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Journal ArticleDOI

Hypolithic and soil microbial community assembly along an aridity gradient in the Namib Desert

09 Feb 2013-Extremophiles (Springer Japan)-Vol. 17, Iss: 2, pp 329-337

TL;DR: Although null models for patterns in microbial communities were not supported by experimental data, the amount of unexplained variation suggests that stochastic processes also play a role in the assembly of such communities in the Namib Desert.
Abstract: The Namib Desert is considered the oldest desert in the world and hyperarid for the last 5 million years. However, the environmental buffering provided by quartz and other translucent rocks supports extensive hypolithic microbial communities. In this study, open soil and hypolithic microbial communities have been investigated along an East–West transect characterized by an inverse fog-rainfall gradient. Multivariate analysis showed that structurally different microbial communities occur in soil and in hypolithic zones. Using variation partitioning, we found that hypolithic communities exhibited a fog-related distribution as indicated by the significant East–West clustering. Sodium content was also an important environmental factor affecting the composition of both soil and hypolithic microbial communities. Finally, although null models for patterns in microbial communities were not supported by experimental data, the amount of unexplained variation (68–97 %) suggests that stochastic processes also play a role in the assembly of such communities in the Namib Desert.

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Stomeo, F. et al. (2013). Hypolithic and soil microbial community assembly along an aridity
gradient in the Namib Desert.
Extremophiles, 17: 329 337.
http://dx.doi.org/10.1007/s00792-013-0519-7
University of the Western Cape Research Repository don.cowan@up.ac.za
Hypolithic and soil microbial community assembly along an aridity
gradient in the Namib Desert
Francesca Stomeo, Angel Valverde, Stephen B. Pointing, Christopher P. McKay, Kimberley A.
Warren-Rhodes, Marla I. Tuffin, Mary Seely and Don A. Cowan
Abstract
The Namib Dessert is considered the oldest desert in the world and hyperarid for the last
5 million
years. However, the environmental buffering provided by
quartz and other
translucent rocks supports extensive
hypolithic microbial communities. In this study, open
soil
and hypolithic microbial communities have been investigated along an EastWest
transect characterized by an
inverse fog-rainfall gradient. Multivariate analysis showed
that
structurally different microbial communities occur in soil and in hypolithic zones. Using
variation partitioning,
we found that hypolithic communities exhibited a fog-related
distribution as indicated by the significant East
West clustering. Sodium content was
also an important environmental factor affecting the composition of both soil
and
hypolithic microbial communities. Finally, although
null models for patterns in microbial
communities were not supported by experimental data, the amount of unexplained variation
(6897 %) suggests that stochastic processes also play a role in the assembly of such
communities in the Namib Desert.
Introduction
With an estimated age of 80 million years, the Namib
Desert, located in the southwest of
the African continent, is
believed to be the oldest dryland region in the world
(Prestel et al.
2008). Although hyper-aridity, high winds,
extreme temperatures and low nutrient
availability all impose constraints on microbial life, microbial communities proliferate in
these environments in refuge niches
(Pointing and Belnap 2012; Chan et al. 2012). One
of the most studied of these habitats is the lithic environment, where microbial
communities have colonized the underside
(hypolithic) or interior (endolithic) of
translucent rocks.
Such communities are very widespread, but dominate standing biomass in the driest
(Warren-Rhodes et al. 2006; 2007; Walker and Pace 2007; Azua-Bustos et al. 2011) and
coldest (de la Torre et al. 2003; Pointing et al. 2009; Cary
et al. 2010) deserts on Earth.
Translucent rocks create microclimatic conditions where hypolithic microorganisms
benefit
from greater physical stability, desiccation buffering, increased water availability and
protection from UV
fluxes (Pointing et al. 2009; Cowan et al. 2010; Wong et al. 2010).

2
Hypolithic communities in extreme desert environments may be the dominant sites of
primary productivity (Tracy et al. 2010), contributing significantly to N input and carbon in the
form of biomass (Cockell and Stokes 2004; Cowan et al. 2011). Hypoliths have been proposed
as viable model systems for understanding the mechanisms underlying
the assembly of
bacterial communities (Caruso et al. 2011), a major goal in microbial ecology.
All studies on hypoliths have indicated that these communities are most commonly
dominated by photosynthetic cyanobacteria, with a taxonomically diverse heterotrophic
component dominated by the phyla Acidobacteria, Actino-bacteria, Bacteroidetes and
Proteobacteria (Schlesinger
et al. 2003; Warren-Rhodes et al. 2006, 2007; Pointing et al.
2007, 2009; Wood et al. 2008; Chan et al. 2012). However,
the processes shaping the
assembly of such communities are still poorly understood. Historically, community ecologists
have focused on environmental conditions and interspecific
interactions (deterministic
factors) to explain how species
diversity and composition vary along environmental and/or
spatiotemporal gradients (Chase 2007). More recently, ‘‘neutral’’ theory (Hubbell 2001) has
suggested that many
natural patterns can be recreated only by considering stochastic
assembly processes like birth, death, colonization, extinction and speciation. It is now
widely accepted that community assembly can be either regulated by (1) purely
deterministic processes, where habitat heterogeneity creates
different niches in which
different groups of species are favored; (2) purely stochastic processes; or (3) the
interaction between stochastic and deterministic processes
(Chase 2010; Ofiteru et al.
2010).
Understanding the mechanisms that regulate microbial community assembly is of special
interest, because such
mechanisms sustain biodiversity and ecosystem functioning. This is
of particular relevance in arid systems, which
are highly susceptible to disturbance, and
may be particularly threatened by accelerated rates of climate change
(Seager et al. 2007).
Recently, it has been demonstrated
that on a global scale stochastic and deterministic
processes
interact in structuring desert microbial communities (Caruso et al. 2011). In this
instance, whilst heterotrophic
assemblages could be explained partially by climatic and
environmental variables, phototrophic bacterial assemblages exhibited strong signals
related to demographic stochasticity. The latter has been attributed to the lack of gene
flow among cyanobacteria in hypolithic systems
(Bahl et al. 2011). Under harsh
environmental conditions
(such as those present in desert ecosystems), species sorting is
thought to result in more deterministic communities (Chase 2007, 2010).
Water is a scarce resource in the Namib Desert. The annual mean rainfall at Gobabeb,
in the central Namib
Desert, recorded from 1962 to 2010, was 25 mm (Eckardt
et al.
2012) occurring as sporadic events. Precipitation,
therefore, is not a reliable source of
water for sustaining
life in the central arid region of this desert. Relative humidity and
dew are important sources (Henschel and
Seely 2008), but fog events, which are common
in a zone
from the coast to approx. 60 km inland (Eckardt et al. 2012), are thought to be
the dominant source of bioavailable water in the region (Bu¨del et al. 2009). Water
availability is considered to be one of the most important factors
affecting hypolithic
http://repository.uwc.ac.za

3
microbial populations in many terrestrial environments (Warren-Rhodes et al. 2006;
Pointing
et al. 2007; Azua-Bustos et al. 2011; Cary et al. 2010; Pointing and Belnap
2012). Both available liquid water,
derived from rainfall (Warren-Rhodes et al. 2006;
Pointing
et al. 2007) and fog (Azua-Bustos et al. 2011), have been
shown to be key
determinants of hypolithic communities in hyper-arid regions. However, to our knowledge,
the influence of water regime (in terms of fog and rainfall sources)
in shaping the structure
of desert microbial communities on
a local scale has never been investigated.
Here, we assessed the relative importance of abiotic factors, such as water regime and soil
chemical properties in
explaining microbial community composition on a local scale.
Specifically, we hypothesized that water regime (i.e. fog- vs.
rainfall-dominated) is a driver of
local-scale variation in microbial community composition. We have examined the structure
of general (open soil) and specific (hypolithic)
microbial communities through an East
West transect across
the Namib Desert. This transect has a well-established water availability
gradient determined by fog and rainfall (Eckardt et al. 2012). We compared the meta-
community structure of
hypolithons to those in adjacent open soil at each site, by
means of
variation partitioning and null model analysis, in an
attempt to unravel the processes that
govern their assembly.
Materials and methods
Sample collection and physicochemical analysis Samples were collected in April 2010 at ten
sites along a V-shaped (northwest-southwest-northeast) transect that extended 100 km
inland from Walvis Bay (Fig. 1). At each GPS-logged site, 5 independent hypolithic
community samples were pooled into sterile Whirl-Pack sample bags (Nasco, WI, USA). All
rocks were similar in composition (quartz), size (1215 cm) and thickness (57 cm) to
minimize the influence of these factors in shaping the structure
of microbial communities.
Simultaneously, multiple open
soil samples (05 cm in depth) were pooled, homogenized,
and directly transferred into sterile 50 ml tubes. Samples
were stored at 4 °C after
sampling and during transport to
the laboratory, and then stored at -80 °C until
further
analysis.
Total carbon, nitrogen, pH, water content, potassium,
calcium, sodium and magnesium
were measured for each soil sample at BemLab (SANAS Accredited Testing Laboratory,
Somerset West, South Africa), according to standard quality control procedures (SSSA
1996).
For clarification (see Fig. 1), western samples (G3, G9,
G12, G15 and G18) are referred to
collectively as fog-dominated, while eastern samples (G20, G22, G2, G27 and
G29) are
referred to as rainfall-dominated, following the climatic zonation of the Namib Desert
(Eckardt et al. 2012).
DNA extraction, PCR amplification and T-RFLP
analysis
Metagenomic DNA was extracted from triplicate sub-samples using the PowerSoil DNA
Isolation Kit (MoBio,
West Carlsbad, CA, USA) following the manufacturer’s
instructions.
http://repository.uwc.ac.za

4
PCR amplification was performed with primer
sets E9F (Hansen et al. 1998): 5
0
-
GAGTTTGATCCTG
GCTCAG-3
0
and U1510R (Reysenbach and Pace 1995): 5
0
-
GGTTACCTTGTTACGACTT-3
0
, for bacteria; and 27F1 (Jungblut et al. 2005): 5
0
-
AGAGTTTGATCCTGGCT-
CAG-3
0
and 809R (Jungblut et al. 2005): 5
0
-GCTTCGG-
CACG
GCTCGGGTCGATA-3
0
, for cyanobacteria. In both
primer sets, the forward primer was
labeled with the fluorescent dye 6-FAM (6-carboxyfluorescein) at the
5
0
end.
PCRs were
carried out in triplicate 50
ll
volumes to
minimize reaction bias. Each PCR
contained 19 PCR
buffer, 200 lM of each dNTP, 0.5 lM of each primer,
0.2 U of
DreamTaq polymerase (Fermentas, USA) and
10 ng of template. Thermal cycling
conditions for bacterial PCR were a 4-min denaturation step at 94 °C; 30 cycles at 94 °C for
30 s, 52 °C for 30 s and 72 °C for 105 s; and a final extension step at 72 °C for 10 min. For
cyanobacteria-specific amplifications, PCR conditions were a denaturation step at 94 °C
for a 4 min; 30 cycles at 92 °C for 20 s,
50 °C for 30 s and 72 °C for 1 min; and a final
extension
step at 72 °C for 7 min. After amplification, the triplicate PCRs were pooled and
purified with an Illustra GFX
TM
PCR DNA and Gel Band Purification kit (GE Healthcare,
UK), digested separately with HaeIII and MspI (Fermentas,
USA) and purified again before
the electrophoretic separation using an ABI 3130XL DNA sequencer (Applied
Biosystems,
USA). Terminal restriction fragments (T-RFs)
generated by Peak Scanner software v1.0
(Applied Biosystems) were filtered and binned by the method developed
by Abdo et al.
(2006).
Statistical analysis
Analysis of variance followed by two sample t tests was
used to determine if there were
significant differences in operational taxonomic unit (OTU) numbers between sample
group (i.e. hypolith vs. soil and fog-dominated vs. rainfall-dominated) at a 95 % confidence
interval.
http://repository.uwc.ac.za

5
Sample-dissimilarity matrices were generated using the BrayCurtis coefficient on
Hellinger-transformed data (Legendre and Gallagher 2001). Community structure was
analyzed using non-metric multidimensional scaling
(nMDS). Since nMDS ordination
uses an iterative algorithm, an important component of a nMDS plot is a measure of the
goodness of fit of the final plot (i.e. stress
value). A stress value greater than 0.2 indicates
that the plot is close to random, stress less than 0.2 indicates a useful
two-dimensional
picture, and less than 0.1 corresponds to an ideal ordination (Clarke 1993).
Between-group variation was tested by pairwise analysis
of similarity (ANOSIM). Within-
group variation (scatter in the nMDS ordination plots) was compared by dispersion
analysis; i.e. by evaluating the differences between sample type and the group centroid
(Anderson et al. 2006). Physicochemical data, except pH, were log
10
-transformed.
Climate regime (fog-dominated vs. rainfall-dominated) was included in the models as a
dummy (qualitative) variable. Spatial variables were derived from longitudelatitude
coordinates using the principal coordinates of
neighbor matrices (PCNM) procedure
(Griffith and Peres-Neto 2006). Separated forward selection of the environmental and
spatial variables was done to find the set of
parameters that could best explain the
variation in community composition (Ramette 2007). We also used
redundancy analysis
(RDA) variation partitioning (Peres-Neto et al. 2006) to determine how much of the
variation in microbial community composition could be attributed to environment, E, and
space, S. The different components are total explained variation [E
?
S], environmental
variation [E], spatial variation [S], environmental variation without a spatial component
[E|S], and spatial variation without
the environmental component [
S
|
E
]. Fraction [
U
]
is the
amount of variation that remains unexplained (1
-
[
E
?
S
]).
Significance testing was
done with 999 Monte Carlo permutations, and all R
2
values were calculated and adjusted
http://repository.uwc.ac.za

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References
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Journal ArticleDOI
K. R. Clarke1Institutions (1)
01 Mar 1993-Austral Ecology
TL;DR: Which elements of this often-quoted strategy for graphical representation of multivariate (multi-species) abundance data have proved most useful in practical assessment of community change resulting from pollution impact are identified.
Abstract: In the early 1980s, a strategy for graphical representation of multivariate (multi-species) abundance data was introduced into marine ecology by, among others, Field, et al. (1982). A decade on, it is instructive to: (i) identify which elements of this often-quoted strategy have proved most useful in practical assessment of community change resulting from pollution impact; and (ii) ask to what extent evolution of techniques in the intervening years has added self-consistency and comprehensiveness to the approach. The pivotal concept has proved to be that of a biologically-relevant definition of similarity of two samples, and its utilization mainly in simple rank form, for example ‘sample A is more similar to sample B than it is to sample C’. Statistical assumptions about the data are thus minimized and the resulting non-parametric techniques will be of very general applicability. From such a starting point, a unified framework needs to encompass: (i) the display of community patterns through clustering and ordination of samples; (ii) identification of species principally responsible for determining sample groupings; (iii) statistical tests for differences in space and time (multivariate analogues of analysis of variance, based on rank similarities); and (iv) the linking of community differences to patterns in the physical and chemical environment (the latter also dictated by rank similarities between samples). Techniques are described that bring such a framework into place, and areas in which problems remain are identified. Accumulated practical experience with these methods is discussed, in particular applications to marine benthos, and it is concluded that they have much to offer practitioners of environmental impact studies on communities.

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  • ...1 corresponds to an ideal ordination (Clarke 1993)....

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TL;DR: It is evident that biofilm formation is an ancient and integral component of the prokaryotic life cycle, and is a key factor for survival in diverse environments.
Abstract: Biofilms--matrix-enclosed microbial accretions that adhere to biological or non-biological surfaces--represent a significant and incompletely understood mode of growth for bacteria. Biofilm formation appears early in the fossil record (approximately 3.25 billion years ago) and is common throughout a diverse range of organisms in both the Archaea and Bacteria lineages, including the 'living fossils' in the most deeply dividing branches of the phylogenetic tree. It is evident that biofilm formation is an ancient and integral component of the prokaryotic life cycle, and is a key factor for survival in diverse environments. Recent advances show that biofilms are structurally complex, dynamic systems with attributes of both primordial multicellular organisms and multifaceted ecosystems. Biofilm formation represents a protected mode of growth that allows cells to survive in hostile environments and also disperse to colonize new niches. The implications of these survival and propagative mechanisms in the context of both the natural environment and infectious diseases are discussed in this review.

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  • ...By contrast, if environmental factors and species interaction are the principal acting forces, shifts in key environmental variables such as water availability, salinity and pH may be responsible for the spatial structures found in species assemblages (Fierer and Jackson 2006; Lozupone and Knight 2007; Pointing et al. 2007)....

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  • ...…factors and species interaction are the principal acting forces, shifts in key environmental variables such as water availability, salinity and pH may be responsible for the spatial structures found in species assemblages (Fierer and Jackson 2006; Lozupone and Knight 2007; Pointing et al. 2007)....

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