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<p>Uricase holds significant pharmaceutical applications, particularly in treating diseases associated with elevated uric acid levels and serving as a diagnostic enzyme to detect uric acid in biological fluids. Enhancing uricase production is crucial to meet the demands of large-scale applications. This study focuses on optimizing process parameters for uricase production using advanced statistical methods, namely Response Surface Methodology (RSM) and Artificial Neural Network-Genetic Algorithm (ANN-GA). Seven key process parameters were investigated: temperature, pH, medium volume, incubation time, inoculum size, inoculum age, and rpm. Conformational experimental studies at the ANN-GA predicted optimal conditions revealed a significant uricase activity of 63.92 ± 0.06 U/mL. The purified uricase exhibited specific activity of 92.48 U/mg and a molecular weight of approximately 32&#xa0;kDa. Itdemonstrated remarkable stability, withstanding a wide pH range (6.0 to 10.0) and temperatures up to 50&#xa0;°C, with an optimum pH of 9.0 and temperature of 30&#xa0;°C. This broad pH and temperature tolerance of the purified uricase from <i>Pseudomonas mosselii</i> DSS002 underscores its potential as a valuable source for industrial-scale production, catering to various pharmaceutical applications. This study’s findings pave the way for efficient and scalable uricase production, offering promising implications for the pharmaceutical industry.</p>

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Statistical Optimization of Process Parameters and Purification of Uricase Using Isolate Pseudomonas mosselii DSS002

  • 期刊论文

  • 发表日期：

    2025年3月19日

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  • Sai Sushma Dudala,
  • T. C. Venkateswarulu,
  • A. Venkata Narayana,
  • D. John Babu

摘要

Uricase holds significant pharmaceutical applications, particularly in treating diseases associated with elevated uric acid levels and serving as a diagnostic enzyme to detect uric acid in biological fluids. Enhancing uricase production is crucial to meet the demands of large-scale applications. This study focuses on optimizing process parameters for uricase production using advanced statistical methods, namely Response Surface Methodology (RSM) and Artificial Neural Network-Genetic Algorithm (ANN-GA). Seven key process parameters were investigated: temperature, pH, medium volume, incubation time, inoculum size, inoculum age, and rpm. Conformational experimental studies at the ANN-GA predicted optimal conditions revealed a significant uricase activity of 63.92 ± 0.06 U/mL. The purified uricase exhibited specific activity of 92.48 U/mg and a molecular weight of approximately 32 kDa. Itdemonstrated remarkable stability, withstanding a wide pH range (6.0 to 10.0) and temperatures up to 50 °C, with an optimum pH of 9.0 and temperature of 30 °C. This broad pH and temperature tolerance of the purified uricase from Pseudomonas mosselii DSS002 underscores its potential as a valuable source for industrial-scale production, catering to various pharmaceutical applications. This study’s findings pave the way for efficient and scalable uricase production, offering promising implications for the pharmaceutical industry.