Characterisation of LAMP1- and LAMP2A-positive organelles in neurons

Characterisation of LAMP1- and LAMP2A-positive organelles in neurons | 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 Characterisation of LAMP1- and LAMP2A-positive organelles in neurons View ORCID Profile Reem Abouward , View ORCID Profile Alya Masoud Abdelhafid , View ORCID Profile Oscar G Wilkins , View ORCID Profile Song-Yi Lee , View ORCID Profile Fairouz Ibrahim , View ORCID Profile Mark Skehel , View ORCID Profile Alice Ting , View ORCID Profile Nicol Birsa , View ORCID Profile Jernej Ule , View ORCID Profile Giampietro Schiavo doi: https://doi.org/10.1101/2025.09.17.676809 Reem Abouward 1 Department of Neuromuscular Diseases and UCL Queen Square Motor Neuron Disease Centre, UCL Queen Square Institute of Neurology, University College London , London WC1N 3BG, UK 2 UK Dementia Research Institute, University College London , London, UK 6 UK Dementia Research Institute, King’s College London , London, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Reem Abouward Alya Masoud Abdelhafid 1 Department of Neuromuscular Diseases and UCL Queen Square Motor Neuron Disease Centre, UCL Queen Square Institute of Neurology, University College London , London WC1N 3BG, UK 2 UK Dementia Research Institute, University College London , London, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Alya Masoud Abdelhafid Oscar G Wilkins 1 Department of Neuromuscular Diseases and UCL Queen Square Motor Neuron Disease Centre, UCL Queen Square Institute of Neurology, University College London , London WC1N 3BG, UK 3 The Francis Crick Institute , London, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Oscar G Wilkins Song-Yi Lee 4 Department of New Biology , DGIST, Daegu, KR 5 New Biology Research Center , DGIST, Daegu, KR 7 Department of Genetics, Stanford University , Stanford, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Song-Yi Lee Fairouz Ibrahim 3 The Francis Crick Institute , London, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Fairouz Ibrahim Mark Skehel 3 The Francis Crick Institute , London, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Mark Skehel Alice Ting 7 Department of Genetics, Stanford University , Stanford, USA 8 Department of Biology, Stanford University , Stanford, USA 9 Department of Chemistry, Stanford University , Stanford, USA 10 Chan Zuckerberg Biohub , San Francisco, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Alice Ting Nicol Birsa 1 Department of Neuromuscular Diseases and UCL Queen Square Motor Neuron Disease Centre, UCL Queen Square Institute of Neurology, University College London , London WC1N 3BG, UK 3 The Francis Crick Institute , London, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Nicol Birsa Jernej Ule 3 The Francis Crick Institute , London, UK 6 UK Dementia Research Institute, King’s College London , London, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Jernej Ule Giampietro Schiavo 1 Department of Neuromuscular Diseases and UCL Queen Square Motor Neuron Disease Centre, UCL Queen Square Institute of Neurology, University College London , London WC1N 3BG, UK 2 UK Dementia Research Institute, University College London , London, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Giampietro Schiavo For correspondence: giampietro.schiavo{at}ucl.ac.uk Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract LAMP1 and LAMP2A are abundant proteins of late endosomal/lysosomal compartments, which are often used interchangeably to label what is thought to be the same pool of organelles, potentially obscuring their unique physiological roles. Here, we characterised the transport dynamics of LAMP1- and LAMP2A-positive compartments in human iPSC-derived cortical neurons. We found that axonal LAMP1-positive organelles move more slowly in the retrograde direction, pause more frequently, and show a broader velocity distribution in the anterograde direction than LAMP2A-positive vesicles, suggesting they are distinct compartments with differential trafficking behaviour. To explore the molecular mechanism underlying these differences, we characterised with high spatiotemporal precision, the protein interactomes of LAMP1 and LAMP2A-positive compartments through proximity labelling, using full-length LAMP1 or LAMP2A fused to the light-activated biotin ligase LOV-Turbo. We identified and validated the endosomal protein, ZFYVE16, as a novel member of LAMP1 and LAMP2A interactomes. We suggest that LAMP2A-positive organelles represent a subset of LAMP1-positive compartments, which are surprisingly enriched in synaptic vesicle proteins. Summary statement LAMP1- and LAMP2A-positive organelles have different axonal transport dynamics and form distinct organelle pools characterised by specific protein compositions. Introduction The endolysosomal pathway is a dynamic network of membrane-bound organelles required for several important cellular processes, including growth factor signalling, trafficking of proteins, lipids, and RNA granules, and the regulation of protein translation and degradation ( Cosker and Segal, 2014 ; Villarroel-Campos, Schiavo and Lazo, 2018 ; Kuijpers et al ., 2021 ; Vargas et al ., 2022 ; De Pace et al ., 2024 ). This pathway is formed by early endosomes (EEs), late endosomes (LEs), multivesicular bodies and lysosomes. However, these organelles undergo multiple fusion and fission events, maturing from one type to another, making the distinction between them rather blurred ( Huotari and Helenius, 2011 ; Platta and Stenmark, 2011 ). EEs are the first element of this complex network, sorting material endocytosed at the plasma membrane (PM) further along the pathway or recycling it back to the PM via recycling endosomes ( Maxfield and McGraw, 2004 ). EEs mature into LEs, which are more acidic and highly motile, transporting internalised material towards the perinuclear region, where they eventually fuse with lysosomes ( Gruenberg and Stenmark, 2004 ). Within their highly acidic lumen (pH 4.5 - 5.0), lysosomes house a wide range of acid hydrolases and lipases ( Saftig, 2007 ), which are critical for degrading endocytosed cargoes or cytoplasmic content, such as protein aggregates and damaged organelles, via autophagy ( Perera and Zoncu, 2016 ; Galluzzi et al ., 2017 ). Additionally, lysosomes function as signalling hubs, regulating processes such as nutrient sensing, calcium signalling, and plasma membrane repair ( Ballabio and Bonifacino, 2020 ; Settembre and Perera, 2024 ). In neurons, the distribution of endolysosomal organelles is polarised, with lysosomes enriched in the soma and EEs in neurites, thus forming a gradient of organelles with increasing luminal acidity closer to the soma ( Kulkarni and Maday, 2018 ). This means endosomal cargo requires transport over long distances to reach mature lysosomes for degradation, presenting unique challenges for neurons due to the length of their axons and complexity of dendritic arborisations. Therefore, it comes as no surprise that disruptions in the endolysosomal pathway are strongly associated with neurodegenerative disorders (NDs) ( Sharma et al ., 2018 ; Roney et al ., 2022 ). In particular, lysosomal dysfunction underlies and/or exacerbates many NDs, either directly due to mutations in lysosomal proteins and hydrolases, or secondary to impairments in lysosomal integrity and autophagy ( Wallings et al ., 2019 ; Parenti et al ., 2021 ). Moreover, altered motility of endolysosomal organelles, especially of their axonal transport, is an early feature of several NDs and has been causally linked to their pathogenesis ( Sleigh et al ., 2019 ; Roney et al ., 2022 ). Given that dysfunction of the endolysosomal pathway is a hallmark of neurodegeneration, a detailed characterisation of lysosomal composition, heterogeneity and dynamics in neurons is crucial. Two of the most used late endosomal/lysosomal markers are LAMP1 and LAMP2. These are type-1 transmembrane proteins with heavily glycosylated luminal domains, together accounting for ∼50% of the protein content of lysosomal membranes ( Eskelinen et al ., 2003 ; Wilke, Krausze and Büssow, 2012 ). LAMP2 is the only member of the LAMP family of proteins to undergo alternative splicing, producing three distinct isoforms (LAMP2A, B and C) with different transmembrane and cytoplasmic regions, and tissue-specific expression patterns ( Hatem et al ., 1995 ; Furuta et al ., 1999 ). Amongst them, LAMP2A is the best studied due to its role in chaperone-mediated autophagy (CMA), whereby proteins carrying a unique targeting motif are specifically delivered by chaperones to lysosomal degradation ( Kaushik and Cuervo, 2012 ). LAMP1 and LAMP2 are similar in size and structure, sharing about 37% sequence homology ( Fukuda, 1991 ). Mice lacking both LAMP1 and LAMP2 die during embryonic development, and their fibroblasts show a buildup of autophagosomes and cholesterol in endolysosomal compartments, suggesting that LAMP1 and 2 are required for lysosomal maturation and cholesterol processing ( Eskelinen et al ., 2004 ; Eskelinen, 2006 ; Huynh et al ., 2007 ; Schneede et al ., 2011 ). In contrast, LAMP1 knock-out mice are normal with only mild brain astrogliosis ( Andrejewski et al ., 1999 ). LAMP2 knock-out mice, however, show a more severe phenotype with a 50% mortality rate between postnatal days 20 and 40, due to skeletal muscle degeneration and reduced heart contractility ( Tanaka et al ., 2000 ). Consistently, mutations in human LAMP2 cause Danon’s disease, a lysosomal storage disorder characterised by fatal cardiomyopathy, vacuolar myopathy, and cognitive impairments ( Nishino et al ., 2000 ). Despite these functional differences, LAMP1 and LAMP2 continue to be interchangeably used as lysosomal markers. Several studies have shown that neuronal LAMP1 and LAMP2 localise to a variety of endolysosomal organelles, many lacking classic lysosomal features. For example, in mouse dorsal root ganglion neurons, only ∼30% of LAMP-positive organelles have degradative capacity ( Cheng et al ., 2018a , 2018b ). In mouse hippocampal neurons, LAMP2A/B-containing vesicles were specifically found to undergo activity-dependent membrane fusion in the dendrites to release CMA-targeted proteins into the extracellular space, with only ∼40% colocalisation between LAMP1- and LAMP2-positive organelles ( Grochowska et al ., 2023 ). This study showed a functional distinction between LAMP1- and LAMP2A/B-positive compartments ( Grochowska et al ., 2023 ), suggesting that the two proteins label different endocytic pools. Based on these results, the interchangeable use of LAMP1 and LAMP2 as endolysosomal markers may limit the interpretation of research findings, with potential implications on our understanding of NDs. Therefore, there is a need to better define the endolysosomal identity of LAMP1- and LAMP2A-positive organelles in neurons. In this work, we aim to characterise LAMP1- and LAMP2A-positive organelles in human induced pluripotent stem cell (hiPSC)-derived cortical neurons, focusing on LAMP2A due to the wealth of published information on its specific functions as compared to other isoforms. We used live-imaging in microfluidic chambers and a novel proximity labelling approach, to compare the dynamic properties of these organelles in axons and uncover the interactors of LAMP1 and LAMP2A in human neurons. Results LAMP1- and LAMP2A-positive organelles have distinct transport dynamics in axons To study the axonal transport of LAMP1- and LAMP2A-positive organelles, we used microfluidic chambers (MFCs), an established system for separating somatodendritic and axonal compartments ( Restani et al ., 2012 ; Panzi et al ., 2023 ). MFCs are formed by two chambers connected by microgrooves (10 μm wide and 500 μm long), which selectively allow the passage of axons, isolating them physically and fluidically from somas seeded in the “somatic” compartment. We used hiPSCs genetically engineered to express Neurogenin-2 ( NGN2 ) under the control of a doxycycline (DOX)-inducible promoter, which allows their direct differentiation into cortical neurons (I3Ns) in a rapid, efficient, and scalable manner using an established two-step protocol ( Fernandopulle et al ., 2018 ). I3Ns were seeded into the “somatic” chamber of MFCs and transduced at day in vitro (DIV) 10, with EGFP or mScarlet, fused to the cytoplasmic domains of LAMP1 or LAMP2A, respectively. Neuron-specific low expression levels of the two fusion proteins were ensured by a human Synapsin-1 ( SYN ) promoter. At DIV13, live-imaging of the transport of LAMP1- and LAMP2A-positive organelles was carried out at the distal end of the microgrooves (axonal side). Data was blinded and semi-manually analysed using Trackmate ( Tinevez et al ., 2017 ), capturing information on the displacement and speed of the moving compartments ( Fig. 1A ). Stationary organelles were rarely observed and were excluded from subsequent analysis. This approach allowed terminal pausing to be reflected in the average track velocity, while still enabling consistent comparison of organelle movement prior to pausing. Download figure Open in new tab Figure 1: Transport dynamics of LAMP1- and LAMP2A-positive organelles. A) Experimental design and timeline for live-tracking organelle transport in axons. DIV3- differentiated I3Ns were seeded into one side of the MFCs. At DIV10, I3Ns were transduced with either LAMP1-EGFP or LAMP2A-mScarlet lentiviruses, and at DIV13, live-imaging of the distal end of the microgrooves (∼500 μm away from the soma) was carried out at 2 frames/s for 125 s. B) Representative kymographs for LAMP1-EGFP and LAMP2A-mScarlet transport. Movement to the right (indicated by the arrow) is anterograde. C) Cumulative displacement graphs of LAMP1-positive (left) and LAMP2A-positive (right) organelles over the recording period. Directionality was determined based on the displacement between the first and final location of an organelle. Organelles were tracked from four replicates and from at least three separate microgrooves per replicate. n is the total number of all organelles tracked. D) Relative mean velocity distribution for LAMP1- (top) and LAMP2A-positive organelles (bottom), bin = 0.25 μm/s. Organelles that did not move were few and were not tracked. If organelles terminally paused after a period of motion, a maximum of 10 frames of pausing were recorded. E) Mean speed ±SD of LAMP1- and LAMP2A-positive organelles in the anterograde and retrograde directions. Mean anterograde speed ±SD of LAMP1 = 3.45 ±0.126 μm/s, and LAMP2A = 3.768± 0.333 μm/s. Mean retrograde speed ±SD of LAMP1 = 1.74 ±0.119 μm/s, and LAMP2A = 2.441 ±0.253 μm/s. P -value = 0.000871 (*** for p < 0.001). Each dot is a biological replicate. Number of organelles tracked per replicate was comparable between LAMP1 and LAMP2A. For LAMP1, 252, 344, 194 and 259 organelles were tracked for Rep1 to 4 respectively. For LAMP2A, 297, 213, 307 and 225 organelles were tracked for Rep1 to 4 respectively. Statistical significance was determined by an emmeans test using an error model from a mixed-effects linear model. Representative kymographs ( Fig. 1B ) show that LAMP1- and LAMP2A-positive organelles are highly motile, displaying diverse motion dynamics. To quantify their transport, the cumulative total displacement of each fluorescent spot was plotted over time for LAMP1 and LAMP2A ( Fig. 1C ). These plots reveal that for both populations, transport is bidirectional and varied, with puncta showing fast processive movements as well as slower motion modalities characterised by frequent pausing, and direction reversals. Notably, LAMP2A-positive organelles displayed more sustained, processive movement with fewer pauses than their LAMP1 counterparts. This observation prompted us to investigate the relative speed distribution of LAMP1- and LAMP2A-positive organelles ( Fig. 1D ). Whilst both showed a broad range of velocities in either the anterograde or retrograde directions, anterograde movement was generally faster. However, LAMP1-positive organelles had a wider anterograde speed distribution with seemingly two subpopulations of organelles, a slow and a fast one, compared to LAMP2A. Additionally, LAMP2A-positive compartments exhibited a distribution of retrograde movements shifted towards higher speeds compared to LAMP1 ( Fig. 1D ). Mean transport speeds per replicate are shown in Fig. 1E . LAMP1-positive organelles moved at 3.45 ± 0.13 μm/s anterogradely and 1.74 ± 0.12 μm/s retrogradely, whereas LAMP2A-positive vesicles exhibited a comparable mean anterograde speed (3.77 ± 0.33 μm/s) and a significantly faster retrograde speed (2.44 ± 0.25 μm/s). In summary, our transport analysis shows that LAMP1- and LAMP2A-positive organelles have different motion dynamics, with LAMP1-positive organelles having a wider anterograde transport speed distribution, whereas LAMP2A-positive organelles exhibit more processive, faster transport, particularly in the retrograde direction. Comparison of LAMP1 and LAMP2A interactomes Given the differences we observed in axonal transport dynamics, we sought to further characterise the composition of the organelles carrying LAMP1 and LAMP2A by proximity labelling (PL). PL can be carried out in living cells to capture the proximal proteome of a protein of interest ( Qin et al ., 2021 ). In this approach, an enzyme (typically a biotin ligase or a peroxidase) is genetically fused to the protein of interest and under specific conditions (e.g., addition of biotin or biotin-phenol/hydrogen peroxide), it catalyses the formation of small reactive molecules, which covalently label neighbouring proteins within a <20 nm radius. The chemical tag can then be used as an affinity handle for the purification and identification of the local protein environment by mass spectrometry (MS) ( Qin et al ., 2021 ). To avoid toxicity associated with the use of hydrogen peroxide, and for a more effective spatiotemporal control of biotinylation, we opted to use LOV-Turbo, a blue light-activated variant of the promiscuous biotin ligase TurboID ( Lee et al ., 2023 ). LOV-Turbo consists of TurboID fused to a light-oxygen-voltage (LOV) domain that suppresses ligase activity in the dark. Blue light induces a conformational change that activates TurboID allosterically, allowing proximity-dependent biotinylation in the presence of biotin and ATP ( Fig. 2A ) ( Lee et al ., 2023 ). Download figure Open in new tab Figure 2: The localisation and biotinylation activity of LOV-Turbo fusion proteins. A ) Schematic depicting the conformational changes of LOV-Turbo upon exposure to blue light (470 nm) leading to biotinylation if biotin and ATP are present (adapted from Lee et al ., 2023 ). B ) LOV-Turbo fusion constructs generated in this work. LOV-Turbo is ∼50 kDa. C) LOV-Turbo regulation by blue light in I3Ns. I3Ns were transduced with LAMP1-LOV (top) or NES-LOV (bottom), fixed for imaging on DIV18 after three days of LOV-Turbo expression. Both were treated with 250 μM biotin on the day of the experiment and exposed to blue light pulses for 30 min. Scale bar = 15 μm. D) Western blot showing the light-dependent activity of LOV-Turbo. I3Ns were transduced at DIV15 with NES-LOV and collected on DIV18, after treatment with two different concentrations of biotin and exposure to 30 min of blue light, as indicated. The blots were probed for biotinylation and protein expression by incubation with streptavidin-HRP and an anti-V5 antibody. Equal protein amounts were loaded across conditions. E-G) Visualisation of LOV-Turbo fusion proteins by V5 staining for E) LAMP1-LOV, F) LAMP2A- LOV, showing colocalisation with LAMP1 or LAMP2, respectively and biotinylated proteins (visualised by streptavidin staining), magnified in inset. G) NES-LOV (V5) is widespread across the cytoplasm, with similar localisation for biotinylated proteins, magnified in insets. Scalebar of full images (left panels) = 20 μm, and insets = 10 μm. We generated fusion constructs of LOV-Turbo with LAMP1 (LAMP1-LOV) or LAMP2A (LAMP2A-LOV) designed to direct the ligase to the cytosol-facing surface of LAMP-positive organelles. In addition, LOV-Turbo was also fused to a nuclear export signal (NES), which targets it to the cytoplasm (NES-LOV), providing a spatial reference for cytoplasmic labelling ( Cho et al ., 2020 ). This control was important to distinguish organelle-associated proteins from non-specific cytoplasmic labelling, as the LAMP-positive organelles are highly dynamic. All constructs were driven by a SYN promoter (unless otherwise stated) and included a V5 tag as a linker between LOV-Turbo and the protein of interest, which facilitated subsequent validation by immunofluorescence and western blotting ( Fig. 2B ). We also designed and manufactured in house a light box using blue light-emitting diodes (LEDs) to reliably activate LOV-Turbo fusion proteins ( Supplementary Fig. 1A ). To test the light-dependent biotinylation of LOV-Turbo, DIV15 I3Ns were transduced with either LAMP1-LOV or NES-LOV and kept in the dark. At DIV18, 250 µM biotin was added to the media and neurons were kept in the dark or exposed to blue light for 30 min pulsed at a 50% duty cycle (30 s on/off) to minimise the risk of overheating. The cells were then stained with a V5-specific antibody, which displayed punctate distribution for LAMP1-LOV or diffuse cytoplasmic localisation for NES-LOV, with biotinylation only occurring when cells were exposed to blue light, as demonstrated by staining with fluorescent streptavidin ( Fig. 2C ) . To verify this result by western blotting, HEK293T cells were transfected with a version of the NES-LOV construct identical to that used in Fig. 2B , but with a DOX-inducible promoter. The cells were kept in the dark and exposed to 30 min of blue light after DOX induction for 24 h. Western blots shown in Supplementary Fig. 1B confirm the light-dependent activity of LOV- Turbo, as biotinylated protein smears were only visible when cells were exposed to blue light, whilst only endogenously biotinylated proteins were detected in the dark. Similar results were observed in I3Ns ( Fig. 2D ). I3Ns were transduced with DOX-inducible NES-LOV and collected on DIV18, following three days of DOX treatment and exposed to blue light with no additional biotin, or upon addition to the media of a final concentration of 125 or 250 μM of biotin. Fig. 2D shows increasing biotinylation with higher biotin concentrations, with only endogenously biotinylated proteins at ∼50, ∼75 and ∼150 kDa detectable in the absence of additional biotin. Having established that LOV-Turbo fusion proteins enable light-dependent biotinylation, we used high-resolution confocal imaging in I3Ns to confirm whether they co-localise with their endogenous counterparts and biotinylated proteins. Neurons were transduced and treated as previously described, with all constructs regulated by SYN promoter. Both LAMP1- and LAMP2A-LOV colocalise with LAMP1 and LAMP2, respectively, and with the biotinylated protein signal ( Fig. 2E,F ). In contrast, NES-LOV is distributed across the cytoplasm with similarly diffused biotinylation signal, albeit the latter also shows an enrichment in an unknown pool of perinuclear organelles ( Fig. 2G ). We then proceeded to identify the LAMP interactomes using LAMP1-, LAMP2A- and NES- LOV samples and an untransduced (UT) control. Neurons were first transduced with the corresponding lentivirus on DIV15 and biotinylation carried out as previously described in four independent replicates per condition. Following streptavidin pulldown, western blotting of a small portion of the eluate showed that the biotinylation was highest in the LAMP1-LOV sample with most biotinylated proteins depleted from the flow-through ( Supplementary Fig. 2A ). Samples were processed using label-free data-dependent MS over two rounds, once with one run per condition and another with three technical runs per condition. Regrettably, a NES- LOV sample was lost during processing. Each condition yielded >1,000 proteins ( Supplementary Fig. 2B ). Principal component analysis (PCA) showed clear clustering by condition, with a batch effect between MS runs, reflecting the known variability associated with MS data acquisition ( Fig. 3A ). Download figure Open in new tab Figure 3: The interactomes of LAMP1- and LAMP2A in I3Ns. A) PCA using the top 500 most variable proteins. Each dot is a biological replicate, coloured by condition. All four conditions were run twice on a MS machine, named batch 1 and 2 in the figure, with batch 2 being an average of three technical runs. There were four replicates per condition, except for NES-LOV (n = 3). B-C) Volcano plots of the fold change in log 2 protein intensities of B) LAMP1-LOV and C) LAMP2A-LOV over NES-LOV control, plotted against - log 10 adjusted p -values (adj. p -value). The dotted lines mark the adj. p -value and log 2 fold-change (log 2 FC) cut-offs of 0.05 and 1.5, respectively. NS refers to non-significant proteins. Proteins at the top of the graph have infinite p -values and cannot be fit on the graph. Additionally, some proteins were only detected in the LAMP1/2A-LOV conditions and not in the NES control. The top 10 of these are listed on the right of the volcano plot ranked by intensity. D-E) GSEA showing the top 10 enriched terms (GO cellular component) for the proteins significantly enriched in D) LAMP1-LOV or E) LAMP2A-LOV condition over the NES cytoplasmic control, including those detected exclusively in LAMP1/2A-LOV datasets. All proteins identified in the MS were used as a background dataset for GSEA. F) Overlap between LAMP1- and LAMP2A-LOV datasets. To identify enriched proteins, we calculated log 2 fold-changes of protein intensity in LAMP1- LOV and LAMP2A-LOV samples relative to both NES-LOV and UT controls. If a protein was found enriched in the UT condition in any comparison (log 2 fold-change > 1.5 and adjusted p - value < 0.05), it was filtered out of the full dataset. Remaining proteins were taken forward for further analysis, comparing the LAMP1 and LAMP2A datasets to the NES control ( Fig. 3B,C ). In addition to enriched proteins identified through this analysis, 375 and 67 proteins were uniquely detected in the LAMP1-LOV and LAMP2A-LOV samples, respectively, and were not present in the NES-LOV control. These proteins were not imputed as part of the MSstats package used for MS analysis. The top ten most abundant proteins of this group are listed in Fig. 3B and C , ranked by decreasing intensity. Proteins present in the LAMP1-LOV dataset include LAMP1 itself and several known functional constituents of lysosomes, such as BORC5, a subunit of the BORC complex regulating lysosome positioning within the cell, KIF1A, which regulates lysosomal transport, and the ATP6V0A1 subunit of the v-ATPase which is known to mediate lysosomal acidification ( Ballabio and Bonifacino, 2020 ). Similar observations were made for the LAMP2A-LOV dataset, where LAMP2 itself is exclusively detected, together with NDRG4, a protein regulating brain derived neurotrophic factor (BDNF) in the brain ( Yamamoto et al ., 2011 ). Due to their biological relevance, these proteins are included in the total LAMP1/2A interactome dataset in Supplementary Table 1 . Gene set enrichment analysis (GSEA) for the LAMP1-LOV dataset shows an enrichment of endosomal and lysosomal gene ontology (GO) terms ( Fig. 3D ). Compared to LAMP1-LOV, the LAMP2A-LOV dataset had fewer significantly enriched proteins over the cytoplasmic control ( Supplementary Table 1 ). This is possibly due to a lower expression level of LAMP2A- LOV and consequently less biotinylation, as suggested by enrichment ratios in the volcano plot ( Fig. 3C ), or if LAMP2A-interacting proteins are equally abundant in the cytosol. Nonetheless, GSEA for LAMP2A-LOV shows an enrichment in clathrin-coated vesicle-related GO terms ( Fig. 3E ). Interestingly, we found several synaptic proteins, such as SYN1, SV2A, SYT1 and SNAP25, in the interactomes of both LAMP1 and LAMP2A. However, in the LAMP2A-LOV dataset, synaptic proteins constituted a larger proportion of the total interactome, resulting in the "synaptic vesicle membrane" GO term reaching the top ten enriched terms ( Fig. 3E ) . Further analysis revealed that LAMP2A interacts with a subset of the total LAMP1 interactome ( Fig. 3F ) , with the remaining LAMP1-specific interactors enriched for lysosomal and late endosomal GO terms ( Supplementary Fig. 2C ) . In summary, we were able to capture comprehensive interactome datasets for LAMP1 and LAMP2A in human I3Ns, with GSEA highlighting that LAMPs interact with a diverse repertoire of endolysosomal proteins. LAMP1 and LAMP2A interactome validation To validate our results, we selected two proteins with synaptic GO term localisation, Synaptotagmin 1 (SYT1) and SNAP25. SYT1 is the main calcium sensor for synaptic vesicle exocytosis ( Sudhof, 2004 ), whilst SNAP25 is a SNARE protein essential for synaptic vesicle fusion ( Sudhof, 2004 ). I3Ns were fixed on DIV18 and stained for LAMP1/2 and SYT1 or SNAP25 and imaged using high-resolution confocal microscopy to test whether these synaptic proteins colocalise with LAMP1 and LAMP2 ( Fig. 4 ). Neurofilament heavy chain (NFH) staining was used to label axons. Intensity profile plots across LAMP1/2-positive organelles in NFH-positive projections, show partial colocalisation with small SYT1 and SNAP25 puncta decorating the surface of these organelles ( Fig. 4 ). However, quantifying the degree of overlap of SYT1 and SNAP25 with LAMP1/2, was challenging due to the high abundance of these proteins in neurons. Download figure Open in new tab Figure 4: LAMP1- and LAMP2A colocalise with synaptic proteins. Airyscan2 images of I3Ns stained for A) LAMP1 and SYT1, B) LAMP1 and SNAP25, C) LAMP2 and SYT1 and D) LAMP2 and SNAP25. Neurons were also stained for NFH, an axonal marker. A portion of the image marked by a dashed square is magnified in the inset showing LAMP1/2 colocalising with SYT1 or SNAP25 in a neurite. Intensity measurements were taken along a 10 µm line represented by a dashed arrow on the inset and in a straightened format below it. The semi-transparent rectangle surrounding the arrow illustrates the area across which the intensity was averaged. The intensity profile is shown on the right; intensity was measured in only one image plane and scaled within each channel. Scalebar of full image = 10 μm, inset = 2 μm. To enable a more precise quantification, we employed a proximity ligation assay (PLA), which enables the detection of the co-distribution and localisation of two proteins within a ∼40 nm radius. Co-distribution is marked by discrete fluorescent puncta on an otherwise negative background ( Klaesson et al ., 2018 ; George et al ., 2022 ). For this analysis, we focused on SNX3, a member of the sorting nexin family mainly associated with early endosomes highly enriched in our dataset, and ZFYVE16/endofin, an early endosomal protein implicated in regulating membrane trafficking that was not previously known to interact with LAMP1/2, for validation. RAB7, a master regulator of the endolysosomal pathway, was used as a positive control ( Fig. 5 ). PLA was carried out in DIV18 I3Ns and DAPI staining was used to quantify the total number of neurons. All proteins tested showed abundant PLA puncta with both LAMP1 and LAMP2 ( Fig. 5A ). Negligible signal was detected in the negative controls, whereby only one of the two primary antibodies was omitted ( Supplementary Fig. 3 ). Data were quantified using an automated analysis pipeline to segment and count the number of PLA puncta and DAPI signal, calculating the number of puncta per neuron ( Supplementary Fig. 4 ). Three biological replicates were performed per protein of interest, with a LAMP1- or LAMP2-only negative control included with each replicate for normalisation purposes. This analysis confirmed that SNX3, ZFYVE16/endofin and RAB7 are in close proximity to LAMP1 and LAMP2, as indicated by the robust PLA signal compared to negative controls ( Fig. 5B, C ). Download figure Open in new tab Figure 5: Validation of identified interactors of LAMP1 and LAMP2A via PLA. A) Representative PLA images for LAMP1 and LAMP2A to validate interactomes identified by LOV-Turbo biotinylation. Two top enriched proteins (ZFYVE16 and SNX3) were selected in addition to a positive control, RAB7. DIV18/19 I3Ns were fixed and incubated with primary antibodies against RAB7, ZFYVE16 and SNX3, either with anti-LAMP1 (left panel pairs) or anti-LAMP2 primary antibodies (right panel pairs). For all proteins, neurons were fixed and the PLA carried out simultaneously with their respective controls. All images were captured using the same settings as the controls. However, the images presented here have their brightness/contrast adjusted to enable better visualisation of the PLA puncta. Scale bar = 20 μm. B-C) PLA quantification. The number of PLA puncta per neuron (nuclei count), was normalised to the average count in a LAMP1-only (B) or LAMP2A-only (C) primary antibody control (CTRL) per replicate. 3-5 images were taken per replicate, with three replicates in total per protein of interest. Data are presented as boxplots with Q1, median and Q3. The minimum and maximum values are also shown with the red dot being the mean. Adjusted p -value is denoted by * for p < 0.05, ** for p < 0.01, *** for p < 0.001 and **** for p < 0.0001. Statistical significance was determined by an emmeans test using error models from a mixed-effects linear model, and multiple testing correction using the false discovery rate (FDR) method of Benjamini and Hochberg. In summary, we were able to confirm the results obtained by LOV-Turbo using imaging-based techniques as orthogonal validation approaches. Discussion In this study, we characterised the transport dynamics and interactomes of LAMP1- and LAMP2A in hiPSC-derived cortical neurons. We found that the two proteins associate with a heterogeneous population of motile organelles with a wide range of velocities and directionalities. Additionally, PL with LOV-Turbo revealed a range of protein interactions, including with early endosomal and synaptic components. Our data show that LAMP1-positive organelles exhibited faster anterograde speed (3.45 ± 0.13 μm/s) compared to published in vivo speed in mouse thalamocortical axons (2.37 μm/s) ( Nassal et al ., 2022 ). This in vivo speed was itself higher than mean speeds measured in vitro in hiPSC-derived neurons (∼1.5 μm/s) and rat hippocampal neurons (1.5 - 1.7 μm/s and 2 μm/s) ( Boecker et al ., 2020 ; De Pace et al ., 2020 ). The retrograde LAMP1 speed (1.74 ± 0.12 μm/s) was more comparable to that measured in vivo in mouse thalamocortical axons (1.48 μm/s) ( Nassal et al ., 2022 ). To our knowledge, the only published analysis for LAMP2A- posive organelles was performed in hippocampal rat neurons 1 and 4 hours after LAMP2A release from the endoplasmic reticulum (ER) ( Li et al ., 2024 ). In this study, authors measured LAMP2A-positive organelle speeds between 1-1.5 μm/s in the anterograde direction, and 0.75 - 0.83 μm/s in the retrograde direction, being faster for newly released proteins. In contrast, we observed significantly higher speeds (3.77 ± 0.33 μm/s anterograde; 2.44 ± 0.25 μm/s retrograde). This discrepancy may stem from differences in methodology; previous studies relied on kymograph analysis of ∼100-500 organelles, whereas we semi-manually tracked over 2,000 organelles using TrackMate, allowing for the inclusion of small or dim puncta often overlooked in kymographs. Furthermore, Li et al . (2024) focused on proximal axons in rat neurons, while our measurements were taken in distal axons (>500 µm from the soma) of human iPSC-derived neurons. We also found that retrograde transport is slower than anterograde transport for both LAMP1- and LAMP2A-positive organelles, consistent with published data ( Boecker et al ., 2020 ; Li et al ., 2024 ). Interestingly, LAMP2A-positive organelles moved significantly faster in the retrograde direction compared to LAMP1-positive vesicles, suggesting differences in motor recruitment and/or regulation. In a recent publication by Li et. al. (2024), the percentage of LAMP2A-positive organelles co-transported retrogradely with LAMP1 was found to be between 50-60% in axons of rat hippocampal neurons. Additionally, LAMP2A moving retrogradely was only present on acidic organelles, and only if they also carried LAMP1. Together, these findings suggest that retrogradely-moving LAMP2A preferentially associates with fast-moving LAMP1-positive organelles and/or that LAMP2A association changes organelle transport kinetics, perhaps through changes in adaptor proteins to facilitate motor recruitment ( Cason and Holzbaur, 2022 ). In the anterograde direction, LAMP1- and LAMP2A-positive organelles have similar mean speeds, with velocity histograms suggesting the presence of two organelle pools. The LAMP2A-positive population was more processive, with less slow-moving organelles, suggesting reduced pausing events or distinct regulatory mechanisms. These findings align with literature reporting subpopulations amongst LAMP-positive compartments ( Cheng et al ., 2018a ; Kulkarni and Maday, 2018 ). A recent super-resolution study in non-neuronal cell lines identified eight lysosomal subtypes based on late endosomal/lysosomal protein distributions across LAMP1/2-positive organelles, although LAMP1 and LAMP2 were largely colocalised in this cell model ( Bond et al ., 2025 ). In neurons, however, LAMP1 and 2 are sorted into distinct post-Golgi vesicles and traffic separately into axons ( Li et al ., 2024 ); furthermore, they localise to functionally distinct organelles in dendrites ( Goo et al ., 2017 ; Grochowska et al ., 2023 ). Li et al . (2024) also showed that anterogradely-transported, newly synthesised LAMP2A- containing vesicles moved faster than more mature organelles, potentially reflecting differences in motor protein usage. Along with our findings, this suggests that a pool of anterograde LAMP2A-positive organelles may be independently transported from LAMP1- positive compartments and may employ distinct motor arrays. Further studies characterising organelle-associated CMA activity, pH and enzymatic content could help to further characterise the pools of organelles carrying LAMP2A in axons. LOV-Turbo PL was then used to glean new insights on the molecular underpinnings of these transport differences. We were able to capture several known interactors, such as KIF1A, BORC5 and LAMTORs ( Farías et al ., 2017 ), and several pre-synaptic proteins, such as SYN1, SV2A, SYT1, and SNAP25. Additionally, we verified the co-distribution of SYT1, and SNAP25 with LAMP1 and LAMP2 via confocal imaging. Recently, it was shown that LAMP1/2 co-segregates with SYT1 in the Golgi apparatus and is co-transported into axons, further validating our findings ( Li et al ., 2024 ). However, further studies are needed to clarify the percentage of LAMP2A-positive organelles that carry synaptic proteins and whether this differs from LAMP1-positive organelles. It is also unclear how these synaptic proteins distribute between organelles and if the mechanisms are conserved across species, e.g., whether a specialised type of organelle carries all presynaptic proteins, or if they are carried by different compartments based on specific molecular determinants ( Roney et al ., 2022 ). The LAMP1-LOV dataset we generated was smaller than a published LAMP1-TurboID dataset (∼1,500 vs >2,500 proteins identified, respectively) ( Liao et al ., 2019 ). However, we were able to enrich a higher percentage of significant proteins, despite applying stricter thresholds. Notably, we did not capture RNA granule interactors, such as FUS and G3BP1, which were previously linked to RNA hitchhiking and local translation in neurons ( Cioni et al ., 2019 ; Liao et al ., 2019 ; De Pace et al ., 2024 ). This discrepancy may be due to a combination of low, physiologically-relevant LOV-Turbo expression and steric hindrance, allowing the detection of only the most proximal interactors of LAMP1 and 2. In fact, both BORC5 and KIF1A, which were detected in the LAMP1 interactome, directly bind to the lysosomal surface ( Pu et al ., 2015 ; Guardia et al ., 2016 ). RNA-binding proteins, such as G3BP2 and FUS, found associated with LAMP1-positive compartments in other studies ( Liao et al ., 2019 ; Li et al ., 2024 ), are components of RNA granules and may not be in direct contact with the surface of LAMP1- positive organelles. Nonetheless, we found several ribosomal proteins in our LAMP interactome, suggesting that LAMP-positive organelles could support local translation. A possible limitation of our approach is that we did not stimulate and/or quantify CMA activity. The binding of client proteins to LAMP2A is a rate-limiting step of CMA and specifically differentiates this protein to the other LAMP family members ( Cuervo and Dice, 2000 ; Kaushik and Cuervo, 2018 ). Whilst the level of CMA activity taking place in I3Ns is currently unknown, the LAMP2A interactor and essential CMA chaperone, HSC70 ( Agarraberes and Dice, 2001 ; Kaushik and Cuervo, 2018 ), was not detected in our study, suggesting a low level of CMA activity in our experimental conditions. Additionally, unlike LAMP1, LAMP2A is known to dynamically associate to cholesterol/glycosphingolipid-rich microdomains in a process dependent on CMA activity ( Kaushik et al ., 2006 ). Thus, in absence of CMA activation, LAMP2A may be sequestered in specific areas of its vesicular carriers, further restricting its interactions. Our findings reinforce the view that LAMP1 and LAMP2A label distinct organelle populations, with different motility and molecular signatures and further support the idea that LAMPs are perhaps not ideal markers for mature lysosomes in neurons ( Cheng et al ., 2018a ; Li et al ., 2024 ; Bond et al ., 2025 ). Future work is needed to capture the dynamic changes to organelle identity under physiological stimuli and in the context of neurodegeneration. Notably, several key pathogenic proteins, including tau, α-synuclein, and amyloid precursor protein, hijack pre-existing transport routes and organelle subtypes for propagation across neuronal circuits ( Abeliovich and Gitler, 2016 ; Nixon, 2017 ; Evrard et al ., 2018 ; Soares et al ., 2021 ; Xie et al ., 2022 ). Moreover, targeted manipulation of organelle identity is emerging as a promising therapeutic strategy for NDs ( See et al ., 2021 ; Hung et al ., 2023 ). Therefore, a deeper understanding of the molecular and functional heterogeneity within the neuronal endolysosomal network is critical for advancing both basic neuroscience and therapeutic development. Author contributions RA: conceptualisation, formal analysis, investigation, validation, visualisation, and writing (original draft). AA: performed some transport experiments. OW: assisted in making the blue light box. SL and AT: provided LOV-Turbo constructs and advised on experimental optimisations. FI and MS acquired MS data. NB: conceptualisation and supervision. JU: conceptualisation, funding acquisition, supervision. GS: conceptualisation, funding acquisition, supervision, and writing (original draft). All authors approved the final version of this manuscript and submission of this work. Materials and methods Human iPSC and neuronal cultures Cells were cultured in a humidified incubator at 37°C with a 5% CO 2 supply and routinely tested to ensure they were mycoplasma free. Experiments were carried out using neurons differentiated from hiPSCs (male; WTC11 background) with a DOX-inducible Neurogenin-2 ( NGN2 ) cassette inserted into a safe AAVS1 locus, and CAG promoter driven expression of catalytically-dead Cas9 fused to KRAB transcriptional repression domain (dCas9-KRAB), inserted into CLYBL intragenic safe harbour site ( Wang et al ., 2017 ; Fernandopulle et al ., 2018 ; Tian et al ., 2019 ). iPSCs were cultured on plates coated with Geltrex basement membrane matrix (Gibco) in mtseR Plus (STEMCELL Technologies) media, following published guidelines ( Fernandopulle et al ., 2018 ). For passaging, they were split using Versene (Gibco) with Accutase (Sigma-Aldrich) used prior to neuronal induction. For neuronal induction, iPSCs were switched to induction media consisting of DMEM/F-12- GlutaMAX media (Gibco), 1× N2 supplement (Gibco), 1× MEM Non-Essential Amino Acids Solution (Gibco), 2 μg/ml DO× (Sigma-Aldrich, dissolved in water) and 10 μM ROCK inhibitor (Tocris) added on the day of seeding ( Fernandopulle et al ., 2018 ), with daily media changes for two more days. On the fourth day, they were split using Accumax (Invitrogen) and replated onto plates coated with 0.1 mg/ml poly-D-lysine (Gibco) and 10 μg/ml laminin (Sigma-Aldrich). At this stage, I3Ns are at DIV3. 50,000 cells were seeded on 13 mm acid-etched glass coverslips ( Lazo and Schiavo, 2023 ) for imaging, 150,000 cells were added to the somatic side of MFCs and 10,000,000 were used per 10 cm dish for proteomics. In the latter case, dishes were additionally coated with Geltrex to improve cell attachment. Neuronal maintenance media consisted of Brainphys (StemCell Technologies) supplemented with 1× B27 (Gibco), 1× N2 (Gibco), 10 ng/ml recombinant brain-derived neurotrophic factor (PeproTech), 10 ng/ml recombinant glial cell line derived neurotrophic factor (PeproTech) and 1 μg/ml laminin. Additionally, 2 μg/ml DOX and 1× CultureOne supplement (Gibco) were added on the first day after replating, with half-media changes every 3-4 days. For proteomics experiments, Geltrex (1 in 100) was additionally added to the media. Lentivirus production Lenti-HEK293T cells were used to produce lentiviruses using VSV-G (Addgene #12259) and PAX (Addgene #22036) plasmids. Cells were cultured in Dulbecco’s Modified Eagles Medium (DMEM, Gibco) supplemented with 10% heat inactivated foetal bovine serum (FBS) and 1× GlutaMAX (Gibco). The media was collected twice starting two days after transfection with Lipofectamine 3000 (Invitrogen) and concentrated using Lenti-X concentrator (Takara Bio), following manufacturers’ instructions. Lentiviruses were titrated in I3Ns using increasing viral dilutions (1:100-1:2,000) and tested by immunofluorescence to identify appropriate concentrations maximising transduction with minimal cell death. Microfluidic chambers MFCs were prepared following published protocols ( Restani et al ., 2012 ; Panzi et al ., 2023 ) and baked in resin moulds at 65°C for 1 h, sterilised with 70% ethanol and attached to plasma cleaned glass-bottom dishes (WillCo Wells), followed by further sterilisation by UV light for 10 min. Plasmids All plasmids used in this study were generated using Gibson assembly (HiFi 2× Mastermix, NEB), following manufacturer’s guidelines. Inserts were PCR-amplified using Q5 polymerase master mix (NEB) and plasmid backbones were linearised by restriction digestion ( Supplementary Table 2 ). The linearised backbone was digested with DpnI (Invitrogen), and both backbone and insert DNA were purified using SPRI beads (Mag-Bind Total Pure NGS, Omega Biotech). Following assembly, constructs were purified using SPRI beads, transformed into DH5α competent cells (NEB) and verified by whole-plasmid nanopore sequencing. For lentiviral plasmids, verified constructs were transformed into NEBStable (NEB) or One Shot Stbl3 (Invitrogen). Immunofluorescence For immunofluorescence (IF) experiments, cells were fixed in 4% paraformaldehyde (PFA), 4% sucrose in PBS for 15 min at room temperature (RT), followed by an incubation for 1 h at RT in blocking solution (4% bovine serum albumin (BSA) and 0.1% saponin in PBS). This was followed by 2 h incubation at RT (or overnight at 4°C) with primary antibodies diluted in antibody buffer (4% BSA, 0.05% saponin in PBS), washed with PBS and incubated for 1-2 h with secondary antibodies conjugated to AlexaFluor dyes (Invitrogen) diluted 1:1,000 in the same buffer. Antibodies are listed in Supplementary Table 3 . Imaging was carried out on LSM 980 confocal microscope (Zeiss) using an oil immersion Plan-Apochromat 63x/1.40 NA objective or an oil immersion EC Plan-Neofluar 40x/1.30 NA objective. Selected samples were imaged using Airyscan2 and processed with 3D Airyscan deconvolution software using default settings on Zen Blue (Zeiss). Shifts in the z-plane were measured using fluorescent microbeads with the same imaging conditions as the experiment and corrected prior to image analysis. For LOV-Turbo light-dependent activity, the images were acquired on an Olympus IX3 Series (IX83) inverted microscope using a Yokogawa W1 spinning disk equipped with a Hamamatsu Orca Fusion CMOS camera. Subsequent image processing was done in Fiji ImageJ ( Schindelin et al ., 2012 ). Unless otherwise stated, all images presented are maximal projections of a z-stack. Proximity ligation assay PLA was carried out following manufactures’ instructions using a Duolink Proximity Ligation Assay (Sigma-Aldrich) kit, using cells fixed in 4% PFA as before, and permeabilised for 5 min in methanol at −20°C. After the PLA protocol was completed, cells were incubated with 4’,6-diamidino-2-phenylindole, dihydrochloride (DAPI) in PBS for 10 min at RT. A LAMP1-only control was included with every LAMP1 experiment, however, one RAB7 PLA was lost during processing and needed to be repeated alongside the control, hence there are four replicates for LAMP1-only control and three for every protein tested. For analysis, we used a custom Fiji ImageJ pipeline to process all the images applying the following set of steps. All channels were first maximally projected and background subtraction was performed on the PLA channel using a rolling ball radius = 2. A Gaussian filter (sigma = 0.5/1) was applied to the background subtracted PLA channel, followed by auto-thresholding using Renyi’s entropy method ( Sahoo, Wilkins and Yeager, 1997 ) and further refined using a watershed algorithm to separate any overlapping PLA puncta. Puncta were counted using the Analyze Particles function, with an upper size limit of 0.2/0.3 µm 2 . For the DAPI channel, the contrast was enhanced to enable all nuclei to be counted. A Gaussian filter (sigma = 2) was then applied to define the nuclei. Thresholding was performed using Huang’s auto-thresholding followed by a watershed filter to separate touching nuclei. Nuclei were counted using the Analyze Particles function, with a lower size limit of 45 µm 2 . Images were then manually assessed, and nuclei counts were corrected where necessary. Images where the segmentation failed were removed from subsequent analysis. Data were exported as a .csv file for further processing in R (version 4.3.1) and RStudio ( RStudio Team, 2020 ). Intensity profile blots We used the line drawing feature in Fiji ImageJ to add a 10 µm line (width = 20 points) tracing a section of a neuron with colocalised puncta. The intensity profile plot tool was used to measure intensity per point for the two channels of interest. Data were then analysed using R and RStudio. Intensity was scaled per channel using the following equation: normalised x = x − minimum( x ) / (maximum( x ) − minimum( x )). The values were plotted using the geom_smooth function from Ggplot2 package ( Wickham, 2016 ) with a span of 0.085. This fits a smoothed line to the plotted points using the LOESS (Locally Estimated Scatterplot Smoothing) function, where the span is twice the distance between consecutive intensity measurements. Axonal transport analysis I3Ns cultured in MFCs were transduced with lentiviruses to express either LAMP1-EGFP or LAMP2A-mScarlet-I on DIV10 and transport was visualised on DIV13. Prior to imaging, HEPES-NAOH buffer, pH 7.4, was added to the media at a final concentration of 20 mM. The imaging was carried out in an environmental chamber maintained at 37°C. 250 frames were captured at a frame rate of 2 frames/s, averaging four frames imaged as fast as possible in a 500 ms interval, with 0.085 × 0.085 µm pixel size, zooming on axons in the distal part of the microgrooves where visible moving organelles could be detected. Organelle speed and directionality were analysed using Trackmate ( Tinevez et al ., 2017 ; Ershov et al ., 2022 ). All organelles that moved for at least five frames and across a third of the field-of-view were tracked, taking a maximum of 10 tracks following pausing, if organelles terminally paused. Stationary organelles that did not move at all during the recording were rare and were not tracked. Trackmate outputs three types of files: spots.csv, edges.csv and tracks.csv. The edges.csv file was used to calculate frame-to-frame directionality with negative consecutive displacements in the x-axis indicating retrograde transport, and positive indicating anterograde transport. This information was copied into the spots.csv file and was used to plot cumulative displacement of each organelle over time. Overall directionality of an organelle was inferred from the direction of the final displacement subtracted from the location in x-axis on the first frame, negative values were classified as retrograde and positive as anterograde. The mean speed of an organelle over the course of its movement was taken from the tracks.csv file. These operations were carried out using custom Python scripts ( Python Software Foundation, 2022 ), and subsequent statistical analysis and graphs were made using R and RStudio. Statistical analysis For the transport data, we fit a linear mixed-effects model including replicates as a random effect. We used a likelihood ratio test comparing two models, a full model including an interaction term between directionality and marker protein (LAMP1/LAMP2A) to a reduced model without the interaction term, which showed that the full model was a significantly better fit for the data. Therefore, we included an interaction term between directionality and marker protein (LAMP1/LAMP2A) in the linear mixed-effects model. We compared the velocity between LAMP1 and LAMP2A using an estimated marginal means (Emmeans) test, which is robust to outliers, utilising the fitted model to account for variability. The same test was used for the PLA analysis, with p -values adjusted for multiple testing using FDR method of Benjamini and Hochberg. The package used for statistical analysis is Rstatix (Kassambara, 2023). Western blotting Cells were lysed in 50 mM Tris-HCl pH 7.5, 100 mM NaCl, 1% Igepal CA- 630, 0.1% SDS and 0.5% sodium deoxycholate containing 1× Halt Protease Inhibitor Cocktail with EDTA (Thermo Scientific) for 15 min at 4°C. Lysates were then clarified by centrifugation at 20,000 rpm at 4°C for 20 min. Clarified cell lysates were boiled for 10 min at 96°C in 1× NuPAGE LDS loading buffer (Invitrogen) with 100 mM dithiothreitol (DTT). Lysates were resolved by SDS-PAGE using 4-12% NuPAGE Bis-Tris Mini Protein Gels (Invitrogen) and nitrocellulose membranes (Whatman) using semi-dry transfer kit (Bio-Rad) or by wet transfer using the Novex wet transfer system (Thermo Scientific), following manufacturers’ instructions. Protein concentrations were measured using Bradford assay (Thermo Scientific) following manufacturer’s instructions. For streptavidin blots, beads were boiled in 1× NuPAGE LDS loading buffer to release biotinylated proteins. Membranes were blocked for 1 h in 5% skimmed milk in TBST (0.1% Tween-20 in Tris-buffered saline; TBST) and incubated overnight at 4°C with primary antibodies diluted in blocking buffer ( Supplementary Table 3 ). For Extravidin-HRP (horseradish peroxidase) or IRDye 680RD Streptavidin, the blocking buffer was 5% BSA in TBST as milk contains biotin. After primary antibody incubation, membranes were washed three times in TBST followed by an incubation with a secondary HRP-conjugated antibody diluted 1:1,000 in blocking buffer for 90 min. Blots were visualised using Bio-Rad Chemidoc Touch following 1 min incubation with Immobilon Classico Western HRP substrate (Millipore) or Odyssey CLx LI-COR 4.11 for blots incubated with IRDye. Blue light box The box was made by laser-cutting a 5 mm thick black acrylic sheet to assemble a 25 cm × 25 cm × 10 cm box that can fit four 10 cm dishes side-by-side. The inside of the box contains a 3 mm thick frosted acrylic sheet cut slightly smaller to fit into the box. For the circuit 16 super-bright LEDs (∼2.5 V measured forward voltage, 50 lumens) were connected in parallel to an Arduino Nano with a ∼11 Ω resistor in series with the LEDs and the Arduino Nano. A transistor (TIP120) was added to allow more current to reach the LEDs without compromising the Arduino Nano and a voltage regulator (Wurth Elektronik, 7806CT) was added to ensure the voltage drop across the LEDs remains consistent. The frosted acrylic sheet rests on thin styrofoam supports glued at the corners of the box. The circuit with the Arduino Nano was glued to the side of the box to minimise interference with light. Using a Thorlab PM100D with a S120VC sensor, we measured a light power of ∼135 µW/cm 2 . Proximity labelling Biotin (Sigma-Aldrich) was made as a 250 mM stock in dimethyl sulfoxide (DMSO) and stored in aliquots at −20°C until use. In all biotinylation experiments in I3Ns, the cells were transduced on DIV15 with LOV-Turbo lentiviruses at an appropriate dilution, and when DOX-inducible NES-LOV was used, the media was supplemented with 200 ng/ml DOX. On DIV18, biotin was added to I3Ns at a final concentration of 250 µM and the cells were immediately exposed to blue light pulses for 30 min, followed by three washes with cold PBS before snap-freezing. For experiments using DOX-inducible NES-LOV in Lenti-HEK293T cells, cells were transfected with 500 ng of the plasmid using Lipofectamine 3000, and the media supplemented with 200 ng/ml DOX for 24 h before exposure to blue light and cell lysis. For MS experiments, I3Ns were washed by cold PBS and pelleted by centrifugation at 1,000 x g for 1 min at 4°C and snap-frozen in liquid nitrogen. Prior to pulldown of biotinylated proteins, pellets were lysed in 1 ml cold lysis buffer with 1× cOmplete Protease Inhibitor cocktail (Roche) followed by a 45 min incubation shaking at 800 rpm in a cold room set at 4°C. Lysates were then cleared by centrifugation at 20,000 rpm for 20 min at 4°C and supernatants collected. For pulldown of biotinylated proteins, Pierce magnetic A/G beads (Thermo Scientific) were used to pre-clear the lysates and Pierce magnetic streptavidin beads (Thermo Scientific) to pulldown biotinylated proteins. Beads were washed three times in cold lysis buffer prior use for pulldowns/pre-clearing in protein LoBind tubes (Eppendorf). For the pre-clearing step, equal amounts of proteins per condition were added to 50 µl A/G beads and incubated on a rotating wheel for 45 min at 4°C. The supernatants were then incubated with 100 µl streptavidin beads on a rotating wheel overnight at 4°C, keeping ∼25 µl of the pre-cleared lysates for a western blot. The beads were washed three times with cold lysis buffer, three times with high salt buffer (50 mM Tris-HCl pH 7.5, 1 M NaCl, 1 mM EDTA, 1% Igepal CA-630, 0.1% SDS and 0.5% sodium deoxycholate) and once with 50 mM cold NH 4 HCO 3 pH 8. The beads were then transferred into a new tube and washed again twice with NH 4 HCO 3 . MS sample preparation and acquisition Bead-bound proteins were prepared for mass spectrometric analysis by in solution enzymatic digestion. Briefly, bead-bound proteins in 50 mM NH 4 HCO 3 were reduced in 10 mM DTT and then alkylated with 55 mM iodoacetamide. After alkylation, 0.4 µg of trypsin (ThermFisherScientific, USA) was added and the proteins digested overnight at 37 °C in a thermomixer (Eppendorf, Germany), shaking at 800 rpm. After digestion, 1 µl of formic acid (FA) was added and the beads centrifuged for 60 s at 2,000 g , before placing them in a magnetic rack. The supernatant was transferred into a fresh tube and desalted off-line using C18 trap columns (EV2018 Evotip Pure, Evosep Biosystems, Denmark). Peptides were eluted with 50% acetonitrile (ACN), vacuum-dried and resuspended in 30 µl 0.1% v/v FA prior to LC-MS/MS analysis. Peptides were analysed by nano-scale capillary LC-MS/MS using an Ultimate U3000 HPLC (ThermoScientific Dionex, San Jose, USA) to deliver a flow of approximately 300 nl/min. A C18 Acclaim PepMap100 5 µm, 75 µm × 20 mm nanoViper (ThermoScientific Dionex, San Jose, USA), trapped the peptides prior to separation on an EASY-Spray PepMap RSLC 2 µm, 100 Å, 75 µm × 500 mm nanoViper column (ThermoScientific Dionex, San Jose, USA). Peptides were eluted at a constant flow rate of 0.300 μl/min using the following 90 min gradient: 2% Buffer B (75% ACN, 5% DMSO, 0.1% FA in water) for 0 - 6 min, 8-55% Buffer B from 7 - 67 min, 95% Buffer B from 67.5 - 74 min and re-equilibrated at 2% Buffer B from 75 - 90 min. Buffer A was (5% DMSO, 95% 0.1% FA in water). The analytical column outlet was directly interfaced via a nano-flow electrospray ionisation source, with a hybrid dual pressure linear ion trap mass spectrometer (Orbitrap Lumos, ThermoScientific, San Jose, USA). Data dependent analysis was carried out, using a resolution of 120,000 for the full MS spectrum, followed by as many subsequent MS2 scans on selected precursors as possible within a 3 s maximum cycle time. MS1 was performed in the Orbitrap instrument with an AGC target of 4 × 105, a maximum injection time of 50 ms, and a scan range from 375 to 1500 m/z. MS2 was performed in the ion trap with a rapid scan rate, an AGC target of 2 × 103, and a maximum injection time of 300 ms. Isolation window was set at 1.2 m/z, and 32% normalised collision energy was used for HCD. Dynamic exclusion was used with a time window of 40 s. MS data analysis All raw files were then analysed using Fragpipe ( Yu, Haynes and Nesvizhskii, 2021 ; Yang et al ., 2023 ) set at the default “Label-free quantification” workflow using MSFragger ( Kong et al ., 2017 ) against the reviewed UniProt human proteome (UP000005640). LOV-Turbo (translated from amino acid sequence) and streptavidin (P22629) were manually added. MSFragger options were used at default settings with trypsin as the digestion enzyme allowing up to two missed cleavages. Cysteine carbamidomethylation was set as a fixed modification, while oxidation of methionine, acetylation of N-termini and biotinylation of lysine (Unimod Accession #3) were set as variable modifications. FDR was set at 1% at the peptide-level. Reverse decoys were generated for all sequences by Fragpipe and used to calculate the FDR. MSbooster, IonQuant and match-between-runs (MBR) were all used with MBR min correlation = 0 and MBR toprun = 10, and FDR set at 1%. The MSstats file generated was used in RStudio for subsequent analysis using MSstats (version 4.8.7) ( Kohler et al ., 2023 ), with normalisation using ‘globalStandards’ (LOV-Turbo, PCCA, PCCB and PYC) and summarisation using all features with Tukey’s median polish. Data were imputed using MBimpute. For quantitative analysis of differential protein abundance, a comparison matrix was generated for Batch 1 and Batch 2 MS runs using the MSstats groupComparison function, applying 0.5 weights for batch 1 and batch 2, with pairwise comparisons between all conditions. For comparison, the degree of protein enrichment in the UT condition over all other conditions (LAMP1, LAMP2A or NES) was calculated. If a protein was found enriched in the UT condition in one or more comparisons (log 2 fold-change > 1.5 and adjusted p -value < 0.05), it was filtered out of the full dataset. Remaining proteins were taken forward for further analysis, comparing LAMP1 and LAMP2A respectively to the cytoplasmic NES control. Any proteins that had a fold-change > 1.5 and adjusted p -value < 0.05 were selected for another screen, selecting from this list proteins that were also enriched over the UT control. Volcano plots were generated using Ggplot, with test_gsea and plot_PCA code from DEP package ( Zhang et al ., 2018 ) to carry out and plot GSEA and PCA. For Venn diagrams, the VennDiagram package ( Chen and Boutros, 2011 ) was used. Data have been deposited to the ProteomeXchange Consortium via the PRIDE ( Perez-Riverol et al ., 2025 ). partner repository with the dataset identifier PXD067562. Artificial intelligence ChatGPT (OpenAI) was used to assist in generating analysis code presented in this manuscript. It was also used in a limited capacity for manuscript editing, such as rewording and summarising text to improve readability. View this table: View inline View popup Supplementary Table 2: List of plasmids used and generated in this study. The restriction sites used to cut the plasmid backbone and the primers used to amplify the insert sequences via PCR, are included. View this table: View inline View popup Supplementary Table 3: Antibodies used for western blot (WB) and IF. Supplementary figure legends Download figure Open in new tab Supplementary Figure 1: Blue light box design and blue light-dependent activity of LOV-Turbo in HEK cells. A) Box design. Only three out of sixteen total LEDs are illustrated for clarity. B) Lenti-HEK293T cells were transfected with NES-LOV and treated with increasing amounts of biotin, and either left in the dark or exposed to blue light pulses for 30 min. Cells were also treated with B27, a supplement to neuronal media which contain biotin. The red asterisk refers to cells transduced but not treated with DOX and displays leaky expression of the fusion protein. Untransduced cells (Untrans.) were also supplemented with 100 μM biotin as an additional negative control. Equal amounts of protein were loaded. Download figure Open in new tab Supplementary Figure 2: Quality control and GSEA for LAMP1-specific interactome. A) Western blot for the different conditions used in the MS and the flow-through after biotinylated protein pulldown. The blot was probed for biotinylated proteins by incubation with IRDye 680RD Streptavidin. The strong bands are endogenously biotinylated proteins and the faint smear in between is the biotinylation driven by LOV-Turbo. B) The number of unique proteins detected across all replicates per condition, after removing contaminants, but prior to any additional filtering. C) The top 10 enriched terms (GO cellular component) for proteins which are only enriched in the LAMP1-LOV interactome and do not overlap with LAMP2A-interactome. Download figure Open in new tab Supplementary Figure 3: Negative controls for PLA. A-E) Representative images of the negative controls for the PLA experiments in Fig. 5 , using only one primary antibody as indicated in the figure: A) LAMP1, B) LAMP2, C) RAB7, D ) ZFYVE16 and E) SNX3. A and B were used as controls for PLA puncta quantification and were carried out for every PLA replicate. C-E were carried out once initially to confirm the primary antibody alone against the proteins of interest had no punctate signal. Scale bar = 20 μm. Download figure Open in new tab Supplementary Figure 4: PLA image analysis pipeline. A) PLA channel before and after segmentation (mask) with counting (Analyze Particles). The image analysis pipeline removes background from the PLA channel, adds a threshold for detecting PLA puncta and counts them using the “Analyze particles” feature in FIJI ImageJ. Scale bar = 10 μm. B) DAPI channel before and after segmentation (mask) with counting (Analyze Particles). This is used to count the number of nuclei and hence neurons present in the field of view. Scale bar = 10 μm. Acknowledgments We are grateful to Dr. James Sleigh, Dr. David Villarroel Campos (University College London) and Dr. Flora Lee (King’s College London) for helpful discussions and feedback. We thank Gavin Kelly (The Francis Crick Institute) for advice regarding statistical analysis. We also thank members of the Ule and Schiavo labs for their valuable input and support over the years. This work was supported by the Wellcome Trust (4-year PhD studentship 175261 to RA, Investigator Award 223022/Z/21/Z to GS and Joint Investigator Award 215593 to JU), the UK Dementia Research Institute (UKDRI-1005 to GS, and UKDRI-RE21605 to JU), the Motor Neurone Disease Association (186479 to AA, and Birsa/Oct21/976-799 to NB) and the Lady Edith Wolfson Fellowship funded by the Motor Neuron Disease Association and the Rosetrees Charity to OW, the GPCR collaborative of the St. Jude Children’s Research Hospital to AT, the DGIST Start-up Fund Program of the Ministry of Science (ICT 2025020055) to S-YL. and The Francis Crick Institute, which receives its core funding from Cancer Research UK (CC0102), the UK Medical Research Council (CC0102), and the Wellcome Trust (CC0102) [FI, MS]. The authors declare no competing financial interests. All data required to evaluate the conclusions in the paper are present in the paper and/or in the Supplementary Materials. Funder Information Declared Wellcome Trust, https://ror.org/029chgv08 , 175261 , 223022/Z/21/Z , 215593 , CC0102 UK Dementia Research Institute, https://ror.org/02wedp412 , UKDRI-1005 , UKDRI-RE21605 Motor Neurone Disease Association , 186479 , Birsa/Oct21/976-799 , Lady Edith Wolfson Fellowship St. Jude Children's Research Hospital , GPCR collaborative Rosetrees Trust, https://ror.org/04e3zg361 Daegu Gyeongbuk Institute of Science and Technology, https://ror.org/03frjya69 Cancer Research UK, https://ror.org/054225q67 , CC0102 Medical Research Council, https://ror.org/03x94j517 , CC0102 References ↵ Abeliovich , A. and Gitler , A. D . ( 2016 ). Defects in trafficking bridge Parkinson’s disease pathology and genetics . Nature 539 , 207 – 216 . OpenUrl CrossRef PubMed ↵ Agarraberes , F. A. and Dice , J. F . ( 2001 ). A molecular chaperone complex at the lysosomal membrane is required for protein translocation . J. Cell Sci . 114 , 2491 – 2499 . 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Share Characterisation of LAMP1- and LAMP2A-positive organelles in neurons Reem Abouward , Alya Masoud Abdelhafid , Oscar G Wilkins , Song-Yi Lee , Fairouz Ibrahim , Mark Skehel , Alice Ting , Nicol Birsa , Jernej Ule , Giampietro Schiavo bioRxiv 2025.09.17.676809; doi: https://doi.org/10.1101/2025.09.17.676809 Share This Article: Copy Citation Tools Characterisation of LAMP1- and LAMP2A-positive organelles in neurons Reem Abouward , Alya Masoud Abdelhafid , Oscar G Wilkins , Song-Yi Lee , Fairouz Ibrahim , Mark Skehel , Alice Ting , Nicol Birsa , Jernej Ule , Giampietro Schiavo bioRxiv 2025.09.17.676809; doi: https://doi.org/10.1101/2025.09.17.676809 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 (7635) Biochemistry (17691) Bioengineering (13892) Bioinformatics (41937) Biophysics (21452) Cancer Biology (18588) Cell Biology (25504) Clinical Trials (138) Developmental Biology (13378) Ecology (19899) Epidemiology (2067) Evolutionary Biology (24320) Genetics (15609) Genomics (22506) Immunology (17736) Microbiology (40394) Molecular Biology (17181) Neuroscience (88605) Paleontology (666) Pathology (2832) Pharmacology and Toxicology (4824) Physiology (7641) Plant Biology (15156) Scientific Communication and Education (2045) Synthetic Biology (4294) Systems Biology (9825) Zoology (2271)