<p>Food-borne bacterial pathogens remain a major public health concern, causing extensive illness and economic losses worldwide. Conventional detection methods are often slow and insufficient for identifying viable but non-culturable pathogens. Recent microbiological, biotechnological and bioinformatic advances have markedly improved food safety monitoring. Rapid molecular assays (PCR, qPCR, microarrays), next-generation sequencing, metagenomics, and emerging CRISPR-based diagnostics enable faster and more accurate pathogen detection and outbreak tracing. Bioinformatic tools—including genomic databases, phylogenetics, and machine-learning models—support predictive risk assessment and real-time surveillance. Preventive innovations such as bacteriophages, probiotics, antimicrobial peptides, nanotechnology-based interventions, and engineered microbes provide sustainable alternatives to chemical preservatives. Key challenges include variability across food matrices, biosafety considerations, and limited integration of multi-omics approaches into routine workflows. Overall, these emerging strategies offer improved precision and responsiveness for detecting and preventing food-borne bacterial pathogens.</p> Graphical abstract <p></p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Food-borne bacterial pathogens: emerging approaches in detection and prevention

  • Zaryab Shafi,
  • Mohammad Shahid,
  • Rahul Singh

摘要

Food-borne bacterial pathogens remain a major public health concern, causing extensive illness and economic losses worldwide. Conventional detection methods are often slow and insufficient for identifying viable but non-culturable pathogens. Recent microbiological, biotechnological and bioinformatic advances have markedly improved food safety monitoring. Rapid molecular assays (PCR, qPCR, microarrays), next-generation sequencing, metagenomics, and emerging CRISPR-based diagnostics enable faster and more accurate pathogen detection and outbreak tracing. Bioinformatic tools—including genomic databases, phylogenetics, and machine-learning models—support predictive risk assessment and real-time surveillance. Preventive innovations such as bacteriophages, probiotics, antimicrobial peptides, nanotechnology-based interventions, and engineered microbes provide sustainable alternatives to chemical preservatives. Key challenges include variability across food matrices, biosafety considerations, and limited integration of multi-omics approaches into routine workflows. Overall, these emerging strategies offer improved precision and responsiveness for detecting and preventing food-borne bacterial pathogens.

Graphical abstract