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Concentrated efforts have been made to better understand microbiome diversity and abundance, as another aspect of capturing difference and similarities between individuals in healthy and pathological conditions. Age2,3, geography4, lifestyle5,6, and illness5 were shown to be associated with the composition of the gut microbiome, but many conditions and populations have not yet been fully characterized. Recently it has been reported that the microbiome can be modified for therapeutic applications7,8,9. Therefore, additional insight into the relationship between various physiological conditions and the microbial composition is the first step toward optimization of potential future modifications.
The traditional microbial culture methods are limited by low yields10,11, and are conceptualized as a binary state where a bacteria is either present in the gut or not. High-throughput DNA-based sequencing has revolutionized microbial ecology, enabling the capture of all members of the microbial community. However, sequence read length and quality remain significant barriers to accurate taxonomy assignment12. Furthermore, high-throughput based experiments may suffer from batch effects, where measurements are affected by non-biological or non-scientific variables13. In recent years, several programs have been established to study the human microbiome, including the American Gut project, the United States (US) Human Microbiome Project, and the United Kingdom (UK) MetaHIT project. These initiatives have generated vast amounts of data that are not easily comparable due to a lack of consistency in their approaches. A variety of international projects such as the International Human Microbiome Consortium, the International Human Microbiome Standards project, and the National Institute of Standards and Technology (NIST) attempted to address some of these issues14, and developed standards for microbiome measurements which should enable the achievement of reliable reproductive results. Described here is an integrated protocol of several broadly used methods15,16 for 16S rRNA high-throughput sequencing (16S-seq) starting from fecal sample collection thru data analyses. The protocol describes a column-free PCR approach, originally designed for direct extraction of plant DNA16, to enable the simultaneous handling of large numbers of fecal samples in a relatively short time with high quality amplified DNA for targeted sequencing of the microbial variable V4 region on a common sequencing platform. This protocol aims to guide scientists interested in initiating the use of 16S rRNA-amplicon sequencing in a robust, reproductive, easy to use, detailed way, using important controls. Having a guided and detailed step-by step protocol may minimize batch effect and thus will allow more comparable sequencing results between labs.