Cyclic AMP is dispensable for allorecognition in Dictyostelium cells overexpressing PKA-C

An integrated, cross-regulation pathway model involving activating/adaptive and feed-forward/feed-back loops for directed oscillatory cAMP signal-relay/response during the development of Dictyostelium

Self-organized and excitable signaling activities play important roles in a wide range of cellular functions in eukaryotic and prokaryotic cells. Cells require signaling networks to communicate amongst themselves, but also for response to environmental cues. Such signals involve complex spatial and temporal loops that may propagate as oscillations or waves. When Dictyostelium become starved for nutrients, cells within a localized space begin to secrete cAMP. Starved cells also become chemotactic to cAMP. cAMP signals propagate as outwardly moving waves that oscillate at ∼6 min intervals, which creates a focused territorial region for centralized cell aggregation. Proximal cells move inwardly toward the cAMP source and relay cAMP outwardly to recruit additional cells. To ensure directed inward movement and outward cAMP relay, cells go through adapted and de-adapted states for both cAMP synthesis/degradation and for directional cell movement. Although many immediate components that regulate cAMP signaling (including receptors, G proteins, an adenylyl cyclase, phosphodiesterases, and protein kinases) are known, others are only inferred. Here, using biochemical experiments coupled with gene inactivation studies, we model an integrated large, multi-component kinetic pathway involving activation, inactivation (adaptation), re-activation (re-sensitization), feed-forward, and feed-back controls to generate developmental cAMP oscillations.

Development of the dictyostelid Polysphondylium violaceum does not require secreted cAMP

Group 4 Dictyostelia, like Dictyostelium discoideum, self-organize into aggregates and fruiting bodies using propagating waves of the chemoattractant cAMP, which are produced by a network containing the adenylate cyclase AcaA, cAMP receptors (Cars) and the extracellular cAMP phosphodiesterase PdsA. Additionally, AcaA and the adenylate cyclases AcrA and AcgA produce secreted cAMP for induction of aggregative and prespore gene expression and intracellular cAMP for PKA activation, with PKA triggering initiation of development and spore and stalk maturation. Non-group 4 species also use secreted cAMP to coordinate post-aggregative morphogenesis and prespore induction but use other attractants to aggregate. To understand how cAMP's role in aggregation evolved, we deleted the acaA, carA and pdsA genes of Polysphondylium violaceum, a sister species to group 4. acaA- fruiting bodies had thinner stalks but otherwise developed normally. Deletion of acrA, which was similarly expressed as acaA, reduced aggregation centre initiation and, as also occurred after D. discoideum acrA deletion, caused spore instability. Double acaA-acrA- mutants failed to form stable aggregates, a defect that was overcome by exposure to the PKA agonist 8Br-cAMP, and therefore likely due to reduced intracellular cAMP. The carA- and pdsA- mutants showed normal aggregation and fruiting body development. Together, the data showed that P. violaceum development does not critically require secreted cAMP, while roles of intracellular cAMP in initiation of development and spore maturation are conserved. Apparently, cell-cell communication underwent major taxon-group specific innovation in Dictyostelia.

PKR Protects the Major Catalytic Subunit of PKA Cpk1 from FgBlm10-Mediated Proteasome Degradation in Fusarium graminearum

For optimal proteolytic function, the proteasome core (CP or 20S) must associate with activators. The cAMP-PKA pathway is reported to affect the activity of the proteasome in humans. However, the relationship between the proteasome and PKA is not well characterized. Our results showed that the major catalytic subunit Cpk1 was degraded without the protection of Pkr. Eleven (out of 67) pkr suppressors had FgBlm10 C-terminal truncation, one suppressor had an amino acid change mutation in the PRE6 ortholog (FGRRES_07282), and one in the PRE5 ortholog (FGRRES_05222). These mutations rescued the defects in growth and conidial morphology, Cpk1 stability, and PKA activities in the pkr mutant. The interaction of FgBlm10 with FgPre5 and FgPre6 were detected by co-immunoprecipitation, and the essential elements for their interaction were characterized, including the FgBlm10 C-terminus, amino acid D82 of FgPre6 and K62 of FgPre5. Additional FgBlm10-interacting proteins were identified in the wild type and pkr mutant, suggesting that PKA regulates the preference of FgBlm10-mediated proteasome assembly. In addition, PKA indirectly affected the phosphorylation of FgBlm10, and its localization in the nucleus. The truncation of the FgBlm10 C terminus also enhanced nuclear import and bleomycin resistance, suggesting its role in proteasome assembly at DNA damage sites. Collectively, our data demonstrated that regulation between PKA and proteasome degradation is critical for the vegetative growth of F. graminearum.

Leveraging the model-experiment loop: Examples from cellular slime mold chemotaxis

Interplay between models and experimental data advances discovery and understanding in biology, particularly when models generate predictions that allow well-designed experiments to distinguish between alternative mechanisms. To illustrate how this feedback between models and experiments can lead to key insights into biological mechanisms, we explore three examples from cellular slime mold chemotaxis. These examples include studies that identified chemotaxis as the primary mechanism behind slime mold aggregation, discovered that cells likely measure chemoattractant gradients by sensing concentration differences across cell length, and tested the role of cell-associated chemoattractant degradation in shaping chemotactic fields. Although each study used a different model class appropriate to their hypotheses - qualitative, mathematical, or simulation-based - these examples all highlight the utility of modeling to formalize assumptions and generate testable predictions. A central element of this framework is the iterative use of models and experiments, specifically: matching experimental designs to the models, revising models based on mismatches with experimental data, and validating critical model assumptions and predictions with experiments. We advocate for continued use of this interplay between models and experiments to advance biological discovery.