Over the years, I have contributed to various research projects, each enriching my experience and knowledge. I began my journey as an intern at the Nutraceutical Lab at Amity University, where I was responsible for preparing bacterial growth media for anti-microbial testing. Yes, I did spend time in the wet lab before becoming a full-time bioinformatician.
This page showcases a list of my publications, including journal articles, conference papers, and posters. These accomplishments were made possible through the unwavering support and guidance of my mentors and co-authors. I am deeply grateful to each of them.
You can click on their names to learn more about their exceptional contributions and expertise. If you need full access to any of these publications, feel free to write to me.
2024
Title: scMaSigPro: Differential Expression Analysis along Single-Cell Trajectories.
Authors: Priyansh Srivastava, Marta Benegas Coll, Stefan Götz, María José Nueda, Ana Conesa
Journal: Oxford Academic Bioinformatics (ISSN 1367-4811)
Type: Original Article | Software Package
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Abstract:
Understanding the dynamics of gene expression across different cellular states is crucial for discerning the mechanisms underneath cellular differentiation. Genes that exhibit variation in mean expression as a function of Pseudotime and between branching trajectories are expected to govern cell fate decisions. We introduce scMaSigPro, a method for the identification of differential gene expression patterns along Pseudotime and branching paths simultaneously. We assessed the performance of scMaSigPro using synthetic and public datasets. Our evaluation shows that scMaSigPro outperforms existing methods in controlling the False Positive Rate and is computationally efficient.
2023
Title: Mesenchymal Stromal Cells from Individuals with DNMT3A mut Clonal Hematopoiesis Instruct Young Healthy Hematopoietic Stem/Progenitor Cells Towards a Myeloid-Biased Aging Phenotype Resembling That of Patients with Clonal Cytopenia of Undetermined Significance (CCUS).
Authors: Anna Navarro Figueredo, Wencke Walter, Jennifer Rivière, Marit Leilich, Siddhi Pawar, Michèle Buck, Judith S. Hecker, Marta Benegas Coll, Carolina Monzó, Maki Sakuma, Priyansh Srivastava, Ana Conesa, Torsten Haferlach, Mark Van Der Garde, Katharina S. Götze
Journal: Blood (ISSN 0006-4971)
Type: Poster Presentation
2022
Title: PepEngine: A Manually Curated Structural Database of Peptides Containing α, β-Dehydrophenylalanine (ΔPhe) and α-Amino Isobutyric Acid (Aib)
Authors Siddharth Yadav, Samuel Bharti, Priyansh Srivastava, Puniti Mathur
Journal: International Journal of Peptide Research and Therapeutics (ISSN 1573-3904)
Type: Database
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Abstract:
Protein design is the systematic and rational design of protein/peptide molecules for various purposes such as improved activity, novel function, understanding structure–activity relationships (SARs) etc. A common approach to protein design involves methodical and sequential linking of various independently stable structural motifs to arrive at the desired global architecture. Non-standard amino acids which are not present in the classical set of 20 naturally coded amino acids have been utilized to induce, reinforce and stabilize certain desired secondary conformations. Hence, peptides containing non-standard residues can be utilized as structural blocks towards protein/peptide design. To facilitate the above, ‘PepEngine’: a manually curated database providing detailed structural information of synthetic peptides containing non-standard amino acid residues; α, β-dehydrophenylalanine (ΔPhe/ΔF) and α-aminoisobutyric acid (Aib); has been designed. 100 peptides were modelled with accurate, experimentally derived structural information (φ/ψ angles) using the Maestro suite of Schrödinger™. The database was further expanded to include information such as conformation type, terminal modifications, dihedral angles, original references etc. The database was then hosted as a web service including a comprehensive search function with interactive 3D visualization tools to enable wide public dissemination enhancing its utility. Apart from protein/peptide design; PepEngine can also be utilized as a benchmarking dataset for testing computational conformational sampling approaches and validating minimum energy state prediction algorithms. Further expansion of the database has been planned to include other classes of non-standard residues along with a text mining-based pipeline to automatically search the relevant literature for novel peptides. The database is available at www.pepengine.in.
2021
Title: Exposure of androgen mimicking environmental chemicals enhances proliferation of prostate cancer (LNCaP) cells by inducing AR expression and epigenetic modifications.
Authors: Vipendra Kumar Singh, Rajesh Pal, Priyansh Srivastava, Gauri Misra, Yogeshwer Shukla, Pradeep Kumar Sharma
Journal: Elsevier Environmental Pollution (ISSN 0269-7491)
Type: Original Article | Investigative Study
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Abstract:
Exposure to environmental endocrine disrupting chemicals (EDCs) is highly suspected in prostate carcinogenesis. Though, estrogenicity is the most studied behavior of EDCs, the androgenic potential of most of the EDCs remains elusive. This study investigates the androgen mimicking potential of some common EDCs and their effect in androgen-dependent prostate cancer (LNCaP) cells. Based on the In silico interaction study, all the 8 EDCs tested were found to interact with androgen receptor with different binding energies. Further, the luciferase reporter activity confirmed the androgen mimicking potential of 4 EDCs namely benzo[a]pyrene, dichlorvos, genistein and β-endosulfan. Whereas, aldrin, malathion, tebuconazole and DDT were reported as antiandrogenic in luciferase reporter activity assay. Next, the nanomolar concentration of androgen mimicking EDCs (benzo[a]pyrene, dichlorvos, genistein and β-endosulfan) significantly enhanced the expression of AR protein and subsequent nuclear translocation in LNCaP cells. Our In silico studies further demonstrated that androgenic EDCs also bind with epigenetic regulatory enzymes namely DNMT1 and HDAC1. Moreover, exposure to these EDCs enhanced the protein expression of DNMT1 and HDAC1 in LNCaP cells. These observations suggest that EDCs may regulate proliferation in androgen sensitive LNCaP cells by acting as androgen mimicking ligands for AR signaling as well as by regulating epigenetic machinery. Both androgenic potential and epigenetic modulatory effects of EDCs may underlie the development and growth of prostate cancer.
2020
Title: Screening the binding potential of quercetin with parallel, antiparallel and mixed G-quadruplexes of human telomere and cancer proto-oncogenes using molecular docking approach.
Authors: Shikhar Tyagi, Sarika Saxena, Priyansh Srivastava, Taniya Sharma, Nikita Kundu, Sarvpreet Kaur, Jadala Shankaraswamy
Journal: SN Applied Sciences (ISSN 3004-9261)
Type: Original Article
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Abstract:
The bioinformatics analysis revealed that more than 400,000 DNA sequences within the human genome have the potential of forming G-quadruplex structures. Specifically, G-quadruplexes have been proved to be involved in the regulation of replication, DNA damage repair, transcription and translation of cancer-related genes and hence a therapeutic target. Targeting G4 with small molecules may regulate its expression. Chemical molecules generally shows more cellular toxicity while natural small molecules are more bioavailable and hence shows high biological activity together with low toxicity. In the present study, we have screened the binding potential of quercetin with parallel, anti-parallel and mixed conformations of telomeric G-quadruplexes, cancer protoncogenes and RNA G-quadruplex using molecular docking approach. Our results suggest that the quercetin mainly binds with grooves of all selected G-quadruplxes and its planer aromatic rings stabilizes the structure by π-π stacking. The binding energies were in a range of -40.24 to -17.11 kcal/mol, -35.73 to -18.09 kcal/mol, -32.68 to -22.47 kcal/mol for telomeric parallel, anti-parallel and mixed G-quadruplexes respectively. Further, binding energies of quercetin with selected cancer proto-oncogenes are in a range of -38.67 to -12.95 kcal/mol and -14.8 and -14.6 kcal/mol for selected RNA G-quadruplex. Hence, this study highlights the comparative differences in binding energies of quercetin even with a group of single conformation of G-quadruplex and helpful to evaluate the binding potential of quercetin to inhibit the activity of telomerases and down-regulate the expression of oncogenes and to be used as a potential anti-cancer agent.
2019
Title: VIRdb: a comprehensive database for interactive analysis of genes/proteins involved in the pathogenesis of vitiligo.
Authors: Priyansh Srivastava, Alakto Choudhury, Mehak Talwar, Sabyasachi Mohanty, Priyanka Narad, Abhishek Sengupta
Journal: PeerJ Bioinformatics and Genomics (ISSN 2167-8359)
Type: Database
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Abstract:
Vitiligo is a chronic asymptomatic disorder affecting melanocytes from the basal layer of the epidermis which leads to a patchy loss of skin color. Even though it is one of the neglected disease conditions, people suffering from vitiligo are more prone to psychological disorders. As of now, various studies have been done in order to project auto-immune implications as the root cause. To understand the complexity of vitiligo, we propose the Vitiligo Information Resource (VIRdb) that integrates both the drug-target and systems approach to produce a comprehensive repository entirely devoted to vitiligo, along with curated information at both protein level and gene level along with potential therapeutics leads. These 25,041 natural compounds are curated from Natural Product Activity and Species Source Database. VIRdb is an attempt to accelerate the drug discovery process and laboratory trials for vitiligo through the computationally derived potential drugs. It is an exhaustive resource consisting of 129 differentially expressed genes, which are validated through gene ontology and pathway enrichment analysis. We also report 22 genes through enrichment analysis which are involved in the regulation of epithelial cell differentiation. At the protein level, 40 curated protein target molecules along with their natural hits that are derived through virtual screening. We also demonstrate the utility of the VIRdb by exploring the Protein–Protein Interaction Network and Gene–Gene Interaction Network of the target proteins and differentially expressed genes. For maintaining the quality and standard of the data in the VIRdb, the gold standard in bioinformatics toolkits like Cytoscape, Schrödinger’s GLIDE, along with the server installation of MATLAB, are used for generating results. VIRdb can be accessed through “http://www.vitiligoinfores.com/”.
2018
Title: Comparative modelling and virtual screening to discover potential competitive inhibitors targeting the 30s ribosomal subunit S2 and S9 in Acinetobacter baumannii.
Authors: Priyansh Srivastava, Rajesh Pal, Gauri Misra
Journal: IEEE 2018 International Conference on Bioinformatics and Systems Biology (BSB)
Type: Conference Proceedings
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Abstract:
Development of multidrug resistance in pathogenic bacterial species is one of the most catastrophic problems faced by mankind these days. Acinetobactor baumannii belongs to the group of `ESKAPE’ pathogens which includes the bacterial species that have developed the resistance to first-line antibiotics. It is responsible for causing community acquired diseases. Therefore, identification of new drug targets holds considerable importance in order to combat the drug resistance in this pathogen. In this context, 30s ribosomal subunit S2 (rpsI) and 30s ribosomal subunit S9 (rpsB) appears to be a promising choice as they are found in most of the pathogenic strains and is crucial for protein synthesis in this bacteria.