Biogeography of hot spring photosynthetic microbial biofilms in Southeast Asia

doi:10.21203/rs.3.rs-3922714/v1

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Biogeography of hot spring photosynthetic microbial biofilms in Southeast Asia

https://doi.org/10.21203/rs.3.rs-3922714/v1

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Hot springs are tractable model systems in microbial ecology for investigating the interactions of photosynthetic microbial biofilms. This is because they occur across broad geographic scales, possess readily identified major abiotic variables, and are subject to minimal influence from metazoans. Despite this regional scale investigations are lacking, and major questions persist concerning the evolutionary drivers responsible for biofilm turnover at broad geographic scales. Here, we present the largest study to date, incorporating concurrent measurement of biotic and abiotic diversity and rigorous statistical analysis and modelling. We characterized 395 biofilms from neutral-alkaline hot springs spanning a 2,100km latitudinal gradient in Southeast Asia. The data clearly resolved six biogeographic regions with each defined by a core microbiome comprising specific cyanobacteria and other diverse photosynthetic, chemoheterotrophic, and chemoautotrophic taxa. Our findings demonstrated that the most influential abiotic variables (pH, conductivity, carbonate) accounted for relatively little of the observed variation in biofilm communities, and that extensive biotic interactions spanned multiple trophic levels. Importantly, we present quantitative evidence that stochasticity due to ecological drift was the most important evolutionary driver of spatial turnover at a regional scale. These insights establish a pivotal milestone in understanding of this model system, fostering enhanced testing and comparison with more intricate microbial ecosystems.

Biological sciences/Microbiology/Microbial communities/Microbial ecology

Biological sciences/Ecology/Biogeography

Biogeography

Cyanobacteria

Photosynthetic biofilms

Stochasticity

Thermophiles

The demographic patterns of distribution for microorganisms across spatial and temporal scales is key to understanding variation in their ecosystem functionality and resilience ^1,2.

Ecological theory identifies that this distribution, or biogeography, is subject to the influence of stochastic and deterministic drivers. Neutral theories predict a tendency towards random patterns in species co-occurrence and environmentally independent spatial autocorrelation ³, whilst deterministic processes due to niche partitioning (i.e. due to environmental variables) and species interaction lead to segregation in species co-occurrence ⁴. These theories were largely developed for application to a single trophic level and so complications may arise when interpreting their application to complex multi-trophic community data ⁵. A simple multi-trophic system is therefore advantageous for better elucidation on the relative role of stochastic and deterministic determinants of community assembly ⁶.

Several studies have reported large scale biogeographic patterns for microbial distribution in terrestrial ^7,8 and marine ^9,10 microbial ecosystems, although resolving direct evidence for the evolutionary drivers responsible remains a challenge in part due to the biocomplexity of these systems ¹¹. Hot springs present a potentially useful model system against which to test hypotheses in microbial biogeography, and in particular the neutral-alkaline hot springs that are widely distributed globally in tectonic landscapes ^12,13. This is because they comprise spatially well constrained habitats with readily defined major abiotic variables, their biotic component is dominated by epilithic photosynthetic microbial biofilms of relatively limited taxonomic and trophic biocomplexity ^14,15, and minimal interaction with metazoans. Photosynthetic biofilms are also a potentially widely applicable model community for use in microbial ecology, because they are widely distributed throughout diverse terrestrial ¹⁶, marine ^17,18, and engineered habitats ¹⁹ and fulfill important ecological roles ²⁰.

Previous studies of hot spring biofilms have demonstrated that the dominant photosynthetic Cyanobacteriia ^21–24 and Chloroflexia ^25–27 taxa display patterns of occurrence linked to temperature from ambient temperatures up to the thermal limit for photosynthesis at approximately 73 ^oC ¹⁵. The observation of distinct phylotypes for certain groups including Cyanobacteriia ^21,28 and Chloroflexia ^22,29 from different hot spring locations has led to the proposal that this reflects allopatric speciation due to geographic isolation and that some taxa therefore display endemism. The extent to which such patterns hold for communities across continuous broad environmental and spatial gradients to create clearly defined biogeographic regionalization, and the identification of evolutionary drivers that underly claims of biogeographic regionalization and endemism remain largely unresolved.

The lack of integrative studies for hot spring biofilms across large continuous regional geographic scales has hindered robust recognition of biogeographic regionalization and undermines support for claims of local endemicity. Addressing this knowledge gap should be regarded as an essential pre-requisite for engagement of hot springs as a model system in microbial ecology. We hypothesized that an approach which encompassed a large continuous regional geographic scale would yield valuable novel insight on the delineation of biogeographic regions and provide mechanistic insight on the drivers of observed distribution for hot spring photosynthetic microbial biofilms.

Here we report the interactions that explain microbial biogeography of 395 hot spring photosynthetic biofilms across a large regional scale (2,100km) in Southeast Asia. Hot springs in this region support prolific photosynthetic biofilms ^30–32, they are culturally important and have economic value, and yet their diversity and biogeography has not been systematically studied. We gathered an original dataset and employed rigorous statistical ecological approaches to identify the phylogenetic structure and biogeography of communities using 16S rRNA gene sequencing. We identified the interaction of abiotic and biotic factors on the observed patterns and applied statistical null models to quantify the relative influence of selection, dispersal limitation, and genetic drift in shaping community structure. The bounds of distinct biogeographic regions were delinetaed for hot spring biofilm communities, and we present evidence that stochastic influence due to ecological drift is a major evolutionary driver of observed patterns. We hypothesize that this explains the large and longstanding ‘unexplained’ variation observed in beta diversity for hot spring microbial communities. This novel insight will be essential for future development and testing of hypotheses that further address large scale spatial distributions of microorganisms in other systems.

Sample collection and environmental metadata

Detailed sampling protocols are described in the Supplementary Methods. Briefly, photosynthetic microbial biofilms (N = 395) were sampled aseptically at 40 thermally defined hot spring locations at 15 geothermal sites in Southeast Asia along a ~ 2,100km north-south transect in Southeast Asia during March-October 2022 (Fig. 1a). Abiotic variables (temperature, pH, alkalinity, conductivity, nitrate, nitrite, phosphate, sulfide) were measured on-site for each location using hand-held probes and colorimetric test kits, or visual observation (pools v flowing water, human usage of hot springs).

DNA sequencing

Detailed sequencing and quality control protocols are described in the Supplementary Methods. Briefly, DNA extraction from biofilm samples was carried out using the Powerlyzer Powersoil Kit (Qiagen) with modifications to optimize recovery from photosynthetic biofilms ³². Samples were then processed for paired-end amplicon sequencing using the NovaSeq 6000 platform (Illumina) and PE250 kits (Illumina). Taxonomic diversity was estimated using 16S rRNA gene amplicon sequencing of the V4 region, using universal primers 515F (GTGCCAGCMGCCGCGGTAA) and 806R (GGACTACHVGGGTWTCTAAT) ³³ and the PCR workflow developed by the Earth Microbiome Project ³⁴. Negative controls comprising only 500 µl RNA-later preservative solution were subjected to the same DNA extraction and sequencing workflow as experimental samples in order to test for potential contamination (N = 3). All samples were randomized for sequencing workflow to minimise any potential batch effects.

Bioinformatic analysis

Detailed bioinformatic protocols are described in the Supplementary Methods. Briefly, sequences were processed in R (version 4.2.2) ³⁵ using the DADA2 ³⁶ pipeline customized for NovaSeq data ³⁷. The processed reads were denoised (paired-end sequences merged) and chimeric reads removed before taxonomic assignment of amplicon sequence variants (ASVs) using the SILVA 16S database ^38,39 (version 138.1) with the RDP naive Bayesian classifier. The data was rarified to the minimum sequencing depth (62,868 reads per sample) and further filtered to contain ASVs with > 1% relative abundance.

Statistical analysis and data visualization

Detailed statistical analysis protocols are described in the Supplementary Methods. Briefly, alpha diversity indices comprising the Chao richness estimator, Shannon’s Index (H), Gini-Simpson Index (1-λ) and Pielou’s eveness (J) were calculated using ‘vegan’ ⁴⁰. Distance decay was plotted from unweighted UniFrac phylogenetic distances using ‘phyloseq’ ⁴¹ against pairwise geographical distances in kilometres calculated using ‘geodist’ ⁴². Taxonomic diversity was visualized using ‘Complex Heatmap’ ^43,44. Beta diversity was visualized using Principal Coordinate Analysis (PCoA) of unweighted UniFRAC distances (without transformation) using ‘phyloseq’ ⁴¹. Differential heat trees were generated using ‘metacoder’ ⁴⁵. Iris plots were generated using ‘microviz’ ⁴⁶. Core microbiomes (> 1% relative abundance and ≥ 95% prevalence) were determined using ‘microbiome’ ⁴⁷. Screening of human-associated taxa was achieved by identifying ASVs associated with twenty indicator genera ⁴⁸. Correlation of environmental variables with microbial community assembly (unweighted UniFrac) was estimated with a Mantel’s test using Pearson’s correlation coefficient and default 999 permutations using ‘microeco’ ⁴⁹. Variance partitioning was performed using ‘vegan’ ⁴⁰. Network plots were constructed using “SPIEC-EASI” (Sparse Inverse Covariance for Ecological Statistical Inference) with the 'mb' (Meinshausen-buhlmann's neighborhood selection) method using ‘netcomi’ ⁵⁰. Cluster hubs were defined by their eigenvector centrality using the ‘cluster_fast_greedy’ method. Biotic interaction between taxa were visualized as chord diagrams constructed using ‘microeco’ ⁴⁹. To generate statistical null models ⁵¹, the beta net relatedness index (betaNRI) was calculated as a standardized measure of mean phylogenetic distance to the nearest taxon in the community, and beta nearest taxon index (betaNTI) was calculated to infer contribution to ecological convergence or divergence. The Raup-Crick metric was calculated as the difference between observed and mean null community turnover using Bray-Curtis-based Raup-Crick models (RCbray) with ‘microeco’ ⁴⁹. All statistical analyses were subjected to significance testing. Analyses of variance (ANOVA), permutational Multivariate Analysis of Variance (permANOVA), Betadispersion, paired T-tests, and post-hoc Tukey’s Honest Significant Difference (HSD) were performed using ‘vegan’ ⁴⁰.

Southeast Asian hot springs are a tractable model system for interrogating photosynthetic biofilm biogeography. To provide novel ecological insight in support of the potential utility of hot springs as an ecological model system, we conducted a comprehensive sampling of 395 photosynthetic biofilms from 40 neutral-alkaline hot springs (39–66°C, pH 6.4–9) along a 2,100km transect of geothermal activity in Southeast Asia (Fig. 1A). Our approach to estimating biofilm community composition employed high-coverage sequencing of 16S rRNA genes from environmental samples (Supplementary Fig. S1) and this resulted in a quality-filtered and rarefied dataset of 24,832,860 reads and 50,538 ASVs. Alpha diversity estimates of this rarefied dataset (211–3441 ASVs per sample) revealed species richness, Pielou’s eveness, Shannon’s diversity index, and Gini-Simpson’s index displayed a weak but significant negative correlation with temperature (Supplementary Fig. S2). This indicated an overall trend towards lower alpha diversity with increased abundance of fewer (specialized) taxa as temperature increased. To better focus our subsequent ecological analyses, the rarified dataset was further stringently filtered to contain taxa with relative abundance > 1% (20,833,623 reads, 572 ASVs, 1.13% of total ASVs). This final working dataset (rarified and filtered) was subjected to statistical analysis of distribution patterns in relation to abiotic variables and biotic interactions, and ecological modelling to resolve the underlying mechanistic evolutionary drivers influencing the observed distributions.

Hot spring photosynthetic biofilms display distinct biogeographic regionalization. Resolving biogeographic patterns for hot spring photosynthetic biofilms requires expanding scale beyond the few well studied local systems so that regional biogeographic species pools can be determined as a step towards establishing global biogeographic patterns. Our dataset covered a large latitudinal gradient that elicited a strongly significant positive distance-decay correlation between community phylogenetic distance and geographical distance of the hot spring communities (Fig. 1B; linear regression: R = 0.66, P < 2.2e-16). We also estimated distance decay patterns for the different ecological groups within the biofilms and this unveiled differential responses by certain groups. The strongest distance-decay relationships were apparent for photosynthetic (R = 0.63, P < 2.2e-16) and heterotrophic (R = 0.64, P < 2.2e-16) groups compared to a relatively weaker pattern for chemoautotrophs (R = 0.45, P < 2.2e-16) (Supplementary Fig. S3). Among the photosynthetic bacterial ASVs the Cyanobacteriia accounted for the strongest distance decay signal (R = 0.61, P < 2.2e-16) whilst the Chloroflexia displayed the weakest pattern (R = 0.34, P < 2.2e-16) (Supplementary Fig. S3).

Visualization of beta diversity using PCoA ordination of unweighted UniFrac distances illustrated that communities clustered into six distinct and statistically supported biogeographic regions that we named North Thailand, Central Thailand, South Thailand, North Malaysia, South Malaysia, and Singapore (PCoA 99% confidence intervals, one-way permANOVA P < 0.001; Fig. 2A). The clustering of regions broadly matched latitudinal distance and was not autocorrelated to the sampling dates. Our study suggests that for hot springs each region may extend approximately 300km, and these largely but not exclusively reflected the different underlying geological faults despite differences in major abiotic variables between hot spring locations within each region (Supplementary Table 1). This suggested that drivers beyond deterministic influence of measured abiotic variables were also responsible for the observed regionalism.

Cyanobacterial diversity defines regional core microbiomes and biogeographic signals. Comparison of diverse hot spring biofilms across wide geographic and environmental gradients has not been undertaken and so we rationalized that doing so would yield novel insight on community assembly, including identification of characteristic taxa and core microbiomes. The Biofilms of Southeast Asian hot springs supported a highly diverse taxonomic composition comprising 28 bacterial phyla and 2 archaeal phyla. We acknowledge, however, that the Earth Microbiome Project primers we used have recognized limitations in detecting archaeal taxa and thus archaeal diversity may have been underestimated. Communities were characterized by four dominant phyla comprising the Bacteroidota, Chloroflexota, Cyanobacteria, and Gammaproteobacteria (Supplementary Fig. S4). The most abundant and prevalent class in biofilms overall were the oxygenic photoautotrophic Cyanobacteriia followed by the anoxygenic photoautotrophic/photoheterotrophic Chloroflexia thus underscoring the importance of photosynthesis to community assembly. The Chloroflexia were more abundant than the Cyanobacteriia at a small number of locations with elevated sulfide levels (≥ 0.5 ppm). Other photosynthetic bacteria, including the Chlorobia which are photosynthetic under anoxic conditions were detected at relatively few locations.

Heterotrophic ASVs were recovered from diverse phyla with known thermophilic representatives. Particularly abundant taxa at specific locations affiliated with cellulolytic genera, e.g. Cytophaga and Ignavibacterium, and chemolithoheterophic sulfur-dependent taxa, e.g., Meiothermus and Tepidimonas. Chemoautotrophic taxa notably from the Aquificae occurred patchily and were relatively more abundant only at elevated temperatures (≥ 55^oC). Archaeal ASVs were recovered predominantly from the Nanoarchaeota which are small parasitic taxa of prokaryotic hosts. Many of the hot spring locations in our study are heavily utilized nearby for varied human activities including bathing, laundry, and food preparation (Supplementary Table S1). Our sampling included only undisturbed springs however to be cautious we performed an estimate of human-associated bacteria present in the biofilms. This revealed that the occurrence of 20 common human-associated genera (Supplementary Methods) contributed to only 0.145% of the total relative abundance of ASVs.

Phylogenetic lineages that defined the observed biogeographic patterns were visualized using a differential heat tree showing pairwise comparisons of median taxon abundances between the six identified biogeographic regions (Fig. 2B, Supplementary Fig. S5). This illustrated that whilst thermophily appears to be a widespread evolutionary adaptation among diverse phyla, a few lineages appear to be particularly well adapted to photosynthetic biofilm formation in hot springs. Some groups such as the Cyanobacteria and Chloroflexota displayed differences attributed to late-branching taxonomic groups between locations, whilst for others such as the Acidobacteriota deeper lineages explained differential occurrence between locations. The tree also highlighted that some differences between regions were likely related to temperature preference, e.g., for the Aquificota which were relatively more abundant at hotter locations in North Thailand and Singapore compared to cooler locations in North Malaysia.

We then identified specific taxa that were most abundant in the biogeographic regions (Fig. 3A, Supplementary Fig. S6). Eighteen of the 25 most abundant genera were photosynthetic bacteria and trends for various ecological groups highlighted that the Cyanobacteriia displayed the most region-specificity/dominance. This emphasizes the importance of these photosynthetic bacteria as potential keystone taxa in biofilm communities and reinforces the view that they can be used as a key descriptor for specific biofilms. Core microbiome analysis revealed that whilst there was no pan-Asian core microbiome, each biogeographic region displayed a distinct core comprising 49–99% of ASVs (Fig. 3B). The Cyanobacteria, through various lineages, were part of every core microbiome underscoring biofilm dependence upon photoautotrophy for energetic and carbon input to the system. Whilst the Chloroflexota were also core to all regional microbiomes they variously comprised anoxygenic photosynthetic (e.g. Chloroflexus, Chloroploca, Roseiflexus) or non-photosynthetic (e.g. RBG-13-54-9, family Anaerolineae) taxa. Each of the core regional microbiomes supported multiple ASVs associated with nitrogen-fixing taxa and this likely reflected the low combined nitrogen levels in hot spring water (Supplementary Table S1).

Environmental variables only partially explain the observed biogeographic patterns. A core assumption in extreme environments is that strong selection pressure arises due to the influence of harsh environmental conditions. To determine potential deterministic influence of environmental variables on community assembly we performed a

Mantel’s test for biotic data against major geographic and environmental variables relevant to biofilm communities (Fig. 4A, Supplementary Table 1). Against our expectations temperature exerted comparatively low influence on overall community assembly (‘All’) and for individual ecological groups of taxa within the range 39–66 ^oC (All Mantel’s r = 0.12; Photosynthetic Mantel’s r = 0.11; Chemoheterotrophs Mantel’s r = 0.14; Chemoautotrophs Mantel’s r = 0.08; P < 0.01). Instead, we found that carbonate (Mantel’s r = 0.31; P < 0.01), conductivity (Mantel’s r = 0.5; P < 0.01), latitude (Mantel’s r = 0.65, P < 0.01), longitude (Mantel’s r = 0.58; P < 0.01), and pH (Mantel’s r = 0.35, P < 0.01) were more significant drivers influencing the biogeographic/beta diversity variation of the biofilm communities (Fig. 4A). Conductivity was also identified as a more significant influence on photosynthetic bacteria than for other ecological groups (Mantel’s r = 0.76, P < 0.01,). Weaker correlations were observed for the overall community with alkalinity (Mantel’s r = 0.10, P < 0.01), phosphate (Mantel’s r = 0.20, P < 0.01), and sulfide (Mantel’s r = 0.25; P < 0.01) (Fig. 4A).

We further evaluated and quantified the influence of the most significant and non-covariate variables (carbonate, conductivity, geographic distance [latitude], and pH) on observed biogeographic diversity through variance partitioning. Overall, this explained 29% of the observed patterns in diversity, with the largest influence exerted by latitude (9.4%) followed by pH (6.7%), conductivity (6.6%) and carbonate (4.2%) (Fig. 4B). The conditional and shared effects of these environmental variables were significant (one-way ANOVA P < 0.001). The interacting influence of all 4 factors accounted for only 0.7% of the microbial diversity patterns and was not comparable to the conditional effects of individual factors. This indicated that each of the variables acted largely independently in shaping the observed biogeographic patterns. The proportion of observed diversity patterns unexplained by environmental variables was 71%. We identified that for photosynthetic biofilms which occupy broad niches in varied neutral-alkaline hot springs, pH was also the most influential physicochemical driver and add new insight that conductivity (an indicator for the overall concentration and valence of metal ions) and carbonate are also important to photosynthetic biofilms.

Biofilms displayed evidence of complex biotic interaction networks. Abiotic variables could only account for a small amount of the variation responsible for biogeographic patterns. Recognizing the potential influence of biotic interactions in complex biofilms, we then performed a co-occurrence network analysis to identify putative biotic interactions in the communities (Fig. 5A, Supplementary Fig. S7). This revealed distinct modules of interaction with positive correlations between taxa within and between modules. Each module was characterized by at least one ASV from the photosynthetic Cyanobacteriia, Chloroflexia, and Proteobacteria. Other photosynthetic groups were restricted to fewer modules, i.e., Chloracidobacteriales (4) and Chlorobiales (1). Chemoheterotrophic bacteria were the most abundant component in all module networks, whilst chemoautotrophic ASVs displayed high variability ranging from a single ASV to 18 ASVs. We identified 29 hub ASVs denoting their putative importance in community assembly, and these comprised both photosynthetic and heterotrophic taxa (Supplementary Fig. S7). These data point to a complex suite of biotic interactions between trophic levels within biofilms, and we postulate this is driven by energetic and carbon/nitrogen inputs from the photoautotrophs.

Major interactions were further visualized using a chord diagram to highlight node associations (Fig. 5B). Seven of the 15 highest interacting genera were photosynthetic, and included known nitrogen-fixing bacteria (e.g. Leptolyngya, Pseudanabaena). The most prolific interactions occurred between Anaerolineae ASVs and other phototrophic and heterotrophic taxa suggesting the Anaerolineae occupy a key role in facilitating metabolic cooperation within the biofilms. A single chemoautotrophic taxon Venenvibrio sp. was identified to share significant co-occurrence with various Chloroflexia taxa, and this may reflect their shared growth requirement for sulfur.

Ecological drift was the dominant evolutionary process driving biogeographic regionalization. Having identified the potential influence of abiotic constraints and biotic interactions on community assembly, we then set out to quantify the relative influence of niche and neutral evolutionary drivers on the observed community structure using statistical modelling. By testing the observed data using a net relatedness index against that expected under a purely random community assembly using null models we were able to discern the influence of evolutionary drivers on observed community assembly (Fig. 6, Supplementary Fig. S8). For the inter-regional metacommunity community and region-specific communities the relatively weak influence of variable selection towards more diverse communities, or homogenizing selection towards more similar communities, supported our observation of the relatively weak influence from environmental filtering due to abiotic variables. Instead, we show that stochasticity was the most influential evolutionary driver accounting for 93% of explained beta diversity in the overall metacommunity. This implied that ecological drift which is mainly a stochastic process where diversification and genetic drift with weak influence from selection or dispersal limitation plays a major role in defining the turnover and composition that determines the biogeographic structure of the community. The dominant evolutionary drivers observed among the different ecological groups in our study corroborated our other lines of evidence on their distribution (Supplementary Fig. S8): The pronounced biogeography and response to environmental variables for Cyanobacteriia was reflected in the highest influence for variable selection (7.17%) acting on the photosynthetic group. In contrast, the heterotrophic component where certain taxa displayed a more cosmopolitan distribution displayed highest values for homogenizing selection (5.60%).

Our findings demonstrated unequivocal evidence for biogeographic regionalism of photosynthetic microbial biofilms in the hot springs of Southeast Asia. Identifying this phenomenon across a broad geographic scale among neutral-alkaline hot springs with differing physicochemical properties is an important step towards the delineation and practical use of these habitats as tractable model systems for photosynthetic biofilms in microbial ecology. Our findings demonstrated that, as for globally distributed soil samples, a relatively small number of the overall taxa dominated diverse hot spring photosynthetic microbial biofilms and overall most taxa were relatively rare ⁸. We showed that different biofilms are readily characterized by their dominant cyanobacterial component. Furthermore, nearby human usage did not significantly impact the biofilm composition and so we anticipate a wide variety of locations may be amenable to use in future studies regardless of their usage provided that appropriate quality control measures are employed. We demonstrated the complex interaction of geographic, abiotic, and biotic factors influencing community assembly and highlighted that selection due to environmental filtering plays a relatively minor role. Moreover, this study provides the first quantitative evidence for the relative influence of evolutionary forces in shaping observed patterns in thermophilic photosynthetic biofilm biogeography and identified stochastic influence via ecological drift as a major though previously unappreciated influence.

Our study revealed several important novel findings regarding community assembly and turnover in thermophilic photosynthetic biofilms. Trends in alpha diversity with temperature were consistent with well-established phenomena on the response of microorganisms to environmental stress ¹³. Several studies have demonstrated the influence of temperature on thermophilic bacterial diversity at local scales for biofilms ^25,52, water and sediment ⁵³ communities and here we demonstrate that this relationship holds across a broad regional biogeographic scale. A recent study of speciation rates in hot spring sediments identified the co-occurrence of niche specialists adapted to narrow thermal ranges and niche generalists that exhibited broader distribution and abundance ⁵⁴. They showed that the relative influence of diversification over environmental filtering decreased with increasing temperature, and this may explain our observed reduction in alpha diversity with temperature.

Against our expectations temperature exerted low influence on beta diversity in the meta-community or its various ecological groups of taxa. Instead, we demonstrated that at a regional scale the single most influential abiotic variable was pH. This finding aligns with observed patterns for planktonic aquatic and sediment geothermal systems ^53,55, thus reinforcing the notion that pH is a common driver of microbial diversity in geothermal environments and mirrors trends for other biomes such as soil ⁷. Abiotic and geographic variables only partially explained the biogeographic signal in our study (29%) and this is comparable to values observed for studies of other thermophilic habitats ^53,56. Importantly, we identified that different ecological groups responded differently to abiotic variables, and this highlights that broad community-level analyses may mask differential responses between groups of taxa.

We identified the Cyanobacteriia as abundant taxa present in all biofilms. They displayed the most variable distribution amongst all photosynthetic bacteria regarding location, and conductivity was strongly correlated with taxonomic diversity for this ecological group. This is consistent with observations for photosynthetic biofilms in mesophilic freshwater and coastal environments where cyanobacterial diversity also correlated strongly with conductivity ⁵⁷. It has been proposed that high conductivity may inhibit the proliferation of nitrogen-fixing marine cyanobacteria ⁵⁷, and our data showed that higher conductivity in hot springs also reduced occurrence of nitrogen-fixing cyanobacteria. The influence of conductivity on other bacterial groups in our study was also significant and this is consistent with observations for other mesophilic habitats ⁵⁸. Our analysis also revealed that carbonate was significantly correlated with microbial distribution, and we hypothesize that this may also reflect influence on the dominant cyanobacterial taxa. Elevated carbonate levels have been shown to increase photosynthetic activity ⁵⁹ and substrate availability for carbon fixation ⁶⁰ in mesophilic freshwater cyanobacteria. Together these findings reinforce the view that photosynthetic hot spring biofilms may be widely applicable as a model system that can be used to test hypotheses that are applicable to other systems. However, the influence of conductivity and carbonate that was evident in influencing the microbial biogeography of the tectonic neutral-alkaline hot springs in our study appear to be weak or absent as drivers in volcanic acidic hot springs where the Cyanobacteriia are absent or recovered with low abundance ⁵⁶. This highlights that the major poly-extreme abiotic factors influencing community assembly in different hot spring habitats display key differences.

A number of studies at a well-studied location, Yellowstone National Park, have highlighted that the Synechococcus biofilms typical of higher temperatures within the photic gradient invariably co-occur with anoxygenic photosynthetic Chloroflexia such as Chloroflexus and Roseiflexus, e.g., ⁶¹. Our study corroborates this co-occurrence for Thermosynechococcus biofilms in Southeast Asia but also highlights that photosynthetic Chloroflexia may not be essential taxa for biofilms that are dominated by other cyanobacterial groups. Instead, our core microbiome analysis points to a common association for all biofilm types that includes a cyanobacterial and a Chloroflexota component where the latter may or may not be photosynthetic. This was further supported by our co-occurrence network analysis and suggests that interaction may lie with a metabolic syntrophy that does not require anoxygenic photosynthesis. This suggested that non-photosynthetic processes such as sulfur cycling may be a key contribution from this phylum in biofilm assembly. This is supported by physiological linkages between photoautotrophs and sulfur-dependent metabolism in the Chloroflexota ^62–64.

The heterotrophic bacterial taxa in our hot spring biofilms displayed high variability but provided strong evidence that some co-occurrence associations occur between specific photosynthetic and heterotrophic groups, e.g., Cyanobacteriia with Aggregatillineales and Gemmataceae. A further observation revealed that the Cyanobacteriia involved in the most significant correlations belonged to genera with known nitrogen-fixing taxa suggests that these photoautotrophs are important for both carbon and nitrogen input to the community. This is consistent with observations that cyanobacteria are capable of nitrogen fixation in hot springs ^65,66. Among the heterotrophic taxa we hypothesize that the high abundance of those associated with cellulolytic activity, e.g., Cytophaga and Ignavibacterium, may reflect the large allochthonous input of plant debris to hot springs erupting in forested areas within tropical Asia ³². Some heterotrophic ASVs also indicated Southeast Asian hot springs have potential for bioprospecting thermophilic taxa for industrial use, e.g., Ideonella, a genus associated with breakdown of plastic polymers ⁶⁷. The parasitic Nanoarchaeota recovered in our study did not co-occur with commonly described archaeal hosts and this is consistent with recent evidence that they may have a broader host range than previously envisaged ⁶⁸. The temperature range for the hot springs in our study falls within the lower range for many chemoautotrophic thermophiles and their distribution was patchier compared to other ecological groups. The obligate chemoautotrophic taxa belonged largely to anaerobic sulfur reducing groups and this indicates that biofilms likely support steep environmental gradients within the biofilm structure that allow aerobic and anaerobic metabolism. Our findings are consistent with a recent observation in a Chilean hot spring that chemoautotrophic sulfate reduction occurs across a broad geothermal gradient at temperatures as low as 48^oC ⁶³.

The clear biogeographic regionalism displayed by our large original dataset fills a critical knowledge gap for Southeast Asia that accelerates the effort to map global hot spring microbial diversity. Previous studies have recorded distinct phylogenetic lineages of cyanobacteria in geographically distant hot springs ²⁸, and this mirrors observations for other ecological groups ^29,69,70. Our study highlights a predictable linear relationship between geographic and phylogenetic distance at the community level, and clearly resolved the bounds of six discrete geographic bioregions for Southeast Asian hot springs. The findings also expand the described biogeographic range for taxa within several groups including the Aquificota, Bacteroidota, Chloroflexota, Cyanobacteria, and Proteobacteria. This highlights that appropriate nuancing is required when inferring endemicity from patchy global datasets.

The relatively weak explanatory power of environmental variables is emerging as a common theme in hot spring microbial ecology across multiple habitat types ^53,56,71, and additional explanatory drivers may include geological setting and unmeasured tectonic variables ^72,73, biotic interactions, and spatial/temporal turnover related to evolutionary drivers. The biogeographic regions delineated by our study indicated interacting communities that extend over hundreds of kilometres, and this generally but not exclusively reflected association with the specific geological faults underlying the hot springs. We envisage that a combination of tectonic and physicochemical factors play a role in environmental filtering but this is unlikely to occur without influence from other ecological interactions. We presented evidence for biotic interactions between trophic levels within biofilms although it is not currently possible to quantify the influence of such interactions.

Statistical modelling using null models is a useful tool to gain insight on the influence of evolutionary drivers such as selection, dispersal limitation, and ecological drift that may be shaping microbial biogeography. Our study provides the first regional scale evidence for the relative influence of these processes on photosynthetic microbial biofilms in hot springs. The fidelity of null model outputs is strongly dependent on the scale and depth of the input matrix, and so large-scale studies such as ours offer important novel insight on regional-scale processes. A notable observation was the lack of influence from dispersal limitation and despite earlier hypotheses that this may be a major explanatory variable our data is consistent with recent studies that observed atmospheric microbial dispersal occurs across large inter-continental distances ^74,75. Despite this the influence of deterministic selection due to local abiotic variables was also low for the regional metacommunity.

The most influential process contributing to observed regional turnover was ecological drift. This novel finding suggests a regional meta-community where stochastic changes in regional population size are the major driver ⁷⁶, and was testable by our application of null models to ecological data ⁷⁷. This finding is congruent with our other multiple lines of evidence and analyses demonstrating the effects of environmental variables and biotic interactions on the meta-community. Ecological drift is a stochastic process characterized by weak selection and rare movement of taxa between communities. We envisage these evolutionary forces to operate as continuous variables in hot springs. Thus, whilst moderate levels of both movement (dispersal) and birth-death (selection) are expected, neither process is dominant. Hence, this has also been termed ‘undominated’ evolution ⁷⁷. This contrasts with the more traditional view that spatial turnover in hot springs might arise from spatial differences in abiotic conditions (variable selection), and its opposing force of homogenous selection where more consistent environmental filtering leads to greater similarity between communities. It also counters the assumption that high dispersal rates contribute to observed similarities. Our findings highlight that the 71% variance in communities that was unexplained by abiotic variables was most likely due to the stochastic influence of ecological drift. We propose that ecological drift may emerge as an explanation for the mechanistic basis of the large ‘unexplained’ variance in community structure for other biogeographic studies of hot springs, e.g., ^21,56.

We further demonstrated a differential contribution of evolutionary forces acting on the ecological groups within communities. Whilst overall and for photosynthetic and heterotrophic taxa ecological drift was the major factor, it was clear that photosynthetic taxa were subject to greater influence from variable selection than heterotrophs. This points to the Cyanobacteriia, Chloroflexia, and other phototrophs exhibiting distributions more consistent with niche specialists, compared to heterotrophic taxa tending towards being generalists with a wider niche breadth. This may emerge as a common feature of photosynthetic biofilms in diverse extreme environments given our findings also mirror the relationship observed for cyanobacteria-dominated biofilms in extreme deserts ⁶. Possible explanations for the observed stochastic influence in our study may include extinction events due to tectonic variability e.g. thermal surges ⁷⁸, or thermal variability due to monsoon flooding in the tropics ⁷⁹. We envisage these may result in genetic bottlenecks for some populations in hot springs and thus contribute to genetic drift. In addition, ancient historical legacies may contribute to stochasticity, as observed for persistent photosynthetic microbial communities in deserts and lakes ^80,81, and for chemoautotrophic bacteria in volcanic calderas where geothermal history explained more variation than extant geochemical or geographic variables ⁷³. Other non-extreme aquatic freshwater and marine photosynthetic microbial populations have also been shown to exhibit a lack of dispersal limitation and yet exhibit high levels of stochastic assembly in the absence of satisfactory explanation by environmental variables ^80,82, and this highlights a general similarity that may emerge as typical in diverse microbial systems.

Our regional atlas of thermophilic biodiversity and clear resolution of biogeographic regionalism for photosynthetic microbial biofilms in Southeast Asia accelerates the global effort to map biodiversity in this extreme ecosystem and fills a major knowledge gap for biofilms that are the most abundant microbial colonization in neutral-alkaline hot springs. It also addresses a general under-representation of studies from the Global South and so assists with efforts to decolonize the global dataset, which is an important goal towards more equitable practice in ecology ⁸³. The study revealed a previously unappreciated major role for ecological drift as a stochastic determinant of spatial turnover in communities and this helps resolve a longstanding discrepancy between the occurrence of extreme environmental stressors but their low correlation with observed diversity. The identification of the mechanistic evolutionary processes that underly observed patterns of biogeography and their compatibility with other biofilm-supporting ecosystems helps lay a solid foundation for further use of hot spring photosynthetic biofilms as a model system in microbial ecology. Fruitful areas for further research include further unraveling the functional basis of co-occurrence between ecological groups, and their response to stochastic disturbance events on a temporal scale. It is predicted from classical population models that populations closely tracking environmental stochasticity are highly prone to extinction ⁸⁴, and so this study also highlights a conservation priority for hot spring microbiota. Finally, the interrogation of photosynthetic biofilms that occur at elevated temperatures has value in understanding future trajectories for their ecology in a warming world. Overall, this study contributes significantly to the ongoing effort to unravel potential universal constraints governing microbial biogeography in photosynthetic biofilms.

Author contribution statement

K.G.C., K.M.G., S.B.P., and R.W.S. designed the study and secured funding; C.G., C.K., N.K., A.B., K.M.G., K.D.H., S.B.P., and W.R.S. conducted field sampling. C.G. and N.K. performed laboratory experiments; C.G. and S.B.P. performed data analysis; K.G.C., M.D., C.G., K.M.G., P.K.H.L., D.L., S.B.P., and W.R.S. interpreted the findings; C.G. and S.B.P. wrote the paper with input from all authors.

Supplementary Material

Supplementary methods and data for this article are available online.

Acknowledgements

The authors acknowledge support provided by the Ranong Municipality and Kamphaengphet Provincial Administrative Organization (Thailand) and National Parks Board (Singapore) for facilitating access to field locations. We thank Tancredi Caruso (University College, Dublin) for advice on null model analysis, Lynn Drescher (National University of Singapore) and Chayanard Phukhamsakda (Mae Fah Luang University) for research support, and Poh Moi Goh (National University of Singapore) for technical support. The research was funded by a Singapore Ministry of Education AcRF Tier 2 grant awarded to K.G.C., K.M.G., S.B.P., and W.R.S. (award number MOE-T2EP30123-0007). K.M.G. acknowledges additional support from the Malaysia Ministry of Higher Education Fundamental Research Grant Scheme (award number FRGS/1/2023/STG02/UTM/02/1).

Data availability statement

All DNA sequence data generated from this study has been deposited in the NCBI Sequence Read Archive under BioProject accession number PRJNA1052408. All R codes used in data processing for this study are available at https://github.com/PointingLab.

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Biogeography of hot spring photosynthetic microbial biofilms in Southeast Asia

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