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New Beginnings and New Adventures!

Thursday, December 24, 2015

The New Year is a time for many of us to set our resolutions and with all probability fail. According to the statistics[i] 45% of Americans usually make resolutions (I would have guessed higher), but only 8% are successful in achieving their goals (room for improvement!). On the top 10 list for resolutions…there are a couple I find very admirable and maybe for me to work on this year: “Enjoy life to the fullest” and “Help others in their dreams”.


In my last blog I discussed how thankful and inspired I am, but today I am looking forward to the new beginning of 2015 and the new adventures I plan to have along the way. Last year I visited 15 states and seven different countries. I hope this year I can top both of them and meet some incredible industry allies along the way. I am most excited about my adventure in May to attend the Digestive Pig Physiology Symposium in Poland as this year I have the quest to soak up as much knowledge as possible in the areas of gut health, fiber, and the microbiome. Another area of interest for me this year is “Big Data” (large, encompassing data sets) and how to effectively use and interpret the data out there to maximize profitability and sustainability for animal agriculture.

With these endeavors in mind I want to discuss the new tools available to understand the microbiome of different species and why this is “Big Data”. Thanks to Dr. Nicola Walker, AB Vista’s Ruminant Product Manager and Ruminant Microbiologist, I had a go-to person to discuss the different techniques available for microbiome research. The newest and much more cost-effective technique to define the microbiome population is High-Throughput Sequencing. But within High-Throughput Sequencing there are several avenues to approach an analysis of the microbiome. To summarize the review by Di Bella[i] et al (2013) there are three main experimental approaches that utilize high-throughput sequencing technology:

  1. Amplicon Sequencing: a specific gene or gene fragment or sequence is amplified and the sequence is determined for identification.
  2. Metagenome sequencing: the entire DNA in a sample is sequenced to determine which genes are present in a sample and thus determine how the functionalities or pathways differ between environments.
  3. Metatranscriptome Sequencing: the entire RNA in a sample is sequenced and proportionally analyzed to determine which transcripts are present and if genes are differentially expressed within the environment.

Within these experimental approaches there has been several advances in techniques, equipment, and computation software to help researchers to get the right answers they are searching for. I am not going to play an expert in this arena, but I would highly recommend this review as a starting point in understanding the opportunities available to researchers of today. The more I read the review I clearly understood how important it is to what type of information you are after and what is the best approach to achieve these answers. Also, that area of microbiome research is really “Big Data” and could lead to incredible discoveries on how we feed and raise pigs in the future. It will not just be about Ca:P ratios or AA ratios moving forward. For example, research conducted by Park[ii] et al. (2014) found microbiome differences in swine related to meat and fat quality: the Roseburia spp that produces CLA and the Clostridium spp. That produces SCFAs; the researchers indicate that their research could be used in the future to develop diagnostic kits to determine the meat grade of swine before they ever get to slaughter.

In closing, I want to thank everyone who is working in this area and I know in my recent visit to Purdue University that Dr Kolapo Ajuwons group who are researching microbiome changes in swine will help us find the future answers to this microbiome conundrum.



[ii] Di Bella, J.M.; Y. Bao, G. B. Gloor, J. P. Burton, and G. Reid. 2013. High throughput sequencing methods and analysis for microbiome research. J. Microbiological Methods. 95: 401-414.

[iii] Park, S. J.; J. Kim, J. S. Lee, S. K. Rhee, and H. Kim. 2014. Characterization of the fecal microbiome in different swine groups by high-throughput sequencing. Anaerobe. 28: 157-162.

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