Cellulase with Bacillus velezensis improves physicochemical characteristics, microbiota, and metabolites of two-stage solid-state fermented corn germ meal

doi:10.21203/rs.3.rs-3216722/v1

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Research Article

Cellulase with Bacillus velezensis improves physicochemical characteristics, microbiota, and metabolites of two-stage solid-state fermented corn germ meal

https://doi.org/10.21203/rs.3.rs-3216722/v1

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published 03 Jan, 2024

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Corn germ meal (CGM) is one of the major byproducts of corn starch extraction. Although CGM has rich fiber content, it lacks good protein content and amino acid balance, and therefore cannot be fully utilized as animal feed. In this study, we investigated the processing effect of cellulase synergized with Bacillus velezensis on the nutritional value of pretreated CGM (PCGM) in two-stage solid-state fermentation (SSF). High-throughput sequencing technology was used to explore the dynamic changes in microbial diversity. The results showed that compared with three combinations of B. velezensis + Lactobacillus plantarum (PCGM-BL), cellulase + L. plantarum (PCGM-CL), and control group (PCGM-CK), the fourth combination of cellulase + B. velezensis + L. plantarum (PCGM-BCL) significantly improved the nutritional characteristics of PCGM. After two-stage SSF (48 h), viable bacterial count and contents of crude protein (CP) and trichloroacetic acid-soluble protein (TCA-SP) all were increased in PCGM-BCL (p < 0.05), while the pH was reduced to 4.38 ± 0.02. In addition, compared with PCGM-BL, the cellulose degradation rate increased from 5.02 to 50.74%, increasing the amounts of short-chain fatty acids (216.61 ± 2.74 to 1727.55 ± 23.00 µg/g) and total amino acids (18.60 to 21.02%) in PCGM-BCL. Furthermore, high-throughput sequencing analysis revealed significant dynamic changes in microbial diversity. In the first stage of PCGM-BCL fermentation, Bacillus was the dominant genus (99.87%), which after 24 h of anaerobic fermentation changed to lactobacillus (37.45%). Kyoto Encylopaedia of Genes and Genomes (KEGG) metabolic pathway analysis revealed that the pathways related to the metabolism of carbohydrates, amino acids, cofactors, and vitamins accounted for more than 10% of the enriched pathways throughout the fermentation period. Concisely, we show that cellulase can effectively improve the nutritional value of PCGM when synergized with B. velezensis in two-stage SSF.

Nutritional value

Two-stage solid-state fermentation

Microbial diversity

Fermented feed

Cellulase+B.velezensis improve pretreated CGM nutrition in two-stage SSF;
This strategy overcomes the cellulases deficiency in B. velezensis;
Microbial diversity analysis could explain potential and symbiotic strains for SSF.

Soybean meal (SBM) is an important protein source in animal diets. However, the growing demand and sharp fluctuation in the price of SBM have severely constrained the sustainable development of the animal husbandry industry (Li et al. 2018). Therefore, there is a huge demand to develop alternative protein feed products. Corn germ meal (CGM) is considered an unconventional protein feed resource in the Jilin Province of China. CGM, having a crude protein (CP) content of 22.6%, is a deep-processing by-product of corn. Additionally, its fiber content is comparable to that of corn distiller's dried grains with solubles (Zhang et al. 2018). The primary fiber components in CGM are cellulose and arabinoxylan, while the neutral detergent fiber content of CGM is about 50.44% (Jaworski et al. 2015). Currently, animal nutritionists mainly optimize the ratio of CGM in animal feed or add enzyme preparations to replace a part of SBM (Shi et al. 2019). However, more than 30% CGM in the diet will reduce the growth performance of finishing pigs (Lee et al. 2012). On similar lines, it was shown that any increase in CGM proportion in the diet correspondingly decreases the apparent total gut digestibility of CP, indicating that added dietary fiber content can unfavorably impact protein digestibility in animals. Besides, having the high fiber content, standard and apparent ileal digestibility of CP and most amino acids in CGM is lower than corn (Huang et al. 2015). Essentially, the nutritional inadequacies of CGM consist of a high fiber content, low crude CP, and an imbalanced amino acid profile. The high fiber content is the main factor limiting CGM application in pig, poultry, ruminant, and fish feed (Zhang et al. 2013). The fundamental problem of high fiber content in CGM remains a challenge and has not been solved yet.

In recent years, microbial fermented feeds have become an effective way to improve the utilization and feeding efficiency of plant-based protein feeds (Olukomaiya et al. 2019). However, there are not many reports on the microbial fermentation of CGM. In our earlier investigation (Chen et al. 2022), we discovered that pretreating CGM with sodium bicarbonate can successfully neutralize its pH during corn deep processing, improving the fermentation efficiency of pretreated CGM (PCGM). In addition, B. velezensis fermentation significantly improved the overall nutritional level of CGM. Furthermore, the study of differential metabolites and differentially expressed genes during the B. velezensis fermentation showed that CAZymes enzyme genes mainly involved the degradation of cellulose, starch, pectin, and hemicellulose were significantly upregulated (Chen et al. 2023). However, from the results of comparative genomics, enzyme activity assays, and cellulose degradation rate of fermented CGM, we found that B. velezensis lacks cellulase and cannot directly hydrolyze cellulose in CGM. Also, the used CGM substrate needed sterilization and therefore could only be produced on a small scale due to high energy consumption, limiting the large-scale application of the method.

Therefore, here, we investigated the processing effect of cellulase synergized with B. velezensis on the nutritional value of PCGM during two-stage solid-state fermentation (SSF) by examing the change in physicochemical properties (viable bacterial count, contents of crude protein (CP), trichloroacetic acid-soluble protein (TCA-SP), short-chain fatty acids (SCFAs) and total amino acids and cellulose degradation rate) and microbial diversity of PCGM. This study provides theoretical and foundational data for the development and application of CGM-based bio-protein feed as an alternative to SBM.

Microorganisms and enzymes

Bacillus velezensis CL-4 (CTCC NO: M2020811) and Lactobacillus plantarum C37 (CCTCCM NO: 20211494) were obtained from cecal contents of broilers and soil of Changbai Mountain primeval forest. B. velezensis CL-4 and L. plantarum C37 were maintained on Luria broth (LB) and de Man, Rogosa, and Sharp (MRS) plates at 4 ℃. Trichoderma cellulase (50000 U/g, C8271) was from Beijing Solarbio Science & Technology Co., Ltd. CGM was purchased from Gongzhuling Wellhope Animal Husbandry Co., Ltd. CGM maintained its original state, was crushed and screened through a 40-mesh sieve.

Effect of cellulase on two-stage fermentation of CGM

For CGM fermentation, B. velezensis CL-4 was cultured in liquid LB medium at 37°C for 20 h. L. plantarum C37 was cultured in liquid MRS at 37°C for 24 h. Subsequently, the vegetative cells were washed three times in a sterile 0.85% NaCl solution, followed by suspension in the same liquid at 10⁷ CFU/mL. Pretreatment stage: According to our previous research (Chen et al. 2022), CGM was pretreated with sodium bicarbonate (baking soda) to neutralize the pH before fermentation. In brief, 150 g CGM was treated with 60 mg/mL of sodium bicarbonate solution to obtain PCGM. Then, to verify the effect of cellulase, the fermentation experiment was divided into four groups. In the first group (PCGM-BL), PCGM fermentation was performed with B. velezensis CL-4 (10⁷ CFU/g). Then, the PCGM final moisture content was adjusted to 50% using a sterile breathable membrane at 37°C for 24 h. Next, PCGM was inoculated with L. plantarum C37 (7.0 log CFU/g), the sterile membrane was replaced with a sealing membrane, and the fermented was performed at 37°C for another 24 h. In the second group (PCGM-CL), we replaced B. velezensis CL-4 with cellulase (250 U/g), and the rest of the steps were the same. In the third group (PCGM-BCL), we used cellulase (250 U/g) in combination with B. velezensis CL-4, and the other steps were the same. Also, there was a control group (PCGM-CK) without any treatment. All samples were tested in quintuplicate. The wet samples were collected at 0, 24, and 48 h to analyze pH, bacteria viable count, organic acid content, and microstructure. The fermentation process was heat terminated 30 min at 105°C. Subsequently, all samples were dried at 65°C for 24 h, cooled down, ground, and subjected to physicochemical and free amino acid analyses.

Chemical analyses

The samples collected at 0 and 48 h of fermentation were dried, ground, and then screened through a 1 mm sieve. The contents of dry matter (DM), CP, crude fat (EE), crude fiber (CF), acid detergent fiber (ADF), and neutral detergent fiber (NDF) were determined as described (AOAC International Guidelines, 2005). TCA-SP content was determined using the method of (Shi et al. 2017). Sample amino acid profiles were determined using an automated analyzer (LA8080; Hitachi, Tokyo, Japan).

Microorganisms and microbial metabolites

The pH and microbial cell counts were determined as described previously (Chen et al. 2021). The amount of SCFAs was analyzed by gas chromatography as described by (Franklin et al. 2002).

Mycotoxin content determination

The contents of aflatoxin B1 (µg/kg), zearalenone (mg/kg), and deoxynivalenol (mg/kg) were determined by Enzyme Linked Immunosorbent Assay (ELISA) using mycotoxin detection kits from Beijing Longkefang Bioengineering Technology Co., LTD.

Microscopy

The pre and post-fermentation alterations in the physical characteristics of the substrates were evaluated by scanning electron microscopy (SEM) following the guidelines of the Electronic Microscopy Center of Zibo Huayuan Testing Technology Co., Ltd. The microstructures of PCGM and fermented PCGM (at 24 and 48 h) were observed under a field-emission SEM (JSM-7900, JEOL, Japan) at 1000, 1500, 3000, and 5000 times magnifications.

Bacterial and fungal community analysis and metabolic function prediction

Total genomic DNA was extracted from the wet samples at 0, 24, and 48 h using the OMEGA Soil DNA kit (D5625-01; Omega Bio-Tek, Norcross, GA, USA). The amplification of the bacterial 16S V3V4(a) rRNA gene was performed with primers 338F (ACTCCTACGGGAGGCAGCA) and 806R (GGACTACHVGGG TWTCTAAT), while primers ITS1F (CTTGGTCATTTAGAGGAAGTAA) and ITS2R (GCTGCGTTCTTCATCGATGC) were used to amplify the ITS1(b) region of the fungal ITS gene. PCR was performed as follows: initial denaturation, 2 min at 98 ℃; 27 cycles of 15 s for denaturation at 98 ℃; 30 s annealing at 55 ℃, and 30 s extension at 72 ℃, and final extension at 72 ℃ for 5 min. PCR amplicons were purified with Vazyme VAHTSTM DNA Clean Beads (Vazyme, Nanjing, China) and quantified using the Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen, Carlsbad, CA, USA). The purified amplicons were pooled in equal amounts and subjected to pair-end 2X250 bp sequencing at the Illumina MiSeq platform with MiSeq Reagent Kit v3 at Shanghai Personal Biotechnology Co., Ltd (Shanghai, China).

The microbiome bioinformatics analysis was performed using QIIME2 2019.4 (Bolyen et al. 2019) according to the official tutorials with slight modifications (https://docs.qiime2.org/2019.4/tutorials/). Raw sequence data were demultiplexed using the demux plugin, followed by primers sequence removal with the cutadapt plugin (Kechin et al. 2017). The sequences were then quality filtered, denoised, merged, and cleared for chimera sequences using the DADA2 plugin (Callahan et al. 2016). Non-singleton amplicon sequence variants (ASVs) were aligned with mafft (Katoh et al. 2002). The sequence data analyses were mainly performed using QIIME2 and R packages (v3.2.0). The alpha diversity indices at the ASV level were calculated using the ASV table in QIIME2 and are visualized as box plots. β-diversity analysis was performed using Jaccard metrics and visualized via principal coordinate analysis (PCoA). The random forest analysis was conducted in QIIME2 with default settings (Rigatti 2017). Microbial functions were predicted using PICRUSt2 (Gavin M. Douglas, et al., preprint) based on KEGG (https://www.kegg.jp/) and MetaCyc (https://metacyc.org/) databases. All raw sequences (accession numbers SRP PRJNA936640 and PRJNA936641) have been deposited in the NCBI Sequence Read Archive.

Statistical and bioinformatics analyses

The assay data were analyzed using the SPSS 24.0 software (SAS Inc., Chicago, IL). One-way ANOVA and Duncan's test were employed to determine the difference between the mean values and those with P-values < 0.05 were considered significant. Bar plots were generated using GraphPad Prism 8.0 (San Diego, CA, USA).

Selection of the strain and enzyme combinations

The two-stage SSF fermentation process is illustrated in Fig. 1. The results of bacterial viable count and pH determination for PCGM and PCGM fermented with the different combinations are listed in Table 1. At 24 h, the count of B. velezensis CL-4 in PCGM-BCL began to rise from an initial count of 11.71 ± 0.15 to 12.24 ± 0.08 log CFU/g. After 48 h of fermentation, the final count of L. plantarum C37 in PCGM-BCL (13.56 ± 0.87 log CFU/g) was significantly higher than that in PCGM-BL (10.39 ± 0.22 log CFU/g) and PCGM-CL (12.29 ± 0.45 log CFU/g). Meanwhile, the pH gradually decreased from 6.55 ± 0.08 (24 h) to 4.38 ± 0.02 (48 h). Nonetheless, the population of B. velezensis CL-4 in PCGM-BCL declined from 12.24 ± 0.08 to 8.54 ± 0.22 log CFU/g at 48 h of fermentation. This indicated that oxygen was consumed in the aerobic fermentation stage, forming an anaerobic environment for the subsequent fermentation.

Table 1

Microorganisms and pH of pretreated corn germ meal (PCGM) and PCGM fermented with different microbes and cellulase.
Item	0h	24h			48h
Item	PCGM-CK	PCGM-BL	PCGM-CL	PCGM-BCL	PCGM-BL	PCGM-CL	PCGM-BCL
pH	6.89 ± 0.04	6.71 ± 0.04^a	6.47 ± 0.03^b	6.55 ± 0.08^b	5.94 ± 0.05^a	4.43 ± 0.02^b	4.38 ± 0.02^b
B. velezensis log CFU/g	-	11.71 ± 0.15	-	12.24 ± 0.08	8.34 ± 0.14	-	8.54 ± 0.22
L. plantarum log CFU/g	-	-	-	-	10.39 ± 0.22^c	12.29 ± 0.45^b	13.56 ± 0.87^a
PCGM-CK: the CGM was pretreated with sodium bicarbonate.
PCGM-BL-24h: the PCGM was incubated with B. velezensis CL-4 at 37°C for 24 h.
PCGM-CL-24h: cellulase was added into PCGM at 37 ℃ for 24h.
PCGM-BCL-24h: the PCGM was incubated with B. velezensis CL-4 and cellulase at 37°C for 24 h.
PCGM-BL-48h: the PCGM was incubated with B. velezensis CL-4 at 37°C and then added L. plantarum C37 for another 24h under anaerobic conditions at 37°C.
PCGM-CL-48h: cellulase was added into PCGM at 37 ℃ for 24h and then added L. plantarum C37 for another 24h under anaerobic conditions at 37°C.
PCGM-BCL-48h: the PCGM was incubated with B. velezensis CL-4 and cellulase at 37°C and then added L. plantarum C37 for another 24h under anaerobic conditions at 37°C.
Values are mean ± SD, n = 3. Means followed with different superscript letters (a, b, c) within each line are significantly different (p < 0.05).

The nutritional characteristics of PCGM and PCGM fermented with different combinations are listed in Table 2. After 48 h of fermentation, PCGM-BCL had 23.22 ± 0.10% CP and 15.57 ± 0.08% TCA-SP, which were significantly higher than in the other groups; meanwhile, DM and CF decreased in all fermentation groups. Additionally, the relative rate of hemicellulose degradation was reduced by 35.04% at the 48-h fermentation of PCGM-BCL. Moreover, compared with other fermentation combinations (PCGM-CK, PCGM-BL, and PCGM-CL), there was a significant improvement in cellulose degradation in the PCGM-BCL group, which was about 52.80% at 48 h of fermentation. Notably, the addition of B. velezensis CL-4 and L. plantarum C37 had a significant impact on the amino acid profiles of PCGM after 48 h of fermentation. Specifically, compared to PCGM-CK (18.60 ± 0.28%), PCGM-BL (20.20 ± 0.11%), and PCGM-CL (19.15 ± 0.04%) groups, the total amino acid content in PCGM-BCL was significantly increased to 21.02 ± 0.09% after 48 h of fermentation. The estimation results of SCFAs are listed in Table 3. In general, after 48 h of fermentation, the contents of various SCFAs in PCGM-BCL were higher (1660.89 ± 134.53 µg/g) than in PCGM-CK (216.61 ± 2.74 µg/g), PCGM-BL (1426.67 ± 145.00 µg/g), and PCGM-CL (823.87 ± 17.62 µg/g) groups. The mycotoxin contents in different fermentation groups are presented in Table 4. Aflatoxins (B₁, B₂, G_1, and G₂) were not detected in any sample during the whole fermentation process. Though deoxyniverenol and zearalenone were detected, they were below the feed safety limits. The physical structures of differently fermented PCGM are presented in Fig. 2. PCGM-CK exhibited a compact and smooth-faced structure, but after 48 h of fermentation, the structures of PCGM-BL, PCGM-CL, and PCGM-BCL became fragmented, cracked, and porous. In addition, more inoculated microorganisms were gathered on the surface of PCGM-BL, PCGM-CL, and PCGM-BCL than on PCGM-CK.

Table 2

Nutrient composition of pretreated corn germ meal (PCGM) and PCGM fermented with different microbes and cellulase.
Item (%)	0h	48h
Item (%)	PCGM-CK	PCGM-BL	PCGM-CL	PCGM-BCL
Dry matter	93.75 ± 0.11^a	88.72 ± 0.25^c	91.72 ± 0.25^b	87.72 ± 0.25^d
Crude protein	21.00 ± 0.12^d	22.86 ± 0.07^b	22.24 ± 0.07^c	23.22 ± 0.10^a
Crude fibre	8.70 ± 0.05^a	8.31 ± 0.10^b	7.80 ± 0.12^c	7.71 ± 0.08^c
TCA-SP	11.15 ± 0.18^d	14.84 ± 0.43^b	12.52 ± 0.21^c	15.57 ± 0.08^a
Ash	4.81 ± 0.03^b	8.01 ± 0.10^a	7.91 ± 0.03^a	8.00 ± 0.08^a
EE	4.37 ± 0.07^a	4.30 ± 0.01^a	4.40 ± 0.07^a	4.11 ± 0.05^b
Ca	0.05 ± 0.01	0.05 ± 0.01	0.05 ± 0.01	0.05 ± 0.01
Total P	1.00 ± 0.01^c	1.06 ± 0.01^a	1.05 ± 0.01^b	1.07 ± 0.05^a
Cellulose¹	12.14 ± 0.95^a	11.53 ± 0.37^a	8.40 ± 0.35^b	5.98 ± 0.55^c
Hemicellulose²	22.29 ± 2.33^a	15.18 ± 0.44^b	16.27 ± 0.07^b	14.48 ± 0.45^b
Cellulose degradation (%)³	-	5.02%	30.80%	50.74%
Hemicellulose degradation (%)⁴	-	31.89%	27.00%	35.04%
Lactic acid (mg/100g)	23.87 ± 2.39^d	125.95 ± 1.83^b	79.31 ± 1.51^c	150.21 ± 1.01^a
Indispensable aa
Arg	1.23 ± 0.03^a	1.11 ± 0.01^c	1.15 ± 0.03^b	1.09 ± 0.02^c
His	0.76 ± 0.02^c	0.87 ± 0.03^b	0.79 ± 0.02^c	0.92 ± 0.01^a
Ile	0.60 ± 0.02^c	0.64 ± 0.02^b	0.59 ± 0.02^c	0.71 ± 0.01^a
Leu	1.94 ± 0.03^c	2.11 ± 0.02^b	1.95 ± 0.02^c	2.18 ± 0.02^a
Lys	0.79 ± 0.03^c	0.88 ± 0.01^b	0.80 ± 0.02^c	0.93 ± 0.01^a
Met	0.18 ± 0.01^a	0.13 ± 0.01^c	0.20 ± 0.01^a	0.16 ± 0.01^b
Phe	0.88 ± 0.03^d	1.01 ± 0.02^b	0.96 ± 0.02^c	1.06 ± 0.02^a
Thr	0.81 ± 0.03^b	0.88 ± 0.02^a	0.82 ± 0.01^b	0.93 ± 0.03^a
Val	1.19 ± 0.02^c	1.34 ± 0.02_b	1.28 ± 0.03^b	1.42 ± 0.04^a
Dispensable aa
Asp	1.42 ± 0.04	1.42 ± 0.02	1.41 ± 0.02	1.45 ± 0.02
Ser	0.94 ± 0.03^a	0.87 ± 0.02^b	0.88 ± 0.01^b	0.88 ± 0.02^b
Glu	3.04 ± 0.02^d	3.80 ± 0.03^b	3.40 ± 0.04^c	3.96 ± 0.01^a
Gly	1.04 ± 0.03	1.06 ± 0.03	1.03 ± 0.02	1.07 ± 0.02
Ala	1.60 ± 0.05^b	1.70 ± 0.04^a	1.60 ± 0.02^b	1.77 ± 0.02^a
Cys	0.25 ± 0.03^b	0.29 ± 0.02^ab	0.28 ± 0.01^ab	0.31 ± 0.01^a
Tyr	0.46 ± 0.01^a	0.48 ± 0.02^a	0.48 ± 0.01^a	0.51 ± 0.01^b
Pro	1.46 ± 0.04^b	1.59 ± 0.03^a	1.50 ± 0.03^b	1.63 ± 0.01^a
Total aa	18.60 ± 0.28^d	20.20 ± 0.11^b	19.15 ± 0.04^c	21.02 ± 0.09^a
PCGM-CK: the CGM was pretreated with sodium bicarbonate.
PCGM-BL: the PCGM was incubated with B. velezensis CL-4 at 37°C and then added L. plantarum C37 for another 24h under anaerobic conditions at 37°C.
PCGM-CL: cellulase was added into PCGM at 37 ℃ for 24h and then added L. plantarum C37 for another 24h under anaerobic conditions at 37°C.
PCGM-BCL: the PCGM was incubated with B. velezensis CL-4 and cellulase at 37°C and then added L. plantarum C37 for another 24h under anaerobic conditions at 37°C.
¹ Cellulose = ADF- residue after 72% sulfuric acid treatment.
² Hemicellulose = NDF-ADF.
³ Cellulose degradation= (relative content of cellulose before - relative content of cellulose after pretreatment or fermentation)/relative content of hemicellulose before.
⁴ Hemicellulose degradation= (relative content of hemicellulose before - relative content of hemicellulose after pretreatment or fermentation)/relative content of hemicellulose before.
^a−d Values were mean ± SD, n = 3. Means followed with different superscript letters (a-d) within each line are significantly different (p < 0.05).

Table 3

Short-chain fatty acid (SCFA) of pretreated corn germ meal (PCGM) and PCGM fermented with different microbes and cellulase.
Item	0h	48h
Item	PCGM-CK	PCGM-BL	PCGM-CL	PCGM-BCL
Acetic acid µg/g	201.73 ± 2.17^d	1266.88 ± 23.62^b	791.24 ± 16.16^c	1658.73 ± 21.85^a
Propionic acid µg/g	3.77 ± 0.32^c	6.06 ± 1.16^b	5.82 ± 0.48^b	8.12 ± 0.26^a
Isobutyric acid µg/g	1.51 ± 0.05^d	6.95 ± 1.01^b	4.00 ± 0.08^c	12.98 ± 0.28^a
Butyric acid µg/g	0.86 ± 0.05^c	1.21 ± 0.22^ab	1.06 ± 0.11^bc	1.41 ± 0.04^a
Isovaleric acid µg/g	5.68 ± 0.14^d	25.18 ± 3.73^b	18.12 ± 0.60^c	42.32 ± 0.83^a
Valeric acid µg/g	0.60 ± 0.02^b	0.74 ± 0.12^a	0.72 ± 0.05^ab	0.75 ± 0.03^a
Hexanoic acid µg/g	2.45 ± 0.22	2.98 ± 0.77	2.90 ± 0.31	3.24 ± 0.08
Total_SCFA µg/g	216.61 ± 2.74^d	1310.00 ± 17.19^b	823.87 ± 17.62^c	1727.55 ± 23.00^a
PCGM-CK: the CGM was pretreated with sodium bicarbonate.
PCGM-BL: the PCGM was incubated with B. velezensis CL-4 at 37°C and then added L. plantarum C37 for another 24h under anaerobic conditions at 37°C.
PCGM-CL: cellulase was added into PCGM at 37 ℃ for 24h and then added L. plantarum C37 for another 24h under anaerobic conditions at 37°C.
PCGM-BCL: the PCGM was incubated with B. velezensis CL-4 and cellulase at 37°C and then added L. plantarum C37 for another 24h under anaerobic conditions at 37°C.
Values were mean ± SD, n = 3. Means followed with different superscript letters (a-d) within each line are significantly different (p < 0.05).

Table 4

Mycotoxin content of pretreated corn germ meal (PCGM) and PCGM fermented with different microbes and cellulase.
Item	0h	48h
Item	PCGM-CK	PCGM-BL	PCGM-CL	PCGM-BCL
Aflatoxins B₁ µg/kg	-	-	-	-
Aflatoxins B₂ µg/kg	-	-	-	-
Aflatoxins G₁ µg/kg	-	-	-	-
Aflatoxins G₂ µg/kg	-	-	-	-
Deoxyniverenol mg/kg	0.4	4.2	4.4	4.0
Zearalenone µg/kg	569	545	562	542
PCGM-CK: the CGM was pretreated with sodium bicarbonate.
PCGM-BL: the PCGM was incubated with B. velezensis CL-4 at 37°C and then added L. plantarum C37 for another 24h under anaerobic conditions at 37°C.
PCGM-CL: cellulase was added into PCGM at 37 ℃ for 24h and then added L. plantarum C37 for another 24h under anaerobic conditions at 37°C.
PCGM-BCL: the PCGM was incubated with B. velezensis CL-4 and cellulase at 37°C and then added L. plantarum C37 for another 24h under anaerobic conditions at 37°C.

Concisely, fermentation with B. velezensis CL-4, L. plantarum C37, and cellulase effectively improved the number of viable bacteria, nutritional quality, and content of SCFAs, and lowered pH in PCGM-BCL. Subsequently, the PCGM-BCL group was analyzed for the changes in microbial diversity during the fermentation.

Changes in the bacterial community

Overall, 169091.67 ± 6585.50, 148944.33 ± 2919.23 and 108488.50 ± 5700.98 high-quality sequences were collated from PCGM-CK-0h, PCGM-BC-24h (BC24h) and PCGM-BCL-48h (BC48h) samples, respectively; the 16S rRNA OTUs (operational taxonomic units; selected based on 97% sequence similarity) numbers in these samples were 975 ± 59.27, 38.5 ± 2.73 and 55.50 ± 5.25, respectively. We used alpha-diversity and rarefaction curve indices to estimate the richness and diversity of bacterial communities during SSF. In general, all samples had high-coverage OTUs and adequate sequencing depth required for bacterial community analysis (Figs. 3A and B). The PCoA plot shown in Fig. 3C indicated that samples at 0, 24, and 48 h had clear differences. In PCGM-CK, the main phyla were Firmicutes (54.15%), Proteobacteria (25.60%), Chlamydiae (6.25%), Actinobacteria (5.55%), and Bacteroidetes (4.59%). However, with the progress of fermentation, Firmicutes became the predominant phylum, comprising around 99.94% (24h) and 99.88% (48h) of the sequences (Fig. 3D). The genus-level results mirrored those at the phylum level (Fig. 3E). Bacillus was the dominant genus in BC24h, accounting for 99.87%. Upon L. plantarum C37 inoculation, the content of Lactobacillus increased to 37.45% in BC48h. The random forests analysis also revealed significant differences in bacterial taxonomy composition among the different fermentation time points (Fig. 3F). Specifically, the abundance of Bacillus increased significantly after 24 h of aerobic fermentation, while Lactobacillus became predominant after 24 h of subsequent anaerobic fermentation.

Changes in the fungal community

In total, 97388.17 ± 1000.37, 95265.17 ± 1820.12 and 104090.17 ± 1966.12 high-quality ITS genes sequences were collated from PCGM-CK-0h, BC24h, and BC48h samples, respectively. Additionally, the ITS OTU numbers (based on 95% sequence similarity) reached up to 64.17 ± 4.53, 72 ± 2.32, and 56 ± 5.92 in PCGM-CK-0h, BC24h, and BC48h, respectively. The results from alpha-diversity and rarefaction curve analyses revealed that all samples had sufficient coverage of fungal communities and the sequencing depth was suitable for analyzing the fungal community structure during SSF (Figs. 4A and B). The PCoA plot in Fig. 4C showed a distinct separation of samples collected at 0, 24, and 48 h. In all samples, the dominant phyla were Ascomycota and Basidiomycota; Ascomycota was the most abundant phylum, accounting for 97.80%, 95.24%, and 94.46% sequences in PCGM-CK-0h, BC24h, and BC48h, respectively (Fig. 4D). Importantly, these changes in the fungal community structure at the genus level were consistent with those observed at the phylum level (Fig. 4E). In PCGM-CK-0h, various native fungi, such as Fusarium and Didymella, were present, but Fusarium was almost completely inhibited during subsequent fermentation. Furthermore, the random forests analysis revealed significant differences in the taxonomic composition of the fungal communities at different fermentation time points (Fig. 4F).

Cooperative bacterial and fungal metabolism of PCGM

Microbial metabolic functions that were derived from the KEGG pathway database are shown in Supplemental Fig. S1. Among the six different metabolic functions, the protein sequences predicted at three-time points are shown in Supplemental Fig. S1-A, which represented different pathways (Supplemental Fig. S1-B). Notably, the pathways related to carbohydrate, amino acid, cofactor, and vitamin metabolism were significantly enriched, constituting more than 10% of the total enriched pathways during the entire fermentation process. Additionally, pathways related to cellular communication, membrane transport, signal transduction, carbohydrate metabolism, lipid metabolism, and metabolism of other amino acids were also enriched during the whole fermentation process. However, the sequences related to cell motility, transport, and catabolism, protein folding, sorting and degradation, transcription, and metabolism of amino acids, cofactors, and vitamins were enriched only in the BC24h sample. Supplemental Fig. S1-C illustrates certain variations in the effectiveness of bacterial gene functions at KEGG level 3 throughout SSF. The abundance of a majority of the genes assigned to membrane transport (phosphotransferase system (PTS)), amino acid metabolism (alanine, aspartate, and glutamate metabolism, cysteine and methionine metabolism, and histidine metabolism) and carbohydrate metabolism (amino sugar and nucleotide sugar metabolism, glycolysis/gluconeogenesis, pyruvate metabolism, fructose, and mannose metabolism, pentose and glucuronate interconversions, pentose phosphate pathway, propanoate metabolism and starch and sucrose metabolism) increased dramatically during the fermentation process. Similarly, the genes associated with the metabolism of other amino acids, such as D-Alanine metabolism, D-Arginine and D-ornithine metabolism, D-Glutamine and D-glutamate metabolism, and selenocompound metabolism were markedly enriched during the fermentation (p < 0.05). Moreover, the abundance of most genes related to the metabolism of cofactors and vitamins (folate biosynthesis, lipoic acid metabolism, thiamine metabolism, and vitamin B₆ metabolism) also increased with the progress of fermentation. During the aerobic fermentation period, a noticeable decline was observed in the abundance of genes associated with amino acid metabolism, specifically lysine biosynthesis, while these again increased after anaerobic fermentation. The gene function prediction for the fungal community was performed using the Metacyc tool (Supplemental Fig. S2 A and B). Since no exogenous fungi were added during the fermentation, the detected fungi were from the environment that came along with CGM. Their metabolic pathways were influenced by the fermentation environment but the differences in samples were not significant.

In recent years, there have been numerous studies reporting the beneficial effects of microorganisms and their metabolites in fermented feed (Su et al. 2021). Microorganisms such as Bacillus, yeast, and lactic acid bacteria secrete enzymes that effectively degrade anti-nutritional factors (ANFs) and improve the nutritional value of the feed (Arevalo-Villena et al. 2017). Previously, we reported about B. velezensis which secrete a large amount of lignocellulose-degrading enzymes (Chen et al. 2018b; Chen et al. 2023). However, CGM pretreatment with sodium bicarbonate was necessary before B. velezensis fermentation to solve the problem of low pH during corn deep processing. Although the method improved the number of viable bacteria, fermentation rate, and nutritional composition of CGM, the cellulose degradation rate of CGM was still limited (Chen et al. 2022). In this study, we investigated the impact of cellulase in combination with B. velezensis on the nutritional value of PCGM during the two-stage SSF. We found that the combined fermentation with B. velezensis CL-4, L. plantarum C37, and cellulase can significantly reduce the cellulose content in PCGM, further improving its quality.

In this study, we found that the combination of B. velezensis CL-4 and cellulase increased the number of B. velezensis CL-4 in the aerobic stage and that of L. plantarum C37 in the subsequent anaerobic fermentation process; meanwhile, the system pH also dropped to 4.38 ± 0.02. In the anaerobic environment, the viable count of B. velezensis CL-4 declined from 12.24 ± 0.08 to 8.54 ± 0.22 cfu/g. Notably, it has been reported that B. velezensis can colonize plant roots and therefore may be a facultative aerobic bacterium bacteria (Khalid et al. 2021), while our experimental results confirmed the activity of B. velezensis CL-4 during the 48 h fermentation process, showing no inhibition effect on L. plantarum C37. However, the feasibility of combining B. velezensis CL-4 with L. plantarum C37 and cellulase in anaerobic fermentation still needs to be tested.

In terms of improving nutritional quality, the contents of CP, TCA-SP, and amino acids significantly increased in PCGM-BCL after 48h of fermentation. The increase in CP amount can be attributed to the accumulation of single-cell proteins generated by microorganisms. The relative rise in CP concentration leads to the loss of DM (predominantly carbohydrates) in the fermentation substrate (Stokes and Gunness 1946). TCA-SP, comprised of small peptides and free amino acids, is mostly absorbed in the gastrointestinal tract (Gilbert et al. 2008). Alteration in amino acid composition during the fermentation process is due to the breakdown and formation of microbial proteins (Metges 2000). As a result, TCA-SP levels increase, altering amino acid composition to enhance the nutritional quality of fermented PCGM-BCL at 48 h. In this study, the content of CF, cellulose, and hemicellulose was effectively reduced after fermentation. Although B. velezensis secretes a large number of lignocellulosic degrading enzymes, it has limited cellulose degradation ability. It can only degrade amorphous cellulose but not that in crystalline form (Chen et al. 2018a). In this study, the exogenous addition of cellulase, together with B. velezensis secreted endocellulase, amylase, and protease, increased the cellulose degradation rate of PCGM from 5.02 to 50.74%, compared with the PCGM-BL group. The degradation of cellulose, hemicellulose, and starch makes internal proteins more vulnerable to the environment of gastric and pancreatic proteases (Agama-Acevedo et al. 2005; Yang et al. 2010), which further improves the digestion of CP and amino acids. Additionally, the CGM pH in the PCGM-BCL group was lower than that in the PCGM-BL group, which could have enhanced the activity of gastric protease (Mat et al. 2018). Compared with PCGM-CK, the PCGM-BCL showed smaller cracks and larger pores in the SEM structures. This change in the surface structure after fermentation may be related to the action of extracellular enzymes and exogenous cellulase. Furthermore, this cracking and porous structure increases lignocellulases efficiency on the substrate (Zheng et al. 2017). Moreover, microstructure changes may have influenced the physicochemical properties of PCGM-BCL. The growth of L. plantarum C37 in the anaerobic phase increased the contents of SCFAs in PCGM, mainly acetic, propionic, isobutyric, butyric, isovaleric, and pentanoic acids, which are produced by the fermentation of undigestible carbohydrates such as dietary fiber, resistant starch, and oligosaccharides by beneficial bacteria such as Lactobacillus and Bifidobacterium in the colon (de Vos et al. 2022). Studies have shown that SCFAs play important regulatory roles in host health, including regulation of blood glucose, drug release by conjugation with monosaccharides, and regulation of intestinal flora balance and intestinal function (Parada Venegas et al. 2019). In this study, the levels of acetic, propionic, isobutyric, and isovaleric acids were significantly increased in PCGM-BCL (p < 0.05). Acetic acid is mainly produced by the fermentation of pectin, xylan, and arabinogalactan by bacterial genera such as Bacteroides, Ruminococcus, Eubacterium, and Streptococcus in the intestine (Ziętek et al. 2021). Propionic acid is mainly produced by the fermentation of arabinogalactan by Bacteroidetes, which converts succinate into methylmalonyl-CoA (Lymperopoulos et al. 2022). In the first stage of the fermentation, B. velezensis CL-4 and cellulase provided more oligosaccharides that could be directly utilized by L. plantarum C37 in the second-stage anaerobic fermentation of PCGM. The increase in isobutyric and isovaleric acids content may be due to the decomposition of nitrogen-containing substances such as leucine and valine (Morrison and Preston 2016). In addition, high amounts of lactic acid produced during anaerobic fermentation not only improve palatability but also rapidly lowers intestinal pH, inhibiting harmful bacteria and maintaining intestinal flora balance (Su et al. 2022). Therefore, adding L. plantarum to PCGM at the anaerobic stage further improved the nutritional value and palatability of PCGM.

Using high-throughput sequencing technology, we analyzed the changes in microbial communities of fermented PCGM during the fermentation process. In PCGM-CK-0h, at the phyla level, Firmicutes accounted for more than 50%, followed by Proteobacteria at 25.60%. Proteobacteria comprises a wide range of bacteria, including both pathogenic bacteria like Escherichia coli, Salmonella, and Pseudomonas aeruginosa, and beneficial bacteria that can fix atmospheric nitrogen (Shin et al. 2015). In this study, due to the lack of high-pressure sterilization of the CGM in the early stages, the original dynamic changes of the microorganisms during fermentation were restored. After two stages of SSF, Proteobacteria were almost undetectable, indicating that B. velezensis CL-4, under aerobic conditions, vigorously proliferated and inhibited other bacteria and fungi to become the dominant species, decreasing corresponding numbers of OTUs. Furthermore, the second stage of anaerobic fermentation by L. plantarum C37 further ensured the safety of the fermented product. Lactobacillus belongs to a moderate-temperature genus, and its members produce acidic products (Yuan et al. 2018). At the genera level, most bacteria detected in PCGM-CK-0h are widely distributed in nature, existing in soil or the environment, such as Thermoactinomyces, Acinetobacter, Paenibacillus, Exiguobacterium, Methylobacterium, and others. Acinetobacter is a non-fermenting and conditionally pathogenic bacterium, which causes infection in low-resistance hosts (Ibrahim et al. 2021). After two stages of SSF, the abundance of these bacteria significantly decreased. At 24 h, Bacillus accounted for 99.87%, and at 48 h, Bacillus accounted for 62.33% and Lactobacillus accounted for 37.45%, consistent with the results of viable cell counts in this study.

At the phylum level, the Ascomycota phylum was identified as the core fungi in fermented PCGM. This finding is consistent with Su's report, showing that Ascomycota fungi consume oxygen during the first stage of fermentation, which suppresses the growth of pathogenic aerobic microorganisms (Su et al. 2021). At the genus level, Xeromyces accounted for 39.19%, 37.50%, and 53.62% in PCGM-CK-0h, BC24h, and BC48h, respectively. Xeromyces are extreme xerophilic fungi that can grow at a water activity (aw) of 0.85 or less, making them highly adaptable to their environment (Leong et al. 2015). Moreover, a culture medium pH of around 4.0 and cultivation at 35–37°C can maximize its growth rate and reduce competition with other fungi (Stevenson et al. 2017). Therefore, the increase in the abundance of Xeromyces in BC48h was related to the lowering of environmental pH and optimal temperature.

Aspergillus accounted for 40.01% and 41.02% in PCGM-CK-0h and BC24h, respectively, but then decreased to 27.03% during anaerobic fermentation due to its aerobic characteristic. Considering that Aspergillus includes highly toxic molds such as Aspergillus flavus (Hedayati et al. 2007), we conducted mycotoxin detection, however, we found no Aflatoxins B₁, B₂, G₁, and G₂. In addition, Aspergillus also includes other probiotics such as Aspergillus oryzae and Aspergillus niger, which exhibit strong enzyme activity and are widely used in food fermentation of soy sauce, beer, and enzymes such as glucose oxidase, amylase, and protease in modern fermentation industries (Frisvad et al. 2018). Therefore, in future research, the addition of A. oryzae or A. niger could be considered to further enhance the nutritional value and metabolic diversity of CGM. In PCGM-CK-0h, the abundance of Didymella was 10.89%. Some reports observed that Didymella is the pathogen responsible for "Tea Disease" (Liu et al. 2022). Also, Fusarium, a member of the genus Fusarium, was identified in PCGM-CK-0h. This fungus is known to produce plant pathogens and toxins that can be harmful to humans and animals. Vomitoxin (DON) is predominantly produced by Fusarium species, particularly Fusarium graminearum and Fusarium culmorum, and causes vomiting in pigs (Yao and Long 2020). The detection of mycotoxins revealed a significant reduction in the abundance of Didymella and Fusarium in the two-stage SSF process. The levels of vomitoxin (DON) and zearalenone, which are class 3 carcinogens, were reduced and within the feed safety limits (Evans and Shao 2022). Concisely, the two-stage SSF effectively inhibited the growth of pathogenic fungi. Kazachstania was found in BC24h and BC48h. Kazachstania yeast can ferment sugars, produce secondary metabolites, inhibit the growth of fungal toxins, and have several enzyme activities (Kaeuffer et al. 2022). The change in bacterial and fungal microbiota during fermentation indicates that the addition of artificial inoculants not only increases the quantity of added microorganisms but also promotes the growth of other functional microorganisms, which can work as symbiotics with inoculants. This provides a basis for the antagonistic and symbiotic relationship of multi-strain use in the future.

The KEGG genes functional analysis showed a consistent trend from KEGG level 1 to level 3. The abundance of genes associated with the metabolism of carbohydrates, co-factors, vitamins, and amino acids increased with the progress of fermentation. The breakdown of cellulose and hemicellulose produces various compounds that provide nourishment to bacteria, while amino acids serve as a carbon and energy source (Sánchez Ó et al. 2017). Hence, an increase in sugar and amino acid levels from the degradation of large carbohydrates and proteins ensured proper energy sources for the microbial community in fermented PCGM. Additionally, during fermentation, the abundance of genes involved in membrane transport and the phosphotransferase system (PTS) increased, indicating the role of core bacterial enzymes in FCGM synthesis and membrane transport activity. According to the previous report, significant changes in fungal microbial diversity and metabolic pathways were found in a mixture of corn by-products fermented with Pichia kudriavzevii, L. plantarum, and neutral protease (Su et al. 2021). Here, no exogenous fungal fermenting strains were added, so the microbial diversity and predicted metabolic pathways are related to native fungi, and the overall differences were not significant.

In summary, cellulase synergized with B. velezensis can degrade large protein molecules into TCA-SP in the two-stage SSF fermentation process, improving the amino acid composition pattern, and viable count of the fermentation strains. Furthermore, this strategy improves the cellulose degradation rate of CGM, overcoming the cellulases deficiency in B. velezensis. The two-stage SSF process utilized in this study can enhance the nutritional value of CGM. The findings presented here improve our understanding of dynamic changes in physicochemical properties, microbial communities, and metabolic functions of inoculated microorganisms during the fermentation process. These results offer valuable insights for both industrial feed practice and SSF system metabolomics research. In future research, one should explore the addition of other supplementary enzymes (such as proteases) or fungi (such as yeast, Aspergillus niger, and Aspergillus oryzae) to achieve greater reduction in ANFs and generate a wider range of advantageous metabolic compounds in fermented CGM.

Author’s contributions

L.C. conceived the study; Y.G., X.L., L.Z. and L.Z. implemented the methodology; Z.Z. and B.W. analyzed the results; L.C. and Z.Z. wrote the manuscript. All authors read and approved the manuscript in its final form.

Funding information

This research was supported by the Postdoctoral Grant of Jilin Province (JLSB2022001);The Basic scientific research fund project of Jilin Academy of Agricultural Sciences (KYJF2021JQ103);Funding program for High-level scientifc and technological innovation talents introduced by Scientifc research Institutes of Jilin Province.

Conflicts of Interest

The authors declare no conflicts of interest.

Data availability statement

All data analyzed during this study are included in this manuscript and additional material.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Acknowledgements

The authors would like to thank all the reviewers who participated in the review, as well as MJEditor (www.mjeditor.com) for providing English editing services during the preparation of this manuscript.

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No competing interests reported.

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published 03 Jan, 2024

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Cellulase with Bacillus velezensis improves physicochemical characteristics, microbiota, and metabolites of two-stage solid-state fermented corn germ meal

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Journal Publication

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Abstract

Figures

Key Points

Introduction

Materials and methods

Microorganisms and enzymes

Effect of cellulase on two-stage fermentation of CGM

Chemical analyses

Microorganisms and microbial metabolites

Mycotoxin content determination

Microscopy

Bacterial and fungal community analysis and metabolic function prediction

Statistical and bioinformatics analyses

Results

Selection of the strain and enzyme combinations

Changes in the bacterial community

Changes in the fungal community

Cooperative bacterial and fungal metabolism of PCGM

Discussion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1