Mr. Arunmozhi Bharathi Achudhan | Computational Chemistry |  Best Scholar Award

SRM Institute of Science and Technology, India

👨‍🎓Profiles

• Scopus Profile
• ORICD Profile
• Google Scholar

🧬 Academic and Research Background

Mr. Arunmozhi Bharathi Achudhan is a dynamic early-career researcher specializing in environmental genomics and microbiome analysis, currently pursuing his Ph.D. at SRM Institute of Science and Technology, Chennai, with his thesis submitted for review. His doctoral research, titled “Structural and Functional Genomic Analysis of Coal Microbiome and Machine Learning-Based Recovery of Novel Metagenome-Assembled Genomes (MAGs),” integrates next-generation sequencing (NGS) data analysis with computational biology and machine learning. Originally trained in microbiology, he has independently mastered advanced genomics techniques and computational pipelines, using over 150 workflows to deeply explore microbial communities in extreme environments.

🧪 Research Focus and Innovations

His research focuses on unculturable microbial genomes, recovering novel MAGs from coal microbiomes and evaluating their ecological and industrial significance. By analyzing structural diversity and mining functional genes, he has identified and validated novel enzymes like amidase and nitrilase through comparative structure analysis with protein crystal structures available in the Protein Data Bank. These findings carry high biotechnological potential for industrial applications. He has also developed a read-specific binning strategy for improved MAG reconstruction, now filed as a patent, which addresses limitations in existing metagenomics workflows.

💻 Technical and Computational Skills

Mr. Arunmozhi is adept at working in Linux environments and cloud platforms like AWS. He is highly skilled in coding with Python, R, and Perl, and proficient in setting up automated workflows using Snakemake and Conda. His experience includes using powerful metagenomic and proteomic analysis pipelines such as metaWRAP, MuDoGer, SqueezeMeta, Traitar, GTDB-tk, Prokka, Prodigal, AlphaFold, and Gromacs. He also utilizes AutoDockVina, PyMOL, and Schrödinger Suite for molecular docking and structure analysis. His strong command over bioinformatics tools bridges the gap between raw sequencing data and functional biological insights.

🧫 Laboratory Training and Teaching

In addition to his computational expertise, he has received formal training in Microbiology and Molecular Biology techniques, including GLP, and has instructed undergraduate laboratory courses in these areas. He also taught Computational Biology and delivered academic training in research methods, APA formatting, SPSS, and Sigma Plot, equipping students with both theoretical knowledge and practical scientific skills.

🎓 Education and Early Scientific Engagement

Mr. Arunmozhi holds a Master’s degree in Applied Microbiology and a Bachelor’s degree in Microbiology from Madras Christian College, where he also completed a Postgraduate Diploma in Medical Laboratory Technology. His postgraduate research included the molecular characterization of β-agarase from Sphingomonas paucimobilis, and he actively participated in international and national conferences, presenting research on larvicidal activity, microbial virulence, and antimicrobial agents.

🌍 Broader Contributions to Microbiome Science

His independent project on the Indian healthy human gut microbiome involved shotgun metagenomic analysis of 110 samples, where he employed language-based machine learning to identify hidden probiotic genomes. This study provided new insights into unculturable probiotic microbes and showcased how integrating metagenomics with machine learning can revolutionize microbiome research and gut health diagnostics.

🏅 Awards and Recognition

His academic contributions have been recognized through multiple oral presentation awards, including the Best Oral Presentation at the International Conference on Advances and Applications of Biotechnology (2024), and the Young Scientist Award at the International Conference on Innovation in Science and Technology for Sustainable Development (2023). He has also presented his work at several national and international platforms, including the National Conference on Structural Biology and Drug Discovery, and New Horizons in Bioengineering, among others.

🧠 Innovation and Intellectual Property

Mr. Arunmozhi is an innovator in the domain of metagenomic genome reconstruction. His patented approach, A Read-Specific Binning Strategy for the Recovery of Unculturable MAGs, improves the reliability and efficiency of genome assembly from complex microbial communities. This contribution represents a significant advancement in bioinformatics methodology, with applications across environmental microbiology, health, and industrial biotechnology.

🔮 Future Contributions and Vision

With a multidisciplinary skill set spanning microbiology, computational genomics, structural biology, and AI-driven analysis, Mr. Arunmozhi Bharathi Achudhan is poised to make impactful contributions to sustainable biotechnology, precision microbiome therapeutics, and enzyme discovery. He envisions continuing his journey in postdoctoral research, focused on unraveling complex microbial systems and translating genomic discoveries into real-world applications that benefit health and the environment.

📖Notable Publications

1. A review on applications of β-glucosidase in food, brewery, pharmaceutical and cosmetic industries
   Contributors: P. Kannan, A.B. Achudhan, A. Gupta, L.M. Saleena
   Journal: Carbohydrate Research, 530, 108855
   Year: 2023

2. Functional metagenomics uncovers nitrile-hydrolysing enzymes in a coal metagenome
   Contributors: A.B. Achudhan, P. Kannan, L.M. Saleena
   Journal: Frontiers in Molecular Biosciences, 10, 1123902
   Year: 2023

3. A Review of web-based metagenomics platforms for analysing next-generation sequence data
   Contributors: A.B. Achudhan, P. Kannan, A. Gupta, L.M. Saleena
   Journal: Biochemical Genetics, 62(2), 621–632
   Year: 2024

4. CRISPR detection in metagenome-assembled genomes (MAGs) of coal mine
   Contributors: A.B. Achudhan, P. Kannan, L.M. Saleena
   Journal: Functional & Integrative Genomics, 23(2), 122
   Year: 2023