Genetic Biodiversity Analysis

Methods

The data collection of this test was from 16s rRNA sequencing which was completed through the website Nephele using DADA2 and QIIME analysis. Rush University in Chicago performed gDNA extraction and 16s rRNA sequencing. Nephele obtained H, S, E, taxonomic bar plots, and specific genus counts.

  Genetic Biodiversity in Rain Garden and Non-Rain Garden Samples (4A Shannon Diversity Index graph from 16S rRNA sequencing, 4B Richness graph from 16S rRNA sequencing, 4C evenness graph from 16S rRNA sequencing, 4D Species Taxonomic Bar Graphs, 4E Specific Phyla Counts). 

DNA was isolated from both rain garden samples and non-rain garden samples and sent to Rush University to be sequenced. The sequenced data was analyzed using Nephele. For figures 4A, 4B, and 4C, the average (mean) of each data set is represented by the X mark on the plots. The line dividing the boxes represents the median. The upper portion of each large rectangle represents the 3rd quartile range for each data set. The lower portion of the large rectangle represents the 1st quartile range for each data set. The upper whisker line represents the maximum value of each data set. The lower whisker line represents the minimum value of each data set. The inner points are used to identify any potential outliers between the box section of the plot, or they may be used to simply determine any differences between data sets.

 An unpaired t-test assuming unequal variance was used to determine the p-value for figures 4A, 4B, and 4C (4A p = 0.446 , 4B p = 0.498, 4C p = 0.567) with a critical value of 0.05. Figure 4D represents a taxonomic graph bar plots demonstrating the relative frequency of different species of phyla in the 5 non-rain garden and 5 rain garden samples. 

A comparison was made of the relative frequency of each phylum class in the non-rain garden versus the rain garden samples. Figure 4E shows us many different specific species of bacteria and the amount of times they showed up in the sample. Each of the four species we chose to use in our website are analyzed with the amount of times they showed up in our non-rain garden and rain garden samples. 

Evidence

The mean for the Shannon Diversity Index (H) of our non-rain garden was 4.386, and 4.453 for our rain garden samples. We can see that the Shannon Diversity Index was slightly lower for our non-rain garden than our rain garden. The standard deviation for our Shannon Diversity Index of our non-rain garden and rain garden was 0.147 and 0.113 respectively. Our non-rain garden sample has a higher variance (30.09%) in Shannon Diversity Index than our rain garden sample. Our p-value for the Shannon Diversity Index was 0.446. With a critical value of 0.05, there is no statistically significant evidence of a difference in the H value of our two conditions.

 The mean for the Species Richness of our non-rain garden was 124.4, and 131.2 for our rain garden samples. We can see that the Species Richness (S) was slightly higher (5.47%) for our rain garden than our non-rain garden. The standard deviation for our Species Richness of our non-rain garden and rain garden was 16.38 and 13.37 respectively. Our non-rain garden sample has a higher variance (22.51%) in Species Richness than our rain garden sample. The p-value for our species richness was 0.498, and therefore the difference between samples in richness is not significant because the value is not less than 0.05. 

 The mean species Evenness (E) for our non-rain garden samples was 0.911 and 0.914 for our rain garden samples. The species evenness was, on average, slightly higher (3.29%) in our non-rain garden samples than in our rain garden samples. The standard deviation for our non-rain garden samples was 0.010 and 0.006 for our rain garden samples. We can observe that the non-rain garden samples had higher variance (66.67%) than our rain garden samples. The p-value for the species evenness of our two conditions was 0.567, suggesting that there is no statistically significant evidence of a significant difference in the evenness of the two populations.

 In the rain garden samples, there appears to be a slightly higher relative frequency of the phylums represented by the dark blue and the hot pink colors in comparison to the non-rain garden samples. Phylums included in the dark blue are: Bacteroidota, Desulfobacteroidota, Armatimonadota, Patescibacteria, Fusobacteriodota, and Sumerlaeota. The phylums included in the hot pink are: Chloroflexi, Entotheonellaeota, Dadabacteria, and Spirochaetota. The four bacteria species we used in our specific species counts are Pseudomonas, Rhodococcus, Sphingobium, Sphingomonas. The average number of times Pseudomonas, Rhodococcus, and Sphingomonas showed up in our samples is greater for non-rain garden samples than for rain garden samples. However, the average number of times Sphingobium showed up is greater for our rain garden samples than for our non-rain garden samples. We can clearly see that the standard deviation for all four of our bacteria species is greater for our non-rain garden soil samples than for our rain garden soil samples. While the p-values for all of our bacteria species are also not significant since the values are not below 0.05, for the Pseudomonas species, the p-value comes very close to 0.05, showing its significance albeit not its statistical significance.

Conclusion

To begin, we can conclude that there is no significant difference within the data for the graphs 4A-C . We can be confident in this conclusion because we are able to see that the p-value from the t-test for each of these mentioned graphs are not below 0.05, showing us there is no significant difference. For figure 4A we were analyzing the 16s rRNA gene for Shannon Diversity between the two different sites finding the p-value to be 0.446, for figure 4B we analyzed the 16s rRNA gene for richness between the two sites finding the p-value to be 0.498, and for figure 4C we analyzed the gene 16s rRNA for evenness between the two sites finding the p-value to be 0.567. For the final two figures we analyzed the different types of species found between the two sites, figure 4D, and the different number of a certain type of species, figure 4E. Based on our data we can conclude confidently that there is no significant difference with any of the measured biodiversity. 

 Explanation

To simplify, we can dissect why there was no significant difference between the two sites based on what is happening in the soil. To begin with figure 4A, we are analyzing the Shannon Diversity, which “reflects the ecological complexity of a community species” (del Rey, n.d.). This signifies how the living systems in the soil interplay with each other and how they interact with the rest of their environment (Definitions of Complexity, 2004). Based on our data from the two samples and the p-value calculated we are able to determine there is no significant difference between two and they both have around the same ecological complexity. 

The second figure 4B we analyze the difference in genes 16s rRNA for we are analyzing the richness of the soil, which is analyzing the number of species in these two samples (Dirmann, 2021). In other words we are analyzing how saturated the two different samples of soil are with bacterial species and those different species are able to perform different “tasks” for the soil such as nitrogen fixation, phosphorus solubilization, or improvement of plant stress, for example (Bell, 2021). Based on our data and p-values we can determine the two sample genes 16s rRNA have relatively the same number of species in the two samples. 

In the third figure 4C we examined evenness between the 16s rRNA gene between the two samples, which is essentially the “proportion of species present” (Why Measure Biodiversity?, n.d.) within the two samples. Based on our data, we were able to determine from the p-value being above 0.05 there was not any significant difference between the proportion of species in the two samples. Again with having the same proportion of species in both of the samples they both are performing the same functions as mentioned before, nitrogen fixation, etc., showing both of the samples are performing the same functions. 

Finally with the final two figures 4D and 4E we analyze the different types and numbers in the two samples respectively. With these types of analysis we are able to specialize and search for the type of bacteria we are wanting to analyze and be able to see if it is present in the sample, and we were able to see there were the same amount of the specific bacteria in each sample. Overall showing both of the samples perform the same functions with no significant differences.  Studies suggest that bacterial biodiversity both above and below ground is influenced by the species response to the same or similar environmental driving conditions (Coleman, D. C., & Whitman, W. B.). As our samples were collected in close proximity to each other, they have rather similar environmental conditions, thus potentially explaining the lack of significant differences in the genetic biodiversity. This is congruent with our experimental findings that there was no significant difference in the genetic biodiversity in the two samples.