Bioinformatics: from Algorithms to Applications 2020

Heavy metal contamination in mining sites causes growth inhibition of green vegetation. Fortunately, there are photosynthetic autotrophs, the cyanobacteria that can survive in extreme conditions of the mine tailings. Surface water samples were collected from three sampling points in each Tailings Storage Facility (TSF) of Philex mines in Benguet Province, Philippines such as the re-vegetated Philex TSF1 and the currently active Philex TSF3. Genomic DNA was extracted from all water samples and subjected to shotgun sequencing. A total of 72.87 Gbases raw reads were successfully assembled using St. Petersburg genome assembler (SPAdes). A default and custom-based approaches for both CLARK v1.2.5 and Kraken2 metagenomic classifiers were used in determining taxonomic assignments to contigs using k-mer matches. Prokka was used for the rapid annotation and its output coding sequences were subjected to the evolutionary genealogy of genes-Non-supervised Orthologous Groups (eggNOG) mapper for the analysis of gene ontology. The default CLARK classified a large number of sequences across all sampling points in both re-vegetated and active mining sites. Taxonomic assignments revealed the top five cyanobacteria, namely, the unicellular Synechococcus sp., Cyanobium sp., and Gloeobacter sp., the filamentous, non-heterocystous Leptoplyngbya sp., and the filamentous, heterocystous Nostoc sp. Whereas the custom-based CLARK classified the Leptolyngbya sp., which is about 3% to 4% of the assembled contigs. On the other hand, Kraken2 results revealed the most dominant Rank Order Nostocales ranging from 0.05% to 0.63% of the classified sequences. The cyanobacterial custom-based Kraken2 revealed a large number of sequences belonging to filamentous Fischerella sp. and Trichodesmium sp. in Philex TSF1. A unicellular Microcystis and filamentous Nostoc sp., Spirulina sp., and Pseudanabaena sp. dominated the active Philex TSF3 site. CLARK was able to discriminate cyanobacteria up to the species level while the default Kraken2 classifier was able to distinguish up to the dominant Rank Order taxon. Although the custom-based CLARK detected more cyanobacteria at the Rank Order level compared to Kraken2, the former was only able to determine a single cyanobacterium at the genus level. Kraken2 revealed varying identifications of cyanobacteria in all sites while CLARK consistently identify the same cyanobacterial species among all sites. Protein-coding sequences output from Prokka that were evaluated using eggNOG revealed the genes conferring stress response to Cu2+, Zn2+, Pb2+, Cd2+, Ca2+ metal ions and smt metallothionein. These genes are reported to be responsible for the efflux/transport functions and heavy metal resistance that can be major attributes of cyanobacterial species for their survival to extreme metal conditions. Enhanced growth of Leptolyngbya sp. might also lead to probable formation of viable biological crusts initiating a re-vegetation process. This is the first report of filamentous cyanobacteria dominating the copper and gold mine tailings in Benguet Province successfully assembled and analyzed using a shotgun metagenomic approach.