Proteins are essential for nearly every cellular process to sustain a healthy organism. A complex network of pathways and signalling molecules regulates the proteins so that they work correctly in a process known as proteostasis.

As the body ages, this network can become damaged, which leads to the production of faulty proteins. Many proteins end up being misfolded – in other words, they are misshapen on the molecular level, which can be toxic for the cell. A build-up of such misfolded proteins is implicated in several neurological conditions, including Alzheimer’s, Parkinson’s and Huntington’s disease.

Cells have various ways to detect and respond to internal stressors, such as tissue or organ damage. For example, specific proteins in the nervous system can raise a ‘central’ alert when damage is detected, which then primes and coordinates the body’s systems to respond in the peripheral cells and tissues. But exactly how this happens is still unclear.

To find out more about the central coordination of stress responses, Lazaro-Pena et al. studied one such sensor protein, called HPK-1, in the roundworm C. elegans. They first overexpressed the protein in various tissues. This revealed that only when HPK-1 was overactive in nerve tissue, it protected proteins and prolonged the lifespan of the worms. An increased amount of HPK-1 improved the health span of the worms and older worms also moved better. However, genetically manipulated worms lacking HPK-1 in their nerve cells showed a faster decline in nervous system health as they aged, which could be reversed once HPK-1 was activated again.

Lazaro-Pena et al. then measured the amount of HPK-1 in worms at different stages of their life. This showed that as the worms aged, the amount of HPK-1 increased in the nerve cells. The nerve cells in which HPK-1 levels increased overlapped with an increased expression of proteins associated with longevity. Moreover, when HPK-1 was overexpressed, it stimulated the release of other cell signals, which then triggered protective responses to prevent the misfolding and aggregation of proteins and to help degrade damaged proteins.

This study shows for the first time that HPK-1 appears to play a protective role during normal ageing and that it may act as a key switch to stimulate other protective mechanisms. These findings may give rise to new insights into how the nervous system can coordinate many different stress responses, and ultimately delay ageing throughout the whole body.

The gradual decline of function within the proteome (proteostasis) is a characteristic of aging, which precipitates the onset and progression of a growing number of age-associated diseases (Balch et al., 2008; Gidalevitz et al., 2006; Gidalevitz et al., 2010; Kikis et al., 2010; Morimoto, 2011; Sala et al., 2017; Taylor and Dillin, 2011): Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease, and amyotrophic lateral sclerosis (ALS) are neurodegenerative diseases driven by genetic alterations that typically predispose a mutant protein isoform to aggregate and have toxic gain of function properties on the neuronal proteome. Outside of the nervous system, age-associated proteostatic decline also leads to disease, for example, the onset of diabetes mellitus (Jaisson and Gillery, 2014); thus, the decline in proteostasis during normal aging is not limited to the nervous system. A growing number of studies suggest that aging is not simply the result of stochastic accumulation of damage, but is determined through genetics and coordinated mechanisms across tissues and cell types (Labbadia and Morimoto, 2015; Lazaro-Pena et al., 2022; López-Otín et al., 2013). Proteostatic decline corresponds with the age-associated breakdown of a large proteostasis network (PN), which integrates stress-responsive control of protein folding, degradation, and translation in response to myriad cell intrinsic and non-autonomous signals. And yet, while major components of the proteostatic network have been identified, how multi-cellular organisms maintain systemic proteostasis within and across tissues to delay aging is still poorly understood.

The relatively simple metazoan animal Caenorhabditis elegans (C. elegans) is a premier model system to elucidate how proteostasis is coordinated across cell and tissue types in response to myriad signals. Discoveries of cell non-autonomous signaling first made in C. elegans have evolutionarily conserved components, and revealed that the nervous system acts as a key cell non-autonomous regulator of organismal proteostasis and longevity (reviewed in Miller et al., 2020). For example, a pair of thermosensory neurons systemically regulate the heat shock response (HSR) in a serotonin-dependent manner (Prahlad et al., 2008; Tatum et al., 2015). In contrast, a second regulatory component from the GABAergic and cholinergic systems normally limits muscle cell proteostasis (Garcia et al., 2007; Silva et al., 2013).

The first discovery of a putative link between the transcriptional cofactor homeodomain-interacting protein kinase (HPK-1) and longevity was from our genome-wide RNAi screen that identified 103 genes essential for decreased insulin-like signaling (ILS) to extend longevity (Samuelson et al., 2007). In C. elegans, hpk-1 preserves proteostasis, stress response, and organismal longevity (Berber et al., 2016; Das et al., 2017; Samuelson et al., 2007). Additionally, we have previously shown that HPK-1 extends longevity through distinct genetic pathways defined by HSF-1 and the target of rapamycin complex 1 (TORC1) (Das et al., 2017). Activation by either metabolic or genotoxic stressors has been observed from yeast to mammals, suggesting that this family of transcriptional cofactors arose early in evolution to couple metabolic and stress signaling (Hofmann et al., 2003; Kim et al., 2006; Lee et al., 2008; Shojima et al., 2012).

In general, mammalian HIPK family members regulate the activity of transcription factors (TFs), chromatin modifiers, signaling molecules, and scaffolding proteins in response to cellular stress (Calzado et al., 2007; de la Vega et al., 2012; Song and Lee, 2003a; Song and Lee, 2003b). For example, nutrient stress, such as glucose deprivation, can activate Hipk1 and Hipk2 (Ecsedy et al., 2003; Garufi et al., 2013; Song and Lee, 2003b). Conversely, hyperglycemia triggers HIPK2 degradation via the proteasome (Baldari et al., 2017).

We sought to identify the tissue and cell types in which the HPK-1 transcriptional circuits act to extend longevity, increase resistance to acute proteotoxic stress, and which PN components are regulated across tissues. We have discovered that HPK-1 functions as a key regulator of the proteostatic response, originating in the nervous system of C. elegans. We find that hpk-1 is the most broadly upregulated kinase during normal C. elegans aging, predominantly within the nervous system, and acts to preserve neuronal function and proteostasis within the nervous system. Further, HPK-1 kinase activity within the nervous system initiates cell non-autonomous signals that trigger protective peripheral responses to maintain organismal homeostasis. Responses can qualitatively differ depending on the neuronal type from which they arise: serotonergic HPK-1 activity increases thermotolerance and protects the proteome from acute stress by enhancing the HSR, without increasing lifespan or altering basal autophagy. In contrast, GABAergic HPK-1 activity induces autophagy and extends longevity, without altering thermotolerance. HPK-1 overexpression is sufficient to induce autophagy gene expression, and autophagosome formation requires hlh-30 (TFEB), mxl-2 (MLX), and daf-16 (FOXO) TFs. We posit that serotonergic HPK-1 signaling responds to acute proteotoxic stress, whereas GABAergic HPK-1 responds to chronic metabolic changes mediated through TORC1 (Das et al., 2017). Yet, each of these distinct adaptive responses is sufficient to activate the PN and improve proteostasis outside of the nervous system. Our findings reveal HPK-1 as a key neuronal regulator in coordinating adaptive metabolic and stress response pathways across tissues to delay aging throughout the animal.

It has been known that a core group of TFs integrates various types of metabolic and stress signals; moreover, this group of TFs can extend longevity when overexpressed, and conversely hasten aging when lost (reviewed in Denzel et al., 2019), but whether the activity or expression of these longevity-associated transcriptional regulators are activated by signals of increasing damage or dysfunction during normal aging was unknown. Recently, single-cell RNA-Seq has revealed that these longevity-associated TFs increase in expression during aging in wild-type animals across multiple somatic tissues (Roux et al., 2022). This comprehensive empirical dataset provides foundational support for a key theme in aging research: during aging in wild-type animals, increasing damage and dysfunction is mitigated by the activation of stress response programs. Our findings that: (1) hpk-1 expression is upregulated during normal aging in more neurons and non-neuronal cells than any other kinase, and (2) that hpk-1 is induced in cell clusters that overlap with longevity-associated TFs, including daf-16, hlh-30, skn-1, and hif-1, implies that HPK-1 is a key transcriptional regulator that mitigates aging. We posit this response is activated in the nervous system during normal aging in wild-type animals to mitigate increasing stress and the breakdown of homeostatic mechanisms within the nervous system. Consistently, the presence of human neurodegenerative disorders, a severe form of neuronal proteotoxic stress, correlates with activation of human hpk-1 expression: for example, human HIPK2 is activated in frontal cortex samples of patients with AD, in motor neurons of ALS patients, and in mouse models of ALS (Lee et al., 2016). Thus, our results suggest that overexpression of hpk-1 in the C. elegans nervous system may extend longevity by preemptively delaying the accumulation of age-associated damage and dysfunction to the proteome (Figure 9A). However, hpk-1 homologs in more complex metazoans can also promote cell death, a key homeostatic component of tissue regeneration, indicating that chronic activation of HIPKs is not always beneficial (Calzado et al., 2007; Lee et al., 2016; Wang et al., 2020; Zhang et al., 2020). Whether activated HIPKs will fortify proteostasis and extend longevity, or promote cell death is likely to be dependent on many factors, including the specific homolog, levels of expression, physiological context, genetic background, and cell type.

Figure 9

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We find that hpk-1 prevents age-associated decline of axonal and synaptic integrity, which together preserve neuronal function during the aging process and thus also promote longer healthspan. In support of this concept, adult hipk2-/- mice display normal neurogenesis but manifest delayed-onset severe psychomotor and behavioral deficiencies, as well as degeneration of dopaminergic neurons, reminiscent of PD (Zhang et al., 2007). Loss of hpk-1 results in dysregulation of neuronal gene expression by early adulthood; some changes are consistent with neuronal aging but in other cases we observe an inverse correlation. For example, one-third of all neuropeptides are induced in the absence of hpk-1; yet increased neuropeptide signaling has been associated with extended C. elegans longevity and is considered protective in AD (Chen et al., 2018; Hodge et al., 2022; Petrella et al., 2019). One possibility is in the absence of hpk-1, attenuated inducibility of the proteostatic network accelerates age-associated cellular dysfunction (Figure 9A), and upregulation of neuropeptide signaling compensates in the nervous system for the loss of proteostatic response. This concept is consistent with our finding that increasing neuronal HPK-1 activity does not require neuropeptides to improve proteostasis in distal tissues. An alternative possibility for the connection between protective effects of HPK-1 and neuropeptides in neurons is that HPK-1 may reduce insulin signaling by suppressing the processing of ins peptides, thereby decreasing ILS to activate DAF-16 (FOXO) transcriptional quality control programs. For example, loss of egl-3, a neuropeptide processing gene, extends longevity by inactivating processing of insulins (Hamilton et al., 2005), and egl-3 is upregulated in hpk-1 loss of function.

Impairment of the proteostatic network after loss of hpk-1 results in broad upregulation of gene expression, which may provide additional levels of compensatory mechanisms to mitigate neuronal dysfunction. For example, loss of hpk-1 induces expression of intraflagellar transport (IFT) components in sensory cilia. Mutations within sensory neurons can alter longevity (Alcedo and Kenyon, 2004; Apfeld and Kenyon, 1999), and decreased IFT during C. elegans aging impairs sensory perception and metabolism (Zhang et al., 2021). Deficiencies in primary cilia impairs neurogenesis in AD transgenic mice, resulting in accumulation of Aβ₄₂ and tau protein and disease progression (Armato et al., 2013; Chakravarthy et al., 2012; Ma et al., 2022; Morelli et al., 2017). However, our bulk RNA-Seq analysis cannot decipher changes in gene expression at the level of individual neurons after loss of hpk-1. hpk-1 and orthologs are known to have roles in development, differentiation, and cell fate specification (Berber et al., 2013; Blaquiere and Verheyen, 2017; Calzado et al., 2007; Hattangadi et al., 2010; Rinaldo et al., 2007; Rinaldo et al., 2008; Steinmetz et al., 2018), therefore we cannot preclude the possibility that HPK-1 may function to broadly limit neuronal gene expression during the course of normal development and differentiation, thereby specifying neuronal transcriptional programs. Mis-differentiation of the nervous system in the absence of hpk-1 could result in both intracellular transcriptional noise and cell non-autonomous noise across cell types and tissues.

We show that HPK-1 expression in serotonergic neurons activates a cell non-autonomous signal to prime induction of molecular chaperones in muscle cells, whereas HPK-1 expression in GABAergic neurons signals induces autophagy in hypodermal tissue (Figure 9B). Our findings place HPK-1 within a selective cohort of transcriptional regulators within the C. elegans nervous system that are activated in response to metabolic, environmental, and intrinsic cues; thereby initiating distinct cell non-autonomous signals to regulate components of the PN in peripheral tissues (Douglas et al., 2015; Durieux et al., 2011; Frakes et al., 2020; Imanikia et al., 2019; Prahlad et al., 2008; Prahlad and Morimoto, 2011; Silva et al., 2013; Tatum et al., 2015; Taylor and Dillin, 2013; Morimoto, 2020). Loss of serotonin production in tph-1 mutant animals has a minimal impact on lifespan at basal temperature (Murakami and Murakami, 2007). However, simultaneous loss of both serotonin and DA biosynthesis shortens lifespan (Murakami and Murakami, 2007). Serotonin biosynthesis is also required for several conditions that extend longevity: animals treated with an atypical antidepressant serotonin antagonist (mianserin) (Petrascheck et al., 2007), changes in food perception (Entchev et al., 2015), and neuronal cell non-autonomous induction of the mitochondrial unfolded protein response (Berendzen et al., 2016; Zhang et al., 2018). In contrast, loss of either of the serotonin receptors ser-1 or ser-4 have opposing effects on lifespan, suggesting antagonistic activity between serotonin receptors (Murakami and Murakami, 2007).

Surprisingly, we find that increased HPK-1 activity in serotonergic neurons does not increase lifespan, but is sufficient to improve muscle proteostasis and amplify the expression of molecular chaperones that maintain proteostasis within the cytosol and nucleus. Interestingly, neuronal HSF-1 regulation of the HSR through thermosensory circuits is also separable from lifespan (Douglas et al., 2015). Serotonin signaling and the serotonin receptor ser-1 are essential for the induction of the HSR (Prahlad et al., 2008; Tatum et al., 2015). ADF serotoninergic neurons receive upstream stress signals from the thermosensory circuit, consisting of the amphid sensory neurons (AFD) and the AIY interneurons, which regulate HSF-1 activity in the germline in a serotonin-dependent manner (Tatum et al., 2015). However, increased serotonergic HPK-1 activity is not equivalent to altered thermosensory signals: hpk-1 improves proteostasis within body wall muscles but not intestinal cells through neurotransmitters, and is independent of dense core vesicles. In contrast, loss of the guanylyl cyclase (gcy-8) in AFD thermosensory neurons or the LIM-homeobox TF (ttx-3) in AIY interneurons improves intestinal proteostasis through dense core vesicle neurosecretion (i.e., unc-31). hpk-1 is expressed in AFD, but only at very low levels in AIY neurons (data not shown and Taylor et al., 2021), and hpk-1 is essential for the induction of the HSR within intestinal cells (Das et al., 2017). Whether hpk-1 activity within thermosensory neurons functions within the canonical thermosensory-serotonin circuit to regulate the intestinal HSR or proteostasis is not mutually exclusive from our findings and will be interesting to pursue in future studies. Our results suggest that serotonergic HPK-1 is an important regulator of the HSR, potentially functioning in parallel to the thermosensory-serotonin circuit to restore proteostasis in response to acute thermal stress.

We posit that increased serotonergic HPK-1 activity further activates HSF-1 in response to heat (Figure 9B). This would be consistent with known hyperphosphorylation of HSF-1 and amplification of the HSR in response to increasingly severe heat stress (reviewed in Lazaro-Pena et al., 2022). Interestingly, HPK-1 limits SUMOylation of HSF-1, SUMO limits the HSR in both C. elegans and mammals, and severe heat shock results in HSF1 deSUMOylation (Das et al., 2017; Hietakangas et al., 2003; Hietakangas et al., 2006). To our surprise, while increased neuronal hsf-1 expression increases longevity (Douglas et al., 2015; Morley and Morimoto, 2004), we could find no study that has identified specific neuronal cell types in which increased HSF-1 activity is sufficient to extend longevity or enhance the HSR. Whether or not HPK-1 regulates HSF-1 within the nervous system and/or in peripheral muscle cells through cell non-autonomous signals will be interesting to determine in future studies. HPK-1 co-localizes with HSF-1 in neurons, HPK-1 protein is stabilized after heat shock, hpk-1 is essential for induction of the HSR, and hsf-1 and hpk-1 are mutually interdependent to extend longevity (Das et al., 2017; Figure 9B).

Increased HPK-1 activity in GABAergic neurons induces autophagy in peripheral cells, improves proteostasis and longevity. Whether HPK-1 functions in GABAergic neurons through alteration of GABA or another neurotransmitter is unknown, but proper differentiation of GABAergic neurons is essential for neuronal HPK-1 activation of autophagy in distal tissue. We posit that HPK-1 cell non-autonomous signaling occurs via antagonism of GABA signaling. Loss of GABA increases C. elegans lifespan (Chun et al., 2015; Yuan et al., 2019). However, not all neurotransmitters regulate lifespan, as only mutants for the GABA biosynthetic enzyme, unc-25, increase lifespan. This GABAergic-mediated control in lifespan seems to be mediated by the gbb-1 metabotropic GABA_B receptor (Chun et al., 2015). Interestingly, GABA signaling inhibits autophagy and causes oxidative stress in mice, which is mitigated via Tor1 inhibition (Lakhani et al., 2014). In fact, we previously found that neuronal expression of HPK-1 is inhibited by TORC1 and hpk-1 is required for TORC1 inactivation to extend longevity and the induction of autophagy gene expression (Das et al., 2017). Both TORC1 inactivation and hpk-1 overexpression requires the Myc-family member mxl-2 to extend longevity (Das et al., 2017; Johnson et al., 2014; Nakamura et al., 2016; Figure 8—figure supplement 2). Consistently, TORC1 also acts within neurons to regulate aging (Zhang et al., 2019); our results suggest that GABAergic neurons might be the specific neuronal cell type through which alterations in TORC1 activity regulate longevity. Collectively, our results position HPK-1 activity in GABAergic neurons as the likely integration point for cell non-autonomous regulation of autophagy via TORC1 (Figure 9B).

A growing number of longevity-associated TFs have been linked to autophagy, including pha-4 (FOXA), mxl-2 (MLX), hlh-30 (TFEB), daf-16 (FOXO), and hsf-1 (Hansen et al., 2008; Kumsta et al., 2017; Lapierre et al., 2013; Lapierre et al., 2015; Nakamura et al., 2016; O’Rourke and Ruvkun, 2013). We find that hlh-30, daf-16, and hlh-30 are all required for the induction of autophagosomes when hpk-1 is overexpressed in GABAergic neurons. We posit these TFs respond within the distal hypodermal seam cells in response to a neuronal signal initiated by HPK-1, as neurons are largely refractory to RNAi. However, this does not preclude cell intrinsic neuronal interactions; future refined spatial genetic analysis will be required to definitively decipher the precise tissues of action. DAF-16 and HLH-30 have previously been shown to function in combination to promote stress resistance and longevity (Lin et al., 2018). Analogously, the MML-1::MXL-2 complex and HLH-30 activate each other and are downstream effectors of longevity after TORC1 inhibition (mml-1 encodes the MondoA/ChREBP ortholog, an obligate interactor with MXL-2) (Nakamura et al., 2016). Based on our discovery that all three of these longevity-associated TFs are essential for GABAergic HPK-1 activity to induce autophagy, it is tempting to speculate HPK-1 acts as a key mediator of pro-longevity signaling after TORC1 inhibition through coordinated activation of MML-1::MXL-2, HLH-30, and DAF-16 (Figure 9B).

This work reveals a new level of specificity in the capacity of the nervous system to initiate adaptive responses by triggering distinct components of the proteostatic network across cell types. Results elucidating how neuronal cell types generate heterotypic signals to coordinate the maintenance of homeostasis are just beginning to emerge. For example, a previous study discovered that activating non-autonomous signaling of the ER-UPR via the XBP-1 TF can be initiated from serotonergic neurons and dopaminergic neurons; these signals are unique and converge to activate distinct branches of the ER-UPR within the same distal tissues (intestinal cells) (Higuchi-Sanabria et al., 2020). In contrast, our work demonstrates differential, yet specific, activation of cytosolic components of the PN in separate peripheral tissues through neurotransmitters. Our work suggests that the nervous system partitions neuronal cell types to coordinate the activation of complementary proteostatic mechanisms across tissues, despite utilizing the same transcriptional regulator within each neuronal cell type. One possibility is that HPK-1 regulates specific adaptive responses based on the unique epigenetic states between differentiated neuronal subtypes, which would be consistent with recent findings: during development and differentiation, transcriptional rewiring of cells sets chaperoning capacities and alters usage of mechanisms that maintain protein quality control (Nisaa and Ben-Zvi, 2022; Shemesh et al., 2021). Our work reveals HPK-1 as a novel transcriptional regulator within the nervous system of metazoans, which integrates diverse stimuli to coordinate specific adaptive responses that promote healthy aging.

While single-cell RNA-Seq is a powerful approach already, well-documented challenges remain with respect to consistency in cell captures and differentiating biological noise from technical artifacts such as ‘drop-outs’ from low numbers of average reads per cell (Hwang et al., 2018; Hwang et al., 2021; Ke et al., 2022; Nayak and Hasija, 2021). We attempted to identify gene-gene correlations within cell clusters across individual ages based on the C. elegans Aging Atlas dataset and found that inconsistency in the number of cells per cluster across time points limits our ability to identify many robust and significant associations – such variability is likely technical in nature, as it is not globally consistent across cell clusters for a given time point. In most cases, when aggregated into ‘young’ and ‘old’ sample groups, as was done for differential expression analysis in the original Aging Atlas analysis (Roux et al., 2022) the groups represent comparable numbers of total cells for most clusters. The trends we have observed at the level of individual time points indicate that the age-associated upregulation of hpk-1 does not always occur at the same time point across cell clusters and is not necessarily tightly linked to the upregulation of longevity-associated TFs in the same cluster (Appendix 1—figure 1). Thus, the age-associated upregulation of pro-longevity factors in many cell clusters may not be due to a highly coordinated regulatory process, but rather a distributed response to accumulating local stress or damage. More work will be necessary to resolve if such late-life expression changes indeed contribute to maintenance of wild-type lifespan and healthspan, and the mechanism of the changes thereof (e.g., increased transcription, downregulation of miRNA targeting, epigenetic changes) and the factors that mediate these changes.

Appendix 1—figure 1

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Loss of hpk-1 upregulates expression of a number of neuronal genes including those involved in neuropeptide signaling, neurotransmission, release of synaptic vesicles, calcium homeostasis, and function of sensory neurons. In addition to upregulation of ins neuropeptides, 12 FMRFamide-related (flp) peptides, 19 neuropeptide-like proteins (nlp), 9 neuropeptide maturation genes (e.g., egl-3 [proprotein convertase subtilisin/kexin type 2] and egl-21 [carboxypeptidase E]), and 9 putative GPCR neuropeptide receptors were also significantly upregulated in hpk-1 null mutants. Neurotransmitters are signaling molecules that trigger a response by binding to ionotropic or metabotropic neurotransmitter receptors in recipient neurons or tissues; we find that mainly the latter are upregulated in hpk-1 null mutant animals, including acetylcholine (gar-1, gar-2, and gar-3), GABA (gbb-2), and glutamate (mgl-3 and uncharacterized C30A5.10). In total, 9 metabotropic and 2 ionotropic glutamate receptors, 14 vesicular glutamate transport family genes, 9 acetylcholine receptor ligand-gated ion channels, and 9 GABA receptor ligand-gated ion channels were upregulated. Additionally, ace-2, ace-3, and cha-1, involved in acetylcholine degradation and synthesis (respectively), were upregulated. comt-4, a catechol-O-methyltransferase expected to be involved in the degradation of DA, was significantly downregulated.

Synaptic transmission, the formation and release of synaptic vesicles, carry neurotransmitters and rely on proteins necessary for docking, priming, and fusing to the axon terminal plasma membrane, which releases cargo into the synaptic cleft. Interestingly, loss of hpk-1 causes the upregulation of synaptic proteins such as unc-13, unc-10, and rab-3, which are essential for vesicle priming, recruitment, and sequestration of vesicles, respectively. The process of vesicle release is highly dependent on a Ca²⁺ signal detected by synaptotagmins proteins, which promotes vesicle fusion to the plasma membrane (Deák, 2014). In hpk-1 null mutant animals, we observed upregulation of synaptotagmin snt-1, snt-3, and snt-4 Ca²⁺ sensor proteins for vesicle release.

Neuronal function is regulated by changes in calcium levels: a decrease in calcium uptake reduces neuronal function by a reducing neurotransmitter release (Scriabine and Kazda, 1989). In contrast, increasing calcium influx triggers activation of proteases and phospholipases, resulting in cell damage and cell death (Cheung et al., 1986; Siesjö, 1989). Voltage-gated Ca²⁺ channels (VGCCs) are composed of 24 transmembrane alpha-1 subunits and associate with auxiliary beta-1 and alpha-2-delta subunits. hpk-1 null mutant animals have increased expression of two of five alpha-1 subunits (egl-19 and unc-2), and both alpha-2-delta subunits (unc-36 and tag-180). Previous research describes the role of egl-19 VGCC in the induction of the heat stress response (Silva et al., 2013): moderate upregulation of acetylcholine signaling improves muscle proteostasis by the activation of HSF-1, triggered by the egl-19-dependent Ca²⁺ influx.

Neuronally expressed cilia are essential for cell motility, sensory perception, and signaling. The assembly and maintenance of sensory cilia depends on IFT: bidirectional movement of cargo to and from the base and tip of the axoneme. The C. elegans IFT machinery is composed of anterograde IFT motors, heterotrimeric kinesin-II and homodimeric OSM-3, retrograde dynein motors; and the IFT-A, -B, and BBSome particle complexes (Hao et al., 2009; Scholey et al., 2004). Loss of hpk-1 induces the expression of a high number of IFT machinery components including klp-11 (kinesin II motor), che-3 (dynein motor), three and seven members of the IFT-A and -B complexes (respectively), and five members of BBSome complex. In mammals, there is a link between primary cilia signaling and aging-related brain disease, including neurodegenerative disorders (Ma et al., 2022).

Our primary RNA-Seq data is available for review (GEO accession GSE220744: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE220744). Data analysis scripts have been deposited at: https://github.com/samuelsonlab-urmc/hpk1_manuscript_2023 (copy archived at Cornwell, 2023). All data generated or analyzed during this study are included in the manuscript and supporting files; Source data files have been provided for all figures and figure supplements in 14 supplementary files.

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Author details

1. Maria I Lazaro-Pena

   Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, United States

   Contribution

   Conceptualization, Resources, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3061-8835

2. Adam B Cornwell

   Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, United States

   Contribution

   Conceptualization, Resources, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0572-3107

3. Carlos A Diaz-Balzac

   Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Rochester Medical Center, Rochester, United States

   Contribution

   Resources, Validation, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4723-1282

4. Ritika Das

   1. Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, United States
   2. Department of Biology, University of Rochester, Rochester, United States
   3. Department of Cell Biology, Skirball Institute of Biomolecular Medicine, NYU School of Medicine, New York, United States

   Contribution

   Conceptualization, Resources, Investigation, Visualization, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

5. Zachary C Ward

   Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, United States

   Contribution

   Investigation, Methodology

   Competing interests

   No competing interests declared

6. Nicholas Macoretta

   Department of Biology, University of Rochester, Rochester, United States

   Contribution

   Conceptualization, Resources, Formal analysis, Validation, Investigation, Methodology

   Competing interests

   No competing interests declared

7. Juilee Thakar

   1. Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, United States
   2. Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, United States
   3. Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester, United States

   Contribution

   Conceptualization, Resources, Formal analysis, Supervision, Methodology, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

8. Andrew V Samuelson

   Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, United States

   Contribution

   Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing – review and editing

   For correspondence

   Andrew_Samuelson@URMC.Rochester.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3071-5766

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