Celiac Disease (CeD) is a chronic small intestinal immune-mediated enteropathy caused by the ingestion of dietary gluten proteins in genetically susceptible individuals. CeD is one of the most common autoimmune diseases, affecting around 1.4% of the population globally. To date, the only acceptable treatment for CeD is strict, lifelong adherence to a gluten-free diet (GFD). However, in some cases, GFD does not alter gluten-induced symptoms. In addition, strict adherence to a GFD reduces patients’ quality of life and is often a socio-economic burden. This narrative review offers an interdisciplinary overview of CeD pathomechanism and the limitations of GFD, focusing on current research on possible dietary interventions. It concentrates on the recent research on the degradation of gluten through enzymes, the modulation of the microbiome, and the different types of “biotics” strategies, from probiotics to the less explored “viromebiotics” as possible beneficial complementary interventions for CeD management. The final aim is to set the context for future research that may consider the role of gluten proteins and the microbiome in nutritional and non-pharmacological interventions for CeD beyond the sole use of the GFD.

Legumes ( Fabaceae ) form symbiotic associations with rhizobia ( Rhizobiaceae ), but unchecked bacterial proliferation can lead to loss of host fitness. In the Inverted Repeat Lacking Clade (IRLC) legumes, Nodule-specific Cysteine-Rich (NCR) peptides regulate rhizobial differentiation, limiting their pathogenic potential and maintaining a balanced symbiosis that supports plant growth. In planta screening of NCRs is challenging for multiple reasons; hence, bioinformatics prediction from genomic and transcriptomic data offers a high-throughput alternative. In this study, an \textit{in silico} workflow was developed that incorporates established bioinformatics tools with R programming and local BLASTp to identify NCR-like peptides from genomic data. Various R libraries, including packages of the Bioconductor suite, ampir,and dplyr, were used to screen peptides based on specific criteria, such as a length of 20–180 amino acids and at least four cysteine residues. The identified peptides were further analyzed for motif patterns, sequence similarity with NCRs previously reported by Montiel et al. [1], and signal peptide cleavage sites. Using this approach, 284 and 497 NCR-like peptides with conserved cysteine positions were identified in Trigonella foenum-graecum and Medicago truncatula genome assemblies, respectively. The predicted physicochemical properties of the screened peptides from the two legumes were comparable because they are evolutionarily closely related. This suggests that the workflow can be applied to other IRLC legumes to screen for NCRs and explore their functions in rhizobial symbiosis and antimicrobial defense.