11/27/14
Wed, 11/26/2014 at 6:43 AM
Customer: We are doing research on soil bacteria. We would like to describe the bacterial population w and w/o addition of fertilizer. I would like to get some information about bioinformatic work that can be done regarding this subject.
Wed, 11/26/2014 at 7:50 AM
AccuraScience LB: We have had discussions with several researchers in recent months about strategies and methods for similar projects. May I suggest that you take a look at the edited logs of these discussions: http://www.accurascience.com/lstyuo/php/recent_inquiries.php?id=%27inquiry_44_09_23_2014%27, http://www.accurascience.com/lstyuo/php/recent_inquiries.php?id=%27inquiry_38_09_17_2014%27 and http://www.accurascience.com/lstyuo/php/recent_inquiries.php?id=%27inquiry_34_09_08_2014%27, and let us know whether the approaches discussed might be applicable to your project? If not, then would you tell us a little more about the specifics of your project, so that we will try to come up with a strategy and methods for your purposes?
Thu, 11/27/2014 at 6:43 AM
Customer: Our project is a bit different. We are working on soil samples and are interested in the bacterial and archaeal population composition of the soil after adding fertilizer. There could be a change in the population regarding their participation in the nitrogen cycle. In addition, we are interested to see the diversity of functional genes involved in the nitrogen cycle. We already took soil samples and extracted DNA. We are not sure which way to choose: whole genome sequencing, 16s or if there is a need for more.
Sat, 11/29/2014 at 9:47 AM
AccuraScience LB: Although the samples you have are different from those in the studies I cited - yours are soil samples instead of fecal samples, the objectives of your project are similar to those other studies, and they are: (1) analyze taxonomic compositions of the microbiomes in the two conditions (with and without fertilizer), and make comparison between them, and (2) characterize functional difference between the two microbiomes, in terms of differential expression of specific metabolic pathways and genes involved in the metabolic pathways.
To accomplish objective (1), 16s rDNA-based sequencing would be adequate. To achieve objective (2), however, short-gun sequencing (for either RNA or DNA) is often needed. However, a recently published paper describing a new methodology named PICRUSt, which uses 16s rRNA-based data as sole input, and impute or predict functional aspects of the microbiome (e.g., metabolic pathways). If you have difficulty performing shot-gun sequencing, you might want to consider this as a possible alternative.
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Note: LB stands for Lead Bioinformatician. An AccuraScience LB is a senior bioinformatics expert and leader of an AccuraScience data analysis team.
Disclaimer: This text was selected and edited based on genuine communications that took place between a customer and AccuraScience data analysis team at specified dates and times. The editing was made to protect the customer’s privacy and for brevity. The edited text may or may not have been reviewed and approved by the customer. AccuraScience is solely responsible for the accuracy of the information reflected in this text.