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Title of the Project:

of salivary samples of pediatric population for various diagnostic biomarkers
by characterization of transcriptomic, proteomic, lipidomic and metabolomics profiles
of saliva for Mycobacteriuum tuberculosis

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Aims and Objectives:

1.      Comparative
transcriptome (mRNA, miRNA) and proteome profiling of salivary samples of Pediatric
TB patients with disease controls and healthy controls.

2.      Comparative
characterization of salivary lipidome and metabolome profiling of pediatric TB

3.      Statistical
analysis to evaluate the discriminatory accuracy of the various biomarkers. 

Review of literature: Biomarkers
are entities within the body which provide information regarding the current
physiological state of a living organism and exist in different forms like DNA,
RNA, proteins and lipids. Biomarkers are known to serve as a valuable tool for
diagnosis, prognosis and monitoring of diseases as alternation in their
concentration, structure, function or action can be correlated to onset,
progression or even regression of a particular disease or infection.

hunt for cost-effective and noninvasive diagnostic methodologies for TB is an
endeavor among clinicians and scientists. Diagnosis and monitoring TB mostly
require invasive and painful clinical procedures like biopsies and repeated
blood draws. Keeping this in mind there is a strong recommendation for
discovery of saliva based microbial, immunologic and molecular biomarkers which
will make us able to bypass the invasive diagnostic methodologies. Studies have
shown that saliva actually contains a variety of molecular and microbial
analytes (1, 2, 3,4) and these
salivary contents may actually be effective indicators of local as well as
systematic disorders/infections (5).
For the past two decades, salivary diagnostic have been developed to monitor
oral diseases but recently amalgamation of biotechnology and salivary
diagnostics has enhanced the range of salivary diagnostics from oral diseases
to whole physiological system.  Large
numbers of medically valuable analytes in saliva are gradually unveiled and
represent biomarkers for different diseases including cancer (Boyle et al., 1994, Li et al., 2004a, Zhang
et al., 2010), autoimmune (Hu et al., 2007b, Streckfus et al., 2001),
viral (Ochnio et al., 1997) (Chaita et al., 1995, El-Medany et al.,
1999, Pozo & Tenorio, 1999) and bacterial (Kountoruras, 1998, Lendenmann et al., 2000) diseases
as well as HIV (Emmons, 1997, Malamud,

studies have identified more than 3,000 species of mRNA and over 300 miRNAs in
the salivary fluids of healthy and diseased subjects, suggesting the
possibility that transcriptomic analysis may yield valuable information
regarding an infection (95).Another
study carried by Li et al., 2004b
showed that a set of 185 mRNA were consistently detected in healthy subjects
and are known as normal salivary core transcripts (NSCT). Further the
identification of proteins in saliva provides an insight into complex cellular
regulatory networks (Domon &
Aebersold, 2006). Studying the proteome, the protein complement of the
genome, in bio fluids is valuable due to its clinical significance as source of
disease markers and thus, the proteome of human salivary fluid has the
potential to open new doors for disease biomarker discovery. Although its
proteomic content is estimated to be only 30% that of blood (99), saliva is
actively being investigated as a rich source of protein biomarkers (100)
capable of discerning healthy from diseased subjects (101). Patients with
suspected HIV infections can now be screened for HIV-1 and -2 via a
saliva-based enzyme-linked immunosorbent assay (ELISA) (67). Although positive
results must be confirmed with a follow-up Western blot, this ELISA commonly
generates accurate (99.3% sensitivity, 99.8% specificity) results rapidly
(i.e., 20 min) and eliminates the necessity for invasive blood draws (68,
69).The table below provide a promising insight into salivary biomarkers
associated with different infections.












HIV antibody, RNA

2006; Malamud, 2011;
et al., 2010)


Reactivation of Bell’s palsy

DNA herpes virus type 1

et al., 2006)




et al., 2012)


Epstein-Barr virus


et al., 2011)



Hepatitis virus antigen A, B, C,
IgM, and IgG antibodies

et al., 2013;
et al., 2012)



Antibodies to rubella virus

(Oliveira et al., 2003)



Measles virus antibodies

et al., 2003)


Rotavirus infection
Gastritis / stomach cancer

Presence of IgA in infants
Helicobacter pylori DNA

et al., 1996)
 (Yee et al., 2013; Greabu et al., 2009;
et al., 2012),



Shigella antibodies

et al., 1992)


Lyme disease

Borrelia burdogferi antibodies

et al., 2004)


Entamoeba histolytica

Entamoeba histolytica DNA
Mitochondrial cytochrome b gene
Taenia solium antibodies

et al., 2010),
(Putaporntip et al., 2011; Fung et al., 2012)
(Feldman et al., 1990, Bueno et al., 2000)






of the genome, transcriptome, proteome, metabolome and salivary lipidome,
utilizing the approaches of various “omics”, may be the driving force for
biomarker development at present, since changes in the quantity, composition or
structure of salivary biomolecules may allow diagnosis and monitoring of the
development of various diseases (Zimmermann
et al., 2007). As Lipids are
known to play a regulatory  role in
invasion, persistence, replication and several immune responses to parasitic
bacteria (45*46*).Virulent bacteria such as Mycoplasma
and Salmonella interfere with the
host lipid metabolism to effectively invade and replicate in the host (47*).  A correlative study of serum and
saliva performed in about 100 healthy individuals showed moderate correlation
of total cholesterol, triglycerides, high density, and very low lipoprotein
cholesterol between the serum and saliva emphasizing the use of saliva as a
non-invasive diagnostic fluid for lipid analysis to investigate the disease
associated changes in lipid profile (Singh
S. et all; Jan 2014). Similar to the transcriptome and proteome, the
metabolome changes continually and any single profile is a snapshot reflecting
gene and protein expression. Metabolomic investigations can generate
quantitative data for metabolites in order to elucidate metabolic dynamics
related to disease state and drug exposure (Spielmann
N, Wong DT Oral Dis. 2011 May;


recruitment: For this study, specimens will be
collected from outpatient department of Advanced Pediatric Centre, PGIMER, Chandigarh,
India. Following groups of subjects will be recruited for this study.

I: tuberculosis patients 

Patients of either sex,
presenting to department of Advanced Pediatric Centre, PGIMER, Chandigarh, of
age 1-15 years having clinical and radiological features of tuberculosis will
be enrolled for this study. Diagnosis of cases will be made on the basis of
histopathological and microbiological evidence of tuberculosis. Patients
suffering from tuberculosis of any site other than pulmonary like skeletal,
miliary or meningitis will be excluded.

II: Diseased controls

Diseased controls will
be patients of either sex suffering from conditions mimicking tuberculosis
clinically such as benign tumors, fungal infections and other respiratory

III: Healthy controls

Healthy volunteers,
with no history or symptoms of tuberculosis of any body part, no history of
contact with tuberculosis patients, with clear chest will be taken as healthy


The subjects will be
asked to refrain from eating, drinking or using oral hygiene products for at
least 1 hour prior to saliva collection. Subjects will rinse their mouth with
water and, 5 minute later they will be instructed to spit into a sample
container without coughing mucus (age 10-15). Lashley cup will be used for
saliva collection from patients of age 4-9 years. 5ml of saliva sample will be
collected and processed further.

transcriptome and proteome profiling:

 RNA isolation:   Collected saliva samples will be centrifuged
at 2600×g for 15 min. at 4?C. Supernatant will be removed from the pallet and
treated with DNase. RNA will be isolated from 560 µl saliva supernatant with
QIAmp RNA kit (Qiagen, Valencia, CA). Aliquots of isolated RNA will be treated
with RNase-free DNase according to the manufacturer’s instructions. The quality
of isolated RNA will be examined by RT-PCR for three cellular maintenance gene
transcripts: glyceraldehyde-3-phosphate dehydrogenase (GAPDH), actin–? (ACTB),
and ribosomal protein S9 (RPS9). Only those samples exhibiting PCR products for
all three mRNAs will be used for subsequent analysis.

Microarray analysis:
 Isolated RNA from saliva will be
subjected to linear amplification by RNA Amplification kit. The RNA
amplification efficiency will be measured by using control RNA of known
quantity (0.1 ?g) running in parallel with the samples. The Human Genome U133A
Array (HG U133A, Affymetrix) will be applied for gene expression analysis.
arrays will be scanned and the fluorescence intensity will be measured by
appropriate software.

Total protein
isolation: Collected saliva samples will be centrifuged at
2600×g for 15 min. at 4?C.

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