Maintenance of protein solubility is crucial for proteostasis. Dysfunction can lead to the aggregation of functional soluble proteins into pathologic self-templating complexes called amyloid. Amyloid aggregates underlie the cytotoxicity seen in Alzheimer’s disease, type II diabetes, amyotrophic lateral sclerosis, and many other pathologic conditions (Knowles et al., 2014). However, the coalescence of proteins into macromolecular complexes, which undergo liquid-liquid phase separation (LLPS) (Banani et al., 2016; Berry et al., 2018; Courchaine et al., 2016; Lee et al., 2013) or self-assemble into amyloid fibrils, is vital to a diverse set of cellular processes. These aggregated proteins contribute to activities such as hormone storage, formation of non-membrane bound organelles, and long-term memory (Courchaine et al., 2016; Boke et al., 2016; Heinrich and Lindquist, 2011; Maji et al., 2009; Majumdar et al., 2012). Many proteins naturally aggregate. For example, some proteins with RNA binding or low complexity domains exist in both soluble and aggregated states. Switching from one state to the another can be controlled by concentration, environment, or presence of a co-aggregate. In other instances, the switch is an energy dependent process (Phair and Misteli, 2000; Shorter and Lindquist, 2004).

Depletion of adenosine triphosphate (ATP) has been shown to influence the balance between soluble and aggregated states for proteins in yeast and metazoans, suggesting normal proteostasis is maintained by energy dependent chaperones and disaggregases (Lee et al., 2013; Brangwynne et al., 2011; Feric et al., 2016; Hyman et al., 2014; Kroschwald et al., 2015; Saad et al., 2017). These enzymes, such as yeast Hsp104 or the Hsp70 co-chaperone complex in metazoans, rely on ATP hydrolysis to maintain the dynamic nature of functionally aggregated proteins and reverse pathological aggregation (Kroschwald et al., 2015; Saad et al., 2017; Nillegoda et al., 2015; Shorter, 2011; Vacher et al., 2005).

ATP, best known as the energy currency of the cell, has recently been shown to act as a hydrotrope to destabilize aggregated proteins (Patel et al., 2017). Hydrotropes are co-solvents capable of bringing poorly soluble or insoluble compounds into solution (Eastoe et al., 2011). Hydrotropic solubilization is concentration dependent requiring that the minimum hydrotropic concentration of the hydrotrope be reached before they act as a co-solvent (Eastoe et al., 2011; Schreier et al., 2000). Above the minimum hydrotropic concentration, hydrotropes promote solubilization by decreasing the interfacial tension between solute and solvent. Some hydrotropes seem to assume micellular structures while others facilitate solubilization through the formation of more open, planar structures (Schreier et al., 2000). Meyer and Voigt, (Meyer and Voigt, 2017) in discussing the possible role of ATP as a hydrotrope, point out that ATP would not be expected to form micelles but does have the chemical features needed to serve as a hydrotrope. ATP is able to function as a hydrotrope because it is an amphiphile, a compound with hydrophilic and hydrophobic properties. For ATP, the adenosine ring contributes a hydrophobic moiety while the 5' triphosphate contributes the hydrophilic component.

Using recombinant protein in vitro, Patel and colleagues demonstrated that the hydrotropic activity of ATP was sufficient to solubilize LLPS droplets made from purified protein at concentrations approaching ATP's maximum physiologic level (4–8 mM). In contrast, lower yet still physiologic, concentrations of ATP (1–2 mM) had a limited effect on protein solubility. Patel et al. (Patel et al., 2017) postulated that high intracellular concentration of ATP contributes to maintenance of protein solubility and inhibits pathologic protein aggregation in an energy independent manner (Patel et al., 2017). How interactions with other proteins, post translational modification, or the presence of co-aggregates, like RNA or poly-ADP ribose, may influence an endogenous aggregate’s susceptibility to hydrotropic action was not investigated (Saad et al., 2017; Andersen et al., 2005; Boamah et al., 2012; Ellis et al., 2010; Kar et al., 2011; Tollervey and Kiss, 1997). Among the cellular structures that feature aggregated proteins are non-membrane bound organelles. For example, nucleoli are formed by the coalescence of proteins into functional aggregates, some of which demonstrate liquid-like behavior, yet contain an amyloid-like component (Brangwynne et al., 2011; Feric et al., 2016; Hayes and Weeks, 2016). These features make nucleoli an ideal tissue to test the ability of ATP to act as hydrotrope on aggregates of proteins in vivo.

Nucleoli are centers for rRNA synthesis, processing, modification, and ribosome-subunit assembly. They have 100s of proteins, and multiple classes of RNA, including rRNA precursors, mature rRNA species and many small nucleolar RNAs (snoRNAs). RNA metabolism plays a central role in nucleolar formation, maintenance, and retention of nucleolar components (Hayes and Weeks, 2016; Franke et al., 1981; Verheggen et al., 2000). De novo nucleolar formation is dependent upon the coalescence of RNA binding proteins, such as fibrillarin (Fbl), nucleolin, and nucleophosmin (Npm1), around pre-made 40S rRNAs (Verheggen et al., 2000). For at least two of these proteins, Fbl and Npm1, rRNA helps to mediate protein aggregation and LLPS in vitro (Feric et al., 2016). The nucleolus is composed of three subregions, whose separation and immiscibility is believed to be the result of differing surface tension values between subregions (Feric et al., 2016). The subregions are the granular component, which is the site of ribosome assembly, the dense fibrillar component where rRNA processing and modification occurs, and the fibrillar core, which is the site of rRNA transcription. Each subregion is readily identified by specific markers. Npm1 is found within the granular component, while Fbl marks the dense fibrillar component, and the fibrillar core can be identified by the presence of rDNA repeats or RNA polymerase I (Feric et al., 2016).

The contents of the vertebrate nucleus, including proteome and pool size of various compounds including ATP, has been reported (Wühr et al., 2015; Andersen et al., 2005; Gall et al., 2004; Kiseleva et al., 2004). Most cells have one or a few nucleoli. Xenopus oocyte nuclei contain hundreds of functional nucleoli, some of which are larger than entire eukaryotic cells (Gall et al., 2004). Their large size is amenable to visual assays, and there is specific information regarding proteins that participate or interact with aggregated nucleolar proteins (Brangwynne et al., 2011; Feric et al., 2016). Using Xenopus oocyte nuclei, we developed a novel system to investigate the capacity of ATP to act as a hydrotrope on endogenous aggregates. We assembled a roster of proteins that form or are tightly associated with aggregates in the nucleus and nucleolus. Next, we identified conditions where the nuclear environment can be manipulated to vary ATP concentration and alter the relationship between soluble and aggregated proteins. This allowed us to ask specific questions using naturally occurring aggregates in their endogenous, or near endogenous, environment. Under some conditions ATP and a non-hydrolysable analog, 5′-(β,γ-imido)triphosphate (AMP-PNP) behave similarly, supporting an energy independent role for ATP in solubilization of aggregated nucleolar proteins. However, this process requires a sensitization step, such as aggregate destabilization by RNA depletion or an energy dependent process that requires one or more soluble factors. These results support a two-step model of in vivo solubilization of poteins that coalesce to make aggregates. We propose that ATP initially acts as an energy source for a destabilizing step conferring susceptibility to solubilization, and is supported by the energy independent action of ATP as a biological hydrotrope.

Conditions that promote formation of protein aggregates have been the focus of innumerable studies, identifying contributions by amino acid sequence, protein concentration and modification and co-aggregates. Biological aggregates are in equilibrium with pools of non-aggregated protein, but are conditionally solubilized in response to environment, cell cycle, and other influences. Thus, the solubilization of protein aggregates is an essential process. Aggregate deconstruction has classically been attributed to energy dependent enzymatic reactions involving chaperones, such as Hsp70, and disaggregases like Hsp104. In in vitro studies using purified proteins, Patel and colleagues (Patel et al., 2017) reported that ATP can function as a hydrotrope to prevent or reverse protein aggregation. However, the ability of ATP to act as a hydrotrope in the context of endogenous protein aggregates was not investigated. Using isolated Xenopus oocyte nuclei, we dissected the ability of ATP to act as a hydrotrope to non-specifically solubilize endogenous protein aggregates or as an energy source to power enzymatic disaggregation.

The rapid loss of soluble proteins from nuclei isolated in aqueous buffer has been problematic for experiments requiring an intact nucleoplasm or full complement of nuclear factors (Wühr et al., 2015; Carroll and Lehman, 1991; Gardner et al., 2012). We took advantage of this phenomenon to identify proteins which are stably associated with endogenous nuclear aggregates. Mass spectrometric analysis of retained complexes revealed ~120 proteins, accounting for ~10% of the total nuclear protein mass. Within this selective proteome are proteins that are part of non-membrane bound nuclear structures, RNA binding proteins, and proteins that are capable of forming aggregates (Kato et al., 2012). While our study focuses on the dynamics of aggregated nucleolar proteins, the aggregate enriched nuclear proteome generated provides a starting point for an expanded analysis of other nuclear structures.

The nucleolus is a non-membrane bound sub-nuclear organelle with verified protein aggregates. The nucleolus has well characterized domains and signature proteins within each domain have been shown to form LLPS aggregates (Feric et al., 2016). Of these, the best characterized are Nucleophosmin (Npm1) and Fibrillarin (Fbl), both of which were identified within our proteomic analysis.

We used fluorescently labeled variants GFP-Npm1 and RFP-Fbl (Feric et al., 2016), to investigate the role ATP plays during endogenous aggregate solubilization. We took advantage of being able to isolate nuclei in three distinct states. (1) Isolation of nuclei in OR2 buffer followed by one hour incubation in OR2 creates nuclei that have lost 90% of total nuclear proteins but retain aggregated proteins. We refer to these nuclei as soluble protein depleted. These nuclei will rapidly equilibrate small molecules, like ATP, to match the small molecule concentration of the assay buffer. (2) Isolation in OR2, and immediate placement in ISB supplemented with the desired concentration of nucleotide and immediately assayed. These nuclei will have at least a partial complement of soluble nuclear proteins in addition to aggregated complexes as long as they are assayed quickly (typically within 15 min of isolation). The more rapid exchange of small molecules like ATP allow manipulation of their concentration by addition to ISB. We refer to these as in situ nuclei. (3) Nuclei can be isolated under oil. Oil isolated nuclei retain endogenous levels of soluble proteins, aggregated proteins and small molecules. We refer to these nuclei as oil isolated or ex vivo.

Npm1 and Fbl nucleolar aggregates assayed in nuclei that were depleted of soluble nuclear proteins remain stable when treated with 8 mM ATP or AMP-PNP. Although 8 mM is slightly higher than the reported in vivo concentration of frog oocyte ATP (6.2 ± 0.7 mM) (Miller and Horowitz, 1986), 8 mM ATP, GTP or AMP-PNP was effective when used by Patel et al. (Patel et al., 2017) for hydrotropic solubilization of purified protein aggregates in vitro. The failure to respond to hydrotropic conditions lead to testing for conditions that would lead to changes in the Npm1 and Fbl coalesced in nucleoli.

The nucleolar Npm1 and Fbl had not been rendered permanently aggregated. Fusion of soluble protein depleted nuclei with oil isolated nuclei showed that nucleoli from soluble protein depleted nuclei can act as both donor and acceptor of aggregation prone proteins such as Npm1 and Fbl. The exchange of proteins between nuceloli has been noted by others and is a reminder that participation in an aggregate is not necessarily a static state (Phair and Misteli, 2000). The fusion of two soluble protein depleted nuclei had low but decernible exchange of Npm1 and Fbl. Exchange activity was enhanced in the presence of soluble nuclear proteins and approximately half normal nuclear levels of ATP provided when oil isolated nuclei were fused with soluble protein depleted nuclei. We note that in these assays Npm1 seemed to be more active in exchange than Fbl. This is consistent with previous work emphasizing that aggregated protein complexes may exhibit different properties (Feric et al., 2016; Kato et al., 2012; Schwartz et al., 2013).

Banini and colleagues (Banani et al., 2016), proposed a model where client proteins aggregate around a more stable scaffold. In this context, Npm1 likely falls into the client category. The relative resistance of RFP-Fbl to solubilization suggests that it may contribute to nucleolar structure as a scaffold. Fbl is an RNA binding protein that demonstrates viscoelastic properties following phase separation in vitro, indicating Fbl may assume LLPS droplet and polymer structure. (Feric et al., 2016) Consistent with our previous work, this observation suggests that at least a subset of phase-separated Fbl may exist within an amyloid fiber conformation that could contribute to maintenance of a nucleolar scaffold.

The nuclear fusion experiment indicated that even half the levels of soluble nuclear proteins and small molecules allowed enhanced ability of proteins to join and leave their aggregated state. Using in situ conditions, by immediately assaying after isolation, we were able to show that 8 mM ATP or GTP, but not AMP-PNP leads to disruption of aggregates. We note that although GTP works in this assay, the cellular concentration of GTP is estimated to be between one quarter to one tenth that of ATP. It is also important to note that many enzymes, for example Hsp70 (Abravaya et al., 1992), are able to use GTP as a substitute for ATP, although, based on cellular concentration, the normal substrate for these enzymes would be ATP. Immediately treating isolated nuclei with 8 mM ATP revealed distinct domain specific responses. Aggregated Npm1 is largely dispersed, however, a thin veil of ATP resistant Npm1 was often observed surrounding RFP-Fbl foci.This observation is consistent with a strong interaction of coalesced Npm1 at the granular component: dense fibrillar component interface. Feric et al. examined the physical properties of purified Fbl and Npm1 in an aqueous environment (Feric et al., 2016) and found that the interfacial tension between phases drives Npm1 to engulf Fbl. A phenomenon we also note here.

Although the fluorescence intensity from aggregated RFP-Fbl foci was decreased, we noted expansion of RFP-Fbl aggregates that settled to the bottom of the depression slide used for imaging. The decrease in fluorescent signal was consistent with RFP-Fbl leaving the aggregated state, while the spreading of the remaining signal was reminiscent of the liquid droplet properties described by others (Brangwynne et al., 2011; Feric et al., 2016).

When Npm1 and Fbl aggregates were assayed using in situ conditions 2–8 mM ATP supplementation effectively changes aggregate appearrance. A similar assay using 1 mM ATP showed little effect, however, a mix of 1 mM ATP with 3 mM AMP-PNP mimics the effect on Npm1 aggregates seen with 4 mM ATP. We interpret this as evidence that the process depends upon both a hydrolyzable form of ATP needed by soluble nuclear proteins and a hydrotropic effect that can be provided by the non-hydrolyzable analog AMP-PNP.

RNA has previously been shown to induce aggregate formation or contribute to aggregate maintenance (Banani et al., 2016; Boke et al., 2016; Feric et al., 2016; Hayes and Weeks, 2016; Kato et al., 2012; Schwartz et al., 2013). We investigated the contribution of RNA to maintenance of aggregate stability of Npm1 and Fbl in nucleoli by treating isolated nuclei with RNase A. We found that RNA depletion sensitized nucleoli to solubilization by ATP and the non-hydrolysable analog AMP-PNP thus removing the requirement for ATP hydrolysis. We suggest that RNase A treatment may mimic or substitute for the destabilization step provided by ATP hydrolysis. These findings implicate ATP dependent remodeling enzymes, such as chaperones, disaggregases, and RNA helicases, as possible mediators of aggregated protein turnover. Furthermore, our results suggest that differences between our observations and those made Patel et al. in vitro may be in part due to differences in the RNA content of the examined LLPS aggregates (Patel et al., 2017).

We propose a 2-step model for the in vivo solubilization of nucleolar aggregates that takes into account our experimental observations and suggest that this model may be relevant for many functional aggregates (Figure 9).

Figure 9

Download asset Open asset

In the proposed model, an initial sensitization requires concentrations of ATP 1 mM or less and is mediated by a soluble factor (Figures 2–6) or detabilzation of a co-aggregate like RNA. We suggest a second step, aggregate solubilization, can be mediated by the energy independent hydrotropic activity of ATP (Figures 7–8), but requires a relatively high (2 mM or more) concentration. Assembly of nuclear aggregates could be a simple reversal of this model, where a stabilizing interaction, such as RNA binding or protein modification exceeds the capacity of ATP to maintain protein solubility in the absence of hydrolysis. Stabilization promotes the coalescence of proteins and other components inducing liquid-like phase separation. Once phase separated, particles can mature into a more stable form through limited formation of amyloid fibers, whose maintenance is dependent on continuous interaction with a stabilizing factor.

Invoking the ability of ATP to behave as a hydrotrope raises the interesting possibility that the equilibrium between the aggregated and free pool of aggregate forming proteins is affected by protein sequence, co-aggregates, or post-translational modification; but also by cellular compartment and local concentration of ATP. There are differences in published values, both for intracellular ATP levels and total ATP levels (Patel et al., 2017; Miller and Horowitz, 1986; Traut, 1994; Harper et al., 1998; Imamura et al., 2009; Miyoshi et al., 2006; Wright et al., 2016; Ytting et al., 2012). In the conditions tested here the concentration of ATP in the nucleus may favor solubilization unless a stabilizer is present or proteins are altered to promote aggregation. Alternatively, the 4 or 5-fold lower concentration reported in the cytosol may require proteins, once aggregated, to undergo active regulation to take them apart.

The ability to measure and observe temporospatial variability of ATP concentrations is becoming more feasible. New tools have been developed to document changes in ATP concentration in response to metabolic conditions within single cells, and regional changes to intracellular ATP concentrations in response to cellular morphology (Imamura et al., 2009; Ytting et al., 2012; Yaginuma et al., 2014; Suzuki et al., 2015). These changes ranged from a 10% decrease to an over three-fold increase in local concentration and can be transient or long lived. Another factor that may influence the local concentration of ATP is the aggregation of proteins themselves. Patel et al. (Patel et al., 2017) note that FUS aggregates formed in a solution containing fluorescently labeled ATP were enriched in ATP by fourfold over the solution concentration. Thus, local cellular environment, age, metabolic changes in ATP turnover, or free intracellular ATP likely play an underappreciated role in the biology of protein aggregation.

Our observations add to the deliberation on the contribution ATP makes to the maintenance of protein solubility, functional protein aggregation and the regulation of non-membrane bound organelles. By showing that the hydrotropic properties of ATP can affect naturally occurring aggregates, we highlight the need to view endogenous levels of ATP within cellular compartments as more than a source of energy.

Our work also emphasizes the need to control for, or acknowledge, the influence of local concentrations when designing or interpreting experiments. This is readily apparent when looking at functional protein aggregation, where the average cellular contents or concentration of a molecule does not accurately reflect cellular conditions or the local protein environment. The local changes may also play an underappreciated role in the etiology of aggregate associated diseases, such as Alzheimer’s and Parkinson’s disease (Harper et al., 1998; Miyoshi et al., 2006).

Proteomic Data set access directions are in the Supplemental text: "Proteomic data sets generated for this study are deposited at MassIVE data ftp://massive.ucsd.edu/MSV000081690/."

1. 1. N Dovichei
   2. E Peuchen

   (2017) Collaboration between Iowa and Notre Dame. Proteomic data run at Notre Dame

   Publicly available at MassIVE data.

   ftp://massive.ucsd.edu/MSV000081690/

1. 1. Abravaya K
   2. Myers MP
   3. Murphy SP
   4. Morimoto RI

   (1992) The human heat shock protein hsp70 interacts with HSF, the transcription factor that regulates heat shock gene expression

   Genes & Development 6:1153–1164.

   https://doi.org/10.1101/gad.6.7.1153

   • PubMed
   • Google Scholar
2. 1. Andersen JS
   2. Lam YW
   3. Leung AK
   4. Ong SE
   5. Lyon CE
   6. Lamond AI
   7. Mann M

   (2005) Nucleolar proteome dynamics

   Nature 433:77–83.

   https://doi.org/10.1038/nature03207

   • PubMed
   • Google Scholar
3. 1. Banani SF
   2. Rice AM
   3. Peeples WB
   4. Lin Y
   5. Jain S
   6. Parker R
   7. Rosen MK

   (2016) Compositional control of Phase-Separated cellular bodies

   Cell 166:651–663.

   https://doi.org/10.1016/j.cell.2016.06.010

   • PubMed
   • Google Scholar
4. 1. Berry J
   2. Brangwynne CP
   3. Haataja M

   (2018) Physical principles of intracellular organization via active and passive phase transitions

   Reports on Progress in Physics 81:046601.

   https://doi.org/10.1088/1361-6633/aaa61e

   • PubMed
   • Google Scholar
5. 1. Boamah EK
   2. Kotova E
   3. Garabedian M
   4. Jarnik M
   5. Tulin AV

   (2012) Poly(ADP-Ribose) polymerase 1 (PARP-1) regulates ribosomal biogenesis in Drosophila nucleoli

   PLoS Genetics 8:e1002442.

   https://doi.org/10.1371/journal.pgen.1002442

   • PubMed
   • Google Scholar
6. 1. Boke E
   2. Ruer M
   3. Wühr M
   4. Coughlin M
   5. Lemaitre R
   6. Gygi SP
   7. Alberti S
   8. Drechsel D
   9. Hyman AA
   10. Mitchison TJ

   (2016) Amyloid-like Self-Assembly of a cellular compartment

   Cell 166:637–650.

   https://doi.org/10.1016/j.cell.2016.06.051

   • PubMed
   • Google Scholar
7. 1. Boyle EI
   2. Weng S
   3. Gollub J
   4. Jin H
   5. Botstein D
   6. Cherry JM
   7. Sherlock G

   (2004) GO::TermFinder--open source software for accessing gene ontology information and finding significantly enriched gene ontology terms associated with a list of genes

   Bioinformatics 20:3710–3715.

   https://doi.org/10.1093/bioinformatics/bth456

   • PubMed
   • Google Scholar
8. 1. Brangwynne CP
   2. Mitchison TJ
   3. Hyman AA

   (2011) Active liquid-like behavior of nucleoli determines their size and shape in Xenopus laevis oocytes

   PNAS 108:4334–4339.

   https://doi.org/10.1073/pnas.1017150108

   • PubMed
   • Google Scholar
9. 1. Carroll D
   2. Lehman CW

   (1991) DNA recombination and repair in oocytes, eggs, and extracts

   Methods in Cell Biology 36:467–486.

   https://doi.org/10.1016/S0091-679X(08)60292-7

   • PubMed
   • Google Scholar
10. 1. Chen D
    2. Huang S

    (2001) Nucleolar components involved in ribosome biogenesis cycle between the nucleolus and nucleoplasm in interphase cells

    The Journal of Cell Biology 153:169–176.

    https://doi.org/10.1083/jcb.153.1.169

    • PubMed
    • Google Scholar
11. 1. Courchaine EM
    2. Lu A
    3. Neugebauer KM

    (2016) Droplet organelles?

    The EMBO Journal 35:1603–1612.

    https://doi.org/10.15252/embj.201593517

    • PubMed
    • Google Scholar
12. 1. Cox J
    2. Hein MY
    3. Luber CA
    4. Paron I
    5. Nagaraj N
    6. Mann M

    (2014) Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ

    Molecular & Cellular Proteomics 13:2513–2526.

    https://doi.org/10.1074/mcp.M113.031591

    • PubMed
    • Google Scholar
13. 1. Cox J
    2. Mann M

    (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification

    Nature Biotechnology 26:1367–1372.

    https://doi.org/10.1038/nbt.1511

    • PubMed
    • Google Scholar
14. 1. Cox J
    2. Neuhauser N
    3. Michalski A
    4. Scheltema RA
    5. Olsen JV
    6. Mann M

    (2011) Andromeda: a peptide search engine integrated into the MaxQuant environment

    Journal of Proteome Research 10:1794–1805.

    https://doi.org/10.1021/pr101065j

    • PubMed
    • Google Scholar
15. 1. Eastoe J
    2. Hatzopoulos MH
    3. Dowding PJ

    (2011) Action of hydrotropes and alkyl-hydrotropes

    Soft Matter 7:5917.

    https://doi.org/10.1039/c1sm05138e

    • Google Scholar
16. 1. Ellis JC
    2. Brown DD
    3. Brown JW

    (2010) The small nucleolar ribonucleoprotein (snoRNP) database

    RNA 16:664–666.

    https://doi.org/10.1261/rna.1871310

    • PubMed
    • Google Scholar
17. 1. Feric M
    2. Vaidya N
    3. Harmon TS
    4. Mitrea DM
    5. Zhu L
    6. Richardson TM
    7. Kriwacki RW
    8. Pappu RV
    9. Brangwynne CP

    (2016) Coexisting liquid phases underlie nucleolar subcompartments

    Cell 165:1686–1697.

    https://doi.org/10.1016/j.cell.2016.04.047

    • PubMed
    • Google Scholar
18. 1. Franke WW
    2. Kleinschmidt JA
    3. Spring H
    4. Krohne G
    5. Grund C
    6. Trendelenburg MF
    7. Stoehr M
    8. Scheer U

    (1981) A nucleolar skeleton of protein filaments demonstrated in amplified nucleoli of Xenopus laevis

    The Journal of Cell Biology 90:289–299.

    https://doi.org/10.1083/jcb.90.2.289

    • PubMed
    • Google Scholar
19. 1. Gall JG
    2. Wu Z
    3. Murphy C
    4. Gao H

    (2004) Structure in the amphibian germinal vesicle

    Experimental Cell Research 296:28–34.

    https://doi.org/10.1016/j.yexcr.2004.03.017

    • PubMed
    • Google Scholar
20. 1. Gardner EJ
    2. Nizami ZF
    3. Talbot CC
    4. Gall JG

    (2012) Stable intronic sequence RNA (sisRNA), a new class of noncoding RNA from the oocyte nucleus of Xenopus tropicalis

    Genes & Development 26:2550–2559.

    https://doi.org/10.1101/gad.202184.112

    • PubMed
    • Google Scholar
21. 1. Handwerger KE
    2. Cordero JA
    3. Gall JG

    (2005) Cajal bodies, nucleoli, and speckles in the Xenopus oocyte nucleus have a low-density, sponge-like structure

    Molecular Biology of the Cell 16:202–211.

    https://doi.org/10.1091/mbc.e04-08-0742

    • PubMed
    • Google Scholar
22. 1. Harper ME
    2. Monemdjou S
    3. Ramsey JJ
    4. Weindruch R

    (1998) Age-related increase in mitochondrial proton leak and decrease in ATP turnover reactions in mouse hepatocytes

    American Journal of Physiology-Endocrinology and Metabolism 275:E197–E206.

    https://doi.org/10.1152/ajpendo.1998.275.2.E197

    • PubMed
    • Google Scholar
23. 1. Hayes MH
    2. Weeks DL

    (2016) Amyloids assemble as part of recognizable structures during oogenesis in Xenopus

    Biology Open 5:801–806.

    https://doi.org/10.1242/bio.017384

    • PubMed
    • Google Scholar
24. 1. Heinrich SU
    2. Lindquist S

    (2011) Protein-only mechanism induces self-perpetuating changes in the activity of neuronal Aplysia cytoplasmic polyadenylation element binding protein (CPEB)

    PNAS 108:2999–3004.

    https://doi.org/10.1073/pnas.1019368108

    • PubMed
    • Google Scholar
25. 1. Hyman AA
    2. Weber CA
    3. Jülicher F

    (2014) Liquid-liquid phase separation in biology

    Annual Review of Cell and Developmental Biology 30:39–58.

    https://doi.org/10.1146/annurev-cellbio-100913-013325

    • PubMed
    • Google Scholar
26. 1. Imamura H
    2. Nhat KP
    3. Togawa H
    4. Saito K
    5. Iino R
    6. Kato-Yamada Y
    7. Nagai T
    8. Noji H

    (2009) Visualization of ATP levels inside single living cells with fluorescence resonance energy transfer-based genetically encoded indicators

    PNAS 106:15651–15656.

    https://doi.org/10.1073/pnas.0904764106

    • PubMed
    • Google Scholar
27. 1. Kar B
    2. Liu B
    3. Zhou Z
    4. Lam YW

    (2011) Quantitative nucleolar proteomics reveals nuclear re-organization during stress- induced senescence in mouse fibroblast

    BMC Cell Biology 12:33.

    https://doi.org/10.1186/1471-2121-12-33

    • PubMed
    • Google Scholar
28. 1. Kato M
    2. Han TW
    3. Xie S
    4. Shi K
    5. Du X
    6. Wu LC
    7. Mirzaei H
    8. Goldsmith EJ
    9. Longgood J
    10. Pei J
    11. Grishin NV
    12. Frantz DE
    13. Schneider JW
    14. Chen S
    15. Li L
    16. Sawaya MR
    17. Eisenberg D
    18. Tycko R
    19. McKnight SL

    (2012) Cell-free formation of RNA granules: low complexity sequence domains form dynamic fibers within hydrogels

    Cell 149:753–767.

    https://doi.org/10.1016/j.cell.2012.04.017

    • PubMed
    • Google Scholar
29. 1. Kiseleva E
    2. Drummond SP
    3. Goldberg MW
    4. Rutherford SA
    5. Allen TD
    6. Wilson KL

    (2004) Actin- and protein-4.1-containing filaments link nuclear pore complexes to subnuclear organelles in Xenopus oocyte nuclei

    Journal of Cell Science 117:2481–2490.

    https://doi.org/10.1242/jcs.01098

    • PubMed
    • Google Scholar
30. 1. Knight ZA
    2. Shokat KM

    (2005) Features of selective kinase inhibitors

    Chemistry & Biology 12:621–637.

    https://doi.org/10.1016/j.chembiol.2005.04.011

    • PubMed
    • Google Scholar
31. 1. Knowles TP
    2. Vendruscolo M
    3. Dobson CM

    (2014) The amyloid state and its association with protein misfolding diseases

    Nature Reviews Molecular Cell Biology 15:384–396.

    https://doi.org/10.1038/nrm3810

    • PubMed
    • Google Scholar
32. 1. Kroschwald S
    2. Maharana S
    3. Mateju D
    4. Malinovska L
    5. Nüske E
    6. Poser I
    7. Richter D
    8. Alberti S

    (2015) Promiscuous interactions and protein disaggregases determine the material state of stress-inducible RNP granules

    eLife 4:e06807.

    https://doi.org/10.7554/eLife.06807

    • PubMed
    • Google Scholar
33. 1. Lee CF
    2. Brangwynne CP
    3. Gharakhani J
    4. Hyman AA
    5. Jülicher F

    (2013) Spatial organization of the cell cytoplasm by position-dependent phase separation

    Physical Review Letters 111:088101.

    https://doi.org/10.1103/PhysRevLett.111.088101

    • PubMed
    • Google Scholar
34. 1. Lehman CW
    2. Carroll D

    (1993) Isolation of large quantities of functional, cytoplasm-free Xenopus laevis oocyte nuclei

    Analytical Biochemistry 211:311–319.

    https://doi.org/10.1006/abio.1993.1275

    • PubMed
    • Google Scholar
35. 1. Lopez-Buesa P
    2. Pfund C
    3. Craig EA

    (1998) The biochemical properties of the ATPase activity of a 70-kDa heat shock protein (Hsp70) are governed by the C-terminal domains

    PNAS 95:15253–15258.

    https://doi.org/10.1073/pnas.95.26.15253

    • PubMed
    • Google Scholar
36. 1. Love NR
    2. Thuret R
    3. Chen Y
    4. Ishibashi S
    5. Sabherwal N
    6. Paredes R
    7. Alves-Silva J
    8. Dorey K
    9. Noble AM
    10. Guille MJ
    11. Sasai Y
    12. Papalopulu N
    13. Amaya E

    (2011) pTransgenesis: a cross-species, modular transgenesis resource

    Development 138:5451–5458.

    https://doi.org/10.1242/dev.066498

    • PubMed
    • Google Scholar
37. 1. Lund E
    2. Paine PL

    (1990) Nonaqueous isolation of transcriptionally active nuclei from xenopus oocytes

    Methods in Enzymology 181:36–43.

    https://doi.org/10.1016/0076-6879(90)81110-G

    • PubMed
    • Google Scholar
38. 1. Maji SK
    2. Perrin MH
    3. Sawaya MR
    4. Jessberger S
    5. Vadodaria K
    6. Rissman RA
    7. Singru PS
    8. Nilsson KP
    9. Simon R
    10. Schubert D
    11. Eisenberg D
    12. Rivier J
    13. Sawchenko P
    14. Vale W
    15. Riek R

    (2009) Functional amyloids as natural storage of peptide hormones in pituitary secretory granules

    Science 325:328–332.

    https://doi.org/10.1126/science.1173155

    • PubMed
    • Google Scholar
39. 1. Majumdar A
    2. Cesario WC
    3. White-Grindley E
    4. Jiang H
    5. Ren F
    6. Khan MR
    7. Li L
    8. Choi EM
    9. Kannan K
    10. Guo F
    11. Unruh J
    12. Slaughter B
    13. Si K

    (2012) Critical role of amyloid-like oligomers of Drosophila Orb2 in the persistence of memory

    Cell 148:515–529.

    https://doi.org/10.1016/j.cell.2012.01.004

    • PubMed
    • Google Scholar
40. 1. Meyer T
    2. Voigt N

    (2017) In search for novel functions of adenosine 5'-triphosphate (ATP) in the heart

    Cardiovascular Research 113:e59–e60.

    https://doi.org/10.1093/cvr/cvx207

    • PubMed
    • Google Scholar
41. 1. Miller DS
    2. Horowitz SB

    (1986)

    Intracellular compartmentalization of adenosine triphosphate

    The Journal of Biological Chemistry 261:13911–13915.

    • PubMed
    • Google Scholar
42. 1. Miyoshi N
    2. Oubrahim H
    3. Chock PB
    4. Stadtman ER

    (2006) Age-dependent cell death and the role of ATP in hydrogen peroxide-induced apoptosis and necrosis

    Proceedings of the National Academy of Sciences 103:1727–1731.

    https://doi.org/10.1073/pnas.0510346103

    • Google Scholar
43. 1. Nillegoda NB
    2. Kirstein J
    3. Szlachcic A
    4. Berynskyy M
    5. Stank A
    6. Stengel F
    7. Arnsburg K
    8. Gao X
    9. Scior A
    10. Aebersold R
    11. Guilbride DL
    12. Wade RC
    13. Morimoto RI
    14. Mayer MP
    15. Bukau B

    (2015) Crucial HSP70 co-chaperone complex unlocks metazoan protein disaggregation

    Nature 524:247–251.

    https://doi.org/10.1038/nature14884

    • PubMed
    • Google Scholar
44. 1. Paine PL
    2. Johnson ME
    3. Lau YT
    4. Tluczek LJ
    5. Miller DS

    (1992)

    The oocyte nucleus isolated in oil retains in vivo structure and functions

    BioTechniques 13:238–246.

    • PubMed
    • Google Scholar
45. 1. Patel A
    2. Malinovska L
    3. Saha S
    4. Wang J
    5. Alberti S
    6. Krishnan Y
    7. Hyman AA

    (2017) ATP as a biological hydrotrope

    Science 356:753–756.

    https://doi.org/10.1126/science.aaf6846

    • PubMed
    • Google Scholar
46. 1. Peuchen EH
    2. Sun L
    3. Dovichi NJ

    (2016) Optimization and comparison of bottom-up proteomic sample preparation for early-stage Xenopus laevis embryos

    Analytical and Bioanalytical Chemistry 408:4743–4749.

    https://doi.org/10.1007/s00216-016-9564-2

    • PubMed
    • Google Scholar
47. 1. Phair RD
    2. Misteli T

    (2000) High mobility of proteins in the mammalian cell nucleus

    Nature 404:604–609.

    https://doi.org/10.1038/35007077

    • PubMed
    • Google Scholar
48. 1. Saad S
    2. Cereghetti G
    3. Feng Y
    4. Picotti P
    5. Peter M
    6. Dechant R

    (2017) Reversible protein aggregation is a protective mechanism to ensure cell cycle restart after stress

    Nature Cell Biology 19:1202–1213.

    https://doi.org/10.1038/ncb3600

    • PubMed
    • Google Scholar
49. 1. Scalenghe F
    2. Buscaglia M
    3. Steinheil C
    4. Crippa M

    (1978) Large scale isolation of nuclei and nucleoli from vitellogenic oocytes of Xenopus laevis

    Chromosoma 66:299–308.

    https://doi.org/10.1007/BF00328531

    • PubMed
    • Google Scholar
50. 1. Schreier S
    2. Malheiros SVP
    3. de Paula E

    (2000) Surface active drugs: self-association and interaction with membranes and surfactants. Physicochemical and biological aspects

    Biochimica Et Biophysica Acta (BBA) - Biomembranes 1508:210–234.

    https://doi.org/10.1016/S0304-4157(00)00012-5

    • Google Scholar
51. 1. Schwartz JC
    2. Wang X
    3. Podell ER
    4. Cech TR

    (2013) RNA seeds higher-order assembly of FUS protein

    Cell Reports 5:918–925.

    https://doi.org/10.1016/j.celrep.2013.11.017

    • PubMed
    • Google Scholar
52. 1. Shorter J
    2. Lindquist S

    (2004) Hsp104 catalyzes formation and elimination of self-replicating Sup35 prion conformers

    Science 304:1793–1797.

    https://doi.org/10.1126/science.1098007

    • PubMed
    • Google Scholar
53. 1. Shorter J

    (2011) The mammalian disaggregase machinery: hsp110 synergizes with Hsp70 and Hsp40 to catalyze protein disaggregation and reactivation in a cell-free system

    PLoS ONE 6:e26319.

    https://doi.org/10.1371/journal.pone.0026319

    • PubMed
    • Google Scholar
54. 1. Suzuki R
    2. Hotta K
    3. Oka K

    (2015) Spatiotemporal quantification of subcellular ATP levels in a single HeLa cell during changes in morphology

    Scientific Reports 5:16874.

    https://doi.org/10.1038/srep16874

    • PubMed
    • Google Scholar
55. 1. Tollervey D
    2. Kiss T

    (1997) Function and synthesis of small nucleolar RNAs

    Current Opinion in Cell Biology 9:337–342.

    https://doi.org/10.1016/S0955-0674(97)80005-1

    • PubMed
    • Google Scholar
56. 1. Traut TW

    (1994) Physiological concentrations of purines and pyrimidines

    Molecular and Cellular Biochemistry 140:1–22.

    https://doi.org/10.1007/BF00928361

    • PubMed
    • Google Scholar
57. 1. Vacher C
    2. Garcia-Oroz L
    3. Rubinsztein DC

    (2005) Overexpression of yeast hsp104 reduces polyglutamine aggregation and prolongs survival of a transgenic mouse model of Huntington's disease

    Human Molecular Genetics 14:3425–3433.

    https://doi.org/10.1093/hmg/ddi372

    • PubMed
    • Google Scholar
58. 1. Verheggen C
    2. Almouzni G
    3. Hernandez-Verdun D

    (2000) The ribosomal RNA processing machinery is recruited to the nucleolar domain before RNA polymerase I during Xenopus laevis development

    The Journal of Cell Biology 149:293–306.

    https://doi.org/10.1083/jcb.149.2.293

    • PubMed
    • Google Scholar
59. 1. Wiśniewski JR
    2. Zougman A
    3. Nagaraj N
    4. Mann M

    (2009) Universal sample preparation method for proteome analysis

    Nature Methods 6:359–362.

    https://doi.org/10.1038/nmeth.1322

    • PubMed
    • Google Scholar
60. 1. Wright RH
    2. Lioutas A
    3. Le Dily F
    4. Soronellas D
    5. Pohl A
    6. Bonet J
    7. Nacht AS
    8. Samino S
    9. Font-Mateu J
    10. Vicent GP
    11. Wierer M
    12. Trabado MA
    13. Schelhorn C
    14. Carolis C
    15. Macias MJ
    16. Yanes O
    17. Oliva B
    18. Beato M

    (2016) ADP-ribose-derived nuclear ATP synthesis by NUDIX5 is required for chromatin remodeling

    Science 352:1221–1225.

    https://doi.org/10.1126/science.aad9335

    • PubMed
    • Google Scholar
61. 1. Wühr M
    2. Güttler T
    3. Peshkin L
    4. McAlister GC
    5. Sonnett M
    6. Ishihara K
    7. Groen AC
    8. Presler M
    9. Erickson BK
    10. Mitchison TJ
    11. Kirschner MW
    12. Gygi SP

    (2015) The nuclear proteome of a vertebrate

    Current Biology 25:2663–2671.

    https://doi.org/10.1016/j.cub.2015.08.047

    • PubMed
    • Google Scholar
62. 1. Yaginuma H
    2. Kawai S
    3. Tabata KV
    4. Tomiyama K
    5. Kakizuka A
    6. Komatsuzaki T
    7. Noji H
    8. Imamura H

    (2014) Diversity in ATP concentrations in a single bacterial cell population revealed by quantitative single-cell imaging

    Scientific Reports 4:6522.

    https://doi.org/10.1038/srep06522

    • PubMed
    • Google Scholar
63. 1. Ytting CK
    2. Fuglsang AT
    3. Kalervo Hiltunen J
    4. Kastaniotis AJ
    5. Özalp VC
    6. Nielsen LJ
    7. Olsen LF

    (2012) Measurements of intracellularATP provide new insight into the regulation of glycolysis in the yeast Saccharomyces cerevisiae

    Integr. Biol. 4:99–107.

    https://doi.org/10.1039/C1IB00108F

    • Google Scholar
64. 1. Zernicka-Goetz M
    2. Pines J
    3. Ryan K
    4. Siemering KR
    5. Haseloff J
    6. Evans MJ
    7. Gurdon JB

    (1996)

    An indelible lineage marker for Xenopus using a mutated green fluorescent protein

    Development 122:3719–3724.

    • PubMed
    • Google Scholar

Author details

1. Michael H Hayes

   Molecular Medicine Doctoral Program, University of Iowa Carver College of Medicine, Iowa City, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing

   Competing interests

   No competing interests declared

2. Elizabeth H Peuchen

   Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, United States

   Contribution

   Data curation, Formal analysis, Validation, Investigation, Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

3. Norman J Dovichi

   Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, United States

   Contribution

   Resources, Data curation, Supervision, Funding acquisition, Writing—review and editing

   Competing interests

   No competing interests declared

4. Daniel L Weeks

   1. Molecular Medicine Doctoral Program, University of Iowa Carver College of Medicine, Iowa City, United States
   2. Department of Biochemistry, University of Iowa Carver College of Medicine, Iowa City, United States

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing—original draft, Project administration, Writing—review and editing

   For correspondence

   daniel-weeks@uiowa.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4977-2410