Ashok K Sharma, PhD Computational Biology
Current Role:
📚 Scientist-II, Computational Biology, Takeda, San Diego
- As part of the Computational Biology and Toxicology (CBT) team at the Global Drug Safety Research Evaluation (DSRE), I drive safety risk assessment through predictive modeling and large-scale transcriptomic data analysis, enhancing drug discovery research efficiency and consistency.
- Developing AI/ML models for predicting toxicological endpoints like Hepatotoxicity (DILI) and Neurotoxicity, and supporting the Oligo working group with off-target identification strategies to improve the safety and effectiveness of different modalities, including small molecules and biologics.
Previous Experience:
📚 Postdoctoral Researcher, Cedars Sinai Medical Center
- Thoroughly analyzed and integrated multi-omics datasets, aiming to identifying pathogenic factors in Inflammatory Bowel Disease (IBD). Projects included:
- Analyzed Imaging Mass Cytometry Datasets for Bacterial Co-Localization in Crohn's Disease.
- Quantified bacterial growth rates from metagenomic datasets to identify activities associated with Crohn’s disease progression.
- Investigated microbial role in SARS-COV-2 persistence in the GI Tract.
- Explored the impact of Human Milk Oligosaccharides on Gene Expression and Immune Response in the Intestines.
📚 Postdoctoral Associate, University of Minnesota Twin Cities
- Delved into understanding microbiome-host interactions in both animal and human models under diverse physiological conditions. Projects included:
- Primates Gut Bacteriome & Mycobiome defies evolutionary constraints.
- Gut microbial functional adaptations influenced by diet and lifestyle factors.
- Oral microbiome studies in HNSCC and ex-vivo dental caries.
- Animal microbiome research on Beef cattle, Horses and other domestic animals.
Education:
- Ph.D. in Computational Biology, IISER Bhopal
- I applied computational biology to various domains such as drug discovery and microbiome-host interactions, laying the foundation for my passion in computational biology and its applications in addressing key questions from complex biological datasets.
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Research
I was deeply engaged in the development and application of AI/machine learning and other data-driven methodologies to discern the impact of the microbiome on the general growth, health, and well-being of both animals and humans. A significant portion of my research focused on deducing diet-microbiome-host interactions from multi-omics libraries. The following is a list of my representative papers from that time:
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The role of the intestine in metabolic dysregulation in murine Wilson disease
Gaurav V Sarode,
Tagreed Mazi,
Kari Neier,
Shibata, Noreene M,
Guillaume Jospin ,
Nathaniel Harder H.O,
AmandaCaceres,
Marie Heffern ,
Ashok K. Sharma,
Shyam More,
Maneesh Dave,
Shannon Schroeder,
Li Wang,
Janine LaSalle,
Svetlana Lutsenko,
Valentina Medici
Hepatology Communications, 2023
paper
Intestine-specific ATP7B deficiency affected both intestinal and systemic response to a high-fat challenge but not the microbiome profile, at least at early stages.
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Functional signatures of ex-vivo dental caries onset
Dina Moussa,
Ashok K. Sharma,
Tamer Mansour,
Bruce Witthuhn,
Jorge Perdigao
Henriques,
Joel Rudney,
Conrado
Aparicio Badenas,
Andres Gomez
Journal of Oral Microbiology, 2022
raw data /
paper
We optimize ex-vivo model integrated with the advanced imaging combined with
multi-omics libraries to detect functional signatures associated with dental
caries.
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In-Patient Antibiotic Exposure Promotes SARS-COV-2 Persistence in
the Gi Tract in Covid-19 Admitted Patients
Ashok K. Sharma,
Anthony Martin,
Jacob
Moskowitz,
Stephanie Bora,
Katherine Lagree,
Pieter Dorrestein,
David
Underhill,
Rob Knight,
Peter
Chen,
Suzanne Devkota
Gastroenterology, 2022   (Oral
Presentation)
raw data /
presentation /
abstract
The heavy-dose antibiotic regimen administered to COVID-19 in-patients is
associated with viral persistence of SARS-COV-2 in the GI tract, suggesting an
important role of the gut microbiome in excluding SARS-COV-2 from the GI tract,
perhaps by competitive exclusion or promoting interferon responses.
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Human Milk Oligosaccharides Impact Cellular and Inflammatory Gene
Expression and Immune Response
Fernanda
Rosa,
Ashok K. Sharma,
Manoj
Gurung,
David
Casero,
Katelin Matazel,
Lars Bode,
Christy
Simecka,
Ahmed
Elolimy,
Patricia
Tripp,
Christopher E
Randolph,
Timothy W
Hand,
D Keith
Williams,
Tanya LeRoith,
Laxmi
Yeruva
Frontiers in Microbiology , 2022
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paper
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project page
In this study, we have shown that HMO administration appears to promote
immunoregulatory effects at the gene expression level in the absence of gut
microbiota.
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Dietary zinc restriction affects the expression of genes related to
immunity and stress response in the small intestine of pigs
Ramya Lekha
Medida,
Ashok K. Sharma,
Yue Guo,
Lee Johnston,
Pedro Urriola,
Andres Gomez,
Milena Saqui Salces
Journal of Nutritional Science, 2022
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paper
The main goal of the present study was to understand intestinal responses to
nutritional Zn restriction and supplementation that could influence overall
health of the animal and indicate early changes in response to Zn restriction.
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Human Assessing the Effect of Smokeless Tobacco Consumption on Oral
Microbiome in Healthy and Oral Cancer Patients
Rituja
Saxena,
Vishnu
Prasoodanan,
Sonia Vidushi
Gupta,
Sudheer Gupta,
Prashant Waiker,
Atul Samaiya,
Ashok K. Sharma,
Vineet
K. Sharma
Frontiers in Cellular and Infection Microbiology , 2022
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paper
In this study, we profiled oral microbiome of healthy and oral cancer patients
to decipher the microbial dysbiosis due to the consumption of
smokeless-tobacco-based products and also revealed the tobacco-associated
microbiome.
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Microbiome network traits in the rumen predict average daily gain in
beef cattle under different backgrounding systems
Bobwealth
Oakina Omontese,
Ashok K. Sharma,
Samuel Davison,
Emily Jacobson,
Alfredo
DiCostanzo,
Megan Webb,
Andres Gomez
Animal Microbiome , 2022
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paper
This longitudinal study was designed to assess how BKG affects rumen bacterial
communities and average daily gain (ADG) in beef cattle.
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The primate gut mycobiome-bacteriome interface is impacted by
environmental and subsistence factors
Ashok K. Sharma,
Samuel Davison,
Barbora Pafco,
Jonathan B. Clayton,
Jessica Rothman,
Matthew
McLennan,
Marie
Cibot,
Terence
Fuh,
Roman
Vodicka,
Carolyn Jost Robinson,
Klara Petrzelkova,
Andres Gomez
npj Biofilms and Microbiomes , 2022
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paper /
project page
Our main findings indicate a strong influence of host-ecological factors
including diet and lifestyle in shaping the fungal community composition in the
primate’s gut. This is in contrast with the gut bacterial fraction, which seems
to be more influenced by the host genetics.
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Western and non-western gut microbiomes reveal new roles of
Prevotella in carbohydrate metabolism and mouth–gut axis
Vishnu
Prasoodanan,
Ashok K. Sharma,
Shruti Mahajan,
Darshan
Dhakan,
Joy Scaria,
Vineet
K. Sharma
npj biofilms and microbiomes , 2021
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paper
A population-wide analysis was carried out on 586 healthy samples from western
and non-western populations including the largest Indian cohort comprising of
200 samples, and 189 Inflammatory Bowel Disease samples from western
populations.
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Traditional Human Populations and Nonhuman Primates Show Parallel
Gut Microbiome Adaptations to Analogous Ecological Conditions
Ashok K. Sharma,
Klara Petrzelkova,
Barbora Pafco,
Carolyn Jost Robinson,
Terence
Fuh,
Brenda Anne
Wilson,
Rebecca M.
Stumpf,
Manolito
Torralba,
Ran Blekhman,
Bryan White,
Karen E.
Nelson,
Steven Leigh,
Andres Gomez
mSystems , 2020
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paper /
project page
The results of this study highlight parallel gut microbiome traits in human and
nonhuman primates, depending on subsistence strategy.
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The Horse Gut Microbiome Responds in a Highly Individualized Manner
to Forage Lignification
Andres Gomez,
Ashok K. Sharma,
Amanda Grev,
Craig C
Sheaffer,
Krishona Martison
Journal of Equine Veterinary Science , 2020
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paper
Results in this study indicate that the horse gut microbiome responds in an
individualized manner to changes in the amount of acid detergent lignin in
alfalfa hay, potentially impacting several feed digestibility characteristics.
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Molib: A machine learning based classification tool for the
prediction of biofilm inhibitory molecules
Gopal Narayan
Srivastava,
Aditya
Malwe,
Ashok K. Sharma,
Vibhuti
Shastri,
Keshav
Hibare,
Vineet
K. Sharma
Genomics , 2020
paper
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web page
We developed the ‘Molib’ tool to predict the biofilm inhibitory activity of
small molecules.
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Oral Microbiome Profiling in Smokers with and without Head and Neck
Cancer Reveals Variations Between Health and Disease
Ashok K. Sharma,
William Debusk,
Irina
Stepanov,
Andres Gomez,
Samir Khariwala
Cancer Prevention Research , 2020
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paper
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project page
To determine microbial associations with oral/head and neck cancer (HNSCC) among
tobacco users, we characterized oral microbiome composition in smokers with and
without HNSCC. 16S rRNA MiSeq sequencing was used to examine the oral mucosa
microbiome of 27 smokers with (cases) and 24 without HNSCC (controls).
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Association of Flavonifractor plautii, a Flavonoid-Degrading
Bacterium, with the Gut Microbiome of Colorectal Cancer Patients in India
Ankit Gupta,
Darshan
Dhakan,
Abhijit Maji,
Rituja
Saxena,
Vishnu
Prasoodanan,
Shruti Mahajan,
Joby
Pulikkan,
Kurian Jacob,
Andres Gomez,
Joy Scaria,
Katherine R. Amato,
Ashok K. Sharma,
Vineet
K. Sharma
mSystems , 2019
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paper
This study provides novel insights on the CRC-associated microbiome of a unique
cohort in India, reveals the potential role of a new bacterium in CRC, and
identifies cohort-specific biomarkers, which can potentially be used in
noninvasive diagnosis of CRC.
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Plasticity in the Human Gut Microbiome Defies Evolutionary
Constraints
Andres Gomez,
Ashok K. Sharma**,
Elizabeth K
Mallott,
Klara Petrzelkova,
Carolyn Jost Robinson,
Carl
J Yeoman,
Franck
Carbonero,
Barbora Pafco,
Jessica Rothman,
Alexander
Ulanov,
Klara
Vlckova,
Katherine R. Amato,
Stephanie L.
Schnorr,
Nathaniel J
Dominy,
David
Modry,
Angelique Todd,
Manolito
Torralba,
Karen E.
Nelson,
Michael Burns,
Ran Blekhman,
Melissa J. Remis,
Rebecca M.
Stumpf,
Brenda Anne
Wilson,
Rex Gaskins,
Paul A Garber,
Bryan White,
Steven Leigh
mSphere , 2019
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project page
The results of this study indicate a discordance between gut microbiome
composition and evolutionary history in primates, calling into question previous
notions about host genetic control of the primate gut microbiome.
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Mapping gastrointestinal gene expression patterns in wild primates
and humans via fecal RNA-seq
Ashok K. Sharma,
Barbora Pafco,
Klara
Vlckova,
Barbora Cervena
Jakub
Kreisinger,
Samuel Davison,
Karen Beeri,
Terence
Fuh,
Steven Leigh,
Michael Burns,
Ran Blekhman,
Klara Petrzelkova,
Andres Gomez
BMC Genomics , 2019
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paper
Results in this study suggest that fecal RNA-seq, targeting gastrointestinal
epithelial cells can be used to evaluate primate intestinal physiology and gut
gene regulation, in samples obtained in challenging conditions in situ.
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Gut microbiome composition of wild western lowland gorillas is
associated with individual age and sex factors
Barbora Pafco,
Ashok K. Sharma**
Klara Petrzelkova,
Klara
Vlckova,
Angelique Todd,
Carl
J Yeoman,
Brenda Anne
Wilson,
Rebecca M.
Stumpf,
Bryan White,
Karen E.
Nelson,
Steven Leigh,
Andres Gomez
American Journal of Biological Anthropology , 2019
paper
Objective of this study was to determine the associations between an
individual's age and sex on the diversity and composition of the gut microbiome
in wild western lowland gorillas.
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The unique composition of Indian gut microbiome, gene catalogue, and
associated fecal metabolome deciphered using multi-omics approaches
Darshan
Dhakan,
Abhijit Maji,
Ashok K. Sharma,
Rituja
Saxena,
Joby
Pulikkan,
Tony Grace,
Andres Gomez,
Joy Scaria,
Katherine R. Amato,
Vineet
K. Sharma
GigaScience , 2019
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data
We analyzed the gut microbiome of 110 healthy individuals from two distinct
locations (North-Central and Southern) in India using multi-omics approaches,
including 16S rRNA gene amplicon sequencing, whole-genome shotgun metagenomic
sequencing, and metabolomic profiling of fecal and serum samples.
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Genome Sequence of Peacock Reveals the Peculiar Case of a Glittering
Bird
Subham
K. Jaiswal,
Ankit Gupta,
Rituja
Saxena,
Vishnu
Prasoodanan,
Ashok K. Sharma,
Parul Mittal,
Ankita Roy,
,
Nagarjun Vijay,
Vineet
K. Sharma
Frontiers in Genetics , 2018
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paper
Here, we report the first genome sequence and comparative analysis of
peacock with the high quality genomes of chicken, turkey, duck, flycatcher
and zebra finch.
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Mechanistic and structural insight into promiscuity based metabolism
of cardiac drug digoxin by gut microbial enzyme
Kundan Kumar,
Subham
K. Jaiswal,
Gaurao Dhoke,
Gopal Narayan
Srivastava,
Ashok K. Sharma,
Vineet
K. Sharma
Journal of Cellular Biochemistry , 2017
paper
We report the atomistic details and energy economics binding and metabolism of
Digoxin by the Cgr2 protein of Eggerthella lenta DSM 2243.
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Prediction of anti-inflammatory proteins/peptides: an insilico
approach
Sudheer
Gupta,
Ashok K. Sharma**,
Vibhuti
Shastri,
Midhun K. Madhu
Dhakan,
Vineet
K. Sharma
Journal of Translational Medicine , 2017
paper
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web page
In this study, we have developed a prediction tool for the classification of
peptides as anti-inflammatory epitopes or non anti-inflammatory epitopes.
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Approach for the prediction of species-specific biotransformation
of xenobiotic/drug molecules by the human gut microbiota
Ashok K. Sharma,
Subham
K. Jaiswal
Nikhil
Chaudhary,
Vineet
K. Sharma
Scientific Reports , 2017
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web page
DrugBug is a computational approach to predict the metabolic enzymes and gut
bacterial species, which can potentially carry out the biotransformation of a
xenobiotic/drug molecule
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ToxiM: A Toxicity Prediction Tool for Small Molecules Developed
Using Machine Learning and Chemoinformatics Approaches
Ashok K. Sharma,
Gopal Narayan
Srivastava,
Ankita Roy,
Vineet
K. Sharma
Frontiers in Pharmacology , 2017
paper
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web page
ToxiM is a machine-learning based binary classifier for the prediction of
toxicity of molecules. Regression models for CaCo-2 permeability and Aqueous
solubility has been provided to support the predicted toxicity for a given
molecule. For the batch processing please download standalone version of ToxiM
from Dataset page.
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Prediction of Biofilm Inhibiting Peptides: An In silico Approach
Sudheer
Gupta,
Ashok K. Sharma,
Subham
K. Jaiswal,
Vineet
K. Sharma
Frontiers in Microbiology , 2016
paper
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web page
BioFin is a unique computational method for the prediction of biofilm inhibiting
peptides. The experimentally validated biofilm inhibiting peptides sequences and
their features were used for the training.
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ProInflam: a webserver for the prediction of proinflammatory
antigenicity of peptides and proteins
Sudheer
Gupta,
Midhun K. Madhu
Dhakan,
Ashok K. Sharma,
Vineet
K. Sharma
Journal of Translational Medicine , 2016
paper
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web page
ProInFlam is a unique tool for the computational identification of
proinflammatory peptide antigen/candidates and provides leads for experimental
validations
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Prediction of peptidoglycan hydrolases- a new class of antibacterial
proteins
Ashok K. Sharma,
Sanjiv
Kumar,
Harish K.,
Darshan
Dhakan,
Vineet
K. Sharma
BMC Genomics , 2016
paper
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web page
The present tool helps in the identification and classification of novel
peptidoglycan hydrolases from complete genomic or metagenomic ORFs. To our
knowledge, this is the only tool available for the prediction of peptidoglycan
hydrolases from genomic and metagenomic data.
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Reconstruction of Bacterial and Viral Genomes from Multiple
Metagenomes
Ankit Gupta,
Sanjiv
Kumar,
Vishnu
Prasoodanan,
Harish K.,
Ashok K. Sharma,
Vineet
K. Sharma
Frontiers in Microbiology , 2016
paper
In this work, Binning-Assembly approach has been proposed and demonstrated for
the reconstruction of bacterial and viral genomes from 72 human gut metagenomic
datasets.
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Woods: A fast and accurate functional annotator and classifier of
genomic and metagenomic sequences
Ashok K. Sharma,
Ankit Gupta,
Sanjiv
Kumar,
Darshan
Dhakan,
Vineet
K. Sharma
Genomics , 2015
paper
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web page
Integrated approach for fast and accurate functional annotation of proteins in
both genomic and metagenomic datasets. It is available as stand-alone tool as
well as a publicly available web-server.
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The 16S Classifier: A Tool for Fast and Accurate Taxonomic
Classification of 16S rRNA Hypervariable Regions in Metagenomic Datasets
Nikhil
Chaudhary,
Ashok K. Sharma**,
Piyush
Agarwal,
Ankit Gupta,
Vineet
K. Sharma
PLOS ONE , 2015
paper
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web page
'16S Classifier' is a Random Forest based tool which is developed to carry out
fast, efficient and accurate taxonomic classification of 16S rRNA sequences. It
has the unique ability to classify small Hypervariable Regions of 16S rRNA.
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