Comparative Analysis of the Microbiota of Vaccinium myrtillus and Vaccinium uliginosum in the Central Italian Apennines

Comparative Analysis of the Microbiota of Vaccinium myrtillus and Vaccinium uliginosum in the Central Italian Apennines | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Comparative Analysis of the Microbiota of Vaccinium myrtillus and Vaccinium uliginosum in the Central Italian Apennines Francesca Vaccaro , Ginevra Cambi , Stefano Biricolti , Edgardo Giordani , View ORCID Profile Alessio Mengoni , View ORCID Profile Camilla Fagorzi doi: https://doi.org/10.1101/2025.05.26.655108 Francesca Vaccaro 1 Department of Biology, University of Florence , Florence, Italy Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ginevra Cambi 1 Department of Biology, University of Florence , Florence, Italy Find this author on Google Scholar Find this author on PubMed Search for this author on this site Stefano Biricolti 2 Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence , Florence, Italy Find this author on Google Scholar Find this author on PubMed Search for this author on this site Edgardo Giordani 2 Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence , Florence, Italy Find this author on Google Scholar Find this author on PubMed Search for this author on this site Alessio Mengoni 1 Department of Biology, University of Florence , Florence, Italy Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Alessio Mengoni Camilla Fagorzi 1 Department of Biology, University of Florence , Florence, Italy Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Camilla Fagorzi For correspondence: camilla.fagorzi{at}unifi.it Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Vaccinium is a genus of shrubs known for their antioxidant and anti-inflammatory compounds. While the commercially cultivated blueberry ( V. corymbosum ) originates from North America, European species like myrtillus (bilberry) and V. uliginosum (bog bilberry) remain uncultivated due to poor adaptability to conventional growing media. At present, bilberries, which are more valued for fresh consumption, are exclusively harvested from wild populations, particularly in subalpine and mountain environments, where unique soil and climate conditions prevail. This study explores the bacterial and fungal communities associated with V. myrtillus and V. uliginosum in wild populations of the Central Italian Apennines, using 16S rRNA and ITS amplicon sequencing. Microbiota from plant and soil were analyzed, revealing distinct microbial community compositions based on species and plant compartments. Bacterial diversity was highest in bulk soil, while fungal diversity dominated plant tissues. Co-occurrence network analysis showed greater connectivity in V. uliginosum microbiota, suggesting higher resilience. Functional predictions indicated roles in nitrogen cycling, cellulose degradation, and plant-microbe interactions. These findings offer insights into the native microbiota of wild Vaccinium species and could inform conservation and cultivation efforts. 1. Introduction Vaccinium spp . sect. Cyanococcus are perennial flowering plants of the Ericaceae family, known for their blue or purple berries. They encompass approximately ∼500 shrubs/small tree species globally 1 . Commercial blueberry cultivars are all native to North America and mostly derive from breeding programs of blueberry ( V. corymbosum L.) and cranberry ( V. macrocarpon Ait.) 2 . Blueberry fruits have high content of flavonoids, phenolic acids, polyphenols, anthocyanins, pro-anthocyanidins, and stilbenes, and show antioxidant and anti-inflammatory activities (see for instance 3 ). In the last years, numerous studies have investigated the role of blueberry fruit juice on human health and human gut microbiota 4 , 5 (REF). In the European flora Vaccinium species are represented by four species only, V. myrtillus, V. uliginosum, V. oxycoccus and V. vitis idaea 6 . The bilberry or forest blueberry V. myrtillus , and the lingonberry, V. vitis idaea , are the only two of any economic significance, but are mainly consumed locally, within traditional and family-based practices. Forest bilberry ( V. myrtillus , L.) is a small deciduous, broadleaf shrub with oval, light green leaves; the flowers are white with fused petals. In Italy, it is found in the Alps and the Apennines, particularly in subalpine and montane beech forests (from 500 to 2500 meters). The genetic diversity of the Tuscan mountain populations of bilberry and the biochemical traits of both V. myrtillus and V. uliginosum have been clearly shown 7 . Vaccinium species naturally grow in well-drained, sandy acidic (pH 4.0-5.5) soils that tend to be low in nutrients and with 2-7 % of organic matter 8 . Moreover, in contrast to cultivated blueberries, forest bilberry of the Tuscan mountains, notwithstanding the recent results achieved in the in vitro and in vivo propagation 9 shows a very low adaptability to natural soil and growing media specifically selected well suited for other Ericaceae species, including blueberry ( V. corymbosum ). Although tolerant of partial shade, these plants require sufficient sunlight to maximize fruit production, but thrive in cool, humid climates and can be damaged by late frosts, drought, or excessive heat. In Central Italy, populations of forest bilberry are consequently particularly threatened as a result of climate change. Moreover, in Central Italian Apennines V. myrtillus and V. uliginosum often co-occur and in some cases V. uliginosum is invading the spots of V. myrtillus , creating additional concern over the preservation of V. myrtillus populations 7 . Since the soils in which these plants grow are not typical, compared to the soils in which most crops are grown, the rhizosphere microbiota assumes somewhat unique features, especially in relation to the contribution to plant nutrition in low organic matter, acidic soils. Indeed, the bacterial communities in the rhizosphere of Vaccinium species are dominated by various groups, as Proteobacteria and Acidobacteria in North American cultivated Vaccinium species 10 or dominated by Actinobacteria (for the Asian species V. ashei 11 or by all these three bacterial groups 12 . These bacteria are likely involved in various possible host beneficial processes such as nitrogen cycling, including nonsymbiotic nitrogen fixation, phosphorus solubilization, and production of plant growth-promoting hormones. Phosphate-solubilizing bacteria should be particularly important in the acidic soils where Vaccinium species are typically found, as phosphorus availability is often limited under such conditions. Fungi are another essential component of the rhizosphere microbiome in Vaccinium species. Mycorrhizal fungi, particularly ericoid mycorrhizae (ErM), are of special interest 13 . ErM are fungi that form symbiotic relationships with the roots of Vaccinium plants, enhancing their ability to absorb water and nutrients, especially phosphorus. The symbiosis between Vaccinium species and ErM is highly specialized, with Vaccinium roots providing carbon to the fungi in exchange for improved nutrient uptake. Recent findings also suggest that the colonization by ErM fungi could also involve above-ground tissues, such as stem and leaves 14 , possibly opening to speculate about more direct modulation of secondary metabolite production by the plant. The interaction between ErM and bacteria seem to have a role in resilience to heat stress 15 . The co-occurrence and invasion of V. uliginosum of the spots of V. myrtillus can lead to hypothesis that differences in the recruitment of the associated microbiota from the soil could be relevant for thriving under the pedo-climatic conditions of these areas. Indeed, comparative studies on V. uliginosum and V. myrtillus microbiota are lacking, while only a few studies analyzed some aspects of the associated microbiota of these two species individually 14 , 16 , 17 . Moreover, the still lack of cultivation practices for V. myrtillus could be partly attributed to challenges in establishing a suitable microbiota under cultivation. It is then interesting, both for understanding the presence of species-specific features of the forest and bog bilberry microbiomes and defining specificities for approaching bilberry cultivation, the analysis of the rhizosphere and endosphere microbiota of V. uliginosum and V. myrtillus collected in the wild spots, either in single or co-occurring populations. Here we report findings obtained from microbiota analysis performed by amplicon sequencing of 16S rRNA gene (bacteria) and Internal Transcribed Spacer (ITS, fungi) for five spontaneous populations in Central Italian Apennines. We aim to identify the importance of site and host species ( V. uliginosum and V. myrtillus ) in affecting the diversity and taxonomy of bacterial and fungal microbiota, trying to hypothesize also possible roles of the microbiota in the partial invasiveness by V. uliginosum of the spots colonized by V. myrtillus . 2. Results and Discussion 2.1 Overall Diversity of the Bacterial and Fungal Microbiota For the V3-V4 amplicon sequencing, a total of 4’159’967 16SrRNA amplicons reads were obtained, and 3’836’541 (92% of total reads) passed quality filtering. After the merging step and chimera removal, a total of 2’194’373 reads were obtained (Supplementary Information File, Table S1), corresponding to 1921 ASVs (Supplementary Dataset). For the ITS amplicon sequencing a total of 4’138’283 ITS reads were obtained, and 3’727’259 (90% of total reads) passed quality filtering (Supplementary Information File, Table S2). After the merging step and chimera removal, a total of 3’537’840 reads were obtained, corresponding to 728 ASVs (Supplementary Dataset). Rarefaction curves obtained from the ASVs reached a plateau for all samples (Supplementary Information File, Figure S1), indicating a satisfactory survey of the bacterial diversity (Good’s coverage, Supplementary Information File, Tables S3 and S4), which allowed to estimate alpha diversity indices. 3.2. Bacterial and fungal microbiota are differentially affected by host plant species Alpha diversity estimates were obtained ( Figure 1 ), with comparisons made between different plant compartments (origin), plant species, and sampling sites for both bacterial (16SrRNA) and fungal (ITS) microbiota. The bacterial microbiota diversity analysis in V. myrtillus and V. uliginosum across compartments (leaves, roots, rhizosphere) revealed significant differences in plant-associated microbiota compared to bulk soil. In particular, Shannon and Chao1 indices showed the highest values for bulk soil, followed by rhizosphere and roots, and then by leaves. Interestingly, an inverse trend was observed for Pielou’s evenness values, leaves having the highest, followed by root, and then soil and rhizosphere. The analysis across species did not show differences between the whole V. myrtillus and V. uliginosum samples but still showed bulk soil having different alpha diversity values compared to plant-associated samples. For the fungal microbiota, alpha diversity analysis ( Figure 1 ) revealed, in contrast with bacterial microbiota, higher Pielou’s evenness in leaves compared to the other compartments. Additionally, while bacterial microbiota alpha diversity was similar between V. myrtillus and V. uliginosum , the fungal microbiota alpha diversity was higher in V. uliginosum samples compared to V. myrtillus for Shannon and Simpson indices. Download figure Open in new tab Figure 1. Alpha diversity indices of the bacterial and fungal microbiota associated with V. myrtillus and V. uliginosum (a) Shannon index; (b) Simpson index; (c) Chao1 index; (d) Pielou index). Lines and the numbers above the lines indicate the p-values of the contrasts (Wilcoxon test). Bulk soil (S), V. myrtillus (Vm), V. uliginosum (Vu). Asterisks indicate level of significance (* p≤ 0.05; **p≤0.01; *** p≤ 0.001; **** p≤ 0.0001). The evidence reported above on alpha diversity of bacterial and fungal microbiota suggests that these two fractions of microbiota are differentially affected by the host plant. In fact, while for the bacterial fraction the host plant clearly selects a group of taxa (Shannon and Chao1 diversity is lower than that of soil), the fungal fraction showed that leaves harbor higher diversity than soil. Moreover, the fungal fraction also showed between host species differences. Such different behaviors of bacterial and fungal plant-associated microbiota with environmental changes (including site, host plant genotypes etc.) have been observed frequently in other systems. In Photinia x fraseri we previously observed that the fungal leaf microbiota is more influenced by plant growth conditions (presence of particulate pollution) than the bacterial microbiota 18 . Similar results have been reported for several plant species in relation to drought stress 19 . Indeed, bacterial and fungal communities associated with plants exhibit distinct sensitivity to environmental conditions, influenced by factors such as water availability, land use, and soil properties 20 – 22 . Our results are adding novelty to this evidence; overall, the body of results on alpha diversity indicates that both V. myrtillus and V. uliginosum actively shape their microbiota, possibly resulting in communities that are potentially functionally specialized, either among plant compartments or between host species. The indication that the fungal fraction is able to differentiate between the two species is stirring attention over the possibility that species-specific associations between fungi and host plant could be key in shaping the microbiota. A similar pattern of differences was observed for the taxonomic similarities among microbiota ( Figure 2 ). NMDS showed a clear separation between leaf and bulk/rhizosphere associated bacterial fraction, with samples from root compartment being more widely dispersed between these two poles, suggesting greater taxonomic heterogeneity in the root compartment microbiota. PERMANOVA ( Table 1 ) confirmed that both host species and origin (compartments leaves, root, rhizosphere, and bulk soil) significantly influenced bacterial composition (p < 0.05), with a significant interaction effect (p = 0.003). For the fungal community ( Figure 2b ) the NMDS did not show clear clusterization, possibly suggesting that the fungal taxa identified could be relatively ubiquitous in different plant compartments and between V. myrtillus and V. uliginosum . However, the PERMANOVA results indicated that host plant species and origins (plant compartments) do have a statistically significant effect on fungal microbiota composition, in line with also the results from alpha diversity. The relationship between fungal taxonomic diversity and host plants was further confirmed by a beta-dispersion test (Table S1). View this table: View inline View popup Table 1. Microbial communities are structured by Vaccinum species, sampling site, and compartment. Permutational Multivariate Analysis of Variance (PERMANOVA performed to assess the effect of origin and site on beta diversity based on Bray-Curtis distances. The model tested the interaction between Species, Site, and Origin (Species x Site x Origin) for both (a) the bacterial (16SrRNA) and (b) fungal (ITS) microbiota. Asterisks indicate significance thresholds (*, <0.05; ** <0.01; *** < 0.001). Download figure Open in new tab Figure 2. Nonmetric multidimensional scaling (NMDS) of a) bacterial and b) fungal community. Ordination based on Bray-Curtis distance. Colors indicate origin of the samples (violet= bulk soil, blue=leaves, green=rhizosphere, yellow=roots). Shape indicates species (triangle= V. myrtillus , square= V. uliginosum , circle= bulk soil. Actually, it is known that the fungal microbiota associated with Vaccinium species varies significantly, influenced by several factors such as plant species (genotype), environmental conditions, and soil characteristics. For the rhizosphere microbiota, for instance, research comparing the rhizosphere microbiomes of southern highbush blueberry ( Vaccinium corymbosum ), Darrow’s blueberry ( Vaccinium darrowii ), and rabbiteye blueberry ( Vaccinium virgatum ) revealed significant differences in the abundance of ErM fungi among these species. ErM fungi are indeed important for the adaptation to acidic soils with low nutrient availability 23 , 24 . For V. myrtillus and V. uliginosum previous studies have actually found relevant differences in the endophytic fungal microbiota (Daghino et al., 2022; Yang et al., 2018). We cannot exclude that these differences in fungi can impact the ability of V. myrtillus and V. uliginosum to adapt to specific habitats and explain the partial invasion of V. myrtillus by populations of V. uliginosum . However, we cannot exclude that the statistically significant differences detected could be influenced by the disparity in within-group variability. Actually, unequal sample sizes, particularly for V. uliginosum , could lead to greater variability in dispersion, potentially distorting the interpretation of species-related differences. 2.3 Taxonomic characterization of V. myrtillus and V. uliginosum microbiota The taxonomic representation of V. myrtillus and V. uliginosum showed among the most abundant bacterial classes Alphaproteobacteria, Bacteroidia, Acidobacteriae and Actinobacteria, and for fungi Agaricomycetes, Sordariomycetes, Dothideomycetes, Leotiomycetes, Tremellomycetes, Mortierellomycetes and Glomeromycetes were the most abundant classes (Figure S1). Leaves vs. bulk soil bacterial microbiota showed the highest statistically significant differences (by DESeq2) in the presence and abundance of ASVs affiliated with several classes ( Figure 3a ). Enrichment in Bacteoridia and Alphaproteobacteria was shared among all the tested contrasts. Interestingly V. myrtillus and V. uliginosum contrast showed statistically significant differences in 7 classes (more abundant in V. myrtillus than V. uliginosum ). A previous study in V. angustifolium the rhizosphere was found to be predominantly inhabited by Alphaproteobacteria, mainly from the genus Bradyrhizobium 24 . The role of these bacteria (nitrogen-fixer of leguminous plants) is still unclear but is in line with a general observation that Alphaproteobacteria are a key bacterial class in plant-microbe interaction 26 . The same and another study in Vaccinium corymbosum 27 found also abundant presence of Acidobacteria in the rhizosphere suggests their potential role in soil nutrient cycling. It is worth noticing in our study that Bacteoridia differentiate among either species or origin. Although Bacteoridia are well studied as an important member of the human intestinal tract, their functional roles in plant microbiomes remain largely elusive 28 . However, recent research has shown that they actively colonize various plant districts and can contribute to nutrient cycling 28 , 29 . As for the bacterial microbiota, several fungal classes showed statistically significant enrichment between plant samples and soil and between V. myrtillus and V. uliginosum ( Figure 3b ) as: Agaricomycetes, Dothideomycetes, Leotiomycetes, Mortierellomycetes, Saccharomycetes, Sordariomycetes and Tremellomycetes. The presence of these fungal classes in the microbiota of Vaccinium spp. across different compartments (roots, rhizosphere, and leaves) could be justified based on their ecological roles and their interactions with plants in these specific niches. While mycorrhizal fungi (like Leotiomycetes and Glomeromycetes ) enhance nutrient availability in the root zone by facilitating nutrient exchange between plant roots and the soil 14 , 30 , saprotrophic fungi (such as Tremellomycetes, Mortierellomycetes , and Agaricomycetes ) break down organic matter, releasing nutrients into the soil and enhancing plant health 31 . In previous studies, while in V. myrtillus fungi from the genus Hyaloscypha and the Phialocephala-Acephala applanate complex, in V. uliginosum genera as Rhizoscyphus and Meliniomyces dominated ErM communities, followed by Clavaria, Oidiodendron, Lachnum, Acephala , and Phialocephala were recovered 25 , 32 . All (but Clavaria ) of these taxa are belonging to Leotiomycetes, one of the above reported classes, which includes many ericoid mycorrhizal fungi. Clavaria is a member of Agaricomycetes, another of the classes which statistically differentiates between V. myrtillus and V. uliginosum . Download figure Open in new tab Figure 3. Taxonomic enrichment between microbiota. Bubble plot depicting the relative abundance of classes for a) the bacterial (16S) microbiota and b) the fungal (ITS) community, based on differentially abundant ASVs (padj<0.05) across each contrast. Diameter of bubbles is proportional to relative abundance of each class. “Bulk” indicates bulk soil samples. 3.4. Network analysis of interactions within the microbiota To further inspect the microbiota of V. myrtillus and V. uliginosum in relation to host-species differences, co-occurrences among the total set of ASVs (both bacterial and fungal) were computed and network representations were used to determine the presence of microbial groups which may potentially interact among them. Such representation may help to decipher the structure of microbiota to help understanding the ecological rules guiding community assembly 33 . Results from analysis of co-occurrence networks ( Figure 4 ) showed three clearly different patterns among soil, V. uliginosum and V. myrtillus . As expected (Yang et al., 2024), soil microbiota showed the highest number of edges (7947) when compared to the plant-associated microbiota, indicating a very high level of interactions between microbial phyla. The high connectivity of soil co-occurrence network highlights the importance of native soil in providing many ecological niches for microorganisms, aligning with previous studies emphasizing the role of soil microbiota in maintaining ecosystem stability and functioning 35 . The relatively lower number of nodes (284) compared to the number of edges suggests that the distinct microbial groups interact extensively with each other, forming a dense network and describing a possible high degree of ecological complexity within the soil. This result may suggest good resilience and ecosystem services provided by the samples soil microbiota. Download figure Open in new tab Figure 4. Co-occurrence networks strongly distinguish soil, V myrtillus and V. uliginosum microbiota. Network analysis of co-occurrence between bacterial and fungal phyla associated with V. myrtillus and V. uliginosum species and their soil. Each node in the network represents a phylum, and the connecting lines indicate positive co-occurrence interactions between ASVs affiliated to these phyla. Concerning the two host plant species, the co-occurrence network of the microbial communities associated with V. myrtillus presents a higher number of nodes (475) than the soil or V. uliginosum , indicating a greater number of distinct microbial groups present within this plant species. However, the number of edges (2897) is lower than that of soil, suggesting that while V. myrtillus supports a diverse microbial community, the level of microbial interactions might be less complex than in the soil, possibly due to a more selective and specialized microbiome 34 , 36 . The higher number of edges (4970), in V. uliginosum compared to V. myrtillus, together with the lower number of nodes (321), suggest that microbial taxa are more tightly ecologically connected in V. uliginosum than in V. myrtillus , with several taxa having the same co-occurrence patterns (lower number of nodes compared to V. myrtillus ). This may imply that V. uliginosum microbiota could be more resilient to changes or that V. uliginosum better recruit soil taxa than V. myrtillus . However, we should be cautious to infer ecological properties of the microbiota from the sole network analysis 37 . 3.4 Prediction of potential functions and metabolic pathways Considering the taxonomic enrichment between host species and compartments, as well as differences in networks reported above, we hypothesized that some functional (metabolic and ecological) differences may be associated with such taxonomic variations. Consequently, functional profiles were inferred from retrieved taxonomies, in terms of the metabolic pathways and ecological roles present in the bacterial taxa ( Figure 5 ) and trophic mode for fungi ( Figure 6 ). Fermentation pathways showed higher relative abundance in V. myrtillus and V. uliginosum , especially in the root and leaf compartments. This suggests that endophytic microbiota of these plant species may rely on the use of unusual carbon sources, possibly including (e.g. in roots) anaerobic processes). Under this assumption, the aromatic compound degradation pathway, slightly more abundant in V. uliginosum leaves, is in line with the utilization of unusual carbon and energy sources by plant endophytes. Leaves of several plant species, especially medicinal plants, have shown the presence of a microbiota adapted to tolerate and thrive in presence of metabolites (often toxic) present in plant tissues 38 . Since bilberry tissues harbor several compounds with antimicrobial activity 39 we cannot exclude that leaf microbiota of V. myrtillus and V. uliginosum could harbor metabolic activities able to tolerate and possibly utilize toxic compounds, including aromatic molecules, as carbon and energy sources. Another interesting function was the nitrate reduction pathway; this was notably more abundant in the roots of both V. myrtillus and V. uliginosum , than in other compartments, suggesting that plants, particularly V. myrtillus , host several bacteria which may help in soil nitrogen assimilation by roots. Actually, it is known that soil acidic pH reduces soil nitrate reduction potential 40 , leading to lower nitrate levels. Additionally, acidic conditions favor ammonium (NH 4 + ) retention over nitrate because nitrate is more prone to leaching in acidic soils 41 . Acidophilic plants, as V. myrtillus and V. uliginosum may take advantage in recruiting beneficial nitrate reducing bacteria in their root apparatus. Among the other functions, the relative abundance of cellulolysis was highest in V. uliginosum , followed by V. myrtillus , and bulk soil. Notably, cellulolytic activity was also particularly pronounced in the rhizosphere and bulk soil. Cellulolytic activity could be related to the high abundance of Actinobacteria, which are known to harbor cellulase genes and are key players in organic matter cycling in the soil. We could then hypothesize that rhizosphere and soil have good potential for carbon cycling, then also humification processes. However, we cannot exclude that some cellulase activities, not detected in our analysis, could also be present in some plant pathogen. Actually, bacteria assigned as “animal parasites and symbionts” were found, especially prominent in V. myrtillus and V. uliginosum . Previous analyses have reported that other Vaccinium species also harbor potential symbiotic bacteria 24 , as members of the order Rhizobiales, within the class of Alphaproteobacteria. However, we can likely assume that these bacteria behave as commensal endophytes, not as symbiotic nitrogen fixing bacteria (as they do with leguminous plants). Download figure Open in new tab Figure 5. Metabolic pathways and their relative abundances across different conditions. The heatmap shows the relative abundances of ecologic functions and metabolic pathways identified through FAPROTAX in the bacterial microbiota. Abundances with respect to compartment (origin) and host the species are reported. (Vm, V. myrtillus ; Vu, V. uliginosum ; Soil, bulk soil. The color gradient indicates relative abundance, with darker shades representing higher values. Download figure Open in new tab Figure 6. Pie chart of fungal trophic mode distribution, showing the relative abundance of each mode based on the total count. Only modes representing more than 0.5% are labeled. The analysis of fungal trophic modes revealed a diverse distribution of functional roles within the community. The most abundant trophic mode is saprotroph, which accounts for 31.47% of the total occurrences, indicating that a significant portion of the fungal community is involved in decomposing dead organic matter, as previously observed for V. myrtillus in coniferous forests in Norther Europe 32 . This is followed by saprotroph-symbiotroph (17.60%) and pathotroph-saprotroph-symbiotroph (17.16%), suggesting that many fungi exhibit mixed functional strategies, playing roles in both decomposition and symbiotic relationships with plants. Symbiotrophs (13.93%), which include ErM fungi 42 , and pathotroph-saprotroph (14.97%) also contribute to the overall functional diversity, with fungi in these categories likely playing key roles in nutrient exchange and mutualistic symbioses. The relatively lower representation of pathotrophs (2.32%) and pathotroph-symbiotrophs (1.96%) indicates that pathogens, although present, are less prevalent in this community. This functional diversity highlights the complex ecological interactions within the fungal community, with a predominance of decomposers and symbionts contributing to nutrient cycling and plant interactions. 3. Conclusion This study provides a comprehensive analysis of the bacterial and fungal microbiota associated with V. myrtillus and V. uliginosum in wild populations of the Central Italian Apennines. By utilizing 16S rRNA and ITS amplicon sequencing, we demonstrated that microbial communities differ significantly between plant compartments and species. Our taxonomic analyses highlighted key microbial groups, including Alphaproteobacteria, Actinobacteria, and Acidobacteria among bacteria, and Agaricomycetes and Leotiomycetes among fungi. While these taxa have been found in other Vaccinium species, it is worth noticing that our study showed that V. myrtillus and V. uliginosum host different abundances of members of these classes. Our experimental plan cannot provide mechanistic indications on the role of such taxa in the biology of the two Vaccinium species, including the different colonization ability and possibly the production of the relevant secondary metabolites in leaves and fruits. The co-occurrence network analysis supports the hypothesis that microbiota structure is shaped by both environmental and host-related factors. The interpretation on the number of nodes and edges identified suggests that the microbiota of V. myrtillus are more selectively filtered than that of V. uliginosum . We may speculate that V. uliginosum more tightly associated and possibly functionally integrated microbiota, makes the host plant potentially more resilient to environmental changes than V. myrtillus . Based on this hypothesis, it could be plausible that the invasiveness displayed by V. uliginosum populations against V. myrtillus populations could possibly relate to such a broader ability of the former species to recruit the soil microbiota. The functional predictions, which indicated potential roles in nitrogen cycling, cellulose degradation, and plant-microbe interactions, with a particular emphasis on the microbial contributions to organic matter decomposition and nitrogen solubilization, may suggest several direct and indirect effects on plant species physiology and growth. However, the level of functional inference we may derive from 16S rRNA and ITS amplicon sequencing cannot provide evidence for differentiation between V. myrtillus and V. uliginosum microbiota at this level. In conclusion, the findings obtained provide novel insights into the microbiota of wild bilberries, highlighting their ecological significance in subalpine environments. Understanding these microbial communities will be crucial for developing microbiome-based strategies to enhance plant resilience and productivity and develop innovative cultivation practices for V. myrtillus . 4. Materials and Methods 4.1 Sampling sites and sampling methods Five sampling sites were identified in Central Apennines, Tuscany (Italy) ( Table 2 ). In each site, populations of V. myrtillus were present. For two sites, coverage by V. uliginosum was also present, directly in contact with V. myrtillus vegetation. Sampling was performed on 29 th June 2023. Sampling methods were in accordance with standard methods defined for the Crop Microbiome Survey Initiative ( https://www.globalsustainableagriculture.org/the-crop-microbiome-survey/ ) and previously published 43 . Briefly, for each sampling site, a plot of 2 m x 2 m was identified, three randomly selected plants along the vertices of the plot were used to collect leaves, roots, and rhizospheric soil sample. Three bulk soil samples, at a depth of 5 cm, were also collected. The samples from individual plants and soil were mixed to produce a single composite sample. For each plot two duplicate composite samples were created. View this table: View inline View popup Download powerpoint Table 2. Description of the sampling sites. Acronyms are used to indicate Vaccinium species, plant compartment and soils collected. 4.2 eDNA extraction and amplicon sequencing Environmental DNA (eDNA) was extracted from 250 mg of soils and plant tissues using the DNeasyPowerSoil Pro (Qiagen Italy, Milan, Italy). The V3-V4 region of the bacterial 16SrRNA gene was amplified as reported in the Illumina 16S Metagenomic Sequencing Library Preparation protocol with primers as reported in 44 . Fungal Internal Transcribed Spacer 1 (ITS1) was amplified following standards of Hearth Microbiome Project ( https://earthmicrobiome.org/protocols-and-standards/its/ ) and ITS1f-ITS2 primer pairs 45 . Amplicons were used to construct libraries and sequenced on an Illumina NovaSeq6000 instrument (Illumina, San Diego, CA) SP flow cell using 250 bp paired-end cycles at Biomarker Technologies (BMK) GmbH (Münster, Germany), following Illumina protocols. Reads were trimmed using Cutadapt 46 to remove the following sequencing primers: V3-V4_F: ACTCCTACGGGAGGCAGCA, V3-V4_R: GGACTACHVGGGTWTCTAAT, ITS1_F: CTTGGTCATTTAGAGGAAGTAA, ITS1_R: GCTGCGTTCTTCATCGATGC. Raw reads are available from NCBI SRA database under Bioproject PRJNA1250273. 4.3 Bioinformatic analysis of sequencing data, clustering of reads and taxonomic assignment Data analysis was performed as previously reported 47 . In brief, DADA2 pipeline (version 1.24.0) 48 as used to cluster amplicon sequence variants (ASVs). Bacterial taxonomy assignment was carried out comparing 16SrRNA ASV against SILVA_SSU_r138 database 49 using “DECIPHER” R package (version 2.24.1) 50 . Annotated ASVs count tables were processed in Phyloseq package 51 . All sequences classified as chloroplasts were removed. For ITS ASV taxonomy assignment was carried out on the UNITE ITS database 52 , (UNITE_v2020_February2020). 4.4 Statistical analysis of microbiota diversity Alpha diversity (Shannon and Pielou’s Evenness indices) were calculated using the function “diversity()” within “Phyloseq” R package 51 . Good’s coverage and evenness indices were calculated through the R functions ‘goods()’ and ‘evenness()’, respectively, within the ‘microbiome’ R package (version 1.12.0). Taxonomic differences among microbiota were inspected by non-metric multidimensional scaling (nMDS), using the “ordinate” function and plotting by the “plot_ordination()” function within phyloseq package. The “ggplot2” R package (version 3.3.6) 53 was used to generate relative abundance plots. Different community structures were analyzed using permutational a multivariate analysis of variance (PERMANOVA) using the R packages “vegan” (version 2.6.2) and the function “adonis2()”. Wilcoxon tests for multiple comparisons of averages were performed on alpha diversity indices using ‘ggviolin()’ and ‘stat_compare_means()’ within the ‘ggpubr’ R package (version 0.4.0). Differential abundance analysis was performed using the R package DESeq2 (version 1.36.0) 54 . Network analysis of ASVs co-occurrence was performed using SpeSpeNet 55 . 4.5 Functional inference on bacterial and fungal microbiota Ecological functions of microbial communities were predicted with FAPROTAX 56 for 16S sequencing data, while for the fungal microbiome, the ecological roles were assigned using”FunguildR” package (version 0.2.0.900) 57 . Supplementary Materials The following supporting information can be downloaded at: www.mdpi.com/xxx/s1 Supplementary Information File; Supplementary Dataset. Author Contributions Conceptualization, E.G., A.M., F.V., and C.F.; methodology, F.V.; validation, F.V., C.F., E.G. S.B., and A.M.; formal analysis, G.C., F.V., and C.F.; investigation, F.V., C.F., G.C.; resources, A.M. E.G. and S.B.; data curation, F.V., C.F.; writing—original draft preparation, F.V., A.M. and C.F.; writing—review and editing, F.V. A.M. C.F. E.G., and S.B.; visualization, F.V.; supervision, A.M.; project administration, A.M., C.F.; funding acquisition, A.M.. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by PNRR CN2 AGRITECH, SPOKE 7, WP 7.2.2 “Promotion of wood and non-timber forest products, foods, and no-food chains (ecosystem services)”. FV is supported by a PhD fellowship co-funded by the European Union –PON Research and Innovation 2014–2020 in accordance with Article 24, paragraph 3a), of Law No. 240 of December 30, 2010, as amended and Ministerial Decree No. 1062 of August 10, 2021. CF is supported by a post-doctoral fellowship funded by PNRR_CN 5_National Biodiversity Future. A.M. is funded by the Italian Ministry of University and Research grant number 20225WER57. Data Availability Statement Sequence reads are available on SRA database under the Bioproject PRJNA1250273. Conflicts of Interest The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Abbreviations The following abbreviations are used in this manuscript: 16SrRNA 16S ribosomal RNA ITS Internal Transcribed spacer nMDS nonmetric Multimensional scaling References 1. ↵ Ballington JR . Collection, utilization, and preservation of genetic resources in Vaccinium . 2. ↵ Manzanero BR , Kulkarni KP , Vorsa N , et al. Genomic and evolutionary relationships among wild and cultivated blueberry species . BMC Plant Biol 2023 ; 23 : 126 . 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