Biochemical and molecular characterisation of selected microorganisms isolated from beef, chicken, mutton and pork meat products
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 microorgani...
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| Format: | Thesis |
| Language: | English |
| Published: |
2017
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| Online Access: | http://psasir.upm.edu.my/id/eprint/70177/1/FBSB%202017%2012%20-%20IR.pdf http://psasir.upm.edu.my/id/eprint/70177/ |
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| Summary: | 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. |
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