The initial discovery that IgG sialylation plays a key role in the suppressive activity of IVIg in autoimmunity was a hallmark in the appreciation of the role of glycans in immune responses (16–18, 27). In murine models, sialylated IgGs bind to DC-SIGN, inducing the production of IL-33, an infection-linked cytokine that activates basophils to produce IL-4, leading to the upregulation of the inhibitory Fc receptor FcγRIIb (27, 51). In our study, the IL-33 and IL-4 levels were not different between MGUS and MM patients (**Figure 4**; Table S1 in Supplementary Material), thus in MM the IL-33 level may not be sufficient to induce IL-4 and expression of FcγRIIb. In fact, Musolino et al. (52) found that the IL-33 plasma levels were reduced in MM and were associated with more advanced disease. These observations support the hypothesis that latent infection and inflammation could be the early events for subsets of MGUS and MM, and *via* their pro-inflammatory effects, the hyposialylated IgGs (mc IgGs and in 11% of cases, pc IgGs also) contribute to the inflammatory environment and the progression to myeloma.

Our study shows that inflammation occurs early in myeloma pathogenesis since a very similar chronic state of inflammation was observed in MGUS and MM patients *vs* healthy controls: 35/42 molecules linked to inflammation were similarly increased in MGUS and MM. The similar inflammatory status observed in MGUS, considered a benign condition, and MM, a severe, overtly malignant and often invalidating disease, was unexpected. A such observation was observed by Zheng et al. (53) who showed that only IL-17 was highly increased in MM patients in comparison to MGUS patients but their cohort included 55 MM patients and only 8 MGUS patients. HGF was more strongly expressed in MM. HGF plays an important role in MM, inducing IL-11 and IL-6, two markers of disease activity and poor prognosis in MM (54–56). HGF and IL-11 are anti-inflammatory cytokines; in addition, IL-11 promotes bone destruction by osteoclasts and inhibits bone formation by osteoblasts, thus causing cancer-induced bone lesions (57). We also confirmed that TGF-β is less expressed in MM than in MGUS (58). This could be explained by the antiproliferative and pro-differentiation effects on hematopoiesis of TGF-β *in vivo* (59).

In the context of MM, we found positive correlations with β2-microglobulin concentration and expression levels of IL-9, IL-26, MIP-1β and PDGF-BB (**Figure 5**). β2-Microglobulin helps

patients with hyposialylated or hyper-sialylated pc IgGs. Forty cytokines and 2 cytokine receptors were quantified using the Biorad Luminex technology in the serum of 19 MGUS or SM/MM patients with hyposialylated pc IgGs (hypo), and 16 MGUS or SM/MM patients with hyper-sialylated pc IgGs (hyper). The 6 cytokines found to be more expressed in patients with hyposialylated pcIgGs were interleukin 6 (IL-6), hepatocyte growth factor (HGF), tumor necrosis factor (TNF)-α, TGF-β1, IL-17, and IL-33. Horizontal bars indicate median values ± ranges. Statistical analysis was performed using Mann–Whitney *U* test. \**p* < 0.05, \*\**p* < 0.01, and \*\*\**p* < 0.001. Normal values for IL-6: <9 pg/mL; HGF, median: 195 pg/mL, range: 63–1,283 pg/mL; TNF-α, median: 0 pg/mL, range: 6–98 pg/mL; TGF-β1, median: 47 pg/mL, range: 0–932 pg/mL; IL-17, median: 0 pg/mL, range: 0.22–31 pg/mL; and IL-33, not defined.

to characterize the severity and define the stage and prognosis of MM. Like MIP-1α, MIP-1β plays a role in hematopoiesis and osteoclast recruitment, and MIP-1α/β secretion correlates with lytic bone lesions in MM patients (60, 61). Several cytokines, including VEGF and PDGF-BB, are released by MM tumoral cells and also by endothelial cells, thereby contributing to the marked bone marrow micro-vessel density, a constant hallmark of active MM and of acquired refractoriness of MM plasma cells to conventional therapies (62, 63). Consistently, anti-tumor/vessel dasatinib, an inhibitor of PDGF receptor, significantly delays MM plasma cell growth and angiogenesis *in vivo* (64).

Since IgG hyposialylation is a hallmark of pro-inflammatory state, we investigated whether sialylation of IgG was linked to the secretion of specific pro-inflammatory cytokines. Such studies had never been done previously. We found that patients who have hyposialylated pc IgGs in addition to mc IgGs secrete several proinflammatory cytokines (IL-6, TNF-α, TGF-β, IL-17, and IL-33) or cytokines involved in MM progression (HGF) at significantly higher levels than patients with hyper-sialylated pc IgGs. The increased production of IL-17 may be of interest: in addition to its anti-microbial action, inhibition of Th1 response, and production of pc IgM and IgA, IL-17 has been shown to act directly on the expression of α2,6-sialyltransferase. Moreover, this enzyme is downregulated by IL-17 in autoimmune diseases, leading to decreased IgG sialylation (65). Accordingly, we found an inverse correlation between levels of IL-17 (and IL-33) and the degree of sialylation of pc IgGs in both MM and MGUS. Conversely, the levels of anti-inflammatory cytokines IFN-α2 and IL-13 were positively correlated with mc IgG sialylation. We also found an inverse correlation between the sialylation level of both pc and mc IgG and the leptin level in male patients. An increase in leptin level in serum has been observed in blood malignancies (66, 67) and particularly in newly diagnosed MM (68). This adipokine induces pro-inflammatory IL-1β as well as the expression of IL-6, TNF-α and many genes involved in the growth and metabolism of MM plasma cells (68, 69).

On the basis of our previous (11) and present findings, we propose a schematic model of the relation between chronic

mc IgG sialylation data). Statistical analysis was performed using the Spearman *t*-test.

inflammation/infection and the structure/function of mc IgG in myeloma (**Figure 9**). Over-expression of HGF is observed in MM vs MGUS, as well as IL-22, IL-26, and IL-33 in MM patients with a pathogen-specific mc IgG (MIAA+) vs MM patients with mc IgG of undetermined specificity, is consistent with the presence of a pro-inflammatory microenvironment. Under these conditions, MM plasma cells produce large quantities of hyposialylated mc IgGs, which activate macrophages *via* FcγRs. The resulting secretion by activated macrophages of TGF-β1, TNF-α, and IL-6 stimulates the production of Th17 cells, which secrete IL-17, IL-22, and IL-26. IL-22 is a marker of poor prognosis in MM (70), and IL-17 can induce the downregulation of sialyltransferase activity, thus maintaining the hyposialylation of mc IgG and to a lesser extent, of pc IgGs too (33).

## CONCLUSION

In MGUS, SM, and MM, mc IgGs are hyposialylated compared to pc IgGs from both healthy controls and MPN patients. Mc IgG hyposialylation was lowest in MM, particularly when the purified mc IgG targeted an infectious pathogen. Although the exact mechanisms of IgG hyposialylation in MM remain to be identified, IgG hyposialylation correlated with the overproduction of several cytokines (IL-17, IFN-α2, IL-33, and IL-13) that play a major role in inflammation and anti-microbial response. Altogether, the data suggest that infection, inflammation, and an abnormal immune response are early events for subsets of MM patients.

## ETHICS STATEMENT

The study was performed with the approval of the local ethics committee (# RC12 0085, University Hospital of Nantes) and the Commission Nationale de l'Informatique et des Libertés (CNIL # 912335).

#### AUTHOR CONTRIBUTIONS

JH, SH, AB, and EB-C designed the research, analyzed data, and wrote the paper. AB, JH, SA-M, NM, and HP performed experiments. AT, CR, DC, LG, PM, EP, and FG contributed patient samples and data, and critically read the manuscript. AN contributed to the statistical analysis of data. HP, AN, and SB critically read the manuscript. All authors gave final approval of the version to be submitted to publication and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the article are appropriately investigated and resolved.

## ACKNOWLEDGMENTS

We thank all the colleagues from the Departments of Hematology or Internal Medicine of the University Hospitals of Dijon, Nantes, Paris Saint-Antoine and Tours, who contributed to the diagnosis and care of patients in this study. We also thank Emy Komatsu and Luka Markovic (Winnipeg, MB, Canada) for technical help with mass spectrometric measurements.

## FUNDING

This work was realized in the context of the IHU-Cesti project, which received funds from the French government *via* the Region Pays de la Loire. This work was realized in the context of the LabEX IGO program supported by the National Research Agency (ANR) *via* the "Investment for the future" program ANR-11-LABX-0016-01. The study was also supported by grants from the Comités Départementaux of Loire-Atlantique, Maine et Loire, Vendée and Finistère from the Ligue Nationale contre le Cancer, to EB-C (2013–2014); by a grant from the Cancéropôle Grand Ouest and Région Pays de la Loire, to SH and JH (HII-GO project, 2015–2017); and by a grant from the Cancéropôle Grand Ouest and Région Centre, to EP (2015–2017). The Cancéropôle Grand Ouest and Région Pays de la Loire financed the salary of AB (2015–2016).

### REFERENCES

## SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at http://www.frontiersin.org/article/10.3389/fimmu.2017.01347/ full#supplementary-material.

high performance liquid chromatography: role of glycosyltransferases in the structures. *Cancer Res* (1990) 50:5345–50.

multiple myeloma during autologous stem cell transplantation. *Clin Cancer Res* (2014) 20:1366–74. doi:10.1158/1078-0432.CCR-13-2442

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

*Copyright © 2017 Bosseboeuf, Allain-Maillet, Mennesson, Tallet, Rossi, Garderet, Caillot, Moreau, Piver, Girodon, Perreault, Brouard, Nicot, Bigot-Corbel, Hermouet and Harb. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# Intestinal Microbiome Shifts, Dysbiosis, Inflammation, and Non-alcoholic Fatty Liver Disease

#### Emma T. Saltzman1,2 \*, Talia Palacios 1,2, Michael Thomsen1,2 and Luis Vitetta1,2 \*

*1 Sydney Medical School, University of Sydney, Sydney, NSW, Australia, 2 Medlab Clinical, Sydney, NSW, Australia*

Adverse fluctuations in the distribution of the intestinal microbiome cohort has been associated with the onset of intra- and extra-intestinal inflammatory conditions, like the metabolic syndrome (MetS) and it's hepatic manifestation, non-alcoholic fatty liver disease (NAFLD). The intestinal microbial community of obese compared to lean subjects has been shown to undergo configurational shifts in various genera, including but not limited to increased abundances of *Prevotella, Escherichia, Peptoniphilus,* and *Parabacteroides* and decreased levels of *Bifidobacteria, Roseburia,* and *Eubacteria* genera. At the phylum level, decreased *Bacteroidetes* and increased *Firmicutes* have been reported. The intestinal microbiota therefore presents an important target for designing novel therapeutic modalities that target extra-intestinal inflammatory disorders, such as NAFLD. This review hypothesizes that disruption of the intestinal–mucosal macrophage interface is a key factor in intestinal-liver axis disturbances. Intestinal immune responses implicated in the manifestation, maintenance and progression of NAFLD provide insights into the dialogue between the intestinal microbiome, the epithelia and mucosal immunity. The pro-inflammatory activity and immune imbalances implicated in NAFLD pathophysiology are reported to stem from dysbiosis of the intestinal epithelia which can serve as a source of hepatoxic effects. We posit that the hepatotoxic consequences of intestinal dysbiosis are compounded through intestinal microbiota-mediated inflammation of the local mucosa that encourages mucosal immune dysfunction, thus contributing important plausible insight in NAFLD pathogenesis. The administration of probiotics and prebiotics as a cure-all remedy for all chronic diseases is not advocated, instead, the incorporation of evidence based probiotic/prebiotic formulations as adjunctive modalities may enhance lifestyle modification management strategies for the amelioration of NAFLD.

Keywords: intestinal microbiome, intestinal epithelial cell dysbiosis, dysbiosis, macrophage, inflammation, mucosal immunity, NAFLD

#### INTRODUCTION

NAFLD is a growing public health concern, laying claim to both a steadily rising prevalence as well as an increasingly young age at diagnosis (Welsh et al., 2013; Nobili et al., 2014). These trends reflect the increased rates of risk factors associated with an obesogenic lifestyle and the development of type 2 diabetes mellitus (T2DM) (Targher et al., 2007; Welsh et al., 2013). The prevalence of NAFLD in obese adults or those with T2DM has been reported to be 67.5 and 74%, respectively,

#### Edited by:

*Gayane Manukyan, Institute of Molecular Biology (NAS RA), Armenia*

#### Reviewed by:

*Michael Kogut, Agricultural Research Service (USDA), United States Mario M. D'Elios, University of Florence, Italy*

#### \*Correspondence:

*Emma T. Saltzman<EMAIL_ADDRESS>Luis Vitetta<EMAIL_ADDRESS><EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Microbial Immunology, a section of the journal Frontiers in Microbiology*

Received: *02 August 2017* Accepted: *10 January 2018* Published: *30 January 2018*

#### Citation:

*Saltzman ET, Palacios T, Thomsen M and Vitetta L (2018) Intestinal Microbiome Shifts, Dysbiosis, Inflammation, and Non-alcoholic Fatty Liver Disease. Front. Microbiol. 9:61. doi: 10.3389/fmicb.2018.00061* (Williams et al., 2011; Paquissi, 2016) compared to only 25% in the general adult population (Younossi et al., 2016). As a spectrum of diseases, NAFLD has been associated with significant morbidity and mortality, with advanced forms of the disease expressed as fibrosis, cirrhosis, and hepatocellular carcinoma (HCC).Additionally, insulin resistance (IR) and obesity have been identified as NAFLD risk factors (Gaggini et al., 2013), with NAFLD also reported to increase the risk of T2DM and cardiovascular disease, justly classifying NAFLD as the hepatic manifestation of the metabolic syndrome (MetS) (Adams et al., 2005; Targher et al., 2007, 2010; Dunn et al., 2008; Starley et al., 2010; Gregor and Hotamisligil, 2011; Lumeng and Saltiel, 2011; Dietrich and Hellerbrand, 2014; Paolella et al., 2014; Paquissi, 2016). NAFLD hence presents as a multi-systemic disease (Starley et al., 2010; Paolella et al., 2014). In light of the potential of NAFLD to progress to an ever-increasing prevalence, an appreciation of the molecular mechanisms that facilitate the manifestation of NAFLD disease chronicity and the pathways that trigger the transition across the spectrum of diseases is a pertinent aspect in designing novel effective therapeutic modalities. With the purported pathogenic mechanisms of NAFLD being intertwined with peripheral IR, increased liver lipolysis is reported to contribute to increased levels of hepatic free fatty acids (FFAs) (Paolella et al., 2014). IR simultaneously triggers increased gluconeogenesis and reduced glyconeogenesis, which further increases the production of circulating FFAs (Paolella et al., 2014).

The definition of NAFLD covers a spectrum of liver histologies, ranging from the benign and usually non-progressive simple steatosis (SS) (Tilg and Moschen, 2010; characterized by the accumulation of lipid droplets that exceed 5% of the total weight of the liver) to non-alcoholic steatohepatitis (NASH) which is found in 30% of NAFLD patients and is described as the beginning stages of inflammation and lobular ballooning which results from persistent hepatic injury (Jiang et al., 2015). Chronic inflammation can cause the liver to respond with compensatory tissue repair, a mechanism that initiates fibrosis and even cirrhosis through collagen deposition and scarring—which eventually forms the foundation of hepatocellular cancer (HCC) in extremely rare cases (Tilg and Moschen, 2010; Bieghs and Trautwein, 2014). Systems biology continues to probe the pathophysiology of this disease and the factors that establish it's manifestation and drives disease progression across the spectrum toward severe phenotypes.

The manifestation and progression of NAFLD is tentatively attributed to a range of factors as part of the multiple parallel hits hypothesis, which postulates that NAFLD is the result of inflammation in the liver induced by numerous intestinal-derived or adipose tissue-derived triggers (Tilg and Moschen, 2010). With the first hit said to be the onset and maintenance of SS, and the additional hits of gut-derived endotoxins and pro-inflammatory cytokines from adipose tissue reported to provide the impetus for NASH development and subsequent progression (Day and James, 1998). This hypothesis is flagging the importance of aberrant innate immunity as a central pathway for NAFLD progression (Miele et al., 2009; Tilg and Moschen, 2010) along with stress signaling networks and circulating adipocytokines and pro-inflammatory cytokines (Miele et al., 2009; Tilg and Moschen, 2010).

Although the molecular pathways that lead to the pathogenesis and progression of NAFLD remain poorly understood, it is accepted that inflammation is a major factor in hepatic injury (Bieghs and Trautwein, 2014). Currently, experimental data suggests that interactions of the innate immune system with the different resident liver cell types help perpetuate and maintain adverse inflammatory responses in the liver (Starley et al., 2010; Farrell et al., 2012; Bieghs and Trautwein, 2014). Serum markers of inflammation, including C-reactive protein (CRP), interleukins (ILs), and other general immunity markers are associated with the diagnosis and prognosis of NAFLD (Chiang et al., 2010; Harley et al., 2014), whilst at the cellular level, data has implicated an imbalance in T helper 17 (Th17) cells over regulatory T (Treg) cells, that occurs from an over-differentiation of T helper cells (Hammerich et al., 2011). A disturbance to the equilibrium between Th17 and Treg cells is a key event in the initiation of pro-inflammatory activity.

The innate immune system responds to cell damage or pathogenic invasion through pattern recognition receptors (PRRs), that are expressed intracellularly or on the surface of resident liver cells (Bieghs and Trautwein, 2014). These PRRs are programmed to detect damage-associated molecular patterns (DAMPs) that are released by injured cells or pathogen-associated molecular patterns (PAMPs), which are derived from intestinal bacterial metabolites (Pedra et al., 2009; Takeuchi and Akira, 2010). From a consideration of the consequences of intestinal epithelial dysbiosis, this review hypothesizes that the cascade of signals that activate adverse innate immune system and inflammatory activity implicated in NAFLD pathophysiology are triggered by the continuous release of endotoxins and other intestinal bacterial-derived products which can reach the liver through the gut-liver axis interface.

Resident liver cells have their own PRRs in toll-like receptors (TLRs). Activating these TLRs is an important step in the development of NAFLD as they are responsible for inducing gene transcription that facilitates responses of the innate immune system (Takeuchi and Akira, 2010). Kupffer cells, stellate cells, and hepatocytes amongst others, express TLRs and recognize a large array of PAMPs, which enable pro-inflammatory activity by activating different liver cells. PAMPs and DAMPs as well as irritants from the host's environment are themselves recognized by inflammasomes, receptors of the innate immune system. In response to sensing infectious microbes, inflammasomes are responsible for the pro-inflammatory activity observed in the initiation or manifestation of inflammatory diseases, like NAFLD. NLRP3 is an inflammasome that has been reported to be specifically and critically involved in NAFLD progression, with experimental and clinical data identifying higher levels of expression in NASH-affected subjects.

The intestinal microbiome is central to the narrative that NAFLD manifestation is largely a consequence of dysregulated innate immunity in response to persistent pro-inflammatory activity. The role of the intestinal microbiome is multi-factorial, functioning as an immunological, metabolic, and protective tool for optimal host health. When the intestinal microbiome is in dysbiosis, the health of the host is compromised as the microbiome is unable to maintain control of local homeostasis, increasing intestinal permeability. Disruption to intestinal epithelial homeostasis leads to hepatic exposure to exogenous and endogenous antigens that drives hepatoxic influences via the gut-liver axis interface (Glavan et al., 2016).

#### THE INTESTINAL MICROBIOME AND THE EPITHELIAL BARRIER

The microbial ecosystem of the gastrointestinal tract (GIT) comprises a metabolically and immunologically complex and active organ (Vitetta et al., 2013). Recognized as the most biodiverse and dense microbial site, the intestinal microbiome is estimated to harbor over 1014 bacterial cells (Jiang et al., 2015). Serving as a key influence of host health, the GIT is the site that facilitates the exposure of environmental, dietary, and microbial antigens to the immune system (Vitetta et al., 2013). Existing in a state of symbiotic homeostasis, the intestinal microbiome and the immune system largely co-develop from birth (Nicholson et al., 2012). Subject to an array of complex interactions, dependent on host genetics, lifestyle, dietary and environmental cues, the microbiome and host share a bi-directional relationship, with both parties helping to shape each other's development and composition (Nicholson et al., 2012).

The intestinal epithelial barrier is a dynamic network made up of luminal and mucosal components (Paolella et al., 2014); with an epithelial cell layer interlaced with innate mucosal immunity and neuroendocrine elements, encasing the paracellular space that houses the intestinal microbiome diverse niches (Paolella et al., 2014; Ringel et al., 2015). The single layer of epithelial cells that line the intestines is bound by a tight junction protein (TJP) network, serving to form the physical barrier, which provides protection against potential pathogenic assaults and toxins that increases the risk of systemic sepsis. Intestinal epithelial cells have a rapid time of turnover of between 2 and 6 days (Ramachandran et al., 2000). The TJP network also regulates intestinal permeability, providing the pores and channels for passage of molecules (i.e., water, electrolytes, nutrients) by selective permeability (Paolella et al., 2014). The intestinal barrier is also involved in the co-ordination of responses of the innate immune system, with macrophage/dendritic cell activation contributing to host defenses against microbial-induced systemic infections (Paolella et al., 2014). The protrusions that characterize macrophages/dendritic cells allow for the sensation of potential pathogens that have breached the intestinal mucus layers, the mucosa, as well as those sensed in other parts of the intestinal lumen, resulting in the induction of responses such as phagocytosis and of the acquired immune system through B-cell activation (Kumar et al., 2011; Kinnebrew and Pamer, 2012). **Figure 1** details the maintenance of the homeostatic state of the intestinal barrier.

Intestinal microbial metabolites provide the substrate for the fermentation of complex dietary carbohydrates to produce short-chain fatty acids (SCFAs), as well as assist the host in harnessing maximal energy from dietary consumption (Jiang et al., 2015). The various metabolites exert varying effects on the host, from the beneficial production of signaling molecules (e.g., butyrate), to inducing mucus and other secretions, to provide the triggers that facilitate the innate mucosal system to maintain local homeostasis. In states of dysbiosis, the intestinal barrier increases in permeability as a result of a disruption to the regulation of the epithelial cell-to-cell tight junction protein network. A compromised intestinal barrier can be associated with bacterial translocation from the gut into the systemic circulation increasing the risk of sepsis. Lipopolysaccharides (LPS), a constituent of gram negative bacteria (Jiang et al., 2015), is found to be increased in the systemic circulation, indicative of dysbiosis (Boulangé et al., 2016). LPS has been associated with inducing apoptosis of lymphocytes under in vivo conditions (Norimatsu et al., 1995; Nielsen et al., 2012; Jiang et al., 2015) demonstrating an immune-modulatory effect. Studies have posited that a loss of lymphocytes in the intestinal mucosa is a consequence of intestinal epithelial dysbiosis and subsequent release of metabolic endotoxins (Jiang et al., 2015). LPS has also been implicated as an inductor of a pro-inflammatory environment which is conducive to MetS, IR and T2DM (Cani et al., 2008). Gram-negative bacteria containing LPS are therefore hypothesized to contribute to NAFLD development. Furthermore, dysbiosis and elevated systemic LPS can be envisaged as markers of intestinal toxicity (Nolan, 2010). Intestinal toxicity driven dysbiosis supports local mucosal inflammatory responses that is concomitant with an increase in intestinal permeability. This combined disruption of the intestinal barrier/mucosal immunity activity can promote and mediate NAFLD pathogenesis via the gut-liver axis (Littman and Pamer, 2011; Wieland et al., 2015).

## THE GUT-LIVER AXIS

The venous system of the portal circulation defines the gut-liver axis and highlights the close anatomical proximity and functional interactions of the gastrointestinal tract and the liver (Paolella et al., 2014; Brandl et al., 2017). The axis is described as a means of enhancing interactions between metabolites of the intestinal microbiome and receptors on the liver, which can trigger a cascade of events that culminates in IR, inflammation of the liver, and eventually the development of liver fibrosis (Paolella et al., 2014). The anatomical and functional link between the gut and liver delivers 70% of hepatic blood supply via the portal vein. The portal vein is the direct venous outflow from the intestines and thus when the intestinal mucosal barrier is compromised it exposes hepatic tissue to toxic factors derived from the intestines. Therefore, various metabolites produced by intestinal bacteria that reach the liver, have been linked to the manifestation of simple steatosis and NASH (Raman et al., 2013). Dynamic shifts in the gut-liver axis, contributed by either the physical barrier, the microbiome or the liver itself, are a result of alterations to the permeability of the intestinal epithelium and or microbial composition that have been implicated in NAFLD manifestation (Mehal, 2012). Experimental and clinical evidence increasingly implicate dysfunctions of the gut-liver axis in the development

2015; Robinson et al., 2015; Nakahashi-Oda et al., 2016) Adapted from Peterson and Artis (2014).

and progression of NAFLD through small intestinal bacterial overgrowth (SIBO) in conjunction with intestinal dysbiosis and increased permeability (Compare et al., 2012; Li et al., 2013; Miele et al., 2013; Vajro et al., 2013; Paolella et al., 2014). Recent experimental and clinical studies suggest that the gastrointestinal microbiome affects NAFLD pathogenesis through pathways that (i) facilitate metabolism and energy harvesting (Turnbaugh et al., 2006; Jiang et al., 2015), as described from high-fat fed mice models treated with high levels of pro-inflammatory cytokines that promote NAFLD development (Le Roy et al., 2013); (ii) dynamic interactions with the host's innate immune system where NAFLD is reported consequent to disrupted local immune cell functionality (Su et al., 2012).

#### INTESTINAL MICROBIAL COMPOSITION AND NAFLD

Widespread biodiversity exists in the microbial ecosystems of humans, particularly in the intestinal tract. However, despite the extensive variety of bacteria, four main phylum dominate in the intestines: Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria (Mokhtari et al., 2017), with up to 90% of microbes estimated to belong to the Firmicutes and Bacteroidetes phyla (Eckburg et al., 2005). In both human and experimental model based studies, NAFLD has been associated with altered microbiome abundance, composition and dysbiosis (Wigg et al., 2001; Mouzaki et al., 2013; Zhu et al., 2013). Analyses have also correlated changes in microbiota composition with change in disease severity (Shavakhi et al., 2013; Eslamparast et al., 2014, 2015; Rahimlou et al., 2015; Yari et al., 2016).

In reviewing the literature, studies that have analyzed the intestinal microbial composition of NAFLD patients in comparison to healthy controls have reported identifying patterns or trends that can be associated with NAFLD development (Harris et al., 2012).

Studies that have profiled the intestinal microbiome of NAFLD patients report that specific configurational and compositional shifts are associated with intestinal epithelial

cell dysbiosis and the elicitation of pro-inflammatory immune responses, central to NAFLD manifestation and progression (Kirpich et al., 2015). Specific bacteria have been associated with NAFLD phenotypes, serving as both antagonists and protagonists in NAFLD pathogenesis. Studies which profiled the intestinal microbiome of healthy controls and NAFLD patients across the spectrum, were able to identify families, genera and phyla that differed significantly in their abundance between the healthy controls and those with a NAFLD diagnosis. Whilst data is inconsistent regarding the association between the intestinal microbiome profile and NAFLD, patterns are emerging which highlight potential relationships between bacterial types and host health (Lau et al., 2015). A study comparing subjects diagnosed with NAFLD compared to lean adults, reported that gram negative bacteria were significantly enriched (P =0 .009) and gram positive bacteria were markedly decreased (P = 0.001) in the NAFLD cohort (Wang et al., 2016). Findings from similar studies confirm the strong relationship between the composition and configuration of the intestinal microbiome and fatty liver histologies, suggesting that adverse shifts in intestinal microbiome profiles are related to the development of NAFLD (Wang et al., 2016). In a prospective cross sectional study, a 20% increase in the Bacteroidetes phylum (p = 0.005) and a 24% decrease in Firmicutes (p = 0.002) was found in healthy controls in comparison to NAFLD patients (Wang et al., 2016). Interestingly, among the species belonging to the Firmicutes phylum, SCFA-producing bacteria were significantly decreased. Specific microbiome signatures of intestinal bacteria that are reported to be associated with significant reductions in butyric acid (Consolandi et al., 2015) may comprise a significant marker for the depletion of intestinal bacterial species that are important for the maintenance of intestinal barrier integrity and innate mucosal immunity equilibrium. However, currently it is difficult to identify which microbiome differences are causal and which are coincidental in the development of intestinal barrier dysbiosis and moreover NAFLD. Variations between studies, which profile microbiome composition of NAFLD patients, may in part be accounted for by different analytical techniques that have been employed. Furthermore, differences in study design, including anthropometric measures, markers used for NAFLD diagnosis as well as ultra-sonographic vs. biopsy NAFLD diagnosis adds additional discrepancies. As such Mouzaki et al. (2013),reported an inverse relationship between NASH diagnosis and the proportion of the phyla Bacteroidetes detected. These results were contrasted by Zhu et al (Zhu et al., 2013) who reported that NASH diagnosis was accompanied by higher levels of alcohol-producing bacteria and endogenous levels of ethanol, a result that was supported by Wong et al. (2013).

The intestinal microbial variations were also observed at the genus level, with data purporting to Ruminococcus and Roseburia genera being shown to be inconclusive. Whilst Zhu et al. (2013) and Raman et al. (2013) reported a nonsignificant decrease in the abundance of Ruminococcus in NAFLD patients compared to a group of healthy controls, whereas Del Chierico et al. (2017) and Jiang et al. (2015) found an increase in the genus' abundance in NAFLD patients.

Despite the various limitations, preliminary studies highlight and support the hypothesis that configurational shifts in the intestinal microbiome composition may contribute to the development and progression of NAFLD. Whilst further studies on a larger scale with accurate measures and controlled variables are warranted, the potential contribution of intestinal microorganisms and their metabolites are implicated in the pathophysiology of NAFLD. Studies that administer probiotics/prebiotics, which posit to encourage the intestinal microbiome to re-establish intestinal-mucosal macrophage crosstalk homeostasis that then translates to reducing the progression of NALFD are very much warranted.

#### MECHANISMS LINKING THE INTESTINAL MICROBIOTA AND NAFLD

Research identifies several mechanisms by which the intestinal microbiome cohort-arrangement can affect NAFLD pathogenesis and maintenance. Increased intestinal permeability (Jandhyala et al., 2015), small intestine bacterial overgrowth (SIBO) (Zhu et al., 2013) and elevated serum endotoxin like lipopolysaccharide (LPS) (Brun et al., 2007; Soares et al., 2010), have been reported by studies with NAFLD patients, with varying disease severity and staging (Elshaghabee et al., 2016). LPS, a component of gramnegative bacteria, is elevated in cases of bacterial overgrowth and increased intestinal permeability, yielding hepatoxic effects through the activation of TLR4 and initiation of a cascade of proinflammatory innate immune responses (Wigg et al., 2001; Soares et al., 2010).

Experimental and clinical data suggests that SIBO and a disturbed intestinal epithelial barrier are involved in NAFLD pathogenesis (Bode et al., 1987; Purohit et al., 2008; Wan et al., 2016). Furthermore, investigations have shown that the serum from NAFLD patients have elevated levels of LPS-binding protein, TLR-4, and TNF-α in hepatic tissue (Ruiz et al., 2007; Wan et al., 2016).

The gut microbiota also contributes to NAFLD pathogenesis through enriched numbers of ethanol-producing bacteria, primarily Escherichia coli (Small et al., 2013; Zhu et al., 2013; Jiang et al., 2015). The alcohol produced by these bacteria are reported to be involved in compromising intestinal barrier integrity which instigates inflammatory activity and ultimately hepatoxic events. Ethanol is a common and dominant metabolite of numerous resident intestinal microbes. As a product of hetero-lactic organisms, endogenously produced ethanol is implicated as a pro-inflammatory hepatoxic factor in NAFLD pathogenesis (Cope et al., 2000; Baker et al., 2010). Linked with increased concentrations of serum ethanol, enrichment in the presence of alcohol-producing intestinal bacteria, like E. coli, has been demonstrated to increase intestinal epithelial permeability (Aron-Wisnewsky et al., 2013; Jiang et al., 2015).

A prelude to the liver's averseness to excessive accumulation of FFAs, is intestinal dysbiosis. Dysbiosis is the concept that describes compositional alterations away from the conventional symbiotic intestinal microbiota that may be associated with pathology within the host and is visually described in **Figure 2**. Herein we further posit that compositional alterations in the intestinal microbiota adversely affect the intestinal epithelial barrier exacerbating epithelial cell dysbiosis. It has been shown that intestinal epithelial cell disruption can directly adversely affect intestinal resident macrophages and act as critical effector cells in the initiation of inflammation in the pathogenesis of metabolic diseases (Chawla et al., 2011). Disturbances of the TJP network which link the epithelial cells to form the intestinal barrier is a central regulatory mechanism, facilitating selective permeability across the intestinal mucosa and limiting bacterial translocation. Examining the duodenum of NAFLD patients and healthy adults has revealed that in comparison to NAFLD patients, (Jiang et al., 2015) the TJP network was significantly more intact in the duodenum of a healthy adult, with regular alignment and extensive abundance of the microvilli(Jiang et al., 2015). These observations are in stark contrast to the significantly wider gaps and disrupted TJPs reported in NAFLD patients, suggesting a loss of barrier integrity with a consequent increase in bacterial translocation through increased intestinal permeability (Briskey et al., 2016). Additional assessment of the serum biomarkers of the TJPs, including occludin proteins, which are structural components of the tight junctions, have been reported with significantly higher levels in the intestinal mucosa of healthy adults compared to NAFLD patients (Jiang et al., 2015). Measuring the serum levels of the proteins that comprise the structural backbone of the intestinal TJP network lends further supportive data to the hypothesis that intestinal mucosal permeability is greater in NAFLD patients than lean subjects or controls, suggesting intestinal epithelial dysbiosis is a causal factor in NAFLD pathogenesis.

With the establishment of the intestinal microbiota as a participant in the onset and maintenance of low-grade systemic inflammation, the probing of the intestinal microbiome as a potential therapeutic target for extra-intestinal inflammatory conditions, such as NAFLD begun.

The supposition that the intestinal microbiome could indirectly and adversely influence the physiological function of an end–organ such as the liver, by contributing pro– inflammatory activity in the intestinal mucosa, is a novel concept with biological plausibility. As an example, the uptake of Shigatoxin from the pathogen enterohemorrhagic E. coli by M cells and the underlying macrophages in the Peyer's patches is a critical step that teaches about bacterial translocation. This step has been correlated to the efficiency of the infection by the pathogen (Etienne-Mesmin et al., 2011). Numerous bacterial pathogens and their products cross the epithelial barrier though M cell junctions that are then subsequently captured by intestinal resident macrophages (Alisi et al., 2017). Moreover, the LPS components of bacteria are ligands of TLR4 that are expressed on various immune cells, including intestinal macrophages (Vijayan et al., 2017). TLR4 in the M1 configuration is a mediator of inflammation that may imply that increased LPS/TLR4 signaling could be a driving factor in the accelerated inflammation process in patients with NAFLD (Alisi et al., 2017). LPS also induces activation of genes on macrophages such as the early growth response gene 1 (EGR1) as well as the LPS-induced expression of TNF-α, an action that is directly mediated through EGR1 and NF-kB (Xu et al., 2001). Therefore bacterial products that activate macrophages and other immune cells to produce proinflammatory mediators can trigger inflammation in an end organ such as the liver (Tateya et al., 2013). Signals released in response to microbial dangers are absorbed on a backgorund of increased and dysregulated intestinal barrier permeability. These signals are recognized by PRRs, including TLR-4 (Szabo et al., 2010; Wan et al., 2016), and when sensed by NLRP3, support the hypothesis that inflammasome-driven microflora are potential drivers of NAFLD onset (Wan et al., 2016).

Intestinal homeostasis is pivotal in optimal functionality of the innate immune system and hinges on macrophages eliminating pathogenic bacteria and their particles (Vitetta, 2016). Activated macrophages play a dual role within the innate immune system (Sansonetti, 2002; Vitetta, 2016). Firstly, they help to elicit appropriate immune responses to detected microbial proteins by facilitating the presentation of antigens to T lymphocytes (Sansonetti, 2002; Vitetta, 2016). Secondly, activated macrophages serve as a secretory source for an array of cytokines that regulate the activation of T cell lymphocytes, including IL-1, INF–α, and cytotoxic proteins (Sansonetti, 2002; Vitetta, 2016). The overall action of the macrophage within the immune responses rely on their ability to neutralize exogenous antigens, cellular debris, insoluble particles, and activated clotting factors via phagocytic activity (Tacke, 2017).

#### REPRISE

NAFLD's pathway to pathogenicity is characterized by the presence of ectopic fat within hepatocytes that results from an imbalance in the levels of lipogenesis and lipolysis (Machado and Cortez-Pinto, 2014). Triglycerides are synthesized from FFAs that are reported to accumulate in the liver. Therefore, it is envisaged that the concentration of FFAs function as a regulator of lipogenesis in the liver.

Previous studies have associated bacterial phyla, families, or even single genera with obese or lean phenotypes, with an increased lactobacilli count and decreased Bacteroidetes presence associated with leanness (Armougom et al., 2009). In support of this, an increased abundance of genus' of the Bifidobacterium animalis or Lactobacillus species were associated with weight management and a healthy body weight (Million et al., 2012). Lactobacillus reuteri has specifically been identified as being associated with an obese phenotype (Million et al., 2012). Assessing intestinal microorganisms for possible correlations with NAFLD is a biologically plausible next step in progressing an understanding of how much influence the intestinal microbiome as a metabolic and immunological organ may have on the development and progression of NAFLD.

Methodological and technological difficulties have largely prevented robust and definitive data from studies that specifically assess the intestinal microbiota of adults with NAFLD and the health of the intestinal mucosal barrier as well as a need for further knowledge into what constitutes a healthy microbiota. When the mucosal barrier of the intestine, which also serves as the largest immune area of the intestinal immune system, is impaired and disrupted, the liver is exposed to intestinal-derived bacterial factors, which are potentially hepatoxic through the gut-liver axis.

A majority of the current literature details the involvement of the innate branch of the immune system in pro-inflammatory pathways leading to NAFLD pathogenesis and progression. However, the adaptive immune system is also implicated in NAFLD development (Ganz and Szabo, 2013; Sutti et al., 2016). Linking the innate and adaptive branches, natural killer (NK) cells are abundant in hepatic tissue and have been reported to influence the development of liver injury and fibrotic deposition that spark NASH materialization (Ganz and Szabo, 2013). Studies in both animal and human models have found a decrease in circulating NK cells in obese subjects compared to lean counterparts (Ganz and Szabo, 2013), with further exploratory investigations suggesting a reduction in their levels and thus activity may in turn increase the sensitivity of obese patients to develop progressive forms of NAFLD, including cirrhosis (Radaeva et al., 2006). A subset of NK cells, the natural killer T (NKT) cells, also known for their exhibition of both innate and adaptive immunity features, serve to regulate hepatic immune responses by secreting both Th1 and Th2 cytokines (Godfrey et al., 2000). Experimental and clinical data indicates that a depletion in NKT cells can lead to the chronic pro-inflammatory environment that can accompanies hepatic steatosis (Li et al., 2005; Ronchi and Falcone, 2008).

With no effective medication having yet been tested for managing or treating NAFLD and the only universally accepted treatment strategy being lifestyle modifications that focus of weight loss, novel therapeutic agents are being pursued in an endeavor to address the rise of NAFLD as one of the most common non-communicable liver disease world-wide (Volynets et al., 2012).

Whilst lifestyle modification recommendations encourage weight loss, this approach requires significant commitment and efficiency decreases over the long term due to waning dedication. Intestinal microbial manipulation through the administration of probiotics presents as an attractive therapeutic adjunct. In an attempt to reduce intestinal epithelial inflammation, probiotics shift the intestinal microbial community toward beneficial bacterial communities such as the Parabacteroides, Prevotella, and Oscillibacter (Ohland and MacNaughton, 2010). These microbial communities are well known to produce antiinflammatory metabolites such as SCFAs (Schwiertz et al., 2010). SCFAs, such as butyrate, serve as important facilitators in the harvesting of energy and harnessing it for peripheral tissues and the intestinal epithelia (Elshaghabee et al., 2016). Oscillibacter and Parabacteroides are associated with T-cell differentiation by enhancing and maintaining the IL-10 producing Treg cells (Arpaia et al., 2013). Moreover, a probiotic formulation that attenuated hepatocellular carcinoma in a murine model offered further insight on how the intestinal microbiota influences the regulation of T-cell differentiation of mucosal immunity in the intestines and in turn, there is down-regulation of the level of pro-inflammatory cytokines (Li et al., 2016). A recently completed murine study by our group reported attenuation of steatosis by 60% in a high fat diet model of NAFLD (Briskey et al., 2016). As such the administration of probiotics to attenuate the progression of NAFLD is both clinically plausible and very much warranted.

Despite increasing focus and attention directed at identifying the mechanisms by which NAFLD develops and progresses, ambiguity remains surrounding the driving factors and molecular pathways that result in NAFLD onset. Immunological mechanisms, including the collaboration of the consequences of innate immunity, adaptive immunity, and TLR receptor

#### REFERENCES

signaling dysfunction with the gut-liver axis are each posited to contribute to disease pathogenesis and maintenance.

This narrative review has highlighted the requisite for the completion of a systematic literature review detailing the association between innate immune responses triggered by intestinal epithelial inflammation and dysbiosis and the onset of extra-intestinal pathologies, such as NAFLD. The intestinal microbiome is a significant environmental factor in NAFLD pathogenesis, specifically through effects on intestinal barrier integrity. A review of the literature which explores the correlation between changes in intestinal integrity, intestinal permeability, and therefore endotoxin translocation will help elucidate the specific patterns or profiles of intestinal microorganisms that are of interest in NAFLD manifestation and therefore relevant for therapeutic target purposes. Furthermore, such a review may also define bacterial species that elicit a hepatoprotective effect on the microbiome and extra-intestinal inflammation.

#### AUTHOR CONTRIBUTIONS

ES and LV: Conception and design of commentary, review; ES, LV, MT, and TP: Read, amended and approved final version of manuscript.

#### FUNDING

LV has received National Institute of Complementary Medicine and National Health and Medical Research Council of Australia competitive funding and Industry support for research into biocompounds and probiotics. ES, LV, and MT participate in research on probiotics in Medlab Clinical's research laboratory facility in Sydney, Australia.

endotoxin, and medical consequences: summary of a symposium. Alcohol 42, 349–361. doi: 10.1016/j.alcohol.2008.03.131

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest

Copyright © 2018 Saltzman, Palacios, Thomsen and Vitetta. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Fructose: A Dietary Sugar in Crosstalk with Microbiota Contributing to the Development and Progression of Non-Alcoholic Liver Disease

#### *Jessica Lambertz1 , Sabine Weiskirchen1 , Silvano Landert2 and Ralf Weiskirchen1 \**

*1 Institute of Molecular Pathobiochemistry, Experimental Gene Therapy and Clinical Chemistry (IFMPEGKC), RWTH University Hospital Aachen, Aachen, Germany, 2Culture Collection of Switzerland AG (CCOS), Wädenswil, Switzerland*

#### *Edited by:*

*Wesley H. Brooks, University of South Florida, United States*

#### *Reviewed by:*

*Jieliang Li, Temple University, United States Ruchi Tiwari, Veterinary University (DUVASU), India Maryam Dadar, Razi Vaccine and Serum Research Institute, Iran Ashok Munjal, Barkatullah University, India*

> *\*Correspondence: Ralf Weiskirchen<EMAIL_ADDRESS>
#### *Specialty section:*

*This article was submitted to Microbial Immunology, a section of the journal Frontiers in Immunology*

*Received: 14 July 2017 Accepted: 01 September 2017 Published: 19 September 2017*

#### *Citation:*

*Lambertz J, Weiskirchen S, Landert S and Weiskirchen R (2017) Fructose: A Dietary Sugar in Crosstalk with Microbiota Contributing to the Development and Progression of Non-Alcoholic Liver Disease. Front. Immunol. 8:1159. doi: 10.3389/fimmu.2017.01159*

Fructose is one of the key dietary catalysts in the development of non-alcoholic fatty liver disease (NAFLD). NAFLD comprises a complex disease spectrum, including steatosis (fatty liver), non-alcoholic steatohepatitis, hepatocyte injury, inflammation, and fibrosis. It is also the hepatic manifestation of the metabolic syndrome, which covers abdominal obesity, insulin resistance, dyslipidemia, glucose intolerance, or type 2 diabetes mellitus. Commensal bacteria modulate the host immune system, protect against exogenous pathogens, and are gatekeepers in intestinal barrier function and maturation. Dysbalanced intestinal microbiota composition influences a variety of NAFLD-associated clinical conditions. Conversely, nutritional supplementation with probiotics and preobiotics impacting composition of gut microbiota can improve the outcome of NAFLD. In crosstalk with the host immune system, the gut microbiota is able to modulate inflammation, insulin resistance, and intestinal permeability. Moreover, the composition of microbiota of an individual is a kind of fingerprint highly influenced by diet. In addition, not only the microbiota itself but also its metabolites influence the metabolism and host immune system. The gut microbiota can produce vitamins and a variety of nutrients including short-chain fatty acids. Holding a healthy balance of the microbiota is therefore highly important. In the present review, we discuss the impact of long-term intake of fructose on the composition of the intestinal microbiota and its biological consequences in regard to liver homeostasis and disease. In particular, we will refer about fructose-induced alterations of the tight junction proteins affecting the gut permeability, leading to the translocation of bacteria and bacterial endotoxins into the blood circulation.

Keywords: fructose, gut-liver-axis, inulin, insulin resistance, microbiota, SCFA, probiotics, prebiotics

**Abbreviations:** AMPK, adenosine monophosphate kinase; BDL, bile duct ligation; DNL, *de novo* lipogenesis; ENL, enterolactone; F-1-P, fructose-1-phosphate; FOS, fructooligosaccharides; IBS, irritable bowel syndrome; IL-1β, interleukin-1β; IL-6, interleukin-6; LPS, lipopolysaccharide(s); MD, Mediterranean diet; NAFLD, non-alcoholic fatty liver disease; NASH, non-alcoholic steatohepatitis; PAMP(s), pathogen-associated molecule(s); SCFA, short-chain fatty acid(s); TLR(s), toll-like receptor(s); TNF-α, tumor necrosis factor α.

#### DIET INFLUENCES MICROBIOTA

Diet and connected nutritional status depict important, modifiable factors of human health. Major determinants are gut microbial community (microbiota) and its genes (microbiome) (1, 2). In turn, the gastrointestinal microbiota is highly influenced by the diet of the host. Turnbaugh et al. showed that a shift from a Mediterranean diet (MD) rich in polysaccharides to a Western diet, high in fat and sugar, low in fiber, is able to alter microbiota within a day (1). Similarly, diets high in sugar significantly decrease the microbial diversity in the gut after just 1 week (3).

Also another more recent study has shown that the consuming of a MD promotes a gut flora enriched in polysaccharidedegrading microbes and end products of polysaccharide fermentation, whereas in contrast, a Western diet leads to a community of microorganisms in the digestive tract that mostly contain proteolytic microbes and end products of protein and fat metabolism (4).

During metabolism, a part of the ingested food such as dietary fiber or resistant starch escapes digestion in the small intestine, reaches the colon and is fermented by gut microbes, which produce products such as short-chain fatty acids (SCFA), trimethylamine, ammonia, and hydrogen sulfide, which have beneficial impact on its host. With the diet also the economy of microbiota changes, because the different strains favor different environment and nutrients. Differences in microbial structure and function are reflected in the diversity of intestinal metabolites. For example, SCFA such as acetate, butyrate and propionate representing end products of fermentation of complex carbohydrates, were significant higher in samples taken from Egyptian teenagers consuming a MD than in teenagers from the United States absorbing a typical Western diet (4). SCFA are known to inhibit inflammation and obesity (5), while the end products resulting from lipid and protein degradation are associated with arteriosclerosis and colon cancer (6). Moreover, intestines of teenagers consuming a Western diet have elevated amino acid content and higher levels of lipid metabolism-associated compounds, and higher concentrations of 1-methylhistamine indicating allergic reactions and suggesting that the intestinal microbiota is majorly determined by the host diet (4). In line with these findings, the Western diet was found to be one of the causes for metabolic diseases such as non-alcoholic fatty liver disease (NAFLD).  In contrast, the consumption of components of the MD enriched in olive oil, fish, nuts, whole grains, fruits, and vegetables is negatively correlated with the pathogenesis of NAFLD (8).

#### FRUCTOSE IN HUMAN DIETS

Fructose is an integral part of human diets. This monosaccharide appears naturally in ripe fruits, honey, and in small amounts in vegetables including carrot, onion, sweet potato, and paprika. In the 1960s, fructose has been shown to have positive effects in the treatment of diabetes because it does not need insulin to be metabolized. Fructose feeding had no influence on fasting blood glucose and its excretion into the urine (9, 10). This sugar was described as a "useful therapeutic agent" stabilizing blood glucose in diabetic patients to the normal fasting level, improving the overproduction of acetone, restoring the nitrogen balance, and decreasing the loss of water (9). All these changes were induced without any changes in insulin therapy, just by substitution of fructose for glucose (9). Similarly, intravenous administration of fructose was effective in the treatment of diabetic ketosis (11). In the 1960, high fructose corn syrup was inserted in the food industry as a substitute of sugar and the intake increased, while the clinical importance of this sugar is still discussed controversially and in the focus of research (12). In particular, fructose was identified as a sugar affecting lipid metabolism by rising plasma triglycerides and fasting plasma free fatty acids. Therefore, the usage of this sugar was challenged for treatment of diabetes (10). Today, the view on fructose has changed dramatically. It is now handled as a risk factor in the development of obesity and several metabolic disturbances. In addition, fructose worsens symptoms in irritable bowel syndrome (IBS), an inflammatory condition characterized by abdominal pain, diarrhea, and bloating (13). Human studies performed in patients suffering from IBS showed a high prevalence of fructose malabsorption up to 64% (14). Interestingly, also patients tested negative for disorders in fructose metabolism showed abdominal symptoms after fructose ingestion suggesting fructose intolerance as a highly common condition (13). In both studies, 25 g of fructose were orally administered in a fructose breath test to prove malabsorption. Noteworthy, beverages usually contain 10 g sugar/100 mL. On the other side, if beverages are sweetened with high-fructose corn syrup such as HFCS-55 containing 55% of fructose, consumers absorb 27.5 g fructose drinking a volume of 500 mL. This amount is more than tested in the mentioned human studies and again emphasizes the fact that fructose in beverages and food nutrients should be critically considered as risk factors for inflammatory diseases.

#### MICROBIOTA IMPACTS THE HOST IMMUNE SYSTEM

Bacteria in the gut are responsible for digestion and producing essential vitamins and minerals (2). In addition, they are important for host physiology, digestion of indigestible food materials, and production of bile acids (15). Moreover, the gut microbiota has an influence on several immune functions, protects against pathogens, and joins in the maturation of the gut barrier (16).

Our intestine is an individual immunological site where interaction between microbiota and its host takes place (17). If the homeostasis between microbiota and host is disturbed, inflammation and cancer can occur (17). The crosstalk of the intestinal microbiota with the immune system of the host can modulate insulin resistance and intestinal permeability (16). Furthermore, it has an impact on the body weight. This could be demonstrated by transplant experiments in which gut communities isolated from obese mice fed a Western diet were transplanted into germfree recipient mice. The colonization produced adiposity in the recipient mice within 2 weeks (1).

### SHORT-CHAIN FATTY ACIDS, METABOLITES OF MICROBIOTA AFFECT THE IMMUNE SYSTEM AND INFLUENCE DISEASE PROGRESSION

Not only the microbiota itself but also its products influence the metabolism, energy intake and immunity (18). The human digestive system is restricted of debranching enzymes necessary to digest fibers and higher non-digestible carbohydrates such as pectin, inulin, gums, and cellulose (15). When these nutrients reach the distal gut, they stimulate growth and activity of bacteria that can ferment these compounds (19). During this microbial fermentation, SCFAs are formed influencing gut health and affecting as signaling molecules metabolism and function of peripheral tissues (20). There are three main SCFA, namely acetate, propionate and butyrate, which are the most important gut-derived products, acting as signal transduction molecules with epigenetic impact (21). Almost 10% of the human energy requirement per day is provided by SCFA *via* the host colonic epithelial cells (22). In particular, butyrate is the main energy source for normal colonic epithelial cells, protecting against colorectal, cancer, and inflammation (23). Especially, the fermentation of butyrate is highly inducible by lactate through lactate-utilizing bacterial strains converting starch and fructooligosaccharides (FOS) into butyrate (24, 25). In line, high intake of non-digestible fibers caused an accumulation of lactate exhibiting a low pKa value and provoking metabolic acidosis (25). Therefore, the utilization of lactate by lactate-utilizing microbiota is important in the context of SCFAs formation. SCFAs are absorbed by both passive diffusion and *via* monocarboxylic acid transporters (26). However, the production and molecular effects of SCFAs is presently controversially discussed. On one hand, SCFAs provide energy for the body (17, 21), while on the other site they can lead to extra fat deposition in the body and obesity (27). Moreover, SCFAs can directly influence several different functions such as satiety and host metabolism, improve glucose homeostasis, and insulin sensitivity (20). Although SCFAs are a rich source of calories, their intestinal production is associated with lean body weight, reduced inflammation, and increased satiety (28). They are ligands for receptors regulating appetite, inhibiting gastric emptying, while at the same time stimulating insulin secretion. Thereby SCFAs influence eating habits and the metabolism of the host and prevent exaggerate energy intake and obesity (15). Moreover, butyrate is an important molecule in the lipid metabolism of the host used to synthesize cholesterol and palmitate, while propionate is the principal gluconeogenic substrate decreasing hepatic glucose production (22, 29). Furthermore, butyrate has direct anti-inflammatory potential in the gut and the brain that helps to maintain the gut-barrier integrity and protects against the influx of toxins (29, 30).

Acetate promotes antilipolytic activity and it may also have metabolically beneficial effects in white adipose tissue (17). Furthermore, it mediates effects in the central nervous system suppressing appetite (31). So it is obviously that SCFAs affect metabolism and energy homeostasis by impacting glucose homeostasis, insulin sensitivity, skeletal muscle and liver tissue functions, adipose tissue biology (20, 21). With regard to the current literature, there is no reported direct interaction between the monosaccharide fructose and SCFA. Fructose consumption influences the microbiota and therefore affects the composition of SCFA in the gut. Interestingly, cross-feeding studies between *Bifidobacterium* and two acetate-converting, butyrate-producing strains (i.e., *Anaerostipes caccae* DSM 14662 and *Roseburia intestinalis* DSM 14610) in which fructose was used as the sole energy source allowed oligofructose breakdown by the strains not able to degrade the substrate itself (32). In this coculture study, *Bifidobacterium* releases small amounts of free fructose and acetate during degradation of fructooligosacharides.

Noteworthy, all three SCFA were able to decrease tight junction permeability, protecting barrier properties during increased microvascular leakage, which is the reason for several disease conditions (33). However, the effective concentration of each SCFA necessary to mediate these effects is different. The most effective concentration of butyrate (0.5 mmol/L) to decrease paracellular permeability was lower than that of propionate (1 mmol/L) and acetate (32 mmol/L) suggesting that in particular butyrate producers in the gut strengthens the gut barrier (33). SCFAs can influence the enteric nerve system, stimulating motility and secretion activity or affecting immune cells thereby reducing inflammation and tumorigenesis (34). Similar to the effect of histone deacetylases, SCFAs have anti-inflammatory and immune-suppressive functions and act as modulators in immune homeostasis and cancerogenesis (17, 21).

Short-chain fatty acids are able to reduce the pH of the gut, altering the composition of microbiota. Changing the pH from 5.5 to 6.7 favors the population of gut microbiota that produces propionate, while reducing the pH to 5.5 favored bacteria producing butyrate (35). This process maintains the gut homeostasis and economy. As outlined above, butyrate is already more effective at lower concentrations than propionate and acetate, and it need to be considered that butyrate at higher concentrations may provide too much energy which can promote obesity.

Dietary fiber is known to promote weight loss and improve glycemic control. High fat diet enriched in SCFAs protected from obesity and improved glucose tolerance (36). However, studies on propionate have shown that the effects of SCFA are tissue specific. While propionate-dependent gluconeogenesis had a beneficial effect on metabolic health in the small intestine, it was detrimental in the liver (17).

The gut microbiota also produces diet-dependent many other metabolites such as secondary bile acids and amino acid derivatives that have essential functions in the body. An increased production of intestinal bile acid occurs in a high fat diet. Bile plays important roles in lipid and carbohydrate metabolism and also in mediating inflammatory responses (37). Diets rich in saturated fatty acids can change the composition of the bile acids and promote dysbiosis. The changed microbiota is then able to inhibit hepatic gluconeogenesis and glycolysis and impact insulin sensitivity (16). As a consequence, bile-sensitive bacteria, such as *Prevotella* will be less prevalent, and more bile-tolerant bacteria will be predominant. In contrast to these findings, the bile acids chenodeoxycholic acid and cholic acid have been shown to improve the conditions of fructose-induced NAFLD by regulating intestinal transepithelial permeability and prohibiting the translocation of bacterial endotoxin from the gut into the portal plasma, thereby diminishing the activation of hepatic Kupffer cells (38). Additionally, these bile acids protected against the loss of tight junctions proteins in the intestinal epithelium. *Vice versa* the composition of bile acids is mutual influenced by diet and microbiota modulating the immune system of the host and impacting the development of diseases such as NAFLD.

## HOW DOES FRUCTOSE CONTRIBUTE TO NAFLD AND NON-ALCOHOLIC STEATOHEPATITIS (NASH)

Non-alcoholic fatty liver disease is one of the most frequent hepatic disease (39). It incorporates a disease spectrum, which includes steatosis (fatty liver), NASH, and cirrhosis. While simple steatosis is reversible, NASH provokes hepatocyte injury, inflammation, and fibrosis that can aggravate to cirrhosis, liver failure, and even hepatocellular carcinoma (40). Moreover, NAFLD is associated with characteristics of the metabolic syndrome, which includes abdominal obesity, insulin resistance, glucose intolerance or type 2 diabetes mellitus, and dyslipidemia syndrome (41–43).

Gut microbiota has been recognized as the main environmental factor promoting metabolic diseases (28). Multiple studies reported fructose as a critical factor contributing to NAFLD progression by modulating intestinal microbiota (**Table 1**). It performs crosstalk with its host, maintaining the host's energy homeostasis and stimulating the host's immunity. Shifts in this composition can result in alterations of the symbiotic relationship, which can promote metabolic diseases (28). The key bacterial products involved in the pathogenesis of NAFLD are lipopolysaccharides (LPS) (44). LPS is derived from gram-negative bacteria and are known to critically contribute to inflammation-related processes and insulin resistance. It is able to cross the gastrointestinal mucosa *via* leaky tight junctions or infiltrating chylomicrons (28). Recent studies connected NAFLD to disturbances in the gut microbial environment. The microbial composition differed between healthy individuals and NAFLD patients (45). In line, a diet enriched in fructose not only induced NAFLD but also negatively affected the gut barrier and the microbiota, leading to dysbiosis (46).

In addition, the microbiota itself was shown to contribute to the progression of liver disease and injury and diet-induced NAFLD resulted in dysbiosis and a strong decrease in microbial diversity (66). Although the underlying mechanisms are not fully discovered yet, fructose is known to be highly involved in the development of NAFLD by altering gut metabolites (52, 60). Fructose increased the intestinal translocation of endotoxins and endotoxin levels in plasma (49, 64) contributing to inflammation and degrading of the mucosa barrier. Consequently, acute and chronic exposure to high fructose increased circulating endotoxin in patients with NAFLD, accompanied by markers of insulin resistance and inflammation (65). Interestingly, hepatic damage implicated by epitopic fat deposition occurred rapidly and significantly in non-human primates, even in the absence of weight gain (64) suggesting that arising periportal inflammation is the result of bacterial products overwhelming immune system and being presented to Kupffer cells (64). Altogether these studies indicate that fructose is able to induce inflammation promoting the development of NAFLD in two ways: it contributes to the formation of excessive fat triggering inflammation and it causes microbial dysbiosis promoting NAFLD pathogenesis.

In line, NAFLD and NASH patients were shown to consume more carbohydrates and particularly fructose (50). In a study, in which rats were fed a diet enriched in fructose, Wei et al. showed that the fecal metabolome profile was associated with the dietary fructose (60). Moreover, the chosen diet provoked formation of high quantities of SCFAs as well as C15:0 and C17:0 long chain fatty acids that are only produced by a special set of bacteria. This suggests that fructose-induced alterations in microbiota and not fructose itself are responsible for alterations in metabolome profile.

## FRUCTOSE SAVAGES THE INTESTINAL BARRIER

The intestinal barrier represents a physiological boundary protecting the host by preventing entry of intestinal microbiota and microbial products (**Figure 1**). In particular, tight junctions, adherens junctions, and desmosomes connect epithelial cells, which together form a selective permeable epithelial barrier limiting the penetration of potentially pathogen substances (47).

Chronic intake of fructose is associated with a loss of tight junction proteins in the duodenum, elevated translocation of endotoxin, and induction of toll-like receptors (TLRs) in the liver (50, 53, 54, 56, 58). TLRs can be activated by microbial pathogenassociated molecular patterns (PAMPs). LPS is the most common PAMP, occurring in the cell membrane of gram-negative bacteria. LPS binds to its receptor TLR4, inducing nuclear translocation of transcription factor nuclear factor kappa (NF-κB)-light-chain enhancer of activated B cells resulting in an increased expression of pro-inflammatory cytokines including tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and interleukin-1β (IL-1β) (63). Especially the tight junction proteins occludin and claudin-1 have been shown to decrease during fructose consumption (53, 58, 67). This process causes mucosal inflammation and intestinal epithelial barrier disruption, increasing the translocation of microbial products (47). A recent study of Volynets et al. pointed out that a sucrose-rich diet and a fructose-rich diet affected the intestinal microbiome in different ways (55). While a Westerndiet high in sucrose primarily promoted weight gain, the intake of fructose, especially in combination with a Western diet, caused barrier dysfunction accompanied with loss of mucus thickness and endotoxin translocation (55).

Mice with a knockout in the *F11r* gene encoding the tight junction adhesion molecule A showed increased infiltration of intrahepatic macrophages, elevated recruitment of inflammatory monocytes to the liver, upregulation of TLRs and higher content Table 1 | Fructose in the crosstalk with microbiota in the pathogenesis of NAFLD.

Fructose in Crosstalk with Microbiota in the Pathogenesis of NAFLD

(*Continued*)

of inflammatory cytokines when fed a diet high in fructose and fat (47). High fructose consumption promotes gut inflammation accompanied by rising endotoxin release, epithelial dysfunction, and decline of tight junctions proteins (50, 55, 56) independent of the fat content in the diet and energy intake (55). These data again illustrate the high impact of nutritional fructose on the intestinal barrier function.

The hepatic portal system connects the liver and the intestine, commonly called the "gut-liver-axis" (44). Consequently, the liver is the first organ exposed to gut-derived exotoxins, receiving 70% of the blood supply from the intestine. Therefore, the liver acts as a first defense against bacterial pathogens possibly explaining the relation between the influx of endotoxin and the progression of NAFLD and other liver diseases (68). Additionally, the gut microflora is able to stimulate hepatic fat deposition contributing to NAFLD and NASH (68). Fructose-induced impairment of intestinal gut barrier function enables the entering of bacterial products into the portal vein system and the liver, leading to Kupffer cell-mediated activation of inflammasomes and inflam mation, increased formation of reactive oxygen species and proinflammatory cytokines such as TNFα that are major causes of insulin resistance and dyslipidemia (16, 50, 67). Long periods of feeding a high fructose and high fat cause a rise in serum LPS, liver TLR4 expression and circulating cytokines suggesting that LPS and TLR4 are key molecules in the pathogenesis of NAFLD (3, 44, 47). In combination with dysbiosis, impaired gut function can promote metabolic endotoxemia as it was observed in animals that received a high sugar diet ( 3).

In addition, endotoxins are able to damage hepatocytes, caus ing activation of Kupffer cells that produce and release inflam matory cytokines and oxygen radicals. These products further aggravate liver damage (44). In line, mice fed fructose, fat or a combination of both showed elevated endotoxin and TLR4 levels, which were associated with changing the polarization of Kupffer cells and infiltrating macrophages, contributing to NAFLD (56). Infiltration of lymphocytes in the liver was increased when mice were fed a high fat diet supplemented with high fructose compared to mice fed a high fat diet alone (54, 69). In the respective model, fructose consumption induced increased lymphocyte recruit ment that was accompanied by higher inflammation indicated by the elevated mRNA expression of TNFα (54).

#### FRUCTOS E CAUS ES DYSB IOS I S

The structure and biology of gut microbiota are highly individu ally so that individuals can be identified simply on the basis of their "microbiota fingerprint" (15). Mostly six different bacterial phyla colonize the healthy gut (**Figure 2**), namely *Firmicutes*, *Bacteriotedes*, *Proteobacteria*, *Actinobacteria*, *Fusobacteria*, and *Verrucomicrobia* (70). About 90% of total bacteria in the gut of an adult are represented by three major divisions, the *Firmicutes* (gram-positive), *Bacteroidetes* (gram-negative), and *Actinobacteria* (gram-positive) (15).

Microbial diversity significantly decreases when consuming a high sugar diet already after 1 week, independent of the fat content ( 3). Fructose was shown to induce a different pattern of dysbiosis than a high fat diet.

resulting in a higher permeability of the gut barrier. In addition, endotoxins enter the leaky barrier leading to epithelial disruption and increase penetration of pathogens into the blood stream. Reaching the liver, endotoxins increase inflammation by activation Kupffer cells through binding to TLR4 and formation of reactive

oxygen (ROS). The formed radicals induce hepatic damage and fibrosis. Furthermore, in the liver the fructokinase generate fructose-1-phosphate from fructose that is degraded into products providing substrate for *de novo lipogenesis* promoting steatosis.

Ferrere et al. found increased hepatic lymphocyte infiltration when mice were fed with a high fat and fructose diet compared to mice fed with high fat without fructose (57). Dysbiosis was observed in several studies when fructose was added to a normal diet (57). Mostly, a decrease of *Bacteriodes* and an increase of *Firmicutes* were observed when consuming a Western diet (27, 71–73). Independent studies comparing lean and diet-induced obese subjects suggested that *Firmicutes* promotes body fat accumulation (71, 72). Turnbaugh et al. reported that *Firmicutes* helps obese subjects to get more calories from the ingested food, which in turn leads to obesity (74). Also an increase in *Betaproteobacteria*, genera *Sutterella* was associated with enhanced hepatic fat deposition (3). Other studies demonstrated *Proteobacteria* as the main bacteria contributing to hepatic fibrosis and liver damage (47, 66). Furthermore, *Proteobacteria* is observed to be increased in several forms of dysbiosis and associated with NAFLD (75).

Rats subjected to different diets, marked changes in the microbiota already occurred already 1 week after the dietary switch to a diet enriched with high fat and high sugar (3). In a kind of circle, the increase in body fat mass correlated with shifts in the gut microbiota and gut-brain communication, possibly providing the basis for the pathogenesis of obesity (3).

Jegatheesan reported about alterations in colon mucosaassociated microbiota feeding a Western diet high in fat and fructose for 8 weeks (58). This was associated with lower levels of *Clostridium leptum*, *Bacteroides/Prevotella*, and *Lactobacillus/ Leuconostoc*, while the content of *Akkermansia muciniphila* was not affected (58). *A. muciniphila* is known to strengthen the epithelial barrier function and to impact the systemic health of the host (76). It has been shown that this cross-talk between the host and gut microbiota protects against high fat diet-induced LPS endotoxemia in obese mice (77). In the above mentioned study of Sen et al., a high fat/high sugar diet resulted in a specific

Figure 2 | Bacterial phyla colonizing the healthy or diseased gut. (A) *Bifidobacterium longum* is a gram-positive, rod-shaped, health-promoting lactic acid bacterium present in the human gastrointestinal tract contributing to the production of butyrate. (B) *Bacteroides thetaiotaomicron* is a gram-negative, anaerobic microbe which dominates the intestinal tract flora of most mammals and provides the host with metabolic capabilities. (C) *Enterobacter cloacae* is a gram-negative, facultative-anaerobic, rod-shaped bacterium of the normal gut flora helping to debranch organic substances for energy production. (D) *Citrobacter freundii* is a common component of the gut microbiome of healthy humans. It is a facultative anerobic, rod-shaped gram-negative bacteria. (E) *Escherichia coli* is a gramnegative, facultative anaerobic, rod-shaped, "coliform" bacterium, which is commonly found in the lower intestine of warm-blooded organisms. Although most *E. coli* strains are harmless and part of the normal gut flora, some serotypes are occasionally responsible for food contamination causing serious intoxication in their hosts. They have capacity to produce vitamin K2 and prevent colonization of the intestine with pathogenic bacteria. (F) *Enterococcus faecalis* is a gram-positive, commensal bacterium inhabiting the gastrointestinal tracts. They are often arranged in pairs or in chain form and have both an anaerobic and aerobic metabolism. (G) *Salmonella enterica* is a gram-negative bacterium, flagellated, facultative anaerobic with a rod-shaped phenotype. A number of *Salmonella* variations are serious human pathogens provoking (spontaneous healing) diarrhea. (H) *Clostridium difficile* is a gram-positive, anaerobic, spore-forming bacterium able to produce multiple toxins causing diarrhea and inflammation. It may become opportunistically established in the human colon during antibiotic therapy. (A–H) All images were taken from cultures deposited in the national Culture Collection of Switzerland AG (CCOS, Wädenswil, Switzerland, https://www.ccos.ch/). The respective CCOS strain numbers are: CCOS 606, CCOS 632, CCOS 668, CCOS 669, CCOS 684, CCOS 688, CCOS 739, and CCOS 958. All images were taken using a phase contrast microscope at 1,000×. Space bars, 10 µm.

increase in *Anaeroplasmatales,* which are an order of *Mollicutes* bacteria, a class of *Tenericutes* which is linked to diet-induced fat deposition and obesity (3). Adipose tissue inflammation plays a major role in the pathogenesis of NAFLD, intestinal dysbiosis might therefore be an additional factor leading to disease progression (78).

In line with this assumption, Raman et al. discovered a significant difference in the fecal microbiome in NAFLD patients and healthy subjects (75). In patients with NAFLD, the dysbiosis is mainly characterized by a decrease in *Bacterioides* (*Prevotella*) and an increase of *Clostridium coccoides* (45). Consistently, patients with IBS showed a similar dysbiosis characterized by an increase in *Clostridium* cluster XIVa and *Ruminococcaceae* with a concomitant decrease in *Bacteroidetes* and *Bifidobacteria* (79). In a more recent study, Xue et al. detected an increase of serum LPS and aerobic bacteria, such as *Escherichia coli* and *Enterococcus* and a decrease in the amounts of *Lactobacillus, Bifidobacteria*, and *Bacteriodes* in rats that were subjected to diets inducing experimental NAFLD (44).

De Minics et al. investigated the transformation of the microbiome in animal models of NAFLD, and compared high fat dietinduced NAFLD and bile duct ligation-induced liver damage. In the respective study, it was found that intestinal permeability and bacterial translocation are the key pathogenetic events triggering progression of liver damage. Moreover, the authors showed that the main effector in the degree of liver damage is related to microbiota changes (66). Similarly, fructose induced alterations in the microbiome of rats were associated with metabolic dysregulation and inflammation in gut, liver, and fat tissue that could be attenuated by antibiotic treatment or treatment with control fecal samples (59, 62). These observations again underpin the importance of microbiota in the development of metabolic diseases. Therefore, the authors of respective studies concluded that manipulation of the gut bacteria interferes with liver injury and progression of NAFLD.

To sum up, the human gut is colonized by several strains of microbiota, some with pro- and some with anti-inflammatory effects. A healthy gut is characterized by a homeostasis requiring a balance between the gut flora and the immune system of its host. Triggers that provoke intestinal leakage such as fructose cause a shift in this homeostasis favoring proinflammatory microbiota, suppression of anti-inflammatory microbiota, and reduction of their overall diversity.

#### FRUCTOSE-INDUCED PRODUCTION OF URIC ACID FURTHER PROVOKES LIVER DAMAGE

It was demonstrated that a Western diet leads to an increase in uric acid within the blood and that measured serum levels of uric acid directly correlate to the intake of fructose (80). The primary producers of uric acid are the hepatocytes and an anomalous metabolism of uric acid causes hepatocyte damage and produce oxidative stress (81). When fructose from dietary sources is absorbed through the fructose transporter GLUT5 within the intestinal epithelium and transported to the liver, it is rapidly phosphorylated in the liver by fructokinase, causing hepatic accumulation of fructose-1-phosphate (F-1-P) and a simultaneously increase in AMP (82) (**Figure 3**). Subsequently, the elevated hepatic concentration of F-1-P induces changes of several other metabolites such as glucose, lactate and uric acid (82). F-1-P is converted in triosephosphate providing substrates for *de novo* lipogenesis (DNL) (80, 82). Simultaneously, the decrease in intracellular phosphate stimulates AMP deaminase stimulating the generation of uric acid *via* xanthine oxidase and production of superoxide anion ( ) O2 − and hydrogen peroxidase (H2O2) (80, 83, 84). This process is reinforced under inflammatory conditions (80). Lanaspa et al. suggested that uric acid plays a pivotal role in the lipogenic ability of fructose. In the respective study, triglyceride accumulation was decreased by adding an inhibitor of xanthine oxidase (84). Likewise, Choi et al. showed that uric acid induced fat accumulation in HepG2 and in primary hepatocytes as a result of endoplasmatic reticulum stress induction, which could activate SREBP-1c and stimulate steatosis (85).

Mitochondrial oxidative stress inhibited aconitase resulting in accumulation of cytosolic citrate. This tricarboxylic acid promoted DNL by activating ATP-sensitive lipase converting citrate to acetyl-CoA, thereby inducing fatty acid synthesis (84). Simultaneously, oxidative stress in the liver mitochondria induced by uric acid leads to alterations of mitochondrial function and cell damage (81, 84). Even a single administration of fructose attenuates uric acid excretion in the ileum (83), and long-term consumption of fructose was shown to suppress renal uric excretion resulting in increased serum uric acid levels (86). Consequently, high uric acid impaired glucose tolerance, causing insulin resistance and inhibition of insulin signaling (87).

#### IMPROVEMENT OF DIET-INDUCED NAFLD

Currently, there is no real effective drug therapy for treatment of NAFLD. However, interventions in lifestyles, health-promoting diets, application of probiotics, nutritional supplementation with prebiotics inducing growth or activity of beneficial microorganisms, and exercise resulting in weight loss (88) have been shown to improve NAFLD (**Figure 4**). Some aspects of the beneficial effects of each intervention are discussed later.

### HEALTH-PROMOTING EFFECTS OF Mediterranean diets

The traditional MD is based on high intake in mono- and polyunsaturated fatty acids derived from olive oil or fish, vegetables, fruits, and nuts providing high fiber entry. MD has been shown to correlate negatively with NAFLD, and in combination with salt restriction, MD was shown to lower blood pressure, improve blood lipids, and improve steatosis and steatohepatitis, while omega-3 polyunsaturated fatty acids have been shown to reduce accumulation of lipid and liver enzymes, improve insulin sensitivity, and act as an anti-inflammatory compound (8). The high amount of fibers in the MD is accompanied by polyphenols, antioxidants and phytochemicals, plant metabolites capable to inhibit DNL, liver steatosis, and inflammation. Furthermore, fiber and phytochemicals enriched in whole grain are able to reduce energy

hepatocytes, thereby leading to a direct activation of genes such as SREBP-1c stimulating hepatic steatosis.

This results in increased cytosolic acetyl-CoA which is a substrate for *de novo* lipogenesis. In addition, uric acid can induce endoplasmatic reticulum stress in

function facilitating bacterial translocation. Bacterial-derived products [e.g., lipopolysaccharide (LPS)] are key driver of hepatic inflammation. Although effective pharmacological therapies for NAFLD are not available, lifestyle changes (modulation of diet), exercise, and weight loss have been shown to be beneficial on NAFLD outcome. Supplementation with probiotics and prebiotics restoring the microbial balance and changing the "*bad microbiota*" to "*good microbiota*" have healthpromoting effects by generation of short-chain fatty acids (e.g., acetate, propionate, and butyrate) interfering with NAFLD progression.

intake, promote SCFA-producing gut bacteria, and have significant prebiotic effects. Based on these positive health-promoting effects, it is obvious that changing to a MD is one therapeutically effective mean to improve the outcome or severity of NAFLD (8).

## SCFA INFLUENCE FAT METABOLISM *VIA* ACTIVATION OF ADENOSINE MONOPHOSPHATE KINASE (AMPK)

Adenosine monophosphate kinase is an important enzyme expressed mainly in the liver and skeletal muscles, playing a crucial role in cellular energy homeostasis (15). It is one of the central regulators of the body's metabolisms by promoting catabolic pathways to generate more ATP and inhibition of anabolic pathway. The enzyme is a heterotrimer composed of a catalytic α-subunit and two regulatory subunits (β and γ) (**Figure 5**). The activity of AMPK is strongly influenced by the gut microbiota (**Figure 6**). Drugs increasing expression of AMPK stimulate fatty acid oxidation in liver and muscle tissues, resulting in energy loss and prohibition of obesity (89). Specifically, certain food compounds and dietary strategies are suitable to activate AMPK and to mediate antidiabetic effects. Some intestinal bacteria are able

Figure 5 | Structure, regulation and functional aspects of adenosine monophosphate kinase (AMPK) biology. (A,B) The AMPK is a heterotrimeric protein kinase complex comprised of α-, β-, and γ-subunits. AMPK is activated by phosphorylation of a critical threonine residue located within the α-subunit that is triggered by binding of AMP and/or ADP to the γ-subunit. ATP competitively inhibits the binding of both AMP and ADP to the γ-subunit suggesting that AMPK is a critical sensor of AMP/ATP or ADP/ATP ratios (93). The space bar represents 10 Å. The CPK representation in (A) was generated with the interactive web-based tool NGL (94) and the ribbon drawing in (B) with Ribbons XP Version 3.0 (95) using the structure coordinates 5UFU deposited in the PDB Brookhaven database. More structural details of human AMPK are given elsewhere (96, 97).

to digest polyphenols and isoflavones from plants and convert it to enterolactone (ENL) or to equol, which both activates AMPK (63, 90). Furthermore, ENL ameliorates abnormal lipid metabolism, inhibits anabolic glycogen storage, and improves insulin sensitivity (63, 90). In the respective study it was shown that ENL dose dependently promoted glucose uptake under insulin absent condition, which was completely eliminated by an AMPK inhibitor suggesting that ENL is an antidiabetic substance. Conversely, the inhibition of AMPK prevented fatty acid oxidation in several organs and tissues, promoted the synthesis of cholesterol and triglycerides, and favored lipogenesis leading to excess fat storage and obesity (28). Therefore, food enriched in such pharmacological active substances including grapes, plums, strawberries, passion fruit, white tea, and soy are predicted to improve diet-induced NAFLD. Another study focusing on the beneficial impact of butyrate on the gut barrier reported that butyrate activates AMPK and induced a redistribution of the tight junction proteins zonula occudens-1 (ZO-1) and occludin (91). Additionally, butyrate activated AMPK induced SIRT1 phosphorylation that influences glucose homeostasis and insulin sensitivity in a positive way (92).

#### PROBIOTICS

There is now ample evidence showing the importance of probiotics in host health. As already discussed above, the main bacterial bioproduct, which is associated with the pathogenesis of NAFLD, is LPS. Xue et al. detected a positive correlation between serum LPS and aerobic bacteria, such as *Escherichia coli* and *Enterococcus* and a negative correlation between the amount of *Lactobacillus*, *Bifidobacteria*, and *Bacteriodes* in rats subjected to NAFLD inducing diets (44). Interestingly, it was demonstrated in the respective study that the amounts of anaerobic bacteria such as *Lactobaiullus* and *Bifidobacteria* could be restored by probiotics (44). The application of probiotics ameliorated the intestinal barrier in NAFLD and tight junctions were shown to be more complete in comparison to NAFLD rats without probiotics (44, 48). Furthermore, serum levels of LPS and TLR4 decreased significantly after administration of probiotics in a NAFLD rat model. In addition, the livers of the respective animals showed less hepatocyte swelling, less cell infiltration, lower degree of inflammation, and overall milder steatosis (44, 48). Along with that, serum levels of triglycerides, total cholesterol, LDL, and free fatty acids were diminished. Interestingly, the amount of high density lipoprotein (HDL) was increased compared to the control group and animals exhibited better glucose tolerance in comparison to NAFLD rats without probiotic treatment (44). Moreover, different *Lactobacillus* strains were identified that diminished hepatic fat accumulation, increased of serum alanine aminotransferase (ALT) levels, and improved intestinal gut barrier in a NASH model (48, 51). The combination of multiple

unit. (C) Representative fructooligosaccharides (FOS) are kestose (GF2), nystose (GF3), fructosylnystose (GF4) differing in number of fructose residues. The general molecular formula of a FOS is C6(*n*+1)H10(*n*+1)+2O5(*n*+1)+1 giving rise to a molecular mass of (*n* + 1) × 180.156 − *n* × 18.015 g/mol when *n* is the total number fructose residues.

*Lactobacillus* strains reduced plasma glucose and insulin levels, triglycerides, and oxidative stress. Moreover, high probiotic treatment reduced liver mass and liver cholesterol by increasing β-oxidation and lowering the expression of sterol regulatory element-binding transcription factor 1 (SREBP-1), stearoyl-CoA desaturase-1 (SCD-1), and fatty acid synthase (FAS) mRNA levels that are critically associated with fructose-induced metabolic syndrome (37). In similar studies, *Lactobacillus casei* was shown to decrease fat storage, oxidative stress, and hepatic inflammation in a NASH mouse model and to diminish the activation of the TLR4 signaling cascade (51, 98).

In a rat model, treatment with the butyrate-producing gram positive strain *Clostridium butyricum* prevented the progression of nutrient-induced NAFLD (92). When given as dietary supplement (i.e., MIYAIRI 588), this bacterial strain suppressed the diet-induced increase in endotoxin levels, and restored the expression of the tight junction proteins ZO-1 and occludin (92). It altered the intestinal flora and restored gut-barrier functions, reduced hepatic levels of cytokines as TNF-α and was able to regulate the activation of NF-κB (92).

Toll-like receptor 4 is the main receptor that detects gutderived endotoxins and regulates hepatic inflammation in NASH and probiotics were shown to decelerate the progress of NAFLD by inhibiting the LPS-TLR4-signaling pathway, improving intestinal flora dysbiosis, restoring normal gut homeostasis, and upregulating expression of tight junction proteins strengthening the gut barrier (44, 48). Patients with IBS exhibited a high activity of intestinal serine proteases, which could be biologically sequestered by *Bifidobacteria* acting as an antagonist of this endopeptidase (79). Therefore, probiotics are presently discussed as new therapeutics in clinical management of NAFLD (99).

#### PREBIOTICS

In addition, gut microbial modulation can also be achieved by intake of substances that induce the growth or activity of beneficial microorganisms. These prebiotics act as substrate for respective bacteria and can be supplied as a functional food component. Prototypically, the plant polyphenol Quercetin found in many fruits has been shown to modulate diet-induced dysbiosis in mice with NAFLD by increasing the production of SCFA, thereby improving the intestinal gut barrier and inhibition of diet-induced hepatic inflammasome activation (100). In addition, Quercetin supplementation counteracted the upregulation of lipogenic genes and reduced the amount of *Helicobacter*, which is more frequent in diet-induced NAFLD (100). In a similar study from Baldwin et al., the feeding of powdered grape extracts reduced fat gain and hepatic lipid accumulation in a high fat mouse model (101). Also fructooligosaccharides (FOS) were shown to act as prebiotics in a metabolic syndrome model (61). FOS are composed of relative short chains of less than 20 molecules of fructose that are linked to a glucose terminal residue and cannot be digested by humans (**Figure 7**). They can be extracted from many plants (e.g., blue Agarve) and naturally occur in high concentration in many fruits and vegetables such as bananas, artichokes, onions, chicory root, garlic, asparagus, and leeks. In combination with *Lactobacillus fermentum*, FOS were effective in preventing intestinal permeability, systemic inflammation, hepatic steatosis and insulin resistance without inducing an innate immune system reaction at the intestinal level during high fat diet (61). Similarly, the mentioned study of Baldwin et al. showed that FOS mediated an increase in *A. muciniphila*, which was accompanied by decreased metabolic endotoxemia and reduced expression of inflammatory markers in white adipose tissue (101). Increased abundance of this mucin degrader residing in the mucus layer correlated with improvement of high-fat diet-induced metabolic disorders, reduction of obesity, reduced metabolic endotoxemia, adipose tissue inflammation, and insulin resistance (77).

## PHYSICAL ACTIVITY

It is already well established that exercise is associated with the production and release of potent, pharmacologically active, anti-inflammatory mediators, which can principally counteract liver inflammation and chronic low-grade inflammation (102). In a recent study, Batacan et al. investigated the combined effect of exercise and diet treatments on intestinal microbiota in a rat model (103). The authors found that the development of the microbiota in response to physical activity depends on basic starting microbiota. Moreover, training could induce a microbiota composition which is able to break down carbohydrates more effectively, improving the performance through energy provision, and increasing the production of SCFAs. Therefore, the authors suggested exercise as a factor for remodeling microbiota and gut health which is negatively influenced by high

#### REFERENCES

fat diets preventing microbiota differentiation in response to exercise (103).

## CONCLUSION

Non-alcoholic fatty liver disease is a systemic disease induced and modulated by different metabolic components, in which the liver is the main affected organ. Fructose consumption causes dysbiosis in the microbiota, leading to an increased permeability of the gut barrier, hepatic inflammation, progressive development of metabolic syndrome, and insulin resistance (57, 62, 69). Microbiota is highly influenced by diet and lifestyle of its host and a major factor influencing the outcome of metabolic diseases. Changing gut flora by intake of dietary fiber (i.e., roughage), probiotics, prebiotics, as well as intensifying frequency and duration of physical activity, leads to improvement of hepatic inflammation and fibrosis. These dietary and lifestyle interventions affecting microbiota are presently the most effective treatment options to improve NAFLD. Therefore, these nutritional and behavioral therapies should be combined with diets that lack excessive NAFLD-promoting compounds such as fructose and fat that are majorly contributing to the pathogenesis of NAFLD.

#### AUTHOR CONTRIBUTIONS

JL and RW have written this review. SW prepared the final **Figures 1**, **3**, **4** and **6**. SL provided images of bacterial cultures depicted in **Figure 2**. RW prepared **Figures 5** and **7** and has made the final editorial assignments. All authors agreed to submit this review and to be accountable for the content of the work.

#### FUNDING

RW is supported by grants from the German Research Foundation (DFG, SFB/TRR 57 P13 and Q3) and the Interdisciplinary Centre for Clinical Research (IZKF) within the Faculty of Medicine at the RWTH Aachen University (E7-6). None of the funding sources exerted influence on content of this review or decision to submit this article for publication.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Copyright © 2017 Lambertz, Weiskirchen, Landert and Weiskirchen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

, Laura Jordán-Martínez3

, Antonio J. Muñoz-Garcia3

,

,

# Role of Gut Microbiota on Cardio-Metabolic Parameters and Immunity in Coronary Artery Disease Patients with and without Type-2 Diabetes Mellitus

#### Edited by:

Lidia Sanchez-Alcoholado1†

Isabel Moreno-Indias1,2, Pilar Cardila-Cruz3

Marina I. Arleevskaya, Kazan State Medical Academy, Russia

#### Reviewed by:

Yuji Naito, Kyoto Prefectural University of Medicine, Japan Undurti Narasimha Das, UND Life Sciences LLC, United States Amanda Cox, Griffith University, Australia

#### \*Correspondence:

Maria I. Queipo-Ortuño<EMAIL_ADDRESS>
†These authors have contributed equally to this work.

#### Specialty section:

This article was submitted to Microbial Immunology, a section of the journal Frontiers in Microbiology

Received: 25 July 2017 Accepted: 21 September 2017 Published: 05 October 2017

#### Citation:

Sanchez-Alcoholado L, Castellano-Castillo D, Jordán-Martínez L, Moreno-Indias I, Cardila-Cruz P, Elena D, Muñoz-Garcia AJ, Queipo-Ortuño MI and Jimenez-Navarro M (2017) Role of Gut Microbiota on Cardio-Metabolic Parameters and Immunity in Coronary Artery Disease Patients with and without Type-2 Diabetes Mellitus. Front. Microbiol. 8:1936. doi: 10.3389/fmicb.2017.01936 Maria I. Queipo-Ortuño1,2 \* and Manuel Jimenez-Navarro3 1 Unidad de Gestión Clínica de Endocrinología y Nutrición, Instituto de Investigación Biomédica de Málaga, Hospital Universitario Virgen de la Victoria, Universidad de Málaga, Málaga, Spain, 2 CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain, 3 Unidad de Gestión Clínica Área del Corazón, Hospital Universitario Virgen de la

, Daniel Elena3

, Daniel Castellano-Castillo1,2†

Victoria, Instituto de Investigación Biomédica de Málaga, Universidad de Málaga, CIBERCV Enfermedades Cardiovasculares, Málaga, Spain

Gut microbiota composition has been reported as a factor linking host metabolism with the development of cardiovascular diseases (CVD) and intestinal immunity. Such gut microbiota has been shown to aggravate CVD by contributing to the production of trimethylamine N-oxide (TMAO), which is a pro-atherogenic compound. Treg cells expressing the transcription factor Forkhead box protein P3 (FoxP3) play an essential role in the regulation of immune responses to commensal microbiota and have an atheroprotective role. However, the aim of this study was to analyze the role of gut microbiota on cardio-metabolic parameters and immunity in coronary artery disease (CAD) patients with and without type-2 diabetes mellitus (DM2). The study included 16 coronary CAD-DM2 patients, and 16 age, sex, and BMI matched CAD patients without DM2 (CAD-NDM2). Fecal bacterial DNA was extracted and analyzed by sequencing in a GS Junior 454 platform followed by a bioinformatic analysis (QIIME and PICRUSt). The present study indicated that the diversity and composition of gut microbiota were different between the CAD-DM2 and CAD-NDM2 patients. The abundance of phylum Bacteroidetes was lower, whereas the phyla Firmicutes and Proteobacteria were higher in CAD-DM2 patients than those in the CAD-NDM2 group. CAD-DM2 patients had significantly less beneficial or commensal bacteria (such as Faecalibacterium prausnitzii and Bacteroides fragilis) and more opportunistic pathogens (such as Enterobacteriaceae, Streptococcus, and Desulfovibrio). Additionally, CAD-DM2 patients had significantly higher levels of plasma zonulin, TMAO, and IL-1B and significantly lower levels of IL-10 and FOXP3 mRNA expression than CAD-NDM2. Moreover, in the CAD-MD2 group, the increase in Enterobacteriaceae and the decrease in Faecalibacterium prausnitzii were significantly associated with the increase in serum TMAO levels, while the decrease in the abundance of Bacteroides fragilis was associated with the reduction in the FOXP3 mRNA expression, implicated in the

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development and function of Treg cells. These results suggest that the presence of DM2 is related to an impaired regulation of the immune system in CAD patients, mediated in part by the gut microbiota composition and functionality and the production and effects of their gut microbiota derived molecules.

Keywords: gut microbiota, coronary artery disease, zonulin levels, gut permeability increase, TMAO production, factor Forkhead box P3, type-2 diabetes mellitus, anti-inflammatory IL-10

#### INTRODUCTION

Previous studies have shown an important connection between metabolism, intestinal microbial composition and the development of cardiovascular risk (Tremaroli and Backhed, 2012; Tang and Hazen, 2014; Org et al., 2015). Several authors have strongly supported the contribution of intestinal microbiota in the conversion of L-carnitine and dietary phosphatidylcholine in trimethylamine (TMA), which is absorbed into the bloodstream and then oxidized to trimethylamine N-oxide (TMAO) (a pro-atherogenic compound) by the hepatic enzyme flavin-containing monooxygenase-3 (Ufnal et al., 2015; Stremmel et al., 2017). Independent of traditional CVD risk factors, this microbiota-dependent metabolite TMAO has been related with the development of clinical CVD in the general population (Koeth et al., 2013; Tang et al., 2013, 2014, 2015; Wang et al., 2014; Troseid et al., 2015). Furthermore, elevated TMAO plasma levels are associated with increased CVD (Wang et al., 2011; Tang et al., 2013, 2014; Koeth et al., 2014).

Nevertheless, the intestinal bacterial species responsible for phosphatidylcholine breakdown have not yet been completely described, however, some species of Bacteroidetes (such as, B. thetaiotaomicron and B. fragilis) may be involved in the formation of TMA since they express phospholipases which hydrolyse dietary phosphatidylcholine to choline (Sitaraman, 2013). In addition, it has been reported that bacteria of the Erysipelotrichia class (Firmicutes phylum) can produce TMA from choline whereby it imitates a choline deficiency (Serino et al., 2014), while several families of bacteria such as Deferribacteraceae, Anaeroplasmataceae, Prevotellaceae (Koeth et al., 2013), and Enterobacteriaceae (Craciun and Balskus, 2012; Zhu et al., 2014) have been also associated with TMA/TMAO production.

On the other hand, TMAO has also been suggested to be a strong candidate molecule to mediate the development of type-2 diabetes mellitus (DM2) in animal and human studies (Kim et al., 2015). Moreover, coronary artery disease (CAD) is an important determining factor of the long term prognosis among patients with DM2 and the prevalence of diabetes in patients with CAD is up to 50% in many countries. Patients with diabetes have a 2- to 4-fold greater risk of developing atherosclerotic CAD than non-diabetic patients (Aronson and Edelman, 2016; Hölscher et al., 2016). Accumulating evidence suggests that DM2 and cardiovascular diseases such as hypertension, atherosclerosis, or heart failure are associated with alterations in the integrity of the gut barrier and augmented gut permeability (Ufnal and Pham, 2017).

Finally, gut microbiota has been reported to be a factor that is able to link intestinal immunity and host metabolism. It has been suggested that the increase or decrease of the abundant quantities of some specific bacteria may result in an increased generation of Tregs or in the reduced differentiation of pathogenic T cells, which may prevent inflammatory diseases (Smith et al., 2013). Treg cells expressing the transcription factor Forkhead box protein P3 (FoxP3) play an essential role in the regulation of immune responses to commensal microbiota. Furthermore, metabolites of commensal bacteria might regulate Treg development (Pereira et al., 2017). The administration of Bifidobacterium infantis 35624 has been found to induce Foxp3 T regulatory cells in human peripheral blood (Konieczna et al., 2012). It has also been described that FOXP3 positive regulatory T cells play a crucial role in maintaining the immune balance having an atheroprotective role (Hasib et al., 2016).

Therefore, the aim of this study was to analyze the role of gut microbiota on cardio-metabolic parameters and immunity in CAD patients with and without DM2. Furthermore, we have also analyzed the association of the gut microbiota found in these patients with the glucose metabolism, inflammatory status, intestinal permeability, and serum levels of TMAO and FOXP3 gene expression in peripheral blood.

#### MATERIALS AND METHODS

#### Study Subjects

We included a total of 32 patients with CAD who were divided into two groups: 16 patients with DM2 (the CAD-DM2 group) and 16 patients without DM2 (the CAD-NDM2). The CAD group was defined by the presence of at least one coronary stenosis ≥50% of luminal diameter diagnosed by coronary angiogram. DM2 was defined by the history of diabetes diagnosed and/or the presence of treatment with medication (insulin or anti-diabetic drugs) and/or fasting blood glucose ≥126 mg/dl and/or glycated hemoglobin (HbA1c) ≥6.5%. Diabetic treatment of CAD patients with DM2 was the following: oral anti-diabetic (metformin n = 8 and glibenclamide n = 3) and insulin (n = 5).

All subjects underwent a complete physical examination, including measurements of height, weight, and blood pressure. The medical history of all patients was recorded, including the duration of diabetes, hypertension history, the history of taking anti-hypertensive and hypoglycemic drugs, and smoking history. The definition of systemic arterial hypertension was determined as a history of high blood pressure or treatment with antihypertensive medication. The definition of Dyslipidemia was determined as known but untreated dyslipidemia or currently

undergoing treatment with lipid lowering medication. The family history of coronary heart disease was determined by interviewing the patients. The definition of a positive smoking history was determined as current smokers or cessation of smoking within the previous 3 months before the start of the study.

The following were considered as exclusion criteria: acute inflammatory disease, severe infective disease and/or cancer, chronic kidney disease (GFR < 45 mL/min/1.73 m2 ), hepatic impairment and autoimmune disease. This study was carried out in accordance with the recommendations of the Ethical Committee of the Virgen de la Victoria Hospital. Written informed consent was obtained in all cases in accordance with the Declaration of Helsinki. The protocol was approved by the Ethical Committee of the Virgen de la Victoria Hospital.

#### Biochemical Variable Analysis

Serum was separated from blood samples which were collected after an overnight fast, aliquoted and immediately frozen at −80◦C. Enzymatic methods (Randox Laboratories Ltd., United Kingdom) were employed to analyze the levels of serum cholesterol, triglycerides, HDL-cholesterol, glucose, and glycated hemoglobin (HbA1c) using a Dimension autoanalyzer (Dade Behring Inc., Deerfield, IL, United States). The Friedewald equation was used to calculate LDL-cholesterol. Standard enzymatic methods (Wako Bioproducts, Richmond, VA, United States) were used to measure gamma-glutamyl transpeptidase (GGT), glutamate-oxaloacetate transaminase (GOT), and glutamic pyruvic transaminase (GPT). RIA provided by BioSource S.A. (Nivelles, Belgium) was utilized for insulin quantification. The ELISA kit from BLK Diagnostics (Badalona, Spain) was employed to measure high sensitivity C-reactive protein (CRP) levels. To calculate the HOMA-IR we used the equation: HOMA-IR = fasting insulin (mIU/mL)/fasting glucose (mol/L)/22.5.

IL-10 and IL-1β cytokines were measured in serum samples using commercially available Novex R ELISA Kits (Life Technology), performed according to the manufacturer's instructions. The assay range was 7.8–500 pg/mL for IL-10 and 3.9–250 pg/mL for IL-1β.

#### Anthropometric Measures

Standardized procedures were used to measure body weight, height, waist, and hip circumferences (Lohman et al., 1988). BMI was calculated as weight (kilograms) divided by height (in meters) squared.

### PCR Amplification and Analysis of 16S rDNA Sequences

DNA was extracted from fecal samples using the QIAamp DNA Stool Mini Kit (Qiagen, Hilden, Germany) following the manufacturer's protocol. Amplification of genomic DNA was performed using barcoded primers that targeted the V2 to V3 regions of the bacterial 16S rRNA gene. Amplification, sequencing, and basic analysis were performed by using a GS Junior 454 platform according to the manufacturer's protocols using a Titanium chemistry apparatus (Roche Applied Science, Indianapolis, IN, United States). For further details, see Moreno-Indias et al. (2015).

### Bioinformatic Analysis

Quantitative Insights into Microbial Ecology (QIIME) 1.8.0 software was used to analyze the 454-pyrosequencing data sets as previously described by our group (Moreno-Indias et al., 2015). Raw reads were filtered first following the 454 amplicon processing pipeline. The pyrosequencing reads were de-multiplexed and filtered further by means of the split\_library.py script of QIIME. Reads with an average quality score lower than 25, ambiguous base calls, primer mismatches or shorter than 100 bp were excluded from the analysis in order to increase the level of accuracy. After the quality filter, the pipeline analysis used to analyze the 16S gene reads was the following: sequences were denoised and singletons excluded. The operational taxonomic units (OTUs) were selected by clustering sequences with a similarity of >97% and the representative sequences, selected as the most abundant in each cluster, were passed on to the UCLUST to obtain the taxonomy assignment and the relative abundance of each OTU by means of using the Greengenes 16S rRNA gene database. QIIME was used to evaluate alpha and beta diversity, as described (De Filippis et al., 2013).

## PICRUSt Analysis

The PICRUSt analysis was used to predict metagenome function by picking OTUs against the Greengenes database.1 As has been previously described by Bhute et al. (2016), "a closed reference based OTU picking approach was utilized to bin the amplicon sequences using latest Greengenes database 13.5 at 97% sequence similarity cut-off. The normalization for 16S rRNA gene copy number was carried out before prediction of the metagenome. This OTU table was used for predicting metagenome at different KEGG levels." The R packages "pheatmap" were used for data analysis and plotting. Statistical analysis was done in R 3.3.3. P-values were corrected for multiple comparisons using the Benjamini–Hochberg method. A corrected p < 0.05 was considered as statistically significant.

#### Intestinal Permeability

The plasma level of zonulin was determined by means of the enzyme linked immunosorbent assay (ELISA) using commercial kits (Immundiagnostik AG, Bensheim, Germany). Measurements were made in duplicate, and the mean values were used for the analysis. The detection limit for zonulin was established at 0.22 ng/mL. Intra- and inter-assay coefficients of variation were between 3 and 10%.

#### Total RNA Extraction, cDNA Synthesis, and Real-Time Quantitative PCR (qRT-PCR)

The total RNA was extracted from peripheral blood mononuclear cells using TRIPURE Reagent (Sigma–Aldrich, United States) according to the manufacturer's protocol. RNA was diluted

1http://huttenhower.sph.harvard.edu/galaxy/

in 20 µl RNase-free water and was subsequently quantified with a spectrophotometer (Nanodrop N-100, Thermo Scientific). Reverse transcriptions were performed using 1 µg of total RNA with the Transcriptor First Strand cDNA Synthesis Kit (Roche) and random hexamers in 20 µl reactions. The amplifications were performed by means of a MicroAmpH Optical 96-well reaction plate (Applied Biosystems, Foster City, CA, United States) on an ABI 7500 Fast Real-Time PCR System (Applied Biosystems, Foster City, CA, United States). Pre-validated and commercially available TaqMan R primer/probe sets were used as follows: 18S rRNA (4319413E) used as the endogenous control for the target gene in each reaction and FOXP3 gene (RefSeq NM\_001114377.1). A threshold cycle (Ct value) was obtained for each amplification curve and a 1Ct value was calculated first by subtracting the Ct value for human 18S rRNA cDNA from the Ct value for every sample and transcript. mRNA expression levels relative to 18S rRNA were calculated by means of the 2−1Ct method. All tests were performed in duplicate.

#### Quantification TMAO in Serum Samples

Trimethylamine N-oxide was quantified in serum samples using Nuclear Magnetic Resonance (NMR) (Embade et al., 2016). For NMR analysis, serum samples were thawed for 30 min and aliquots of 300 µL were mixed with 300 µL of phosphate buffer (pH 7.0) containing 5 mmol/L TSP (Trimethylsilyl propionate) and 5% v/v D2O. The final mixtures were gently shaken and transferred to NMR 96 rack tubes. NMR spectra were measured at 300 K on a Bruker Avance IVDr 600 MHz spectrometer (Bruker Biospin, Germany) and a Sample Jet Robot (Bruker Biospin, Germany) was used for automatization of the measurements. For each sample, three complementary NMR spectra were recorded. A standard 1H spectrum with water suppression (NOESY) was assessed. We repeated the same experiment with an appended T2 relaxation filter implemented as a CPMG module to decrease broad signals from proteins and lipoproteins. Finally, a two dimensional 1H,1H JRES was measured to help with the identification of the metabolites. All spectra were acquired and processed within the TopSpin program (Bruker Biospin, Germany) applying an automatic phase correction and referenced against internal TSP (δ = 0.00 ppm). To identify and quantify the desired metabolites (TMAO) different amounts of these compounds were added to the serum samples, were measured by NMR and the values of the intensity peaks were represented against concentration. The pure metabolite molecules used for referencing were all obtained from Sigma–Aldrich (St. Louis, MO, United States). For all the spectra we measured the intensity of the peaks corresponding to TMAO (singlets) and the concentrations in the samples were calculated with the power fitted calibration curves.

#### Statistical Analysis

Given that there are no previous studies assessing gut microbiota differences between patients with CAD with or without DM2, we have based our sample size estimation on a previous paper from Emoto et al. (2016). To calculate the sample size, we considered a difference in the mean relative abundance of Bacteroidetes between CAD patients and non-CAD controls with coronary risk factors of 0.084 and an estimated standard deviation between groups of 0.05, at least 9 patients in each study group were needed (90% power and a two-sided alpha level of 0.05). However, we increased the sample size to 16 samples per group.

The relative abundance of each OTU (taxa) were compared by a Wilcoxon test with a continuity correction using the Explicit software package specifically addressed to analyze microbiome data. α- and β-diversities were achieved by QIIME: α-diversity using a non-parametric t-test with a default number of Monte Carlo permutations of 999, and β-diversity using the ANOSIM statistical method with 99 permutations (Moreno-Indias et al., 2015). Continuous variables are summarized as mean ± SD. Discrete variables are presented as frequencies and percentages. Differences in clinical characteristics between two groups were analyzed using the Mann–Whitney U test. The Spearman correlation coefficients were calculated to estimate the correlations between variables. A lineal regression analysis was performed to identify individual bacteria as independent predictors for HOMA-IR, levels of inflammatory mediators, serum TMAO and plasma zonulin levels and relative expression of FOXP3 in the study groups. Statistical analyses were carried out with the statistical software package SPSS version 15.0 (SPSS Inc., Chicago, IL, United States). Values were considered to be statistically significant when the p < 0.05.

## RESULTS

The general characteristics of the patients in both study groups are summarized in **Table 1**. There were no significant differences in age, sex, and body mass index (BMI) between the two study groups. The number of patients with dyslipidemia and hypertension was significantly higher in CAD-DM2 patients when compared with the CAD-NM2 patients. Triglyceride, glucose, and HbA1C were significantly higher and HDL-cholesterol was significantly lower in CAD-DM2 patients when compared with CAD-NM2 (P < 0.05). There was no significant difference in serum total cholesterol and LDL-cholesterol between the two study groups (P > 0.05). CAD-DM2 patients had significantly higher levels of inflammatory markers IL-1B and significantly lower levels of anti-inflammatory IL-10 when compared with non-diabetic patients. TMAO plasma levels were also significantly increased in CAD-DM2 patients when compared with CAD-NDM2 (P < 0.05). Finally, FOXP3 mRNA expression in PBMC was significantly lower (2.9-fold decrease) in CAD-DM2 patients when compared with CAD-NDM2 (p < 0.001).

#### Analysis of the Diversity and Similarity of Microbial Communities in the Study Patients

A total of 249.815 good quality 16S rRNA gene sequences with an average of 11.895 ± 6527 sequences per sample passed the filters, which were applied by means of QIIME. In order to obtain a detailed structural overview of the microbiome of each subject who was enrolled in this study, an analysis of OTU was developed. The microbiota of all fecal samples after QIIME was

composed by 2701 OTUS with a relative abundance higher than 1% in at least two samples (97% similarity cut-off).

Before assessing alpha and beta diversity measures, samples were rarefied to 3119 sequences, which represents the lowest number of quality reads which were obtained from any individual sample in the data set. The CAD-DM2 group had a lower number of OTUs than the CAD no-diabetic group (mean = 925 versus 987, P < 0.05, respectively).

The Chao index and Shannon index were calculated to estimate the alpha diversity. The average of community richness (Chao 1) and Shannon index of each group suggested a significant decrease in bacterial richness and diversity in fecal samples of CAD-DM2 with respect to CAD-NDM2 (P = 0.036 and P < 0.001, respectively) (**Table 2**). The rarefaction curve of the OTUs observed started to plateau at approximately 100 reads which suggests that a greater number of reads per sample

TABLE 1 | Biochemical, clinical characteristics, TMAO and inflammatory mediators serum levels and PBMC relative expression of FOXP3 in both study groups.

BMI, body mass index; CVA, cerebrovascular accident; ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin II receptor blocker; LDL, low density lipoprotein; HDL, high density lipoprotein; HbA1c, glycated hemoglobin; GGT, gamma-glutamyl transferase; GOT, glutamic oxaloacetic transaminase; GPT, glutamic pyruvic transaminase, TMAO: trimethylamine N-oxide; L-1β, interleukin-1β; CRP, C-reactive protein; Foxp3, Forkhead box P3. Values are expressed as mean ± SD. ∗P < 0.05.

would not have supplied a more extensive catalog of bacterial taxa.

Principal coordinate analysis (PCoA) plots based on unweighted UniFrac metrics was used to evaluate the beta diversity. The present study showed that apart from a few samples from both study groups closer together in the ordination, a separation between the samples from the diabetic group and the non-diabetic group could be observed from PC1 and PC2 scores that accounted for 22.08 and 24.39% of total variations. ANOSIM with permutations suggested that the intestinal microflora composition of these two groups is significantly different (P = 0.039) (**Figure 1**).

#### 16S rRNA Gene Pyrosequencing in Fecal Samples from CAD-DM2 and CAD-NDM2 Patients

In this study, variations in the composition of fecal microbiota of CAD-DM2 and CAD-NDM2 groups were observed at different bacterial levels. At the phyla level the majority of the OTUS were found to belong to Bacteroidetes (53.87% CAD-DM2 vs. 63.42% CAD-NDM2, P < 0.001), Firmicutes was the next most abundant (25.69% CAD-DM2 vs. 23.29% CAD-NDM2, P = 0.49) followed by Proteobacterias (3.67% CAD-DM2 vs. 2.05% CAD-NDM2, P = 0.04), but only Bacteroidetes and Proteobacterias exhibited significant differences between both, the CAD-DM2 and the CAD-NDM2 study groups. The remaining bacterial population belonged to the other four phyla (Fusobacteria, Actinobacteria, Verrucomicrobia, and Tenericutes) that had a relative abundance lower than 1% in at least two samples (**Figure 2**).

Twenty-two families were detected among all groups. We found a significant increase in Veillonellaceae (28.93% CAD-DM2 vs. 16.97% CAD-NDM2, P < 0.001), Enterobacteriaceae (19.53% CAD-DM2 vs. 4.73% CAD-NDM2, P = 0.016), Rikenellaceae (11.13% CAD-DM2 vs. 9.92% CAD-NDM2, P = 0.023, Streptococcaceae (6.64% CAD-DM2 vs. 2.55% CAD-NDM2, P < 0.001), and Desulfovibrionaceae (13.95% CAD-DM2 vs. 10.69% CAD-NDM2, P < 0.001) in CAD-DM2 group. Furthermore, a significant decrease in the abundance was found in CAD-DM2 when compared with CAD-NDM2 for Bacteroidaceae (49.02% CAD-DM2 vs. 60.48% CAD-NDM2, P < 0.001), Lachnospiraceae (14.67% CAD-DM2 vs. 20.56% CAD-NDM2, P < 0.001), Prevotellaceae (5.06% CAD-DM2 vs. 8.85% CAD-NDM2, P = 0.05), S24-7 (1.59% CAD-DM2 vs. 2.38% CAD-NDM2, P = 0.023, P < 0.001),

TABLE 2 | Estimate richness (Chao1) and diversity index (Shannon) indices among microbial communities obtained from fecal samples from CAD-DM2 and CAD-NDM2 patients.

The richness estimator Chao and diversity estimator Shannon were calculated at 3% distance. ∗P < 0.05.