de Smidt O
Department of Life Sciences, Centre for Applied Food Safety and Biotechnology, Central University of Technology, Free State, Bloemfontein, South Africa.
Lett Appl Microbiol. 2016 Jan;62(1):1-8. doi: 10.1111/lam.12505. Epub 2015 Nov 25.
Strict legislation and chemical composition monitoring of effluent may be useful, but the data generated do not allow for source tracking, and enforcing legislation remains problematic in the South African setting. These difficulties emphasize the necessity for effluent source traceability. Denaturing gradient gel electrophoresis (DGGE) targeting the V3 region of the 16S rRNA gene was considered as fingerprinting technique for effluent originating from abattoirs slaughtering different animal species. The influence of treatment to remove excess fat from effluent prior to molecular analyses and different PCR approaches on the detection of bacterial diversity were considered. Use of a treatment option to remove fat and a nested PCR approach resulted in up to 51% difference in inter-sample diversity similarity. A robust approach with no pre-treatment to remove PCR inhibitors, such as fat, and direct amplification from genomic DNA yielded optimal/maximal bacterial diversity fingerprints. Repeatable fingerprints were obtained for poultry abattoir effluent over a 4-month period, but profiles for the red meat abattoir varied with maximum similarity detected only 33·2%. Genetic material from faecal indicators Aeromona spp and Clostridium spp were detected. Genera unique to each effluent were present; Anoxybacillus, Patulibacter and Oleispira in poultry abattoir effluent and Porphyromonas and Peptostreptococcus in red meat abattoir effluent.
This study was the first to demonstrate the application of denaturing gradient gel electrophoresis (DGGE) to construct bacterial diversity fingerprints for high-throughput abattoir effluents. Proved redundancy of fat removal as PCR inhibitor and change in diversity similarity introduced by nested PCR approach. The importance of limiting excessive handling/processing which could lead to misrepresented diversity profiles was emphasized.
对废水实施严格的立法和化学成分监测或许有用，但所产生的数据无法用于源头追踪，而且在南非的环境中执行立法仍然存在问题。这些困难凸显了废水源头可追溯性的必要性。针对16S rRNA基因V3区域的变性梯度凝胶电泳（DGGE）被视为一种指纹识别技术，用于分析屠宰不同动物种类的屠宰场产生的废水。研究了在分子分析之前去除废水中多余脂肪的处理方法以及不同PCR方法对细菌多样性检测的影响。使用去除脂肪的处理方法和巢式PCR方法导致样本间多样性相似度相差高达51%。一种无需预处理以去除PCR抑制剂（如脂肪）并直接从基因组DNA进行扩增的稳健方法产生了最佳/最大的细菌多样性指纹。在4个月的时间里，家禽屠宰场废水获得了可重复的指纹图谱，但红肉屠宰场的图谱有所不同，检测到的最大相似度仅为33.2%。检测到了粪便指示菌气单胞菌属和梭菌属的遗传物质。每种废水都存在独特的属；家禽屠宰场废水中的嗜热栖热放线菌属、嗜冷栖热放线菌属和嗜油螺旋菌属，以及红肉屠宰场废水中的卟啉单胞菌属和消化链球菌属。
本研究首次证明了应用变性梯度凝胶电泳（DGGE）构建高通量屠宰场废水的细菌多样性指纹图谱。证明了去除脂肪作为PCR抑制剂的冗余性以及巢式PCR方法引入的多样性相似度变化。强调了限制可能导致多样性图谱被错误呈现的过度处理的重要性。
