Micro-/nano-plastics accentuate Parkinson’s Disease-relevant phenotypes in a Drosophila model

Micro-/nano-plastics accentuate Parkinson’s Disease-relevant phenotypes in a Drosophila model | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Micro-/nano-plastics accentuate Parkinson’s Disease-relevant phenotypes in a Drosophila model View ORCID Profile Simon A. Lowe , View ORCID Profile James E.C. Jepson doi: https://doi.org/10.1101/2025.11.17.688805 Simon A. Lowe 1 Department of Epilepsy, UCL Queen Square Institute of Neurology , London, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Simon A. Lowe For correspondence: s.lowe{at}ucl.ac.uk James E.C. Jepson 1 Department of Epilepsy, UCL Queen Square Institute of Neurology , London, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for James E.C. Jepson Abstract Full Text Info/History Metrics Supplementary material Preview PDF ABSTRACT Micro- and nano-plastic (MNP) particles are a ubiquitous environmental contaminant that are increasingly bioaccumulating in human tissues, particularly the brain. MNPs induce mitochondrial defects, oxidative stress, inflammatory responses and neurotoxicity in cellular and organismal models. This raises the possibility that MNP exposure could cause or exacerbate neurological conditions associated with these pathological phenomena. Parkinson’s Disease (PD), a common movement disorder characterised by degeneration of striatal dopaminergic neurons, and associated with mitochondrial dysfunction, represents such a condition. We therefore hypothesised that MNP exposure might interact with PD risk mutations affecting mitochondrial fidelity. We used a fruit fly model of PRKN -dependent PD associated with defects in mitophagy, a mitochondrial quality control pathway, to test this hypothesis. We found that ingestion of MNPs at concentrations tolerated by wild-type controls selectively enhanced PD-relevant phenotypes – including progressive dopaminergic neurodegeneration, movement defects, and sleep disruption – in this model of PD. Our data suggest that defects in mitochondrial quality control can increase vulnerability to MNP exposure, and more broadly, that MNPs may synergistically interact with existing genetic risk factors to worsen neurological disease. INTRODUCTION The rapidly changing environment has the potential to impact human neuronal health via increasing global temperatures 1 , reduced air quality 2 , and exposure to neurotoxic environmental pollutants 3 . Collectively, neurological disorders are currently the leading cause of disability worldwide; and incidence rates and associated social challenges are expected to increase in the coming decades 4 . Due to the ageing global population, this increase is projected to be particularly prominent for age-related neurological disorders such as Parkinson’s Disease (PD) 5 . Thus, understanding how the changing environment may impact the incidence and progression of these disorders is essential to inform policy and shape social responses. The impact of plastic pollution on human health 6 , and particularly neurological health 7 8 , is emerging as a potential global health crisis. Micro- and nano-plastics (MNPs) are defined as plastic particles on the < 1 μM and 1 μM - 1 mm scale respectively, which are either manufactured or generated from the breakdown of macro-plastics by UV light degradation, mechanical abrasion from water and sand, etc 9 . Global annual plastic production exceeds 400 million tons, a majority of which are single-use, and only a small minority of which is recycled 10 . MNP pollution is now ubiquitous: significant levels have been identified in the air, soil, ocean and drinking water, including in remote regions 9 , with evidence that they bioaccumulate up the food chain 11 . Unsurprisingly given the range of absorption routes, MNPs have been isolated in a range of human tissues 12 . MNPs cross the blood-brain barrier (BBB) and preferentially bioaccumulate in the brain over other tissues 13 . Levels in post-mortem human brain tissue positively correlate with more recent time of death (2016 vs 2024) 12 , consistent with increasing environmental levels. Particularly worryingly, MNPs have been identified in the placenta 14 , indicating that nervous system exposure to constantly rising MNP levels from the earliest stages of development onwards will now be the norm. The health implications of this exposure are not understood, but MNP levels were higher in brains with documented dementia diagnoses 13 , suggesting a possible causative role and indicating an urgent need to understand how MNPs interact with neural tissue and organismal health. An extensive body of work demonstrates the cytotoxicity of MNPs to cultured cells. Exposure disrupts the morphology and function of mitochondria 15 , possibly by binding directly to complex 1 16 , and induces excess production of reactive oxygen species (ROS), oxidative stress 17 , and upregulation of inflammatory markers 18 . These effects overlap with cellular mechanisms known to contribute to a range of neurological disorders, particularly PD, in which the mechanistic contributions of mitochondrial dysfunction, oxidative stress, and chronic inflammation are well documented 19 . Dopaminergic neurons, which selectively degenerate in PD, are particularly vulnerable to mitochondrial toxins 20 , and exposure to mitotoxic pesticides may contribute to the aetiology of PD 21 22 . This raises the possibility that exposure to MNPs could similarly induce PD-like symptoms. Indeed, oral ingestion or inhalation of MNPs cause PD-like motor defects and dopaminergic degeneration 23 24 25 in mice, alongside a wide range of behavioural defects in vertebrate and non-vertebrate models 26 , 27 , 28 , 29 . On the basis that vulnerable populations are likely to be first impacted by adverse conditions, we hypothesised that MNP exposure might interact with intrinsic genetic risk for PD. Thus, as environmental contamination levels rise, carriers of risk mutations would be expected to be first impacted, prefiguring effects on the general population. The PINK1/Parkin-mediated mitophagy pathway represents a potential nexus for vulnerability. This pathway performs essential mitochondrial quality control by targeting damaged mitochondria for degradation. PINK1 accumulates on the outer membrane of depolarised mitochondria, recruiting the E3 ubiquitin ligase Parkin, which (poly)ubiquitinates mitochondrial outer membrane proteins, tagging the mitochondria for engulfment by the autophagosome and transport to the lysosome for degradation 30 . A number of the strongest genetic risk factors for PD cluster in genes encoding components of this pathway, including PINK1, PRKN and DJ-1 31 32 . It is believed that impaired mitophagy results in an accumulation of defective mitochondria, leading to excessive ROS production, oxidative stress and an inflammatory response, which contribute to dopaminergic neurotoxicity 31 . Mitophagy is upregulated in response to mitochondrial toxins such as MPP+ and rotenone, and loss-of-function PRKN and PINK1 mutations causing defective mitophagy increase vulnerability to their neurotoxic effects in patient-derived dopaminergic neuronal culture and Drosophila models 33 34 35 . Exposure to MNPs also induces PINK1/Parkin-mediated mitophagy in differentiated dopaminergic neuronal cell culture 36 . We therefore hypothesised that genetic defects in this pathway would increase susceptibility to MNP neurotoxicity. We tested this hypothesis using Drosophila as an in vivo model. Due to its relatively short lifespan and an extensive toolkit for genetic manipulation, this species represents a powerful system to interrogate age-dependent neurodegeneration, the role of the highly conserved PINK1/Parkin pathway in PD 37 , and genetic variance in resistance to environmental toxins associated with PD 38 39 . LOF of the highly conserved Drosophila PRKN homologue parkin ( park ) causes impaired age-related mitophagy 40 and recapitulates key aspects of PD 41 42 . We found that lifetime exposure MNPs in the form of orally ingested polystyrene micro-spheres accelerated dopaminergic neurodegeneration and exacerbated behavioural phenotypes in park LOF flies, at levels tolerated by controls. We conclude that disease-associated mutations can alter susceptibility to MNP neurotoxicity; that environmental MNP pollution may impact the incidence or progression of PD; and that genetic variations in mitophagy may define a group at particular risk from MNP exposure. RESULTS Ingested MNPs enter the brain and induce a cellular stress response in Drosophila We raised and maintained control flies and flies homozygous for the well-characterised park 1 LOF mutation on food contaminated with 100 parts-per-million (ppm) 100 nm-diameter polystyrene nanospheres (hereafter “MNP food”, compared to “std food”). While not faithfully recapitulating the diversity of plastic polymers present in real-world conditions, several studies have reported the effects of similar feeding protocols 43 , 44 , 45 , and found only subtle effects on viability and behaviour. Hence, this condition allowed us to test for increased vulnerability to conditions known to be broadly tolerated by flies with intact mitophagy. Initially, we validated the effects of this feeding protocol in control flies. While extensive evidence demonstrates that MNPs cross the blood-brain-barrier in humans and mammalian models 13 46 , it has been reported that orally-ingested microspheres fail to permeate the Drosophila brain 28 . In contrast, we clearly identified ingested fluorophore-tagged MNPs in the brains of adult flies ( Fig. 1A and Supp. Fig. 1). The difference between our own and prior studies is likely due to the smaller size of the MNPs used herein (0.1 vs 1-5 μM 28 ), which has been demonstrated to affect efficiency of crossing cell membranes 47 . Download figure Open in new tab Figure 1. Orally ingested polystyrene microspheres permeate the brain and activate the JNK stress pathway A. Representative image of a whole ex vivo brain from a 20 d post-eclosure control fly raised on food contaminated with 100ppm fluorophore (540/560)-tagged 0.1 μM polystyrene microspheres. Left: tagged micro-spheres; Centre : DAPI counterstain; Right : merge. Scale bar = 50 μM. B. i. Representative image of a whole ex vivo brain stained with anti-phospho-JNK, from a 20 d post-eclosure control fly raised on ( left ) standard food or ( right ) food contaminated with 100ppm 0.1 μM polystyrene microspheres (MNP). Representative ROI around horizontal mushroom body (MB) lobes is indicated. Scale bar = 50 μM. ii. Quantified anti-phospho-JNK immunofluorescence within horizontal (MB) lobes (two analysed per brain). Comparison is Mann-Whitney test, *P < 0.05. Activation via phosphorylation of the c-Jun N-terminal kinase (JNK) is a primary response to ROS production 48 49 . At 20 d post-eclosure, we observed increased levels of phospho-JNK within the horizontal mushroom body lobes - a neuropil region of the brain which receives dopaminergic input 50 and exhibited robust phosphor-JNK immunofluorescence - in flies raised on MNP food ( Fig. 1B ), confirming that our protocol replicates the extensively reported finding that MNP exposure induces excess ROS production and oxidative stress in a range of model systems 49 51 52 . We did not quantify volume or spatial distribution of MNPs in the brain, but note that MNP localisation does not appear to overlap with regions of high phospho-JNK ( Fig. 1B and Supp. Fig. 1), suggesting a systemic stress response. MNP exposure accelerates degeneration of dopaminergic neurons in park mutants The ∼ 130 dopaminergic neurons in the adult Drosophila brain are well-characterised and readily visualised by immunostaining against the dopamine precursor tyrosine hydroxylase (TH) ( Fig. 2A ) 50 . park LOF causes selective progressive degeneration of the protocerebral posterior lateral 1 (PPL1) subpopulation, while surrounding populations are spared 42 . PPL1 neurons are considered to share homology with dopaminergic neurons of the mammalian substantia nigra pars compacta region 53 , which selectively degenerate in PD and appear particularly susceptible to mitochondrial damage and oxidative stress 54 . As expected 42 , aged (30 d post-eclosure) but not young (3-5 d) park 1 flies raised on std food exhibited an ∼ 20% reduction in TH + cell bodies within the PPL1 cluster. Notably, this trend was exacerbated by lifetime exposure to MNPs ( Fig. 2B,C ), with no cell loss observed in two other distinct TH + subpopulations (Supp. Fig. 2). These data suggest that MNP exposure does not cause widespread neurodegeneration, but instead exacerbates specific phenotypes induced by park LOF. No loss of neurons in any subpopulation was observed in control flies ( Fig. 2B-C , Supp. Fig 2), further supporting the premise that defective Parkin-dependent mitophagy increases susceptibility to MNP neurotoxicity. Download figure Open in new tab Figure 2. Chronic MNP exposure accelerates degeneration of dopaminergic PPL1 neurons in park 1 mutants, at dosages tolerated by controls A. (Top) Schematic showing the position of the protocerebral posterior medial (PPM) 1-3 and protocerebral posterior lateral (PPL) 1-2c clusters of TH + neurons in the adult Drosophila brain, with the degenerating PPL1 cluster highlighted. (Bottom) Representative ex vivo brain (control, std food, 3 d) immunostained with anti-TH (red) against F-actin counterstain (grey). Scale bar = 50 μm. B. Manually counted TH + cell bodies within the PPL1 subpopulation. Grey bars indicate control and blue bars park 1 flies. Empty bars indicate flies raised and maintained on std food; filled bars indicate MNP-containing food. Comparison is 2-way ANOVA, within genotype, with age (young = 3-5 d; aged = 30 d) and diet (std vs MNP-containing food) as factors. *P < , * 0.05, **P < 0.01 C. Representative control and park 1 ex vivo brains immunostained with anti-TH, comparing young (3-5 d) vs aged (30 d) flies, raised on std vs MNP-containing food. Enlarged insets show left PPL1 subpopulation. Scale bars = 50 μm (main), 25 μm (insets). MNPs exacerbate dysfunctional limb kinematics in park mutants The defining clinical characteristic of PD is progressive decline in motor performance 55 , which is recapitulated in park LOF mutant flies 56 . Based on the accelerated rate of dopaminergic neurodegeneration, we hypothesised that lifetime MNP exposure would exacerbate motor decline in park 1 flies. We tested gross movement in response to a mechanical stimulus at 3, 10, 20 and 30d post-eclosure, using a video-tracking method: the Drosophila ARousal Tracking (DART) system 57 58 . As previously reported across a range of assays 59 60 , control flies raised on standard food exhibited an age-dependent decline in motor response. Exposure to MNPs caused a transient increase in response in 10 d old controls, consistent with the MNP-induced hyperactivity reported in a range of model systems 61 62 44 . As expected, park 1 flies exhibited significantly decreased responses at all time points tested; however, MNP exposure caused no significant difference at any age (Supp. Fig 3). We hypothesised that an MNP-induced exacerbation of movement defects might be masked by an opposing tendency towards hyperactivity, or by a ‘floor effect’, whereby aged park 1 flies moved so little that enhancement of the motor phenotype was not apparent. We therefore turned to a more rigorous analysis of locomotor performance, using the Feature Learning Leg Segmentation and Tracking (FLLIT) system 63 58 to analyse limb kinematics in high-speed videos of freely walking flies ( Fig. 3A-B ). First, we identified three gait parameters by which park 1 flies differed from controls. These are: reduced stride length (displacement), reminiscent of the shuffling gait observed in PD 64 ; increased non-linearity of limb movement (derived by normalizing the path moved by a limb during a stride to the distance displaced), indicative of a loss of motor co-ordination; and reduced % of time a limb was moving, indicative of a “plodding gait” with greater pauses between limb movements. Download figure Open in new tab Figure 3. Chronic MNP exposure exacerbates dysfunctional limb kinematics in park 1 mutants, at dosages tolerated by controls A. Schematic showing the function of the Feature Learning-based Limb segmentation and Tracking (FLLIT) system for analysing limb kinematics. B. Representative FLLIT-derived schematics showing overlaid movement of each limb over multiple strides, relative to body center, for control (left) and park 1 3 d old flies. C. Quantification of two FLLIT-derived gait parameters: stride length (displacement) and path/displacement. Data points represent individual limbs, 6 per fly. Comparisons are 2-way ANOVA, within age point, with genotype and diet as factors. *P < 0.05, **P < 0.01, *** P < 0.001, ****P < 0.0001. Testing at 20 d (since by 30 d park 1 flies moved very little), we found that long-term MNP exposure exacerbated the reduced displacement and enhanced non-linearity of movement in park 1 flies, with no effect on controls ( Fig. 3C ). The effect on movement % was more complex. Young park 1 exposed to MNPs exhibited an increased movement % relative to those raised on standard food, with controls showing a similar, albeit non-significant, trend (p = 0.08). By 20 d, however, MNP-exposed control flies exhibited increased movement % relative to those raised on standard food, while the effect had disappeared in park 1 flies (Supp. Fig. 4). We conclude that MNP exposure indeed causes hyperactivity, manifesting here as more rapid limb movements while walking, while simultaneously exacerbating the park 1 phenotype of a slower, plodding gait. Thus, park 1 flies are affected in a qualitatively different manner to controls; first, hyperactivity becomes apparent after shorter periods of exposure due to their enhanced susceptibility to the neurotoxic effects of MNPs, then by the time hyperactivity manifests in controls, the effect is masked by exacerbation of the opposing phenotype of a reduction in movement %. MNP exposure exacerbates night sleep loss in park 1 mutants Sleep dysfunction is increasingly recognised as a feature of PD, both as a primary symptom affecting quality of life, and as a predictor of and potential factor contributing to disease progression 65 . In Drosophila , park LOF causes circadian abnormalities and sleep disturbance 66 67 . We interrogated the effect of MNP exposure on this phenotype using 5H Drosophila A ctivity M onitors (DAM5H) ( Fig. 4A ), a multi-infrared beam system that facilitates high-resolution measures of sleep and activity in Drosophila 68 . While we clearly saw an effect of park 1 on both day and night sleep ( Fig. 4A ), we focused on the previously published phenotype of reduced night sleep 66 . Strikingly, in park 1 flies, MNP exposure caused a further reduction in night sleep levels by 20 d, with no significant effect observed in control flies ( Fig. 4A, B ). Download figure Open in new tab Figure 4. Chronic MNP exposure exacerbates night sleep loss in park 1 mutants, at dosages tolerated by controls A. (Left) Schematic showing function of the DAM5 system. (Right) Mean sleep in 12L: 12D conditions of young (5-7 d) and aged (20 d) park 1 and control flies, raised on standard or MNP food. B. Night sleep, as the fraction of time from ZT12-24 (lights-off) spent asleep. Data points represent individual flies. Comparisons are 2-way ANOVA, within age point, with genotype and diet as factors. *P < 0.05, *** P < 0.001, ****P < 0.0001. Collectively, the above data demonstrate a detrimental and genotype-specific impact of chronic MNP on disease-relevant phenotypes in a well-characterized Drosophila model of PD. DISCUSSION MNP pollution is now ubiquitous in the environment, and bioaccumulation in the human brain, together with a wealth of evidence of cytotoxic effects from in vitro and in vivo models, raise the possibility that chronic exposure could cause or contribute to neurological disease 6 , 7 . Understanding how this environmental factor interacts with underlying genetic vulnerabilities can therefore help delineate the scale of the problem and identify populations at specific risk. Together, the data presented herein demonstrate that chronic MNP exposure exacerbates degenerative, motor, and non-motor PD-like phenotypes in an established invertebrate model of PRKN -linked PD. We conclude that disease-associated mutations can modify susceptibility to the neurotoxic effects of MNP exposure, that genetic defects in mitophagy may define a subpopulation at particular risk, and that research into MNP pollution as an environmental factor potentially impacting rising rates of PD 5 is warranted. Here, we focused on PD, on the basis that the potential of environmental factors to contribute to PD-like phenotypes is well-established 3 69 ; that mitotoxic effects of MNP exposure 15 overlap with the mechanism of action of pesticides associated with PD-like phenotypes 22 70 ; and that chronic exposure has been reported to induce dopaminergic neurodegeneration in model systems 23 24 25 . However, the effects of MNP exposure – such as mitochondrial dysfunction, oxidative stress and neuroinflammation 15 – overlap with a cellular mechanisms contributing to a range of neurodegenerative and neurodevelopmental disorders 71 72 73 . Thus, the contribution of plastic pollution to a much wider range of neurological health outcomes should be considered. Here we focused on PD-associated defects in PINK1/Parkin-dependent mitophagy as a genetic risk factor. However, the cellular effects of MNP exposure are widespread, and a large number of mutations affecting a range of cellular processes increase risk for PD 74 , so genetic defects in mitophagy are likely not to be unique in increasing susceptibility to MNP exposure is unclear. Further, our interpretation that park 1 flies’ increased vulnerability to MNPs is due to defective mitophagy is based on extensive published data on the effects of MNP exposure 15 , Parkin LOF 40 , and the interaction between Parkin LOF and exposure to mitochondrial toxicants 35 75 , but is not explicitly demonstrated here. Further work could directly interrogate the molecular mechanisms underlying the interaction between Parkin LOF and MNP toxicity by directly measuring rates of mitophagy, ROS production and accumulation of abnormal mitochondria, and/or strengthen the genetic evidence associating mitophagy with resistance to MNP neurotoxicity by testing whether LOF of other components of the PINK1/Parkin-dependent mitophagy pathway similarly increased vulnerability to MNP exposure 37 32 . Furthermore, while we demonstrate that MNPs permeated the brain, we did not interrogate the extent to which neuronal effects were attributable to MNPs within the brain versus elsewhere in the body, for example via the gut-brain axis 76 45 . These limitations can be addressed through further studies that build upon the data presented in this work. MNPs levels are difficult to assess, due to challenges in direct measurement 77 huge range of particle size and type, geographical differences, and changes over time 78 79 80 , leading to a large range of estimates in levels in relevant sources of absorption 81 . The concentrations used in this study are likely to be significantly higher than those most of the global population are currently exposed to. In other ways, however, this feeding protocol may underestimate toxicity; it does not recapitulate the full range of MNP absorption routes 82 , particle sizes 47 and shapes 83 , or potentially additive interactions with other environmental contaminants 84 present in real-world conditions. Further, since MNPs bioaccumulate in brain tissue over time 13 , short-lived organisms such as Drosophila may be expected to tolerate higher levels of pollutions than humans. Thus, while we demonstrate a clear interaction between a PD genetic risk factor and exposure to MNPs, further work is required to interrogate the effects in more ecologically relevant conditions. MATERIALS AND METHODS Experimental models and MNP exposure conditions Experimental models were fruit flies of the species Drosophila melanogaster . Flies were maintained on standard fly food under 12 h: 12 h light-dark cycles (12L: 12D) at a constant 25°C. Experiments were conducted at the age indicated, on male flies. Genotypes used were park 1 (Bloomington Drosophila Stock Centre stock number 34747) and the isogenised w 1118 control line iso 31 (a kind gift from Prof. Kyunghee Koh, Thomas Jefferson University). Flies were raised on a standard food medium. MNP food was generated by mixing 0.1 μM-diameter Opti-Bind polystyrene microparticles (ThermoFisher) to a concentration of 100pp into melted fly food. For visualisation, fluorophore-tagged 0.1 μM-diameter polystyrene FluoSpheres (excitation/emission 540/560) (ThermoFisher) were substituted. Immuno-histochemistry Brains were dissected in phosphate-buffered saline (PBS) (Sigma Aldrich) at the time point indicated and immuno-stained as described previously 85 . Briefly, brains were fixed by 20 min room temperature incubation in 4% paraformaldehyde (MP biomedicals) and blocked for 1 h in 5% normal goat serum in PBS + 0.3% Triton-X (Sigma-Aldrich) (PBT). Brains were incubated overnight in primary antibody at 4°C, washed three times in PBT and incubated overnight in secondary antibody at 4°C, then washed a final time before mounting in SlowFade Gold anti-fade mountant (ThermoFisher). Primary antibodies were rabbit anti-TH/tyrosine hydroxylase (Abcam, ab128249; 1:500) and rabbit anti-phospho-JNK1/JNK2 (Thr183, Tyr185) (ThermoFisher MA5-14943; 1:500). Secondary antibody was goat anti-mouse AlexaFluor 647 at 1:1000 (ThermoFisher). Images were taken with a Zeiss LSM 980 confocal microscope with an EC ‘Plan-Neofluar’ 20x/0.50 M27 air objective, taking z-stacks through the entire brain with step sizes of 1-2 μm. Images were visualised and analysed using ImageJ. TH+ cells were manually counted. For fluorescence quantification, z-stacks of the whole brain were 3D-projected using a maximum intensity projection. From these whole-brain stacks, ROIs were drawn around the horizontal mushroom body lobes, an axonal/synaptic neuropil region receiving dopaminergic input. Mean fluorescence values were taken with background subtracted. Brains compared were dissected, stained and imaged in parallel. Locomotor and sleep analysis DAM Sleep analysis was performed using the Drosophila Activity Monitor 5 system (DAM5H, Trikinetics inc., MA, USA), which improves on the fidelity of the earlier DAM2 system by using 15 infrared beams per tube, rather than a single one, to track movement 68 . Male flies of the age indicated were loaded into glass behavioural tubes (Trikinetics inc., MA, USA) containing 4% sucrose and 2% agar and left for two full days to acclimatise. On the third day the number of beam breaks was measured using Drosophila Activity Monitor. Sleep was defined using the standard definition of >5 min of inactivity, which has been shown to correlate with postural changes, increased arousal threshold and altered brain activity patterns 68 . Sleep bout number and duration were analysed using the open-source software suite phaseR ( https://github.com/abhilashlakshman/phaseR/tree/main ) 86 . DART As above, flies were loaded into behavioural tubes with flies. After 24 h acclimatisation, a single stimulus in the form of a mechanical vibration (a train of five 200 ms pulses separated by 800 ms intervals, set at the DART system’s maximum intensity) was delivered at Zeitgeber Time (ZT) 3. Locomotor activity was recorded using the Drosophila ARousal Tracking (DART) system (BFKlabs) 57 as previously described 58 . Videos were taken using a USB webcam (Logitech) and speed (mm / s) was analysed by the DART system from absolute position, and binned in 1 min intervals. Flies were excluded from analysis if they exceeded an average of 1 mm / s speed in the five 1 min bins preceding the stimulus. The mean speed (mm / s) in the 1 min bin following the stimulus was analysed. FLLIT For FLLIT (Feature Learning-based LImb segmentation and Tracking) measurements, de-winged male flies were loaded into custom-made 2x2 cm arenas without anaesthesia. 500 fps videos consisting of flies walking in a straight line and taking at least three clear strides were taken using a Photron FASTCAM Mini UX50 High Speed Camera with a Sigma 105 mm Macro lens. Gait analysis was performed using the FLLIT system 63 , as previously described 58 . Where FLLIT generates data for parameters per stride, the first and last stride were excluded and a mean of the remaining values taken. Values for each leg were pooled, giving six values per fly. Definitions of the parameters used are as follows. Stride length : Straight-line distance between the posterior and anterior extreme positions of the limb in each stride. Directly output by FLLIT as “Displacement”. Path / displacement : Path Travelled (directly output by FLLIT) is the total actual distance covered by a limb during a stride; this is divided by Stride Displacement to compensate for differences in stride length. Larger values indicate greater deviation from an optimal straight-line path. Movement % : % of the video for which a given limb is in motion. Quantification and statistical analysis Statistical analyses were performed using Graphpad Prism. Data sets were tested for normal distributions using the Shapiro-Wilk test. Normally distributed data sets were tested for statistical differences using unpaired t-tests with Welch’s correction for non-identical variance, and non-normally distributed data sets were tested using Mann-Whitney U-test. Interactions between genotype and age/food type were analysed using 2-way ANOVA with Sidak’s correction for multiple comparisons. AUTHOR CONTRIBUTIONS S.A.L – Conceptualization, Methodology, Investigation, Writing - Original Draft, Writing – Review & Editing, Visualization, Funding acquisition; J.E.C.J – Writing – Review & Editing, Supervision, Project administration, Funding acquisition. DECLARATION OF INTERESTS The authors declare no competing interests. SUPPLEMENTARY FIGURE LEGENDS Supplementary Fig. 1. Two representative whole ex vivo brains of 20 d post-eclosure control flies raised on food contaminated with 100ppm fluorophore (540/560)-tagged 0.1 μM polystyrene microspheres. Arrows indicate accumulations of MNPs. Scale bar = 50 μM. Note: left image is also shown in Fig. 1A . Supplementary Fig. 2. A-B. Manually counted TH + cell bodies within the PPLM1+2 ( A ) and PPM3 ( B ) subpopulations. Grey bars indicate control and blue bars park 1 flies. Empty bars indicate flies were raised and maintained on std food; filled bars indicate MNP-containing food. Comparisons are 2-way ANOVA, within genotype, with age (young = 3-5 d; aged = 30 d) and diet (std vs MNP-containing food) as factors. *P < 0.05. Supplementary Fig. 3. A. Schematic showing the use of the Drosophila ARousal Tracking (DART) system to assay stimulus-dependent locomotion. B. Traces showing average speed (mm / s) over time in 1 min bins for control and park 1 10 d old flies, in standard vs MNP food, in response to a mechanical stimulus occurring at 10 mins. C. Age-dependent change in motor performance. Quantification of mean speed in the 1 min bin immediately following mechanical stimulus, at 4 age points. N values indicated on graph, referring to number of animals. Comparisons are 2-way ANOVA, within genotype, with age (3, 10, 20 and 30d post-eclosure) and diet (std vs MNP-containing food) as factors. **P < 0.01. Supplementary Fig. 4. Quantification of the FLLIT-derived gait parameter movement %. Data points represent individual limbs, 6 per fly. Comparisons are 2-way ANOVA, within age point, with genotype and diet as factors. *P < 0.05, **P < 0.01, *** P < 0.001, ****P < 0.0001. ACKNOWLEDGEMENTS This study was funded by a MRC Senior Non-Clinical Fellowship (MR/V03118X/1) to J.E.C.J, a BBSRC Project Grant (BB/X00094X/1) to S.L and J.E.C.J. Funder Information Declared Medical Research Council, https://ror.org/03x94j517 , MR/V03118X/1 Biotechnology and Biological Sciences Research Council , BB/X00094X/1 Footnotes Updated version; author affiliations have been corrected. REFERENCES 1. ↵ Sisodiya , S. M. et al. Climate change and disorders of the nervous system . The Lancet Neurology 23 , 636 – 648 ( 2024 ). OpenUrl PubMed 2. ↵ Hooper , L. G. & Kaufman , J. D . Ambient Air Pollution and Clinical Implications for Susceptible Populations . Ann Am Thorac Soc 15 , S64 – S68 ( 2018 ). OpenUrl CrossRef PubMed 3. ↵ Atterling Brolin , K ., et al. Environmental Risk Factors for Parkinson’s Disease: A Critical Review and Policy Implications . Movement Disorders 40 , 204 – 221 ( 2025 ). OpenUrl PubMed 4. ↵ Feigin , V. L. et al. The global burden of neurological disorders: translating evidence into policy . Lancet Neurol 19 , 255 – 265 ( 2020 ). OpenUrl CrossRef PubMed 5. ↵ Su , D. et al. Projections for prevalence of Parkinson’s disease and its driving factors in 195 countries and territories to 2050: modelling study of Global Burden of Disease Study 2021 . BMJ 388 , e080952 ( 2025 ). OpenUrl Abstract / FREE Full Text 6. ↵ Landrigan , P. J. et al. The Lancet Countdown on health and plastics . The Lancet 0 , ( 2025 ). 7. ↵ Zheng , Y. , Xu , S. , Liu , J. & Liu , Z . The effects of micro- and nanoplastics on the central nervous system: A new threat to humanity? Toxicology 504 , 153799 ( 2024 ). OpenUrl PubMed 8. ↵ Gao , H.-T. et al. From exposure to neurotoxicity induced by micro-nanoplastics with brain accumulation and cognitive decline . Ecotoxicology and Environmental Safety 304 , 119114 ( 2025 ). OpenUrl PubMed 9. ↵ Wang , C. , Zhao , J. & Xing , B . Environmental source, fate, and toxicity of microplastics . Journal of Hazardous Materials 407 , 124357 ( 2021 ). OpenUrl CrossRef PubMed 10. ↵ Houssini , K. , Li , J. & Tan , Q . Complexities of the global plastics supply chain revealed in a trade-linked material flow analysis . Commun Earth Environ 6 , 257 ( 2025 ). OpenUrl 11. ↵ Saeedi , M . How microplastics interact with food chain: a short overview of fate and impacts . J Food Sci Technol 61 , 1 – 11 ( 2023 ). OpenUrl 12. ↵ Roslan , N. S. et al. Detection of microplastics in human tissues and organs: A scoping review . J Glob Health 14 , 04179 . 13. ↵ Nihart , A. J. et al. Bioaccumulation of microplastics in decedent human brains . Nat Med 1 – 6 ( 2025 ) doi: 10.1038/s41591-024-03453-1 . OpenUrl CrossRef 14. ↵ Ragusa , A. et al. Plasticenta: First evidence of microplastics in human placenta . Environ Int 146 , 106274 ( 2021 ). OpenUrl CrossRef PubMed 15. ↵ Lee , S. E. , Yi , Y. , Moon , S. , Yoon , H. & Park , Y. S . Impact of Micro- and Nanoplastics on Mitochondria . Metabolites 12 , 897 ( 2022 ). OpenUrl PubMed 16. ↵ Huang , Y. et al. Polystyrene nanoplastic exposure induces excessive mitophagy by activating AMPK/ULK1 pathway in differentiated SH-SY5Y cells and dopaminergic neurons in vivo . Particle and Fibre Toxicology 20 , 44 ( 2023 ). OpenUrl 17. ↵ Das , A . The emerging role of microplastics in systemic toxicity: Involvement of reactive oxygen species (ROS) . Science of The Total Environment 895 , 165076 ( 2023 ). OpenUrl PubMed 18. ↵ Gautam , R. et al. Evaluation of potential toxicity of polyethylene microplastics on human derived cell lines . Sci Total Environ 838 , 156089 ( 2022 ). OpenUrl PubMed 19. ↵ Beal , M. F . Mitochondria, oxidative damage, and inflammation in Parkinson’s disease . Ann N Y Acad Sci 991 , 120 – 131 ( 2003 ). OpenUrl CrossRef PubMed Web of Science 20. ↵ Wimalasena , K . The inherent high vulnerability of dopaminergic neurons toward mitochondrial toxins may contribute to the etiology of Parkinson’s disease . Neural Regen Res 11 , 246 – 247 ( 2016 ). OpenUrl PubMed 21. ↵ Lüth , T. et al. Longitudinal assessment of the association between pesticide exposure and lifestyle with Parkinson’s disease motor severity . NPJ Parkinsons Dis 11 , 164 ( 2025 ). OpenUrl PubMed 22. ↵ Utyasheva , L. , Amarasinghe , P. & Eddleston , M . Paraquat at 63—the story of a controversial herbicide and its regulations: It is time to put people and public health first when regulating paraquat . BMC Public Health 25 , 3089 ( 2025 ). OpenUrl PubMed 23. ↵ Polystyrene nanoplastics trigger pyroptosis in dopaminergic neurons through TSC2/TFEB-mediated disruption of autophagosome-lysosome fusion in Parkinson’s disease | Journal of Translational Medicine | Full Text. https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-025-06634-9 . 24. ↵ Liang , B. et al. Brain single-nucleus transcriptomics highlights that polystyrene nanoplastics potentially induce Parkinson’s disease-like neurodegeneration by causing energy metabolism disorders in mice . Journal of Hazardous Materials 430 , 128459 ( 2022 ). OpenUrl CrossRef PubMed 25. ↵ Jeong , H. et al. Nanoplastics Cause an Increased Risk of Parkinson’s Disease Compared to Microplastics at Environmental Exposure Levels . Journal of Hazardous Materials Advances 100941 ( 2025 ) doi: 10.1016/j.hazadv.2025.100941 . OpenUrl CrossRef 26. ↵ Wang , G. , Lin , Y. & Shen , H . Exposure to Polystyrene Microplastics Promotes the Progression of Cognitive Impairment in Alzheimer’s Disease: Association with Induction of Microglial Pyroptosis . Mol Neurobiol 61 , 900 – 907 ( 2024 ). OpenUrl CrossRef PubMed 27. ↵ Gaspar , L. , Bartman , S. , Coppotelli , G. & Ross , J. M . Acute Exposure to Microplastics Induced Changes in Behavior and Inflammation in Young and Old Mice . Int J Mol Sci 24 , 12308 ( 2023 ). OpenUrl PubMed 28. ↵ Yan , W. et al. Microplastic exposure disturbs sleep structure, reduces lifespan, and decreases ovary size in Drosophila melanogaster . zr 45 , 805 – 820 ( 2024 ). OpenUrl PubMed 29. ↵ Kong , F. , Jin , H. , Xu , Y. & Shen , J . Behavioral toxicological tracking analysis of Drosophila larvae exposed to polystyrene microplastics based on machine learning . Journal of Environmental Management 359 , 120975 ( 2024 ). OpenUrl PubMed 30. ↵ Ashrafi , G. & Schwarz , T. L . The pathways of mitophagy for quality control and clearance of mitochondria . Cell Death Differ 20 , 31 – 42 ( 2013 ). OpenUrl CrossRef PubMed Web of Science 31. ↵ Pickrell , A. M. & Youle , R. J . The Roles of PINK1, Parkin and Mitochondrial Fidelity in Parkinson’s Disease . Neuron 85 , 257 – 273 ( 2015 ). OpenUrl CrossRef PubMed 32. ↵ Imberechts , D. et al. DJ-1 is an essential downstream mediator in PINK1/parkin-dependent mitophagy . Brain 145 , 4368 – 4384 ( 2022 ). OpenUrl CrossRef PubMed 33. ↵ Chung , S. Y. et al. Parkin and PINK1 Patient iPSC-Derived Midbrain Dopamine Neurons Exhibit Mitochondrial Dysfunction and α-Synuclein Accumulation . Stem Cell Reports 7 , 664 – 677 ( 2016 ). OpenUrl PubMed 34. ↵ Schwartzentruber , A. et al. Oxidative switch drives mitophagy defects in dopaminergic parkin mutant patient neurons . Sci Rep 10 , 15485 ( 2020 ). OpenUrl CrossRef PubMed 35. ↵ Wang , C. et al. Drosophila Overexpressing Parkin R275W Mutant Exhibits Dopaminergic Neuron Degeneration and Mitochondrial Abnormalities . J Neurosci 27 , 8563 – 8570 ( 2007 ). OpenUrl Abstract / FREE Full Text 36. ↵ Liu , T. , Hou , B. , Wang , Z. & Yang , Y . Polystyrene microplastics induce mitochondrial damage in mouse GC-2 cells . Ecotoxicology and Environmental Safety 237 , 113520 ( 2022 ). OpenUrl PubMed 37. ↵ Clark , I. E. et al. Drosophila pink1 is required for mitochondrial function and interacts genetically with parkin . Nature 441 , 1162 – 1166 ( 2006 ). OpenUrl CrossRef PubMed Web of Science 38. ↵ Villalobos-Cantor , S. , Arreola-Bustos , A. & Martin , I . Genetic basis of maneb-induced dopaminergic neurodegeneration in Drosophila . G3 Genes|Genomes|Genetics 15 , jkaf159 ( 2025 ). OpenUrl 39. ↵ Villalobos-Cantor , S. , Arreola-Bustos , A. & Martin , I . Genome-wide analysis reveals genes mediating resistance to paraquat neurodegeneration in Drosophila . Genetics 230 , iyaf087 ( 2025 ). OpenUrl PubMed 40. ↵ Cornelissen , T. et al. Deficiency of parkin and PINK1 impairs age-dependent mitophagy in Drosophila . eLife 7 , e35878 ( 2018 ). OpenUrl PubMed 41. ↵ Cackovic , J. et al. Vulnerable Parkin Loss-of-Function Drosophila Dopaminergic Neurons Have Advanced Mitochondrial Aging, Mitochondrial Network Loss and Transiently Reduced Autophagosome Recruitment . Front. Cell. Neurosci . 12 , ( 2018 ). 42. ↵ Whitworth , A. J. et al. Increased glutathione S-transferase activity rescues dopaminergic neuron loss in a Drosophila model of Parkinson’s disease . Proceedings of the National Academy of Sciences 102 , 8024 – 8029 ( 2005 ). OpenUrl Abstract / FREE Full Text 43. ↵ Aloisi , M. et al. Plastic Fly: What Drosophila melanogaster Can Tell Us about the Biological Effects and the Carcinogenic Potential of Nanopolystyrene . Int J Mol Sci 25 , 7965 ( 2024 ). OpenUrl PubMed 44. ↵ Matthews , S. et al. Polystyrene micro- and nanoplastics affect locomotion and daily activity of Drosophila melanogaster . Environ. Sci.: Nano 8 , 110 – 121 ( 2021 ). OpenUrl CrossRef 45. ↵ Zhang , Y. , Wolosker , M. B. , Zhao , Y. , Ren , H. & Lemos , B . Exposure to microplastics cause gut damage, locomotor dysfunction, epigenetic silencing, and aggravate cadmium (Cd) toxicity in Drosophila . Science of The Total Environment 744 , 140979 ( 2020 ). OpenUrl CrossRef PubMed 46. ↵ Shan , S. , Zhang , Y. , Zhao , H. , Zeng , T. & Zhao , X . Polystyrene nanoplastics penetrate across the blood-brain barrier and induce activation of microglia in the brain of mice . Chemosphere 298 , 134261 ( 2022 ). OpenUrl CrossRef PubMed 47. ↵ Choi , H. et al. Size-Dependent Internalization of Microplastics and Nanoplastics Using In Vitro Model of the Human Intestine—Contribution of Each Cell in the Tri-Culture Models . Nanomaterials (Basel ) 14 , 1435 ( 2024 ). OpenUrl PubMed 48. ↵ Ugbode , C. et al. JNK signalling regulates antioxidant responses in neurons . Redox Biol 37 , 101712 ( 2020 ). OpenUrl PubMed 49. ↵ Zhang , Y. & Chen , F . Reactive Oxygen Species (ROS), Troublemakers between Nuclear Factor-κB (NF-κB) and c-Jun NH2-terminal Kinase (JNK) . Cancer Res 64 , 1902 – 1905 ( 2004 ). OpenUrl Abstract / FREE Full Text 50. ↵ Mao , Z. & Davis , R. L . Eight Different Types of Dopaminergic Neurons Innervate the Drosophila Mushroom Body Neuropil: Anatomical and Physiological Heterogeneity . Front Neural Circuits 3 , 5 ( 2009 ). OpenUrl CrossRef PubMed 51. ↵ Qiao , R. et al. Microplastics induce intestinal inflammation, oxidative stress, and disorders of metabolome and microbiome in zebrafish . Science of The Total Environment 662 , 246 – 253 ( 2019 ). OpenUrl PubMed 52. ↵ Chen , Y. et al. Polystyrene nanoplastics exposure induces cognitive impairment in mice via induction of oxidative stress and ERK/MAPK-mediated neuronal cuproptosis . Part Fibre Toxicol 22 , 13 ( 2025 ). OpenUrl CrossRef PubMed 53. ↵ Strausfeld , N. J. & Hirth , F . Deep Homology of Arthropod Central Complex and Vertebrate Basal Ganglia . Science 340 , 157 – 161 ( 2013 ). OpenUrl Abstract / FREE Full Text 54. ↵ Ni , A. & Ernst , C . Evidence That Substantia Nigra Pars Compacta Dopaminergic Neurons Are Selectively Vulnerable to Oxidative Stress Because They Are Highly Metabolically Active . Front. Cell. Neurosci . 16 , ( 2022 ). 55. ↵ Armstrong , M. J. & Okun , M. S . Diagnosis and Treatment of Parkinson Disease: A Review . JAMA 323 , 548 – 560 ( 2020 ). OpenUrl CrossRef PubMed 56. ↵ Greene , J. C. et al. Mitochondrial pathology and apoptotic muscle degeneration in Drosophila parkin mutants . Proceedings of the National Academy of Sciences 100 , 4078 – 4083 ( 2003 ). OpenUrl Abstract / FREE Full Text 57. ↵ Faville , R. , Kottler , B. , Goodhill , G. J. , Shaw , P. J. & van Swinderen , B . How deeply does your mutant sleep? Probing arousal to better understand sleep defects in Drosophila . Sci Rep 5 , 8454 ( 2015 ). OpenUrl CrossRef PubMed 58. ↵ Lowe , S. A. et al. Modulation of a critical period for motor development in Drosophila by BK potassium channels . Current Biology 34 , 3488 – 3505.e3 ( 2024 ). OpenUrl CrossRef PubMed 59. ↵ Iliadi , K. G. & Boulianne , G. L . Age-related behavioral changes in Drosophila . Annals of the New York Academy of Sciences 1197 , 9 – 18 ( 2010 ). OpenUrl CrossRef PubMed 60. ↵ Lowe , S. A. , Usowicz , M. M. & Hodge , J. J. L . Neuronal overexpression of Alzheimer’s disease and Down’s syndrome associated DYRK1A/minibrain gene alters motor decline, neurodegeneration and synaptic plasticity in Drosophila . Neurobiology of Disease 125 , 107 – 114 ( 2019 ). OpenUrl CrossRef PubMed 61. ↵ Chen , Q. et al. Microplastics Lead to Hyperactive Swimming Behaviour in Adult Zebrafish . Aquat Toxicol 224 , 105521 ( 2020 ). OpenUrl PubMed 62. ↵ Vignon , A. N. et al. Lifelong exposure to polystyrene-nanoplastics induces an attention-deficit hyperactivity disorder-like phenotype and impairs brain aging in mice . Journal of Hazardous Materials 494 , 138640 ( 2025 ). OpenUrl PubMed 63. ↵ Banerjee , A. , Wu , S. , Cheng , L. & Aw , S. S . Fully Automated Leg Tracking in Freely Moving Insects using Feature Learning Leg Segmentation and Tracking (FLLIT) . J Vis Exp https://doi.org/10.3791/61012 ( 2020 ) doi: 10.3791/61012 . OpenUrl CrossRef 64. ↵ Creaby , M. W. & Cole , M. H . Gait characteristics and falls in Parkinson’s disease: A systematic review and meta-analysis . Parkinsonism & Related Disorders 57 , 1 – 8 ( 2018 ). OpenUrl PubMed 65. ↵ Stefani , A. & Högl , B . Sleep in Parkinson’s disease . Neuropsychopharmacol . 45 , 121 – 128 ( 2020 ). OpenUrl CrossRef PubMed 66. ↵ Doktór , B. , Damulewicz , M. & Pyza , E . Effects of MUL1 and PARKIN on the circadian clock, brain and behaviour in Drosophila Parkinson’s disease models . BMC Neuroscience 20 , 24 ( 2019 ). 67. ↵ Julienne , H. , Buhl , E. , Leslie , D. S. & Hodge , J. J. L . Drosophila PINK1 and parkin loss-of-function mutants display a range of non-motor Parkinson’s disease phenotypes . Neurobiol Dis 104 , 15 – 23 ( 2017 ). OpenUrl CrossRef PubMed 68. ↵ Sitaraman , D. , Vecsey , C. G. & Koochagian , C . Activity Monitoring for Analysis of Sleep in Drosophila melanogaster . Cold Spring Harb Protoc 2024 , pdb.top108095 ( 2024 ). OpenUrl Abstract / FREE Full Text 69. ↵ Dorsey , E. R. & Bloem , B. R . Parkinson’s Disease Is Predominantly an Environmental Disease . J Parkinsons Dis 14 , 451 – 465 . 70. ↵ Uversky , V. N . Neurotoxicant-induced animal models of Parkinson’s disease: understanding the role of rotenone, maneb and paraquat in neurodegeneration . Cell Tissue Res 318 , 225 – 241 ( 2004 ). OpenUrl CrossRef PubMed Web of Science 71. ↵ Qin , P. , Sun , Y. & Li , L . Mitochondrial dysfunction in chronic neuroinflammatory diseases (Review) . Int J Mol Med 53 , 47 ( 2024 ). OpenUrl PubMed 72. ↵ Chen , Y. , Zhou , Z. & Min , W. Mitochondria, Oxidative Stress and Innate Immunity . Front. Physiol. 9 , ( 2018 ). 73. ↵ Dash , U. C. et al. Oxidative stress and inflammation in the pathogenesis of neurological disorders: Mechanisms and implications . Acta Pharmaceutica Sinica B https://doi.org/10.1016/j.apsb.2024.10.004 ( 2024 ) doi: 10.1016/j.apsb.2024.10.004 . OpenUrl CrossRef PubMed 74. ↵ Nalls , M. A. et al. Identification of novel risk loci, causal insights, and heritable risk for Parkinson’s disease: a meta-analysis of genome-wide association studies . The Lancet Neurology 18 , 1091 – 1102 ( 2019 ). OpenUrl CrossRef PubMed 75. ↵ Pesah , Y. et al. Drosophila parkin mutants have decreased mass and cell size and increased sensitivity to oxygen radical stress . Development 131 , 2183 – 2194 ( 2004 ). OpenUrl Abstract / FREE Full Text 76. ↵ Sofield , C. E. , Anderton , R. S. & Gorecki , A. M . Mind over Microplastics: Exploring Microplastic-Induced Gut Disruption and Gut-Brain-Axis Consequences . Curr Issues Mol Biol 46 , 4186 – 4202 ( 2024 ). OpenUrl CrossRef PubMed 77. ↵ A. Monikh , F. , et al. Challenges in studying microplastics in human brain . Nat Med 1 – 2 ( 2025 ) doi: 10.1038/s41591-025-04045-3 . OpenUrl CrossRef 78. ↵ Gimiliani , G. T. & Izar , G . Difficulties in Comparison Among Different Microplastic Studies: The Inconsistency of Results and Lack of Guide Values . Environmental Toxicology and Chemistry 41 , 820 – 821 ( 2022 ). OpenUrl 79. ↵ Lamichhane , G. et al. Microplastics in environment: global concern, challenges, and controlling measures . Int. J. Environ. Sci. Technol . 20 , 4673 – 4694 ( 2023 ). OpenUrl 80. ↵ Zhao , X. & You , F . Microplastic Human Dietary Uptake from 1990 to 2018 Grew across 109 Major Developing and Industrialized Countries but Can Be Halved by Plastic Debris Removal . Environ. Sci. Technol . 58 , 8709 – 8723 ( 2024 ). OpenUrl PubMed 81. ↵ Mason , S. A. , Welch , V. G. & Neratko , J . Synthetic Polymer Contamination in Bottled Water . Front Chem 6 , 407 ( 2018 ). OpenUrl PubMed 82. ↵ Enyoh , C. E. et al. Microplastics Exposure Routes and Toxicity Studies to Ecosystems: An Overview . Environ Anal Health Toxicol 35 , e2020004 ( 2020 ). OpenUrl 83. ↵ Martin , L. M. A. , Gan , N. , Wang , E. , Merrill , M. & Xu , W. Materials, Surfaces, and Interfacial Phenomena in Nanoplastics Toxicology Research . Environ Pollut 292 , 118442 ( 2022 ). OpenUrl PubMed 84. ↵ Yu , F. et al. Interaction of microplastics with perfluoroalkyl and polyfluoroalkyl substances in water: A review of the fate, mechanisms and toxicity . Science of The Total Environment 948 , 175000 ( 2024 ). OpenUrl PubMed 85. ↵ Deneubourg , C. et al. Epg5 links proteotoxic stress due to defective autophagic clearance and epileptogenesis in Drosophila and Vici syndrome patients . Autophagy 1 – 13 ( 2024 ) doi: 10.1080/15548627.2024.2405956 . OpenUrl CrossRef PubMed 86. ↵ Persons , J. L. et al. PHASE: An Open-Source Program for the Analysis of DrosophilaPhase, Activity, and Sleep Under Entrainment . J Biol Rhythms 37 , 455 – 467 ( 2022 ). OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted November 18, 2025. Download PDF Supplementary Material Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Micro-/nano-plastics accentuate Parkinson’s Disease-relevant phenotypes in a Drosophila model Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Micro-/nano-plastics accentuate Parkinson’s Disease-relevant phenotypes in a Drosophila model Simon A. Lowe , James E.C. Jepson bioRxiv 2025.11.17.688805; doi: https://doi.org/10.1101/2025.11.17.688805 Share This Article: Copy Citation Tools Micro-/nano-plastics accentuate Parkinson’s Disease-relevant phenotypes in a Drosophila model Simon A. Lowe , James E.C. Jepson bioRxiv 2025.11.17.688805; doi: https://doi.org/10.1101/2025.11.17.688805 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Neuroscience Subject Areas All Articles Animal Behavior and Cognition (7622) Biochemistry (17648) Bioengineering (13870) Bioinformatics (41880) Biophysics (21423) Cancer Biology (18553) Cell Biology (25458) Clinical Trials (138) Developmental Biology (13364) Ecology (19866) Epidemiology (2067) Evolutionary Biology (24290) Genetics (15589) Genomics (22475) Immunology (17711) Microbiology (40326) Molecular Biology (17145) Neuroscience (88471) Paleontology (666) Pathology (2826) Pharmacology and Toxicology (4815) Physiology (7635) Plant Biology (15114) Scientific Communication and Education (2044) Synthetic Biology (4286) Systems Biology (9815) Zoology (2268)