A semester long project conducted in the class BIOL340 at Rochester Institute of Technology with the rest of the class. The project involved the isolation of bacteria from wild fungi collected from Black Creek, NY (43.0721° N, 77.8076° W). These bacteria were then sequenced to determine their secondary metabolite production.
Wild fungi were gathered from Black Creek Park in NY and identified using Mushrooms of Northeast North America: Midwest to New England by Barron. Bacteria were then isolated from the fungi in 4 media types: LB, TS, PD, and R2A broth. Single colonies were then isolated on matching media plates and subsequently cultured for V3/V4 region PCR and sanger sequencing.
A DNeasy Ultraclean Microbial PCR Kit was used with the forward primer 341F (5’-CCTACGGGNGGCWGCAG-3’) and the reverse primer 805R (5’-GACTACHVGGGTATCTAATCC-3’) to amplify the V3/V4 regions of the 16sRNA. The resulting samples were then run on an agarose gel to determine purity and concentration was assessed using the Nanodrop and Qubit. Due to the low detection range for the Qubit, 1:10 dilutions of the samples were also analyzed. The samples were then send for sanger sequencing.
Using the results of the sanger sequencing the individual genera and possible families were identified using the Basic Local Alignment Search Tool (BLAST). This allowed for the class to select strains for further sequencing using the Illumina MiSeq.
The genomic library of the selected strains were prepared using the Illumina Nextera XT DNA Library Prep Kit. The gDNA samples were normalized to 0.2ng/ul each prior to tagmentation. Following the clean-up step of the protocol the libraries were checked using the Bioanalyzer in a DNA1000 chip. The libraries were normalized to a final loading concentration of 10pM and sequenced using an Illumina V3 600 Cycle Cartirtige with 2x250 paired-end reads.
The paired reads were assembled into a whole genome sequencing using Unicycler V0.4.8.0 within Galaxy V19.09.rc1 while filtering out contigs smaller than 200bp. Quast V5.0.2 was used to generate statistics on the final assemblies. The assemblies were submitted as whole-genome shotgun sequences to Genbank for annotation using the NCBI Prokaryotic Genome Assembly Pipeline to identify Open Reading Frames (ORFs), rRNAs, and tRNAs.
The 16S regions of the sequences were used to identify the bacterial genus using the Ribosomal Database Project (RDP) V11.5. The whole genome sequence was also used to identify the bacterial genus using Type (Strain) Genome Server (TYGS) V182. The Orthologous Average Nucleotide Identity Tool (OAT) V0.93.1 was then used to determine the relatedness of the selected strains one such result is shown to the right.
A search for phage sequences was performed using Phaster was run to determine if the presence of phage genomes could account for differences in genomic sequence of those related by 97.39%. The result of which indicated that a 37Kb phage sequence in RIT702 could potentially account for the difference between the two genomes.
The full alignments were uploaded to the antiSMASH V5.1 online program to identify potential secondary metabolite production (Blin, 2019). The program was set to run KnownClusterBlast, ClusterBlast, SubClusterBlast and ActiveSiteFinder.
Strain RIT694 was identified as a Bacillus sp., RIT697 as an Unc. Enterobacteriaceae, RIT698 was an Acinetobacter guillouiae, and RIT702 was also an Unc. Enterobacteriaceae
The small difference between RIT702 and RIT697 could potentially be accounted for by a 37Kb fully intact phage sequence.
While antiSMASH did not report the presence of any antibiotic resistance clusters in any of the isolates it did report the presence of bacteriocins in RIT694 and homoserine lactones in RIT697 and 702. Homoserine lactones have the potential to be quorum sensing molecules that allow for increased pathogenicity via communication with neighboring bacteria (Landman, 2018). In contrast bacteriocins are ribosomally synthesized molecules that inhibit the growth of neighboring bacteria (Lopetuso, 2019).