What is Culturomics?
Microbiology research relies heavily on working with pure, isolated bacterial cultures. Selecting and isolating individual bacterial colonies is a time and labor-intensive task, and becomes even more challenging in applications like microbiome studies where there may be over a thousand bacterial species present in a sample at varying abundance.
“Culturomics” is a relatively new phrase that refers to high throughput techniques for comprehensively culturing and identifying the bacterial species present in a sample of interest. The “-omics” portion of culturomics comes from genomics – specifically metagenomics, which refers to genomic sequencing of all of the genomes contained in an environmental sample, such as a fecal sample to study the human gut microbiome.
A New High Throughput Machine Learning Method for Culturomics
Although metagenomics has been transformative for microbiome studies, sequencing approaches alone will often over-represent dominant species in the sample. Mass spectrometry has been used in culturomics thus far, but is relatively low throughput and still requires manual processing.
A new method published in Nature Biotechnology on Monday from Huang et. al. details a partially automated machine learning platform that comprehensively selects and isolates individual bacterial species from a complex microbial community, generates morphological and genomic data for each isolate, and results in a physical isolate biobank with a corresponding searchable database that integrates genotype and phenotype information.
CAMII Unravels Culturomics’ Complexity
If it sounds complex, it’s because it is: the Culturomics by Automated Microbiome Imaging and Isolation (CAMII) platform involves an anaerobic imaging chamber, a robot, machine learning algorithms, and an updated, low-cost genomic sequencing pipeline. The authors’ new imaging platform and corresponding machine learning-based colony identification algorithms are able to capture bacterial colony features including size, shape, color, depth, and texture to distinguish different species.
When integrated with whole genome sequencing or 16s rRNA sequencing, CAMII can provide insight into bacterial evolution, selection, and horizontal gene transfer within an individual microbiome. The authors applied CAMII to fecal samples from 20 different people, identifying almost 27,000 isolates representing over 80% of all abundant species and creating personalized microbiome biobanks. The applications of powerful platforms like CAMII will help move complex microbiome studies forward, delivering new insights into the variety of interactions between humans and the microorganisms we live with.
Outsourcing Bioinformatics Analysis: How Bridge Informatics Can Help
Metagenomic studies like those frequently used in microbiome analysis generate enormous amounts of data. As experts across data types from cutting-edge sequencing platforms, we can help you tackle the challenging computational tasks of storing, analyzing and interpreting genomic and transcriptomic data. Bridge Informatics’ bioinformaticians are trained bench biologists, so they understand the biological questions driving your computational analysis. From pipeline development and software engineering to deploying existing bioinformatics tools, Bridge Informatics can help you on every step of your research journey. Click here to schedule a free introductory call with a member of our team.
Jane Cook, Biochemist & Content Writer, Bridge Informatics
Jane Cook, leading Content Writer for Bridge Informatics, has written over 100 articles on the latest topics and trends for the bioinformatics community. Jane’s broad and deep interdisciplinary molecular biology experience spans developing biochemistry assays to genomics. Prior to joining Bridge, Jane held research assistant roles in biochemistry research labs across a variety of therapeutic areas. While obtaining her B.A. in Biochemistry from Trinity College in Dublin, Ireland, Jane also studied journalism at New York University’s Arthur L. Carter Journalism Institute. As a native Texan, she embraces any challenge that comes her way. Jane hails from Dallas but returns to Ireland any and every chance she gets. If you’re interested in reaching out, please email jennifer.martinez@old.bridgeinformatics.com or dan.ryder@old.bridgeinformatics.com.
