The biological significance of decreased secretory immunoglobulin A reactivity against gut microbiota in mice fed with high-fat diet

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The biological significance of decreased secretory immunoglobulin A reactivity against gut microbiota in mice fed with

high-fat diet

2019, March

Muhomah Teresia Aluoch

Graduate School of

Environmental and Life Sciences (Doctor’s Course)

OKAYAMA UNIVERSITY

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PREFACE

This thesis represents work to fulfil partial requirements of Ph.D. in Agriculture at the Graduate School of Environmental and Life Sciences, Okayama University, Japan. The research was conducted between April 2016 and December 2019. The aim of this Ph.D. thesis was to study the effects of high fat diet induced obesity on the immune function of secretory immunoglobulin A in the gut. Overall, the study results demonstrate the influence of excessive consumption of dietary fats on secretory immunoglobulin A- mediated gut immunity.

Supervisor: Assoc. Prof. T. Tsuruta Okayama University

Graduate School of Environmental and Life Sciences Department of Animal Science, Animal nutrition laboratory

Co- supervisor: Prof. N. Nishino Okayama University

Graduate School of Environmental and Life Sciences Department of Animal Science, Animal nutrition laboratory

Co- supervisor: Assoc. Prof. T. Hatabu Okayama University

Graduate School of Environmental and Life Sciences

Department of Animal Science, Animal nutrition laboratory

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Acknowledgements

I would like to sincerely thank everyone who has been involved in this work. I am grateful for your contributions towards the successful completion of this study. I would especially like to mention:

My main supervisor, Assoc. Prof Takeshi Tsuruta, for your patience, invaluable guidance and support. Thank you for introducing me to the field of nutritional biochemistry and immunology.

Thank you for the countless hours you put in to ensure that I completed my study in a timely manner. I am forever indebted to you for the technical, practical and analytical expertise you shared since the first day I joined your team.

My co-supervisor, Prof. Naoki Nishino, for your invaluable mentorship and constant encouragement. Thank you first and foremost for accepting me as the first African candidate in your laboratory. I will forever be grateful for the psychosocial as well as technical support you offered during this rigorous and demanding journey towards attainment of my Ph.D. Thank you for the words of wisdom you freely shared that will keep guiding me in my professional career.

My co-supervisor, Assoc. Prof. Toshimitsu Hatabu, for your academic guidance and counseling. I also very much appreciate your reading of my thesis and suggestions given.

The Assisted Reproductive Technology Center and Department of Genomics and Proteomics (Okayama University) for technical support given.

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All my colleagues at the Animal Nutrition Lab, for the great team work exhibited. Thank you for the technical assistance as well as the helpful discussions revolving around experiments and lab work. Thank you for contributing towards a conducive and productive work environment. Thank you for the rich and cross cultural exchanges I had with each one of you throughout my three year stay in Japan. Let us continue to do our best wherever we go.

To Japan International Cooperation Agency (JICA) who fully funded my Ph.D. course as well as living expenses in Japan. I am truly grateful for ensuring my learning experience in Japan was free from financial stress. Special thanks also go to Jomo Kenyatta University of Agriculture and Technology (JKUAT), Kenya, through whom I obtained the opportunity to attain a JICA funded scholarship.

My deepest thanks go to my closest family and friends for the physical, mental, social and spiritual support you gave to my family and I. To the Kibuchis and Muhomahs, you went above and beyond what families do, and for that I am forever grateful. To Robert and Kiki, my deepest love, gratitude and respect go to you. You bore the greatest brunt of my absence yet still wore brave and happy faces daily, I dedicate this work to you. Finally, I thank the Almighty God, without whom none of this would have been possible.

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Abbreviations

AID Activation induced cytidine deaminase DIO Diet induced obesity

ELISA Enzyme linked immunosorbent assay FITC Fluorescein isothiocyanate

FMT Fecal microbial transplant

GF Germ free

HFD High fat diet

IgA Immunoglobulin A

KO Knock out

LPS Lipopolysaccharide NFD Normal fat diet

SCFA Short chain fatty acids SIgA Secretory immunoglobulin A

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Chapter 1 General introduction 1.1. Secretory immunoglobulin A

1.1.1.What is secretory immunoglobulin A?

Secretory immunoglobulin A (SIgA) is the most abundant immunoglobulin isotype produced in the body and is predominant on mucosal surfaces [1]. SIgA antibodies are produced in B cells situated in gut-associated lymphoid tissues [2]. The SIgA production process involves class switching and somatic hypermutation, processes that enable the antibody develop specificity for commensal gut microbiota. For instance, commensal sensing of gut microbes by antigen sampling across the M cells into Peyers patches triggers production of SIgA with high specificity for the sampled microbes [3]. In addition to bacteria induced SIgA secretion, approximately 2.5g of IgA is naturally secreted into the lumen daily [4]. This non-specific SIgA also plays a key role in protecting the intestinal mucosa. Polymeric immunoglobulin receptor deficient (pIgR-/-) mice, which are mice lacking the ability to produce SIgA, had increased luminal Salmonella typhimurium invasion [5]. However, mice with low specifity SIgA were protected from S.typhimurium epithelium infiltration.

SIgA is an integral part of the body’s innate immunity and forms part of the first line of defense against mucosal pathogenistic bacteria. Using activation-induced cytidine deaminase knock out mice (AIDKO), researchers have demonstrated that SIgA plays an important role in regulation of gut microbiota. AIDKO mice lack the enzyme required for antibody differentiation into IgA and are consequently IgA deficient. AIDKO mice had a change in composition of gut microbiota with a dramatic expansion in segmented filamentous bacteria (SFB) [6]. AID-/- mice also exhibited more than 100-fold increase in culturable bacteria as compared to the control group

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[7]. It is evident from this studies that in the absence of SIgA there is a shift in microbial composition favouring proliferation of pathobiont bacteria. Subsequent inflammatory responses have been associated with bacteria such as Helicobacter and Clostridium [8,9]. The presence of SIgA in the gut mucosa therefore also serves to protect against potential inflammation induced by invasive bacteria. Considering the beneficial role of IgA in maintenance of stable gut composition and protection against inflammation, we will next examine factors that influence its functioning.

1.1.2. Factors influencing SIgA function

Through various researches conducted, it has emerged that SIgA immune response is modulated by two main factors, namely disease and diet.

1.1.2.1. Disease.

Studies in mice and humans have shown varying SIgA immune responses depending on health status. Colitogenic mice showed an increased SIgA immune response with preferential SIgA coating of colitis-driving bacteria. In these mice, Prevotellaceae and Helicobacter were found to be highly coated in mice suffering from inflammatory bowel disease [8]. Further, a study on African children demonstrated a stronger SIgA immune response against Enterobacteriaceae in children suffering from Kwashiorkor as compared to the healthy cohort [10]. It is also apparent that SIgA coats both pathogenic for example Shigella and Faecalibacterium as well as beneficial commensal bacteria such as Bifidobacterium and Akkermansia [10]. These studies demonstrate that one of the modulating factors of a SIgA immune response is diseases that result in gut dysbiosis.

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1.1.2.2. Diet.

The effect of diet on the SIgA immune response has hitherto focused on nutrient sufficient diets, nutrient deficient diets and probiotics. In a study investigating infant diets, Planer et al.

demonstrated shifts in IgA coating of different gut microbiota dependent on diet [11]. SIgA coating of Escherichia coli was significantly higher in breastfed children than those on infant formula. On the other hand, Ruminococcus gnavus had higher SIgA coating in infant formula fed children. In the next experiment, germ free (GF) mice that had undergone fecal microbial transplants (FMT) were fed on different diets derived from infant complementary foods. SIgA coating of certain microbiota varied depending on diet. For instance, proportion of Akkermancia muciniphila and Ruminococcus sp ce2 coated with SIgA increased during consumption of fruits and vegetables, while that of Ruminococcus gnavus and Clostridium boltae decreased.

Similarly, mice that received FMT from undernourished subjects and were fed on a diet containing no carbohydrate and lower fat, protein, minerals and vitamins had a significantly higher coating of Enterobacteriaceae as compared to their counterparts who were fed on normal chow diet [10].

Probiotic effect was examined on female subjects who consumed probiotic yogurt containing Bifidobacterium lactis for 3 weeks. There was a significant increase in luminal IgA during the probiotic consumption as compared to baseline [12]. Similarly, consumption of probiotic infant formula containing Bifidobacterium lactis resulted in a significant increase in SIgA produced in children[13]. These studies illustrate how diet influences SIgA immune response due to its effect on gut microbial composition. They underscore the importance of diet as a potential regulator of SIgA. However, influence of energy-rich diets on SIgA has hitherto not been investigated.

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1.2. Over-nutrition and obesity 1.2.1. State of the world

The world has experienced an increase in prevalence of obesity over the past three decades.

A recent report indicates that in the past three decades alone, the prevalence of obesity has doubled in almost half of countries globally [14]. Global rapid urbanization has resulted in changes in lifestyle and food choices. Agrarian and industrial nations have benefitted from technological improvements in machinery which have improved efficiency and productivity. These advances have however resulted in less energy intensive occupations and lower need for manpower. This has contributed to a more sedentary lifestyle. In addition, urbanization has also resulted in changes in dietary options due to increase in affordable, available and accessible refined, energy dense foods [15]. Consequently, fiber rich diets low in saturated fats and sugars have progressively been substituted with the available less healthy options. These changes have in part contributed to the growing obesity pandemic, an underlying cause of diverse undesirable health outcomes. In this study, we investigate the effect of diet induced obesity (DIO) on gut health by focusing on the most abundant antibody in the gut, that is, SIgA-mediated gut health.

1.2.2. Obesity and gut immunity

Weight gain and overweight are important modulators of the gut microbiota. Research using overweight human subjects as well as mice models has demonstrated the changes that occur in the gut environment due to excessive weight gain as well as consumption of foods rich in fats.

At the phylum level, obesogenic diets result in increases in Firmicutes bacteria and decrease in

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Bacteroidetes. Further, weight loss interventions on obese individuals focused on reduced dietary intake have demonstrated an increase in Bacteroidetes and decrease in Firmicutes populations [16].

These studies suggest that there is an association between obesity and gut microbiota.

Studies involving transplantation of fecal microbiota of obese mice have hitherto provided insight on the relationship between weight gain, energy dense diets and gut microbiota. First, the effect of high fat diet (HFD) was demonstrated using germ free (GF) C57BL/6 mice which had undergone human fecal microbial transplant. Change of diet from a low fat/polysaccharide rich chow diet to a high-fat/high-sugar diet resulted in increase in relative abundance of Firmicutes population with significant enrichment of the classes Erysipelotrichi and Bacilli [17]. Secondly, the effect of gut microbiota on adiposity was demonstrated using ob/ ob mice, which are mice lacking the satiety hormone leptin. Transplantation of cecal microbiota from ob/ob to GF mice resulted in significantly higher adiposity than in mice which had lean donors [18]. In a different experiment, GF mice which received cecal microbiota from obese HFD-fed mice had greater adiposity than those who received microbiota from lean carbohydrate-fed mice [19]. Apart from the influence of diet on weight gain, these studies illustrate the influence of fat rich diets on gut microbiota. In addition, they also suggest HFD-modulated gut microbiota may have an influence on an obese phenotype.

These DIO-associated microbial changes are linked to compromised gut immunity. DIO mice developed colonic inflammation as evidenced by increased expression of Tnfa, Il-1b and Il-6 inflammatory cytokines. DIO mice were also reported to have diminished barrier function due to reduced expression of colonic tight junction proteins claudin-1 and occludin as well as lower Muc2 expression [20,21]. Further, DIO specific pathogen free (SPF) mice had elevated ileal Tnfa as compared to their GF counterparts [22]. Among the mechanisms that have been proposed to

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explain these changes include increased accumulation of bacteria close to the mucosa and bacterial invasion of the epithelium [23,24]. One of the functions of SIgA is protection of the epithelium against microbial invasion [25]. It is therefore imperative to investigate how prolonged consumption of a HFD and subsequent development of obesity influences the protective function of SIgA.

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Chapter 2 High-fat diet reduces the level of secretory immunoglobulin A coating of commensal gut microbiota

2.1. Abstract

Excessive fat intake is associated with changes in gut microbiota composition. In the present study, we focused on the secretory immunoglobulin A (SIgA) coating of gut microbiota as a mucosal immune response affecting the gut microbiota following a high-fat diet (HFD). The level of SIgA coating of gut microbiota was evaluated in normal-fat diet (NFD)- and HFD-fed mice. HFD significantly decreased the level of SIgA coating the gut microbiota compared to NFD. Of note, substitution of HFD with NFD resulted in a complete recovery of the level of SIgA coating. These findings suggest that dietary fat influences the SIgA coating of the gut microbiota. Furthermore, we analyzed the composition of the gut microbiota and the concentration of cecal short chain fatty acids. HFD feeding changed the gut microbiota composition at the phylum and family levels.

Pearson’s correlation analysis between the level of SIgA coating of gut microbiota and the relative abundance of gut microbiota showed that the relative abundances of Clostridiaceae, Mogibacteriaceae, Turicibacteraceae, and Bifidobacteriaceae were negatively correlated with the level of SIgA coating of gut microbiota. Conversely, the relative abundances of Desulfovibrionaceae, S24-7 and Lactobacillaceae were positively correlated with the level of SIgA coating. The concentrations of cecal acetate and butyrate were lower in HFD-fed mice, and positively correlated with the level of SIgA coating of gut microbiota. Our observations suggest that a decrease in the level of SIgA coating of the gut microbiota through a HFD might relate to HFD-induced changes in microbial composition and microbial metabolites production.

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2.2 . Introduction

Excessive consumption of dietary fat alters the composition of gut microbiota. High-fat diet (HFD) consumption increases the ratio of Firmicutes : Bacteroidetes, the dominant phyla in the human and mouse gut [26]. Family-level changes in gut microbiota have also been reported, including increases in Enterobacteriaceae, Enterococcaceae, and Bifidobacteriaceae, as well as decreases in Lactobacillaceae and Prevotellaceae [17,27,28]. In addition, HFD consumption has been associated with decreased microbial diversity [19]. Several factors such as bile acid, dietary fat, and short chain fatty acids (SCFA) may induce shifts in microbial composition as a result of HFD feeding. Firstly, elevated fat consumption triggers increased bile acid synthesis, a process required in lipid digestion and absorption. Unabsorbed bile acids are hydrolyzed into secondary bile acids by gut microbial bile salt hydrolase [29]. The antimicrobial nature of the resultant secondary bile acids has been suggested to favor the growth of bile tolerant microbiota [30].

Secondly, movement of unabsorbed dietary fat into the distal intestine after HFD consumption has been shown to cause an increase in the Firmicutes : Bacteroidetes ratio due to the bacteriostatic properties of saturated fatty acids [31,32]. Further, prolonged consumption of a diet rich in saturated fats is associated with ER stress- mediated reduction in colonic mucin production resulting in changes in gut microbiota composition [33]. These HFD-related changes in gut microbiota result in lower SCFA production in the intestinal lumen [34]. The subsequent increase in luminal pH inhibits the growth of pH-sensitive bacteria, further modulating the gut microbiota composition [35]. In addition to these factors, we hypothesized that the secretory immunoglobulin A (SIgA) coating of gut microbiota relates to changes in microbial composition upon HFD consumption. This is because SIgA plays an important role in maintaining a stable gut microbial composition [36]. SIgA is the predominant antibody isotype secreted into the intestinal lumen [1]

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SIgA specifically coats gut microbiota [8] and suppresses the overgrowth of gut microbiota [6,37].

While it is evident that the SIgA coating of gut microbiota modulates the gut microbial composition, the relationship between the SIgA coating of gut microbiota and HFD-induced changes in gut microbiota remains unclear. To investigate this relationship, we evaluated the level of IgA coating of gut microbiota and the gut microbial composition in NFD- and HFD-fed mice and explored the correlation between them.

2.3 . Materials and methods

2.3.1. Experimental design

The experimental protocol was approved by the Animal Care and Use Committee of Okayama university, Japan (approval no. OKU-2016305). Thirty male BALB/c mice (9-week-old) were allocated into groups based on body weight and acclimated for a week. We conducted two experiments which differed in dietary treatment and dissection period.

In experiment 1, 20 mice were allocated into 2 groups and allowed free access to water and to either a normal-fat diet (NFD) or a high-fat diet (HFD). The diet composition can be found in Table 1. Fecal samples were collected at the start of the experiment, and at weeks 6 and 12. Before dissection at week 12, the body weight was measured. The mice were then killed by exsanguination via cardiac puncture under pentobarbital anesthesia. The cecal content and colonic tissue were collected.

In experiment 2, 10 mice were divided into 2 groups; one group was fed NFD for 18 weeks, and the other group was fed HFD for the first 12 weeks and then switched to NFD for the following 6 weeks. At week 18, fecal samples were collected.

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2.3.2. Flow cytometry analysis of IgA-coated bacteria

One fecal pellet was suspended in 500 µL PBS and sedimented by centrifugation (100 × g for 20 min). The supernatant was then centrifuged at 9,000 × g for 10 min. After centrifugation, the supernatant was collected for fecal IgA ELISA. The resultant bacterial pellet was washed twice with PBS. The bacterial cells were then fixed with 4% paraformaldehyde (Wako) overnight at 4ºC.

After washing twice with PBS, the bacterial cells were stained with FITC-labelled anti-mouse IgA (BD Pharmingen) for 30 min. After washing twice with PBS, the bacterial cells were stained with propidium iodide (PI; Sigma Aldrich) solution (4 µg/mL). The bacterial suspension was analyzed by a Gallios flow cytometer (Beckman Coulter). The gating strategy used to identify SIgA-coated and non-coated bacteria is shown in Fig. 1. FCS Express V3 (De Novo Software) was used to calculate the average FITC intensity emitted by a single SIgA-coated bacterium. The average FITC intensity emitted by a single SIgA-coated bacterium was defined as the average level of SIgA coating per fecal bacterium.

2.3.3. Quantification of Fecal IgA concentration

The concentration of fecal IgA in the aforementioned fecal supernatant was measured using a Mouse IgA ELISA quantification kit (Bethyl) according to the manufacturer’s instructions. The absorbance of each well was read at 450 nm using a microplate reader (Bio-Rad).

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2.3.4. Western blot of IgA bound to fecal bacteria

The samples containing fecal bacteria were prepared as described above. The bacterial pellet was lysed with 15 µL RIPA lysis buffer. Mouse serum IgA (Bethyl) was also lysed and used as standard for the quantification of IgA. The bacterial lysate was mixed with 4 × Laemmli buffer and separated on 10% SDS-PAGE. The separated proteins were transferred onto a PVDF membrane using the Power Blotter System (Thermo Fisher Scientific). After blocking with 1 % skim milk buffer, the membrane was stained with anti-mouse IgA antibody (Bethyl) and HRP- conjugated anti-goat IgG antibody (R&D systems) as primary and secondary antibodies, respectively, and visualized using Chemi-Lumi One super substrates (Nacalai). Imaging and quantification of IgA coating fecal bacteria were performed using ChemiDoc XRS+ system (Bio- Rad). The amount of IgA coating fecal bacteria was quantified by measuring the band intensity and comparing it to reference bands of serum IgA.

2.3.5 Analysis of gene expression

Total RNA was extracted from colonic samples using ISOGEN II according to manufacturer’s protocol (Nippon gene). Random primers were then used to reverse transcribe the RNA (Takara). qPCR was performed using AriaMx Real-Time PCR (Agilent Technologies).

Sample quantification cycle (Cq) values were normalized using housekeeping gene GAPDH. Fold changes were then calculated relative to the average NFD group value using the ∆∆Cq method.

Primer pair sequences used were as follows: Mouse GAPDH forward primer 5′- TCAAGAAGGTGGTGAAGCAG -3′; reverse primer 5′-AAGGTGGAAGAGTGGGAGTTG -3;

mouse IgA forward primer 5′-TGCACAGCTTTCTTCTGCAC-3′; reverse primer 5′-

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TGCCAGCCTCACATGTACTC-3′ [38]; mouse Muc2 forward primer 5′-

GCTGACGAGTGGTTGGTGAATG -3′; reverse primer 5′-

GATGAGGTGGCAGACAGGAGAC -3 [39].

2.3.6. Illumina MiSeq sequencing

Bacterial DNA was extracted from fecal samples by using the QIAamp stool mini kit (Qiagen) according to the manufacturer's instructions, with additional freeze and thaw, and bead- beating steps. Next-generation sequencing analysis was performed as previously described [40].

All bacterial species obtained from fecal samples were classified, and the proportion of different phyla and families was computed using QIIME (version 1.9.1). The alpha diversity (Chao1 and Shannon index) of species-level microbial taxa was computed for rarefied operational taxonomic units (OTUs) (5000 reads) using the Primer version 7 with Permanova + add-on software (Primer- E, Plymouth Marine Laboratory, and Plymouth, UK).

2.3.7. SCFAs in cecum

Cecal SCFAs determination was conducted using a gas chromatograph (GC-14a;

Shimadzu) fitted with a glass capillary column coated with nitroterephthalic acid modified polyethylene glycol (TC- FFAP; GL Sciences). Cecum samples were weighed, homogenized, and then deproteinized using 10 % trichloroacetic acid. The samples were then centrifuged before injection into the TC-FFAP column. The column oven temperature was programmed at 80°C for the first 2 minutes and then increased to 200°C at a rate of 10 per minute [41].

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2.3.8. Statistical analysis

Data are expressed as means  SEM. All statistical analysis was conducted using GraphPad Prism version 7.00 for Windows (GraphPad Software, USA). Values obtained from experiment 1 and 2 were compared between diet groups using Student's t test at each time point. Correlations between the average level of SIgA coating per fecal bacterium and fecal IgA concentration, body weight, colonic IgA mRNA expression, relative abundance of gut microbiota, and cecal SCFA concentration were analyzed using Pearson’s correlation coefficients. P < 0.05 was considered statistically significant in all experiments.

2.4 . Results

2.4.1. HFD feeding reduces SIgA coating of gut microbiota

In experiment 1, we detected by flow cytometry SIgA-coated bacteria in the feces of mice fed either NFD or HFD for 6 and 12 weeks. Representative results of the flow cytometry for the detection of SIgA-coated bacteria are shown in Fig. 2A. SIgA-coated bacteria were recognized as both a FITC- and PI-positive population, and were also gated. The average level of SIgA coating per fecal bacterium was significantly lower in HFD-fed mice on week 6 and 12 than in NFD-fed mice (Fig. 2B). Although no significant differences between the diet groups were detected, the amount of SIgA coating of fecal bacteria measured by western blotting was also lower in HFD- fed mice compared with NFD-fed mice on week 6 and week 12 (Fig. 2C). Fecal IgA concentration tended to be lower in HFD-fed mice than in NFD-fed mice on week 6 and 12 (Fig. 2D). Body weight was significantly higher in HFD-fed mice than in NFD-fed mice at week 12 (Fig. 2E). The

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gene expression of IgA in the colon did not differ between diet groups at week 6 and week 12 (Figure 2F).

2.4.2 Level of SIgA coating of gut microbiota is associated with fecal IgA concentration and body weight

The fecal IgA concentration positively correlated with the average level of SIgA coating per fecal bacterium (r = 0.64, P < 0.01) (Fig. 3A). Body weight negatively correlated with the average level of SIgA coating per fecal bacterium (r = - 0.56, P < 0.01) (Fig. 3B). There was no correlation between the gene expression of IgA in the colon and the average level of SIgA coating per fecal bacterium (r = -0.24, P = 0.22) (Fig. 3C).

2.4.3. HFD-induced reduction of SIgA coating of gut microbiota is reversed by NFD feeding In experiment 2, we detected SIgA-coated bacteria in the feces of mice fed NFD for 18 weeks (NFD) or fed HFD for the first 12 weeks and then switched to NFD for the subsequent 6 weeks (HFD + NFD). Representative results of flow cytometry for the detection of SIgA-coated bacteria are shown in Fig. 4A. There were no significant differences in the average level of SIgA coating per fecal bacterium between NFD and HFD + NFD (Fig. 4B). The level of SIgA coating fecal bacteria measured by western blotting was also not significantly different between the diet groups (Fig. 4C).

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2.4.4 HFD-induced changes in gut microbiota and cecal SCFAs concentration are associated with the level of SIgA coating of gut microbiota

The relative abundances of fecal microbial taxa at the phylum and family levels, and cecal SCFAs in mice fed NFD or HFD for 12 weeks are shown in Table 2. HFD feeding elevated the relative abundance of Firmicutes (P = 0.06) and reduced that of Bacteroidetes (P = 0.09). The ratio of Firmicutes : Bacteroidetes was not significantly different between NFD-fed (20.1±16.7) and HFD-fed mice (34.3±12.7). The relative abundance of Actinobacteria was significantly higher, while that of Proteobacteria was significantly lower in HFD-fed mice, compared with NFD-fed mice. Further, HFD-fed mice showed significantly higher relative abundance of Bifidobacteriaceae, Clostridiaceae, Mogibacteriaceae and Turicibacteraceae compared with NFD-fed mice. Conversely, Lactobacillaceae, S24-7 and Desulfovibrionaceae were less abundant in HFD-fed mice. To determine the effect of HFD on microbial diversity, the Shannon index and the Chao1 index were computed. HFD-fed mice exhibited a significantly lower diversity at the species level based on observed richness (Chao1) and Shannon’s diversity index (Fig. 5A and 5B).

A heat map of the 20 most abundant microbiota at the family level was generated to examine the individual microbial differences at 12 weeks. The heat map showed that the samples were separated into two different clusters based on diet, with the exception of one individual in the NFD group (Fig. 5C). HFD-feeding decreased the concentrations of cecal acetate, propionate, and butyrate, however, the differences were not significant between the diet groups.

The relative abundance of Firmicutes tended to be negatively correlated with the average level of SIgA coating per fecal bacterium (Table 2). The relative abundances of Clostridiaceae, Mogibacteriaceae, Turicibaceteriaceae and Bifidobacteriaceae were also negatively correlated with average level of SIgA coating per fecal bacterium. The relative abundances of

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Lactobacillaceae, S24-7 and Desulfovibrionaceae were positively correlated with average level of SIgA coating per fecal bacterium.

The concentrations of cecal acetate and butyrate were positively correlated with the average level of SIgA coating per fecal bacterium.

2.5 Discussion

In the present study, we investigated the relationship between SIgA coating of gut microbiota and HFD-induced changes in gut microbiota. Our study demonstrates that the level of SIgA coating fecal bacteria greatly decreased in HFD-fed mice compared with NFD-fed mice, which suggests that SIgA coating of gut microbiota may be suppressed by HFD feeding. Furthermore, we observed that the suppression of SIgA coating of gut microbiota induced by HFD is completely reversed by substitution of HFD with NFD. It was reconfirmed that excessive fat intake is a major cause of suppression of SIgA coating of gut microbiota. Although the exact underlying mechanism remains unclear, we showed the possibility that fat content in diet is one of the determinant factors modulating the adaptive mucosal immune response associated with SIgA against gut microbiota.

There are two possible causes for the decrease of SIgA coating of gut microbiota induced by HFD: one is fecal IgA concentration and the other is SIgA specificity against gut microbiota.

Although no significant difference was found, fecal IgA concentration was decreased by HFD ingestion. Furthermore, fecal IgA concentration was positively correlated with the average level of SIgA coating per fecal bacterium. This implies that the decreased SIgA secretion induced by HFD feeding might decrease the level of SIgA coating the gut microbiota. However, a previous study demonstrated that fecal IgA concentration is not a determinant factor for the amount of SIgA

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coating gut microbiota, because only less than 1 % of fecal IgA is used for the coating of gut microbiota [42]. Therefore, this possibility should be further examined in a future study.

SIgA specificity against luminal antigens is partly regulated by dendritic cells and T cells present in the Peyer’s patches [3]. James et al. reported that HFD feeding reduces the ability of dendritic cells to induce T cell expansion, which plays a critical role in the differentiation of antigen-specific IgA plasmablast [43]. Together with these studies, our results suggest that HFD consumption might suppress the differentiation of IgA plasmablast specific for the gut microbiota, resulting in a decrease of SIgA coating of gut microbiota.

In line with previous studies, we observed that HFD feeding induced changes in the microbial composition at the phylum level [19,26]. HFD-fed mice had a higher abundance of Firmicutes and a lower abundance of Bacteroidetes. At the family-level, the relative abundances of Clostridiaceae and Bifidobacteriaceae were significantly increased in HFD-fed mice compared to NFD-fed mice, while that of Lactobacillaceae and S24-7 significantly decreased as in previous studies [17,27]. In the present study, we found a clear correlation between the level of SIgA coating gut microbiota and the relative abundance of gut microbiota in mice fed NFD or HFD for 12 weeks. There was a tendency of negative correlation between the relative abundance of Firmicutes and the level of SIgA coating gut microbiota. Furthermore, we observed a significant negative correlation between the relative abundances of Clostridiaceae, Mogibacteriaceae, Turicibacteraceae and Bifidobacteriaceae and the level of SIgA coating gut microbiota. Peterson et al. demonstrated that the growth of Bacteroides thetaiotaomicron, a dominant gut bacterium, is suppressed in IgA- deficient mice transplanted with hybridoma cells secreting IgA that specifically binds to B.

thetaiotaomicron, compared with IgA-deficient mice without hybridoma cells [44]. Furthermore, Wei et al. reported that both aerobic and anaerobic gut microbiota grow excessively in AID^G23S

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mice, whose intestinal IgA has a low-specificity against gut microbiota compared with wild-type mice [45]. These reports suggest that SIgA coating of gut microbiota plays a crucial role in suppressing gut microbiota coated by SIgA. Therefore, the negative correlation between the level of SIgA coating of gut microbiota and the relative abundances of the phylum Firmicutes and the families Clostridiaceae, Mogibacteriaceae, Turicibacteraceae and Bifidobacteriaceae indicates that the overgrowth of these microbial groups might have occurred due to a decrease in the SIgA coating against these microbial groups upon HFD feeding. As opposed to these microbial groups, a positive correlation between the level of SIgA coating of gut microbiota and relative abundance was observed for S24-7, a major family of Bacteroidales, and for Lactobacillaceae. A report showed that Bacteroides and Lactobacillus, major genera of Bacteroidales and Lactobacillaceae, resist the SIgA coating in NFD-fed mice [46]. This report and our observation suggest that S24-7 and Lactobacillaceae might show reduced levels of SIgA coating and thus be less affected by the ability of SIgA to suppress the growth of gut microbiota. Consequently, the relative abundance of these microbial families might be higher in NFD-fed mice. However, it is unclear from our study why the relative abundances of these microbial families decrease when the level of SIgA coating gut microbiota is decreased by HFD feeding. There is the possibility that HFD feeding promotes the overgrowth of other bacteria that depress the growth of these microbial families.

Our study also showed that HFD-fed mice have a significantly lower microbial diversity compared with NFD-fed mice, which is consistent with previous reports [47]. Using AID^G23S mice, Wei and colleagues demonstrated that a decrease of SIgA specificity against gut microbiota results in low microbial diversity [45]. So, a decrease of SIgA coating of gut microbiota induced by HFD feeding might relate to reduced microbial diversity in HFD-fed mice.

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Acetate, propionate, and butyrate are major SCFAs produced by intestinal fermentation of dietary fibers. These SCFA ameliorate HFD-induced obesity and insulin resistance to a similar extent when given as a dietary supplement [48]. In the present study, the concentration of SCFAs was decreased in HFD-fed mice, which is in line with previous reports [49]. In fact, in the present study, SCFA-producing gut microbiota, such as Ruminococcaceae and S24-7 [50,51], were decreased in HFD-fed mice compared with NFD-fed mice. There is a possibility that the reduction in SCFA producers may be due to reduction in available substrate owing to the reduced starch content in the HFD. Further research needs to be conducted to clarify this.

Interestingly, there was a significant positive correlation between the concentrations of cecal acetate and butyrate and the level of SIgA coating of gut microbiota. Kim et al. reported that oral administration of an SCFA mixture containing acetate, propionate, and butyrate increases the ratio of SIgA-coated bacteria to total intestinal bacteria, suggesting that SCFAs can promote SIgA coating of gut microbiota [52]. Therefore, our observations suggest that reduction in the concentration of SCFAs in the gut induced by HFD consumption might be linked to a decrease of SIgA coating of gut microbiota.

In conclusion, our study clearly showed that excessive dietary-fat intake decreases the level of SIgA coating of gut microbiota. The reduced levels of SIgA coating gut microbiota after HFD consumption might relate to HFD-induced changes in microbial composition and microbial metabolites production.

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2.6 Tables and figures

Table 1. Composition of experimental diets

NFD HFD

Ingredients g/kg diet

Maize starch¹ 465.692 290.692

α- Maize starch¹ 155 -

Casein¹ 140 140

Sucrose² 100 100

Cellulose¹ 50 50

Soybean oil³ 40 70

Lard⁴ - 300

AIN-93 Mineral mix¹ 35 35

AIN- 93 Vitamin mix¹ 10 10

L- cystine³ 1.8 1.8

Choline bitartrate⁵ 2.5 2.5

Tert- butylhydroquinone⁶ 0.008 0.008

kcal/g diet

Total energy 3.8 5.5

NFD, normal fat diet; HFD, high fat diet

1 Purchased from CLEA Japan, Japan.

2 Purchased from Nippon Beet Sugar, Japan.

3 Purchased from Nacalai Tesque, Inc, Japan.

4 Purchased from Yukijirushi, Japan.

5 Purchased fromTokyo Chemical Industry, Japan.

6 Purchased fromWako Chemicals, Japan.

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21 Table 2: Relative abundances (%) of fecal microbial taxa at the phylum and family level¹ and cecal SCFAs in mice fed on NFD and HFD for 12 weeks (Experiment 1).

Correlation with average

level of IgA coating per fecal bacterium

NFD HFD r P value

Relative abundance (%)

Firmicutes 69.98 ± 3.79 80.43 ± 2.54 -0.65 0.08

Clostridiaceae 0.49 ± 0.10 2.59 ± 0.58* -0.79 0.02^¶

Lactobacillaceae 6.19 ± 1.13 1.81 ± 0.90* 0.62 0.1

Mogibacteriaceae 0.32 ± 0.12 0.97 ± 0.12* -0.78 0.02^¶

Turicibacteraceae 6.26 ± 2.57 25.52 ± 2.68* -0.85 0.01^¶

Bacteroidetes 15.15 ± 4.84 4.60 ± 2.38 0.59 0.12

S24-7 10.42 ± 3.57 1.43 ± 0.49* 0.65 0.08

Actinobacteria 5.45 ± 1.55 12.35 ± 0.97* -0.77 0.03^¶

Bifidobacteriaceae 5.36 ± 1.57 12.24 ± 0.95* -0.77 0.03^¶

Proteobacteria 7.60 ± 2.11 0.18 ± 0.08* 0.73 0.04^¶

Desulfovibrionaceae 7.48 ± 2.15 0.14 ± 0.08* 0.72 0.04^¶ SCFA (µmol/g)

Acetate 3.11 ± 0.78 1.81 ± 0.32 0.76 0.05^¶

Propionate 0.40 ± 0.08 0.21 ± 0.01 0.68 0.09

Butyrate 0.40 ± 0.11 0.22 ± 0.01 0.78 0.04^¶

1Results include only family level microbial taxa that were significantly different between diet groups.

Values are given as means ± SEMs, n=5 per group. *Different from NFD, P<0.05. ^¶Significant correlation, P<0.05

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Figure 1. Gating on unstained bacterial pellet was used to identify bacteria from mouse feces.

(A) The microbial fraction was first identified by forward scatter (FS) and side scatter (SS) properties, as shown in gate 1. (B) A quadrant on FL1 vs FL3 dot plot using gate 1 was used to identify bacteria. IgA-coated bacteria were identified as PI and FITC positive populations; IgA- non-coated bacteria were identified as PI positive and FITC negative populations.

IgA coated bacteria

IgA non-coated bacteria

FITC (IgA)

PI B

A

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B C

W e e k 0 W e e k 6 W e e k 1 2

0 1 0 0 2 0 0 3 0 0 4 0 0

Averagelevel ofIgAcoating perfecal bacterium (arbitraryunit)

N F D

H F D

*

W e e k 0 W e e k 6 W e e k 1 2

0 1 0 0 0 2 0 0 0 3 0 0 0 4 0 0 0 5 0 0 0

Amount of IgA coating fecal bacteria (ng/g faeces)

N F D H F D

D

W e e k 0 W e e k 6 W e e k 1 2

0 5 0 1 0 0 1 5 0 2 0 0

Fecal IgA concentration (g/mg faeces)

N F D H F D

W e e k 0 W e e k 6 W e e k 1 2

0 1 0 2 0 3 0 4 0 5 0

Bodyweight(g)

H F D

N F D *

E

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Figure 2. HFD consumption decreases the level of SIgA coating of gut microbiota (Experiment 1). (A) Representative results of flow cytometry for the detection of SIgA-coated bacteria in feces at week 0 and after 6 and 12 weeks of NFD or HFD feeding. Gated population represents SIgA-coated bacteria. (B) Average level of SIgA coating per fecal bacterium analyzed by flow cytometry. Average FITC intensity of SIgA-coated bacteria measured by flow cytometry and defined as the average level of SIgA coating per fecal bacterium. (C) Amount of IgA coating fecal bacteria analyzed by western blotting. Fecal bacteria were subjected to western blotting using an anti-IgA antibody. A representative blot is shown above the graph. The amount of IgA coating fecal bacteria was quantified by reference to band intensity of a reference serum IgA. (D) Fecal IgA concentration. (E) Body weight. (F) Colonic mRNA expression of IgA was determined by qPCR. Values are given as means ± SEMs, n=5 per group. Unpaired student’s t test HFD vs NFD for week 6 and week 12: *P<0.05.

F

W e e k 0 W e e k 6 W e e k 1 2

0 1 2 3

Relative colonic IgA mRNA level (Arbitary unit)

N F D H F D

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Figure 3. Level of SIgA coating of gut microbiota is associated with fecal IgA concentration and body weight. Pearson’s correlation between (A) fecal IgA concentration, (B) body weight and (C) relative expression of colonic IgA and the average level of SIgA coating per fecal bacterium.

Each dot represents measurements of a single mouse. The correlation coefficient (r), the corresponding P value and the linear regression line are shown. Values are given as means ± SEMs, n=5 per group. *Different from NFD, P<0.05

A B

C

0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0

0 1 0 0 2 0 0 3 0 0

A v e r a g e l e v e l o f I g A c o a t i n g p e r f e c a l b a c t e r i u m

( a r b i t r a r y u n i t ) Fecal IgA concentration (g/mg faeces)

r = 0 . 6 4 p < 0 . 0 1

0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0

2 0 2 5 3 0 3 5 4 0 4 5 5 0

( a r b i t r a r y u n i t )

Body weight (g)

r = - 0 . 5 6 p < 0 . 0 1

0 1 0 0 2 0 0 3 0 0

0 1 2 3 4

( a r b i t r a r y u n i t ) Relative colonic IgA mRNA level (Arbitary unit)

r = - 0 . 2 4 p = 0 . 2 2

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Figure 4. Reduction in the level of SIgA coating of gut microbiota induced by HFD consumption is reversed by NFD consumption (Experiment 2). (A) Representative results of flow cytometry for the detection of SIgA-coated bacteria in mice fed NFD for 18 weeks (NFD) and in mice fed HFD for the first 12 weeks and switched to NFD for the following 6 weeks (NFD+HFD). (B) Average level of SIgA coating per fecal bacterium analyzed by flow cytometry. (C) Amount of IgA coating fecal bacteria analyzed by western blotting. Values are given as means ± SEMs, n=5 per group.

B C

N F D H F D + N F D

0 5 0 1 0 0 1 5 0 2 0 0

Average level of IgA coating perfecal bacterium (arbitraryunit)

N F D H F D + N F D

0 1 0 0 0 2 0 0 0 3 0 0 0 4 0 0 0

Amount of IgA coating fecal bacteria (ng/g faeces)

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Figure 5. HFD consumption influences fecal microbial composition of mice fed NFD or HFD for 12 weeks. Alpha diversity of species-level microbial taxa using (A) Chao1 and (B) Shannon indexes for rarefied OTUs (5000 reads). (C) Heat map representing the 20 most abundant families in NFD- and HFD-fed mice. A Euclidean distance metric was used to group individuals into clusters n=4 per diet group. Values are given as means ± SEMs, *Different from NFD, P<0.05.

A B

C

N F D H F D

0 2 0 4 0 6 0 8 0

Alphadiversity(Shannon) *

N F D H F D

0 3 0 0 0 6 0 0 0 9 0 0 0 1 2 0 0 0

Alphadiversity(Chao1)

*

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Chapter 3 High-fat diet-induced reduction in level of secretory immunoglobulin A coating of gut microbiota exacerbate insulin resistance

3.1. Abstract

Diet induced obesity (DIO) is associated with a compromised gut barrier function. We previously determined that prolonged consumption of dietary fat causes a reduction in level of SIgA coating gut microbiota. In this study, we first investigated the influence of high fat DIO on gut mediated SIgA immune function. The level of IgA coating was evaluated in normal-fat diet (NFD)- and high fat diet (HFD)-fed wild type (WT) mice. The level of IgA coating of gut microbiota was significantly higher in HFD-fed WT mice. In addition, there was a significant decrease in ileum gut barrier function of HFD-fed WT mice as evidenced by lower gene expression of Ocln Zo1 and Muc2. Furthermore, there were significant correlation between Ocln, Zo1, Cldn1 and Muc2 with level of SIgA coating of gut microbiota.

Secondly, we investigated the effect of SIgA on DIO gut inflammation and insulin resistance using activation induced deaminase (AID) knock out (KO) mice. There was significantly higher ileal pro-inflammatory cytokine gene expression of Tnfa, Mcp1 and Ifng in HFD-fed KO mice as compared to their HFD-fed WT counterparts. HFD-fed KO mice also exhibited insulin resistance as shown by HOMA-IR. There were however no differences in adipose tissue inflammatory cytokines Tnfa, Mcp1 and Ifng between HFD-fed WT and KO mice.

Our observations suggest that decreased level of SIgA coating in DIO mice may contribute to DIO- induced gut permeability and insulin resistance.

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3.2. Introduction

Secretory immunoglobulin A (SIgA) is the most abundant antibody in the gut [36] and is predominantly found on mucosal surfaces [53]. A huge number of gut microbiota inhabit the gastrointestinal tract and these gut microbita are partly coated by SIgA. We recently demonstrated that the level of SIgA coating gut microbiota was significantly lower in high-fat diet (HFD)-fed mice compared to normal-fat diet (NFD)-fed mice. Furthermore, the level of SIgA coating gut microbiota was correlated with the relative abundance of gut microbiota, suggesting that the decrease of the level of SIgA coating gut microbiota in HFD-induced obesity are associated with HFD-induced changes in gut microbiota composition, namely microbial dysbiosis.

It has been reported that HFD-induced obesity causes not only microbial dysbiosis but impairment of intestinal barrier function, metabolic endotoxemia, low grade chronic inflammation in the peripheral tissues and insulin resistance. Microbial dysbiosis in HFD-induced obesity leads to the impairment of intestinal barrier function by decreasing expression of tight junction proteins [20] and reducing production of mucin, the principal component in the mucus layer lining the intestines [33]. As a result of impairment of intestinal barrier function, entry of lipopolysaccharides (LPS) into the circulation increases because of high intestinal permeability. LPS is a cell-wall compound of Gram-negative bacterial species and can induce low grade inflammation in the peripheral tissues such as white adipose tissues, skeletal muscle and liver through toll like receptor 4 signaling. Low grade inflammation induced by LPS exposure is associated with occurrence of insulin resistance. Previously, we showed the possibility that HFD-induced decrease of level of SIgA coating gut microbiota associate with microbial dysbiosis. However, it remains unclear how HFD-induced decrease of level of SIgA coating gut microbiota associate with the disorders caused by gut dysbiosis in HFD-induced obesity including impairment of intestinal barrier function,

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chronic inflammation in the peripheral tissue and insulin resistance. Therefore, we firstly evaluated the level of SIgA coating gut microbiota, intestinal barrier function, inflammation in the white adipose tissue and insulin resistance in NFD-fed and HFD-fed mice to determine the association between SIgA coating of gut microbiota and obesity-associated disorders. In the second experiment, we used activation induced cytidine deaminase (Aicda) deficient mice which are lack of SIgA in the intestine. Obesity-associated disorders were evaluated in HFD-fed wild-type and Aicda deficient mice to determine whether SIgA coating of gut microbiota directly causes the occurrence of disorders.

3.3. Methods

3.3.1. Mice

Experimental protocols were approved by the Animal Care and Use Committee of Okayama University, Japan (approval no. OKU-2016305). Aicda heterozygous mice (Aicda^+/-) were procured from RIKEN BioResourse Research Center (Tsukuba, Japan). Wild-type mice (WT, Aicda^+/+) and Aicda deficient mice (KO, Aicda^-/-) were generated by heterozygous crossing. All of the mice were on a Balb/c background and housed in stainless steel cages (2-3 mice per cage) in a temperature-controlled room with a 12- h light- dark cycle. We conducted two different experiments; the first experiment using only WT mice fed normal fat diet (NFD) or high fat diet (HFD) and the second experiment using WT mice and KO mice fed HFD.

In the first experiment, 5 wks-old twelve female WT mice were allocated into 2 groups dependent on their body weight and allowed free access to water and to either NFD (Research diet;

10 kcal% fat) or HFD (Research diet; 60 kcal% fat) for 12 weeks. Body weight and amount of feed intake were measured biweekly. Fecal samples were collected at the end of the experiment.

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In the second experiment, 5 wks-old twelve female WT and KO mice were fed HFD for 12 weeks. Body weight and amount of feed intake were measured biweekly. Fecal samples were collected at the end of the experiment.

At the end of both experiments, the mice were killed by exsanguination via cardiac puncture under pentobarbital anesthesia. Ileum and parametrial adipose tissues were collected and stored at -80 ºC awaiting analysis.

3.3.2. Analysis of gene expression

Total RNA was extracted from parametrial adipose tissue and ileum samples using ISOGEN II according to manufacturer’s protocol (Nippon gene). Random primers were then used to reverse transcribe the RNA (Takara). qPCR was performed using AriaMx Real-Time PCR (Agilent Technologies). Sample quantification cycle (Cq) values were normalized using housekeeping gene GAPDH. Fold changes were then calculated relative to the average WT NFD group value using the ∆∆Cq method. Primer pair sequences are listed in table 1.

3.3.3. Flow cytometry analysis of IgA-coated bacteria

Determination of the average level of IgA coating per fecal bacterium was done by flow cytometry as previously described (Paper I; section 2.3.2).

3.3.4. Oral glucose tolerance test

Before dissection, an oral glucose tolerance test (OGTT) was conducted on overnight fasted mice. Glucose was administered via oral gavage at a concentration of 1.7 g/kg body weight.

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Blood glucose was measured using an Accu-Chek Aviva Nano glucose meter (Roche) immediately before and 15, 30, 60 and 120 minutes after oral administration.

3.3.5. Fasting serum insulin and HOMA IR

Blood was collected from the tail vein from overnight fasted mice. Plasma insulin level was measured by an insulin immunoassay (Shibayagi) as per manufacturer’s instructions. To estimate insulin resistance, the homeostasis model assessment for insulin resistance (HOMA-IR) was calculated using the formula; HOMA IR= (serum fasting insulin (mIU/mL) × fasting blood glucose (mg/dL)/ 405).

3.3.6. Statistical analysis

Results are presented as means ± SEM. All statistical analysis was conducted using GraphPad Prism version 7.00 for Windows (GraphPad Software, USA). Differences between groups were assessed using unpaired Student’s t test. Correlations between the average level of SIgA coating a single fecal bacterium and tight junction proteins as well as cytokines were analyzed using Pearson’s correlation coefficients. P < 0.05 was considered statistically significant in all experiments.

3.4. Results

3.4.1. Ingestion of a HFD results in reduced level of SIgA coating of gut microbiota

Body weight was significantly higher in HFD-fed WT mice than in NFD-fed WT mice in the experiment 1 (Fig 1A). Food intake was also significantly higher in HFD-fed WT mice as

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compared to NFD-fed WT mice (Fig 1B). Similar to our previous research findings, HFD consumption resulted in a significantly lower level of SIgA coating per fecal bacterium in WT mice (Fig 2).

3.4.2. HFD induced reduction in level of SIgA coating of gut microbiota is correlated with diminished ileal barrier function and increased peripheral inflammation associated with DIO

The ileal gene expression levels of the tight junction proteins Ocln and Zo1 were significantly lower in HFD-fed WT mice than in NFD-fed WT mice (Fig 3A). The gene expression level of Cldn1 was also lower in HFD fed mice although the difference was not significant (Fig 3A). The gene expression level of Muc2 was also significantly lower in HFD-fed mice (Fig 3A).

There was a positive correlation between the gene expression levels of the tight junction proteins Ocln, Zo1 and Cldn1 as well as the protein Muc2 with the level of IgA coating per fecal bacterium (r=0.86, P<0.01; r=0.77, P<0.01; r=0.57, P=0.05; r=0.7, P=0.01 respectively) (Fig 3B-E).

The adipose tissue gene expression levels of the inflammatory cytokines Mcp1, Ifng and Tnfa were significantly higher in HFD-fed WT mice as compared to NFD-fed WT mice (Fig 4A). The level of SIgA coating per fecal bacterium was negatively correlated with Mcp1 gene expression (r=- 0.59, P=0.04) and tended to be negatively correlated with Ifng gene expression (r=-0.56, P=0.09) (Fig 4B-C). There was however no correlation between level of SIgA coating per fecal bacterium and Tnfa gene expression (Fig 4D).

3.4.3. Obesity-induced insulin resistance is correlated with the level of SIgA coating of gut microbiota

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The blood glucose was significantly higher in HFD-fed WT mice as compared to NFD-fed WT mice upon glucose tolerance test (Fig 5A). The IAUC was also significantly higher in HFD- fed WT mice as compared to their NFD-fed WT counterparts (Fig 5B). The HOMA- IR index was higher in the HFD-fed WT mice, although the difference was not significant (Fig 5C). The IAUC was negatively correlated with the level of IgA coating per fecal bacterium (r=-0.73 P<0.01) (Fig 5D). HOMA-IR was however not correlated with the level of IgA coating per fecal bacterium (Fig 5E).

3.4.4. Obesity-induced insulin resistance is exacerbated in the absence of IgA

In experiment 2, the body weight did not differ significantly between HFD-fed WT and KO mice (Fig 6A). Similarly, there was no significant difference in food intake between HFD-fed WT and KO mice (Fig 6B). Representative results of the flow cytometry for the detection of SIgA- coated bacteria are shown in Fig. 7A. SIgA-coated bacteria were recognized as both a FITC- and PI-positive population and are shown in the gated sections. HFD-fed KO mice had no IgA coated bacteria. The ileal gene expression level of tight junction proteins Ocln, Zo1 and Cldn1 as well as protein Muc2 did not differ between HFD-fed WT and KO mice (Fig. 8). In addition, there was no difference in the adipose tissue gene expression of inflammatory cytokines Tnfa, Mcp1 and Ifng between HFD-fed WT and KO mice (Fig. 9). Although there was no significant difference in blood glucose between HFD-fed WT and KO mice upon glucose tolerance test (Fig 10A-B), the insulin resistance index HOMA-IR was significantly higher in HFD-fed KO mice (Fig 10C).

The biological significance of decreased secretory immunoglobulin A reactivity against gut microbiota in mice fed with high-fat diet