Virio- and bacterioplankton microscale distributions at the sediment-water interface

Abstract

The marine sediment-water interface is an important location for microbially controlled nutrient and gas exchange processes. While microbial distributions on the sediment side of the interface are well established in many locations, the distributions of microbes on the water side of the interface are less well known. Here, we measured that distribution for marine virio- and bacterioplankton with a new two-dimensional technique. Our results revealed higher heterogeneity in sediment-water interface biomass distributions than previously reported with a greater than 45- and 2500-fold change cm(-1) found within bacterial and viral subpopulations compared to previous maxima of 1.5- and 1.4-fold cm(-1) in bacteria and viruses in the same environments. The 45-fold and 2500-fold changes were due to patches of elevated and patches of reduced viral and bacterial abundance. The bacterial and viral hotspots were found over single and multiple sample points and the two groups often coincided whilst the coldspots only occurred over single sample points and the bacterial and viral abundances showed no correlation. The total mean abundances of viruses strongly correlated with bacteria (r = 0.90, p<0.0001, n = 12) for all three microplates (n = 1350). Spatial autocorrelation analysis via Moran's I and Geary's C revealed non-random distributions in bacterial subpopulations and random distributions in viral subpopulations. The variable distributions of viral and bacterial abundance over centimetre-scale distances suggest that competition and the likelihood of viral infection are higher in the small volumes important for individual cell encounters than bulk measurements indicate. We conclude that large scale measurements are not an accurate measurement of the conditions under which microbial dynamics exist. The high variability we report indicates that few microbes experience the 'average' concentrations that are frequently measured.

Figure 1. Identification of bacterial and viral subpopulations via flow cytometry.

Flow cytometric cytograms of side-scatter light versus green fluorescence (SYBR Green) and histograms of green fluorescence (SYBR Green). Noarlunga: A cytogram B histogram; St Kilda: C cytogram D histogram showing two distinct viral populations (VLP 1 and VLP 2) and three distinct bacterial populations (LDNA, HDNA 1 and HDNA 2).

Figure 2. Comparison of total mean bacterial and viral populations at Noarlunga via vertical depth profiles.

Total mean bacterial and total mean viral population abundance within all three microplates. A Noarlunga, (n = 1350). B St Kilda, (n = 1045). Error bars represent the 95% confidence intervals obtained from all three replicates (n = 12).

Figure 3. Single vertical profile of VLP 1 and LDNA populations at Noarlunga.

A Microplate three showing little to no association. B Microplate one showing association. Gap in profile indicates a missing data point.

Figure 4. Rank abundance graphs used to differentiate hotspot and coldspot values from background values.

One linear trend within the background values were characteristic of St Kilda whilst two linear trends were primarily seen at Noarlunga. St Kilda: A VLP 1, microplate 2. B HDNA 1, microplate 2. Noarlunga: C VLP 1, microplate 3. D HDNA 2, microplate 2.

Figure 5. Two-dimensional contour plots showing the highest change in heterogeneity due to the presence of hotspots and coldspots within bacterial and viral subpopulations.

Hotspots and coldspots seen across a distance of 6.3×11.3 cm using Surfer 10 (Golden Software, Inc.). Noarlunga: A VLP 2 showing a 2585-fold change in abundance over 0.9 cm. B LDNA showing a 12.9-fold change in abundance over 0.9 cm. St Kilda: C VLP 1 showing a maximum 10.52-fold change in heterogeneity seen over 0.9 cm. D HDNA 2 showing a maximum 45.2-fold change in heterogeneity seen over 0.9 cm. There were a range of heterogeneities over 0.9 cm (Fig. S4) indicating a variety of intensities for hotspots and coldspots. Abundance levels are indicated by a colour intensity scale in units of cells/particles ml⁻¹. Solid red circles indicate areas of abundance higher than the maximum contour level selected. A minimum contour interval value of at least 1000 was chosen based on maximum machine error. The faint gridlines show sample interval.

Figure 6. Two-dimensional contour plots showing surface gradients within bacterial subpopulations at St Kilda.

Surface gradients seen across a distance of 6.3×11.3 cm using Surfer 10 (Golden Software, Inc.). Microbial abundance levels are indicated by a colour intensity scale in units of cells ml⁻¹. A HDNA 2, microplate 2. B LDNA, microplate 2. Solid red circles indicate areas of abundance higher than the maximum contour level selected. A minimum contour interval value of at least 1000 was chosen based on maximum machine error. The faint gridlines show sample interval.

Figure 7. Significant Moran correlograms of non-randomly distributed bacterial subpopulations at St Kilda.

A LDNA, microplate 2. B LDNA, microplate 3. C HDNA 2, microplate 2. D Total bacteria, microplate 2. Filled and unfilled data points indicate significant and non-significant Moran’s I values (p≤0.01). Only sample points with ≥30 pairs of values were included.