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Modulation of the fecal microbiota in Sprague-Dawley rats using genetically modified and isogenic corn lines Penggao Li, Chun Yang, Rong Yue, Yaping Zhen, Qin Zhuo, Jianhua Piao, Xiaoguang Yang, and Rong Xiao J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b05285 • Publication Date (Web): 21 Dec 2017 Downloaded from http://pubs.acs.org on December 24, 2017

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Journal of Agricultural and Food Chemistry

Modulation of the Fecal Microbiota in Sprague-Dawley Rats Using Genetically Modified and Isogenic Corn Lines

Penggao Li †, ‡, Chun Yang †, ‡, Rong Yue§, Yaping Zhen∥, Qin Zhuo⊥,*, Jianhua Piao⊥, Xiaoguang Yang⊥, Rong Xiao †, ‡,*

†

School of Public Health, Capital Medical University, Beijing 100069, People’s Republic of China ‡

Beijing Key Laboratory of Environmental Toxicology, Beijing 100069, People’s Republic of China §

Yuncheng Central Hospital, Yuncheng, Shanxi 044000, People’s Republic of China

∥

Youanmen Clinical Detection Center, Capital Medical University, Beijing 100069, People’s Republic of China ⊥

Key Laboratory of Trace Element Nutrition NHFPC, Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, People’s Republic of China

*Correspondence: Q Zhuo, Tel: +86-10-66237240. Fax: +86-10-67711813. E-mail: [email protected] or [email protected], or R Xiao, Telephone/Fax: +86-10-83911512. E-mail: [email protected].

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ACS Paragon Plus Environment


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ABSTRACT:

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This study investigated the composition and proportions of fecal microbiota in

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Sprague-Dawley rats after consuming two genetically modified (GM) corn lines in

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comparison with the isogenic corn and the AIN93G standard feed for 10 weeks using

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bar-coded 16S rRNA gene sequencing. As a result, GM corn didn’t significantly alter

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the overall health and alpha-diversity of fecal microbiota. Fecal microbiota structures

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could be separated into non-corn and corn but not non-GM and GM corn subgroups.

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Both non-GM and GM corn caused the increase in bacterial populations related to

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carbohydrates utilization, such as Lactobacillus, Barnesiella and Bifidobacterium, and

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the reduction in potentially pathogenic populations, such as Tannerella and

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Moraxellaceae. In conclusion, similar effects on the fecal microbiota were observed

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after consuming a GM- and non-GM-corn-based diet for long periods. Further studies

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are warranted to elucidate the functional relevance of the changes in the proportions

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of bacterial populations in these diets.

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KEYWORDS: gut microbiota; genetically modified corn; diet; feces; rat

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INTRODUCTION

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Corn is a principal crop worldwide and is first among the grain crops in terms of

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production. It is widely used, directly and indirectly, as human food and animal feed

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in most countries. It is also an important raw material for various industries. As a

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result, the demand for this grain is increasing. Over the past two decades, to improve

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the production and quality of corn, genetic engineering with desired target genes has

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been extensively employed to produce transgenic corn cultivars with improved traits,

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and a great number of genetically modified (GM) corn lines have been

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commercialized. However, concerns over the safety of GM food consumption still

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exists.1 Although a scientific consensus that currently available food derived from

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GM crops poses no greater risk to human health than conventional food, 2-3 each GM

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food and its safety must be tested on a case-by-case basis before introduced to the

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market.4

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In recent years, it has been recognized that the gut microbiota plays an important

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role in maintaining the health of the host. Changes in the structure of the bacterial

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communities within the gastrointestinal tract have been implicated in many conditions,

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such as inflammatory bowel diseases, type 2 diabetes and brain abnormalities.5

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However, the composition of the gut microbiota is influenced by a myriad of

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exogenous factors, such as diet, antibiotic use and exercise.6-8 Among these

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exogenous factors, a long-term dietary pattern may play a significant role in shaping

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the gut microbial community.9-11 Thus, several studies have investigated the influence 4



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of GM corn on gut microbiota in different animal models and have provided valuable

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insights into the effects of GM corn on microbial communities.12-17 However, in these

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studies, the amount of the GM corn added to the animal feed was usually less than

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70%. Most studies only compared one GM corn cultivar with its non-GM counterpart,

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and some studies did not contain a blank control that consumed the standard feed.

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Additionally, many studies investigated only the short-term effects of consumption,

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which may not be informative because it may take six weeks of exposure for the

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intestinal microbiota to adapt to the feed structure.18

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Thus, in the present study, two GM corn cultivars, one herbicide-resistant cultivar

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carrying the endolpyruvylshikimate-3-phosphate synthase (EPSPS) and the

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phosphinothricin acetyl transferase (PAT) genes and one insect- and

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herbicide-resistant cultivar carrying the insecticidal Cry1Ab gene from Bacillus

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thuringiensis and EPSPS genes, in comparison with their common isogenic parental

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line and the standard AIN93G rodent chow, were investigated simultaneously to

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observe changes in the gut microbiota after 10 weeks of dietary intervention in

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Sprague-Dawley (SD) rats. The dietary pattern in early life is vital for shaping the gut

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microbial structure of an individual.19,20 Thus, weaning animals were used in the

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present study. Moreover, because the main objective was to observe the effects of the

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consumption of GM corn on the gut microbiota, as long as the nutritional needs of the

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animals were met, the percentage of the corn in their diet was as high as possible.

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After careful determination, calculation and comparison with the AIN93G standard

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feed, approximately 75% of the feed composition was replaced by corn flour without 5


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significantly changing the energy and nutrient composition of the feed. Thus, the

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percentages of the three corn flours in their respective feeds were all greater than 75%

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in the present study.

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MATERIALS AND METHODS

Animals.

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All animal work was performed according to the guidelines of the Institutional

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Animal Care and Use Committee and a local veterinary office. The experimental

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protocol was approved by, and a license (No. 20141011) obtained from, the

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Experimental Animal Ethics Committee of the Institute for Nutrition and Food Safety,

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Chinese Center for Disease Control and Prevention. All animal experiments were

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strictly supervised to ensure that the animals were treated humanely and their needs

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for habitat, food type and food supply mode, as well as their olfactory, entertainment,

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training and social needs were met according to the relevant guidelines. Forty (20

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female and 20 male) 4-week-old weaning Sprague-Dawley (SD) rats with body

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weights of 60–80 g were purchased from Beijing HFK Bioscience Co., Ltd (Beijing,

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China) and housed in a specific pathogen-free animal experiment center at the

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Chinese Center for Disease Control and Prevention. The rats were housed at

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24 °C±2 °C with 65%±5% humidity on a 12h light/dark cycle with free access to feed

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and water. After one week of adaption, they were randomly and evenly assigned to

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four groups to receive different feeds for 10 weeks. Five animals of the same group

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and same sex were housed in one regular rat cage when they were young and then

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separated to two cages when they grow older. All animals were monitored daily for

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abnormalities and mortality. The abnormality signs include, but were not limited to,

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changes in skin, fur, eyes and mucous membranes, as well as the occurrence of 7


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secretions and excretions, and autonomic activities (e.g. unusual respiratory patterns).

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Other abnormalities were behavioral, such as changes in gait, posture and response to

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handling, as well as the presence of clonic or tonic movements, stereotypy (e.g.

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excessive grooming and repetitive circling) or bizarre behaviors (e.g. self-mutilation

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and walking backwards). The body weight of each animal was recorded once a week.

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Average food consumption for each animal was determined twice a week by

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subtracting the amount remaining from the initial amount provided for each cage and

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then dividing the days and the number of the animals in the cage. After 10 weeks of

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dietary intervention, fresh feces of each animal were collected in sterile tubes and

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stored at −80 °C immediately.

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Feeds.

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The herbicide-resistant corn carrying the EPSPS and PAT genes (C0010.3.7), the

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insect- and herbicide-resistant corn carrying the Cry1Ab and EPSPS genes

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(C0030.3.5), and their parental non-GM counterpart (DBN318) were used in the

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current work. The expression of the EPSPS protein imparts the tolerance to the

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herbicide glyphosate. The expression of the PAT gene imparts the tolerance to the

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herbicide phosphinotricin (glufosinate). The C0030.3.5 corn has been engineered to

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express the insecticidal Cry1Ab protein from B. thuringiensis to resist crop damage

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caused by insects. It was also transformed with the EPSPS gene to provide

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herbicide-resistant capabilities. The two GM corn lines were produced by Beijing

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DBN Biotech Co., Ltd. (Beijing China) using Agrobacterium-mediated 8



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transformations. Both the GM corn lines and their parental corn were simultaneously

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cultivated in adjoining plots in the experimental field of Yitong Manchu Autonomous

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County, Siping City, Jilin Province, P. R. China. They were planted and raised under

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identical conditions, and were harvested and stored in the same way. The presence of

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the Cry1Ab, EPSPS and PAT transformation cassettes was confirmed by PCR using

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standard protocols.

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The nutritional compositions of the corn lines (supplementary Table S1) were

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determined and compared with that of the AIN93G standard feed to determine which

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ingredient was needed to make all of the feeds used in the current experiment meet the

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specifications of the AIN93G standard feed, which was used as a negative control in

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the present study. The formulas of the corn-based feeds are provided in supplementary

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Table S2. The percentages of the flour powders from DBN318, C0010.3.7 and

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C0030.3.5 corn in the feeds were 75.0%, 76.5% and 76.2%, respectively. After

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mixing, all feeds were pelleted by the Beijing HFK Bioscience company (Beijing,

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China), and then vacuum-packed and sterilized by gamma-irradiation. The final

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compositions of the feeds were determined again to ensure that they met the

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specifications of AIN93G as shown in supplementary Table S3.

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Fecal DNA Extraction and PCR Amplification.

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Genomic DNA was extracted from 0.18 to 0.22 g of stool using the E.Z.N.ATM

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Mag-Bind Soil DNA Kit (Omega Bio-tek, Norcross, GA, USA) according to

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manufacturer’s protocol. The V3–V4 regions of the bacterial 16S ribosomal RNA 9


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genes were amplified by PCR (94 °C for 3 min, followed by 5 cycles at 94 °C for 30 s,

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45 °C for 20 s and 65 °C for 30 s and another 20 cycles at 94 °C for 20 s, 55 °C for 20

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s and 72 °C for 30 s, with a final extension at 72 °C for 10 min, using primers 341F

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5′-CCCTACACGACGCTCTTCCGATCTG-barcode-CCTACGGGNGGCWGCAG-3′

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and 805R

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5′-GACTGGAGTTCCTTGGCACCCGAGAATTCCAGACTACHVGGGTATCTAAT

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CC-3′. An 8-bp barcode sequence unique to each sample was attached to primers for

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multiplexing. PCRs were performed in triplicate in 50-µL reaction mixtures

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containing 5 µL of 10× PCR buffer, 0.5 µL of 10 mM dNTPs, 10 ng of genomic DNA,

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0.5 µL of each primer (50 µM) and 0.5 µL of Plantium Taq polymerase (5 U/µL). The

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PCR products were separated with 1.2% agarose gel electrophoresis and bands of the

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desired size (> 600 bp) were purified using the SanPrep DNA Gel Extraction Kit

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(Sangon Biotech, Shanghai, China) according to the manufacturer’s instructions.

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Illumina MiSeq Sequencing.

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Samples were sent to the Sangon Biotech Co., Ltd. (Shanghai, China) for

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sequencing. The DNA concentration of each PCR product was determined using

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Qubit2.0 DNA (Life Tech, CA, USA) before sequencing. Equimolar purified products

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were pooled and paired-end sequenced (2 × 300) on an Illumina MiSeqPE300

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platform according to the standard protocol at Sangon Biotech.

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Bioinformatics Analysis.

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Demultiplexing and quality-filtering of the raw fastq files were performed using

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QIIME (version 1.8.0).21 An operational taxonomic unit (OTU)-based method was

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performed to analyze where sequences were split into bins based on taxonomy. They

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were clustered into each bin using a cutoff point of 0.05. UPARSE was used to cluster

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OTUs with a 97% similarity cutoff level, and UCHIME was applied to identify and

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remove chimeric sequences. The phylogenetic affiliation analysis of each 16S rRNA

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gene sequence was introduced by RDP Classifier against the SILVA (SSU115) 16S

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rRNA database with a confidence threshold of 70%.22 An alpha-diversity analysis was

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applied to analyze the complexity of the species’ diversity through several indices,

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including Richness, Shannon, Coverage and Simpson. Estimators of community

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richness, evenness and diversity were calculated based on OTUs (97% similarity).

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The overall microbiota’ dissimilarities among all of the samples were accessed using

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the weighted principal coordinates analysis by the R package (R 3.0.2). The heatmap

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construction and clustering analysis were also performed using the R package. Data

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are expressed as mean ± standard deviation. A statistical analysis of differences

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among groups was performed by one-way ANOVA using SPSS Statistics 18.0 (IBM,

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New York, USA), and P < 0.05 was considered statistically significant.

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RESULTS

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Health and Behavioral Features.

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During the experiment, rats in all of the groups were in good general health with no

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abnormalities in skin, fur, eyes or mucous membranes, no abnormities in secretion,

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excretion or autonomic activities, no changes in gait, posture or response to handling,

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and no other abnormal behaviors, such as clonic or tonic movements, excessive

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grooming, repetitive circling, self-mutilation, or walking backwards. Figure 1 shows

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that the daily feed intakes of the rats eating corn-based feeds were relatively higher

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than those of rats eating the standard chow along the intervention; these differences

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were more evident in females than in males. Generally, the rats eating the non-GM

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corn had the highest intakes and the rats eating the standard chow had the lowest

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intakes, with the rats eating the two GM corn lines between them. In spite of this, the

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body weights of the rats from the four feeding groups were not significantly different

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from each other throughout the experimental period, indicating that their growth was

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not affected by the differences in the feeds.

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Microbial Richness and Diversity Differences Owing to Diet.

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The Illumina MiSeq PE300 high-throughput 16S rRNA sequencing provided 361,351

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usable sequence reads, with a mean length of 413.2 ± 10.3 bp, that were obtained

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from 20 fecal samples from female rats, corresponding to 686 OTUs, with an average

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of 329 ± 61 per biological sample at a similarity level of 97%. Each sample was 12



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covered by an average of 18,068 reads. For male rats, 441,844 usable sequence reads,

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with a mean length of 413.1 ± 12.3 bp, were obtained from 20 fecal samples,

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corresponding to 634 OTUs, with an average of 333 ± 39 per biological sample at a

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similarity level of 97%. Each sample was covered by an average of 22,092 reads. The

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raw sequencing data have been uploaded to the NCBI SRA database (accession No.

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SRX3299851). The coverage indices for all of the samples were above 0.99,

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indicating that the depth of sequencing was sufficient. The flattening of the rarefaction

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curve based on the values of species richness (OTU number) and Shannon indices

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(supplementary Figure S1) indicated that our data volume covered all species in the

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fecal samples’ communities. Figure 2 shows that the alpha-diversity indices, including

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the species richness, the Shannon and the Simpson indices, were slightly higher in the

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corn-fed groups but were not significantly different among the four dietary groups (P >

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0.05). This indicates that the microbial richness and diversity in the feces of the

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GM-corn-fed rats did not significantly change in comparison with the non-GM-corn

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and the standard-chow-fed rats.

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Effects of Dietary GM and non-GM Corn Intake on Gut Microbial Community

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Structure.

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The weighted principal coordinate analysis plot in Figure 3A shows that in female

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animals, 43.4%, 23.6% and 8.2% of variation could be explained by PC1, PC2 and

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PC3, respectively, and most samples from corn-fed rats had a negative PC1 value,

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while most samples from the standard feed group had a positive PC1 value. Figure 3B 13


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shows that in male animals, 48.0%, 18.4% and 9.8% of variation could be explained

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by PC1, PC2 and PC3, respectively, and most samples from corn-fed rats had a

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negative PC2 value, while most samples from the standard feed group had a positive

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PC2 value. Samples from the GM- and non-GM-corn-fed rats were interspersed

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among each other with no clear distribution pattern to separate them from each other,

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suggesting that the microbiota structures of the rats consuming the GM corns were not

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significantly different from that of the non-GM-corn-fed rats. The similarities among

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the fecal samples were further analyzed by the hierarchically clustered heatmap

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analysis (Figure 3, right panel), which showed that samples from the GM- and

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non-GM-corn-fed rats could not be clearly clustered into separate subgroups and that

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the composition and relative abundances of the predominant gut bacterial genera were

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very similar among individuals from the different feeding groups.

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Fecal Bacterial Taxonomic Compositions in Rats Consuming Different Feeds.

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Although it was hard to clearly distinguish the microbiota community structures of the

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GM- and non-GM-corn-fed rats, there were differences in the relative abundance

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levels of the fecal bacteria. An outline of the relative abundance levels of the bacterial

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populations at different taxonomic levels are presented in supplementary Table S4–S8

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to show the influence of the different diets. As shown in Figure 4, distribution

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histograms of the taxonomic composition of each sample from the respective groups

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at the phylum and genus level were constructed. 9 and 10 different bacterial phyla

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were identified in male and female rats, respectively. In accordance with previous 14



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reports, Firmicutes, Bacteroidetes, Actinobacteria, Proteobacteria and

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Verrucomicrobia were the major phyla in all of the samples. Lactobacillus,

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Barnesiella, Ruminococcus, Bacteroides, Clostridium XI and Clostridium XlVa were

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the predominant genera in all of the samples. Figure 4 also shows that the different

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bacterial genera were more evenly distributed in the feces of the rats eating the

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standard feed than in those eating a corn-based diet. The dominant bacteria appeared

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to become more predominant after dietary intervention with corn, indicating that

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consuming a large amount of corn for a long period of time might facilitate the growth

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of the already dominant bacterial populations in the gut. And, compared with the

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standard feed, the similarities of the gut microbiota patterns among the three different

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groups of corn-fed rats could be partly attributed to similar changes occurring in the

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abundance levels of the main gut bacteria in the three groups of rats fed corn. The

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Firmicutes/Bacteroidetes ratio also showed a tendency to decrease in both sexes for

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all of the corn-fed groups, although differences were not statistically significant owing

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to the high inter-individual variances (supplementary Tables S4).

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The relative proportion of phyla and genera as depending on the types of the diets

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differed between males and females. As shown in Figure 5, in female animals, the

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abundance levels of the major phyla were not significantly different among the four

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feeding groups. However, in male animals, in comparison with the standard feed

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group, the proportion of Firmicutes in the C0030.3.5 group decreased significantly

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(59.59 vs. 80.25%, P < 0.05), and the proportions of Verrucomicrobia and Candidatus

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Saccharibacteria increased significantly in the DBN318 group (5.74% and 1.85% vs. 15


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0.32% and 0.19%, respectively, P < 0.05).

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At the genus level, 119 and 120 different bacterial populations were identified in

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the female and male animals, respectively. The proportions of 29 and 28 genera were

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significantly different among the four dietary groups in female and male rats,

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respectively (supplementary Tables S8). Compared with the standard feed,

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Lactobacillus, the largest genus in all of the fecal samples, showed an increase after

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corn-feeding (Figure 5), which was significant in the C0030.3.5 group of female rats

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(36.13 vs. 12.02%, P

Modulation of the Fecal Microbiota in Sprague ... - ACS Publications

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