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Effects of Bacillus subtilis on carbon components and microbial functional metabolism during cow manure–straw composting
Bioresource Technology 303 (2020) 122868
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Effects of Bacillus subtilis on carbon components and microbial functional metabolism during cow manure–straw composting
T
Manli Duana, Yuhua Zhanga, Beibei Zhoua, , Zhenlun Qina, Junhu Wua, Quanjiu Wanga, Yanan Yinb ⁎
a
State Key Laboratory of Eco-hydraulics in Northwest Arid Region of China, Xi’an University of Technology, Xi’an 710048, China Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, School of Environmental and Municipal Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China
b
GRAPHICAL ABSTRACT
ARTICLE INFO
ABSTRACT
Keywords: Bacillus subtilis Carbon Composting Functional metabolism Redundancy analysis
This study is the first to investigate the changes in the composting process and carbon conversion in a cow manure–straw compost matrix with Bacillus subtilis added at four different levels (0, 0.5%, 1%, and 2% w/w compost), and to explain the mechanism responsible for carbon conversion through microbial functional metabolism. Inoculation with Bacillus subtilis at 2% had the best effect on fermentation among all treatments, but it inhibited the synthesis of total organic carbon and humus. Bacillus subtilis at 0.5% reduced mineralization in the cooling and maturity stages of composting, and enhanced the humification of carbon. The total organic carbon and humic sequence contents were significantly higher with Bacillus subtilis at 0.5% (12.5% and 20.2%, respectively) than Bacillus subtilis at 2% (P < 0.05). Redundancy analysis demonstrated that the pH and microbial functional metabolism were closely related to carbon sequestration during composting.
1. Introduction The large-scale development of modern livestock breeding has led to the production of large volumes of livestock manure, which is a challenge for the ecological environment. According to statistics for 2017, the annual output of manure in China was about 3.8 billion tons
⁎
(Ma et al., 2018). Aerobic composting is an effective technique for treating solid organic waste because it can convert animal manure into stable organic fertilizer for use as a soil amendment. Aerobic composting involves the decomposition and transformation of organic matter, and the synthesis of humus due to the activities of microorganisms (Zhao et al., 2017; Yu et al., 2019a; Yin et al., 2019b).
Corresponding author. E-mail address: [email protected] (B. Zhou).
https://doi.org/10.1016/j.biortech.2020.122868 Received 18 November 2019; Received in revised form 14 January 2020; Accepted 21 January 2020 Available online 28 January 2020 0960-8524/ © 2020 Elsevier Ltd. All rights reserved.
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However, this process is often accompanied by organic carbon losses in the form of greenhouse gases such as CO2 and CH4. These emissions decrease carbon sequestration during composting and affect the quality of the compost, but they also aggravate the greenhouse effect (Zhang et al., 2019). Previous studies have shown that the proportions of composting materials, composting methods, and composting conditions can affect the succession of the microbial community to different degrees (An et al., 2012; Wang et al., 2017a; Zhang et al., 2018; Li et al., 2019), thereby affecting the mineralization and humification of compost. Humification is a key step for carbon sequestration in compost, and fixing carbon in humus is important for reducing carbon losses (Qi et al., 2019). Previous studies of compost humification focused mainly on humic substances (HS) and their components comprising humic acid (HA) and fulvic acid (FA) (Yu et al., 2019a; Zhu et al., 2020). It has been shown that HA and FA can be transformed into each other due to the activities of microorganisms, and that an increase in HA and decrease in FA occur mainly in the thermophilic phase of composting, and thus the HA content can reflect the maturity of compost (Wang et al., 2019; Yu et al., 2019b). HS precursors such as amino acids, polyphenols, and soluble sugars are the main factors that contribute to the formation of HS (Zhang et al., 2019; Zhu et al., 2020). Microorganisms can promote the formation of HS precursors via the metabolism of organic matter. Most HS precursors can be completely mineralized by microorganisms to produce CO2 (via the tricarboxylic acid (TCA) cycle) during the mesophilic and thermophilic stages of composting (Lu et al., 2018; Wang et al., 2019). Therefore, improving the pathways for microbial metabolism, reducing mineralization, and enhancing the transformation of organic matter into HS are effective for carbon sequestration. In recent years, many studies have investigated the degradation and formation of HS from organic components during composting after inoculation with bacterial strains or supplementation with additives (Voběrková et al., 2017; Wu et al., 2018). Previous research into the humification mechanism has focused mainly on analyses of microbial communities by determining their changes during composting via highthroughput sequencing, and by exploring the relationships between humus and members of the microbial community by conducting network analysis in order to understand the changes in the physical and chemical properties of compost (Wei et al., 2018). In fact, microbial metabolism is fundamentally responsible for the changes in the properties of compost (Wang et al., 2018). Microorganisms release energy and nutrients by metabolizing organic matter, thereby promoting the maturation of compost as well as allowing their growth and reproduction. Carbon and nitrogen are often lost in this process, but few studies have investigated their changes. Therefore, the present study investigated the changes in humus by predicting the functional genes associated with microbial metabolism and determining the carbon transformation pathway. Bacillus subtilis is a thermophilic spore-producing Gram-positive bacterium and it is present in the composting process. The spores produced by Bacillus subtilis can persist in high temperature, high acid, or high alkali conditions, as well as other adverse environments. Bacillus subtilis is the dominant species in compost (Siu-Rodas et al., 2018). Many enzymes are secreted by Bacillus subtilis, such as protease, cellulase, amylase, and phytase, which can compensate for the enzymes lacking in other microorganisms to promote their growth (David and Gary, 1997). It was shown that an extract from Bacillus subtilis had a high cellulase activity during the decomposition of cellulose, and it effectively promoted the degradation of cellulose (Siu-Rodas et al., 2018). Yin et al. (2019a) found that Bacillus is closely related to carbohydrate metabolism using the Biolog method. However, the effects of Bacillus subtilis on the transformation of carbon and the functional genes associated with carbon metabolism during composting require further analysis. In this study, cow manure and wheat straw were used as the composting materials in an aerobic composting experiment to explore the
effects of different concentrations of Bacillus subtilis on the compost maturation process and carbon transformation mechanisms. In addition, PICRUSt was used to predict the metabolic functions of microorganisms during different composting stages in order to elucidate the carbon transformation mechanism. Finally, the appropriate amount of Bacillus subtilis was determined for accelerating the composting process, reducing carbon losses, and improving the compost quality. 2. Materials and methods 2.1. Experimental design and sample collection The raw compost materials used in this study comprised cattle manure and wheat stalks. Fresh cow dung was collected from Shaanxi Qinbao Animal Husbandry Co. Ltd and wheat straw was collected from a local farm in Yangling, China. The physicochemical properties of the cattle manure and straw were determined after air drying and crushing. The characteristics of the cattle manure were as follows: total carbon content = 292 g/kg, total nitrogen (TN) content = 16.7 g/kg, pH = 8.41, C/N = 17.5, water content = 7.52%, cellulose content = 33.9%, hemicellulose content = 26.8%, and lignin content = 10.5%. The characteristics of the straw were as follows: total carbon content = 414 g/kg, TN content = 6.9 g/kg, C/N = 60, pH = 7.61, water content = 5.88%, cellulose content = 38.0%, hemicellulose content = 28.5%, and lignin content = 0.4%. Bacillus subtilis was purchased from Baoding Kelvfeng Biochemical Technology Co. Ltd, China, as a wettable powder with an active ingredient content of 1 billion live spores per gram. Strain number of the Bacillus subtilis was CMCC(B)63501. The composting experiment was conducted in the composting area at Xi’an University of Technology, Shaanxi, China. The reactors comprised four insulated foam boxes with dimensions of: length = 60 cm, width = 58 cm, height = 57 cm, and thickness = 6 cm, which had two circular holes (2 × 2 cm) in the top, bottom, and four walls of the foam boxes to ensure ventilation and the supply of oxygen. Cow manure and wheat straw were mixed and adjusted to a C:N ratio of 25:1. The weight of each treated compost mixture was 9 kg, with 3 kg of straw and 6 kg of cow manure. Bacillus subtilis was inoculated at four different concentrations of 0 (CK), 0.5% (B0.5), 1.0% (B1), and 2.0% (B2) relative to the dry weight of the compost. Bacillus subtilis powder was mixed evenly with 5.4 L deionized water and allowed to equilibrate for 2 h, before the mixture was poured into the composting material and mixed evenly, where the water content of the compost was adjusted to 60%. The composting process was conducted for 26 days, and the compost reactors were turned over on days 2, 4, 7, 15, 20, and 21 to enhance aeration. Samples were collected in the initial phase (day 0), mesophilic phase (day 4), thermophilic phase (day 7), cooling phase (day 15), and maturation phase (day 26). According to the compost temperature, the samples were taken from the top, middle, and bottom of each reactor and mixed well, where a total of 900 g (fresh weight was collected. Each sample was divided into two parts. The first part was stored in a refrigerator at 4 °C to determine the physical and chemical parameters. The second part was freeze dried at low temperature (Beijing Songyuan, China), crushed with a low temperature freeze-grinding machine (Retsch Z200, Germany), and sieved through a mesh of 0.5 mm, before storing at −80 °C for molecular biological experiments. 2.2. Analytical methods 2.2.1. Analysis of physicochemical parameters The temperature of the compost was monitored twice every day (9:00 and 19:00) at the top, core, and bottom of compost. The moisture contents of the fresh samples were measured as the loss after heating at 105 °C for 8 h. Each fresh sample was mixed with deionized water at a ratio of 1:5 2
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(m/v) (25 °C), before mechanically shaking at 200 rpm for 40 min and centrifuging at 8000 rpm for 8 min. The supernatant was collected and tested using a pH meter. Next, 5 mL of the supernatant was used to soak a filter paper in a glass Petri dish, before evenly distributing 15 Chinese cabbage seeds on the filter paper and incubating in the dark at 25 °C for 48 h. Distilled water was used as the control. The seed germination index (GI) was calculated according to the following formula.
GI =
Seed Germination × Root Length of Treatment (mm ) × 100% Seed Germination × Root Length of Control (mm)
The C/N ratio was calculated as the total organic carbon (TOC)/ total nitrogen (TN). TOC was determined using the potassium dichromate volumetric method (Bolden et al., 1999). TN was determined with a Kjeldahl analysis system (FOSS, Denmark). Water-soluble carbon (WSC) was extracted using the air-dried samples at a sample:deionized water ratio of 1:5 (m/v) (25 °C). The extract was mechanically shaken at 200 rpm for 40 min, before centrifugation at 8000 rpm for 8 min, and the supernatant was collected for analysis using an Analytikjen multiN/C 3100. All of the samples were analyzed three times. The cellulose, hemicellulose, and lignin contents were determined using the Van Soest method (Soest, 1963).
Fig. 1. Changes in temperature under different treatments during composting.
2.3. Data analysis Microsoft Excel 2018 was used for statistical analyses of the data and to prepare the tables. MATLAB 2016 was used to simulate the carbon degradation kinetics. SPSS 22.0 was used to calculate the standard error and the significance of differences at P < 0.05. Sigma Plot 14.0 was used to draw the graphics. Canoco 5.0 was used for redundancy analysis (RDA).
2.2.2. Humic carbon and separate components Air-dried samples weighing 5.0 g were shaken with 50 mL sodium hydroxide:tetrasodium pyrophosphate (1:10 w:v) solution for 24 h at a rotational speed of 200 rpm and 25 °C. After centrifugation, the supernatant was filtered through a 0.45-μm Millipore membrane. The pH of the supernatant was adjusted to 1 using 1 M H2SO4 and kept for 12 h at room temperature, before separating the HA and FA contents. HA was obtained by washing with 0.05 M H2SO4 several times and dissolving in 0.05 M NaOH. The pH of the HA was adjusted to 7 and evaporated to dryness. Finally, the HA carbon (HA-C) and HS carbon (HS-C) contents were measured based on the potassium dichromate volumetric method, and the FA carbon (FA-C) content was calculated as HS-C minus HA-C.
3. Results and discussion 3.1. Changes during the composting process Temperature is one of the most important indicators during composting, where it can reflect the composting process and changes in microbial activities (Zheng et al., 2015). The composting period was 26 days in this study (Fig. 1). The maturity time is similar to that found by Sun et al. (2019), i.e., about 30 days. The temperatures in CK, B0.5, B1, and B2 increased to their highest levels (> 70 °C) on day 3 and they remained at a high temperature (> 50 °C) for 8–10 days. During this thermophilic period, a large number of pathogenic bacteria and toxic substances were inactivated, and organic substances were rapidly decomposed (Chang et al., 2019). The temperature then continued to decreased, thereby indicating that the composting material was gradually maturing, which is consistent with the results obtained by Xu et al. (2020). It should be noted that treatment B0.5 had the most rapid temperature rise, where it reached 63.2 °C on day 2, which was 2.2 °C, 8.2 °C, and 17 °C higher than those in CK, B1, and B2, respectively, and the thermophilic phase was 1 to 2 days longer than those in the other treatments. These differences may be explained by the fact that Bacillus subtilis is a thermophilic bacterium and it can rapidly decompose organic substances to increase the temperature. In addition, inoculation with an appropriate amount of Bacillus subtilis might have resulted in a synergistic effect on the native microbial community to extend the high-temperature period. Table 1 shows the changes in the pH, C/N ratio, and GI during composting. The pH and C/N ratio increased initially in all treatments and then decreased, which was consistent with the trends in the temperature. The pH in all treatments increased to its highest level on day 4, which was attributed to the rapid increase in the temperature during the early stage of composting and the rapid degradation of nitrogencontaining organics in the compost by microorganisms generating large amounts of ammonium nitrogen to increase the pH (Yang et al., 2019). The C/N ratio reached its highest level on day 4, which might have been related to the greater degradation of nitrogen compared with carbon by microorganisms in the mesophilic phase. On day 26, the C/N ratios in all of the treatments decreased to their lowest levels, where the
2.2.3. DNA extraction and prediction of functional gene profiles DNA was extracted from the samples frozen at −80 °C using a FastDNA kit. The PICRUSt database was used to predict microbial metabolic functional genes. Bacterial 16S rRNA was determined using DNA extracted from 0.1 g of each freeze-dried compost sample with a FastDNA Kit for Soil (MP Biomedical, USA) according to the manufacturer's instructions. The concentration and purity of the DNA samples were detected with an Epoch MultiVolume Spectrophotometer (BioTek, USA). The quality checked DNA samples were stored at −20 °C. High-throughput sequencing was performed for the 16S rRNA gene in soil bacteria by Novogene Bioinformatics Technology Co. Ltd using the Ion S5XL platform. The 16S V4 region was amplified using the primers: 515F (GTGCCAGCMGCCGCGGTAA) and 806R (GGACTACHVGGGTWTCTAAT). The raw data were then subjected to a quality control procedure using UPARSE.28. USEARCH was used to filter chimeras and the remaining sequences were clustered to generate operational taxonomic units (OTUs) at the 97% similarity level. The OTUs in each sample were analyzed with QIIME software. The OTUs in each sample were classified with the RDP classifier and detailed annotations were obtained for the OTUs. A table of OTUs was constructed using the PICRUSt program (Langille et al., 2013), where the OTU counts were standardized with PICRUSt according to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database in order to consider the number of 16S rRNA genes in different taxa. Principal component analysis was conducted and heat maps were generated to visualize the data. 3
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enhanced mineralization caused by rapid heating. At the end of the composting process, the WSC contents of the treatments were: 12.75 g/ kg in CK > 12.05 g/kg in B2 > 11.1 g/kg in B0.5 > 10.75 g/kg in B1, and they all conformed with the maturity standard for compost (WSC < 17 g/kg) proposed by Bernai et al. (1998), thereby indicating that the final composts obtained after all four treatments were completely mature. Compared with the WSC contents on day 1, the decreases in WSC were largest in B0.5 and B1, and the WSC contents were significantly lower than those in CK and B2 (F = 126.398, P < 0.05). In order to evaluate the TOC losses during composting, simulations were conducted with the first-order degradation kinetics equation (Jain and Jambhulkar, 2018) expressed as follows.
Table 1 Changes in physicochemical properties (pH, C/N ratio (total organic carbon/ total nitrogen), Seed germination index (GI)) under different treatments during composting. Treatment Day 1 Day 4
Day 7
Day 15
Day 26
pH CK CK B0.5 B1 B2 CK B0.5 B1 B2 CK B0.5 B1 B2 CK B0.5 B1 B2
7.64 8.35 8.30 8.41 8.33 8.14 8.08 8.15 8.17 7.99 8.02 7.94 7.96 7.94 7.92 7.84 7.81
C/N ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.01a 0.02b 0.02c 0.00a 0.01b 0.01b 0.01c 0.01b 0.01a 0.02a 0.02a 0.02b 0.01b 0.02a 0.01a 0.03b 0.02c
25.8 26.2 27.5 24.7 24.4 24.1 25.1 23.8 22.6 23.2 24.1 21.2 22.0 22.3 22.8 20.4 20.7
GI (%) ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.3a 1.8ab 1.4a 0.7b 0.3b 0.1ab 1.0a 1.2ab 0.7b 0.1ab 0.7a 1.c 0.6bc 0.8a 0.1a 1.2b 0.3b
24.5 ± 1.6a 43.6 ± 4.9a 52.2 ± 10.8a 47.4 ± 4.4a 53.4 ± 5.8a 55.6 ± 15.8c 68.7 ± 6.8bc 81.2 ± 10.1ab 92.4 ± 6.8a 95.9 ± 19.2a 104.2 ± 18.4a 106.9 ± 20.8a 108.3 ± 21.0a 155.5 ± 42.1a 161.9 ± 30.3a 168.4 ± 32.3a 182.6 ± 34.4a
d (BVS ) = dx
k (BVS )
At the initial composting time, t = 0 and BVS = BVS0, and thus the equation can be simplified as follows.
BVS = BVS0
(1
e
kt )
In the equations above, BVS represents the total amount of carbon degraded during composting, BVS0 represents the total initial degradable carbon-containing substances, t represents the time, and k is the first-order reaction rate constant. According to the calculated R2 values (Table 2), the equation fitted for CK was the best, whereas the fit was poor for B0.5 and the value of k was the lowest. The lower k value indicates that B0.5 could reduce the degradation and mineralization of carbon and enhance carbon sequestration.
C/N ratio in B0.5 was significantly higher than those in B1 and B2 (F = 6.817, P < 0.05), thereby indicating that B0.5 was beneficial for carbon sequestration during composting. GI can be used to measure the maturity of compost. Previous studies have shown that biological methods can be used to effectively determine the toxicity of compost and evaluate the degree of compost maturity (Liu et al., 2018; Cui et al., 2017). The GI in all of the treatments tended to increase throughout the composting process. After day 15 of composting, the GI values exceeded 96% in all of the treatments to satisfy the maturity standard (GI > 80%), and the higher Bacillus subtilis inoculation levels led to higher GI values, although there were no significant differences among the treatments (P > 0.05). These results are similar to those obtained by Yang et al. (2020). The results indicate that the toxic substances in the compost gradually degraded during the composting process, and B2 was the most effective of all the treatments. However, the seed germination rate was relatively high, which may have been related to the 48-h culture period in the experiment.
3.3. Changes in humus carbon and its components Humification is a process that transforms organic matter into HS and it is also the key step for carbon sequestration in compost. Humification has direct effects on the fertility and stability of compost (Qi et al., 2019). During the composting process, complex organic matter is gradually decomposed into HS precursors by microorganisms. These HS precursors can be completely mineralized by microorganisms to produce CO2 or transformed into HS under the action of enzymes (Wu et al., 2017; Huang et al., 2019). Fig. 3(a) shows the changes in the HS-C contents during composting. The HS-C content decreased significantly in B0.5 during the mesophilic period of composting (F = 89.690, P < 0.05), which was due to the rapid temperature increase and strong mineralization in the initial stage of composting, thereby decreasing the synthesis of HS from HS precursors. The HS-C content was significantly higher in B0.5 compared with the other treatments during the cooling and maturation phase (F = 9.200, P < 0.05). Thus, B0.5 could significantly reduce the mineralization during the middle and late stages of composting to promote the transformation of HS precursors into HS and conserve carbon in the form of humus. HA and FA are important components of HS. FA is more active than HA, and the high content of unstable FA in the original compost was gradually converted into the more stable HA, where this process occurred mainly in the thermophilic period of composting (Yu et al., 2019a). Fig. 3(b) shows the changes in the HA-C contents during composting. The HA-C contents increased initially and then decreased. The increases in the HA-C contents in the mesophilic and thermophilic stages of composting were due to the active transformation of FA into HA, and the HS precursors were used to synthesize HA (Wang et al., 2019). In the later stage, the microorganisms decomposed HA and HS precursors in order to maintain their own metabolism, and mineralization also led to carbon release, thereby resulting in decreases in the HA-C contents. The FA-C contents decreased in the four treatments during the composting process (Fig. 3(c)), and these changes are consistent with the results obtained by Wang et al. (2017b). These decreases occurred because microorganisms preferentially utilize simple
3.2. Differences in the carbon contents during composting Composting involves a combination of the mineralization and humification of organic matter. Mineralization refers to the process where microorganisms degrade organic substances to release CO2 and reduce carbon sequestration during composting (Qi et al., 2019). TOC is present in organic matter and it can reflect the nutritional characteristics and quality of compost. Fig. 2(a) shows the changes in the TOC contents during composting. The TOC concentrations decreased in all of the treatments due to the mineralization of the compost. Similar results were obtained by Awasthi et al. (2020). After day 26 of the composting process, 2.8%, 1.0%, 4.1%, and 8.7% of the initial TOC contents were degraded in CK, B0.5, B1, and B2, respectively. Therefore, inoculation with 0.5% Bacillus subtilis could effectively reduce the mineralization of compost and the carbon losses. WSC is an important carbon source that can be used directly by microorganisms to support their growth and reproduction, and it is closely related to the maturity and microbial activity levels of compost (Straathof, 2015). According to Fig. 2(b), the WSC contents decreased in all of the treatments. In the initial stage of composting, the raw materials contained large amounts of readily degradable substances with a high soluble carbon content, whereas the mature compost contained more macromolecular substances with low solubility in water and less soluble carbon due to the action of microorganisms (Zbytniewski, 2005; Zhu et al., 2020). During the mesophilic period, the decrease in WSC was largest in B0.5 (14.6%), which was related to the 4
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Fig. 2. Changes in total organic carbon (TOC) and water soluble carbon (WSC) contents during composting: (a) TOC; and (b) WSC. The bars represent standard deviations (n = 3).
(44.9–48.4%), followed by the genetic information processing group (20.4–21.4%), environmental information processing group (13.1–15.0%), cell process group (6.5–8.4%), unclassified group (5.3–5.9%), human disease group (2.8–3.0%), and organismal system group (1.7–1.9%). Twelve typical metabolic pathways were identified (Fig. 4(b)), where carbohydrate metabolism and amino acid metabolism were the top two pathways, which accounted for 40% of the total metabolic pathways. During the composting process, the abundances of metabolism genes increased gradually and then eventually remained stable, with similar changes in the different treatments. Compared with CK, inoculation with Bacillus subtilis reduced microbial metabolism in the mesophilic and thermophilic stages of composting, where the higher inoculation amounts led to more obvious reductions. Inoculation with 0.5% Bacillus subtilis effectively reduced microbial metabolism in the cooling and maturation stages of composting. Among the 12 metabolic pathways, amino acid metabolism was the most abundant during composting. A previous study stated that amino acids are HS precursors and they play important roles in the formation of HS (Zhang et al., 2019). Moreover, amino acids are sources of energy and carbon for microbial metabolism throughout the composting process (López-González et al., 2015). According to the level 3 functional
Table 2 Parameters of carbon degradation kinetics during composting. (R2 means Correlation coefficient, k means the first-order reaction rate constant, RMSE means Root Mean Squared Error). Treatment
Carbon loss (%)
k
R2
RMSE
CK B0.5 B1 B2
2.8 1.0 4.0 8.7
0.00175 0.00064 0.00278 0.00615
0.919 0.829 0.891 0.86
0.313 0.158 0.582 1.323
organic matter such as FA (Zhang et al., 2019), and FA can be converted into HA. In addition, the FA-C contents decreased rapidly in the mesophilic and thermophilic phases, thereby indicating that FA was mainly changed into HA during these two periods. 3.4. Microbial functional metabolism genes during composting The PICRUSt database was used to analyze the effects of Bacillus subtilis on microbial functional genes. As shown in Fig. 4(a), the abundance of microbial metabolic function genes was highest
Fig. 3. Changes in contents of humic substance carbon (HS-C) and carbon components (humic acid carbon (HA-C) and fulvic acid carbon (FA-C)) during composting: (a) changes in HS-C contents during composting; (b) changes in HA-C content during composting; and (c) change in FA-C contents during composting. The bars represent standard deviations (n = 3). 5
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Fig. 4. Changes in the microbial function profiles during composting: (a) biochemical metabolic pathways; (b) level 2 KEGG function predictions in terms of the relative abundances of the 13 main metabolic functions; (c) level 3 KEGG function predictions in terms of the relative abundances of the 13 main functions related to amino acid metabolism and carbohydrate metabolism.
predictions (Fig. 4(c)), the abundances of arginine and proline metabolism, and aspartate and glutamate metabolism genes related to TCA were lower in B0.5 than the other treatments during composting. The TCA cycle is an important metabolic pathway for CO2 production during composting (Wang et al., 2019). In addition, B0.5 reduced purine metabolism of nucleotides and prevented the combination of nucleotide purine and deamination, thereby inhibiting the decomposition of amino acids into H2O and CO2 (Bhagavan et al., 2015). Carbohydrate metabolism was another major metabolic pathway. The KEGG pathway annotations predicted that carbohydrate metabolism mainly comprised the following metabolic pathways: pyruvate metabolism, butanoate metabolism, glycolysis, propanoate metabolism, amino sugar and nucleotide sugar metabolism, and TCA cycle. Nakasaki and Araya (2013) reported that acetic acid, propionic acid, butyric acid, and lactic acid are the four main types of organic acids, and the pH is decreased due to the production of organic acids. As shown in Fig. 4(c), the metabolic intensity was relatively low for butanoate and propanoate in the early stage of composting when a large amount of organic acids accumulated and the pH of the compost decreased continually. After the thermophilic stage of composting, the metabolic intensity increased and stabilized, and thus the pH gradually stabilized. The intensities of methane metabolism and TCA cycle in the middle and late stages of composting were lower under B0.5 than the other treatments, thereby indicating that B0.5 could effectively reduce the carbon losses during composting. The abundance of carbohydrate metabolism genes is associated with the carbon conversion rate (Hartman et al., 2017), which represents the amount of solid carbon released in the form of CO2, CH4, and other gases. Therefore, the higher TOC, HS-C, FA-C, and HA-C levels in B0.5 were due to the low carbon conversion rate in the compost because of low carbohydrate metabolism.
pH, and TN) and functional metabolism (Pyruvate_metabolism, Butanoate_metabolism, Propanoate_metabolism, Methane_metabolism, Citrate_cycle_(TCA_cycle), Arginine_and_proline_metabolism) on the carbon contents of the compost (TOC, WSC, HS-C, HA-C, and FA-C) (Fig. 5). RDA1 and RDA2 explained 81.67% of the total variation in carbon (pH = 44.7%, Butanoate_metabolism = 10.8%, Propanoate_metabolism = 8.9%, Arginine_and_proline_metabolism = 4.8%,
3.5. Relationship between the composting environment and carbon
Fig. 5. Redundancy analysis based on environment factors, functional metabolism genes and carbon, where blue represents carbon, red represents environmental factors; and black represents the sample points. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
The environmental characteristics and microbial metabolism in the compost directly affected the changes in the carbon contents. RDA was used to further evaluate the effects of environmental factors (temperature, 6
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Citrate_cycle_(TCA_cycle) = 3.9%, Methane_metabolism = 5.3%, temperature = 1.8%, Pyruvate_metabolism = 1.5%, and TN < 0.1%). The lengths and angles of the arrows in Fig. 5 indicate the importance and correlations of the variables, where an angle < 90° represents a positive relationship and a smaller angle denotes a stronger positive relationship, whereas an angle > 90° indicates a negative relationship and a greater angle denotes a stronger negative relationship. Fig. 5 shows that B0.5, B1, and B2 were distributed near the horizontal axis, and the distribution of B0.5 was relatively concentrated, thereby indicating that inoculation with Bacillus subtilis could affect the transformation of carbon, where B0.5 had the most significant effect. There was a significant positive correlation between pH and carbon because the pH of the compost was related to the accumulation of ammonium ions and organic acids (Chen et al., 2019). As the composting process continued, ammonium ions were gradually nitrated and the organic acids generated by microbial metabolism were continuously enriched, so the pH decreased. An appropriate pH is conducive to microbial metabolism and it can affect the carbon content of compost (Wang et al., 2017c). Therefore, the pH was the main reason for the changes in the carbon contents during composting. In this study, the pH value (7.92) in B0.5 during the maturity stage was significantly higher than those in B1 and B2, and it facilitated reductions in carbon metabolism and thus carbon retention. Temperature had positive relationships with WSC and HS-C because large amounts of simple organic matter were utilized directly by microorganisms for their growth during the mesophilic stage of composting, and thus the temperature increased rapidly. In addition, microorganisms decomposed complex organic matter (cellulose and hemicellulose) into simple organic matter to promote the generation of HS precursors (Wu et al., 2017; Huang et al., 2019). During the middle and later stages of composting, the abundances of functional metabolism genes such as pyruvate metabolism, methane metabolism, and TCA cycle increased, and they were negatively correlated with WSC and TOC. These changes might have been related to the rapid consumption of simple compounds by microorganisms via mineralization (Lu et al., 2018; Wang et al., 2019). TN was positively correlated with metabolism genes, but negatively correlated with TOC and WSC because the metabolism of organic matter reduces the compost quality (Pan et al., 2018). The results obtained in this study showed that 0.5% Bacillus subtilis could significantly increase the humus and carbon contents of the composting products. Therefore, during actual production, 0.5% Bacillus subtilis can be inoculated to improve the quality of compost. The application of compost products containing Bacillus subtilis in agricultural production may help to improve the soil quality and crop growth (D’Hose et al., 2014). In addition, the form of Bacillus subtilis used in this study was a wettable powder, which has advantages in terms of its low price and convenient use. Therefore, low-cost compost products and high-yield crops will contribute to agricultural economic benefits.
CRediT authorship contribution statement Manli Duan: Conceptualization, Funding acquisition, Methodology, Investigation. Yuhua Zhang: Investigation, Data curation, Writing original draft. Beibei Zhou: Investigation, Methodology, Formal analysis. Zhenlun Qin: Investigation, Methodology. Junhu Wu: Conceptualization, Project administration, Software. Quanjiu Wang: Conceptualization, Visualization, Funding acquisition. Yanan Yin: Writing - review & editing, Visualization. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements This study was funded by the National Natural Science Foundation of China (41807131, 41977007 and 41830754), China Postdoctoral Science Foundation (2019M653707), and Natural Science Foundation of Shaanxi province of China (2019JQ-537), Research project of State Key Laboratory of Eco-hydraulics in Northwest Arid Region of China (2019KJCXTD-4 and QJNY-2019-01). We thank Dr. Duncan E. Jackson for language editing. References An, C.J., Huang, G.H., Yao, Y., Sun, W., 2012. Performance of in-vessel composting of food waste in the presence of coal ash and uric acid. J. Hazard. Mater. 203, 38–45. Awasthi, M.K., Duan, Y., Awasthi, S.K., Liu, T., 2020. Effect of biochar and bacterial inoculum additions on cow dung composting. Bioresour. Technol. 297, 122407. Bernai, M.P., Paredes, C., Sanchez-Monedero, M.A., 1998. Maturity and stability parameters of composts prepared with a wide range of organic wastes. Bioresour. Technol. 63 (1), 91–99. Bhagavan, N.V., Chung-Eun, H. 2015. Chapter 15: Protein and Amino Acid Metabolism Essentials of Medical Biochemistry (Second Edition), 227–268. Chang, R., Li, Y., Chen, Q., Guo, Q., 2019. Comparing the effects of three in situ methods on nitrogen loss control, temperature dynamics and maturity during composting of agricultural wastes with a stage of temperatures over 70 °C. J. Environ. Manage. 230, 119–127. Chen, M., Huang, Y., Liu, H., Xie, S., 2019. Impact of different nitrogen source on the compost quality and greenhouse gas emissions during composting of garden waste. Process Saf. Environ. Prot. 124, 326–335. Cui, H.Y., Zhao, Y., Chen, Y.N., Zhang, X., Wang, 2017. Assessment of phytotoxicity grade during composting based on EEM/PARAFAC combined with projection pursuit regression. J. Hazard. Mater. 326, 10–17. David, J., Gary, N., 1997. Formation of volatile compounds during fermentation of soya beans bacillus subtilis. J. Sci. F. Agri. 74 (8), 132–140. D’Hose, T., Cougnon, M., De Vliegher, A., Vandecasteele, B., Viaene, N., 2014. The positive relationship between soil quality and crop production: a case study on the effect of farm compost application. Appl. Soil Ecol. 75, 189–198. Hartman, W.H., Ye, R., Horwath, W.R., 2017. A genomic perspective on stoichiometric regulation of soil carbon cycling. The ISME journal 11 (12), 2652. Huang, Y., Danyang, L., Shah, G.M., Chen, W., Wang, W., Xu, Y., 2019. Hyperthermophilic pretreatment composting significantly accelerates humic substances formation by regulating precursors production and microbial communities. Waste Manage. 92, 89–96. Jain, M.S., Jambhulkar, R., 2018. Biochar amendment for batch composting of nitrogen rich organic waste: effect on degradation kinetics, composting physics and nutritional properties. Bioresour. Technol. 253, 204–213. Langille, M.G., Zaneveld, J., Caporaso, J.G., McDonald, D., Knights, D., Reyes, J.A., 2013. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotechnol. 31 (9), 814–821. Li, Y., Liu, Y., Yong, X., Wu, X., Jia, H., Wong, J.W., 2019. Odor emission and microbial community succession during biogas residue composting covered with a molecular membrane. Bioresour. Technol. 297, 122518. Liu, L., Wang, S., Guo, X., Zhao, T., 2018. Succession and diversity of microorganisms and their association with physicochemical properties during green waste thermophilic composting. Waste Manage. 73, 101–112. López-González, J.A., Suárez-Estrella, F., Vargas-García, M.C., López, M.J., Jurado, M.M., 2015. Dynamics of bacterial microbiota during lignocellulosic waste composting: Studies upon its structure, functionality and biodiversity. Bioresour. Technol. 175, 406–416. Lu, Q., Zhao, Y., Gao, X., Wu, J., Zhou, H., Tang, P., 2018. Effect of tricarboxylic acid cycle regulator on carbon retention and organic component transformation during food waste composting. Bioresour. Technol. 256, 128–136.
4. Conclusion Inoculation with Bacillus subtilis at 2% accelerated the maturation of compost and improved the seed GI, but the carbon losses were greater. Inoculation with Bacillus subtilis at 0.5% prolonged the thermophilic period, reduced mineralization during the cooling and maturation stages of composting, and increased the TOC and HS-C contents. Adding Bacillus subtilis at 0.5% effectively decreased the abundances of functional carbon metabolism genes. RDA demonstrated that pH and microbial functional metabolism were closely related to carbon sequestration during composting. Inoculating cow manure–straw compost with 0.5% Bacillus subtilis can accelerate compost maturation, retain carbon, and improve the compost quality.
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affect humus formation during bio-composting of chicken manure and corn straw? Bioresour. Technol. 269, 169–178. Wu, J., Zhao, Y., Qi, H., Zhao, X., Yang, T., Du, Y., 2017. Identifying the key factors that affect the formation of humic substance during different materials composting. Bioresour. Technol. 244, 1193–1196. Xu, Z., Li, G., Huda, N., Zhang, B., Wang, M., 2020. Effects of moisture and carbon/ nitrogen ratio on gaseous emissions and maturity during direct composting of cornstalks used for filtration of anaerobically digested manure centrate. Bioresour. Technol. 298, 122503. Yang, X.C., Han, Z.Z., Ruan, X.Y., Chai, J., Jiang, S.W., 2019. Composting swine carcasses with nitrogen transformation microbial strains: Succession of microbial community and nitrogen functional genes. Environ. Sci. Technol. 688, 555–566. Yang, Y., Du, W., Ren, X., Cui, Z., Zhou, W., 2020. Effect of bean dregs amendment on the organic matter degradation, humification, maturity and stability of pig manure composting. Environ. Sci. Technol. 708, 134623. Yin, Y., Gu, J., Wang, X., Zhang, Y., Zheng, W., Chen, R., 2019a. Effects of rhamnolipid and Tween-80 on cellulase activities and metabolic functions of the bacterial community during chicken manure composting. Bioresour. Technol. 288, 121507. Yin, Y., Yang, C., Gu, J., Wang, X., Zheng, W., Wang, R., 2019b. Roles of nxrA-like oxidizers and nirS-like reducers in nitrite conversion during swine manure composting. Bioresour. Technol. 297, 122426. Yu, H., Xie, B., Khan, R., 2019a. The changes in carbon, nitrogen components and humic substances during organic-inorganic aerobic co-composting. Bioresour. Technol. 271, 228–235. Yu, H., Zhao, Y., Zhang, C., Wei, D., Wu, J., Zhao, X., 2019b. Driving effects of minerals on humic acid formation during chicken manure composting: Emphasis on the carrier role of bacterial community. Bioresour. Technol. 294, 122239. Zbytniewski, R., 2005. Characterization of natural organic matter (NOM) derived from sewage sludge compost. Part 1: chemical and spectroscopic properties. Bioresour. Technol. 96 (4), 471–478. Zhang, D., Luo, W., Li, Y., Wang, G., 2018. Performance of co-composting sewage sludge and organic fraction of municipal solid waste at different proportions. Bioresour. Technol. 250, 853–859. Zhang, Z., Zhao, Y., Yang, T., Wei, Z., Li, Y., Wei, Y., 2019. Effects of exogenous proteinlike precursors on humification process during lignocellulose-like biomass composting: Amino acids as the key linker to promote humification process. Bioresour. Technol. 291, 121882. Zhao, G.H., Yu, Y.L., Zhou, X.T., Lu, B.Y., Li, Z.M., 2017. Effects of drying pretreatment and particle size adjustment on the composting process of discarded flue-cured tobacco leaves. Waste Manage. Res. 35 (5), 534–540. Zheng, G., Chen, T., Yu, J., Gao, D., Shen, Y., Niu, M., 2015. Impact of composting strategies on the degradation of nonylphenol in sewage sludge. Ecotoxicology 24 (10), 2081–2087. Zhu, L., Wei, Z., Yang, T., Zhao, X., Dang, Q., Chen, X., 2020. Core microorganisms promote the transformation of DOM fractions with different molecular weights to improve the stability during composting. Bioresour. Technol. 299, 122575.
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Bioresource Technology journal homepage: www.elsevier.com/locate/biortech
Effects of Bacillus subtilis on carbon components and microbial functional metabolism during cow manure–straw composting
T
Manli Duana, Yuhua Zhanga, Beibei Zhoua, , Zhenlun Qina, Junhu Wua, Quanjiu Wanga, Yanan Yinb ⁎
a
State Key Laboratory of Eco-hydraulics in Northwest Arid Region of China, Xi’an University of Technology, Xi’an 710048, China Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, School of Environmental and Municipal Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China
b
GRAPHICAL ABSTRACT
ARTICLE INFO
ABSTRACT
Keywords: Bacillus subtilis Carbon Composting Functional metabolism Redundancy analysis
This study is the first to investigate the changes in the composting process and carbon conversion in a cow manure–straw compost matrix with Bacillus subtilis added at four different levels (0, 0.5%, 1%, and 2% w/w compost), and to explain the mechanism responsible for carbon conversion through microbial functional metabolism. Inoculation with Bacillus subtilis at 2% had the best effect on fermentation among all treatments, but it inhibited the synthesis of total organic carbon and humus. Bacillus subtilis at 0.5% reduced mineralization in the cooling and maturity stages of composting, and enhanced the humification of carbon. The total organic carbon and humic sequence contents were significantly higher with Bacillus subtilis at 0.5% (12.5% and 20.2%, respectively) than Bacillus subtilis at 2% (P < 0.05). Redundancy analysis demonstrated that the pH and microbial functional metabolism were closely related to carbon sequestration during composting.
1. Introduction The large-scale development of modern livestock breeding has led to the production of large volumes of livestock manure, which is a challenge for the ecological environment. According to statistics for 2017, the annual output of manure in China was about 3.8 billion tons
⁎
(Ma et al., 2018). Aerobic composting is an effective technique for treating solid organic waste because it can convert animal manure into stable organic fertilizer for use as a soil amendment. Aerobic composting involves the decomposition and transformation of organic matter, and the synthesis of humus due to the activities of microorganisms (Zhao et al., 2017; Yu et al., 2019a; Yin et al., 2019b).
Corresponding author. E-mail address: [email protected] (B. Zhou).
https://doi.org/10.1016/j.biortech.2020.122868 Received 18 November 2019; Received in revised form 14 January 2020; Accepted 21 January 2020 Available online 28 January 2020 0960-8524/ © 2020 Elsevier Ltd. All rights reserved.
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However, this process is often accompanied by organic carbon losses in the form of greenhouse gases such as CO2 and CH4. These emissions decrease carbon sequestration during composting and affect the quality of the compost, but they also aggravate the greenhouse effect (Zhang et al., 2019). Previous studies have shown that the proportions of composting materials, composting methods, and composting conditions can affect the succession of the microbial community to different degrees (An et al., 2012; Wang et al., 2017a; Zhang et al., 2018; Li et al., 2019), thereby affecting the mineralization and humification of compost. Humification is a key step for carbon sequestration in compost, and fixing carbon in humus is important for reducing carbon losses (Qi et al., 2019). Previous studies of compost humification focused mainly on humic substances (HS) and their components comprising humic acid (HA) and fulvic acid (FA) (Yu et al., 2019a; Zhu et al., 2020). It has been shown that HA and FA can be transformed into each other due to the activities of microorganisms, and that an increase in HA and decrease in FA occur mainly in the thermophilic phase of composting, and thus the HA content can reflect the maturity of compost (Wang et al., 2019; Yu et al., 2019b). HS precursors such as amino acids, polyphenols, and soluble sugars are the main factors that contribute to the formation of HS (Zhang et al., 2019; Zhu et al., 2020). Microorganisms can promote the formation of HS precursors via the metabolism of organic matter. Most HS precursors can be completely mineralized by microorganisms to produce CO2 (via the tricarboxylic acid (TCA) cycle) during the mesophilic and thermophilic stages of composting (Lu et al., 2018; Wang et al., 2019). Therefore, improving the pathways for microbial metabolism, reducing mineralization, and enhancing the transformation of organic matter into HS are effective for carbon sequestration. In recent years, many studies have investigated the degradation and formation of HS from organic components during composting after inoculation with bacterial strains or supplementation with additives (Voběrková et al., 2017; Wu et al., 2018). Previous research into the humification mechanism has focused mainly on analyses of microbial communities by determining their changes during composting via highthroughput sequencing, and by exploring the relationships between humus and members of the microbial community by conducting network analysis in order to understand the changes in the physical and chemical properties of compost (Wei et al., 2018). In fact, microbial metabolism is fundamentally responsible for the changes in the properties of compost (Wang et al., 2018). Microorganisms release energy and nutrients by metabolizing organic matter, thereby promoting the maturation of compost as well as allowing their growth and reproduction. Carbon and nitrogen are often lost in this process, but few studies have investigated their changes. Therefore, the present study investigated the changes in humus by predicting the functional genes associated with microbial metabolism and determining the carbon transformation pathway. Bacillus subtilis is a thermophilic spore-producing Gram-positive bacterium and it is present in the composting process. The spores produced by Bacillus subtilis can persist in high temperature, high acid, or high alkali conditions, as well as other adverse environments. Bacillus subtilis is the dominant species in compost (Siu-Rodas et al., 2018). Many enzymes are secreted by Bacillus subtilis, such as protease, cellulase, amylase, and phytase, which can compensate for the enzymes lacking in other microorganisms to promote their growth (David and Gary, 1997). It was shown that an extract from Bacillus subtilis had a high cellulase activity during the decomposition of cellulose, and it effectively promoted the degradation of cellulose (Siu-Rodas et al., 2018). Yin et al. (2019a) found that Bacillus is closely related to carbohydrate metabolism using the Biolog method. However, the effects of Bacillus subtilis on the transformation of carbon and the functional genes associated with carbon metabolism during composting require further analysis. In this study, cow manure and wheat straw were used as the composting materials in an aerobic composting experiment to explore the
effects of different concentrations of Bacillus subtilis on the compost maturation process and carbon transformation mechanisms. In addition, PICRUSt was used to predict the metabolic functions of microorganisms during different composting stages in order to elucidate the carbon transformation mechanism. Finally, the appropriate amount of Bacillus subtilis was determined for accelerating the composting process, reducing carbon losses, and improving the compost quality. 2. Materials and methods 2.1. Experimental design and sample collection The raw compost materials used in this study comprised cattle manure and wheat stalks. Fresh cow dung was collected from Shaanxi Qinbao Animal Husbandry Co. Ltd and wheat straw was collected from a local farm in Yangling, China. The physicochemical properties of the cattle manure and straw were determined after air drying and crushing. The characteristics of the cattle manure were as follows: total carbon content = 292 g/kg, total nitrogen (TN) content = 16.7 g/kg, pH = 8.41, C/N = 17.5, water content = 7.52%, cellulose content = 33.9%, hemicellulose content = 26.8%, and lignin content = 10.5%. The characteristics of the straw were as follows: total carbon content = 414 g/kg, TN content = 6.9 g/kg, C/N = 60, pH = 7.61, water content = 5.88%, cellulose content = 38.0%, hemicellulose content = 28.5%, and lignin content = 0.4%. Bacillus subtilis was purchased from Baoding Kelvfeng Biochemical Technology Co. Ltd, China, as a wettable powder with an active ingredient content of 1 billion live spores per gram. Strain number of the Bacillus subtilis was CMCC(B)63501. The composting experiment was conducted in the composting area at Xi’an University of Technology, Shaanxi, China. The reactors comprised four insulated foam boxes with dimensions of: length = 60 cm, width = 58 cm, height = 57 cm, and thickness = 6 cm, which had two circular holes (2 × 2 cm) in the top, bottom, and four walls of the foam boxes to ensure ventilation and the supply of oxygen. Cow manure and wheat straw were mixed and adjusted to a C:N ratio of 25:1. The weight of each treated compost mixture was 9 kg, with 3 kg of straw and 6 kg of cow manure. Bacillus subtilis was inoculated at four different concentrations of 0 (CK), 0.5% (B0.5), 1.0% (B1), and 2.0% (B2) relative to the dry weight of the compost. Bacillus subtilis powder was mixed evenly with 5.4 L deionized water and allowed to equilibrate for 2 h, before the mixture was poured into the composting material and mixed evenly, where the water content of the compost was adjusted to 60%. The composting process was conducted for 26 days, and the compost reactors were turned over on days 2, 4, 7, 15, 20, and 21 to enhance aeration. Samples were collected in the initial phase (day 0), mesophilic phase (day 4), thermophilic phase (day 7), cooling phase (day 15), and maturation phase (day 26). According to the compost temperature, the samples were taken from the top, middle, and bottom of each reactor and mixed well, where a total of 900 g (fresh weight was collected. Each sample was divided into two parts. The first part was stored in a refrigerator at 4 °C to determine the physical and chemical parameters. The second part was freeze dried at low temperature (Beijing Songyuan, China), crushed with a low temperature freeze-grinding machine (Retsch Z200, Germany), and sieved through a mesh of 0.5 mm, before storing at −80 °C for molecular biological experiments. 2.2. Analytical methods 2.2.1. Analysis of physicochemical parameters The temperature of the compost was monitored twice every day (9:00 and 19:00) at the top, core, and bottom of compost. The moisture contents of the fresh samples were measured as the loss after heating at 105 °C for 8 h. Each fresh sample was mixed with deionized water at a ratio of 1:5 2
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(m/v) (25 °C), before mechanically shaking at 200 rpm for 40 min and centrifuging at 8000 rpm for 8 min. The supernatant was collected and tested using a pH meter. Next, 5 mL of the supernatant was used to soak a filter paper in a glass Petri dish, before evenly distributing 15 Chinese cabbage seeds on the filter paper and incubating in the dark at 25 °C for 48 h. Distilled water was used as the control. The seed germination index (GI) was calculated according to the following formula.
GI =
Seed Germination × Root Length of Treatment (mm ) × 100% Seed Germination × Root Length of Control (mm)
The C/N ratio was calculated as the total organic carbon (TOC)/ total nitrogen (TN). TOC was determined using the potassium dichromate volumetric method (Bolden et al., 1999). TN was determined with a Kjeldahl analysis system (FOSS, Denmark). Water-soluble carbon (WSC) was extracted using the air-dried samples at a sample:deionized water ratio of 1:5 (m/v) (25 °C). The extract was mechanically shaken at 200 rpm for 40 min, before centrifugation at 8000 rpm for 8 min, and the supernatant was collected for analysis using an Analytikjen multiN/C 3100. All of the samples were analyzed three times. The cellulose, hemicellulose, and lignin contents were determined using the Van Soest method (Soest, 1963).
Fig. 1. Changes in temperature under different treatments during composting.
2.3. Data analysis Microsoft Excel 2018 was used for statistical analyses of the data and to prepare the tables. MATLAB 2016 was used to simulate the carbon degradation kinetics. SPSS 22.0 was used to calculate the standard error and the significance of differences at P < 0.05. Sigma Plot 14.0 was used to draw the graphics. Canoco 5.0 was used for redundancy analysis (RDA).
2.2.2. Humic carbon and separate components Air-dried samples weighing 5.0 g were shaken with 50 mL sodium hydroxide:tetrasodium pyrophosphate (1:10 w:v) solution for 24 h at a rotational speed of 200 rpm and 25 °C. After centrifugation, the supernatant was filtered through a 0.45-μm Millipore membrane. The pH of the supernatant was adjusted to 1 using 1 M H2SO4 and kept for 12 h at room temperature, before separating the HA and FA contents. HA was obtained by washing with 0.05 M H2SO4 several times and dissolving in 0.05 M NaOH. The pH of the HA was adjusted to 7 and evaporated to dryness. Finally, the HA carbon (HA-C) and HS carbon (HS-C) contents were measured based on the potassium dichromate volumetric method, and the FA carbon (FA-C) content was calculated as HS-C minus HA-C.
3. Results and discussion 3.1. Changes during the composting process Temperature is one of the most important indicators during composting, where it can reflect the composting process and changes in microbial activities (Zheng et al., 2015). The composting period was 26 days in this study (Fig. 1). The maturity time is similar to that found by Sun et al. (2019), i.e., about 30 days. The temperatures in CK, B0.5, B1, and B2 increased to their highest levels (> 70 °C) on day 3 and they remained at a high temperature (> 50 °C) for 8–10 days. During this thermophilic period, a large number of pathogenic bacteria and toxic substances were inactivated, and organic substances were rapidly decomposed (Chang et al., 2019). The temperature then continued to decreased, thereby indicating that the composting material was gradually maturing, which is consistent with the results obtained by Xu et al. (2020). It should be noted that treatment B0.5 had the most rapid temperature rise, where it reached 63.2 °C on day 2, which was 2.2 °C, 8.2 °C, and 17 °C higher than those in CK, B1, and B2, respectively, and the thermophilic phase was 1 to 2 days longer than those in the other treatments. These differences may be explained by the fact that Bacillus subtilis is a thermophilic bacterium and it can rapidly decompose organic substances to increase the temperature. In addition, inoculation with an appropriate amount of Bacillus subtilis might have resulted in a synergistic effect on the native microbial community to extend the high-temperature period. Table 1 shows the changes in the pH, C/N ratio, and GI during composting. The pH and C/N ratio increased initially in all treatments and then decreased, which was consistent with the trends in the temperature. The pH in all treatments increased to its highest level on day 4, which was attributed to the rapid increase in the temperature during the early stage of composting and the rapid degradation of nitrogencontaining organics in the compost by microorganisms generating large amounts of ammonium nitrogen to increase the pH (Yang et al., 2019). The C/N ratio reached its highest level on day 4, which might have been related to the greater degradation of nitrogen compared with carbon by microorganisms in the mesophilic phase. On day 26, the C/N ratios in all of the treatments decreased to their lowest levels, where the
2.2.3. DNA extraction and prediction of functional gene profiles DNA was extracted from the samples frozen at −80 °C using a FastDNA kit. The PICRUSt database was used to predict microbial metabolic functional genes. Bacterial 16S rRNA was determined using DNA extracted from 0.1 g of each freeze-dried compost sample with a FastDNA Kit for Soil (MP Biomedical, USA) according to the manufacturer's instructions. The concentration and purity of the DNA samples were detected with an Epoch MultiVolume Spectrophotometer (BioTek, USA). The quality checked DNA samples were stored at −20 °C. High-throughput sequencing was performed for the 16S rRNA gene in soil bacteria by Novogene Bioinformatics Technology Co. Ltd using the Ion S5XL platform. The 16S V4 region was amplified using the primers: 515F (GTGCCAGCMGCCGCGGTAA) and 806R (GGACTACHVGGGTWTCTAAT). The raw data were then subjected to a quality control procedure using UPARSE.28. USEARCH was used to filter chimeras and the remaining sequences were clustered to generate operational taxonomic units (OTUs) at the 97% similarity level. The OTUs in each sample were analyzed with QIIME software. The OTUs in each sample were classified with the RDP classifier and detailed annotations were obtained for the OTUs. A table of OTUs was constructed using the PICRUSt program (Langille et al., 2013), where the OTU counts were standardized with PICRUSt according to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database in order to consider the number of 16S rRNA genes in different taxa. Principal component analysis was conducted and heat maps were generated to visualize the data. 3
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enhanced mineralization caused by rapid heating. At the end of the composting process, the WSC contents of the treatments were: 12.75 g/ kg in CK > 12.05 g/kg in B2 > 11.1 g/kg in B0.5 > 10.75 g/kg in B1, and they all conformed with the maturity standard for compost (WSC < 17 g/kg) proposed by Bernai et al. (1998), thereby indicating that the final composts obtained after all four treatments were completely mature. Compared with the WSC contents on day 1, the decreases in WSC were largest in B0.5 and B1, and the WSC contents were significantly lower than those in CK and B2 (F = 126.398, P < 0.05). In order to evaluate the TOC losses during composting, simulations were conducted with the first-order degradation kinetics equation (Jain and Jambhulkar, 2018) expressed as follows.
Table 1 Changes in physicochemical properties (pH, C/N ratio (total organic carbon/ total nitrogen), Seed germination index (GI)) under different treatments during composting. Treatment Day 1 Day 4
Day 7
Day 15
Day 26
pH CK CK B0.5 B1 B2 CK B0.5 B1 B2 CK B0.5 B1 B2 CK B0.5 B1 B2
7.64 8.35 8.30 8.41 8.33 8.14 8.08 8.15 8.17 7.99 8.02 7.94 7.96 7.94 7.92 7.84 7.81
C/N ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.01a 0.02b 0.02c 0.00a 0.01b 0.01b 0.01c 0.01b 0.01a 0.02a 0.02a 0.02b 0.01b 0.02a 0.01a 0.03b 0.02c
25.8 26.2 27.5 24.7 24.4 24.1 25.1 23.8 22.6 23.2 24.1 21.2 22.0 22.3 22.8 20.4 20.7
GI (%) ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.3a 1.8ab 1.4a 0.7b 0.3b 0.1ab 1.0a 1.2ab 0.7b 0.1ab 0.7a 1.c 0.6bc 0.8a 0.1a 1.2b 0.3b
24.5 ± 1.6a 43.6 ± 4.9a 52.2 ± 10.8a 47.4 ± 4.4a 53.4 ± 5.8a 55.6 ± 15.8c 68.7 ± 6.8bc 81.2 ± 10.1ab 92.4 ± 6.8a 95.9 ± 19.2a 104.2 ± 18.4a 106.9 ± 20.8a 108.3 ± 21.0a 155.5 ± 42.1a 161.9 ± 30.3a 168.4 ± 32.3a 182.6 ± 34.4a
d (BVS ) = dx
k (BVS )
At the initial composting time, t = 0 and BVS = BVS0, and thus the equation can be simplified as follows.
BVS = BVS0
(1
e
kt )
In the equations above, BVS represents the total amount of carbon degraded during composting, BVS0 represents the total initial degradable carbon-containing substances, t represents the time, and k is the first-order reaction rate constant. According to the calculated R2 values (Table 2), the equation fitted for CK was the best, whereas the fit was poor for B0.5 and the value of k was the lowest. The lower k value indicates that B0.5 could reduce the degradation and mineralization of carbon and enhance carbon sequestration.
C/N ratio in B0.5 was significantly higher than those in B1 and B2 (F = 6.817, P < 0.05), thereby indicating that B0.5 was beneficial for carbon sequestration during composting. GI can be used to measure the maturity of compost. Previous studies have shown that biological methods can be used to effectively determine the toxicity of compost and evaluate the degree of compost maturity (Liu et al., 2018; Cui et al., 2017). The GI in all of the treatments tended to increase throughout the composting process. After day 15 of composting, the GI values exceeded 96% in all of the treatments to satisfy the maturity standard (GI > 80%), and the higher Bacillus subtilis inoculation levels led to higher GI values, although there were no significant differences among the treatments (P > 0.05). These results are similar to those obtained by Yang et al. (2020). The results indicate that the toxic substances in the compost gradually degraded during the composting process, and B2 was the most effective of all the treatments. However, the seed germination rate was relatively high, which may have been related to the 48-h culture period in the experiment.
3.3. Changes in humus carbon and its components Humification is a process that transforms organic matter into HS and it is also the key step for carbon sequestration in compost. Humification has direct effects on the fertility and stability of compost (Qi et al., 2019). During the composting process, complex organic matter is gradually decomposed into HS precursors by microorganisms. These HS precursors can be completely mineralized by microorganisms to produce CO2 or transformed into HS under the action of enzymes (Wu et al., 2017; Huang et al., 2019). Fig. 3(a) shows the changes in the HS-C contents during composting. The HS-C content decreased significantly in B0.5 during the mesophilic period of composting (F = 89.690, P < 0.05), which was due to the rapid temperature increase and strong mineralization in the initial stage of composting, thereby decreasing the synthesis of HS from HS precursors. The HS-C content was significantly higher in B0.5 compared with the other treatments during the cooling and maturation phase (F = 9.200, P < 0.05). Thus, B0.5 could significantly reduce the mineralization during the middle and late stages of composting to promote the transformation of HS precursors into HS and conserve carbon in the form of humus. HA and FA are important components of HS. FA is more active than HA, and the high content of unstable FA in the original compost was gradually converted into the more stable HA, where this process occurred mainly in the thermophilic period of composting (Yu et al., 2019a). Fig. 3(b) shows the changes in the HA-C contents during composting. The HA-C contents increased initially and then decreased. The increases in the HA-C contents in the mesophilic and thermophilic stages of composting were due to the active transformation of FA into HA, and the HS precursors were used to synthesize HA (Wang et al., 2019). In the later stage, the microorganisms decomposed HA and HS precursors in order to maintain their own metabolism, and mineralization also led to carbon release, thereby resulting in decreases in the HA-C contents. The FA-C contents decreased in the four treatments during the composting process (Fig. 3(c)), and these changes are consistent with the results obtained by Wang et al. (2017b). These decreases occurred because microorganisms preferentially utilize simple
3.2. Differences in the carbon contents during composting Composting involves a combination of the mineralization and humification of organic matter. Mineralization refers to the process where microorganisms degrade organic substances to release CO2 and reduce carbon sequestration during composting (Qi et al., 2019). TOC is present in organic matter and it can reflect the nutritional characteristics and quality of compost. Fig. 2(a) shows the changes in the TOC contents during composting. The TOC concentrations decreased in all of the treatments due to the mineralization of the compost. Similar results were obtained by Awasthi et al. (2020). After day 26 of the composting process, 2.8%, 1.0%, 4.1%, and 8.7% of the initial TOC contents were degraded in CK, B0.5, B1, and B2, respectively. Therefore, inoculation with 0.5% Bacillus subtilis could effectively reduce the mineralization of compost and the carbon losses. WSC is an important carbon source that can be used directly by microorganisms to support their growth and reproduction, and it is closely related to the maturity and microbial activity levels of compost (Straathof, 2015). According to Fig. 2(b), the WSC contents decreased in all of the treatments. In the initial stage of composting, the raw materials contained large amounts of readily degradable substances with a high soluble carbon content, whereas the mature compost contained more macromolecular substances with low solubility in water and less soluble carbon due to the action of microorganisms (Zbytniewski, 2005; Zhu et al., 2020). During the mesophilic period, the decrease in WSC was largest in B0.5 (14.6%), which was related to the 4
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Fig. 2. Changes in total organic carbon (TOC) and water soluble carbon (WSC) contents during composting: (a) TOC; and (b) WSC. The bars represent standard deviations (n = 3).
(44.9–48.4%), followed by the genetic information processing group (20.4–21.4%), environmental information processing group (13.1–15.0%), cell process group (6.5–8.4%), unclassified group (5.3–5.9%), human disease group (2.8–3.0%), and organismal system group (1.7–1.9%). Twelve typical metabolic pathways were identified (Fig. 4(b)), where carbohydrate metabolism and amino acid metabolism were the top two pathways, which accounted for 40% of the total metabolic pathways. During the composting process, the abundances of metabolism genes increased gradually and then eventually remained stable, with similar changes in the different treatments. Compared with CK, inoculation with Bacillus subtilis reduced microbial metabolism in the mesophilic and thermophilic stages of composting, where the higher inoculation amounts led to more obvious reductions. Inoculation with 0.5% Bacillus subtilis effectively reduced microbial metabolism in the cooling and maturation stages of composting. Among the 12 metabolic pathways, amino acid metabolism was the most abundant during composting. A previous study stated that amino acids are HS precursors and they play important roles in the formation of HS (Zhang et al., 2019). Moreover, amino acids are sources of energy and carbon for microbial metabolism throughout the composting process (López-González et al., 2015). According to the level 3 functional
Table 2 Parameters of carbon degradation kinetics during composting. (R2 means Correlation coefficient, k means the first-order reaction rate constant, RMSE means Root Mean Squared Error). Treatment
Carbon loss (%)
k
R2
RMSE
CK B0.5 B1 B2
2.8 1.0 4.0 8.7
0.00175 0.00064 0.00278 0.00615
0.919 0.829 0.891 0.86
0.313 0.158 0.582 1.323
organic matter such as FA (Zhang et al., 2019), and FA can be converted into HA. In addition, the FA-C contents decreased rapidly in the mesophilic and thermophilic phases, thereby indicating that FA was mainly changed into HA during these two periods. 3.4. Microbial functional metabolism genes during composting The PICRUSt database was used to analyze the effects of Bacillus subtilis on microbial functional genes. As shown in Fig. 4(a), the abundance of microbial metabolic function genes was highest
Fig. 3. Changes in contents of humic substance carbon (HS-C) and carbon components (humic acid carbon (HA-C) and fulvic acid carbon (FA-C)) during composting: (a) changes in HS-C contents during composting; (b) changes in HA-C content during composting; and (c) change in FA-C contents during composting. The bars represent standard deviations (n = 3). 5
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Fig. 4. Changes in the microbial function profiles during composting: (a) biochemical metabolic pathways; (b) level 2 KEGG function predictions in terms of the relative abundances of the 13 main metabolic functions; (c) level 3 KEGG function predictions in terms of the relative abundances of the 13 main functions related to amino acid metabolism and carbohydrate metabolism.
predictions (Fig. 4(c)), the abundances of arginine and proline metabolism, and aspartate and glutamate metabolism genes related to TCA were lower in B0.5 than the other treatments during composting. The TCA cycle is an important metabolic pathway for CO2 production during composting (Wang et al., 2019). In addition, B0.5 reduced purine metabolism of nucleotides and prevented the combination of nucleotide purine and deamination, thereby inhibiting the decomposition of amino acids into H2O and CO2 (Bhagavan et al., 2015). Carbohydrate metabolism was another major metabolic pathway. The KEGG pathway annotations predicted that carbohydrate metabolism mainly comprised the following metabolic pathways: pyruvate metabolism, butanoate metabolism, glycolysis, propanoate metabolism, amino sugar and nucleotide sugar metabolism, and TCA cycle. Nakasaki and Araya (2013) reported that acetic acid, propionic acid, butyric acid, and lactic acid are the four main types of organic acids, and the pH is decreased due to the production of organic acids. As shown in Fig. 4(c), the metabolic intensity was relatively low for butanoate and propanoate in the early stage of composting when a large amount of organic acids accumulated and the pH of the compost decreased continually. After the thermophilic stage of composting, the metabolic intensity increased and stabilized, and thus the pH gradually stabilized. The intensities of methane metabolism and TCA cycle in the middle and late stages of composting were lower under B0.5 than the other treatments, thereby indicating that B0.5 could effectively reduce the carbon losses during composting. The abundance of carbohydrate metabolism genes is associated with the carbon conversion rate (Hartman et al., 2017), which represents the amount of solid carbon released in the form of CO2, CH4, and other gases. Therefore, the higher TOC, HS-C, FA-C, and HA-C levels in B0.5 were due to the low carbon conversion rate in the compost because of low carbohydrate metabolism.
pH, and TN) and functional metabolism (Pyruvate_metabolism, Butanoate_metabolism, Propanoate_metabolism, Methane_metabolism, Citrate_cycle_(TCA_cycle), Arginine_and_proline_metabolism) on the carbon contents of the compost (TOC, WSC, HS-C, HA-C, and FA-C) (Fig. 5). RDA1 and RDA2 explained 81.67% of the total variation in carbon (pH = 44.7%, Butanoate_metabolism = 10.8%, Propanoate_metabolism = 8.9%, Arginine_and_proline_metabolism = 4.8%,
3.5. Relationship between the composting environment and carbon
Fig. 5. Redundancy analysis based on environment factors, functional metabolism genes and carbon, where blue represents carbon, red represents environmental factors; and black represents the sample points. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
The environmental characteristics and microbial metabolism in the compost directly affected the changes in the carbon contents. RDA was used to further evaluate the effects of environmental factors (temperature, 6
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Citrate_cycle_(TCA_cycle) = 3.9%, Methane_metabolism = 5.3%, temperature = 1.8%, Pyruvate_metabolism = 1.5%, and TN < 0.1%). The lengths and angles of the arrows in Fig. 5 indicate the importance and correlations of the variables, where an angle < 90° represents a positive relationship and a smaller angle denotes a stronger positive relationship, whereas an angle > 90° indicates a negative relationship and a greater angle denotes a stronger negative relationship. Fig. 5 shows that B0.5, B1, and B2 were distributed near the horizontal axis, and the distribution of B0.5 was relatively concentrated, thereby indicating that inoculation with Bacillus subtilis could affect the transformation of carbon, where B0.5 had the most significant effect. There was a significant positive correlation between pH and carbon because the pH of the compost was related to the accumulation of ammonium ions and organic acids (Chen et al., 2019). As the composting process continued, ammonium ions were gradually nitrated and the organic acids generated by microbial metabolism were continuously enriched, so the pH decreased. An appropriate pH is conducive to microbial metabolism and it can affect the carbon content of compost (Wang et al., 2017c). Therefore, the pH was the main reason for the changes in the carbon contents during composting. In this study, the pH value (7.92) in B0.5 during the maturity stage was significantly higher than those in B1 and B2, and it facilitated reductions in carbon metabolism and thus carbon retention. Temperature had positive relationships with WSC and HS-C because large amounts of simple organic matter were utilized directly by microorganisms for their growth during the mesophilic stage of composting, and thus the temperature increased rapidly. In addition, microorganisms decomposed complex organic matter (cellulose and hemicellulose) into simple organic matter to promote the generation of HS precursors (Wu et al., 2017; Huang et al., 2019). During the middle and later stages of composting, the abundances of functional metabolism genes such as pyruvate metabolism, methane metabolism, and TCA cycle increased, and they were negatively correlated with WSC and TOC. These changes might have been related to the rapid consumption of simple compounds by microorganisms via mineralization (Lu et al., 2018; Wang et al., 2019). TN was positively correlated with metabolism genes, but negatively correlated with TOC and WSC because the metabolism of organic matter reduces the compost quality (Pan et al., 2018). The results obtained in this study showed that 0.5% Bacillus subtilis could significantly increase the humus and carbon contents of the composting products. Therefore, during actual production, 0.5% Bacillus subtilis can be inoculated to improve the quality of compost. The application of compost products containing Bacillus subtilis in agricultural production may help to improve the soil quality and crop growth (D’Hose et al., 2014). In addition, the form of Bacillus subtilis used in this study was a wettable powder, which has advantages in terms of its low price and convenient use. Therefore, low-cost compost products and high-yield crops will contribute to agricultural economic benefits.
CRediT authorship contribution statement Manli Duan: Conceptualization, Funding acquisition, Methodology, Investigation. Yuhua Zhang: Investigation, Data curation, Writing original draft. Beibei Zhou: Investigation, Methodology, Formal analysis. Zhenlun Qin: Investigation, Methodology. Junhu Wu: Conceptualization, Project administration, Software. Quanjiu Wang: Conceptualization, Visualization, Funding acquisition. Yanan Yin: Writing - review & editing, Visualization. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements This study was funded by the National Natural Science Foundation of China (41807131, 41977007 and 41830754), China Postdoctoral Science Foundation (2019M653707), and Natural Science Foundation of Shaanxi province of China (2019JQ-537), Research project of State Key Laboratory of Eco-hydraulics in Northwest Arid Region of China (2019KJCXTD-4 and QJNY-2019-01). We thank Dr. Duncan E. Jackson for language editing. References An, C.J., Huang, G.H., Yao, Y., Sun, W., 2012. Performance of in-vessel composting of food waste in the presence of coal ash and uric acid. J. Hazard. Mater. 203, 38–45. Awasthi, M.K., Duan, Y., Awasthi, S.K., Liu, T., 2020. Effect of biochar and bacterial inoculum additions on cow dung composting. Bioresour. Technol. 297, 122407. Bernai, M.P., Paredes, C., Sanchez-Monedero, M.A., 1998. Maturity and stability parameters of composts prepared with a wide range of organic wastes. Bioresour. Technol. 63 (1), 91–99. Bhagavan, N.V., Chung-Eun, H. 2015. Chapter 15: Protein and Amino Acid Metabolism Essentials of Medical Biochemistry (Second Edition), 227–268. Chang, R., Li, Y., Chen, Q., Guo, Q., 2019. Comparing the effects of three in situ methods on nitrogen loss control, temperature dynamics and maturity during composting of agricultural wastes with a stage of temperatures over 70 °C. J. Environ. Manage. 230, 119–127. Chen, M., Huang, Y., Liu, H., Xie, S., 2019. Impact of different nitrogen source on the compost quality and greenhouse gas emissions during composting of garden waste. Process Saf. Environ. Prot. 124, 326–335. Cui, H.Y., Zhao, Y., Chen, Y.N., Zhang, X., Wang, 2017. Assessment of phytotoxicity grade during composting based on EEM/PARAFAC combined with projection pursuit regression. J. Hazard. Mater. 326, 10–17. David, J., Gary, N., 1997. Formation of volatile compounds during fermentation of soya beans bacillus subtilis. J. Sci. F. Agri. 74 (8), 132–140. D’Hose, T., Cougnon, M., De Vliegher, A., Vandecasteele, B., Viaene, N., 2014. The positive relationship between soil quality and crop production: a case study on the effect of farm compost application. Appl. Soil Ecol. 75, 189–198. Hartman, W.H., Ye, R., Horwath, W.R., 2017. A genomic perspective on stoichiometric regulation of soil carbon cycling. The ISME journal 11 (12), 2652. Huang, Y., Danyang, L., Shah, G.M., Chen, W., Wang, W., Xu, Y., 2019. Hyperthermophilic pretreatment composting significantly accelerates humic substances formation by regulating precursors production and microbial communities. Waste Manage. 92, 89–96. Jain, M.S., Jambhulkar, R., 2018. Biochar amendment for batch composting of nitrogen rich organic waste: effect on degradation kinetics, composting physics and nutritional properties. Bioresour. Technol. 253, 204–213. Langille, M.G., Zaneveld, J., Caporaso, J.G., McDonald, D., Knights, D., Reyes, J.A., 2013. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotechnol. 31 (9), 814–821. Li, Y., Liu, Y., Yong, X., Wu, X., Jia, H., Wong, J.W., 2019. Odor emission and microbial community succession during biogas residue composting covered with a molecular membrane. Bioresour. Technol. 297, 122518. Liu, L., Wang, S., Guo, X., Zhao, T., 2018. Succession and diversity of microorganisms and their association with physicochemical properties during green waste thermophilic composting. Waste Manage. 73, 101–112. López-González, J.A., Suárez-Estrella, F., Vargas-García, M.C., López, M.J., Jurado, M.M., 2015. Dynamics of bacterial microbiota during lignocellulosic waste composting: Studies upon its structure, functionality and biodiversity. Bioresour. Technol. 175, 406–416. Lu, Q., Zhao, Y., Gao, X., Wu, J., Zhou, H., Tang, P., 2018. Effect of tricarboxylic acid cycle regulator on carbon retention and organic component transformation during food waste composting. Bioresour. Technol. 256, 128–136.
4. Conclusion Inoculation with Bacillus subtilis at 2% accelerated the maturation of compost and improved the seed GI, but the carbon losses were greater. Inoculation with Bacillus subtilis at 0.5% prolonged the thermophilic period, reduced mineralization during the cooling and maturation stages of composting, and increased the TOC and HS-C contents. Adding Bacillus subtilis at 0.5% effectively decreased the abundances of functional carbon metabolism genes. RDA demonstrated that pH and microbial functional metabolism were closely related to carbon sequestration during composting. Inoculating cow manure–straw compost with 0.5% Bacillus subtilis can accelerate compost maturation, retain carbon, and improve the compost quality.
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