Deciphering the biosynthetic landscape of biofilms in glacier-fed streams

Abstract

Glacier-fed streams are permanently cold, ultra-oligotrophic, and physically unstable environments, yet microbial life thrives in benthic biofilm communities. Within biofilms, microorganisms rely on secondary metabolites for communication and competition. However, the diversity and genetic potential of secondary metabolites in glacier-fed stream biofilms remain poorly understood. In this study, we present the first large-scale exploration of biosynthetic gene clusters (BGCs) from benthic glacier-fed stream biofilms sampled by the Vanishing Glaciers project from the world's major mountain ranges. We found a remarkable diversity of BGCs, with more than 8,000 of them identified within 2,868 prokaryotic metagenome-assembled genomes, some of them potentially conferring ecological advantages, such as UV protection and quorum sensing. The BGCs were distinct from those sourced from other aquatic microbiomes, with over 40% of them being novel. The glacier-fed stream BGCs exhibited the highest similarity to BGCs from glacier microbiomes. BGC composition displayed geographic patterns and correlated with prokaryotic alpha diversity. We also found that BGC diversity was positively associated with benthic chlorophyll a and prokaryotic diversity, indicative of more biotic interactions in more extensive biofilms. Our study provides new insights into a hitherto poorly explored microbial ecosystem, which is now changing at a rapid pace as glaciers are shrinking due to climate change.

Importance: Glacier-fed streams are characterized by low temperatures, high turbidity, and high flow. They host a unique microbiome within biofilms, which form the foundation of the food web and contribute significantly to biogeochemical cycles. Our investigation into secondary metabolites, which likely play an important role in these complex ecosystems, found a unique genetic potential distinct from other aquatic environments. We found the potential to synthesize several secondary metabolites, which may confer ecological advantages, such as UV protection and quorum sensing. This biosynthetic diversity was positively associated with the abundance and complexity of the microbial community, as well as concentrations of chlorophyll a. In the face of climate change, our study offers new insights into a vanishing ecosystem.

Keywords: biofilms; glacier-fed streams; microbiomes; secondary metabolites.

Fig 1

The biosynthetic potential in glacier-fed streams assessed based on the number of BGCs per MAG, BGC category composition, and BGC novelty in the most abundant bacterial phyla. On the x-axis are the different phyla (BGC number/MAG number) ordered by their average number of BGCs per genome. Phyla with less than 10 BGCs are excluded. The x-axis is the same for all subfigures A–C. (A) The number of BGCs per MAG. The blue horizontal line denotes the average number of BGCs across all MAGs across all phyla. (B) Relative prevalence of BGC categories: non-ribosomal peptide synthetase (NRPS), polyketide synthase (PKS), ribosomally synthesized and post-translationally modified peptides (RIPPs), PKS–NPRS hybrids, terpenes, and others (C) Percentage of novel BGCs. Novelty is determined by a comparison to known BGCs sourced from the NCBI database using BiG-SLiCE. The standard threshold of a Euclidian distance (based on identified Pfam domains) >900 was taken.

Fig 2

Comparison of BGC diversity between different aquatic microbiomes and glacier fed streams. (A) Relative prevalence of the BGC categories in the investigated microbiomes. Below the ratio of detected BGCs to MAGs in the respective microbiomes. (B) Overlap of the biosynthetic potential between the different microbiomes (rows) displayed by using an UpSet plot based on GCF presence and absence, where each column depicts an intersection between one or more microbiomes. The bar chart at the top represents the size of the respective intersection, with the exact number of GCFs written at the top. The intersections are ordered by their respective size, and intersections with >40 GCFs are displayed. The bar chart at left side gives the total number of GCFs in the respective microbiomes. GCFs that are only present in one microbiome are marked as unique (blue), and the percentage of unique GCFs per microbiome is written in white.

Fig 3

Diversity of the GCFs in the glacier-fed stream biofilms. (A) Alpha diversity of GCFs in different mountain ranges and epilithic and epipsammic biofilms. (B) Significant correlations of GCF Shannon alpha diversity to chlorophyll a and bacterial abundances. (C) Correlations of GCF Shannon alpha diversity to 16S prokaryotic and 18S photosynthetic eukaryotic Shannon diversity. (D) Beta diversity of GCF abundances using an NMDS plot based on Bray–Curtis distances, coloured by biofilm type. (E) Beta diversity of GCF abundances in only the epipsammic biofilms using an NMDS plot based on Bray–Curtis distances, colored by mountain range.

Fig 4

Distance–decay curves of biosynthetic, prokaryotic, and photosynthetic eukaryote diversity. The respective community similarity (1 − Bray–Curtis dissimilarity) is plotted against the distances between samples. (Epipsammic samples only). The slope of linear model between the community similarity and the distance is displayed in the top right corner, with the adjusted P-value of the correlation denoted by stars (*** P < 0.001, **P = 0.001–0.01, *P = 0.01–0.05).

Fig 5

Investigation of environmental influences on the biosynthetic potential and the microbial community by differential abundance analysis of GCFs (A) and MAGs (B) in epipsammic biofilms for selected environmental variables. Color coded by their BGC category or phylum attribution. Positively associated GCFs/MAGs are always on the left for each environmental variable, and negatively associated are always on the right (same x-axis for all the subplots). (C) Number of BGCs per genome in the differentially enriched MAGs. Testing the difference in the number of BGCs per genome between positively and negatively enriched MAGs resulted in the P-values displayed at the top of the bracket (t-test, adjusted for multiple testing).

Fig 6

The abundance of secondary metabolites of interest between epilithic and epipsammic biofilms, and up- and downstream reaches (red and green). In the header in brackets, the number of GCFs per secondary metabolite. Testing the difference in abundance between the epilithic and epipsammic biofilms (t-test) and upstream vs downstream epipsammic biofilms (paired t-test) resulted in the displayed P-values (adjusted for multiple testing).