Development and validation of miRNA based method for rapid identification of offal meats in processed chicken meat products

Food labelling requirements specify manufacturers to indicate the actual ingredients used in the processed meat products. However, several times, skeletal meat is replaced by less costly offal meats to maximize the revenues from the processed meats. Available DNA based analytical methods are inappropriate for declaration of “true to its labelling” within the species, because all the tissues have exactly the same DNA sequence. In this study, tissue specific candidate miRNA biomarkers were used to detect the presence of offal (liver, heart and gizzard) in skeletal meat of chicken. Deep sequencing of chicken microRNAs from liver, heart, gizzard, muscle and blood was performed using Illumina Nextseq 500 and 11, 25, 9.2, 8.8 and 6.1 million reads were analyzed for each sample. Unique and differentially expressed miRNAs were evaluated. Specific miRNAs having differential expression in each tissue studied were selected as candidate markers. A qRT-PCR based on SYBR® Green chemistry was standardized in terms of PCR efficiency, limit of detection and limit of quantification for expression analysis. These candidate biomarkers were validated in tissues as such and further in minced chicken meat samples admixture with 5, 25 and 50% of liver, heart and gizzard separately. The candidate biomarker gga-mir-148a -3p, gga-mir-126 -5p and gga-mir-490 -5p were proven as organ specific marker for detection of chicken gizzard, gga-mir-122 -5p and gga-mir-27b -5p are for liver and gga-mir-218 -5p and gga-mir-499 -3p for heart. Further, gga-mir-34a -5p and gga-mir-21 -5p shown to be specific marker for identification of two offal at a time. The developed assay was validated in processed ready to cook/eat commercial products. This method offers highly reproducible results with easy interpretation and can be combined with DNA techniques without requirement for any extra equipment, in regulatory laboratories for accurate detection of species and tissue origin of real world samples.