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Microbiota and Nod-like receptors balance inflammation and metabolism during obesity and diabetes

Gut #microbiota influence host immunity and metabolism during obesity. Bacterial sensors of the innate immune system relay signals from specific bacterial components (i.e., postbiotics) that can have opposing outcomes on host metabolic #inflammation. NOD-like receptors (NLRs) such as Nod1 and Nod2 both recruit receptor-interacting protein kinase 2 (RIPK2) but have opposite effects on blood glucose control. Nod1 connects bacterial cell wall-derived signals to metabolic inflammation and i#nsulin resistance, whereas Nod2 can promote immune tolerance, insulin sensitivity, and better blood glucose control during #obesity. NLR family pyrin domain containing (NLRP) inflammasomes can also generate divergent metabolic outcomes. NLRP1 protects against obesity and metabolic inflammation potentially because of a bias toward IL-18 regulation, whereas NLRP3 appears to have a bias toward IL-1β-mediated metabolic inflammation and insulin resistance. Targeting specific postbiotics that improve immunometabolism is a key goal. The Nod2 ligand, muramyl dipeptide (MDP) is a short-acting insulin sensitizer during obesity or during inflammatory lipopolysaccharide (LPS) stress. LPS with underacylated lipid-A antagonizes TLR4 and counteracts the metabolic effects of inflammatory LPS. Providing underacylated LPS derived from Rhodobacter sphaeroides improved insulin sensitivity in obese mice. Therefore, certain types of LPS can generate metabolically beneficial metabolic endotoxemia. Engaging protective adaptive immunoglobulin immune responses can also improve blood glucose during obesity. A bacterial vaccine approach using an extract of the entire bacterial community in the upper gut promotes protective adaptive immune response and long-lasting improvements in blood glucose control. A key future goal is to identify and combine postbiotics that cooperate to improve blood glucose control.


Obesity is a complex disease characterized by increased body fat accumulation. Many factors contribute to obesity risk and progression, including diet, genetics, sedentary lifestyle, and environment. Obesity increases the risk of other metabolic diseases, including type 2 diabetes (T2D) [1]. Chronic low-grade inflammation is a characteristic shared by obesity and T2D. Obesity-induced changes in the immune system occur in various metabolic tissues, such as adipose tissue, liver, skeletal muscle, pancreas, and the intestine. Obesity-related inflammation is characterized by a lower magnitude immune response compared to during overt (bacterial or viral) infections, but this metabolic inflammation can be chronic and compartmentalized [2]. White adipose tissue (WAT) inflammation is often an instigating event and can initiate and coordinate whole body changes in metabolism during the progression of obesity [3].

Many different types of immune cells are increased in metabolic tissues during obesity. For example, macrophages infiltrate hypertrophic WAT in both animal models of obesity and people with obesity [4]. Macrophages are a key source of increased proinflammatory cytokines during obesity, and macrophages and their inflammatory mediators participate in tissue and whole body insulin resistance and progression of T2D [5,6]. Tumor necrosis factor-α (TNF-α) is a proinflammatory cytokine produced by macrophages that can alter insulin action. TNF-α ablation reduces insulin resistance in both diet-induced and genetic model of obese mice [7]. Many different immune pathways within metabolic and immune cells are active during obesity. Inhibitor of nuclear factor kappa-B kinase subunit beta (IKK-β) and NF-κB pathways bridge inflammation and metabolism, including insulin resistance during obesity. Pharmacological inhibition or genetic deletion IKK-β/NF-κB-dependent inflammatory signaling can protect mice from development of insulin resistance during diet-induced obesity [8].

The source or triggers of metabolic Inflammation during obesity are not well defined, but several candidates have been identified. The intestinal microbiota is one possible origin of inflammation during obesity. Cani et al. show that short term (i.e., 4 weeks) feeding of a high fat diet (HFD) increased circulating lipopolysaccharides (LPS), which is known as the metabolic endotoxemia [9]. This seminal study also indicates that LPS, a membrane component of Gram-negative bacteria, is a causative factor contributing to obesity-induced inflammation and insulin resistance. The elevated LPS may be a result of combination of HFD-induced changes in gut microbiota composition and increase in gut permeability [10,11]. Modulation of gut microbiota either by antibiotics, probiotic or prebiotics supplementation can lower metabolic endotoxemia, inflammation, and improve blood glucose control during obesity, demonstrating that the gut microbiota can be targeted to alter obesity-associated inflammation [[11], [12], [13]]. Many studies have attempted to correlate changes in the microbial taxonomy with metabolic inflammation during obesity. For example, foods high in fat and low in fiber decrease the abundance and diversity of the gut microbiota and reduce the Bacteroidetes/Firmicutes ratio [14,15]. A key goal moving forward is to determine how functional units of the microbiota engage immune receptors to alter metabolic inflammation and host metabolism.

It is well-established that the gut microbiota programs and influences host immunity [16]. Obesity can alter the host–microbe relationship with consequences on metabolic inflammation and host metabolism. Gut mucosal barrier and epithelium are layers of defence mitigating the translocation of microbial components into host. Increased levels of bacteria translocation into adipose tissue and blood is observed as soon as one-week HFD feeding [17]. A HFD-induced disruption in the gut mucosal barrier integrity involves decreased epithelial tight-junction proteins, which allow increased paracellular translocation of LPS, contributing to metabolic endotoxemia, inflammation and metabolic dysfunction [18]. Recently it was reported that obesity generates a microbiota in the upper intestinal tract that poorly metabolizes ethanolamine. High levels of ethanolamine were associated with impaired intestinal permeability by increasing the activity of the transcription factor ARID3 in the promoter region of miRNA-101a-3p, a miRNA capable of interacting and destabilizing the tight-junction protein zona occludens-1 mRNA, causing metabolic endotoxemia and inflammation through decreased zona occludens-1 translation, and consequently reducing its expression [19].

LPS engages the innate immune toll-like receptor (TLR) 4. TLR4 expression and activation is increased in monocytes from T2D patients [20]. Inhibition of LPS/TLR4 signaling by deletion of CD14, a co-receptor of TLR4, protects the mice from LPS and HFD-induced glucose tolerance and inflammation [9]. This is only one example of an innate immune response that connects the microbiota, metabolic inflammation, and host metabolism. There are many intracellular components of the innate immune system that can relay microbiota derived signals to cause changes in metabolism. Nucleotide-binding oligomerization domain-like receptors, or NOD-like receptors (NLRs), including several inflammasomes detect microbial or danger signals that can alter host metabolism. For example, the NLR family, pyrin domain-containing protein (NLRP) 3 inflammasome is a cytosolic multiprotein “metabolic danger sensor” involved in innate immunity, which regulate the activation of caspase-1, leading to the maturation and subsequent release of interleukin-1β (IL-1β) and interleukin-18 (IL-18) [21]. In the absence of NLRP3 or adaptor protein ASC or caspase-1, mice are resistant to HFD-induced obesity and associated insulin resistance [22,23], and lower macrophage recruitment and inflammation in WAT [24,25].

The purpose of this review is to highlight how the microbiota engage bacterial sensors involved in innate and adaptive immunity to impact metabolic inflammation and host metabolism, during obesity and progression of T2D. We will review how NOD-like proteins connect the microbiota and metabolic disease and revisit the concept of metabolic endotoxemia referring to how different types of LPS from the microbiota influence host metabolism.

Detecting microbes with immune responses that alter metabolism

In addition to physical barriers, innate and adaptive immune responses confer protection from invading bacteria [26]. The combination of defense ready responses and immunological memory can mitigate many microbial threats to the host [27,28]. However, engagement of innate and/or adaptive immune response is sufficient to alter host metabolism.

A general concept in innate immunity involves pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs) engage recognition receptors (PRR), including TLRs and NLRs. A common node of these immune pathways is NF-κB and increased transcription of many pro-inflammatory cytokines such as IL-1β, IL-18, TNF-α and interleukin-6 (IL-6) [29,30]. NF-κB can mediate metabolic inflammation and insulin resistance during obesity [31]. The gut microbiota is source of triggers for innate immune responses [32]. Commensal, symbiotic and pathogenic organisms provide a plethora of unique PAMPs and DAMPs to the host. LPS, peptidoglycan, flagellin, microbial genetic material can all engage components of innate immunity and alter host metabolism [33].

In adaptive immunity, microbial-derived antigens can engage antigen presenting cells (APCs) and dictate T cells, including effector and regulatory T-cell function. Microbiota-derived factors also influence T helper 17 (Th17) cells, including a major influence from segmented filamentous bacteria [34]. Th17 lymphocytes are the main producers of interleukins of the IL-17 family. Circulating levels of IL-17E and IL-17F are positively correlated with increased BMI, in the same way that circulating levels of IL-17E are also positively correlated with subcutaneous fat. IL-17 also acts on adipose tissue by decreasing insulin sensitivity, which may lead to T2D in long-term [35]. Dietary habits also show a correlation with IL-17, where the consumption of vegetables and fruits lower IL-17 in children, whereas the consumption of highly processed (fast) food and foods rich in saturated fat increase IL-17 [36,37]. Lower levels of Th17 cytokines in the gut and adipose tissue and higher levels of these cytokines in the liver were observed after a HFD in mice, indicating that the Th17 immune response during obesity is compartmentalized. The impaired Th17 response in the gut is associated with a permissive immune environment, promoting the evasion of bacterial components across the intestinal mucosal barrier that cause metabolic endotoxemia and inflammation of metabolic tissues involved in glycemic control, such as liver [38].

One key adaptive immune response is immunoglobulin A (IgA). Intestinal microbiota is an important influencer and source of IgA [39]. Gut-derived antigens interact with M cells to initiate IgA synthesis. Thereafter, gut luminal IgA can confer mucosal protection and regulate metabolic function [40]. IgA lowers chronic and systemic inflammation and prevents encroachment of bacteria components in the gut that cause insulin resistance and dysglycemia. IgA downregulates proinflammatory cytokines from monocytes (such as macrophages) [41]. Obese mice have lower IgA+ immune cells and restoration of IgA+ B-cell populations (particularly in the gut) improves blood glucose control in obese mice [42]. Breaking the cycle of adipose inflammation and lower IgA is a mechanism that improves long-lasting blood glucose control.

Bacterial sensors that alter metabolism during obesity and type 2 diabetes

NLRC (NOD1 and NOD2)

NLRs can be divided into two major sub-families, NLRC and NLRP. NLRC proteins are PRRs of the innate immunity that include NOD1, NOD2, NLRC4, NLRC3, NLRC5 and NLRX1. NLRCs share region rich in repeated residues of leucine (LRR) in the C-terminal domain, and a central nucleotide-binding oligomerization domain (NOD). They differ from each other mainly due to a third region in the N-terminal formed by a caspase recruitment containing domain (CARD), varying in number or type of CARD, or even lacking a CARD domain [43]. NOD1 and/or NOD2 can influence metabolism including insulin resistance, and blood glucose control during obesity [[44], [45], [46]] (Fig. 1). NOD1 and NOD2 engage unique patterns PAMPs derived from the bacterial cell wall. NOD1 recognizes γ-D-glutamyl-meso-diaminopimelic acid (iE-DAP) from the peptidoglycan mainly from Gram-negative and some Gram-positive bacteria, NOD2 is able to recognize muramyl dipeptide (MDP) which is more abundant in Gram-positive bacteria [47]. The detection of both molecules induces the recruitment of the receptor-interacting protein kinase 2 (RIPK2), initiating a series of events that culminate in the activation of NF-κB and mitogen-activated protein kinase signaling [48]. Free article. Read more at:

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