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. 2015 Oct 26:5:15607.
doi: 10.1038/srep15607.

Niche differentiation of bacterial communities at a millimeter scale in Shark Bay microbial mats

Affiliations

Niche differentiation of bacterial communities at a millimeter scale in Shark Bay microbial mats

Hon Lun Wong et al. Sci Rep. .

Abstract

Modern microbial mats can provide key insights into early Earth ecosystems, and Shark Bay, Australia, holds one of the best examples of these systems. Identifying the spatial distribution of microorganisms with mat depth facilitates a greater understanding of specific niches and potentially novel microbial interactions. High throughput sequencing coupled with elemental analyses and biogeochemical measurements of two distinct mat types (smooth and pustular) at a millimeter scale were undertaken in the present study. A total of 8,263,982 16S rRNA gene sequences were obtained, which were affiliated to 58 bacterial and candidate phyla. The surface of both mats were dominated by Cyanobacteria, accompanied with known or putative members of Alphaproteobacteria and Bacteroidetes. The deeper anoxic layers of smooth mats were dominated by Chloroflexi, while Alphaproteobacteria dominated the lower layers of pustular mats. In situ microelectrode measurements revealed smooth mats have a steeper profile of O2 and H2S concentrations, as well as higher oxygen production, consumption, and sulfate reduction rates. Specific elements (Mo, Mg, Mn, Fe, V, P) could be correlated with specific mat types and putative phylogenetic groups. Models are proposed for these systems suggesting putative surface anoxic niches, differential nitrogen fixing niches, and those coupled with methane metabolism.

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Conflict of interest statement

The authors declare no competing financial interests.

Figures

Figure 1
Figure 1. Vertical cross section of Shark Bay microbial mats indicating layers analysed.
(A) Smooth mat sample of 2 cm vertical depth, dissected into ten 2 mm-layers. (B) Pustular mat sample of 1 cm vertical depth, dissected into five 2 mm-layers. Lines indicate the line of sectioning.
Figure 2
Figure 2. Bacterial phyla distribution in Shark Bay microbial mats at 2 mm depth intervals.
(A) Bacterial phyla and proteobacterial classes found in different depths in smooth mats. Bacterial phyla with a relative abundance lower than 0.5% were classified into the group ‘Other’, that includes Acidobacteria, Actinobacteria, Gemmatimonadetes, Verrucomicrobia, Lentisphaerae, Chlorobi, SAR406, WS1, WS3, KSB3, Hyd24-12, OP9, Aquificae, LCP-89, FCPU426, Armatimonadetes, Tenericutes. (B) Bacterial phyla and proteobacterial classes found in different depths in pustular mats. Bacterial phyla with a relative abundance lower than 0.5% were classified into the group ‘Other’ that includes, Lentisphaerae, Chlorobi, SAR406, GN02, NKB19, Nitrospirae, PAUC34f, OD1, TM6, Dictyoglomi and SR1.
Figure 3
Figure 3. In situ depth profiles of oxygen and sulfide concentrations in Shark Bay microbial mats.
Oxygen and sulfide concentrations were measured during peak photosynthesis between noon and 2:00pm (open symbols) and the end of the night, between 4:00 and 5:00am (closed/filled symbols). Oxygen and sulfide electrodes were deployed within 1.5 mm from each other. Multiple profiles (n = 3–7) were measured and representative profiles are shown. Squares represent oxygen, triangles sulfide concentrations. (A) Smooth mat. The oxygen concentration peaks at the subsurface layer of smooth mats during daytime (1–2 mm), but is zero below 4 mm. The sulfide concentration increases from 3 mm to 8 mm, with lower concentration during the day compared to night. (B) Pustular mat. The maximum oxygen concentration is found at the subsurface layer of pustular mats during daytime (1–2 mm). Permanent anoxic conditions prevail below 5 mm. The sulfide concentration is first observed at 5 mm, increases with increasing depth and has a lower concentration during the day compared to night.
Figure 4
Figure 4. Depth profiles of oxygen production and consumption in the Shark Bay microbial mats.
Oxygen production and consumption were measured ex situ using the light-dark shift technique. Increase in [O2] in the light is a function of production (i.e., photosynthesis) and consumption (i.e., predominantly aerobic respiration, chemolithotrophic sulfide oxidation and chemical reactions). (A) Smooth mat, which show high rates of production (closed bars) and consumption (open bars) in a shallow surface horizon. (B) Pustular mat, showing low rates of O2 production and consumption that prevail down to ca. 5.5 mm depth.
Figure 5
Figure 5. Two-dimensional distribution of sulfate reduction in Shark Bay mats visualized using the silver foil technique.
Trace near the top of the panels indicates the surface of the mats. Pixels indicate hotspots of sulfate reduction; darker pixels represent higher rates. (A) Smooth mat, showing high rates, especially close to the surface of the mat, coinciding with the zone of supersaturated [O2]. (B) Pustular mat, displaying a more diffuse pixel pattern, i.e., lower rates and a sulfate reduction distribution pattern that is less concentrated in the oxic zone than was found in the smooth mat.
Figure 6
Figure 6. Principal coordinate analysis (PCoA) of Shark Bay smooth mat microbial commumity profiles from different depths.
Bray-Curtis similarity matrices of bacterial 16S rRNA gene sequence abundance derived from square-root treatment were used. The green circles represent cluster analysis, which groups layers that share 40% of phylogenetic similarity together at OTU level. PCoA clearly depicts four clustered formed within the smooth mats. The groups were designated surface, group A, group B and bottom. Bacterial phyla with strong correlation (Pearson’s p > 0.7) with respect to depth were overlaid on the PCO plot. Black lines indicate the direction of increased taxon abundance at phylum level, and the length indicates the degree of correlation of the taxa with community data. Cyanobacteria was most abundant at the surface layer, Bacteroidetes is correlated between the surface and group A, Chloroflexi and candidate phylum GN04 are stronlgy correlated to Group A, Planctomycetes showing strong relationship to Group B and Firmicutes linked to the bottom layer.
Figure 7
Figure 7. Principal coordinate analysis (PCoA) of Shark Bay pustular mats microbial community profiles from different depths.
Results indicated that pustular mat layers were stratified at OTU level into three groups, designated the surface (0–2 mm), Group C (2–8 mm) and the bottom (8–10 mm). Bacterial phyla with strong correlation (Pearson’s p > 0.7) with respect to depth were overlaid on the PCO plot. Black lines indicate direction of increased taxon abundance at phylum level (Class level for Proteobacteria), and the length indicates the degree of correlation of the taxa with community data. Alphaproteobacteria and Cyanobacteria were affiliated with the surface layer, whilst Delta-, Gammaproteobacteria, Spirochaetes and Firmicutes showed very strong correlation to Group C.
Figure 8
Figure 8. Network correlation analysis between elements (Mg, Mn, Fe and Mo) and bacteria in Shark Bay smooth mats.
(A) Magnesium. (B) Manganese. (C) Iron correlation. (D) Molybdenum. Connections are given for a strong (Pearson’s p > 0.6) and significant (p-value < 0.001) correlations. Each node represents a bacterial class or element. Alpha- and Deltaproteobacteria are presented at the order level. Green lines indicate positive correlations whilst red lines indicate negative correlations. The reoccurring bacterial taxa may indicate overlapped niches. Diamond shape indicates element whilst eclipse shapes represent bacteria. Different colours indicate elements and bacterial phyla. Yellow: element, Green: Cyanobacteria, Blue: Alphaproteobacteria Orange: Gammaproteobacteria, Pink: Deltaproteobacteria, Purple: Chloroflexi, White: Planctomycetes, Light pink: Caldithrix, Light blue: Lentisphaeria, Light grey: OP8.
Figure 9
Figure 9. Network correlation analysis between elements (P and V) and bacteria in Shark Bay pustular mats.
(A) Phosphorus correlation with bacteria, (B) Vanadium correlation with bacteria. Connections are given for a strong (Pearson’s p > 0.6) and significant (p-value < 0.001) correlations. Each node represents a bacterial class or element. Alpha- and Deltaproteobacteria were presented at the order level. Green lines indicate positive correlations whilst red lines indicate negative correlations. The reoccurring bacterial taxa may indicate overlapped niches. Diamond shape indicates element whilst eclipse shapes represent bacteria. Different colours indicate elements and bacterial phyla. Yellow: element, Green: Cyanobacteria, Red: Bacteroidetes, Blue: Alphaproteobacteria, Orange: Gammaproteobacteria, Pink: Deltaproteobacteria, Brown: Spirochaetes, Light green: Verrucomicrobia, Dark purple: Firmicutes, Dark green: SAR406.

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