Harinder Singh, PhD

Staff Scientist
301-795-7684

Harinder Singh, PhD is a Staff Scientist in the Infectious Disease Department at the J. Craig Venter Institute (JCVI). Dr. Singh's area of research is mostly focused on various data analysis, data mining, development of prediction algorithm and databases and bioinformatics pipelines for the scientific community. Dr. Singh has significant experience in analyzing proteomics, metabolomics, expression, microbiome and metagenomics datasets using various bioinformatics pipelines. Dr. Singh's interest lies in understanding the long-term effects of diabetes and predict bio-signature with the progression of diabetes using meta-omics dataset and system biology. Dr. Singh received his PhD from CSIR-Institute of Microbial Technology in Bioinformatics and obtained his master’s degree in biotechnology from Thapar University, INDIA.

Research Priorities

Analysis of microbiomes using metagenomics
  • Understanding human disease diagnosis and progression due to changes in the microbiome.
  • Prediction of geo-location based on the personal microbiome.
Understanding diabetes and chronic kidney diseases
  • Protein biomarkers for diagnosis and progression of diabetes and chronic kidney disease.
Development of Bioinformatics tools
  • Pipeline for analyzing different ‘omics data.
  • Development of prediction methods for understanding complex datasets.
  • Management and development of databases and web-based applications.

Publications

Cantwell AM, Singh H, Platt M, Yu Y, Lin YH, Ikeno Y, Hubbard G, Xiang Y, Gonzalez-Juarbe N, Dube PH
Kinetic Multi-omic Analysis of Responses to SARS-CoV-2 Infection in a Model of Severe COVID-19.
Journal of virology. 2021-09-27; 95.20: e0101021.
PMID: 34319784
Yu Y, Singh H, Tsitrin T, Bekele S, Lin YH, Sikorski P, Moncera KJ, Torralba MG, Morrow L, Wolcott R, Nelson KE, Pieper R
Urethral Catheter Biofilms Reveal Plasticity in Bacterial Composition and Metabolism and Withstand Host Immune Defenses in Hypoxic Environment.
Frontiers in medicine. 2021-06-23; 8.667462.
PMID: 34249966
HaileMariam M, Yu Y, Singh H, Teklu T, Wondale B, Worku A, Zewude A, Mounaud S, Tsitrin T, Legesse M, Gobena A, Pieper R
Protein and Microbial Biomarkers in Sputum Discern Acute and Latent Tuberculosis in Investigation of Pastoral Ethiopian Cohort.
Frontiers in cellular and infection microbiology. 2021-06-04; 11.595554.
PMID: 34150670
Hertzberg VS, Singh H, Fournier CN, Moustafa A, Polak M, Kuelbs CA, Torralba MG, Tansey MG, Nelson KE, Glass JD
Gut microbiome differences between amyotrophic lateral sclerosis patients and spouse controls.
Amyotrophic lateral sclerosis & frontotemporal degeneration. 2021-04-05; 1-9.
PMID: 33818222
Yu Y, Singh H, Kwon K, Tsitrin T, Petrini J, Nelson KE, Pieper R
Protein signatures from blood plasma and urine suggest changes in vascular function and IL-12 signaling in elderly with a history of chronic diseases compared with an age-matched healthy cohort.
GeroScience. 2021-04-01; 43.2: 593-606.
PMID: 32974878
Singh H, Clarke T, Brinkac L, Greco C, Nelson KE
Forensic Microbiome Database: A Tool for Forensic Geolocation Meta-Analysis Using Publicly Available 16S rRNA Microbiome Sequencing.
Frontiers in microbiology. 2021-03-23; 12.644861.
PMID: 33833745
Singh H, Miyamoto S, Darshi M, Torralba MG, Kwon K, Sharma K, Pieper R
Gut Microbial Changes in Diabetic db/db Mice and Recovery of Microbial Diversity upon Pirfenidone Treatment.
Microorganisms. 2020-09-03; 8.9:
PMID: 32899353
Yu Y, O'Rourke A, Lin YH, Singh H, Eguez RV, Beyhan S, Nelson KE
Predictive Signatures of 19 Antibiotic-Induced Escherichia coli Proteomes.
ACS infectious diseases. 2020-08-14; 6.8: 2120-2129.
PMID: 32673475
Bluemel S, Wang L, Kuelbs C, Moncera K, Torralba M, Singh H, Fouts DE, Schnabl B
Intestinal and hepatic microbiota changes associated with chronic ethanol administration in mice.
Gut microbes. 2020-05-03; 11.3: 265-275.
PMID: 30982395
Chodisetti SB, Fike AJ, Domeier PP, Singh H, Choi NM, Corradetti C, Kawasawa YI, Cooper TK, Caricchio R, Rahman ZSM
Type II but Not Type I IFN Signaling Is Indispensable for TLR7-Promoted Development of Autoreactive B Cells and Systemic Autoimmunity.
Journal of immunology (Baltimore, Md. : 1950). 2020-02-15; 204.4: 796-809.
PMID: 31900342
Singh H, Torralba MG, Moncera KJ, DiLello L, Petrini J, Nelson KE, Pieper R
Gastro-intestinal and oral microbiome signatures associated with healthy aging.
GeroScience. 2019-12-01; 41.6: 907-921.
PMID: 31620923
Lin YH, Eguez RV, Torralba MG, Singh H, Golusinski P, Goliusinski W, Golusinski W, Masternak M, Nelson KE, Freire M, Yu Y
Self-Assembled STrap for Global Proteomics and Salivary Biomarker Discovery.
Journal of proteome research. 2019-04-05; 18.4: 1907-1915.
PMID: 30848925
Moustafa A, Li W, Singh H, Moncera KJ, Torralba MG, Yu Y, Manuel O, Biggs W, Venter JC, Nelson KE, Pieper R, Telenti A
Microbial metagenome of urinary tract infection.
Scientific reports. 2018-03-12; 8.1: 4333.
PMID: 29531289
Clarke TH, Gomez A, Singh H, Nelson KE, Brinkac LM
Integrating the microbiome as a resource in the forensics toolkit.
Forensic science international. Genetics. 2017-09-01; 30.141-147.
PMID: 28728057
Singh H, Yu Y, Suh MJ, Torralba MG, Stenzel RD, Tovchigrechko A, Thovarai V, Harkins DM, Rajagopala SV, Osborne W, Cogen FR, Kaplowitz PB, Nelson KE, Madupu R, Pieper R
Type 1 Diabetes: Urinary Proteomics and Protein Network Analysis Support Perturbation of Lysosomal Function.
Theranostics. 2017-07-07; 7.10: 2704-2717.
PMID: 28819457
Singh H, Singh S, Singla D, Agarwal SM, Raghava GP
QSAR based model for discriminating EGFR inhibitors and non-inhibitors using Random forest.
Biology direct. 2015-03-25; 10.10.
PMID: 25880749
Singh H, Singh S, Raghava GP
Evaluation of protein dihedral angle prediction methods.
PloS one. 2014-01-01; 9.10: e105667.
PMID: 25166857
Singh H, Ansari HR, Raghava GP
Improved method for linear B-cell epitope prediction using antigen's primary sequence.
PloS one. 2013-01-01; 8.12: e62216.
PMID: 23667458
Singh H, Chauhan JS, Gromiha MM, Open Source Drug Discovery Consortium, Raghava GP
ccPDB: compilation and creation of data sets from Protein Data Bank.
Nucleic acids research. 2012-01-01; 40.Database issue: D486-9.
PMID: 22139939

Research Priorities

Analysis of microbiomes using metagenomics
  • Understanding human disease diagnosis and progression due to changes in the microbiome.
  • Prediction of geo-location based on the personal microbiome.
Understanding diabetes and chronic kidney diseases
  • Protein biomarkers for diagnosis and progression of diabetes and chronic kidney disease.
Development of Bioinformatics tools
  • Pipeline for analyzing different ‘omics data.
  • Development of prediction methods for understanding complex datasets.
  • Management and development of databases and web-based applications.

Improving Treatments for Urinary Tract Infections

Gut Microbiome Sysbiosis in Childhood Acute Lymphoblastic Leukemia (ALL) Patients

Forensics Microbiome Database

Biomarker Discovery and Systems Biology for Types 1 and 2 Diabetes and Healthy Aging

Genomics and Proteomics Approaches to T1D

This study addresses the complex interactions between the host and environmental factors as they relate to the development of Type I Diabetes (T1D). 

Human Hair Microbiota

Past Project
31-May-2016
Blog

Unlocking the Mysteries of the Microbiome