Open Journal of Soil Science, 2012, 2, 333-340
http://dx.doi.org/10.4236/ojss.2012.23039 Published Online September 2012 (http://www.SciRP.org/journal/ojss) 333
Microarray Technology and Its Applicability in Soil
Science—A Short Review
Stella Asuming-Brempong
Department of Soil Science, School of Agriculture, University of Ghana, Legon, Ghana.
Received May 30th, 2012; revised June 30th, 2012; accepted July 10th, 2012
ABSTRACT
The GeoChip is a glass slide containing oligonucleotide probes targeting genes that confer specific function to micro-
organism. The GeoChip has been used to dissect the microbial community functional structure of environmental sam-
ples. The PhyloChip is a glass slide containing oligonucleotide probes of the 16S rRNA genes and it offers tremendous
potential to monitor microbial population. Below ground microbial community can be linked to the above ground plant
community by the use of these Chips in a high throughput manner. This review seeks to determine the various roles of
the GeoChip and the PhyloChip in soil microbial ecology studies. During biostimulation of uranium in groundwater,
microbial community dynamics was linked to functional processes and in global warming studies, microbial response to
functional gene structure has been possible by the use of the GeoChip. The PhyloChip, on the other hand, provides
more comprehensive survey of the microbial diversity, composition and structure and are less susceptible to the influ-
ence of dominance in microbial community. Some of the concerns regarding th e use of compost in agricultural so ils i.e.
the spread of human, animal and plant pathogens were reduced when the PhyloChip was used to monitor composting.
Keywords: GeoChip; PhyloChip; Biodiversity; Microarray
1. Introduction
The soil environment is highly complex with the diver-
sity of soil microorganisms being extremely high.
Through DNA re-association kinetics, it is known that a
gram of soil contains more than 4000 different genomes.
Diverse systems such as soil, maybe more resilient to
perturbation because removal of a portion of microbial
components or the microbial component being com-
promised in some way, others that prevail will be able to
compensate. However, more diverse systems may be less
efficient since a greater proportion of available energy is
used in generally countering competitive interactions
between the various microbial components. Microorga-
nisms play unique roles in ecosystem functions such as
biogeochemical cycling of carbon, nitrogen, sulfur,
phosphorus and various metals. Microorganisms also
regulate nitrous oxide emissions in soil. However, the
precise roles of many of the microorganisms in these
cycles are unknown [1]. Owing to their extremely high
diversity and their as yet uncultivated status, microbial
detection, characterization and quantification in natural
systems are difficult especially in a large scale and in a
parallel and high throughput manner. Also, owing to the
high versatility, rapid adaptation of microbial populations,
high heterogeneity and microscale diversity in soils,
high-throughput methods have to be applied in order to
understand population shifts at a finer level and to be
better able to link microbial diversity with function ing of
ecosystems.
Microarrays represent a powerful tool for the parallel,
high-throughput identification of many microorganisms
in different environmental samples. A microarray is
made up of thousands of spots on a slide with each spot
containing multiple copies of unique nucleic acid se-
quences that correspond to a single gene. Microarray
technology facilitates the detection of genetic sequences
or expressed gene from particular samples in a high
throughput format. In the case of expressed genes, micro-
arrays are popular due to their unique ability to q uery the
mRNA expression levels of thousands of genes (poten-
tially all of the genes of an organism) simultaneously
with relatively high specificity, providing a snapshot in
time of the overall gene expression of the system under
study. Compared to conventional membrane-based hybri-
dization methods, microarrays offer the additional advan-
tages of rapid detection, low cost, automation and low
background level [2].
Living organisms contain thousands of genes that
control cellular activities in their cells. Studying one
component of the cell at a time will not give a complete

Microarray Technology and Its Applicability in Soil Science—A Short Review 334
picture of the cellular activities, it is on ly through a com-
prehensive integration of the entire molecular machinery
controlling the cell that a thorough understanding can be
gained. Similarly, a comprehensive integration of the
microbial activities in enviro nmental samples such as soil
can be captured by the use of microarray technology and
thus obtaining a holistic view of the microbial com-
munity. The traditional soil microbiological approaches,
analyze material derived from microbial growth such as
liquid cultures or colonies obtained by plating. However,
such methods have often met with strong limitations, the
reason being that only a small fraction of the microbiota
(<0.01%) in soil can be accessed on the basis of cul-
tivation, thus a complete picture of the microbial com-
munity is not obtained and about 99% of the microbial
population in soil still remains unknown.
Also, some soil microbiologists have focused on evi-
dence of processes and activities such as respiration and
enzymatic transformation of adding substrates to soil.
Measurements of soil processes give insight into micro-
bial mediated transformations in soils. Such microbial
mediated transformations do not inform us of the mecha-
nisms, microbial functional composition and diversity
that underlie the process level differences. Thus, relating
microbial diversity and function to ecological processes
remains a critical issue in the study of soil microbial
ecology [1,3]. This review seeks to determine the various
roles of the functional gene array (the GeoChip) and the
PhyloChip in soil microbial ecology studies.
2. GeoChip and Its Relevance
The GeoChip is made of a glass slide containing
thousands of bound oligonucleotide probes (of about 40 -
70 mers long) targeting genes that confer specific fun-
ction to the microorganism. Thus, one can monitor the
levels of thousands of functional genes simultaneously
thereby gaining a window into the soil microbial com-
munity function of an environmental sample. The Geo-
Chips 2 and 3 have so far been developed for soil micro-
bial ecological studies. Geochip 2.0 contains over 24,000
probes covering more than 10,000 genes distributed
among more than 150 functional groups involved in
nitrogen, carbon, su lphur cycling, phosphorus utilization ,
metal resistance, metal reduction and organic contami-
nant degradation [4]. GeoChip 2.0 is useful for studying
biogeochemical processes and functional activities of
microbial communities which is important to human
health, agriculture, energy, global climate change, ecosy-
stem management and environmental clean-up and re-
storation. Because the arrays contain probes from genes
with known biological functio n, they are useful in linking
microbial diversity to ecosystem processes and functions.
This array allows for a detailed analysis of the biogeo-
chemical gene profiles of soil microbe and is ideal for
understanding how these profiles change in response to
environmental perturbations and experimentally imposed
conditions [5,6]. To increase the confidence of detection,
multiple probes for each sequence or each group of se-
quences were designed for the GeoChip 2.0. The positive
controls are made of 16S rRNA gene probes (192 probes)
and negative controls with 10 probes from human genes
(960 spots) and blanks [4]. Later experiments showed
that the GeoChip 2.0 was highly specific to their corre-
sponding targets at 45˚C to 50˚C and with 50% forma-
mide during hybridization.
The GeoChip 3.0 is a more comprehensive microarray
than GeoChip 2.0 which currently is available for micro-
bial community studies. The developed GeoChip 3.0 can
be used as a generic high throughput tool to address
various biological questions in different systems such as
bioreactors, soils, groundwater, marine, sediments and
animal guts. The GeoChip 3.0 has about 28,000 probes
covering 57,000 gene variants from 292 functional gene
families involved in carbon, nitrogen, phosphorus and
sulphur cycles, energy metabolism, antibiotic resistance,
metal resistance and organic contaminant degradation. It
has several other distinct features and one of such is the
gyrB gene for phylogenetic analysis [7]. The gyrB gene,
encodes DNA gyrase β-subunit gene that has been used
to differentiate closely related species/strains. Phyloge-
netic tree based on gyrB results in a magnitude higher
resolution than a tree based on 16S rRNA gene [8,9].
GeoChip 3.0 contains eight degenerate probes for the
16S rRNA genes and 672 unique probes designed from
hypothetical genes of seven sequenced genomes of
hyperthermophiles for negative controls. In addition, a 50
mer common oligonucleotide reference standard (CORS)
is mixed with all these probes, including gene probes and
controls and co-spotted on GeoChip 3.0 as a common
reference standard for data normalization and com-
parison [10].
In addition, the GeoChip probes are selected from
coding sequences of functional genes, GeoChip can be
used not only for measuring the abundance, but also for
the expression of functional genes in a microbial com-
munity if high quality of mRNAs can be recovered from
environmental samples. Thus, probing mRNA with the
developed GeoChip will provide valuable insight into
functions of the genes/populations in critical geoche-
mical and ecological processes. Su ch information will be
useful in establishing mechanistic linkages between di-
versity of microbial genes/populations and ecosystem
functions.
3. The Usefulness of the GeoChip in Soil
Microbial Ecological Studies
Studies have demonstrated that GeoChip is an ideal tool
for dissecting the microbial community functional struc-

Microarray Technology and Its Applicability in Soil Science—A Short Review 335
ture in both natural and contaminated environments
[11-13]. Using the GeoChip 2.0, Liang et al. [14] found
high abundance of genes involved in organic conta-
minant degradation in an oil-contaminated site indicating
the biodegradation potential of the indigenous microor-
ganisms for oil contaminant degradation. Also, the exi-
stence of key genes at that contaminated site (such as
genes encoding alkane monooxygenase and benzene dio-
xygenase) involved in hydrocarbon degradation across
the oil-contaminated site implied that stimulating indi-
genous microorganisms could be a valid option for reme-
diating oil-contaminated sites. However, the degradation
process might be influenced by low nutrients [15,16].
Nitrogen could be limited because of the decrease in
nitrogen cycling genes with oil concentration which may
indicate decrease in nitrogen-cycling activity. Adjust-
ment of the carbon/nitrogen ratio by adding nitrogen
maybe important for in situ bioremediation of oil con-
taminated fields.
He et al. [4] monitored microbial community dynamics
in groundwater undergoing in situ biostimulation for
uranium reduction by using the GeoChip. Their results
showed that the GeoChip is able to reveal microbial
community differences and that it could track bioremedi-
ation processes for linking microbial populations to fun-
ctional processes. During the uranium reduction period,
both FeRB (iron reduction bacteria) and SRB (sulphate
reduction bacteria) populations reached their highest
levels followed by a gradual decrease over 500 days.
Consequently, the uranium in groundwater and sediments
reduced and thus uranium concentrations in groundwater
decreased. Because Geobacter-type FeRB and some SRB
can use U(VI) as electron acceptor by obtaining energy
for growth. The uranium concentrations in the ground
water were significantly correlated with the total abun-
dance of c-type cytochrome genes from Geobacter-type
FeRB and Desulfovibrio-type and with the total abun-
dance of dsrAB (dissimilatory sulfite reductase). Experi-
mental results from GeoChip analysis suggested that
Geobacter-type FeRB and SRB played significant roles
in uranium reduction suggesting that uranium remedi-
ation using indigenous microorganisms could be a valid
option in heavily uranium contaminated sites.
Other types of microarrays have been developed for
application in bioremediation studies. An example of
such an array was developed by Rhee et al. [17], that
comprised of 1662 unique and group-specific 50 mer
probes targeting most of the genes and pathways known
to be involved in biodegradation and metal resistance. Its
applicability was demonstrated in naphthalene-amended
enrichment cultures as well as in soil microcosm experi-
ments, the soil contai ning polyc hl orinated bipheny l .
A three year experimental field warming (+0.5˚C to
2˚C) to determine microbial response to global warming
using the GeoChip microarray analyses showed signi-
ficant warming effects on functional communities, speci-
fically in the N-cycling microorganisms [18]. The num-
ber of functional genes detected on the GeoChip was
significantly lower in the plots subjected to higher tem-
perature as compared with the controls. For a range of
gene families (amo A, cellulase, chitinase, laccase, nif H,
nir K, nir S, nos Z, pmo A and urease) the number of
variants detected on the GeoChip was generally lower in
the plots subjected to higher temperature as compared
with the control plo ts.
Understanding the factors influencing methanotrophs
diversity and activity is of high importance in order to
adapt environmental remediation strategies for optimal
methane oxidation. Methanotrophs play an essential role
in mitigating the greenhouse effect by metabolizing most
of the methane produced for example in landfill sites.
The gene encoding the particulate methane monooxy-
genase (pmo A) the key enzyme in methane oxidation
was chosen for the development of a microarray to
identify methanotrophs [19], bacteria that are capable of
utilizing methane as their sole source of carbon and
energy. The improved pmo A microarray contained 68
(18 - 28 mer) probes targeting all known methanotrophs
including uncultivated members as well as the related
ammonium monooxygenase (amo A) genes of ammonium
oxidizing bacteria. The pmo A microarray identified
Methylocystis spp. was dominating and was an efficient
methane oxidizer.
The use of the functional gene array provided insight
into the forces driving important processes of terrestrial
Antartic nutrient cycling [20]. In the Antarctica, denitrifi-
cation genes were linked to higher soil temperatures and
N2 fixation genes were linked to plots mainly vegetated
by lichens. The relative detection of cellulose degra-
dation genes was correlated with temperature and micro-
bial carbon fixation genes were more present in plots
principally lacking vegetation. Yergeau et al. [20] also
showed a significant correlation between cellulase acti-
vity and the number of cellulase gene variants deter-
mined by the functional gene array. In a similar study,
Reeve et al. [21] observed a significant correlation be-
tween cellulase gene signal intensity and cellulase acti-
vity in the soil (p < 0.01), correlation between dehydro-
genase gene signal intensity and dehydrogenase activity,
urease gene signal intensity and urease activity and so
forth demonstrating that functional gene array can to
some extent complement soil process measurements.
4. Some Challenges to Addressing the Use of
GeoChip
1) High quality community DNA is required to mini-
mize experimental variations for improving microarray-
bored quantitative accuracy. Impure community DNA

Microarray Technology and Its Applicability in Soil Science—A Short Review 336
with humic acid can affect amplification reactions. Hence
to increase sensitivity to amplification reactions, pre am-
plification by rolling circle can be included in the metho -
dology. This allows for the amplification of low micro-
bial biomass communities before microarray hybridi-
zation and thereb y increasing the signal levels from such
environmental samples [22]. The reaction involves the
use of spermidine and single-strand binding protein
added to the reaction mix to facilitate amplification. The
reactions are then incubated and the enzymatic reaction
stopped and the amplification product was used for
labeling.
2) The target sequences in public database increase
exponentially and hence the GeoChip needs to be con-
tinuously updated. That could mean the quantity of data
generated by microarray studies of environmental sam-
ples will be enormous but rapidly processing, comparing,
interpreting hybridization data still remain difficult en-
deavors.
3) A large component of the soil microbial population
may be inactive. Soil DNA hybridizations cannot diffe-
rentiate between active and inactive microbial cells and
potential contribution to signal intensity of the inactive
i.e. spores or dead biomass or damaged copies of genes
cannot be determined. For this reason, caution should be
used when interpreting DNA functional gene array [23].
To overcome this criticism, researchers are beginning to
use RNA for environmental microarray analysis [17,24].
Analysis of mRNA would allow more direct connection
to be drawn. Recent research on environmental samples
using both mRNA and genomic DNA microarrays has
shown that the dominant species identified by mRNA
arrays are also the most abundant in terms of genomic
DNA [25]. This suggests that connection drawn between
genomic DNA and biogeochemical cycles is reasonable.
Yergeau et al. [20] had microarray-based results that
were confirmed for a number of gene families using
specific real-time PCR, enzymatic assays and process
rate measurements suggesting a quantitative relationship
between microarray signals and environmental gene den-
sities. The significant correlations between the enzymatic
activities measured in soil and the microarray data
provided so me indication that the detected genes are also
expressed in the soil system examined.
5. The PhyloChip
The PhyloChip is made of slide on which are attached
thousands of oligonucleotide probes (of about 50 mers
long) of the 16S rRNA genes. The PhyloChip microarray
allows the molecular biologist to monitor the levels of
16S rRNA genes (thousands of them) simultaneously
thereby giving an ‘inner picture’ of microbial community
in an environmental sample such as so il. PhyloChip (G2)
consists of 506,944 probe features, and of these features,
297,851 are oligonucleotide perfect match or mismatch
(MM) probes of 16S rRNA genes [26,27]. Depending on
the type of probe set used, the PhyloChip can allow the
parallel detection of up to several thousand microbial
strains, species, genera or higher taxonomic groups in a
single experiment [19,28,29]. The parallel detection of
numerous 16S rRNA genes makes the PhyloChip useful
for environmental studies of phylogenetically diverse
microbial groups.
In a variety of environments, such as contaminated
sites [26,28] air [27] water [30] soil [31-33], the Phylo-
Chip has been u sed to detect micro organisms. In addition ,
the PhyloChip can detect much more bacterial taxa as
compared with the 16S rRNA gene-based clone library
approach [28,34] suggestin g that the PhyloChip provides
more comprehensive surveys of microbial diversity,
composition and structure. Furthermore, such micro-
array-based approaches are less susceptible to the in-
fluence of dominance in microbial communities, where-
by sequences of more abundant members mask the
presence of other numerically significant taxa and rare
species [34]. PhyloChip has been considered a powerful
tool to comprehensively and rapidly analyze microbial
communities.
6. The Use of the PhyloChip in Soil
Microbial Community Studies
Among the concerns regarding the composting process
and the use of compost in agriculture and horticulture are
the survival and spread of animal, human and plant
pathogens. Thus any composting process must be cap-
able of eliminating any health risk th at may be present in
the end product. The microarray technology offers tre-
mendous potential to monitor the detection of pathogens
and of beneficial microbial populations during compost-
ing and this helps in the management of the compost
before being sold to the public. A microarray was de-
signed targeting the species of microorganisms usually
encountered in compost [35] and it offered potential for
process monitoring, and the detection of pathogens as
well as of beneficial microbes [35]. This microarray con-
tained probes targeting actinomycetes and other orga-
nisms in the composting process and 35 probes specific
to other pathogens. The use of this microarray reduced
the concerns regarding the use of composts on agricul-
tural soils and the spread of human, animal and plant
pathogens.
He et al. [36] used the PhyloChip to determine the
impact of elevated CO2 on the diversity and function of
soil microbial communities. Richness of soil microbial
communities at the Phylum, Class, Orders, Families and
Subfamilies levels i.e. at the different taxanomic levels
was detected. Thus, the taxonomic structure of microbial
communities was linked with soil and plant properties

Microarray Technology and Its Applicability in Soil Science—A Short Review 337
through Mantel an d such tests to know the extent, the soil
and plant properties helped to shape the taxanomic stru-
cture. Shifts in the richn ess, composition and structure of
soil microbial communities under elevated carbon dio-
xide were observed [36]. As noted by Cheneby et al. [ 37]
and Hallin et al. [38], shifts in diversity will not neces-
sarily alter the ability of soil microb es to perform biogeo-
chemical functions.
The PhyloChip allows for the simultaneous detection
of thousands of bacterial and archeal taxa and has been
shown to reveal a broader range of diversity than mo-
desty sized 16S rRNA gene libraries for soil, water and
aerosol samples [33]. PhyloChip analyses also offer the
opportunity to link microbial community composition to
analyses of enzyme activity, density of functional gene
families and the distribution of nutrient cycle-related fun-
ctional gene sequences. It is possible to use both the
GeoChip and the PhyloChip in an experiment [39]. To
determine whether phylogenetic community structure,
based on PhyloChip analysis was related to the distri-
bution of microbial genes involved in nutrient cycling,
the PhyloChip data was compared to the GeoChip data.
Results showed that communities with more similar taxa
composition were also more closely related in their
functional genes supporting the notion that the functional
genes detected in soils are strongly linked to community
composition as determined by 16S rRNA gene-based.
Such analysis provides evidence for a strong link be-
tween composition and functional gene distribution in
Antarctic soils.
Like other high-throughput technologies, however,
PhyloChip has its limitations. For example, PhyloChip
only detects known sequences already present in a data-
base at the time of probe design, so the G2 PhyloChip
may not fully cover the species richness of soil microbial
communities. Another limitatio n might be to improve th e
sensitivity and selectivity of the analysis. To discover
unkown 16S rRNA genes, future investigations may use
high-quality, full-length sequencing as a complementary
approach to further understand the taxonomic and phy-
logenetic diversity, composition, structure and function
of the soil microb ial communities.
Integral to most methods of microbial community
analysis is PCR amplification of small-subunit rRNA
genes, undertaken primarily to obtain a sufficient mass of
genetic material for analysis. This manipulation has well-
known inherent biases and potentially unknown effect.
The biggest bias is associated with multi-template PCR,
in which the relative abundances of 16S rRNA gene
signatures are distorted during PCR amplification [40].
The choice of primer pairs as well as the number of amp-
lification cycles strongly influence the ratios of ampli-
cons in the final pool when mixed templates are ampli-
fied by PCR [41]. Uneven amplification of mixed
templates precludes both accurate estimation of evenness
in communities and estimates of fold change in response
to perturbation or experimental manipulation. Other pro-
blems include formation of chimeric amplicons and dele-
tion and point mutations and amplification of conta-
minating DNA.
7. Methodology in the Use of the PhyloChip
and the GeoChip
PhyloChip analysis includes three major steps: 1) Ampli-
fication of the target genomic DNA using 16S rRNA
primers; 2) Adding an amount of the amplified DNA (50
- 500 ng PCR products) and hybridizing to the PhyloChip
[26,27]; 3) Hybridization data being processed prior to
statistical analysis. PCR amplification for microarray
hybridization is carried out using a bacterial specific 16S
rRNA primer e.g. 27 F1 and 1492 R and an archeal-
specific 16S rRNA primers. Many independent PCRs are
performed in a thermocycler with different annealing
temperatures (eg. 48˚C, 51.9˚C, 54.4˚C and 58˚C). The
samples are pooled per treatment then concentrated to a
smaller volume. The pooled PCR product of each sample
is spiked with known concentration of amplicons derived
from yeast and bacterial metabolic genes serving as
internal controls during the process of normalization.
This mixture is fragmented to 50 - 200 bp with DNase 1
and One-Phor-All buffer following the manufacturer’s
protocol. The mixture is normally labeled with biotin or
Cy5 or Cy3. Next, the labeled DNA is denatured at high
temperature (for instance at 99˚C) for 5 min and hybri-
dized to custom made Gene Chips. PhyloChip washing
and staining are performed according to the manu-
facturer’s prescription. Each PhyloChip is scanned and
recorded as a pixel image and the initial data acquisition
and intensity determination performed using standard
Affymetrix (or type of platform software used). Back-
ground subtraction, data normalization and probe pair
scoring are done.
To use GeoChip, soil DNA is extracted after mecha-
nical lysis in a CTAB buffer using a phenol-chloroform
purification protocol [42]. Other similar methods of soil
DNA extraction such as the one by Zhou et al. [43] have
been used. The genomic soil DNA can be labeled with
cystidine-5 (Cy-5) dye or the Cy-3 dye. Hybridization of
the labeled soil genomic DNA to a custom made Geo-
Chip can be carried out at a hybridization station for
instance TECAN US, Durham, NC, USA. The first wash
is carried out followed by the prehybridization, hybri-
dization and post hybridization washes. Scanning and
imaging are then done.
One must take into consideration both the biological
and the technical replications in performing experiments
using the GeoChip and the PhyloChip. Environmental
samples such as soil, the source of biological variation

Microarray Technology and Its Applicability in Soil Science—A Short Review 338
include macro environmental differences such as those
caused by growth room/greenhouse effects (light, heat,
humidity, location etc.) watering/fertilizing programs,
soil conditions, pathogen/herbivore pressures, etc. Sam-
ple pooling and replication are the primary methods used
to account for biological variation. Biologcal replication
is necessary: 1) to estimate the biological variation
within an experiment for downstream statistical analysis;
2) to extend the generality of the co nclusions beyond the
tested samples to the untested population as a whole.
Technical variations include differences in labeling effi-
ciencies, amplification reactions and the methodologies
involved in h ybridization.
8. Conclusion
Soil has been considered as a black box all this while.
Especially on earlier the twenty century, it was difficult
to establish the link between microbial community stru-
cture and function and even to link them to the above
ground plant community. With the advent of microarray
for microbial ecology studies, such linkages can be
established. The time is draw ing closer wh en th e soil will
no longer be considered as a blackbox.
9. Acknowledgements
I am very grateful to African Women in Agricultural
Research and Development (AWARD) for awarding me
fellowship to do my postdoctoral studies at the Dow
AgroSciences, Indianapolis, Indiana, USA. I am also
very grateful to Dr. Delkin Orlando Gonzalez, of the Mi-
croarray Laboratory, Dow AgroSciences for reviewing
this manuscript thoroughly for me.
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