## Materials and Methods
### Quality Analysis, Genome Assembly, and Annotation of Geobacillus  
Sp. G4  
The raw fastq files (paired-end) comprising 13,778,078 sequences with an average length of 151 bp were imported into the FastQC v0.12.1 tool for quality assessment. The quality filtering was performed using Trimmomatic v0.38 to remove sequences with low-quality scores, applying the following parameters: SLIDINGWINDOW (4:30) and PHRED 30. The remaining sequences were then imported into the SPAdes v3.15.4 tool for genome assembly using the parameters k-mer (21, 33, 55, and 77) and a Phred score of 64 (Illumina). Short contigs (<200 bp) were removed from the assembly using seqtk v.1.4 ([[https://github.com/lh3/seqtk](https://github.com/lh3/seqtk)]([https://github.com/lh3/seqtk](https://github.com/lh3/seqtk)), accessed on 13 November 2024). The completeness and contamination of the genome were analyzed using the CheckM v1.2.2 tool and CoverM v0.7.0 ([[https://github.com/wwood/CoverM](https://github.com/wwood/CoverM)]([https://github.com/wwood/CoverM](https://github.com/wwood/CoverM)), accessed on 13 November 2024), while the size and quality of the assembled genome were assessed using Quast v5.2.0 and Busco v5.5.0 [30; 31; 32].  
Functional genome annotation was performed in the Galaxy ([[https://usegalaxy.org/](https://usegalaxy.org/)]([https://usegalaxy.org/](https://usegalaxy.org/))) environment using Prokka v1.14.6 with default parameters. Prokka predicted CDSs, rRNAs, and tRNAs, assigning functions initially through BLAST+ searches against core databases (ISfinder, NCBI AMR, and UniProtKB/SwissProt), followed by refinement using HM-MER3 [33; 34; 35; 36; 37]. After annotation, the genome was mapped according to its functional categories and enzyme classes using the online mapper eggNOG-mapper v2 (eggNOG-mapper) with the eggNOG 5.0 database [38]. Type strains from the most similar species, based on the results from the Digital DNA-DNA hybridization (dDDH) analysis, were used for comparison with the literature.  
To analyze and highlight the biotechnological potential of the _Geobacillus_ sp. G4 strain, three metabolic pathways were highlighted in the KEGG annotation: glycogen biosynthesis (M00854), glycogen degradation (M00855), and trehalose biosynthesis (M00565) (Supplementary Figure S1). The visualization of the pathways of interest was performedusing the KEGG mapper (www.genome.jp/kegg/mapper, accessed on 20 November 2024) via the KEGG database.  
To identify gene clusters related to secondary metabolism (BCGs) in microorganisms, AntiSMASH v7.1.0 software was used [39]. The Antibiotic Resistance Genes Database (ARDB) was used to select and annotate genes potentially responsible for antibiotic resistance [40].  
The genome of _Geobacillus_ sp. G4, along with three reference genomes (_G. kaustophilus_ HTA426, _G. kaustophilus_ NBRC12445, and _G. thermolevorans_ KCTC3570), was functionally annotated using the eggNOG-mapper online tool ([[http://eggnog-mapper.embl.de/](http://eggnog-mapper.embl.de/)]([http://eggnog-mapper.embl.de/](http://eggnog-mapper.embl.de/)), accessed on 6 January 2025). Genes related to four functional categories of interest--carbon starvation, DNA repair and supercoiling, heat-shock response, and oxidative stress--were selected based on their presence in the genomes. Gene presence/absence analyses and graphical visualization were performed using R statistical software ([[https://www.r-project.org/](https://www.r-project.org/)]([https://www.r-project.org/](https://www.r-project.org/))).