (OD600 less than 0.70).From Figure 4a,b, when there was increase in concentration of glycine, while there was little or no glutamine in the system, the res was a decline in the population of bacteria from OD600 = 1.90 to OD600 = 1.00.In glutamine-threonine system (Figure 4c,d), when there was increase in the concentrat of threonine, while there was little or no glutamine in the system, a mild decrease in population of bacteria from OD600 = 2.1 to OD600 = 1.50 (for up to 1.5 g/L threonine) w observed and there was a sudden decrease in OD600 to 0.50, after reaching 3 g/L threon The interaction for glycine-threonine system is presented in Figure 4e,f and shows

Mixing of Amino Acids
Based on the results in the previous section, 3 g/L of each amino acid was maximum level that bacteria could survive and produce reasonable concentrations of b CN.Therefore, 3 g/L was considered as the maximum limit for the amino acids designing the next phase of experiments to optimize the ratios of glycine, threonine, a glutamine for maximum bacterial growth (OD600), and bio-CN production (Table S1 in supplementary materials).

Monitor of Bacterial growth
The analysis of variance (ANOVA) for bacterial growth (OD600) was made based the results of mixing amino acids at different ratios.As shown in the ANOVA ta (supplementary information Table S2), all three amino acids showed significant effects the growth of bacteria (p-value smaller than 0.005 model was valid within 95% confide interval [21]).In addition, threonine-glutamine and glycine-glutamine were interactions with the highest level of influence on bacterial growth in mixed amino a conditions.The model suggested the medium with no amino acid (0 g/L of any of amino acid) was the best condition for maximum growth of bacteria and results shown Figure 3 agree with this outcome.This is mainly because of the inhibitory effect of am acids which prevent formation of certain enzymes by the bacteria responsible biosynthesis of the bacteria cell walls [22,23].
In terms of parameter interactions, Figure 4 shows the effect of changing concentration of two of the amino acids at a time (the graphs are results of simulation the Design Expert software, based on 20 experiments including replicates and cen points).Here, medium with 0 g/L amino acid showed the highest level of OD600 (ca. 2 and the medium with threonine and either glycine or glutamine had the lowest bacte growth (OD600 less than 0.70).From Figure 4a,b, when there was increase in concentration of glycine, while there was little or no glutamine in the system, the res was a decline in the population of bacteria from OD600 = 1.90 to OD600 = 1.00.In glutamine-threonine system (Figure 4c,d), when there was increase in the concentrat of threonine, while there was little or no glutamine in the system, a mild decrease in population of bacteria from OD600 = 2.1 to OD600 = 1.50 (for up to 1.5 g/L threonine) w observed and there was a sudden decrease in OD600 to 0.50, after reaching 3 g/L threon The interaction for glycine-threonine system is presented in Figure 4e,f

Mixing of Amino Acids
Based on the results in the previous section, 3 g/L of each amino acid was maximum level that bacteria could survive and produce reasonable concentrations of b CN.Therefore, 3 g/L was considered as the maximum limit for the amino acids designing the next phase of experiments to optimize the ratios of glycine, threonine, a glutamine for maximum bacterial growth (OD600), and bio-CN production (Table S1 in supplementary materials).

Monitor of Bacterial growth
The analysis of variance (ANOVA) for bacterial growth (OD600) was made based the results of mixing amino acids at different ratios.As shown in the ANOVA ta (supplementary information Table S2), all three amino acids showed significant effects the growth of bacteria (p-value smaller than 0.005 model was valid within 95% confide interval [21]).In addition, threonine-glutamine and glycine-glutamine were interactions with the highest level of influence on bacterial growth in mixed amino a conditions.The model suggested the medium with no amino acid (0 g/L of any of amino acid) was the best condition for maximum growth of bacteria and results shown Figure 3 agree with this outcome.This is mainly because of the inhibitory effect of am acids which prevent formation of certain enzymes by the bacteria responsible biosynthesis of the bacteria cell walls [22,23].
In terms of parameter interactions, Figure 4 shows the effect of changing concentration of two of the amino acids at a time (the graphs are results of simulation the Design Expert software, based on 20 experiments including replicates and cen points).Here, medium with 0 g/L amino acid showed the highest level of OD600 (ca. 2 and the medium with threonine and either glycine or glutamine had the lowest bacte growth (OD600 less than 0.70).From Figure 4a,b, when there was increase in concentration of glycine, while there was little or no glutamine in the system, the res was a decline in the population of bacteria from OD600 = 1.90 to OD600 = 1.00.In glutamine-threonine system (Figure 4c,d), when there was increase in the concentrat of threonine, while there was little or no glutamine in the system, a mild decrease in population of bacteria from OD600 = 2.1 to OD600 = 1.50 (for up to 1.5 g/L threonine) w observed and there was a sudden decrease in OD600 to 0.50, after reaching 3 g/L threon The interaction for glycine-threonine system is presented in Figure 4e,f and shows

Monitor of Bacterial Growth
The analysis of variance (ANOVA) for bacterial growth (OD 600 ) was made based on the results of mixing amino acids at different ratios.As shown in the ANOVA table (Supplementary Information Table S2), all three amino acids showed significant effects on the growth of bacteria (p-value smaller than 0.005 model was valid within 95% confidence interval [21]).In addition, threonine-glutamine and glycine-glutamine were the interactions with the highest level of influence on bacterial growth in mixed amino acid conditions.The model suggested the medium with no amino acid (0 g/L of any of the amino acid) was the best condition for maximum growth of bacteria and results shown in Figure 3 agree with this outcome.This is mainly because of the inhibitory effect of amino acids which prevent formation of certain enzymes by the bacteria responsible for biosynthesis of the bacteria cell walls [22,23].
In terms of parameter interactions, Figure 4 shows the effect of changing the concentration of two of the amino acids at a time (the graphs are results of simulation by the Design Expert software, based on 20 experiments including replicates and center points).Here, medium with 0 g/L amino acid showed the highest level of OD 600 (ca.2.10) and the medium with threonine and either glycine or glutamine had the lowest bacterial growth (OD 600 less than 0.70).From Figure 4a,b, when there was increase in the concentration of glycine, while there was little or no glutamine in the system, the result was a decline in the population of bacteria from OD 600 = 1.90 to OD 600 = 1.00.In the glutamine-threonine system (Figure 4c,d), when there was increase in the concentration of threonine, while there was little or no glutamine in the system, a mild decrease in the population of bacteria from OD 600 = 2.1 to OD 600 = 1.50 (for up to 1.5 g/L threonine) was observed and there was a sudden decrease in OD 600 to 0.50, after reaching 3 g/L threonine.The interaction for glycine-threonine system is presented in Figure 4e,f and shows an overall low OD 600 for all concentrations.In this graph, basically no bacteria grew in the system with 3 g/L threonine.However, if the level of threonine was low, adding more glycine from 0 to 3 g/L could decrease the population of the bacteria steadily from ca.OD 600 = 1.30 to OD 600 = 0.70.
overall low OD600 for all concentrations.In this graph, basically no bacteria grew in the system with 3 g/L threonine.However, if the level of threonine was low, adding more glycine from 0 to 3 g/L could decrease the population of the bacteria steadily from ca.OD600 = 1.30 to OD600 = 0.70.

Bio-CN Production in Mixed Amino Acid Medium
The ANOVA table for bio-CN production in response to mixing the three amino acids is shown in the supplementary information Table S3.Based on the numbers of p-value (smaller than 0.005) the model is valid in 95% confidence interval [21].Table S3 shows that glycine and glutamine had the most influence on the level of bio-CN, and threonine and glutamine were the only couple with a meaningful interaction.The rest of the parameters and interactions were valid in about 85% to 90% of confidence interval (according to their corresponding p-value and degree of freedom) [21].

Bio-CN Production in Mixed Amino Acid Medium
The ANOVA table for bio-CN production in response to mixing the three amino acids is shown in the Supplementary Information Table S3.Based on the numbers of p-value (smaller than 0.005) the model is valid in 95% confidence interval [21].Table S3 shows that glycine and glutamine had the most influence on the level of bio-CN, and threonine and glutamine were the only couple with a meaningful interaction.The rest of the parameters and interactions were valid in about 85% to 90% of confidence interval (according to their corresponding p-value and degree of freedom) [21].
Figure 5 shows the effect of glycine, threonine, and glutamine on the concentration of bio-CN produced in mixed amino acid medium by B. megaterium (here, the graphs are results of simulation by the Design Expert software based on 20 experiments including replicates and center points).Based on the simulation, the effect of glycine on bio-CN concentration was best described in a form of a quadratic model with a second order effect for concentration of glycine.Effects of threonine and glutamine were determined to be linear.Figure 5a shows that glycine had a significant positive influence on the level of bio-CN.As it increased from 0 to 3 g/L, the concentration of bio-CN rose from ca.50 mg/L to over 80 mg/L.Threonine in mixed amino acid medium had a minor effect on the level of bio-CN, as the concentration of bio-CN stayed around 80 at all concentrations of threonine (Figure 5b).The effect of glutamine from 0 to 3 g/L in mixed amino acid medium was moderate, as it was only responsible for an increase from 67 mg/L to 87 mg/L in the level of bio-CN.
Based on the analysis of variance (ANOVA), the most significant interaction between the concentrations of amino acids in mixed amino acid medium was threonine-glutamine, which is shown in Figure 6 (the rest of the interactions were not significant in 95% confidence interval).Based on the graph, both threonine and glutamine exhibited a positive influence on cyanide production by B. megaterium; however, glutamine had a slightly more significant role.In addition, the graphs show that a higher concentration of glutamine could guarantee a production of about 85 mg/L bio-CN at any concentration of threonine.
Sustainability 2022, 14, x FOR PEER REVIEW 11 of 18 Figure 5 shows the effect of glycine, threonine, and glutamine on the concentration of bio-CN produced in mixed amino acid medium by B. megaterium (here, the graphs are results of simulation by the Design Expert software based on 20 experiments including replicates and center points).Based on the simulation, the effect of glycine on bio-CN concentration was best described in a form of a quadratic model with a second order effect for concentration of glycine.Effects of threonine and glutamine were determined to be linear.Figure 5a shows that glycine had a significant positive influence on the level of bio-CN.As it increased from 0 to 3 g/L, the concentration of bio-CN rose from ca.50 mg/L to over 80 mg/L.Threonine in mixed amino acid medium had a minor effect on the level of bio-CN, as the concentration of bio-CN stayed around 80 at all concentrations of threonine (Figure 5b).The effect of glutamine from 0 to 3 g/L in mixed amino acid medium was moderate, as it was only responsible for an increase from 67 mg/L to 87 mg/L in the level of bio-CN.Based on the analysis of variance (ANOVA), the most significant interaction between the concentrations of amino acids in mixed amino acid medium was threonine-glutamine, which is shown in Figure 6 (the rest of the interactions were not significant in 95% confidence interval).Based on the graph, both threonine and glutamine exhibited a positive influence on cyanide production by B. megaterium; however, glutamine had a slightly more significant role.In addition, the graphs show that a higher concentration of glutamine could guarantee a production of about 85 mg/L bio-CN at any concentration of threonine.Based on the analysis of variance (ANOVA), the most significant interaction between the concentrations of amino acids in mixed amino acid medium was threonine-glutamine, which is shown in Figure 6 (the rest of the interactions were not significant in 95% confidence interval).Based on the graph, both threonine and glutamine exhibited a positive influence on cyanide production by B. megaterium; however, glutamine had a slightly more significant role.In addition, the graphs show that a higher concentration of glutamine could guarantee a production of about 85 mg/L bio-CN at any concentration of threonine.The following equation was suggested by the software for the prediction of bio-CN concentration as a result of mixing glycine, threonine, and glutamine (each up to 3 g/L) in LB medium at starting pH = 10.The equation is helpful in prediction of the produced bio-CN in any combination of the amino acids.
where C represents concentration of each amino acid in g/L (glycine, threonine, and glutamine each up to 3 g/L).
The coefficient of each concentration in Equation ( 1) indicates the significance of each component.It shows that there is a higher positive coefficient for concentration of glycine, and relatively lower for concentrations of threonine and glutamine, which suggests that there is a greater role for glycine in production of bio-CN.In terms of amino acid interactions, each pair of glycine-threonine, glycine-glutamine, and threonine-glutamine have small negative coefficients, indicating their minor and negative influence on the production of bio-CN.Considering the coefficient for all the three amino acids at the same time, there is a small number which suggests little influence of their triple interaction on bio-CN concentration.After optimization, the RSM D-optimal optimization method suggested 2.84 g/L glycine, 0 g/L threonine, and 3.00 g/L glutamine as the optimum condition for maximum bio-CN production equal to 93.13 mg/L and desirability of 0.95.In practice, this medium was prepared and produced 86.59 ± 4.23 mg/L after three replicates at identical condition.A graph comparing the actual results based on the performed experiments and the predicted values for bio-CN concentration using the Equation ( 1) is presented in Figure 7.The plot shows a relatively high accuracy for the model over the range of 30 mg/L to 96 mg/L bio-CN concentration.
glutamine each up to 3 g/L).
The coefficient of each concentration in Equation ( 1) indicates the significance o component.It shows that there is a higher positive coefficient for concentration of gly and relatively lower for concentrations of threonine and glutamine, which suggest there is a greater role for glycine in production of bio-CN.In terms of amino interactions, each pair of glycine-threonine, glycine-glutamine, and threonine-gluta have small negative coefficients, indicating their minor and negative influence o production of bio-CN.Considering the coefficient for all the three amino acids at the time, there is a small number which suggests little influence of their triple interacti bio-CN concentration.After optimization, the RSM D-optimal optimization m suggested 2.84 g/L glycine, 0 g/L threonine, and 3.00 g/L glutamine as the opti condition for maximum bio-CN production equal to 93.13 mg/L and desirability of In practice, this medium was prepared and produced 86.59 ± 4.23 mg/L after replicates at identical condition.A graph comparing the actual results based o performed experiments and the predicted values for bio-CN concentration usin Equation ( 1) is presented in Figure 7.The plot shows a relatively high accuracy fo model over the range of 30 mg/L to 96 mg/L bio-CN concentration.

Biogenic Mechanism in Bio-CN Production
The growth and production of bio-CN by B. megaterium is influenced by the pre of different types of amino acids as the supplier of nitrogen and carbon.It is reported in B. megaterium, there are numerous intercellular reactions responsible for bio formation, carbohydrate metabolism, and amino acid conversion.There are ove reactions for amino acid metabolism (including bio-CN formation) [24].All these reac are functioning through multiple biological pathways and metabolic cycles; importantly the glycolysis pathway, pentose-phosphate (PP) pathway, amino pathway, and tricarboxylic acid (TCA) cycle [25].The interactions between

Biogenic Mechanism in Bio-CN Production
The growth and production of bio-CN by B. megaterium is influenced by the presence of different types of amino acids as the supplier of nitrogen and carbon.It is reported that in B. megaterium, there are numerous intercellular reactions responsible for biomass formation, carbohydrate metabolism, and amino acid conversion.There are over 300 reactions for amino acid metabolism (including bio-CN formation) [24].All these reactions are functioning through multiple biological pathways and metabolic cycles; most importantly the glycolysis pathway, pentose-phosphate (PP) pathway, amino acid pathway, and tricarboxylic acid (TCA) cycle [25].The interactions between these metabolic pathways and cycle that contribute to creation of ATP (adenosine triphosphate) and DHAP (dihydroxyacetone phosphate) as the main energy carriers and blocks for cell formation and production of bio-CN in B. megaterium species, are explicitly explained by Aminian-Dehkordi et al. (2020) [15].First, in the glycolysis pathway, carbohydrates are phosphorylated and are converted to different enzymes and coenzymes.In conjunction with the PP pathway, some other intermediate products are formed through transaldolase and transketolase reactions.The products of these two pathways are fed to the TCA cycle and result in the formation of ATP (energy carrier molecule), NAD(P)H (nicotinamide adenine dinucleotide phosphate; trigger for amino acid conversion and cell production), and accumulation of bio-CN [26,27].
The reactions below show some of the general reactions in biogenic production of cyanide through HCN synthase enzyme and flavin adenine dinucleotide (FAD) from glycine [26,28]: (2) In intercellular reactions, ATP and NAD(P)H are produced which play roles as electron donors (chemical energy supply).They also produce adenosine diphosphate (ADP: as biological energy supply) and inorganic phosphate (Pi: essential nutrient for bacterial activity) which contribute to reducing the amino acids through different reactions.Some of the redox reactions could be in the following forms [29]: Comparing different types of amino acids, Aminian-Dehkordi et al. (2020) [15] employed the mentioned pathways, cycle, and reactions to simulate the effect of some amino acids on bacterial growth and bio-CN production based on iJA1121 gene in B. megaterium.The results revealed that threonine has a greater potential for growth of bacteria than glycine, and glutamine has a less significant influence.In terms of bio-CN production, threonine and glutamine have similar potential and higher than glycine.Comparing their findings to the result of our study, in our experiment glycine was the most successful candidate that stood above glutamine and threonine.A reason that our results did not exactly follow the prediction of Aminian-dehkordi et al. was our medium ingredient and pH is not identical and, therefore, the metabolic reactions were altered.Their simulation was based on a glucose medium, which started at pH 7, while our study was carried out in an LB medium, at an initial pH 10.Moreover, the metabolic cycles and pathway for extracting C-N for cyanide production in B. megaterium are more successful in breaking the simpler compounds, rather than the more complicated ones [30,31].Comparing glycine, threonine, and glutamine, glycine is the simplest amino acid and has a relatively simple structure; therefore, it produces a greater concentration of cyanide, even though it may not have the highest density of C-N in its structure.

Gold Leaching in Mixed Amino Acid Medium
The optimized condition for maximum bio-CN production was employed for leaching gold from gold powder.Figure 8 shows the concentration of gold in the solutions over a 24 h period after adding 1.0 mg gold powder in the optimized medium (containing ca.86 mg/L bio-CN), control medium (0 mg/L cyanide), and chemical cyanide (Chem-CN, at 85 mg/L cyanide).The bio-CN could leach an average 0.45 ± 0.05 mg/L gold, which is almost equal to the concentration of the leached gold from chemical cyanide (0.43 ± 0.03 mg/L) and the difference is insignificant.At the same time, approximately no gold was leached in the control medium, indicating the insignificant role of mixed amino acid medium for gold leaching over a 24 h period.Comparing the result with our previous study by using standard LB medium and 5 g/L glycine [17], 62 mg/L bio-CN was produced and about 0.33 mg/L gold was leached under similar conditions which confirms the higher potential of the biological system with an optimized mixture of the selected amino acids.
leached in the control medium, indicating the insignificant role of mixed amino acid medium for gold leaching over a 24 h period.Comparing the result with our previous study by using standard LB medium and 5 g/L glycine [17], 62 mg/L bio-CN was produced and about 0.33 mg/L gold was leached under similar conditions which confirms the higher potential of the biological system with an optimized mixture of the selected amino acids.Gold leaching results regarding bio-CN and Chem-CN are almost close in numbers.Due to the presence of multiple chemicals (such as amino acids and certain enzymes) in the biological medium, it was expected that higher gold leaching efficiency would be observed in the system with bio-CN compared to Chem-CN (at equal concentration of cyanide).A reason for that is the synergistic effect of the multiple lixiviants in the biological medium that can complex with gold and assist the cyanidation reaction [32][33][34].However, there are also some enzymes (such as cyanidase, β-cyanoalanine synthase, and γ-cyano-α-aminobutyric acid synthase for B. megaterium) in the biogenic medium that are responsible for degradation of bio-CN [18,35,36], and it is highly possible that the enzymes contributed to deactivation of the bio-CN during the leaching step.There are methods to deactivate the enzymes from the biological systems and prevent cyanide degradation.Therefore, the next step of study is to investigate the role of enzymes in conversion of bio-CN and explore options to deactivate the obstructing enzymes.

Comparison Study
Table 2 compares the concentration of bio-CN produced at optimum medium condition in this study with the reported bio-CN values from other studies using B. megaterium.As shown in the Table 2, most of the researchers have used glycine as the sole amino acid to stimulate cyanide in their system.In this comparison, either low concentration of glycine or low pH resulted in lesser concentration of bio-CN (bio-CN does not exceed 16 mg/L in a medium at pH 7 or glycine concentration of 0.5 g/L).In the report with no amino acid, a negligible concentration of 2 mg/L bio-CN was produced [15], which demonstrates the significant role of amino acids in production of bio-CN.Adding a small amount of glycine (0.5 g/L) to the system resulted in a considerable improvement in the concentration of bio-CN of up to 16 mg/L [37].At pH values close to 10, when concentration of glycine was higher than 0.5 g/L and lower than 10 g/L, there Gold leaching results regarding bio-CN and Chem-CN are almost close in numbers.Due to the presence of multiple chemicals (such as amino acids and certain enzymes) in the biological medium, it was expected that higher gold leaching efficiency would be observed in the system with bio-CN compared to Chem-CN (at equal concentration of cyanide).A reason for that is the synergistic effect of the multiple lixiviants in the biological medium that can complex with gold and assist the cyanidation reaction [32][33][34].However, there are also some enzymes (such as cyanidase, β-cyanoalanine synthase, and γ-cyano-αaminobutyric acid synthase for B. megaterium) in the biogenic medium that are responsible for degradation of bio-CN [18,35,36], and it is highly possible that the enzymes contributed to deactivation of the bio-CN during the leaching step.There are methods to deactivate the enzymes from the biological systems and prevent cyanide degradation.Therefore, the next step of study is to investigate the role of enzymes in conversion of bio-CN and explore options to deactivate the obstructing enzymes.

Comparison Study
Table 2 compares the concentration of bio-CN produced at optimum medium condition in this study with the reported bio-CN values from other studies using B. megaterium.As shown in the Table 2, most of the researchers have used glycine as the sole amino acid to stimulate cyanide in their system.In this comparison, either low concentration of glycine or low pH resulted in lesser concentration of bio-CN (bio-CN does not exceed 16 mg/L in a medium at pH 7 or glycine concentration of 0.5 g/L).In the report with no amino acid, a negligible concentration of 2 mg/L bio-CN was produced [15], which demonstrates the significant role of amino acids in production of bio-CN.Adding a small amount of glycine (0.5 g/L) to the system resulted in a considerable improvement in the concentration of bio-CN of up to 16 mg/L [37].At pH values close to 10, when concentration of glycine was higher than 0.5 g/L and lower than 10 g/L, there was a greater production of bio-CN in the system.In a medium with 5 g/L glycine, between 37 mg/L to 62 mg/L bio-CN was reported.Based on the results presented in the table, pH is another contributing factor interacting with amino acids in bio-CN production by B. megaterium.There is an impact on bio-CN production if pH is low and close to 7. The parameter of pH is a complicated factor, as it contributes in different ways to bacterial growth, metabolic pathways/cycle of bio-CN, and speciation of cyanide [6].It has been comprehensively studied that pH values closer to 7 are the best for bacterial growth; however, there is a condition that it is suitable for consumption of cyanide (as a source of food/nitrogen) when there are many bacteria in the system and overall metabolic activities are high [17,18].At the same time, HCN gas is the stable form of cyanide at pH values lower than 9.2, which contributes to loss of cyanide as gas [38].Cysteine and glutamine are the only amino acids, except for glycine, that have been explored.In such systems, cysteine at 20 g/L and starting pH of 7 resulted in a maximum 35 mg/L bio-CN concentration.Cysteine (NH 2 -CH 2 -SH) has a sulfur and a more complex structure compared to glycine (NH 2 -CH 2 -COOH), and is reactive and oxidizes quickly to other compounds [39].Therefore, it may seem reasonable to see a lower concentration of bio-CN produced from cysteine.Our results indicated a significantly better performance of B. megaterium in the system with mixed glycine (2.84 g/L) and glutamine (3.00 g/L), which could produce the greatest concentration of bio-CN (86 mg/L).

Conclusions
A bio-cyanidation process using B. megaterium in standard LB medium and at initial pH 10 was investigated to evaluate the effect of amino acids on bacterial growth and bio-CN production.The results of analyzing three types of amino acids (glycine, threonine, and glutamine) over 0 to 10 g/L showed glycine is the best option to stimulate bio-CN, despite the greater potential of glutamine.At 5 g/L amino acid, a maximum concentration of ca.110 mg/L bio-CN was recorded in glycine medium (24 h), which was, respectively, higher than ca.72 mg/L bio-CN from glutamine (48 h), and ca.65 mg/L bio-CN from threonine (10 h).The results of bacterial growth suggested that OD 600 decreased as the concentration of amino acid increased, and an insignificant growth could be observed after 3 g/L amino acid (any type).The optimization results for mixing amino acids, based on the D-optimal method of response surface methodology, suggested a greater role for glycine and glutamine in bio-CN production.The mechanisms involved in conversion of the amino acids and nutrients were explained through the following multiple biological pathways and a metabolic cycle: glycolysis pathway, pentose-phosphate pathway, amino acid pathway, and TCA cycle.Here, an equation to predict the concentration of bio-CN based on the amino acid concentration was achieved.The optimum condition for maximum bio-CN was determined to be 2.84 g/L glycine, 0 g/L threonine, and 3.00 g/L glutamine, which could deliver a satisfactory gold leaching efficiency.This shows the positive role of glutamine as an alternative to glycine in the process of bio-CN production and opens the door for more exploration about amino acid alternatives in the bio-cyanidation of gold.

Figure 1 .
Figure 1.Major sequences in cyanide production from glycine through bacterial activity.

Figure 1 .
Figure 1.Major sequences in cyanide production from glycine through bacterial activity.

Figure 3 .
Figure 3. Changes in (a) OD600, (b) concentration of bio-CN, (c) pH, and (d) DO as a result of different concentrations of amino acids after 48 h.

Figure 3 .
Figure 3. Changes in (a) OD 600 , (b) concentration of bio-CN, (c) pH, and (d) DO as a result of different concentrations of amino acids after 48 h.

Table 1 .
Structure and mass percentage of C-N in in glycine, threonine, and glutamine.

Figure 4 .
Figure 4. Parameter interactions for monitoring growth of B. megaterium in mixed amino acid condition; (a,b) interactions of glycine-glutamine, (c,d) interactions of threonine-glutamine, and (e,f) interactions of glycine-threonine.

Figure 4 .
Figure 4. Parameter interactions for monitoring growth of B. megaterium in mixed amino acid condition; (a,b) interactions of glycine-glutamine, (c,d) interactions of threonine-glutamine, and (e,f) interactions of glycine-threonine.

Figure 5 .
Figure 5.Effect of concentration of (a) glycine, (b) threonine, and (c) glutamine on the level of bio-CN in a mixed amino acid medium.

Figure 6 .
Figure 6.Interactions between threonine and glutamine in mixed amino acid medium for bio-CN production by B. megaterium; (a) 2D view and (b) 3D view.The following equation was suggested by the software for the prediction of bio-CN concentration as a result of mixing glycine, threonine, and glutamine (each up to 3 g/L) in LB medium at starting pH = 10.The equation is helpful in prediction of the produced bio-CN in any combination of the amino acids. (/) = +32.98+ 24.69 ×  + 10.20 ×  + 11.71 ×  − 3.11 ×  ×  − 2.35 ×  ×  −

Figure 5 .
Figure 5.Effect of concentration of (a) glycine, (b) threonine, and (c) glutamine on the level of bio-CN in a mixed amino acid medium.

Figure 5 .
Figure 5.Effect of concentration of (a) glycine, (b) threonine, and (c) glutamine on the level of bio-CN in a mixed amino acid medium.

Figure 6 .
Figure 6.Interactions between threonine and glutamine in mixed amino acid medium for bio-CN production by B. megaterium; (a) 2D view and (b) 3D view.The following equation was suggested by the software for the prediction of bio-CN concentration as a result of mixing glycine, threonine, and glutamine (each up to 3 g/L) in LB medium at starting pH = 10.The equation is helpful in prediction of the produced bio-CN in any combination of the amino acids. (/) = +32.98+ 24.69 ×  + 10.20 ×  + 11.71 ×  − 3.11 ×  ×  − 2.35 ×  ×  −

Figure 6 .
Figure 6.Interactions between threonine and glutamine in mixed amino acid medium for bio-CN production by B. megaterium; (a) 2D view and (b) 3D view.

Figure 7 .
Figure 7. Predicted versus actual value for bio-CN concentration.

Figure 7 .
Figure 7. Predicted versus actual value for bio-CN concentration.

Figure 8 .
Figure 8. Concentration of leached gold in the optimized medium, control medium, and chemical cyanide.

Figure 8 .
Figure 8. Concentration of leached gold in the optimized medium, control medium, and chemical cyanide.

Table 1 .
Structure and mass percentage of C-N in in glycine, threonine, and glutamine.

of Amino Acid Molar Mass (g/Mole) Structure of Amino Acid Mass Percentage of C-N in the Structure (%)
Sustainability 2022, 14, x FOR PEER REVIEW 9 o

Table 1 .
Structure and mass percentage of C-N in in glycine, threonine, and glutamine.

Table 1 .
and shows Structure and mass percentage of C-N in in glycine, threonine, and glutamine.
Sustainability 2022, 14, x FOR PEER REVIEW 9 o