Abstract
SummaryThe biological regime of Pseudomonas putida (and any other bacterium) under given environmental conditions results from the hierarchical expression of sets of genes that become turned on and off in response to one or more physicochemical signals. In some cases, such signals are clearly defined, but in many others, cells are exposed to a whole variety of ill‐defined inputs that occur simultaneously. Transcriptomic analyses of bacteria passed from a reference condition to a complex niche can thus expose both the type of signals that they experience during the transition and the functions involved in adaptation to the new scenario. In this article, we describe a complete protocol for generation of transcriptomes aimed at monitoring the physiological shift of P. putida between two divergent settings using as a simple case study the change between homogeneous, planktonic lifestyle in a liquid medium and growth on the surface of an agar plate. To this end, RNA was collected from P. putida KT2440 cells at various times after growth in either condition, and the genome‐wide transcriptional outputs were analysed. While the role of individual genes needs to be verified on a case‐by‐case basis, a gross inspection of the resulting profiles suggested cells that are cultured on solid media consistently had a higher translational and metabolic activity, stopped production of flagella and were conspicuously exposed to a strong oxidative stress. The herein described methodology is generally applicable to other circumstances for diagnosing lifestyle determinants of interest.
Highlights
Before the onset of genomic technologies, the way to inspect complex environmental adaptations of microorganisms largely relied – whenever possible – on generation of mutant libraries followed by phenotypic characterization
While the platforms and technologies available to this end have evolved over the years, for example, from DNA arrays to deep sequencing of transcripts (RNA-Seq), the results deliver a list of genes that go up or down depending on the specific scenarios and their differences (Wang et al, 2009)
There are multiple ways to group data using DAVID software, we propose a functional annotation chart setting with only four parameters: three types of Gene Ontology (GO) terms (GOTERM_BP_DIRECT, GOTE RM_CC_DIRECT and GOTERM_MF_DIRECT) and one pathway (KEGG_PATHWAY; Huang da et al, 2009a,b)
Summary
Before the onset of genomic technologies, the way to inspect complex environmental adaptations of microorganisms largely relied – whenever possible – on generation of mutant libraries followed by phenotypic characterization. Pseudomonas putida has not been alien to such technical and conceptual developments and a suite of transcriptomes of this bacterium have been published in recent years with different methods for inspecting the responses of this microorganism to different physicochemical settings (Yuste et al, 2006; Kim et al, 2013, 2016; La Rosa et al, 2015; Bojanovic et al, 2017; Molina-Santiago et al, 2017) Such experiments were run by different laboratories with diverse RNA extraction and preparation methods, and with different data analysis and representation tools, and make comparisons challenging.
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