In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

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Autophagy is emerging as a crucial defense mechanism against bacteria, but the host intracellular sensors responsible for inducing autophagy in response to bacterial infection remain unknown. Here we demonstrated that the intracellular sensors Nod1 and Nod2 are critical for the autophagic response to invasive bacteria. By a mechanism independent of the adaptor RIP2 and transcription factor NF-kappaB, Nod1 and Nod2 recruited the autophagy protein ATG16L1 to the plasma membrane at the bacterial entry site. In cells homozygous for the Crohn's disease-associated NOD2 frameshift mutation, mutant Nod2 failed to recruit ATG16L1 to the plasma membrane and wrapping of invading bacteria by autophagosomes was impaired. Our results link bacterial sensing by Nod proteins to the induction of autophagy and provide a functional link between Nod2 and ATG16L1, which are encoded by two of the most important genes associated with Crohn's disease.

Nod1 and Nod2 are mammalian proteins implicated in the intracellular detection of pathogen-associated molecular patterns. Recently, naturally occurring peptidoglycan (PG) fragments were identified as the microbial motifs sensed by Nod1 and Nod2. Whereas Nod2 detects GlcNAc-MurNAc dipeptide (GM-Di), Nod1 senses a unique diaminopimelate-containing GlcNAc-MurNAc tripeptide muropeptide (GM-Tri DAP ) found mostly in Gram-negative bacterial PGs. Because Nod1 and Nod2 detect similar yet distinct muropeptides, we further analyzed the molecular sensing specificity of Nod1 and Nod2 toward PG fragments. Using a wide array of natural or modified muramyl peptides, we show here that Nod1 and Nod2 have evolved divergent strategies to achieve PG sensing. By defining the PG structural requirements for Nod1 and Nod2 sensing, this study reveals how PG processing and modifications, either by host or bacterial enzymes, may affect innate immune responses. Peptidoglycan (PG)1 is a major constituent of the cell wall of Gram-positive bacteria and consists of glycan chains of alternating N-acetylglucosamine (GlcNAc) and N-acetylmuramic acid (MurNAc) that are cross-linked to each other by short peptides, allowing the formation of a rigid polymer that surrounds the bacterial cell. During bacterial life cycle, peptidoglycan is constantly degraded by specific hydrolases, and newly synthesized subunits are integrated into the polymeric structure, allowing biological processes such as cell division. In Gram-negative bacteria, a thin layer of peptidoglycan is also found in the periplasmic space. Apart from the thickness and the degree of stem peptides cross-linking, an important difference between Gram-positive and Gram-negative peptidoglycans resides in the nature of the third amino acid of the peptides. In Gram-positive bacteria, this amino acid is commonly a lysine, whereas a diaminopimelic acid is found in most Gramnegative bacteria. Extensive analysis from many bacteria has revealed that, in steady state conditions, peptidoglycans from each bacterial strain have somehow fixed proportions of di-, tri-, tetra-, or pentapeptide substituted to the MurNAc sugar moiety.

Toll-like receptor 2 (TLR2) has been shown to recognize several classes of pathogen-associated molecular patterns including peptidoglycan (PG). However, studies linking PG with TLR2 recognition have relied mainly on the use of commercial Staphylococcus aureus PG and have not addressed TLR2 recognition of other PG types. Using highly purified PGs from eight bacteria (Escherichia coli, Pseudomonas aeruginosa, Yersinia pseudotuberculosis, Helicobacter pylori, Bacillus subtilis, Listeria monocytogenes, Streptococcus pneumoniae and S. aureus), we show that these PGs are not sensed through TLR2, TLR2/1 or TLR2/6. PG sensing is lost after removal of lipoproteins or lipoteichoic acids (LTAs) from Gram-negative and Gram-positive cell walls, respectively. Accordingly, purified LTAs are sensed synergistically through TLR2/1. Finally, we show that elicited peritoneal murine macrophages do not produce tumour necrosis factor-a or interleukin-6 in response to purified PGs, suggesting that PG detection is more likely to occur intracellularly (through Nod1/Nod2) rather than from the extracellular compartment.

Diabetes mellitus (DM) encompasses a multitude of secondary disorders, including heart disease. One of the most frequent and potentially life threatening disorders of DM-induced heart disease is ventricular tachycardia (VT). Here we show that toll-like receptor 2 (TLR2) and NLRP3 inflammasome activation in cardiac macrophages mediate the production of IL-1β in DM mice. IL-1β causes prolongation of the action potential duration, induces a decrease in potassium current and an increase in calcium sparks in cardiomyocytes, which are changes that underlie arrhythmia propensity. IL-1β-induced spontaneous contractile events are associated with CaMKII oxidation and phosphorylation. We further show that DM-induced arrhythmias can be successfully treated by inhibiting the IL-1β axis with either IL-1 receptor antagonist or by inhibiting the NLRP3 inflammasome. Our results establish IL-1β as an inflammatory connection between metabolic dysfunction and arrhythmias in DM.

While a number of microbial-associated molecular patterns have been known for decades to act as adjuvants, the mechanisms and the signaling pathways underlying their action have remained elusive. Here, we examined the unfolding of the adaptive immune response induced by Nod2 in vivo upon activation by its specific ligand, muramyl dipeptide, a component of peptidoglycan. Our findings demonstrate that this bacterial sensor triggers a potent Ag-specific immune response with a Th2-type polarization profile, characterized by the induction of IL-4 and IL-5 by T cells and IgG1 Ab responses. Nod2 was also found to be critical for the induction of both Th1- and Th2-type responses following costimulation with TLR agonists. Importantly, the synergistic responses to Nod2 and TLR agonists seen in vivo were recapitulated by dendritic cells in vitro, suggesting that these cells likely play a central role in the integration of Nod2- and TLR-dependent signals for driving the adaptive immune response. Taken together, our results identify Nod2 as a critical mediator of microbial-induced potentiation and polarization of Ag-dependent immunity. Moreover, these findings affect our understanding of Crohn’s diseases pathogenesis, where lack of Nod2-dependent Th2 signaling in a subset of these patients might explain heightened Th1-mediated inflammation at the level of the intestinal mucosa.