Metagenomic-driven predictive biosafety and contamination traceability in stem cell manufacturing: Translating
Marwa M Elmaghrabi1,2, Saleh A Alghofaili3, Mohamed M Mahmoud4
1Center of Excellence for Research in Regenerative Medicine and Applications (CERRMA), Faculty of Medicine, Alexandria University, Alexandria, Egypt.
Abstract:
Stem cell manufacturing and regenerative medicine laboratories are highly vulnerable to microbial contamination due to complex processing workflows, extensive manipulation, prolonged culture conditions, and continuous environmental exposure. Conventional microbiological methods remain fundamental for laboratory quality control; however, they may underestimate concealed resistance determinants, microbial diversity, contamination pathways, and transmission dynamics. Recent advances in metagenomic sequencing have transformed outbreak investigation, resistome characterization, and genomic surveillance, providing unprecedented opportunities for contamination monitoring and biosafety management. This review proposes a translational biosafety framework that integrates metagenomic surveillance with contamination traceability systems in stem cell manufacturing and regenerative medicine laboratory environments. The review discusses contamination challenges, limitations of conventional microbiological diagnostics, metagenomic surveillance approaches, predictive biosafety concepts, genomic traceability systems, corrective and preventive action (CAPA) integration, and future artificial intelligence (AI)-assisted monitoring strategies. Lessons from sequencing-based outbreak investigations involving multidrug-resistant microorganisms highlight the potential utility of metagenomic surveillance for early detection of contamination, microbial source attribution, resistome characterization, environmental monitoring, and contamination traceability. Integrating sequencing-guided diagnostics with laboratory traceability systems and CAPA-based quality management may shift biosafety practices from reactive contamination control toward proactive predictive biosurveillance. The proposed framework may strengthen contamination prevention, improve manufacturing reproducibility, support regulatory compliance, and enhance the reliability of stem cell processing and regenerative medicine applications. Future studies are needed to standardize sequencing-guided biosafety workflows and evaluate their implementation in academic, research, and clinical-grade stem cell manufacturing laboratories.
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