Genome Report of Microcystis aeruginosa Isolated from a Wetland in Llanquihue, Chile: An Integrated One Health Approach

Daniel A Medina^*Francisca Paredes-CárcamoDanilo Contreras-SánchezJavier Campanini-Salinas

• Universidad San Sebastián, Puerto Montt, Chile

Wetlands are complex ecosystems increasingly impacted by human activities, global warming, and extreme weather events, which intensify thermal stratification of water columns, affecting water quality and promoting the growth of microorganisms such as cyanobacteria (1,2). From a One Health perspective, the changes associated with the proliferation of cyanobacteria have critical implications for environmental, human, and animal health (3). Certain cyanobacteria, including Microcystis aeruginosa, can produce cyanotoxins, posing health risks to humans and animals while disrupting aquatic ecosystems, compromising water quality, and reducing biodiversity (4). For these reasons, it is necessary to have methodologies that allow describing the potential biological risks that cyanobacterial blooms may constitute. M. aeruginosa is a dominant species in toxic cyanobacterial blooms, and some strains are significant producers of cyanotoxins, particularly known as microcystins (5). This toxin is a cyclic heptapeptide with various isoforms that accumulates in the liver and kidneys of mammals, exerting its toxicity through the inhibition of phosphatases PP1 and PP2A (6). Exposure to toxin can occur through ingestion of contaminated water, direct contact, or inhalation, potentially causing severe health issues such as hepatoenteritis, symptomatic pneumonia, and dermatitis. Microcystins can bioaccumulate in aquatic organisms, such as mussels, crustaceans, and fish, leading to trophic transfer and posing risks to both human health and marine biodiversity (7)(8)(9).The ability of M. aeruginosa to produce microcystins is largely determined by the presence and expression of genes within the mcy operon, the composition of which can vary among strains (10). In addition, microcystin production is also influenced by environmental factors such as nutrient availability, light, and salinity (11). Determining the presence of these genes in places where M. aeruginosa is present allows action to be taken against potential biological risks in which microcystins can affect animal and human health. The genetic diversity found among species and strains of the Microcystis genus can be studied through genome reconstruction and functional analysis. Genome sequencing and analysis provide valuable tools for studying the genetic diversity of Microcystis and identifying genes involved in microcystin production, allowing for a better understanding of their ecology, toxicological impact, and implications for One Health (12). This report presents the genome assembly of M. aeruginosa isolated from the El Loto urban wetland in Llanquihue, Chile. The primary aim was to investigate the presence of genes associated with microcystin production (belonging to the cluster mcy) and other functional factors to assess the potential risks posed by this strain from a One Health perspective. A total of 7 whole genome sequencing data were obtained from 5 isolates of M. aeruginosa obtained on May 22, 2023 (Figure 1A-C), from the urban wetland, namely "El Loto", located in the city of Llanquihue, Chile [41°15'16.4 "S 73°00'32.9 "W]. This wetland has the particularity of presenting a cyanobacteria bloom (13,14) (https://doi.org/10.1080/24749508.2025.2535067). Microbial isolates of M. aeruginosa were obtained using BG-11 media (Sigma-Aldrich, C306) and previously identified as M. aeruginosa (14). A total of 5 isolates with microscopic morphology of M. aeruginosa (Figure 1C), were obtained from different culture plates, which were used to extract total bacterial DNA using a modified protocol consisting of phenol-chloroform-isoamilic-acohol (25:24:1) and microbial rupture by means of glass beads and enzymatic digestion (15). The DNA concentration obtained was measured using Qubit 4 Fluorometer (Invitrogen). The M. aeruginosa taxonomy of the 5 isolates was confirmed using the specific 16S rRNA cyanobacteria primers (CYA359F [5'-GGGGAATYTTCCGCAATGGG-3'] and CYA781R [5'-GACTACWGGGGTATCTAATCCCWTT-3'] as previously described (16). PCR products were analyzed using Sanger sequencing with an ABI PRISM 3500 XL sequencer (Applied Biosystems, USA), and the obtained sequences were used for BLAST analysis (17). Whole-genome sequencing was done using seven total DNA extractions, repeating two of the five microbial sample isolates to improve sequence confidence and data robustness. The samples were sequenced using the Illumina Novaseq 6000 platform at 2×150 paired-end, performed by the provider Novogene Corporation Inc. (Sacramento, USA). Raw sequences generated were filtered and trimmed using Trimmomatic (18) utilizing the following parameters: LEADING:20, TRAILING:20, SLIDINGWINDOW:5:20, AVGQUAL:20, and MINLEN:90, followed by the application of Bowtie2 to screen out the contaminant DNA sequences from human and intestinal viruses (19,20). Because the sequenced samples are biologically similar, a joint co-assembly strategy was performed with all the reads combined into a single forward and reverse fastq file. Then, the reads were assembled in contigs using the Megahit bioinformatic tool (21). Contaminant contigs and fragments below 1000 bp were eliminated, and the resultant contigs were ordered, reoriented, and used to scaffold assembly by means of RagTag software (22), using the M. aeruginosa NIES-88 genome assembly as reference genome (NCBI Accession number AP024565). Gap filling between adjacent scaffolds and error refining were performed using the Pilon bioinformatic tool, comparing the assembled scaffold with the original raw data reads (18). The quality of the scaffolds obtained was assessed using QUAST (23), resulting in 48 scaffolds with a total length of 5.04 Mb and N50 of 4,8 Mb (Figure 1D). A consensus sequence of the genome was obtained using samtools and mpileup bioinformatic tools (24), comparing the scaffolds with the NIES-88 reference genome. The coverage of the consensus sequence regarding NIES-88 was inspected using qualimap (25) and samtools (24), obtaining a median coverage of 1. Alternatively, individual genomes were obtained from each raw data sequenced individually, following the same pipeline. Using the co-assembly genome, a functional search of antimicrobial resistance, virulence, and mcy genes A, B, C, D, E, and F was performed using ABRicate (26) using the NCBI AMRFinder (27), VFDB (28), and a mcy genes custom database built following ABRicate instructions using mcy sequences found in the NCBI. Sequences related to mcy genes were identified by ABRicate in the assembled genome (mcyA, mcyC, mcyD, mcyE, mcyF). Additionally, a functional analysis and annotation were performed with Prokka (29), allowing the identification of genes involved in the adaptation of M. aeruginosa to adverse environmental conditions. Among these, genes related to the response to iron limitation (isiA and isiB), the reduction of metabolism in the presence of limited resources (vapC2), the regulation of cellular homeostasis (pipB2), the efflux systems that confer resistance to environmental toxicity (mdtA and mdtC), and DNA repair against damage caused by environmental factors, such as UV radiation and oxidative stress (recA) were recognized. These adaptive mechanisms are essential for the resistance and survival of M. aeruginosa in water bodies, facilitating its proliferation and bloom formation in extreme environmental conditions and under resource limitation. Finally, the assembled genome was compared with others bacterial completes genomes to determine the similarity between them using 8 M. aeruginosa genomes (including the assembled genome in this study, namely as LOTO), 2 other cyanobacteria's genomes (namely Microcystis wesenbergii and Microcystis panniformis), 2 Escherichia coli genomes, and 4 Mycobacterium genomes from different species, by means of genomic Average Nucleotide Identity (ANIm) based on MUMmer3, to perform pairwise comparisons between each possible pair of input genomes, to identify homologous (alignable) regions, included in pyani software (30). All M. aeruginosa genomes resulted in a high identity cluster (Figure 1E), confirming the taxonomy of the assembled genome. Harmful genomic elements were found, this study constitutes an example of genome analysis to evaluate the potential biohazard of cyano blooms in water ecosystems using genomics, bioinformatics and microbial tools, as integrated One Health approach.