Novel mechanistic understanding that Lactiplantibacillus plantarum is more capable of improving the ensiling performance of wheat straw silage than xylanase by driving certain key metabolites

Novel mechanistic understanding that Lactiplantibacillus plantarum is more capable of improving the ensiling performance of wheat straw silage than xylanase by driving certain key metabolites | 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 Novel mechanistic understanding that Lactiplantibacillus plantarum is more capable of improving the ensiling performance of wheat straw silage than xylanase by driving certain key metabolites Haoran Yu, Richa Hu, Yushan Jia, Yanzi Xiao, Shuai Du This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4794446/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 16 You are reading this latest preprint version Abstract Microbial and enzyme additives can improve silage performance, but there is limited comparative research on the effects of microbial and enzyme additives on improving silage fermentation quality, and the underlying microbial and metabolic mechanisms remain unclear. This study investigate the effects without inoculants (CK treatment) or with Lactiplantibacillus plantarum (LP treatment) , xylanase (XY treatment) and their combination (LPXY treatment) on the fermentation quality, as well as on the microbial communities and metabolite profiles of the wheat straw silage. The results demonstrated that the LP treatment has a better effect on improving the fermentation quality of wheat straw silage compared to other treatments, as evidenced by markedly ( p < 0.05) decreased the pH, acid detergent and neutral fiber (ANF, NDF), and increased the lactic acid (LA) and acetic acid (AA) concentrations. After the fermentation process, the LP treatment significantly ( p < 0.05) enhanced the abundance of Lactobacillus , reduced bacterial Shannon ( p < 0.05) and increased some key metabolites content. The structural equation models (SEMs) and Pearson’s correlation results proved that the LP treatment drives the wheat straw silage fermentation quality via increasing the abundance of Lactobacillus , decreasing the diversity of bacterial community and enriching the content of certain key metabolites. The present study provides mechanistic evidence that Lactiplantibacillus plantarum additive is superior to xylanase additive and their combination on improving fermentation quality of wheat straw silage, that is, by enriching certain key metabolites to increase AA and LA concentrations, providing a reference for the cross study of silage feed fermentation microbiome and metabolome. Wheat straw Ensiling Microbiome Metabolome Fermentation quality Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Wheat ( Triticum aestivum L. ) straw is a common agricultural residue utilized as ruminant feed owing to its high carbohydrate content [ 1 ]. Ensiling, as a method for large-scale preservation of wet materials, reduces dry matter loss in feed and has increasingly become a long-term utilization strategy for wheat straw [ 2 ]. Compared with other storage, ensiling not only improves biodegradability but also saves costs [ 3 ]. Nevertheless, wheat straw typically possesses low water-soluble carbohydrates (WSC) and lacks epiphytic lactic acid bacteria, making it challenging to produce high-quality silage through natural anaerobic fermentation [ 4 ]. Silage microbial additives are commonly employed in feed production to effectively enhance fermentation quality [ 5 ]. Lactic acid bacteria inoculants have the capability to rapidly accumulate lactic acid and lower pH during the early stages of silage, thereby enhancing fermentation quality [ 6 ]. Xylanase (XY) can improve the fermentation quality and rumen digestion rate of silage feed [ 7 ]. However, there is little research on whether the mixed additions of lactic acid bacteria and XY have a synergistic effect, as well as the comparative study of the two types of additives on the improvement of wheat straw silage quality. Xylan is among the hemicelluloses that are not fully utilized in the rumen, leading to the inefficient utilization of feed energy [ 8 ]. XY can disrupt its internal structure, release soluble sugars, increase the concentration of fermentation substrates, and improve feed utilization efficiency[ 9 ]. Homofermentative bacteria (e.g. Lactiplantibacillus plantarum ) are widely used as they are safe and easy to use [ 10 ]. Homofermentative bacteria can reduce the loss of silage fermentation quality by directly increasing lactate and acidification rates [ 10 ]. Therefore, both two types of additives may enhance the fermentation quality of wheat straw silage. Silage is a fermentation process dominated and driven by microorganisms, so changes in microbial communities are usually related to fermentation quality [ 11 ]. Understanding the microbial community’s contribution to silage feed not only provides insights into high-quality feed preparation techniques, but also helps maintain the quality of silage feed [ 12 ]. Lactic acid bacteria are considered beneficial bacteria in the production of organic acids such as lactic acid (LA) and are key to ensuring high-quality silage feed [ 13 ]. Throughout the silage fermentation process, the production of harmful bacteria like Listeria sp. and Clostridia can diminish feed quality [ 14 ]. The microbial community diversity of silage feed includes both beneficial and harmful bacteria [ 15 ]. Therefore, changes in lactate content in silage feed typically regulate microbial diversity. An increase in lactic acid bacteria content within the microbial community tends to reduce microbial diversity [ 16 ]. While some research has investigated the effects of microbial additives on microbial community changes during ensiling fermentation, there remains a lack of mechanistic understanding, particularly concerning microbial community changes in oat ensiling with lactic acid bacteria and XY additives [ 17 , 12 ]. In addition to microbial community succession, the fermentation process of silage also involves changes in metabolites and metabolic pathways [ 18 ]. The quality of feed fermentation is closely related to the relationship between silage microorganisms and metabolites, and fermentation quality is usually driven by microorganisms and metabolites [ 19 ]. Recently, metabolomics has been applied to the study of silage ecosystems [ 20 , 17 , 21 ], and these results indicate a strong interaction between these metabolites and microorganisms. Since the fermentation process of silage is dominated by microorganisms, microorganisms also determine the changes in metabolic products, ultimately affecting the fermentation quality. However, there is a lack of comprehensive understanding regarding the microbial community's role in driving metabolic product changes in silage ecosystems, and the mechanism through which microbes drive such changes and enhance fermentation quality remains elusive. To data, there is limited literature on the fermentation quality and microbial community changes of wheat straw with the additions of XY and Lactiplantibacillus plantarum (LP), and the potential synergistic effect of combining these two additives remains unclear. And there has been no investigation into how the microbial community of silage influences metabolic products to enhance fermentation quality. The aim of the present study was to identify microbial additives that enhance the fermentation pathway and mechanism of wheat straw based on metabolomic and microbiome analyses, and to assess their potential synergistic effect. 2. Materials and methods 2.1. Substrate and silage Wheat straw originated from the Hulunber Grassland Ecosystem National Observation and Research Station of the Chinese Academy of Agricultural Sciences in Hulunber, Inner Mongolia, China. The wheat straw was harvested at the late maturity stage, then chopped and immediately taken to the laboratory for silage making when the wheat straw samples were picked. Inoculants, XY (total Xylanase activity of 50,000 U/g) purchased from Hefei Bomei Biotechnology Co., Ltd, Hefei, China; Lactiplantibacillus plantarum purchased from Jiangsu Lvke Biotechnology Company, Gaoyou, China. The treatments were as follows: control (CK), XY, LP and LPXY (mixed LP and XY). The inoculants were distinctively diluted in distilled water and added according to the manufacturer’s guidelines, 5 mg/kg of inoculant power was added on a fresh matter (FM) basis, after which the number of LP was equivalent to 1.0 × 10 5 colony-forming unit per gram (cfu/g), the CK treatment was also treated with the same volume of distilled water. Both fresh materials wheat straw and wheat straw silage were stored at a small-scale fermentation system (260 cm × 380 cm; Hiryu KN type; Asahi kasei, Tokyo, Japan). A 200 gram of the samples were packed into the polyethylene plastic bag, and removing air with a vacuum sealer (N-14886, Deli Group Co., Ltd., Zhejiang, China). A total of 24 bags (4 treatments × 6 replicates) of wheat straw were stored at room temperature (23 ± 2°C). After 60 days of fermentation process, these bags were opened and the ensiling performance, bacterial community and metabolites profiles were analyzed. 2.2. Ensiling performance and nutritive values analyses Clean containers were used to collect FM and wheat straw silage after being uniformly blended for ensiling performance and nutritive values analyses. The dry matter (DM) content of the FM and silage samples were measured after drying the sample for 72 h at 65°C with an oven. The dried samples were ground and through a 1 mm screen for the nutritive values analysis. The crude protein (CP) and acid detergent lignin (ADL) contents were analyzed according to the method of the Association of Official Analytical Chemists (AOAC, 2005). The neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents were determined by a ANKOM A200i Fiber Analyzer (ANKOM Technology, Macedon, NY, USA) with the report [ 22 ]. The fraction of cell wall constituents, including cellulose, hemicellulose and holocellulose was calculated using methods briefed by [ 23 ]. The anthrone method was selected to evaluate the WSC content [ 24 ]. A 20 gram of the wheat straw silage samples were mixed with 180 mL sterile water and stored for 24 h at 4°C fridge for the extractions, then the extracts were filtered through four layers of cheesecloth. A glass-electrode pH meter was used to measure the pH value of the filtrate. The organic acids concentrations in the filtrate, mainly lactic acid, acetic acid, propionic acid and butyric acid, were measured by the high-performance liquid chromatography methods [ 25 ]. The plate count method was used to analysis the microbial population of the wheat straw silage according to the previously published methods [ 25 ]. Cellulose (CL), hemicellulose (HC) and holocellulose (Hoc) contents were determined as described [ 22 ]. 2.3. Microbial analysis The genomic DNA of bacterial community was extracted from the FM and wheat straw silage samples by the CTAB method. The Nano Drop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) was used to determine the concentrations and qualities of the extracted genomic DNA. The V3–V4 regions of 16S rDNA gene was targeted with the universal primer pair 341F and 806R. The Illumina NovaSeq 6000 platform (IlluminaInc., San Diego, CA, USA) was used to sequence. The Raw pair-end reads were analyzed by the Qiime2 platform ( https://qiime2.org/ ). Amplicon sequence variants (ASVs) were obtained by eliminating low-quality data using DADA2 [ 26 ]. Subsequently, the ASVs were taxonomically annotated against the SILVA database ( https://www . arb-silva.de/, Release 138) using mothur [ 27 ]. 2.4. Metabolites profiles analyses The metabolites in the wheat straw silage samples were extracted according to the previous methods [ 28 ]. The raw data files of the 24 wheat straw silage samples generated by the liquid chromatography-mass spectrometry (LC–MS) platform (Thermo Fisher, Ultimate 3000LC, Q Exactive) using the compound Discover 3.1 (CD 3.1 Thermo Fisher) to perform peak picking, peak alignment and quantitation for each metabolite. After that, peak intensities were normalized to the total spectral intensity [ 29 ]. The normalized data was used to predict the molecular formula based on additive ions, molecular ion peaks and fragment ions [ 30 ]. Then peaks were matched with the mzCloud ( https://www.mzcloud.org/ ) mz Vault and Mass List database to obtain the accurate qualitative and relative quantitative results. After mean centering and unit variance scaling, the principle component analysis (PCA) and (orthogonal) partial least squares discriminant analysis (O)PLS-DA were selected to show the differences of the metabolites among the treatments by R package (prcomp). The variable importance in the projection (VIP) ranks and VIP > 1.7 were considered as the relevant for treatment discrimination, and the results were displayed by the (O)PLS-DA plots. The plots package in R was used for significant metabolites for expression pattern clustering using. Hierarchical clustering method were used for distance calculation algorithms. The metabolites set enrichment was analyzed with the Stats package in R and the SciPy package in Python using the MetaboAnalyst 6.0 ( https://www.metaboanalyst.ca ). 2.5 Statistical analysis The chemical compositions and bacterial alpha diversity (Shannon, Richness) data of wheat straw and wheat silage were analyzed by a one-way ANOVA and Kruskal Wallis test (HC and HoC do not follow a normal distribution). Tukey’s test and Fisher’s test were utilized to assess significant differences in comparisons at the 5% level. The linear discriminant analysis (LDA) effect size (LEfSe) with relative abundance data was utilized to assess the significance. To compare functional profiles among groups, metabolites from different treatments were analyzed using Duncan-test. We correct for the false discovery rate by controlling FDR (False Discovery Rate) to not exceed 5%. Five differential metabolites were ultimately identified (enriched in LP), including positive and negative. To determine the relationship between differential metabolites and fermentation quality, Pearson’s correlation analysis was conducted, using log10-tranformed to differential metabolites. Structural equation modeling (SEMs) was employed to evaluate key drivers of fermentation quality (CP, LA, AA, ADL, ADF, and NDF), including bacterial community and differential metabolites. One useful characteristic of SEMs for our purposes here is its utility for partitioning direct and indirect effects that one variable may have on another, and estimate the strengths of these multiple effects. Unlike regression or ANOVA, SEMs offers the ability to separate multiple pathways of influence and view them as parts of a system, and thus is useful for investigating the relationship complex networks found in silage fermentation ecosystems [ 31 ]. We calculated the standardized of all index in SEMs. All the data were analysed using open-source tools for R software (version 4.3.2). 3. Result and discussion 3.1 Chemical characteristics and microbial population of raw materials The DM of the fresh wheat straw was 50.30%, ADF, NDF, CP contents were 29.50, 37.10 and 12.90%DM, respectively (Table 1 ). The counts of LAB, yeasts, aerobic bacteria, and coliform bacteria were 4.27, 8.47, 8.35, 8.40 and 8.32 log10 cfu/g of FM, respectively. Table 1 Chemical and microbial characteristics of substrates before ensiling Items Wheat straw Dry matter (%) 50.30 Water-soluble carbohydrates (% DM) 3.42 Crude protein (% DM) 12.90 Acid detergent fiber (% DM) 29.50 Neutral detergent fiber (% DM) 37.10 Lactic acid bacteria (log 10 cfu/g FM) 4.27 Yeast (log 10 cfu/g FM) 8.47 Aerobic bacteria (log 10 cfu/g FM) 8.35 Coliform bacteria (log 10 cfu/g FM) 8.40 Mold (log 10 cfu/g FM) 8.32 DM, dry matter; cfu, colony-forming units. 3.2 Fermentation quality of different treatment The fermentation characteristics of the wheat straw silage with different treatments are shown in Fig. 1 . All the additions remarkably ( p < 0.05) decreased the pH value. Compared to the CK and XY treatments, the LP and LPXY treatments enhanced LA and AA ( p < 0.05). XY-treated silage and LAB-treated silage treatment significantly reduced ADF, NDF and ADL ( p < 0.05). While there was no distinction between additives and CK on the CP content in wheat straw silage. 3.3 Bacterial community of wheat straw silage The bacterial community in the different treated silages were clearly distinguished at 60 days of wheat straw (Fig. S1 ). Alpha diversity of wheat straw silage bacteria is shown in Fig. 2 A and Fig. 2 B. LP-treated silage significantly reduced bacterial Shannon diversity ( P < 0.05), while XY-treated silage and LPXY-treated silage did not exhibit a decrease in bacterial Shannon diversity compared to CK. Furthermore, all three additives had no impact on bacterial Richness. 3.4 Metabolomic profiles Metabolomes in the different treated silages were clearly separated at 60 days of wheat straw (Fig. S2). Overall, 2,557 metabolites were identified in the wheat straw silage samples. Based on Duncan-tests and variable importance in projection (VIP) filtering of the relative contents of wheat straw silage samples, 57 metabolites exhibited significant differences between the two groups ( p 1.7). Among these, 30 were positively ionized metabolites (Fig. 4 A and 4 B), and 27 were negatively ionized metabolites (Fig. 4 C and 4 D), including carboxylic acids and derivatives, amino acids, peptides, analogues, and other metabolites. Specifically, three metabolites were enriched in positive ionization mode, and two metabolites were enriched in negative ionization mode in LP-treated silage. Additionally, combined with LDA analysis, the results confirmed the enrichment of five metabolites in LP-treated silage (Fig. S3 and S4). 3.5 Lactobacillus driven fermentation quality of wheat straw Results from the SEMs showed that 88% (CP), 24% (LA), 25% (AA), 59% (ADL), 28% (ADF) and 80% (NDF) of the variance in fermentation quality could be explained by Lactobacillus of wheat straw silage respectively (Fig. 6 ). Lactobacillus had a negative and large effect on bacterial Shannon (63%), indicating a reduction in bacterial diversity in silage Lactobacillus had a direct positive effect on differential metabolites, while bacterial diversity had a negative effect on differential metabolites. In summary, Lactobacillus promotes the production of differential metabolites. In addition, our SEMs demonstrate that LA and AA are influenced by differential metabolites. LP-treated silage decreased bacterial diversity and enriched some metabolites, thereby affecting LA and AA production. 5. Discussion The WSC and LA of wheat straw before ensiling was much higher than the detected by other research [ 32 ], may due to the factors like climate and season of harvest, which have influence on the feeding value of the forage. LP treatment has shown a stronger promote effect than other treatments in LA and AA. After anaerobic fermentation process, the organic acid (especially the LA and AA concentrations) is the largest contributor for pH value, previous studies have also provided the same result [ 33 ]. These results found that the LA and AA contents in LP-treated and LPXY-treated silage were higher than in other treatments, confirming the significant influence of LA and AA on the pH value of silage [ 12 , 34 ]. Besides, the higher AA concentration in LP-treated silage may reflect a higher count of LA-produced bacteria in the process. Interestingly, the pH value of LPXY-treated silage was higher than that of XY-treated and LP-treated silage, possibly due to higher levels of bioactive components in XY-treated and LP-treated silage, such as phenolic acids [ 34 ]. However, the NH3-N during the fermentation process may also neutralize acids and prevent pH reduction [ 35 ]. Therefore, LPXY-treated silage may also exhibit higher NH3-N content to neutralize LA and AA [ 35 ]. LP treatment has the highest content of LA and AA, for wheat straw silage, directly increasing lactic acid bacteria has a stronger promoting effect on the enhancement of volatile fatty acids. LP and XY treatment have more impact on silage fiber. Ruminant animals prefer high protein and low fiber feed because these feeds can have higher nutrition and energy [ 36 ]. According to our results, LP additives exhibited the most significant degradation effect on fibers in wheat straw feed, which may be more favored by ruminants, despite not increasing protein content. In addition, based on the comprehensive analysis of ADL, CL, HC, and HoC, the LP additive exhibits the strongest effect on fiber decomposition in wheat silage feed, surpassing that of LPXY-treated silage. Lactic acid bacteria inoculum contains cellulase, reducing fiber content [ 37 ]. The increase of lactic acid bacteria directly enhances the utilization of compounds to improve the efficiency of lactic acid production in feed, thereby enhancing fermentation quality [ 13 ]. Contrary to expectations, there was no synergistic effect between XY additive and LP additive. Wheat straw contains a significant amount of lignin [ 38 ] Lignin is a complex polymer composed of phenolic monomers, which can prevent glycoside hydrolases from coming into contact with their substrates [ 38 , 39 ]. Lignin is a difficult substance to decompose, and fungi with strong decomposition ability usually have good effects on lignin decomposition, such as saprophytic fungi (e.g. white-rot fungi) [ 40 , 41 ]. The XY additive primarily decomposes hemicellulose and effectively utilizes free xylan, thus its impact on lignin decomposition may be minimal [ 42 ]. Our analysis of dominant bacterial relative abundance revealed that Lactobacillus is the predominant genus in LP-treated silage. The abundance of Lactobacillus exceeds half of all bacterial communities’ genus. According to the principle of ‘competitive exclusion’, the dominant microbial community is abundant, while the non-dominant microbial community is reduced, resulting in a corresponding decrease in microbial diversity [ 43 , 44 ]. Thus, inoculation with LP increased the number of dominant bacterial genera (Lactobacillus) and reduced bacterial diversity. Similarly, previous results also revealed the same results [ 45 ]. Although the XY and LPXY treatments increased the abundance of Lactobacillus compared to CK, the differences were not significant. Firmicutes was the dominant phylum in LP-treated silage, whereas Proteobacteria were dominant in the other treatments [ 46 ]. Many spoilage and harmful microorganisms belong to Proteobacteria (e.g. Escherichia coli). The high pH value of silage feed is conducive to the growth of other spoilage or pathogenic microorganisms [ 47 ]. LPXY-treated silage and CK exhibited higher pH levels than LP-treated silage, providing conditions conducive to the growth of harmful microorganisms, which may explain why Proteobacteria are the predominant phylum. Meanwhile, fermentation of silage is mainly carried out by lactic acid bacteria [ 48 ]. Our experiment also provides evidence from the perspective of silage microorganisms, that LP additives can directly increase the number of Lactobacillus and improve fermentation quality of wheat straw silage. The abundance of Lactobacillus in the silage with mixed LP and XY addition is not sufficient, thus the synergistic effect of bacteria and enzymes is not significant. Additionally, Lactobacillus was found to be relatively abundant in LP-treated silages during ensiling, as indicated by LEfSe analysis (Fig. 3 A), further highlighting the difference of LAB treatment compared to other treatments due to the enrichment of Lactobacillus ( p < 0.05). The enriched metabolites in LP-treated silage include Furoic acid and derivatives and Pyridines and derivatives. Varied microbial communities and metabolites influence fermentation quality [ 49 ]. The microbial community of inoculated microbes in silage feed, such as LP, produces more complex metabolites [ 17 ]. Our results indicate that LP treatment resulted in better fermentation quality compared to other treatments. Therefore, the bacterial community in LP-treated silage may generate distinct metabolites. Five metabolites enriched in LP-treated silage exhibited significant differences compared to other treatments. Metabolomic data suggest differences in microbial activity among silage feed treated with different additives [ 50 ]. To our knowledge, this is the first application of SEMs in silage research to elucidate the pathways and mechanisms underlying changes in fermentation quality of silage feed by integrating metabolomics and microbiome data. More importantly, we have provided compelling evidence supporting the use of microbial additives to enhance the quality of silage feed, as Lactobacillus altered bacterial diversity and enriched certain metabolites. Abundant organic acids can usually improve the palatability of feed, high LA indicates good fermentation quality, and high AA contributes to the aerobic stability of feed [ 51 , 52 ]. Previous studies combined with metabolomics, have shown that LP-treated produces more organic acids, but specific mechanisms and pathways have not been proposed [ 21 ]. Our Pearson’s correlation analysis also revealed a positive linear relationship between LA, AA, and differential metabolites, respectively (Fig. 5 A and B). With comprehensive Pearson’s analysis and SEMs, our results are more reliable, providing a compelling explanation of the role of differential metabolites in LA and AA production. However, the results of the present study also confirm that carbohydrates in feed are not influenced by differential metabolites (Figs. 5 and 6 ). This may be attributed to the production of certain enzymes by Lactobacillus during the silage fermentation process, such as cellulase and feruloyl esterase, which degrade structural carbohydrates [ 53 ]. Therefore, Lactobacillus directly explained ADF, NDF and ADL (Fig. 6 ). It is important to acknowledge objectively that differential metabolites cannot fully account for the changes in AA and LA. Out of the 2557 metabolites detected, only 5 differential products accounted for a very small proportion, less than 0.2%, yet they explained over 20% of LA and AA. This demonstrates the significance of these 5 differential metabolites. Ultimately, silage can be viewed as a complex ecosystem, where multiple biotic and abiotic factors interact to shape its composition [ 54 , 55 ]. 5. Conclusion Our study findings suggest that Lactiplantibacillus plantarum additives enhanced the abundance of Lactobacillus, reduced bacterial diversity, and enriched certain metabolites. These enriched metabolites effectively enhanced LA and AA, thereby improving the fermentation quality of wheat straw silage. Overall, our study not only confirms the positive effect of Lactiplantibacillus plantarum additives on wheat straw silage but also provides a mechanistic explanation for the improved quality of silage feed due to these additives. Declarations Funding: This work was supported by Inner Mongolia Autonomous Region Science and Technology Innovation Guidance Award Fund Project, Research and Demonstration of Fermentation Technology for Crop Straw Silage Feed in Hulunbuir Region (2022CXYD006), Research and application of rapeseed straw fermentation and feeding utilization technology in the eastern region of Inner Mongolia (NC2023022). Conflict of interest: The authors have no conflict of interest to declare. Authors’ contributions YH: Methodology, Investigation, Writing-original draft. XY: Conceptualization, Formal analysis. HR: Formal analysis, Methodology, Validation. JY: Conceptualization, Data curation, Writing review & editing. 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Yan J, Sun Y, Kang Y, Meng X, Zhang H, Cai Y, et al. An innovative strategy to enhance the ensiling quality and methane production of excessively wilted wheat straw: Using acetic acid or hetero-fermentative lactic acid bacterial community as additives. Waste Management. 2022;149:11–20. Li X, Chen F, Wang X, Xiong Y, Liu Z, Lin Y, et al. Innovative utilization of herbal residues: Exploring the diversity of mechanisms beneficial to regulate anaerobic fermentation of alfalfa. Bioresource Technology. 2022;360:127429. Li, Zhao W, Yan L, Chen L, Chen Y, Gou W, et al. Inclusion of abandoned rhubarb stalk enhanced anaerobic fermentation of alfalfa on the Qinghai Tibetan Plateau. Bioresource Technology. 2022;347:126347. Bai J, Ding Z, Ke W, Xu D, Wang M, Huang W, et al. Different lactic acid bacteria and their combinations regulated the fermentation process of ensiled alfalfa: ensiling characteristics, dynamics of bacterial community and their functional shifts. Microb Biotechnol. 2021;14:1171–82. Egan AR. Host Animal—rumen Relationships. Proceedings of the Nutrition Society. 1980;39:79–87. Romero JJ, Zhao Y, Balseca-Paredes MA, Tiezzi F, Gutierrez-Rodriguez E, Castillo MS. Laboratory silo type and inoculation effects on nutritional composition, fermentation, and bacterial and fungal communities of oat silage. Journal of Dairy Science. 2017;100:1812–28. Jung S-J, Kim S-H, Chung I-M. Comparison of lignin, cellulose, and hemicellulose contents for biofuels utilization among 4 types of lignocellulosic crops. Biomass and Bioenergy. 2015;83:322–7. Niu D, Yu C, Zheng M, Ren J, Li C, Xu C. Effects of ensiling on Irpex lacteus fermentation in wheat straw: Chemical composition, in vitro rumen digestibility, and fungal community. Animal Feed Science and Technology. 2022;292:115433. Tian S-Q, Zhao R-Y, Chen Z-C. Review of the pretreatment and bioconversion of lignocellulosic biomass from wheat straw materials. Renewable and Sustainable Energy Reviews. 2018;91:483–9. Huang W, Yu W, Yi B, Raman E, Yang J, Hammel KE, et al. Contrasting geochemical and fungal controls on decomposition of lignin and soil carbon at continental scale. Nat Commun. 2023;14:2227. Bhat MK, Hazlewood GP. Enzymology and other characteristics of cellulases and xylanases. Enzymes in farm animal nutrition. 2001;11–60. Wayne Polley H, Wilsey BJ, Derner JD. Dominant species constrain effects of species diversity on temporal variability in biomass production of tallgrass prairie. Oikos. 2007;116:2044–52. Eldridge DJ, Delgado-Baquerizo M, Travers SK, Val J, Oliver I, Hamonts K, et al. Competition drives the response of soil microbial diversity to increased grazing by vertebrate herbivores. Ecology. 2017;98:1922–31. Ogunade IM, Jiang Y, Pech Cervantes AA, Kim DH, Oliveira AS, Vyas D, et al. Bacterial diversity and composition of alfalfa silage as analyzed by Illumina MiSeq sequencing: Effects of Escherichia coli O157:H7 and silage additives. J Dairy Sci. 2018;101:2048–59. Duniere L, Xu S, Long J, Elekwachi C, Wang Y, Turkington K, et al. Bacterial and fungal core microbiomes associated with small grain silages during ensiling and aerobic spoilage. BMC Microbiology. 2017;17:50. Woolford MK. The detrimental effects of air on silage. J Appl Bacteriol. 1990;68:101–16. Wang T, Teng K, Cao Y, Shi W, Xuan Z, Zhou J, et al. Effects of Lactobacillus hilgardii 60TS-2, with or without homofermentative Lactobacillus plantarum B90, on the aerobic stability, fermentation quality and microbial community dynamics in sugarcane top silage. Bioresource Technology. 2020;312:123600. Li M, Lv R, Zhang L, Zi X, Zhou H, Tang J. Melatonin Is a Promising Silage Additive: Evidence From Microbiota and Metabolites. Front Microbiol;12. Xia G, Wu C, Zhang M, Yang F, Chen C, Hao J. The metabolome and bacterial composition of high-moisture Italian ryegrass silage inoculated with lactic acid bacteria during ensiling. Biotechnology for Biofuels and Bioproducts. 2023;16:91. Whiting GC. Organic Acid Metabolism of Yeasts During Fermentation of Alcoholic Beverages—a Review. Journal of the Institute of Brewing. 1976;82:84–92. Broberg A, Jacobsson K, Ström K, Schnürer J. Metabolite profiles of lactic acid bacteria in grass silage. Appl Environ Microbiol. 2007;73:5547–52. Ning T, Wang H, Zheng M, Niu D, Zuo S, Xu C. Effects of microbial enzymes on starch and hemicellulose degradation in total mixed ration silages. Asian-Australasian Journal of Animal Sciences. 2017;30:171. Shah AA, Liu Z, Qian C, Wu J, Zhong X, Kalsoom U-E-. Effect of endophytic Bacillus megaterium colonization on structure strengthening, microbial community, chemical composition and stabilization properties of Hybrid Pennisetum. J Sci Food Agric. 2020;100:1164–73. Cheong JZA, Johnson CJ, Wan H, Liu A, Kernien JF, Gibson ALF, et al. Priority effects dictate community structure and alter virulence of fungal-bacterial biofilms. ISME J. 2021;15:2012–27. Additional Declarations No competing interests reported. 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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-4794446","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":340800458,"identity":"f90a4121-2be9-4fbc-88e9-3a831d838c49","order_by":0,"name":"Haoran Yu","email":"","orcid":"","institution":"Northeast Normal University","correspondingAuthor":false,"prefix":"","firstName":"Haoran","middleName":"","lastName":"Yu","suffix":""},{"id":340800459,"identity":"e4d42246-36da-44f4-a027-ef81567f715c","order_by":1,"name":"Richa Hu","email":"","orcid":"","institution":"Hulunbuir University","correspondingAuthor":false,"prefix":"","firstName":"Richa","middleName":"","lastName":"Hu","suffix":""},{"id":340800460,"identity":"8f0811af-cc73-4955-b146-72d375c1ea45","order_by":2,"name":"Yushan Jia","email":"","orcid":"","institution":"Inner Mongolia Agricultural University, Hohhot Inner Mongolia","correspondingAuthor":false,"prefix":"","firstName":"Yushan","middleName":"","lastName":"Jia","suffix":""},{"id":340800461,"identity":"874292a1-e330-4b2b-98c2-80911d313f67","order_by":3,"name":"Yanzi Xiao","email":"","orcid":"","institution":"Hulunbuir University","correspondingAuthor":false,"prefix":"","firstName":"Yanzi","middleName":"","lastName":"Xiao","suffix":""},{"id":340800462,"identity":"b5422be4-e405-48e1-a7dc-1e91d897b5fa","order_by":4,"name":"Shuai Du","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYDCCAwxsQFICiJkPMCSQqIUtgSQtIMBjQJy7+G6kP3vMU2PBYC525vOHhzvsGPjbu/FbJnkjx9yY55gEg+Xs3G0SiWeSGSTOnN2AV4vBjRw2aR42CQaD27nbGBLbmBkMJHIJaUl/Js3zD6Ql5/GHxLZ6YrQkmEnztoG1MEgkth0mrEXyzBszybl9IC1pZkAtx3kI+oXvePoziTff6oBakh9//NlWLcff3otfCwzUN0AZPEQpHwWjYBSMglGAHwAARRxEdzsE5dAAAAAASUVORK5CYII=","orcid":"","institution":"Inner Mongolia Agricultural University, Hohhot Inner Mongolia","correspondingAuthor":true,"prefix":"","firstName":"Shuai","middleName":"","lastName":"Du","suffix":""}],"badges":[],"createdAt":"2024-07-24 10:10:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4794446/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4794446/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":63044650,"identity":"1e0db6ac-7541-452a-b690-00008e05c6af","added_by":"auto","created_at":"2024-08-22 12:15:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":84863,"visible":true,"origin":"","legend":"\u003cp\u003eFermentation quality and chemical composition in wheat straw silage (LA, lactic acid; AA, acetic acid; DM, dry matter; CP, crude protein; ADF, acid detergent fiber; NDF, neutral detergent fiber; ADL, acid detergent lignin; CL, cellulose; HC, hemicellulose; HoC, holocellulose. Propionic acid and butyric acid were not detected in all wheat straw silages. CK, control treatment; XY, wheat straw inoculated with xylanasetreatment; LP, wheat straw inoculated with \u003cem\u003eLactiplantibacillus plantarum\u003c/em\u003e treatment; LPXY, wheat straw inoculated with \u003cem\u003eLactiplantibacillus plantarum\u003c/em\u003e and xylanase treatment.).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4794446/v1/b078f8085c270fdd3fd6d542.png"},{"id":63044934,"identity":"df800f50-abb0-4728-8d53-e32a40a3f383","added_by":"auto","created_at":"2024-08-22 12:23:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":65481,"visible":true,"origin":"","legend":"\u003cp\u003eAlpha\u003cstrong\u003e \u003c/strong\u003ediversity (A, B) and the relative abundance of bacterial phyla (C) and genus (D) of the wheat straw silage indices of wheat straw with different treatments.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4794446/v1/1311955f8672a2820cd65fee.png"},{"id":63044655,"identity":"0d08b1b2-0755-4eae-bdf3-c0087d786ffd","added_by":"auto","created_at":"2024-08-22 12:15:18","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":37811,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of bacterial variations using the LDA analysis for wheat straw silages (A); B, Pearson’s analysis shows the relationship between bacterial Shannon and differential metabolism (log10).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4794446/v1/066b1955bba408f3437f56d8.png"},{"id":63044654,"identity":"e85dfae6-789f-404f-8bbb-14765bd0e15b","added_by":"auto","created_at":"2024-08-22 12:15:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":224417,"visible":true,"origin":"","legend":"\u003cp\u003eBar plot with significantly differential metabolites among the wheat straw silage. A, B positive mode ionization; C, D negative mode ionization.A, C: LP vs XY; B, D: LP vs LPXY (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Marked red indicate enriched in LP treatment.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4794446/v1/1af6c69705a0527ee5ad45bf.png"},{"id":63044651,"identity":"bca98280-1626-46c1-98ed-dc9179559dd9","added_by":"auto","created_at":"2024-08-22 12:15:18","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":134306,"visible":true,"origin":"","legend":"\u003cp\u003ePearson’s analysis shows the relationship between differential metabolism (log10) and fermentation quality.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4794446/v1/7107d44e45c15b71e73cbe21.png"},{"id":63044653,"identity":"936c7049-48a0-4e56-9522-361143fda3a0","added_by":"auto","created_at":"2024-08-22 12:15:18","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":123864,"visible":true,"origin":"","legend":"\u003cp\u003eStructural equation models (SEMs) show the direct and indirect effects of \u003cem\u003eLactobacillus\u003c/em\u003e on wheat straw silage fermentation quality. Solid and dashed arrows, respectively, represent significant (\u003cem\u003ep\u003c/em\u003e ≤ 0.05) and non-significant (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05) paths. Blue and red arrows, respectively, represent positive and negative effects. Numbers adjacent to arrows represent the standardized path coefficients. R\u003csup\u003e2\u003c/sup\u003e indicates the proportion of variance explained. There was non-significant deviation of the data from the models (\u003cem\u003ep \u003c/em\u003e= 0.11; df = 12; χ\u003csup\u003e2 \u003c/sup\u003e= 18.15; gfi = 0.98; srmr = 0.05; cfi = 0.95).\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4794446/v1/f2f40f8d5f54a9335542cef4.png"},{"id":63044960,"identity":"3d70946b-0b45-40d3-8074-9a88fcde011f","added_by":"auto","created_at":"2024-08-22 12:23:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1150702,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4794446/v1/31f8d26a-2798-46db-9d98-18e1912cad01.pdf"},{"id":63044652,"identity":"b6e46773-7c21-4a91-9700-827730ae8e33","added_by":"auto","created_at":"2024-08-22 12:15:18","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":296581,"visible":true,"origin":"","legend":"","description":"","filename":"supplement1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4794446/v1/37663845d3954ddf7e941dd4.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Novel mechanistic understanding that Lactiplantibacillus plantarum is more capable of improving the ensiling performance of wheat straw silage than xylanase by driving certain key metabolites","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eWheat (\u003cem\u003eTriticum aestivum L.\u003c/em\u003e) straw is a common agricultural residue utilized as ruminant feed owing to its high carbohydrate content [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Ensiling, as a method for large-scale preservation of wet materials, reduces dry matter loss in feed and has increasingly become a long-term utilization strategy for wheat straw [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Compared with other storage, ensiling not only improves biodegradability but also saves costs [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Nevertheless, wheat straw typically possesses low water-soluble carbohydrates (WSC) and lacks epiphytic lactic acid bacteria, making it challenging to produce high-quality silage through natural anaerobic fermentation [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Silage microbial additives are commonly employed in feed production to effectively enhance fermentation quality [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Lactic acid bacteria inoculants have the capability to rapidly accumulate lactic acid and lower pH during the early stages of silage, thereby enhancing fermentation quality [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Xylanase (XY) can improve the fermentation quality and rumen digestion rate of silage feed [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, there is little research on whether the mixed additions of lactic acid bacteria and XY have a synergistic effect, as well as the comparative study of the two types of additives on the improvement of wheat straw silage quality.\u003c/p\u003e \u003cp\u003eXylan is among the hemicelluloses that are not fully utilized in the rumen, leading to the inefficient utilization of feed energy [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. XY can disrupt its internal structure, release soluble sugars, increase the concentration of fermentation substrates, and improve feed utilization efficiency[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Homofermentative bacteria (e.g. \u003cem\u003eLactiplantibacillus plantarum\u003c/em\u003e) are widely used as they are safe and easy to use [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Homofermentative bacteria can reduce the loss of silage fermentation quality by directly increasing lactate and acidification rates [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Therefore, both two types of additives may enhance the fermentation quality of wheat straw silage.\u003c/p\u003e \u003cp\u003eSilage is a fermentation process dominated and driven by microorganisms, so changes in microbial communities are usually related to fermentation quality [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Understanding the microbial community\u0026rsquo;s contribution to silage feed not only provides insights into high-quality feed preparation techniques, but also helps maintain the quality of silage feed [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Lactic acid bacteria are considered beneficial bacteria in the production of organic acids such as lactic acid (LA) and are key to ensuring high-quality silage feed [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Throughout the silage fermentation process, the production of harmful bacteria like \u003cem\u003eListeria sp.\u003c/em\u003e and \u003cem\u003eClostridia\u003c/em\u003e can diminish feed quality [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The microbial community diversity of silage feed includes both beneficial and harmful bacteria [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Therefore, changes in lactate content in silage feed typically regulate microbial diversity. An increase in lactic acid bacteria content within the microbial community tends to reduce microbial diversity [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. While some research has investigated the effects of microbial additives on microbial community changes during ensiling fermentation, there remains a lack of mechanistic understanding, particularly concerning microbial community changes in oat ensiling with lactic acid bacteria and XY additives [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to microbial community succession, the fermentation process of silage also involves changes in metabolites and metabolic pathways [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The quality of feed fermentation is closely related to the relationship between silage microorganisms and metabolites, and fermentation quality is usually driven by microorganisms and metabolites [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Recently, metabolomics has been applied to the study of silage ecosystems [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and these results indicate a strong interaction between these metabolites and microorganisms. Since the fermentation process of silage is dominated by microorganisms, microorganisms also determine the changes in metabolic products, ultimately affecting the fermentation quality. However, there is a lack of comprehensive understanding regarding the microbial community's role in driving metabolic product changes in silage ecosystems, and the mechanism through which microbes drive such changes and enhance fermentation quality remains elusive.\u003c/p\u003e \u003cp\u003eTo data, there is limited literature on the fermentation quality and microbial community changes of wheat straw with the additions of XY and \u003cem\u003eLactiplantibacillus plantarum\u003c/em\u003e (LP), and the potential synergistic effect of combining these two additives remains unclear. And there has been no investigation into how the microbial community of silage influences metabolic products to enhance fermentation quality. The aim of the present study was to identify microbial additives that enhance the fermentation pathway and mechanism of wheat straw based on metabolomic and microbiome analyses, and to assess their potential synergistic effect.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Substrate and silage\u003c/h2\u003e \u003cp\u003eWheat straw originated from the Hulunber Grassland Ecosystem National Observation and Research Station of the Chinese Academy of Agricultural Sciences in Hulunber, Inner Mongolia, China. The wheat straw was harvested at the late maturity stage, then chopped and immediately taken to the laboratory for silage making when the wheat straw samples were picked. Inoculants, XY (total Xylanase activity of 50,000 U/g) purchased from Hefei Bomei Biotechnology Co., Ltd, Hefei, China; \u003cem\u003eLactiplantibacillus plantarum\u003c/em\u003e purchased from Jiangsu Lvke Biotechnology Company, Gaoyou, China. The treatments were as follows: control (CK), XY, LP and LPXY (mixed LP and XY). The inoculants were distinctively diluted in distilled water and added according to the manufacturer\u0026rsquo;s guidelines, 5 mg/kg of inoculant power was added on a fresh matter (FM) basis, after which the number of LP was equivalent to 1.0 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e colony-forming unit per gram (cfu/g), the CK treatment was also treated with the same volume of distilled water. Both fresh materials wheat straw and wheat straw silage were stored at a small-scale fermentation system (260 cm \u0026times; 380 cm; Hiryu KN type; Asahi kasei, Tokyo, Japan). A 200 gram of the samples were packed into the polyethylene plastic bag, and removing air with a vacuum sealer (N-14886, Deli Group Co., Ltd., Zhejiang, China). A total of 24 bags (4 treatments \u0026times; 6 replicates) of wheat straw were stored at room temperature (23\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C). After 60 days of fermentation process, these bags were opened and the ensiling performance, bacterial community and metabolites profiles were analyzed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Ensiling performance and nutritive values analyses\u003c/h2\u003e \u003cp\u003eClean containers were used to collect FM and wheat straw silage after being uniformly blended for ensiling performance and nutritive values analyses. The dry matter (DM) content of the FM and silage samples were measured after drying the sample for 72 h at 65\u0026deg;C with an oven. The dried samples were ground and through a 1 mm screen for the nutritive values analysis. The crude protein (CP) and acid detergent lignin (ADL) contents were analyzed according to the method of the Association of Official Analytical Chemists (AOAC, 2005). The neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents were determined by a ANKOM A200i Fiber Analyzer (ANKOM Technology, Macedon, NY, USA) with the report [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The fraction of cell wall constituents, including cellulose, hemicellulose and holocellulose was calculated using methods briefed by [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The anthrone method was selected to evaluate the WSC content [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. A 20 gram of the wheat straw silage samples were mixed with 180 mL sterile water and stored for 24 h at 4\u0026deg;C fridge for the extractions, then the extracts were filtered through four layers of cheesecloth. A glass-electrode pH meter was used to measure the pH value of the filtrate. The organic acids concentrations in the filtrate, mainly lactic acid, acetic acid, propionic acid and butyric acid, were measured by the high-performance liquid chromatography methods [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The plate count method was used to analysis the microbial population of the wheat straw silage according to the previously published methods [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Cellulose (CL), hemicellulose (HC) and holocellulose (Hoc) contents were determined as described [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Microbial analysis\u003c/h2\u003e \u003cp\u003eThe genomic DNA of bacterial community was extracted from the FM and wheat straw silage samples by the CTAB method. The Nano Drop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) was used to determine the concentrations and qualities of the extracted genomic DNA. The V3\u0026ndash;V4 regions of 16S rDNA gene was targeted with the universal primer pair 341F and 806R. The Illumina NovaSeq 6000 platform (IlluminaInc., San Diego, CA, USA) was used to sequence. The Raw pair-end reads were analyzed by the Qiime2 platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://qiime2.org/\u003c/span\u003e\u003cspan address=\"https://qiime2.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Amplicon sequence variants (ASVs) were obtained by eliminating low-quality data using DADA2 [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Subsequently, the ASVs were taxonomically annotated against the SILVA database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www\u003c/span\u003e\u003cspan address=\"https://www\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. arb-silva.de/, Release 138) using mothur [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Metabolites profiles analyses\u003c/h2\u003e \u003cp\u003eThe metabolites in the wheat straw silage samples were extracted according to the previous methods [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The raw data files of the 24 wheat straw silage samples generated by the liquid chromatography-mass spectrometry (LC\u0026ndash;MS) platform (Thermo Fisher, Ultimate 3000LC, Q Exactive) using the compound Discover 3.1 (CD 3.1 Thermo Fisher) to perform peak picking, peak alignment and quantitation for each metabolite. After that, peak intensities were normalized to the total spectral intensity [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The normalized data was used to predict the molecular formula based on additive ions, molecular ion peaks and fragment ions [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Then peaks were matched with the mzCloud (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mzcloud.org/\u003c/span\u003e\u003cspan address=\"https://www.mzcloud.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) mz Vault and Mass List database to obtain the accurate qualitative and relative quantitative results. After mean centering and unit variance scaling, the principle component analysis (PCA) and (orthogonal) partial least squares discriminant analysis (O)PLS-DA were selected to show the differences of the metabolites among the treatments by R package (prcomp). The variable importance in the projection (VIP) ranks and VIP\u0026thinsp;\u0026gt;\u0026thinsp;1.7 were considered as the relevant for treatment discrimination, and the results were displayed by the (O)PLS-DA plots. The plots package in R was used for significant metabolites for expression pattern clustering using. Hierarchical clustering method were used for distance calculation algorithms. The metabolites set enrichment was analyzed with the Stats package in R and the SciPy package in Python using the MetaboAnalyst 6.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.metaboanalyst.ca\u003c/span\u003e\u003cspan address=\"https://www.metaboanalyst.ca\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e \u003cp\u003eThe chemical compositions and bacterial alpha diversity (Shannon, Richness) data of wheat straw and wheat silage were analyzed by a one-way ANOVA and Kruskal Wallis test (HC and HoC do not follow a normal distribution). Tukey\u0026rsquo;s test and Fisher\u0026rsquo;s test were utilized to assess significant differences in comparisons at the 5% level. The linear discriminant analysis (LDA) effect size (LEfSe) with relative abundance data was utilized to assess the significance. To compare functional profiles among groups, metabolites from different treatments were analyzed using Duncan-test. We correct for the false discovery rate by controlling FDR (False Discovery Rate) to not exceed 5%. Five differential metabolites were ultimately identified (enriched in LP), including positive and negative. To determine the relationship between differential metabolites and fermentation quality, Pearson\u0026rsquo;s correlation analysis was conducted, using log10-tranformed to differential metabolites. Structural equation modeling (SEMs) was employed to evaluate key drivers of fermentation quality (CP, LA, AA, ADL, ADF, and NDF), including bacterial community and differential metabolites. One useful characteristic of SEMs for our purposes here is its utility for partitioning direct and indirect effects that one variable may have on another, and estimate the strengths of these multiple effects. Unlike regression or ANOVA, SEMs offers the ability to separate multiple pathways of influence and view them as parts of a system, and thus is useful for investigating the relationship complex networks found in silage fermentation ecosystems [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. We calculated the standardized of all index in SEMs. All the data were analysed using open-source tools for R software (version 4.3.2).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Result and discussion","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Chemical characteristics and microbial population of raw materials\u003c/h2\u003e \u003cp\u003eThe DM of the fresh wheat straw was 50.30%, ADF, NDF, CP contents were 29.50, 37.10 and 12.90%DM, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The counts of LAB, yeasts, aerobic bacteria, and coliform bacteria were 4.27, 8.47, 8.35, 8.40 and 8.32 log10 cfu/g of FM, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChemical and microbial characteristics of substrates before ensiling\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItems\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWheat straw\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry matter (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater-soluble carbohydrates (% DM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrude protein (% DM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcid detergent fiber (% DM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutral detergent fiber (% DM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactic acid bacteria (log\u003csub\u003e10\u003c/sub\u003e cfu/g FM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYeast (log\u003csub\u003e10\u003c/sub\u003e cfu/g FM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAerobic bacteria (log\u003csub\u003e10\u003c/sub\u003e cfu/g FM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColiform bacteria (log\u003csub\u003e10\u003c/sub\u003e cfu/g FM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMold (log\u003csub\u003e10\u003c/sub\u003e cfu/g FM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDM, dry matter; cfu, colony-forming units.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Fermentation quality of different treatment\u003c/h2\u003e \u003cp\u003eThe fermentation characteristics of the wheat straw silage with different treatments are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. All the additions remarkably (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) decreased the pH value. Compared to the CK and XY treatments, the LP and LPXY treatments enhanced LA and AA (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). XY-treated silage and LAB-treated silage treatment significantly reduced ADF, NDF and ADL (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). While there was no distinction between additives and CK on the CP content in wheat straw silage.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Bacterial community of wheat straw silage\u003c/h2\u003e \u003cp\u003eThe bacterial community in the different treated silages were clearly distinguished at 60 days of wheat straw (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Alpha diversity of wheat straw silage bacteria is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB. LP-treated silage significantly reduced bacterial Shannon diversity (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while XY-treated silage and LPXY-treated silage did not exhibit a decrease in bacterial Shannon diversity compared to CK. Furthermore, all three additives had no impact on bacterial Richness.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Metabolomic profiles\u003c/h2\u003e \u003cp\u003eMetabolomes in the different treated silages were clearly separated at 60 days of wheat straw (Fig. S2). Overall, 2,557 metabolites were identified in the wheat straw silage samples. Based on Duncan-tests and variable importance in projection (VIP) filtering of the relative contents of wheat straw silage samples, 57 metabolites exhibited significant differences between the two groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and VIP\u0026thinsp;\u0026gt;\u0026thinsp;1.7). Among these, 30 were positively ionized metabolites (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), and 27 were negatively ionized metabolites (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD), including carboxylic acids and derivatives, amino acids, peptides, analogues, and other metabolites. Specifically, three metabolites were enriched in positive ionization mode, and two metabolites were enriched in negative ionization mode in LP-treated silage. Additionally, combined with LDA analysis, the results confirmed the enrichment of five metabolites in LP-treated silage (Fig. S3 and S4).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Lactobacillus driven fermentation quality of wheat straw\u003c/h2\u003e \u003cp\u003eResults from the SEMs showed that 88% (CP), 24% (LA), 25% (AA), 59% (ADL), 28% (ADF) and 80% (NDF) of the variance in fermentation quality could be explained by \u003cem\u003eLactobacillus\u003c/em\u003e of wheat straw silage respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). \u003cem\u003eLactobacillus\u003c/em\u003e had a negative and large effect on bacterial Shannon (63%), indicating a reduction in bacterial diversity in silage \u003cem\u003eLactobacillus\u003c/em\u003e had a direct positive effect on differential metabolites, while bacterial diversity had a negative effect on differential metabolites. In summary, \u003cem\u003eLactobacillus\u003c/em\u003e promotes the production of differential metabolites. In addition, our SEMs demonstrate that LA and AA are influenced by differential metabolites. LP-treated silage decreased bacterial diversity and enriched some metabolites, thereby affecting LA and AA production.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThe WSC and LA of wheat straw before ensiling was much higher than the detected by other research [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], may due to the factors like climate and season of harvest, which have influence on the feeding value of the forage. LP treatment has shown a stronger promote effect than other treatments in LA and AA. After anaerobic fermentation process, the organic acid (especially the LA and AA concentrations) is the largest contributor for pH value, previous studies have also provided the same result [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. These results found that the LA and AA contents in LP-treated and LPXY-treated silage were higher than in other treatments, confirming the significant influence of LA and AA on the pH value of silage [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Besides, the higher AA concentration in LP-treated silage may reflect a higher count of LA-produced bacteria in the process. Interestingly, the pH value of LPXY-treated silage was higher than that of XY-treated and LP-treated silage, possibly due to higher levels of bioactive components in XY-treated and LP-treated silage, such as phenolic acids [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. However, the NH3-N during the fermentation process may also neutralize acids and prevent pH reduction [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Therefore, LPXY-treated silage may also exhibit higher NH3-N content to neutralize LA and AA [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. LP treatment has the highest content of LA and AA, for wheat straw silage, directly increasing lactic acid bacteria has a stronger promoting effect on the enhancement of volatile fatty acids. LP and XY treatment have more impact on silage fiber. Ruminant animals prefer high protein and low fiber feed because these feeds can have higher nutrition and energy [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. According to our results, LP additives exhibited the most significant degradation effect on fibers in wheat straw feed, which may be more favored by ruminants, despite not increasing protein content. In addition, based on the comprehensive analysis of ADL, CL, HC, and HoC, the LP additive exhibits the strongest effect on fiber decomposition in wheat silage feed, surpassing that of LPXY-treated silage. Lactic acid bacteria inoculum contains cellulase, reducing fiber content [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The increase of lactic acid bacteria directly enhances the utilization of compounds to improve the efficiency of lactic acid production in feed, thereby enhancing fermentation quality [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Contrary to expectations, there was no synergistic effect between XY additive and LP additive. Wheat straw contains a significant amount of lignin [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] Lignin is a complex polymer composed of phenolic monomers, which can prevent glycoside hydrolases from coming into contact with their substrates [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Lignin is a difficult substance to decompose, and fungi with strong decomposition ability usually have good effects on lignin decomposition, such as saprophytic fungi (e.g. white-rot fungi) [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The XY additive primarily decomposes hemicellulose and effectively utilizes free xylan, thus its impact on lignin decomposition may be minimal [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur analysis of dominant bacterial relative abundance revealed that Lactobacillus is the predominant genus in LP-treated silage. The abundance of Lactobacillus exceeds half of all bacterial communities\u0026rsquo; genus. According to the principle of \u0026lsquo;competitive exclusion\u0026rsquo;, the dominant microbial community is abundant, while the non-dominant microbial community is reduced, resulting in a corresponding decrease in microbial diversity [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Thus, inoculation with LP increased the number of dominant bacterial genera (Lactobacillus) and reduced bacterial diversity. Similarly, previous results also revealed the same results [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Although the XY and LPXY treatments increased the abundance of Lactobacillus compared to CK, the differences were not significant. Firmicutes was the dominant phylum in LP-treated silage, whereas Proteobacteria were dominant in the other treatments [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Many spoilage and harmful microorganisms belong to Proteobacteria (e.g. Escherichia coli). The high pH value of silage feed is conducive to the growth of other spoilage or pathogenic microorganisms [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. LPXY-treated silage and CK exhibited higher pH levels than LP-treated silage, providing conditions conducive to the growth of harmful microorganisms, which may explain why Proteobacteria are the predominant phylum. Meanwhile, fermentation of silage is mainly carried out by lactic acid bacteria [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur experiment also provides evidence from the perspective of silage microorganisms, that LP additives can directly increase the number of Lactobacillus and improve fermentation quality of wheat straw silage. The abundance of Lactobacillus in the silage with mixed LP and XY addition is not sufficient, thus the synergistic effect of bacteria and enzymes is not significant. Additionally, Lactobacillus was found to be relatively abundant in LP-treated silages during ensiling, as indicated by LEfSe analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), further highlighting the difference of LAB treatment compared to other treatments due to the enrichment of Lactobacillus (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eThe enriched metabolites in LP-treated silage include Furoic acid and derivatives and Pyridines and derivatives. Varied microbial communities and metabolites influence fermentation quality [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The microbial community of inoculated microbes in silage feed, such as LP, produces more complex metabolites [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Our results indicate that LP treatment resulted in better fermentation quality compared to other treatments. Therefore, the bacterial community in LP-treated silage may generate distinct metabolites. Five metabolites enriched in LP-treated silage exhibited significant differences compared to other treatments. Metabolomic data suggest differences in microbial activity among silage feed treated with different additives [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo our knowledge, this is the first application of SEMs in silage research to elucidate the pathways and mechanisms underlying changes in fermentation quality of silage feed by integrating metabolomics and microbiome data. More importantly, we have provided compelling evidence supporting the use of microbial additives to enhance the quality of silage feed, as Lactobacillus altered bacterial diversity and enriched certain metabolites. Abundant organic acids can usually improve the palatability of feed, high LA indicates good fermentation quality, and high AA contributes to the aerobic stability of feed [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Previous studies combined with metabolomics, have shown that LP-treated produces more organic acids, but specific mechanisms and pathways have not been proposed [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Our Pearson\u0026rsquo;s correlation analysis also revealed a positive linear relationship between LA, AA, and differential metabolites, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA and B). With comprehensive Pearson\u0026rsquo;s analysis and SEMs, our results are more reliable, providing a compelling explanation of the role of differential metabolites in LA and AA production.\u003c/p\u003e \u003cp\u003eHowever, the results of the present study also confirm that carbohydrates in feed are not influenced by differential metabolites (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). This may be attributed to the production of certain enzymes by Lactobacillus during the silage fermentation process, such as cellulase and feruloyl esterase, which degrade structural carbohydrates [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Therefore, Lactobacillus directly explained ADF, NDF and ADL (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). It is important to acknowledge objectively that differential metabolites cannot fully account for the changes in AA and LA. Out of the 2557 metabolites detected, only 5 differential products accounted for a very small proportion, less than 0.2%, yet they explained over 20% of LA and AA. This demonstrates the significance of these 5 differential metabolites. Ultimately, silage can be viewed as a complex ecosystem, where multiple biotic and abiotic factors interact to shape its composition [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eOur study findings suggest that \u003cem\u003eLactiplantibacillus plantarum\u003c/em\u003e additives enhanced the abundance of Lactobacillus, reduced bacterial diversity, and enriched certain metabolites. These enriched metabolites effectively enhanced LA and AA, thereby improving the fermentation quality of wheat straw silage. Overall, our study not only confirms the positive effect of \u003cem\u003eLactiplantibacillus plantarum\u003c/em\u003e additives on wheat straw silage but also provides a mechanistic explanation for the improved quality of silage feed due to these additives.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis work was supported by\u0026nbsp;Inner Mongolia Autonomous Region Science and Technology Innovation Guidance Award Fund Project, Research and Demonstration of Fermentation Technology for Crop Straw Silage Feed in Hulunbuir Region (2022CXYD006), Research and application of rapeseed straw fermentation and feeding utilization technology in the eastern region of Inner Mongolia (NC2023022).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eThe authors have no conflict of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYH: Methodology, Investigation, Writing-original draft. XY: Conceptualization, Formal analysis. HR: Formal analysis, Methodology, Validation. JY: Conceptualization, Data curation, Writing review \u0026amp; editing. DS: Supervision, Project administration, Funding acquisition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBattaglia M, Thomason W, Fike JH, Evanylo GK, von Cossel M, Babur E, et al. The broad impacts of corn stover and wheat straw removal for biofuel production on crop productivity, soil health and greenhouse gas emissions: A review. GCB Bioenergy. 2021;13:45\u0026ndash;57. \u003c/li\u003e\n\u003cli\u003eTeixeira Franco R, Buffi\u0026egrave;re P, Bayard R. Ensiling for biogas production: Critical parameters. A review. 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An innovative strategy to enhance the ensiling quality and methane production of excessively wilted wheat straw: Using acetic acid or hetero-fermentative lactic acid bacterial community as additives. Waste Management. 2022;149:11\u0026ndash;20. \u003c/li\u003e\n\u003cli\u003eLi X, Chen F, Wang X, Xiong Y, Liu Z, Lin Y, et al. Innovative utilization of herbal residues: Exploring the diversity of mechanisms beneficial to regulate anaerobic fermentation of alfalfa. Bioresource Technology. 2022;360:127429. \u003c/li\u003e\n\u003cli\u003eLi, Zhao W, Yan L, Chen L, Chen Y, Gou W, et al. Inclusion of abandoned rhubarb stalk enhanced anaerobic fermentation of alfalfa on the Qinghai Tibetan Plateau. Bioresource Technology. 2022;347:126347. \u003c/li\u003e\n\u003cli\u003eBai J, Ding Z, Ke W, Xu D, Wang M, Huang W, et al. 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The metabolome and bacterial composition of high-moisture Italian ryegrass silage inoculated with lactic acid bacteria during ensiling. Biotechnology for Biofuels and Bioproducts. 2023;16:91. \u003c/li\u003e\n\u003cli\u003eWhiting GC. Organic Acid Metabolism of Yeasts During Fermentation of Alcoholic Beverages\u0026mdash;a Review. Journal of the Institute of Brewing. 1976;82:84\u0026ndash;92. \u003c/li\u003e\n\u003cli\u003eBroberg A, Jacobsson K, Str\u0026ouml;m K, Schn\u0026uuml;rer J. Metabolite profiles of lactic acid bacteria in grass silage. Appl Environ Microbiol. 2007;73:5547\u0026ndash;52. \u003c/li\u003e\n\u003cli\u003eNing T, Wang H, Zheng M, Niu D, Zuo S, Xu C. Effects of microbial enzymes on starch and hemicellulose degradation in total mixed ration silages. Asian-Australasian Journal of Animal Sciences. 2017;30:171. \u003c/li\u003e\n\u003cli\u003eShah AA, Liu Z, Qian C, Wu J, Zhong X, Kalsoom U-E-. 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ISME J. 2021;15:2012\u0026ndash;27.\u003c/li\u003e\n\u003c/ol\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":"chemical-and-biological-technologies-in-agriculture","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Chemical and Biological Technologies in Agriculture](https://chembioagro.springeropen.com/)","snPcode":"40538","submissionUrl":"https://submission.nature.com/new-submission/40538/3","title":"Chemical and Biological Technologies in Agriculture","twitterHandle":"@SpringerPlants","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Wheat straw, Ensiling, Microbiome, Metabolome, Fermentation quality","lastPublishedDoi":"10.21203/rs.3.rs-4794446/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4794446/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMicrobial and enzyme additives can improve silage performance, but there is limited comparative research on the effects of microbial and enzyme additives on improving silage fermentation quality, and the underlying microbial and metabolic mechanisms remain unclear. This study investigate the effects without inoculants (CK treatment) or with \u003cem\u003eLactiplantibacillus plantarum \u003c/em\u003e(LP treatment)\u003cem\u003e, \u003c/em\u003exylanase (XY treatment) and their combination (LPXY treatment) on the fermentation quality, as well as on the microbial communities and metabolite profiles of the wheat straw silage. The results demonstrated that the LP treatment has a better effect on improving the fermentation quality of wheat straw silage compared to other treatments, as evidenced by markedly (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05) decreased the pH, acid detergent and neutral fiber (ANF, NDF), and increased the lactic acid (LA) and acetic acid (AA) concentrations. After the fermentation process, the LP treatment significantly (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) enhanced the abundance of \u003cem\u003eLactobacillus\u003c/em\u003e, reduced bacterial Shannon (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) and increased some key metabolites content. The structural equation models (SEMs) and Pearson’s correlation results proved that the LP treatment drives the wheat straw silage fermentation quality via increasing the abundance of \u003cem\u003eLactobacillus\u003c/em\u003e, decreasing the diversity of bacterial community and enriching the content of certain key metabolites. The present study provides mechanistic evidence that \u003cem\u003eLactiplantibacillus plantarum\u003c/em\u003e additive is superior to xylanase additive and their combination on improving fermentation quality of wheat straw silage, that is, by enriching certain key metabolites to increase AA and LA concentrations, providing a reference for the cross study of silage feed fermentation microbiome and metabolome.\u003c/p\u003e","manuscriptTitle":"Novel mechanistic understanding that Lactiplantibacillus plantarum is more capable of improving the ensiling performance of wheat straw silage than xylanase by driving certain key metabolites","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-22 12:15:12","doi":"10.21203/rs.3.rs-4794446/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-15T17:38:50+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-15T14:35:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-14T14:23:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-11T07:50:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-09T22:48:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-04T11:52:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"188464831488154779952425309253163355082","date":"2024-08-02T18:04:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269227485154122564910387602651421121832","date":"2024-08-02T14:43:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"116691950724265780066359410822890105767","date":"2024-08-01T13:07:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"255456654077495132219301292039124555784","date":"2024-08-01T09:11:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"265572048051771499652916034366068231118","date":"2024-08-01T06:44:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"275129228459616523553972991365877083699","date":"2024-07-31T09:52:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-28T03:01:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-27T05:14:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-27T05:13:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"Chemical and Biological Technologies in Agriculture","date":"2024-07-24T10:08:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"chemical-and-biological-technologies-in-agriculture","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Chemical and Biological Technologies in Agriculture](https://chembioagro.springeropen.com/)","snPcode":"40538","submissionUrl":"https://submission.nature.com/new-submission/40538/3","title":"Chemical and Biological Technologies in Agriculture","twitterHandle":"@SpringerPlants","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fdd83a36-0edc-485f-bd87-1d3ff2cdc252","owner":[],"postedDate":"August 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-09-29T15:23:33+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-22 12:15:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4794446","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4794446","identity":"rs-4794446","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}