Intrinsic factors ofPeltigeralichens influence the structure of the associated soil bacterial microbiota

Abstract

Definition of lichens has evolved from bi(tri)partite associations to multi-species symbioses, where bacteria would play essential roles. Besides, although soil bacterial communities are known to be affected by edaphic factors, when lichens grow upon them these could become less preponderant. We hypothesized that the structure of both the lichen microbiota and the microbiota in the soil underneath lichens is shaped by lichen intrinsic and extrinsic factors. In this work, intrinsic factors corresponded to mycobiont and cyanobiont identities of Peltigera lichens, metabolite diversity and phenoloxidase activity and extrinsic factors involved the site of the forest where lichens grow. Likewise, the genetic and metabolic structure of the lichen and soil bacterial communities were analyzed by fingerprinting. Among the results, metabolite diversity was inversely related to the genetic structure of bacterial communities of lichens and soils, highlighting the far-reaching effect of these substances; while phenoloxidase activity was inversely related to the metabolic structure only of the lichen bacterial microbiota, presuming a more limited effect of the products of these enzymes. Soil bacterial microbiota was different depending on the site and, strikingly, according to the cyanobiont present in the lichen over them, which could indicate an influence of the photobiont metabolism on the availability of soil nutrients.

Carbon Consumption Patterns of Microbial Communities Associated with Peltigera Lichens from a Chilean Temperate Forest

“…Previously, 50 lichen samples from two forested sites in the Coyhaique National Reserve in southern Chile, were identified by phylogenetically related sequences of cyanobacterial small sub-unit (SSU) rDNA and fungal large sub-unit (LSU) rDNA with sequences previously reported for Nostoc and Peltigera . This way, we defined five cyanobiont (C01, C03, C10, C12, and C14) and six mycobiont (M1, M2, M4, M5, M6, and M8) haplotypes [ 42 ]. In our previous phylogenetic analysis [ 24 ], most of our mycobionts formed defined and well-supported monophyletic groups with some of the Peltigera species downloaded from the database: M1 was closely-related to P. ponojensis , M2 to P. extenuata , M4 to P. rufescens , and M6 to P. frigida .…”

“…To carry out the metabolic profiling, composite samples from the lichen thallus and the associated substrate were prepared, grouping them by site (S1 and S2), mycobiont type (M), and cyanobiont type (C). This arrangement produced 11 samples from lichen thalli and 11 samples from the underlying substrates [ 42 ]. The kinetics of the consumption of carbon-sources of all samples were adjusted to the modified Gompertz equation, determining that at 48 h all the communities were in the exponential phase of color development ( Appendix A ).…”

“…Several factors have been identified as descriptors of the lichen bacterial microbiome structure, including both intrinsic and extrinsic factors [ 28 , 39 , 40 , 41 ]. In a previous study, we discovered that the metabolic structure of the bacterial microbiota in Peltigera thallus was influenced by mycobiont identity and by the production of phenoloxidase activity, while the metabolic structure of the bacterial microbiota present in the substrates where lichens grow was shaped by cyanobiont identity and the sampling site [ 42 ]. Here, we hypothesize that the lichen influences the carbon-source consumption pattern of the community associated with its thallus, but has less impact on the microbial community of its underlying substrate.…”

The microbiomes of seven lichen genera reveal host specificity, a reduced core community and potential as source of antimicrobials

“…These differences are thought to be driven by biotic and abiotic factors, of which the photobiont and large-scale geographical distance apparently determine the composition in different lichen types (29). It has also been suggested that a lichen's secondary metabolite production could drive microbiome structure (29,55,56). In this work, we used a differential abundance analysis approach (ALDEx2) to identify OTUs that varied in abundance among samples.…”

A Standardized Method for Estimating the Functional Diversity of Soil Bacterial Community by Biolog® EcoPlatesTM Assay—The Case Study of a Sustainable Olive Orchard

“…Comparing our results with those of other studies [10][11][12][13][14][15][16] using our protocol, we managed to obtain more stable growth curves for AWCD, particularly in the constant phase and relatively low values of SD (Figure 2A). Another important remark is that the inoculum could be relativized simply resuspending soil mass, in order to not to artificially homogenize differences that are intended to be detected among the different soil samples of the same experiment [17][18][19][20]. In order to avoid this possible artefact, in our case, the same dilution (leading to~10 4 CFUs mL −1 ) was chosen for all the samples analysed in the same experiment.…”