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Keywords:

  • genetically modified microorganism (GMM);
  • safety assessment;
  • gut health;
  • fecal microbiota and metabolites;
  • gut permeability and mucosal immunity

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. Acknowledgements
  8. REFERENCES
  9. Supporting Information

Lp was a generally recognized as safe microorganism. Lactobacillus plantarum 590 was obtained by inserting nisI gene into Lp genome to help it tolerate higher concentration nisin. As the unintended effects of the genetically modified microorganism (GMM) are the most important barriers to the progress of GMM, we have performed a useful exploration to establish a new in vivo evaluation model for GMM from the point of view of intestinal health. In this study, Sprague–Dawley rats were orally administered with Lp 590 and Lp for 4 weeks. Fecal samples were collected to determine the number of beneficial bacteria Bifidobacterium and harmful bacteria Clostridium perfringens. Denaturing gradient gel electrophoresis was used to detect the bacterial profiles of every group. Fecal enzyme activities and short-chain fatty acids as main metabolites were also examined. Real time PCR (RT-PCR) and immunohistochemistry were used to analyze two proteins (ZO-1 and occludin) and secretory immunoglobulin A to detect intestinal permeability and mucosal immunity, gut permeability and gut mucosal immunity were analyzed to see whether GM Lp 590 can induce changes of the gut health when compared with non-GM Lp group, andeventually we concluded that there is no significant difference between GM Lp 590-fed group and non-GM Lp-fed group. The conclusion of gut health test was comparable withthat from traditional subchronic test. Evaluation of intestinal health will be a new approach of assessing the safety of GMM. © 2012 IUBMB Life, 64(7): 617–627, 2012.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. Acknowledgements
  8. REFERENCES
  9. Supporting Information

With the development of biological engineering technology, there are now many types of genetically modified microorganisms (GMMs) (1). GMM provides a new way to develop food production, pharmaceutical industries, and so forth (2). As gene technology progresses from modifications aimed at relatively simple traits to addressing more complex attributes, the challenges of evaluating the unintended effects of GMMs on human health will increase (3). Documents giving guidance on the safety assessment of GM foods have been developed. However, for issues concerning the safety, no specific instructions on how to perform the requested investigations are given (4).

Gastrointestinal (GI) microbiota acts as an essential “organ” and comprises a complex microecological system (5). GI microbiota can provide nourishment, regulate epithelial development, protect against pathogens, and instruct innate immunity (6). There is a slight difference of GI microbiota according to their histories and lifestyles, including diet (7). However, for health individual, the proportion of the main beneficial intestinal bacterium and potential pathotens is in the normal range (8). As beneficial intestinal bacteria, Bifidobacterium has abilities, including modulation of the GI tract, acetic acid production, antagonism against other pathogenic bacteria, and tolerance to diet allergens (9). Clostridium perfringens have long been considered as potential pathogens, as it produces harmful gases such as ammonia and hydrogen sulfide and even other carcinogens that cause GI tract diseases and disorders (3). The production of metabolic reactions of GI microbiota including fecal enzyme activity and short-chain fatty acids (SCFAs) can play an important role in health and disease (10). Constipation, colonic cancer, and inflammatory bowel diseases, for example, can be influenced by their metabolic activities (3). So, gut health is inseparable from intestinal microbiota and their metabolites (10).

Normally, the intestinal epithelium acts as a continuous barrier to protect from endogenous or exogenous damage. Gut permeability and mucosal immunity can reflect the function of the intestinal barrier, further present intestine and body health (11–13). To detect gut permeability and mucosal immunity, two tight junction proteins (ZO-1 and occludin) and secretory immunoglobulin A (SIgA) are usually used as the main parameters (11, 13).

Genetically modified Lactobacillus plantarum 590 (GM Lp 590) derived from electroporation of pLEB590 as a food-grade vector (2) into L. plantarum showed that nisI function as an immunity protein in Lactobacilli, enabling nisin resistant (14, 15). Microorganism intake can more directly effect on GI microbiota, their metabolites (9, 10), gut permeability, and mucosal immunity (3, 16). However, it is unfortunate that little has been done to establish a specific uniform concept of gut health with respect to GMM safety. Therefore, in this study, we observed intestinal bacteria, their main metabolites, intestinal permeability, and intestinal mucosal immunity by administration of L. plantarum and L. plantarum 590 to Sprague Dawley (SD) rats for 4 weeks. We attempted to establish a GMM food safety assessment gut health model.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. Acknowledgements
  8. REFERENCES
  9. Supporting Information

Bacterial Strains

GM Lp 590 was obtained from non-GM Lp (numbered AS1.2986) with the gene nisI inserted (numbered LM0230). The two strains were derived from the Chinese Academy of Microbiology Culture Collection.

Collection of Bacterial Cells

Lp and Lp 590 were anaerobically propagated in Man-Rogosa-Sharpe broth (Hispanlab, Madrid, Spain) at 37°C for 16 h. Bacterial cells were harvested by centrifugation at 6,000 × g for 15 min, washed three times with phosphate buffer solution (PBS), resuspended at 2.5 × 109 CFU/mL, respectively, and collected for further test.

Animal Feeding, Grouping, and Experimental Design

Male and female SD rats at 4 weeks of age and with an average body weight of 40–60 g were purchased from Beijing Weitonglihua Experimental Animal Technique Co. (Beijing, China). Following 1 week acclimatization, 36 rats (18 males and 18 females) were divided randomly into six groups (six rats per group) according to weight. The rats were kept in stainless steel wire cages (two/cage) at 21–23°C and a relative humidity of 40–60%, with an air change 15 times per hour and electric light from 9 a.m. to 9 p.m. in animal rooms. Sterilized food and water were supplied to the rats from the public supply, which was available ad libitum.

Throughout the experiment, the general condition, behavior, and mortality of all animals were checked daily, the body weight was measured twice 1 week, and all the data were recorded systematically. The general behavior signs of observation included changes in the skin, fur, eyes, and membranes, as well as respiratory, circulatory, autonomic and central nervous system function, and behavioral patterns.

Both Lp and Lp 590 for feeding were freshly cultured according to mentioned above every day, and the numbers of living bacteria were determined by pour plate method every 3 days (3). For the administration, bacteria were inoculated intragastrically with a sterile gauge stainless steel feeding needle. One milliliter of bacterial suspension (2.5 × 109 CFU/mL, the high dosage according to Lee et al. (3) or PBS were fed to each rat using a sterile pipette once a day for 4 weeks. On day 0, 7, 14, 21, and 28, fresh fecal samples were taken from each animal for microbial and metabolic analysis. Rats were anesthetized by carbon dioxide inhalation and killed by exsanguinations for organ weighs, gross, and histopathological examinations (17). Blood biochemistry and hematology assay were also measured. The intestinal segments (jejunum and ileum) were immersed in liquid nitrogen and stored at −80°C for further analysis.

DNA Extraction

Two reference bacterial strains at the stationary growth phase were used for DNA extraction with a Wizard genomic DNA purification kit (Cat. #A1120, Promega, Madison, WI) according to the manufacturer's protocol: Bifidobacterium longum (CGMCC 2265), and C. butyricum (CGMCC 1.209). Fecal bacteria DNA was extracted from 0.2–0.25 g samples with a QIAamp DNA stool extraction mini kit (QIAGEN, Hilden, Germany) according to the manufacturer's instructions. DNA with optical density ratio OD260/OD280 ranging from 1.8 to 2.0 was taken for quantification (8).

Analysis of Fecal Microbiota by Real-time Quantification Method

The real-time method was performed with fecal samples from days 0, 7, 14, 21, and 28 using a quantification PCR core kit (TOYOBO, Tokyo, Japan) and an ABI Prism SDS 7500 instrument (Applied Biosystems, Foster City, CA). Standard curves were established as described by Rinttil et al. (16). Primer sequences targeting 16SrDNA of different groups or genera of bacteria have been designed and optimized (14, 18) and are listed in Table 1. Briefly, specific DNA from the two standard bacterial strains was extracted and diluted to 10-fold serial concentrations ranging from 1010 to 102 DNA copies/μL according to the average genome size of the specific bacteria and ignoring differences in rrn copy numbers. A mixture of DNAs isolated from non-target bacteria (100 pg each) was taken as the negative control. The PCR mixture contained 1 μL of DNA dilutions from standard strains or 50 ng of DNA samples from feces, 25 μL of real-time PCR Master Mix (TOYOBO, Tokyo, Japan) and 0.2 μmol/L of each primer specific to genera or groups of bacteria. The PCR protocol was 2 min at 50°C, 5 min at 95°C, 40 cycles of 20 sec at 94°C and 30 sec at annealing temperature, and 1 min at 72°C for signal collection. The final results were expressed as log10 target genome copy number/g feces.

Table 1. Primer details of fecal microbiota RT-PCR
Target bacteriaAmlicon size (bp)Annealing temperature (°C)Sequence (5′–3′)
  1. F: forward primer, R: reverse primer.

Bifidobacterium43760F:GGGTGGTAAT GCCGGATG
R: TAAGCCATGG ACTTTCACACC
Clostridium12057F: ATGCAAGTCG AGCGAGG
R: TATGCGGTATT AATCTCCCTTT

Microbiota Analysis of Fecal Samples by Denaturing Gradient Gel Electrophoresis Method

The above final fecal DNA of the rats (five/group) was randomly selected. Denaturing gradient gel electrophoresis (DGGE) on the intestinal microbiota was performed to study the effect of the treatment on the intestine microbiota composition (19, 20). DGGE with a 35%–60% denaturing gradient was used to separate the PCR products obtained using a nested approach with the bacterial universal primers 338F (5′-ACTCC TACGGGAGGCAGCAG-3′), 518R (5′-ATTACCGCGGCTGC TGG-3′) for the 16S rRNA gene, with a 5′ GC clamp (20). The first PCR round was followed by a second amplification with primers 338F-GC and 518R. The latter primers were also used to amplify the 16SDNA of all bacterial total extracted DNA. The obtained DGGE patterns were analyzed using Bionumerics software version 2.0 (Applied Math, SintMartens-Latem, Belgium) (19). Clustering analysis was performed using the UPGMA (unweighted pair group method with arithmetic mean clustering algorithm) to calculate the dendrograms of each DGGE gel and a combination of all gels (19). The latter was performed on a created composite data set (20).

Analysis of Fecal Enzyme Activity and SCFAs

Every 7 days during administration, fecal sample from each rat was divided into three equal portions to determine fecal enzyme activity and fecal SCFAs levels. The fecal samples for enzyme activity analysis were homogenized (1:10) in PBS (w/v) at pH 7.0. Thereafter, the samples were sonicated (4 × 15 sec) and centrifuged at 500 × g for 10 min at 2–4°C. The supernatant fraction was used for the activity analysis of β-glucuronidase, β-glucosidase, and nitroreductase (21) at 37°C.

β-glucuronidase activity was measured by the method of Freeman (21). A known volume of 0.02 M PBS (pH 7.0), 0.1 mM EDTA, 3.0 mM ρ-nitrophenyl-β-D-glucopyranoside (Sigma), and the enzyme supernatant was made up to a final volume of 1 mL, and the mixture was incubated at 37°C for 15min. The reaction was arrested with 0.2 M glycine buffer (pH 10.4), and the amount of ρ-nitrophenol released was read at 540 nm with a spectrophotometer (Shimadzu, Japan). All reactions were linear with respect to concentration and incubation time to 45 min. The amount of ρ-nitrophenol liberated was determined by comparison with a standard nitrophenol curve.

β-glucosidase activity was measured by the method of Freeman (21). The mixture of samples and substrate (ρ-nitrophenyl-β-D-glucoside) were incubated with 37°C for 60 min. After incubation, 0.2 M Na2CO3 was added to arrest the reaction. The released ρ-nitrophenol was measured at 400 nm. All reactions were linear with respect to concentration and incubation time to 60 min. The amount of ρ-nitrophenol liberated was determined by comparison with a standard nitrophenol curve.

Nitroreductase activity was measured by the method of Freeman (21). The mixture contained 1.5 mM ρ-nitro benzoic acid (Sigma), 0.1 M PBS, and known amount of sample. The reaction was arrested by the addition of 20% TCA and centrifuged. ρ-aminobenzoic acid released was measured at 550 nm. The amount of transformed substrate was determined by comparison with a standard curve. Protein content of fecal and mucosal samples was measured by the method of Lowry et al. (22).

The concentrations of SCFAs in the fecal samples were quantified with a gas chromatograph (GC-2014 Shimadzu, Japan) according to the method described by Carneiro et al. (23). Briefly, 0.2 g fecal sample and 4 mL NaCl (0.9%, w/v) were vortexed and homogenized. After overnight at room temperature, the mixture of fecal sample and NaCl solution were then centrifuged at 4,000 rpm for 20 min to obtain the supernatants. The supernatants (200 μL) mixed with 32 mM α-methylhexanoic acid (20 μL, Sigma) and H3PO4 (20 μL) were centrifuged at 12,000 rpm for 15 min. After centrifugation, the resulting supernatant was filtrated through membrane filter (pore size 0.2μm, Whatman, England) and 1 μL were injected onto the gas chromatograph. The initial oven temperature was 80°C (retained 1 min) and was increased at 10°C/min to 150°C and retained 10 min; the detector temperature was 300°C. The standard solution was as follows: acetic acid (150 mM), propionic acid (50 mM), and butyric acid (40 mM) (Sigma). The gas chromatograph was equipped with a capillary free fatty acid-packed column (32 m × 0.32 mm; film thickness 0.25 mm). Nitrogen was used as the carrier gas at a flow rate of 25 mL/min. The column temperature was 125°C, and the temperature of the injection port and detector was 190°C. The concentration of SCFAs was calculated in mmol/L (8).

Analysis of DX-4000-FITC

This measure is based on the intestinal permeability of 4,000 Da fluorescent dextran-FITC (DX-4000-FITC) (FD4000 Sigma-Aldrich, St. Louis, MO) and has been previously described (24). The DX-4000-FITC concentration was analyzed with a fluorescence spectrophotometer (Perkin Elmer, HTS-7000 Plus-plate-reader, Wellesley, MA).

Immunohistochemistry Localization Analysis of ZO-1 and Occludin

The jejunum sample of each rat was analyzed for the localization of ZO-1 and occludin. A segment of the jejunum was immediately removed, longitudinally opened, and washed with PBS. Tissues were fixed in 10% (w/v) PBS-buffered formaldehyde, and 4-μm sections were prepared from paraffin-embedded tissues. After deparaffinization, endogenous peroxidase was quenched with 0.3% (v/v) hydrogen peroxide in 60% (v/v) methanol for 30 min. Nonspecific adsorption was minimized by incubating the section in 2% (v/v) normal goat serum in PBS for 20 min. Endogenous biotin and avidin binding sites were blocked by sequential incubation for 15 min with biotin and avidin (DBA, Milan, Italy), respectively. Sections of jejunum were incubated overnight with a polyclonal rabbit anti-occludin (1:100 in PBS, w/v) or rabbit anti-ZO-1 antibody (1:100 in PBS, w/v). The sections were then washed with PBS and incubated with biotin-conjugated goat anti-rabbit IgG (1:50, v/v). Specific labeling was detected with avidin-biotin peroxidase complex (DBA kit, Invitrogen). The counter-stain was developed with diaminobenzidine (brown color) and hematoxylin (red background). Sections were visualized on a microscope using a 40 × objective, and images were digitally stored with Nikon i50 software. To verify the binding specificity, some sections were also incubated with only biotin-conjugated goat anti-rabbit IgG as a negative control. In these situations, no positive staining was found in the sections, indicating that the immunoreaction was positive in all experiments. All the stainings were performed in duplicate in nonserial distant sections and analyzed in a double-blind fashion by two different investigators.

RT-PCR of SIgA, ZO-1, and Occludin

Total RNA from the jejunum and ileum of every rat was prepared using the TriPure reagent (Roche, Basel, Switzerland) for quantification of ZO-1, occludin, and SIgA, respectively, as previously described (25). cDNA was synthesized using a reverse transcription kit (Promega, Madison, WI) from 1 μg of total RNA. RT-PCR was performed with ABI 7500 instrument and software (Applied Biosystems, Foster City, CA) (11). The primer sequences for the targeted rat genes are presented in Table 2.

Table 2. RT-PCR primers used to amplification jejunum or ileum samples
Target proteinAmplicon size (bp)Annealing temperature (°C)Sequence (5′–3′)
  1. F: forward primer, R: reverse primer.

ZO-110858F: GAGGCTTCAGAA CGAGGCTATTT
R: CATGTCGGAGAG TAGAGGTTCGA
Occludin15558F: GCCTATGGAACG GGCATCTT
R: GCCAGCAGGAA ACCCTTTG
SIgA16859F: CACCACTGGGA AGGATGCA
R: GCAATTTCGC CGGTTAAGG

Statistical Analysis

Statistical comparisons were performed to determine whether significant differences were attributable to consumption of the GM Lp590. One-way analysis of variance (ANOVA) was conducted to evaluate homogeneity variance, then a least squares difference model was applied using SPSS Version 12 (SPSS, Chicago, IL) to detect differences in variables. Data were expressed as mean ± standard deviation. Differences were considered significant at *P < 0.05.

RESULTS AND DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. Acknowledgements
  8. REFERENCES
  9. Supporting Information

During the course of the experiment, no treatment-related adverse effects in the clinical appearance of the animals were observed. The body weights of male and female rats in the experimental groups were comparable with the control groups at the beginning, day 7, day 14, day 21, and the end of the experiment (219–225 g for females and 224–231 g for males). Results of the blood biochemistry and hematology assessment for males and females measured at study termination (day 28). There were no statistically significant differences between male and female microorganism-fed groups and the controls groups for all the parameters measured (Supporting Information Tables S1 and S2). There were no group-related alterations or statistically identified differences in the organ/body weights of male and female rats given Lp or Lp 590, when compared with the control groups (Supporting Information Table S3). No group-related histopathologic observations were found. The few spontaneous findings observed were generally minimal to slight/mild in severity, were randomly distributed among all groups, and were the type commonly observed in control rats of this age and strain (Supporting Information Fig. S1).

Subchronic experiment is considered to be the general procedure to evaluation GMM (4). In this study, there was no mortality or toxic effect observed in rats after subchronic oral administration of GM Lp 590.

Analysis of Microbiota

Intestinal microbiota is known as an indicator of health (12). The relative amount of main intestinal bacteria and their metabolites are usually analyzed, as any peroral food tends to affect on intestinal microbiota (11). However, intestinal microbiota analysis of intestinal contents cannot be readily available. Fortunately, the change of fecal microbiota can reflect the change of intestinal microbiota (6, 12). So, in this study, fecal samples were used to evaluate effects of GM Lp 590 as a model GMM on intestinal microbiota and their metabolites.

Previous research indicated that the change of relative amount of intestinal microbiota generally appear in prophase of treatment, after 14 days or 21 days intestinal microbiota would reach new balance (3). Therefore, 28 days is appropriate treatment time for assessment of the effect of microorganism on intestinal microbiota and their metabolites (3, 26).

Changes in the microbial community composition were observed by RT-PCR analysis. In recent years, RT-PCR has proven to be a simple yet reliable technique to quantify microorganisms and has been used successfully with bacteria, yeasts in milk products (27), and Penicillium camemberti and P. roqueforti mycelium in cheese (28). The problem of some bacteria being unable to be cultured by traditional plate counting techniques was solved by RT-PCR.

Bifidocbacterium and C. perfringens are the most important bacteria in the GI tract (3), and some researchers considered them to be beneficial and harmful bacteria, respectively (3, 29). At all five time-points (day 0, 7, 14, 21, and 28), no statistically significant differences in the numbers of specific bacteria were found between the GM Lp 590 group and its parental group (non-GM Lp) (Table 3). Compared with the PBS-fed group, significant changes of the two bacteria were observed in microorganism-fed groups, with higher levels of Bifidobacterium, and lower levels of C. perfringen (P < 0.05) at day 7 and day 14. After 14 days, there was no notable difference in cell numbers of the two bacteria in all groups. L. plantarum has long been considered as a probiotic and been used for food fermentation (30). Probiotic increased the number of beneficial bacteria Bifidocbacterium, reduced the number of harmful bacteria C. perfringen in the early phase of treatment is an indisputable fact (3). The results indicated that L. plantarum do play a role of improvement health. The similar result can be found in many references about assessment of Lactobacillus strains (3, 6, 26). From the result of DGGE at the time-point of day 28, the bacterial composition in Lp- and Lp590-fed rats show high similarities to those in PBS-fed rats (Fig. 1). Consistency of data changes in Lp and Lp 590 groups demonstrated that both GM and non-GM L. plantarum affected intestinal microbiota in a similar way.

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Figure 1. Analysis of intestinal microbiota by DGGE. DGGE fingerprint patterns of the fecal microbial community in selected male SD rats fed with PBS, Lp or Lp 590 on day 28. The DGGE profiles were constructed using primers for the fecal microbiota. The cluster analysis was based on the Pearson product-moment correlation coefficient and UPGMA linkage. The results with female rats were similar to those of the male rats and data are not shown. 1–5: PBS-fed males; 6–10: Lp-fed males; 11–15: Lp 590-fed males.

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Table 3. RT-PCR quantification of fecal samples
 BifidobacteriumClostridium
Day 0Day 7Day 14Day 21Day 28Day 0Day 7Day 14Day 21Day 28
  • Data are presented as log10 target genome copy number g−1 feces ± SD.

  • *

    Statistically significantly different from PBS-fed group (P < 0.05).

♂PBS8.42 ± 0.018.41 ± 0.078.42 ± 0.058.44 ± 0.068.45 ± 0.055.95 ± 0.155.97 ± 0.215.92 ± 0.335.95 ± 0.115.95 ± 0.08
♂Lp8.39 ± 0.038.72 ± 0.08*8.76 ± 0.03*8.39 ± 0.068.42 ± 0.075.94 ± 0.275.89 ± 0.325.85 ± 0.225.84 ± 0.295.91 ± 0.33
♂Lp5908.40 ± 0.048.74 ± 0.06*8.78 ± 0.09*8.36 ± 0.058.43 ± 0.055.85 ± 0.185.92 ± 0.195.94 ± 0.315.85 ± 0.285.82 ± 0.24
♀PBS8.41 ± 0.038.43 ± 0.098.44 ± 0.018.45 ± 0.028.44 ± 0.055.96 ± 0.235.97 ± 0.215.95 ± 0.285.86 ± 0.375.95 ± 0.12
♀Lp8.44 ± 0.078.76 ± 0.04*8.79 ± 0.02*8.41 ± 0.018.38 ± 0.115.94 ± 0.295.91 ± 0.245.91 ± 0.315.97 ± 0.195.84 ± 0.35
♀Lp5908.39 ± 0.098.71 ± 0.03*8.78 ± 0.03*8.44 ± 0.028.39 ± 0.035.86 ± 0.215.92 ± 0.335.75 ± 0.075.94 ± 0.315.88 ± 0.13

Analysis of Microbiota Metabolites

A number of studies indicated that intestinal microbiota enzymes play a very vital role in the development of colon cancer (30). In contrast to the control group, Lp- and Lp 590-fed rats exhibited a statistically significant decrease in the activities of β-glucuronidase, β-glucosidase, and nitroreductase, which are known to be associated with the conversion of procarcinogens into proximal carcinogens (21) before 14 days. Then, the three enzyme activities showed no remarkable change in all groups at day 21 and day 28. According to previous studies, a decrease in β-glucuronidase, β-glucosidase, and nitroreductase, which had positive correlation with beneficial Bifidocbacterium (21) can promote intestinal health (21, 31). Our results just proved the above correlation (Table 4). And lower three enzyme activities in Lp- and Lp 590-fed groups at day 7 and day 14 (P < 0.05) further suggested that there is no different effect of non-GM and GM L. plantarum on intestinal microbial metabolites.

Table 4. Fecal enzyme activities mean values ± SD
 Day 0Day 7Day 14Day 21Day 28
  • a

    Milligrams of p-nitrophenol liberated/min/g protein.

  • b

    Micromoles of p-aminobenzoic liberated/min/g protein.

  • c

    Micromoles of p-nitrocatechol liberated/min/g protein.

  • *

    Statistically significantly different from PBS-fed group (P < 0.05).

β-glucuronidasea
 ♂PBS23.12 ± 3.6323.42 ± 4.6322.75 ± 3.2123.33 ± 4.3622.87 ± 5.45
 ♂Lp23.51 ± 2.6320.74 ± 5.48*19.58 ± 6.09*23.21 ± 3.1923.05 ± 4.59
 ♂Lp59022.91 ± 4.0319.96 ± 3.99*19.71 ± 3.99*23.11 ± 5.2122.88 ± 3.75
 ♀PBS22.92 ± 4.5323.29 ± 2.5322.48 ± 3.6722.99 ± 5.2823.17 ± 5.39
 ♀Lp23.01 ± 3.6620.04 ± 3.18*19.87 ± 4.38*23.22 ± 4.5723.21 ± 3.47
 ♀Lp59023.21 ± 4.9520.22 ± 4.19*19.43 ± 5.22*23.17 ± 3.9823.38 ± 2.88
β-glucosidaseb
 ♂PBS65.27 ± 6.0765.86 ± 5.3764.77 ± 4.5864.62 ± 6.4165.52 ± 6.27
 ♂Lp64.54 ± 5.6263.15 ± 4.15*62.09 ± 5.24*64.49 ± 5.6864.67 ± 5.49
 ♂Lp59065.99 ± 4.8363.09 ± 4.89*63.23 ± 4.45*65.08 ± 3.7564.88 ± 4.76
 ♀PBS64.67 ± 5.3965.41 ± 5.9965.75 ± 3.9464.86 ± 4.5764.67 ± 4.76
 ♀Lp63.52 ± 4.4862.45 ± 3.05*62.56 ± 5.21*64.08 ± 5.7264.92 ± 5.39
 ♀Lp59065.61 ± 3.1763.09 ± 4.18*63.42 ± 4.37*64.46 ± 2.7465.09 ± 2.89
Nitroreductasec
 ♂PBS28.56 ± 3.5928.41 ± 4.6728.97 ± 4.6727.92 ± 4.3328.32 ± 2.95
 ♂Lp29.05 ± 4.2626.05 ± 2.84*26.14 ± 2.86*28.07 ± 3.5728.63 ±.341
 ♂Lp59028.38 ± 4.3125.38 ± 5.28*25.66 ± 5.28*27.86 ± 2.4128.31 ± 5.15
 ♀PBS29.06 ± 5.0829.06 ± 3.7728.79 ± 3.7728.75 ± 5.1828.19 ± 4.77
 ♀Lp28.65 ± 4.5627.03 ± 6.56*26.95 ± 6.56*28.46 ± 1.9628.26 ± 3.74
 ♀Lp59028.38 ± 3.9826.38 ± 4.98*26.19 ± 4.98*28.11 ± 3.5128.52 ± 5.07

In contrast to the control group, the level of butyric acid of Lp- and Lp 590-fed groups significantly increased at day 7 and day 14 (P < 0.05) (Table 5). At other time-points, for the level of butyric acid, there was no prominent change in all groups. It is known that Bifidocbacterium produce more SCFAs especially butyric acid (32), which was in agreement with our results. Compared with control group, the level of both acetic acid and propionic acid are not significant increase in microorganism-fed groups. However, in view of no statistically difference in non-GM or GM groups, it cannot be regarded as being associated with GM Lp 590 consumption. The same result can be found in the previous study (26).

Table 5. Fecal SCFAs
 Day 0Day 7Day 14Day 21Day 28
  • Data are expressed mean ± SD of eight rats from each group.

  • *

    Statistically significantly different from group CK (P < 0.05).

Acetate
 ♂PBS31.76 ± 1.3432.97 ± 3.0832.49 ± 4.3432.46 ± 5.3131.59 ± 1.94
 ♂Lp32.65 ± 2.4633.41 ± 1.9333.05 ± 1.4633.02 ± 2.5832.05 ± 3.22
 ♂Lp59030.99 ± 2.7233.47 ± 1.7933.17 ± 2.5433.14 ± 3.3733.16 ± 5.08
 ♀PBS32.98 ± 3.0333.77 ± 4.3433.28 ± 1.8832.24 ± 1.6832.38 ± 3.45
 ♀Lp31.05 ± 4.9434.05 ± 5.2534.05 ± 5.9934.01 ± 3.4531.95 ± 5.19
 ♀Lp59033.76 ± 1.2934.76 ± 3.8734.51 ± 3.2534.47 ± 2.5532.63 ± 2.97
Propionate
 ♂PBS9.81 ± 2.689.99 ± 3.389.74 ± 1.898.76 ± 2.699.99 ± 3.68
 ♂Lp9.58 ± 2.1410.85 ± 2.4510.12 ± 1.328.58 ± 1.4410.58 ± 2.45
 ♂Lp5909.26 ± 1.1210.26 ± 1.7110.01 ± 2.479.26 ± 1.6910.26 ± 1.71
 ♀PBS9.33 ± 2.019.59 ± 4.589.59 ± 3.069.09 ± 3.559.59 ± 4.58
 ♀Lp9.28 ± 1.7810.28 ± 5.949.57 ± 2.859.28 ± 4.9310.28 ± 5.94
 ♀Lp5909.91 ± 3.279.91 ± 3.7910.15 ± 2.999.91 ± 3.7510.91 ± 3.79
Butyrate
 ♂PBS8.17 ± 1.578.23 ± 0.978.49 ± 1.688.22 ± 3.048.11 ± 0.98
 ♂Lp7.97 ± 1.2610.89 ± 1.33*10.87 ± 3.33*7.79 ± 2.258.52 ± 1.66
 ♂Lp5908.21 ± 0.9610.21 ± 1.46*10.99 ± 2.46*8.01 ± 1.998.09 ± 2.87
 ♀PBS8.46 ± 1.058.51 ± 1.218.88 ± 2.248.33 ± 1.958.08 ± 3.01
 ♀Lp8.17 ± 1.3311.17 ± 1.09*11.25 ± 3.09*8.21 ± 2.388.21 ± 1.24
 ♀Lp5908.67 ± 0.8911.01 ± 1.69*10.91 ± 1.58*8.54 ± 3.258.19 ± 0.79

Relatively large changes of the fecal bacteria and their metabolites occurred in the first two weeks, which were both related to the fast growing of the rats during this period and the different diets. And gender cannot affect any test result. These results were consistent with the study of Wang et al. (32). Fecal bacteria and metabolites play a crucial part in gut health (11, 21, 25). As collection of fecal samples is easy and related tests are nondestructive and can be monitored continuously, feces could be proposed to be a vital target for evaluation of genetically modified food gut health.

Analysis of Gut Permeability

Indeed, the intestine is the body's largest microecological environment and its first line of defense against disease (11, 33). And the intestine is not only the longest pipeline in the intestinal digestive system but also the body's largest immune organ (11). Thus, the parameters about fecal bacteria and metabolites seemed not enough to describe gut health. Good intestinal function provides nutrients as well as improves the body's overall immune system (1). Therefore, gut permeability and mucosal immunity were also detected to evaluation gut health (11, 25).

Plasma DX-4000-FITC was used to analyze gut permeability (22). Both Lp 590- and Lp-fed rats showed a two-fold lower plasma DX-4000-FITC area under the curve (Figs. 2A and 2B) compared with the PBS-fed rats. Gut permeability is controlled by several specific tight junction proteins (11). Among these, ZO-1 and occludin have been proposed as key markers of tight junction integrity (11). Lp and Lp 590 treatment increased ZO-1 and occludin mRNA in the jejunum segment (Figs. 2C and 2E). ZO-1 and occludin immunohistochemical staining appeared to be increased uniformly and continuously distributed in Lp- and Lp 590-fed rats tissues (Figs. 3A and 3B). In accordance with the mRNA analysis, compared with the control group, Lp- and Lp 590-fed improved the tight-junctions of rats (P < 0.05), because the immunohistochemical staining of both proteins localized along the apical cellular border was greater with Lp and Lp 590 treatment compared with PBS treatment. Previous studies on the relationship between intestinal beneficial bacteria and permeability illustrated that Bifidobacteria can augment two proteins of ZO-1 and occludin and then promote gut permeability (34). The tendency also appeared in this study. To identify whether the changes in the gut microbiota and the expression of tight-junction proteins were associated with in vivo gut permeability, multiple correlation analysis between these parameters was performed. Indeed, a negative correlation between tight-junction protein mRNA level and plasma DX-4000-FITC was found in the jejunum segment (Figs. 2D and 2F). This is consistent with the previous findings (22).

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Figure 2. Analysis of gut permeability. A: Intestinal permeability assay: plasma DX-4000-FITC (μg/mL) oral challenge measured in SD male (-1) and females (-2) rats fed PBS, Lp or Lp590 for 4 weeks; B: The corresponding areas under the curve (AUC) for each group; C, E: Jejunum epithelial tight-junction markers (ZO-1 and occludin mRNA concentrations) relative to the PBS group. Data are the mean ± SEM. Data with different superscript letters are significantly different (*P < 0.05) according to post hoc ANOVA statistical analysis; D, F: Correlations between intestinal permeability markers: plasma DX-4000-FITC, ZO-1 and occludin mRNA concentrations (*P < 0.05) corresponding to Pearson's correlation and P values.

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Figure 3. Tight-junction protein distributions. Representative immunohistochemical staining for ZO-1 (A) and occludin (B) in male SD rats fed with PBS, Lp or Lp 590 for 28 days. The results with female rats were similar to those of the male rats, and data are not shown. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

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Analysis of Intestinal Mucosal Immunity

The local immunological defense of the gut is mainly provided by the gut-associated lymphoid tissue, principally in the form of SIgA, which is the predominant immunoglobulin present in mucosal secretions and is the first line of defense on the intestinal mucosal surface (12, 35). The results of the RT-PCR analysis showed that the level of SIgA in the ileum was higher in the Lp and Lp 590 groups than in the control group (P < 0.05) (Fig. 4A).

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Figure 4. Analysis of intestinal mucosal immunity by RT-PCR. (A) Ileum mucus SIgA relative to the PBS group. Data are the mean ± SEM. Data with different superscript letters are significantly different (*P < 0.05) according to post-hoc ANOVA statistical analysis. (B) Correlations between intestinal mucus SIgA and fecal bifidobacteria (*P < 0.05), corresponding to Pearson's correlation and P values.

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The results of previous studies with animals and volunteers as object all suggested that live bacteria are especially efficient mucosal immunogens (36). Moreover, the synthesis and excretion of SIgA depends mainly on healthy and stable beneficial intestinal bacteria especially Bifidobacteria (37). It was once again verified from our results that the number of Bifidobacteria on day 28 and SIgA mRNA level had positive correlation (Fig. 4B).

Unintended effects and unexpected effects are the most important in the safety assessment of GMM (4). “Unintended effects” refer to a statistically significant difference in the phenotype, response compared with the parent from which it is derived, except taking the expected effect of the target gene into account. The approaches used in the safety assessment of GMM have been developed in collaborative work with international agencies (38, 39); however, substantial equivalence has always been regarded as the first step for unintended effects (4). The principle of “substantial equivalence” became a key element in the safety assessment of foods derived from genetically modified organisms from the beginning the 1990s (39). The concept is used to identify similarities and differences between the genetically modified food and a comparator with a history of safe use, which subsequently guides the safety assessment process (4).

In this study, on the basis of traditional subchronic experiment, we aimed at proof of the substantial equivalence of GM Lp 590 and non-GM Lp from the point of view of gut health. Gut health can be well-described by intestinal microbiota, theirmetabolites, gut permeability, and gut mucosal immunity (4, 25, 34). Beneficial Bifidobacteria made the above four parts to become an interrelated whole (25). Our results were supported by previous published reports (4, 25, 32, 34). The results of intestinal health were comparable with those from the traditional methods in the study.

CONCLUSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. Acknowledgements
  8. REFERENCES
  9. Supporting Information

In this study, based on subchronic test, intestinal microbiota, their metabolites, gut permeability, and gut mucosal immunity of the rats fed with GM Lp 590 and non-GM Lp were tested, analyzed, and discussed. And eventually we concluded that no significant differences between GM Lp 590- and non-GM Lp-fed groups. The conclusion of gut health was comparable with that from the traditional subchronic test. Evaluation of gut health including intestinal microbiota, their metabolites, gut permeability, and gut mucosal immunity will be a new approach of assessing the safety of GMM.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. Acknowledgements
  8. REFERENCES
  9. Supporting Information

The study was supported by the National GMO Cultivation Major Project of New Varieties (2009ZX08019-001B and 2009ZX08011-001B), and the authors express their gratitude to the Ministry of Science and Technology and the Ministry of Agriculture of China for financial support, respectively. All other product names, brand names, or company names are used for identification purposes only and may be (registered) trademarks of their respective owners.

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  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. Acknowledgements
  8. REFERENCES
  9. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. Acknowledgements
  8. REFERENCES
  9. Supporting Information

Additional Supporting Information may be found in the online version of this article.

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