Microbial high throughput phenomics: The potential of an irreplaceable omics

Abstract

The phenotype-genotype landscape is a projection coming from detailed phenotypic and genotypic data under environmental pressure. Although phenome of microbes or microbial consortia mirrors the functional expression of a genome or set of genomes, metabolic traits rely on the phenotype. Phenomics has the potential to revolution functional genomics. In this review, we discuss why and how phenomics was developed. We described how phenomics may extend our understanding of the assembly of microbial consortia and their functionality, and then we outlined the novel applications within the study of phenomes using Omnilog platform together with a revision of its current application to study lactic acid bacteria (LAB) metabolic traits during food processing. LAB were proposed as a suitable model system to analyze and discuss the implementation and exploitation of this emerging omics approach. We introduced the 'phenotype switching', as a new phenotype microarray approach to get insights in bacterial physiology. An overview of methodologies and tools to manage and analyze the generated data was provided. Finally, pro and cons of pipelines developed so far, including the most innovative ones were critically analyzed. We propose an R pipeline, recently deposited, which allows to automatically analyze Omnilog data integrating the latest approaches and implementing the new concepts described here.

Keywords: Lactic acid bacteria; Microbial metabolism; Omnilog data analysis; Phenomics; Phenotype microarray.

Graphical abstract

Fig. 1

A) Omnilog reads over time for Lactobacillus plantarum in Phenotype Microarray (PM) plates PM1 for d-Mannitol. The decreasing metabolic signal pattern appears after 12 h. B) Metabolic curve for d-Gluconic Acid (PM1) showing two growth phases.

Fig. 2

Schematic representation of PM data analysis workflow using Micro4Food PM pipeline complemented with signal decomposition and Bayesian effect estimation over time.

Fig. 3

Principal component analysis (PCA) of PM1 and PM2 data from two Lactobacillus plantarum strains cultured in MRS media and in a plant-based model media (unpublished data) (A) and from two Lactobacillus plantarum strains cultured in MRS and in two model media (B). PCA was annotated by culture media. Data input was the Area Under the Curve (AUC) computed with Micro4Food PM pipeline in switching mode. PM inoculum was prepared using pelleted cells (A) or colonies grown on agar media (B).

Fig. 4

Custom chemical assay plate. One Lactobacillus plantarum strain was inoculated into PM 9–20 fluid. Wells contained gallic acid and vanillin at a final concentration of 1 mM. Control wells contained no inhibitory substances. Assays were carried out in triplicate. Compared to control, kinetic plot shows a metabolism inhibition due to the presence of these phenolic compounds.