Browsing by Author "Upasna Srivastava"

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Ecology and environmental omics
(Elsevier, 2024) Minu Kesheri; Swarna Kanchan; Upasna Srivastava; Bhaskar Chittoori; Ratnaprabha Ratna-Raj; Rajeshwar P. Sinha; Akhouri Vaishampayan; Rajesh P. Rastogi; Donald A. Primerano
Advancements in high-throughput omics technologies enabling rapid profiling of genes, mRNA, proteins, metabolites, metagenomes, etc. have accelerated the research in ecological and environmental omics. Ecological and environmental omics focus on a better understanding of the environmental and genetic factors, chemical toxicity mechanisms/pathways, biomarkers, and modes of action in response to exposure to a single or mixture of chemicals that result in the development of environmental diseases as long-term effects. Environmental omics also aims to investigate the identification of unknown environmental target organisms, environmental monitoring enabling risk assessment, diverse human health outcomes, environmental impacts, ecological functions, and environmental adaptation. Environmental and ecological omics explore acceptable levels and potential impacts of environmental toxicants on environmental target species and ecosystems. Multiomics technologies are also being used in accessing the environment to revise the existing law related to environmental protection. To date, single omics such as transcriptomics (∼43%) are being used frequently compared with multiomics (∼13%) in environmental research, showing the urgent need for multiomics technologies in environmental research. This chapter focuses on the use of various multiomics studies in accessing the environment, exploring the toxicity mechanisms due to exposure to single and mixture of chemicals to the target organisms. This chapter also focuses on the effect of exploring dietary and environmental factors on an organism's genome, environmental monitoring of health risks assessment, etc. © 2024 Elsevier Inc. All rights reserved.
Exploring Human Brain Disorders Through Multi-Omics Approaches
(Springer Science+Business Media, 2025) Swarna Kanchan; Minu Kesheri; Upasna Srivastava; Bhagaban Mallik; Pramod Katara; Shivani Sharda; Chandandeep Kaur; Rajeshwar Prasad Sinha
Among all the organs, brain is considered as most complex organ in humans. Brain includes various disorders called as neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s disease, which represent one of the top healthcare problems in developed countries. In recent years, the omics technologies have contributed a lot to the identification of novel biomarkers, such as genes and biological pathways, to understand the mechanisms of various brain disorders. These omics approaches help in identifying the molecular signatures of various brain disorders and their interactions at various levels. In this chapter, we describe the applications of omics, single-cell omics, and spatial transcriptomics in brain research. Various omics technologies individually as well as their integration to elucidate various stages of neurological disorders, disease progression and identification of biomarkers have been highlighted. An extensive overview illustrating the state of the art in omics methodologies for exploring brain diseases in lucid style makes this chapter informative and reader friendly. © 2025 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Human–Environment Interactions: A Multi-Omics and Interactome Perspective
(Springer Science+Business Media, 2025) Swarna Kanchan; Minu Kesheri; Poonam Kaithal; Upasna Srivastava; Harleen Kaur; Jainendra K. Pathak; Rajeshwar Prasad Sinha
To understand the effects of the environment as a whole (envirome), it is important to explore various specific domains to assess how, individually and collectively, these domains affect human health. Natural environment features such as sunlight, altitude, diurnal rhythms, vegetation, and biodiversity affect human health. However, the effects of the natural environment are moderated by the social environment, which comprises built environments, agricultural and industrial activities, pollutants and contaminants, culture, economic activities, and social networks that affect health by influencing access to health care. An understanding of the interactions between different domains of the envirome and their integrated effects on human health using various muti-omics and their integration studies could help in exploring the human–environment interactions. This chapter also discusses the concept of interactome and its role in unrevealing human diseases. This chapter illuminates the basic concepts of human health, focusing on elaborating various multi-omics approaches that are instrumental in elucidating the complex interactions between humans and the environment. © 2025 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Integrative omics data mining: Challenges and opportunities
(Elsevier, 2024) Swarna Kanchan; Minu Kesheri; Upasna Srivastava; Hiren Karathia; Ratnaprabha Ratna-Raj; Bhaskar Chittoori; Lydia Bogomolnaya; Rajeshwar P. Sinha; James Denvir
Next-generation sequencing-based high-throughput data has opened novel opportunities to analyze and describe biological processes at a higher resolution. Nowadays, multiomics technologies are generating large amounts of heterogeneous genomics, proteomics, and metabolomics datasets. Integrative approaches enable us to study complex biological processes that combine the analysis of multiple omics datasets to highlight the interplay of the involved genes, transcripts, proteins, metabolites, etc., and their functions. Thus, data integration and data mining are imperative to exploring the mysteries of life and complex diseases in life sciences research. In the present scenario, integrating heterogeneous and huge amounts of genomics, proteomics, and metabolomics data poses conceptual and practical challenges, and encourages researchers to develop novel data integration methodologies, tools, and virtualization platforms. This chapter reviews the current efforts and state of the art about data integration and its mining in life sciences research. This chapter describes various tools and methods in detail that adopt an integrative approach to analyze multiomics data and data mining methods to address phenotype prediction, disease subtyping, a novel biomarker, novel pathways discovery, etc. This chapter provides an extensive overview in lucid style illustrating the methodologies, limitations of these tools, multiomics data repositories, and visualization platforms along with enumerating the challenges associated with multiomics data integration and mining making this chapter informative and reader friendly. © 2024 Elsevier Inc. All rights reserved.
Peculiar Endosymbiosis in the Cyanobiont Nostoc azollae 0708: An In Silico Approach
(Springer Nature, 2024) Minu Kesheri; Swarna Kanchan; Amit Kumar; Upasna Srivastava; Shivani Sharda; Bhagwan Malik; Tarun Mishra; Poonam Kaithal; Jitendra Narayan; Prashant Kumar; Prerna Priya; Rajeshwar P. Sinha
Nostoc azollae 0708 exhibits peculiar endosymbiosis owing to the unique commitment of cyanobiont’s association with fern throughout its life cycle. This chapter elaborates various in silico approaches adopted for intriguing proteomics aspects of Fe and Mn superoxide dismutase in the cyanobiont Nostoc azollae 0708. Prediction of physicochemical parameters elucidating molecular weight, isoelectric point (pI), instability index, aliphatic index, total no. of negatively charged residues (Asp + Glu), total no. of positively charged residues (Arg + Lys), extinction coefficient, and GRAVY are discussed in detail. Generating good quality 3D structural models for Fe-SOD and Mn-SOD by homology modeling and validation by Prosa-web, verify-3D, and PROCHECK is elaborately explained. Conservation of metal binding positions, domains, and motifs suggesting functional conservation, highly conserved exposed as well as buried amino acid residues advocating their structural and functional importance is also discussed. Generation of protein–protein interaction network using STRING illustrating the physical and functional interaction of superoxide dismutase with other proteins and biological cascade of these proteins in Nostoc azollae has been described. The NJ phylogenetic tree for Fe-SOD depicts Nostoc sp. PCC 7524 as the nearest evolutionary homolog, whereas Nostoc sp. PCC 7107 and Nostoc piscinale CENA 21 as evolutionary close homologs of Mn-SOD in Nostoc azollae. The present in silico methodologies discussed in this chapter may pave the way for further experimental validation aiding in exploring the biochemical, biotechnological, and biofertilizer potential of the cyanobiont recruited by the fern Azolla. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.