An experimental test of the influence of microbial manipulation on sugar kelp (Saccharina latissima) supports the core influences host function hypothesis

Abstract

Kelp are valued for a wide range of commercial products and their role in kelp forest ecosystems, making kelp cultivation a rapidly expanding economic sector. Microbes associated with kelp and other macroalgae play a critical role in processes such as nutrient exchange, chemical signaling, and defense against pathogens. Thus, manipulating the microbiome to enhance macroalgal growth and resilience is a promising yet underexplored approach for sustainable kelp cultivation. The core microbiome hypothesis suggests that the bacteria that are consistently found on a host (the core microbes) are likely to have a disproportionate impact on host biology, making them an attractive target for microbiome manipulation. In this study, we surveyed wild Saccharina latissima and their surrounding environment to identify core bacterial taxa, compared them to cultivated kelp, and experimentally tested how cultured bacterial isolates affect kelp development. We found that core bacteria are nearly absent in cultivated juvenile sporophytes in nurseries, but eventually colonize them after outplanting to ocean farm sites. Bacterial inoculants had both positive and negative effects on kelp development. Notably, the strength of association of a bacterial genus with kelp in the wild positively correlated with its impact on gametophyte settlement and sporophyte development in kelp co-culture experiments, aligning with predictions from the core microbiome influences host function hypothesis. These findings affirm the feasibility of using microbial manipulations to improve current kelp aquaculture practices and provide a framework for developing these techniques.

Importance: Microorganisms consistently associated with hosts are widely thought to be more likely to impact host biology and health. However, this intuitive concept has not been experimentally evaluated. This study formalizes this concept as the Core Microbiome Influences Host Function hypothesis and experimentally tests this hypothesis in sugar kelp (Saccharina). The distribution of bacteria on wild kelp and core microbes was first identified by compiling a broad dataset of the kelp microbiome sampled across space and time. Bacterial cultures were isolated from the surface of sugar kelp and individually grown in laboratory co-culture with sugar kelp spores to assess the ability of bacterial isolates to influence kelp growth and development. In support of the core influences host function hypothesis, isolates belonging to bacterial genera that are more strongly associated with wild sugar kelp are more likely to influence development in laboratory experiments.

Keywords: Saccharina latissima; bacterial isolation; core microbiome; kelp cultivation; microbial ecology; microbial manipulation.

Fig 1

The experimental design for bacterial sampling and co-culturing Saccharina with bacterial isolates. (A) Bacterial communities associated with Saccharina were sampled from various out-planted sites across British Columbia and northern Washington. Samples from Loughborough Inlet sites 1 and 2 (LI), East West Bay (EWB), Talbot (TAL), Interfor (INT), and Hood Head Farm (HHF) were taken by Davis et al. (57). Additional samples from Bamfield (BAM) were taken for this study. (B) Bacterial communities associated with wild Saccharina were sampled biweekly from April to July 2021 at various sites across Vancouver, BC. Additional samples were taken monthly from the Girl in a Wetsuit (GWS) site from July 2020 to July 2021. Bacterial isolates used in part C were collected from GWS. Maps in panels A and B were created in Rstudio with the “rnaturalearth,” “sf,” and “ggplot2” packages. (C) (1) Saccharina zoospores were released and cultured with purified bacterial isolates (2) in the laboratory to assess the impact of different bacterial isolates on the early development of Saccharina. (3) Bacterial communities associated with Saccharina were analyzed using bioinformatics techniques to identify core bacterial taxa and quantify the strength of bacterial associations with Saccharina using IndVal analysis. Graphic made using Canva.

Fig 2

NMDS plots using Bray-Curtis dissimilarities and a taxa plot were made to compare the microbiota found on different Saccharina populations and on surrounding abiotic substrates. (A) Bacterial community composition on Saccharina compared to rocky substrate and seawater in the surrounding environment. (B) Bacterial community composition on Saccharina samples collected from wild populations throughout the year in comparison to samples from cultivated Saccharina in the nursery and ocean farm sites. (C) The most abundant taxa found on several outplanted and wild Saccharina populations. Abundances are summed across all samples collected at the same timepoint for a given site.

Fig 3

Distribution of core taxa Saccharina in four intertidal sites (GWS, TB, LHP, and SCP). The dots represent the average relative abundance and frequency of core bacterial taxa across four locations over time. The y-axis displays the core bacterial taxa identified at the genus level in blue text and at the ASV level in black text, along with the overall frequency percentage of the core bacteria. “Other ASVs” refer to the summed abundance of all non-core ASVs assigned to the core bacterial genus. The monthly seawater and rock sample data were aggregated across all dates.

Fig 4

The average relative abundance and frequency of Saccharina core bacterial taxa identified from wild populations (shown in Fig. 3) on cultivated kelp. Cultivated kelp samples come from three nurseries and seven ocean farm sites. Ocean farm sites, except BAM, were sampled at 2, 4, and 6 months after outplanting, as described in reference . Two-month samples failed for all INT and TAL samples, and all but one sample for LI2 and EWB. See Fig. 3 for additional notes.

Fig 5

Volcano plot depicting the effect of bacterial inoculants on Saccharina across all four trials. The x-axis depicts the log2 fold change for each bacterial isolate compared to the control groups in each experimental trial on (A) gametophyte percent cover and (B) the number of sporophytes produced. The y-axis displays log10 Bonferroni-corrected P-value from two-tailed t-tests comparing the control group to co-culture treatments with each bacterial isolate. Isolates are colored by co-culture trial, and gray if their effect was not significant.

Fig 6

The relationship between the strength of association with wild Saccharina (IndVal statistic) and the effects of bacterial inoculation on Saccharina development. The y-axis displays the log2 fold changes for each bacterial isolate compared to the control groups in each experimental trial, for the number of sporophytes (A) and gametophyte percent coverage (B). Points and trend lines are colored co-culture trial, while black trend lines represent the relationship across all trials.

Fig 7

The relationship between isolated auxin production and distribution and effect in co-culture. The x-axis shows whether auxin was produced in a detectable amount in IAA-screening experiments. The y-axis shows (A) the strength of an isolate’s association with Saccharina (IndVal stat), and the isolates’ effect in co-culture on the number of sporophytes produced (B) or the change in gametophyte coverage (C). Significant differences between group averages as determined by a t-test are noted by letter.