Aspergillus fumigatus secretes a protease(s) that displays in silico binding affinity towards the SARS-CoV-2 spike protein and mediates SARS-CoV-2 pseudovirion entry into HEK-293T cells.

BACKGROUND: The novel coronavirus disease of 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Data from the COVID-19 clinical control case studies showed that this disease could also manifest in patients with underlying microbial infections such as aspergillosis. The current study aimed to determine if the Aspergillus (A.) fumigatus culture media (i.e., supernatant) possessed protease activity that was sufficient to activate the SARS-CoV-2 spike protein. METHODS: The supernatant was first analysed for protease activity. Thereafter, it was assessed to determine if it possessed proteolytic activity to cleave a fluorogenic mimetic peptide of the SARS-CoV-2 spike protein that contained the S1/S2 site and a full-length spike protein contained in a SARS-CoV-2 pseudovirion. To complement this, a computer-based tool, HADDOCK, was used to predict if A. fumigatus alkaline protease 1 could bind to the SARS-CoV-2 spike protein. RESULTS: We show that the supernatant possessed proteolytic activity, and analyses of the molecular docking parameters revealed that A. fumigatus alkaline protease 1 could bind to the spike protein. To confirm the in silico data, it was imperative to provide experimental evidence for enzymatic activity. Here, it was noted that the A. fumigatus supernatant cleaved the mimetic peptide as well as transduced the HEK-293T cells with SARS-CoV-2 pseudovirions. CONCLUSION: These results suggest that A. fumigatus secretes a protease(s) that activates the SARS-CoV-2 spike protein. Importantly, should these two infectious agents co-occur, there is the potential for A. fumigatus to activate the SARS-CoV-2 spike protein, thus aggravating COVID-19 development.

Transcriptome analysis reveals the underlying mechanism for over-accumulation of alkaline protease in Bacillus licheniformis.

AIMS: Bacillus licheniformis AQ is an industrial strain with high production of alkaline protease (AprE), which has great industrial application value. However, how to regulate the production of AprE in the process of industrial fermentation is still not completely clear. Therefore, it is important to understand the metabolic process of AprE production in the industrial fermentation medium. METHODS AND RESULTS: In this study, transcriptome sequencing of the whole fermentation course was performed to explore the synthesis and regulation mechanism of AprE in B. licheniformis AQ. During the fermentation process, the AprE got continuously accumulated, reaching a peak of 42 020 U/mL at the fermentation endpoint (48 h). Meanwhile, the highly expressed genes were observed. Compared with the fermentation endpoint, there were 61 genes in the intersection of differentially expressed genes, functioning as catabolic processes, peptidases and inhibitors, chaperones, and folding catalysts. Furthermore, the protein-protein interactions network of AprE was constructed. CONCLUSION: This study provides important transcriptome information for B. licheniformis AQ and potential molecular targets for further improving the production of AprE.

Optimization of welan gum extraction and purification using lysozyme and alkaline protease.

Welan gum, a natural polysaccharide produced by Sphingomonas sp. ATCC 31555, has attracted considerable attention in the scientific community due to its desirable properties. However, challenges, such as high viscosity, residual bacterial cells, carotenoids, and protein complexation, hinder the widespread application of welan gum. In this study, we established a method for the extraction and purification of welan gum using a synergistic approach with lysozyme and alkaline protease. Lysozyme hydrolysis conditions were optimized by applying response surface methodology, and the best results for bacterial cell removal were achieved at 11 000 U/g, 44 °C, and pH 9 after 3 h of treatment. Subsequently, we evaluated protein hydrolysis through computer simulation and identified alkaline protease as the most suitable enzyme. Through experimental investigations, we found that the optimal conditions for alkaline protease hydrolysis were 7500 U/g, 50 °C, pH 10, and 600 rpm. These conditions resulted in a sugar recovery rate of 76.1%, carotenoid removal rate of 89.5%, bacterial removal rate of 95.2%, and protein removal rate of 87.3% after 3 h of hydrolysis. The purified welan gum exhibited high transparency and purity. Structural characterization and antioxidant activity evaluation revealed that enzymatically purified welan gum has potential application prospects. Our study provides valuable insights into the optimal method for the enzymatic extraction and purification of welan gum. Such a method is conducive to the development of the multiple potential applications of welan gum. KEY POINTS: • A novel process for the synergistic purification of welan gum using lysozyme and alkaline protease was established. • In silico virtual digestion was employed to select the purification enzyme. • Welan gum with high transparency and purity was obtained.

Release of CM-12 from A2-type casein by the cleavage of Ser-Leu-Xaa at the C-terminus using Aspergillus oryzae alkaline protease.

BACKGROUND: Aspergillus oryzae protease can release the opioid peptide ß-casomorphin-10 (CM-10, YPFPGPIPNS, 60-69) from A2-type casein. However, not only is the yield of the active peptide low, but the key enzyme involved in processing has yet to be identified. RESULTS: A significant amount of the opioid peptide 60YPFPGPIPNSLP71 (CM-12) was produced from the A2-type casein peptide 53AQTQSLVYPFPGPIPNSLPQNIPPLTQTPV82 when the active protease in A. oryzae protease extract was fractionated with DEAE-Sepharose. The fractionated enzyme produced CM-12 from bovine A2-type casein but not from bovine A1 casein. A major protein of 34 kDa was purified and identified as an alkaline protease (Alp). Motif prediction of the Alp cleavage site using Multiple EM for Motif Elicitation analysis revealed preferable cleavage at the C-terminal end of Ser-Leu-Xaa for the release of CM-12. A2-type casein hydrolysate by Alp exhibited similar levels of opioid activity to that of synthetic CM-12 in cAMP-Glo assays with µ-opioid receptor-expressing HEK293 cells. These results suggest that CM-12 is a major opioid peptide in the casein hydrolysate. CONCLUSION: Our findings showed that Alp fractionated from A. oryzae protease extract produced the opioid peptide CM-12 from A2-type casein as a result of preferential cleavage at the C-terminal end of Ser-Leu-Xaa and the removal of coexisting enzymes. Moreover, docking predictions suggested a stable interaction between CM-12 and the 3D structure of Alp. Casein hydrolysate with Alp-containing CM-12 has the potential for use as a bioactive peptide material with opioid activity. © 2024 Society of Chemical Industry.

Tuning transcription factor DegU for developing extracellular protease overproducer in Bacillus pumilus.

BACKGROUND: Global transcription machinery engineering (gTME) is an effective approach employed in strain engineering to rewire gene expression and reshape cellular metabolic fluxes at the transcriptional level. RESULTS: In this study, we utilized gTME to engineer the positive transcription factor, DegU, in the regulation network of major alkaline protease, AprE, in Bacillus pumilus. To validate its functionality when incorporated into the chromosome, we performed several experiments. First, three negative transcription factors, SinR, Hpr, and AbrB, were deleted to promote AprE synthesis. Second, several hyper-active DegU mutants, designated as DegU(hy), were selected using the fluorescence colorimetric method with the host of the Bacillus subtilis ΔdegSU mutant. Third, we integrated a screened degU(L113F) sequence into the chromosome of the Δhpr mutant of B. pumilus SCU11 to replace the original degU gene using a CRISPR/Cas9 system. Finally, based on transcriptomic and molecular dynamic analysis, we interpreted the possible mechanism of high-yielding and found that the strain produced alkaline proteases 2.7 times higher than that of the control strain (B. pumilus SCU11) in LB medium. CONCLUSION: Our findings serve as a proof-of-concept that tuning the global regulator is feasible and crucial for improving the production performance of B. pumilus. Additionally, our study established a paradigm for gene function research in strains that are difficult to handle.

Complete genome sequence of Bacillus Licheniformis NWMCC0046, a candidate for the laundry industry.

In this study, selected properties of protease and the complete genome sequence of Bacillus licheniformis NWMCC0046 were investigated, to discover laundry applications and other potential probiotic properties of this strain. Partial characterization of B. licheniformis NWMCC0046 showed that its protease has good activity both in alkaline environments and at low temperatures. Also, the protease is compatible with commercial detergents and can be used as a detergent additive for effective stain removal at low temperatures. The complete genome sequence of B. licheniformis NWMCC0046 is comprised of a 4,321,565 bp linear chromosome with a G + C content of 46.78% and no plasmids. It had 4504 protein-encoding genes, 81 transfer RNA (tRNA) genes, and 24 ribosomal RNA (rRNA) genes. Genomic analysis revealed genes involved in exocellular enzyme production and probiotic properties. In addition, genomic sequence analysis revealed specific genes encoding carbohydrate metabolism pathways, resistance, and cold adaptation capacity. Overall, protease properties show its potential as a detergent additive enzyme. The complete genome sequence information of B. licheniformis NWMCC0046 was obtained, and functional prediction revealed its numerous probiotic properties.

Alkaline Thermo- and Oxidant-Stable Protease from Bacillus pumilus Strain TNP93: Laundry Detergent Formulations.

The study aims to produce a detergent-compatible and alkaline thermophilic protease from a Bacillus strain and to investigate its usability as a detergent bio-additive. The protease-producing bacterium was identified as Bacillus pumilus strain TNP93 according to the 16S rRNA sequence. The bacterium optimally synthesized the protease at 40 °C and pH 10 in 40 h. The raw protease displayed its optimum activity at pH 10 and 60 °C and its stability between pH 6-13 and 30-100 °C for 24 h. The molecular mass of the proteolytic band was estimated to be about 85 kDa. The protease was not inhibited by any of the metal ions used (Ba2+, Ca2+, Co2+, Cu2+, Mg2+, Mn2+, Zn2+). 97 and 90% of its original activity with 5 mM PMSF and EDTA remained. The activity was measured as 84, 124, and 95%, respectively, in the presence of 1% concentrations of Tween 20, Tween 80, and Triton X-100. In addition, all of its activity was preserved when the enzyme was exposed to 5% H2O2. The end products of casein were detected as tyrosine, aspartic acid, glycine, and cysteine by thin-layer chromatography. Considering the wash performance analysis, the mix of 1% commercial detergent and enzyme almost removed all of the protein-based stains (blood and egg yolk albumin). These remarkable findings indicate that the alkaline, thermo-, and oxidant-stable TNP93 protease is a valuable candidate for usage as a biological additive in various laundry detergents.

Biocatalytic one pot three component approach: Facile synthesis, characterization, molecular modelling and hypoglycemic studies of new thiazolidinedione festooned quinoline analogues catalyzed by alkaline protease from Aspergillus niger.

A novel ANAP (Aspergillus niger from alkaline protease) catalyzed one pot three component approach in the synthesis of new thiazolidinedione festooned quinoline analogues via Knoevenagel condensation and N-alkylation have been reported. The catalytic effect of enzyme was monitored and optimized by adjusting various parameters including catalyst concentration, choice of solvent and temperature. The isolated alkaline protease exhibits favorable features for the reaction response such as the shorter reaction time, simple work-up procedure, clean reaction profiles and excellent product yields through reusability of the catalyst upto five cycles. In silico molecular docking simulations were carried out to find out the effective binding affinity of the synthesized quinoline analogues 4(a-i) towards PPARγ protein (Id-2XKW). In vitro α-amylase and α-glucosidase assays were performed for hypoglycemic activity evaluation. In vivo hypoglycemic studies carried out on streptozotocin (SZT) induced diabetic male albino rats have shown that compounds 4e and 4f significantly reduced blood glucose levels with percentage reduction of 43.7 ± 0.91 and 45.6 ± 0.28 at a concentration of 50 mg/kg body wt. The results obtained from molecular docking simulations and in vitro enzyme assays are in consistent with in-vivo studies which clearly demonstrated that out of the synthesized quinoline analogues, compounds 4e and 4f possess promising hypoglycemic activity which was on par to that of standards pioglitazone and rosiglitazone respectively.

Statistical optimization of thermostable alkaline protease from Bacillus cereus KM 05 using response surface methodology.

OBJECTIVES: Proteases have gained great attention due to their enormous applications in food, tannery, detergent, photography and many other industries. Proteases rank third position in the production of enzymes. This paper targets to isolate a bacterium with high alkaline protease activity and optimization of its production conditions using Response Surface Methodology (RSM). RESULTS: A bacterium isolated from soil contaminated with detergent exhibited clearance zone on skim milk agar medium with a protease activity of 22 U/ml. The bacterial strain was identified as Bacillus cereus KM05 and optimization of its production conditions were performed using statistical methods. Further optimization with Box Behnken design resulted in an increase in protease activity by 1.5-fold (28.6 U/ml). The protease enzyme was thermotolerant up to 70 °C with stability towards alkaline pH (pH 9). The enzyme was not affected by most of the metal ions and solvents. Moreover, the protease was also compatible with six commercial detergents tested. Densitometric analysis of the destained fabric materials following the detergent-enzyme treatment, revealed a stain removal efficiency of 97%. CONCLUSION: The alkaline protease enzyme obtained was stable at different conditions with stain removal efficacy. Hence, the present alkaline protease could be used for detergent formulations.

A dynamic soft senor modeling method based on MW-ELWPLS in marine alkaline protease fermentation process.

The vital state variables in marine alkaline protease (MP) fermentation are difficult to measure in real-time online, hardly is the optimal control either. In this article, a dynamic soft sensor modeling method which combined just-in-time learning (JITL) technique and ensemble learning is proposed. First, the local weighted partial least squares algorithm (LWPLS) with JITL strategy is used as the basic modeling method. For further improving the prediction accuracy, the moving window (MW) is used to divide sub-dataset. Then the MW-LWPLS sub-model is built by selecting the diverse sub-datasets according to the cumulative similarity. Finally, stacking ensemble-learning method is utilized to fuse each MW-LWPLS sub-models. The proposed method is applied to predict the vital state variables in the MP fermentation process. The experiments and simulations results show that the prediction accuracy is better compared to other methods.

Soft - sensing modeling based on ABC - MLSSVM inversion for marine low - temperature alkaline protease MP fermentation process.

BACKGROUND: Aiming at the characteristics of nonlinear, multi-parameter, strong coupling and difficulty in direct on-line measurement of key biological parameters of marine low-temperature protease fermentation process, a soft-sensing modeling method based on artificial bee colony (ABC) and multiple least squares support vector machine (MLSSVM) inversion for marine protease fermentation process is proposed. METHODS: Firstly, based on the material balance and the characteristics of the fermentation process, the dynamic "grey box" model of the fed-batch fermentation process of marine protease is established. The inverse model is constructed by analyzing the inverse system existence and introducing the characteristic information of the fermentation process. Then, the inverse model is identified off-line using MLSSVM. Meanwhile, in order to reduce the model error, the ABC algorithm is used to correct the inverse model. Finally, the corrected inverse model is connected in series to the marine alkaline protease MP fermentation process to form a composite pseudo-linear system, thus, real-time on-line prediction of key biological parameters in fermentation process can be realized. RESULTS: Taking the alkaline protease MP fermentation process as an example, the simulation results demonstrate that the soft-sensing modeling method can solve the real-time prediction problem of key biological parameters in the fermentation process on-line, and has higher accuracy and generalization ability than the traditional soft-sensing method of support vector machine. CONCLUSIONS: The research provides a new method for soft-sensing modeling of key biological parameters in fermentation process, which can be extended to soft-sensing modeling of general nonlinear systems.

High copy number and highly stable Escherichia coli-Bacillus subtilis shuttle plasmids based on pWB980.

BACKGROUND: pWB980 derived from pUB110 is a promising expression vector in Bacillus for its high copy number and high stability. However, the low transformation rate of recombinant plasmids to the wild cells limited the application of it. On the basis of pWB980, constructing an E. coli-B. subtilis shuttle plasmid could facilitate the transformation rate to Bacillus cells. Because the insertion site for E. coli replication origin sequence (ori) is not unique in pWB980, in order to investigate the best insertion site, eight shuttle plasmids (pUC980-1 ~ pUC980-8) containing all possible insertion sites and directions were constructed. RESULTS: The results showed that all the selected insertion sites could be used to construct shuttle plasmid but some sites required a specific direction. And different insertion sites led to different properties of the shuttle plasmids. The best shuttle plasmids pUC980-1 and pUC980-2, which showed copies more than 450 per cell and segregational stabilities up to 98%, were selected for heterologous expressions of an alkaline pectate lyase gene pelN, an alkaline protease spro1 and a pullulanase gene pulA11, respectively. The highest extracellular activities of PelN, Spro1 and PulA11 were up to 5200 U/mL, 21,537 U/mL and 504 U/mL correspondingly after 54 h, 60 h and 48 h fermentation in a 10 L fermentor. Notably, PelN and Spro1 showed remarkably higher yields in Bacillus than previous reports. CONCLUSION: The optimum ori insertion site was the upstream region of BA3-1 in pWB980 which resulted in shuttle plasmids with higher copy numbers and higher stabilities. The novel shuttle plasmids pUC980-1 and pUC980-2 will be promising expression vectors in B. subtilis. Moreover, the ori insertion mechanism revealed in this work could provide theoretical guidance for further studies of pWB980 and constructions of other shuttle plasmids.

Optimized expression and enhanced production of alkaline protease by genetically modified Bacillus licheniformis 2709.

BACKGROUND: Bacillus licheniformis 2709 is extensively applied as a host for the high-level production of heterologous proteins, but Bacillus cells often possess unfavorable wild-type properties, such as production of viscous materials and foam during fermentation, which seriously influenced the application in industrial fermentation. How to develop it from a soil bacterium to a super-secreting cell factory harboring less undomesticated properties always plays vital role in industrial production. Besides, the optimal expression pattern of the inducible enzymes like alkaline protease has not been optimized by comparing the transcriptional efficiency of different plasmids and genomic integration sites in B. licheniformis. RESULT: Bacillus licheniformis 2709 was genetically modified by disrupting the native lchAC genes related to foaming and the eps cluster encoding the extracellular mucopolysaccharide via a markerless genome-editing method. We further optimized the expression of the alkaline protease gene (aprE) by screening the most efficient expression system among different modular plasmids and genomic loci. The results indicated that genomic expression of aprE was superior to plasmid expression and finally the transcriptional level of aprE greatly increased 1.67-fold through host optimization and chromosomal integration in the vicinity of the origin of replication, while the enzyme activity significantly improved 62.19% compared with the wild-type alkaline protease-producing strain B. licheniformis. CONCLUSION: We successfully engineered an AprE high-yielding strain free of undesirable properties and its fermentation traits could be applied to bulk-production by host genetic modification and expression optimization. In summary, host optimization is an enabling technology for improving enzyme production by eliminating the harmful traits of the host and optimizing expression patterns. We believe that these strategies can be applied to improve heterologous protein expression in other Bacillus species.

Alkaline protease for an efficacious rehydration of skin matrix by a novel Bacillus crolab MTCC 5468 in sustainable leather production: a green approach.

OBJECTIVES: The utilization of biotechnology in leather sector has more extensive in modern years; more particular to proteolytic enzymes and employed in several steps of the leather making such as soaking, dehairing, bating, solid waste management etc. The current study evaluates the performance of alkaline protease from Bacillus crolab MTCC 5468 in single soaking of goat skins matrix by comparing with the conventional multiple soaking processes. RESULTS: According to the obtained results, the optimum concentration for maximum rehydration of goat skins was accomplished at 1.0% (v/w) of alkaline protease at duration of 3 h over traditional rehydration method (4-6 h). The moisture level, total protein, chloride content and total organic carbon of enzymatic rehydration was superior to that of conventional rehydration and it was also used to measure the effectiveness of rehydration process. Scanning electron microscopic images of enzymatically processed leather exhibits enhanced opening of fiber bundles and smooth grain surface than conventional method. Furthermore, the alkaline protease treated leather exhibited improved moisture uptake, removal of chlorides and suppleness because of hydrolysis of non-collagenous proteins as indicated by well opened up fiber bundles in histological analysis. CONCLUSIONS: The application of alkaline protease in rehydration operation of leather production confirmed scope for diminishing water quantity around 66.6%, soaking duration at 50%, minimizing use of harmful dehairing chemicals at 50-60%, thereby, eliminating the bating operation during pre-tanning. These outcomes suggest that alkaline protease have potential application in rehydration of skins for immense environmental concerns of leather tanning sectors.

Optimized production of extracellular alkaline protease from Aspergillus tamarii with natural by-products in a batch stirred tank bioreactor.

Proteolytic enzymes are one of the significant commercially manufactured enzymes. The manufacture of extracellular alkaline protease by Aspergillus tamarii MTCC5152 was explored using several agricultural by-products as substrates viz., cottonseed meal, wheat bran, skimmed milk and soya flour in submerged fermentation, were found to be efficient for enzyme production and commercially significant. Response surface methodology (RSM) is a statistics-based experimental design, sourced to explore the impact of physical parameters on the manufacture of protease from A. tamarii in a batch stirred tank bioreactor (STBR). The four substantial variables (pH, temperature, inoculum size, and agitation) were carefully chosen for optimization analyses and the statistical pattern was created using a central composite design and the quadratic model has been developed. The optimum conditions for protease production (1.51 U mL-1) where: pH 6.4, temperature 27 °C, inoculum size 2.6%, and agitation 327 rpm. The analysis revealed that the anticipated values were in accord with trial data with a correlation coefficient of 0.969.

Kinetics, detergent compatibility and feather-degrading capability of alkaline protease from Bacillus subtilis AKAL7 and Exiguobacterium indicum AKAL11 produced with fermentation of organic municipal solid wastes.

Alkaline proteases having activity and stability at alkaline pH possess a large variety of applications in many industries. Growing renewed interest urges the need to find a single alkaline protease with promising properties to be used in different industrial processes. Herein, alkaline proteases produced through fermentation of cheap and easily available organic municipal solid wastes by Bacillus subtilis AKAL7 and Exiguobacterium indicum AKAL11 were purified to investigate their kinetic and thermodynamic parameters, detergent compatibility, dehairing and feather-degrading capability. Sodium dodecyl sulfate polyacrylamide gel electrophoresis revealed that the purified protease from B. subtilis and E. indicum had molecular mass of ∼45 and 75 kDa, respectively. The protease from B. subtilis and E. indicum showed highest activity at 55 and 50 °C having low K m 1.17 and 0.567 mg/mL and high V max 416.67 and 333.33 µmole/min, respectively. The activation energy and temperature quotient of protease from B. subtilis and E. indicum were 26.52 and 65.75 kJ/mole, and 1.0004 and 1.0003 at 20-55 and 20-50 °C, respectively. Thermodynamics analysis revealed the formation of more ordered enzyme-substrate complexes along with spontenity of enzyme reaction. The protease from E. indicum exhibited better compatibility at higher concentration of detergents compared to that from B. subtilis. However, both proteases could retain more than 80% of the activity in the presence of 0.1% commercial laundry detergents. The purified protease from the both sources could degrade almost 90% of barbs and 40% of dry weight of the native feather and that from E. indicum could dehair cow skin. Results reported herein suggest that the alkaline protease from B. subtilis AKAL7 and E. indicum AKAL11 has biotechnological implications in detergent, leather and poultry feather processing industries.

Inactivation of Polymyxin by Hydrolytic Mechanism.

Polymyxins are nonribosomal peptide antibiotics used as the last-resort drug for treatment of multidrug-resistant Gram-negative bacteria. However, strains that are resistant to polymyxins have emerged in many countries. Although several mechanisms for polymyxin resistance have been well described, there is little knowledge on the hydrolytic mechanism of polymyxin. Here, we identified a polymyxin-inactivating enzyme from Bacillus licheniformis strain DC-1 which was produced and secreted into the medium during entry into stationary phase. After purification, sequencing, and heterologous expression, we found that the alkaline protease Apr is responsible for inactivation of polymyxins. Analysis of inactivation products demonstrated that Apr cleaves polymyxin E at two peptide bonds: one is between the tripeptide side chain and the cyclic heptapeptide ring, the other between l-Thr and l-α-γ-diaminobutyric acid (l-Dab) within the cyclic heptapeptide ring. Apr is highly conserved among several genera of Gram-positive bacteria, including Bacillus and Paenibacillus It is noteworthy that two peptidases S8 from Gram-negative bacteria shared high levels of sequence identity with Apr. Our results indicate that polymyxin resistance may result from inactivation of antibiotics by hydrolysis.

Antibacterial substances produced by pathogen inhibitory gut bacteria in Labeo rohita: Physico-chemical characterization, purification and identification through MALDI-TOF mass spectrometry.

Application of antibiotics to combat bacterial diseases in fish has been criticized due to likely emergence of drug resistance. Therefore, investigation of new bioactive compounds from natural sources has been taken into account. This study was designed to purify and characterize the bioactive compound in the cell free supernatant (CFSs) of autochthonous gut bacteria (Bacillus methylotrophicus KU556164, B. amyloliquefaciens KU556165, Pseudomonas fluorescens KU556166 and B. licheniformis KU556167) isolated from rohu, Labeo rohita. CFSs were antagonistic to fish pathogenic Aeromonas spp., moderately thermo-tolerant and active in wide range of pH (5-11). Antibacterial activity of the CFSs was reduced by the action of proteases (e.g., Proteinase K and Trypsin), indicating proteinaceous nature of the bioactive compound like the bacteriocins. Three-step purification procedure resulted in recovery of 16.97%, 18.04%, 33.33% and 6.38% activity of the antimicrobial protein produced by B. methylotrophicus, B. amyloliquefaciens, P. fluorescens and B. licheniformis, respectively. Purification at each step revealed decrease in protein content with gradual increase in the specific activity of the antimicrobial protein. The purified antibacterial compound ranged between 18.2 and 25.6 kDa. Identification through MALDI-TOF MS/MS and database search through Mascot search engine predicted that the bactericidal compound belonged to either alkaline proteases, or, transcriptional regulator and some hypothetical proteins. Apart from potential technological application of the antibacterial compound, the present study might show promise for application of gut-associated bacteriocinogenic bacteria to control diseases in fish caused by pathogenic bacteria.

Optimization of alkaline protease production by rational deletion of sporulation related genes in Bacillus licheniformis.

BACKGROUND: Our laboratory has constructed a Bacillus licheniformis strain that secretes alkaline protease (AprE) with excellent enzymatic properties. B. licheniformis is generally regarded as safe and has a high industrial exoenzyme secretion capacity, but the host retains some undomesticated characteristic that increase its competitiveness and survival, such as spore-formation, which increases the requirements and difficulties in industrial operations (e.g. sterilization and enzyme activity control). Furthermore, the influence of sporulation on alkaline protease production in B. licheniformis has not been elucidated in detail. RESULT: A series of asporogenic variants of the parent strain were constructed by individually knocking out the master regulator genes (spo0A, sigF and sigE) involved in sporulation. Most of the variants formed abortively disporic cells characterized by asymmetric septa at the poles and unable to survive incubation at 75 °C for 10 min. Two of them (ΔsigF and ΔsigE) exhibited superior characteristics in protease production, especially improving the expression of the aprE gene. Under the currently used fermentation conditions, the vegetative production phase of ΔsigF can be prolonged to 72 h, and the highest protease production of ΔsigF reached 29,494 ± 1053 U/mL, which was about 19.7% higher than that of the wild-type strain. CONCLUSION: We first constructed three key sporulation-deficient strain to investigate the effect of sporulation on alkaline protease synthesis. The sigF mutant retained important industrial properties such as facilitating the sterilization process, a prolonged stable phase of enzyme production and slower decreasing trend, which will be superior in energy conservation, simpler operations and target product controlling effect. In summary, the work provides a useful industrial host with preferable characteristics and a novel strategy to enhance the production of protease.

Soft-sensing method based on FDLS-SVM in marine alkaline protease fermentation process.

To overcome the problem that soft-sensing model cannot be updated with the bioprocess changes, this article proposed a soft-sensing modeling method which combined fuzzy c-means clustering (FCM) algorithm with least squares support vector machine theory (LS-SVM). FCM is used for separating a whole training data set into several clusters with different centers, each subset is trained by LS-SVM and sub-models are developed to fit different hierarchical property of the process. The new sample data that bring new operation information is introduced in the model, and the fuzzy membership function of the sample to each clustering is first calculated by the FCM algorithm. Then, a corresponding LS-SVM sub-model of the clustering with the largest fuzzy membership function is used for performing dynamic learning so that the model can update online. The proposed method is applied to predict the key biological parameters in the marine alkaline protease MP process. The simulation result indicates that the soft-sensing modeling method increases the model's adaptive abilities in various operation conditions and can improve its generalization ability.