Raw organic materials used for composting consisted of chicken manure and cow dung at a rate of 1:1 collecting from local farm of Yancheng, China. The raw materials were mixed with straw at a rate of approximately 15% (weight/weight). The properties of the raw materials are given in Supplementary Table S1. After thorough mixing, 1 kg of raw materials were sealed in a 2 L Mason jar and incubated in electro heating standing temperature cultivator (DH3600II, Taisite, Tianjin, China) with eight replicate jars for each treatment. A rapid heating composting strategy was adopted in this study to simulate the internal conditions of bioreactor. The composting process lasted a total of 6 days, including 5 days of heating-up and thermophilic process and 1 day of cooling process. The temperature in the incubator was gradually elevated by 5°C per hour from the initial 25°C to the highest temperature 60°C. Raw materials were subsequently incubated under 60°C for 5 days before gradually cooling down. Samples were collected at the initial stage (0 d), heating-up stage (1 d), thermophilic stage (3 d), and cooling stage (6 d). Aliquote of the manure samples were stored immediately in −70°C for molecular characterizations.

Eight compost samples from each of the four composting steps were collected and sent to Shanghai Majorbio Bio-pharm Technology Co., Ltd. for amplicon sequencing (Yan et al., 2024). Following the manufacturer’s instructions, the E.Z.N.A.^® soil DNA Kit (Omega Bio-tek, Norcross, GA, United States) was used to extract microbial community genomic DNA from composting samples. The hypervariable region V3-V4 of the bacterial 16S rRNA gene were amplified with primer pairs 338F (5’-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5’-GGACTACHVGGGTWTCTAAT-3′). Purified amplicons were pooled in equimolar and performed paired-end sequencing on an Illumina MiSeq PE300 platform (Illumina, San Diego, United States) in accordance to the standard protocols by Majorbio. The raw reads were deposited into the NCBI Sequence Read Archive (SRA) database (Accession number: SRP513095).

The raw 16S rRNA gene sequencing reads were demultiplexed, quality-filtered by fastp version 0.20.0 (Chen et al., 2018) and merged by FLASH version 1.2.7 (Magoc and Salzberg, 2011). The direction of the sequences were adjusted and barcodes were extracted. Operational taxonomic units (OTUs) with 97% similarity cutoff (Edgar, 2013) were clustered using UPARSE version 7.1 (Edgar, 2013), and chimeric sequences were identified and removed. The taxonomy of each OTU representative sequence was analyzed by RDP Classifier version 2.2 (Wang et al., 2007) against the 16S rRNA database Silva v138 with a confidence threshold of 0.7.

The Majorbio online analysis platform was used to calculate the alpha diversity indices (Richness, Shannon, Chao1, Simpson index) and beta diversity metrics based on the shared presence (Jaccard distance) or abundance (Bray-Curtis distance) of taxa. These metrics were then ordinated via Principal Coordinates Analysis (PCoA). Direct gradient analysis, distance-based redundancy analysis, and permutative ANOVA were used to test for separation (10,000 permutations). The taxonomy differential analysis was conducted using non parametric Kruskal Wallis sum-rank test among each two pairs of the four steps. Random forest analysis was used to identify the key OTUs that can distinguish differences between the two groups of composting steps, as well as their impact on the model. The network analysis of bacterial community was conducted though Random Matrix Theory (RMT)-based network construction methods (Deng et al., 2012).¹ The prediction of community metagenomic functional abundance was performed using PICRUSt1 and FAPROTAX.

Microbes were isolated from thermophilic and maturated stage samples. Three separate 1 g compost sub-samples were obtained from each sample and individually placed in tubes containing 10 mL sterile distilled water. Compost suspensions were prepared by mixing on a vortex mixer for 60s, serially diluted, and spread onto nutrition agar (Aoboxing Bio-tech Co., Ltd., Beijing, China) plates for isolating bacteria. Culturing plates were incubated at 45°C and 60°C for isolating heat tolerant and extreme heat tolerant microorganisms. Colonies that can grow at 45 or 60°C were transferred to new media and morphologically redundant ones were removed. The left colonies were subjected to DNA extraction and molecular identification based on 16S sequences. The 16S rDNA sequences of the bacterial isolates were deposited into NCBI GenBank database with the Accession Numbers of PQ462071 to PQ462113 and PQ459755-PQ459762.

For cellulase assay, the bacterial isolates were incubated on sodium carboxymethyl cellulose medium at 45°C for 18 h. Congo red [0.1% (volume/volume); Macklin, Shanghai, China] staining was performed for 5 min, and then the destaining process was carried out by soaking the stained sample in 1.0 M NaCl for 10 min. Ligninase production activity was assessed by incubating bacterial isolates on nutrient agar medium containing aniline blue (Solarbio, Beijing, China), and the results were assessed 18 h post incubation. The enzyme activity and enzyme-degrading ability could be assessed by the size of the clear zone on the medium around the bacterial colonies (Teather and Wood, 1982).

Three bacterial inocula with targeted properties were selected for microbial-aided thermophilic composting experiment as previous described. The selected strains were incubated in liquid LB medium and shaken at 45°C, 150 r/min overnight. The inocula were collected by centrifuging, and fresh cells were inoculated individually in manure at a ratio of 1: 100 (weight/weight) with 3 replicates for each microbial treatment. A non-microbial inoculation control (NI) with 3 replicates was included in this experiment. Compost samples were collected at 3 days and 5 days post heat treatment.

Composting temperatures were recorded using a temperature sensor. Moisture was measured by drying fresh solid samples at 105°C for approximately 8 h to achieve a constant weight. Total carbon and total nitrogen were determined using an elemental analyzer (FlashSMART, Thermo Fisher Scientific Inc., MA, United States). Fresh solid samples were mixed with deionized water at a mass ratio of 1:10 and shaken for 1 h to obtain the water extract for the measurement of pH, electrical conductivity (EC), and seed Germination Index (GI). The pH and EC values were determined using a FiveEasy Plus™ pH/EC meter (Mettler Toledo, Shanghai, China). The GI was measured following the methods described previously by Wang et al. (2023) and Liu et al. (2023b). The GI values were measured using 10 cucumber seeds cultured in the water extract at 25°C for 48 h in darkness. Deionized water was used as a control. Organic matter content in the compost was determined by potassium dichromate volumetric method. In addition, total soluble phosphorus and total potassium contents were determined using UV-1900i spectrophotometers (Shimadzu Co., Ltd, Shanghai, China) and TAS-990 atomic absorption spectroscopy (Beijing Puxi General Instrument Co., Ltd, Beijing, China), respectively.

Composted manure was subjected to wheat growth tests to examine the quality of the fermentation products. After fermentation, composts from different treatments were thoroughly mixed with growing substrates at a volume ratio of 2:1. The growing substrates contained vermiculite and potting mix (Klasmann-Deilmann, Germany) at a ratio of 7:1 to create a barren nutritional environment. Wheat seeds were transplanted in the culture mix after germinating in Petri dish using distilled water. Five pots were applied for each compost sample with 2 seeds in each pot. Pots were arranged in a completely randomized design in an artificial climate growth chamber (PRX-800D-F, Ningbo, China). Plants were grown in the greenhouse at 25–28°C with a 14-h photoperiod, watered at 3-day intervals, and harvested 1 month after planting. Wheat seedlings shoot height, shoot, and root dry weight were measured at harvest.

Genome sequencing was conducted at Shanghai Majorbio Bio-pharm Technology Co., Ltd. Genomic DNA was extracted using Bacterial DNA extraction kit (magnetic beads) (BioDynami, Alabama, United States) according to the manufacture’s protocol. Paired-end Illumina sequencing (2 × 150 bp) on Illumina Novaseq 6,000 (Illumina Inc., SanDiego, CA, United States) was used to sequence the whole-genome of FSB24, FSB30 and FSB35. The raw reads were deposited into the NCBI SRA database (Accession number: SRP513345).

The low-quality reads were filtered to obtain clean data using fastp 0.20.0 (Chen et al., 2018). After quality control, clean reads were de novo assembled to obtain genome draft using short sequence assembly software SOAP denovo2 (Luo et al., 2012), resulting in the optimal contigs assembly. Then, aligned contigs were locally assembled and optimized base on the paired-end and overlap relationships of reads to construct scaffold. Glimmer3 (Delcher et al., 2007), GeneMarkS-2 (Lomsadze et al., 2018), and Prodigal v2.6.3 (Hyatt et al., 2010) were used to predict the coding sequence (CDS) on the genome. tRNAscan-SE v2.0 (Chan and Lowe, 2019), Barrnap,² and Tandem Repeats Finder v 4.09 (Benson, 1999) were used to predict tRNAs, rRNAs, and tandem repeat sequences, respectively. Genes were annotated against Gene Ontology (GO),³ Kyoto Encyclopedia of Genes and Genomes (KEGG),⁴ Cluster of Orthologous Groups of proteins (COG),⁵ KOG, evolutionary genealogy of genes: Non-supervised Orthologous Groups (eggNOG), Non-Redundant Protein Database (NR), Transporter Classification Database (TCDB), Swiss-Prot,⁶ Carbohydrate-Active enZYmes Database (CAZy) databases using diamond v2.1.9 (Buchfink et al., 2021) with an cutoff E-value of 1.0 e-5. Secondary metabolism gene cluster analysis was performed using antiSMASH v2.0.2 (Blin et al., 2013).

Based on the genome maps of three isolates, their genes on genomes were compared to understand the functions, expression mechanisms, and evolution process. OrthoMCL v2.0 (Li et al., 2003) was used to obtain homologous gene families, as well as gene number and information in each gene family. The genomes of the three isolates FSB24, FSB30 and FSB35 were then screened for core genes (genes included in all isolates) and unique genes (genes included only in a specific isolate).

Genomic collinearity analysis and phylogenomic analysis were conducted by Mauve 2.4.0 (Darling et al., 2004). Isolates FSB24, FSB30 and FSB35 were aligned to 12 other Bacillus species, and also individually mapped to the known thermophile Bacillus thermotolerans (GCF_000812025.2) and mesophile Bacillus cereus (GCF_000007825.1) using BLAST+ with an E value ≤1e-5. Genes with identity <80% were considered as non-homolog genes. The phylogenetic relationship of the selected genes was constructed with MEGA 7.0 (Kumar et al., 2016) using the maximum likelihood method and 1,000 bootstrap replicates. Multiple sequence alignment was performed using ClustalW (Thompson et al., 1994), and p-distance was calculated.

Plant growth and physicochemical compost properties data were subjected to ANOVA using SAS (Version 9.4; SAS Institute, Cary, NC) GLM model for a completely randomized design. Data were subjected to analysis of variance and means separation using Fisher’s least significant test, with p ≤ 0.05 considered significant.

The heat treatment resulted in decreasing Chao 1 indices of bacterial communities than the initial stage (Control). The Chao 1 indices of bacterial communities were not different between thermophilic (TC) and cooling (CL) steps, but they both significantly lower than heat-up (HT) step and the Control. In addition, the bacterial abundance, indicated by the Chao 1 index, in HT step was significantly higher than that in the Control (Figure 1a). PCoA analysis indicated that bacterial community compositions of the TC and CL steps were more similar to each other but distinct from that of the Control and HT (Figure 1b), additionally, the bacterial community compositions of Control and HT were more similar to each other. A total of 726 bacterial OTUs presented in all the composting steps, and individually, 24, 1, 33 and 49 OTUs were only presented in the Control, HT, TC and CL steps (Figure 1c). Among the 49 unique OTUs detected in CL process, OTU596 from the Genus of Paenibacillus (15.01%), OTU918 from the Genus of Thermobacillus (9.12%) and OTU556 from the Family of Limnochordaceae (8.71%) represented the greatest proportion among the unique OTUs. While among the unique OTUs in the Control, OTU63 from the Genus of Brumimicrobium (17.31%), OTU392 from the Family of Sphingobacteriaceae (9.62%), and the OTU47 from the Order of Peptostreptococcales-Tissierellales (9.62%) represented the greatest proportion.

Among bacterial phyla, Firmicutes, Actinobacteriota, Proteobateria, Bacteroidota, Gemmatimonadota, Deinococcota, Halanaerobiaeota, Myxococcota, Chloroflexi, and Desulfobacterota were detected at greater abundance in TC and CL processes (Figure 1d). The bacterial phylum that was significantly altered in abundance during the composting process was Firmicutes (Figure 1d), with about 2.5 fold increase in TC (67.21 ± 9.60%) and CL (62.5 ± 7.35%) steps relative to the Control (25.71 ± 14.27%). The abundance of Actinobacteriota was first increased and then decreased during the whole composting process. The abundances of Proteobacteria and Bacteroidota were decreased during composting, whereas the abundance of Gemmatimonadota was dramatically increased with the rising temperature (Figure 1d). Besides, the phyla Gemmatimonadota and Halanaerobiaeota were only in the top 10 abundant bacterial phyla of TC and CL, but not in HT or the Control.

Random forest analysis showed that the top 50 differentially abundant bacterial OTUs among the four fermentation steps were mainly in the phyla of Firmicutes, Proteobacteria, Bacteroidota, and Myxococcota (Supplementary Figure S2). Among them, the thermophilic bacteria Ammoniibacillus agariperforans (Sakai et al., 2015), Novibacillus thermophiles (Yang et al., 2015), and Ureibacillus thermosphaericus (Jia et al., 2017) were significantly abundant in the TC and CL steps. Whereas Facklamia tabacinasalis (Collins et al., 1999) and Aerococcus urinaeequi (Rasmussen, 2016), two potential human pathogens, were more abundant in HT step and the Control (Supplementary Figure S2).

Since bacterial communities in the TC and CL steps were similar to each other (so were HT and the Control) based on diversity and taxonomy analysis, samples from TC and CL (thermophilic group), as well as the Control and HT (control group) were combined to conduct the pairwise comparison. Through differential analysis of control group and thermophilic group, 464 differentially abundant bacterial OTUs were obtained. The top 50 significantly abundant bacteria in thermophilic group were mainly in the Phyla of Firmicutes, including the thermotolerant bacteria Sinibacillus soli (Yang and Zhou, 2014), Bacillus thermolactis (Coorevits et al., 2011), and A. agariperforans (Sakai et al., 2015) (Figure 2a). Besides, several bacteria in the Phyla of Gemmatimonadota, Myxococcota, and Proteobacteria were also significantly abundant in the thermophilic group (Figure 2a). The top 50 significantly abundant bacteria in the control group were mainly in the Phyla of Firmicutes, Bacteroidota, and Proteobacteria. Among them, Streptococcus equinus (Park et al., 2023), F. tabacinasalis (Collins et al., 1999), A. urinaeequi (Rasmussen, 2016), and Enterococcus faecalis (Kristich et al., 2014) from the Phylum of Firmicutes, and Escherichia coli from the Phylum of Proteobacteria are reported human/animal pathogens (Figure 2a).

Molecular ecological network (MENs) through RMT-based methods was constructed for all the differentially abundant bacterial OTUs between the thermophilic and control group, resulting in 172 nodes and 2,616 edges (Figure 2b). The 172 OTUs were classified into 5 modules, and OTU1379 (Firmicutes), OTU432 (Bacteroidota), and OTU491 (Bacteroidota) were in the centre of the network (Figure 2b). There were 72 bacterial OTUs classified to module 1 with 64 of them were significantly abundant in the thermophilic group, while eight of them were significantly abundant in the control group (Figure 2c). Among the 64 bacterial OTUs enriched in the thermophilic group, the slow growing species Thermobifida fusca, which was reported to promote the growth of other bacteria by sharing cobalamin in a quasi-natural composting system (Zhao et al., 2023), was related to 75 OTUs, and all the relationships were positive. There were 85 bacterial OTUs classified to module 2 with 44 of them were significantly abundant in the thermophilic group, while 41 of them were significantly abundant in the control group. The thermophilic species Clostridiales bacterium and Bacillus thermocloacae that significantly abundant in the thermophilic group had 1 negative and 3 positive connections with other OTUs, respectively. There were only three and two OTUs classified to module 4 and 5, respectively, and they were all significantly more abundant in the control group (Figure 2c).

FAPROTAX was used to map bacterial taxonomy to metabolic related functions. Through Wilcoxon rank-sum test, we found that the abundance of bacteria with metabolic functions of cellulolysis, xylanolysis, methanotrophy and manganese oxidation were significantly higher in the thermophilic group, while functions related to animal/plant pathogenesis were significantly higher in the control group (Figure 2d). Besides, functions related to nitrogen cycle, such as nitrite ammonification and nitrate reduction, were significantly decreased with temperature increasing (Figure 2d), suggesting the functions of bacterial community converted during the thermophilic composting process. It was consistent with previous reports (Song et al., 2016).

A total of 47 bacterial isolates were obtained from the plate culture based on colony morphology, color and shape. The 47 bacterial isolates were identified through 16S rDNA sequencing (Supplementary Table S3). A maximum likelihood dendrogram was generated with the 16S rDNA sequences of the bacteria and representative sequences from the databases. Phylogenetic analysis of the 47 isolates mainly matched with the genera of Bacillus, Ureibacillus, Geobacillus, Acinetobacter, Sphingomonas, Lactobacillus, Staphylococcus, and Burkholderia. Among the 47 bacterial isolates, 11 isolates produced the cellulose enzyme. A clear halo zone was found around the colonies in the Congo red agar plates (Figure 3a; Supplementary Figure S4). Nine of the isolates were able to produce lignin peroxidase, as clear halo zones were observed around the colonies in the aniline blue agar plates (Figure 3a; Supplementary Figure S5).

According to the 16S rDNA conserved region taxonomy identification and enzyme production, three isolates FSB24, FSB30, and FSB35, were selected as microbial inocula, and they were classified to Bacillus stercoris, B. stercoris, and Bacillus licheniformis, respectively, wherein B. stercoris is the sub-species of Bacillus subtilis (Figures 3b–d). In fact, through our subsequent whole genome sequencing, the taxonomy of FSB24 and FSB30 were closer to Bacillus spizizenii (Figure 4a).

Generally, compost is considered mature when the GI value of seed germination is >50%, and it is considered completely mature when GI is >80% (Zucconi et al., 1981). The compost inoculated with microbial agents FSB24 and FSB30 had GI values higher than 90% after 3 days of fermentation, which were significantly higher than those inoculated with FSB35 and no inoculation (NI) (Figure 5a). After 5 days of fermentation, the compost inoculated with microbial agents all possessed GI values significantly higher than the NI, among which the GI of FSB35 and NI were significantly increased comparing to 3 days’ fermentation (Figure 5a).

It is generally believed that compost is considered mature when its carbon to nitrogen (C/N) ratio close to 16, which is the C/N ratio of microorganisms (Li et al., 2022). The C/N ratios of compost inoculated with microbial agents FSB24, FSB30 and FSB35 after 3 days of fermentation were 13.97, 13.64, and 13.10 respectively, which were significantly higher than that of the NI (Figure 5b). The C/N values of compost inoculated with microbial inoculation after 5 days of fermentation were 13.97, 14.49, and 13.07, respectively, which were again significantly higher than that of the NI (Figure 5b). Additionally, the C/N ratios of FSB30 was closer to 16, indicating this treatment possessed higher degree of maturity than others (Figure 5b).

The initial organic matter content (OMC) of the raw manure materials was 54.38% (Supplementary Table S1). After fermentation, the OMC of all the treatments decreased, while the OMC of the composts with microbial inoculations were significantly lower than that of the NI regardless of the fermentation days, indicating that the microbial inoculation did a good job in decomposing the organic matter in the manure (Figure 5c). The OMC were not significantly different from each other among the three inoculation treatments regardless of the fermentation days (Figure 5c).

The total soluble phosphorus content of compost inoculated with microbial agents were all significantly higher than that of the NI after fermentation for 3 days. In addition, phosphorus content of the compost inoculated with FSB35 was significantly higher than that inoculated with FSB24 at 3 days of fermentation (Supplementary Figure S6a). At 5 days post fermentation, the phosphorus content of compost inoculated with microbial agents FSB35 was significantly higher than the NI, whereas the phosphorus content were not different among composts inoculated with FSB24, FSB30, and the NI (Supplementary Figure S6a).

The total potassium content of compost inoculated with microbial agents FSB35 was significantly higher than that inoculated with FSB24 after 3 days of fermentation, however, the potassium content in the composts inoculated with FSB24, FSB30 and the NI were not significantly different among each other (Supplementary Figure S6b). The total potassium content of compost after 5 days of fermentation were not significantly different among each other (Supplementary Figure S6b).

The conductivity of all the treatments were not significantly different among each other at 3 days of fermentation (Supplementary Figure S6c). However, the conductivity of the NI significantly decreased at 5 days of fermentation comparing to 3 days, resulting in a significantly lower value than the composts with microbial inoculations (Supplementary Figure S6c).

Overall, the wheat cultivated in substrates mixed with composts grew better comparing to no treatment control (NTC) (Figures 6a,b). The root dry weight of wheat cultivated in 3-day-fermentation compost inoculated with microbial agents FSB24 was greater than other microbial inoculation treatments and the NI (Figure 6c). The root dry weight of wheat cultivated in 5-day-fermentation compost that inoculated with FSB24 and FSB30 were greater than those of the FSB35 and the NI treatments, whereas FSB35 and NI were not significantly different from each other (Figure 6c).

The shoot dry weight of wheat cultivated in 3-day-fermentation compost that inoculated with microbial agents were greater than that of the NI, and the wheat cultivated in compost inoculated with FSB24 performed the best in shoot growth (Figure 6d). Likewise, the shoot dry weight of wheat cultivated in 5-day-fermentation compost that inoculated with microbial agents were greater than that of the NI, and the wheat cultivated in compost inoculated with FSB24 performed significantly greater shoot growth than that of the FSB30 (Figure 6d).

The shoot height of wheat cultivated in 3-day-fermentation compost that inoculated with FSB24 and FSB35 were significantly greater than that of the FSB30 and NI (Figure 6e). The shoot height of wheat cultivated in 5-day-fermentation compost that inoculated with microbial agents were all significantly greater than that of the NI (Figure 6e). Wheat cultivated in 5-day-fermentation compost inoculated with FSB35 had the greatest shoot height among all the treatments (Figure 6e).

The genome sequence of the three bacteria generated about 1.2 Gb clean data, and the coverage base on reads mapping of FSB24, FSB30, and FSB35 were 98.70, 98.76, and 98.81%, respectively. Comparing to the genome of mesophilic bacterium B. cereus, the genome sizes of the three isolates, FSB24, FSB30, and FSB35 were smaller, but they all larger than the genomes of thermophilic bacterium B. thermotolerans (Table 1). The genomes of FSB24, FSB30, and FSB35 comprised of 8, 21, and 23 scaffolds, with GC contents of 43.38, 43.93, and 45.88%, respectively (Table 1), which were consistent with their (species) conformis genomes B. spizizenii (GCF_000227465.1) and B. licheniformis (GCF_000011645.1), but higher than the mesophilic bacterium B. cereus (Table 1).

There were 4,292, 4,118, and 4,482 protein coding genes (CDS) recognized on the genomes of FSB24, FSB30, and FSB35, respectively, which were more than that on the conformis genomes of B. spizizenii and B. licheniformis as well as the thermophilic bacterium B. thermotolerans (Table 2). Whereas the numbers of CDS on the genome of the three isolates were smaller than the mesophilic bacterium B. cereus (Table 1). Among the three isolates, FSB30 and FSB35 comprised of plasmids (Table 2). Additionally, the tandem repeat number in isolates FSB24 and FSB30 were much lower than that in FSB35 (Table 2).

There were 3,026 genes commonly found in the three isolates, while there were 266, 461, and 1,114 unique genes found in FSB24, FSB30 and FSB35, respectively (Figure 7d). In total 3,932 homologous gene families were found through OrthoMCL annotation, including 33 of them possessed homologous genes ≥5. The 33 homologous gene families contain genes functioning in some basic life activities, such as non-ribosomal peptide synthesis, cell wall synthesis (LTA synthase family protein) and glycosyl transfer (Figure 7e). Besides, there are also homologous genes that explain why the three strains of bacteria are suitable for survival under stress (NADP-malic enzyme) (Chen et al., 2019). In addition, there are more than 5 homologous genes annotated to phosphotransferase system (PTS), which is a well-documented microbial system with a prominent role in carbohydrates transportation (Xu et al., 2023).

CAZymes play a significant role in degradation of complex carbohydrates. In the six categories of CAZymes, number of genes in carbohydrate esterases and glycosyl transferases presented obvious differences among the three isolates (Figure 7f). In carbohydrate esterases group, acetylxylan esterase plays an important role in the hydrolysis of xylan and possess 16, 20 and 22 genes in FSB24, FSB30 and FSB35, respectively (Figure 7f). Pectin methylesterase, which plays a critical role in modifying pectins, was only found in FSB35 (Figure 7f). In glycosyl transferases group, lipid-A-disaccharide synthase, which function in lipopolysaccharide biosynthesis, was only found in FSB24 and FSB35. The genes annotated to sucrose synthase in FSB24, FSB30, and FSB35 were 8, 6, and 7, respectively (Figure 7f).

Phylogenomics analysis of the three isolates together with 12 bacteria in the genus of Bacillus revealed that their genomes was classified by evolutionary relationships rather than heat tolerance (Figure 4a). Comparing to the genome of thermophilic bacterium B. thermotolerans, 7.45, 5.53, and 5.74% of genes on the genomes of FSB24, FSB30 and FSB35 were homologous (with identity ≥80%), respectively (Figures 4b–d).

Targeted to specific genes, we found that some genes in the three isolates homologous to B. thermotolerans were not homolog to mesophile B. cereus. The genes annotated to small acid-soluble protein (SASP) in the three isolates were more similar to B. thermotolerans according to the phylogenetic analysis than to the mesophiles B. subtilis, B. velezensis, B. cereus and their conformis genomes (Figure 4e). SASP are double-stranded DNA-binding proteins that contribute to the dormant spore’s high resistance to UV radiation by protecting the DNA backbone from enzymatic and chemical cleavage. The genes in FSB24 and FSB35 that encoded fatty acid desaturase were more similar to that in the thermophiles B. thermotolerans and B. licheniformis rather than the mesophiles (Figure 4f). Fatty acid desaturase catalyzes the desaturation reactions of saturated fatty acids thereby accelerate the metabolism of fatty acid. In addition, through phylogenetic analysis we found that transcriptional factor LysR of these three isolates were distantly away from their respective reference genomes but close to the thermophiles B. thermozeamaize and B. smithii (Figure 4g). LysR-type transcriptional regulators (LTTRs) regulate a diverse set of genes, including those involved in virulence, metabolism, quorum sensing and motility (Maddocks and Oyston, 2008).