动物肠道中存在着一些参与猪肠道微生物互作的基因,这些基因具有一定的宿主特异性,利用其设计分子标记能准确识别粪便污染来源.该文共采集6个物种(猪、牛、羊、鸡、鸭、鹅)的145个粪便样品,提取其DNA后利用竞争性杂交的基因片段富集方法(genome fragment enrichment,GFE),靶向筛选参与猪肠道微生物互作的特异性基因.经BLASTX分析发现,82%的猪特异性非冗余DNA片段存在相似序列,以拟杆菌纲(Bacteroidetes)(43.2%)、梭菌纲(Clostridia)(19.5%)、芽孢杆菌纲(Bacilli)(8.6%)相似序列为主.从蛋白质功能方面分析,61.5%的非冗余序列功能明确,有7.6%的序列与信息贮存及加工有关,12.8%的序列与细胞加工及信息传导有关,22%的序列与代谢有关,其中,碳水化合物和氨基酸的转移代谢相关序列含量最为丰富,均占总特异性序列的6.3%.研究发现,能够编码拟杆菌纲(Bacteroidetes)和梭菌纲(Clostridials)等表面蛋白、膜分泌蛋白及碳水化合物代谢蛋白的相关基因可作为猪特异性分子标记筛选的靶点.%Due to the rapid development of livestock breeding and poultry raising,non-point source pollution has become a significant threat to environmental management and aquaculture industry development,as well as to human health in the last few decades. Therefore,it is particularly urgent to establish a monitoring method that can be used as the efficient indicator of fecal pollution with high sensitivity and strong specificity. In animal guts,genes which are directly involved in bacterium-host interactions may display increased level of host-associated genetic variation,making them promising candidates for fecal source tracking. Specific markers targeting bacterium-host interaction genes for human,cattle and chicken were reported previously;however,swine-specific marker for fecal source tracking has not been found yet. We applied a genome fragment enrichment (GFE) method to enrich swine-specific metagenomic regions that differ from those of other animal species. Briefly,a portion of swine fecal DNA was labeled with biotin and pre-hybridized with a composite fecal DNA pool of other animals including cow (n=20),goat (n=20),chicken (n=8),duck (n=20) and goose (n=5) to block non-unique fragments. Then the pre-hybridized product and another portion of swine fecal DNA labeled with K9 primer were taken together to perform a competitive DNA hybridization. After streptavidin enrichment and long-linker PCR amplification by K9 primer,the products that were assumed as swine-specific fecal DNA were cloned into vectors and were sequenced. Dot blot hybridization with negative control fecal DNA (composite fecal DNA pool of other animals) was used to identify the cloned GFE sequences which were not swine-specific. The cloned GFE sequences were assigned to bacterial class annotations based on the top BLASTX hit (the lowest E-value score) with the GenBank non-redundant database. The putative protein transcript of each sequence was analyzed based on the similarity of gene sequences by using BLASTX with the GenBank non-redundant database, and their biochemical functions were therefrom predicted. Sequence analyses of five hundred randomly selected clones from the libraries obtained by three rounds of metagenomic GFE revealed that this subset contained a total of 384 non-redundant sequences and most sequences (87%) ranged from 400 bp to 600 bp in size. Dot blot hybridization using DNA composite of non-target animals as probes showed that only eight clones exhibited cross-reaction,indicating a very low false-positive rate of 2.8%. BLASTX searches identified homologous sequences in GenBank database for 315 non-redundant DNA inserts,with other 69 (17.9% of 384 swine fecal DNA sequences) inserts showed no homology with any previously reported genes. Based on top BLASTX hits,the sequences were putatively grouped into 20 bacterial classes including the predominant group of Bacteroidetes-like sequences (43.2%),among which,120 sequences were similar to Bacteroidetes-Prevotella. Clostridia-like sequences were the second most abundant group (19.5%),and Bacilli-like sequences represented 8.6% of the clones. Moreover,three sequences exhibited identity to genes in Archaea. Biochemical function annotation revealed that 38.5% of the total analyzed sequences were predicted as genes with unknown functions. Among the fragments associated with characterized function genes (61.5%),the sequences were most frequently assigned to putative proteins associated with metabolism (22%,e.g.,carbohydrate metabolism and amino acid metabolism),cellular process (12.8%,e.g.,membrane transport and DNA repair/replication/recombination) and information storage and processing (7.6%). It is concluded that gene encoding surface proteins,membrane associated proteins,secretary proteins and carbohydrate metabolism proteins of dominant bacterial classes could be regarded as putative targets for swine-specific microbial genetic markers.
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