Controlled protein synthesis plays a fundamental role in orchestrating gene expression, and cellular protein amounts are thought to be primarily determined at the level of translation (Schwanhäusser et al., 2011). Translational control is integral to cellular development and homeostasis and becomes dysregulated in numerous disease states including cancer (Robichaud and Sonenberg, 2017), autism (Gkogkas et al., 2013), and neurodegeneration (Wiebe et al., 2020). Within a complex organ like the brain, the specialized and distinct properties of neuronal and glial subtypes arise from variable expression of many protein components which are subject to translational control (Doyle et al., 2008). Regulation of global protein synthesis as well as the modulated synthesis of specific proteins at the synapse is important in synaptic plasticity and memory formation (Sossin and Costa-Mattioli, 2019).

Despite advances in assessing the transcriptome with cellular resolution, mRNA levels are an imprecise surrogate for protein abundance, and methods to capture the nascent proteome of individual cell populations in vivo have lagged behind. Current methods employ indiscriminate protein synthesis labeling in all cells of a tissue followed by flow sorting of tagged cell suspensions from these tissues (Hidalgo San Jose and Signer, 2019) or regional microdissection (Griesser et al., 2020) and suffer from a lack of precision or substantial loss of protein. An alternative method for quantifying protein synthesis is through non-canonical amino acid (NCAA) protein labeling, using methionine analogs. This approach recently progressed toward cell-type specificity through the expression of engineered methionyl-tRNA synthetase (MetRS) (Alvarez-Castelao et al., 2017; Erdmann et al., 2015; Tanrikulu et al., 2009). Only mutant MetRS can charge methionyl-tRNA with azidonorleucine (ANL) which is amenable to protein capture by BONCAT (biorthogonal non-canonical amino acid tagging) and visualization by FUNCAT (fluorescent non-canonical amino acid tagging) (Alvarez-Castelao et al., 2017; Erdmann et al., 2015; Tanrikulu et al., 2009). Hence, nascent protein labeling is restricted to cells that express mutant MetRS. However, this labeling strategy requires extended dietary methionine depletion and lengthy ANL feeding in mice or 1–2d of ANL feeding in flies, and chronic feeding is associated with significant developmental toxicity and behavioral deficits (Alvarez-Castelao et al., 2017; Erdmann et al., 2015).

A potentially more efficient approach to protein synthesis labeling is through the use of puromycin analogs (Barrett et al., 2016; Liu et al., 2012). Puromycin is structurally similar to tyrosyl tRNA, yet its incorporation is not amino acid-specific, hence in contrast to NCAA, its incorporation into nascent proteins is not biased by their sequence or extent of methionine content. This facilitates more uniform incorporation into newly-synthesized proteins (Nathans, 1964), which is advantageous in the assessment of global protein synthesis. One caveat to this approach is that puromycin incorporation results in premature chain termination and therefore the production of truncated puromycylated proteins that, while still generally amenable to MS-based proteomic analysis, may be targeted for proteasome-mediated degradation. Addition of an O-propargyl group to puromycin allows visualization or capture of newly-synthesized protein via click-chemistry conjugation to a fluorophore-azide or a biotin-tagged azide, respectively, and has been successfully demonstrated in cultured cells (Liu et al., 2012) and in cells isolated from OP-puromycin (OPP)-injected animals (Hidalgo San Jose and Signer, 2019). We developed an analog of OPP called PhAc-OPP that harbors an enzyme-labile blocking group (Barrett et al., 2016). This blocking group renders OPP incapable of nascent protein incorporation until its removal by the E. coli enzyme PGA (Barrett et al., 2016). Hence, targeted expression of PGA can, in principle, be used to limit OPP proteome labeling to individual cell populations within animal tissues. To directly test this, we generated PGA-transgenic Drosophila and developed a method that we call POPPi for rapid, cell type-specific labeling of protein synthesis in intact fly brains. Here, we show that POPPi is a versatile labeling strategy that can achieve efficient visualization and identification of newly-synthesized proteins in a cell population of interest. Our approach enables cell-specific nascent proteome labeling from complex brain tissue within just a few hours, making it a powerful and efficient tool for examining the role of translational control in different physiological and pathological states.

We previously demonstrated that neuronal PGA expression successfully converts PhAc-OPP to OPP, thus enabling OPP labeling of nascent proteins in cultured primary mouse neurons (Barrett et al., 2016; Figure 1—figure supplement 1A). Toward cell type-specific protein labeling in complex nervous system tissue in vivo, we generated a transgenic PGA fly line that can express FLAG-tagged PGA when crossed to any of the commonly available fly lines expressing a cell type-specific GAL4 driver of choice (Figure 1—figure supplement 1B). Following ubiquitous PGA expression, we assessed PGA levels in embryos and the brains of larvae, pupae, and adults. PGA expression is detectable in both developing and adult flies, with the highest expression levels seen in larval and pupal brains, followed by adult brains and embryos (Figure 1—figure supplement 1C). We reasoned that cell type-specific nascent protein labeling in the CNS might be efficiently achieved using intact Drosophila brain explants. Drosophila whole brains isolated and maintained ex vivo are remarkably stable, exhibiting sustained neuronal morphology and physiological properties for many hours (Ayaz et al., 2008; Brown et al., 2006; Essers et al., 2016; Gibbs and Truman, 1998; Gu and O’Dowd, 2006; Wang et al., 2003; Li et al., 2020; Lee et al., 2006). Fly brain explants have been used to study neuronal activity such as response to odor stimulation (Gu and O’Dowd, 2006; Wang et al., 2003), axon remodeling (Brown et al., 2006; Gibbs and Truman, 1998), neuronal wiring (Li et al., 2020), neural stem cell proliferation (Lee et al., 2006), and protein synthesis (Essers et al., 2016). To examine whether isolated adult fly brains exhibit stable protein synthesis, we generated fly brain preparations and assessed ³⁵S-methionine/cysteine incorporation levels over 8 hr. We observe no significant change in global protein synthesis rates over this time period (Figure 1A), suggesting that protein synthesis is stable in newly-isolated whole brain preparations and that these may therefore be suitable for capturing in vivo protein synthesis states.

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Rapid cell type-specific protein synthesis labeling with PhAc-OPP

We next assessed if targeted PGA expression can promote PhAc-OPP unblocking and OPP labeling of newly-synthesized proteins in cell populations of interest. We expressed PGA pan-neuronally in Drosophila brain using the elavC155-GAL4 driver, which we confirmed by immunoblot (Figure 2—figure supplement 1A) and then treated freshly-isolated brain explants with PhAc-OPP for 2 hr. Robust neuronal protein synthesis labeling is seen following PhAc-OPP treatment, but not in the absence of PhAc-OPP (Figure 2A) or in PhAc-OPP treated brains in the absence of GAL4-driven PGA expression (Figure 2—figure supplement 1B), suggesting that PhAc-OPP is not substantially uncaged in the absence of PGA expression and therefore that it can be reliably used to label newly-synthesized protein in targeted cell populations expressing PGA. The extent of labeling is time-dependent, although appears to be maximal at around 2 hr (Figure 2B). This is consistent with a prior study of OPP labeling in cells (Liu et al., 2012), and with a scenario that OPP-peptide conjugates eventually undergo turnover. Cellular AF488-azide signal is not uniform across the cell cortex (Figure 2A), which is consistent with cell-to-cell variability in PGA expression observed in FLAG immunostained brains (Figure 2—figure supplement 1C). When PGA expression was restricted to dopamine neurons using TH-GAL4, newly-synthesized proteins are clearly visible in the soma of dopamine neurons within intact brain explants briefly treated with PhAc-OPP, but not in the surrounding tissue (Figure 2C). PGA expression targeted to glia via repo-GAL4, also confirmed via immunoblot (Figure 2—figure supplement 1A), results in visible nascent protein labeling in glial cells (co-labeled with mCherry) upon brief PhAc-OPP treatment, but not in the absence of PhAc-OPP (Figure 2D). Hence, POPPi can efficiently label newly-synthesized proteins in neuronal and glial cell populations within the fly brain.

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Since OPP incorporation into NPC results in peptide chain termination, we queried whether PhAc-OPP treatment diminishes overall protein synthesis rates. To assess this, we performed ³⁵S-methionine labeling in parallel to PhAc-OPP treatment of brain explants expressing PGA ubiquitously. We found that PhAc-OPP causes a dose-dependent inhibition of global protein synthesis rates but that this inhibition was minimal up to 100 μM PhAc-OPP (Figure 2E) which is the standard concentration used in our labeling experiments. A significant disruption of protein synthesis is only seen above 100 μM PhAc-OPP (Figure 2E). Additionally, protein ubiquitination levels are not affected by incubating brains in up to 100 μM PhAc-OPP for 2 hr (Figure 2F and G), consistent with PhAc-OPP not having a major impact on protein turnover under these conditions.

While our primary focus was on labeling brain cell populations, we probed whether PhAc-OPP can penetrate other dissected tissues besides the brain. Rather than express PGA in several individual tissues separately, we drove ubiquitous PGA expression via Actin5C-Gal4 and incubated inverted L3 larvae (which exhibit robust PGA expression (Figure 1—figure supplement 1)) in PhAc-OPP, followed by AF488-azide under the same conditions used for labeling and visualizing protein synthesis in isolated brains. We then dissected the fat body, trachea, muscle, and salivary gland for imaging. As seen in the brain, newly-synthesized protein can be clearly visualized in all larval bodily tissues examined (Figure 3), suggesting that PhAc-OPP can readily penetrate a variety of tissues besides the brain.

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Rapid cell type-specific nascent proteome capture with PhAc-OPP

As observed upon treating brain explants with OPP (Figure 1E), we find that PGA-dependent unblocking of PhAc-OPP in all neurons or in all glia of adult fly brains gives rise to OPP-labeled proteins that span a wide molecular weight range consistent with broad incorporation into the nascent proteome (Figure 4A and D). Pan-neuronal PGA expression was coupled to PhAc-OPP treatment and brain lysates were click conjugated to desthiobiotin azide for affinity purification of the neuronal proteome using neutravidin beads. Detection of total biotin-tagged protein with anti-biotin reveals robust enrichment of OPP-labeled protein in pulldown fractions relative to input (whole lysates) (Figure 4B). In support of widespread incorporation into NPC, we were able to label specific neuronal proteins of interest. Three crucial synaptic proteins involved in neurotransmitter release, namely Bruchpilot (ERC2 ortholog), Synapsin and Syntaxin, are all substantially enriched in the OPP-labeled neuronal proteome following affinity purification (Figure 4C). Similarly, glial PGA expression coupled to PhAc-OPP incubation and affinity purification with desthiobiotin azide yields strong enrichment of desthiobiotin-tagged OPP-labeled protein (Figure 4E) and of the glial-specific protein Draper (ortholog of the mammalian engulfment receptor MEGF10) (Figure 4F). Conversely, the neuronal SNARE complex protein Syntaxin is not enriched upon pan-glial PGA expression, supporting the conclusion that proteome labeling is restricted to the cell population expressing PGA.

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No effect of cell type-specific PGA expression on adult fitness or survival

Having found that PGA expression coupled to PhAc-OPP incubation can be used to visualize and capture the nascent proteome in a cell type-specific manner, we sought to determine whether PGA expression in flies affects their development, function, or survival. Toward this goal, we crossed UAS-PGA flies to pan-neuronal, pan-glial, or ubiquitous GAL4 driver strains and assessed the resulting progeny. Startle-induced negative geotaxis behavior is dependent on a functionally-intact nervous system and declines progressively with age in flies (Gargano et al., 2005; Martin and Grotewiel, 2006). Neither pan-neuronal nor pan-glial PGA expression affects negative geotaxis performance across age (Figure 5A), while ubiquitous PGA expression causes a pronounced deficit in 3-week-old flies but not at a more advanced age in 6-week-old flies (Figure 5B). In accordance with this, ubiquitous PGA expression impairs adult survival, resulting in a ~20% decrease in median lifespan (Figure 5D and Table 1), whereas no lifespan shortening is seen following pan-neuronal or pan-glial PGA expression (Figure 5C and Table 2). In fact, lifespan appears to be slightly extended by pan-glial PGA (Figure 5C and Table 2). Besides its negative effect on function and survival, ubiquitous PGA expression is also associated with major larval lethality suggesting that development is perturbed, while larval and pupal survival are unaffected by pan-neuronal or pan-glial PGA expression (Figure 5—figure supplement 1) and eclosion occurs at the expected Mendelian frequency. Collectively, these data suggest that PGA expression within the brain is well tolerated across the fly lifespan, and raise the possibility that PGA expression in an unknown tissue outside of the nervous system has a negative impact on development, function, and adult survival.

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Table 1

Genotype	N	Median lifespan (d)	Mean lifespan (d)	Log-rank (vs PGA/+ctrl)
UAS-PGA/+	142	54	53.1	-
Actin5C-GAL4/UAS-PGA	110	44	45.6	.006

Table 2

Genotype	N	Median lifespan (d)	Mean lifespan (d)	Log-rank (vs. PGA/+ctrl)
UAS-PGA/+	152	52	50.8	-
elavC155-GAL4/UAS-PGA	147	52	52.1	0.002
Repo-GAL4/UAS-PGA	112	63	58.4	<0.001

Brain explant labeling can capture in vivo protein synthesis states

In order to measure cell type-specific protein synthesis under various physiological or pathological conditions, it is important to know whether POPPi can be used to capture in vivo protein synthesis states in newly-isolated brains. To address this question, we examined neuronal protein synthesis labeling in the brains of young and aged flies. It is well established that a widespread age-related decline in protein synthesis occurs in the tissues of numerous organisms including Drosophila, when measured across the whole body (Fleming et al., 1986) or in heads (Yang et al., 2019), and that the decline is due to reduced mRNA translation as well as transcript abundance. To determine whether this same decline is seen specifically in the brains of aging flies, we measured global protein synthesis in young (4-day-old) and aged (21-day-old) wild-type fly brains and observe a substantial decrease in radiolabeled protein from aged fly brain, indicative of decreased protein synthesis (Figure 6A). Next, using POPPi in which PGA was expressed pan-neuronally, we were able to observe a decline in neuron-specific bulk protein synthesis in the aging fly brain (Figure 6B and C). Strikingly, neuronal protein synthesis was reduced by almost 50% in 3-week-old elavC155-GAL4/UAS-PGA flies relative to young (4-day-old) flies of the same genotype (Figure 6B and C). Measurement of PGA expression confirmed that this age-related decline in protein labeling was not due to a loss of PGA expression in aged flies (Figure 6D). These data support the conclusion that PGA expression coupled with PhAc-OPP incubation can be used to achieve a quantitative assessment of protein synthesis and that an age-dependent decline in protein synthesis can be effectively captured by this method.

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Protein synthesis labeling via PhAc-OPP dietary intake

While incubating brain explants in PhAc-OPP allows rapid protein synthesis labeling in cell populations of interest, we queried whether PhAc-OPP ingested in food can penetrate the brain and label newly-synthesized protein. To assess the feasibility of this approach, we exposed pan-neuronal PGA-expressing flies to various concentrations of PhAc-OPP in sugar-yeast extract food medium for 48 hr then determined whether OPP-labeled nascent protein can be visualized following AF488-azide conjugation. We observe concentration-dependent labeling with PhAc-OPP and that AF488-azide signal becomes significantly higher than background at concentrations ≥1 mM (Figure 7A and B). Importantly, flies appear to consume 4 mM PhAc-OPP-containing food in similar quantities to that of control food (Figure 7C), suggesting that food consumption is not significantly impaired by the presence of PhAc-OPP, even at the highest dose tested. These results suggest that PhAc-OPP administered dietarily can penetrate the brain at levels sufficient to obtain detectable albeit subtle nascent protein labeling.

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POPPi is a new method to rapidly visualize and capture cell-specific nascent proteomes in whole Drosophila brains. This method extends the demonstrated capability of PGA-dependent OPP labeling in cultured neurons (Barrett et al., 2016) to proteome labeling within complex nervous system tissue. OPP efficiently labels nascent proteomes within the fly brain and this is substantially blocked by the protein synthesis inhibitor cycloheximide (Figure 1C and D), indicating that de novo protein synthesis is key for labeling to occur. We show that our strategy is versatile and can be used to visualize nascent protein synthesis across all CNS neurons, specific to a small population of dopaminergic neurons or limited to glia (Figure 2). We also demonstrate that POPPi can be used to capture neuronal or glial proteomes and enrich proteins of interest within those cell populations (Figure 4). Global protein synthesis is stable for at least 8 hr in isolated whole brain preparations (Figure 1A), supporting an ability to capture in vivo protein synthesis states using this approach. Consistent with this, we were able to detect an age-related decline in bulk neuronal protein synthesis in the fly brain using PhAc-OPP (Figure 6). Future efforts will be focused on coupling proteome enrichment to mass spectrometry to interrogate the effects of physiological or pathological stimuli on the proteome at the level of individual proteins.

Spatially-resolved proteomic studies have lagged behind transcriptomic studies in part because issues with limited RNA starting material can be overcome by PCR amplification of cDNA, while no equivalent exists for protein. Nonetheless, flies can be rapidly bred to vast numbers and we anticipate that the facile scalability of Drosophila can be leveraged for proteomic studies that focus on small-cell populations. PGA transgenic flies are well-suited for CNS proteomic studies because PGA is robustly expressed in adult, larval, and pupal brains (Figure 1—figure supplement 1) as well as via neuronal and glial GAL4 drivers (Figure 2—figure supplement 1). Accordingly, while our efforts centered on characterizing proteome labeling within the adult CNS in this study, we anticipate that our chemical genetic approach should be applicable to examining CNS proteomes during fly development. Drosophila has been widely used in genetic studies of nervous system development (Jan and Jan, 2010), function (Noyes et al., 2021), aging (Piper and Partridge, 2018), and disease (Şentürk and Bellen, 2018). Major insights from these studies highlight strong conservation with mammalian biology and have spurred diverse proteomic analyses of gene expression in the fly nervous system (Li et al., 2020; Owald et al., 2010; Mangleburg et al., 2020; Wang et al., 2020) and interest in using flies to model the role of translational regulation in nervous system disease (Greenblatt and Spradling, 2018; Lu et al., 2014; Mizielinska et al., 2014). In addition to the work on diseases such as fragile X syndrome (Greenblatt and Spradling, 2018), frontotemporal dementia (Mizielinska et al., 2014), and diseases associated with aminoacyl-tRNA synthetase mutations (Lu et al., 2014) by others, we recently showed how aberrant translation contributes to neurodegenerative phenotypes caused by the common Parkinson’s disease-causing mutation LRRK2 G2019S in Drosophila and iPSC-derived dopamine neurons (Martin et al., 2014a; Martin et al., 2014b; Kim et al., 2020), adding to emerging evidence of translational dysregulation in models of Parkinson’s disease (Martin, 2016). Hence, we foresee many opportunities for PGA-expressing flies to generate insight into nervous system function and disease through cell type-specific proteomic studies. Our study builds on previous findings that OP-puromycin can successfully label cellular protein synthesis when applied to cultured mammalian cells (Liu et al., 2012; Forester et al., 2018) and from bone marrow cells when administered by i.p. injection to mice (Hidalgo San Jose and Signer, 2019). These findings indicate that OP-puromycin can readily penetrate cell membranes and is also able to permeate tissues. PhAc-OPP differs from OP-puromycin by the addition of a phenylacetyl group and N- (benzyloxy) carbamate spacer which renders PhAc-OPP more hydrophobic than OP-puromycin. This is anticipated to enhance the ability of PhAc-OPP to penetrate cell membranes by diffusion, while diluted concentrations can still be prepared in an aqueous solution for tissue incubation (see Materials and methods).

One potential concern surrounding the use of puromycin labeling is that its incorporation into NPC causes chain termination, therefore, at high-enough doses, it could impede cellular protein synthesis (Liu et al., 2012). This may be circumvented by finding an optimal concentration of puromycin (or analog) which permits sufficient labeling for detection while having minimal impact on total protein synthesis. We assessed this in Drosophila brains and found that 100 μM PhAc-OPP allowed us to obtain robust and rapid proteome labeling while not observing significant deficits in global protein synthesis that were seen at a higher concentration (Figure 2E). Another consequence of chain termination when occurring prematurely is the production of truncated protein. Interestingly, we were only able to detect what appears to be full-length protein by western blot following neutravidin enrichment and blotting for individual proteins (Figure 4C and F). While truncated proteins may be targeted for degradation and thus depleted from the lysate pool, another simple explanation for this observation is that all antibodies we used which have reported epitopes bind to C-terminal epitopes. These would be missing in truncated proteins, thus precluding their detection using these antibodies.

We assessed whether ectopic PGA expression in fly cell populations perturbs organism development, function, or survival. In contrast to ubiquitous PGA expression, neither neuronal nor glial PGA expression has any discernible negative impact on development, adult function, or survival (Figure 5 and Figure 5—figure supplement 1). Hence, when expressed in individual nervous system cell populations, PGA expression seems to be well tolerated. This may provide an advantage over existing NCAA-based cell-specific labeling strategies, where chronic ANL feeding to flies prior to proteomic assessment significantly impairs fly eclosion as well as negative geotaxis behavior in adults (Erdmann et al., 2015). There are additional concerns over how chronic NCAA feeding in this approach might affect protein abundance and overall proteome makeup. For example, the replacement of methionine with the NCAA L-azidohomoalanine (AHA) was seen to cause substantial changes in the abundance of numerous proteins in HeLa cells while AHA incorporation into the developing mouse proteome results in altered expression of about 10% of proteins (Bagert et al., 2014; Calve et al., 2016). It is also currently unclear whether long-term NCAA administration disrupts eukaryotic metabolism given that AHA and L-homopropargylglycine (HPG) were found to alter global metabolism in E. coli (Steward et al., 2020). Taken together with the fact that NCAA labeling requires extended dietary methionine depletion, lengthy feeding with amino acid analogs (Alvarez-Castelao et al., 2017; Erdmann et al., 2015), and that NCAA are not incorporated equally across the proteome, there are significant caveats associated with this labeling strategy that can be avoided using POPPi.

While here we focused on protein synthesis labeling in intact isolated brains, this method should in theory be amenable to proteome labeling in tissues throughout the body, wherever PGA can be adequately expressed. In support of this, we obtained preliminary evidence demonstrating the ability of PhAc-OPP to penetrate and label several bodily tissues (fat body, trachea, muscle, and salivary gland) under the same conditions used for protein synthesis labeling in the brain (Figure 3). We also obtained preliminary evidence that PhAc-OPP can penetrate the brain when administered dietarily to intact flies (Figure 7). Based on the magnitude of AF488-azide labeling, ingestion at the PhAc-OPP concentration range tested yields lower nascent protein labeling than we were able to achieve in brain explants at much lower concentrations, which we speculate may be due to comparatively lower levels of PhAc-OPP reaching the brain. Future studies will address whether labeling in other tissues can be achieved via dietary PhAc-OPP intake, as this approach may be crucial when tissues cannot be isolated and effectively sustained. Despite this uncertainty, the ability to rapidly quantify protein synthesis in cell populations within the CNS established here opens up many possibilities to address important questions pertaining to nervous system development, function, aging, and disease.

Current proteomic approaches for measuring protein synthesis harbor strengths and weaknesses compared to transcriptomic approaches. Ribosomal profiling and other ribosome capture methods such as TRAP measure ribosomal density on a given transcript which provides a proxy for the rate of protein synthesis but not an actual measure of protein product. Ribosomal profiling has provided important insights into mechanisms of translational control, yet, there are some weaknesses to the method (Brar and Weissman, 2015). Perhaps most importantly, inferring protein synthesis rates from a single snapshot of average ribosomal occupancy on a given mRNA is based on assumptions that all ribosomes complete translation, and are not subject to regulated translational pausing or abortion at the time of capture or at any time prior to finishing translation. Additionally, the method itself may miss ribosomal footprints if nuclease digestion is incomplete, and give rise to false readouts of translation from contaminating non-coding RNA fragments. In contrast, assessing translation at the level of synthesized protein, e.g., through quantitative proteomics, should avoid errors associated with inferring protein synthesis rates from ribosomal occupancy, with the caveat that higher sensitivity limits relative to transcriptomic approaches may make transcriptomics the method of choice when starting material is low. We believe a potential major advantage of POPPi over existing methods for measuring cell type-specific protein synthesis is its efficiency, particularly for visualizing protein synthesis – PhAc-OPP labeling coupled to AF488-azide conjugation can be completed within a few hours (see Methods). Future work will seek to understand the full capabilities and limitations of POPPi, e.g., for profiling rare cell populations in the brain.

In summary, we provide a new labeling method for rapidly visualizing, capturing, and quantifying cell type-specific nascent proteomes within the Drosophila brain. We believe this method will be a powerful tool for studying the role of the proteome and translational control in nervous system function with cellular resolution.

All data generated or analyzed during this study are included in the manuscript and supporting files.

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Author details

1. Stefanny Villalobos-Cantor

   Jungers Center for Neurosciences, Department of Neurology, Oregon Health and Science University, Portland, United States

   Contribution

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

   Competing interests

   No competing interests declared

2. Ruth M Barrett

   Jungers Center for Neurosciences, Department of Neurology, Oregon Health and Science University, Portland, United States

   Contribution

   Conceptualization, Formal analysis, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

3. Alec F Condon

   Jungers Center for Neurosciences, Department of Neurology, Oregon Health and Science University, Portland, United States

   Present address

   Department of Biology, Stanford University, Stanford, United States

   Contribution

   Conceptualization, Formal analysis, Validation, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2655-2121

4. Alicia Arreola-Bustos

   Jungers Center for Neurosciences, Department of Neurology, Oregon Health and Science University, Portland, United States

   Contribution

   Formal analysis, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

5. Kelsie M Rodriguez

   Department of Chemical Physiology and Biochemistry, Oregon Health and Science University, Portland, United States

   Contribution

   Investigation

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0821-6717

6. Michael S Cohen

   Department of Chemical Physiology and Biochemistry, Oregon Health and Science University, Portland, United States

   Contribution

   Conceptualization, Resources, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-7636-4156

7. Ian Martin

   1. Jungers Center for Neurosciences, Department of Neurology, Oregon Health and Science University, Portland, United States
   2. Department of Chemical Physiology and Biochemistry, Oregon Health and Science University, Portland, United States
   3. Parkinson Center of Oregon, Oregon Health and Science University, Portland, United States

   Contribution

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

   For correspondence

   martiia@ohsu.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5912-1777

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