Results for “PM (phenotype microarray)”

PubMed2025

Phenotypic profiling of carbon utilization of Pectobacterium brasiliense (Pbr1692).

Pectobacterium brasiliense 1692 (Pbr1692) is a necrotrophic pathogen that infects many crops such as potatoes and ornamental plants and derives nutrients from degraded plant tissue. Previous studies have identified Pbr1692 genes required for ecological fitness and virulence, however there is a lack of information on nutrient utilization in Pbr1692. Carbon source utilization profiling in Pbr1692 could provide a platform to decipher its metabolic flexibility and adaptation. This study assessed the nutrient utilization of Pbr1692 in different carbon sources, using Biolog Phenotypic Microarray (PM). An array of carbon sources utilized by Pbr1692 were identified, 32 carbohydrates and 8 carboxylic acids were among the preferred carbon nutrients utilized by Pbr1692. The PM results also revealed that the citric acid cycle, amino acid metabolism, and pentose phosphate metabolic pathways might be used to produce energy for Pbr1692. In addition, growth of Pbr1692 cells in minimal medium supplemented with citric acid, glucose, and aspartic acid retained the typical rod shape, suggesting that nutrient variation did not influence Pbr1692 cell morphology adaptation. This study provides an understanding on the adaptation of Pbr1692 and lays a foundation for understanding carbon metabolism of Pbr1692.

Carbon↗

PubMed2025

PMkbase (version 1.0): an interactive web-based tool for tracking bacterial metabolic traits using phenotype microarrays made interoperable with sequence information and visualizing/processing PM data.

Bacteria showcase remarkable metabolic diversity and traits, even among strains of the same species. In recent years, a large number of bacterial genomes have been sequenced, leading to the elucidation and documentation of genomic differences and commonalities across and within species. Genome-scale metabolic reconstructions, which are often defined and curated using data from phenotype microarrays, elucidate the differences in metabolic traits resulting from genomic diversity. These microarrays measure cellular respiration on a variety of carbon, nitrogen, phosphorus, and sulfur sources and various stressors and inhibitors over a period of time to determine the metabolic activity of a given strain. Despite their popularity in measuring bacterial metabolic activity and traits, no public databases that allow researchers to warehouse, access, and analyze this information currently exist. Additionally, there are no publicly available tools that allow researchers to view the variance of these metabolic traits across bacterial strains. To address this need, we present Phenotype Microarray Knowledgebase (PMkbase [version 1.0], https://pmkbase.com/), an interactive database that acts as a repository of phenotype microarray (PM) data with integrated sequence information. Binarized activity calls, along with associated kinetic parameters, are made for all metabolic substrates and inhibitors. Users can upload their own data for analysis and visualization and to perform quality checks on their experiments. PMkbase will address an unmet need to track and view bacterial metabolic traits and provide researchers with valuable information to develop metabolic models, enrich pangenomic analyses, and design new experiments.IMPORTANCEBacterial species can be differentiated by their metabolic profiles or the type of nutrients they consume. Interestingly, strains within the same species also display differences in nutrient consumption. Phenotype microarrays are a high-throughput, widely used technology to measure which substrates can be metabolized by various microbial strains and the extent to which inhibitors can affect it. Despite their widespread use, public databases to parse and access this data type at scale do not exist. PMkbase, which contains 9,024 data points for nitrogen substrate utilization, 41,664 data points for carbon substrate utilization, 8,448 data points for phosphorus/sulfur substrate utilization, and 27,264 data points on various antibiotics across three species (Escherichia coli, Pseudomonas putida, and Staphylococcus aureus), has been developed to allow researchers to freely access PM data, along with enriching the data with sequence information.

Bacteria↗