Improved L-Asparaginase Properties and Reusability by Immobilization onto Functionalized Carbon Xerogels

Enzyme immobilization can offer a range of significant advantages, including reusability, and increased selectivity, stability, and activity. In this work, a central composite design (CCD) of experiments and response surface methodology (RSM) were used to study, for the first time, the L-asparaginase (ASNase) immobilization onto functionalized carbon xerogels (CXs). The best results were achieved using CXs obtained by hydrothermal oxidation with nitric acid and subsequent heat treatment in a nitrogen flow at 600 degrees C (CX-OX-600). Under the optimal conditions (81 min of contact time, pH 6.2 and 0.36 g/L of ASNase), an immobilization yield (IY) of 100 % and relative recovered activity (RRA) of 103 % were achieved. The kinetic parameters obtained also indicate a 1.25-fold increase in the affinity of ASNase towards the substrate after immobilization. Moreover, the immobilized enzyme retained 97 % of its initial activity after 6 consecutive reaction cycles. All these outcomes confirm the promising properties of functionalized CXs as support for ASNase, bringing new insights into the development of an efficient and stable immobilization platform for use in the pharmaceutical industry, food industry, and biosensors. The development of an efficient strategy for immobilizing L-asparaginase enzyme onto functionalized carbon xerogels is the focus of this work. The results reveal the importance of tuning the surface chemistry of the materials and prove the enhanced activity, higher affinity with the substrate, and reusability of L-asparaginase achieved through immobilization.+ imag

Unveiling the Influence of Carbon Nanotube Diameter and Surface Modification on the Anchorage of L-Asparaginase

L-asparaginase (ASNase, EC 3.5.1.1) is an amidohydrolase enzyme known for its anti-cancer properties, with an ever-increasing commercial value. Immobilization has been studied to improve the enzyme's efficiency, enabling its recovery and reuse, enhancing its stability and half-life time. In this work, the effect of pH, contact time and enzyme concentration during the ASNase physical adsorption onto pristine and functionalized multi-walled carbon nanotubes (MWCNTs and f-MWCNTs, respectively) with different size diameters was investigated by maximizing ASNase relative recovered activity (RRA) and immobilization yield (IY). Immobilized ASNase reusability and kinetic parameters were also evaluated. The ASNase immobilization onto f-MWCNTs offered higher loading capacities, enhanced reusability, and improved enzyme affinity to the substrate, attaining RRA and IY of 100 and 99%, respectively, at the best immobilization conditions (0.4 mg/mL of ASNase, pH 8, 30 min of contact time). In addition, MWCNTs diameter proved to play a critical role in determining the enzyme binding affinity, as evidenced by the best results attained with f-MWCNTs with diameters of 10-20 nm and 20-40 nm. This study provided essential information on the impact of MWCNTs diameter and their surface functionalization on ASNase efficiency, which may be helpful for the development of innovative biomedical devices or food pre-treatment solutions

Talaromyces atroroseus, a new species efficiently producing industrially relevant red pigments

Some species of Talaromyces secrete large amounts of red pigments. Literature has linked this character to species such as Talaromyces purpurogenus, T. albobiverticillius, T. marneffei, and T. minioluteus often under earlier Penicillium names. Isolates identified as T. purpurogenus have been reported to be interesting industrially and they can produce extracellular enzymes and red pigments, but they can also produce mycotoxins such as rubratoxin A and B and luteoskyrin. Production of mycotoxins limits the use of isolates of a particular species in biotechnology. Talaromyces atroroseus sp. nov., described in this study, produces the azaphilone biosynthetic families mitorubrins and Monascus pigments without any production of mycotoxins. Within the red pigment producing clade, T. atroroseus resolved in a distinct clade separate from all the other species in multigene phylogenies (ITS, β-tubulin and RPB1), which confirm its unique nature. Talaromyces atroroseus resembles T. purpurogenus and T. albobiverticillius in producing red diffusible pigments, but differs from the latter two species by the production of glauconic acid, purpuride and ZG-1494α and by the dull to dark green, thick walled ellipsoidal conidia produced. The type strain of Talaromyces atroroseus is CBS 133442

Data - Effect of electrolytes as adjuvants in GFP and LPS partitioning on aqueous two-phase systems: 1. Polymer-polymer systems

<p><strong>Overview</strong></p> <p>The production of recombinant biopharmaceuticals is highly dependent of a proper choice of the downstream processing stages. Particularly, the purification that must ensure that all the endotoxins (lipopolysaccharide - LPS) are efficiently removed from the final product. This dataset contains the raw data and statistical analysis for the research entitled - "Effect of electrolytes as adjuvants in GFP and LPS partitioning on aqueous two-phase systems: 1. Polymer-polymer systems". </p> <p><strong>Info</strong></p> <p>ANOVA_Turkey_Sub.R <- code for ANOVA analysis in R statistic 3.3.3    <br> glm.R <- code for GLM analysis in R statistic 3.3.3<br> K&REC_LPS_PEG_NaPA.xlsx <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) and recover (REC) for ANOVA analysis<br> K&REC_LPS_PEG_NaPA_K.docx <- File with ANOVA result of partition coefficient (K) for GFP<br> K&REC_LPS_PEG_NaPA_REC.docx <- File with ANOVA result of recover (REC) for GFP         <br> K_GFP_Pol_005.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in 0.05M salt assays    <br> K_GFP_Pol_005.doc <- File with GLM analysis of GFP partition coefficient (K) in 0.05M salt assays  <br> K_GFP_Pol_005_QQ.png <- Residual quantile plot of GLM analysis for partition coefficient (K) in 0.05M salt assays  <br> K_GFP_Pol_025.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in 0.25M salt assays  <br> K_GFP_Pol_025.doc  <- File with GLM analysis of GFP partition coefficient (K) in 0.25M salt assays  <br> K_GFP_Pol_025_QQ.png <- Residual quantile plot of GLM analysis for partition coefficient (K) in 0.25M salt assays         <br> REC_GFP_Pol_005.csv <- File with raw values organized in a spreadsheet of GFP recover (REC) for GLM analysis in 0.05M salt assays         <br> REC_GFP_Pol_005.doc  <- File with GLM analysis of GFP recover (REC) in 0.05M salt assays    <br> REC_GFP_Pol_005_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in 0.05M salt assays   <br> REC_GFP_Pol_025.csv <- File with raw values organized in a spreadsheet of GFP recover (REC) for GLM analysis in 0.25M salt assays          <br> REC_GFP_Pol_025.doc  <- File with GLM analysis of GFP recover (REC) in 0.25M salt assays <br> REC_GFP_Pol_025_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in 0.25M salt assays        <br> REM_LPS_PEG_NaPA.docx  <- File with ANOVA result of LPS removal          <br> REM_LPS_PEG_NaPA.xlsx <- File with raw values organized in a spreadsheet of LPS removal for ANOVA analysis<br> Stability_GFP_PEG_NaPA.docx <- File with ANOVA result of GFP stability<br> Stability_GFP_PEG_NaPA.xlsx <- File with raw values organized in a spreadsheet of GFP stability results for ANOVA analysis</p> <p>REM_LPS_Pol_005.csv  <- File with raw values organized in a spreadsheet of LPS removal (REM) for GLM analysis in 0.05M salt assays         <br> REM_LPS_Pol_005.doc  <- File with GLM analysis of LPS removal (REM) in 0.05M salt assays    <br> REM_LPS_Pol_005_QQ.png <- Residual quantile plot of GLM analysis of LPS removal (REM) in 0.05M salt assays  <br> REM_LPS_Pol_025.csv  <- File with raw values organized in a spreadsheet of LPS removal (REM) for GLM analysis in 0.25M salt assays         <br> REM_LPS_Pol_025.doc   <- File with GLM analysis of LPS removal (REM) in 0.25M salt assays    <br> REM_LPS_Pol_025_QQ.png <- Residual quantile plot of GLM analysis of LPS removal (REM) in 0.25M salt assays</p> <p>K_GFP_Pol_025_NaCl_Li2SO4.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in 0.25M salt assays comparing NaCl and Li2SO4 effect <br> K_GFP_Pol_025_NaCl_Li2SO4.doc  <- File with GLM analysis of GFP partition coefficient (K) in 0.25M salt assays comparing NaCl and Li2SO4 effect <br> K_GFP_Pol_025_NaCl_Li2SO4_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in 0.25M salt assays comparing NaCl and Li2SO4 effect   </p> <p>REM_LPS_Pol_KI_0.05_vs_0.25.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in KI assays comparing salt concentration effect  <br> REM_LPS_Pol_KI_0.05_vs_0.25.doc <- File with GLM analysis of GFP partition coefficient (K) in KI assays comparing salt concentration effect<br> REM_LPS_Pol_KI_0.05_vs_0.25_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in KI assays comparing salt concentration effect<br> REM_LPS_Pol_KNO3_0.05_vs_0.25.csv  <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in KNO3 assays comparing salt concentration effect  <br> REM_LPS_Pol_KNO3_0.05_vs_0.25.doc <- File with GLM analysis of GFP partition coefficient (K) in KNO3 assays comparing salt concentration effect<br> REM_LPS_Pol_KNO3_0.05_vs_0.25_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in KNO3 assays comparing salt concentration effect<br> REM_LPS_Pol_Li2SO4_0.05_vs_0.25.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in Li2SO4 assays comparing salt concentration effect  <br> REM_LPS_Pol_Li2SO4_0.05_vs_0.25.doc <- File with GLM analysis of GFP partition coefficient (K) in Li2SO4 assays comparing salt concentration effect<br> REM_LPS_Pol_Li2SO4_0.05_vs_0.25_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in Li2SO4 assays comparing salt concentration effect<br> REM_LPS_Pol_NaCl_0.05_vs_0.25.csv <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in NaCl assays comparing salt concentration effect  <br> REM_LPS_Pol_NaCl_0.05_vs_0.25.doc <- File with GLM analysis of GFP partition coefficient (K) in NaCl assays comparing salt concentration effect <br> REM_LPS_Pol_NaCl_0.05_vs_0.25_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in NaCl assays comparing salt concentration effect</p> <p> </p> <p><strong>Annotation</strong></p> <p>12/12 - Concentration of 12% of each polymer PEG/NaPA</p> <p>16/16 - Concentration of 16% of each polymer PEG/NaPA</p> <p>P/N -  PEG/NaPA</p> <p>10e4, 10e5, 10e6 - Concentration of LPS in scientific notation - 10000, 100000, 100000 EU/mL</p> <p>poly - Polymer</p> <p>salt - Salt concentration in the assay</p> <p>tsalt - Type of salt in the assay (NaCl, KNO3, KI and Li2SO4)</p> <p>lps - lipopolysaccharide</p> <p>K - GFP partition coefficient</p> <p>REM - LPS removal</p> <p>REC - GFP recover</p> <p>wo_salt - Assay without salt addition</p> <p><strong>Acknowledgements</strong></p> <p>The authors are grateful for financial support from FAPESP (São Paulo Research Foundation, Brazil) through the following projects: 2005/60159-7; 2007/51978-0; 2014/16424-7; and 2014/19793-3. The authors also acknowledge the support from CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brazil) through the process #0366/09-9 and CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico, Brazil).</p> <p><strong>Consider citing our work. </strong></p> <p>1. Work in progress...</p

Data - Effect of electrolytes as adjuvants in GFP and LPS partitioning on aqueous two-phase systems: 2. Nonionic micellar systems

<p><strong>Overview</strong></p> <p>The production of recombinant biopharmaceuticals is highly dependent of a proper choice of the downstream processing stages. Particularly, the purification that must ensure that all the endotoxins (lipopolysaccharide - LPS) are efficiently removed from the final product. This dataset contains the raw data and statistical analysis for the research entitled - "Effect of electrolytes as adjuvants in GFP and LPS partitioning on aqueous two-phase systems: 2. Nonionic micellar systems". </p> <p><strong>Info</strong></p> <p>ANOVA_Turkey_Sub.R <- code for ANOVA analysis in R statistic 3.3.3    <br> glm.R <- code for GLM analysis in R statistic 3.3.3<br> K&REC_ORG_ANOVA.csv  <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) and recover (REC) for ANOVA analysis</p> <p>K_ORG_ANOVA.docx <-  File with ANOVA result of partition coefficient (K) for GFP</p> <p>REC_ORG_ANOVA.docx  <- File with ANOVA result of partition coefficient (REC) for GFP</p> <p>REM_LPS_ORG_ANOVA.csv  <- File with raw values organized in a spreadsheet of LPS removal for ANOVA analysis</p> <p>REM_LPS_ORG_ANOVA.docx  <- File with ANOVA result of removal of LPS</p> <p>Stability__ORG_ANOVA.csv <- File with raw values organized in a spreadsheet of GFP stability for ANOVA analysis</p> <p>Stability__ORG_ANOVA.docx  <- File with ANOVA result of GFP stability</p> <p>K_ORG_glm_005.csv  <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in 0.05M salt assays    </p> <p>K_ORG_glm_005.doc <- File with GLM analysis of GFP partition coefficient (K) in 0.05M salt assays  </p> <p>K_ORG_glm_005_QQ.png <- Residual quantile plot of GLM analysis for partition coefficient (K) in 0.05M salt assays  </p> <p>K_ORG_glm_025.csv  <- File with raw values organized in a spreadsheet of GFP partition coefficient (K) for GLM analysis in 0.25M salt assays    </p> <p>K_ORG_glm_025.doc <- File with GLM analysis of GFP partition coefficient (K) in 0.25M salt assays  </p> <p>K_ORG_glm_025_QQ.png <- Residual quantile plot of GLM analysis for partition coefficient (K) in 0.25M salt assays  </p> <p>REC_ORG_glm_005.csv <- File with raw values organized in a spreadsheet of GFP recover (REC) for GLM analysis in 0.05M salt assays</p> <p>REC_ORG_glm_005.doc <-  File with GLM analysis of GFP recover (REC) in 0.05M salt assays    </p> <p>REC_ORG_glm_005_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in 0.05M salt assays   </p> <p>REC_ORG_glm_025.csv <- File with raw values organized in a spreadsheet of GFP recover (REC) for GLM analysis in 0.25M salt assays</p> <p>REC_ORG_glm_025.doc <-  File with GLM analysis of GFP recover (REC) in 0.25M salt assays    </p> <p>REC_ORG_glm_025_QQ.png <- Residual quantile plot of GLM analysis of GFP recover (REC) in 0.25M salt assays   </p> <p>REM_ORG_glm_005.csv <- File with raw values organized in a spreadsheet of LPS removal (REM) for GLM analysis in 0.05M salt assays</p> <p>REM_ORG_glm_005.doc <-  File with GLM analysis of LPS removal (REM) in 0.05M salt assays  </p> <p>REM_ORG_glm_005_QQ.png <-  Residual quantile plot of GLM analysis of LPS removal (REM) in 0.25M salt assays</p> <p>REM_ORG_glm_025.csv <- File with raw values organized in a spreadsheet of LPS removal (REM) for GLM analysis in 0.25M salt assays</p> <p>REM_ORG_glm_025.doc <-  File with GLM analysis of LPS removal (REM) in 0.25M salt assays </p> <p>REM_ORG_glm_025_QQ.png <-  Residual quantile plot of GLM analysis of LPS removal (REM) in 0.25M salt assays</p> <p> </p> <p><strong>Annotation</strong></p> <p>12/12 - Concentration of 12% of each polymer PEG/NaPA</p> <p>16/16 - Concentration of 16% of each polymer PEG/NaPA</p> <p>P/N -  PEG/NaPA</p> <p>10e4, 10e5, 10e6 - Concentration of LPS in scientific notation - 10000, 100000, 100000 EU/mL</p> <p>poly - Polymer</p> <p>salt - Salt concentration in the assay</p> <p>tsalt - Type of salt in the assay (NaCl, KNO3, KI and Li2SO4)</p> <p>lps - lipopolysaccharide</p> <p>K - GFP partition coefficient</p> <p>REM - LPS removal</p> <p>REC - GFP recover</p> <p>wo_salt - Assay without salt addition</p> <p><strong>Acknowledgements</strong></p> <p>The authors are grateful for financial support from FAPESP (São Paulo Research Foundation, Brazil) through the following projects: 2005/60159-7; 2007/51978-0; 2014/16424-7; and 2014/19793-3. The authors also acknowledge the support from CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brazil) through the process #0366/09-9 and CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico, Brazil).</p> <p><strong>Consider citing our work. </strong></p> <p>1. Work in progress...</p