Francesca Marzorati

Pseudomonas simiae WCS417 is a plant growth–promoting rhizobacterium that improves plant health and development. In this study, we investigate the early leaf responses of Arabidopsis thaliana to WCS417 exposure and the possible involvement of formate dehydrogenase (FDH) in such responses. In vitro–grown A. thaliana seedlings expressing an FDH::GUS reporter show a significant increase in FDH promoter activity in their roots and shoots after 7 days of indirect exposure (without contact) to WCS417. After root exposure to WCS417, the leaves of FDH::GUS plants grown in the soil also show an increased FDH promoter activity in hydathodes. To elucidate early foliar responses to WCS417 as well as FDH involvement, the roots of A. thaliana wild-type Col and atfdh1-5 knock-out mutant plants grown in soil were exposed to WCS417, and proteins from rosette leaves were subjected to proteomic analysis. The results reveal that chloroplasts, in particular several components of the photosystems PSI and PSII, as well as members of the glutathione S-transferase family, are among the early targets of the metabolic changes induced by WCS417. Taken together, the alterations in the foliar proteome, as observed in the atfdh1- 5 mutant, especially after exposure to WCS417 and involving stress-responsive genes, suggest that FDH is a node in the early events triggered by the interactions between A. thaliana and the rhizobacterium WCS417. [ ] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

What can you do when you feel hungry? You could go to the kitchen and prepare a sandwich, or you could buy yourself a snack. But what if you are fixed to the ground? Plants are champions at reaching food that is far away from them while they are standing still. Below a plant, roots branch out into the soil in many directions, looking for the nutrients plants need for survival and growth. Iron is a very important nutrient for plants because it is essential for growth and development, and it also helps plants to face stresses in the environment. Even if iron availability in soil is very low, plants have developed two strategies for efficiently taking up iron and storing it. In this article, we will explore the importance of iron in plants’ lives, explaining how plants take up it and how balanced iron levels are important for plants’ (and our) survival.

Iron (Fe) is an essential plant micronutrient since many cellular processes including photosynthesis, respiration, and the scavenging of reactive oxygen species depend on adequate Fe levels; however, non-complexed Fe ions can be dangerous for cells, as they can act as pro-oxidants. Hence, plants possess a complex homeostatic control system for safely taking up Fe from the soil and transporting it to its various cellular destinations, and for its subcellular compartmentalization. At the end of the plant’s life cycle, maturing seeds are loaded with the required amount of Fe needed for germination and early seedling establishment. In this review, we discuss recent findings on how the microbiota in the rhizosphere influence and interact with the strategies adopted by plants to take up iron from the soil. We also focus on the process of seed-loading with Fe, and for crop species we also consider its associated metabolism in wild relatives. These two aspects of plant Fe nutrition may provide promising avenues for a better comprehension of the long pathway of Fe from soil to seeds.

Transcriptomics studies have been facilitated by the development of microarray and RNA-Seq technologies, with thousands of expression datasets available for many species. However, the quality of data can be highly variable, making the combined analysis of different datasets difficult and unreliable. Most of the microarray data for Medicago truncatula, the barrel medic, have been stored and made publicly accessible on the web database Medicago truncatula Gene Expression atlas (MtGEA). The aim of this work is to ameliorate the quality of the MtGEA database through a general method based on logical and statistical relationships among parameters and conditions. The initial 716 columns available in the dataset were reduced to 607 by evaluating the quality of data through the sum of the expression levels over the entire transcriptome probes and Pearson correlation among hybridizations. The reduced dataset shows great improvements in the consistency of the data, with a reduction in both false positives and false negatives resulting from Pearson correlation and GO enrichment analysis among genes. The approach we used is of general validity and our intent is to extend the analysis to other plant microarray databases.