Understanding microbial infections using microarray technology

7 White et al.
International Journal of Microbiology and Mycology | IJMM |
pISSN: 2309-4796
http://www.innspub.net
Vol. 11, No. 3, p. 7-13, 2020
Understanding microbial infections using microarray
technology
Erin N. White*1
, Evandrew Washington1
, Lawrence O. Flowers2
1
Department of Biological and Forensic Sciences, Fayetteville State University, United States2
3
Biology Department, Livingstone College, United States
Keywords: Microarray technology, Bacteria, Protozoa, Bioinformatics analysis
Publication date: March 30, 2020
Abstract
Human microbial infections are symbiotic processes between pathogens and humans that often lead to
human disease and death. Microbial infections involve the attachment, growth, and survival of
microorganisms on human skin, inside the body, or inside specific cells. Microbial infections can be
localized to one body region or migrate to secondary body locations utilizing various transport
mechanisms. An understanding of host-pathogen interactions related to the expression of essential
genes during and after infection can lead to valuable information for biologists and clinicians. Microarray
technologies allow researchers to perform genomic characterization experiments rapidly and efficiently.
Microarray experiments support the resolution of underlying molecular events that play a role in normal
and aberrant physiologic activities in living systems. Microarray technology, coupled with bioinformatics
analysis, generates comprehensive insights into relevant genes, proteins, and protein-protein
interactions. This review article explores recent microarray research studies from select protozoan and
bacterial pathogens to illustrate how researchers utilize microarray technology to examine aspects of
microbial infection. Microarray studies of pathogen and host genomes at different stages of the infection
process will generate a more precise understanding of pathogenic life cycles and pathogen survival
strategies. Detailed knowledge of the genes involved in the microbial infection process will lead to the
discovery of disease biomarkers and potent therapeutic solutions.
* Corresponding Author: Erin N. White  lflowers@livingstone.edu
Open Access REVIEW PAPER

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Introduction
The completion of the human genome project
paved the way for the development of high
throughput technologies in functional genomics
such as DNA microarrays and next generation
RNA sequencing. DNA microarray protocols are
widely useful methods for investigating genome-
level transcription events in cells and tissues in a
separate experiment (Dufva, 2009). DNA
microarrays are solid surfaces that contain
microscopic copies of complementary DNA or
oligoncleotides of varying lengths (e.g., short or
long) arranged in spots (Petersen et al., 2005).
Common microarray platforms such as
Affymetrix, Agilent, and Illumina are more
ubiquitous in today’s market and can even be
customized to address specific research
questions. In the past, the costs to conduct
microarray experiments were not cost-effective
for most life science laboratories. Today,
however, costs associated with microarray
experiments are somewhat manageable for
laboratories with relatively small budgets.
Nucleic acid microarray experiments involve the
selection of an appropriate biological process to
examine. Next, mRNA is isolated and converted
to complementary DNA (cDNA). The cDNA is then
labeled with a fluorescent molecule and applied to
a microarray surface containing oligonucleotides.
Fluorescence intensity comparisons of
experimental treatments and baseline samples,
following hybridization of nucleic acid sequences
provide evidence regarding up-regulated genes,
down-regulated genes and non-active genes
(Dufva, 2009). Comparing differential gene
expression in normal cells vs. abnormal cells or
healthy cells vs. diseased cells is a routine
strategy to elucidate the relevance of underlying
genetic mechanisms that participate in biological
processes. In addition to the identification of
particular activated genes and gene expression
levels, analysis of microarray data sets can
provide information about biological processes,
transcription factors, signal transduction
pathways, biomarkers, and diseases associated
with gene expression clusters.
DNA microarrays are now being used to rapidly
diagnose microbial pathogens in patients, food
samples, and water samples (Hou et al., 2018;
Kostić, Stessl, Wagner, Sessitsch, & Bodrossy,
2010; Sakai, Kohzaki, Watanabe, Tsuneoka, &
Shimadzu, 2012; Thissen et al., 2014).
Microarrays are demonstrating application in
resolving antimicrobial resistance in clinically-
relevant microbes (Charnock, Samuelsen,
Nordlie, & Hjeltnes, 2018; Uddin et al., 2018) and
in biomarker elucidation (Chen et al., 2019;
Tiwary, Kumar & Sundar, 2018). Microbial-based
microarrays are cost-effective when compared to
other microbe detection techniques and offer the
added benefit of providing valid identification of
test samples in less time. Using the approach
under discussion, clinical samples such as
nasopharyngeal, respiratory, blood, buccal, fecal,
urine, spinal fluid, and saliva samples can be used
to detect the presence of specific microbes or a
spectrum of microbes known to cause disease. As
referenced above, this technique has been used to
detect the difference between antibiotic
susceptible and antibiotic resistant bacteria.
Recognition of antibiotic resistance genes in clinical
samples can impact therapeutic strategies and
potentiate patient recovery and survival.
Microbial Infections
A microbial infection occurs when a
microorganism (e.g., protozoa, bacteria, fungi)
invades the human body through a specific portal
of entry. Humans can be exposed to microbes in
a number of ways including ingestion, inhalation,
fecal contamination, physical contact with
fomites, and body fluid transfer. Moreover, the
existence of co-infections in which more than one
type of microbe (e.g., bacterial and viral)
participates in a primary and secondary infection
is possible and represents a dangerous situation
(Abelenda-Alonso et al., 2020; Jia et al., 2017).
Fig. 1 summarizes the general stages of many

9 White et al.
microbial infections. Fig. 1 does not account for
all known microbial infections. The first major
step involved in the infection process is the
attachment phase. Microbes possess attachment
factors that mediate attachment to the skin or
mucous membranes. Specific receptor molecules
on the surface of the skin and mucous
membranes are complementary to microbial
attachment factors. During this phase some
microbes remain attached to the skin or
membranes, others penetrate these outer layers
and become positioned in the internal
environment. Some pathogenic microbes are
ingested via contaminated food and water.
Fig. 1. Basic microbial infection strategy.
Some microbes also have the ability to invade
specific cells, tissues, and organ systems using
complex host-pathogen mechanisms in which
microbial growth, differentiation, proliferation,
and survival are the main biologic objectives. In
terms of microbial infections, examination of
gene expression data can reveal how microbes
activate human and microbial genes in order to
complete the fundamental infection strategy
shown in Fig. 1. The next section of this review
discusses research utilizing DNA microarrays to
detect specific microbes and examine microbial
gene expression profiles.
Protozoa and Microarray
Protozoa are unicellular eukaryotes that cause a
variety of human diseases such as
Toxoplasmosis, Giardiasis, Malaria, and
Trypanosomiasis. There are now a pleothora of
useful DNA microarray platforms to explore
pathogenic protozoa (Kafsack, Painter, & Llinás,
2012; Moon, Xuan, & Kong, 2014; Wang, Orlandi,
& Stenger, 2005). Chen et al. (2016) developed a
DNA microarray system to concurrently detect 18
different species of human bloodborne protozoa
from 5 of the most common genera of protozoa
found in mammalian blood (Plasmodium,
Leishmania, Trypanosoma, Toxoplasma gondii,
and Babesia). A diagnostic test with a relatively
low limit of detection was designed to detect
waterborne pathogenic protozoa such as
Cryptosporidium parvum (Lee, Seto, & Korczak,
2010). The microarray was deemed effective and
clinically relevant based on comparative
verification tests.
The investigators utilized protozoan small
ribosomal RNA (rRNA) nucleotide sequence
probes on the microarray platform. Ribosomal
RNA subunit gene sequences serve as excellent
sources of microbial probes for diagnostic
microarrays for a number of reasons. First, it is
well known that both the small and large subunits
of prokaryotic and eukaryotic ribosomes are
highly conserved among species. Additionally,
rRNA gene sequences undergo fewer nucleotide
modifications when compared to their
macromolecular counterparts.
Classification of gene profiles during the various
stages of infection could be used to create
molecular countermeasure approaches that
suppress microbial infection capacity and kill the
microorganism or activate host immune
mechanisms. Some protozoal parasites, such as
amoeboid microbes have the ability to transition
into multiple biological and structural forms (e.g.,
trophozoite, cyst) depending on the type of host
they inhabit. The trophozoite stage is the vegetative
phase or feeding and amplification stage of the
parasite and is typically found in the human host,
while the cyst stage is the protective form of the
microbe and is found in the environment after being
passed in the feces of mammals.
The cyst stage is a resistant form of the parasite
that can survive harsh stimuli (e.g., climatic
changes, chemicals). The cyst form is converted
back to the trophozoite stage inside the intestines
of the human host following human consumption

10 White et al.
of the cyst via contaminated water or food.
Understanding the genetic changes that occur
during trophozoite-cyst conversion is paramount
to control efforts.
Moon, Xuan, Chung, Hong, and Kong (2011)
performed a microarray study to map the key genes
responsible for Acanthamoeba castellanii
encystation. Gene expression profiles of cysts were
compared to Acanthamoeba trophozoites following
microarray and bioinformatics procedures. There
were 701 upregulated genes and 859
downregulated genes in the cyst stage compared to
the trophozoite stage. Not surprisingly, a portion of
the differentially expressed genes were associated
with metabolic functions according to KOG analysis.
Since Acanthamoeba encystation within the host
further exacerbates immunological eradication
efforts, understanding the essential genes involved
in the encystation process may be beneficial.
Recently, a group of molecular parasitologists set
out to identify biomarkers associated with
miltefosine-resistance in visceral leishmaniasis.
Following treatment with miltefosine, patients
were evaluated. Leishmania parasites were then
extracted from patients demonstrating visceral
leishmaniasis relapse. Comparing differential
gene expression characteristics of parasites from
relapsed and cured patients, Tiwary, Kumar, and
Sundar (2018) demonstrated that a cysteine
protease-like protein was highly upregulated in
the parasites from relapsed patients, suggesting
that the cysteine protease-like protein could
serve as a biomarker to monitor patient relapse.
Bacteria and Microarray
Bacteria are unicellular prokaryotes that account
for a large number of human microbial diseases.
Some of the well-known bacterial diseases are
leprosy, diphtheria, plague, tuberculosis, and
cholera. Ranjbar, Behzadi, Najafi, and Roudi
(2017) recently designed a DNA microarray
platform that contained distinct oligonucleotide
sequences that were specific to ten different
medically relevant bacteria (Escherichia coli
Shigella boydii, Sh.dysenteriae, Sh.flexneri,
Sh.sonnei, Salmonella typhi, S. typhimurium,
Brucella sp., Legionella pneumophila, and Vibrio
cholera). Following the experiment, the
microarray successfully detected all ten bacteria
at the same time. Moreover, researchers recently
used microarray technology (FDA-ECID DNA
Microarray) to identify and characterize virulence
gene composition of non-O157 E. coli serovars
(Shridhar et al., 2019). Virulence gene
identification in clinical isolates is equally as
important as microbial identification and can
provide a greater depth of understanding
regarding the nature of infection and genetic
factors influencing patient-related pathop
hysiological outcomes.
Nosocomial infections are contracted during a
stay at a healthcare facility and were not present
before the patient was admitted. Keum et al.
(2006) developed a DNA microarray-based
detection system to identify nosocomial
pathogenic Pseudomonas aeruginosa and
Acinetobacter baumannii in clinical isolates. The
microarray technology demonstrated a sensitivity
of 84.6% and 96.2% for A. baumannii and P.
aeruginosa, respectively. Both nosocomial
pathogens displayed a positive predictive value of
100%. Purulent meningitis is characterized by
acute inflammation of the membranes associated
with the central nervous system and is
particularly devastating in neonatal populations
(He, Li, & Jiang, 2016). Purulent meningitis is
primarily caused by bacterial and viral infections.
Purulent meningitis leads to a variety of
unpleasant symptoms which in part depends on
the microbial agent and can lead to death if
untreated. Hou et al. (2018) designed a DNA-
based microarray to enhance diagnostic efforts of
the bacterial agents that cause purulent
meningitis. A significant number of positive test
results (87.5%) were generated using the
microarray detection approach compared to only
58.3% using the traditional cerebrospinal fluid

11 White et al.
culture detection method. The application of a rapid
identification and detection procedure significantly
reduces diagnostic deliberations. Antibiotic resistant
bacteria are the scourge of healthcare facilities
across the world. Antibiotic resistant bacteria lead to
unimaginable loss of life and account for millions in
medical treatment costs.
Antibiotic resistant bacteria are a global health
threat that could render today’s powerful
antimicrobial options essentially useless.
Moreover, as many have pointed out, antibiotic
resistance may be further complicated by severe
acute respiratory syndrome coronavirus 2
infections and COVID-19 (Rawson et al., 2020).
The use of rapid molecular recognition technology
that allows multiple bacteria to be tested for
genetic signatures that confirm antibiotic
resistant genes is extraordinarily beneficial to
physicians and patients. Carbapenemase and
extended-spectrum β-lactamases (ESBLs) are
particularly worrisome enzymes produced by
some bacteria because they confer antibiotic
resistance to bacteria. Carbapenemase- and
ESBL-producing bacteria have generated a
significant number of hospital-acquired infections
(HAI) worldwide. Uddin et al. (2018) created a
microarray platform designed to detect
Acinetobacter baumannii carbapenemase and
ESBL genes in patient specimens. Researchers
demonstrated that their microarray-based
method (CT 103XL Check-MDR) of antibiotic
resistance genes detection is equally or more
effective than other methods.
Conclusions
Less than 1% of the microbes on earth actually
lead to human disease. However, the impact that
microbial infections have on the economy, human
health, and other societal factors elicit enormous
responses from the medical and research
communities. Techniques such as DNA
microarrays and now next generation RNA
sequencing or RNA Seq are becoming increasingly
more prevalent in life science laboratories
because of their sensitive nature, high throughput
capacity and application. Moreover, these
techniques are more advantageous for microbial
detection and identification compared to traditional
sequencing and PCR arrays. Microbial detection
microarrays are constructed by adding
oligonucleotides (probes) from specific microbes to
a solid matrix. From a microbial perspective, nucleic
acid hybridization techniques are largely applied to
clinical diagnostic assays. However, a growing
segment of the literature points to a shift in the
use of DNA microarrays to study underlying
genetic mechanisms of fundamental biological
processes. The determination of the molecular
constituency, biomolecular interactions, and
canonical signaling pathways associated with
microorganisms can provide a wealth of beneficial
biologic and clinical information.
A review of the DNA microarray investigations in
this article highlight previous uses of this
technology to examine the biology of
microorganisms. This review also focuses on the
use of nucleic acid technology to accurately and
rapidly detect unique microbial species from
clinical, food, and water samples.
In clinical and hospital environments, tests that
have the ability to rapidly detect and identify
microbes is paramount. A delay in the diagnosis
of an infectious entity may provide the microbial
agent more time to proliferate and potentially
expand to other ectopic sites in the human body
thereby causing more damage to tissues and vital
organs. Elaborate time course studies could be
developed that allow microbiologists an
opportunity to map the global gene expression
profiles of bacteria and protozoa at different
phases of the infection process (e.g., attachment,
penetration, proliferation, etc.).
It is hypothesized that unique genes or gene
families are involved in discrete stages of the
microbial infection process. Further, microbial
genes can be identified that likely play a role in

12 White et al.
host symptoms and clinical outcomes. With such
detailed molecular characterizations, it would be
possible to not only identify biomarkers but to link
specific microbial gene changes with distinct phases
of infection (i.e., pathogenesis markers). Moreover,
connecting gene expression profiles with microbial
responses to drugs and other treatments is also
possible using DNA microarrays.
Performing microarray procedures to analyze host
cell gene expression profiles during a microbial
infection can also have tremendous scientific and
therapeutic value. New microarray platforms are
needed to further assist microbiologists, clinicians,
and other healthcare workers. The authors future
microbiological investigations will explore the use
of microarray technology to understand host
responses following viral and bacterial infections at
the molecular level. The advent of new, quality
control, normalization, and bioinformatics software
is certain to have a constructive impact on
microarray data usability and diversity of data
visualizations. Findings generated from DNA
microarray studies will open up new possibilities to
treat and prevent microbial diseases.
Acknowledgements
This work was supported by a grant funded by
the National Science Foundation (HRD-1533536).
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