Functional dissection of the autophagy interaction network

While individual modules within the autophagy pathway are relatively well characterized, much less is known concerning the overall organization of the pathway and to what extent the various functional elements communicate with each other. Recently, we have performed a systematic proteomic analysis of the human autophagy system coupled with a functional analysis of a subset of genes in the pathway. This effort has provided a glimpse into the global architecture of the autophagy interaction network (AIN) and has yielded a resource for further mechanistic analysis of this pathway (http://falcon.hms.harvard.edu/ipmsmsdbs/comppass.html).
In total, 65 AIN components have been analyzed proteomically in human cells under conditions of ongoing (basal) autophagy, revealing a network of 751 interactions among 409 non-redundant candidate interacting proteins, with extensive cross-talk among sub-networks. This set of interactions greatly expands the number of known interactions and multi-protein complexes in the human autophagy system. The network contains new components linked to vesicle trafficking, ATG8 conjugation, protein phosphorylation, protein ubiquitylation/deubiquitylation, and lipid modification, and together with genetic (RNAi) and localization studies performed in parallel, provides a framework for understanding the molecular architecture of the pathway and how individual sub-networks communicate with each other.

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Fig. 2 Functional integration of the AIN. Proteins in colored, round boxes are baits, yellow, square boxes are HCIPs. Dotted lines, cross-module interaction. Solid lines, this study. Dotted arrows, potential functional interactions. Red or green full circle, three-quarter circle, and half-circle re-present a reduction or increase in auto-phagosomes with 4, 3, and 2 siRNAs, respectively, in GFP-LC3B expressing cells. Proteins in white boxes were not found by proteomics. The six ATG8 family members are represented by ATG8.

Behrends C., Sowa M. E., Gygi S. P., and Harper J. W. Network organization of the human autophagy system. Nature 466: 68-76 (2010).

We seek to understand the dynamic organization of protein complexes in the human autophagy network upon activation or inhibition of the pathway. Furthermore, we aim to elucidate the contribution of recently identified AIN components to selective recruitment of cargo and to formation and maturation of autophagosomes.

Xenophagy and bacterial avoidance

In the course of its role in host innate immune response, autophagy acts as a cell-autonomous defence directly eliminating intracellular microbes (xenophagy). However, as a result of this selective evolutionary pressure, microbial pathogens that successfully parasitize eukaryotic cells (i.e. intracellular pathogens) have evolved to block autophagic microbial defense and subvert host autophagic responses for their own survival or growth. Microbial adaptation strategies identified to date include prevention of autophagy induction or maturation of autophagosomes into autolysosomes, avoidance of pathogen recognition by the autophagic machinery, and utilization of the autophagic machinery to enhance intracellular survival, replication, or extracellular release of intracellular pathogens. However, the exact molecular mechanisms underlying avoidance of auto(phago)lysosomal degradation and/or attenuation of autophagy-dependent activation of host immune responses and their potential roles in microbial pathogenesis are only rudimentarily understood.

Fig. 3 Scheme of host-pathogen interactions.

We seek to deepen our understanding of the complex interplay between autophagy and microbial adaptations against autophagy, which governs the net outcome of host-microbe encounters. We will take advantage of a multidisciplinary platform combing state-of-the-art proteomic and microscopic tools to systematically uncover signalling pathways and molecular machineries at the interface of host autophagy and intracellular pathogen survival. A major goal of this work is to identify emerging mutual themes in xenophagic induction and microbial avoidance by analyzing different host-pathogen interactions.