The spatial distribution patterns of micro-organisms

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Microbial diversity in alpine tundra soils correlates with snow cover dynamics

The temporal and spatial snow cover dynamics is the primary factor controlling the plant communities’ composition and biogeochemical cycles in arctic and alpine tundra. However, the relationships between the distribution of snow and the diversity of soil microbial communities remain largely unexplored. Over a period of 2 years, we monitored soil microbial communities at three sites, including contiguous alpine meadows of late and early snowmelt locations (LSM and ESM, respectively). Bacterial and fungal communities were characterized by using molecular fingerprinting and cloning/sequencing of microbial ribosomal DNA extracted from the soil. Herein, we show that the spatial and temporal distribution of snow strongly correlates with microbial community composition. High seasonal contrast in ESM is associated with marked seasonal shifts for bacterial communities; whereas less contrasted seasons because of long-lasting snowpack in LSM is associated with increased fungal diversity. Finally, our results indicate that, similar to plant communities, microbial communities exhibit important shifts in composition at two extremes of the snow cover gradient. However, winter conditions lead to the convergence of microbial communities independently of snow cover presence. This study provides new insights into the distribution of microbial communities in alpine tundra in relation to snow cover dynamics, and may be helpful in predicting the future of microbial communities and biogeochemical cycles in arctic and alpine tundra in the context of a warmer climate.

Introduction

Seasonally, snow-covered soils account for 20% of the global land surface (Beniston et al., 1996). It is largely assumed that these soils sequester large amounts of organic carbon (Davidson and Janssens, 2006), and that the mineralization of this carbon stock is of increasing concern in a warmer climate (Hobbie et al., 2000; Oechel et al., 2000; Melillo et al., 2002). In arctic and alpine tundra, the duration of snow cover has dramatic impacts on ecosystem structure and functioning (Fisk et al., 1998; Walker, 2000; Welker et al., 2000; Edwards et al., 2007). The high topographic complexity found in alpine tundra triggers strong landscape-scale snow-cover gradients, which in the short term strongly affects local climatic conditions. In the long term, it leads to striking differences in plant cover and ecosystem processes (Billings, 1973; Bowman et al., 1993; Ko¨rner, 1999; Choler, 2005). Thus, alpine tundra offers ecologically relevant opportunities to assess the impact of snow on local climatic conditions and ecosystem processes (Olear and Seastedt, 1994; Litaor et al., 2001; Choler, 2005). Several studies have suggested that many key drivers of soil organic matter mineralization, such as soil temperature, soil moisture, and litter quantity and quality, vary in a conserved manner along snow cover gradients in alpine landscapes (Fisk et al., 1998; Hobbie et al., 2000). Concomitantly, other studies highlighted the seasonal shift of microbial communities and activities in dry alpine tundra (Lipson et al., 1999; Schadt et al., 2003; Lipson and Schmidt, 2004; Schmidt et al., 2007). Given that increasing temperatures will influence the snow cover dynamics in the alpine tundra (Marshall et al., 2008), mineralization processes and associated microbial communities will most likely be affected by these changes as well. However, alpine microbial communities are not well known, and only a few comparative studies of microbial community.
In this study, our main objective was to test for comprising neighboring LSM and ESM locations. spatial (that is, plant cover and soil characteristics) For each site, the locations stand a few meters away and temporal co-variations between soil bacterial (5–10 m) and the sites are separated by 200–500 m. and fungal communities, and for snowcover dy- The surface of each location is comprised between namics in alpine tundra. We compared two con- 50 and 100 m2. Plant coverage and soil parameters trasted conditions in alpine tundra, namely early are same among sites for a given location (ESM or snowmelt (ESM) and late snowmelt (LSM) locations, LSM). Five spatial replicates for each plot at each for 2 years. The phylogenetic structure of bacterial date were collected from the top 10 cm of soil and and fungal communities was first assessed using sieved (2 mm). During the first year of the survey single-strand conformation polymorphism (SSCP) (2005–2006), only site B was sampled on 24 June, 10 (Stach et al., 2001; Zinger et al., 2007, 2008) and August and 10 October 2005, and 3 May 2006. Sites were further characterized by cloning/sequencing. A, B and C were monitored during the second year
The molecular diversity in microbial communities (2006–2007), and were sampled on 30 July and 2
was examined at four different sampling periods: (i) October 2006, and 18 May 2007 (Figure 1a). Late- May, in the presence of late winter snowpack in winter snow cover consisted of 1–2.5 m depth in LSM or immediately after thawing in ESM; (ii) June, LSM locations. Soil organic matter content was corresponding to snowmelt in LSM locations and determined by loss on ignition (Schulte and Hop- the greening phase for ESM; (iii) August, when there kins, 1996) in soil sampled in September. Soil is a peak of standing biomass; and (iv) October, texture was determined using standard methods by during litterfall and just before the early snowfalls the Institute National de la Recherche Agronomique
(Figure 1a). (Laboratoire d’Analyses des Sols, Arras, France). For each spatial replicate (n ¼ 5), 5 g of soil were mixed in 15 ml of distilled water to determine the pH.
Materials and methods Differences of pH (Po0.05) between each point were determined by Tukey’s test with the R software (The Sample collection and soil characterization R Development Core Team, 2007).
The study site was located in the Grand Galibier massif (French southwestern Alps, 451 0.050 N, 061 0.380 E) on an east-facing slope. Microbial commu- CE-SSCP analysis of microbial diversity
nities were studied in three sites (ESM A: 451 10 Three replicates of soil DNA extraction were carried 48.470N 61 130 50.140W, B: 451 10 52.780N 61 130 out for each sample with the Power Soil Extraction Kit (MO BIO Laboratories, Ozyme, St Quentin en Yvelines, France) according to the manufacturer’s instructions. To limit the effects of soil spatial heterogeneity, 15 DNA extracts obtained from the five spatial replicates per location and date were pooled, rendering one DNA pool per location per date. This sampling and pooling strategy is in accordance with recent reports (Schwarzenbach et al., 2007; Yergeau et al., 2007a, b), and have been validated for fungal communities (June 2005 to May 2006, Zinger, unpublished data). The V3 region of 16S rRNA gene was used as the bacterial-specific marker using the primers W49 (50-ACGGTCCA-GACTCCTACGGG-30) and W104-FAM (50-TT ACCGCGGCTGCTGGCAC-30) (Delbes et al., 1998), whereas the ITS1 region, amplified with the primers ITS5 (50-GGAAGTAAAAGTCGTAACAACG-30) and ITS2-FAM (50-GCTGCGTTCTTCATCGATGC-30) (White et al., 1990), was used as a fungal marker. PCRs (25 ml) were set up as follows: 2.5 mM of MgCl2, 1 U of AmpliTaq Gold polymerase (Applied Biosys-tems, Courtaboeuf, France), 1 of buffer provided by the manufacturer, 20 g l 1 of bovine serum albumin, 0.1 mM of each dNTP, 0.2 mM of each primer and 10 ng of DNA template. A 9700 dual 96-well sample block (Applied Biosystems) was used for thermocycling, with an initial denaturation at 95 1C for 10 min, 30 cycles of denaturation at 95 1C for 30 s, annealing at 56 1C for 15 s and extension at 72 1C for 15 s, and a final elongation at 72 1C for 7 min. The amplicons of each sample were then submitted to CE-SSCP as described earlier (Zinger et al., 2007, 2008). The profiles obtained from CE-SSCP were normalized and compared by construct-ing dendrograms from Edwards’ distance and Neighbor-Joining, with 1000 bootstrap replications. These analyses were carried out with the R software (R Development Core Team, 2007).

Clone library construction and analysis

Clone libraries were constructed for the samples from the site B (2005–2006). Bacteria communities were monitored using the 16S rRNA genes, ampli-fied with 63F (50-CAGGCCTAACACATGCAAGTC-30) (Marchesi et al., 1998) and Com2-ph (50-CCGTCAATTCCTTTGAGTTT-30) (Schmalenberger et al., 2001). The 28S rRNA genes were amplified for fungal communities with U1 (50-GTGA AATTGTTGAAAGGGAA-30) (Sandhu et al., 1995) and with nLSU1221R (50-CTAGATGAACYAA-CACCTT-30) (Schadt et al., 2003). PCRs were carried out with 2.5 mM MgCl2, 0.1 mM each ddNTP, 0.4 mM (bacteria) or 0.2 mM (fungi) each primer, 1 U Ampli-Taq Gold polymerase, 1 of buffer provided by the manufacturer, 20 g l 1 of bovine serum albumin and 10 ng of DNA of each location pool as a template. PCR was carried out as follows: initial denaturation at 95 1C for 10 min, 25 (bacteria) or 30 (fungi) cycles at 95 1C for 30 s, 54 1C (bacteria) or 53 1C (fungi) for 30 s and 72 1C for 1 min and 30 s, and final elongation at 72 1C for 15 min (bacteria) or 7 min (fungi). Eight independent PCR amplifications were carried out on each sample, pooled and cloned using a TOPO TA PCR 4.1 cloning kit (Invitrogen SARL, Molecular Probes, Cergy Pontoise, France). The titers of ligation were between 25 and 446 c.f.u. ng 1 of soil DNA. The transformation and sequencing were carried out at the Centre National de Se´quenc¸-age (Genoscope, Evry, France). Approximately 350– 380 sequences per library were obtained. Clones were identified using Ribosomal Database Project’s Classifier (Cole et al., 2003) for bacteria and BLAST (Altschul et al., 1997) for fungi. Bellerophon (Huber et al., 2004) was used to identify chimerical sequences. A multiple alignment for each kingdom was carried out with ClustalW (Chenna et al., 2003) and cleaned by removing nucleotide positions with more than 30% of gaps and sequences smaller than 400 bp. After this cleaning step, 2226 sequences with 499 nucleotide positions for bacteria (GenBank accession nos. FJ568339–FJ570564) and 2559 se-quences with 617 nucleotide positions for fungi (GenBank accession nos. FJ568339–FJ570564) were included in the phylotype composition and diver-sity analysis. We used pairwise distances and complete linkage method to cluster 700 randomly sampled DNA sequences of bacteria or of fungi. Sequences were then pooled according to different similarity thresholds (from 70 to 100%). For each sequence similarity level, we calculated the con-verse of the Simpson index to estimate the evenness of the profile of OTU abundances (Smith and Wilson, 1996). The procedure was repeated 1000 times. All computations were carried out using the R software (The R Development Core Team, 2007).

Results

Characterization of ESM and LSM locations

The temperature of soil from ESM and LSM locations was determined for 7 years. ESM locations are characterized by shallow or inconsistent winter snow cover, leading to long periods of soil freezing (Figure 1a). In contrast, LSM locations exhibit long-lasting, deep and insulating snowpack almost 8 months per year, which leads to a fairly constant winter soil temperature around 0 1C (Figure 1a). In almost all the cases, the soil temperature during sampling was comprised between the usual tem-peratures for the season (Figure 1a). The contrasting snow cover environments are associated with marked variations in plant communities (Table 1) (Choler, 2005). LSM are dominated by low-stature species, such as Carex foetida (Cyperaceae) and Salix herbacea (Salicaceae), which must cope with a shorter growing season. Plant cover in ESM loca-tions is more discontinuous and dominated by Kobresia myosuroides (Cyperaceae), a stress-tolerant turf graminoid, and Dryas octopetala (Rosaceae), a dwarf shrub. The upper soil layer in ESM locations
has a higher soil organic matter content than that in LSM locations, but the carbon stock is lower due to shallower soils (Table 1). Soil pH is stable and higher in ESM throughout the year, except in winter when ESM soils become more acidic than LSM soils (Figure 1b).

Effects of snow cover patterns on temporal microbial community structure revealed by molecular profiling

The microbial communities were monitored from August 2006 to May 2007 at three sites, each including ESM and LSM locations. The structure of the microbial communities was assessed using capillary electrophoresis-based SSCP (CE-SSCP) by amplifying the V3 region of ssu gene using PCR for bacteria and the ITS1 (internal-transcribed spacer 1) for fungi. Distance trees based on the SSCP profiles revealed a significant difference within bacterial and fungal communities between ESM and LSM. This pronounced difference was noticed for all study sites and sampling dates (Figure 2a).

Table of contents :

CHAPITRE 1 : Introduction
Background and objective of the thesis
Thesis content and structure
The challenge of environmental microbiology
Microbial ecology history
Bacteria
Bacterial genetic diversity
Bacterial roles in nature
Bacterial Diversity
Importance of bacterial diversity in ecosystem
Factors important on bacterial diversity
Abiotic factors
Biotic factors
Measurement of bacterial diversity
Measurements of taxonomic distinctness
The species equal to OUT
How to assess microbial diversity?
Traditional methods
Culture-independent method
Importance of soil
The spatial distribution patterns of micro-organisms
The temporal distribution patterns of micro-organisms
Alpine ecosystem
Definition
Heterogeny of the alpine stage
The history of bacterial characterization in artico-alpine
Phenotypic characterization and adaptation to cold condition
Bacterial diversity in cold environment
Bacterial diversity and structure based on culture
Bacterial diversity and structure based on method molecular
CHAPITR 2: Effet des régimes d’enneigement sur la diversité et relative abondance de la communauté bactérienne des sols alpins 
Contexte général
Objectifs de l’étude
Article I: Microbial diversity in alpine tundra soils correlates with snow cover dynamics
Principaux résultats et discussion
CHAPITRE 3: Effet des régimes d’enneigement sur la structure phylogénétique des communautés bactériennes des sols alpins 
Contexte général
Objectifs de l’étude
Article II: Snow cover dynamics and phylogenetic structure of bacterial communities in alpine tundra soils
Abstract
Introduction
Material and Methods
Study site, sample collection and bacterial ssu sequences
Sequence data treatment
Statistical Analysis
Results
Comparison of bacterial communities using taxonomic information
Comparison of bacterial communities using phylogenetic information
Distribution of bacterial groups at finer taxonomic scale
Discussion
Conclusion
Acknowledgements
References
Principaux résultats et discussion
CHAPITRE 4 : Effet des régimes d’enneigement sur la richesse des espèces bactériennes cultivables des sols alpins
Contexte général
Objectifs de l’étude
Article III: Phylogenetic diversity of cultivable bacteria in soils of temperate alpine tundra
Abstract
Introduction
Material and Method
Site sampling description and sample collection
Culture media
Isolation of bacterial strains
PCR amplification and sequencing of 16S rRNA
Phylogenetic analysis and sequence comparison
Results
Counts and phenotypic characterization of the isolates
Phylogenetic analysis of isolated strains
Comparison with ESM and LSM ssu libraries
Seasonal and spatial distribution
Discussion
Conclusion
Acknowledgements
References
Principaux résultats et discussion
L’effet le enneigement sur la richesse, abondance et composition des bactéries cultivable
Comparaison des résultats obtenus par approches classiques et moléculaires
CHAPITRE 5: Synthèse et perspectives
The limits of molecular approaches
DNA extraction and PCR
Molecular profiling method: CE-SSCP
Random sequencing of ssu libraries
Importance of traditional and cultural methods
Link between bacterial phylogenetic and function
Bacterial assemblage and filtering factors
Link between snow cover and bacterial activity
Bacteriobio geography
Conclusion
Bibliographie
Annexe

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