«——[Functions and physiological significance of extracellular proteases.] ——»
In recent years, the application of enzymes in industrial processing has received considerable attention, mainly due to environmental concerns, proteases to themselves have accounted for CA, 40% of the total sales of enzymes worldwide, proteases are indeed necessary for cell growth and differentiation.
Therefore, they are ubiquitous in living organisms and are associated with Pseudomonas aeruginosa, Bacillus cereus, Bacillus licheniformis, Bacillus lentil sprouts, and Clostridium-sP.
Aeromonas hydrophila is by far the most synthesized extracellular protease, which is particularly convenient from a production point of view, and significant productivity has also been observed in several species Bacil-Lus.
As a result of the large number of commercially available proteases today, it is also witnessing a growing portfolio of uses.
However, increasing demand is driving efforts to comprehensively screen new strains that can produce proteases with better characteristics or industrial processes that are easy to develop at lower cost/higher yields.
Examples include organic solvent-stabilized proteases from Bacillus sphericalis and lactation proease from Bacillus subtilis.
However, our native strains seem to be quite different, so any better achievement requires a different species elsewhere and about different species that do not necessarily parallel our unique strains.
It has long been recognized that a major barrier to the successful application of biotechnology in industry is the total cost of enzyme production and downstream purification, and 40% of the final cost of the enzyme actually comes from the medium used for fermentation from its source.
Therefore, if an economically viable process is sought, the optimization of fermentation bears a great deal of relevance.
Each microorganism actually has its own unique constraints on growth and enzyme synthesis/secretion.
As a result, unique physicochemical and nutritional requirements have been identified, and the qualitative and quantitative profiles of the medium should be optimized, among other operational factors, for each microorganism and desired metabolite.
For example, the production of extracellular proteases is strongly influenced by properties such as C/N ratio, the presence/absence of easily metabolized sugars and nitrogen sources, and the availability of specific metal ions, while treatment conditions such as aeration rate, seeding density, pH, temperature, and incubation time also play a key role.
Optimizing the volume changes of process parameters "one variable at a time" using classical methods is time-consuming.
Therefore, it is expensive when considering a large number of variables, and although the interaction between parameters is ignored, it is still the most commonly used strategy in bioprocess engineering to obtain high yields of enzymes in microbial systems.
Especially in the early stages of process optimization, preliminary studies that actually affect the synthesis yield and rate of en-enzymes, with results ignored for mutual treatment interactions, are acceptable.
Just to find out whether there is a factor that affects protease production to a SIG, the most reasonable range of further optimization, including the interaction between these factors, are therefore ordered.
In order to overcome the previously mentioned "once in a time" method that cannot precisely indicate the interaction between processing parameters, factorial designs are proposed, which are actually often used to screen for effects of reactions.
When more than 3 key factors need to be tested, they are usually in the form of appropriate scores to avoid the need for extensive experimentation.
Therefore, the main objective of this study is to find the optimal combination of processing factors to increase the protease yield of the wool-associated Ba-cillussp strain HTS102.
This is a new strain recently isolated from a native Portuguese sheep breed that secretes a very strong and stable protease with keratinizing properties.
After several comparative "univariate real-time" studies, a 2V6-L fractional fuzzy design was adopted to better articulate the main effects and bivariate interactions associated with the most promising processing parameters.
and eventually increased the protease yield of this microorgan, in part, was enough to support the eventual interest of industry.
«——[Preliminary screening by the "one factor at a time" approach ·] ——»
Nutrient solution medium was used as a control; While this may not be the cheapest medium on an industrial scale, the stability of its composition was found to be a determining factor in the reproducibility of the technology, leading us to choose pure media obtained from inexpensive sources.
Beef and yeast extracts, replacing cheaper carbon and fluoride sources, respectively, tested at the same concentration of starch, glycerin, lactose, sucrose, glucose and fructose, and nitrogen sources considered are protein age, trypsin age, chlorination and sulfuric acid.
To find out the key factors in the production of proteases by Bacillus, 10 physicochemical factors that influence the production of proteases by many bacteria were tested.
HTS102 metal ion concentration -10mMFeso01gL-Mgso inoculation density and pH value were the main factors affecting the inoculation amount.
Several media formulations were prepared by the "move one component at a time" method to determine the effect of each component of NB on protease.
Six key factors affecting Bacillus bacillus protease production were screened, HTS102 yeast level extract and protease, seeding density, stirring speed, pH and culture temperature were optimized by 2v, reproducible-free design.
The range of values for each factor was chosen based on information in the literature, plus experience gained during the trial.
Erlenmeyer flasks are seeded with 1% fresh inoculum 0.60 Donm, extracellular protease activity is quantified after a 36 h incubation period at 37 °C, unless otherwise stated.
The microorganism used in this study is Bacillus braceus, superconducting 102 isolated from Portuguese Me-rino wool – and officially preserved in a publicly available cultural collection collected from BCCMLMG bacterial cultures in Ghent, Belgium.
Filter the sterilized cell-free supernatant with a 0.45um filter, determine the degree of casein decomposition by colorimetry at 660 nm, and protease activity assay with Folin-Ciocalteu reagent.
A unit of proteolytic activity refers to the amount of enzyme that hydrolyzes casein so that the change in absorbance per minute at a pH of 7.5 at 37°C is equal to 1.0 umol of tyrosine.
Throughout the 36-h incubation period, aliquots are extracted, total protein assays are performed using BCA absorbance at 562 nm, and the protein assay kits are then directed according to the supplier.
«——[Carbon source selection for extracellular proteases.] ——»
Of the several carbon sources tested, the original NB medium formulation yielded the highest protease activity, and the production of proteases was almost completely re-suppressed in the presence of glucose.
Therefore, carbon sources do not serve as an optimization factor, and when considering nitrogen sources, all tested inorganic and organic compounds appear to impede enzyme production, relative to those observed in the plain control group.
When replacing yeast paste and protein aged with pure protein aging, protease production is significantly reduced, indicating that yeast paste and protein aged may have a synergistic effect.
To determine the effect of different components on protease activity, reference media are enriched on one basis after another.
All tested components resulted in lower protease yields than reference media, seeking the effect of initial pH on protease production at pHs of 4, 7, and 10.
These results suggest that Bacillus blossomensis HTS102 is capable of growing and releasing proteases over a wide pH range.
Stirring speed affects protease yield, consistent with U-mode In all four trials performed, culture shaking at 50 rpm level yielded lower protease activity than any other test rate.
Surprisingly, no stirring at all produces a very similar effect, like stirring at a speed of more than 50 revolutions.
Protease activity reaches its maximum at 37 °C, while the activity obtained at 30 °C and 55 °C is significantly reduced, i.e. 23% and 25% of the activity observed at 37 °C, respectively.
The most influential nutrient broth component protease yield is beef extract, while the other components of alkaline NB medium play a role in enzyme production because it greatly reduces enzyme synthesis along the action of AP-proach.
When yeast extract and NaCl are simultaneously excreted from the medium, the yield of protease decreases further, indicating that although naci is not a source of nitrogen or carbon, proba-bly plays an important role in guaranteeing proper ionic strength for protease synthesis.
Due to the need to meet stratification conditions, the term cannot exclude a higher overall F-value from the model findings indicating that posture-related models provide a good fit, with only a 0.17% chance that such a large value occurs due to pure noise.
Therefore, our experimental data fit the following - reduced two-factor interaction model equation:
where Y is the predicted response, the intercept term PP is the linear effect, B is the interaction effect, and X and X are the processing variables, and in order to determine the level of each variable that results in maximum protease production, a contour map is constructed by representing protease activity relative to any two independent variables.
Among the various combinations of processing factors studied, the measured protease activity varied greatly between 7.40 and 54.64U-. From the results of linear regression analysis based on the 2V score factor design, there is a form that is simplified:
The first step in developing an industrial bioprocess is to isolate a strain capable of producing the metabolite of interest and obtaining a sufficiently high yield, a method that requires intensive screening.
Therefore, a large number of strains need to be tested to identify rapidly producing bacteria, or even alternative useful metabolites for extracellular microbial products, and the conventional experimental method is to grow them on agar plate medium.
The strategy of then evaluating the microbial capacity of a product from the radius of the product area spread around the source colony and was detailed elsewhere, when separating the new modified protease-producing bacteria used in wool in the textile industry.
Due to the increasing economic value of alkaline proteases, HTS102, including media composition and culture conditions, was screened for Bacillus bacillussP with extracellular protease yield as the objective function.
After isolating a strain with promising properties, the synthesis and secretion of metabolites should continue to be optimized to make their industrial applications as attractive as possible, recall that the optimization protocol follows the results here -
Two sequential approaches are adopted: first, a set of single-factor real-time experiments with a total of 24 factors in order to reduce the long list to a smaller, more manageable list of key factors.
Second, the 2v61 fractional factorial design tests the effects of only 6 more relevant key factors.
After comprehensive pre-screening based on the "one-factor real-time method", the 2V6 score factor design was used to further test the six variables.
Yeast extract, protease, temperature, and pH ultimately greatly influence protease production, and this experimental method is statistically proven to be sufficient and has significant improvements.
Of the several carbon sources tested, none were more productive than the protein plum formulated with NB medium.
It is thus indicated that the presence of other components in the medium, other than beef extract, either inhibits protease production or, at least, does not promote its production, and that protease synthesis reduces glucose content by about 93%, possibly due to catabolic inhibition.
Since yeast extract and protease co-produce proteases, the results indicate synergy.
Therefore, these two nutrients were chosen as subsequent optimization steps, pH7 seems to be the most suitable, but as an important factor, as an important factor, the fractional factorial design of 2v is also considered.
Protease synthesis can be favorably aided by facilitating cell access to nutrients in the medium while avoiding the accumulation of inhibitory product concentrations, however, high agitation rates can also lead to cell disruption, a difficulty that may outweigh the advantages of stirring described above.
At high stirring rates and without stirring at all, the results of protease production are essentially similar.
This may be due to the low oxygen supply and the inherent difficulties in obtaining nutrients, and since agitation is an important factor in economically viable industrial processes, the mixing rate was chosen as a factor.
While 37 °C appears to be optimal, it is clear that temperature is an important factor in protease production.
It is included in the 2v6-partial factor design, and inoculation density seems to have a certain effect on enzyme production levels, which is undoubtedly an important parameter for industrial scale-up, so this factor is also included in subsequent optimization studies.
After a single-factor real-time analysis of the effects of individual NB components, it is difficult to draw conclusions about which nutrients should be selected for the next optimization step.
Therefore, through the framework factorial design of four independent factors, the interaction between them was further studied, and only the concentration range to be considered was determined.
The experiment is based on the results of previous screening experiments centered on NB medium, each performed only once, through the response of Bacillus bacillus to the levels of beef extract and yeast extract, based on the protease producer HTS102:
This regression equation has a good fit because its complex correlation coefficient is 0.9695, and recall that a value greater than 0.75 indicates that the model fits the experimental data acceptably.
This coefficient is actually an estimate of the overall variation in the data that the model can explain, so our model was able to statistically explain 96.95% of the variation in response, with a value of 0.9466 for "adjusted R2", further confirming the significance of the above model, which is different from the "predicted R".
«——[·Extracellular protease study results.] ——»
The interaction between factors occurs when the overall response differs from their combination considering that the two factor interactions are independent and can be easily explained.
Because when the influence of one factor depends on the level of the other, it shows non-parallel lines.
Therefore, the interaction between yeast extract and pH proved important, and the contour map is a two-dimensional representation of the response to the selected factor with surface asymmetry.
So no peaks are visible, so there is clearly room to further fine-tune the optimal trajectory we ultimately predict using the RSM model.