Abstract
Notch signalling pathway plays a key role in metazoan biology by contributing to resolution of binary decisions in the life cycle of cells during development. Outcomes such as proliferation/differentiation dichotomy are resolved by transcriptional remodelling that follows a switch from Notchon to Notchoff state, characterised by dissociation of Notch intracellular domain (NICD) from DNA-bound RBPJ. Here we provide evidence that transitioning to the Notchoff state is regulated by heat flux, a phenomenon that aligns resolution of fate dichotomies to mitochondrial activity. A combination of phylogenetic analysis and computational biochemistry was utilised to disclose structural adaptations of Notch1 ankyrin domain that enabled function as a sensor of heat flux. We then employed DNA-based micro-thermography to measure heat flux during brain development, followed by analysis in vitro of the temperature-dependent behaviour of Notch1 in mouse neural progenitor cells. The structural capacity of NICD to operate as a thermodynamic sensor in metazoans stems from characteristic enrichment of charged acidic amino acids in β-hairpins of the ankyrin domain that amplify destabilising inter-residue electrostatic interactions and render the domain thermolabile. The instability emerges upon mitochondrial activity which raises the perinuclear and nuclear temperatures to 50 °C and 39 °C, respectively, leading to destabilization of Notch1 transcriptional complex and transitioning to the Notchoff state. Notch1 functions a metazoan thermodynamic sensor that is switched on by intercellular contacts, inputs heat flux as a proxy for mitochondrial activity in the Notchon state via the ankyrin domain and is eventually switched off in a temperature-dependent manner.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12964-022-00886-4.
Keywords: Notch1, Ankyrin, Heat flux, Mitochondria
Background
Notch signalling pathway is a metazoan novelty [1], whereby downstream signals contribute to coordinated resolution of diverse fate dichotomies confronted by individual cells via input from neighbouring cells. Decisions such as proliferation versus differentiation [2], or assumption of mutually exclusive sub-lineage fates [3] are modulated by Notch-mediated transcriptional remodelling of cycling cells [4]. Assumption of an alternative fate requires emergence of a competing fate and simultaneous abolition of the dominant fate, in a stepwise manner. Initially, Notch signalling pathway is switched on by trans- [4] or cis-ligands [5] that trigger enzymatic release of Notch intracellular domain (NICD) followed by subsequent translocation of NICD to the nucleus where it associates with RBPJ. Transcriptional remodelling in the Notchon state facilitates partial emergence of the transcriptional profile of a coupled competing fate (e.g. differentiation profile in the context of cycling cells) leading to a bistable transcriptional profile [6]. Subsequent transitioning to mono-stability by termination of the dominant fate and adoption of the competing fate requires a second wave of transcriptional remodelling that is invoked by switching from a Notchon to Notchoff state [2, 3]. Both activation and inactivation of Notch signalling pathway are controlled at multiple levels.
While activation of Notch signalling has been extensively studied, molecular mechanisms for switching off the signalling cascade are not as well-defined. In the Notchon state, termination of Notch signalling output requires intervention at four distinct levels: transcriptional silencing of the active notch locus, degradation of the available notch mRNAs, removal or inhibition of the existent Notch receptors, and dissociation of NICD from the binding partner RBPJ. Several mechanisms have been proposed for removal of the existing Notch receptors including endocytosis [7], autophagy [8] and ubiquitination [9]. As a membrane-tethered receptor, Notch requires endocytosis, not only to release the NICD from the membrane [10] but also to partition the receptor into late endosomes for degradation [7]. Apart from endocytosis, Notch can be degraded by incorporation into autophagosomes [8]. Finally, ubiquitination serves as another important decision point in regulating the half-life and activity of the membrane-bound Notch receptor. While mono-ubiquitination directs the receptor to the vesicular trafficking pathway, poly-ubiquitination leads to its degradation [11]. It appears that the post-translational modifications described above either fine-tune the steady-state rate of signalling output in the Notchon state or set an upper limit to the signalling output by blocking further generation of NICD. To be effective, the post-translational regulation of Notch receptor must be complemented by transcriptional and post-transcriptional modulation of the encoding locus and the associated mRNAs.
We recently reported that transcription from human notch-1 locus is regulated by generation of a cis-natural antisense transcript that restricts the active transcriptional window to G0/early G1 phase of cell cycle [12]. The antisense transcript also regulates the availability of notch-1 transcript at G1 phase of cell cycle by calibrating RNA editing of the transcript and its subsequent degradation by nonsense-mediated decay [12]. The critical role of mRNA titre in determining Notch signalling output [12] is foreshadowed by the evolution of multiple parallel mechanisms that enhance the fidelity of notch transcriptional landscape [13, 14]. While knowledge of the Notch signalling cascade has grown extensively over the past decade [4], one major question remains unanswered; that is the mechanism(s) that regulate termination of Notch/RBPJ signalling output by triggering dissociation of the active transcriptional complex. A preliminary clue regarding transitioning from Notchon to Notchoff state was provided by the observation that amplified mitochondrial activity during brain development coincides with abrupt inactivation of Notch signalling cascade and accelerated adoption of neuronal fate [15]. However, it remained unclear whether these two events are causally linked.
Here, we adopt an evolutionary approach to probe the causal link between mitochondrial activity and transitioning to the Notchoff state. We provide evidence that the ankyrin domain of Notch-1 has progressively evolved to acquire structural properties of a thermodynamic sensor that inputs heat flux as a proxy for mitochondrial activity in the Notchon state and is eventually switched off in a temperature-dependent manner. This mechanism ensures optimal timing of major biological decisions, such as differentiation, by aligning the resolution of fate dichotomies to mitochondrial activity. Together with previous knowledge regarding transitioning from Notchon to Notchoff state, our findings advance the blueprint of a circuitry that regulates biological decision making.
Results
Ankyrin domain as a stress sensor in major kingdoms of life
Notch is a transmembrane protein with an extracellular domain consisting of multiple epidermal growth factor-like (EGF) repeats, and an intracellular domain comprising a RAM domain and multiple tandem ankyrin (ANK) repeats [16]. Subsequent to enzymatic cleavage the intracellular domain (NICD) translocates to the nucleus, wherein the RAM and ankyrin domains of NICD associate with the ß-trefoil and C-terminal domains of a DNA-bound RBPJ (alias CSL) and MAML-1 to recruit RNAP-II [17, 18] and to trans-activate the downstream loci (i.e. Notchon state). To disclose the mechanistic basis for transitioning from the Notchon to the Notchoff state, we investigated the evolutionary basis for co-opting various domains of Notch receptors. We began by reconstructing the comparative network topologies populated by EGF and ANK domains of the representative Notch-1 receptor after the three-way split of plants, animals and fungi. The reconstruction was restricted to the best studied species from each taxonomic division; Saccharomyces cerevisiae from the fungi, Arabidopsis thaliana from the plant kingdom, and Homo sapiens as the representative metazoan species.
While the EGF domain (InterPro ID: IPR001881) and the intrinsically disordered RAM domain are not deployed in S. cerevisiae (strain ATCC 204,508 / S288c), the ANK domain (InterPro ID: IPR002110) contributes to multiple related protein families. These ANK+ proteins facilitate adaptation of the yeast to exogenous stressors that affect the cell wall and plasma membrane (Fig. 1a). For example, ANK+ Mga2/Spt23 complex senses lipid-packing within the lipid bilayer [19] and activates Δ9 fatty acid desaturase of yeast, OLE1, at high temperature to enhance the fluidity and hence the mechanical durability of nuclear [20] and cytoplasmic membranes [21]. A key facet of accommodating stressors is modulation of cell cycle dynamics that is achieved by two ANK+ protein assemblies of yeast, namely SBF (Swi6/Swi4) and MBF (Swi6/Mbp1) complexes [22]. To adapt to stressors, Swi6 receives input from Mpk-1 protein kinase regarding cell wall integrity of yeast [23, 24] and reprograms cycle dynamics accordingly [25]. While ANK+ proteins remained the centrepiece of adaptation to stressors in multicellular life forms, novelties came about that enabled heightened response to stressors by integration of organism-level (i.e. systemic) memory of exposure to stressors. One such major change was recruitment of the EGF domain.
In plants, the EGF domain uniquely characterises a single protein family, wall-associated kinases (WAKs) (Fig. 1b). WAKs bind to cell wall pectin and activate stress adaptation pathways upon sensing alterations of cell wall by biotic and abiotic stressors [26]. Trans-activation of WAKs by the plant stress hormone salicylic acid (SA) [27] requires critical input from two ANK+ proteins, the upstream mediator BDA1 [28] and the downstream mediator NPR1 [27] (Fig. 1b). Therefore, WAKs interpret modifications of cell wall in the context of hormonal input from other, distal cells (Fig. 1c), a phenomenon that maximises the chance of survival [29] by calibrating the response of individual cells to systemic memory of exposure to stressors [30]. It becomes apparent that ANK+ proteins of fungi and plants, with high structural and functional homology (Fig. 1d), have populated key nodes of signalling cascades that facilitate adaptation to stressors by signalling input from cell wall integrity receptors (Fig. 1c, e).
In metazoans, replacement of the yeast Swi6/Mbp1/CDC28 signalling axis [31] by the E2F family of transcription factors [32] (Fig. 1f), and the disappearance of cell wall facilitated repurposing and broader exaptation of EGF and ANK motifs by diverse protein families (Fig. 2a). In C. elegans, ANK domain characterises five major families, I. Notch homologues Glp1 and Lin12, and E3 ubiquitin ligase Mib1, II. Neuronal mechanosensory receptors, III. Integrin-linked kinase homologue Pat4, IV. Ape1 (a homologue of human Tp53bp2), V. The IκB homolog Ikb1 (Fig. 2a). This ANK+ cluster expands to include multiple components of the NF-κB signalling cascade in higher metazoans. The EGF domain in C. elegans is restricted to members of the Notch signalling pathway and structural components of the extracellular matrix, such as laminins. Similar to ANK, exaptation of EGF increases in higher metazoans where the domain contributes to other novelties such as coagulation factors and mucins of saliva (Fig. 2a). Ankyrin domain in metazoan animals is also deployed as a reporter of abiotic stress.
In neuronal ion channels ANK functions as a reporter of abiotic stressors in a rather unique manner. Modularity of ANK and spatial organisation of individual repeat modules gives rise to a molecular spring which stores and releases mechanical energy [33]. This structural property has been utilised in neuronal ion channels to generate a thermal nano-spring [34] that undergoes temperature-dependent structural changes leading to channel opening [35]. In higher metazoan species with a closed circulation [36], a reduction of oxygen partial pressure in capillaries is directly sensed by the Band 3–ankyrin complex of RBCs leading to increased deformability of RBCs, increased velocity of blood flow, and re-establishment of the oxygen tension [37]. Likewise, function of the key ANK+ proinflammatory transcription factor NFκB is regulated by oxidative stress [38] and thermal fluctuation [39].
Apart from high structural homology of the ankyrin domains (Fig. 2b), the function of Notch-1 in driving progression of cell cycle (G1-S transition) by regulating the anabolic flux bears close similarity to Swi6 (Fig. 2c, d). There is, however, a radical difference in the network topologies and the signalling logics of the Swi6 and Notch1 pathways (Fig. 2e). Swi6 functions as a downstream mediator of Pho80-Pho85 family of cyclin-dependent kinases that interact to report abiotic stressors. Transition to multicellularity was concurrent with redundancy of the Pho80-Pho85 pathway [40] leading to emergence of Notch-1 as an upstream pro-anabolic mediator, a hierarchical position that must be occupied by a protein with sensory capacity (Fig. 2e). Given the sensory functionality of the ankyrin domain in other proteins as discussed above, we postulated that deployment of the ankyrin domain could have equipped Notch-1 with a capacity to interact with and report specific stressors. To investigate whether Notch ankyrin domain could interact with stressors, we probed evolutionary adaptations of ANK after deployment of the domain as a structural component of the Notch receptor with reference to Swi6.
ANK domain of Notch-1 has adopted structural features that renders it responsive to thermal fluctuations
Despite significant inter-species divergence of ligand-binding EGF repeats and the RBPJ-binding RAM domain of Notch (amino acid similarity < 75% except for EGF-32), the ANK domain of the protein is highly conserved between the human and fruit fly orthologues (Fig. 3a, amino acid similarity > 75%). Absence of a significant divergence suggested that the ANK domain of Notch is subject to selective pressures that are common to both species, and that are somewhat uncoupled from the selective pressures that have shaped the evolutionary trajectories of the EGF and RAM domains. To gain insight into the potential selective pressure acting upon ANK domains of the Notch protein, we mapped structural adaptations of the domains with reference to yeast Swi6.
Each module of ANK domain in Notch is comprised of 33 residues that form two anti-parallel α-helices (α1 and α2) followed by a β-hairpin (βhp) (Fig. 3b). Structural alignment of the consensus ANK sequence revealed major adaptations in ANK domains of the Notch protein. A key structural adaptation was enrichment of alanine and charged residues in α-helices and β-hairpins of the ANK domains of the human Notch-1 receptor which came at the cost of depletion of hydrophilic residues (Fig. 3c). Alanine is a known stabiliser of α-helices [41, 42], a propensity that is amplified by proximity to charged residues [43]. We used a PDB structure with a resolution better than 1.55 Å (ID: 2F8Y) to study spatial distribution of the charged residues. While the side chains of positively charged residues mainly populated the pocket formed between the inner α-helix (i.e. α2) and the β-hairpins (RBP-J binding pocket), negatively charged side chains occupied the outer surface of the outer α-helices (i.e. α1) and the β-hairpins (Fig. 3c). It is known that arrangement of side chains with similar electrostatic charges in dense pockets could potentially lead to coulomb repulsion [44]. Application of the Adaptive Poisson-Boltzmann Solver (APBS) to visualise the electrostatic potential around Notch-1 ANK revealed two zones of high net negative potential (Fig. 4a). One region (≈289 Å2) corresponded to the solvent-exposed surface of the β-hairpins of ANK3 and ANK4 (residues ASP-1987, ASP-1989, ASP-2020) (Fig. 4b). The other zone (≈327 Å2) was populated by the side chains of the acidic residues in α2-helices of ANK4 (residues GLU-2008, GLU-2012, ASP-2013). Anisotropic distribution of dense pockets of similar charges in Notch ANK domain was a unique structural adaptation that was not observed in Swi6 (Fig. 4a) and in other studied ANK domains such as NF-κB (Fig. 4a). The combination of high net charge and reduced hydrophobicity is a unique structural feature of "natively unfolded" proteins [45] and localised adoption of this feature by ANK4 (Fig. 4b) is expected to destabilise the ankyrin domain of Notch protein. This finding raised an important question. Is Notch ankyrin domain unique in adopting the described destabilising structural feature?
We used IUPred [46] to gain quantitative insight into divergence of Notch1 ankyrin domain from ankyrin domains of other proteins, in adopting destabilising structural features (Fig. 5). Consistent with previous analyses, Notch-1 ankyrin domain exhibited a high IUPred score (average: 0.37). The average IUPred score for ankyrin domains of other human proteins was 0.22, a value close to the average IUPred score of S. cerevisiae ankyrin domains (average score: 0.21). Ankyrin domains of A. thaliana, on the other hand, showed the opposite trend of a reduced IUPred score (Average score: 0.16). We then estimated the entropic cost of Notch-1 structural adaptation knowing that the IUPred score is generated by a method developed by Thomas and Dill which uses Boltzmann statistics to extract the dimensionless energy-like inter-residue interaction potential [47]:
where k is the Boltzmann constant, and T is absolute temperature, and ρij and ρ*ij represent the pairing frequencies of amino acid type i with amino acid type j in a protein of interest and in a reference state, respectively. After rearrangement of the latter equation, nAkΔT × (IUPrednotch/IUPredref) corresponds to the entropic cost of the evolutionary adaptations of Notch-1 ankyrin domain (nA: Avogadro’s number, IUPrednotch: IUPred score for Notch-1 ANK, IUPredref: average IUPred score for ANK domains of other human proteins). This corresponds to an entropic cost of
In other words, Notch ankyrin becomes destabilised by 0.8ΔT (kcal⋅mol−1) in a temperature-dependent manner and relative to the more stable ANK domains of other proteins. Given the ΔG0 for binding of Notch1 intracellular domain to RBPJ (≈ -8 kcal⋅mol−1) [48], a temperature rise of 10°K could potentially provide sufficient energy to disrupt the association of Notch1 intracellular domain and RBPJ. Further, given the reported flexibility of ankyrin domain along one major axis that accommodates the flexible β-hairpins [34], even a more modest temperature rise of ≈3°K (i.e. 10°K/3 degrees of freedom) would be theoretically sufficient to trigger dissociation of the Notch-1/RBPJ/MAML complex. In order to investigate the behaviour of Notch-1 ankyrin domain as a function of temperature, we carried out molecular dynamic simulations at different temperatures.
Molecular dynamics analysis of Notch-1 ankyrin was performed on a PDB structure with a resolution of 1.55 Å (ID: 2F8Y) (see methods for the details). The root-mean-square fluctuation (RMSF) that represents fluctuation of individual amino acids during the trajectory of the dynamics, revealed that two regions fluctuate more than others (Fig. 6a). A region corresponding to the negatively charged pocket formed by ARG-2060, GLU-2061, and GLU2062 of ANK5 was unstable both at 37 °C and 39 °C. A second region corresponding to the negatively charged zone populated by the side chains of the acidic residues in α2-helices of ANK4 (residues GLU-2008, GLU-2012, ASP-2013) became unstable only at 39 °C. Both these regions exhibited high net negative potential suggesting that coulomb repulsion is potentially involved in driving the fluctuations. Consistent with this notion, mutating ASP-1989 to ASN-1989 in silico, to reduce the repulsive force from ASP-1987 and ASP-2020 on ANK4, resulted in dampening of molecular fluctuations at 39 °C (Fig. 6b). The in-silico findings regarding the critical role of ASP-1987 were aligned to the observation that the substitution in Adams-Oliver syndrome leads to disruption of Notch-1 signalling [49]. The acidic amino acids in ANK4, apart from fluctuating in a temperature-dependent manner, are essential for stabilising the RBPJ/Notch1/MAML1 transcriptional complex (Fig. 6c). GLU-2008 of ANK4 and ASP-1972 of ANK3 establish five hydrogen bonds with MAML-1 (total number of inter-chain hydrogen bonds: 8) (Fig. 6c). Further, ASP-1994 of ANK4 makes two hydrogen bonds with GLN-347 of RBPJ (Fig. 6c). The dual role of the acidic amino acids of ANK4 in stabilising and destabilising the Notch1 transcriptional complex bolstered the suggestion that the ankyrin domain has evolved to function as a thermodynamics sensor that terminates Notch signalling output in a temperature-dependent manner. Accordingly, enrichment of alanine and the resultant stabilisation of α-helices [41–43], is a structural adaptation that enhances efficient transmission of vibrational energy via rigid α-helices as opposed to its dissipation as heat [50, 51]. We finally set about to experimentally test whether increased temperature would result in termination of Notch1 signalling output by destabilisation of ankyrin domain and whether such an increased temperature arises upon cannibalisation of erythroblasts and the resultant activation of mitochondria [15].
Heat flux: a physical signal arising at the interface of metazoan biophysics and bioenergetics
In order to measure the intracellular temperature, we used two L-DNA (optical isomer of naturally occurring D-DNA) molecular beacons (MB) that do not bind to cellular nucleic acids and hence accurately report alterations of intracellular temperature [52]. The L-MB4 and L-MB5 had a Tm of 36 °C and 50 °C, respectively (see Methods). We employed ex ovo electroporation of MB4 and MB5 into chick embryos (Hamburger-Hamilton stage 9–10) to investigate the intracellular temperature of neuroepithelial cells upon cannibalisation of erythroblasts. In the mesencephalon, MB-5 reported an intracellular temperature of ≥ 50 °C in the intravascular erythroblasts prior to cannibalisation by neuroepithelial cells (Fig. 7a). This observation provided an internal control for the DNA-based micro-thermography as heat production is a reported feature of avian erythroblasts that is tuned by mitochondrial activity [53] whose temperature approaches 50 °C upon activation of oxidative phosphorylation [54]. Upon cannibalisation of erythroblasts, the intracellular temperature of cannibalistic cells also raised to ≥ 50 °C (Fig. 7a). While this observation provided assurance that the raised temperature is a physiological phenomenon that occurs during brain development, the presence of non-cannibalistic cells with a normal temperature and the transient nature of this event made it challenging to advance the findings in vivo. In parallel experiments in vitro, incubation of cultured neural progenitor cells in heme-rich medium (10 μM heme) confirmed that access to heme for t = 1 h is sufficient to raise the perinuclear temperature to ≥ 50 °C and the nuclear temperature to 39–40 °C in a synchronised manner and in the entire cellular population (Fig. 7b, c). This nuclear-cytoplasmic gradient is consistent with perinuclear clustering of active mitochondria (Fig. 7d) [55], and curbed diffusion of the thermal energy via the nuclear membrane that has a lower thermal conductivity compared to that of water (0.20 W.m−1.K−1 for lipid bilayer vs. 0.63 W.m−1.K−1 for water) [56]. Given that access to exogenous heme leads to suppression of the Notch-1 signalling pathway [15], we next asked whether increased temperature mediates this effect. To answer this question, cells were incubated at a temperature of 39 °C for 2 h to uniformly increase the cytoplasmic and nuclear temperatures to 39 °C. To improve the accuracy of control experiments, we carried out preliminary experiments to determine the incubation temperature at which the heat sink buffers against transient temperature rise beyond 37 °C due to mitochondrial activity. Based on the preliminary results, the control experiments were performed at 35 °C for 2 h.
Incubating the neural progenitor cells for 2 h at 39 °C, with or without H2O2 (a proxy for reactive oxygen species of mitochondrial origin), was sufficient to trigger depletion of the intracellular Notch-1 from the nucleus (Fig. 8a). Endogenous controls, the membrane-tethered β-catenin and the nuclear MCM1 (minichromosome complex 1), remained unaffected by the increased temperature. We next studied the impact of temperature on two downstream mediators of Notch-1 signalling. While the expression of Hey1 is specifically controlled by Notch-1, Hes-1 is regulated by Notch-dependent and Notch-independent mechanisms [57]. Therefore, Hes-1 provides an internal control for the specificity of the impact of temperature on Notch-1 signalling output. Downregulation of Hey-1 at 39 °C (Fig. 8b) supported the IHC findings regarding temperature-dependent removal of intracellular Notch-1 from the nucleus (Fig. 8a). Hes-1, on the other hand, was upregulated at 39 °C. The upregulation of Hes-1 suggests that the impact of temperature is somewhat specific to Notch-1 signalling output. Adding other mitochondrial products, GTP and ROS, did not alter the effect of temperature on Notch-1 downstream reporters (Fig. 8b). We finally questioned whether temperature-dependent downregulation of Notch-1 signalling output would accelerate neuronal differentiation. In heme-treated cells, pro-neural transcription factors Ngn-1 and Mash-1 were not differentially expressed at 35 °C and 39 °C. This is expected as addition of heme leads to amplified production of heat by mitochondria and hence obliterates the exogenous heat gradient. Mitochondrial by-products GTP and ROS, however, required exogenous heat to upregulate the level of Ngn-1 and Mash-1 (Fig. 8c). This finding was consistent with the demonstrated role of Notch-1 in maintaining stemness and in opposing neuronal differentiation [2]. Further, RNAi-mediated depletion of Notch-1 transcript complemented the impact of increased temperature on intracellular Notch-1 and led to more pronounced upregulation of the pro-neural transcription factors. Taken together, findings indicate that the heat produced by mitochondria is an essential biophysical signal, rather than a by-product, that operates in combination with GTP and ROS to regulate the rate of neuronal differentiation by supressing Notch-1 signalling output. As predicted by molecular dynamics of the ankyrin domain of Notch-1, elevation of the nuclear temperature to 39 °C (equivalent to a perinuclear temperature of 50 °C) was sufficient to terminate the signalling output of Notch-1 signalling cascade.
Discussion
Herein, we combined an evolutionary approach with molecular biology to probe an unresolved facet of the Notch-1 signalling pathway, that is the mechanistic basis for termination of Notch-1 signalling during neuronal differentiation. We provide evidence that the ankyrin domain of Notch-1 has adopted specific structural features in order to function as a thermodynamic sensor that inputs heat flux as a proxy for mitochondrial activity in the Notchon state and is eventually switched off in a temperature-dependent manner. Evolutionary adaptations that gave rise to this thermodynamic switch were facilitated by two major adaptations in multicellular metazoans.
The three-way split of plants, animals and fungi [58] was concurrent with altered signalling network topology of cell cycle in multicellular organisms. Not only did the E2F family of transcription factors, Rb, and various cyclins [32] replace the yeast Swi6/Mbp1/CDC28 signalling axis [31], but also the cell-intrinsic autonomy of cell cycle was partially abandoned to install a collective cycling mode [59]. Apart from cell cycle, the nature of outside-in stress signals capable of reprogramming the cell changed markedly in metazoan animals. For example, components of the cell wall integrity pathway [59] became partially redundant in metazoans due to the absence of a cell wall. Altered signalling network topology of cell cycle was a key step in facilitating the repurposing of proteins with ankyrin domains that originally functioned as stress sensors. While major groups of stress signals and receptors became redundant, it is noteworthy that transition to multicellularity gave rise to a new set of stress sensors.
The average cellular metabolic rate is estimated as ≈0.5 pW for bacteria, and as ≈2200 pW for eukaryotes [60]. The rate of heat production is higher by an order of magnitude during development. For example, zebrafish embryos at the 2-cell stage exchange heat at an approximate rate of 30 nW/cell [61]. Given the specific heat capacity of water (4.184 J⋅g−1⋅K−1) and the typical eukaryotic cell mass (≈1 ng), a conservative heat output of 20 nW/cell is expected to induce a temperature spike of ≈4.8 K in a period of one second (i.e. 20 nJ.s−1/4.184 nJ⋅ng−1⋅K−1 × 1 ng). This estimated value is consistent with the experimentally measured temperature spike of ≈4.8 K/s that is observed upon near-complete conversion of mitochondrial output to heat [62]. The generated heat has to dissipate and biophysical parameters that constrain the dissipation of thermal energy put an upper limit to metabolic rate even in unicellular organisms [63]. In a closely associated population of cells dissipation of heat by convection becomes more difficult and there is some evidence that the retained metabolic heat is used to raise the local temperature within a bacterial colony when the external temperature decreases [64]. However, quorum sensing in bacteria reduces the metabolic activity proportional to the density of a population [65–67]. It seems plausible that a mechanism akin to bacterial “quorum sensing” must exist in multicellular metazoans to precisely calibrate metabolism and heat production by monitoring the density of a cell population. What would the circuitry of a putative metazoan “quorum sensing” cascade accommodate to achieve this function?
A putative metazoan “quorum sensing” (mQS) pathway would ideally accommodate a linear stoichiometry to precisely convey information regarding the density of a population to the recipient cell. The pathway will be switched on (mQSon) via paracrine interactions with a non-diffusible ligand in order to minimise signalling noise. Further, removal of the non-diffusible (i.e. membrane-tethered) ligands after binding to the receptor that activates the mQS cascade enhances the sharpness of generated signals in the putative mQSon state. Finally, the mQS signals must regulate mitochondrial activity and the pathway must be calibrated by negative feedback provided via mitochondrial activity. Notch signalling cascade fulfills a majority of the requirements of a metazoan “quorum sensor” (Fig. 8d).
Notch signalling pathway accommodates a linear hierarchical network topology [4]. The pathway is activated upon association of Notch receptors on recipient cells with membrane tethered ligands on adjacent cells. Upon binding to Notch receptor, endocytosis of the ligand serves the dual purposes of generating the mechanical force to expose the ADAM10 cleavage site and removing the membrane-tethered ligand [10]. Subsequent to activation of the signalling cascade, Notch-1 amplifies mitochondrial activity by canonical [68] and non-canonical [69] upregulation of respiratory chain components. Specifically, expression of cytochrome-c oxidase, the key enzyme in the electron transport chain, is regulated by the Notch1 binding partner RBPJ [70]. By communication with mitochondria, Notch-1 aligns the cellular energetic demand to the anabolic flux, another function that is in part regulated by this signalling pathway [71]. Unlike amplification of mitochondrial activity by Notch signalling, the nature of a potential feedback mechanism that relays information regarding mitochondrial activity to the Notch/RBPJ transcriptional complex to complete the signalling loop, remains unknown. Earlier dissection of the Notch-1 signalling circuitry suggested that individual signalling modules are bistable, and an as-yet-unknown signalling factor is required to complete the signalling circuitry [6]. Here, we provided evidence that thermal energy is consistent with the proposed unknown signal. Subsequent to dismantling of the cell wall integrity pathway, Swi6 was repurposed to a thermodynamic sensor as an integral part of Notch receptors. Enrichment of acidic residues in strategic positions of Notch-1 ankyrin domain facilitates emergence of molecular fluctuations that lead to an emergent entropy of 0.8 (kcal⋅K−1.mol−1) relative to more stable ankyrin domains of other proteins. Both theoretical and experimental analysis support a model in which a nuclear temperature of 39 °C equivalent to a cytoplasmic temperature of 50 °C is sufficient to destabilize Notch-1 ankyrin domain and terminate the signalling output by dissociation of the transcriptional complex. Structural adaptation to sense stressors is not confined to the ankyrin domain of Notch-1. Modular organisation of ankyrin domain whereby individual modules are connected via flexible β-hairpins gives rise to a molecular nano-spring that converts thermal fluctuations into mechanical energy [33] in neuronal ion channels [34] leading to temperature-dependent channel opening [35]. NF-κB, a key ANK+ proinflammatory, senses and responds to thermal fluctuation in a similar manner but in a range close to that of Notch-1 ankyrin [39]. The sensory function of ankyrin domain is not limited to those discussed above. In capillaries, a reduction of oxygen partial pressure is directly sensed by the Band 3–ankyrin complex of RBCs leading to increased deformability of RBCs, increased velocity of blood flow, and re-establishment of the oxygen tension [37]. The sensory activities of ankyrin domain reflect subtle structural modification to utilise the modular organisation of the domain to receive and transmit kinetic energy to adjacent structures. The structural adaptation of Notch-1 ankyrin domain to function as a thermodynamic sensor completes a signalling loop whereby just as Notch-1 amplifies activity of the mitochondrial respiratory chain, resultant thermal energy provides negative feedback to terminate the activity of Notch1 transcriptional complex and to sustain the intracellular temperature within a narrow physiological window. We therefore propose that Notch signalling has evolved to function as a metazoan quorum sensor and the evolutionary adaptations of the ankyrin domain of Notch-1 are central to the activity of this QS pathway.
While the proposed QS mechanism safeguards against random fluctuation of temperature, it also provides a conduit for morphogens to alter mitochondrial activity and Notch signalling output during differentiation. During brain development, cannibalisation of erythroblasts leads to synchronised mitochondrial activation that triggers abrupt inactivation of Notch signalling cascade and accelerated adoption of neuronal fate [15]. This mechanism is compatible with the demonstrated role of mitochondria in neurogenesis [72–75]. Resolution of differentiation/self-renewal dichotomy in cycling neural progenitor cells requires input from mitochondria and a reduction of mitochondrial activity by fusion is a major determinant of sustained self-renewal capacity [76].
Conclusion and future directions
Findings show that the ankyrin domain of Notch-1 intracellular domain functions as a thermodynamic sensor that inputs heat flux as a proxy for mitochondrial activity in the Notchon state that is eventually switched off in a temperature-dependent manner. The disclosed mode of communication between mitochondria and the Notch signalling pathway foreshadows the importance of these organelles in regulating the metazoan developmental landscape. While our findings provide evidence for regulation of the canonical Notch signalling pathway via heat flux, it remains unclear whether the ankyrin domain plays a similar role in non-canonical Notch signalling pathways [77]. In non-canonical regulation of β-catenin by Notch-1, the RAM domain plays the key role in stabilising the association of the β-catenin/Notch1 [78]. Could mitochondrial heat flux calibrate the stability of β-catenin/Notch1 assembly? Further experiments are required to answer this question, amongst others, regarding the interface of mitochondrial activity and non-canonical Notch signalling mechanisms.
Methods
Reagents
All chemicals were purchased from Sigma-Aldrich Inc. unless stated otherwise. All primers were purchased from IDT DNA.
Chicken embryos
Fertilised Rhode Island Red eggs were obtained from a local hatchery (Barter & Sons Hatchery). The eggs were transferred to a shell-less culture system after three days and incubated at a temperature of 37 °C and relative humidity of 70%. Experiments were performed on cultivated embryos at defined Hamburger Hamilton stages [79] as per results section. The protocols for this study were approved by the ethics committee of the University of Sydney. All experiments were performed in accordance with guidelines and regulations of University of Sydney and Sydney West Local Health Service.
Cells
The established mouse multipotent neural stem cells (NSCs: C17.2) were purchased from CellBank Australia (Children’s Medical Research Institute, Australia). Growth medium for NSCs consisted of DMEM/F12 supplemented with 10% fetal Bovine serum and Antibiotic–Antimycotic (100X, Life Technologies). To induce neural differentiation, NSCs were cultured in Knockout™ DMEM (Gibco), GlutaMAX™ supplement, N2 supplement (Gibco), and brain-derived neurotrophic factor (BDNF, 10 ng/ml, Sigma).
Immunohistochemistry
Specimens were fixed in 2% paraformaldehyde/5% sucrose in 0.02 M phosphate buffer pH: 7.4 (680 mOsm), for 4 h at 4 °C. After blocking in incubation buffer containing 0.1 M PBS, 1% BSA, 0.1% Tween-20, and 5% normal goat serum (for detection with rabbit Abs) or 5% normal rabbit serum (for detection with mouse Abs) for 40 min, sections were incubated with the primary antibodies overnight at 4 ˚C and secondary antibodies for 1 h at room temperature. Specificity controls were carried out by incubating sections with rabbit or mouse IgG negative control antibodies.
Transmission electron microscopy
For TEM analysis, tissues were fixed in Karnovsky's fixative overnight at room temperature followed by post-fixation in OsO4 for 1 h. Preparations were dehydrated in graded alcohols and embedded in low viscosity resin (TAAB Laboratory and Microscopy, United Kingdom). Ultrathin sections were mounted on Pioloform/formvar coated slot grids, stained in uranyl acetate and lead citrate and examined in a Phillips CM120 BioTWIN electron microscope.
Gene expression analysis
RNA was isolated using RNeasy Mini Kit (Qiagen). After DNase treatment, reverse transcription of the extracted RNA was carried out using a mixture of 1 μL of oligo-dT, 4 μL of total RNA, 1 μL of dNTP Mix (10 mM each), 4 μL of 5 × First-Strand synthesis Buffer, 1 μL of 0.1 M DTT, 1 μL of RNaseOUT (40 units/μL), 1 μL of SuperScript-III reverse transcriptase (200 units). Reverse transcription was performed at 50˚C for 50 min followed by 55˚C for 15 min. RNA was subsequently digested with RNAase H. To design primers, gene sequence data and exon/intron boundaries were obtained from GenBank database (see Table S1). In each of the primer sets, the common 3΄- or 5΄-primer spanned the adjacent exons to prevent amplification of genomic DNA.
Real-time PCR
Real-time PCR (38 cycles) was performed using SensiFAST™ SYBR® Lo-ROX reagents (BIOLINE®). Reaction mix comprised of 2 μl of cDNA, 400 nM inner primers (1.5 μl/primer), 10 μl of 2 × SensiFAST SYBR Lo-ROX Mix, and 5 μl of PCR-grade water on a Stratagene® Mx3000P real-time PCR instrument. Average efficiency of PCR amplification for each gene of interest was quantified based on a linear regression model using the LineRegPCR software [80]. The relative expression ratio of gene of interest (test:control) was then calculated using the efficiency (Eff.) values based on the method proposed by Pffafi as follows:
RNA interference
For small interfering RNA (siRNA)-mediated knockdown of mm-notch-1, cells were electroporated with 200 nM of either the targeting or control siRNA. The sequence of siRNA targeting mm-notch-1 is as follows:
sense: 5'-rUrGrCrUrGrCrArCrArCrCrArArCrGrUrGrGrUrCrUrUrCAA-3'.
antisense: 5'-rUrUrGrArArGrArCrCrArCrGrUrUrGrGrUrGrUrGrCrArGrCrArCrG-3'.
For electroporation in RNAi, cells were harvested, mixed with Dsi-RNA (i.e. siRNA) and resuspended in 400 μL of electroporation buffer (106 cells/400 μL). Electroporation buffer comprised 20 mM HEPES, 135 mM KCl, 2 mM MgCl2, 0.5% Ficoll 400, and 2 mM ATP/5 mM glutathione (pH 7.6). Electroporation was carried out at 1700 V/cm, 700 μs, four pulses at 1-s intervals.
Molecular beacons
The L-DNA molecular beacons (MB-4 and MB-5) was designed as described elsewhere [52]. Molecular beacons were labelled with a 6-FAM reporter dye at the 5′ end, and an Iowa Black FQ quencher at the 3′ end (Integrated DNA Technologies).
The sequence of MB-4 is as follows:
FAM-CGAGTTTTTTTTTTTTTTTCTCG-IBFQ
The sequence of MB-5 is as follows:
FAM-GCGAGTTTTTTTTTTTTTTTCTCGC-IBFQ
Ex ovo electroporation of embryos
ECM 830 electroporator (Harvard Apparatus®) was used to generate square-wave electric pulses. A solution (20 mM HEPES, 135 mM KCl, 2 mM MgCl2, 0.5% Ficoll 400, 2 mM ATP/5 mM glutathione) containing the molecular beacons (200 nM) was injected into the canal of the neural tube under illumination using a surgical microscope (Leica M320). Platinum Tweezertrodes (5 mm, Harvard Apparatus®) were carefully positioned bilaterally around the embryo’s head and 4 mm apart. Parameters for ex ovo electroporation of chicken embryos were adapted from Sauka–Spengler et al. [81]. Electroporation was carried out at 62.5 V/cm, 50 ms, 5 pulses at 1-s intervals. The electroporated embryos were then incubated for 24 h at 37 °C before harvesting for histological processing.
Adaptive Poisson-Boltzmann solver
The APBS Electrostatics Plugin was accessed from PyMOL (v.2.5). Visualisation of surface potential was also done using PyMOL. All calculations were performed at 0.15 M ionic strength in monovalent salt, 298.15° K, protein dielectric 2, and solvent dielectric 78.
Molecular dynamics
The open-source GROMACS tools provided through the Galaxy platform was used to simulate the temperature-dependent dynamics of Notch-1 ankyrin domain (PDB ID: 2F8Y). Simulations were performed using the water model of SPC/E [82] and OPLS/AA force-field [83]. Equilibrating simulations under an NVT (isothermal-isochoric) ensemble, followed by an NPT (isothermal-isobaric) ensemble were performed at 298 K until the root mean-square deviation (RMSD) was stable. The root mean-square fluctuation (RMSF) values were calculated with Gromacs 4.5 through the Galaxy platform. Mutation of ASP-1989 to ASN-1989 in silico (ID: 2F8Y) was performed using PyMOL.
Quantification and statistical analysis
SPSS statistical software (SPSS v.16, Chicago, Illinois, US) was used for the statistical analysis of data. The relative expression levels of genes of interest were compared using univariate ANOVA and non-parametric Mann–Whitney U test. The results of statistical analysis can be found in figure legends. Plots were generated using Prism software. Data are presented as Mean ± SD. In the present study, a p-value < 0.01 (*) was considered as statistically significant.
Supplementary Information
Acknowledgements
Not applicable.
Abbreviations
- NICD
Notch intracellular domain
- ANK
Ankyrin
- DSL
Delta-Serrate-Lag
- RBP-J
Recombination signal binding protein-J
- MAML
Mastermind like transcriptional coactivator
- APBS
Adaptive Poisson-Boltzmann solver
Author contributions
FV performed experiments and contributed to analysis and interpretation of data. NH contributed to interpretation of the data and writing the manuscript. RMF conceived and designed the study, analyzed and interpreted data, and wrote the manuscript. All authors read and approved the final manuscript.
Funding
This work was supported by internal funding.
Availability of data materials
The published article includes all datasets generated or analyzed during this study.
Declarations
Ethical approval and consent to participate
This study was carried out in strict accordance with applicable standards. The protocols for this study were approved by the ethics committee of Sydney West Local Health Service. All experiments were performed in accordance with guidelines and regulations of Sydney West Local Health Service. Diet and water were provided ad libitum, and standard light cycles were used. All efforts were made to minimize animal suffering.
Consent for publication
All authors read and approved the final manuscript.
Competing interests
The authors declare that they have no conflict of interest.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Filip Vujovic, Email: filip.vujovic@sydney.edu.au.
Neil Hunter, Email: neil.hunter@health.nsw.gov.au.
Ramin M. Farahani, Email: ramin.mostofizadehfarahani@sydney.edu.au
References
- 1.Gazave E, Lapebie P, Richards GS, Brunet F, Ereskovsky AV, Degnan BM, et al. Origin and evolution of the Notch signalling pathway: an overview from eukaryotic genomes. BMC Evol Biol. 2009;9:249. doi: 10.1186/1471-2148-9-249. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Liu J, Sato C, Cerletti M, Wagers A. Notch signaling in the regulation of stem cell self-renewal and differentiation. Curr Top Dev Biol. 2010;92:367–409. doi: 10.1016/S0070-2153(10)92012-7. [DOI] [PubMed] [Google Scholar]
- 3.Morrison SJ, Perez SE, Qiao Z, Verdi JM, Hicks C, Weinmaster G, et al. Transient Notch activation initiates an irreversible switch from neurogenesis to gliogenesis by neural crest stem cells. Cell. 2000;101(5):499–510. doi: 10.1016/S0092-8674(00)80860-0. [DOI] [PubMed] [Google Scholar]
- 4.Bray SJ. Notch signalling in context. Nat Rev Mol Cell Biol. 2016;17(11):722–735. doi: 10.1038/nrm.2016.94. [DOI] [PubMed] [Google Scholar]
- 5.Nandagopal N, Santat LA, Elowitz MB. Cis-activation in the Notch signaling pathway. Elife. 2019;8. [DOI] [PMC free article] [PubMed]
- 6.Vujovic F, Hunter N, Farahani RM. Notch pathway: a bistable inducer of biological noise? Cell Commun Signal. 2019;17(1):133. doi: 10.1186/s12964-019-0453-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.McGill MA, Dho SE, Weinmaster G, McGlade CJ. Numb regulates post-endocytic trafficking and degradation of Notch1. J Biol Chem. 2009;284(39):26427–26438. doi: 10.1074/jbc.M109.014845. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Wu X, Fleming A, Ricketts T, Pavel M, Virgin H, Menzies FM, et al. Autophagy regulates Notch degradation and modulates stem cell development and neurogenesis. Nat Commun. 2016;7:10533. doi: 10.1038/ncomms10533. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Lai EC. Protein degradation: four E3s for the notch pathway. Curr Biol. 2002;12(2):R74–R78. doi: 10.1016/S0960-9822(01)00679-0. [DOI] [PubMed] [Google Scholar]
- 10.Musse AA, Meloty-Kapella L, Weinmaster G. Notch ligand endocytosis: mechanistic basis of signaling activity. Semin Cell Dev Biol. 2012;23(4):429–436. doi: 10.1016/j.semcdb.2012.01.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Qiu L, Joazeiro C, Fang N, Wang HY, Elly C, Altman Y, et al. Recognition and ubiquitination of Notch by Itch, a hect-type E3 ubiquitin ligase. J Biol Chem. 2000;275(46):35734–35737. doi: 10.1074/jbc.M007300200. [DOI] [PubMed] [Google Scholar]
- 12.Vujovic F, Rezaei-Lotfi S, Hunter N, Farahani RM. The fate of notch-1 transcript is linked to cell cycle dynamics by activity of a natural antisense transcript. Nucleic Acids Res. 2021;49(18):10419–10430. doi: 10.1093/nar/gkab800. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Farahani R, Rezaei-Lotfi S, Simonian M, Hunter N. Bi-modal reprogramming of cell cycle by MiRNA-4673 amplifies human neurogenic capacity. Cell Cycle. 2019;18(8):848–868. doi: 10.1080/15384101.2019.1595873. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Farahani RM, Rezaei-Lotfi S, Hunter N. Genomic competition for noise reduction shaped evolutionary landscape of mir-4673. NPJ Syst Biol Appl. 2020;6(1):12. doi: 10.1038/s41540-020-0131-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Ozsoy S, Vujovic F, Simonian M, Valova V, Hunter N, Farahani RM. Cannibalized erythroblasts accelerate developmental neurogenesis by regulating mitochondrial dynamics. Cell Rep. 2021;35(1):108942. doi: 10.1016/j.celrep.2021.108942. [DOI] [PubMed] [Google Scholar]
- 16.Andersson ER, Sandberg R, Lendahl U. Notch signaling: simplicity in design, versatility in function. Development. 2011;138(17):3593–3612. doi: 10.1242/dev.063610. [DOI] [PubMed] [Google Scholar]
- 17.Wilson JJ, Kovall RA. Crystal structure of the CSL-Notch-Mastermind ternary complex bound to DNA. Cell. 2006;124(5):985–996. doi: 10.1016/j.cell.2006.01.035. [DOI] [PubMed] [Google Scholar]
- 18.Nam Y, Weng AP, Aster JC, Blacklow SC. Structural requirements for assembly of the CSL intracellular Notch1. Mastermind-like 1 transcriptional activation complex. J Biol Chem. 2003;278(23):21232–9. doi: 10.1074/jbc.M301567200. [DOI] [PubMed] [Google Scholar]
- 19.Covino R, Ballweg S, Stordeur C, Michaelis JB, Puth K, Wernig F, et al. A Eukaryotic Sensor for Membrane Lipid Saturation. Mol Cell. 2016;63(1):49–59. doi: 10.1016/j.molcel.2016.05.015. [DOI] [PubMed] [Google Scholar]
- 20.Zhang S, Skalsky Y, Garfinkel DJ. MGA2 or SPT23 is required for transcription of the delta9 fatty acid desaturase gene, OLE1, and nuclear membrane integrity in Saccharomyces cerevisiae. Genetics. 1999;151(2):473–483. doi: 10.1093/genetics/151.2.473. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Fang Z, Chen Z, Wang S, Shi P, Shen Y, Zhang Y, et al. Overexpression of OLE1 Enhances Cytoplasmic Membrane Stability and Confers Resistance to Cadmium in Saccharomyces cerevisiae. Appl Environ Microbiol. 2017;83(1). [DOI] [PMC free article] [PubMed]
- 22.Horak CE, Luscombe NM, Qian J, Bertone P, Piccirrillo S, Gerstein M, et al. Complex transcriptional circuitry at the G1/S transition in Saccharomyces cerevisiae. Genes Dev. 2002;16(23):3017–3033. doi: 10.1101/gad.1039602. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Kim KY, Truman AW, Caesar S, Schlenstedt G, Levin DE. Yeast Mpk1 cell wall integrity mitogen-activated protein kinase regulates nucleocytoplasmic shuttling of the Swi6 transcriptional regulator. Mol Biol Cell. 2010;21(9):1609–1619. doi: 10.1091/mbc.e09-11-0923. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Madden K, Sheu YJ, Baetz K, Andrews B, Snyder M. SBF cell cycle regulator as a target of the yeast PKC-MAP kinase pathway. Science. 1997;275(5307):1781–1784. doi: 10.1126/science.275.5307.1781. [DOI] [PubMed] [Google Scholar]
- 25.Nasmyth K, Dirick L. The role of SWI4 and SWI6 in the activity of G1 cyclins in yeast. Cell. 1991;66(5):995–1013. doi: 10.1016/0092-8674(91)90444-4. [DOI] [PubMed] [Google Scholar]
- 26.Kohorn BD. Cell wall-associated kinases and pectin perception. J Exp Bot. 2016;67(2):489–494. doi: 10.1093/jxb/erv467. [DOI] [PubMed] [Google Scholar]
- 27.He ZH, He D, Kohorn BD. Requirement for the induced expression of a cell wall associated receptor kinase for survival during the pathogen response. Plant J. 1998;14(1):55–63. doi: 10.1046/j.1365-313X.1998.00092.x. [DOI] [PubMed] [Google Scholar]
- 28.Yang YA, Zhang YX, Ding PT, Johnson K, Li X, Zhang YL. The ankyrin-repeat transmembrane protein BDA1 functions downstream of the receptor-like protein SNC2 to regulate plant immunity. Plant Physiol. 2012;159(4):1857–1865. doi: 10.1104/pp.112.197152. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Mittag T, Strader LC. I will survive: how NPR1 condensation promotes plant cell survival. Cell. 2020;182(5):1072–1074. doi: 10.1016/j.cell.2020.08.011. [DOI] [PubMed] [Google Scholar]
- 30.Spoel SH, Dong XN. How do plants achieve immunity? Defence without specialized immune cells. Nat Rev Immunol. 2012;12(2):89–100. doi: 10.1038/nri3141. [DOI] [PubMed] [Google Scholar]
- 31.Mendenhall MD, Hodge AE. Regulation of Cdc28 cyclin-dependent protein kinase activity during the cell cycle of the yeast Saccharomyces cerevisiae. Microbiol Mol Biol Rev. 1998;62(4):1191–1243. doi: 10.1128/MMBR.62.4.1191-1243.1998. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Dimova DK, Dyson NJ. The E2F transcriptional network: old acquaintances with new faces. Oncogene. 2005;24(17):2810–2826. doi: 10.1038/sj.onc.1208612. [DOI] [PubMed] [Google Scholar]
- 33.Sotomayor M, Corey DP, Schulten K. In search of the hair-cell gating spring elastic properties of ankyrin and cadherin repeats. Structure. 2005;13(4):669–682. doi: 10.1016/j.str.2005.03.001. [DOI] [PubMed] [Google Scholar]
- 34.Lee G, Abdi K, Jiang Y, Michaely P, Bennett V, Marszalek PE. Nanospring behaviour of ankyrin repeats. Nature. 2006;440(7081):246–249. doi: 10.1038/nature04437. [DOI] [PubMed] [Google Scholar]
- 35.Low C, Weininger U, Neumann P, Klepsch M, Lilie H, Stubbs MT, et al. Structural insights into an equilibrium folding intermediate of an archaeal ankyrin repeat protein. Proc Natl Acad Sci U S A. 2008;105(10):3779–3784. doi: 10.1073/pnas.0710657105. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Monahan-Earley R, Dvorak AM, Aird WC. Evolutionary origins of the blood vascular system and endothelium. J Thromb Haemost. 2013;11(Suppl 1):46–66. doi: 10.1111/jth.12253. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Zhou S, Giannetto M, DeCourcey J, Kang H, Kang N, Li Y, et al. Oxygen tension-mediated erythrocyte membrane interactions regulate cerebral capillary hyperemia. Sci Adv. 2019;5(5):eaaw4466. [DOI] [PMC free article] [PubMed]
- 38.Li N, Karin M. Is NF-kappaB the sensor of oxidative stress? FASEB J. 1999;13(10):1137–1143. doi: 10.1096/fasebj.13.10.1137. [DOI] [PubMed] [Google Scholar]
- 39.Harper CV, Woodcock DJ, Lam C, Garcia-Albornoz M, Adamson A, Ashall L, et al. Temperature regulates NF-kappaB dynamics and function through timing of A20 transcription. Proc Natl Acad Sci U S A. 2018;115(22):E5243–E5249. doi: 10.1073/pnas.1803609115. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Huang D, Friesen H, Andrews B. Pho85, a multifunctional cyclin-dependent protein kinase in budding yeast. Mol Microbiol. 2007;66(2):303–314. doi: 10.1111/j.1365-2958.2007.05914.x. [DOI] [PubMed] [Google Scholar]
- 41.Marqusee S, Robbins VH, Baldwin RL. Unusually stable helix formation in short alanine-based peptides. Proc Natl Acad Sci U S A. 1989;86(14):5286–5290. doi: 10.1073/pnas.86.14.5286. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Pace CN, Scholtz JM. A helix propensity scale based on experimental studies of peptides and proteins. Biophys J. 1998;75(1):422–427. doi: 10.1016/S0006-3495(98)77529-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Vila JA, Ripoll DR, Scheraga HA. Physical reasons for the unusual alpha-helix stabilization afforded by charged or neutral polar residues in alanine-rich peptides. Proc Natl Acad Sci U S A. 2000;97(24):13075–13079. doi: 10.1073/pnas.240455797. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Norouzy A, Assaf KI, Zhang S, Jacob MH, Nau WM. Coulomb repulsion in short polypeptides. J Phys Chem B. 2015;119(1):33–43. doi: 10.1021/jp508263a. [DOI] [PubMed] [Google Scholar]
- 45.Uversky VN. The alphabet of intrinsic disorder: II. Various roles of glutamic acid in ordered and intrinsically disordered proteins. Intrinsically Disord Proteins. 2013;1(1):e24684. [DOI] [PMC free article] [PubMed]
- 46.Dosztanyi Z. Prediction of protein disorder based on IUPred. Protein Sci. 2018;27(1):331–340. doi: 10.1002/pro.3334. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Thomas PD, Dill KA. An iterative method for extracting energy-like quantities from protein structures. Proc Natl Acad Sci U S A. 1996;93(21):11628–11633. doi: 10.1073/pnas.93.21.11628. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Lubman OY, Ilagan MX, Kopan R, Barrick D. Quantitative dissection of the Notch:CSL interaction: insights into the Notch-mediated transcriptional switch. J Mol Biol. 2007;365(3):577–589. doi: 10.1016/j.jmb.2006.09.071. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Stittrich AB, Lehman A, Bodian DL, Ashworth J, Zong Z, Li H, et al. Mutations in NOTCH1 cause Adams-Oliver syndrome. Am J Hum Genet. 2014;95(3):275–284. doi: 10.1016/j.ajhg.2014.07.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Botan V, Backus EH, Pfister R, Moretto A, Crisma M, Toniolo C, et al. Energy transport in peptide helices. Proc Natl Acad Sci U S A. 2007;104(31):12749–12754. doi: 10.1073/pnas.0701762104. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Davydov AS. Solitons in molecular-systems. Phys Scripta. 1979;20(3–4):387–394. doi: 10.1088/0031-8949/20/3-4/013. [DOI] [Google Scholar]
- 52.Ke G, Wang C, Ge Y, Zheng N, Zhu Z, Yang CJ. L-DNA molecular beacon: a safe, stable, and accurate intracellular nano-thermometer for temperature sensing in living cells. J Am Chem Soc. 2012;134(46):18908–18911. doi: 10.1021/ja3082439. [DOI] [PubMed] [Google Scholar]
- 53.Nord A, Metcalfe NB, Page JL, Huxtable A, McCafferty DJ, Dawson NJ. Avian red blood cell mitochondria produce more heat in winter than in autumn. FASEB J. 2021;35(5):e21490. doi: 10.1096/fj.202100107R. [DOI] [PubMed] [Google Scholar]
- 54.Chretien D, Benit P, Ha HH, Keipert S, El-Khoury R, Chang YT, et al. Mitochondria are physiologically maintained at close to 50 degrees C. PLoS Biol. 2018;16(1):e2003992. doi: 10.1371/journal.pbio.2003992. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Al-Mehdi AB, Pastukh VM, Swiger BM, Reed DJ, Patel MR, Bardwell GC, et al. Perinuclear mitochondrial clustering creates an oxidant-rich nuclear domain required for hypoxia-induced transcription. Sci Signal. 2012;5(231):ra47. [DOI] [PMC free article] [PubMed]
- 56.Bastos ARN, Brites CDS, Rojas-Gutierrez PA, DeWolf C, Ferreira RAS, Capobianco JA, et al. Thermal Properties of Lipid Bilayers Determined Using Upconversion Nanothermometry. Adv Funct Mater. 2019;29(48).
- 57.Katoh M, Katoh M. Integrative genomic analyses on HES/HEY family: Notch-independent HES1, HES3 transcription in undifferentiated ES cells, and Notch-dependent HES1, HES5, HEY1, HEY2, HEYL transcription in fetal tissues, adult tissues, or cancer. Int J Oncol. 2007;31(2):461–466. [PubMed] [Google Scholar]
- 58.Wang DY, Kumar S, Hedges SB. Divergence time estimates for the early history of animal phyla and the origin of plants, animals and fungi. Proc Biol Sci. 1999;266(1415):163–171. doi: 10.1098/rspb.1999.0617. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59.Levin DE. Cell wall integrity signaling in Saccharomyces cerevisiae. Microbiol Mol Biol Rev. 2005;69(2):262–291. doi: 10.1128/MMBR.69.2.262-291.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Lane N. Energetics and genetics across the prokaryote-eukaryote divide. Biol Direct. 2011;6:35. doi: 10.1186/1745-6150-6-35. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61.Rodenfels J, Neugebauer KM, Howard J. Heat Oscillations Driven by the Embryonic Cell Cycle Reveal the Energetic Costs of Signaling. Dev Cell. 2019;48(5):646–58 e6. [DOI] [PMC free article] [PubMed]
- 62.Rajagopal MC, Brown JW, Gelda D, Valavala KV, Wang H, Llano DA, et al. Transient heat release during induced mitochondrial proton uncoupling. Commun Biol. 2019;2. [DOI] [PMC free article] [PubMed]
- 63.Niebel B, Leupold S, Heinemann M. An upper limit on Gibbs energy dissipation governs cellular metabolism. Nat Metab. 2019;1(1):125–132. doi: 10.1038/s42255-018-0006-7. [DOI] [PubMed] [Google Scholar]
- 64.Tabata K, Hida F, Kiriyama T, Ishizaki N, Kamachi T, Okura I. Measurement of soil bacterial colony temperatures and isolation of a high heat-producing bacterium. BMC Microbiol. 2013;13:56. doi: 10.1186/1471-2180-13-56. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65.An JH, Goo E, Kim H, Seo YS, Hwang I. Bacterial quorum sensing and metabolic slowing in a cooperative population. Proc Natl Acad Sci U S A. 2014;111(41):14912–14917. doi: 10.1073/pnas.1412431111. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Dandekar AA, Chugani S, Greenberg EP. Bacterial quorum sensing and metabolic incentives to cooperate. Science. 2012;338(6104):264–266. doi: 10.1126/science.1227289. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67.Goo E, An JH, Kang Y, Hwang I. Control of bacterial metabolism by quorum sensing. Trends Microbiol. 2015;23(9):567–576. doi: 10.1016/j.tim.2015.05.007. [DOI] [PubMed] [Google Scholar]
- 68.Xu J, Chi F, Guo T, Punj V, Lee WN, French SW, et al. NOTCH reprograms mitochondrial metabolism for proinflammatory macrophage activation. J Clin Invest. 2015;125(4):1579–1590. doi: 10.1172/JCI76468. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69.Hossain F, Sorrentino C, Ucar DA, Peng Y, Matossian M, Wyczechowska D, et al. Notch Signaling Regulates Mitochondrial Metabolism and NF-kappaB Activity in Triple-Negative Breast Cancer Cells via IKKalpha-Dependent Non-canonical Pathways. Front Oncol. 2018;8:575. doi: 10.3389/fonc.2018.00575. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70.Aras S, Pak O, Sommer N, Finley R, Jr, Huttemann M, Weissmann N, et al. Oxygen-dependent expression of cytochrome c oxidase subunit 4–2 gene expression is mediated by transcription factors RBPJ, CXXC5 and CHCHD2. Nucleic Acids Res. 2013;41(4):2255–2266. doi: 10.1093/nar/gks1454. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 71.Palomero T, Lim WK, Odom DT, Sulis ML, Real PJ, Margolin A, et al. NOTCH1 directly regulates c-MYC and activates a feed-forward-loop transcriptional network promoting leukemic cell growth. Proc Natl Acad Sci U S A. 2006;103(48):18261–18266. doi: 10.1073/pnas.0606108103. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 72.Beckervordersandforth R, Ebert B, Schaffner I, Moss J, Fiebig C, Shin J, et al. Role of Mitochondrial Metabolism in the Control of Early Lineage Progression and Aging Phenotypes in Adult Hippocampal Neurogenesis. Neuron. 2017;93(6):1518. doi: 10.1016/j.neuron.2017.03.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 73.Khacho M, Clark A, Svoboda DS, Azzi J, MacLaurin JG, Meghaizel C, et al. Mitochondrial Dynamics Impacts Stem Cell Identity and Fate Decisions by Regulating a Nuclear Transcriptional Program. Cell Stem Cell. 2016;19(2):232–247. doi: 10.1016/j.stem.2016.04.015. [DOI] [PubMed] [Google Scholar]
- 74.Khacho M, Slack RS. Mitochondrial dynamics in the regulation of neurogenesis: From development to the adult brain. Dev Dyn. 2018;247(1):47–53. doi: 10.1002/dvdy.24538. [DOI] [PubMed] [Google Scholar]
- 75.Khacho M, Harris R, Slack RS. Mitochondria as central regulators of neural stem cell fate and cognitive function. Nat Rev Neurosci. 2019;20(1):34–48. doi: 10.1038/s41583-018-0091-3. [DOI] [PubMed] [Google Scholar]
- 76.Iwata R, Casimir P, Vanderhaeghen P. Mitochondrial dynamics in postmitotic cells regulate neurogenesis. Science. 2020;369(6505):858–862. doi: 10.1126/science.aba9760. [DOI] [PubMed] [Google Scholar]
- 77.Andersen P, Uosaki H, Shenje LT, Kwon C. Non-canonical Notch signaling: emerging role and mechanism. Trends Cell Biol. 2012;22(5):257–265. doi: 10.1016/j.tcb.2012.02.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 78.Kwon C, Cheng P, King IN, Andersen P, Shenje L, Nigam V, et al. Notch post-translationally regulates beta-catenin protein in stem and progenitor cells. Nat Cell Biol. 2011;13(10):1244–1251. doi: 10.1038/ncb2313. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 79.Hamburger V, Hamilton HL. A series of normal stages in the development of the chick embryo. J Morphol. 1951;88(1):49–92. doi: 10.1002/jmor.1050880104. [DOI] [PubMed] [Google Scholar]
- 80.Ruijter JM, Ramakers C, Hoogaars WM, Karlen Y, Bakker O, van den Hoff MJ, et al. Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data. Nucleic Acids Res. 2009;37(6):e45. doi: 10.1093/nar/gkp045. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81.Sauka-Spengler T, Barembaum M. Gain- and loss-of-function approaches in the chick embryo. Methods Cell Biol. 2008;87:237–256. doi: 10.1016/S0091-679X(08)00212-4. [DOI] [PubMed] [Google Scholar]
- 82.Mark P, Nilsson L. Structure and dynamics of the TIP3P, SPC, and SPC/E water models at 298 K. Journal of Physical Chemistry B. 2001;105(43):24a-a.
- 83.Smith MD, Rao JS, Segelken E, Cruz L. Force-Field Induced Bias in the Structure of Abeta21-30: A Comparison of OPLS, AMBER, CHARMM, and GROMOS Force Fields. J Chem Inf Model. 2015;55(12):2587–2595. doi: 10.1021/acs.jcim.5b00308. [DOI] [PubMed] [Google Scholar]
- 84.Riggi M, Niewola-Staszkowska K, Chiaruttini N, Colom A, Kusmider B, Mercier V, et al. Decrease in plasma membrane tension triggers PtdIns(4,5)P2 phase separation to inactivate TORC2. Nat Cell Biol. 2018;20(9):1043–1051. doi: 10.1038/s41556-018-0150-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 85.Loar JW, Seiser RM, Sundberg AE, Sagerson HJ, Ilias N, Zobel-Thropp P, et al. Genetic and biochemical interactions among Yar1, Ltv1 and RpS3 define novel links between environmental stress and ribosome biogenesis in Saccharomyces cerevisiae. Genetics. 2004;168(4):1877–1889. doi: 10.1534/genetics.104.032656. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 86.Mou Z, Fan WH, Dong XN. Inducers of plant systemic acquired resistance regulate NPR1 function through redox changes. Cell. 2003;113(7):935–944. doi: 10.1016/S0092-8674(03)00429-X. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The published article includes all datasets generated or analyzed during this study.