Simultaneous analysis of seven 16S rRNA hypervariable gene regions increases efficiency in marine bacterial diversity detection.

Environmental DNA sequencing is the gold standard to reveal microbial community structures. In most applications, a one-fragment PCR approach is applied to amplify a taxonomic marker gene, usually a hypervariable region of the 16S rRNA gene. We used a new reverse complement (RC)-PCR-based assay that amplifies seven out of the nine hypervariable regions of the 16S rRNA gene, to interrogate bacterial communities in sediment samples collected from different coastal marine sites with an impact gradient. In parallel, we employed a traditional one-fragment analysis of the hypervariable V3-V4 region to investigate whether the RC-PCR reveals more of the 'unseen' diversity obtained by the one-fragment approach. As a benchmark for the full deck of diversity, we subjected the samples to PCR-free metagenomic sequencing. None of the two PCR-based approaches recorded the full taxonomic repertoire obtained from the metagenomics datasets. However, the RC-PCR approach detected 2.8 times more bacterial genera compared to the near-saturation sequenced V3-V4 samples. RC-PCR is an ideal compromise between the standard one-fragment approach and metagenomics sequencing and may guide future environmental sequencing studies, in which bacterial diversity is a central subject.

Above- and below-ground microbiome in the annual developmental cycle of two olive tree varieties.

The olive tree is a hallmark crop in the Mediterranean region. Its cultivation is characterized by an enormous variability in existing genotypes and geographical areas. As regards the associated microbial communities of the olive tree, despite progress, we still lack comprehensive knowledge in the description of these key determinants of plant health and productivity. Here, we determined the prokaryotic, fungal and arbuscular mycorrhizal fungal (AMF) microbiome in below- (rhizospheric soil, roots) and above-ground (phyllosphere and carposphere) plant compartments of two olive varieties 'Koroneiki' and 'Chondrolia Chalkidikis' grown in Southern and Northern Greece respectively, in five developmental stages along a full fruit-bearing season. Distinct microbial communities were supported in above- and below-ground plant parts; while the former tended to be similar between the two varieties/locations, the latter were location specific. In both varieties/locations, a seasonally stable root microbiome was observed over time; in contrast the plant microbiome in the other compartments were prone to changes over time, which may be related to seasonal environmental change and/or to plant developmental stage. We noted that olive roots exhibited an AMF-specific filtering effect (not observed for bacteria and general fungi) onto the rhizosphere AMF communities of the two olive varieties/locations/, leading to the assemblage of homogenous intraradical AMF communities. Finally, shared microbiome members between the two olive varieties/locations include bacterial and fungal taxa with putative functional attributes that may contribute to olive tree tolerance to abiotic and biotic stress.

Comparing quantile regression spline analyses and supervised machine learning for environmental quality assessment at coastal marine aquaculture installations.

Organic enrichment associated with marine finfish aquaculture is a local stressor of marine coastal ecosystems. To maintain ecosystem services, the implementation of biomonitoring programs focusing on benthic diversity is required. Traditionally, impact-indices are determined by extracting and identifying benthic macroinvertebrates from samples. However, this is a time-consuming and expensive method with low upscaling potential. A more rapid, inexpensive, and robust method to infer the environmental quality of marine environments is eDNA metabarcoding of bacterial communities. To infer the environmental quality of coastal habitats from metabarcoding data, two taxonomy-free approaches have been successfully applied for different geographical regions and monitoring goals, namely quantile regression splines (QRS) and supervised machine learning (SML). However, their comparative performance remains untested for monitoring the impact of organic enrichment introduced by aquaculture on marine coastal environments. We compared the performance of QRS and SML using bacterial metabarcoding data to infer the environmental quality of 230 aquaculture samples collected from seven farms in Norway and seven farms in Scotland along an organic enrichment gradient. As a measure of environmental quality, we used the Infaunal Quality Index (IQI) calculated from benthic macrofauna data (reference index). The QRS analysis plotted the abundance of amplicon sequence variants (ASVs) as a function to the IQI from which the ASVs with a defined abundance peak were assigned to eco-groups and a molecular IQI was subsequently calculated. In contrast, the SML approach built a random forest model to directly predict the macrofauna-based IQI. Our results show that both QRS and SML perform well in inferring the environmental quality with 89% and 90% accuracy, respectively. For both geographic regions, there was high correspondence between the reference IQI and both the inferred molecular IQIs (p < 0.001), with the SML model showing a higher coefficient of determination compared to QRS. Among the 20 most important ASVs identified by the SML approach, 15 were congruent with the good quality spline ASV indicators identified via QRS for both Norwegian and Scottish salmon farms. More research on the response of the ASVs to organic enrichment and the co-influence of other environmental parameters is necessary to eventually select the most powerful stressor-specific indicators. Even though both approaches are promising to infer environmental quality based on metabarcoding data, SML showed to be more powerful in handling the natural variability. For the improvement of the SML model, addition of new samples is still required, as background noise introduced by high spatio-temporal variability can be reduced. Overall, we recommend the development of a powerful SML approach that will be onwards applied for monitoring the impact of aquaculture on marine ecosystems based on eDNA metabarcoding data.

Environmental DNA-based profiling of benthic bacterial and eukaryote communities along a crude oil spill gradient in a coral reef in the Persian Gulf.

Coral reef ecosystems in the Persian Gulf are frequently exposed to crude oil spills. We investigated benthic bacterial and eukaryote community structures at such coral reef sites subjected to different degrees of polycyclic aromatic hydrocarbon (PAH) pollution using environmental DNA (eDNA) metabarcoding. Both bacterial and eukaryote communities responded with pronounced shifts to crude oil pollution and distinguished control sites, moderately and heavily impacted sites with significant confidentiality. The observed community patterns were predominantly driven by Alphaproteobacteria and metazoans. Among these, we identified individual genera that were previously linked to oil spill stress, but also taxa, for which a link to hydrocarbon still remains to be established. Considering the lack of an early-warning system for the environmental status of coral reef ecosystems exposed to frequent crude-oil spills, our results encourage further research towards the development of an eDNA-based biomonitoring tool that exploits benthic bacterial and eukaryote communities as bioindicators.

Comparative Transcriptomics and Metabolomics Reveal an Intricate Priming Mechanism Involved in PGPR-Mediated Salt Tolerance in Tomato.

Plant-associated beneficial strains inhabiting plants grown under harsh ecosystems can help them cope with abiotic stress factors by positively influencing plant physiology, development, and environmental adaptation. Previously, we isolated a potential plant growth promoting strain (AXSa06) identified as Pseudomonas oryzihabitans, possessing 1-aminocyclopropane-1-carboxylate deaminase activity, producing indole-3-acetic acid and siderophores, as well as solubilizing inorganic phosphorus. In this study, we aimed to further evaluate the effects of AXSa06 seed inoculation on the growth of tomato seedlings under excess salt (200 mM NaCl) by deciphering their transcriptomic and metabolomic profiles. Differences in transcript levels and metabolites following AXSa06 inoculation seem likely to have contributed to the observed difference in salt adaptation of inoculated plants. In particular, inoculations exerted a positive effect on plant growth and photosynthetic parameters, imposing plants to a primed state, at which they were able to respond more robustly to salt stress probably by efficiently activating antioxidant metabolism, by dampening stress signals, by detoxifying Na+, as well as by effectively assimilating carbon and nitrogen. The primed state of AXSa06-inoculated plants is supported by the increased leaf lipid peroxidation, ascorbate content, as well as the enhanced activities of antioxidant enzymes, prior to stress treatment. The identified signatory molecules of AXSa06-mediated salt tolerance included the amino acids aspartate, threonine, serine, and glutamate, as well as key genes related to ethylene or abscisic acid homeostasis and perception, and ion antiporters. Our findings represent a promising sustainable solution to improve agricultural production under the forthcoming climate change conditions.

Plant biodiversity assessment through pollen DNA metabarcoding in Natura 2000 habitats (Italian Alps).

Monitoring biodiversity is of increasing importance in natural ecosystems. Metabarcoding can be used as a powerful molecular tool to complement traditional biodiversity monitoring, as total environmental DNA can be analyzed from complex samples containing DNA of different origin. The aim of this research was to demonstrate the potential of pollen DNA metabarcoding using the chloroplast trnL partial gene sequencing to characterize plant biodiversity. Collecting airborne biological particles with gravimetric Tauber traps in four Natura 2000 habitats within the Natural Park of Paneveggio Pale di San Martino (Italian Alps), at three-time intervals in 1 year, metabarcoding identified 68 taxa belonging to 32 local plant families. Metabarcoding could identify with finer taxonomic resolution almost all non-rare families found by conventional light microscopy concurrently applied. However, compared to microscopy quantitative results, Poaceae, Betulaceae, and Oleaceae were found to contribute to a lesser extent to the plant biodiversity and Pinaceae were more represented. Temporal changes detected by metabarcoding matched the features of each pollen season, as defined by aerobiological studies running in parallel, and spatial heterogeneity was revealed between sites. Our results showcase that pollen metabarcoding is a promising approach in detecting plant species composition which could provide support to continuous monitoring required in Natura 2000 habitats for biodiversity conservation.

Bacterial Communities in the Rhizosphere and Phyllosphere of Halophytes and Drought-Tolerant Plants in Mediterranean Ecosystems.

The aim of the study was to investigate the bacterial community diversity and structure by means of 16S rRNA gene high-throughput amplicon sequencing, in the rhizosphere and phyllosphere of halophytes and drought-tolerant plants in Mediterranean ecosystems with different soil properties. The locations of the sampled plants included alkaline, saline-sodic soils, acidic soils, and the volcanic soils of Santorini Island, differing in soil fertility. Our results showed high bacterial richness overall with Proteobacteria and Actinobacteria dominating in terms of OTUs number and indicated that variable bacterial communities differed depending on the plant's compartment (rhizosphere and phyllosphere), the soil properties and location of sampling. Furthermore, a shared pool of generalist bacterial taxa was detected independently of sampling location, plant species, or plant compartment. We conclude that the rhizosphere and phyllosphere of native plants in stressed Mediterranean ecosystems consist of common bacterial assemblages contributing to the survival of the plant, while at the same time the discrete soil properties and environmental pressures of each habitat drive the development of a complementary bacterial community with a distinct structure for each plant and location. We suggest that this trade-off between generalist and specialist bacterial community is tailored to benefit the symbiosis with the plant.

Plant growth promoting rhizobacteria isolated from halophytes and drought-tolerant plants: genomic characterisation and exploration of phyto-beneficial traits.

Plant growth promoting rhizobacteria (PGPR) are able to provide cross-protection against multiple stress factors and facilitate growth of their plant symbionts in many ways. The aim of this study was to isolate and characterize rhizobacterial strains under natural conditions, associated with naturally occurring representatives of wild plant species and a local tomato cultivar, growing in differently stressed Mediterranean ecosystems. A total of 85 morphologically different rhizospheric strains were isolated; twenty-five exhibited multiple in vitro PGP-associated traits, including phosphate solubilization, indole-3-acetic acid production, and 1-aminocyclopropane-1-carboxylate deaminase activity. Whole genome analysis was applied to eight selected strains for their PGP potential and assigned seven strains to Gammaproteobacteria, and one to Bacteroidetes. The genomes harboured numerous genes involved in plant growth promotion and stress regulation. They also support the notion that the presence of gene clusters with potential PGP functions is affirmative but not necessary for a strain to promote plant growth under abiotic stress conditions. The selected strains were further tested for their ability to stimulate growth under stress. This initial screening led to the identification of some strains as potential PGPR for increasing crop production in a sustainable manner.