Physiological diversity of bacterial communities from different soil locations on Livingston Island, South Shetland archipelago, Antarctica Anelia Kenarova, Marta Encheva, Valentina Chipeva, Nesho Chipev, Petya Hristova & Penka Moncheva Polar Biology ISSN 0722-4060 Volume 36 Number 2 Polar Biol (2013) 36:223-233 DOI 10.1007/s00300-012-1254-8
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Author's personal copy Polar Biol (2013) 36:223–233 DOI 10.1007/s00300-012-1254-8
ORIGINAL PAPER
Physiological diversity of bacterial communities from different soil locations on Livingston Island, South Shetland archipelago, Antarctica Anelia Kenarova • Marta Encheva • Valentina Chipeva Nesho Chipev • Petya Hristova • Penka Moncheva
•
Received: 14 March 2012 / Revised: 1 October 2012 / Accepted: 8 October 2012 / Published online: 23 October 2012 Ó Springer-Verlag Berlin Heidelberg 2012
Abstract Terrestrial food webs of Antarctica are simple and dominated by microorganisms. Soil bacteria play an important role in nutrient cycling, yet little is known about their capacity to utilize different carbon sources and to participate in site nutrient turnover. Biolog EcoPlateTM was applied to study the catabolic activity and physiological diversity of bacteria inhabiting the soil of moss, vascular plants, and fell field habitats from Livingston Island, Antarctica. Additionally, the number of oligotrophic and copiotrophic bacteria was counted by the agar plate method. Results indicated a lack of site-specific distribution of bacterial abundance, in contrast to bacterial catabolic activity and community level physiological profiles. Community level physiological profiles revealed a common capacity of soil bacteria to intensively utilize polyols, which are cryoprotectants widely produced by Antarctic organisms, as well as site-specific phenolic compounds (vegetated habitats), amino acids/amines (moss habitats), carbohydrates and carboxylic acids (fell field habitat). It was concluded that the physiology of soil bacteria is habitat specific concerning both the rate of catabolic activity and pattern of carbon source utilization. Keywords Antarctica Soil bacterial communities Biolog EcoPlates Community level physiological profile Bacterial physiological diversity A. Kenarova (&) M. Encheva V. Chipeva P. Hristova P. Moncheva Biological Faculty, Sofia University, 8 Dragan Tsankov Blvd., 1164 Sofia, Bulgaria e-mail:
[email protected] N. Chipev Institute of Biodiversity and Ecosystem Research, 2 Yuri Gagarin Str., 1113 Sofia, Bulgaria
Abbreviations AWCD Average well color development AWCDN Normalized average well color development CLPP Community level physiological profile CV Coefficient of variability FTC Freeze–thaw cycle
Introduction The terrestrial environments of Antarctica are dynamic and variable with low temperatures, low moisture availability, frequent freeze–thaw cycles (FTCs), scarce vegetation cover, and limited organic matter (Convey 1996). They exhibit low complexity food web structures which are dominated by microorganisms. Most of the energy and materials assimilated by primary production become detritus because of the absence of herbivores (Heal and Block 1987), and soil bacteria play a crucial role in its turnover. Bacterial diversity, community structure, abundance, and function of maritime and continental Antarctica are all reported to be affected to some extent by environmental conditions, usually in interaction with aboveground cover (Eriksson et al. 2001; Yergeau et al. 2007b; Yergeau and Kowalchuk 2008), yet bacteria are highly adaptable to extreme and changing environments (Cavicchioli et al. 2000; Georlette et al. 2004; Thomas 2005). The community structures and diversity of Antarctic bacteria have been studied by molecular-based methods such as phospholipid fatty acids analysis (Yergeau et al. 2007a, 2009) and/or DNA analyses (Ganzert and Wagner 2007; Yergeau et al. 2007a, b, 2009; Villaescusa et al. 2010; Ganzert et al. 2011). Measurements of physiological diversity (metabolic capacity) and bacterial activity represent another approach,
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allowing the study of different characteristics of bacterial communities. The metabolic response of soil bacteria (fast growing copiotrophs) to local nutrient sources can be evaluated using the Biolog technique (Garland 1997; Preston-Mafham et al. 2002). Biolog EcoPlateTM is designed to estimate community level physiological profiles (CLPPs) of bacteria by measuring the relative utilization of various ecologically relevant organic substrates. The Biolog technique suffers from the drawbacks of cultivation methods (Preston-Mafham et al. 2002); nevertheless, Biolog plates have been shown to be a useful tool for the detection of differences in CLPPs of bacteria in water (Bradley and Lind 2007; Lyons and Dobbs 2012), soil (Stephan et al. 2000; Calbrix et al. 2005; Lo˜hmus et al. 2006), and artificial (van der Marwe et al. 2003; Kashama et al. 2009) environments. The physiological diversity of Antarctic bacteria is poorly studied and limited to some single studies of water (Sala et al. 2005) and terrestrial (Mallosso et al. 2005; Leflaive et al. 2008) environments. The objective of the present study was to assess the physiological diversity and metabolic activity of soil bacterial communities inhabiting different terrestrial habitats on Livingston Island in maritime Antarctica. The hypothesis that habitat type and dominant vegetation type affect bacterial carbon utilization rate and CLPP and that vegetation is the major factor differentiating bacterial communities according to their physiological diversity was tested.
Materials and methods Study area Figure 1 shows that the studied territories are 130 m inland from the shore of Emona Anchorage Bay on Livingston Island in the South Shetlands archipelago of Maritime Antarctica, close to the Bulgarian Antarctic Station (62°380 2900 S, 60°210 5300 W). The climate can be defined as cold maritime, with an average summer temperature of *2 °C, and a daily maximum of up to 10 °C, while the winter temperatures are always \0 °C with a minimum of -35 °C (Chipev and Veltchev 1996; Toro et al. 2007). The average annual precipitation is much higher than in most continental areas of Antarctica with values between 500 and 1,000 mm (Ban˜o´n 2001; Viera and Ramos 2003). Sampling sites The soil samples were collected during the austral summer of 2010 from ice-free areas at a depth of 0–5 cm. Sites were chosen by different habitat characteristics and noted as follows: S1) Playa Bulgara vegetated with Deschampsia
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Fig. 1 Location of Livingston Island, Antarctica and the positions of the sampling plots
antarctica and located on the coast at 62°380 1400 S, 60°210 3700 W, S2) gravel shore of the South Bay with cryptogam (moss) coverage at 62°380 0700 S, 60°210 1500 W, S3) Punta Hesperides with cryptogam coverage and individual vascular plants at 62°380 3600 S, 60°220 1400 W, S4) plot in the vicinity of Sea Lion Lake with vascular plant and moss coverage at 62°380 4700 S, 60°220 1700 W, S5) rocky terrain named ‘‘Papagal’’ with non-vegetated soil among the rocks at 62°380 5300 S, 60°210 5900 W, S6) terrain with moss coverage located on the hill southwest of the Bulgarian station at 62°380 3000 S, 60°210 5600 W, and S9) Caleta Argentina vegetated with D. antarctica terrain at 62°400 0700 S, 60°240 0600 W. Subsamples for microbiological and physicochemical analyses were placed in 50 ml sterile tubes which were stored and shipped to the laboratory under ice and after that stored at 4 °C. Soil analysis Water content was determined gravimetrically after drying the soil samples at 105 °C. pH was measured on a 1:2.5 soil: deionized water suspension mixed for 1 h on a rotary shaker at 160 rpm. Humus content was analyzed following the method of Koleshko (1981). Samples (5 g) were placed in 100 ml flasks, and 50 ml of 2 % Na2CO3 (Sigma-Aldrich) was added and boiled for 10 min. After filtration, 25 ml of HCl (SigmaAldrich) was added. The precipitates (humus) were collected by filtration and weighed after drying at 105 °C.
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Cell suspensions Cell suspensions were prepared from 5 g soil samples suspended in 45 ml sterile 0.9 % NaCl (Sigma-Aldrich) for 30 min on a rotary shaker at 220 rpm followed by filtration through 8.0 and 3.0 lm nucleopore membranes (Whatman). The bacterial cell suspensions were used for bacterial enumeration on agar plates and Biolog tests. Bacterial enumeration The cultural method and two media were chosen to plate decimal dilution series (100–10-5) of soil suspensions and to enumerate oligotrophic (10 % water extract of local soil amended with 0.1 % glucose and 0.05 % K2HPO4 [SigmaAldrich]) and copiotrophic (1/10 strength Difco nutrient agar) bacteria. The inoculated agar plates were incubated in dark at 15 °C for 8 days. Biolog test A Biolog EcoPlate (Biolog Inc., Hayward CA, USA) containing 31 different carbon (C) sources was used to assess the rate (AWCD) and the pattern (CLPP) of C source utilization by Antarctic soil bacterial communities. The plate wells were inoculated with 120 ll bacterial cell suspension, and following an initial (time 0) optical density (OD) reading (590 nm, Microplate Reader LKB 5060-006 and software DV990 ‘‘Win 6’’), the Biolog plates were incubated at 15 °C in dark for 8 days. Color development in the wells was measured every day.
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by the number of copiotrophic bacteria (N) and was noted as normalized average well color development (AWCDN 9 10-7). Oligotrophic bacteria are characterized by slow growth and low rates of metabolism, and their contribution to the color development on EcoPlates can be considered low to negligible for the time of incubation. Kinetic curve The AWCDs were calculated daily and the kinetic curves reflect the AWCD versus time. Physiological diversity The physiological diversity of bacterial communities was quantified using the Shannon, Simpson, and McIntosh indices (Magurran 1988) based on CLPPs. These indices define distinct types of heterogeneity. The Shannon index is more sensitive to changes in rare species, while the McIntosh and Simpson indices are more sensitive to changes in the most abundant species (Peet 1974). Cluster analysis The cluster analysis was conducted to group bacterial communities that are similar in their CLPPs using the SynTax 2000 software package, method of the nearest neighbors, and index for similarity ratio (Podani 2000).
Results Statistical analysis Soil characteristics Data were represented by the mean (n = 3). A one-way ANOVA was performed using NCSS 97 (NCSS, Kaysville, Utah) to determine significant differences at p \ 0.05. Principal component analysis (PCA) was conducted using the PRIMER 6 software package (Clarke and Gorley 2005) to reduce the n-dimensional data of soil characteristics into a series of linear axes that explain the maximum amount of variance in the data. Soil plot S4 was not analyzed by PCA because of a lack of data. The color development of each plate was expressed as average well color development (AWCD) as suggested by Garland and Milles (1991): AWCD ¼
X ðni cÞ 31
where ni and c were the average absorption of the three wells of the substrate and the control wells (without a C source), respectively. To reduce the influence of the inoculum density, the AWCD value of each plate was divided
The soils were analyzed for pH, moisture content, and humus content (Table 1). The other soil characteristics were provided by the Bulgarian Antarctic Institute (personal communication). The moisture content of the soils was high at 11–14 % and even higher for plot S5 at 50 %. The soil pH was slightly acidic with values in a relatively narrow range. Humus content was low, from undetectable to 0.28 %. Maritime Antarctic soils were more abundant in phosphorus (P) than nitrogen (N). PCA demonstrated higher spatial distance between soil plots S1 and S9 from the others suggesting much more distinct physicochemical characteristics (Fig. 2). Soil bacterial abundance Heterotrophic (oligotrophic and copiotrophic) bacteria were counted on plates as colony forming units (cfu) to follow their distribution along the soil plots and for the
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Table 1 Soil characteristics of the sampling sites Total C (%)
K mg g-1
Na mg g-1
Ca mg g-1
pH (in H2O)
Moisture (%)
Humus (%)
S1
6.43
14
ULa
6.60
0.66
2.79
8.73
1.97
0.99
S2
6.29
14
0.28
21.12
0.16
1.90
7.07
1.11
1.07
S3
5.86
11
UL
20.46
0.095
0.97
1.91
1.47
0.76
b
Total N (%)
Total P mg g-1
Plot
S4
5.74
12
UL
ND
ND
ND
ND
ND
ND
S5
6.33
50
0.1
18.21
0.16
1.25
2.54
0.82
1.62
S6
6.20
14
UL
20.46
0.12
1.46
2.52
1.29
1.03
S9
5.79
12
0.05
14.92
0.115
2.69
1.50
2.55
2.01
a
UL under the limit of the method
b
ND no data
Fig. 3 Bacterial abundance (Ln N) in different soil plots on Livingston Island
AWCDN and CLPP Fig. 2 Ordination of soil plots based on physicochemical characteristics by principal component analysis. PC1 axis (score for total C, N and P) explains 40.2 % of variance, while PC2 axis (score for pH and Na) describes an additional 20.0 % of variance among the plots
purpose of Biolog tests. The total number of heterotrophic bacteria was 6.76 9 106 cfu g-1 on average, and it varied from 4.20 9 105 cfu g-1 (plot S6) to 2.63 9 107 cfu g-1 (plot S5). The soil bacterial abundance did not correspond directly to habitat type. Plots S4, S5, and S9 had more abundant soils (Fig. 3) which differed in environmental characteristics such as humus content, pH, soil moisture, and the presence/absence/type of vegetation cover. Differences were also recorded in the distribution of the two kinds of heterotrophic bacteria among the plots. The distribution of oligotrophic bacteria (CV = 1833 %) was much more variable than that of copiotrophs (CV = 0.79 %, excluding plot S5 where the number differed significantly from that of the other plots) as they predominated in plots S2, S4, and S9.
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The values of AWCDN are shown in Fig. 4. The copiotrophic bacteria from plots S2, S3, and S6 were more active on the EcoPlates and represented the soil habitats with cryptogam (moss) coverage. The lowest substrate utilization rate was indicated for plot S5 which represented the skeletal fell field soils of maritime Antarctica inhabited mainly by bacteria and algae. The color development on EcoPlates was recorded over time to create kinetic curves (Fig. 5). Kinetic analysis illustrated different patterns of substrate utilization. There was a short lag phase of color development and sigmoid curves for plots S1, S2, S3, and S6 with almost equal maximum rates of substrate utilization in S2, S3, and S6 (AWCDN = 20.57, 19.46, and 18.66, respectively). There was a long lag phase for plot S5 and very fast color development after day three. There were no well-defined sigmoid curves for plots S9 and S4. The rates of substrate utilization were habitat rather than biochemically dependent. Polyols, carboxylic acids, amino acids, and amines were widely used as nutrients by soil
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227 Table 2 Mean rates of substrate utilization (MRSU) on EcoPlates by bacteria from different soil plots (n = 7; SD standard deviation) Substrate Tween 40 D-Galacturonic
acid
D-Glucosaminic
acid N-Acetyl-D-glucosamine
Fig. 4 Rates of substrate utilization (AWCDN) by bacteria inhabiting different soil plots on Livingston Island
Physiological diversity The physiological diversity of copiotrophic bacteria was calculated by the Shannon, Simpson, and McIntosh indices on EcoPlates (Fig. 6). The values of the Shannon index were high with a narrow range (3.6–4.1) without distinction
SD (910-7)
C
28.00
20.3
C
24.10
26.7
C C
23.52 23.23
25.8 23.6
L-Asparagine
C?N
22.82
25.5
C
22.88
18.3
L-Arginine
C?N
22.35
23.9
D-Mannitol
C
21.05
21.9
Tween 80
C
20.33
20.3
C?N
19.16
20.1
C
15.27
16.7
Putrescine
C?N
14.74
14.6
Pyruvic acid methyl ester
C
12.78
8.7
Glycyl-L-glutamic acid
C
9.64
10.6
Phenylethylamine
C?N
8.59
16.8
D-Malic
C
6.72
4.4
Glycogen
C
6.27
6.1
2-Hydroxybenzoic acid phosphate
C C?P
5.94 5.00
7.5 25.2 2.6
L-Serine
acid
acid
D,L-a-Glycerol
bacteria, and the rates of their utilization varied according to the total activity of the relevant bacterial community. Table 2 shows that among the 13 substrates with higher utilization rates, there were four carboxylic acids (D-Galacturonic acid, D-Glucosaminic acid, D-Galactonic acid, and Pyruvic acid methyl ester), three amino acids (L-Asparagine, L-Arginine, and L-Serine), three polyols (D-Mannitol, two derivatives of Sorbitol—Tween 40 and Tween 80), one carbohydrate (N-Acetyl-D-glucosamine), one phenolic compound (4-Hydroxybenzoic acid), and one amine (Putrescine). The average value of the utilization rate of the above-mentioned substrates represented 77 % of the AWCDN, and they could be assumed to be the most preferable nutrient sources for maritime Antarctic soil bacterial communities.
MRSU (910-7)
4-Hydroxybenzoic acid
D-Galactonic
Fig. 5 Kinetic curves of color development (AWCD) by bacteria inhabiting different soil plots on Livingston Island
Nutrients
L-Phenylalanine
C?N
4.81
i-Erythritol
C
4.16
2.8
c-Hydroxybutyric acid
C
4.10
2.4
D-Cellobiose
C
3.64
3.0
a-Ketobutyric acid
C
3.56
2.4
D-Lactose
C
3.32
2.3
a-Cyclodextrin
C
3.27
2.3
D-Xylose
C
3.00
3.1
Itaconic acid
C
2.86
2.2
Glucose-1-phosphate
C?P
2.75
2.1
L-Threonine
C?N
2.12
2.0
b-Methyl-D-glucoside
C
2.06
1.6
between soil type. The Simpson index (D) segregated plots S2 (D = 20.45) with the highest and S5 (D = 0.19) with the lowest physiological diversity, but it could not detect significant differences (p [ 0.05) between the other plots. The McIntosh index (U) differentiated physiological diversity of bacterial communities into groups with low (plot S5), medium (plots S1, S4 and S9), and high (plots S2, S3, and S6) values, which was a site-specific grouping of fell field (U = 0.17), vascular (U = 5.28, 3.83, and 3.79), and moss (U = 15.5, 16.5, and 15.4) habitats. The cluster analysis of the data from EcoPlates grouped the habitats into three principal clusters as did the McIntosh index, comprising the vascular (Cluster 1), moss (Cluster 2), and fell field (Cluster 3) plots (Fig. 7).
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Discussion
Fig. 6 Physiological diversity of soil bacteria calculated on the base of EcoPlates
Fig. 7 Dendrogram of the soil plots based on bacterial CLPPs
The CLPPs from the moss (Cluster 2) were much more similar to those of the vascular (Cluster 1) plots as the dissimilarity between them was 0.75. The dissimilarity index value between the vegetated (S1, S2, S3, S4, S6, and S9) and the non-vegetated (S5) plots was much higher. The three clusters demonstrated very different site-specific physiological profiles (Fig. 8). Bacteria from cluster 1 utilized the C sources more equally than the others, but the spectrum of the most intensively used substrates (Pyruvic acid, Tweens, Glycogen, and phenolic compounds) was very narrow. Bacteria from cluster 2 demonstrated much more physiological versatility than cluster 1 and intensively utilized a wider range of C sources from different biochemical categories: polyols (Tweens and D-Mannitol), carboxylic acids (D-Glucosaminic acid, D-Galactonic acid, D-Galacturonic acid), amino acids and amines (L-Arginine, L-Asparagine, L-Serine, Putrescine), carbohydrates (N-Acethyl-D-glucosamine), and phenolic compounds (4-Hydrohybenzoic acid). Bacteria from cluster 3 more intensively utilized carbohydrates (Glycogen, D-Cellobiose, L-D-Lactose, b-Methyl-D-glucoside, D-Xylose) and carboxylic acids (Pyruvic acid, D-Galacturonic acid, Itaconic acid, D-Malic acid), as well as polyols (Tweens).
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The primary role of microorganisms in nutrient cycling in Antarctic terrestrial environments has increased research interest in their distribution (Aislabie et al. 2008), diversity (Smith et al. 2006; Yergeau et al. 2009; Ganzert et al. 2011), activity (Nichols et al. 1999), and mechanisms of adaptation (Nichols et al. 2004; Novis et al. 2007). However, knowledge of their physiological adaptation to the variety of different terrestrial environments is still scarce. The aim of this study was to highlight the physiological capacity of the soil bacterial communities to utilize a set of C sources in terms of their primary role in the local organic matter turnover and the level of adaptation to the indigenous C inputs. The soil of Livingston Island has a relatively high bacterial abundance, and the number of heterotrophic bacteria (6.76 9 106 cfu g-1 dry soil) is comparable with plate counts (1.7 9 103–6.1 9 107 cfu g-1 dry soil) obtained from other Antarctic studies (Kenarova and Bogoev 2002; Raykovska et al. 2005; Saul et al. 2005; Aislabie et al. 2006, 2008; Ganzert et al. 2011). In general, cell number is represented by oligotrophic bacteria (60–90 %) with the exception of plot S5 where the number of copiotrophs is extremely high, reaching up to 75 % of the total. The reason for copiotrophic bacteria selection at plot S5 is unclear but the same tendency has also been recorded for soils taken in 2009 (unpublished data). The proliferation of copiotrophs at plot S5 may be supported by the extracellular metabolites of terrestrial cyanobacteria (Matsunaga et al. 1993; Vincent et al. 1993; Kenarova and Bogoev 2002; Zakhia et al. 2008) and from the high level of humidity (50 %) which is the main factor determining bacterial number (Christie 1987), activity (Bo¨lter 1992), and diversity (Aislabie et al. 2006). The capacity of heterotrophic (copiotrophic) bacteria to utilize different C sources (AWCDN and CLPPs) is especially important in Antarctic terrestrial ecosystems where plant material turns entirely into detritus and the microorganisms are the main factors taking part in its degradation. Soil habitats manifest different patterns of similarity according to their physicochemical and biological characteristics. For example, soils from plots S2, S3, S6, and S5 exhibit high levels of similarity according to their chemistry but plot S5 harbors a very distinct bacterial community referring to its physiological profile. The opposite tendency is found for plots S1 and S9, which differ from each other in their soil characteristics but are similar in the physiology of their indigenous bacteria. There are a number of possible explanations why the soils have different patterns of similarity in their physicochemical and biological characteristics including organic matter quality and soil nutrient status. In this study, it was revealed that moss mats are the most favorable environments supporting bacterial
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Fig. 8 Average substrate well color development normalized (ASWCDN) and AWCDN of a moss, b vascular plants and c fell field bacterial CLPPs
catabolic activity (high AWCDN and short lag phase), high physiological versatility (intensively utilize C sources from different biochemical categories), and heterogeneity (U = 15.8 on average). The high metabolic activity of the
moss plots refers to the low number of copiotrophic and oligotrophic bacteria (*5–6 % from the average count); hence, the ecological strategy of bacteria in these habitats is to use the energy for maintaining a high metabolic activity (K-strategy)
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rather than to proliferate. The vascular and the fell field plots support high bacterial abundances (copiotrophs for the fell field and oligotrophs for the vascular plots) but low metabolic activity (AWCDN), a long lag phase in AWCD curves, and low physiological heterogeneity (U = 4.3 and 0.19 for the vascular and fell field plots, respectively). Deschampsia plots and especially the fell fields are less favorable for bacterial activity than moss environments because of the stronger adverse effects of bacterial interactions with the vascular plants (Yergeau et al. 2007b) or the freeze-thaw and wet-dry cycles in fell fields (Yergeau et al. 2007a). It seems that the high inputs of dead organic matter (Davis 1986) and root exudates (Melick et al. 1994; Roberts et al. 2009) into the soils of vascular plots do not promote bacteria to overcome the environmental stress. The main bacterial nutrients in Antarctic soil are the compatible solutes: cryoprotectants (Tearle 1987; Roser et al. 1992; Duman and Olsen 1993; Chapman et al. 1994; Yamashita et al. 2002; Bravo and Griffith 2004; Griffith and Yaish 2004; Waller et al. 2006), cyanobacterial and microalgae mucilage (Metaxatos et al. 2003; Nichols et al. 2005), as well as root exudates and intermediates from the degradation pathways of dead plant matter (Bo¨lter et al. 2002; Roberts et al. 2009). Tearle (1987) reported that the peak of intracellular levels of polyols and sugars in the cryptogams accounted for up to 24 % of the dry weight of the plants, and their leaching in a single year implied more than 15 % of the total organic matter available to the soil microbiota. This contrasts with the 1.5 % of plant material which becomes available each year with the breakdown of dead sub-surface material (Davis 1986). The specific origin of the Antarctic soil nutrient pool (mainly easily degradable antifreeze substances) suggests that bacteria are adapted to it and use it intensively. Therefore, it is not surprising that the most common utilizable substrates from the studied soil plots are polyols— mainly the derivatives of Sorbitol (Tweens), followed by D-Mannitol, and Erythritol. With the exception of the bacteria from the fell field, the intensive utilization of polyols contrasts to the low utilization rate of carbohydrates which are the other high abundant antifreeze agents used in Antarctica. This contradiction may lie in both the low carbohydrate availability in soils and their different content (Metaxatos et al. 2003; Nichols et al. 2005) compared with that on EcoPlates. Low concentrations of carbohydrates in the surface layer were reported by Bo¨lter (1990), who found that they are up to 7–10 times lower than that of free amino acids, and later by Buyer and Drinkwater (1997) and Buyer et al. (2001) who reported that carbohydrates migrate easily to the deeper soil layers, and their content in soil surface is low to negligible. Bacteria from the vegetated (S1, S4 and S9) plots are specialized to assimilate phenolic compounds which are
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synthesized by plants and mosses as antioxidants (Feild et al. 2001; Close and McArthur 2002) or allelopathic agents (Mutikainen et al. 2002; Bais et al. 2003; SanchezMoreiras et al. 2004; Meier et al. 2008), and/or released substances into the soil during the degradation of plant matter (Ha¨ttenschwiler and Vitousek 2000). Among the commonly used C sources, the high heterogeneity of terrestrial environments selects for adaptation to indigenous C sources. Bacteria from the moss (S2, S3, and S6) and the fell field (S5) plots are similar in their physiological adaptation to use a limited number of C sources, but differ in their rates of catabolic activities (AWCDN) and preferred biochemical categories of substrates. Except the commonly used polyols, bacteria from the moss plots are adapted to utilize amino acids/amines and phenolic compounds while those from the fell field are adapted to use carbohydrates and carboxylic acids. The high physiological adaptation of the bacteria of the vascular plots to the local C sources is manifested also by the high rate of benzoic acid utilization including 2-Hydrohybenzoic (salicylic) acid which is an allelopathic substance used by plants in their survival strategy (Kupferwasser et al. 2003; Vasyukova and Ozeretskovskaya 2007). Soil bacteria are not only resistant to this antiseptic agent but they use it as one of the most available C sources. Amino acids are the most intensively utilized C sources in soils of moss plots, but not in the vascular plots. The shift in the substrate utilization pattern of bacteria from the vascular plots is assumed to be a result of competition between bacteria and higher plants for amino acids. Hill et al. (2011) estimated that the rates of peptide and amino acid N uptake per unit ground area were of the same order for both D. antarctica and microbes; hence, D. antarctica has the potential to be an effective competitor for organic N. Hill et al. 2011 also reported that D. antarctica acquired N as short peptides more than 160 times faster than the mosses. The higher competition of D. antarctica for N likely reduced the importance of amino acids as nutrients for soil bacteria in the vascular plots but not in the moss plots. Mosses are not effective competitors for soil amino acid N because of their alternative pathways for supplying with N entering into symbiotic relationships with cyanobacteria or other N-fixing bacteria. The low rate of amino acid utilization in the fell field (S5) plot is probably a result of their low availability in these environments. Buyer et al. (2001) reported that the distribution of proteins into the soil depths depends on the type of environment; amino acids are located in the topsoil of vegetated environments and migrate into the deeper layers of the fell fields making them unavailable for bacteria inhabiting the topsoil. Bacteria from the fell fields are adapted to utilize carbohydrates, mainly Glycogen (energy
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pool) and Cellobiose (derivatives of Cellulose), as well as Galacturonic acid, which is a component of bacterial mucilage (Nichols et al. 2005). The CLPP of the fell field bacteria closely corresponds to the findings of high cyanobacterial abundance (Kenarova and Bogoev 2002) and the suggestion of site-specific adaptation of copiotrophs to utilize intensively some components of mucilage synthesized by photoautotrophs.
Conclusion The results confirm the hypothesis indicating that the type of vegetation or the absence of it contributes to the site specificity of the pattern of bacterial C source utilization rate and community physiological diversity. Bacterial physiological diversity differentiates between three distinguishable groups of soil habitats: fell field, vascular plant, and moss plots with increasing physiological diversity in that order. Soil bacteria intensively use polyols, which are widespread antifreeze agents among cold-adapted organisms. The site specificity of bacterial metabolic activity (AWCDN and CLPPs) depends on the presence/absence and the type of vegetation. Bacteria from the vascular plots have the widest metabolic capacity utilizing the EcoPlate’s C sources at relatively equal rates with an insignificant preference to polyols and phenolic compounds. Bacteria from the moss plots have the highest catabolic activity which is based mainly on the utilization of polyols, amino acids/amines, and phenolic compounds. Bacteria from the fell field are very specific in C source utilization as the highest catabolic rates are for polyols, carbohydrates, and carboxylic acids. Acknowledgments We are grateful to Dr. Valentin Andreev, member of the Bulgarian Antarctic Institute, for soil samples’ collection. This study was supported by the National Scientific Foundation of Bulgaria, Project D RNF 02.2.2009. Conflict of interest The authors declare that they have no conflicts of interest.
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