The Regulatory Network Controlling Ethanol-Induced Expression of Alcohol Dehydrogenase in the Endophyte <i>Azoarcus</i> sp. Strain BH72

Krause, Andréa; Julich, Henrike; Mankar, Manasee; Reinhold‐Hurek, Barbara

doi:10.1094/mpmi-01-17-0013-r

Cited by 8 publications

(6 citation statements)

References 42 publications

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“…Among such genes in A. olearius DQS4 T is a homolog of the BH72 exaA5 gene (azo3865), predicted to encode a pyrroloquinoline quinone-dependent alcohol dehydrogenase (DQS_RS19730) involved in methanol oxidation. Consistent with these findings, previous reports showed that mutation of ADH genes inhibited competitive colonization of rice roots by A. olearius BH72 (21,52). Similarly, Methylobacterium spp.…”

Section: Discussionsupporting

confidence: 85%

Diverse Bacterial Genes Modulate Plant Root Association by Beneficial Bacteria

Amaral

Tuleski

Pankievicz

et al. 2020

mBio

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The plant rhizosphere harbors a diverse population of microorganisms, including beneficial plant growth-promoting bacteria (PGPB), that colonize plant roots and enhance growth and productivity. In order to specifically define bacterial traits that contribute to this beneficial interaction, we used high-throughput transposon mutagenesis sequencing (TnSeq) in two model root-bacterium systems associated with Setaria viridis: Azoarcus olearius DQS4T and Herbaspirillum seropedicae SmR1. This approach identified ∼100 significant genes for each bacterium that appeared to confer a competitive advantage for root colonization. Most of the genes identified specifically in A. olearius encoded metabolism functions, whereas genes identified in H. seropedicae were motility related, suggesting that each strain requires unique functions for competitive root colonization. Genes were experimentally validated by site-directed mutagenesis, followed by inoculation of the mutated bacteria onto S. viridis roots individually, as well as in competition with the wild-type strain. The results identify key bacterial functions involved in iron uptake, polyhydroxybutyrate metabolism, and regulation of aromatic metabolism as important for root colonization. The hope is that by improving our understanding of the molecular mechanisms used by PGPB to colonize plants, we can increase the adoption of these bacteria in agriculture to improve the sustainability of modern cropping systems.IMPORTANCE There is growing interest in the use of associative, plant growth-promoting bacteria (PGPB) as biofertilizers to serve as a sustainable alternative for agriculture application. While a variety of mechanisms have been proposed to explain bacterial plant growth promotion, the molecular details of this process remain unclear. The current research supports the idea that PGPB use in agriculture will be promoted by gaining more knowledge as to how these bacteria colonize plants, promote growth, and do so consistently. Specifically, the research seeks to identify those bacterial genes involved in the ability of two, PGPB strains, Azoarcus olearius and Herbaspirillum seropedicae, to colonize the roots of the C4 model grass Setaria viridis. Applying a transposon mutagenesis (TnSeq) approach, we assigned phenotypes and function to genes that affect bacterial competitiveness during root colonization. The results suggest that each bacterial strain requires unique functions for root colonization but also suggests that a few, critical functions are needed by both bacteria, pointing to some common mechanisms. The hope is that such information can be exploited to improve the use and performance of PGPB in agriculture.

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Section: Discussionsupporting

confidence: 85%

Diverse Bacterial Genes Modulate Plant Root Association by Beneficial Bacteria

Amaral

Tuleski

Pankievicz

et al. 2020

mBio

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“…Few TCS have been reported to regulate ethanol metabolism to date, with only ExaS-ExaR and ElmS-GacA found to be indispensable for growth in ethanol of Azoarcus sp. strain BH72, an endophytic bacteria with nitrogen-fixing activity that colonizes rice roots under waterlogged conditions which favor the production of ethanol [ 26 ]. However, only one alcohol dehydrogenase (ExaA2) was regulated by ExaS-ExaR.…”

Section: Discussionmentioning

confidence: 99%

“…Our observations suggest that the network for A. baumannii regulation of ethanol metabolism differs from that of Azozrcus sp. strain BH72 [ 26 ]. Interestingly, a complex TCS regulatory network for aerobic ethanol oxidation has been found and studied in Pseudomonas aeruginosa [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

Role of EmaSR in Ethanol Metabolism by Acinetobacter baumannii

Shu

Huang

Tsai

et al. 2022

IJMS

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Acinetobacter baumannii is a well-known nosocomial pathogen that can survive in different environments through the use of intricate networks to regulate gene expression. Two-component systems (TCS) form an important part of such regulatory networks, and in this study, we describe the identification and characterization of a novel EmaSR TCS in A. baumannii. We constructed a Tn5-tagged mutagenesis library, from which an emaS sensor kinase gene and emaR response regulator gene were identified. We found that emaS/emaR single-mutants and double-mutants were unable to replicate in M9 medium with 1% ethanol as the single carbon source. Motility and biofilm formation were negatively affected in double-mutants, and transcriptomic analysis showed that mutation of emaSR dysregulated genes required for carbon metabolism. In addition, emaS/emaR single-mutants and double-mutants were unable to survive in acetic acid- and sodium acetate-containing medium, indicating that the EmaSR TCS is also important for acetate metabolism. Furthermore, virulence against Galleria mellonella was diminished in emaS/emaR single- and double-mutants. Taken together, these results show that this novel EmaSR TCS is involved in the regulation of A. baumannii ethanol metabolism and acetate metabolism, with important implications on motility, biofilm formation, and virulence if mutated. Further research on the underlying mechanisms is warranted.

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“…Azoarcus olearius deeply invades rice roots inter‐ and intracellularly, yet rice roots show strong autofluorescence of plant cell walls (Hurek et al ., 1994b; Reinhold‐Hurek & Hurek, 1998; Miché et al ., 2006). In association with roots, several plant‐infection‐related bacterial genes show various degrees of expression, as visualized by transcriptional fusions with reporter genes encoding fluorescent proteins (Hauberg‐Lotte et al ., 2012; Krause et al ., 2017; Sarkar et al ., 2017). However, the fluorescence quantification in vivo was impeded by autofluorescence.…”

Section: Introductionmentioning

confidence: 99%

Deep‐learning‐based removal of autofluorescence and fluorescence quantification in plant‐colonizing bacteria in vivo

2022

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Summary Fluorescence microscopy is common in bacteria–plant interaction studies. However, strong autofluorescence from plant tissues impedes in vivo studies on endophytes tagged with fluorescent proteins. To solve this problem, we developed a deep‐learning‐based approach to eliminate plant autofluorescence from fluorescence microscopy images, tested for the model endophyte Azoarcus olearius BH72 colonizing Oryza sativa roots. Micrographs from three channels (tdTomato for gene expression, green fluorescent protein (GFP) and AutoFluorescence (AF)) were processed by a neural network based approach, generating images that simulate the background autofluorescence in the tdTomato channel. After subtracting the model‐generated signals from each pixel in the genuine channel, the autofluorescence in the tdTomato channel was greatly reduced or even removed. The deep‐learning‐based approach can be applied for fluorescence detection and quantification, exemplified by a weakly expressed, a cell‐density modulated and a nitrogen‐fixation gene in A. olearius. A transcriptional nifH::tdTomato fusion demonstrated stronger induction of nif genes inside roots than outside, suggesting extension of the rhizosphere effect for diazotrophs into the endorhizosphere. The pre‐trained convolutional neural network model is easily applied to process other images of the same plant tissues with the same settings. This study showed the high potential of deep‐learning‐based approaches in image processing. With proper training data and strategies, autofluorescence in other tissues or materials can be removed for broad applications.

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The Regulatory Network Controlling Ethanol-Induced Expression of Alcohol Dehydrogenase in the Endophyte Azoarcus sp. Strain BH72

Cited by 8 publications

References 42 publications

Diverse Bacterial Genes Modulate Plant Root Association by Beneficial Bacteria

Diverse Bacterial Genes Modulate Plant Root Association by Beneficial Bacteria

Role of EmaSR in Ethanol Metabolism by Acinetobacter baumannii

Deep‐learning‐based removal of autofluorescence and fluorescence quantification in plant‐colonizing bacteria in vivo

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