When did it all begin?
After attending Dr. Guarracino’s bioinformatics workshop, I became more interested in the field of bioinformatics. Then I taught myself through ebooks and attempted to install some bioinformatics-related software on my PC. I was still using BioLinux at the time (a derivative of Ubuntu with many bioinformatics software).
Then, in December 2017, I registered for the SBVIMPROVER Microbiomics Computational Challenge, in which participants were required to analyze metagenomics data and submit a file containing taxonomic profiles. I began downloading datasets (four tar archives containing gzipped Fastq files for the 19 samples, totaling approximately 56 Gb). These datasets are pretty large files, and downloading them all may take some time. I even failed to download entire datasets because my internet connection went down several times. Those were some of the difficulties I encountered. Then I tried to contact my microbiology lecturer on campus to express my interest in competing in this competition. However, our lab lacked High-Performance Computing capabilities (HPC). So I finally withdrew from this competition. But there are some advantages: I’ve become acquainted with metagenomics data analysis. I also learned how to analyze sequencing data using Galaxy (a publicly accessible web server). Also, I realized that if we want to accomplish something significant, we should collaborate with others or join a research group.
I learned more about the world of metagenomics data analysis after participating in a three-month Bioinformatics Research Fellowship. It was organized by PineBio in the United States and the Tauber Bioinformatics Research Center in Israel. There are several pieces of training in multi-omics that I could complete, including Introduction to Bioinformatics, Genomics, Transcriptomics, Metagenomics, Epigenetics, and Machine Learning for Biomedical Data.
One of the projects involved experimenting with metagenomic data analysis. The project focuses on the gut-brain axis and demonstrates how a specific diet affects the gut microbiome and has the potential to influence behavior, with animal studies linking anxiety to a high-fat diet. We practiced working with amplicon data using the DADA2 pipeline on a gut microbiome dataset. This paper contains the references for this project (Bruce-Keller et al., 2015).
My thesis research currently deals with the microbiome under the supervision of Dr. Rarastoeti Pratiwi & Dr. Putra Santoso. One of the variables is the effect of a specific diet (jicama fiber) on the fecal microbiome in mice fed a high-fat diet.
Bruce-Keller, A. J., Salbaum, J. M., Luo, M., Blanchard, E., 4th, Taylor, C. M., Welsh, D. A., & Berthoud, H. R. (2015). Obese-type gut microbiota induce neurobehavioral changes in the absence of obesity. Biological psychiatry, 77(7), 607–615. https://doi.org/10.1016/j.biopsych.2014.07.012