User:Brunjesr/sandbox

Topic: Microbiome Methods

Now what has lead to this massive explosion in microbiome studies? I had this question after reading this article and decided to look up the answer to this question to see how these experiments have changed from the past. I found that two main techniques that have caused this change, this is culture-independent analysis techniques and next-generation sequence. Culture-independent techniques means you do not have to grow the culture in lab these include cellular metabolism, RNA and protein based methods, amplicon sequencing and PCR to name a few. Next generation sequencing is the process of sequencing DNA and RNA. Together these two techniques have revolutionized microbiome research by allowing cheap and quick analysis of samples. This has allowed for changes to be made to microbiome methods in place in order to standardize experimental designs.

So now that I had a better understanding of what techniques caused this explosion of microbiome studies, its now time to look how you specifically design your microbiome experiment. As a researcher you typically already have your question and ultimate goal in mind for your study. Now how do you set up your experimental design? First consider the animal model you wish to study this microbiome or soil/water sample you want to investigate. Afterwards consider what type of study you want to do. Longitudinal studies follows the same group for an extended period of time which helps when looking at confounders effect but timing of sampling becomes extremely important. Cross-sectional is a new group everytime that helps to look at differences in microbial communities between populations and regions. Next consider the confounders that can skew the data, for example age, diet, exercise level and habitat must be taken into consideration. It is important to clearly define criteria that will included to avoid these confounders effects. Finally try to avoid technical variation this can be done by using the same primers, blanks, and reagent kits throughout the experiment.

So you have your experimental design in mind and now we need to dive deeper into how you will method you will use to find your data and analysis this data to find your answer. This article discusses three main genetic analysis techniques for microbiome studies, marker gene, whole metagenome, and metatranscriptome other the article does mention other options as well. Marker gene analysis is great for microbiomes with numerous strains or species giving phylogenies of the sample but offers low resolution. Metagenome this offers total DNA analysis of a sample along with detection of genes that can offer insight into molecular function. Metatranscriptome uses RNA to characterize gene expression in the community being studied. Since you all read the article I will not go into the details of the pros and cons of each analysis option, but the article did provide this great chart listing them.

Now depending on the method you used on your samples along with the question you wish to answer will decide which analysis and program to use. There are two main approaches, read-based or assembly based analysis. Now there are numerous programs tailored to these approaches. This article discusses a lot of these programs and when to use them with each sequence method. The article also goes over what information each program will provide. So before analysing your data make sure you do your own research on the programs available to the sequence method used on your sample.

I visited the International Human Microbiome Standards and Microbiome Quality Control Project to see what type of standards are in place. This is a picture taken from the IHMS website where they have a list of SOPs (standard of practices) for each step of a microbiome study. MBQC also had a list of protocols to follow as well for experiments. All of these help to provide standardization of experiments to ensure reproducibility.

I visited the NIH human microbiome project website to see if they have a list of program options. This is the list of programs they provided along with a brief description of each program on the website As you can see there is a diverse number of program options to choice from to analysis your sample data. It all comes down to what exactly you are testing for and the method used when deciding which program to utilize. If you are interested in learning what each program offers, the NIH Human microbiome project does have descriptions as I mentioned earlier.

So after reading this article and seeing how microbiome studies of changed, I was interested to see where the future of micriobiome experiments was going. Omics seems to be a promising area. Multi-omic analysis offers a more comprehensive assessment of the microbial community and biological system being studied. This integrates the chemical and biological aspects to form a more complete picture. Merging of these different areas can reveal gene regulation in a microbiome and correlate microorganisms with metabolites. This seems to the be very promising future for microbiome studies and applications of those studies.

Some challenges facing microbiome experiments is the need for technological advances to better see and understand microbes. High-resolution imaging of specific molecular tags will reveal the better insight to a cell architecture revealing gene interactions and functions. This along with computer modeling of functional systems and macromolecule structures can be used to design a software that can be used as a global model to of cells. We can then use this model to stimulate synthetic symbiotic relationships and to better disentangle correlation and causation. The future of microbiome research is rapidly expanding as these technological advances become a reality.

Bibliography:

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Human Microbiome Project, N. (2020). Tools and Technology. Retrieved August 24, 2020, from https://www.hmpdacc.org/resources/

International Human Microbiome Standards, I. (2015). SOPS. Retrieved August 24, 2020, from http://www.human-microbiome.org/

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