Biochemical and molecular characterisation of selected microorganisms isolated from beef, chicken, mutton and pork meat products - Amie, Ceesay (2017)
Tracing and identification of meat products is one of the great concerns of consumers and meat products regulators. This is because consumers are more demanding and sensitive to the safety of the meat products they consume. Several methods have been employed in the characterization of microorganisms isolated from meat products such as phenotypic analysis, protein, biochemical, and molecular based techniques. The characterization based on protein and physiological techniques in meat profiling and classification by using microorganisms had been reported to be problematic since they share numerous characteristics. There have been limited reported studies on the characterization and profiling of microorganisms for meat classifications. This study was based on the biochemical and molecular fingerprint in the characterisation and profiling of selected microorganisms isolated from beef, chicken, pork and mutton samples that may be linked statistically to meat sources. In order to determine a specific difference between bacteria genera isolated from different meat sources, 39 Escherichia coli, 66 Lactobacillus, and 54 Pseudomonas isolates identified by using API 20E, 50CHL, and 20NE test kits. The isolates were then analysed using 18 antibiotics for antibiotic susceptibility assay. Thirty four E. coli, was examined by molecular markers such as BOXAIR, Enterobacterial repetitive intergenic consensus (ERIC), polytrinucleotide (GTG)5 and random amplified polymorphic DNA polymerase chain reaction ((RAPD-PCR) to generate genetic fingerprints, while 56 Lactobacillus and 42 Pseudomonas species were typed using RAPD and (GTG)-PCR to generate fingerprint data. The fingerprints were resolved on 1.5% (w/v) agarose gels. The resistance or sensitivity of isolates to antibiotics was score as binary data and a similar procedure was carried out, for the fingerprinting data where absence or presences of bands were scored on excel and used to generate a data matrix. The Unweighted Pair Group Method with Arithmetic Mean (UPGMA) and complete linkage arithmetic were used to analyse percentage of similarity. The similarities level of E. coli, Lactobacillus, and Pseudomonas isolates from different sources were expressed as a dendrogram. Bacteria colony counts (ranging from 2.2 to 6.5-log CFU/mL) showed a significant difference among the meat types (p ≤ 0.05). Further analysis using API Kit revealed Lactobacillus fermentum1 (12), Lb plantarum, Lc brevis 1 (8), Lc lactis spp lactis (5), E. coli 1 (29), Pseudomonas luteola (24) and Aeromonas hydrophila/caviae (7) as major groups identified. The dendrograms generated from antibiotic biogram showed a clear distinction between different meat products at the similarity coefficient of 0.60 to 1.0. The relationship of these isolates from each cluster was compiled and reported on tables. The fingerprints generated band sizes from 0.10 kb to 5.50 kb with the majority of isolates having 15 bands. The UPGMA and Dice coefficient clusters showed dendrograms based on 0.7 similarities of E. coli isolates of four techniques used. The dendrograms of all markers classified E. coli, Lactobacillus spp. and Pseudomonas spp. into five major clusters (I-IV) within the similarity coefficient of 1.0 (100%) to 0.65 (65%). All the markers except (GTG)5 accurately classified grocery pork (TP2), beef (GB1), and wet market beef (PMB1) samples in their respective cluster. Similarly, the (GTG)5 marker showed the same clustering pattern as ERIC marker for E. coli spp. The Principal component analyses (PCA) for BOXA1R and RAPD showed the clear distinction of sample classification. However, ERIC and (GTG)5 showed a weaker correlation between isolates of the same source. RAPD, ERIC, BOXA1R and (GTG)5 fingerprinting markers showed the highest discriminatory index at the following cut-off percentages: 0.80 at 80%, 0.81 at 90% and 0.87 at 100%. These results suggested that RAPD, (GTG)5 and BOXA1R markers could be an effective tool for the characterization of bacteria from different sources. The similarity matrices confirmed the clustering pattern and genetic relationship between and among isolates. The findings of this research revealed that the biochemical and genetic fingerprinting of E. coli, Lactobacillus spp. and Pseudomonas spp. isolated from meat and meat products could be used as a potential technique to characterise microorganism according to meat types.