Which Microbial Sequencing Method Should I Choose?
So you've chosen your research question and you've decided which environment you'd like to study, but then comes the dreaded question..."how?" Choosing the most efficient and cost-effective method for answering your research question can be a daunting task and one we hope you don't hesitate to bring to us. With terms such as metagenomics, shotgun metagenomics, 16s metagenomics, and metatranscriptomics sprinkled throughout the literature, and at times used interchangeably it is easy to understand how the sequencing method the investigator may have in mind does not always align with with sequencing method the service provider may have in mind. So lets try and clear up some of the issues causing confusion.
First off, metagenomics, shotgun metagenomics, and 16s metagenomics are not the same sequencing method. Metagenomics is the overarching field of studying the nucleotides from a given environmental sample. Shotgun metagenome and 16s metagenome sequencing methods are both capable sequencing applications for the purpose of completing metagenomic studies. 16s metagenome sequencing is a method that specifically targets the 16s rRNA gene in order to assess the diversity of a given environmental samples. On the other hand, shotgun metagenome sequencing is designed in such a way that all genes are subsequently sequenced. Each one these methods have their advantages and disadvantages and we would encourage you to visit our pages for 16s ribosomal sequencing and Metagenomics for more information. While each of these sequencing methods are able to provide a snapshot into the diversity present in each sample and elucidate some of the pathways present, neither is able to determine the current expression state of a specific biological process. This is were metatrancriptomics is of great value. There are a number of variables that could result in a certain gene being turned on or off, and evaluating the transcriptome of microbes present in your sample is sure to provide a better understanding of the impact of those variables on the population as a whole.