Proof-of-principle exploration of meat adulteration detection using the ClassIdent pipeline with nanopore sequencing...

Meat adulteration, particularly the substitution of high-value beef with cheaper poultry (chicken, duck) or pork for illicit economic gain, poses significant threats to consumer rights, market integrity, and public health. Accurate identification of components in mixed meat samples is crucial for combating such fraud. Traditional species detection methods have limitations as qPCR with species-specific probes can only target a subset of known species, while Sanger sequencing is inadequate for mixed samples and rapid on-site detection. Building on the previously developed ClassIdent pipeline targeting the mitochondrial 12S rRNA gene and QNome nanopore sequencing, this study focused on verifying its applicability in mixed meat identification. We prepared 48 simulated samples (18 single-source and 30 mixed samples) to mimic common meat fraud scenarios (beef adulterated with chicken, duck, or pork), including 9 binary combinations (weight ratios 1:1, 1:2, 1:4) and 1 quaternary combination (1:1:1:1), with each mixed sample sequenced in triplicate. All single-source samples were accurately identified by ClassIdent, with an average sequence identity of 99.60 %. For mixed samples, ClassIdent successfully distinguished all component species, and the read proportion of each species showed a positive correlation with the fresh weight mixing ratio. The mean absolute difference between the read proportion and the actual fresh weight ratio ranged from 1.11 % to 21.32 % across all mixed combinations. This discrepancy is primarily attributed to biological variables (e.g., interspecific differences in cell size and mitochondrial DNA copy number) and technical biases (including variations in DNA extraction efficiency and species-specific PCR amplification preferences). This study validates the potential of ClassIdent for rapid and reliable detection of meat adulteration, supporting its application in food safety supervision and forensic investigation.