Effects of calcium phosphate and phosphorus-dissolving bacteria on microbial structure and function during Torreya grandis branch waste composting

Effects of calcium phosphate and phosphorus-dissolving bacteria on microbial structure and function during Torreya grandis branch waste composting | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effects of calcium phosphate and phosphorus-dissolving bacteria on microbial structure and function during Torreya grandis branch waste composting Chenliang Yu, Yuanyuan Guan, Qi Wang, Yi Li, Lei Wang, Weiwu Yu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4641249/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Oct, 2024 Read the published version in BMC Microbiology → Version 1 posted 11 You are reading this latest preprint version Abstract Background To investigate the effects of phosphorus solubilizing microorganisms and calcium phosphate on the composting of Torreya grandis branches and leaves, as well as to explain the nutritional and metabolic markers related to the composting process. Methods In this study, we employed amplicon sequencing and untargeted metabolomics analysis to examine the interplay among phosphorus (P) components, microbial communities, and metabolites during T. grandis branch and leaf waste composting that underwent treatment with calcium phosphate and phosphate-solubilizing bacteria ( Burkholderia ). Results The results indicated that Burkholderia inoculation and calcium phosphate treatment affected the phosphorus composition, pH, EC, and nitrogen content. Furthermore, these treatments significantly affected the diversity and structure of bacterial and fungal communities, altering microbial and metabolite interactions. The differential metabolites associated with lipids and organic acids and derivatives treated with calcium phosphate treatment are twice as high as those treated with Burkholderia in both 21d and 42d. The results suggest that calcium phosphate treatment alters the formation of some biological macromolecules. Conclusion These results extend our comprehension of the coupling of matter transformation and community succession in composting with the addition of calcium phosphate and phosphate-solubilizing bacteria. calcium phosphate composting metabolite microbial community phosphorus fractions Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction As China's fruit industry grows, a significant quantity of waste materials such as branches and leaves are generated following the establishment of stable fruit tree production and tree structures [ 1 , 2 ]. Managing branch waste is thus increasingly important. Composting represents a viable strategy for harmlessly reducing and better utilizing resources in the context of agricultural and livestock waste management [ 3 , 4 ]. Composting efficiency is influenced by several key factors: water content, temperature, pH, organic matter content, carbon to nitrogen (C/N) ratio, and microbial agents [ 5 – 8 ]. Composting refers to a complex series of biochemical reactions involving microorganisms [ 9 ]. In addition, changes in the microbial community in response to the evolving pile environment are characteristic of the composting process by [ 10 ]. The succession of functional microorganisms has been used as an indicator to assess the ecological function and product maturity under the co-distribution of manure and crop residues, and can reflect the community distribution at the levels of the microbial family, genus, and phylum at different stages of composting [ 11 , 12 ]. Microbial community characteristics reflect the relationship between microbial changes and the pile environment, and they provide a reference for composting [ 13 ]. Macronutrient phosphorus (P) is essential for plants to grow and develop [ 14 ]. The total phosphorus content of the soil is high, but the content of available phosphorus is low [ 15 ]. The main reason for this is that a large amount of phosphorus in soil is bound by calcium, aluminum, iron, and other metal ions and stored in an invalid state [ 16 ]. The seasonal utilization rate of phosphate fertilizer is generally 10–25% [ 17 ]. Although the total amount of phosphorus in soil increases when phosphorus fertilizer is applied, most of it is adsorbed, precipitated, or fixed by microorganisms in the soil, thereby, reducing the effective concentration of phosphorus [ 18 , 19 ]. Therefore, it is of great significance to fully consider and develop phosphorus recycling to decrease the use of phosphorus fertilizer and improve phosphorus use efficiency. This is also one of the major challenges facing current and future agricultural production. Phosphorus-solubilizing microorganisms are abundant in soils. They can dissolve insoluble phosphorus, increasing the effective soluble phosphorus in the soil through acidification, chelation, and other ways This can be absorbed by crops to improve the use of phosphorus fertilizer and reduce the amount of phosphorus fertilizer applied [ 20 , 21 ]. In the last few years, efficient phosphorus-solubilizing bacteria have effectively improved the rate of utilization of mineral phosphorus in soil [ 22 ]. Various phosphorus-solubilizing bacteria have been reported, such as Bacillus , Pseudomonas , Erwinia , Burkholderia , Rhizobium , Flavobacterium , Penicillium , and Aspergillus [ 23 ]. Agricultural waste contains plenty of nitrogen, phosphorus, and other elements that can be converted into inorganic compounds through fermentation for plant absorption and utilization [ 24 , 25 ]. Reports on the phosphorus-solubilization effect of Burkholderia in the composting process are scarce at present. Our research is thus of great significance for accelerating the conversion of insoluble phosphorus compounds into available phosphorus during the composting process of agricultural waste. Torreya grandis cv. Merrillii is a rare and special dry fruit tree in China. With the continual expansion to the scale of planting, considerable waste is generated by pruning branches. Adding bacterial agents is a necessary means to improve composting efficiency, and has been applied to the treatment of agricultural by-product waste, kitchen garbage, and livestock and poultry manure [ 26 , 27 ]. Impact of phosphorus-solubilizing microorganisms on the composting has not been adequately studied and calcium phosphate on branches, leaves, and other waste materials of T. grandis , as well as the nutrient and metabolite markers associated with the composting process. Investigating the use of nutrient resources is of paramount importance, as it can offer technical assistance in safeguarding the agricultural ecological environment and advancing development of sustainable agricultural. Materials and methods Composting experiments and treatments Each processed branch and leaf of T.grandis weighed 10 kg and was ground into a powder with a particle size of 2 mm. We started composting by adding 10% calcium phosphate (CaP) or 5 mL/kg (1×10 8 / mL Burkholderia ) microbial inoculant (WJP), or adding both at the same time (CaP + WJP). The control group (CK) did not include any calcium phosphate or bacterial agents. Four treatments in the experiment, each with three replicates. The phosphorus-solubilization ability of Burkholderia sp. strain is shown in Figure S1 . We placed the mixture in a 25 L polyethylene fermentation tank (diameter 0.35 m, height 0.41 m). We adjusted the moisture content to 70%. The treatment total time was 42 days, and the pile was flipped every two days to maintain moisture content of around 70% by adding water. Phosphorus and physicochemical analyses Various phosphorus P fractions from the compost was extracted using an improved Hedley phosphorus classification method [ 28 ]. Total of 0.5 g compost sample was weighed into a 50 mL centrifuge tube, resin strips was added (1 × 6 cm) and 30 mL of ddH 2 O, shaken overnight (16 hours, 220 rpm). The resin strip was extracted with 0.5 M HCl, and then we measured the resin phosphorus in the extract. To remove the residual liquid from the resin strip, we centrifuged the supernatant, added 30 mL of NaHCO3 (pH 8.5) to the sediment, shaken overnight (16 hours) and centrifuged, and determined the inorganic phosphorus and total phosphorus in the supernatant. Continued to precipitate by adding 30 mL of 0.1 M NaOH, shook it overnight (16 hours), and centrifuged the supernatant to determine the inorganic phosphorus and total phosphorus. Added 1 M HCl to the precipitate, shook it overnight, and determined the inorganic phosphorus in the supernatant. Finally, transferred all sample residues to a digestion tube, added 5 mL of conc. H 2 SO 4 , placed it in an electrothermal digestion apparatus, slowly heated it until the water evaporated to dryness and the temperature reached 360℃, added 30% H 2 O 2 every 15 minutes until the liquid was clear and transparent, and then heated it for 15 minutes to a constant volume to 30 mL overnight and determined the inorganic phosphorus. Using molybdenum antimony resistance colorimetry, all supernatants were measured for phosphorus content [ 29 ]. A Kjeldahl nitrogen analyzer was used to determinetotal nitrogen (TN)using H 2 SO 4 and H 2 O 2 digestions. A pH/EC meter was used to measure pH and electrical conductivity (EC). DNA extraction and amplicon sequencing The TIANamp Soil DNA Kit (DP336, TIANGEN, Beijing, China) was used to extract DNA from 0.25g sample, ITS1F (5′-GGAAGTAAAAGTCGTAACAAGG-3′)/ITS2R (5′-GCTGCGTTCTTCATCGATGC-3′), 338F (5′-ACTCCTACGGGAGGCAGCA-3′)/806R (5′-GGACTACHVGGGTWTCTAAT-3′), respectively. The sequence library was prepared with VAHTS Universal Plus DNA Library Prep Kit for Illumina (Code: ND617, Vazyme, Nanjing, China) using purified PCR products according to the manufacturer's instructions. Bioinformatic analysis Bioinformation analysis of the microbiome was performed using QIIME 2 2019.4. The primer sequences were removed with QIIME Cutadapt Trim-paired, and the unmatched primers were discarded [ 30 ]. Then, Dada2 was used for quality control, denoising, stitching, and de-chimerism. The SILVA (version 13.2) and UNITE (version 8.0) databases were used to classify bacteria and fungi, respectively. Subsequently, ASV analysis, α-diversity analysis, β-diversity analysis, species composition analysis and the community differences between groups were analyzed. Functional prediction of microorganisms was performed using PICRUSt2 software. Spearman correlation coefficients base co-occurrence network analysis (Spearman’s r > 0.6 or r < − 0.6; P < 0.05). ASV correlation coefficients were calculated using R's “corr.test” function in the software package "psych 2.1.3". With the help of Fruchterman–Reingold layout algorithms, the co-occurrence networks were further visualized in Gephi, and the properties of the networks were collected using the “igraph” function [ 31 ]. Metabolite extraction and metabolomics analysis Accurately weighed 0.1 g compost sample and ground it into powder in liquid nitrogen. Added 1 mL of 70% aqueous methanol for metabolite extraction. The extracts were separated, and then injected into an ultra-high performance liquid chromatography (UHPLC) system (Agilent 1290 Infinity LC, Agilent) with a C-18 column (2.1 × 100 mm, 1.7 µm; Waters). An AB Triple TOF 6600 mass spectrometer was used to collect the primary and secondary spectra of the samples according to the operation of the instrument [ 32 ]. Metabolomics data analysis Raw data analysis was performed with Compound Discoverer 3.2. The metabolomics databases mzCloud, mzVault, Masslists, and Chemspider were used to identify the metabolites. Differential accumulated metabolites (DAMs) were examined the metabolites with different importance in projection (VIP) values > 1.0, P 1. Results Physicochemical indexes and variation during composting Total phosphorus (TP) content was not different between WJP and CK (Fig. 1 ). From days 0 to 21, the TP contents of CaP and CaP + WJP increased. The content of resin phosphorus increased in all treatments. The content of the resin phosphorus of CaP treated was higher than that of WJP and CaP + WJP after 42 days. The total phosphorus content of sodium bicarbonate treated with CaP increased the fastest, while the inorganic phosphorus content of sodium bicarbonate treated with WJP increased the fastest from days 21 to 42. The inorganic phosphorus content of sodium hydroxide increased throughout the treatment cycle, and the increase of the three composting treatments was greater than that of CK. The content of total sodium hydroxide phosphorus was similar to that of sodium hydroxide inorganic phosphorus, which generally increased (Fig. 1 ). Compared to control, EC of all treatments decreased at first and then increased on the 14th day, and the CaP treatment was the highest. On the 21th and 35th days, both WJP and CaP increased at first and then decreased. After 42 days, EC of CK and CaP + WJP treatments increased, while the WJP and CaP showed the opposite trend. The pH range of the three compost treatments and the control ranged from 6.12–7.91 (Fig. S2). Effect of WJP and CaP on bacterial and fungal communities during composting From the compost samples of different composting stages (days 0, 21, and 42) and different treatments (CK, CaP, WJP, and CaP + WJP), 320,945 bacterial sequences were obtained, which were divided into 15759 ASVs (Table S1 ). A total of 320,945 fungal sequences were obtained, which were divided into 2457 ASVs (Table S2). According to the rarefaction curve and rank abundance curve, the changes in the bacterial communities in the compost were effectively reflected in the high-throughput sequencing result (Fig. S3). At the family level, composting significantly changed bacterial and fungal communities (Fig. 2 A and Fig. 2 B). For the CK compost group, the levels of dominant bacteria at on day 0 were Enterobacteriaceae (6.72%), Burkholderiaceae (5.70%), and Pseudomonadaceae (3.8%). The dominant bacteria on day 21 were Enterobacteriaceae (23.98%), Sphingobacteriaceae (13.88%), and Rhizobiaceae (11.13%). The dominant bacteria on day 42 were Sphingobacteriaceae (15.27%), Rhizobiaceae (11.93%), and Enterobacteriaceae (9.39%) (Fig. 2 A). For the WJP-treated compost group, the dominant bacteria on day 21 were Enterobacteriaceae (28.93%), Actinomycetaceae (10.17%), and Sphingobacteriaceae (8.21%). However, the proportions of these three bacteria were 5.09%, 19.55%, and 5.42%, respectively on day 42. Rhizobiaceae increased from 6.63–10.25%, and Flavobactereae increased from 4.33–10.72%. For the CaP-treated compost group, Enterobacteriaceae decreased from 36.87% on day 21 to 10.59% on day 42, and Xanthomonadaceae decreased from 11.02–4.65%. Actinomycetaceae increased from 7.02% on day 21 to 13.46% on day 42, and Flavobacteriaceae increased from 1.65–14.23%. For the CaP + WJP-treated compost group, Enterobacteriaceae decreased from 12.92–6.48%. For fungi, Dipodascaceae and Pichiaceae were the main dominant fungi in the composting process (Fig. 2 B). The bacterial Chao1 value of compost samples with different treatments increased, while the Shannon and Simpson indices decreased (Fig. 2 C). The results showed an increase in the number of bacterial but a decrease in their diversity. Decline Chao1, Shannon, and Simpson indices for fungi indicate that fungi abundance and diversity reduced (Fig. 2 D). The results of principal component analysis (PCA) show that the samples treated are closely gathered (Fig. 3 A and 3 B). Taxa for different treatment compost groups were identified through random forest classification (Fig. 3 C and 3 D). It was found that WJP treatment increased abundance of Pedobacter , Gluconacetobacter and Anaerosporobacter . CaP treatment increased the abundance of Pedobacter , Actinomycetaceae , Anaerosporobacter , Delftia , and Gluconobacter . The abundance of Brevundimonas , Chryseobium , Azotobacter , Ketogulonicigenium , Weissella , Acetobacter , Sphingobacterium and Procabacter was reduced (Fig. 3 C). For fungi, WJP treatment increased the abundance of had an increase in Pichia abundance, Dipodascus abundance increased when treated with CaP. Differentially abundant core and specific taxa under WJP or CaP treatment We also used DESeq software to screen differential abundant bacteria in the composting process based on a fold change of > 2 or < 0.5 and an adjusted P < 0.05(Fig. 4 ). In the CK21D vs WJP21D comparison group, 100 differentials bacterial ASVs, including 31 enriched and 69 depleted ASVs, were identified. These differential bacteria were distributed in three phyla: Bacteroidetes (22ASVs), Firmicutes (11 ASVs), and Proteobacteria (67ASVs). A total of 109 differential bacterial ASVs, including 43 enriched and 66 depleted ASVs, were identified in the CK21D vs. CaP21D comparison group. These differential bacteria were distributed in three phyla: Bacteroidetes (22 ASVs), Firmicutes (14 ASVs), and Proteobacteria (73ASVs). In the CK42D vs WJP42D comparison group, 121 differentials bacterial ASVs, including 58 enriched and 63 depleted ASVs, were identified. These differential bacteria were distributed in four phyla: Actinobacteria (5 ASVs), Bacteroidetes (31 ASVs), Firmicutes (28 ASVs), and Proteobacteria (57 ASVs). A total of 108 differential bacterial ASVs, including 43 enriched and 65 depleted ASVs, were identified in the CK42D vs. CaP42D comparison group. These differential bacteria were distributed in four phyla: Actinobacteria (1 ASV), Bacteroidetes (29 ASVs), Firmicutes (28 ASVs), and Proteobacteria (50 ASVs). The species composition of the bacterial communities changed significantly as a result of a co-occurrence network analysis built at the ASV level (Fig. 5 and Table 1). In CK0D, a total of 134 nodes and 1002 edges, including 60.98% and 39.02% positive correlations of the ecological network, were obtained. In composting 21D, ecological networks of 145, 130, and 141 nodes with 859, 643, and 852 edges were obtained for the CK, WJP, and CaP treatment groups, respectively. In composting 42D, networks of 144, 108, and 116 nodes with 792, 516, and 561 edges were obtained for the CK, WJP, and CaP treatment groups, respectively. Effects of WJP and CaP on microbiome functions in the composting process PICRUSt2 software was used to determine the functional difference of microbiota in the composting process of WJP or CAP treatments. In Fig. 6 , the top 10 KEGG pathways of all nine comparison groups are shown. In the CK0D vs. CK21D comparison group, aerobactin biosynthesis, coenzyme M biosynthesis I, and the superpathway of methylglyoxal degradation increased, while the superpathway of bacteriochlorophyll a biosynthesis, chlorophyllide a biosynthesis I (aerobic, light-dependent), and factor 420 biosynthesis were depleted. In the CK0D vs. CK42D comparison group, aerobactin biosynthesis, pyrimidine deoxyribonucleotides de novo biosynthesis IV, and pyrimidine deoxyribonucleotides biosynthesis from CTP increased, while chlorophyllide a biosynthesis I (aerobic, light-dependent), factor 420 biosynthesis, and vitamin E biosynthesis (tocopherols) were depleted. In the CK21D vs. WJP21D comparison group, the superpathway of demethylmenaquinol-6 biosynthesis II, chondroitin sulfate degradation I (bacterial), and the superpathway of bacteriochlorophyll a biosynthesis increased, while mycolyl-arabinogalactan-peptidoglycan complex biosynthesis, isoprene biosynthesis II (engineered), and coenzyme B biosynthesis were depleted. In the CK21D vs. CaP21D comparison group, the superpathway of bacteriochlorophyll a biosynthesis, chondroitin sulfate degradation I (bacterial), and D-cycloserine biosynthesis increased, while mycolyl-arabinogalactan-peptidoglycan complex biosynthesis, isoprene biosynthesis II (engineered), and coenzyme B biosynthesis were depleted. In the CK42D vs. WJP42D comparison group, p-cumate degradation, p-cymene degradation, and reductive acetyl coenzyme A pathway increased, while the superpathway of bacteriochlorophyll a biosynthesis, L-valine degradation I, and S-methyl-5-thio-α-D-ribose 1-phosphate degradation were depleted. In the CK42D vs. CaP42D comparison group, D-cycloserine biosynthesis, adenosine nucleotides degradation IV, and the reductive acetyl coenzyme A pathway increased, while sucrose degradation II (sucrose synthase), mycolyl-arabinogalactan-peptidoglycan complex biosynthesis, and pyrimidine deoxyribonucleotides de novo biosynthesis IV was depleted. Effects of WJP and CaP on metabolites in the composting process We used liquid chromatography-mass spectrometry (LC-MS) to identify and quantitatively analyze the compost metabolites. There were 4312 metabolites identified in total. Based on principal component analysis (PCA), the treatment and control groups were significantly different, and metabolomes in the same group we closely clustered (Fig. S4). We further identified the significantly different accumulated metabolites (DAMs) between different treatments (Fig. 7 ). A total of 90, 159, 139, and 181 DAMs were identified in the CK21D vs. WJP21D, CK21D vs. CaP21D, CK42D vs. WJP42D, and CK21D vs. CaP21D comparison groups, respectively (Fig. 7 A). These DAMs were classified into 12 main classes (Fig. 7 B). Combined analysis of microbiomes and metabolomes In order to elucidate the changes in specific microorganisms and metabolites during the composting process, the data from microbiomes and metabolomes were correlated. Firstly, the correlations between CK21D, WJP21D, CaP21D, CK42D, WJP42D, and CaP42D were determined, and we calculated the top 10 highest abundance bacterial genera in six group samples, as well as the 10 VIP metabolites with the highest difference (Fig. 8A). Actinomycetaceae , Flavobacterium and Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium were negatively correlated with metabolites. Sphingobacterium , Stenotrophomonas , Klebsiella , Lactobacillus , Comamonas , and Pseudomonas were positively correlated with metabolites. Second, we calculated the top 20 most relevant microbial ASVs and differential metabolites (Fig. 8B). In the CK21D vs. WJP21D comparison group, ASV_36821 ( Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium ) and compound_3970 (Styrene), compound_2346 (Hexanoic acid), and compound_2561(L-Proline) were positively correlated. ASV_11077 ( Weissella ) and compound_0206 ((5E,8Z)-4,7-dihydroxy-2-methyl-2,3,4,7-tetrahydrooxecin-10-one), compound_ 1907 (Diacetoxyscirpenol), and compound_0208 ((5E)-7-methylidene-10-oxo-4-(propan-2-yl)undec-5-enoic acid) were positively correlated. In the CK21D vs. CaP21D comparison group, ASV_21585 ( Sphingobacterium ), ASV_20551( Acetobacter ), and ASV_26983 ( Sphingobacterium ) were positively correlated with most DAMs. In the CK42D vs. WJP42D comparison group, ASV_12156 (unclassified_ Rhodobacteraceae ), ASV_63724 ( Azotobacter ), ASV_55811 ( Sphingobacterium ), and ASV_ 59630 ( Dysgonomonas ) were positively correlated with compound_2726 (Mannitol), compound_1655 (Choline), compound_0650 (2',4'-Dihydroxy-3,4,6'-trimethoxydihydrochalcone), and compound_1654 (Choline O-Sulfate). In the CK42D vs. CaP42D comparison group, ASV_244 ( Sphingobacterium ), ASV_13381 ( Dysgonomonas ), and ASV_50383 (unclassified_ Enterobacteriaceae ) were positively correlated with most DAMs. Third, redundancy analysis (RDA) was used to analyze the relationship between physical and chemical indexes and the microorganisms of compost samples (Fig. 9 ). Total N and P component had a positive correlation with most DAMs in Fig. 9 . EC had a positive correlation with compound_3740 (Quebrachitol) and compound_1656(Choline), and a negative correlation with pH. Compound_0206 ((5E,8Z)-4,7-dihydroxy-2-methyl-2,3,4,7-tetrahydrooxecin-10-one), compound_2346 (Hexanoic acid), compound_2375 (Hydrocinnamic acid), and compound_2726 (Mannitol) were positively correlated with various phosphorus components. Discussion In order to accelerate the biodegradation of compost, several foreign functional strains or indigenous bacterial groups extracted from the original pile can be re-injected into the compost, which can improve the diversity of compost microbial community and improve the degree of compost humification [ 33 , 34 ]. Adding 1% nitrogen turn-over bacterial agent at the initial stage of composting can reduce nitrogen loss and effectively promote pig manure composting, but adding inoculation treatment has no significant effect on shortening composting time [ 34 ]. Similar results were also found in chicken manure and rice straw compost. It was observed that inoculation of ammonia-oxidizing bacteria could change the succession and diversity of bacterial communities and reduce ammonia emissions and nitrogen losses [ 35 ]. Studies have shown that inoculation of exotic microorganisms prolonged the high-temperature period and improved the diversity of bacteria and fungi communities, further increasing the molecular weight of compost products, the content of humic acid and fulvic acid-like compounds and the degree of humification in multi-stage inoculation [ 33 , 36 ]. Many studies have shown that Burkholderia has good adaptability, stability to microenvironment and various functions, such as mobilization of insoluble phosphorus, secretion of cellulase, promotion of plant growth, probiotic potential, etc [ 37 – 39 ]. We studied the effect of Burkholderia on the composting of T. grandis branch and leaf waste, and the results showed that the addition of Burkholderia changed the microbial community and metabolites of the compost. Based on the significant nitrogen fixation of phosphate additives in composting, scholars at home and abroad have conducted extensive research on low-cost phosphorus containing additive materials, including calcium magnesium phosphate fertilizer, superphosphate, double superphosphate, phosphate rock, phosphogypsum, etc [ 40 , 41 ]. Our results also show that calcium phosphate can be used as a commonly used phosphate fertilizer in agricultural production. Although its nitrogen fixation effect is significant during the composting process, it can be used as an effective nitrogen fixation additive to replace phosphoric acid and phosphate. The process of composting is intricate, involving a series of microbial actions. Throughout the process, various microorganisms undergo continuous succession, with distinct microbial populations present in each stage to facilitate the degradation and transformation of organic waste [ 42 ]. Our results indicate that the Shannon and Simpson indices of bacteria and fungi continuously decreased with the composting process. The PCA findings reveal notable variations in the microbial community structure across diverse composting stages and treatments. These outcomes are in line with prior research that has established the occurrence of bacterial and fungal community composition alterations during composting stages, and the impact of phosphorus-solubilizing microorganisms and phosphate on compost microbial composition [ 26 , 43 , 44 ]. Through random forest analysis, network analysis and KEGG pathway analysis, it was found that exogenous WJP and CaP treatment not only had a significant impact on the microbial community structure in the composting system, but also changed the correlation between microorganisms and physical and chemical indicators, functional pathways, phosphorus components, thus making the metabolites and phosphorus components of each treatment group different. Pedobacter is probably the most important bacterial decomposer in the early stages of decomposition in temperate forest ecosystems, as it participates in the degradation of cellulose and hemicellulose [ 45 , 46 ]. A variety of carbohydrates can be fermented by Anaerosporobacter [ 47 ]. Our results show that the abundance of Anaerosporobacter and Pedobacter increased, indicating that WJP and CaP treatments may promote cellulose and hemicellulose degradation and change the total carbon content. It can be seen that WJP and CaP treatments had an effect on the structure of the community in the samples, and the effects generated at different stages of the composting process are different. We believe that this is related to the material properties and the complex environment inside the pile [ 48 , 49 ]. In the process of organic matter decomposition, microbial communities and biochemical metabolic pathways play an irreplaceable role in a series of decomposition processes [ 50 ]. In this study, we employed multiple analytical methods to reveal the metabolic functional changes of microorganisms during the composting process influenced by WJP and CaP. Carbohydrate metabolism during composting can generate various compounds through the degradation of hemicellulose and cellulose [ 12 ]. The readily degradable substances that can be utilized are preferentially degraded by microorganisms, which then utilize more complex molecules such as phenol and lignin during the composting process [ 51 , 52 ]. Amino acids, as energy and carbon sources for bacterial metabolism, can also be produced during the composting process [ 45 , 53 ] According to the research results of [ 54 ], the more amino acid metabolic sequences, the more obvious the promotion of amino acid production and humus synthesis. These results are consistent with the results obtained in our un-target metabolome data, with a significant increase in differential metabolites related to amino acid metabolism. The most abundant metabolites of straw compost are lipids, including fatty acyls, sterols, glycerol phospholipids, sphingolipids, and glycerides [ 55 ]. In the later stage of composting, there are more metabolites of lipids, terpenoids, and polyketones [ 56 ]. At the later stage of composting, a large number of macromolecular substances polymerize, which may be related to the formation of humus in composting [ 55 ]. Our results fshowed that the differential metabolites associated with lipids and organic acids and derivatives treated with CaP are twice as high as those treated with WJP in both 21d and 42d. The results suggest that CaP alters the formation of some biological macromolecules. Environmental factors significantly influence the growth and function of microbial communities [ 57 ]. The results of the RDA showed that there was a significant correlation between microbial community composition and physicochemical characteristics during composting, with different physicochemical characteristics affecting the bacterial community composition. Bacterial communities are also controlled by the quality and quantity of various substrates such as nitrogen sources, and nitrogen sources affect microbial communities by affecting the availability of microbial elements [ 55 , 58 ]. changes in nutrient availability like calcium may be responsible for the effects of pH on bacterial communities [ 59 , 60 ]. Phosphate rocks dissolve during the composting process, due to organic degradation and bacterial secretion of organic acids [ 61 , 62 ]. By accumulating soluble P from rock phosphate-derived P fractions, a "priming effect" could be created, thereby promoting the conversion of non-labile to labile P, and this is associated with increased microbial activity [ 44 ]. Olsen P, NaOH-Pi, and HCl-Pi are the primary factors responsible for the alterations in bacterial community structure [ 44 ]. The presence of P and PSB has a highly notable influence on the composition of the bacterial community throughout the composting process [ 63 ]. Similar results were also shown in our results. Conclusions In summary, this study investigated the effects of phosphorus solubilizing microorganisms ( Burkholderia ) and calcium phosphate on the composting of T. grandis branches and leaves, as well as to explain the nutritional and metabolic markers related to the composting process. Compared with the control, Burkholderia inoculation and calcium phosphate treatment affected the phosphorus composition, pH, EC, nitrogen content of T. grandis branch and leaf waste compost. The L-valine degradation I, and S-methyl-5-thio-&α;-D-ribose 1-phosphate degradation were depleted under Burkholderia inoculation after 42 d. The sucrose degradation II (sucrose synthase) was depleted under calcium phosphate treatment after 42 d. On days 21 and 42, the differential metabolites associated with lipids and organic acids and derivatives treated with CaP were twice as high as those treated with WJP. Our results suggest that calcium phosphate treatment alters the formation of some biological macromolecules. The study also provides a theoretical support for the utilization of forest waste resources. Declarations Ethics approval and consent to participate The plants and microbial materials we use do not use transgenic technology. Torreya grandis is planted in the Donghu campus of Zhejiang agriculture and Forestry University (Hangzhou, Zhejiang Province). Phosphorus dissolving bacteria ( Burkholderia ) isolated from Torreya grandis rhizosphere soil. All samples collected in this study do not require specific permission. Consent for publication Not Applicable Availability of data and materials The raw data are available at the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) with the BioProject PRJNA1126422 (bacterial raw data) and PRJNA1127319(fungal raw data). Conflict of Interests The authors have no conflicts of interest to declare. Funding This work was supported by the cooperative forestry science and technology project of Zhejiang Provincial Academy (2022SY14); the “Pioneer” and “Leading Goose” R&D Program of Zhejiang (2022C02061 and 2022C02009); the Breeding of New Varieties of Torreya grandis Program (2021C02066-11); the National Natural Science Foundation of China (Grant no. 32171830). Authors’ contribution W. Y. and J. W. conceptualized the initial study; C.Y.,Y.G.and Q. W. were involved in the experimental layout and performed the lab experiments; C.Y. and Y.G. drafted the initial article; C.Y., Y.L.and L.W. performed the sequence analyses,All authors read and revised the manuscript and approved the final manuscript. Acknowledgments The 16S and ITS Amplicon sequencing service was provided by Personal Biotechnology Co., Ltd. Shanghai, China. References Kang MZ, Hua J, Wang XJ, de Reffye P, Jaeger M, Akaffou S. 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Cite Share Download PDF Status: Published Journal Publication published 02 Oct, 2024 Read the published version in BMC Microbiology → Version 1 posted Editorial decision: Revision requested 25 Aug, 2024 Reviews received at journal 19 Aug, 2024 Reviewers agreed at journal 02 Aug, 2024 Reviewers agreed at journal 01 Aug, 2024 Reviews received at journal 31 Jul, 2024 Reviewers agreed at journal 18 Jul, 2024 Reviewers invited by journal 18 Jul, 2024 Editor invited by journal 16 Jul, 2024 Editor assigned by journal 16 Jul, 2024 Submission checks completed at journal 16 Jul, 2024 First submitted to journal 26 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4641249","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":337849749,"identity":"8118eecb-682d-422a-9b4c-090d14e87016","order_by":0,"name":"Chenliang Yu","email":"","orcid":"","institution":"Zhejiang A \u0026 F University","correspondingAuthor":false,"prefix":"","firstName":"Chenliang","middleName":"","lastName":"Yu","suffix":""},{"id":337849750,"identity":"2f848832-49c8-4507-803b-baf62cb97f2e","order_by":1,"name":"Yuanyuan Guan","email":"","orcid":"","institution":"Zhejiang A \u0026 F University","correspondingAuthor":false,"prefix":"","firstName":"Yuanyuan","middleName":"","lastName":"Guan","suffix":""},{"id":337849751,"identity":"0646e313-d0bb-41cc-a1cb-53770ed0136a","order_by":2,"name":"Qi Wang","email":"","orcid":"","institution":"Zhejiang A \u0026 F University","correspondingAuthor":false,"prefix":"","firstName":"Qi","middleName":"","lastName":"Wang","suffix":""},{"id":337849752,"identity":"7cf91884-7128-4f39-93a7-64b297f49307","order_by":3,"name":"Yi Li","email":"","orcid":"","institution":"Zhejiang A \u0026 F University","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Li","suffix":""},{"id":337849753,"identity":"28a2ad9c-b700-4db8-9863-707fba261b93","order_by":4,"name":"Lei Wang","email":"","orcid":"","institution":"Zhejiang A \u0026 F University","correspondingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Wang","suffix":""},{"id":337849754,"identity":"875bcc51-5925-4cc1-8b8a-ebae6b031dfe","order_by":5,"name":"Weiwu Yu","email":"","orcid":"","institution":"Zhejiang A \u0026 F University","correspondingAuthor":false,"prefix":"","firstName":"Weiwu","middleName":"","lastName":"Yu","suffix":""},{"id":337849755,"identity":"7ce0656e-df01-411f-9893-b22f6b188d0f","order_by":6,"name":"Jiasheng Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVRIiWNgGAWjYHCCBIYPDAz8IJYE0VoYZzAwSDaQooWBmYckLQY3Eh5/tvljJ2FwgPngbR4GuzxitKRJ5/AkA7WwJVvzMCQXE9RiBtTCnCPBXGdwgMdMmofhQGIDEVqSP1sY1ANt4f9GtJYEaYaEw0AtPGzEabE/8yBNsufAcQnJw2zGlnMMkglrkWzPSf7w40+1BN/x5oc33lTYEdbCwMCTAKGZQYQBYfVAwH6AKGWjYBSMglEwggEANs04Xutq1fEAAAAASUVORK5CYII=","orcid":"","institution":"Zhejiang A \u0026 F University","correspondingAuthor":true,"prefix":"","firstName":"Jiasheng","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2024-06-26 08:45:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4641249/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4641249/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12866-024-03535-7","type":"published","date":"2024-10-02T15:57:39+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62083232,"identity":"b5523f37-57a6-47ac-82e6-ef39b070c561","added_by":"auto","created_at":"2024-08-09 06:10:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1131934,"visible":true,"origin":"","legend":"\u003cp\u003eChange in total P (TP), different P fractions, and total N (TN) during composting.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4641249/v1/8b6aa5594d2813d4e5463088.png"},{"id":62082584,"identity":"d5110d28-89f3-4ce6-8860-b52578006ce7","added_by":"auto","created_at":"2024-08-09 06:02:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":982635,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of microbial community structures. Distribution of bacteria (A) and fungi (B) in different samples at the family level. B. Alpha diversity index analysis of bacteria (C) and fungi (D) compost samples from different treatments.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4641249/v1/34abf1df453e1d1147b1f957.png"},{"id":62083674,"identity":"bfb067f0-7522-4896-8ced-39396b22fd67","added_by":"auto","created_at":"2024-08-09 06:18:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":817694,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of phosphorus-dissolving bacteria and calcium phosphate treatment on the change in microbial community composition. Principal component analysis of bacterial (A) and fungal (B) communities in different treatment groups. An analysis of the dominant bacteria (C) and fungi (D) in different samples using random forest classification.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4641249/v1/98ad62f0a9575579410e86cf.png"},{"id":62082585,"identity":"73c560b7-b65f-4264-b4f1-b9612ea6389e","added_by":"auto","created_at":"2024-08-09 06:02:07","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1462863,"visible":true,"origin":"","legend":"\u003cp\u003eKey taxons in each compost sample comparison group. A. Ternary diagram showing the change of bacteria enrichment ASVs. B. Manhattan diagram showing the change of bacteria enrichment ASVs. Filled triangles denote significantly enriched ASVs and solid circles denote significantly depleted ASVs. Insignificant or non-differentially enriched ASVs are displayed as solid squares. NotSig, not significant; CPM, counts per million reads.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4641249/v1/31744b020df924848002fb3e.png"},{"id":62082588,"identity":"061b28e2-05a3-4ebd-b59f-c2b8638493d2","added_by":"auto","created_at":"2024-08-09 06:02:07","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":6430810,"visible":true,"origin":"","legend":"\u003cp\u003eCo-occurrence network bacterial population analysis. In the upper and lower panels, ASVs are colored according to their modularity and genera, respectively. In the network, strong correlations (Spearman’s r \u0026gt; 0.6) and significant correlations (P \u0026lt; 0.05) were apparent. Positive correlations are indicated by red line, and negative correlations by green line. The node size is proportional to ASV abundance.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4641249/v1/60eb72cf4f0466ef0a267bd4.png"},{"id":62082593,"identity":"14b14c60-17f2-4f66-bf05-780353d8b736","added_by":"auto","created_at":"2024-08-09 06:02:07","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2277538,"visible":true,"origin":"","legend":"\u003cp\u003ePotential functional pathways of bacterial communities in the composting process analyzed using PICRUSt2 software. The top 10 KEGG pathways are displayed in each comparison group.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-4641249/v1/264bbb7f3334951e5eef3278.png"},{"id":62082594,"identity":"613e6973-bc08-40e0-a540-1b54d6432918","added_by":"auto","created_at":"2024-08-09 06:02:07","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":244656,"visible":true,"origin":"","legend":"\u003cp\u003eProportion and trend of main differential metabolites in composting. A. Number of differential metabolites identified in each comparative group. B. Classification of main differential metabolites in compost comparison groups.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-4641249/v1/eadfd52da2f389d51b8843bc.png"},{"id":62083235,"identity":"05297be8-9eaf-44d9-872f-48255ce91112","added_by":"auto","created_at":"2024-08-09 06:10:07","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":2113062,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis between microorganisms and metabolites. A. A heatmap shows the correlation of the top 10 bacterial genera with the highest abundance in six group samples and the 10 VIP metabolites with the highest difference. B. A network diagram shows the top 20 most relevant microbial ASVs and differential metabolites.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-4641249/v1/4910c1d9f9da38d129e898b6.png"},{"id":62083675,"identity":"ece20a9e-d065-49fc-8bac-987d492bcb64","added_by":"auto","created_at":"2024-08-09 06:18:07","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":1422407,"visible":true,"origin":"","legend":"\u003cp\u003eRedundancy analysis (RDA) of bacterial community, differential accumulation of metabolites, and P fractions.\u003c/p\u003e","description":"","filename":"Figure9.png","url":"https://assets-eu.researchsquare.com/files/rs-4641249/v1/3c3a984a9e13ef93ef74a128.png"},{"id":66097164,"identity":"18cb0fe0-b7cf-4927-a541-512b35d891c5","added_by":"auto","created_at":"2024-10-07 16:13:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":17361236,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4641249/v1/4d803beb-0ebb-4e0f-b513-54fcf2c34481.pdf"},{"id":62082591,"identity":"2a6cdfff-3b74-4fa4-b84e-cbecb99c4555","added_by":"auto","created_at":"2024-08-09 06:02:07","extension":"zip","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":10788115,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.zip","url":"https://assets-eu.researchsquare.com/files/rs-4641249/v1/3f085563c27d605dcb60654f.zip"},{"id":62083673,"identity":"b2f8b020-5fb6-407c-b2c1-477fc403aece","added_by":"auto","created_at":"2024-08-09 06:18:07","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":10481,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 1 \u003c/strong\u003eCo-occurrence network characteristics of all sample groups during the composting process.\u003c/p\u003e","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4641249/v1/b5acdeaa0bd331a0b0fd2b40.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effects of calcium phosphate and phosphorus-dissolving bacteria on microbial structure and function during Torreya grandis branch waste composting","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAs China's fruit industry grows, a significant quantity of waste materials such as branches and leaves are generated following the establishment of stable fruit tree production and tree structures [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Managing branch waste is thus increasingly important. Composting represents a viable strategy for harmlessly reducing and better utilizing resources in the context of agricultural and livestock waste management [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Composting efficiency is influenced by several key factors: water content, temperature, pH, organic matter content, carbon to nitrogen (C/N) ratio, and microbial agents [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Composting refers to a complex series of biochemical reactions involving microorganisms [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In addition, changes in the microbial community in response to the evolving pile environment are characteristic of the composting process by [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The succession of functional microorganisms has been used as an indicator to assess the ecological function and product maturity under the co-distribution of manure and crop residues, and can reflect the community distribution at the levels of the microbial family, genus, and phylum at different stages of composting [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Microbial community characteristics reflect the relationship between microbial changes and the pile environment, and they provide a reference for composting [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMacronutrient phosphorus (P) is essential for plants to grow and develop [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The total phosphorus content of the soil is high, but the content of available phosphorus is low [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The main reason for this is that a large amount of phosphorus in soil is bound by calcium, aluminum, iron, and other metal ions and stored in an invalid state [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The seasonal utilization rate of phosphate fertilizer is generally 10\u0026ndash;25% [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Although the total amount of phosphorus in soil increases when phosphorus fertilizer is applied, most of it is adsorbed, precipitated, or fixed by microorganisms in the soil, thereby, reducing the effective concentration of phosphorus [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Therefore, it is of great significance to fully consider and develop phosphorus recycling to decrease the use of phosphorus fertilizer and improve phosphorus use efficiency. This is also one of the major challenges facing current and future agricultural production.\u003c/p\u003e \u003cp\u003ePhosphorus-solubilizing microorganisms are abundant in soils. They can dissolve insoluble phosphorus, increasing the effective soluble phosphorus in the soil through acidification, chelation, and other ways This can be absorbed by crops to improve the use of phosphorus fertilizer and reduce the amount of phosphorus fertilizer applied [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In the last few years, efficient phosphorus-solubilizing bacteria have effectively improved the rate of utilization of mineral phosphorus in soil [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Various phosphorus-solubilizing bacteria have been reported, such as \u003cem\u003eBacillus\u003c/em\u003e, \u003cem\u003ePseudomonas\u003c/em\u003e, \u003cem\u003eErwinia\u003c/em\u003e, \u003cem\u003eBurkholderia\u003c/em\u003e, \u003cem\u003eRhizobium\u003c/em\u003e, \u003cem\u003eFlavobacterium\u003c/em\u003e, \u003cem\u003ePenicillium\u003c/em\u003e, and \u003cem\u003eAspergillus\u003c/em\u003e [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Agricultural waste contains plenty of nitrogen, phosphorus, and other elements that can be converted into inorganic compounds through fermentation for plant absorption and utilization [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Reports on the phosphorus-solubilization effect of Burkholderia in the composting process are scarce at present. Our research is thus of great significance for accelerating the conversion of insoluble phosphorus compounds into available phosphorus during the composting process of agricultural waste.\u003c/p\u003e \u003cp\u003e \u003cem\u003eTorreya grandis\u003c/em\u003e cv. \u003cem\u003eMerrillii\u003c/em\u003e is a rare and special dry fruit tree in China. With the continual expansion to the scale of planting, considerable waste is generated by pruning branches. Adding bacterial agents is a necessary means to improve composting efficiency, and has been applied to the treatment of agricultural by-product waste, kitchen garbage, and livestock and poultry manure [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Impact of phosphorus-solubilizing microorganisms on the composting has not been adequately studied and calcium phosphate on branches, leaves, and other waste materials of \u003cem\u003eT. grandis\u003c/em\u003e, as well as the nutrient and metabolite markers associated with the composting process. Investigating the use of nutrient resources is of paramount importance, as it can offer technical assistance in safeguarding the agricultural ecological environment and advancing development of sustainable agricultural.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eComposting experiments and treatments\u003c/h2\u003e \u003cp\u003eEach processed branch and leaf of \u003cem\u003eT.grandis\u003c/em\u003e weighed 10 kg and was ground into a powder with a particle size of 2 mm. We started composting by adding 10% calcium phosphate (CaP) or 5 mL/kg (1\u0026times;10\u003csup\u003e8\u003c/sup\u003e/ mL \u003cem\u003eBurkholderia\u003c/em\u003e) microbial inoculant (WJP), or adding both at the same time (CaP\u0026thinsp;+\u0026thinsp;WJP). The control group (CK) did not include any calcium phosphate or bacterial agents. Four treatments in the experiment, each with three replicates. The phosphorus-solubilization ability of Burkholderia sp. strain is shown in Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. We placed the mixture in a 25 L polyethylene fermentation tank (diameter 0.35 m, height 0.41 m). We adjusted the moisture content to 70%. The treatment total time was 42 days, and the pile was flipped every two days to maintain moisture content of around 70% by adding water.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePhosphorus and physicochemical analyses\u003c/h2\u003e \u003cp\u003eVarious phosphorus P fractions from the compost was extracted using an improved Hedley phosphorus classification method [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Total of 0.5 g compost sample was weighed into a 50 mL centrifuge tube, resin strips was added (1 \u0026times; 6 cm) and 30 mL of ddH\u003csub\u003e2\u003c/sub\u003eO, shaken overnight (16 hours, 220 rpm). The resin strip was extracted with 0.5 M HCl, and then we measured the resin phosphorus in the extract. To remove the residual liquid from the resin strip, we centrifuged the supernatant, added 30 mL of NaHCO3 (pH 8.5) to the sediment, shaken overnight (16 hours) and centrifuged, and determined the inorganic phosphorus and total phosphorus in the supernatant. Continued to precipitate by adding 30 mL of 0.1 M NaOH, shook it overnight (16 hours), and centrifuged the supernatant to determine the inorganic phosphorus and total phosphorus. Added 1 M HCl to the precipitate, shook it overnight, and determined the inorganic phosphorus in the supernatant. Finally, transferred all sample residues to a digestion tube, added 5 mL of conc. H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e, placed it in an electrothermal digestion apparatus, slowly heated it until the water evaporated to dryness and the temperature reached 360℃, added 30% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e every 15 minutes until the liquid was clear and transparent, and then heated it for 15 minutes to a constant volume to 30 mL overnight and determined the inorganic phosphorus. Using molybdenum antimony resistance colorimetry, all supernatants were measured for phosphorus content [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. A Kjeldahl nitrogen analyzer was used to determinetotal nitrogen (TN)using H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e digestions. A pH/EC meter was used to measure pH and electrical conductivity (EC).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDNA extraction and amplicon sequencing\u003c/h2\u003e \u003cp\u003eThe TIANamp Soil DNA Kit (DP336, TIANGEN, Beijing, China) was used to extract DNA from 0.25g sample, ITS1F (5\u0026prime;-GGAAGTAAAAGTCGTAACAAGG-3\u0026prime;)/ITS2R (5\u0026prime;-GCTGCGTTCTTCATCGATGC-3\u0026prime;), 338F (5\u0026prime;-ACTCCTACGGGAGGCAGCA-3\u0026prime;)/806R (5\u0026prime;-GGACTACHVGGGTWTCTAAT-3\u0026prime;), respectively. The sequence library was prepared with VAHTS Universal Plus DNA Library Prep Kit for Illumina (Code: ND617, Vazyme, Nanjing, China) using purified PCR products according to the manufacturer's instructions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eBioinformatic analysis\u003c/h2\u003e \u003cp\u003eBioinformation analysis of the microbiome was performed using QIIME 2 2019.4. The primer sequences were removed with QIIME Cutadapt Trim-paired, and the unmatched primers were discarded [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Then, Dada2 was used for quality control, denoising, stitching, and de-chimerism. The SILVA (version 13.2) and UNITE (version 8.0) databases were used to classify bacteria and fungi, respectively. Subsequently, ASV analysis, α-diversity analysis, β-diversity analysis, species composition analysis and the community differences between groups were analyzed. Functional prediction of microorganisms was performed using PICRUSt2 software. Spearman correlation coefficients base co-occurrence network analysis (Spearman\u0026rsquo;s r\u0026thinsp;\u0026gt;\u0026thinsp;0.6 or r\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;0.6; P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). ASV correlation coefficients were calculated using R's \u0026ldquo;corr.test\u0026rdquo; function in the software package \"psych 2.1.3\". With the help of Fruchterman\u0026ndash;Reingold layout algorithms, the co-occurrence networks were further visualized in Gephi, and the properties of the networks were collected using the \u0026ldquo;igraph\u0026rdquo; function [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eMetabolite extraction and metabolomics analysis\u003c/h2\u003e \u003cp\u003eAccurately weighed 0.1 g compost sample and ground it into powder in liquid nitrogen. Added 1 mL of 70% aqueous methanol for metabolite extraction. The extracts were separated, and then injected into an ultra-high performance liquid chromatography (UHPLC) system (Agilent 1290 Infinity LC, Agilent) with a C-18 column (2.1 \u0026times; 100 mm, 1.7 \u0026micro;m; Waters). An AB Triple TOF 6600 mass spectrometer was used to collect the primary and secondary spectra of the samples according to the operation of the instrument [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMetabolomics data analysis\u003c/h2\u003e \u003cp\u003eRaw data analysis was performed with Compound Discoverer 3.2. The metabolomics databases mzCloud, mzVault, Masslists, and Chemspider were used to identify the metabolites. Differential accumulated metabolites (DAMs) were examined the metabolites with different importance in projection (VIP) values\u0026thinsp;\u0026gt;\u0026thinsp;1.0, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and |Log2FC| \u0026gt; 1.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePhysicochemical indexes and variation during composting\u003c/h2\u003e \u003cp\u003eTotal phosphorus (TP) content was not different between WJP and CK (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). From days 0 to 21, the TP contents of CaP and CaP\u0026thinsp;+\u0026thinsp;WJP increased. The content of resin phosphorus increased in all treatments. The content of the resin phosphorus of CaP treated was higher than that of WJP and CaP\u0026thinsp;+\u0026thinsp;WJP after 42 days. The total phosphorus content of sodium bicarbonate treated with CaP increased the fastest, while the inorganic phosphorus content of sodium bicarbonate treated with WJP increased the fastest from days 21 to 42. The inorganic phosphorus content of sodium hydroxide increased throughout the treatment cycle, and the increase of the three composting treatments was greater than that of CK. The content of total sodium hydroxide phosphorus was similar to that of sodium hydroxide inorganic phosphorus, which generally increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Compared to control, EC of all treatments decreased at first and then increased on the 14th day, and the CaP treatment was the highest. On the 21th and 35th days, both WJP and CaP increased at first and then decreased. After 42 days, EC of CK and CaP\u0026thinsp;+\u0026thinsp;WJP treatments increased, while the WJP and CaP showed the opposite trend. The pH range of the three compost treatments and the control ranged from 6.12\u0026ndash;7.91 (Fig. S2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEffect of WJP and CaP on bacterial and fungal communities during composting\u003c/h2\u003e \u003cp\u003eFrom the compost samples of different composting stages (days 0, 21, and 42) and different treatments (CK, CaP, WJP, and CaP\u0026thinsp;+\u0026thinsp;WJP), 320,945 bacterial sequences were obtained, which were divided into 15759 ASVs (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). A total of 320,945 fungal sequences were obtained, which were divided into 2457 ASVs (Table S2). According to the rarefaction curve and rank abundance curve, the changes in the bacterial communities in the compost were effectively reflected in the high-throughput sequencing result (Fig. S3). At the family level, composting significantly changed bacterial and fungal communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). For the CK compost group, the levels of dominant bacteria at on day 0 were \u003cem\u003eEnterobacteriaceae\u003c/em\u003e (6.72%), \u003cem\u003eBurkholderiaceae\u003c/em\u003e (5.70%), and \u003cem\u003ePseudomonadaceae\u003c/em\u003e (3.8%). The dominant bacteria on day 21 were Enterobacteriaceae (23.98%), \u003cem\u003eSphingobacteriaceae\u003c/em\u003e (13.88%), and \u003cem\u003eRhizobiaceae\u003c/em\u003e (11.13%). The dominant bacteria on day 42 were \u003cem\u003eSphingobacteriaceae\u003c/em\u003e (15.27%), \u003cem\u003eRhizobiaceae\u003c/em\u003e (11.93%), and \u003cem\u003eEnterobacteriaceae\u003c/em\u003e (9.39%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). For the WJP-treated compost group, the dominant bacteria on day 21 were \u003cem\u003eEnterobacteriaceae\u003c/em\u003e (28.93%), \u003cem\u003eActinomycetaceae\u003c/em\u003e (10.17%), and \u003cem\u003eSphingobacteriaceae\u003c/em\u003e (8.21%). However, the proportions of these three bacteria were 5.09%, 19.55%, and 5.42%, respectively on day 42. \u003cem\u003eRhizobiaceae\u003c/em\u003e increased from 6.63\u0026ndash;10.25%, and \u003cem\u003eFlavobactereae\u003c/em\u003e increased from 4.33\u0026ndash;10.72%. For the CaP-treated compost group, \u003cem\u003eEnterobacteriaceae\u003c/em\u003e decreased from 36.87% on day 21 to 10.59% on day 42, and \u003cem\u003eXanthomonadaceae\u003c/em\u003e decreased from 11.02\u0026ndash;4.65%. \u003cem\u003eActinomycetaceae\u003c/em\u003e increased from 7.02% on day 21 to 13.46% on day 42, and \u003cem\u003eFlavobacteriaceae\u003c/em\u003e increased from 1.65\u0026ndash;14.23%. For the CaP\u0026thinsp;+\u0026thinsp;WJP-treated compost group, \u003cem\u003eEnterobacteriaceae\u003c/em\u003e decreased from 12.92\u0026ndash;6.48%. For fungi, \u003cem\u003eDipodascaceae\u003c/em\u003e and \u003cem\u003ePichiaceae\u003c/em\u003e were the main dominant fungi in the composting process (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). The bacterial Chao1 value of compost samples with different treatments increased, while the Shannon and Simpson indices decreased (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). The results showed an increase in the number of bacterial but a decrease in their diversity. Decline Chao1, Shannon, and Simpson indices for fungi indicate that fungi abundance and diversity reduced (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results of principal component analysis (PCA) show that the samples treated are closely gathered (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Taxa for different treatment compost groups were identified through random forest classification (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). It was found that WJP treatment increased abundance of \u003cem\u003ePedobacter\u003c/em\u003e, \u003cem\u003eGluconacetobacter\u003c/em\u003e and \u003cem\u003eAnaerosporobacter\u003c/em\u003e. CaP treatment increased the abundance of \u003cem\u003ePedobacter\u003c/em\u003e, \u003cem\u003eActinomycetaceae\u003c/em\u003e, \u003cem\u003eAnaerosporobacter\u003c/em\u003e, \u003cem\u003eDelftia\u003c/em\u003e, and \u003cem\u003eGluconobacter\u003c/em\u003e. The abundance of \u003cem\u003eBrevundimonas\u003c/em\u003e, \u003cem\u003eChryseobium\u003c/em\u003e, \u003cem\u003eAzotobacter\u003c/em\u003e, \u003cem\u003eKetogulonicigenium\u003c/em\u003e, \u003cem\u003eWeissella\u003c/em\u003e, \u003cem\u003eAcetobacter\u003c/em\u003e, \u003cem\u003eSphingobacterium\u003c/em\u003e and \u003cem\u003eProcabacter\u003c/em\u003e was reduced (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). For fungi, WJP treatment increased the abundance of had an increase in \u003cem\u003ePichia\u003c/em\u003e abundance, \u003cem\u003eDipodascus\u003c/em\u003e abundance increased when treated with CaP.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDifferentially abundant core and specific taxa under WJP or CaP treatment\u003c/h2\u003e \u003cp\u003eWe also used DESeq software to screen differential abundant bacteria in the composting process based on a fold change of \u0026gt;\u0026thinsp;2 or \u0026lt;\u0026thinsp;0.5 and an adjusted P\u0026thinsp;\u0026lt;\u0026thinsp;0.05(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In the CK21D vs WJP21D comparison group, 100 differentials bacterial ASVs, including 31 enriched and 69 depleted ASVs, were identified. These differential bacteria were distributed in three phyla: Bacteroidetes (22ASVs), Firmicutes (11 ASVs), and Proteobacteria (67ASVs). A total of 109 differential bacterial ASVs, including 43 enriched and 66 depleted ASVs, were identified in the CK21D vs. CaP21D comparison group. These differential bacteria were distributed in three phyla: Bacteroidetes (22 ASVs), Firmicutes (14 ASVs), and Proteobacteria (73ASVs). In the CK42D vs WJP42D comparison group, 121 differentials bacterial ASVs, including 58 enriched and 63 depleted ASVs, were identified. These differential bacteria were distributed in four phyla: Actinobacteria (5 ASVs), Bacteroidetes (31 ASVs), Firmicutes (28 ASVs), and Proteobacteria (57 ASVs). A total of 108 differential bacterial ASVs, including 43 enriched and 65 depleted ASVs, were identified in the CK42D vs. CaP42D comparison group. These differential bacteria were distributed in four phyla: Actinobacteria (1 ASV), Bacteroidetes (29 ASVs), Firmicutes (28 ASVs), and Proteobacteria (50 ASVs).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe species composition of the bacterial communities changed significantly as a result of a co-occurrence network analysis built at the ASV level (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Table\u0026nbsp;1). In CK0D, a total of 134 nodes and 1002 edges, including 60.98% and 39.02% positive correlations of the ecological network, were obtained. In composting 21D, ecological networks of 145, 130, and 141 nodes with 859, 643, and 852 edges were obtained for the CK, WJP, and CaP treatment groups, respectively. In composting 42D, networks of 144, 108, and 116 nodes with 792, 516, and 561 edges were obtained for the CK, WJP, and CaP treatment groups, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eEffects of WJP and CaP on microbiome functions in the composting process\u003c/h2\u003e \u003cp\u003ePICRUSt2 software was used to determine the functional difference of microbiota in the composting process of WJP or CAP treatments. In Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, the top 10 KEGG pathways of all nine comparison groups are shown. In the CK0D vs. CK21D comparison group, aerobactin biosynthesis, coenzyme M biosynthesis I, and the superpathway of methylglyoxal degradation increased, while the superpathway of bacteriochlorophyll a biosynthesis, chlorophyllide a biosynthesis I (aerobic, light-dependent), and factor 420 biosynthesis were depleted. In the CK0D vs. CK42D comparison group, aerobactin biosynthesis, pyrimidine deoxyribonucleotides de novo biosynthesis IV, and pyrimidine deoxyribonucleotides biosynthesis from CTP increased, while chlorophyllide a biosynthesis I (aerobic, light-dependent), factor 420 biosynthesis, and vitamin E biosynthesis (tocopherols) were depleted. In the CK21D vs. WJP21D comparison group, the superpathway of demethylmenaquinol-6 biosynthesis II, chondroitin sulfate degradation I (bacterial), and the superpathway of bacteriochlorophyll a biosynthesis increased, while mycolyl-arabinogalactan-peptidoglycan complex biosynthesis, isoprene biosynthesis II (engineered), and coenzyme B biosynthesis were depleted. In the CK21D vs. CaP21D comparison group, the superpathway of bacteriochlorophyll a biosynthesis, chondroitin sulfate degradation I (bacterial), and D-cycloserine biosynthesis increased, while mycolyl-arabinogalactan-peptidoglycan complex biosynthesis, isoprene biosynthesis II (engineered), and coenzyme B biosynthesis were depleted. In the CK42D vs. WJP42D comparison group, p-cumate degradation, p-cymene degradation, and reductive acetyl coenzyme A pathway increased, while the superpathway of bacteriochlorophyll a biosynthesis, L-valine degradation I, and S-methyl-5-thio-\u0026amp;alpha;-D-ribose 1-phosphate degradation were depleted. In the CK42D vs. CaP42D comparison group, D-cycloserine biosynthesis, adenosine nucleotides degradation IV, and the reductive acetyl coenzyme A pathway increased, while sucrose degradation II (sucrose synthase), mycolyl-arabinogalactan-peptidoglycan complex biosynthesis, and pyrimidine deoxyribonucleotides de novo biosynthesis IV was depleted.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eEffects of WJP and CaP on metabolites in the composting process\u003c/h2\u003e \u003cp\u003eWe used liquid chromatography-mass spectrometry (LC-MS) to identify and quantitatively analyze the compost metabolites. There were 4312 metabolites identified in total. Based on principal component analysis (PCA), the treatment and control groups were significantly different, and metabolomes in the same group we closely clustered (Fig. S4). We further identified the significantly different accumulated metabolites (DAMs) between different treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). A total of 90, 159, 139, and 181 DAMs were identified in the CK21D vs. WJP21D, CK21D vs. CaP21D, CK42D vs. WJP42D, and CK21D vs. CaP21D comparison groups, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). These DAMs were classified into 12 main classes (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eCombined analysis of microbiomes and metabolomes\u003c/h2\u003e \u003cp\u003eIn order to elucidate the changes in specific microorganisms and metabolites during the composting process, the data from microbiomes and metabolomes were correlated. Firstly, the correlations between CK21D, WJP21D, CaP21D, CK42D, WJP42D, and CaP42D were determined, and we calculated the top 10 highest abundance bacterial genera in six group samples, as well as the 10 VIP metabolites with the highest difference (Fig.\u0026nbsp;8A). \u003cem\u003eActinomycetaceae\u003c/em\u003e, \u003cem\u003eFlavobacterium\u003c/em\u003e and \u003cem\u003eAllorhizobium-Neorhizobium-Pararhizobium-Rhizobium\u003c/em\u003e were negatively correlated with metabolites. \u003cem\u003eSphingobacterium\u003c/em\u003e, \u003cem\u003eStenotrophomonas\u003c/em\u003e, \u003cem\u003eKlebsiella\u003c/em\u003e, \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eComamonas\u003c/em\u003e, and \u003cem\u003ePseudomonas\u003c/em\u003e were positively correlated with metabolites. Second, we calculated the top 20 most relevant microbial ASVs and differential metabolites (Fig.\u0026nbsp;8B). In the CK21D vs. WJP21D comparison group, ASV_36821 (\u003cem\u003eAllorhizobium-Neorhizobium-Pararhizobium-Rhizobium\u003c/em\u003e) and compound_3970 (Styrene), compound_2346 (Hexanoic acid), and compound_2561(L-Proline) were positively correlated. ASV_11077 (\u003cem\u003eWeissella\u003c/em\u003e) and compound_0206 ((5E,8Z)-4,7-dihydroxy-2-methyl-2,3,4,7-tetrahydrooxecin-10-one), compound_ 1907 (Diacetoxyscirpenol), and compound_0208 ((5E)-7-methylidene-10-oxo-4-(propan-2-yl)undec-5-enoic acid) were positively correlated. In the CK21D vs. CaP21D comparison group, ASV_21585 (\u003cem\u003eSphingobacterium\u003c/em\u003e), ASV_20551(\u003cem\u003eAcetobacter\u003c/em\u003e), and ASV_26983 (\u003cem\u003eSphingobacterium\u003c/em\u003e) were positively correlated with most DAMs. In the CK42D vs. WJP42D comparison group, ASV_12156 (unclassified_\u003cem\u003eRhodobacteraceae\u003c/em\u003e), ASV_63724 (\u003cem\u003eAzotobacter\u003c/em\u003e), ASV_55811 (\u003cem\u003eSphingobacterium\u003c/em\u003e), and ASV_ 59630 (\u003cem\u003eDysgonomonas\u003c/em\u003e) were positively correlated with compound_2726 (Mannitol), compound_1655 (Choline), compound_0650 (2',4'-Dihydroxy-3,4,6'-trimethoxydihydrochalcone), and compound_1654 (Choline O-Sulfate). In the CK42D vs. CaP42D comparison group, ASV_244 (\u003cem\u003eSphingobacterium\u003c/em\u003e), ASV_13381 (\u003cem\u003eDysgonomonas\u003c/em\u003e), and ASV_50383 (unclassified_\u003cem\u003eEnterobacteriaceae\u003c/em\u003e) were positively correlated with most DAMs.\u003c/p\u003e \u003cp\u003eThird, redundancy analysis (RDA) was used to analyze the relationship between physical and chemical indexes and the microorganisms of compost samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Total N and P component had a positive correlation with most DAMs in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e. EC had a positive correlation with compound_3740 (Quebrachitol) and compound_1656(Choline), and a negative correlation with pH. Compound_0206 ((5E,8Z)-4,7-dihydroxy-2-methyl-2,3,4,7-tetrahydrooxecin-10-one), compound_2346 (Hexanoic acid), compound_2375 (Hydrocinnamic acid), and compound_2726 (Mannitol) were positively correlated with various phosphorus components.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn order to accelerate the biodegradation of compost, several foreign functional strains or indigenous bacterial groups extracted from the original pile can be re-injected into the compost, which can improve the diversity of compost microbial community and improve the degree of compost humification [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Adding 1% nitrogen turn-over bacterial agent at the initial stage of composting can reduce nitrogen loss and effectively promote pig manure composting, but adding inoculation treatment has no significant effect on shortening composting time [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Similar results were also found in chicken manure and rice straw compost. It was observed that inoculation of ammonia-oxidizing bacteria could change the succession and diversity of bacterial communities and reduce ammonia emissions and nitrogen losses [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Studies have shown that inoculation of exotic microorganisms prolonged the high-temperature period and improved the diversity of bacteria and fungi communities, further increasing the molecular weight of compost products, the content of humic acid and fulvic acid-like compounds and the degree of humification in multi-stage inoculation [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Many studies have shown that Burkholderia has good adaptability, stability to microenvironment and various functions, such as mobilization of insoluble phosphorus, secretion of cellulase, promotion of plant growth, probiotic potential, etc [\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. We studied the effect of \u003cem\u003eBurkholderia\u003c/em\u003e on the composting of \u003cem\u003eT. grandis\u003c/em\u003e branch and leaf waste, and the results showed that the addition of \u003cem\u003eBurkholderia\u003c/em\u003e changed the microbial community and metabolites of the compost. Based on the significant nitrogen fixation of phosphate additives in composting, scholars at home and abroad have conducted extensive research on low-cost phosphorus containing additive materials, including calcium magnesium phosphate fertilizer, superphosphate, double superphosphate, phosphate rock, phosphogypsum, etc [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Our results also show that calcium phosphate can be used as a commonly used phosphate fertilizer in agricultural production. Although its nitrogen fixation effect is significant during the composting process, it can be used as an effective nitrogen fixation additive to replace phosphoric acid and phosphate.\u003c/p\u003e \u003cp\u003eThe process of composting is intricate, involving a series of microbial actions. Throughout the process, various microorganisms undergo continuous succession, with distinct microbial populations present in each stage to facilitate the degradation and transformation of organic waste [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Our results indicate that the Shannon and Simpson indices of bacteria and fungi continuously decreased with the composting process. The PCA findings reveal notable variations in the microbial community structure across diverse composting stages and treatments. These outcomes are in line with prior research that has established the occurrence of bacterial and fungal community composition alterations during composting stages, and the impact of phosphorus-solubilizing microorganisms and phosphate on compost microbial composition [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThrough random forest analysis, network analysis and KEGG pathway analysis, it was found that exogenous WJP and CaP treatment not only had a significant impact on the microbial community structure in the composting system, but also changed the correlation between microorganisms and physical and chemical indicators, functional pathways, phosphorus components, thus making the metabolites and phosphorus components of each treatment group different. Pedobacter is probably the most important bacterial decomposer in the early stages of decomposition in temperate forest ecosystems, as it participates in the degradation of cellulose and hemicellulose [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. A variety of carbohydrates can be fermented by Anaerosporobacter [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Our results show that the abundance of Anaerosporobacter and Pedobacter increased, indicating that WJP and CaP treatments may promote cellulose and hemicellulose degradation and change the total carbon content. It can be seen that WJP and CaP treatments had an effect on the structure of the community in the samples, and the effects generated at different stages of the composting process are different. We believe that this is related to the material properties and the complex environment inside the pile [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the process of organic matter decomposition, microbial communities and biochemical metabolic pathways play an irreplaceable role in a series of decomposition processes [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. In this study, we employed multiple analytical methods to reveal the metabolic functional changes of microorganisms during the composting process influenced by WJP and CaP. Carbohydrate metabolism during composting can generate various compounds through the degradation of hemicellulose and cellulose [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The readily degradable substances that can be utilized are preferentially degraded by microorganisms, which then utilize more complex molecules such as phenol and lignin during the composting process [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Amino acids, as energy and carbon sources for bacterial metabolism, can also be produced during the composting process [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] According to the research results of [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], the more amino acid metabolic sequences, the more obvious the promotion of amino acid production and humus synthesis. These results are consistent with the results obtained in our un-target metabolome data, with a significant increase in differential metabolites related to amino acid metabolism. The most abundant metabolites of straw compost are lipids, including fatty acyls, sterols, glycerol phospholipids, sphingolipids, and glycerides [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. In the later stage of composting, there are more metabolites of lipids, terpenoids, and polyketones [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. At the later stage of composting, a large number of macromolecular substances polymerize, which may be related to the formation of humus in composting [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Our results fshowed that the differential metabolites associated with lipids and organic acids and derivatives treated with CaP are twice as high as those treated with WJP in both 21d and 42d. The results suggest that CaP alters the formation of some biological macromolecules.\u003c/p\u003e \u003cp\u003eEnvironmental factors significantly influence the growth and function of microbial communities [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. The results of the RDA showed that there was a significant correlation between microbial community composition and physicochemical characteristics during composting, with different physicochemical characteristics affecting the bacterial community composition. Bacterial communities are also controlled by the quality and quantity of various substrates such as nitrogen sources, and nitrogen sources affect microbial communities by affecting the availability of microbial elements [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. changes in nutrient availability like calcium may be responsible for the effects of pH on bacterial communities [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Phosphate rocks dissolve during the composting process, due to organic degradation and bacterial secretion of organic acids [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. By accumulating soluble P from rock phosphate-derived P fractions, a \"priming effect\" could be created, thereby promoting the conversion of non-labile to labile P, and this is associated with increased microbial activity [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Olsen P, NaOH-Pi, and HCl-Pi are the primary factors responsible for the alterations in bacterial community structure [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The presence of P and PSB has a highly notable influence on the composition of the bacterial community throughout the composting process [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Similar results were also shown in our results.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, this study investigated the effects of phosphorus solubilizing microorganisms (\u003cem\u003eBurkholderia\u003c/em\u003e) and calcium phosphate on the composting of \u003cem\u003eT. grandis\u003c/em\u003e branches and leaves, as well as to explain the nutritional and metabolic markers related to the composting process. Compared with the control, Burkholderia inoculation and calcium phosphate treatment affected the phosphorus composition, pH, EC, nitrogen content of \u003cem\u003eT. grandis\u003c/em\u003e branch and leaf waste compost. The L-valine degradation I, and S-methyl-5-thio-\u0026amp;α;-D-ribose 1-phosphate degradation were depleted under Burkholderia inoculation after 42 d. The sucrose degradation II (sucrose synthase) was depleted under calcium phosphate treatment after 42 d. On days 21 and 42, the differential metabolites associated with lipids and organic acids and derivatives treated with CaP were twice as high as those treated with WJP. Our results suggest that calcium phosphate treatment alters the formation of some biological macromolecules. The study also provides a theoretical support for the utilization of forest waste resources.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe plants and microbial materials we use do not use transgenic technology. \u003cem\u003eTorreya grandis\u003c/em\u003e is planted in the Donghu campus of Zhejiang agriculture and Forestry University (Hangzhou, Zhejiang Province). Phosphorus dissolving bacteria (\u003cem\u003eBurkholderia\u003c/em\u003e) isolated from Torreya grandis rhizosphere soil. All samples collected in this study do not require specific permission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data are available at the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) with the BioProject PRJNA1126422 (bacterial raw data) and PRJNA1127319(fungal raw data).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;This work was supported by the cooperative forestry science and technology project of Zhejiang Provincial Academy (2022SY14); the \u0026ldquo;Pioneer\u0026rdquo; and \u0026ldquo;Leading Goose\u0026rdquo; R\u0026amp;D Program of Zhejiang (2022C02061 and 2022C02009); the Breeding of New Varieties of \u003cem\u003eTorreya grandis\u003c/em\u003e Program (2021C02066-11); the National Natural Science Foundation of China (Grant no. 32171830).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eW. Y. and J. W. conceptualized the initial study; C.Y.,Y.G.and Q. W. were involved in the experimental layout and performed the lab experiments; C.Y. and Y.G. drafted the initial article; C.Y., Y.L.and L.W. performed the sequence analyses,All authors read and revised the manuscript and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 16S and ITS Amplicon sequencing service was provided by Personal Biotechnology Co., Ltd. Shanghai, China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eKang MZ, Hua J, Wang XJ, de Reffye P, Jaeger M, Akaffou S. Estimating Sink Parameters of Stochastic Functional-Structural Plant Models Using Organic Series-Continuous and Rhythmic Development. Front Plant Sci. 2018; 9:1688.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eQiu ZP,\u0026nbsp;Chen GZ,\u0026nbsp;Qiu DL. 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Changes Alter Effects of Dietary Phytase Supplementation on the Fecal Microbiome in Fattening Pigs.\u0026nbsp;Microorganisms.\u0026nbsp;2020;\u0026nbsp;8:1073.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eBiswas DR,\u0026nbsp;Narayanasamy G.\u0026nbsp;Rock phosphate enriched compost:\u0026nbsp;An approach to improve low-grade Indian rock phosphate.\u0026nbsp;Bioresource Technol.\u0026nbsp;2007;\u0026nbsp;97:2243-2251.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eWei YQ,\u0026nbsp;Zhao Y,\u0026nbsp;Shi MZ,\u0026nbsp;Cao ZY,\u0026nbsp;Lu Q,\u0026nbsp;Yang TX,\u0026nbsp;Fan YY,\u0026nbsp;Wei ZM.\u0026nbsp;Effect of organic acids production and bacterial community on the possible mechanism of phosphorus solubilization during composting with enriched phosphate-solubilizing bacteria inoculation.\u0026nbsp;Bioresource Technol.\u0026nbsp;2018;\u0026nbsp;247:190-199.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eWei YQ, Zhao Y, Fan YY, Lu QA, Li MX, Wei QB, Zhao Y, Cao ZY, Wei ZM. \u0026nbsp;Impact of phosphate-solubilizing bacteria inoculation methods on phosphorus transformation and long-term utilization in composting. Bioresource Technol. 2017; 241:134-141. 9\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"calcium phosphate, composting, metabolite, microbial community, phosphorus fractions","lastPublishedDoi":"10.21203/rs.3.rs-4641249/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4641249/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTo investigate the effects of phosphorus solubilizing microorganisms and calcium phosphate on the composting of \u003cem\u003eTorreya grandis\u003c/em\u003e branches and leaves, as well as to explain the nutritional and metabolic markers related to the composting process.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this study, we employed amplicon sequencing and untargeted metabolomics analysis to examine the interplay among phosphorus (P) components, microbial communities, and metabolites during \u003cem\u003eT. grandis\u003c/em\u003e branch and leaf waste composting that underwent treatment with calcium phosphate and phosphate-solubilizing bacteria (\u003cem\u003eBurkholderia\u003c/em\u003e).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe results indicated that \u003cem\u003eBurkholderia\u003c/em\u003e inoculation and calcium phosphate treatment affected the phosphorus composition, pH, EC, and nitrogen content. Furthermore, these treatments significantly affected the diversity and structure of bacterial and fungal communities, altering microbial and metabolite interactions. The differential metabolites associated with lipids and organic acids and derivatives treated with calcium phosphate treatment are twice as high as those treated with Burkholderia in both 21d and 42d. The results suggest that calcium phosphate treatment alters the formation of some biological macromolecules.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThese results extend our comprehension of the coupling of matter transformation and community succession in composting with the addition of calcium phosphate and phosphate-solubilizing bacteria.\u003c/p\u003e","manuscriptTitle":"Effects of calcium phosphate and phosphorus-dissolving bacteria on microbial structure and function during Torreya grandis branch waste composting","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-09 06:02:02","doi":"10.21203/rs.3.rs-4641249/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-25T21:36:18+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-19T12:40:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"32383320981097042094348964578974473771","date":"2024-08-02T16:46:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"214431972162057006491743364021823364765","date":"2024-08-01T19:19:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-31T18:58:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"157571298769920019346037988888128327696","date":"2024-07-18T14:39:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-18T11:47:33+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-16T09:44:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-16T09:34:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-16T09:30:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Microbiology","date":"2024-06-26T08:43:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7eff9f0c-52f4-4210-82d0-71976e6a5d9e","owner":[],"postedDate":"August 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-10-07T16:07:36+00:00","versionOfRecord":{"articleIdentity":"rs-4641249","link":"https://doi.org/10.1186/s12866-024-03535-7","journal":{"identity":"bmc-microbiology","isVorOnly":false,"title":"BMC Microbiology"},"publishedOn":"2024-10-02 15:57:39","publishedOnDateReadable":"October 2nd, 2024"},"versionCreatedAt":"2024-08-09 06:02:02","video":"","vorDoi":"10.1186/s12866-024-03535-7","vorDoiUrl":"https://doi.org/10.1186/s12866-024-03535-7","workflowStages":[]},"version":"v1","identity":"rs-4641249","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4641249","identity":"rs-4641249","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}