Simulated global warming affects endophytic bacterial and fungal communities of Antarctic pearlwort leaves and some bacterial isolates support plant growth at low temperatures

Abstract

Antarctica is one of the most stressful environments for plant life and the Antarctic pearlwort (Colobanthus quitensis) is adapted to the hostile conditions. Plant-associated microorganisms can contribute to plant survival in cold environments, but scarce information is available on the taxonomic structure and functional roles of C. quitensis-associated microbial communities. This study aimed at evaluating the possible impacts of climate warming on the taxonomic structure of C. quitensis endophytes and at investigating the contribution of culturable bacterial endophytes to plant growth at low temperatures. The culture-independent analysis revealed changes in the taxonomic structure of bacterial and fungal communities according to plant growth conditions, such as the collection site and the presence of open-top chambers (OTCs), which can simulate global warming. Plants grown inside OTCs showed lower microbial richness and higher relative abundances of biomarker bacterial genera (Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium, Aeromicrobium, Aureimonas, Hymenobacter, Novosphingobium, Pedobacter, Pseudomonas and Sphingomonas) and fungal genera (Alternaria, Cistella, and Vishniacozyma) compared to plants collected from open areas (OA), as a possible response to global warming simulated by OTCs. Culturable psychrotolerant bacteria of C. quitensis were able to endophytically colonize tomato seedlings and promote shoot growth at low temperatures, suggesting their potential contribution to plant tolerance to cold conditions.

Endophytic bacterial communities of alpine Rosaceae plants are affected by the plant tissue, collection site and host plant and culturable psychrotolerant isolates contribute to plant freezing stress tolerance

“…Culture-independent analysis of DNA extraction, amplification and sequencing was carried out as previously described with some modifications (Perazzolli et al ., 2022). Briefly, genomic DNA was extracted from surface-disinfected tissues using the FastDNA Spin Kit for Soil (MP Biomedical, Santa Ana, CA, USA) with a slight modification.…”

“…16S rRNA gene amplicon sequence processing was carried out as previously described (Perazzolli et al ., 2022). Briefly, Illumina reads were filtered with Bowtie2 v2.4.2 (Langmead & Salzberg, 2012), sequence quality was checked with FastQC v0.11.9 and primers were cut using Cutadapt v3.4 (Martin, 2011).…”

“…Random forest models were performed to identify taxa with strong associations with the four factors (i.e. tissue, alpine Rosaceae plant, collection site and exposition) using a machine learning algorithm, as previously described (Perazzolli et al ., 2022). Rarefied count data were used as predictors, and factors were used as response data.…”

“…Representative bacterial isolates were selected for each sample based on morphological visual observation of bacterial colonies (e.g. size, colour, opacity, texture, form, elevation and margin), as previously described (Perazzolli et al ., 2022). The purified colonies were suspended in 40% (v/v) glycerol and kept at −80°C until use.…”

“…To avoid redundancy, bacterial isolates were taxonomically annotated based on sequencing of the V6–V8 region of the 16S rRNA gene. PCR amplification and DNA sequencing were performed with the universal primers 27 forward (5’-AGAGTTTGATCCTGGCTCAG-3’ and 1492 reverse (5’-GGTTACCTTGTTACGACTT-3’) using the conditions previously described (Perazzolli et al ., 2022). Briefly, the PCR product was purified using a NucleoSpin Gel and PCR Clean-up purification kit (Macherey-Nagel) and subjected to Sanger sequencing at Eurofins Genomics GmbH (Ebersberg, Germany).…”