Bioinformatics Research on Microbes/CRISPRs in Oxygen Minimum Zones in the Pacific Ocean

Undergraduate #118
Discipline: Biological Sciences
Subcategory: Microbiology/Immunology/Virology

Vanessa Ochs - Alverno College

We used bioinformatics to study microbes and Clustered Regularly Interspaced Palindromic Repeats (CRISPRs) in the Eastern Tropical North Pacific (ETNP) Oxygen Minimum Zone (OMZ). Previous studies of the ETNP found that mobile genetic elements were more frequent in Pre-Filter (PF) vs Sterivex (SV) microbial community metagenomes; therefore, we hypothesized that there would be more CRISPR arrays in PF metagenomes compared to the SV metagenomes as naturally occurring microbial CRISPR arrays are part of the adaptive immune system of prokaryotes. This is important because further research could lead to advances in genetic engineering using CRISPRs. Samples were gathered onto a 30 µm nylon mesh (PF) and 1.6 µm glass fiber filter (SV) by in-line filtration using 10 L of seawater at 30 m, 85 m, 100 m, and 125 m depths at two OMZ stations. Filters were then placed in a cryotube with 2.0 mL of extraction buffer. The cryotube was frozen at -80°C for storage until further processing could be done. Samples in the cryotubes were heated to 55°C for 30 minutes and lysates were purified. The DNA pellets were placed in 50 µL of water and placed at -80°C. DNA was amplified and sequenced according to standard procedures using Illumina MiSeq technology (Duret et al., 2015). Raw sequence files were first run through FastQC and TrimGalore! to detect and remove low quality sequences. High quality reads were then assembled with MEGAHIT into longer contiguous sequences. The assembled sequences were annotated with Prokka to determine where the genes were located. To detect CRISPRs in the assembled sequences, we tested several programs. We found that MinCED and CRT were the easiest to use, as well as returned the highest numbers of CRISPRs per sample. We used MinCED on all subsequent samples because we could easily change detection parameters and the output files were in the best format. After running both the PF and SV files through MinCED, results showed there were more CRISPR arrays detected in the PF samples. For example, the 30 SV sample detected 53 CRISPR arrays; however, the 30 PF sample only detected 545 CRISPR arrays. A similar pattern was seen when comparing SV and PF samples at both stations at all depths. On average, there were seven times more CRISPR arrays detected in PF samples compared to SV samples. In conclusion, our results confirm that particle associated microbes are enriched in CRISPR sequences compared to free-living microbes in oxygen minimum zones of the ETNP. In the future, we hope to characterize the taxonomy of the microbes containing CRISPR arrays, the viral spacer sequences in the arrays, and other proteins involved in these naturally occurring CRISPR-Cas systems. Reference: Duret, M. T., Pachiadaki, M. G., Stewart, F. J., Sarode, N., Christaki, U., Monchy, S., Edgcomb, V. P. (2015). Size-fractionated diversity of eukaryotic microbial communities in the eastern tropical north pacific oxygen minimum zone. FEMS Microbial Ecology, 91(5).

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Funder Acknowledgement(s): I would like thank Dr. Sherry Seston and Dr. Frank Stewart for help in the field. I thank the Center for Academic Excellence at Alverno College for the stipend. I would also like to thank WiscAMP (Louis Stokes Alliance for Minority Participation). Funding was provided by the National Science Foundation: ROA Supplement for OCE Grant #1558916.

Faculty Advisor: Sherry Seston, Sherry.Seston@alverno.edu

Role: I was involved in the bioinformatics end of this research project. I ran the sample files through multiple different software programs. I worked on downloading different types of programs and determined how they worked on our files and what type of output files we received. I worked on figuring out how to manually change the settings of programs to get better output files as well. My main responsibility was testing different software programs designed to detect CRISPR patterns in our samples. I tested several programs and narrowed them down to the best programs based off the best output.