# Microbial community structure is stratified at the millimeter-scale across the soil-water interface

Yu-Jia Cai, Zi-Ao Liu, Sha Zhang, Hao Liu, Graeme W. Nicol, Zheng Chen

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Yu-Jia Cai, Zi-Ao Liu, Sha Zhang, Hao Liu, Graeme W. Nicol, et al.. Microbial community structure is stratified at the millimeter-scale across the soil-water interface. ISME Communications, 2022, 2 (1), pp.53. 10.1038/s43705-022-00138-z. hal-03721059

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# Microbial community structure is stratified at the millimeter-scale across the soil-water interface

Yu-Jia Cai<fnref n="1" />,², Zi-Ao Liu<fnref n="1" />, Sha Zhang<fnref n="1" />,², Hao Liu<fnref n="1" />,², Graeme W. Nicol ID ³ and Zheng Chen ID <fnref n="1" />✉

© The Author(s) 2022

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Soil-water interfaces (SWI) are biogeochemical hotspots characterized by millimeter-scale redox gradients, indicating that parallel changes are also present in microbial community structure and activity. However, soil-based analyses of microbial community structure typically examine bulk samples and seldom consider variation at a scale relevant to changes in environmental conditions. Here we presented a study that aimed to describe millimeter-scale variance in both microbial community structure and physicochemical properties in a lab flooded soil. At this fine-scale resolution, the stratification of biogeochemical properties (e.g., redox potential, nitrate concentration) was consistent with the structure of the active microbial community with clear shifts in the relative abundance of transcriptionally active populations associated with changing redox conditions. Our results demonstrate that spatial scale should be carefully considered when investigating ecological mechanisms that influence soil microbial community structures.

ISME Communications; https://doi.org/10.1038/s43705-022-00138-z

The soil-water interface (SWI) is a biogeochemical hotspot where aerobic microbes are enriched at the top and respire oxygen from the surface water, with microbes capable of anaerobic respiration residing toward the bottom [1]. Physicochemical gradients across the SWI create a range of niches for the dwelling microbes [2] and therefore make the SWI an ideal model system to investigate links between microbial community structure and ecosystem processes. However, the microbial community structure across the SWI remains poorly understood.

Environmental filtering, i.e., the shaping of soil microbial community structure by abiotic factors, is considered an important factor influencing microbial community assembly in highly heterogeneous environments [3, 4]. Although the physicochemical gradients across the SWI usually occur at the µm or mm scale, a stratified microbial community is rarely observed, largely limited by the sampling approaches and analytical methods used. In many cases, the interface is sliced into ~1 cm layer to obtain sufficient material for microbiome analysis [5, 6], but these layers are typically too thick to allow determination of physicochemical gradients with any precision. We, therefore, propose that typical centimeter-scale or bulk sampling hinders attempts to adequately characterize patterns of microbial community structure across the SWI. Furthermore, considering that not all microbes are active in any given environment, microbial community structure profiled by the analysis of genomic DNA does not necessarily reflect the active microbes or community assembly processes [7, 8]. We hypothesized that stratification of active microbial community structures would be observed across the SWI if sampled and analyzed appropriately i.e., at the mm-scale using an RNA-based approach.

We conducted a soil incubation experiment for mm-scale sampling (Fig. S1) using analysis of rRNA content to profile the metabolically active members of the microbial community. Specifically, soil was flooded with sterilized deionized water and incubated for 20 days at 25 °C in the dark before a 50 mm soil core was taken and sampled at 2 mm intervals with prokaryote communities profiled using amplicons derived from reverse-transcribed 16S rRNA (detailed in Supplementary Information). After processing and taxonomic assignment of sequences, distance decay relationships (DDR) describing the similarity in community structures over distance were performed [9, 10]. We detected a strong DDR with the bacterial community similarity (1- Canberra dissimilarity) [9] significantly decreasing with distance through the SWI (Mantel $r = 0.547, p < 0.001$) (Fig. 1A). While DDR has been extensively used in microbiome research, patterns vary depending on the sampling scale. Microbial DDR patterns are assumed weak due to the high abundance, short life cycle, and dispersal abilities of microbes [9, 11]. In this study, we observed a DDR that was stronger than that of larger sampling scales (e.g., m or km) [9], but comparable to the cm scale [10]. This demonstrates that the spatial organization of soil microbes with relatively high community dissimilarity can be observed with appropriate spatial scales of analysis [9, 12, 13].

Distinct patterns of active bacterial communities were observed at the phylum level across the SWI (Fig. 1B). For example, the relative abundance of rRNA reads from the *Betaproteobacteria* within the *Gammaproteobacteria* class (a modification in the SILVA 132 database) decreased greatly (27-fold difference at the extremes of the SWI), while *Bacteroidetes* increased with soil depth (13-fold difference at the extremes). We then examined the active bacterial community composition at the family and genus level for a higher taxonomic

<footnote n="1">¹Department of Health and Environmental Sciences, Xi'an Jiaotong-Liverpool University, 111 Ren'ai Road, Suzhou, Jiangsu 215123, China. ²Department of Geography & Planning, School of Environmental Sciences, University of Liverpool, Brownlow Hill, Liverpool L697ZX, UK. ³Univ Lyon, CNRS, INSA Lyon, Université Claude Bernard Lyon 1, Ecole Centrale de Lyon, Ampère, UMR5005, 69134 Ecully cedex, France. ✉email: Zheng.Chen@xjtlu.edu.cn</footnote>
<figure><img src="image_3.png" /><figcaption>**Fig. 1** Community composition of the active microbial communities based on relative abundance of 16S rRNA gene transcripts through a 50 mm water-soil interface. A Changes in Bray-Curtis similarities of microbial communities with spatial distance. A linear trend was determined using ordinary least-squares linear regression with the shaded area representing 95% confidence intervals. B Relative abundance of phyla. Only those with a relative abundance ≥1% were included, while those <1% categorized as "Other". C Heatmap showing the relative abundance difference of the selected 44 bacterial genera (relative abundance ≥1%). An increase in abundance tends toward red, while a decrease tends toward blue.</figcaption></figure>

resolution (Figs. S2 and 1C). Sequences representing 44 bacterial
genera (each with a relative abundance ≥1%) accounted for 77% of
all total sequence and were clustered into three different groups
reflecting different distribution patterns (Fig. 1C). Bacterial genera
within group 1 generally had their lowest relative abundance of 16S
rRNA transcripts in the top 0–6 mm and were dominated by strict or
facultative anaerobic bacteria such as representatives of the
*Ruminococcaceae* family, *Anaeromyxobacter* and *Oxobacter* genera.

Bacteria in group 2 were more active from 2 to 40 mm, generally
showed low relative activity only at the deepest layers of 40–50 mm
and consisted of aerobic and facultative anaerobic bacteria including
*Bacillus* and *Gaiella* representatives. In contrast to groups 1 and 2,
bacteria in group 3 exhibited a clear decrease in their relative
abundance from the surface to 50 mm in the flooded soil profile.
Most of the bacteria in this group had the highest relative abundance
of 16S rRNA transcripts in the first 4 mm topsoil layer, indicating a
<figure><img src="image_4.png" /><figcaption>**Fig. 2** Depth profiles of soil physicochemical properties and microbial community structure through the SWI depth profile. A Redox potential. B Dissolved organic carbon (DOC). C Dissolved organic nitrogen (DON). D Ammonium-N (NH₄-N). E Nitrate-N (NO₃-N). F Distance based-redundancy analysis (dbRDA) triplot based on the selected 44 bacterial genera (relative abundance ≥1%) across the SWI. Triangles, bacterial genera; circles, soil samples across SWI; arrows, environmental factors.</figcaption></figure>

cluster of strictly aerobic organisms including representatives of the genera *Massilia* and *Gemmatimonas*.

We measured a range of soil physicochemical properties (Fig. 2A–E) and performed tbRDA analysis based on the selected 44 bacterial genera (Fig. 2F). The measured physicochemical properties correlated with 80.0% of the variance of the selected taxa (Fig. 2F). The main correlating factors were redox potential (F = 29.6, P < 0.001) and nitrate concentration (F = 50.3, P < 0.001). Consistent with the

distribution of bacteria across the SWI (Figs. 1C and 2), variance in redox potential could be divided into oxic, transition, and anoxic zones (Fig. 2A). The vertical stratification of the microbial community was primarily driven by the availability of oxygen rather than that of other common electron acceptors, as generally observed in lake and marine sediments [6, 14–16].

Microbial communities were functionally annotated using FAPROTAX [17]. While the prediction of metabolic attributes from 16S rRNA
sequences must be interpreted with caution, the results of functional
group distribution were nevertheless consistent with the gradient of
biogeochemical processes across the SWI. For example, transcripts
associated with organisms performing oxygen-dependent nitrifica-
tion processes of ammonia and nitrite oxidation were most abundant
within the first 4 mm and decreased as soil depth increased (Fig. S3a).
This decrease was consistent with the nitrate profile in which nitrate
was not detectable below 8 mm (Fig. 2E). Similarly, the abundance of
transcripts associated with organisms performing aerobic methanol
oxidation and methylotrophy decreased rapidly as soil depth
increased (Fig. S3). The methanotrophic populations demonstrated
high activity at oxic-anoxic interface [18, 19], and was consistent with
the changes in the transcript number of particulate methane
monooxygenase sub-unit A (pmoA) gene transcripts, a functional
marker for methane-oxidizing bacteria) (Fig. S3b). Other metabolic
activities such as iron respiration and fermentation were mainly
distributed in the sub-oxic areas as these metabolic processes are
performed in the absence of oxygen.

In summary, a stratified active microbial community could be
observed through the SWI at the mm-scale. These findings could
direct future biogeochemical research and identification of
corresponding microbial populations across the SWI as these
processes occur at very narrow zones and further affect large-
scale ecosystem responses (e.g., methane fluxes) [1, 20]. "Who is
doing what" remains a major challenge in microbial ecology. We
believe the isolation of the specific strains corresponding to a
targeted process would be more successful if the inoculum was
sampled from hot spots of activity identified via a high resolution,
mm-scale profiling of the microbial community. The method
could further be applied to study microbial responses to
environmental stress (e.g., pollutants, toxics) and allows char-
acterization and enrichment of uncultivated strains with pre-
viously unknown metabolic functions by creating artificial
gradients. We conclude that the analysis of microbial commu-
nities at an appropriate spatial scale should facilitate the
identification of the contributors to specific functions processed
in microbiome research.

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ACKNOWLEDGEMENTS

This work was supported by the National Natural Science Foundation of China (No. 41977320). We thank Prof. John Boyle (School of Environmental Sciences, University of Liverpool, Liverpool, United Kingdom) and Dr. Xue-Ping Chen (School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China) for the valuable comments on this paper. We also thank our lab technicians Ms. Xiao-Ping Xie, Ms. Wen Jiang, and Ms. Xiao Zhou for their assistance in the lab.

AUTHOR CONTRIBUTIONS

Y-JC, Z-AL, and ZC designed the research. Y-JC and Z-AL conducted the experiments and carried out all the chemical and biological analyses with the help of SZ and HL. Y-JC wrote the paper with critical reviews and comments from SZ, GWN, and ZC.

COMPETING INTERESTS

The authors declare no competing interests.

ADDITIONAL INFORMATION

**Supplementary information** The online version contains supplementary material available at https://doi.org/10.1038/s43705-022-00138-z.

**Correspondence** and requests for materials should be addressed to Zheng Chen.

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