Alternative approaches to identify core bacteria in Fucus distichus microbiome and assess their distribution and host-specificity

Abstract

Background Identifying meaningful ecological associations between host and components of the microbiome is challenging. This is especially true for hosts such as marine macroalgae where the taxonomic composition of the microbiome is highly diverse and variable in space and time. Identifying core taxa is one way forward but there are many methods and thresholds in use. This study leverages a large dataset of microbial communities associated with the widespread brown macroalga, Fucus distichus, across sites and years on one island in British Columbia, Canada. We compare three different methodological approaches to identify core taxa at the amplicon sequence variant (ASV) level from this dataset: (1) frequency analysis of taxa on F. distichus performed over the whole dataset, (2) indicator species analysis (IndVal) over the whole dataset that identifies frequent taxa that are enriched on F. distichus in comparison to the local environment, and (3) a two-step IndVal method that identifies taxa that are consistently enriched on F. distichus across sites and time points. We then investigated a F. distichus time-series dataset to see if those core taxa are seasonally consistent on another remote island in British Columbia, Canada. We then evaluate host-specificity of the identified F. distichus core ASVs using comparative data from 32 other macroalgal species sampled at one of the sites. Results We show that a handful of core ASVs are consistently identified by both frequency analysis and IndVal approaches with alternative definitions, although no ASVs were always present on F. distichus and IndVal identified a diverse array of F. distichus indicator taxa across sites on Calvert Island in multiple years. Frequency analysis captured a broader suit of taxa, while IndVal was better at identifying host-specific microbes. Finally, two-step IndVal identified hundreds of indicator ASVs for particular sites/timepoints but only 12 that were indicators in a majority (> 6 out of 11) of sites/timepoints. Ten of these ASVs were also indicators on Quadra Island, 250 km away. Many F. distichus-core ASVs are generally found on multiple macroalgal species, while a few ASVs are highly specific to F. distichus. Conclusions Different methodological approaches with variable set thresholds influence core identification, but a handful of core taxa are apparently identifiable as they are widespread and temporally associated with F. distichus and enriched in comparison to the environment. Moreover, we show that many of these core ASVs of F. distichus are found on multiple macroalgal hosts, indicating that most occupy a macroalgal generalist niche rather than forming highly specialized associations with F. distichus. Further studies should test whether macroalgal generalists or specialists are more likely to engage in biologically important exchanges with host.

Host population crashes disrupt the diversity of associated marine microbiomes

“…Dominant microbial taxa found across both disturbed and non‐disturbed populations were largely aligned with those previously identified in other macroalgae (Lu et al, 2023; Park et al, 2022) and other Durvillaea populations (Pearman et al, 2023). The size of the core microbiome differed between disturbance classes, with 47 core ASVs in the non‐disturbed locations, while 31 core ASVs were found in disturbed locations.…”

The Arctic summer microbiome across Fram Strait: Depth, longitude, and substrate concentrations structure microbial diversity in the euphotic zone

“…The surface signature was underlined by higher proportions of SAR11 clade Ia and SAR86. Detection of Roseibacillus and Saprospiraceae indicates connectivity with nearby Svalbard fjords (Delpech et al, 2021; Park et al, 2022).…”

Non‐native hosts of an invasive seaweed holobiont have more stable microbial communities compared to native hosts in response to thermal stress

“…Also in the present experiment, it was detected in high numbers as epiphyte and correlated positively with growth (Figure S3C). Granulosicoccus species have also been detected in high abundances (Ramirez‐Puebla et al, 2020) or as core microbiota (Park et al, 2022) on other seaweeds. OTU8 (classified to Schizothrix ) is a core OTU (Bonthond et al, 2020) correlating negatively with thallus brittleness, which could hint at a protective role within the holobiont (Saha & Weinberger, 2019).…”

“…The univariate GLMMs for host performance traits and diversity measures were fitted using the R package lme4 (Bates et al, 2015). NMDS was conducted using the R package vegan (Oksanen et al, 2017). The mGLMs were run using the R package mvabund (Wang et al, 2012).…”

“…The NMDS was then conducted on the residuals of the models that were back-transformed to the original scale. Group centroids and their 95% confidence regions were computed using the R package vegan (Oksanen et al, 2017). Statistics for the community response were obtained from the mGLM fitted on the postdisturbance dataset that included all variables (i.e., time, temperature, range, the corresponding interactions, and population identity nested in range), using the anova.manyglm function from the mvabund package, bootstrapping the univariate models with 500 iterations and individual identity as a blocking factor.…”