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Recombinant expression and functional analysis of proteases from Streptococcus pneumoniae, Bacillus anthracis, and Yersinia pestis.

Kwon K, Hasseman J, Latham S, Grose C, Do Y, Fleischmann RD, Pieper R, Peterson SN - BMC Biochem. (2011)

Bottom Line: Overall, 86.1% of selected protease genes including hypothetical proteins were expressed and purified using a combination of five different expression vectors.To detect novel proteolytic activities, zymography and fluorescence-based assays were performed and the protease activities of more than 46% of purified proteases and 40% of hypothetical proteins that were predicted to be proteases were confirmed.The combinatorial functional analysis of the purified proteases using fluorescence assays and zymography confirmed their function.

View Article: PubMed Central - HTML - PubMed

Affiliation: Pathogen Functional Genomics Resource Center, J, Craig Venter Institute, Rockville, Maryland 20850, USA. scottp@jcvi.org

ABSTRACT

Background: Uncharacterized proteases naturally expressed by bacterial pathogens represents important topic in infectious disease research, because these enzymes may have critical roles in pathogenicity and cell physiology. It has been observed that cloning, expression and purification of proteases often fail due to their catalytic functions which, in turn, cause toxicity in the E. coli heterologous host.

Results: In order to address this problem systematically, a modified pipeline of our high-throughput protein expression and purification platform was developed. This included the use of a specific E. coli strain, BL21(DE3) pLysS to tightly control the expression of recombinant proteins and various expression vectors encoding fusion proteins to enhance recombinant protein solubility. Proteases fused to large fusion protein domains, maltosebinding protein (MBP), SP-MBP which contains signal peptide at the N-terminus of MBP, disulfide oxidoreductase (DsbA) and Glutathione S-transferase (GST) improved expression and solubility of proteases. Overall, 86.1% of selected protease genes including hypothetical proteins were expressed and purified using a combination of five different expression vectors. To detect novel proteolytic activities, zymography and fluorescence-based assays were performed and the protease activities of more than 46% of purified proteases and 40% of hypothetical proteins that were predicted to be proteases were confirmed.

Conclusions: Multiple expression vectors, employing distinct fusion tags in a high throughput pipeline increased overall success rates in expression, solubility and purification of proteases. The combinatorial functional analysis of the purified proteases using fluorescence assays and zymography confirmed their function.

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Dependence of purification success rates on fusion tags and sub-cellular localization of proteins. Analysis of purification success rate by expression vectors and (A) subcellular localization of proteins or (B) presence of signal peptide.
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Figure 4: Dependence of purification success rates on fusion tags and sub-cellular localization of proteins. Analysis of purification success rate by expression vectors and (A) subcellular localization of proteins or (B) presence of signal peptide.

Mentions: Characteristics of proteins, such as sub-cellular localization, and localization the presence of signal peptides, are among the most critical factors for expression, solubility and purification. The purified recombinant proteins were confirmed by SDS-PAGE. Because protein purification success rates represent soluble expression of proteins, the correlation between purification and the protein sub-cellular localization were examined. The dependence of purification success rate on the protein localization was clearly evident (Figure 4). Cytoplasmic proteins displayed the highest purification success rate. Proteins with predicted membrane localization and surface were successful in less than 40% of the cases. More than 97% of the attempted cytoplasmic proteins were expressed and purified by at least one of the expression vectors, while 68.1% of non-cytoplasmic proteins were successfully purified. The expression vector, pHis is the least favorable for surface proteins. The other larger fusion proteins increased purification of the surface proteins. The MBP-tag increased the success rate of the surface proteases by approximately 8-fold compared to the His-tag. The presence of signal peptide that targets proteins to the cell surface also decreased the success rate of protein purification. Only one of 38 attempted proteins containing native signal peptide were purified using the pHis expression vector. The expression vector with the GST-tag also performed poorly for proteins containing signal peptide. Half of the proteins containing signal peptide were purified using an expression vector, pMBP, which was also the most successful vector for both the presence and the absence of signal peptide. Approximately 20-fold more proteases containing signal peptide were purified with pMBP compared to pHis. With a combination of 5 expression vectors, 79% of proteins containing native signal peptide were purified.


Recombinant expression and functional analysis of proteases from Streptococcus pneumoniae, Bacillus anthracis, and Yersinia pestis.

Kwon K, Hasseman J, Latham S, Grose C, Do Y, Fleischmann RD, Pieper R, Peterson SN - BMC Biochem. (2011)

Dependence of purification success rates on fusion tags and sub-cellular localization of proteins. Analysis of purification success rate by expression vectors and (A) subcellular localization of proteins or (B) presence of signal peptide.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3113736&req=5

Figure 4: Dependence of purification success rates on fusion tags and sub-cellular localization of proteins. Analysis of purification success rate by expression vectors and (A) subcellular localization of proteins or (B) presence of signal peptide.
Mentions: Characteristics of proteins, such as sub-cellular localization, and localization the presence of signal peptides, are among the most critical factors for expression, solubility and purification. The purified recombinant proteins were confirmed by SDS-PAGE. Because protein purification success rates represent soluble expression of proteins, the correlation between purification and the protein sub-cellular localization were examined. The dependence of purification success rate on the protein localization was clearly evident (Figure 4). Cytoplasmic proteins displayed the highest purification success rate. Proteins with predicted membrane localization and surface were successful in less than 40% of the cases. More than 97% of the attempted cytoplasmic proteins were expressed and purified by at least one of the expression vectors, while 68.1% of non-cytoplasmic proteins were successfully purified. The expression vector, pHis is the least favorable for surface proteins. The other larger fusion proteins increased purification of the surface proteins. The MBP-tag increased the success rate of the surface proteases by approximately 8-fold compared to the His-tag. The presence of signal peptide that targets proteins to the cell surface also decreased the success rate of protein purification. Only one of 38 attempted proteins containing native signal peptide were purified using the pHis expression vector. The expression vector with the GST-tag also performed poorly for proteins containing signal peptide. Half of the proteins containing signal peptide were purified using an expression vector, pMBP, which was also the most successful vector for both the presence and the absence of signal peptide. Approximately 20-fold more proteases containing signal peptide were purified with pMBP compared to pHis. With a combination of 5 expression vectors, 79% of proteins containing native signal peptide were purified.

Bottom Line: Overall, 86.1% of selected protease genes including hypothetical proteins were expressed and purified using a combination of five different expression vectors.To detect novel proteolytic activities, zymography and fluorescence-based assays were performed and the protease activities of more than 46% of purified proteases and 40% of hypothetical proteins that were predicted to be proteases were confirmed.The combinatorial functional analysis of the purified proteases using fluorescence assays and zymography confirmed their function.

View Article: PubMed Central - HTML - PubMed

Affiliation: Pathogen Functional Genomics Resource Center, J, Craig Venter Institute, Rockville, Maryland 20850, USA. scottp@jcvi.org

ABSTRACT

Background: Uncharacterized proteases naturally expressed by bacterial pathogens represents important topic in infectious disease research, because these enzymes may have critical roles in pathogenicity and cell physiology. It has been observed that cloning, expression and purification of proteases often fail due to their catalytic functions which, in turn, cause toxicity in the E. coli heterologous host.

Results: In order to address this problem systematically, a modified pipeline of our high-throughput protein expression and purification platform was developed. This included the use of a specific E. coli strain, BL21(DE3) pLysS to tightly control the expression of recombinant proteins and various expression vectors encoding fusion proteins to enhance recombinant protein solubility. Proteases fused to large fusion protein domains, maltosebinding protein (MBP), SP-MBP which contains signal peptide at the N-terminus of MBP, disulfide oxidoreductase (DsbA) and Glutathione S-transferase (GST) improved expression and solubility of proteases. Overall, 86.1% of selected protease genes including hypothetical proteins were expressed and purified using a combination of five different expression vectors. To detect novel proteolytic activities, zymography and fluorescence-based assays were performed and the protease activities of more than 46% of purified proteases and 40% of hypothetical proteins that were predicted to be proteases were confirmed.

Conclusions: Multiple expression vectors, employing distinct fusion tags in a high throughput pipeline increased overall success rates in expression, solubility and purification of proteases. The combinatorial functional analysis of the purified proteases using fluorescence assays and zymography confirmed their function.

Show MeSH
Related in: MedlinePlus