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Article

Root and Rhizosphere Microbiome of Tomato Plants Grown in the Open Field in the South of West Siberia under Mineral Fertilization

by
Natalia Naumova
1,*,
Olga Baturina
2,
Taisia Nechaeva
1 and
Marsel Kabilov
2
1
Institute of Soil Science and Agrochemistry, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia
2
Institute of Chemical Biology and Fundamental Medicine, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia
*
Author to whom correspondence should be addressed.
Horticulturae 2022, 8(11), 1051; https://doi.org/10.3390/horticulturae8111051
Submission received: 21 October 2022 / Revised: 2 November 2022 / Accepted: 4 November 2022 / Published: 8 November 2022
(This article belongs to the Section Plant Nutrition)
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Abstract

:
Agricultural practices can affect root-associated microbiota, but the effect of fertilization is still poorly examined. The aim of this study was to obtain 16S and ITS metagenomic profiles of tomato rhizosphere and root endosphere under mineral (NPK) fertilization in the open field experiment in the south of West Siberia. We found 6 bacterial and 3 fungal phyla in the roots and 24 bacterial and 16 fungal phyla in the rhizosphere. Proteobacteria and Actinobacteria together contributed 90% of the total number of sequence reads in roots and 50% in the rhizosphere, whereas Ascomycota ultimately prevailed in OTUs’ richness and abundance in both biotopes. Fertilization changed the relative abundance of 32 bacterial and 14 fungal OTUs in the rhizosphere and of 7 bacterial and 3 fungal OTUs in roots. The revealed root bacteriobiome response to conventional mineral NPK fertilization by the dominant taxa at the high taxonomic level (class) illustrates well the role of NPK-changed plant metabolism in shaping endophytic microbiota and hence fertilization potential in enhancing plant growth-promoting microorganisms and mitigating plant pathogens. Using fertilization rate gradient in further research may bring a more detailed understanding of how to modify and even fine-tune root-associated microbiomes in order to enhance crops’ health and yields.

1. Introduction

Agricultural practices can affect soil microbiota, but how such practices, and in particular, fertilization, can affect rhizosphere and root endospheric microbiota in different agricultural contexts is still poorly studied.
Plants, like other eucaryotic organisms, harbor a plethora of microorganisms inside their bodies. A complicated network of diverse above- and below-ground interactions between plants, environment, and microbes determine the establishment of microbial assemblages in plants [1]. This microbiota may be beneficial, harmful, or neutral for the host’s growth and development. The importance of plant-associated microorganisms cannot be overestimated in all types of ecosystems, from natural to agricultural and technogenic, as well as in all kinds of artificially constructed plant-growing environments, as they increase plant resilience, improve plant nutrition, enhance stress tolerance and defense and, consequently, sustain plant growth and production [2] and enable more sustainable agriculture [3]. Pathogenic microbial endophytes can cause serious diseases, sometimes devastating natural or agricultural ecosystems. However, the endophytic microbiome has been poorly investigated even in agriculturally important crops, and researchers still have to work hard to obtain a better insight into “the black box of ecological and evolutionary interactions across phytobiomes” [4], as currently there is very little knowledge on plant–endophyte interactions and mechanisms shaping microbial assemblages in plants [5]. Fertilization treatments were shown to clearly influence the endophytic community structure of potato, for example, [6], and a study with wheat found no effect of mineral N and P fertilization on either bacterial community diversity or bacterial phyla abundance in the rhizosphere soil [7]. Thus, there exists a lack of information on how fertilizers act on the plant-associated microbial communities, not only endophytic but rhizosphere ones as well [8].
Tomato (Licopersicon esculentum L.) is globally one of the most important agricultural crops, with annual production reaching 187 mln tons in 2020 [9] and steadily increasing during the last years. Mineral fertilization, for many years, has been one of the most common fertilization practices for producing tomatoes both in protected conditions and in open fields. However, there is a lack of reports about the effect of conventional mineral fertilization on the microbiome of the rhizosphere and roots of tomato plants, although various organic and synthetic fertilizers seem to have been receiving research attention in this respect [10]. Some publications provide detailed information about the composition, diversity, and influential factors shaping the rhizospheric, phyllospheric, and endophytic bacterial communities of tomato plants [11] yet do not inform at all about the fertilizers used to stimulate plants’ growth and production, briefly mentioning the fertilization was accomplished “following the recommendation of the seed company” [11] (p. 3), the latter also not being specified.
The aim of this research was to obtain 16S and ITS metagenomic profiles of tomato rhizosphere and root endosphere under mineral (NPK) fertilization in the open field experiment in the south of West Siberia, Russia.

2. Materials and Methods

2.1. Experimental Site

To study the microbiome in tomato roots, a microplot field experiment was carried out at the experimental station during the 2021 growing season in the forest-steppe zone in the south of West Siberia (54°58′ N, 83°13′ E). The climate of the region is classified as continental (Table S1) with a 119-day frost-free period. The experiment was conducted on the loamy arable soil classified as Luvic Greyzemic Phaeozem, according to the World Reference Base for Soil Resources [12]; or as gray agricultural soil, according to the Russian Soil Classification [13]. Phaeozem, together with Chernozem, are the most common soil types used in the region for agricultural production. The soil in our study has been in agricultural use for more than 40 years.

2.2. Experimental Setup

The microplot open field experiment was started at the beginning of the growing season (May 2021) and finished at the end of the growing season (September 2021). One cultivar of Licopersicon esculentum L. “Zyryanka”, included in the Russian State Crop Register and recommended for the region, was used. Tomato seedlings were grown in cassettes in a peat substrate in the Central Siberian Botanical Garden SB RAS (Novosibirsk, Russia) and, at the age of 50 days, planted out on 12 May 2021 in the open field microplots at a density of one plant per 0.25 m2. The experiment included two fertilization treatments: no fertilization (No) and mineral fertilization (NPK). Fertilizer application was started one week after planting out and continued throughout the season every fortnight. Mineral fertilizer (Nitrofoska, Agrosintez LLC, Kemerovo, Russia) was applied at the rate commonly recommended for vegetables in the region, i.e., equivalent to 60 kg N, 60 kg P, and 60 kg K per hectare during the first 2/3 of the growing season, and at the half of the rate during the last 1/3. Each treatment was performed in 5 randomized replicates, i.e., altogether, there were 15 microplots with 5 plants.

2.3. Soil Sampling and Chemical Analyses

The soil was sampled at the beginning of May 2021, prior to planting out the tomato seedlings, from the 0–15 cm layer in 3 individual replicates from the plot that were bulked together for further analyses. Soil organic carbon (SOC) content was estimated by dichromate digestion; soil organic nitrogen content (STN) was determined by the Kjeldahl method; the content of soil available nutrients (NO3-, NH4+, P2O5) and pH (H2O) were measured by standard techniques [14]. Briefly, nitrate content was determined potentiometrically in 0.1% AlK(SO4)2 solution (soil–solution ratio 1:5 w/v); ammonium content was measured colorimetrically in 2M KCl extracts (1:10 w/v). Available soil P was extracted by 0.03 M K2SO4 (1:5 w/v) and determined colorimetrically. Soil pH was measured by equilibrating 10 g of field-moist soil with 25 mL of deionized water. All analyses were performed in triplicates, and the data were expressed on the oven (105 °C) dry basis.

2.4. Plant Sampling and Analyses

The growing season in the open field in West Siberia is short, with cool nights already occurring in August, which can prevent the majority of fruits from ripening in situ. Therefore, tomato fruits were collected repeatedly during the growing season, starting at the end of July, as soon as they stopped increasing in size and reached technical maturity. At the end of the experiment, all consumable fruits were collected. Above- and below-ground phytomass was also determined at the end of the experiment. Fruits and phytomass produced by every plant were counted and weighed in fresh form. Roots for the microbiome analysis were washed in distilled water, sterilized by shaking in the peroxide solution, air-dried, and stored at −20 °C until DNA extraction. All plant components were collected from one plant, i.e., one plot.

2.5. DNA Extraction and Sequencing

Total DNA was extracted from 0.40 g of roots using the DNeasy PowerSoil Kit (Qiagen, Hilden, Germany) as per the manufacturer’s instructions. The bead-beating was performed using TissueLyser II (Qiagen, Hilden, Germany) for 10 min at 30 Hz. No further purification of the DNA was needed. The quality of the DNA was assessed using agarose gel electrophoresis.
The V3–V4 region of the 16S rRNA gene and ITS2 region were amplified with the primer pairs 343F/806R and ITS3_KYO2/ITS4, respectively, combined with Illumina adapter sequences [15]. PCR amplification was performed as described earlier [16]. A total of 200 ng PCR product from each sample was pooled together and purified through MinElute Gel Extraction Kit (Qiagen, Hilden, Germany). The obtained amplicon libraries were sequenced with 2 × 300 bp paired-ends reagents on MiSeq (Illumina, CA, USA) in the SB RAS Genomics Core Facility (ICBFM SB RAS, Novosibirsk, Russia). The read data reported in this study were submitted to the NCBI Short Read Archive under bioproject accession number PRJNA887478.

2.6. Bioinformatic Analysis

Raw sequences were analyzed with Usearch v.11.0.667 using the UPARSE pipeline [17], which included the merging of paired read s, read quality filtering (-fastq_maxee_rate 0.005), length trimming (remove less 350 nt), merging of identical reads (dereplication), discarding singleton reads, removing chimeras, and operational taxonomic unit (OTU) clustering using the UPARSE-OTU algorithm. The OTU sequences were assigned a taxonomy using the SINTAX [18] and 16S RDP training set v.16 [19], or fungi ITS UNITE USEARCH/UTAX v.2018.11.18 [20] as a reference. The taxonomic structure of thus obtained sequence assemblages, i.e., a collection of different species at one site at one time [21], was estimated by the ratio of the number of taxon-specific sequence reads (archaeal and non-fungal sequences were removed from the data matrices) to the total number of sequence reads, i.e., by the relative abundance of taxa, expressed as a percentage. A taxon was considered dominant if its relative abundance was equal to or exceeding 1.0%.
The OTUs datasets were analyzed by individual rarefaction (graphs are not shown) with the help of the PAST software [22]: the numbers of bacterial and fungal OTUs detected, reaching a plateau with an increasing number of sequences, confirmed that the sampling effort was close to saturation for all samples, thus being enough to compare diversity [23].

2.7. Statistical Analyses

Statistical analyses (descriptive statistics and ANOVA) were performed by using Statistica v.13.3 a (TIBCO Software Inc., Palo Alto, CA, USA), and PERMANOVA was performed with PAST [22] software packages. OTUs-based α-diversity indices were calculated using PAST. Factor effects and mean differences in post hoc comparisons by Fisher’s LSD test were considered statistically significant at the p ≤ 0.05 level.

3. Results

3.1. Rhizisphere and Root Bacteriobiome

3.1.1. General Pattern

After quality filtering, chimera, and non-bacterial sequences removal, a total of 206 bacterial OTUs were identified at 97% sequence identity level in the roots and 3655 OTUs in the rhizosphere. In total, 6 bacterial phyla were found in the roots, whereas 24 phyla were detected in the rhizosphere.
Most of the total number of bacterial OTUs in roots belonged to the Proteobacteria phylum (85, or 41% of the OTU richness), with Bacteroidetes (49 OTUs) and Actinobacteria (42 OTUs) being the second and third most OTU-rich phyla, accounting for 23 and 20% of the total number of OTUs, respectively. The Firmicutes and Candidatus Saccharibacteria phyla contributed 10 and 11 OTUs, respectively, accounting for 5% of the total species richness in the study; Deinococcus-Thermus was represented by just 3 OTUs. As for the rhizosphere bacteriobiome, most of the OTUs also belonged to Proteobacteria (890, or 24% of the OTU richness), with Firmicutes (815 OTUs) and Actinobacteria (435 OTUs) being second and third most OTU-rich phyla, accounting for 22 and 12% of the total number of OTUs, respectively. Such phyla as Acidobacteria, Chloroflexi, and Verrucomicrobia were represented by 325, 153, and 97 OTUs, accounting for 9, 4, and 3% of the OTUs number, respectively.
As for the relative abundance, the ultimate dominants in both biomes were the Proteobacteria and Actinobacteria phyla, together contributing more than 50% of the total number of sequence reads in the rhizosphere and about 90% in the roots (Figure 1).

3.1.2. The Effect of Mineral Fertilization on the Rhizosphere and Root Bacteriobiome

Mineral fertilization slightly decreased the relative abundance of one of the minor dominants of the rhizosphere bacteriobiome (Table 1). Overall, though, 32 bacterial OTUs showed differential fertilization-related abundance at p ≤ 0.05 significance level, and 28 more OTUs showed differential abundance at the 0.05 ≤ p ≤ 0.10 level; PERMANOVA, performed with bacterial OTUs, did not reveal statistically significant (p = 0.58) effect of fertilization on the rhizosphere bacteriobiome. The same was true for the root bacteriobiome at the OTU level (p = 0.26, PERMANOVA). The relative abundance of bacterial phyla did not show statistically significant changes; however, two of the dominant classes, namely Alphaproteobacteria and Flavobacteriia (of Bacteroidetes), demonstrated NPK-related changes. At the lower taxonomic levels, these changes translated to the changes in Alphaproteobacteria/Sphingomonadales/Sphingomonadaceae/Sphingomonas and Flavobacteriia/Flavobacteriales/Weeksellaceae/Chryseobacterium/Chryseobacterium sp., increasing their relative abundance. The dominant actinobacterial taxa showed a tendency to decrease in roots under fertilization, but one of the dominant OTUs, attributed to Actinobacteria/Actinobacteria/Micrococcales/Microbacteriaceae/Rathayibacter/Rathayibacter sp., was twice as abundant in the roots of the fertilized plants as compared with the non-fertilized ones (Table 1 and Table 2). Seven OTUs, including four dominant ones, were differentially abundant in roots at the p ≤ 0.05 significance level, with eight more OTUs at the 0.05 ≤ p ≤ 0.10 level.
The number of dominant OTUs, i.e., OTUs contributing more than 1% to the total number of sequence reads, was 17 in the root bacteriobiome and 11 in the rhizosphere (Table 2).

3.1.3. Alpha-Biodiversity in the Rhizosphere and Root Bacteriobiome

Neither rhizosphere nor root bacteriobiome α-biodiversity indices changed under fertilization, their values being very similar (Table 3) between the treatments. As expected, all indices indicated much greater bacteriobiome biodiversity in the rhizosphere. Noteworthy, though, is the fact that the p-value for the comparison of root bacteriobiome species evenness was 0.059 (Fisher’s LSD test), i.e., very close to the 0.05 threshold of statistical significance.

3.2. Rhizosphere and Root Mycobiome

3.2.1. General Pattern

After quality filtering, chimera and all plant sequences removal and subsequent removal of non-fungal sequences (just five OTUs in the root mycobiome and 648 OTUs in the rhizosphere one), a total of 387 and 2718 fungal OTUs were identified at 97% sequence identity level in the root and rhizosphere mycobiomes, respectively. Altogether, 16 fungal phyla were detected: all of them in the rhizosphere and only 3 (namely, Basidiomycota, Ascomycota, and Chytridiomycota) in the roots. In both mycobiomes one cluster was attributed to Fungi but not classified below the domain level.
Most of the total number of fungal OTUs belonged to the Ascomycota phylum: 231, or 60% of the OTU richness, in the roots and 1159, or 43%, in the rhizosphere. In both mycobiomes, Basidiomycota was the second OTU-rich phylum with 150 OTUs, or 39% of the OTUs richness in the roots, and 438, or 16%, in the rhizosphere. In the root mycobiome, the other two clusters, i.e., Chytridiomycota and unclassified Fungi, together contributed six OTUs, being negligible in terms of OTUs richness. In the rhizosphere, Chytridiomycota and Mortierellomycota contributed respectively 5 and 2% of the total number of OTUs, the other 12 phyla together accounting for about one-third of the OTUs’ richness.
As for the relative abundance (Figure 2), the Ascomycota phylum showed 40% in both treatments in the roots, whereas in the rhizosphere, the phylum accounted for 80% of the total number of sequence reads, as averaged over both treatments. Basidiomycota accounted for 5.8% as averaged over both treatments. The third-abundant Zygomycota contributed 4.4% in the rhizosphere mycobiome but was not detected at all in the root one. In the root mycobiome Chytridiomycota and unclassified Fungi were virtually non-present with their less than 0.01%, whereas in the rhizosphere, their contribution was 2% and 3.3%, respectively.

3.2.2. The Effect of Mineral Fertilization on the Rhizosphere and Root Mycobiome

In the rhizosphere mycobiome, fertilization-related differences were not revealed at the phylum, class, and order levels for the dominant taxa (Table 4). However, such differences were found at the lower taxonomic levels: three families (Microascaceae, Plectosphaerellaceae, and Lasiosphaeriaceae) showed decreased abundance, whereas two genera (Plectosphaerella and Fusarium) had increased abundance, which at the OTU level translated to the increased abundance of Plectosphaerella plurivora/Plectosphaerella/Plectosphaerellaceae/Sordariomycetidae_incertae sedis/Sordariomycetes/Ascomycota and Fusarium domesticum/Nectriaceae/Hypocreales/Sordariomycetes/Ascomycota (Table 5). Besides these two, twelve more minor or rare fungal OTUs showed NPK-related differential abundance changes; and PERMANOVA, performed with OTUs, revealed a statistically significant (p = 0.04) difference between the fertilization treatments.
The dominant OTUs numbered 22 (summarily 49% of the relative abundance) and 25 (56%) in No and NPK treatments, respectively, with a few variations between them, which resulted in the overall pool of prevailing OTUs totaling 31.
In the root mycobiome, there were no statistically significant differences in the relative abundance of the dominant taxa at all taxonomic levels due to a rather high variation within the NPK treatment (Table 4 and Table 5), which was also confirmed by PERMANOVA (p = 0.70), performed with the entire set of root mycobiome OTUs. Overall, only three very rare OTUs, i.e., with maximal relative abundance of 0.004% among them, revealed NPK-related changes at the p ≤ 0.05 level. The dominant OTUs numbered 16 in each treatment, totaling 20 OTUs and not showing any NPK-related differential abundance.

3.2.3. Alpha-Biodiversity in the Rhizosphere and Root Mycobiome

As for the α-biodiversity indices in the rhizosphere and root mycobiome, there were no statistically significant differences between the treatments (Table 6), although altogether, the indices showed a tendency for the α-biodiversity to decrease in the NPK treatment as compared to the other one. As expected, the root mycobiome was drastically less diverse than the rhizosphere one.

3.3. Tomato Production Properties

As for the biological and consumable tomato plant production, there were no statistically significant differences (Table 7), although, under the NPK treatment, the plants showed a tendency to produce better.

4. Discussion

4.1. Rhizosphere and Root Bacteriobiome

It is universally accepted that rhizosphere and roots harbor distinct bacterial assemblages, and our results showed the same. The strong prevalence of Actinobacteria and Proteobacteria in the rhizosphere soil and roots of tomato plants complies with the results of other studies on tomato [3,24,25], although in the rhizosphere Proteobacteria abundance was two times lower in our study as compared, for instance, with [24]. The ultimate dominance of the Proteobacteria and Actinobacteria phyla in roots agrees with the results of López et al., 2020 [26] and other results reviewed by Bulgarelli et al. (2013) [1] and Trivedi et al. (2021) [3]. They concluded that most plant species harbor an enrichment of bacterial taxa belonging to the phyla Proteobacteria, Bacteroidetes, Firmicutes, and Actinobacteria and that the root endosphere shows an overwhelming dominance of bacteria belonging to the Proteobacteria phylum, also by culture-dependent methods [27]. Our finding that the Acidobacteria phylum, being one of the major dominants in the rhizosphere soil, was not even detected in the root endosphere agrees with the drastically decreased phylum’s abundance in Arabidopsis thaliana roots as compared with the bulk or rhizosphere soil [28,29]. The fact that in our study, other minor dominants in the rhizosphere, i.e., Chloroflexi and Verrucomicrobia, like Acidobacteria, were not even detected in the roots, implies that these phyla are either “actively excluded by the host immune system, outcompeted by more successful root colonizers or metabolically unable to colonize” [28] (p. 90), the root endosphere. However, some studies reported the presence, albeit not prominent, of Chloroflexi and Verrucomicrobia sequence reads in tomato root endosphere bacteriobiome [30]. Such discrepancy implies either the failure of the plant immune system, lack of competition from other root colonizers, strains with some metabolic features facilitating colonization and establishment inside roots, or mere contamination of root endosphere by bacteria from the rhizoplane. It is noteworthy that the three phyla, i.e., Acidobacteria, Chloroflexi, and Verrucomicrobia, are common in similar soils of the region [31]. As for the Bacteroidetes phylum, in our study, it was a moderate dominant in the roots and a minor dominant in the rhizosphere, although in a recent study with tomatoes grown on a soil substrate in a greenhouse, Bacteroidetes was one of the major dominant members of the community in the roots [25]. As for Firmicutes, in our study, the phylum’s representatives displayed negligible abundance in the roots, where the latter was drastically lower as compared with the rhizosphere, where the Firmicutes phylum ranked third in abundance (12–15%). Such a pattern, i.e., significantly decreased presence of Firmicutes in tomato roots as compared with the rhizosphere soil, was reported by Lee et al. (2019) [23]. This is in contrast with the results of some studies of culturable bacteria in tomato plants: the Firmicutes representatives, mainly belonging to the Bacillus genus, were prominent in roots [25,32].
There exists a general belief that a subset of rhizospheric microorganisms penetrates into the plant roots and colonizes the endosphere depending on the plant’s innate immune system [1,28]. Our attempt to identify soil-type-specific OTUs within the root-inhabiting bacterial assemblages rendered extremely few ones: of the rhizosphere bacteriobiome totaling more than 3000 OTUs, only 15 OTUs, each with less than 1% abundance, were detected in the root bacteriobiome. Yet there is also a possibility that the bacteria, compatible with the endophytic lifestyle, might have entered inside the roots from the rhizosphere but were simply below the limit of detection in soil, but it seems unrealistic to spread this assumption for all bacteria detected in roots. Thus, many tomato root endophytes could have entered plants via other routes [28,29].
The finding of much greater α-biodiversity in the root endosphere was to be expected; on average OTUs’ richness was 17 times greater in the rhizosphere samples, with 1360 OTUs per sample. This greater richness complies with a prominent (7% on average) share of the sequence reads, not attributed below the domain level, in the rhizosphere bacteriobiome and a negligible share in the root one.
Mineral fertilization for many years has been one of the most common fertilization practices for producing tomatoes both in protected conditions and in open fields. We showed that such fertilization can change the rhizosphere and root bacteriobiome taxonomic profile, albeit mostly affecting minor or rare taxa. We want to emphasize that we did not correct for multiple comparisons, mainly because our goal was to examine if simple NPK fertilization may bring about some microbiome changes and indicate putative taxa worth focusing attention on in further research.
Our finding that Sphingomonas sp./Sphingomonadaceae/Sphingomonadales/Alphaproteobacteria was 1.5 times more abundant in roots under mineral fertilization implies its role in promoting plants’ performance under fertilization: for instance, some endophytic representatives of the genus, producing gibberellins and indole-acetic acid, were shown to promote tomato growth [33]. Some other representatives of the genus seem to be associated with tomato: novel Sphingomonas species was recently isolated from the soil of a tomato garden [34].
Our finding that a Bacteroidetes species, namely Chryseobacterium sp./Weeksellaceae/Flavobacteriales/Flavobacteriia, increased its abundance due to fertilization, suggests the beneficial effect of fertilization: for instance, a representative of the Chryseobacterium was reported to be able to act as a biocontrol agent and a bio-fertilizer [35], and flavobacterial genome was far more abundant in the rhizosphere microbiome of the tomato plants resistant to the soil-borne pathogen Ralstonia solanacearum as compared with that of the susceptible plant [36].
Notably, one of the root bacteriobiome OTUs, namely Clavibacter sp., being the ultimate dominant in the roots in our study, seemed to decrease its abundance due to fertilization, although the decrease was not statistically significant (Fisher’s LSD test, p = 0.19). The finding that this OTU was not even detected in the rhizosphere bacteriobiome strongly suggests that this endophyte is not soil-derived, which implies another route for the bacterium to colonize and proliferate in the root endosphere: indeed, C. michiganensis subsp. michiganensis was shown to invade tomato fruits and seeds through multiple entry routes [37]. Additionally, the majority of healthy root bacteria could be tracked from the soil, and only a very small portion could be tracked from the soil for diseased samples, as it was shown by Dastogeer et al. (2022) [38]. It is highly likely that in our study, the detected Clavibacter OTU represented the infamous pathogen C. michiganensis subsp. michiganensis, causing often devastating bacterial canker [39,40]: we observed some specific, albeit weakly manifested, disease symptoms, i.e., unilateral leaf wilting, scarce stem canker, and bird’s-eye lesions on fruit in our experimental plants, although fruit yield per plant was similar to the values reported earlier for tomato plants grown in the open field in the same region [41]. Strictly speaking, however, one cannot be fully sure about the pathogenic nature of the Clavibacter sp., first-ranked in the relative abundance in the root bacteriobiome in our study, since (a) the metagenome-based pathogen identification at the strain level cannot be achieved because of the challenges inherent to assigning reads to specific strains [42], and (b) based on comparative genomics and phylogenetic analyses several novel species within the genus Clavibacter were suggested [43], including nonpathogenic tomato-associated strains, belonging to the C. michiganensis clade [44]. Yet, we cannot help but note that our result about the Clavibacter prevalence in the root bacteriobiome and its apparent decrease due to fertilization suggests the possibility of improving plant performance by supplying with extra macronutrients and hence boosting plants’ immunity and defense against pathogens. Besides that, as some of the species from the Sphingomonas genus have been noted to improve plant growth during stress conditions such as drought, salinity, and heavy metals in agricultural soil [45], in our study, it could also help the plants stressed by a pathogen. We should add that the incidence of the visual disease manifestations was rather low, and since we did not expect any such damage to be substantial, we did not record all such data in a reportable form; it seems that high variation in the growth and production characteristics of the fertilized plants might have resulted from the plants’ differential response to the putative pathogen.
Our finding that mineral fertilization affected the relative abundance of only one dominant (a) representative of Acidobacteria_Gp6) and several dozens of minor or rare OTUs of the rhizosphere bacteriobiome suggests two things: (a) that, despite the relatively short growing period, stimulation of tomato plants growth and production by fertilization also somewhat changed their rhizodeposition profile, bringing shifts in bacterial populations attracted by the rhizodeposition; and (b) that under the experimental conditions of our study the key taxa of the rhizosphere bacteriobiome were rather stable, and microbiota fine-tuning was effected by minor or rare members.
The fact that we did not detect any archaea in tomato roots complies with the general view that archaea are less abundant and diverse in association with eukaryotic hosts [46]: the primers we used, albeit not specific for archaea, usually render from several to dozens of archaeal sequences, especially from the environments where they are usually present, such as soil.

4.2. Rhizosphere and Root Mycobiome

Our finding that tomato root and rhizosphere mycobiome was dominated by Ascomycota and Basidiomycota phyla once again confirms their role as major players in diverse environments, ranging from the soil and subsoil [31] to plants [2], from the deep-sea sediments [47] and water [48] to the air [49]. However, the fact that the root mycobiome in our study was almost exclusively composed of these two phyla does not seem common for endophytic fungal communities, for which more diverse phyla profiles were reported [50].
Increased fertilization abundance of Plectosphaerella plurivora in the rhizosphere mycobiome in our study might be due to the increased attractiveness of the fertilized plants’ roots for the pathogenic strains of the fungus [51], as members of the Plectosphaerella genus can be found in various habitats, including plants [52] and soil, are pathogens [53], causing large losses in agriculture. However, some strains can be beneficial for plants, for instance, by attacking plant-parasitic nematodes [54]. Thus, it is difficult to speculate about a putative ecophysiological mechanism and significance of more abundant P. plurivora under mineral fertilization.
As for the NPK-increased abundance of Fusarium domesticum, its detection in the rhizosphere soil is rather unexpected, as Fusarium domesticum is usually found as a part of the specific cheese surface microbiota [55], and we did not manage to find any reports about the fungus detection in the soil in general and tomato rhizosphere soil in particular. The Fusarium genus is versatile, distributed worldwide in soil, aquatic and semiaquatic environments, stored grain, and natural products, and its members are mostly pathogenic [56].
This study showed that mineral NPK fertilization can shift mycobiome towards the enhanced presence of pathogenic fungi in the rhizosphere. However, the fact that in our study, these fungi were not even detected inside roots suggests that (a) the longevity of the growth/fertilization period was not enough for the fungi to colonize and establish themselves inside roots, or (b) they lack such ability, being common soil commensals.
The fact that tomato phytomass production characteristics showed high variation due to the mineral NPK fertilization thus decreasing the statistical significance of the apparent increase, which we fully expected to be significant at the conventional rate for vegetable crops in the country, may have resulted from the plants’ need to control and fight-off the bacterial pathogen. Therefore, the fact that we did not focus on and specifically record the incidence of disease manifestations, albeit seemingly scarce to attract serious attention, we regard as a drawback of the study.
The positive aspect is the fact that we studied root-associated microbiomes of tomato plants grown in the real-world environment in the soil with known genesis and history of agricultural use, with its properties measured and described, as all those provide a detailed set of environmental variables that shall be helpful in meta-analytical attempts to obtain better insights into the factors shaping tomato plant-associated microbiota and its effect on tomato fruit quantity and quality.

5. Conclusions

The results of our study showed very distinct microbiomes around and inside tomato roots. These distinct microbiome patterns, especially in terms of α-biodiversity, were to be expected due to the higher versatility of environmental niches in the rhizosphere, not so narrowly specific and prohibiting as in the endosphere: for instance, bacterial species richness was an order of magnitude higher in the rhizosphere than in the root endosphere. Yet tomato hosts a rather diverse root-associated microbiome composed of dozens of bacterial and fungal species, not all of them originating from rhizosphere soil. Our finding that root bacteriobiome responded to conventional mineral NPK fertilization already at the high taxonomic level (class), and at the dominant ones at that, illustrates very well the role of NPK-changed plant metabolism in shaping endophytic microbiota and hence fertilization potential in mitigating plant pathogens. We did not examine different rates of NPK fertilization as separate treatments/factor levels in our study, but we believe that using such gradient in further research may bring a more detailed understanding of how to modify and even fine-tune phytobiomes in order to enhance crops’ health and yields.
As for the rhizosphere bacteriobiome, the finding of only one minor dominant bacterial OTU, decreasing its presence by 0.5% due to mineral fertilization, indicates the robustness of the rhizosphere bacteriobiome, most likely because of the much more diverse and open microenvironment, where stronger forces are needed to cause greater shifts.
Root bacteriobiome and mycobiome differed in their response to mineral fertilization, most likely due to (a) different mechanisms of tomato roots’ control of bacterial and fungal endophytes and (b) greater recalcitrance of fungal hyphae inside plants to any changes.
Knowledge about the fertilizer-induced microbiome shifts in tomato cultivating systems opens a window of opportunity for designing fertilizers targeted at supporting high quantity and quality of yield. This research field seems rather exciting, albeit agronomically and ecologically may turn out to be strongly contextual.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae8111051/s1, Table S1 Climate (as averaged 1991–2000, available online: https://meteoinfo.ru/climatcities?p=1930, accessed on 31 October 2022) characteristics of the region where the experiment was performed; Table S2: Soil (Phaeozem) properties at the experimental site in the south of West Siberia, mean ± standard deviation.

Author Contributions

Conceptualization, N.N.; methodology, N.N. and M.K.; software, M.K.; validation, O.B. and T.N.; formal analysis, O.B.; investigation, T.N.; resources, M.K.; data curation, N.N., T.N. and O.B.; writing—original draft preparation, N.N.; writing—review and editing, N.N. and M.K.; visualization, T.N.; supervision, M.K.; project administration, M.K.; funding acquisition, M.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by THE MINISTRY OF SCIENCE AND HIGHER EDUCATION OF THE RUSSIAN FEDERATION, projects 121031700309-1 and 121031300042-1.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The sequence read data reported in this study were submitted to the NCBI Short Read Archive under bioproject accession number PRJNA887478: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA887478/ Accessed on 1 November 2022.

Acknowledgments

The authors are very thankful to Galina A. Bugrovskaya for her technical assistance with handling soil samples and performing soil analyses.

Conflicts of Interest

The authors declare no conflict 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.

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Horticulturae 08 01051 g001 550
Figure 1. The relative abundance of bacterial phyla in the rhizosphere (only dominants (a)) and roots (all phyla (b)) of tomato plants grown under different fertilization on Phaeozem in the open field in the south of West Siberia. Squares denote means, boxes denote standard errors, and whiskers denote standard deviations. A taxon was considered dominant if its relative abundance was ≥1.0%.
Figure 1. The relative abundance of bacterial phyla in the rhizosphere (only dominants (a)) and roots (all phyla (b)) of tomato plants grown under different fertilization on Phaeozem in the open field in the south of West Siberia. Squares denote means, boxes denote standard errors, and whiskers denote standard deviations. A taxon was considered dominant if its relative abundance was ≥1.0%.
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Figure 2. The relative abundance of fungal phyla in the rhizosphere (only dominants (a)) and roots (all phyla (b)) of tomato plants grown under different fertilization on Phaeozem in the open field in the south of West Siberia. Squares denote means, boxes denote standard errors, and whiskers denote standard deviations. A taxon was considered dominant if its relative abundance was ≥1.0%.
Figure 2. The relative abundance of fungal phyla in the rhizosphere (only dominants (a)) and roots (all phyla (b)) of tomato plants grown under different fertilization on Phaeozem in the open field in the south of West Siberia. Squares denote means, boxes denote standard errors, and whiskers denote standard deviations. A taxon was considered dominant if its relative abundance was ≥1.0%.
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Table
Table 1. The relative abundance (%, mean ± standard deviation) of the dominant bacterial taxa in the rhizosphere and roots of tomato plants, grown under different fertilization on Phaeozem in the open field in the south of West Siberia (a taxon was considered dominant if its relative abundance was ≥1.0%).
Table 1. The relative abundance (%, mean ± standard deviation) of the dominant bacterial taxa in the rhizosphere and roots of tomato plants, grown under different fertilization on Phaeozem in the open field in the south of West Siberia (a taxon was considered dominant if its relative abundance was ≥1.0%).
TaxonRhizosphereRoots
NoNPKNoNPK
Class level
Actinobacteria13.8 ± 3.418.5 ± 8.343.8 ± 16.633.6 ± 6.7
Alphaproteobacteria11.5 ± 2.613.8 ± 3.428.6 ± 6.8 a 141.9 ± 6.3 b
Thermoleophilia8.4 ± 0.97.0 ± 2.90.03 ± 0.040.01 ± 0.01
Bacilli7.8 ±1.17.3 ± 2.20.3 ± 0.60.0 ± 0.1
Acidimicrobiia7.8 ± 1.06.8 ± 1.9n.d.2n.d.
un. 3 Actinobacteria5.9 ± 1.04.9 ± 2.30.1 ± 0.10.0 ± 0.0 2
Clostridia5.7 ± 1.14.3 ± 1.80.1 ± 0.10.0 ± 0.0
Acidobacteria_Gp65.4 ± 0.94.1 ± 1.6n.d.n.d.
Gammaproteobacteria1.9 ± 0.63.0 ± 1.59.0 ± 5.47.6 ± 4.2
Betaproteobacteria4.7 ± 1.04.5 ± 1.39.4 ± 8.26.7 ± 1.7
Deltaproteobacteria2.6 ± 0.42.7 ± 0.7n.d.n.d.
Anaerolineae1.3 ± 0.50.8 ± 0.6n.d.n.d.
Caldilineae1.2 ± 0.20.9 ± 0.3n.d.n.d.
Cytophagia0.9 ± 0.21.1 ± 0.76.9 ± 3.85.7 ± 3.3
Flavobacteriia0.4 ± 0.11.6 ± 2.81.3 ± 1.0 a3.6 ± 1.4 b
Order level
Micrococcales4.9 ± 4.07.4 ± 6.040.8 ± 16.631.8 ± 6.1
Rhizobiales8.8 ± 2.29.5 ± 2.616.8 ± 7.224.0 ± 4.0
Bacillales7.8 ± 1.17.3 ± 2.20.6 ± 0.30.04 ± 0.07
Acidimicrobiales7.8 ± 1.06.8 ± 1.9n.d.n.d.
Gaiellales6.0 ± 0.94.6 ± 1.9n.d.n.d.
Acidobacteria_Gp65.4 ± 0.94.1± 1.6n.d.n.d.
Clostridiales5.2 ± 1.03.9 ± 1.50.00 ± 0.010.00 ± 0.00
Sphingomonadales0.3 ± 0.20.6 ± 0.411.2 ± 1.0 a17.4 ± 3.9 b
Burkholderiales1.7 ± 0.41.6 ± 0.59.4 ± 8.26.7 ± 1.7
Pseudomonadales0.1 ± 0.20.1 ± 0.28.1 ± 5.17.3 ± 4.3
Cytophagales0.9 ± 0.21.1 ± 0.76.9 ± 3.85.7 ± 3.3
Kineosporialesn.d.n.d.2.1 ± 1.51.1 ± 0.6
Flavobacteriales0.4 ± 0.11.6 ± 2.81.3 ± 1.0 a3.6 ± 1.4 b
Family level
Gaiellaceae6.0 ± 0.94.6 ± 1.9n.d.n.d.
Acidobacteria_Gp65.4 ± 0.94.1 ± 1.6n.d.n.d.
un. Rhizobiales5.0 ± 0.94.7 ± 1.0n.d.n.d.
Ilumatobacteraceae4.3 ± 0.73.5 ± 1.1n.d.n.d.
Micrococcaceae3.6 ± 3.43.7 ± 3.60.3 ± 0.30.0 ± 0.0
Hyphomicrobiaceae2.9 ± 0.72.4 ± 0.5n.d.n.d.
Acidobacteria_Gp162.2 ± 0.72.5 ± 1.1n.d.n.d.
Iamiaceae2.2 ± 0.22.0 ± 0.5n.d.n.d.
Planococcaceae1.7 ± 0.41.6 ± 0.5n.d.n.d.
Bacillaceae11.6 ± 0.11.3 ± 0.5n.d.n.d.
Nocardioidaceae1.6 ± 1.44.9 ± 4.80.1 ± 0.20.03 ± 0.03
Caldilineaceae1.2 ± 0.20.9 ± 0.3n.d.n.d.
Paenibacillaceae11.0 ± 0.11.0 ± 0.40.03 ± 0.040.01 ± 0.01
Clostridiaceae11.0 ± 0.20.8 ± 0.4n.d.n.d.
Rhodobacteraceae1.0 ± 0.21.9 ± 1.10.2 ± 0.20.1 ± 0.1
Microbacteriaceae0.5 ± 0.31.6 ± 1.940.0 ± 17.131.6 ± 6.2
Sphingomonadaceae0.2 ± 0.10.4 ± 0.211.2 ± 1.0 a17.1 ± 3.5 b
Methylobacteriaceae0.1 ± 0.20.1 ± 0.38.9 ± 4.013.4 ± 5.0
Pseudomonadaceae0.1 ± 0.20.1 ± 0.28.1 ± 5.17.3 ± 4.3
Oxalobacteraceae0.04 ± 0.030.10 ± 0.116.7 ± 7.43.5 ± 0.7
Hymenobacteraceae0.2 ± 0.10.1 ± 0.16.4 ± 3.45.1 ± 3.1
Rhizobiaceaen.d.n.d.4.5 ± 1.84.4 ± 1.9
Aurantimonadaceaen.d.n.d.3.2 ± 2.15.9 ± 3.2
Comamonadaceaen.d.n.d.2.7 ± 1.43.2 ± 1.2
Kineosporiaceaen.d.n.d.2.1 ± 1.51.1 ± 0.6
Weeksellaceae0.01 ± 0.010.01 ± 0.001.3 ± 1.0 a3.6 ± 1.4 b
Genus level
Gaiella6.0 ± 0.94.6 ± 1.9n.d.n.d.
Acidobacteria_Gp65.8 ± 1.04.3 ± 1.7n.d.n.d.
un. Rhizobiales5.0 ± 0.94.7 ± 1.00.1 ± 0.20.0 ± 0.0
Clavibactern.d.n.d.36.3 ±18.823.9 ± 6.2
Sphingomonas0.1 ± 0.10.2 ± 0.111.1 ± 1.0 a17.1 ± 3.4 b
Methylobacteriumn.d.n.d.8.9 ± 4.013.4 ± 5.0
Pseudomonas0.1 ± 0.20.1 ± 0.28.1 ± 5.17.3 ± 4.3
Massilian.d.n.d.6.6 ± 7.43.5 ± 0.6
Hymenobactern.d.n.d.6.4 ± 3.45.1 ± 3.1
Agrobacteriumn.d.n.d.4.5 ± 1.84.4 ± 1.9
Aureimonasn.d.n.d.3.2 ± 2.15.9 ± 3.2
Rathayibactern.d.n.d.2.9 ± 1.8 a6.3 ± 3.5 b
un. 2 Comamonadaceae0.2 ± 0.10.2 ± 0.22.7 ± 1.33.2 ± 1.2
Kineococcusn.d.n.d.1.9 ± 1.51.0 ± 1.2
Chryseobacteriumn.d.n.d.1.3 ± 1.0 a3.6 ± 1.4 b
1 Values in rows, followed by different letters, differ significantly (p ≤ 0.05, Fisher’s LSD test). The absence of letters indicates no difference. 2 n.d. stands for “not detected”, meaning that not a single sequence was found, whereas zero values mean that the respective sequences were found, but in numbers much less than 3 un. stands for unclassified.
Table
Table 2. The relative abundance (%, mean ± standard deviation) of the dominant bacterial OTUs in the rhizosphere and roots of tomato plants grown under different fertilization on Phaeozem in the open field in the south of West Siberia (An OTU was considered dominant if its relative abundance was ≥1.0%).
Table 2. The relative abundance (%, mean ± standard deviation) of the dominant bacterial OTUs in the rhizosphere and roots of tomato plants grown under different fertilization on Phaeozem in the open field in the south of West Siberia (An OTU was considered dominant if its relative abundance was ≥1.0%).
No.OTURhizosphereRoots
NoNPKNoNPK
4Clavibacter sp.n.d. 1n.d.36.3 ± 18.823.9 ± 6.2
7Pseudarthrobacter3.6 ± 3.43.6 ± 3.5n.d. 1n.d.
9Sphingomonas sp.n.d.n.d.7.2 ± 3.07.4 ± 3.5
15Methylobacterium sp.n.d.n.d.8.4 ± 4.413.1 ± 4.9
16Aureimonas sp.n.d.n.d.2.9 ± 2.24.9 ± 3.8
26Pseudomonas sp.n.d.n.d.6.5 ± 3.16.5 ± 3.2
27un. 2 Rhizobiales3.6 ± 0.63.0 ± 0.6n.d.n.d.
28Agrobacterium sp.n.d.n.d.4.5 ± 1.84.4 ± 1.9
29Rathayibacter sp.n.d.n.d.2.9 ± 1.8 a 36.3 ± 3.5 b
31Chryseobacterium sp.n.d.n.d.1.2 ±1.0 a3.6 ± 1.4 b
43Sphingomonas sp.n.d.n.d.0.9 ± 1.0 a3.4 ± 1.5 b
56un. Hyphomicrobiaceae1.5 ± 0.31.3 ± 0.3n.d.n.d.
57un. Actinobacteria2.2 ± 0.51.5 ± 0.9n.d.n.d.
58Sphingomonas sp.n.d.n.d.1.6 ± 1.0 a4.3 ± 1.2 b
60un. Comamonadaceaen.d.n.d.2.1 ±1.01.8 ± 0.5
65Kineococcus sp.n.d.n.d.1.9 ± 1.51.0 ± 0.5
68Massilia sp.n.d.n.d.6.6 ± 7.43.5 ± 0.6
84un. Acidobacteria_Gp61.6 ± 0.3 b1.1 ± 0.2 an.d.n.d.
88un. Gaiella1.7 ± 0.21.3 ± 0.8n.d.n.d.
95un. Nocardioides0.5 ± 0.41.5 ± 1.4n.d.n.d.
101Hymenobacter sp.n.d.n.d.5.0 ± 4.03.7 ± 2.9
107un. Actinobacteria1.3 ± 0.30.9 ± 0.4n.d.n.d.
122un. Nocardioides0.4 ± 0.41.2 ± 1.1n.d.n.d.
188un. Desertimonas1.0 ± 0.20.7 ± 0.3n.d.n.d.
1027Gaiella occulta1.0 ± 0.20.8 ± 0.2n.d.n.d.
1099Hymenobacter sp.n.d.n.d.1.0 ± 1.00.6 ± 0.4
3987Sphingomonas sp.n.d.n.d.1.0 ± 0.71.4 ± 0.9
6043Aureimonas sp.n.d.n.d.0.3 ± 0.31.0 ± 1.3
1 n.d. stands for “not detected”. 2 un. stands for unclassified. 3 Values in rows, followed by different letters, differ significantly (p ≤ 0.05, Fisher’s LSD test). The absence of letters indicates no difference.
Table
Table 3. Alpha-biodiversity indices (mean ± standard deviation) of the rhizosphere and root bacteriobiome of tomato plants grown in the open field in the south of West Siberia.
Table 3. Alpha-biodiversity indices (mean ± standard deviation) of the rhizosphere and root bacteriobiome of tomato plants grown in the open field in the south of West Siberia.
TaxonRhizosphereRoots
NoNPKNoNPK
Richness1338 ± 1671381 ± 20390 ± 4776 ± 13
Chao-11909 ± 2181923 ± 234100 ± 4284 ± 15
Simpson (1-D)0.99 ± 0.000.99 ± 0.000.80 ± 0.130.89 ± 0.03
Shannon6.0 ± 0.26.0 ± 0.22.4 ± 0.62.7 ± 0.1
Evenness0.31 ± 0.000.29 ± 0.040.14 ± 0.030.21 ± 0.03
Equitability0.84 ± 0.010.83 ± 0.020.55 ± 0.090.63± 0.02
Dominance (D)0.01 ± 0.000.01 ± 0.000.20 ± 0.130.11 ± 0.03
Berger-Parker0.05 ± 0.010.05 ± 0.020.36 ± 0.190.24 ± 0.06
Table
Table 4. The relative abundance (%, mean ± standard deviation) of the dominant fungal taxa in the rhizosphere and roots of tomato plants, grown under different fertilization on Phaeozem in the open field in the south of West Siberia (a taxon was considered dominant if its relative abundance was ≥1.0%).
Table 4. The relative abundance (%, mean ± standard deviation) of the dominant fungal taxa in the rhizosphere and roots of tomato plants, grown under different fertilization on Phaeozem in the open field in the south of West Siberia (a taxon was considered dominant if its relative abundance was ≥1.0%).
TaxonRhizosphereRoots
NoNPKNoNPK
Class level
Tremellomycetes3.0 ± 3.91.7 ± 0.755.6 ± 16.357.3 ± 26.7
Dothideomycetes13.4 ± 7.920.1 ± 1.634.3 ± 17.830.3 ± 24.8
Microbotryomycetes0.3 ± 0.20.3 ± 0.14.0 ± 3.01.6 ± 1.1
Cystobasidiomycetes0.05 ± 0.030.09 ± 0.121.1 ± 1.60.3 ± 0.3
Leotiomycetes8.2 ± 1.45.5 ± 3.10.1 ± 0.10.4 ±0.6
Sordariomycetes42.6 ± 6.244.8 ± 7.10.1 ± 0.31.1 ± 2.4
Pezizomycetes4.5 ± 1.33.6 ± 0.9n.d. 1n.d.
Eurotiomycetes3.0 ± 0.62.5 ± 0.90.003 ± 0.0020.04 ± 0.04
Agaricomycetes3.6 ± 3.52.0 ± 0.90.1 ± 0.10.02 ± 0.02
Aphelidiomycetes1.0 ± 0.60.6 ± 0.5n.d.n.d.
Order level
Tremellales0.7 ± 0.50.8 ± 0.451.9 ± 14.853.4 ± 24.6
Pleosporales4.0 ± 1.713.0 ± 11.221.3 ± 12.223.1 ± 24.0
Capnodiales0.8 ± 1.81.8 ± 3.712.6 ± 8.36.9 ± 3.7
Cystofilobasidiales0.3 ± 0.20.2 ± 0.13.7 ± 2.73.9 ± 4.2
Leucosporidiales0.05 ± 0.080.01 ± 0.003.2 ± 3.01.1 ± 0.9
Cystobasidiomycetes_is0.004 ± 0.0030.01 ± 0.011.0 ± 1.60.2 ± 0.1
Helotiales7.2 ± 1.24.3 ± 2.80.1 ± 0.10.4 ± 0.6
Glomerellales0.5 ± 0.31.0 ± 0.30.0 ± 0.0 11.1 ± 2.4
Hypocreales13.0 ± 2.219.1 ± 9.10.1 ± 0.30.001 ± 0.002
Microascales15.7 ± 5.910.0 ± 5.7n.d.n.d.
Mortierellales4.0 ± 1.25.1 ± 6.6n.d.n.d.
Pezizales4.3 ± 1.43.5 ±0.9n.d.n.d.
Sordariales4.4 ± 1.53.1 ±1.60.01 ± 0.000.01 ± 0.00
Sordariomycetidae_is 25.2 ± 0.78.9 ±4.0n.d.n.d.
Dothideomycetes_is4.4 ± 1.63.5 ± 2.2n.d.n.d.
Eurotiales1.7 ± 0.71.7 ± 1.1n.d.n.d.
Agaricales2.3 ± 3.40.5 ± 0.20.01 ± 0.010.01 ± 0.01
Coniochaetales2.0 ± 0.41.4 ± 1.0n.d.n.d.
Onygenales1.1 ± 0.50.6 ± 0.4n.d.n.d.
Family level
Pleosporaceae0.2 ± 0.11.8 ± 3.117.4 ± 12.020.7 ± 22.4
un. Tremellales0.0 ± 0.00.0 ± 0.015.9 ± 7.623.1 ± 13.2
Tremellaceae0.5 ± 0.40.5 ± 0.214.9 ± 17.78.0 ± 6.2
Bulleribasidiaceae0.2 ± 0.30.3 ± 0.514.4 ± 10.117.7 ± 16.1
Mycosphaerellaceae0.8 ± 1.81.8 ± 3.712.6 ± 8.36.9 ± 3.7
Tremellales_is0.0 ± 0.00.0 ± 0.06.4 ± 4.34.3 ± 5.8
Cystofilobasidiaceae0.2 ± 0.20.1 ± 0.14.1 ± 2.73.6 ± 4.1
Leucosporidiaceae0.0 ± 0.10.0 ± 0.03.6 ± 3.01.1 ± 0.9
Symmetrosporaceae0.0 ± 0.00.0 ± 0.02.1 ± 1.60.1 ± 0.1
Phaeosphaeriaceae0.1 ± 0.10.0 ± 0.00.9 ± 0.80.7 ± 0.5
Sclerotiniaceae1.0 ± 0.50.8 ± 0.50.0 ± 0.00.0 ± 0.0
Microascaceae10.2 ± 3.67.0 ± 3.5n.d.n.d.
Nectriaceae6.2 ± 1.29.3 ± 5.20.03 ± 0.080.00 ± 0.00
Plectosphaerellaceae5.5 ± 0.9 a 39.9 ± 3.9 b0.0 ± 0.01.1 ± 2.4
Mortierellaceae3.9 ± 1.25.1 ± 6.6n.d.n.d.
Pseudeurotiaceae2.9 ± 1.12.3 ±1.5n.d.n.d.
Psathyrellaceae1.9 ± 3.40.3 ± 0.10.01 ± 0.010.01 ± 0.00
Ascodesmidaceae1.9 ± 0.61.4 ± 0.9n.d.n.d.
Clavicipitaceae1.7 ± 1.00.9 ± 0.70.00 ± 0.000.00 ± 0.00
Trichosporonaceae1.6 ± 3.50.4 ± 0.5n.d.n.d.
Lasiosphaeriaceae1.6 ± 0.5 b 30.8 ± 0.5 an.d.n.d.
Chaetomiaceae1.6 ± 0.51.7 ± 0.60.01 ± 0.000.01 ± 0.00
Pyronemataceae1.5 ± 0.90.9 ± 0.4n.d.n.d.
Aspergillaceae0.7 ± 0.31.2 ± 1.2n.d.n.d.
Didymellaceae1.0 ± 0.68.8 ± 11.92.1 ±1.71.0 ± 0.8
Trichocomaceae1.0 ± 0.50.5 ± 0.4n.d.n.d.
Sclerotiniaceae1.0 ± 0.50.8 ± 0.60.00 ± 0.000.00 ± 0.00
un. 4 GS161.0 ± 0.50.6 ± 0.5n.d.n.d.
Ascobolaceae0.8 ± 0.41.0 ± 0.4n.d.n.d.
Genus level
Alternaria0.01 ± 0.011.6 ± 3.217.3 ±12.020.7 ± 22.4
un. Tremellales0.00 ± 0.000.00 ± 0.0015.9 ± 7.623.1 ± 13.2
Cryptococcus0.5 ± 0.40.5 ± 0.214.2 ± 17.97.4 ± 5.9
Vishniacozyma0.2 ± 0.40.3 ± 0.513.9 ± 10.117.2 ± 16.4
Davidiella0.8 ± 1.81.8 ± 3.712.4 ± 8.36.8 ± 3.7
Dioszegia0.00 ± 0.000.00 ± 0.016.9 ± 4.74.8 ± 6.3
Cystofilobasidium0.00 ± 0.000.00 ± 0.003.6 ± 2.73.6 ± 4.1
Leucosporidium0.01 ± 0.010.01 ± 0.003.2 ± 3.01.1 ± 0.9
un. Didymellaceae0.2 ± 0.20.4 ± 0.41.3 ± 1.60.7 ± 0.5
Botryotinia1.0 ± 0.50.8 ± 0.60.0 ± 0.00.0 ± 0.0
Lectera0.3 ± 0.20.3 ± 0.20.0 ± 0.01.1 ± 2.4
Wardomyces5.2 ± 2.42.6 ± 2.5n.d.n.d.
Tetracladium4.9 ± 1.42.6 ± 1.7n.d.n.d.
Plectosphaerella4.0 ± 0.8 a8.7 ± 4.0 bn.d.n.d.
Mortierella4.0 ± 1.25.1 ± 6.6n.d.n.d.
Gibberella3.7 ± 1.16.1 ± 4.60.0 ± 0.10.0 ± 0.0
Pseudogymnoascus1.9 ± 1.11.7 ± 1.1n.d.n.d.
Metarhizium1.6 ± 1.00.8 ± 0.6n.d.n.d.
Apiotrichum1.6 ± 3.50.4 ± 0.5n.d.n.d.
Parasola1.5 ± 3.30.0 ± 0.0n.d.n.d.
Cephaliophora1.4 ± 0.51.1 ± 0.8n.d.n.d.
Gibellulopsis1.1 ± 0.30.9 ± 0.2n.d.n.d.
Dokmaia1.1 ± 0.61.8 ± 0.50.0 ± 0.10.0 ± 0.0
un. GS161.0 ± 0.60.6 ± 0.5n.d.n.d.
Didymella0.5 ± 0.58.3 ± 12.00.2 ± 0.40.5 ± 0.5
Fusarium0.7 ± 0.3 a2.0 ± 1.1 b0.000 ± 0.0010.000 ± 0.001
Penicillium0.6 ± 0.41.2 ± 1.2n.d.n.d.
Emericellopsis1.0 ± 0.90.8 ± 0.7n.d.n.d.
Ascobolus1.0 ± 0.40.7 ± 0.3n.d.n.d.
1 n.d. stands for not detected, and 0.0 values mean that there were some sequences detected, but their relative abundance was extremely low. 2 “_is” stands for incertae sedis. 3 Values in rows, followed by different letters, differ significantly (≤0.05, Fisher’s LSD test). The absence of letters indicates no difference. 4 un. stands for unclassified.
Table
Table 5. The relative abundance (%, mean ± standard deviation) of the dominant fungal OTUs in the rhizosphere and roots of tomato plants grown under different fertilization on Phaeozem in the open field in the south of West Siberia (an OTU was considered dominant if its relative abundance was ≥1.0%).
Table 5. The relative abundance (%, mean ± standard deviation) of the dominant fungal OTUs in the rhizosphere and roots of tomato plants grown under different fertilization on Phaeozem in the open field in the south of West Siberia (an OTU was considered dominant if its relative abundance was ≥1.0%).
No.OTURhizosphereRoots
NoNPKNoNPK
1un. 1 Alternaria0.0 ± 0.0 21.5 ± 3.05.8 ± 12.119.7 ± 21.7
2un. Tremellalesn.d. 2n.d.11.9 ± 7.817.3 ± 12.5
3un. Ascomycota3.9 ± 7.01.1 ± 1.44.1 ± 2.08.4 ± 7.4
4Davidiella sp.0.8 ± 1.81.8 ± 3.712.4 ± 8.36.8 ± 3.7
7Vishniacozyma victoriaen.d. 2n.d.6.4 ± 2.613.9 ± 13.8
8Cryptococcus sp.n.d.n.d.9.0 ± 19.10.3 ±0.6
10Dioszegia crocean.d.n.d.6.2 ± 4.44.3 ± 5.8
13un. Tremellalesn.d.n.d.3.9 ± 2.55.7 ± 4.1
14Phoma exigua0.5 ± 0.58.3 ± 11.9n.d.n.d.
15Gibberella sp.2.0 ± 0.72.2 ± 1.8n.d.n.d.
18Cystofilobasidium maceransn.d.n.d.2.6 ± 1.23.8 ± 1.7
19Plectosphaerella cucumerina2.5 ± 0.53.0 ± 0.4n.d.n.d.
21Mortierella minutissima3.1 ± 1.04.8 ± 6.7n.d.n.d.
24Leucosporidium sp.n.d.n.d.3.2 ± 2.91.0 ± 0.9
25un. Hypocreales2.1 ± 2.31.1 ±0.6n.d.n.d.
27un. Alternaria0.0 ± 0.00.1 ±0.21.3 ±1.40.9 ± 0.7
31Wardomyces inflatus5.1 ± 2.42.6 ± 2.5n.d.n.d.
33Tetracladium sp.1.8 ± 0.51.3 ± 1.0n.d.n.d.
34un. Microascaceae7.1 ± 2.64.4 ± 2.6n.d.n.d.
35un. Ascomycota3.9 ± 3.31.8 ± 0.7n.d.n.d.
39Cryptococcus chernoviin.d.n.d.2.1 ±1.71.7 ±2.0
40Cryptococcus festucosusn.d.n.d.0.5 ± 0.21.6 ± 1.8
46Dokmaia monthadangii1.0 ± 0.61.7 ± 0.5n.d.n.d.
47Tetracladium maxilliforme2.8 ± 1.21.1 ± 0.9n.d.n.d.
57Botryotinia sp.1.0 ± 0.50.8 ± 0.60.0 ± 0.00.0 ± 0.0
65Fusarium cerealis1.3 ± 0.61.5 ± 1.3n.d.n.d.
66Gibellulopsis nigrescens1.1 ± 0.30.9 ± 0.2n.d.n.d.
67Cephaliophora sp.1.4 ± 0.51.0 ± 0.7n.d.n.d.
70Metarhizium sp.1.4 ± 1.00.7 ± 0.5n.d.n.d.
76un. Dothideomycetes1.1 ± 0.51.1 ± 0.8n.d.n.d.
78Pseudogymnoascus sp.1.0 ± 0.31.1 ± 0.6n.d.n.d.
82Cryptococcus tephrensis0.0 ± 0.00.1 ±0.11.9 ± 2.22.3 ± 2.4
85un. Hypocreales0.0 ± 0.13.0 ± 5.6n.d.n.d.
89Ascobolus sp.0.7 ± 0.31.0 ± 0.4n.d.n.d.
90un. Coniochaetales1.0 ± 0.30.9 ± 0.7n.d.n.d.
101Apiotrichum dulcitum1.6 ± 3.50.4 ± 0.5n.d.n.d.
103Emericellopsis microspora0.8 ± 0.71.0 ± 0.9n.d.n.d.
118Symmetrospora coprosmaen.d.n.d.1.0 ± 1.60.2 ± 0.1
142Fusarium domesticum0.2 ± 0.2 a31.1 ± 1.1 bn.d.n.d.
152Lectera capsica0.3 ± 0.20.3 ±0.20.0 ± 0.01.1 ± 2.4
175Plectosphaerella plurivora1.4 ± 0.5 a5.1 ± 3.7 bn.d.n.d.
190Parasola kuehneri1.5 ± 3.30.0 ± 0.0n.d.n.d.
643Vishniacozyma heimaeyensis0.2 ± 0.30.3 ± 0.57.4 ± 10.13.2 ± 2.5
1095un. Didymellaceae0.2 ± 0.20.4 ± 0.41.3 ± 1.50.7 ± 0.5
3321Cryptococcus magnusn.d.n.d.0.3 ± 0.11.1± 1.3
1 un. stands for unclassified. 2 n.d. stands for no sequences detected, and 0.0 values mean that there were some sequences detected, but their relative abundance was extremely low 3 Values in rows, followed by different letters, differ significantly (≤0.05, Fisher’s LSD test). The absence of letters indicates no difference.
Table
Table 6. Alpha-biodiversity indices (mean ± standard deviation) of the mycobiome in the tomato roots grown under different fertilization on Phaeozem in the open field in the south of West Siberia.
Table 6. Alpha-biodiversity indices (mean ± standard deviation) of the mycobiome in the tomato roots grown under different fertilization on Phaeozem in the open field in the south of West Siberia.
TaxonRhizosphereRoots
NoNPKNoNPK
Richness928 ± 55790 ± 174171 ± 40144 ± 34
Chao-11044 ± 73909 ± 146203 ±52179 ± 40
Simpson (1-D)0.97 ± 0.010.95 ± 0.040.85 ± 0.040.81 ±0.10
Shannon4.8 ± 0.14.4 ±0.72.5 ± 0.22.3 ± 0.4
Evenness0.13 ± 0.020.11 ± 0.040.08 ± 0.010.08 ±0.03
Equitability0.70 ± 0.020.66 ± 0.090.49 ± 0.030.47 ±0.07
Dominance (D)0.03 ± 0.010.04 ± 0.030.15 ± 0.040.19 ±0.10
Berger-Parker0.10 ± 0.030.14 ±0.080.31 ± 0.090.34 ± 0.16
Table
Table 7. Production characteristics of tomato plants grown under different fertilization on Phaeozem in the open field in the south of West Siberia (mean ± standard deviation).
Table 7. Production characteristics of tomato plants grown under different fertilization on Phaeozem in the open field in the south of West Siberia (mean ± standard deviation).
NoNPKp-Value
Fruits, pcs/plant30 ± 1231 ± 160.773
Yield (Y), kg/plant1.28 ± 0.481.65 ± 0.920.312
Average fruit mass, g43 ± 1049 ± 130,261
Aboveground phytomass 1 (A), g/plant224 ± 173340 ± 2750.334
Belowground phytomass (B), g/plant15.6 ± 7.227.8 ± 17.10.226
A/B13.1 ± 6.111.1 ± 6.00.625
Total phytomass, g/plant1.66 ± 0.672.24 ± 1.280.279
1 Without fruit yield.
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Naumova, N.; Baturina, O.; Nechaeva, T.; Kabilov, M. Root and Rhizosphere Microbiome of Tomato Plants Grown in the Open Field in the South of West Siberia under Mineral Fertilization. Horticulturae 2022, 8, 1051. https://doi.org/10.3390/horticulturae8111051

AMA Style

Naumova N, Baturina O, Nechaeva T, Kabilov M. Root and Rhizosphere Microbiome of Tomato Plants Grown in the Open Field in the South of West Siberia under Mineral Fertilization. Horticulturae. 2022; 8(11):1051. https://doi.org/10.3390/horticulturae8111051

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Naumova, Natalia, Olga Baturina, Taisia Nechaeva, and Marsel Kabilov. 2022. "Root and Rhizosphere Microbiome of Tomato Plants Grown in the Open Field in the South of West Siberia under Mineral Fertilization" Horticulturae 8, no. 11: 1051. https://doi.org/10.3390/horticulturae8111051

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