Non-microbiological Mycobacterial Detection Techniques in Biopharmaceutical Manufacturing

Reuel Beckwith^*
*Correspondence: Reuel Beckwith, Department of Biomedical Engineering, Sichuan University, Chengdu 610065, China, Email:

Keywords

Mycobacteria • Biopharmaceutical manufacturing • Non-Tuberculous Mycobacteria (NTM) • Detection techniques • Molecular methods • Mass spectrometry • Imaging technologies

Introduction

Mycobacteria represent a diverse group of bacteria known for their resilient nature and ability to thrive in various environments, including soil, water and aerosols. While the majority of mycobacterial species are harmless, some can cause serious infectious diseases, such as Tuberculosis (TB) and leprosy. In biopharmaceutical manufacturing, mycobacterial contamination poses a significant concern due to its potential to compromise product safety and quality. Traditional microbiological methods, although effective for detecting many types of microbial contaminants, often fall short when it comes to Non-Tuberculous Mycobacteria (NTM). NTM species, characterized by slow growth rates and unique metabolic properties, can evade detection or produce false-negative results using conventional techniques.The detection of mycobacteria in biopharmaceutical manufacturing presents several challenges. NTM species exhibit slow growth kinetics, often requiring extended incubation periods for detection [1].

Literature Review

Moreover, their resistance to disinfectants and ability to form biofilms on surfaces further complicates eradication and detection efforts. Additionally, mycobacterial cells can adopt dormant or Viable-But-Nonculturable (VBNC) states under adverse conditions, making them even more challenging to detect using traditional culture-based methods. These factors underscore the need for alternative detection techniques capable of overcoming the limitations of conventional microbiological approaches. Molecular techniques, such as Polymerase Chain Reaction (PCR) and nucleic acid amplification assays, offer rapid and sensitive detection of mycobacterial DNA or RNA. These methods target specific genetic markers unique to mycobacteria, enabling selective amplification and identification. PCR-based assays can detect even low levels of mycobacterial contamination within a short timeframe, making them invaluable tools for routine monitoring and rapid response in biopharmaceutical manufacturing facilities [2].

Mass Spectrometry (MS) has emerged as a powerful tool for microbial identification in various industries, including biopharmaceutical manufacturing. Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) allows for the rapid and accurate identification of mycobacterial isolates based on their unique protein profiles. By comparing the spectra of unknown isolates to reference databases, MALDI-TOF MS facilitates the precise identification of mycobacterial contaminants, enabling timely intervention to prevent product adulteration or contamination. Advanced imaging technologies, such as fluorescence microscopy and Scanning Electron Microscopy (SEM), provide valuable insights into the morphology and spatial distribution of mycobacterial cells. Fluorescence microscopy, coupled with specific stains targeting mycobacterial cell walls or nucleic acids, enables the visualization of individual cells or biofilm structures in real time. SEM, on the other hand, offers high-resolution imaging of mycobacterial biofilms and surface-associated aggregates, aiding in their characterization and quantification [3].

The detection of mycobacterial contamination in biopharmaceutical manufacturing requires innovative approaches capable of overcoming the limitations of traditional microbiological methods. Non-microbiological detection techniques, such as molecular methods, mass spectrometry and advanced imaging technologies, offer rapid, sensitive and specific detection of mycobacteria in complex matrices. By leveraging these cutting-edge techniques, biopharmaceutical companies can enhance their ability to detect and mitigate mycobacterial contamination risks, thereby safeguarding product integrity and ensuring patient safety. Continued research and development in this field are essential to further improve the efficacy and reliability of mycobacterial detection methods in biopharmaceutical manufacturing settings. Regulatory agencies, such as the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA), provide guidelines and recommendations for microbial control in pharmaceutical manufacturing, including requirements for mycobacterial testing and monitoring [4].

Discussion

For instance, the FDA's Guidance for Industry on Sterile Drug Products Produced by Aseptic Processing emphasizes the importance of monitoring for microbial contamination, including mycobacteria, in aseptically processed pharmaceutical products. Similarly, the EMA's Annex 1 to the EU Good Manufacturing Practice (GMP) Guide outlines principles and guidelines for the manufacture of sterile medicinal products, emphasizing the need for robust microbial control strategies. Biopharmaceutical manufacturers are expected to implement appropriate methods for mycobacterial detection and monitoring as part of their overall quality control measures. Non-microbiological detection techniques, such as those discussed earlier, may offer advantages in terms of sensitivity, speed and specificity, aligning with regulatory expectations for microbial control in pharmaceutical manufacturing. Looking ahead, ongoing advancements in technology and methodology are likely to further enhance mycobacterial detection capabilities in biopharmaceutical manufacturing. Emerging techniques, such as Next-Generation Sequencing (NGS) and microfluidic-based assays, hold promise for high-throughput, multiplexed detection of mycobacteria and other microbial contaminants [5].

Moreover, the integration of Artificial Intelligence (AI) and machine learning algorithms into mycobacterial detection workflows may streamline data analysis and interpretation, enabling more accurate and efficient identification of contaminants. By harnessing the power of AI-driven analytics, biopharmaceutical companies can improve the reliability and scalability of their mycobacterial detection efforts, ultimately enhancing product safety and compliance with regulatory requirements. Collaborative efforts between industry stakeholders, academic researchers and regulatory agencies are essential to drive innovation and standardization in mycobacterial detection methods for biopharmaceutical manufacturing. By fostering an environment of knowledge sharing and collaboration, the pharmaceutical industry can collectively address the challenges posed by mycobacterial contamination and safeguard the integrity of biopharmaceutical products [6].

Conclusion

Non-microbiological mycobacterial detection techniques represent valuable tools for ensuring the safety and quality of biopharmaceutical products. By leveraging molecular methods, mass spectrometry, imaging technologies and other innovative approaches, biopharmaceutical manufacturers can enhance their ability to detect, monitor and control mycobacterial contamination in manufacturing environments. With continued investment in research, development and regulatory compliance, the pharmaceutical industry can mitigate the risks associated with mycobacterial contamination and uphold its commitment to patient safety and product quality.

Acknowledgement

None.

Conflict of Interest

There are no conflicts of interest by author.

References

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