Browsing by Author "Dinesh Kumar Saini"

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A multi-objective hybrid machine learning approach-based optimization for enhanced biomass and bioactive phycobiliproteins production in Nostoc sp. CCC-403
(Elsevier Ltd, 2021) Dinesh Kumar Saini; Amit Rai; Alka Devi; Sunil Pabbi; Deepak Chhabra; Jo-Shu Chang; Pratyoosh Shukla
The cyanobacterial phycobiliproteins (PBPs) are an important natural colorant for nutraceutical industries. Here, a multi-objective hybrid machine learning-based optimization approach was used for enhanced cell biomass and PBPs production simultaneously in Nostoc sp. CCC-403. A central composite design (CCD) was employed to design an experimental setup for four input parameters, including three BG-11 medium components and pH. We achieved a 61.76% increase in total PBPs production and an almost 90% increase in cell biomass by our prediction model. We also established a test genome-scale metabolic network (GSMN) for Nostoc sp. and identified potential metabolic fluxes contributing to PBPs enhanced production. This study highlights the advantage of the hybrid machine learning approach and GSMN to achieve optimization for more than one objective and serves as the foundation for future efforts to convert cyanobacteria as an economically viable source for biofuels and natural products. © 2021 Elsevier Ltd
Algal Biorefinery: An Integrated Approach for Biofuels and Bio Commodities Production Coupled with Environmental Sustainability
(CRC Press, 2024) Dinesh Kumar Saini; Diya Roy; Pratyoosh Shukla; Sunil Pabbi
Algae are fast-growing ubiquitous photosynthetic organisms that are highly diverse and comprise both prokaryotic and eukaryotic organisms. These photoautotrophic organisms with immense plasticity in both morphology (being filamentous, unicellular, and/or colony-forming) and metabolic activity are a well-known natural resource for pigments, vitamins, lipids, biofuels, polysaccharides, bioactive compounds, proteins, etc. In recent times, algae are gaining interest among researchers and industries as a sustainable source of feedstock for biofuels and other non-fuel bioactive compounds. These valuable products have several applications in food and feed, cosmetic, pharmaceutical, and nutraceutical industries. Moreover, the role of algae in environment sustainability, especially in CO2 sequestration and bioremediation of wastewater, is well documented. The present chapter highlights the importance of algae-based biorefinery as a viable approach for biofuel and bio commodities production. In addition, current research on the cultivation of algae with wastewater for remediation and production of high-value compounds is discussed along with its possible impact on the environment. © 2024 selection and editorial matter, Nivedita Sahu and S. Sridhar; individual chapters, the contributors.
Genome-wide association mapping of genomic regions associated with drought stress tolerance at seedling and reproductive stages in bread wheat
(Frontiers Media S.A., 2023) S Srinatha Reddy; Dinesh Kumar Saini; G Mahendra Singh; Sandeep Sharma; Vinod Kumar Mishra; Arun Kumar Joshi
Understanding the genetic architecture of drought stress tolerance in bread wheat at seedling and reproductive stages is crucial for developing drought-tolerant varieties. In the present study, 192 diverse wheat genotypes, a subset from the Wheat Associated Mapping Initiative (WAMI) panel, were evaluated at the seedling stage in a hydroponics system for chlorophyll content (CL), shoot length (SLT), shoot weight (SWT), root length (RLT), and root weight (RWT) under both drought and optimum conditions. Following that, a genome-wide association study (GWAS) was carried out using the phenotypic data recorded during the hydroponics experiment as well as data available from previously conducted multi-location field trials under optimal and drought stress conditions. The panel had previously been genotyped using the Infinium iSelect 90K SNP array with 26,814 polymorphic markers. Using single as well as multi-locus models, GWAS identified 94 significant marker-trait associations (MTAs) or SNPs associated with traits recorded at the seedling stage and 451 for traits recorded at the reproductive stage. The significant SNPs included several novel, significant, and promising MTAs for different traits. The average LD decay distance for the whole genome was approximately 0.48 Mbp, ranging from 0.07 Mbp (chromosome 6D) to 4.14 Mbp (chromosome 2A). Furthermore, several promising SNPs revealed significant differences among haplotypes for traits such as RLT, RWT, SLT, SWT, and GY under drought stress. Functional annotation and in silico expression analysis revealed important putative candidate genes underlying the identified stable genomic regions such as protein kinases, O-methyltransferases, GroES-like superfamily proteins, NAD-dependent dehydratases, etc. The findings of the present study may be useful for improving yield potential, and stability under drought stress conditions. Copyright © 2023 Reddy, Saini, Singh, Sharma, Mishra and Joshi.