Microbiome associated with Ulva lacinulata and seawater in an integrated abalone (Haliotis midae)–Ulva system with partial recirculation - Makhahlela, Nokofa (Department of Molecular and Cell Biology, 2025)
Several commercial abalone farms in South Africa grow Ulva in D-ended raceways to bioremediate farm effluent water, allowing water to be recirculated back to the abalone, while Ulva is often used as a supplementary feed source. Despite Ulva's versatility in integrated multi-trophic aquaculture (IMTA) systems, there are biosecurity concerns with the recirculation of seawater and the use of effluent-grown Ulva as abalone feed, preventing wider adoption of this technology. To better understand the potential disease risks, as well as the benefits of this practise, this study aimed to characterise the bacterial, fungal, and oomycete communities associated with seawater and Ulva in an integrated abalone-Ulva farm with 50% water recirculation. The study was conducted on a commercial abalone farm along the South-Western Cape coast of South Africa. Water (N = 40) and Ulva (N = 20) samples were collected from two different systems. One system consisted of Ulva raceway tanks that received seawater directly from the adjacent coastline, hereafter referred to as the seawater (SW) raceway or non-IMTA system. The other systems comprised raceways receiving abalone effluent water, with 50% recirculation between the abalone and Ulva raceways, referred to as abalone effluent water (AEW) or IMTA systems. Ulva samples were collected from within each raceway, whereas water samples were collected at the inlet (effluent water) and outlet (bioremediated water) of each raceway. One SW raceway (only one exists in the farm) and 4 AEW raceways were sampled in summer, autumn, winter, and spring. The first experimental chapter (Chapter 2) of the study investigated the impact of various DNA extraction kits on the quality and quantity of DNA obtained from environmental samples and compared commonly used bioinformatic pipelines for the 16S rDNA (QIIME2 vs. mothur) and ITS2 (PIPITS vs. QIIME2) genes to evaluate how different bioinformatics pipelines influence taxonomic classification and subsequent diversity analyses. In chapter 3, culture- dependent techniques were used to assess changes in the abundance of specific bacteria on Ulva and in seawater using three selective media types, namely tryptic soy agar (TSA; a general media routinely used for isolation of marine bacteria), thiosulfate-citrate-bile-sucrose (TCBS) agar (Vibrio selective), and Ulvan agar, where the primary carbohydrate of Ulva (Ulvan) was utilised as the main carbohydrate source. A non-culture-based next-generation sequencing (NGS) approach was subsequently used to describe the bacterial microbiome associated with the IMTA and non-IMTA systems, by sequencing the V4 hyper-variable region of the 16S rDNA gene. In Chapter 4, fungi and oomycetes were targeted by sequencing the internal transcriber 2 (ITS2) gene region of nuclear ribosomal DNA. Following NGS using an Illumina MiSeq sequencing platform, sequence data were processed using QIIME2 and reads were mapped against the SILVA 16S rDNA database for the bacterial microbiome and the UNITE database for the mycobiome. The summarised taxonomic abundance was assessed using MicrobiomeAnalyst. The Qiagen QIAamp DNA Micro kit and QIIME2 bioinformatic pipeline exhibited the best overall performance out of the DNA extraction kits and bioinformatic pipelines tested in chapter 2, combining high sensitivity with excellent specificity, and were both used for subsequent analyses. Chapter 3 results showed that culturable bacterial numbers were significantly higher (ANOVA; p < 0.05) in the IMTA raceway systems receiving abalone effluent water than in Ulva raceways receiving seawater directly from the adjacent coastline. Bacterial abundance on all three selective media types was also higher on Ulva blades sampled from AEW systems. However, in both systems, Ulva appeared to have a modulatory effect on the number of culturable bacteria in the water column, as indicated by the general reduction in bacteria recovered from seawater from the inlets to the outlets of both systems (p < 0.001). A greater reduction in marine bacteria between the inlet and outlet of water samples was observed in the effluent water system (IMTA) when compared to the seawater system (non- IMTA), which had lower nutrient levels. A total of 2822 individual bacterial amplicon sequence variants (ASVs) were identified, belonging to 203 family-, 305 genus-, and 320 species-level taxonomic groups. Alpha diversity analyses, based on Chao1, Shannon, and Simpson indices, showed statistically significant differences (ANOVA; p < 0.05) between the respective cohorts, where the greatest amount of diversity was observed in the water cohorts, whereas the Ulva cohorts had the lowest bacterial abundance and diversity relative to the water systems (SW and AEW). The beta diversity analyses (non-metric multidimensional scaling) showed a partial degree of overlap between the water cohorts and Ulva samples from different systems. However, a separation of IMTA and non-IMTA systems was observed. Various genera associated with marine environments were identified, predominantly belonging to Vibrio, Pseudoalteromonas, and Granulosicoccus. Differential abundance analysis (DESeq2) revealed that general marine bacteria such as Roseobacter, Granulosicoccus, and Algitalea were present in high abundance and potentially pathogenic bacteria such as Vibrio exhibited reduced abundance in both system types due to the presence of Ulva. Chapter 4 assessed the fungal communities associated with effluent water and seawater through next-generation sequencing of the ITS2 region and revealed the presence of 169 individual ASVs belonging to 54 family-, 63 genus-, and 71 species. The alpha diversity analyses based on Chao1, Shannon, and Simpson indices displayed a higher degree of fungal diversity (p < 0.001) in the water cohorts (AEW and SW) than in the Ulva cohorts (AEW_Ulva and SW_Ulva), supporting findings from the bacterial microbiome studies. Moreover, the Chao1 richness estimator was significantly (p < 0.001) higher in the AEW (AEW_In and AEW_Out) cohorts than in the SW cohorts. Beta diversity analyses, including principal co-ordinate analysis (PCoA), showed a separation between water samples (AEW and SW), collected from the two system types, which was consistent with the nonmetric multidimensional scaling (NMDS) analysis, demonstrating that sample types tended to have different fungal communities (p < 0.001). Within each cohort, ASVs commonly associated with marine environments were found, predominantly belonging to Ascomycota and Basidiomycota. Collectively, the results of this study indicate that the water cohorts exhibited greater relative abundance and diversity of bacteria and fungi than the Ulva cohorts. Furthermore, the availability of nutrients had a significant impact on the overall diversity of these microbial communities wherein the level of diversity in the IMTA system was notably higher compared to the non-IMTA system. This is because microorganisms tend to proliferate in environments characterised by high nutrient availability. The current study highlights the capability of 16S and ITS2 metabarcoding techniques for assessing microbial diversity within complex environments and has for the first time provided critical in-depth information on the microbiome of an abalone-Ulva IMTA systems and its contribution to system and animal health. Moreover, the observed positive modulatory effect of Ulva on the microbiome of the IMTA system contributes towards a growing body of literature on the benefits of including seaweed(s) in aquaculture systems and aquafeeds. The findings from this study provides critical information on biosecurity of IMTA systems, species health and system health that may promote broader uptake of these more sustainable aquaculture production technologies.