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Gut microbiota community adaption during young children fecal microbiota transplantation by 16s rDNA sequencing
Author’s Accepted Manuscript Gut microbiota community adaption during young children fecal microbiota transplantation by 16s rDNA sequencing Jian-Lei Gu, Yi-Zhong Wang, Shi-Yi Liu, GuangJun Yu, Ting Zhang, Hui Lu www.elsevier.com/locate/neucom
PII: DOI: Reference:
S0925-2312(16)30427-1 http://dx.doi.org/10.1016/j.neucom.2016.01.095 NEUCOM17067
To appear in: Neurocomputing Received date: 31 August 2015 Revised date: 15 November 2015 Accepted date: 17 January 2016 Cite this article as: Jian-Lei Gu, Yi-Zhong Wang, Shi-Yi Liu, Guang-Jun Yu, Ting Zhang and Hui Lu, Gut microbiota community adaption during young children fecal microbiota transplantation by 16s rDNA sequencing, Neurocomputing, http://dx.doi.org/10.1016/j.neucom.2016.01.095 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Gut microbiota community adaption during young children fecal microbiota transplantation by 16s rDNA sequencing Jian-Lei Gu1,4,&, Yi-Zhong Wang2,&, Shi-Yi Liu3,4, Guang-Jun Yu6* ,Ting Zhang*2, Hui Lu*1,5 1 Shanghai Institute of Medical Genetics, Shanghai Children’s Hospital, Shanghai Jiao Tong University, Shanghai 200040, China 2 Department of Gastroenterology, Shanghai Children’s Hospital, Shanghai Jiao Tong University, Shanghai 200040, China 3 Department of Bioinformatics and Biostatistics, School of life science and biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China 4 Key Laboratory of Molecular Embryology, Ministry of Health & Shanghai Key Laboratory of Embryo and Reproduction Engineering. Shanghai 200040, China 5 Department of Bioengineering, Bioinformatics Program, University of Illinois at Chicago, Chicago, IL 60607, USA 6 Department of Children’s Healthcare, Shanghai Children’s Hospital, Shanghai JiaoTong University, Shanghai 200040, China *Corresponding authors &These authors contributed equally to this work Abstract Fecal microbiota transplantation (FMT) is to restore the intestinal environment of a diseased individual by using of intestinal microbiota from a healthy donor. In recent years, FMT has been developed into a useful treatment method for various chronic gastrointestinal disease. There are already some works attempt to explain the mechanism of this treatment for gastrointestinal diseases in adult patients. However, much less effort has been focused on pediatric gastrointestinal disorders. In this work, we have invited 3 young children with chronic immune-mediated gastrointestinal disorders treated by FMT surgery, and systematically investigated their temporal changes of fecal microbiota after transplantation by 16s rDNA sequencing technology. According to our observations, the fecal microbiota composition of these patients appears obviously interindividual variability and the fecal transplantation significantly increased the species richness in these young patients. The species abundance of Pasteurellaceae was remarkably increased during the FMT treatment in all three patients.
Key words: Intestinal microbiota; fecal microbiota transplantation; 16s rDNA; pediatric disease; intestinal dysbiosis Introduction The human gut is colonized by a highly diverse community of microorganisms that play a critical symbiosis with their host, including energy metabolism, immunity and nervous system [1, 2]. Studies of the intestinal microbiota imply that an unbalanced microbial community is associated with the pathogenesis of gastrointestinal symptoms. Growing evidence supported that fecal microbiota transplantation could reestablish the balance of gut microbiota community and is an effective treatment against several gastrointestinal symptoms, best known as a treatment for recurrent Clostridium difficile infection (CDI)[3], current studies suggested it is also promising results with many other digestive or auto-immune disease, including inflammatory bowel disease (IBD), Irritable Bowel Syndrome (IBS), and Ulcerative Colitis (UC) [4]. It is reported that intestinal gut microbiota appears various bacterial richness and diversity among different diseases [5, 6]. The microbiota community studies in CDI indicated that compared with healthy controls, the patients had an initial CDI appears a progressive decrease in species diversity and reduction of Bacteroidetes and Firmicutes phylum in their fecal samples[3]. A larger cohort study of pediatric Crohn’s Disease imply that a set of microorganism taxa associated with disease status, it is might be a bacterial biomarker for early diagnosis [7]. Fecal microbiota transplantation (FMT) is transplantation of a fecal suspension from a healthy donor into the gastrointestinal tract of patient, and to reestablish the balance of intestinal microbiota community of patient. Although FMT has been most accepted treatment for the intestinal microbiota dysbiosis, but the mechanism is still not entirely clear. More research is needed to investigate and understand the dynamic changes of intestinal microbiota community during the FMT treatment, and especially in children patients because children is more impressionable to environmental factors than adult. Gut microbiota studies are commonly performed by analyzing the 16s ribosomal DNA gene (16s rDNA), and it is also current golden standard for microbial community analysis [8, 9]. In present study, we applied 16s rDNA sequencing analysis to profile the fecal microbiota community from 3 young children with Juvenile idiopathic arthritis, Ulcerative colitis or Hemophagocytic syndrome .The aim of this study was to characterize the changes of microbiota community before and after the FMT for these young children.
Material and Methods Patient Information and feces sample process Three young children (1 female, 2 male; aged 19 to 40 months) with immune-imbalance related chronic diseases were planning to undergo FMT surgery at Dept of Gastroenterology at Shanghai Children’s Hospital, and invited to participate in this study. The Shanghai Children’s Hospital review board approved this study and we obtained written informed consent for this study from their guardians. Before donating the feces, the two healthy adult donors were screened following test: HIV1/2 antibodies, treponemal antibody, Hepatitis A IgM antibody, Hepatitis B surface antigen, Hepatitis B core antibody and Hepatitis C antibody. The information of patients and donors were listed in Table 1. The collection and analysis of these feces samples were approved by Shanghai Children’s Hospital. The clinical protocol for the allocation of a donor as the feces for FMT was determined by clinic doctors. Feces samples from each donor were collected in standard containers and frozen at -20℃. The first infusion for FMT surgery was administered into the cecum through nasal jejunal feeding tube. To assess the changes of microbiota community during the FMT treatment, feces samples were collected from the patients at enrolment (before FMT), the first feces after FMT (1-3 day), then at 1 and 2week after the FMT treatment were completed. Table 1. Patient information
Sample
Gender
Age*
D01 Female 35 ys D03 Female 28 ys R01A 40 m R01C Male R01F R01G R02A 19 m R02C Female R02F R02G R07A R07E Male 37 m R07F R07G * ys: years. M: month
Sample Info Donor
Disease Info
FMT Info
Healthy donor
Patient01 Donor:D01
Juvenile idiopathic arthritis
Patient02 Donor:D03
Ulcerative colitis (inflammatory bowel disease)
Patient07 Donor:D01
Hemophagocytic Syndrome
before FMT 1 day after FMT 1 week after FMT 2 week after FMT before FMT 1 day after FMT 1 week after FMT 2 week after FMT before FMT 3 day after FMT 1 week after FMT 2 week after FMT
DNA extraction and sequencing libraries construction Total DNA of feces samples were extracted by the QIAamp DNA Feces Mini kit according to the manufacturer’s protocol. DNA concentrations were determined using Microplate Reader (QubitFluorometer, Invitrogen). DNA integrity and purification is detected by Agarose Gel Electrophoresis (Concentration of Agarose Gel: 1%, Voltage: 150 V, Electrophoresis Time:40 min). The genomic DNA of fecal samples were sent to the Beijing Genomics Institute (BGI) in Shenzhen to construct the 16s rDNA V6 library and sequencing. The total genomic DNA samples after quality control procedure were used for PCR amplification by the V6 primers and PCR master mix. Forward primer: CAACGCGAAGAACCTTACC and Reverse primer: CGACAGCCATGCANCACCT. Purify the PCR products DNA with QIAquick PCR Purification Kit (Qiagen) and then combined with End Repair Mix, incubate at 20℃ for 30 min. Purify the end-repaired DNA with QIAquick PCR Purification Kit (Qiagen), then add A-Tailing Mix, incubate at 37℃ for 30 min. Combine the purified Adenylate 3'Ends DNA, Adapter and Ligation Mix, incubate the ligation reaction at 16℃ for 12-16 hours. Adapter-ligated DNA is selected by running a 2.5% agarose gel for about 2.5 to 3h to recover the target fragments. Purify the gel with QIAquick Gel Extraction kit (QIAGEN). Purify the gel with QIAquick Gel Extraction kit (QIAGEN). The sequencing libraries were validated and quantitated by Agilent 2100 bioanalyzer (Agilent DNA 1000 Reagents) and real-time quantitative PCR (TaqMan Probe). The Qualified libraries will amplify on cBot to generate the cluster on the flow-cell. And the amplified flow-cell will be sequenced on the HiSeq 2000 System with 101 bp paired end strategy. Bioinformatics procedure Clean data were generated after trimming and removing reads with low quality (short than 55bp), and then, PE (paired end sequencing strategy) reads were overlapped to full V6 tags with a minimum overlap length of 30bp. In order to reduce the computational complexity, the redundant tags were calculated and masked by Mothur (Version 1.27.0) [10]. The rest of unique tags were pre-clustered by single-linkage pre-clustering (SLP) following 98% similarity by Mothur to acquire the target Operational Taxonomic Units (OTUs). The unique tags were aligned against the SILVA database by BLAST program (version 2.2.23) [11, 12]. Taxonomic classification was performed using a two-thirds (66%) majority rule [13]. The limitation of OTUs based taxonomic classification, most tags of each sample were annotated with different phylogenetic level, and a few tags were assigned to genus and lower phylogenetic level. To sufficiently utilize annotation information, subsequent analysis was conducted at the phylum and family phylogenetic level. To estimates the species richness and diversity of fecal microbiota, the rarefaction curve and alpha diversity indices, including the species richness (Chao1) and species
diversity index (Simpson index), were also calculated by Mothur. The sequencing and standard bioinformatics data processing was provided by BGI in Shenzhen.
Results and Discussion Using Illumina Hiseq 2000 sequencing platform, a total of 1.4 Gb clean data was generated from 14 samples involving 3 young children patients with different sampling time-point for each patient covered pre-FMT to post-FMT treatment and 2 healthy adult donors, the detailed information of samples listed in Table 1. After removing low quality reads, 776 Mb clean sequencing data were produced. These sequencing reads were pre-assembled and then clustered into operational taxonomic units (OTUs) that contain similar sequences. As a result, an average of 2,376 unique assembled tags and 452 OTUs were obtained in each sample. The summarized information of 16s rDNA sequencing was listed in Table 2. To evaluate the sequencing depth and the species richness, a rarefaction curve was constructed for each sample. The curves suggested that sequencing depth was enough to cover most of the bacteria in fecal samples (Supp Fig 1). As the Fig 1 shown, alpha diversity measurement for 14 samples suggested variations in species richness (Chao1) and diversity (Simpson index) among these samples. The rarefaction curve and alpha diversity shown the patient 01 have relative higher species richness, while the patient 02 has lowest species richness. As expected, the species richness of all three individuals remarkably increased after FMT surgery, but it is appears to drop as the day increase. Surprisingly, the species diversity of these three individuals did not exhibit similar “increase-drop” pattern. Interestingly, in the patient 02 and patient 07, we observed remarkably reduction of species diversity after FMT surgery, furthermore, the species richness were significantly increased. Table 2. The summary of 16s rDNA sequencing and OTU clustering Sample Raw Clean Number of Number of Number name data(Mb) data(Mb) Tagsa unique Tags of OTU 113.89 53.26 69,717 2,324 430 D01 107.24 49.01 70,527 2,025 368 D03 102.26 58.8 71,181 2,983 676 R01A 91.88 52.62 69,191 3,122 950 R01C 95.22 54.07 69,824 3,182 599 R01F 100.22 57.76 70,584 2,214 676 R01G 97.28 54.52 68,802 1,608 168 R02A 103.55 58.39 71,136 2,183 353 R02C 96.33 55.57 70,992 2,435 346 R02F 122.13 58.37 70,958 1,097 222 R02G 102.58 48.51 69,628 1,838 263 R07A 100.19 58.22 71,286 2,972 527 R07E 104.17 59.59 68,872 2,614 391 R07F
100.4 57.43 69,961 2,661 361 R07G a The PE reads were assembled to tags according to their paired end relations.
The fecal microbiota community of healthy donors and children patients According to the alpha diversity, two healthy adult donors have similar species richness level, but distinct species diversity level, of which, the donor D03 have higher species diversity than donor D01. It is indicated that the higher diversity of donor D03 might be resulting from lower species evenness instead of lower species richness. The alpha diversity also suggested significant variations in species richness and diversity among different young children. When we examined species composition and abundance of fecal samples, we found that the two adult donors, family level (phylogenetic level) microbiota assignments showed that the Pearson correlation of species composition (the number of OTUs belong to each taxonomic unit) is over 0.9, but the correlation of species abundance (Tags percentages in each taxonomic unit) is only 0.4 (Fig 2). For this extremely low correlation level, one explanation is a relative large number of sequencing tags were annotated by higher phylogenetic levels than family level in donor D03, such as phylum, order or class, then resulting abnormal distribution of species abundance in donor D03. An average correlation of species composition is 0.9, while 0.8 for species abundance were observed among young children. It is indicated that the species composition might be more reliable and stable than species abundance among different individuals. The correlation analysis of species composition and abundance among all fecal samples also supported this observation (Supp Fig 2).
The dynamic changes of fecal microbiota community after FMT To determine whether the microbiota changed in species composition at the follow-up time points, we analyzed the variance of species richness and abundance during FMT treatment. As shown in Supp Table 1, Fig 4 and Supp Fig 3, the species richness and abundance of microbiota community both at the phylum and family level were observed in all samples after FMT surgery. At phylum level, although Firmicutes appears highest species richness in all fecal samples, the species abundance suggested that Bacteroidaceae and Proteobacteria often have lager population size, for example Bacteroidaceae in donor D03 and Proteobacteria in R02G. At family level, Lachnospiraceae, Ruminococcaceae and Bacteroidaceae were the most dominant species almost all fecal samples (Fig 4 and Supp Fig 3). As the view of ecosystem, these dominant species are often crucial in perpetuating the gut environment, and the dynamic changes of species within this ecosystem closely linked with the changes of environment. In order to gain greater insights into the dynamic changes of gut microbiota after FMT surgery, we performed heatmap clustering for microbiota
abundance data and identified various dynamic patterns of gut microbiota alterations after FMT surgery (Fig 5). Interestingly, the species abundance of Pasteurellaceae exhibit similar pattern in all three patients. It is increased after FMT surgery, but dropped in the treatment complete. But it is reported that the young Crohn’s patients has increased abundance in the species Pasteurellaceae [7]. It is indicated that Pasteurellaceae might be play underlying role for aberrant immune responses to intestinal microbiota, but more study is needed. The possible mechanisms exerted by transplanted species may change the micro-environment of gut, competition for nutrients, secretion of antimicrobial compounds and induction of the production of antimicrobial compounds by the host. Further study is required to investigate which species in the FMT can re-establish the intestinal microbiota community.
Conclusion From this study, some results have shown that FMT surgeries can change the species richness of the gut microbial community, but the bacterial spectrum of fecal samples exhibit strong stability along with the FMT surgeries. 16s rDNA sequencing reports displayed that some species may change sharply after FMT surgeries. However, only with the 16s rDNA data, the results can’t tell what had happened after FMT surgeries. A number of important questions are also raised by these findings. For example, we observed the population explosion of Pasteurellaceaein after FMT surgeries in all three young patients, whether the Pasteurellaceae are closely related to the treatment outcome remains unclear. Acknowledgements This work is supported in part by the National Natural Science Foundation of China (No.31071167 and No.31370751), Shanghai Municipal Commission of Health and Family Planning (Grant No. 201440434, No.20144Y0179 and No.20144Y0175), Shanghai Key Projects for Basic Scientific Research (14JC1405700), Research and Innovation Project of High Level Talents in Putuo District of Shanghai (2014-A-20) and Natural Science Foundation of Shanghai (14ZR1434200), China. Figures legends: Fig 1. Alpha diversity of different fecal samples. Up panel is the species richness of microbiota (Chao1 index) and down panel is the species diversity of microbiota (Simpson index). The sample information listed in Table 1. Fig 2. Comparison of microbiota community between healthy donors. Left panel is the number of OTU (at Phylum level) in fecal samples, while right panel is the
estimated population size for each microorganism in fecal samples. Due to a number of tags annotated as higher phylogenetic level than family, only 50% tags of D03 sample were characterized at family level. The Firmicutes and Bacteroidetes are the most dominate species in the donor fecal samples. Fig 3. Comparison of fecal microbiota community among patients. Left panel is the number of OUT (at Phylum level) in the fecal sample, while right panel is the estimated population size of microorganism in the feces sample. Compared to healthy donor, patients appears highly variability of species spectrum and have decreased species richness and abundance in Bacteroidetes. Fig 4. The species composition of fecal samples at phylum and family level, A, C, E at Phylum level, B, D, F at Family Level. The species richness of fecal samples were remarkably reduced in recurrent severe diarrhea children. The fecal transplantation significantly increased the species richness in these young patients. The detailed information about species composition and abundance were presented in Supp Table 1. Fig 5.The dynamic changes in microbiota population during FMT surgery. A panel is patient 01, B panel is patient 02 and C panel is patient 07.The four columns of heatmaps represented four time-point for each patient, they are pre-FTM, 1 day (or 3 day for patient 07) after FMT, 1 week after FMT and 2 week after FMT. And each row is the sequencing tags proportion for each microorganism. The sequencing tags proportion data were scaled by row.
Figures:
Fig 1.
Fig 2.
Fig 3.
Fig 4.
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Supp Fig 1. Rarefaction curves of 16s rDNA sequences from fecal microbiota. The plot shows the number of OTUs as the number of sequencing reads re-sampled.
Supp Fig 2. Correlation analysis （Pearson） of species composition and abundance among fecal microbiota samples at family level. Left panel is the correlation of species composition, while right panel is the correlation of species abundance in the fecal samples. D is donor, A is before FMT fecal sample, C is 1 day or 3 day after FMT, F is 1week after FMT, G is 2 week after FMT.
Supp Fig 3. The species abundance of fecal samples at family level. The y-axis is the estimated population proportion, and different filled-boxes donated different microorganisms. The detailed abundance information of each OTU taxa listed in Supp Table 1.
Author information
Jianlei Gu, Master, Assistant professor Shanghai Children's Hospital, Shanghai Jiao Tong University. 2008.9-2011.7, Master of microbiology science, Fudan University. 2004.09-2008.7, Bachelor of biological engineering, China University of Mining and Technology
Yizhong Wang, Ph.D, Assistant professor Shanghai Children's Hospital, Shanghai Jiao Tong University. 2009.09-2010.06, Postdoctoral fellow, Division of Gastroenterology, University of Utah School of Medicine. 2010.07-2014.02, Postdoctoral fellow, Department of Pathology and Laboratory Medicine, Temple University School of Medicine.
Shiyi Liu, graduate student, Shanghai Jiaotong University
Guangjun Yu, Ph. D, professor, president of Shanghai Children's Hospital, Shanghai Jiaotong University
Ting Zhang, MD, director of gastroenterology department, Shanghai Children's Hospital, Shanghai Jiaotong University
Hui Lu, Ph. D, professor Hui Lu obtained PhD degree from University of Illinois, and currently at Shanghai Jiao Tong University and Shanghai Children’s Hospital. Education History: 1994/08 - 1999/10, University of Illinois , PhD
1992/01 - 1994/07, University of Massachusetts, physics, Master 1987/09 - 1991/08, Peking University, mathematics and physics, bachelor
PII: DOI: Reference:
S0925-2312(16)30427-1 http://dx.doi.org/10.1016/j.neucom.2016.01.095 NEUCOM17067
To appear in: Neurocomputing Received date: 31 August 2015 Revised date: 15 November 2015 Accepted date: 17 January 2016 Cite this article as: Jian-Lei Gu, Yi-Zhong Wang, Shi-Yi Liu, Guang-Jun Yu, Ting Zhang and Hui Lu, Gut microbiota community adaption during young children fecal microbiota transplantation by 16s rDNA sequencing, Neurocomputing, http://dx.doi.org/10.1016/j.neucom.2016.01.095 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Gut microbiota community adaption during young children fecal microbiota transplantation by 16s rDNA sequencing Jian-Lei Gu1,4,&, Yi-Zhong Wang2,&, Shi-Yi Liu3,4, Guang-Jun Yu6* ,Ting Zhang*2, Hui Lu*1,5 1 Shanghai Institute of Medical Genetics, Shanghai Children’s Hospital, Shanghai Jiao Tong University, Shanghai 200040, China 2 Department of Gastroenterology, Shanghai Children’s Hospital, Shanghai Jiao Tong University, Shanghai 200040, China 3 Department of Bioinformatics and Biostatistics, School of life science and biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China 4 Key Laboratory of Molecular Embryology, Ministry of Health & Shanghai Key Laboratory of Embryo and Reproduction Engineering. Shanghai 200040, China 5 Department of Bioengineering, Bioinformatics Program, University of Illinois at Chicago, Chicago, IL 60607, USA 6 Department of Children’s Healthcare, Shanghai Children’s Hospital, Shanghai JiaoTong University, Shanghai 200040, China *Corresponding authors &These authors contributed equally to this work Abstract Fecal microbiota transplantation (FMT) is to restore the intestinal environment of a diseased individual by using of intestinal microbiota from a healthy donor. In recent years, FMT has been developed into a useful treatment method for various chronic gastrointestinal disease. There are already some works attempt to explain the mechanism of this treatment for gastrointestinal diseases in adult patients. However, much less effort has been focused on pediatric gastrointestinal disorders. In this work, we have invited 3 young children with chronic immune-mediated gastrointestinal disorders treated by FMT surgery, and systematically investigated their temporal changes of fecal microbiota after transplantation by 16s rDNA sequencing technology. According to our observations, the fecal microbiota composition of these patients appears obviously interindividual variability and the fecal transplantation significantly increased the species richness in these young patients. The species abundance of Pasteurellaceae was remarkably increased during the FMT treatment in all three patients.
Key words: Intestinal microbiota; fecal microbiota transplantation; 16s rDNA; pediatric disease; intestinal dysbiosis Introduction The human gut is colonized by a highly diverse community of microorganisms that play a critical symbiosis with their host, including energy metabolism, immunity and nervous system [1, 2]. Studies of the intestinal microbiota imply that an unbalanced microbial community is associated with the pathogenesis of gastrointestinal symptoms. Growing evidence supported that fecal microbiota transplantation could reestablish the balance of gut microbiota community and is an effective treatment against several gastrointestinal symptoms, best known as a treatment for recurrent Clostridium difficile infection (CDI)[3], current studies suggested it is also promising results with many other digestive or auto-immune disease, including inflammatory bowel disease (IBD), Irritable Bowel Syndrome (IBS), and Ulcerative Colitis (UC) [4]. It is reported that intestinal gut microbiota appears various bacterial richness and diversity among different diseases [5, 6]. The microbiota community studies in CDI indicated that compared with healthy controls, the patients had an initial CDI appears a progressive decrease in species diversity and reduction of Bacteroidetes and Firmicutes phylum in their fecal samples[3]. A larger cohort study of pediatric Crohn’s Disease imply that a set of microorganism taxa associated with disease status, it is might be a bacterial biomarker for early diagnosis [7]. Fecal microbiota transplantation (FMT) is transplantation of a fecal suspension from a healthy donor into the gastrointestinal tract of patient, and to reestablish the balance of intestinal microbiota community of patient. Although FMT has been most accepted treatment for the intestinal microbiota dysbiosis, but the mechanism is still not entirely clear. More research is needed to investigate and understand the dynamic changes of intestinal microbiota community during the FMT treatment, and especially in children patients because children is more impressionable to environmental factors than adult. Gut microbiota studies are commonly performed by analyzing the 16s ribosomal DNA gene (16s rDNA), and it is also current golden standard for microbial community analysis [8, 9]. In present study, we applied 16s rDNA sequencing analysis to profile the fecal microbiota community from 3 young children with Juvenile idiopathic arthritis, Ulcerative colitis or Hemophagocytic syndrome .The aim of this study was to characterize the changes of microbiota community before and after the FMT for these young children.
Material and Methods Patient Information and feces sample process Three young children (1 female, 2 male; aged 19 to 40 months) with immune-imbalance related chronic diseases were planning to undergo FMT surgery at Dept of Gastroenterology at Shanghai Children’s Hospital, and invited to participate in this study. The Shanghai Children’s Hospital review board approved this study and we obtained written informed consent for this study from their guardians. Before donating the feces, the two healthy adult donors were screened following test: HIV1/2 antibodies, treponemal antibody, Hepatitis A IgM antibody, Hepatitis B surface antigen, Hepatitis B core antibody and Hepatitis C antibody. The information of patients and donors were listed in Table 1. The collection and analysis of these feces samples were approved by Shanghai Children’s Hospital. The clinical protocol for the allocation of a donor as the feces for FMT was determined by clinic doctors. Feces samples from each donor were collected in standard containers and frozen at -20℃. The first infusion for FMT surgery was administered into the cecum through nasal jejunal feeding tube. To assess the changes of microbiota community during the FMT treatment, feces samples were collected from the patients at enrolment (before FMT), the first feces after FMT (1-3 day), then at 1 and 2week after the FMT treatment were completed. Table 1. Patient information
Sample
Gender
Age*
D01 Female 35 ys D03 Female 28 ys R01A 40 m R01C Male R01F R01G R02A 19 m R02C Female R02F R02G R07A R07E Male 37 m R07F R07G * ys: years. M: month
Sample Info Donor
Disease Info
FMT Info
Healthy donor
Patient01 Donor:D01
Juvenile idiopathic arthritis
Patient02 Donor:D03
Ulcerative colitis (inflammatory bowel disease)
Patient07 Donor:D01
Hemophagocytic Syndrome
before FMT 1 day after FMT 1 week after FMT 2 week after FMT before FMT 1 day after FMT 1 week after FMT 2 week after FMT before FMT 3 day after FMT 1 week after FMT 2 week after FMT
DNA extraction and sequencing libraries construction Total DNA of feces samples were extracted by the QIAamp DNA Feces Mini kit according to the manufacturer’s protocol. DNA concentrations were determined using Microplate Reader (QubitFluorometer, Invitrogen). DNA integrity and purification is detected by Agarose Gel Electrophoresis (Concentration of Agarose Gel: 1%, Voltage: 150 V, Electrophoresis Time:40 min). The genomic DNA of fecal samples were sent to the Beijing Genomics Institute (BGI) in Shenzhen to construct the 16s rDNA V6 library and sequencing. The total genomic DNA samples after quality control procedure were used for PCR amplification by the V6 primers and PCR master mix. Forward primer: CAACGCGAAGAACCTTACC and Reverse primer: CGACAGCCATGCANCACCT. Purify the PCR products DNA with QIAquick PCR Purification Kit (Qiagen) and then combined with End Repair Mix, incubate at 20℃ for 30 min. Purify the end-repaired DNA with QIAquick PCR Purification Kit (Qiagen), then add A-Tailing Mix, incubate at 37℃ for 30 min. Combine the purified Adenylate 3'Ends DNA, Adapter and Ligation Mix, incubate the ligation reaction at 16℃ for 12-16 hours. Adapter-ligated DNA is selected by running a 2.5% agarose gel for about 2.5 to 3h to recover the target fragments. Purify the gel with QIAquick Gel Extraction kit (QIAGEN). Purify the gel with QIAquick Gel Extraction kit (QIAGEN). The sequencing libraries were validated and quantitated by Agilent 2100 bioanalyzer (Agilent DNA 1000 Reagents) and real-time quantitative PCR (TaqMan Probe). The Qualified libraries will amplify on cBot to generate the cluster on the flow-cell. And the amplified flow-cell will be sequenced on the HiSeq 2000 System with 101 bp paired end strategy. Bioinformatics procedure Clean data were generated after trimming and removing reads with low quality (short than 55bp), and then, PE (paired end sequencing strategy) reads were overlapped to full V6 tags with a minimum overlap length of 30bp. In order to reduce the computational complexity, the redundant tags were calculated and masked by Mothur (Version 1.27.0) [10]. The rest of unique tags were pre-clustered by single-linkage pre-clustering (SLP) following 98% similarity by Mothur to acquire the target Operational Taxonomic Units (OTUs). The unique tags were aligned against the SILVA database by BLAST program (version 2.2.23) [11, 12]. Taxonomic classification was performed using a two-thirds (66%) majority rule [13]. The limitation of OTUs based taxonomic classification, most tags of each sample were annotated with different phylogenetic level, and a few tags were assigned to genus and lower phylogenetic level. To sufficiently utilize annotation information, subsequent analysis was conducted at the phylum and family phylogenetic level. To estimates the species richness and diversity of fecal microbiota, the rarefaction curve and alpha diversity indices, including the species richness (Chao1) and species
diversity index (Simpson index), were also calculated by Mothur. The sequencing and standard bioinformatics data processing was provided by BGI in Shenzhen.
Results and Discussion Using Illumina Hiseq 2000 sequencing platform, a total of 1.4 Gb clean data was generated from 14 samples involving 3 young children patients with different sampling time-point for each patient covered pre-FMT to post-FMT treatment and 2 healthy adult donors, the detailed information of samples listed in Table 1. After removing low quality reads, 776 Mb clean sequencing data were produced. These sequencing reads were pre-assembled and then clustered into operational taxonomic units (OTUs) that contain similar sequences. As a result, an average of 2,376 unique assembled tags and 452 OTUs were obtained in each sample. The summarized information of 16s rDNA sequencing was listed in Table 2. To evaluate the sequencing depth and the species richness, a rarefaction curve was constructed for each sample. The curves suggested that sequencing depth was enough to cover most of the bacteria in fecal samples (Supp Fig 1). As the Fig 1 shown, alpha diversity measurement for 14 samples suggested variations in species richness (Chao1) and diversity (Simpson index) among these samples. The rarefaction curve and alpha diversity shown the patient 01 have relative higher species richness, while the patient 02 has lowest species richness. As expected, the species richness of all three individuals remarkably increased after FMT surgery, but it is appears to drop as the day increase. Surprisingly, the species diversity of these three individuals did not exhibit similar “increase-drop” pattern. Interestingly, in the patient 02 and patient 07, we observed remarkably reduction of species diversity after FMT surgery, furthermore, the species richness were significantly increased. Table 2. The summary of 16s rDNA sequencing and OTU clustering Sample Raw Clean Number of Number of Number name data(Mb) data(Mb) Tagsa unique Tags of OTU 113.89 53.26 69,717 2,324 430 D01 107.24 49.01 70,527 2,025 368 D03 102.26 58.8 71,181 2,983 676 R01A 91.88 52.62 69,191 3,122 950 R01C 95.22 54.07 69,824 3,182 599 R01F 100.22 57.76 70,584 2,214 676 R01G 97.28 54.52 68,802 1,608 168 R02A 103.55 58.39 71,136 2,183 353 R02C 96.33 55.57 70,992 2,435 346 R02F 122.13 58.37 70,958 1,097 222 R02G 102.58 48.51 69,628 1,838 263 R07A 100.19 58.22 71,286 2,972 527 R07E 104.17 59.59 68,872 2,614 391 R07F
100.4 57.43 69,961 2,661 361 R07G a The PE reads were assembled to tags according to their paired end relations.
The fecal microbiota community of healthy donors and children patients According to the alpha diversity, two healthy adult donors have similar species richness level, but distinct species diversity level, of which, the donor D03 have higher species diversity than donor D01. It is indicated that the higher diversity of donor D03 might be resulting from lower species evenness instead of lower species richness. The alpha diversity also suggested significant variations in species richness and diversity among different young children. When we examined species composition and abundance of fecal samples, we found that the two adult donors, family level (phylogenetic level) microbiota assignments showed that the Pearson correlation of species composition (the number of OTUs belong to each taxonomic unit) is over 0.9, but the correlation of species abundance (Tags percentages in each taxonomic unit) is only 0.4 (Fig 2). For this extremely low correlation level, one explanation is a relative large number of sequencing tags were annotated by higher phylogenetic levels than family level in donor D03, such as phylum, order or class, then resulting abnormal distribution of species abundance in donor D03. An average correlation of species composition is 0.9, while 0.8 for species abundance were observed among young children. It is indicated that the species composition might be more reliable and stable than species abundance among different individuals. The correlation analysis of species composition and abundance among all fecal samples also supported this observation (Supp Fig 2).
The dynamic changes of fecal microbiota community after FMT To determine whether the microbiota changed in species composition at the follow-up time points, we analyzed the variance of species richness and abundance during FMT treatment. As shown in Supp Table 1, Fig 4 and Supp Fig 3, the species richness and abundance of microbiota community both at the phylum and family level were observed in all samples after FMT surgery. At phylum level, although Firmicutes appears highest species richness in all fecal samples, the species abundance suggested that Bacteroidaceae and Proteobacteria often have lager population size, for example Bacteroidaceae in donor D03 and Proteobacteria in R02G. At family level, Lachnospiraceae, Ruminococcaceae and Bacteroidaceae were the most dominant species almost all fecal samples (Fig 4 and Supp Fig 3). As the view of ecosystem, these dominant species are often crucial in perpetuating the gut environment, and the dynamic changes of species within this ecosystem closely linked with the changes of environment. In order to gain greater insights into the dynamic changes of gut microbiota after FMT surgery, we performed heatmap clustering for microbiota
abundance data and identified various dynamic patterns of gut microbiota alterations after FMT surgery (Fig 5). Interestingly, the species abundance of Pasteurellaceae exhibit similar pattern in all three patients. It is increased after FMT surgery, but dropped in the treatment complete. But it is reported that the young Crohn’s patients has increased abundance in the species Pasteurellaceae [7]. It is indicated that Pasteurellaceae might be play underlying role for aberrant immune responses to intestinal microbiota, but more study is needed. The possible mechanisms exerted by transplanted species may change the micro-environment of gut, competition for nutrients, secretion of antimicrobial compounds and induction of the production of antimicrobial compounds by the host. Further study is required to investigate which species in the FMT can re-establish the intestinal microbiota community.
Conclusion From this study, some results have shown that FMT surgeries can change the species richness of the gut microbial community, but the bacterial spectrum of fecal samples exhibit strong stability along with the FMT surgeries. 16s rDNA sequencing reports displayed that some species may change sharply after FMT surgeries. However, only with the 16s rDNA data, the results can’t tell what had happened after FMT surgeries. A number of important questions are also raised by these findings. For example, we observed the population explosion of Pasteurellaceaein after FMT surgeries in all three young patients, whether the Pasteurellaceae are closely related to the treatment outcome remains unclear. Acknowledgements This work is supported in part by the National Natural Science Foundation of China (No.31071167 and No.31370751), Shanghai Municipal Commission of Health and Family Planning (Grant No. 201440434, No.20144Y0179 and No.20144Y0175), Shanghai Key Projects for Basic Scientific Research (14JC1405700), Research and Innovation Project of High Level Talents in Putuo District of Shanghai (2014-A-20) and Natural Science Foundation of Shanghai (14ZR1434200), China. Figures legends: Fig 1. Alpha diversity of different fecal samples. Up panel is the species richness of microbiota (Chao1 index) and down panel is the species diversity of microbiota (Simpson index). The sample information listed in Table 1. Fig 2. Comparison of microbiota community between healthy donors. Left panel is the number of OTU (at Phylum level) in fecal samples, while right panel is the
estimated population size for each microorganism in fecal samples. Due to a number of tags annotated as higher phylogenetic level than family, only 50% tags of D03 sample were characterized at family level. The Firmicutes and Bacteroidetes are the most dominate species in the donor fecal samples. Fig 3. Comparison of fecal microbiota community among patients. Left panel is the number of OUT (at Phylum level) in the fecal sample, while right panel is the estimated population size of microorganism in the feces sample. Compared to healthy donor, patients appears highly variability of species spectrum and have decreased species richness and abundance in Bacteroidetes. Fig 4. The species composition of fecal samples at phylum and family level, A, C, E at Phylum level, B, D, F at Family Level. The species richness of fecal samples were remarkably reduced in recurrent severe diarrhea children. The fecal transplantation significantly increased the species richness in these young patients. The detailed information about species composition and abundance were presented in Supp Table 1. Fig 5.The dynamic changes in microbiota population during FMT surgery. A panel is patient 01, B panel is patient 02 and C panel is patient 07.The four columns of heatmaps represented four time-point for each patient, they are pre-FTM, 1 day (or 3 day for patient 07) after FMT, 1 week after FMT and 2 week after FMT. And each row is the sequencing tags proportion for each microorganism. The sequencing tags proportion data were scaled by row.
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Supp Fig 1. Rarefaction curves of 16s rDNA sequences from fecal microbiota. The plot shows the number of OTUs as the number of sequencing reads re-sampled.
Supp Fig 2. Correlation analysis （Pearson） of species composition and abundance among fecal microbiota samples at family level. Left panel is the correlation of species composition, while right panel is the correlation of species abundance in the fecal samples. D is donor, A is before FMT fecal sample, C is 1 day or 3 day after FMT, F is 1week after FMT, G is 2 week after FMT.
Supp Fig 3. The species abundance of fecal samples at family level. The y-axis is the estimated population proportion, and different filled-boxes donated different microorganisms. The detailed abundance information of each OTU taxa listed in Supp Table 1.
Author information
Jianlei Gu, Master, Assistant professor Shanghai Children's Hospital, Shanghai Jiao Tong University. 2008.9-2011.7, Master of microbiology science, Fudan University. 2004.09-2008.7, Bachelor of biological engineering, China University of Mining and Technology
Yizhong Wang, Ph.D, Assistant professor Shanghai Children's Hospital, Shanghai Jiao Tong University. 2009.09-2010.06, Postdoctoral fellow, Division of Gastroenterology, University of Utah School of Medicine. 2010.07-2014.02, Postdoctoral fellow, Department of Pathology and Laboratory Medicine, Temple University School of Medicine.
Shiyi Liu, graduate student, Shanghai Jiaotong University
Guangjun Yu, Ph. D, professor, president of Shanghai Children's Hospital, Shanghai Jiaotong University
Ting Zhang, MD, director of gastroenterology department, Shanghai Children's Hospital, Shanghai Jiaotong University
Hui Lu, Ph. D, professor Hui Lu obtained PhD degree from University of Illinois, and currently at Shanghai Jiao Tong University and Shanghai Children’s Hospital. Education History: 1994/08 - 1999/10, University of Illinois , PhD
1992/01 - 1994/07, University of Massachusetts, physics, Master 1987/09 - 1991/08, Peking University, mathematics and physics, bachelor