Embedded Files
Project Topic:
Project Topic:
The soil bacteria - in an urban campus setting - of Brooklyn College
The soil bacteria - in an urban campus setting - of Brooklyn College
Question:
Question:
What is the effect of campus vegetation on the soil microbial community?
What is the effect of campus vegetation on the soil microbial community?
Using past data question updated: What are the seasonal differences in the bacterial community?
Using past data question updated: What are the seasonal differences in the bacterial community?
Campus Variables:
Campus Variables:
Landscape maintenance - Record any activity for the day before and day of sampling
Landscape maintenance - Record any activity for the day before and day of sampling
Irrigation - estimate soil moisture at the time of sampling
Irrigation - estimate soil moisture at the time of sampling
Vegetation - Measure the amount of leaves/ pollen on the ground. Presence absence of different species (eg bush/tree/grass).
Vegetation - Measure the amount of leaves/ pollen on the ground. Presence absence of different species (eg bush/tree/grass).
Birds - Record presence /activity approximately how many birds in a 30 minute window in the am and in a 30 minute window in the pm.
Birds - Record presence /activity approximately how many birds in a 30 minute window in the am and in a 30 minute window in the pm.
Squirrels - Record presence /activity approximately how many birds in a 30 minute window in the am and in a 30 minute window in the pm.
Squirrels - Record presence /activity approximately how many birds in a 30 minute window in the am and in a 30 minute window in the pm.
People - Record the presence of people interference on the grass in a 30 minute window in the morning and in the evening.
People - Record the presence of people interference on the grass in a 30 minute window in the morning and in the evening.
Pesticides/Fertilizer- Ask campus staff (How often is it used & last application?, What chemical do they use?), research effect and residence time.
Pesticides/Fertilizer- Ask campus staff (How often is it used & last application?, What chemical do they use?), research effect and residence time.
Weather- Record the conditions for each day, meaning raining, sunny, cloudy, etc.
Weather- Record the conditions for each day, meaning raining, sunny, cloudy, etc.
Rainfall/Sun - Record the amount of rain / sun for the given days.
Rainfall/Sun - Record the amount of rain / sun for the given days.
UV exposure - Light meter to measure at the time of sampling.
UV exposure - Light meter to measure at the time of sampling.
Animal waste - Record any activity for the day before and day of sampling.
Animal waste - Record any activity for the day before and day of sampling.
Car traffic/pollution - Check for any methane levels in the soil.
Car traffic/pollution - Check for any methane levels in the soil.
Methods
Methods
Samples were collected and DNA was extracted by the Brooklyn College microbiology lab classes during the semesters of Fall 2016, Spring 2017, Fall 2017, and Spring 2018.
Samples were collected and DNA was extracted by the Brooklyn College microbiology lab classes during the semesters of Fall 2016, Spring 2017, Fall 2017, and Spring 2018.
DNA Extraction
DNA Extraction
Measure 0.25 g into MoBio bead beating tube
Measure 0.25 g into MoBio bead beating tube
Following remaining kit (MoBio Qiagen PowerSoil DNA Extraction) instructions
Following remaining kit (MoBio Qiagen PowerSoil DNA Extraction) instructions
Targeted Metagenomics
Targeted Metagenomics
Sequencing was completed by MrDNA, targeting the V1-V3 region of the 16SrRNA gene with Illumina MiSeq.
Sequencing was completed by MrDNA, targeting the V1-V3 region of the 16SrRNA gene with Illumina MiSeq.
Sequence Processing
Sequence Processing
The sequencing lab provided paired-end reads with the barcodes and adapters still within the sequence. Samples for just the campus surface soil were extracted from the files for each semester then concatenated into a single file. The QIIME protocol was followed to generate the minimum necessary files (.biom, .tre) with an overall mapping file including all 4 semesters.
The sequencing lab provided paired-end reads with the barcodes and adapters still within the sequence. Samples for just the campus surface soil were extracted from the files for each semester then concatenated into a single file. The QIIME protocol was followed to generate the minimum necessary files (.biom, .tre) with an overall mapping file including all 4 semesters.
Data Analysis
Data Analysis
Sequencing data was analyzed in R using the following packages: Phyloseq, vegan, & ggplot2. See the course R pipeline for the code for the filtering and summarizing the data.
Sequencing data was analyzed in R using the following packages: Phyloseq, vegan, & ggplot2. See the course R pipeline for the code for the filtering and summarizing the data.
Sample Species Rarefaction
Sample Species Rarefaction
Alpha Diversity
Alpha Diversity
Above is the before rarefying the samples to 18000 sequences (just below the lowest sequence count/sample). Below is after.
Above is the before rarefying the samples to 18000 sequences (just below the lowest sequence count/sample). Below is after.
Beta Diversity
Beta Diversity
Statistical Calculation Results:adonis(formula = distance(BCsoil, method = "bray") ~ Season, data = metadata) Permutation: freeNumber of permutations: 999Terms added sequentially (first to last) Df SumsOfSqs MeanSqs F.Model R2 Pr(>F) Season 1 0.6095 0.60950 1.8846 0.17314 0.027 *Residuals 9 2.9107 0.32342 0.82686 Total 10 3.5202 1.00000 ---Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Similar to how there was minimal change in alpha diversity following rarefaction, the beta diversity dispersion and clustering did not change. The seasons are significantly different in bacteria community (p<0.05).
Similar to how there was minimal change in alpha diversity following rarefaction, the beta diversity dispersion and clustering did not change. The seasons are significantly different in bacteria community (p<0.05).
By looking at the OTUs that have more than 100 sequences each there is a pattern of 4 key phyla and more Bacteroidetes in the Fall than in the Spring.
By looking at the OTUs that have more than 100 sequences each there is a pattern of 4 key phyla and more Bacteroidetes in the Fall than in the Spring.
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