The dynamic and stress-adaptive signaling hub of 14-3-3: emerging mechanisms of regulation and context-dependent protein-protein interactions

Abstract

14-3-3 proteins are a family of structurally similar phospho-binding proteins that regulate essentially every major cellular function. Decades of research on 14-3-3s have revealed a remarkable network of interacting proteins that demonstrate how 14-3-3s integrate and control multiple signaling pathways. In particular, these interactions place 14-3-3 at the center of the signaling hub that governs critical processes in cancer, including apoptosis, cell cycle progression, autophagy, glucose metabolism, and cell motility. Historically, the majority of 14-3-3 interactions have been identified and studied under nutrient-replete cell culture conditions, which has revealed important nutrient driven interactions. However, this underestimates the reach of 14-3-3s. Indeed, the loss of nutrients, growth factors, or changes in other environmental conditions (e.g., genotoxic stress) will not only lead to the loss of homeostatic 14-3-3 interactions, but also trigger new interactions, many of which are likely stress adaptive. This dynamic nature of the 14-3-3 interactome is beginning to come into focus as advancements in mass spectrometry are helping to probe deeper and identify context-dependent 14-3-3 interactions-providing a window into adaptive phosphorylation-driven cellular mechanisms that orchestrate the tumor cell's response to a variety of environmental conditions including hypoxia and chemotherapy. In this review, we discuss emerging 14-3-3 regulatory mechanisms with a focus on post-translational regulation of 14-3-3 and dynamic protein-protein interactions that illustrate 14-3-3's role as a stress-adaptive signaling hub in cancer.

Fig. 1

Amino acid divergence between σ and ζ isoforms superimposed over the 14-3-3ζ structure. The 14-3-3ζ crystal structure (PDB ID: 4FJ3, accessed from RCSB PDB: www.rcsb.org) was color coded to illustrate amino acid differences between the σ and ζ isoforms using PyMOL (Schrödinger, New York, NY, USA). White residues correspond to amino acids that were identical between the two isoforms. Each amino acid was categorized according to its side chain chemistry, and the categorical changes for each variable residue were color coded according to the table in the center. Each image represents differing views of the 14-3-3ζ dimer, as indicated by the rotational angles between each image. Note that the amino acids forming the phospho-binding pocket are identical between the two isoforms

Fig. 2

SAPH-ire analysis of 14-3-3 protein family IPR000308 and relationship to 14-3-3ζ (P63104). a Crystal structure of 14-3-3ζ dimer (PDB ID: 4FJ3, accessed from RCSB PDB: www.rcsb.org) with highlighted PTM sites shown on one of the monomers. Table on the right indicates the PTM identities at each site, as reported from aggregated proteomics data on dbPTM3 and PhosphoSitePlus (phosphosite.org). b A total of 654 distinct PTMs observed across 37 14-3-3 proteins from 10 different eukaryotic species were aligned and analyzed by SAPH-ire, resulting in 109 modified alignment positions (MAPs). Each MAP is represented as a single circle relative to the alignment position of the family. c Each MAP is represented as relative to the SAPH-ire probability-derived rank order. For panels b and c, circle size and color indicate MAP status and graphically reflects the number of sources from which known-functional status is derived for the MAP (colored circles), known-by-neighbor (KbN) status (green circles), or unknown functional status (gray circles). MAPs are labeled corresponding to the native position of 14-3-3ζ (P63104) that falls within the MAP. Functional PTM sites within 14-3-3ζ (P63104) are indicated with boxes. The relative concentration of the observed PTMs (taken as the “cluster count” of modified residues within ±2 alignment positions surrounding the MAP) is shown to highlight dense PTM clusters along the primary structure of the protein family (b, gray line). (See also supplementary Table S1.)

Fig. 3

Model of 14-3-3ζ regulation by acetylations within the 14-3-3ζ binding pocket. HDAC6-mediated deacetylation of K49 and K120 maintains the 14-3-3ζ phospho-binding pocket free for interactions with phospho-proteins, which drive pro-growth and survival signaling. Inhibition of HDAC6 allows an unidentified KAT to acetylate and inhibit the unbound pool of 14-3-3ζ, which, in turn, leads to a loss of pro-growth/survival 14-3-3ζ interactions

Fig. 4

Dynamic 14-3-3 mechanisms drive the adaptive cellular response to stress and nutrient availability. Shown here are 14-3-3 interactions that drive mechanisms of cellular adaptation, as described in the text