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Accepted Manuscript
MicroRNA expression profiling of dibenzalacetone (DBA) treated intracellular
amastigotes of Leishmania donovani
Neeloo Singh, Indira Singh Chauhan
PII:
S0014-4894(17)30603-3
DOI:
10.1016/j.exppara.2018.07.018
Reference:
YEXPR 7593
To appear in:
Experimental Parasitology
Received Date: 13 November 2017
Revised Date:
19 July 2018
Accepted Date: 30 July 2018
Please cite this article as: Singh, N., Chauhan, I.S., MicroRNA expression profiling of dibenzalacetone
(DBA) treated intracellular amastigotes of Leishmania donovani, Experimental Parasitology (2018), doi:
10.1016/j.exppara.2018.07.018.
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MicroRNA expression profiling of Dibenzalacetone (DBA) treated intracellular amastigotes
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of Leishmania donovani
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Neeloo Singha*and Indira Singh Chauhana
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Road, Lucknow- 226031, India
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Biochemistry Division, CSIR Central Drug Research Institute, Jankipuram Extension, Sitapur
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* Corresponding author:
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Dr. Neeloo Singh, Biochemistry Division, CSIR Central Drug Research Institute, Jankipuram
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Extension, Sitapur Road, Lucknow, India, 226031,neeloo888@yahoo.com
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Abstract
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Background
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Among different leishmanial infections, visceral leishmaniasis (VL) if not treated is the most
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severe form with high mortality rates. In India, it is caused by the protozoan parasite Leishmania
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donovani. The therapy of visceral leishmaniasis is limited due to high toxicity, resistance to
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existing drugs and increasing cases of Leishmania co-infections. Hence, there is a need to
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identify novel drug and targets to overcome these hindrances. MicroRNAs (miRNAs) are a class
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of small non-coding RNAs (~22 to 24 nucleotide in length) that regulate gene expression in
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various biological processes. They play as intracellular mediators that are essential for different
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biological processes.
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Objectives
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The aim of present study is to explore the leishmaniacidal role of trans-dibenzalacetone (DBA, a
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synthetic monoketone analog of curcumin) on the expression profile of miRNA in intracellular
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amastigotes of Leishmania donovani.
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Methods:
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Small RNA libraries of samples (macrophages-infected with Leishmania amastigotes; and
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infected macrophages treated with DBA) were prepared by using Illumina Trueseq Small RNA
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kit.
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Results
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Using miRDIP database, we identified target gene of differentially expressed miRNAs (target
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miRNAs: hsa-mir-15b, hsa-mir-671, hsa-mir-151a and has-mir-30c) which was confirmed by
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real time stem-loop PCR. Ten KEGG pathways were significantly enriched with these target
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miRNA genes and they mainly relate to mitogen-activated protein kinases (MAPK) pathway. We
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have previously established the antiproliferative and apoptotic effect of trans-dibenzalacetone
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(DBA, a synthetic monoketone analog of curcumin) on the Leishmania donovani parasites. In the
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present study, using GFP-ATG8 gene as a marker for tracking putative autophagosomes, we
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confirmed that autophagic vacuolization may lead to autophagic cell death in the DBA-treated
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parasites. Our results demonstrated that curcumin analog DBA has a role to play in regulating the
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balance between autophagy and apoptosis.
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Conclusions
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We conclude that curcumin analog DBA triggers imbalance between two known phenotypes of
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cell death viz apoptosis and autophagy.
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Keywords
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Trans-dibenzalacetone (DBA), Leishmania donovani, MicroRNA (miRNA).
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Introduction
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Among different leishmanial infections, visceral leishmaniasis (VL) if not treated is the most
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severe form with high mortality rates. In India, the disease is known as Kala Azar and is endemic
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in
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(http://www.who.int/neglected_diseases/news/Visceral_leishmaniasis_WHO_publishes_validati
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on_document/en/). Leishmania donovani is a species of intracellular protozoan parasites that are
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able to survive and multiply within the hostile phagolysosomal environment of infected
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macrophages (Leirião, et al., 2004). MicroRNAs (miRNAs) are a class of small non-coding
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RNAs (~22 to 24 nucleotide in length) that regulate gene expression in various biological
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processes. They play as intracellular mediators that are essential for different biological
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processes (Lai, et al., 2013, Ling, et al., 2013). Mature miRNAs are produced by sequential
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processing of primary transcripts (pri-miRNAs) mediated by two RNase III enzymes, Drosha
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and Dicer (Siomi and Siomi, 2010). miRNAs regulate gene expression at the post-transcriptional
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level by either degradation or translational repression of a target mRNA (Felekkis, et al., 2010).
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The small, non-coding RNAs bind to the 3′ untranslated region of target messenger RNA
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(mRNA) and negatively regulate the expression of genes involved in development,
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differentiation, proliferation, apoptosis, and other important cellular processes (Felekkis, et al.,
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2010). A single miRNA can modulate the expression of hundreds of different targets and is thus
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implicated in a broad range of physiological and pathological processes (O'Connell, et al., 2010).
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Manipulation in miRNA expression can be used as important biomarkers for disease
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development and altered miRNA expression represents important avenues for therapeutic
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intervention (Hu, et al., 2012). Recent bioinformatics and experimental advances, point towards
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rapid progress in understanding the targets and functions of miRNAs (Lai, et al., 2013).
eastern
region
and
various
other
parts
of
the
country
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Microarray studies revealed that upon infection by Leishmania promastigotes, the mRNA profile
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of the macrophage gets altered and some of the changes in mRNA may be moderated by miRNA
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(Wendlandt, 2013). Alteration in miRNA levels likely plays an important role in regulating
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macrophage functions following L. major infection (Lemaire, et al., 2013). It has been
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established by Erik that miRNAs are important modifiers of mRNA changes during Leishmania
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infection (Wendlandt, 2013). It has been reported by Alok et al. that a novel role of MIR30A-3p
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in regulating autophagic-mediated L. donovani elimination by targeting BECN1 (Singh, et al.,
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2016). A study was recently carried out by Geraci et al. on miRNA profiles upon Leishmania
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infection in human phagocytes (Geraci, et al., 2015). There is increasing evidence that
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chemotherapy with various anticancer drugs such as curcumin (a naturally occurring flavinoid)
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affects miRNA expression in a number of cancers (Srivastava, et al., 2015, Sun, et al., 2008,
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Yang, et al., 2013, Zhang, et al., 2010).
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In our laboratory, we have established that DBA (trans-dibenzalacetone, a synthetic monoketone
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analog of curcumin) has potent antiprolific activity against Leishmania donovani (Chauhan, et
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al., 2018). It alters the general ultrastructure and the mitochondrial physiology of the parasite.
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Autophagy pathway is coordinated by autophagy-related proteins ATG (genes encoding
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proteins) with similarity to the core ATG proteins in yeast and mammals (He and Klionsky,
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2009). They have been described in Leishmania species, suggesting that these parasites possess a
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functional autophagy pathway (Williams, et al., 2009). Using the specific gene marker (ATG8),
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we confirmed that autophagic vacuolization may lead to cell death in the DBA-treated parasites.
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The comparison of miRNA expression between the treatment of intracellular Leishmania and the
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untreated parasite will reveal an explicit impact of chemotherapy with this drug on the miRNA
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expression profile of the parasite.
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Materials and Methods
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Leishmania strain and culture conditions
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The standard strain of L. donovani (MHOM/IN/80/DD8) were routinely cultured as described
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previously (Kaur, et al., 2010). The J774A.1 mouse (BALB/c) macrophage cell line was
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procured from National Centre for Cell Science (Pune, India). The cells were maintained in
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RPMI 1640 medium (Gibco-BRL) adjusted to contain 2 g of sodium bicarbonate/liter, 6 g of
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HEPES/liter, 10% (v/v) heat-inactivated fetal bovine serum (HI-FBS; Gibco, Germany), and 100
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U penicillin and 100 µg of streptomycin/ml at 37°C in a humidified atmosphere of 95% air and
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5% CO2 (Kaur, et al., 2011). Antileishmanial activity of DBA in intracellular amastigotes was
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previously determined by us (Chauhan, et al., 2018). Infected macrophages were treated with
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IC50 value of DBA and incubated at 37°C in 5% CO2 for 24 h (Kaur, et al., 2010).
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Total RNA was isolated using TRI reagent (Molecular Research Center, Cat. No. TR118), as per
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manufacturer`s instruction, from three different samples: [A] mouse macrophage (J774A.1) cells
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(AM); [B] macrophages infected with Leishmania amastigotes (BI); and [C] amastigote-infected
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macrophages treated for 24 h with DBA (CI). The quality of total RNA was checked on 1%
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denatured agarose gel (loaded 5 µl) for the presence of 28S and 18S bands. The gel was run at
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100 V for 30 min. Further, total RNA was quantified using Qubit fluorometer.
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miRNA microarray profiling
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The small RNA libraries from these samples were prepared using Illumina Trueseq SmallRNA
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kit from 1 µg of total RNA. Initially, 3' and 5' adaptors were ligated to each end of the RNA
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molecule and reverse transcription reaction was used to create single stranded cDNA. The cDNA
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was PCR amplified using a common primer and index primer to create cDNA construct. The
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cDNA construct was purified using 6% Novex TBE PAGE gel. After gel purification, the cDNA
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was extracted and concentrated by ethanol precipitation.
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A total 13534082 reads for AM sample, 30909234 reads for BI sample and 18415476 reads for
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CI sample were generated, have been provided in Table S1. High Quality data reads of AM, BI
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and CI samples were imported by discarding the Illumina importer using CLC Genomics
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Workbench. A total 7254885 reads for AM sample, 5561238 reads for BI sample and 12138167
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reads for CI were trimmed, as shown in Table S2. Trimmed reads were mapped to Rfam
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database to remove ribosomal contamination other than miRNAs. Mapping statistics using Rfam
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shown in Table S3. The unmapped reads from Rfam were mapped to Leishmania donovani strain
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BHU1220(http://TriTrypDB.org/common/downloads/Current_Release/L.donovaniBHU1220/fast
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a/data/Tri TrypDB-25_LdonovaniBHU1220_Genome.fasta) and the unmapped reads were
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considered for the downstream analysis. Mapping statistics using Leishmania donovani strain
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BHU1220 shown in Table S4. To identify the known and novel miRNAs, miRDeep2 software
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package was used. The mature Homo sapiens and precursors miRNA was downloaded from
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(www.mirbase.org) and these miRNAs were mapped against BI and CI samples. The below steps
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were carried out to identify the known and the novel miRNAs. The module of miRDeep2
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software was used to process deep sequencing reads and/or map them to the Human genome.
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Bioinformatics analysis
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Target prediction for known miRNAs of BI and CI samples were pulled out from the microRNA
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Data integration Portal (mirDIP http://ophid.utoronto.ca/mirDIP/ ) based on reference paper
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(Geraci, et al., 2015). mirDIP integrates multiple target prediction databases and provides a
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standardized score for each miRNA transcript relationship. While target was predicted for novel
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miRNAs of BI and CI samples using Miranda. Predicted target gene transcripts for the known BI
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and CI samples were used to identify KEGG pathways by using WEB-based Gene set Analysis
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Toolkit (Web Gestalt) with hyper geometric tests, Benjamini-Hocheberg adjustments and Human
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genome as a reference set. In Figure 1 we represent the bioinformatics workflow for small RNA
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analysis.
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Real-time quantification of target miRNAs by stem–loop RT–PCR
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cDNA was synthesized from the individual RNA taking 500 ng total RNA from each sample
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using RevetAid H Minus First Strand cDNA Synthesis Kit (Fermentas, Cat no. K1631) as per the
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manufacturing instruction. cDNA was synthesized, taking approximately 500 ng RNA to which
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1µl of 10 mM dNTPs, stem loop RT primer [10 pM, miR specific primers (hsa-mir-30c-1, hsa-
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mir-15b, hsa-mir-671, hsa-mir-151a and U6) were designed and synthesis by Xcelris Labs] and
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volume was maintained 13 µl. The details of the primers are given below.
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1. hsa-mir-30c-1; miR-30c-1 F: ACACTCCAGCTGGGTGTAAACATCCTACACT
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miR-30c-1RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGGCTGAG
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URP: TGGTGTCGTGGAGTCG
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2. hsa-mir-15b; hsa-miR-15b F: ACACTCCAGCTGGGTAGCAGCACATCATGG
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hsa-miR-15b RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGTGTAAA
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URP: TGGTGTCGTGGAGTCG
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3. hsa-mir-671; hsa-mir-67 F: ACACTCCAGCTGGGAGGAAGCCCTGGAGGGG
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hsa-mir-671 RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGCTCCAG
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URP: TGGTGTCGTGGAGTCG
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4. hsa-mir-151a; hsa-mir-151a F: ACACTCCAGCTGGGTCGAGGAGCTCACAG
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hsa-mir-151a RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGACTAGA
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URP: TGGTGTCGTGGAGTCG
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5. U6 House Keeping Gene: Forward qPCR primer: GCTTCGGCAGCACATATACTAAAAT
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Reverse qPCR Primer: CGCTTCACGAATTTGCGTGTCAT
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RT primer: CGCTTCACGAATTTGCGTGTCAB
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This reaction mix was incubated at 65°C for 5 min. After incubation, each of specific miR-RT
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reactions were kept on ice for 2 min. Rest of cDNA synthesis cocktail was added as follow, 4µl
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of 5X reaction buffer, 1 µl RiboLock RNase Inhibitor (20 U/µl), 1µl RevertAid H minus M-
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MuLV Reverse Transcriptase (200 U/µl), 1µl DTT (100 mM). Final volume of cDNA reaction
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mix was maintained to 20µl. After mixing gently, reactions were placed on thermocycler with
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given stem loop PCR as follow, 30 min at 16°C, cycles at 30°C for 30 seconds, 42°C for 30
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seconds and 50°C for 1 second.
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Real time PCR was carried out in Light Cycler 480 II (Roche) using following conditions: PCR
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mixture (10 µl) consisted of 1 µl of cDNA, 5 µl FastStart Essential DNA Green l Master (2X), 1
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µl of each primer (5 pmole /µl) and 2 µl of nuclease free water. Amplification includes initial
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denaturation at 94ºC for 2 min (1 cycle), followed by 40 cycles of denaturation at 94ºC for 15
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second and annealing of primers at 60ºC for 1 min (Heid, et al., 1996, Schmittgen, et al., 2000).
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Identification of autophagic vacuoles
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Autophagy, characterized by increased formation of lysosomes and autophagolysosomes in
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vacuoles (AVOs), was quantified by flow cytometry after staining the cells with acridine orange
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base dye (AO, Cat. No. 235474, Sigma) (Bhakdi, et al., 2007). Logarithmic phase promastigotes
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of L. donovani (1×106 cells, final volume 2 ml/well) were seeded in 6-well microtiter plates in
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the presence of different concentrations (0 - 40 µg/ml) of DBA and incubated at 25°C for 24 h.
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Then, the, cells were centrifuged (3500 x g for 5 min), washed once with PBS (pH 7.2), re-
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suspended in 1 µg/ml final concentration of AO, and incubated for 15 min in the dark at room
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temperature. After washing, samples were processed on a FACSCalibur flow cytometer and
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analyzed using CellQuest Pro software. 10,000 events from each sample were acquired to ensure
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adequate data. The histogram and images are representative of three independent experiments.
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Monitoring of autophagy: Transfection of GFP-ATG8 gene in L. donovani
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We are grateful to Jeremy C. Mottram for the kind gift of GFP-ATG8 plasmid which is a marker
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for tracking putative autophagosomes (Cull, et al., 2014). Logarithmic phase promastigotes of L.
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donovani (1×107 cell/ml) were harvested by centrifugation at 4500 rpm for 5 min at room
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temperature and transfection of GFP-ATG8 gene in wild type parasites was done by using K2
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transfection system (Biontex, Cat. No. T060-1.5) as per manufacturer`s guidelines. Transfection
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was confirmed by using a FACS Calibur flow cytometer (BD Bioscience, San Jose, CA, USA).
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Fluorescence was collected in the FL1 channel, equipped with 488 nm band pass filter. Analysis
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for mean fluorescence intensity was done using CellQuest Pro software (BD Biosciences, CA).
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Transfectant cells were treated with IC50 value of DBA for 24 h and analysed by using flow
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cytometer. 10,000 events from each sample were acquired to ensure adequate data. The
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histogram and images are representative of three independent experiments.
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Fluorescence Microscopy
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For live cell imaging, transfectant cells were pelleted by centrifugation and washed twice in PBS
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to remove medium. Transfectant cells were viewed by fluorescence microscopy on Olympus
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fluoviewTM FV1000 confocal microscope (America Inc., USA) with GFP filter. Imaging of
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transfectant cells was performed at 60 x magnification. DIC images were obtained under
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polarized light. The level of autophagy is expressed as the percentage of cells in a population
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containing at least one GFP-ATG8-labelled autophagosomes with minimum 200 cells counted
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from at least 3 independent experiments.
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Immunoblotting
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Promastigotes (5 x 106) of L. donovani were treated with different concentrations of (0 - 40
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µg/ml) DBA and after incubation at 25°C for 24 h, cells were centrifuged, washed with PBS (pH
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7.4) and suspended in lysis buffer (20 mM HEPES pH 7.4, 150 mM NaCl, 1 mM dithiothreitol,
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0.5% triton X-100 and 1x protease inhibitor mixture set) for 30 min on ice. The samples were
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centrifuged and supernatant was collected as total protein lysate. Equal amount of protein (20-40
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µg) was resolved on SDS-PAGE and transferred to polyvinyl difluoride (PVDF) membrane (Cat.
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No. IPVH000010, Milipore, Bedford MA, USA) using Hoefer SemiPhor (Amersham Pharmacia
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Biotech). After blocking with 5% (w/v) skimmed milk in PBS, membrane was incubated with
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1:1000 dilution of antibody for 1 h at room temperature. The membrane was then incubated with
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corresponding horseradish peroxidase (HRP)-conjugated secondary antibody (1:1000 ) for 2 h at
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room temperature and protein expression was detected by DAB (3,3'-diaminobenzidine, Sigma)
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chromogenic reagent.
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Results
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In vitro activity of DBA against Leishmania donovani and mammalian cytotoxicity
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In our previous study, we have established the antileishmanial activity of DBA against
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amastigotes of L. donovani. DBA showed apoptotic cell death at IC50 concentration of 7.43
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µg/ml (Figure 2A) against amastigotes. DBA was also tested for cytotoxicity in BALB/c mouse
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cell line J774A.1. It was found that the 50% cytotoxic dose (CC50) was higher than the IC50 dose
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for intracellular amastigotes (Figure 2B) with a SI (selectivity index) value of 15.34 (Chauhan, et
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al., 2018).
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Small RNA library preparation:
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Small RNA libraries were prepared using Illumina Trueseq Small RNA kit from 1 µg of total
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RNA (Figure 3a). The mean sizes of the fragment distribution are 160 bp, 155 bp and 144 bp for
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sample A-macrophage (AM), B-intracellular amastigotes (BI) and C-DBA treated intracellular
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amastigotes (CI) respectively (Figure 3b and c). Final library was validated on Bio-analyzer 2100
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using High-Sensitive DNA Chip for sample A-macrophage (AM), B-intracellular amastigotes
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(BI) and C-DBA treated intracellular amastigotes (CI) respectively (Figure 4a-c). The libraries
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were sequenced using 1 X 75 bp chemistry to generate 10 million reads/sample.
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Predicted known miRNAs
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A total of 212 known miRNAs were predicted for BI sample while a total of 211 known
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miRNAs were predicted for CI sample. Table S5 represents known miRNA statistics. These
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miRNAs were classified into the various families, representative example shown in the Table 1
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and Table 2 for sample BI and CI respectively.
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Predicted novel miRNA
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A total of 6 novel miRNAs were predicted for BI sample while a total of 11 novel miRNAs were
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predicted for CI sample. Table S6 represents novel miRNA statistics. These miRNAs were
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classified into the various families, representative example shown in the Table 3 and Table 4 for
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sample BI and CI respectively.
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Predicted targets for known miRNAs
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In sample BI, a total of 212 known miRNAs were searched for targets against the mirDIP
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transcripts. A total of 675 unique targets were found from BI sample while in sample CI a total
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of 211 known miRNAs were searched for targets against the mirDIP transcripts. A total of 675
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unique targets were found from CI sample. The targets are shown in Table 5 and Table 6 for BI
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and CI samples respectively.
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Predicted targets for novel miRNAs
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A total of 17 novel miRNAs were searched for targets against the 3’UTR, 5‘UTR and CDS
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region of Human genome. In sample BI, a total of 71 from 3’UTR, 9 from 5’UTR and 77 from
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CDS unique targets were found. While in sample CI a total of 367 from 3’UTR, 70 from 5’UTR
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and 280 from CDS unique targets were found (Figure 5). Predicted targets were used for
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functional annotation using blastx (https://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=blastx&
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PAGE_TYPE=BlastSearch). The targets and functional annotation are shown in Table 7, 8 and 9
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for targets of novel miRNA BI sample. While in Table 10, 11, and 12 targets of novel for CI
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sample.
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Differential expression analysis of known miRNAs using counts per million (CPM)
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A total of 133 common known miRNAs from BI and CI samples were used to calculate counts
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per million (CPM). 72 miRNAs were found to be differentially expressed in DBA treated
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intracellular amastigotes (CI) as compared with untreated parasites (BI). Out of these 72
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miRNAs, 12 miRNAs such as hsa-mir-671, hsa-mir-1470, hsa-mir-9-3, hsa-mir-128-1, hsa-mir-
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9-1, hsa-mir-9-2, hsa-mir-128-2, hsa-mir-484, hsa-mir-30c-2, hsa-mir-30c-1, hsa-mir-15b and
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hsa-mir-151a were found to be significantly down regulated while 1miRNAs (hsa-mir-8065)
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was significantly up regulated in treated sample as shown in Table 13.
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Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway
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A total of 133 common known miRNAs from BI and CI samples were used to calculate counts
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per million (CPM). 13 out of 133 known miRNAs has been searched against the mirDIP
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database to pull out target gene symbols of each miRNA. A total of 5 miRNAs found to have
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target gene symbols from miRDIP database. A total of 12000, 9915, 9294, 845 and 819 target
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genes for miRNAs hsa-mir-15b, hsa-mir-671, hsa-mir-484, hsa-mir-30c-2 and hsa-mir-30c-1
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respectively were tabulated as given in Table 14. All the pulled genes symbols of each target
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miRNAs were used to identify KEGG pathways by using WEB-based Gene set Analysis Toolkit
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(Web Gestalt). A total of 10 different enriched KEGG Pathways Table 15 (metabolic pathways,
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pathways in cancer, MAPK signaling pathway, regulation of actin cytoskeleton, focal adhesion,
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insulin signaling pathway, Wnt signaling pathway, calcium signaling pathway, endocytosis and
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axon guidance) where identified in each of these 5 miRNAs.
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Real-time quantification of target miRNAs by stem–loop RT–PCR
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The amplified products of real time stem-loop PCR were analyzed on 3% agarose gel along with
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no template control (NTC) (Figure 6A). Melting curve and peak analysis confirmed the amplicon
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specificity of PCR product of each targeted gene (Figure 6B and C). Expression profiles of hsa-
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mir-30c-1, hsa-mir-15b, hsa-mir-671 and hsa-mir-151a (target miR). CI (experimental) is
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compared against BI (Control) using U6 as housekeeping gene. The targeted miR obtained from
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our miRNA analysis in the infected macrophages treated with DBA contained 5.59, 2.12, 5.21
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and 5.93-fold downregulated in hsa-mir-30c-1, hsa-mir-15b, hsa-mir-671 and hsa-mir-151a
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respectively as compared to control (Figure 6D and Table 16) (Livak and Schmittgen, 2001).
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Cells treated with DBA display autophagic vacuoles
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Autophagy is characterized by increased formation of AVOs which can be quantified by flow
322
cytometry after staining the cells with AO (acridine orange) (Chen, et al., 2007). Cells with
323
AVOs showed enhanced red fluorescence that increased after treatment with DBA in a dose-
324
dependent manner (Figure 7A). It is also known that ATG8 N-terminally tagged with GFP
325
becomes associated with punctate structures (putative autophagosomes) in Leishmania
326
promastigotes, especially under the starvation conditions and during differentiation between its
327
life cycle forms (Besteiro, et al., 2006). In the present study, localization of GFP-ATG8 gene in
328
promastigotes of L. donovani and transfection of GFP-ATG8 gene in wild type parasites was
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done
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(http://www.biontex.com/con_4_6_4/cms/upload/pdf/Singh.pdf). Transfection was confirmed by
331
increased MFI of GFP. New positive cells were treated with IC50 value of DBA for 24 h and
332
samples were analyzed by using flow cytometer (Figure 7B). To confirm the localization of
333
GFP-ATG8 gene in parasites, transfectants treated with or without DBA were analyzed by
334
fluorescence microscope, and the presence and number of GFPATG8-labelled autophagosomes
335
within these cells were recorded. Fluorescence microscopic analysis showed that the untreated
336
promastigotes had no fluorescence and upon DBA treatment, the cells distributed into a punctate
337
structure in the cytosol (Figure 7C). The confirmation of overexpression of GFP-ATG8 gene in
338
the treated cells was carried out by western blot analysis using GFP antibody. One major protein
339
was detected at 40 kDa in the treated cells which was consistent with the predicted mass of the
340
fusion protein (GFP-ATG8) (Figure 7D).
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Discussion:
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The high failure rate of the drugs and their significant side effects against visceral leishmaniasis
344
calls for a mainstay therapy for the same. The traditional drug Miltefosine is teratogenic that
345
should not be administered to pregnant woman. Resistance against sodium stibogluconate has
346
been reported previously. Liposomal formulation of amphotericin B is quite expensive and
347
cannot be labeled as poor man’s drug. No report of vaccine against visceral leishmaniasis is
348
known till date. A rational approach to design and develop new anti-leishmanial agents has
349
identified several metabolic and biochemical differences between host and parasite that can be
350
exploited as drug target (Shukla, et al., 2010). One such approach that we adopted is miRNA
351
expression profiling of drug treated intracellular amastigotes. It has been well documented by
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Zheng et al that miRNA pathways are a potential target for the therapeutic control of parasitic
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diseases (Zheng, et al., 2013).
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MicroRNAs (miRNAs, a class of small non-coding RNAs (~22 to 24 nucleotide)) regulate gene
355
expression at the post-transcriptional level by either degradation or translational repression of a
356
target mRNA (Filipowicz, et al., 2008). Nowadays, miRNAs can be used as biomarkers for
357
disease development and manipulation of miRNAs expression represents a potential avenue of
358
therapy (Hu, et al., 2012).
359
We have previously established the leishmanicidal activity of DBA, which leads to apoptotic cell
360
death in Leishmania donovani via the activation of the MAPK cascades (Chauhan, et al., 2018)
361
and in the present study, we for the first time report the miRNA expression profile in the DBA
362
treated intracellular amastigotes of Leishmania donovani. We identified differentially expressed
363
miRNAs (target miRNAs: hsa-mir-15b, hsa-mir-671, hsa-mir-151a, has-mir-30c-2 and has-mir-
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30c-1) and its related target gene in DBA treated intracellular amastigotes as compared to
365
untreated parasites. Biological pathway analysis of target miRNAs through KEGG analysis
366
revealed mitogen-activated protein kinase (MAPK) signaling pathway as the most significant
367
pathway in our analysis. MAPK pathway is well known pathway in Leishmania infection
368
(Gregory and Olivier, 2005).
369
To validate the expression profile of these target miRNAs, real time stem-loop PCR was carried
370
out and PCR product of these target miRNAs were found to be expressed during DBA treated
371
intracellular amastigotes. Guo et al have reported that miR 15b induces the expression of gene
372
involved in apoptosis by targeting Bcl-2 and the caspase signaling (Guo, et al., 2009). In our
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study the expression level of miR15b in DBA treated intracellular amastigotes was significantly
374
lower (~2 fold) than untreated cell. We identified ATG5 target gene by KEGG analysis of miR
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15b. Williams et al have reported that the ATG5 is essential for ATG8 dependent autophagy and
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phospholipid balance in the mitochondrion in Leishmania major (Williams, et al., 2012). So, we
377
can say that DBA promotes miR 15b expression and plays a role in regulating the balance
378
between autophagic and apoptotic cell death in intracellular amastigotes.
379
Zhou et al have reported that miR151a participates in the regulation of cellular respiration and
380
ATP production by targeting cytochrome b (Zhou, et al., 2015). We found 5-fold downregulation
381
of miR151a in DBA treated intracellular amastigotes. It means that DBA induces mitochondrial
382
dysfunction in parasites which can be correlated with our previous work. We had reported that
383
the main ultrastructural alteration was observed in the mitochondrion-kinetoplast complex,
384
which showed intense mitochondrial swelling with an increase in the number of cristae and that
385
was further confirmed with mitochondrial membrane potential dissipation (Chauhan, et al.,
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2018).
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The molecular mechanism involved in the autophagy response in host cell (macrophages)
388
infected with leishmanial parasites has been well established by Singh et al and they reported
389
that MIR30A-3p was overexpressed in host cells after infection with Leishmania parasites
390
(Singh, et al., 2016). In our study, we found 5-fold down regulation of miR30c with more than
391
800 unique target gene in the DBA treated intracellular amastigotes. So, we can conclude that the
392
downregulation of miR30c inhibits the proliferation and virulence of Leishmania parasites.
393
Autophagy pathway is coordinated by autophagy-related proteins ATG (genes encoding
394
proteins) with similarity to the core ATG proteins in yeast and mammals. They have been
395
described in Leishmania species, suggesting that these parasites possess a functional autophagy
396
pathway (Williams, et al., 2009). In miR30c we identified ATG4, ATG9 and ATG16 target gene.
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William et al have established that ATG4 activity is required for parasite viability and from
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differential expression profiling of DBA treated intracellular amastigotes, we found down
399
regulation of miR30c whose target gene is ATG4 (Williams, et al., 2013). So, we can conclude
400
that the down regulation of ATG4 inhibits the cell viability of parasites via regulation of miR 30c
401
expression. The essential proteins, ATG8 and ATG12/ATG5 required for autophagosome
402
formation and encoding have been established in L. major genome (Williams, et al., 2012).
403
ATG8 has been shown to form putative autophagosomes during differentiation and starvation
404
of L. major. To ascertain whether the several alterations in the ultrastructure that lead to growth
405
inhibition and eventually cell lysis in the DBA-treated parasites are indeed the result of
406
autophagy, we proceeded to verify this with the GFP-ATG8 gene. A major overexpressed
407
protein was detected ~ 40 kDa which is consistent with the predicted mass of the GFP-ATG8
408
protein. Fluorescence microscopy of the untreated, control parasite demonstrated healthy
409
promastigote with no GFP fluorescence while the DBA-treated parasite showed green
410
fluorescence of GFP tagged autophagosome marker, ATG8. The elongated cell body had
411
changed to a pronounced rounded form with morphological alterations which are visible
412
parameters of DBA effect on this parasite.
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Conclusion
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In our study, a total of 13534082 reads for sample AM (macrophages), 30909234 reads for
416
sample BI (intracellular amastigotes) and 18415476 reads for sample CI (DBA treated
417
intracellular amastigotes) were generated. A total of 212 known miRNAs from sample BI and
418
211 known miRNAs from sample CI were identified. A total of 675 targets were pulled out from
419
mirDIP (mircoRNA Data Integration Portal) for both BI and CI sample respectively. A total of
420
10 enriched KEGG pathways were identified from target miRNAs (hsa-mir-15b, hsa-mir-671,
421
hsa-mir-151a, has-mir-30c-2 and has-mir-30c-1). In the present study, we conclude that
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curcumin analog DBA triggers imbalance between two known phenotypes of cell death viz
423
apoptosis and autophagy and thus represents a potential therapeutic value for treatment of
424
visceral leishmaniasis.
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Supplementary data
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Table S1. High quality reads data statistics, Table S2. Trimmed reads data statistics, Table S3.
428
Mapping statistics using Rfam, Table S4. Mapping statistics using BHU1220 strain of
429
Leishmania. Table S5 and S6 statistics of known and novel miRNAs respectively.
430
The data sets supporting the results of this article are submitted at https://submit. ncbi.nlm.nih.
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gov/subs/biosample/ under BioSample accession numbers:
432
SAMN07274573 (http://www.ncbi.nlm.nih.gov/biosample/7274573)
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SAMN07274574 (http://www.ncbi.nlm.nih.gov/biosample/7274574)
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SAMN07274575 (http://www.ncbi.nlm.nih.gov/biosample/7274575).
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Acknowledgments
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We are thankful to late Dr. Govind J. Kapadia and Dr. G. Subba Rao for the dibenzalacetone
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(DBA), which was a kind gift from them and to Jeremy C. Mottram for the kind gift of GFP-
439
ATG8 plasmid. This is CDRI communication no.16/2017/NS.
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Funding
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This work was supported by the Council of Scientific & Industrial Research (CSIR), India (grant
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number BSC-0114). Indira Singh Chauhan was supported by fellowships from Indian Council of
444
Medical Research (ICMR).
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Transparency declarations
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None to declare.
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Table 1: Representation of conserved known miRNAs in BI sample (partial table representation)
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Table 2: Representation of conserved known miRNAs in CI sample (partial table representation)
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Table 3: Representation of conserved novel miRNAs in BI sample
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Table
4:
Representation
of
conserved
novel
miRNAs
in
CI
sample
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Table 5: Targets of known miRNAs in BI
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Table 6: Targets of known miRNAs in CI
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Table 7: 5' UTR Targets of novel miRNAs in BI
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Table 8: 3' UTR Targets of novel miRNAs in BI
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Table 9: CDS Targets of novel miRNAs in BI
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Table 10: 5' UTR Targets of novel miRNAs in CI
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Table 11: 3' UTR Targets of novel miRNAs in CI
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Table 12: CDS Targets of novel miRNAs in CI
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Table 13: Differential expression analysis as BI control and CI treated
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Table 14: Total unique target genes from mirDIP darabase
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Table 15: Identification KEGG pathways and gene counts
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Table 16. Expression ratios of miR hsa-mir-30c-1,hsa-mir-15b, hsa-mir-671, hsa-mir-151a (target miR)
697
with respect to U6 (Housekeeping).
hsa-mir30c-1 16.43
16.58
hsa-mir30c-1 16.43
16.71
hsa-mir30c-1 15.88
16
Average
Ct-hsamir30c-1 16.24666667 0.183333333 16.43
22.94
hsa-mir15b 26.21
23.12
hsa-mir15b 26.41
22.96
ΔCT (BI)
0.21825062 -8.18
∆∆CT
Down2.583333333 5.596666667 0.020665002 -5.596667 Regulated
Down3.993333333 2.123333333 0.229516005 -2.123333 Regulated
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Ct-hsamir-15b 26.29666667 0.059254629 23.00666667 0.056960025 1.87
hsa-mir671 23.62
ΔCT (CI)
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Standard
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Standard
Error
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BI (CT) \
Triplicate
Samples
Normalised
mir amount Regulation
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Value
B1 2((Log2 Regulation
∆∆CT)
Fold
[Fold
Change)
Change]
23.56
hsa-mir671 23.66
22.98
hsa-mir671 23.6
23.73
Average
Ct-hsamir-671 23.62666667 0.017638342 23.42333333 0.227034016 -0.8
40
4.41
5.21
0.027016788
-5.21
DownRegulated
hsa-mir151a 19.91
20.64
hsa-mir151a 20.64
20.64
hsa-mir151a 19.9
20.74
0.245017006 20.67333333 0.033333333 4.276666667 1.66
19.64
mir-U6 23.4
19.11
mir-U6 25.88
18.29
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Average
Ct-U6 24.42666667 0.747023724 19.01333333 0.392697226 0
698
699
Down5.936666667 0.016326206 -5.93667 Regulated
SC
Average
Ct-hsamir151a 20.15
RI
PT
ACCEPTED MANUSCRIPT
0
0
1
0
Figure legends:
701
Figure 1. Bioinformatics workflow for smallRNA analysis.
702
Figure 2.[A] In vitro analysis of antileishmanial activity of DBA in intracellular amastigotes:
703
Macrophages (4000 cells/well, final volume 200 µl) were infected with promastigotes of L.
704
donovani in a ratio of 8:1 (parasites/macrophages) and infected macrophages were treated with
705
increasing concentrations (0, 5, 10, 15 and 20 µg/ml) of DBA for 24 h. After indicated
706
incubation time, treated or untreated cells were stained with Giemsa stain and the slides were
707
viewed on an inverted bright field microscope (IX73 Inverted Microscope, Olympus). The 50%
708
inhibitory concentration (IC50) was obtained by plotting the graph of percentage of cell viability
709
against log value of DBA concentrations (µg/ml). The results were taken as the mean of
710
duplicate experiments and p=0.05 has been considered as the level of significance. [B]
AC
C
EP
TE
D
700
41
ACCEPTED MANUSCRIPT
Cytotoxicity in macrophages: Macrophages (50,000 cells/well, final volume 200 µl) were treated
712
with increasing concentrations (0, 10, 20, 40, 80 and 160 µg/ml) of DBA for 24 h. After
713
indicated incubation time, the viability of the macrophages was estimated by alamarBlue® cell
714
viability reagent. Results are presented as mean ± SD; n=3 and p=0.05 has been considered as
715
the level of significance.
716
Figure 3. [a] Total RNA on 1% denaturing agarose gel. Lane 1: macrophages (AM), Lane 2:
717
intracellular amastigotes (BI) and Lane 3: DBA treated intracellular amastigotes (CI) [b] 6%
718
TBE PAGE gel image of cDNA construct of AM and BI samples. [c] 6% TBE PAGE gel image
719
of cDNA construct of CI sample.
720
Figure 4. [a] Small RNA library profile of sample macrophages (AM) on Agilent DNA HS
721
Chip. [b] Small RNA library profile of sample intracellular amastigotes (BI) on Agilent DNA HS
722
Chip. [c] Small RNA library profile of sample DBA treated intracellular amastigotes (CI) on
723
Agilent DNA HS Chip.
724
Figure 5.Venn diagram showing the predicted novel miRNAs targeting the (A) 3' UTR region,
725
(B) 5' UTR region and (C) CDS region between two groups (BI and CI).
726
Figure 6. (A) 3% Agarose gel showing Amplified PCR Products (~60bp). Lane 1: 100 bp
727
Ladder; Lane 2: miR30-C B1; Lane 3: miR30-C C1; Lane 4: miR15b B1; Lane 5: miR15b C1;
728
Lane 6: miR671 B1; Lane 7: miR671 C1; Lane 8: miR151a B1; Lane 9: miR151a C1; Lane 10:
729
NTC (No Template Control). (B)Melting Curves of hsa-mir-30c-1, hsa-mir-15b, hsa-mir-671
730
and hsa-mir-151a (target miR) in both (BI and CI) RNA. The Melting Curves of each of the miR
731
is shown by their name. (C)Melting Peak of hsa-mir-30c-1, hsa-mir-15b, hsa-mir-671 and hsa-
732
mir-151a (target miR) in both (BI and CI) RNA. The Melting Peaks of each of the miR is shown
733
by their name. (D) Expression profiles of hsa-mir-30c-1, hsa-mir-15b, hsa-mir-671 and hsa-mir-
AC
C
EP
TE
D
M
AN
U
SC
RI
PT
711
42
ACCEPTED MANUSCRIPT
151a (target miR). CI (experimental) are compared against BI (Control) using U6as
735
housekeeping gene.
736
Figure 7 [A]. Autophagosome formation was quantified by flow cytometry after staining the
737
cells with acridine orange (AO). (a) Cells were treated with different concentrations [a, b, c and d
738
represent 0, 10, 20 and 40 µg/ml respectively] of DBA for 24 h, stained with AO and its
739
fluorescence was measured using a flow cytometer. Untreated cells were used as control. [B]
740
Transfection of GFP-ATG8 gene in promastigotes of L. donovani was done by using K2
741
transfection system. After treatment of DBA, transfectants were processed on a FACS Calibur
742
flow cytometer. Fluorescence of the GFP was collected in the FL1 channel; analysis for mean
743
fluorescence intensity was done using CellQuest Pro software. Where (a), (b) and (c) show wild
744
type parasites (WT), untreated transfectants (UT) and DBA treated transfectant (DT)
745
respectively. (b) Graph shows quantitative analysis of transfection which is based on GFP mean
746
fluorescence intensity. [C] Visualization of autophagosome formation in wild type (WT),
747
untreated (UT) and treated transfectants (DT) were obtained by fluorescence microscopy and
748
number of GFP-ATG8-labelled autophagosomes within these cells was recorded. [D] To confirm
749
overexpression of GFP-ATG8 gene in DBA treated transfectant (DT) was carried out by western
750
blot analysis using GFP antibody. M: protein molecular weight marker, UT: untreated
751
transfectants, and DT: DBA treated transfectants.
753
SC
M
AN
U
TE
D
EP
AC
C
752
RI
PT
734
43
ACCEPTED MANUSCRIPT
Table 1: Representation of conserved known miRNAs in BI sample (partial table representation)
9
Reads
Length (nt)
Has-let-7g
Has-let-7f-2
Has-let-7f-1
Has-let-7i
Has-let-7d
Has-let-7c
Has-let-7a-3
Has-let-7a-1
Has-let-7a-2
Has-let-7e
Has-let-7b
Has-mir-7-1
Has-mir-7-3
Has-mir-7-2
Has-mir-9-3
Has-mir-9-1
Has-mir-9-2
ugagguaguaguuuguacaguu
cuauacagucuacugucuuucc
ugagguaguagauuguauaguu
cugcgcaagcuacugccuugcu
cuauacgaccugcugccuuucu
cuguacaaccuucuagcuuucc
ugagguaguagguuguauaguu
ugagguaguagguuguauaguu
ugagguaguagguuguauaguu
ugagguaggagguuguauaguu
cuauacaaccuacugccuuccc
caacaaaucacagucugccaua
uggaagacuagugauuuuguugu
uggaagacuagugauuuuguugu
auaaagcuagauaaccgaaagu
auaaagcuagauaaccgaaagu
auaaagcuagauaaccgaaagu
78
61
59
45
32
19
13
13
11
5
4
2
1
1
4
4
4
22
22
22
22
22
22
22
22
22
22
22
22
23
23
22
22
22
SC
RI
PT
Sequence (5’-3’)
M
AN
U
7
Reference miRNA
TE
D
miRNA family
Table 2: Representation of conserved known miRNAs in CI sample (partial table representation)
Reference miRNA
Sequence (5’-3’)
Reads
Length (nt)
Has-let-7g
Has-let-7f-2
Has-let-7f-1
Has-let-7c
Has-let-7i
Has-let-7d
Has-let-7a-3
Has-let-7a-1
Has-let-7a-2
Has-let-7b
Has-mir-7-1
Has-mir-7-3
Has-mir-7-2
Has-mir-9-3
Has-mir-9-1
Has-mir-9-2
ugagguaguaguuuguacaguu
cuauacagucuacugucuuucc
ugagguaguagauuguauaguu
cuguacaaccuucuagcuuucc
cugcgcaagcuacugccuugcu
cuauacgaccugcugccuuucu
ugagguaguagguuguauaguu
ugagguaguagguuguauaguu
ugagguaguagguuguauaguu
cuauacaaccuacugccuuccc
caacaaaucacagucugccaua
uggaagacuagugauuuuguugu
uggaagacuagugauuuuguugu
auaaagcuagauaaccgaaagu
auaaagcuagauaaccgaaagu
auaaagcuagauaaccgaaagu
74
56
56
41
38
31
13
13
12
4
2
1
1
1
1
1
22
22
22
22
22
22
22
22
22
22
22
23
23
22
22
22
7
AC
C
EP
miRNA family
9
ACCEPTED MANUSCRIPT
Table 3: Representation of conserved novel miRNAs in BI sample
loop
read
count
0
Star
Read
count
1
Chr17_6310
571
571
0
0
ChrX_7528
396
396
0
0
Chr9_3984
582
582
0
0
Chr1_561
584
584
0
0
Chr5_2695
42
42
0
0
Consensus
Mature
sequence
uaaggugcauc
uagugcagau
uagcuuaucaga
cugauguugac
aucaacagacau
uaauugggcgc
aacauucauugc
ugucgguggg
aacauucauugc
ugucgguggg
agcagcauugua
cagggcuauga
Consensus star
sequence
Consensus precursor sequence
acugcccuaagugc
uccuucug
caacaccagucgau
gggcuguc
ccucauuaaaugu
uuguugaauga
cacugaucaaugaa
ugcaaa
cacugaacaaugaa
ugcaac
ucggcuucuuuac
agugcugccuug
uaaggugcaucuagugcagauagugaaguag
auuagcaucuacugcccuaagugcuccuucug
uagcuuaucagacugauguugacuguugaau
cucauggcaacaccagucgaugggcuguc
ccucauuaaauguuuguugaaugaaaaaauga
aucaucaacagacauuaauugggcgc
aacauucauugcugucgguggguuugagucu
gaaucaacucacugaucaaugaaugcaaa
aacauucauugcugucgguggguugaacugu
guggacaagcucacugaacaaugaaugcaac
ucggcuucuuuacagugcugccuuguugcau
auggaucaagcagcauuguacagggcuauga
RI
PT
Mature
Read
count
5
SC
Chr13_5344
Total
read
count
6
M
AN
U
Novel
miRNA ID
Precursor
coordinates
chr13:92003010..
92003073:+
chr17:57918634..
57918694:+
chrX:73438226..7
3438284:+
chr9:127456004..
127456064:+
chr1:198828014..
198828076:+
chr5:167987908..
167987970:+
Table 4: Representation of conserved novel miRNAs in CI sample
Mature
Read
count
468
loop
read
count
0
Star
Read
count
1
ChrX_9148
350
350
0
0
Chr4_2588
21
21
0
0
Chr9_5060
498
498
0
0
Chr1_627
500
500
0
0
Chr4_2344
21
21
0
Chr1_612
15
Chr18_8112
27
Chr15_7377
60
Chr10_5438
Chr13_6722
Consensus
Mature
sequence
Consensus star
sequence
Consensus precursor sequence
Precursor
coordinates
uagcuuaucag
acugauguuga
aucaacagaca
uuaauugggc
cacugcaaacg
cugccacc
aacauucauug
cugucggugg
gu
aacauucauug
cugucggugg
gu
cagccaugagu
guggcag
uucaugauaag
ggacaaa
aaucaugauca
caggaca
aacaccagucgau
gggcuguc
ucauuaaauguuu
guugaauga
uggagugcagug
gc
ucacugaucaaug
aaugcaaa
uagcuuaucagacugauguugacuguugaa
ucucauggcaacaccagucgaugggcuguc
ucauuaaauguuuguugaaugaaaaaauga
aucaucaacagacauuaauugggc
uggagugugcaguggcaugauauuggcuc
acugcaaacgcugccacc
aacauucauugcugucgguggguuugagu
cugaaucaacucacugaucaaugaaugcaaa
chr17:57918634.
57918694:+
chrX:73438228..
73438282:+
chr4:83088035..
83088080:+
chr9:127456004.
.127456064:+
ucacugaacaaug
aaugcaac
aacauucauugcugucgguggguugaacug
uguggacaagcucacugaacaaugaaugca
ac
cagccaugaguguggcagcuccagaauguc
uauaccagaguggcugag
uuuuguacucagaguuugcagcucucaaau
guaagcuucaugauaagggacaaa
aaucaugaucacaggacacacuaggggugu
uucccuuggccaugugccugcaaaucaaag
ugaugug
cauggguccugacaccauauguggauguag
augcagcuguaguugcaucauuuaccagga
gaggaacuccaaugcc
gagaagcacuguuuggguucagagucaguc
uggcucugacugauuuguaucuucucuu
uaaggugcaucuagugcagauagugaagua
gauuagcaucuacugcccuaagugcuccuu
cugg
chr1:198828014.
.198828076:+
EP
TE
D
Chr17_7844
Total
read
count
468
0
AC
C
Novel
miRNA ID
gucuauaccagag
uggcugag
uuuuguacucaga
gu
gccugcaaaucaa
agugaugug
15
0
0
27
0
0
60
0
0
ggagaggaacu
ccaaugcc
cauggguccugac
accau
10
10
0
0
8
6
0
2
gagaagcacug
uuugggu
uaagggugcau
cuagugcagau
ugauuuguaucu
ucucuu
acugcccuaagug
cuccuucugg
chr4:123546431
..123546479:+
chr1:191643722
..191643776:+
chr18:54773768.
.54773835:+
chr15:95089902.
.95089978:+
chr10:10505014
1..105050199:+
chr13:92003010.
.92003074:+
ACCEPTED MANUSCRIPT
EP
AC
C
SC
Rank
bottom_third
bottom_third
bottom_third
bottom_third
bottom_third
bottom_third
mid_third
bottom_third
mid_third
bottom_third
bottom_third
bottom_third
bottom_third
bottom_third
bottom_third
mid_third
bottom_third
bottom_third
bottom_third
M
AN
U
Gene Symbol
ACAD11
AFG3L1
AHI1
ALDH4A1
ANKRD32
ape
ARID1A
ARID4A
ASH2L
ATG12
ATP13A5
ATP9A
BBS10
BCL11B
BCL2L13
BEGIN_HUMAN
Bk125H2.1
C11or f24
C11 or f9
TE
D
miRNA
Has-mir-194_star
Has-mir-124_star
Has-mir-7d_star
Has-mir-18b_star
Has-mir-424_star
Has-mir-373_star
Has-mir-92a-2_star
Has-mir-106b_star
Has-mir-29a_star
Has-mir-513-3p
Has-mir-26a-2_star
Has-mir-130b_star
Has-mir-150_star
Has-mir-302a_star
Has-mir-340_star
Has-mir-23a_star
Has-mir-139
Has-mir-220
Has-mir-3550_star
RI
PT
Table 5: Targets of known miRNAs in BI
ACCEPTED MANUSCRIPT
EP
AC
C
SC
Rank
bottom_third
bottom_third
bottom_third
bottom_third
bottom_third
bottom_third
mid_third
bottom_third
mid_third
bottom_third
bottom_third
bottom_third
bottom_third
bottom_third
bottom_third
mid_third
bottom_third
bottom_third
bottom_third
M
AN
U
Gene Symbol
ACAD11
AFG3L1
AHI1
ALDH4A1
ANKRD32
ape
ARID1A
ARID4A
ASH2L
ATG12
ATP13A5
ATP9A
BBS10
BCL11B
BCL2L13
BEGIN_HUMAN
Bk125H2.1
C11or f24
C11 or f9
TE
D
miRNA
Has-mir-194_star
Has-mir-124_star
Has-mir-7d_star
Has-mir-18b_star
Has-mir-424_star
Has-mir-373_star
Has-mir-92a-2_star
Has-mir-106b_star
Has-mir-29a_star
Has-mir-513-3p
Has-mir-26a-2_star
Has-mir-130b_star
Has-mir-150_star
Has-mir-302a_star
Has-mir-340_star
Has-mir-23a_star
Has-mir-139
Has-mir-220
Has-mir-550_star
RI
PT
Table 6: Targets of known miRNAs in CI
ACCEPTED MANUSCRIPT
Table 7: 5' UTR Targets of novel miRNAs in BI
Novel miRNA
Chr13_5344
Target ID
Hit Acc.
5HSAA092076_BA092076 gi|194382934|dbj|BAG59023.1|
5HSAA098165_BA09816
Chr5_2695
no hit
SC
5HSAA081767_BA081767 gi|694921514|ref|XP_00944136| Predicted: putative
postmeiotic segregation
increased 2-like protein
12 isoform X4 [Pan
troglodytes]
5HSAA111419_BA111419 no hit
no hit
5HSAA111419_BA111421 no hit
no hit
5HSAA111420_BA111420 no hit
no hit
5HSAA111441_BA111441 no hit
no hit
5HSAA094709_BA094709 no hit
no hit
M
AN
U
Chr17_6310
no hit
RI
PT
5HSAA092077_BA092077 gi|194382934|dbj|BAG59023.1|
Protein name
Unnamed protein product
[Homo sapiens]
Unnamed protein product
[Homo sapiens]
Table 8: 3' UTR Targets of novel miRNAs in BI
Target ID
Hit Acc.
3HSAA174308_CA174308 gi|344247605|gb|EGW03709.1|
ChrX_7528
3HSAA050307_CA050307 no hit
AC
C
EP
TE
D
Novel miRNA
Chr17_6310
Protein name
Glyceraldehyde-3phosphate dehydrogenase,
testis-specific [Cricetulus
griseus]
no hit
ACCEPTED MANUSCRIPT
Table 9: CDS Targets of novel miRNAs in BI
Protein name
Protein disulfide-isomerase A6
isoform d precursor [Homo
sapiens]
Ceramide synthase 3 isoform 1
[Homo sapiens]
ENST00000284382
gi|594140617|ref|NP_001277270.1|
ENST00000394113
gi|594140617|ref|NP_001277270.1|
Ceramide synthase 3 isoform 1
[Homo sapiens]
ENST00000394113
gi|594140617|ref|NP_001277270.1|
ENST00000368985
gi|23110962|ref|NP_004070.3|
ENST00000448301
gi|315075311|ref|NP_001186668.1|
ENST00000472977
gi|260656357|pdb|31EJ|A
ENST00000483930
gi|12621903|gb|AAB60643.2|
Ceramide synthase 3 isoform 1
[Homo sapiens]
Cathepsin S isoform 1
preproprotein [Homo sapiens]
Cathepsin S isoform 2
preproprotein [Homo sapiens]
>gi|194376464|dbj|BAG6299
1.1|unnamed protein product
[Homo sapiens]
Chain A, Pyrazole-Based
Cathepsin S Inhibitors With
Arylalkynes As P1 Binding
Elements
Cathepsin S, partial [Homo
sapiens]
TE
D
M
AN
U
SC
RI
PT
Hit Acc.
gi|5031973|ref|NP_005733.1|
EP
ChrX_7528
Target ID
ENST00000272227
AC
C
Novel miRNA
Chr17_6310
ACCEPTED MANUSCRIPT
Table 10: 5' UTR Targets of novel miRNAs in CI
Novel miRNA
Chr1_612
Target ID
Hit Acc.
5HSAA060154_BA060154 gi|521029117|gb|EPQ10905.1|
5HSAA051388_BA051388
5HSAA051390_BA051390
5HSAA051391_BA051391
5HSAA066753_BA066753
no hit
no hit
no hit
gi|432105116 |gb|ELK31485.1|
SC
Chr4_2344
RI
PT
5HSAA060154_BA060155 gi|521029117| gb|EPQ10905.1|
M
AN
U
5HSAA098157_BA098157 gi|562875850| ref|XP_006165720.1
Chr4_2588
Protein name
Hypothetical protein
d623_10027736 [Myotis
brandtii]
Hypothetical protein
d623_10027736 [Myotis
brandtii]
no hit
no hit
no hit
Putative tumor
suppressor protein MN1
[Myotis brandtii]
PREDICTED: LOW
QUALITY PROTEIN:
protein Shroom4-like
[Tupaia chinensis]
PREDICTED: protein
argonaute 12-like[Pan
paniscus]
5HSAA044294_BA044294 gi|675780980| ref|XP_008976930.1
Target ID
3HSAA025272_CA025272
Hit Acc.
gi|343959558|dbj|BAK63636.1|
3HSAA025273_CA025273
gi|578817114|ref|XP_006717042.1|
EP
Novel miRNA
Chr1_612
TE
D
Table 11: 3' UTR Targets of novel miRNAs in CI
AC
C
3HSAA025274_CA025274
ChrX_7528
gi|343959558|dbj|BAK63636.1|
3HSAA025274_CA025276
gi|343959558|dbj|BAK63636.1|
3HSAA025275_CA025275
gi|343959558|dbj|BAK63636.1|
3HSAA025275_CA025277
gi|343959558|dbj|BAK63636.1|
3HSAA025278_CA025278
gi|343959558|dbj|BAK63636.1|
3HSAA050307_CA050307
no hit
Protein name
Tropomodulin-1 [Pan
troglodytes]
PREDICTED: thiosulfate
sulfurtransferase/rhodaneselike domain-containing protein
2 isoform X2 [Homo sapiens]
Tropomodulin-1 [Pan
troglodytes]
Tropomodulin-1 [Pan
troglodytes]
Tropomodulin-1 [Pan
troglodytes]
Tropomodulin-1 [Pan
troglodytes]
Tropomodulin-1 [Pan
troglodytes]
no hit
ACCEPTED MANUSCRIPT
Table 12: CDS Targets of novel miRNAs in CI
ENST00000286744
gi|145275198|ref|NP_997400.2|
ENST00000567476
gi|666875813|ref|NP_001288039.1|
ADAMTS-like protein 3 isoform
a precursor [Homo sapiens]
ENST00000284382
gi|594140617|ref|NP_001277270.1|
ENST00000394113
gi|594140617|ref|NP_001277270.1|
ENST00000538112
gi|594140617|ref|NP_001277270.1|
ENST00000368985
gi|23110962|ref|NP_004070.3|
ENST00000448301
gi|315075311|ref|NP_001186668.1|
ENST00000472977
gi|260656357|pdb|31EJ|A
Ceramide synthase 3 isoform 1
[Homo sapiens]
Ceramide synthase 3 isoform 1
[Homo sapiens]
Ceramide synthase 3 isoform 1
[Homo sapiens]
Cathepsin S isoform 1
preproprotein [Homo sapiens]
Cathepsin S isoform 2
preproprotein [Homo sapiens]
>gi|194376464|dbj|BAG6299
1.1|unnamed protein product
[Homo sapiens]
Chain A, Pyrazole-Based
Cathepsin S Inhibitors With
Arylalkynes As P1 Binding
Elements
Cathepsin S, partial [Homo
sapiens]
SC
M
AN
U
TE
D
ENST00000483930
Protein name
Protein disulfide-isomerase A6
isoform d precursor [Homo
sapiens]
ADAMTS-like protein 3 isoform
a precursor [Homo sapiens]
RI
PT
Hit Acc.
gi|5031973|ref|NP_005733.1|
gi|12621903|gb|AAB60643.2|
EP
ChrX_7528
Target ID
ENST00000272227
AC
C
Novel miRNA
Chr17_7844
ACCEPTED MANUSCRIPT
Table 13: Differential expression analysis as BI control and CI treated
Log2Fold
Change
P Value
19.35
Has-mir-151a
11
4
25.94
Has-mir-30c-2
42
15
Has-mir-30c-1
42
Has-mir-15b
0.24
-2.037
0.009
6.45
4.02
2.007
99.03
24.19
4.09
2.033
15
99.03
24.19
4.09
2.033
28
10
66.02
16.13
4.09
2.033
Has-mir-484
51
18
120.26
29.03
4.14
2.05
0
Down Regulated
Has-mir-128-2
3
1
7.07
1.61
4.39
2.133
0.043
Down Regulated
Has-mir-1470
8
2
18.86
3.23
Has-mir-9-3
4
1
9.43
1.61
Has-mir-128-1
4
1
4.72
1.61
Has-mir-9-1
4
1
9.43
1.61
Has-mir-9-2
4
1
9.43
1.61
Has-mir-671
8
1
18.86
1.61
Up Regulated
0
Down Regulated
0
Down Regulated
0
Down Regulated
0
Down Regulated
5.85
2.548
0
Down Regulated
5.85
2.548
0.012
Down Regulated
5.85
2.548
0.012
Down Regulated
5.85
2.548
0.012
Down Regulated
5.85
2.548
0.012
Down Regulated
11.7
3.548
0
Down Regulated
TE
D
EP
Regulation
RI
PT
4.72
fold
change
SC
CPM
CI
M
AN
U
CPM
BI
Has-mir-8065
BI
CI
read
Read
count count
2
12
AC
C
ID
ACCEPTED MANUSCRIPT
Table 14: Total unique target genes from mirDIP darabase
Total unique pulled target genes from mirDIP database
12000
9915
9294
845
819
0
0
0
0
0
0
0
0
M
AN
U
SC
RI
PT
ID
Has-mir-15b
Has-mir-671
Has-mir-484
Has-mir-30c-2
Has-mir-30c-1
Has-mir-8065
Has-mir-151a
Has-mir-128-2
Has-mir-1470
Has-mir-9-3
Has-mir-128-1
Has-mir-9-1
Has-mir-9-2
Table 15: Identification KEGG pathways and gene counts
Statistics
C=1130;O=560;E=241.47;R=2.32;rawP=4.85e-100;adjP=1.10e-97
C=326;O=225;E=69.66;R=3.23;rawP=1.98e-76;adjP=2.24 e-74
C=268;O=160;E=57.27;R=2.79;rawP=2.68e-42;adjP=2.02e-40
C=213;O=135;E=45.52;R=2.97;rawP=5.38e-40;adjP=3.04e-38
C=200;O=129;E=42.74;R=3.02;rawP=1.77e-39;adjP=8.00e-38
C=138;O=101;E=29.49;R=3.42;rawP=1.16e-38;adjP=4.37e-37
C=150;O=104;E=32.05;R=3.24;rawP=2.51e-36;adjP=8.10e-35
C=177;O=113;E=37.82;R=2.99;rawP=3.80e-34;adjP=1.07e-32
C=201;O=122;E=42.95;R=2.84;rawP=1.37e-33;adjP=3.44e-32
C=129;O=91;E=27.57;R=3.3;rawP=6.64e-33;adjP=1.50e-31
TE
D
#Gene
560
225
160
135
129
101
104
113
122
91
AC
C
EP
Pathway Name
Metabolic pathways
Pathway in cancer
MAPK signaling pathway
Regulation of actin cytoskeleton
Focal adhesion
Insulin signaling pathway
Wnt signaling pathway
Calcium signaling pathway
Endocytosis
Axon guidance
AC
C
EP
TE
D
M
AN
U
SC
RI
PT
ACCEPTED MANUSCRIPT
AC
C
EP
TE
D
M
AN
U
SC
RI
PT
ACCEPTED MANUSCRIPT
AC
C
EP
TE
D
M
AN
U
SC
RI
PT
ACCEPTED MANUSCRIPT
AC
C
EP
TE
D
M
AN
U
SC
RI
PT
ACCEPTED MANUSCRIPT
AC
C
EP
TE
D
M
AN
U
SC
RI
PT
ACCEPTED MANUSCRIPT
AC
C
EP
TE
D
M
AN
U
SC
RI
PT
ACCEPTED MANUSCRIPT
AC
C
EP
TE
D
M
AN
U
SC
RI
PT
ACCEPTED MANUSCRIPT
ACCEPTED MANUSCRIPT
To explore the leishmaniacidal role of trans-dibenzalacetone (DBA) on the expression
profile of miRNA in intracellular amastigotes of Leishmania donovani.
AC
C
EP
TE
D
M
AN
U
SC
mir-151a) and autophagy (has-mir-30c).
RI
PT
DBA triggers imbalance between two known phenotypes of cell death viz apoptosis (hsa-
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