THE FINAL POST: A BITTER SWEET ENDING
THE QUESTION
In my last two blog posts, I've posed a series of questions that I thought might potentially be interesting to explore into given the research data we've been collecting. This week, I intend to explore one of those questions and the question I've selected is...
drum roll, please!
Do starters with fruits classified as "bitter", have microbial compositions that differ from fruits that are classified as "sweet"?
With this question, I intended to explore if fruits that have differing tastes also have microbial communities with differing compositions.
THE HYPOTHESIS
Now, with every research project, no matter how big or small, it is important to have a hypothesis. I always find that coming up with a hypothesis helps me to better understand the question that's being asked (when I'm not the one coming up with it) even more.
In this case, I hypothesize that starters containing fruits that are classified as "bitter" will have a different microbial composition than starters containing fruits that are classified as "sweet".
THE CHOSEN STARTERS
Before getting started on analyzing my questions, I went through on an excel document containing all the starters that were analyzed and color coded the ones that had fruits that were classified as "bitter/sour tasting", the ones that had fruits that were classified as "sweet tasting", and the ones that were controls. Since analyzing all of the data would've probably taken a very long time and I don't know how well my computer would've handled it, I chose the first six samples with "sweet" fruits, the first six samples with "bitter/sour" fruits, and the first six samples that were controls (meaning I analyzed a total of eighteen starters).
Below I'll be listing the sample numbers of each of the starters I analyzed, the fruit they contained, and a link to the blog of the person responsible for creating said starter. I also color-coded them by sweet (purple), sour/bitter (dark orange), and control (green). Since phenotypic differences didn't really play into my selection of these samples (other than the taste, but since we can't taste these starters, I had to use google to help me classify what fruits are classified as "sweet" and which are classified as "bitter/sour"), I will not be mentioning anything about the phenotypic differences of these starters.
- Sample 1 was a control sample, therefore it did not have a taste.
- Learn more about sample 1 here.
- Sample 2 was an apple sample, therefore it was classified as sweet.
- Learn more about sample 2 here.
- Sample 3 was a control sample, therefore it did not have a taste.
- Learn more about sample 3 here.
- Sample 4 was a banana sample, therefore it was classified as sweet.
- Learn more about sample 4 here.
- Sample 5 was a tomato sample, therefore it was classified as sweet (on the sweeter side).
- Learn more about sample 5 here.
- Sample 7 was a control sample, therefore it did not have a taste.
- Learn more about sample 7 here.
- Sample 9 was a lemon sample, therefore it was classified as sour/bitter.
- Learn more about sample 9 here.
- Sample 10 was a control sample, therefore it did not have a taste.
- Learn more about sample 10 here.
- Sample 12 was a control sample, therefore it did not have a taste.
- Learn more about sample 12 here.
- Sample 13 was a grape-muscadine sample, therefore it was classified as sweet.
- Learn more about sample 13 here.
- Sample 14 was a strawberry sample, therefore it was classified as sweet.
- Learn more about sample 14 here.
- Sample 15 was a control sample, therefore it did not have a taste.
- Learn more about sample 15 here.
- Sample 30 was a grapefruit sample, therefore it was classified as sour/bitter.
- Learn more about sample 30 here.
- Sample 31 was a kiwi sample, therefore it was classified as sour/bitter.
- Learn more about sample 31 here.
- Sample 69 was a rambutan sample, therefore it was classified as sour/bitter.
- Learn more about sample 69 here.
- Sample 80 was a mango sample, therefore it was classified as sweet.
- Learn more about sample 80 here.
- Sample 96 was an orange sample, therefore it was classified as sour/bitter.
- Learn more about sample 96 here.
- Sample 102 was a kiwi sample, therefore it was classified as sour/bitter.
- Learn more about sample 102 here.
THE RESULTS
After I chose the samples I would be analyzing, I downloaded them all onto my computer and went through the process of uploading them to nephele. After a series of emails and re-uploading/downloading from nephele, the two graphs below (that display the results for the sample) were created.
ITS Bar Graph - Above is the ITS bar graph and key, which shows the different fungi compositions of the different samples.
16S Bar Graph - Above is the 16S bar graph and key, which shows the different bacteria compositions of the different samples.
INTERPRETING THE RESULTS
After creating these graphs, it was time to interpret my results. While more samples are needed to make a more in-depth analysis, I feel as though these results do allow me to answer my research question. After analyzing the graphs, I found that there was no real distinction between the taste (bitter/sour or sweet) and the microbial composition, therefore I reject my hypothesis that starters containing fruits that are classified as "bitter" will have a different microbial composition than starters containing fruits that are classified as "sweet". It also appears that the microbial communities of the control samples vary from sample to sample. In the samples I analyzed, the most common bacterial microbes present were Lactobacillus brevis and Lactobacillus plantarum. The most common fungal microbes present were unidentified and Saccharomyces cerevisiae. Based on my background research at the beginning of the semester, the fungi and bacteria microbial communities are very similar to what I expected.
Ultimately, the message for the 16S analysis is similar to the message for the ITS analysis: the taste (bitter or sweet) does not seem to have any effect on the fungi or bacterial microbial compositions of any of the samples. With this being said, there also appears to be a slight similarity in fungal compositions between two samples that have the same bacteria composition. For example, samples 1 and 3 both seem to contain the same fungi and bacteria species.
It seems as though there are a lot of organisms that can't be identified when it comes to the fungal composition of these samples; this might be because not as many fungi species have been identified as bacterial species, meaning there will be more unidentified species in a sourdough starter.
RELATIONSHIP BETWEEN BREAD AND MICROBIAL COMMUNITIES
Considering I tried to choose differing sweet fruits and differing bitter/sour fruits, it is difficult to determine whether there is a relationship between bread and the bacterial/fungal communities. However, I remember analyzing the results in the past and my hypothesis is that the microbial compositions of different starters are dependent less on the type of fruit that is present in the sample and more on the environment that the starter is exposed to. I came to this hypothesis based on the fact that I remember people with the same fruit starters had differing microbial compositions of both fungi and bacterial communities. In my research, specifically, it also appears as though the type of fruit used doesn't have any heavy impact on the microbial species that are present.
THE END...
Overall, I had to reject my hypothesis that starters containing fruits that are classified as "bitter" will have a different microbial composition than starters containing fruits that are classified as "sweet". This semester I've really enjoyed experimenting with sourdough starters and analyzing their different microbial compositions. I also enjoyed working with the CLC workbench and nephele. It was interesting to see different ways that research can be interpreted and analyzed. Anyways, thank you for reading my blog over the semester and I hope my research has played a part in better understanding microbial communities!
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