*4.5. Statistical Analysis*

Data from fungal growth analysis and sporulation assay (n = 4) and relative gene expression analysis (n = 3) were subjected to analysis of variance (ANOVA) based on the completely randomized design (CRD). Differences among the treatments were assessed using Tukey's post hoc test at a significance level predetermined at *p* ≤ 0.05. All statistical analyses were performed using SPSS Statistics for Windows, v.25 (IBM Corp., Armonk, NY, USA). For the functional analysis, the Statistical Analysis of Metagenomic Profiles (STAMP) [115] software was used to provide a statistical view of differences in abundant features. The data were subjected to analysis of variance (ANOVA) and differences among the treatments were assessed using Tukey–Kramer post hoc test at a significance level at *p* ≤ 0.05.

### **5. Conclusions**

This is the first attempt to better understand the plant–microbiome interactions in the presence of biosolid application and the biocontrol mechanism against Forl in tomato plants. More specifically, the effect of biosolid application on the biocontrol of Forl was investigated based on the enhanced plant resistance measured as expression of pathogenresponse genes and the pathogen suppression in the context of soil microbiome diversity, abundance, and predicted functions. Plants and rhizosphere microbiome share complex interactions required for optimal root and soil functioning. When this balance is disturbed, changes occur in microbial communities, soil functioning, and soil abiotic properties interactively [106], shaping the resistance potential of plants and the biocontrol of the pathogen. Our results suggest that biosolid application alters microbial diversity and the predicted soil functioning, along with the relative abundance of specific phyla and classes, as a proxy for disease suppression. Further research is required to identify the biochemical and molecular mechanisms of the priming effect induced by the biosolid and specific functional genes associated with bacterial consortia as biological indicators for the identification of the biocontrol potential of biosolid application.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/10 .3390/plants10122789/s1, Figure S1: Rank abundance curves. Abundances of the top 100 OTUs for bacterial communities in: A. Between two time points at 12 and 72 h after inoculation with *Fusarium oxysporum* f. sp. *radicis-lycopersici* and biosolid application. B. amongst the four different treatments control (C), biosolid (B), Forl (F), and Forl and biosolid (FB), Figure S2: Principal Component Analysis (PCA) of the functional diversity for the four different treatments control (C), biosolid application (B), Forl inoculation (F), and Forl inoculation + biosolid application (FB) at 12 and 72 h post inoculation and biosolid application. The different treatments are depicted with different colors and shapes, Figure S3: Post hoc plots for the predicted pathways demonstrating greater abundance of sequences (%) in biosolid-enriched treatments compared to the Control (C) and Forl inoculation + biosolid application (FB) treatments, indicating: (i) the mean proportion of sequences within each treatment, (ii) the difference in mean proportions for each pair of treatments, and (iii) a *p*-value indicating whether the mean proportion is equal for a given pair of treatments. The analysis was performed in the STAMP software using ANOVA with *p*-value ≤ 0.05 and effect size >0.9, Table S1: Relative abundance (%) of bacterial phyla at rate greater than 1%, for the treatments C, B, F, and FB at 12 and 72 h after inoculation with *Fusarium oxysporum* f. sp. *radicis-lycopersici*. Value is the pooled mean of three replicates, Table S2: Relative abundance (%) of bacterial classes at rate greater than 1%, for the treatments C, B, F, and FB at 12 and 72 h after inoculation with *Fusarium oxysporum* f. sp. *radicis-lycopersici*. Value is the pooled mean of three replicates, Table S3: Multiple group statistics table for the predicted functional diversity in the different treatments: Control (C), Biosolid application (B), Forl inoculation (F), and Forl inoculation + biosolid application (FB) based on the abundances of sequences associated with specific metabolic pathways. The analysis was performed in the STAMP software using ANOVA with *p*-value ≤ 0.05 and effect size >0.9. The order of pathways is according to the abundance (%) as indicated in Figure 7.

**Author Contributions:** Conceptualization, A.L.L. and I.N.-O.; methodology, E.S., N.N.K., A.L.L., and I.N.-O.; software, I.K. and E.S.; validation, E.S. and I.K.; formal analysis, E.S. and I.K.; investigation, E.S. (principal investigator), I.G. (principal investigator) and G.L.; resources P.M., I.N.-O., and A.L.L.; data curation, E.S., I.G., and I.K.; writing—original draft preparation, E.S. and I.G.; writing—review and editing, E.S., A.L.L., I.N.-O., C.E. and N.N.K.; visualization, E.S. and I.K.; supervision, P.M., A.L.L., and I.N.-O.; project administration, C.E.; and funding acquisition, C.E., A.K., and I.N.-O. All authors have read and agreed to the published version of the manuscript.

**Funding:** Part of the project was funded by I. Giannakis' PhD Scholarship: European Social Fund— ESF through the Operational Program "Human Resources Development, Education and Lifelong Learning in the context of the project "Strengthening Human Resources Research Potential via Doctorate Research" (MIS-5000432), implemented by the State Scholarships Foundation (IKΥ)".

**Data Availability Statement:** Data is contained within the article or Supplementary Materials.

**Acknowledgments:** The authors are grateful to Ben Lugtenberg, Institute Biology, Leiden University, The Netherlands for providing the isolate of Forl, and EYATH SA for providing biosolids of municipal sludge. All individuals in the Acknowledgments have consented to the acknowledgement.

**Conflicts of Interest:** The authors declare no conflict of interest.
