Why are most of microorganisms yet-to-be cultivated? This question is often answered with the common cliché that many are recalcitrant to cultivation. While this may hold some truth, it is essential to note that the rapid increase in metagenome-assembled genomes (MAGs) without cultivation has surpassed the number of cultured microbes over the last decade. Contrasted with MAGs data, cultivation-dependent microbiology has maintained its classical methodologies, which may have substantial pitfalls. This review aims to provide an overview of these issues to gain a better understanding of the various facets of yet-to-be cultured microbes.

AlphaFold2, a protein structure prediction method developed by Google DeepMind, surprised the world with its high prediction accuracy of protein structures. And it quickly became widely used by researchers around the world. 2020 may be remembered as the year that the long-standing problem of protein structure prediction was solved. Before AlphaFold2 emerged, there are the accumulation of research on protein structures, advances in genome research with the next-generation sequencers, improvements in computing power, and the development of artificial intelligence (AI). In this article, we will explain AlphaFold2 while mentioning these factors. Finally, we would like to look to the future by introducing AlphaFold3, which was just announced this May.

Amplicon sequencing is a method of analyzing 16S ribosomal RNA (16S rRNA) nucleotide sequence information in all bacterial genomes. By amplifying the target sequence, it is possible to determine the phylogenetic composition of the bacteria present in a small sample. We first describe the primers used in the PCR and the general framework of the data analysis. We then describe the experimental design of the dataset and the installation of the R package dada2. Finally, we describe the R functions for string manipulation needed to handle the input and output files.