Neuron labeling method and application thereof in neuron single cell reconstruction

Abstract

The invention relates to a method for marking neurons and application of the neurons to unicellular reconstruction of the neurons. The method comprises the following steps: expressing a proximity marker enzyme with enhanced solubility in a target neuron, and providing biotin to the target neuron so as to form biotinylated protein in the neuron; carrying out integral sample dyeing on the biotinylated protein by using monovalent streptavidin coupled with a detectable marker; imaging the dyed sample to obtain a neuron structure image; and reconstructing the morphological structure of the single neuron based on the image data.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of biological medicine, and in particular to a method for single neuron labeling and morphological reconstruction. BACKGROUND

[0002] The mammalian brain is composed of a large number of neurons and their complex synaptic connections, forming a highly fine neural circuit network. Individual neurons differ significantly in morphological structure, transcriptional characteristics, and functional roles. In order to reveal the organization and functional connections of the brain, it is necessary to obtain and analyze the morphological information of neurons at the single-cell resolution in the whole brain.

[0003] In recent years, the development of gene labeling technology, high-resolution microscopic imaging, and computational reconstruction methods has made important progress in whole-brain single neuron morphological reconstruction, and provides a basis for the mapping of mesoscale neural connectivity. However, existing single neuron reconstruction techniques generally rely on fluorescent proteins for neuron labeling, combined with sub-micron resolution imaging methods to obtain data. Even with advanced imaging platforms, sample preparation and imaging processes still take a long time. Currently, light sheet fluorescence microscopy combined with tissue transparentization technology has become an important method for rapid and high-resolution acquisition of three-dimensional images of large volume tissues, and has shown significant advantages in population-level neural circuit research, but its application in single neuron reconstruction is still limited by the labeling method itself.

[0004] Specifically, fluorescent proteins are prone to signal quenching during tissue transparentization processing, resulting in attenuation of the labeling signal. Although immunostaining of whole tissues using IgG antibodies or nanobodies can achieve signal amplification, there are often problems such as insufficient tissue penetration efficiency, long processing period, or limited amplification effect. In addition, in order to obtain sufficient resolution and distinguishability, single neuron reconstruction usually needs to achieve sparse labeling, but existing sparse labeling strategies still have deficiencies in the stability and controllability of labeling density.

[0005] Existing technologies have room for improvement in signal stability, tissue penetration, sample preparation period, and controllability of sparse labeling. Therefore, it is urgent to develop a method that can maintain the stability and specificity of the labeling signal while significantly improving the labeling efficiency of deep and whole tissues, shortening the preparation period, and achieving precise and controllable labeling density, to support single neuron three-dimensional reconstruction in the whole brain and even the whole body of an animal. SUMMARY

[0006] The present application provides a method for single-cell reconstruction of neuron labeling. The method achieves high-specificity signal labeling in a tissue-wide scale by expressing a soluble-enhanced proximity labeling enzyme in target neurons, catalyzing covalent labeling of proteins within the neurons in the presence of a labeling substrate, and combining monovalent streptavidin with a detectable label. The method has the advantages of high signal intensity, good stability, strong cell type specificity, wide applicability, simple and fast staining process, and high labeling efficiency, and can be used in combination with tissue transparentization and high-resolution imaging technology (such as light sheet microscopy) to support high-throughput and accurate single-neuron reconstruction.

[0007] In a first aspect, the present application provides a method for single-cell reconstruction of neurons, comprising: (1) expressing a soluble-enhanced proximity labeling enzyme in target neurons, and providing biotin to the target neurons to form biotinylated proteins in the neurons; (2) performing whole-sample staining of the biotinylated proteins using monovalent streptavidin coupled with a detectable label; (3) imaging the stained sample to obtain neuron structure images; and (4) reconstructing the morphological structure of a single neuron based on the image data.

[0008] In some embodiments, the proximity labeling enzyme is a biotin ligase.

[0009] In some embodiments, the biotin ligase is selected from BioID, BioID2, TurboID, miniTurbo, Split-BioID, Split-TurboID, BASU, AirID, and variants thereof.

[0010] In some embodiments, the proximity labeling enzyme is obtained by expressing a nucleic acid sequence encoding the enzyme in target neurons.

[0011] In some embodiments, the nucleic acid sequence further comprises a fragment encoding a solubility tag.

[0012] In some embodiments, the solubility tag is GB1 (SEQ ID NO: 6) or a variant thereof.

[0013] In some embodiments, the coding sequence of the solubility tag fragment is located at the 3' end of the coding sequence of the proximity labeling enzyme.

[0014] In some embodiments, the nucleic acid sequence further comprises a fragment encoding a localization signal.

[0015] In some embodiments, the localization signal is selected from a membrane localization signal, a nuclear localization signal, a cytoplasmic localization signal, or an endoplasmic reticulum localization signal.

[0016] In some embodiments, the nucleic acid sequence further comprises a fragment encoding a fluorescent protein.

[0017] In some embodiments, the fluorescent protein is selected from the group consisting of green fluorescent protein (GFP), blue fluorescent protein (BFP), cyan fluorescent protein (CFP), yellow fluorescent protein (YFP), orange fluorescent protein (OFP), red fluorescent protein (RFP), near-infrared fluorescent protein (miRFP670), or derivatives thereof.

[0018] In some embodiments, the nucleic acid sequence is introduced into the host cell genome via genomic integration.

[0019] In some embodiments, the nucleic acid sequence is delivered to the target neuron via an exogenous vector.

[0020] In some embodiments, the exogenous vector is selected from the group consisting of (1) cationic liposome, anionic liposome, pH-sensitive liposome, fusogenic liposome, or immunoliposome; (2) lipid / nucleic acid aggregates or solid lipid nanoparticles (SLN); (3) polymeric nanoparticles, micelles, or calcium phosphate nanoparticles; (4) viral vectors or virus-like particles (VLP); (5) antibody, aptamer, or polypeptide conjugation systems; (6) small molecule conjugation systems such as N-acetylgalactosamine (GalNAc), cholesterol, fatty acids, and the like.

[0021] In some embodiments, the nucleic acid sequence initiates expression of the target gene via a conditional gene expression system.

[0022] In some embodiments, the conditional gene expression system is capable of activating expression of the target gene under specific conditions, which can be chemical, physical, biological, or environmental factors, and the system is selected from the group consisting of Cre-LoxP recombinase-based regulatory systems, Flp-FRT recombinase-based regulatory systems, tetracycline regulatory systems (Tet-on / Tet-off), and temperature-sensitive promoters.

[0023] In some embodiments, the nucleic acid sequence initiates expression of the proximity marker enzyme in only a portion of the target neurons via a sparse expression system.

[0024] In some embodiments, the implementation of the sparse expression is selected from the group consisting of dilution promoter systems, dual promoter control systems, tunable dose induction systems, viral dose control systems, and random recombination systems, or a combination thereof.

[0025] In some embodiments, the sparse expression system is a dual sparse expression system, which requires two sets of different promoter controls to be met sequentially to activate expression of the target gene.

[0026] In some embodiments, the detectable label is selected from a radioisotope label, a fluorescent label, a luminescent label, a chromophore tag, a Raman spectroscopy probe, a polarization frequency probe, a DNA probe, a reporter molecule, a substance or enzyme capable of reacting with a substrate to produce a detectable signal, or a dye.

[0027] In some embodiments, the imaging modality is matched to the type of detectable label and is selected from fluorescent microscopy imaging, chemiluminescence imaging, bioluminescence imaging, Raman spectroscopy imaging, polarization imaging, isotope imaging, or other imaging modality capable of detecting the signal of the label.

[0028] In some embodiments, the target neurons are neuronal cells selected according to anatomical location, neurotransmitter type, gene expression profile, or specific markers.

[0029] In some embodiments, the neurotransmitter type of the target neurons is selected from one or more of glutamatergic neurons, GABAergic neurons, dopaminergic neurons, serotonergic neurons, noradrenergic neurons, or cholinergic neurons.

[0030] In some embodiments, the stained sample is subjected to tissue clearing before imaging the stained sample.

[0031] In some embodiments, the whole sample staining is staining of a tissue sample that has not been physically sectioned and remains intact in three-dimensional structure, the whole sample including a complete animal individual, a complete organ, or a larger tissue block that maintains the integrity of the overall structure, the organ or tissue block including a brain, a spinal cord, a peripheral nerve, a liver, a kidney, or a combination thereof.

[0032] In a second aspect, the present application provides a nucleic acid construct comprising a nucleic acid sequence encoding a proximity labeling enzyme and a nucleic acid sequence encoding a soluble tag, wherein the soluble tag is expressed in fusion with the proximity labeling enzyme.

[0033] In some embodiments, the proximity labeling enzyme is a biotin ligase.

[0034] In some embodiments, the biotin ligase is selected from BioID, BioID2, TurboID, miniTurbo, Split-BioID, Split-TurboID, BASU, AirID, and variants thereof.

[0035] In some embodiments, the soluble tag is GB1 (SEQ ID NO: 6) or a variant thereof.

[0036] In some embodiments, the coding sequence of the soluble tag is located 3’ to the coding sequence of the proximity labeling enzyme.

[0037] In a third aspect, the present application provides an expression vector comprising the nucleic acid construct of the second aspect.

[0038] In a fourth aspect, the present application provides a fusion protein comprising a proximity labeling enzyme and a solubility tag, wherein the solubility tag is expressed in fusion with the proximity labeling enzyme.

[0039] In some embodiments, the proximity labeling enzyme is a biotin ligase.

[0040] In some embodiments, the biotin ligase is selected from the group consisting of BioID, BioID2, TurboID, miniTurbo, Split-BioID, Split-TurboID, BASU, AirID, and variants thereof.

[0041] In some embodiments, the solubility tag is GB1 or a variant thereof.

[0042] In some embodiments, the solubility tag is located at the C-terminus of the proximity labeling enzyme.

[0043] In a fifth aspect, the present application provides use of the nucleic acid construct of the second aspect, the expression vector of the third aspect, or the fusion protein of the fourth aspect in the manufacture of a reagent for neuronal single cell reconstruction.

[0044] The present application further provides the following specific items:

[0045] 1. A method for neuronal single cell reconstruction, the method comprising:

[0046] a) expressing a solubility-enhanced proximity labeling enzyme in a target neuron and providing biotin to the target neuron to form biotinylated proteins in the neuron;

[0047] b) performing whole sample staining of the biotinylated proteins using monovalent streptavidin coupled with a detectable label;

[0048] c) imaging the stained sample to obtain a neuronal structure image;

[0049] d) reconstructing the morphological structure of a single neuron based on the image data.

[0050] 2. The method of item 1, wherein the proximity labeling enzyme is a biotin ligase.

[0051] 3. The method of item 2, wherein the biotin ligase is selected from the group consisting of BioID, BioID2, TurboID, miniTurbo, Split-BioID, Split-TurboID, BASU, AirID, and variants thereof.

[0052] 4. The method of any one of items 1-3, wherein the proximity labeling enzyme is obtained by expression of a nucleic acid sequence encoding the enzyme in the target neuron.

[0053] 5. The method of item 4, wherein the nucleic acid sequence further comprises a fragment encoding a soluble tag.

[0054] 6. The method of item 5, wherein the soluble tag is GB1 (SEQ ID NO: 6) or a variant thereof.

[0055] 7. The method of item 4 or 5, wherein the coding sequence for the soluble tag fragment is located 3’ of the coding sequence for the proximity labeling enzyme.

[0056] 8. The method of any one of items 4-7, wherein the nucleic acid sequence further comprises a fragment encoding a localization signal.

[0057] 9. The method of item 8, wherein the localization signal is selected from the group consisting of a membrane localization signal, a nuclear localization signal, a cytosolic localization signal, or an endoplasmic reticulum localization signal.

[0058] 10. The method of any one of items 4-9, wherein the nucleic acid sequence further comprises a fragment encoding a fluorescent protein.

[0059] 11. The method of item 10, wherein the fluorescent protein is selected from the group consisting of green fluorescent protein (GFP), blue fluorescent protein (BFP), cyan fluorescent protein (CFP), yellow fluorescent protein (YFP), orange fluorescent protein (OFP), red fluorescent protein (RFP), near-infrared fluorescent protein (miRFP670), or a derivative thereof.

[0060] 12. The method of any one of items 4-11, wherein the nucleic acid sequence is introduced into the host cell genome via genomic integration.

[0061] 13. The method of any one of items 4-11, wherein the nucleic acid sequence is delivered to the target neuron via an exogenous vector.

[0062] 14. The method of item 13, wherein the exogenous vector is selected from the group consisting of:

[0063] a) a cationic liposome, an anionic liposome, a pH-sensitive liposome, a fusogenic liposome, or an immunoliposome;

[0064] b) lipid / nucleic acid aggregates or solid lipid nanoparticles (SLN);

[0065] c) polymeric nanoparticles, micelles or calcium phosphate nanoparticles;

[0066] d) viral vectors or virus-like particles (VLP);

[0067] e) antibody, aptamer or polypeptide conjugation system;

[0068] f) small molecule conjugation system such as N-acetylgalactosamine (GalNAc), cholesterol, fatty acid, etc.

[0069] 15. The method of any one of items 4-14, wherein the nucleic acid sequence initiates expression of a gene of interest through a conditional gene expression system.

[0070] 16. The method of item 15, wherein the conditional gene expression system is capable of activating expression of a gene of interest under specific conditions, which can be chemical, physical, biological or environmental factors, and the system is selected from the group consisting of Cre-LoxP recombinase-based regulatory system, Flp-FRT recombinase-based regulatory system, tetracycline regulatory system (Tet-on / Tet-off) and temperature-sensitive promoter, or a combination thereof.

[0071] 17. The method of any one of items 4-16, wherein the nucleic acid sequence initiates expression of the proximity marker enzyme in only a subset of target neurons through a sparse expression system.

[0072] 18. The method of item 17, wherein the sparse expression is achieved by a system selected from the group consisting of dilution promoter system, dual promoter control system, tunable dose induction system, viral dose control system and random recombination system, or a combination thereof.

[0073] 19. The method of item 18, wherein the sparse expression system is a dual sparse expression system that requires two different sets of promoter controls to be satisfied in sequence to activate expression of a gene of interest.

[0074] 20. The method of any one of items 1-19, wherein the detectable label is selected from the group consisting of radioisotope label, fluorescent label, luminescent label, chromophore tag, Raman spectroscopy probe, polarization frequency probe, DNA probe, reporter molecule, substance or enzyme capable of reacting with a substrate to produce a detectable signal, and dye.

[0075] 21. The method of any one of clauses 1-20, wherein the imaging modality is matched to the type of detectable label selected from the group consisting of fluorescent microscopy, chemiluminescence imaging, bioluminescence imaging, Raman spectroscopy imaging, polarization imaging, isotope imaging, or other imaging modality capable of detecting the signal of the label.

[0076] 22. The method of any one of clauses 1-21, wherein the target neurons are neuronal cells selected based on anatomical location, neurotransmitter type, gene expression profile, or specific markers.

[0077] 23. The method of clause 22, wherein the neurotransmitter type of the target neurons is selected from one or more of glutamatergic neurons, GABAergic neurons, dopaminergic neurons, serotonergic neurons, noradrenergic neurons, or cholinergic neurons.

[0078] 24. The method of any one of clauses 1-23, wherein the stained sample is subjected to tissue clearing prior to step c).

[0079] 25. The method of any one of clauses 1-24, wherein the whole sample staining is staining of a tissue sample that has not been physically sectioned and maintains the integrity of the three-dimensional structure, the whole sample comprising a complete animal individual, a complete organ, or a larger tissue block that maintains the integrity of the structure, the organ or tissue block comprising a brain, a spinal cord, a peripheral nerve, a liver, a kidney, or a combination thereof.

[0080] 26. A nucleic acid construct comprising:

[0081] a) a nucleic acid sequence encoding a proximity labeling enzyme; and

[0082] b) a nucleic acid sequence encoding a soluble tag, wherein the soluble tag is expressed in fusion with the proximity labeling enzyme.

[0083] 27. The nucleic acid construct of clause 26, wherein the proximity labeling enzyme is a biotin ligase.

[0084] 28. The nucleic acid construct of clause 27, wherein the biotin ligase is selected from the group consisting of BioID, BioID2, TurboID, miniTurbo, Split-BioID, Split-TurboID, BASU, AirID, and variants thereof.

[0085] 29. The nucleic acid construct of any one of clauses 26-28, wherein the soluble tag is GB1 (SEQ ID NO: 6) or a variant thereof.

[0086] 30. The nucleic acid construct of any one of items 26-29, wherein the coding sequence of the soluble tag is located 3’ to the coding sequence of the proximity labeling enzyme.

[0087] 31. An expression vector comprising the nucleic acid construct of any one of items 26-30.

[0088] 32. A fusion protein comprising:

[0089] a) a proximity labeling enzyme; and

[0090] b) a soluble tag, wherein the soluble tag is expressed in fusion with the proximity labeling enzyme.

[0091] 33. The fusion protein of item 32, wherein the proximity labeling enzyme is a biotin ligase.

[0092] 34. The fusion protein of item 33, wherein the biotin ligase is selected from the group consisting of BioID, BioID2, TurboID, miniTurbo, Split-BioID, Split-TurboID, BASU, AirID, and variants thereof.

[0093] 35. The fusion protein of any one of items 32-34, wherein the soluble tag is GB1 or a variant thereof.

[0094] 36. The fusion protein of any one of items 32-35, wherein the soluble tag is located C-terminal to the proximity labeling enzyme.

[0095] 37. Use of the nucleic acid construct of items 26-30, the expression vector of item 31, or the fusion protein of items 32-35 in the manufacture of a reagent for neuronal single cell reconstruction. BRIEF DESCRIPTION OF DRAWINGS

[0096] The specific features of the invention to which this application relates are as set forth in the claims appended hereto. The features and advantages of the invention to which this application relates are better understood by reference to the detailed description of example embodiments and accompanying drawings. A brief description of the drawings is as follows:

[0097] Figure 1A - H shows the construction of seTurboID by fusing a solubility-enhancing tag (GB1) to the end of TurboID, enabling efficient cell type-specific labeling in neurons.

[0098] Figure 1A Schematic showing cell type-specific neuronal labeling, including three steps of Cre-dependent seTurboID expression, proximity biotinylation, and streptavidin staining.

[0099] Figure 1B Representative confocal immunofluorescence images showing expression of FLAG-tagged TurboID or seTurboID in Sert-Cre mouse dorsal raphe nucleus (DRN) 5-hydroxytryptaminergic neurons. Sections were immunostained for FLAG tag and biotin labeling mediated by seTurboID was detected in PFC and DRN (virus injection site). Scale bar, 250 μm.

[0100] Figure 1C Representative confocal immunofluorescence images showing FLAG-tagged TurboID (left) and seTurboID (middle) in DRN 5-hydroxytryptaminergic neurons. Right panel shows distribution of biotinylated neuronal cell bodies and axons in multiple brain regions mediated by seTurboID. Scale bar, 250 μm.

[0101] Figure 1D Quantitative analysis of TurboID and seTurboID protein expression levels. Expression levels in OB, PFC, STR, LH, and DRN were analyzed by measuring the average FLAG immunofluorescence intensity normalized to the biotinylation area. Data are mean ± s.e.m., n = 3 per group, two-tailed unpaired t test.

[0102] Figure 1E Cell type-specific expression of FLAG-tagged seTurboID in DRN 5-hydroxytryptaminergic neurons and co-labeling with biotin and Tph2. Lower panel is a magnified view of the white box area in the upper panel. Scale bars: upper panel, 250 μm; lower panel, 50 μm.

[0103] Figure 1F Representative confocal microscopy images showing seTurboID labeling in CaMKII-Cre mouse cortical projection neurons. Scale bar, 100 μm.

[0104] Figure 1G Representative confocal microscopy images showing seTurboID labeling in CaMKII-Cre mouse cortical projection neurons. Scale bar, 100 μm. Figure 1F High magnification microscopy images of the area indicated by the dashed box in the middle panel, showing a dendritic spine (indicated by an arrow). Scale bar, 20 μm.

[0105] Figure 1H High magnification microscopy images of the area indicated by the dashed box in the middle panel, showing a dendritic spine (indicated by an arrow). Scale bar, 20 μm. Figure 1G High magnification microscopy images of the area indicated by the dashed box in the middle panel, showing a dendritic spine (indicated by an arrow). Scale bar, 20 μm. Figure 1G Magnified view of the corresponding area in the middle panel. Scale bar, 5 μm.

[0106] Figure 2A-E shows the binding properties and imaging results of the comparison between wild-type and monovalent streptavidin for whole-brain staining of DRN serotonergic neurons.

[0107] Figure 2A A schematic diagram showing the difference in the number of biotin binding sites between wild-type and monovalent streptavidin.

[0108] Figure 2B A schematic diagram showing the workflow of LINCS.

[0109] Figure 2C A sagittal light sheet microscopy imaging result at 0.2 mm from the midline showing the staining of DRN serotonergic neurons by wild-type (left) and monovalent (right) streptavidin, scale bar 500 μm.

[0110] Figure 2D A sagittal light sheet microscopy imaging result at 0.2 mm from the midline showing the staining of DRN serotonergic neurons by wild-type (left) and monovalent (right) streptavidin, scale bar 500 μm. Figure 2C

[0111] Figure 2E A sagittal light sheet microscopy imaging result at 0.2 mm from the midline showing the staining of DRN serotonergic neurons by wild-type (left) and monovalent (right) streptavidin, scale bar 500 μm.

[0112] Figure 3A -C shows the overall workflow of the LINCS method described in this application and its comparison with existing whole-brain labeling methods.

[0113] Figure 3A A schematic diagram showing the workflow of LINCS: in vivo labeling of specific neuronal populations by AAV delivery of seTurboID in Cre transgenic mice; biotin administration via drinking water; brain harvesting three weeks after virus injection and fixation in 4% paraformaldehyde; followed by sequential pretreatment, whole-mount staining, and clearing; and finally light sheet microscopy imaging.

[0114] Figure 3B A schematic diagram showing the comparison between the iDISCO+ method and the LINCS method in the whole-brain labeling workflow, where FP represents fluorescent protein and W represents washing step.

[0115] Figure 3C A schematic diagram showing the comparison between the iDISCO+, vDISCO, and LINCS methods in the workflow.

[0116] Figure 4A -F shows the differences in labeling performance between the LINCS method described in this application and the iDISCO+ and vDISCO methods in labeling midbrain dopaminergic and serotonergic neurons in whole-brain and half-brain samples. ​

[0117] Figure 4A A half-brain level light sheet microscopy image taken 3.1 mm down from the dorsal surface is shown to compare the imaging performance of LINCS (seTurboID, 3 weeks of expression) and iDISCO+ (mGFP, 3 weeks of expression) on VTA and SNc dopaminergic neurons. Below is a magnified view of the area indicated by the dashed box. Scale bars: 1 mm above, 200 pm below.

[0118] Figure 4B A 1 mm thick brain section sagittal light sheet microscopy image taken 1.3 mm from the midline is shown to compare the labeling performance of LINCS (seTurboID, 3 weeks of expression) and iDISCO+ (mGFP, 3 weeks of expression) on VTA and SNc dopaminergic neurons. Right is a magnified view of the area indicated by the dashed box. Scale bars: 1 mm left, 500 pm right.

[0119] Figure 4C A 1 mm thick brain section sagittal light sheet microscopy image taken 1.3 mm from the midline is shown to compare the imaging performance of LINCS and iDISCO+ at 640 nm laser power from 6.0 mW (10%) to 57.8 mW (100%). Scale bar: 1 mm.

[0120] Figure 4D A half-brain coronal light sheet microscopy image taken 0.5 mm anterior to the anterior halved door (left is raw AlexaFluor 647 fluorescence signal, right is extracted signal) is shown to compare the labeling performance of LINCS and iDISCO+ on VTA and SNc dopaminergic neuron axons. Scale bar: 1 mm.

[0121] Figure 4E For Figure 4A Quantitative analysis of signal density and intensity of different labeling methods in different brain regions defined by Allen Common Coordinate Framework v3 (CCFv3) (mean ± s.e.m, n = 2 brain samples per group).

[0122] Figure 4F A heatmap showing the signal density of VTA and SNc dopaminergic neuron axons. Brain regions are arranged in hierarchical order (structural order 0-8). Each column represents an independent sample.

[0123] Figure 5A -L shows the performance evaluation of the LINCS method described in this application in labeling whole brain DRN serotonergic neurons and comparison with existing methods.

[0124] Figure 5AThe results of horizontal light-panel microscopy imaging (3.1 mm from the dorsal surface) are shown, comparing the performance of LINCS (seTurboID, expressed for 3 weeks, whole brain sample) and iDISCO+ (EGFP, expressed for 2 months, whole brain sample; mGFP, expressed for 2 months, hemibrain sample) in DRN 5-hydroxytryptamine neuron labeling. Vascular markers in the iDISCO+ whole brain sample were removed by computer. Scale bar, 1 mm.

[0125] Figure 5B Light sheet microscopy imaging of DRN 5-hydroxytryptamine neurons and their axons in different brain regions. Scale bar, 300 μm.

[0126] Figure 5C right Figure 5B The signal density and intensity of each labeling method shown were quantitatively analyzed in different brain regions defined by Allen CCFv3. Mean ± standard error, n = 3.

[0127] Figure 5D This image shows a coronal light section microscopy image of the whole brain and hemibrain located 0.7 mm posterior to the anterior fontanelle (left: original Alexa Fluor 647 fluorescence signal; right: extracted signal). The labeling effects of LINCS, iDISCO+, and vDISCO on DRN 5-hydroxytryptamine neurons were compared. Scale bar: 1 mm.

[0128] Figure 5E Heatmaps showing axonal signal density of DRN 5-hydroxytryptamine neurons in different brain regions defined by Allen CCFv3. Brain regions are sorted by structural level 0–8, with each column representing an independent sample.

[0129] Figure 5F show Figure 5C High-contrast imaging results of DRN 5-hydroxytryptamine neurons in iDISCO+ labeled whole-brain and hemibrain samples. Scale bar, 300 μm.

[0130] Figure 5G This diagram illustrates radial signal analysis. Axonal signals are quantified in equidistant concentric layers from the brain surface to the brain center, analyzing the signal distribution with depth.

[0131] Figure 5H The radial distribution of signal density (top) and intensity (bottom) of whole-brain DRN 5-hydroxytryptaminergic neurons labeled with LINCS and iDISCO+ is shown from the brain surface (layer 1) to the brain center (layer 24). Mean ± standard error, n = 3.

[0132] Figure 5IImaging results of horizontal light sheet microscopy of LINCS, iDISCO+, and vDISCO in DRN 5-hydroxytryptaminergic neuron cell body labeling (3.1 mm from dorsal surface). Vessel labeling was computationally removed in iDISCO+ whole brain samples. Scale bar, 500 μm.

[0133] Fig. 5J shows horizontal light sheet microscopy imaging results of LINCS labeling (seTurboID, 3 weeks of expression) of DRN 5-hydroxytryptaminergic neurons (projection thickness 40 μm, 3.1 mm from dorsal surface) with AAV injection site marked. Scale bar, 1 mm.

[0134] Figure 5K Magnification of the solid line box area in Fig. 5J, and further magnification of the dashed line box area on the right. Lower contrast settings were applied to enhance visualization of axon details. Scale bars, 500 μm (left), 350 μm (right).

[0135] Figure 5L Imaging results of horizontal light sheet microscopy of iDISCO+ method (whole brain sample) labeling of DRN 5-hydroxytryptaminergic neurons (projection thickness 40 μm, 3.1 mm from dorsal surface). Magnification of the dashed line box labeled area on the right, with white arrows indicating vessel labeling. Scale bars, 1 mm (left), 500 μm (right).

[0136] Figure 6A -G shows the application of LINCS in combination with D-LMBmap in whole brain axon segmentation and signal quantification analysis of different neuron types, and examples of combined use with iDISCO+ immunostaining.

[0137] Figure 6A Show the results of D-LMBmap analysis of DRN 5-hydroxytryptaminergic neuron axon density in different brain regions defined by Allen CCFv3.

[0138] Figure 6B Show representative 3D cube renderings of axon segmentation in selected brain regions. Lower panel shows axon density measurements in anatomical subregions defined by Allen CCFv3.

[0139] Fig. 6C shows the results of D-LMBmap analysis of VTA dopaminergic neuron axon density in different brain regions defined by Allen CCFv3.

[0140] Figure 6D Show the results of D-LMBmap analysis of VTA GABAergic neuron axon density in different brain regions defined by Allen CCFv3.

[0141] Figure 6E Schematic workflow showing iDISCO+ immunostaining combined with LINCS applied to 1 mm thick brain sections. d: days; 1 st Ab: primary antibody; 2 nd Ab: fluorophore-coupled secondary antibody; mSA: fluorophore-coupled monovalent streptavidin.

[0142] Figure 6F Sagittal light sheet microscopy imaging results of a 1 mm thick brain section at 1.1 mm from the midline. The sample was labeled for midbrain dopaminergic neurons using LINCS and for cholinergic neurons (ChAT) using the iDISCO+ method. Sparse LINCS labeling was used to visualize dopaminergic neurons in the VTA and SNc regions. The right panel is a magnification of the area framed by the dashed line in the left image. Scale bars, 2 mm (left), 200 μm (right).

[0143] Figure 6G Sagittal light sheet microscopy imaging results of a 1 mm thick brain section at 1.0 mm from the midline. The sample was labeled for midbrain dopaminergic neurons using LINCS and for microglia cells (Iba1) using the iDISCO+ method. Sparse LINCS labeling was used to visualize dopaminergic neurons in the VTA and SNc regions. The right panel is a magnification of the area framed by the dashed line in the left image. Scale bars, 2 mm (left), 200 μm (right).

[0144] Figure 7A - I shows the application of LINCS to long-range neurons, combined with a retrograde AAV delivery strategy to label and 3D image cortical-spinal projecting neurons. Image orientation is indicated in FIGS. 7D, 7G, 7H, and 7I: L, left; R, right; A, anterior; P, posterior; D, dorsal; V, ventral.

[0145] Figure 7A Schematic showing the experimental procedure for injection of the retrograde AAV vector CAG-DIO-mem-seTurboID in the cervical spinal cord (C7-C8) of CaMKII-Cre mice.

[0146] Figure 7B Representative widefield fluorescence imaging results of brain sections (0.5 mm anterior to the anterior commissure) showing LINCS labeling of DRN serotonergic neurons expressed over 2 weeks. Top, soluble form; bottom, membrane-localized form. Sections were biotin-stained and overlaid with Allen CCFv3 brain region registration results. The right panel is a magnification of the area framed by the solid line in the striatum (STR) of the left image. Scale bars: 1 mm (left), 200 μm (right).

[0147] Figure 7C Quantification of biotin-positive axon density in different brain regions rostral to the midbrain according to Allen CCFv3 standard (mean ± s.e.m., 3 brain samples per group, two-tailed unpaired t-test).

[0148] Figure 7D shows a three-dimensional rendering of a whole brain and partial spinal cord (to L3) sample after unilateral AAV injection (white arrowheads) and LINCS staining. Corticospinal neuron visualization is shown. Scale bar, 2 mm.

[0149] Figure 7E shows a magnified view (1.1 mm projection) of the left solid box region in Figure 7D, corresponding to axon tracts of the corticospinal tract. Scale bar, 250 μm.

[0150] Figure 7F shows a magnified view (1.1 mm projection) of the right dashed box region in Figure 7D, corresponding to labeled axon fibers in the LI vertebral body. Scale bar, 500 μm.

[0151] Figure 7G shows a coronal light sheet microscopy image (cut half, position: 1.3 mm posterior to the anterior rhomencephalic commissure), with labeled neuronal cell bodies in the motor cortex (Ml, M2) and somatosensory cortex (SI, S2). Image is overlaid with Allen CCFv3 brain region registration results. Scale bar, 2 mm.

[0152] Figure 7H shows representative coronal light sheet imaging results (0.5 mm projection) of labeled corticospinal neurons (indicated by dashed arrows in Figure 7G) within the S2 cortex. Scale bar, 100 μm.

[0153] Figure 7I Figure 7I shows a sagittal light sheet microscopy image (3.4 mm projection), showing long-range projections of corticospinal neurons from the Ml / M2 and SI cortex. Scale bar, 250 μm.

[0154] Figure 8A -N shows the application of LINCS at the whole animal level, enabling multi-organ and tissue neuron labeling and three-dimensional imaging through AAV delivery combined with whole-body staining and tissue clearing.

[0155] Figure 8A Schematic showing retro-orbital injection of MaCPNS2 AAV carrying hSyn-mem-seTurboID in wild-type mice, followed by heart perfusion-based whole-body staining and clearing.

[0156] Figure 8B shows whole-body imaging results of a mouse after LINCS staining, using monomeric streptavidin labeling, with autofluorescence providing anatomical reference. Scale bar, 5 mm.

[0157] Figure 8C is a magnified view of the white boxed area in Figure 8B. Scale bar, 1 mm.

[0158] Figure 8D is a magnified view of another white boxed area in Figure 8B. Scale bar, 500 μm.

[0159] Figure 8E Figure 8E is a magnified view of a third white boxed area in Figure 8B. Scale bar, 1 mm.

[0160] Figure 8F shows a three-dimensional visualization of neuron labeling in the large intestine. Scale bar, 1 mm.

[0161] Figure 8G Figure 8G is a magnified view of the white boxed area in Figure 8F. Scale bar, 200 μm.

[0162] Figure 8H shows a three-dimensional visualization of neuron labeling in the proximal small intestine. Scale bar, 1 mm.

[0163] Figure 8I Figure 81 is a magnified view of the white boxed area in Figure 8H. Scale bar, 150 μm.

[0164] Figure 8J shows a three-dimensional visualization of neuron labeling in the distal small intestine. Scale bar, 1 mm.

[0165] Figure 8K Figure 8K is a magnified view of the white boxed area in Figure 8J. Scale bar, 100 μm.

[0166] Figure 8L Figure 8L shows a three-dimensional visualization of neuron labeling in the tail tissue. Scale bar, 1 mm.

[0167] Figure 8M shows a three-dimensional visualization of neuron labeling in the right front paw, with autofluorescence providing anatomical reference. Scale bar, 1 mm.

[0168] Figure 8N Figure 8N is a magnified view of the white boxed area in Figure 8M. Scale bar, 200 μm.

[0169] Figure 9A -E shows the application of LINCS in tissue expansion microscopy (ExM), demonstrating fine visualization and signal quantification of hippocampal PV neurons by different biotin detection methods (fluorescent streptavidin and isHCR).

[0170] Figure 9ASchematic diagram showing two visualization methods for biotin labeling: fluorescent-streptavidin (fluorescent-SA, top) and immunosignal hybridization chain reaction (isHCR, bottom). Both methods include tissue anchoring, gelation, digestion, and amplification steps. AcX, 6-((acryloyl)amino)hexanoic acid, succinimidyl ester; fluorescent-SA, fluorescent dye-conjugated wild-type streptavidin; SA, unconjugated wild-type streptavidin; ssDNA, single-stranded DNA.

[0171] Figure 9B Contrastive confocal images (maximum intensity projection) of 50 μm brain sections after amplification showing hippocampal PV neurons labeled with fluorescent-SA and isHCR methods are shown. Right panel shows high-contrast display of fluorescent-SA images. Images were acquired under identical microscope conditions. Scale bars, 500 μm (left), 100 μm (right).

[0172] Figure 9C Quantification of average signal intensity for fluorescent-SA and isHCR methods is shown. Mean ± s.e.m, n = 4 per group, two-sided unpaired t-test.

[0173] Figure 9D Three-dimensional reconstruction of hippocampal PV neurons labeled by fluorescent-SA method is shown. Side view shows the overall structure. Right panel shows single-layer Z-plane details of the area indicated by the box in the left panel. Images were acquired with Z-stack compensation. Scale bars, 50 μm.

[0174] Figure 9E Three-dimensional reconstruction of hippocampal PV neurons labeled by isHCR method is shown. Side view shows the overall structure. Right panel shows single-layer Z-plane details of the area indicated by the box in the left panel. Images were acquired with Z-stack compensation. Scale bars, 50 μm.

[0175] Figure 10A -K shows the LINCS-based three-dimensional single-neuron reconstruction and sparse labeling strategy described herein.

[0176] Figure 10A Schematic diagram showing the LINCS three-dimensional single-neuron reconstruction workflow is shown.

[0177] Figure 10B Schematic diagram showing retrograde dual-AAV for sparse labeling is shown.

[0178] Figure 10CA composite visualization of 11 reconstructed striatal projections VTA and SNc dopaminergic neurons is shown, aligned with a reference brain and presented in the horizontal (top) and sagittal (bottom) planes.

[0179] Figure 10D This study presents the quantification results of labeled cell numbers obtained under different controlled retrograde AAV titers, where the enhanced AAV titer was maintained at 10. 9 VG / μL. Mean ± standard error, n = 3, 5, 3 brains.

[0180] Figure 10E Representative light-sheet microscopy images (top) and corresponding Imaris-traced reconstructions of neuronal cell bodies and dendrites (bottom) are shown. Images display Z-projections of varying thicknesses (3–99 μm) from left to right. Scale bar, 40 μm.

[0181] Figure 10F Representative light-sheet microscopy images (top) and corresponding Imaris-traced axonal reconstruction results (bottom) are shown. Images were projected using Z-projection at different thicknesses to provide full visualization of the axons. Scale bar: 80 μm.

[0182] Figure 10G Representative light-sheet microscopy images (top) and surface rendering results generated by Imaris (bottom) are shown, revealing the dense axonal and dendritic structure of striatal projection dopaminergic neurons. Scale bar, 120 μm.

[0183] Figure 10H A composite visualization of 11 neurons (dopaminergic neurons 1–11) is shown, aligned with a reference brain. The outlines of the midbrain, dorsal striatum (STRd), and ventral striatum (STRv) regions are marked. Brain orientation is indicated in the images. Individual neurons are also shown separately, with brain regions labeled and the viewing angle adjusted for optimal display. L, left; R, right; D, dorsal; V, ventral.

[0184] Figure 10I Showing Figure 10G The quantitative results of the surface area volume of dense axonal dendrites are shown.

[0185] Figure 10J Light sheet microscopy images (signals) of individual axonal terminals from three dopaminergic neurons (neurons 1–3) and their corresponding tracking reconstructions are shown, presented in the optimal viewing orientation. Scale bar, 30 μm.

[0186] Figure 10K The results of three-dimensional reconstructions of striatal projection dopaminergic neurons from three different morphological subgroups are presented, aligned with a reference brain. The midbrain, dorsal striatum STRd, and ventral striatum STRv regions are marked.

[0187] Figure 11A - J shows the Cre-KO-AAV strategy described in this application, which achieves sparse labeling by partially knocking out Cre expression in Cre transgenic mice, demonstrating the effect of this system in terms of stability, controllability and long-term labeling.

[0188] Figure 11A A schematic diagram of the Cre-KO-AAV strategy is shown. The system consists of three AAV vectors, each encoding SaCas9 and a different guide RNA (sgRNA #1-3) targeting the Cre gene. After delivery to Cre transgenic mice, the system partially eliminates Cre expression in Cre-positive (Cre + ) cells, thereby achieving sparse labeling.

[0189] Figure 11B Sequence alignment of sgRNA #1-3 in the Cre gene targeting region in DAT-Cre and Vgat-Cre mouse strains is shown. The Cre sequence was PCR amplified and verified by Sanger sequencing, and the target sequence is highlighted.

[0190] Figure 11C Quantitative results of the number of sparsely labeled cells obtained using different combinations of Cre-KO AAV in the VTA of Vgat-Cre mice are shown. Cre-KO AAV (total titer 1 x 10 0 VG / μL, mixed in equal proportions) was delivered 1 week before injection of AAV9-CAG-DIO-H2B-GFP reporter virus. Sample sizes were: gRNA #1 (n = 6), gRNA #2 (n = 3), gRNA #3 (n = 4), gRNA #1+#3 (n = 5), gRNA #1+#2+#3 (n = 7). Data are presented as mean ± s.e.m., and multiple comparisons were performed using Welch's corrected unpaired t-test.

[0191] Figure 11D A flowchart showing the experimental procedure for achieving sparse neuron labeling in the VTA of Vgat-Cre mice using the Cre-KO-AAV system is shown. Mice received stereotaxic injection of Cre-KO AAV with AAV9-EF1α-DIO-H2B-GFP (bulk labeling), followed by injection of AAV9-EF1α-DIO-mCherry after a Cre knockdown period to achieve sparse labeling.

[0192] Figure 11E Representative confocal images showing mCherry expression after a 2-week knockdown period using different titers of Cre-KO AAV are shown. Scale bar: 250 μm.

[0193] Figure 11F Representative confocal images showing mCherry expression obtained at different knockout time points with fixed Cre-KO AAV titer (1 x 1011 0 VG / μL, mixed in equal proportion) in VTA. Scale bar: 250 μm.

[0194] Figure 11G Quantification of mCherry positive cells obtained in VTA at different Cre-KO AAV titers after 2 weeks of knockout period (n = 4, 3, 3).

[0195] Figure 11H Quantification of mCherry positive cells obtained in VTA at different knockout time points with fixed Cre-KO AAV titer (1 x 1011 0 VG / μL, mixed in equal proportion) (n = 3, 4, 4).

[0196] Figure 11I Representative confocal images showing neuronal labeling obtained with double AAV system and Cre-KO-AAV system at 3 weeks and 2 months post injection. Scale bar: 100 μm.

[0197] Figure 11J Comparison of labeling stability of double AAV system (control: 1 x 1011 7 VG / μL, enhanced: 1 x 1011 9 VG / μL, ratio 1:10) and Cre-KO-AAV system (1 x 1011 0 VG / μL, mixed in equal proportion) at different expression time points (n = 3, 4, 3, 6).

[0198] Figure 12A - J shows the Cre-KO-AAV combined with double AAV system described in the present application applied to LINCS to achieve sparse labeling of midbrain and hypothalamic GABAergic neurons and three-dimensional single neuron reconstruction.

[0199] Figure 12A A schematic diagram showing the principle of Cre-KO-AAV combined with double AAV system (Cre-KO + double AAV) for achieving sparse labeling of midbrain region.

[0200] Figure 12B A schematic diagram showing the principle of Cre-KO-AAV combined with projection-specific double AAV (retrograde double AAV) system (Cre-KO + retrograde double AAV) for achieving sparse labeling of specific projection neurons.

[0201] Figure 12C Composite visualizations of eight reconstructed VTA and DpMe GABAergic neurons are shown, aligned to a reference brain atlas, and displayed in horizontal (top) and sagittal (bottom) views.

[0202] Figure 12D Statistical results of the number of labeled neurons obtained with different combinations of Cre-KO-AAV and dual-AAV systems (mean ± s.e.m.) are shown.

[0203] Figure 12E Three-dimensional renderings of reconstructed interneurons and projection GABAergic neurons are shown, aligned to a reference brain atlas, and highlighting the midbrain region.

[0204] Figure 12F Composite visualizations of eight VTA and DpMe GABAergic neurons (GABAergic neuron 1-8) are shown, aligned to a reference brain atlas, and highlighting the midbrain region. Each neuron is shown individually, and the brain region orientation is labeled (L, left; R, right; D, dorsal; V, ventral).

[0205] Figure 12G Composite visualizations of five reconstructed hypothalamic GABAergic neurons projecting to the periaqueductal gray (PAG) are shown, aligned to a reference brain atlas, and displayed in horizontal (top) and sagittal (bottom) views.

[0206] Figure 12H Three-dimensional renderings of GABAergic neurons projecting to the PAG are shown, aligned to a reference brain atlas, and highlighting the PAG and hypothalamus.

[0207] Figure 12I Composite visualizations of five hypothalamic GABAergic neurons projecting to the PAG (9-13) are shown, aligned to a reference brain atlas, and highlighting the PAG and hypothalamus. Each neuron is shown individually, and the brain region orientation is labeled (L, left; R, right; D, dorsal; V, ventral).

[0208] Figure 12J Light-sheet microscopy imaging results of single axon terminals of the five GABAergic neurons (9-13) are shown (top) and corresponding fiber-reconstruction results (bottom), with each panel showing a different axon terminal. Arrowheads indicate the axon terminal end. Note that the image of neuron 12 has a slight artifact due to stitching error. Scale bar, 10 μm. DETAILED DESCRIPTION

[0209] The following detailed description of the application is provided as an example to enable those skilled in the art to carry out the application. Other advantages and effects of the application will be apparent from the disclosure.

[0210] Definitions of terms

[0211] As used herein, the term "proximity labeling enzyme" refers to an enzyme that is capable of covalently linking a chemical tag (e.g. biotin) to an endogenous biomolecule in its spatial proximity under live cell or live organism conditions. Typical proximity labeling enzymes include peroxidases (e.g. APEX, APEX2) and biotin ligases (e.g. BioID, BioID2, TurboID, miniTurbo, AirID, BASU, Split-BioID, Split-TurboID). These tool enzymes enable high specificity labeling of spatially proximal targets by catalyzing locally efficient covalent modification reactions. Variants of the above enzymes that contain the same tagging activity are also within the scope of this term.

[0212] As used herein, the term "solubility tag" refers to a polypeptide or protein fragment that is capable of being fused to a target protein (e.g. a proximity labeling enzyme) to improve its solubility and / or stability in cells or in vitro. The solubility tag can also improve the expression level, folding efficiency and yield of the fusion protein in host cells, thus facilitating the production of high levels of functional protein. The solubility tag can be located at the N-terminus, C-terminus or internal junction site of the target protein, and can be connected to the target protein via a flexible or rigid linker peptide. Non-limiting examples include GB1 and its variants, maltose binding protein (MBP), glutathione S-transferase (GST), thioredoxin (TRX), SUMO, NusA, Thioredoxin A, Protein L, Strep-tag II and functional equivalents thereof.

[0213] As used herein, the term "GB1" refers to a protein fragment derived from the B1 domain of streptococcal protein G (US8221998B2). GB1 consists of 56 amino acid residues and folds into a compact conformation consisting of four beta-strands and one alpha-helix. GB1 has a developed hydrophobic core, lacks disulfide bonds, free cysteines, prolines and metal binding motifs, and exhibits good stability and solubility. In the present application, GB1 also includes variants that contain several amino acid substitutions but retain the above-mentioned structure and physicochemical properties.

[0214] As used herein, the term "monovalent streptavidin" refers to a form of streptavidin having a single biotin binding site. In one common form, streptavidin exists as a tetramer, with only one monomer retaining biotin binding activity, the remaining monomers being inactive, thereby enabling a molecule of monovalent streptavidin to bind a molecule of biotin with high specificity. The term also includes other configurations that functionally behave as monovalent, such as configurations formed by coupling a monomeric streptavidin with one or more bulky groups that sterically or structurally limit only one biotin binding site to be available for binding.

[0215] As used herein, the term "detectable label" refers to a moiety that binds to a molecule to be detected (e.g., streptavidin, biotinylated protein, or analyte) that is capable of directly or indirectly producing a detectable signal. A detectable label can directly produce a detectable signal by itself, such as a radioisotope label, a fluorescent label, a chromophore tag, a Raman spectroscopic probe, a polarized frequency probe, a DNA probe, or a reporter molecule; or indirectly produce a detectable signal by catalyzing a chemical change in a substrate compound or composition, such as a horseradish peroxidase, an alkaline phosphatase, a luciferase, or other enzyme capable of generating a detectable substrate. Suitable detectable labels include, but are not limited to, radioisotopes, fluorophores, chemiluminescent compounds, bioluminescent compounds, chromophores, Raman spectroscopic probes, DNA probes, polarized frequency probes, reporter molecules, enzymes, and dyes.

[0216] As used herein, the term "imaging" refers to spatially resolved signal acquisition of a sample using a detection modality adapted to the detectable marker to obtain a structural image of the target neuron. The imaging modality can be selected according to the type of the detectable marker, including but not limited to: wide-field microscopy, confocal microscopy or two-photon microscopy when the detectable marker is a fluorescent marker; chemiluminescence or bioluminescence imaging when the detectable marker is a luminescent marker; Raman spectroscopy when the detectable marker is a Raman spectroscopic probe; positron emission tomography (PET), single photon emission computed tomography (SPECT) or other radioactive imaging modalities when the detectable marker is a radioisotope marker; bright-field optical microscopy when the detectable marker is a chromophore tag or dye; in situ hybridization when the detectable marker is a DNA probe; substrate color development or fluorescent reaction imaging when the detectable marker is a substance or enzyme capable of reacting with a substrate to generate a detectable signal. In certain embodiments, imaging of nervous system samples can be performed using high-resolution three-dimensional imaging methods, such as Light-Sheet Microscopy (LSM) or fluorescence micro-optical sectioning tomography (fMOST), to achieve fast three-dimensional reconstruction of neural tissues and single-cell resolution morphological analysis.

[0217] As used herein, the term "conditional gene expression system" refers to a transcriptional regulatory system and / or nucleic acid sequence that is capable of activating, enhancing, repressing or terminating the expression of a target gene under certain conditions, while not doing so under other conditions. The conditions can be chemical, physical, biological or environmental factors. The system can include, but is not limited to, temperature-sensitive promoters (such as HSF1, MET17), metabolite-responsive promoters (such as pGAL1, PCK1, MAL2, MET3), chemical induction systems (such as the tetracycline-regulated system Tet-on / Tet-off), recombinase systems (such as the Cre-LoxP system, Flp-FRT system) and other inducible systems (such as the LexA-ER-AD system). The term covers conditional gene expression systems known in the art and equivalents thereof, without being limited to a particular species or a particular implementation.

[0218] As used herein, the term "sparse expression system" refers to a regulatory system that initiates target gene expression in only a small number of target cells in a biological sample, for reducing the density of labeled cells to facilitate single-cell resolution and morphological reconstruction. The degree of sparsity is not limited to a fixed number, but under common experimental conditions, the number of labeled cells is usually in an acceptable range, for example, about several to tens of labeled cells in an imaging or reconstruction area. Sparse expression systems include the following types: random sparse expression systems, which randomly reduce the probability of gene expression in target cells through weak promoters, dilution delivery, or low-efficiency translation elements; conditional sparse expression systems, which are based on conditional gene expression systems (such as the Cre-LoxP system, the Flp-FRT system, the tetracycline regulatory system, and the temperature-sensitive promoter system) and achieve sparsity by limiting the spatial or temporal distribution of activation conditions; double-conditional systems, which require two different conditional start controls to be sequentially satisfied (such as the first condition activating the first recombinase and the second condition activating the second recombinase) to significantly reduce the expression range, and can further include a signal amplification module (such as an IRES-driven transcription activator positive feedback loop) to increase the expression level in activated cells; combined sparse expression systems, which combine random sparse strategies with conditional or double-conditional systems to achieve controllable expression density. This term covers currently known sparse expression control strategies and their equivalents, and is not limited to specific species, vector types, or delivery methods.

[0219] As used herein, the term "Cre-LoxP system" refers to a site-specific recombination system based on the interaction between Cre recombinase (Cyclization recombination enzyme) and the specific DNA recognition site LoxP (locus of X-over in P1). Cre recombinase was first discovered in P1 phage, and is a monomeric protein composed of 343 amino acids, with stable catalytic activity, capable of recognizing the LoxP site and mediating the excision, insertion or inversion of DNA sequences between them. The LoxP site is usually composed of two 13 bp inverted repeats and an 8 bp spacer sequence in between, where the inverted repeats are the recognition site for Cre enzyme. After Cre binds to the site, it catalyzes the homologous recombination of DNA strands, thereby achieving rearrangement or deletion of the target sequence located between the two LoxP sites.

[0220] In implementation of conditional gene expression, the Cre-LoxP system can be used in conjunction with various structural patterns, including but not limited to lox-stop-lox and Double-floxed Inverted Orientation (DIO) configurations. In the lox-stop-lox pattern, a stop cassette is placed between a promoter and a target gene, typically consisting of a strong polyA signal and / or a splice donor sequence, which blocks transcription of the target gene, and Cre-mediated excision of the stop cassette initiates transcription. In the DIO pattern, the reading frame of a foreign gene is sandwiched between two pairs of different Lox sites (e.g. LoxP and Lox2272) in reverse orientation, and Cre-mediated recombination of the same Lox sites flips the reading frame to forward orientation and locks it, thus enabling expression of the target gene only in cells where Cre recombinase is present. Variants of the Cre-LoxP system include the drug-inducible CreER-LoxP system, in which Cre recombinase is fused to a mutant estrogen receptor ligand-binding domain, enabling its activity to be regulated by an exogenous inducer (e.g. tamoxifen), to achieve time- and space-controlled gene knockout or expression.

[0221] As used herein, the term "target neuron" refers to a neuron cell that is selectively labeled, imaged, modulated, or analyzed during an experiment or treatment. In some cases, a target neuron refers to a neuron cell that is expected to be expressed by a proximal labeling enzyme, and analyzed in subsequent imaging and reconstruction processes. The neuron can be identified according to its anatomical location, neurotransmitter type, gene expression profile, or other specific markers. Target neurons can be classified according to neurotransmitter type (e.g. glutamatergic, GABAergic, serotonergic, noradrenergic, adrenergic, cholinergic, dopaminergic, glycineric, histaminergic, etc.), functional type (e.g. sensory neuron, motor neuron, interneuron, etc.), or anatomical location (e.g. cortical neuron, hippocampal neuron, thalamic neuron, brainstem neuron, etc.). The term encompasses all types of neurons, known and future discovered, without limitation to a particular species or nomenclature.

[0222] As used herein, the term "tissue clearing" refers to techniques that reduce or eliminate light scattering from biological tissues by physical, chemical or physical-chemical methods, thereby improving tissue transparency and allowing deep optical imaging of the tissues. Clearing methods can be classified into three major categories: (1) organic solvent-based, such as 3DISCO, uDISCO, iDISCO, iDISCO+, vDISCO, wildDISCO, Adipo-Clear, PEGASOS, etc.; (2) hydrophilic reagent-based, such as SeeDB, FRUIT, TDE, ClearT, Scale, CUBIC, etc.; (3) gel-based, such as CLARITY, PACT, PARS, SWITCH, SHIELD, TESOS, ELAST, MPC, etc.

[0223] As used herein, the term "whole-mount staining" refers to staining of a biological tissue sample that retains the integrity of three-dimensional structure, which is larger than a section on a conventional microscope slide, can include a complete biological individual (e.g. an embryo, a small animal model), a complete organ (e.g. a whole brain, a whole spinal cord, a whole liver) or a larger tissue block that retains the integrity of the whole structure (e.g. a complete brain region, a ganglion, a peripheral nerve network, a vascular network), which is performed without physical sectioning of the tissue. Whole-mount staining can be combined with immunohistochemistry, molecular probe staining, fluorescent staining, etc., and can be used in conjunction with tissue clearing techniques to achieve three-dimensional imaging and spatial information preservation of large volume tissues. The term is not limited to a specific tissue type, species or staining method.

[0224] As used herein, the term "biotin" refers to a heterocyclic compound containing an imidazolidone ring and a thiothiazolidine ring, also known as vitamin B7 or vitamin H. Biotin can participate in various carboxylase reactions as a coenzyme, and is also a substrate for biotin ligase-catalyzed reactions. In addition to natural forms of biotin, "biotin" as described herein also includes structural analogs or chemical derivatives thereof, which can be recognized by biotin ligase and form an activated intermediate (e.g. biotin-5'-AMP), and further form a stable covalent bond with the reactive group of the target protein.

[0225] As used herein, the term "neuronal single-cell reconstruction method" refers to a comprehensive technical system constructed based on modularized steps such as proximity labeling enzyme, biotinylation, whole staining and imaging reconstruction. The method can also be referred to as "LINCS method", both of which can be used interchangeably herein.

[0226] The terms "a," "an," "the," and "said," among others, as used herein, are intended to encompass both the singular and plural unless the context clearly indicates otherwise. Stated differently, the terms "a," "an," "the," and "said," among others, as used herein, are intended to be interpreted to mean one or more unless the context clearly indicates otherwise.

[0227] As used herein, the terms "comprising" and "including," are used interchangeably and mean the inclusion of one or more steps, features, components, elements, or the like but do not exclude the inclusion of one or more additional steps, features, components, elements, or the like. In addition, the terms "comprising" and "including" are intended to be synonymous with the terms "consisting of and "consisting essentially of, respectively. Thus, the terms "comprising" and "including" can be used in place of the terms "consisting of and "consisting essentially of, respectively, to provide for more particular embodiments of the present application.

[0228] As used herein, the term "or" is to be interpreted as an inclusive "or" meaning any one or any combination of the listed items. Therefore, "A, B or C" means "any of the following: A; B; C; A and B; A and C; B and C; A, B and C." An exception to this definition will occur only when two or more elements are listed using "either or" language. For example, "A or B," "either A or B," or "A or B" will not be interpreted as an inclusive or when the items are listed using "either or" language. DETAILED DESCRIPTION

[0230] I. Proximity labeling enzyme

[0231] Proximity labeling (PL) is a technology that covalently labels spatially proximal biomolecules (including proteins, nucleic acids, etc.) by expressing an enzyme with proximity labeling function in target cells, and reacting a substrate under the catalysis of the enzyme, thereby covalently labeling spatially proximal biomolecules (including proteins, nucleic acids, etc.). The proximity labeling enzyme can catalyze the conversion of a specific substrate (for example, biotin or a chemical group precursor capable of participating in a biological orthogonal reaction) into a short-lived intermediate with high reactivity under near-physiological conditions of cells or tissues. The intermediate can covalently bind to biomolecules (for example, proteins) within the proximity of the spatial range in a very short time, thereby achieving spatially specific labeling in the target region.

[0232] In some embodiments, the proximity labeling enzyme catalyzes the generation of an intermediate with covalent modification capability from the substrate in the presence of an allowable cofactor (for example, one or more of adenosine triphosphate or other energy donors, oxidizing agents, or reducing agents), and bonds the intermediate to a reactive residue (for example, lysine, tyrosine, cysteine, or a modifiable form thereof) on the proximal protein.

[0233] In some embodiments, the proximity labeling enzyme is selected from the class of peroxidases. The peroxidases include, but are not limited to, horseradish peroxidase (HRP), APEX, APEX2, or variants thereof (e.g., APEX2 C32S). The peroxidases can oxidize a substrate to a short-lived, highly reactive intermediate in the presence of hydrogen peroxide to enable rapid proximity labeling.

[0234] In some embodiments, the proximity labeling enzyme is selected from the class of biotin ligases. This class of enzymes is capable of catalyzing the formation of an activated intermediate of biotin or its structural analogs (e.g., biotin-5'-AMP) and transferring the intermediate to an amino acid residue of a proximal protein to enable region-specific covalent biotinylation. See the section on “Biotin Ligases” below for more details.

[0235] In some embodiments, the proximity labeling enzyme can also be selected from other systems that are capable of generating an active intermediate through enzymatic catalysis and enabling proximity labeling, including but not limited to: the PUP-IT system (based on the bacterial Pup ligase catalyzing the attachment of a PUP tag on a target protein); the NEDDylation or SUMOylation system (enabling proximity labeling through the covalent transfer of small ubiquitin-like modifier proteins); and light-sensitive chemical enzymes or free radical-generating enzymes (e.g., phenol oxidases, laccases, tyrosinases, etc.) that can generate short-lived active species under light or cofactor and modify proteins in a local region.

[0236] Any specific enzyme species, sequence, or configuration mentioned in this specification and claims should be understood as encompassing functional equivalents and homologs thereof, including but not limited to: polypeptides having at least about 70%, 80%, 85%, 90%, 95%, or 98% amino acid identity to the overall sequence of the representative enzyme and retaining the proximity labeling activity; variants including one or more conservative amino acid substitutions, deletions, insertions, or domain swaps without substantially reducing the proximity labeling activity; variants including linker, tag, or excisable sequences for improved stability, expression, or processing; and split forms that can self-assemble to restore the activity in cells.

[0237] Biotin ligases

[0238] Biotin ligases are a class of enzymes that catalyze the covalent linkage between biotin (or its analogs) and acceptor proteins, with natural functions mainly for catalyzing the binding of biotin to lysine residues of specific substrate proteins to enable biotinylation modification.

[0239] In some embodiments, the biotin ligase belongs to Class I, II, or III of the Biotin-Protein Ligase (BPL) family, which can be derived from prokaryotic, archaeal, or eukaryotic organisms. In some embodiments, the proximity labeling enzyme includes any member of the biotin ligase class and functional equivalents thereof, which can be a native enzyme derived from bacteria or other organisms, a variant obtained by mutagenesis / directed evolution, a chimera, a fragment, a split form, a fusion protein form, or a synthetic variant designed artificially. In specific embodiments, the biotin ligase can include, but is not limited to, the following types: BirA* (R118G, BioID); BioID2 (derived from Aquifex aeolicus, R40G, Type-I); BASU (an engineered variant derived from Bacillus subtilis); TurboID and miniTurbo (high-activity variants obtained by directed evolution); AirID (a novel BirA variant designed based on ancestral enzyme reconstruction algorithm and metagenomic data, enabling stable proximity biotinylation in vitro and in cells); split or inducible forms, including split-BioID and split-TurboID (e.g., split at L73 / G74 and conditionally recombined by FRB-FKBP system); and ProtA-TurboID, which can be targeted by antibody binding. In some embodiments, the proximity labeling enzyme can be further modified into a membrane-anchored or membrane-localized form.

[0240] In some embodiments, the substrate of the biotin ligase is not limited to natural biotin, but can also be structural analogs or chemical derivatives with the same or similar activation and transfer mechanism. Such substrates, after recognition by the catalytic domain of the enzyme, can generate an activated intermediate similar to biotin-5'-AMP, and form a covalent bond with the reactive residues of the target protein within the proximity labeling reaction radius. Suitable structural analogs or derivatives include, but are not limited to: analogs lacking or replacing atoms in the ring (e.g., desulfo-biotin); derivatives introducing reactive functional groups on the biotin backbone (e.g., ketone, aldehyde, azide, alkyne, tetrazine, photosensitive groups, etc.); derivatives with cleavable or controllable release linkers (e.g., disulfide-linked biotin, ester- or amide-modified biotin, photocleavable biotin, etc.); derivatives with altered physicochemical properties to expand applications (e.g., PEG-biotin, fluorescein-biotin, isotopically labeled biotin, etc.).

[0241] Solubility enhancement

[0242] In the prior art, the improvement of proximity labeling enzymes mainly focuses on improving catalytic efficiency, and less attention is paid to improving the solubility of enzymes in cells. The present inventors have unexpectedly found that the insufficient solubility of proximity labeling enzymes significantly affects the labeling effect, specifically: first, the distribution in neurons is limited, especially difficult to reach the distal region of long-range axons; second, due to the instability of the activated intermediates generated by substrates (such as biotin and ATP), if the distribution of enzymes is insufficient, the opportunity to bind to adjacent proteins will be limited, thereby significantly reducing the overall labeling efficiency.

[0243] Based on the above understanding, the present application proposes to significantly improve the uniformity of the distribution of proximity labeling enzymes in neurons and the distal labeling efficiency by solubility enhancement means, thereby realizing high-sensitivity long-range labeling.

[0244] In some embodiments, the solubility enhancement can be achieved by fusing known small soluble protein domains, including but not limited to GB1, MBP, and SUMO, etc. In other embodiments, the solubility enhancement can be achieved by increasing the proportion of surface hydrophilic amino acids through site-directed mutagenesis. In further embodiments, the solubility enhancement can be achieved by truncating or modifying non-catalytic domains to reduce the tendency of protein hydrophobic aggregation. In addition, other molecular biology means known in the art or developed in the future to improve the water solubility of proteins can also be used to achieve the same technical effect.

[0245] Tag

[0246] In some embodiments, the proximity labeling enzyme can be fused with one or more tags to improve its solubility, stability, expression level, localization, or detection performance in host cells, etc.

[0247] In some embodiments, the tag is a solubility-enhancing tag. The solubility-enhancing tag helps to improve the folding efficiency and water solubility of the fusion protein, thereby improving the expression level and uniform distribution in host cells. In some embodiments, the tag is a GB1 tag derived from the B1 domain of Streptococcal protein G, consisting of 56 amino acid residues, and folded into a compact conformation composed of four beta sheets and one alpha helix. GB1 has a developed hydrophobic core, lacks disulfide bonds, free cysteine, proline, and metal binding motifs, and exhibits good stability and solubility (US8221998B2). In some embodiments, the GB1 tag is a functional equivalent that has several amino acid substitutions while still maintaining the above structure and physicochemical properties. In some embodiments, the solubility-enhancing tag is maltose binding protein (MBP), glutathione S-transferase (GST), SUMO, thioredoxin (Trx), NusA, Thioredoxin A, or Protein L, etc., or a functional equivalent thereof.

[0248] In some embodiments, the tag is a fluorescent tag, which can be used for imaging, localization or cell monitoring. In some embodiments, the fluorescent tag is green fluorescent protein (GFP), blue fluorescent protein (BFP), cyan fluorescent protein (CFP), yellow fluorescent protein (YFP), orange fluorescent protein (OFP), red fluorescent protein (RFP), near-infrared fluorescent protein (miRFP670), or a functional derivative or engineered variant thereof.

[0249] In some embodiments, the tag is a localization or signaling tag, which can direct the fusion protein to a specific subcellular region. The localization tag includes but is not limited to nuclear localization signal (NLS), nuclear export signal (NES), mitochondrial targeting signal peptide, plasma membrane localization signal (e.g. CAAX motif), or endoplasmic reticulum / Golgi signal peptide.

[0250] In some embodiments, the tag is an affinity tag, which is used for isolation, purification and immobilization of the fusion protein. The affinity tag includes but is not limited to poly(His) tag (e.g. His6 or His10), Strep-tag II, SBP-tag, Calmodulin-Binding Peptide (CBP), FLAG-tag, Protein A or Protein L.

[0251] In some embodiments, the tag is an epitope tag, which is commonly used for immunodetection, immunoprecipitation or immunological imaging. The epitope tag includes but is not limited to HA tag (hemagglutinin tag), Myc tag, FLAG tag, V5 tag, VSV tag, E tag or NE tag.

[0252] In some embodiments, the tag is a self-cleaving tag, which can be autocatalytically cleaved under certain conditions, thereby releasing the native form of the adjacent marker enzyme. The self-cleaving tag includes but is not limited to Sortase tag, Npro tag, FrpC module or cysteine protease domain (CPD).

[0253] In some embodiments, the above different types of tags can be used alone or in combination. For example, in some embodiments, the adjacent marker enzyme carries a GB1 tag (for improving solubility), a membrane localization signal (for achieving subcellular localization) and a fluorescent tag (for real-time imaging) at the same time, to achieve a complex function.

[0254] II. Expression of proximity labeling enzyme

[0255] The methods described herein involve the expression of a proximity labeling enzyme in target neurons to achieve efficient and controllable protein labeling in nervous system samples. The expression of the enzyme can be achieved through various approaches, including integration of a nucleic acid sequence encoding the enzyme into the host genome, or delivery of the nucleic acid sequence to the target neurons through an exogenous vector. In some embodiments, the expression can be combined with a conditional gene expression system, such that the transcription and translation of the target gene is activated only under specific conditions. In some embodiments, the expression can be combined with a sparse expression system to ensure that the expression of the enzyme is initiated only in a fraction of the target neurons, thereby achieving precise control over the labeling range and cell proportion. Through the different modes described above and their combinations, the expression of the proximity labeling enzyme can be flexibly regulated at the spatial, temporal, and cell population levels, thereby meeting different experimental needs for single-cell resolution and neural circuit tracing.

[0256] Genomic integration

[0257] In some embodiments, the expression of the proximity labeling enzyme is achieved through genomic integration.

[0258] In some embodiments, the genomic integration can be achieved through gene editing tools, such as CRISPR / Cas systems (e.g., SpCas9, SaCas9, Cas12a, etc.), by targeting the host genome for cleavage and introducing a nucleic acid sequence encoding the enzyme at the cut site. In some embodiments, the genomic integration can be achieved through zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), etc. In some embodiments, the genomic integration can be introduced through homologous recombination or non-homologous end joining (NHEJ), and the nucleic acid sequence can be located downstream of an endogenous promoter, at a specific site (e.g., the Rosa26 site or the H11 site), or directly replace an endogenous gene.

[0259] In some embodiments, the genomic integration is achieved by viral-mediated integration systems, such as lentiviral vectors or retroviral vectors, which can stably insert the exogenous nucleic acid into the host genome and drive long-term expression. In some embodiments, the genomic integration is achieved by non-viral transposon systems, such as Sleeping Beauty (SB) transposon, PiggyBac transposon, or Tol2 transposon, which rely on transposase-mediated insertion of exogenous fragments with inverted repeat sequences (IR / DR) into the host genome, resulting in stable expression. In some embodiments, the genomic integration is achieved by the host’s own integration machinery, such as the reverse transcription and insertion activities of retrotransposons, to achieve genomic insertion of the exogenous gene. In some embodiments, the genomic integration is achieved by synthetic biology platforms, such as PhiC31 integrase system, Bxb1 integrase system, or other site-directed integration tools, to achieve predictable insertion of nucleic acid sequences into the host genome.

[0260] In some embodiments, the nucleic acid sequence is introduced into the genome of the host cell, primary neuron, stem cell, or experimental animal by genomic integration, enabling the host to stably express the enzyme of interest. For example, a cell line with stable integration of the nucleic acid sequence can be obtained, or a transgenic animal model containing the integrated nucleic acid sequence can be generated. This approach enables long-term, heritable expression of the enzyme of interest in the host, providing a stable source for subsequent neuronal labeling and tracking. In particular embodiments, the transgenic animal is a mouse, zebrafish, or rat, which is used for neural system development, neurodegenerative disease modeling, or long-term tracking experiments.

[0261] Exogenous vector delivery

[0262] In some embodiments, the expression of the proximity labeling enzyme is achieved by delivering the nucleic acid encoding it to the target neuron via an exogenous vector. The exogenous vector can protect the nucleic acid molecule from degradation and facilitate its transmembrane entry into the target cell, enabling the expression of the nucleic acid sequence within the cell. The exogenous vector can be a non-viral vector, a viral vector, or a molecular conjugate delivery system.

[0263] In some embodiments, the exogenous vector is a viral vector, which can be selected from an adeno-associated virus (AAV), an adenovirus, a lentivirus, a retrovirus, or a virus-like particle (VLP). In some embodiments, the exogenous vector is an adeno-associated virus (AAV). In some embodiments, the AAV capsid can be derived from a natural serotype, including but not limited to AAV1, AAV2, AAV3, AAV4, AAV5, AAV6, AAV7, AAV8, AAV9, AAVrh8, AAVrh8R, AAV10, AAV11, AAV12, AAV13, AAVrh33, AAVrh34, AAVrh74, and AAVhu68. In some embodiments, the AAV capsid is a point mutant of a natural serotype, including but not limited to AAV2 N587A, AAV2 E548A, AAV2 N708A, AAV V708K, and AAV2 R471A. In some embodiments, the AAV capsid is a chimera, whose capsid proteins are combined from fragments of different serotypes, including but not limited to AAV1 / AAV2, AAV1 / AAV8, AAV2 / AAV8, AAV2 / AAV9, AAV-DJ, and AAVrhS / AAVrh8. In particular embodiments, AAV delivery can be combined with a conditional gene expression system (e.g., Cre-LoxP system) to achieve selective expression in specific neuronal populations, or with a dual AAV system, retro-AAV system to achieve sparse expression or projection-specific expression.

[0264] Conditional gene expression system

[0265] In some embodiments, the expression of the proximity labeling enzyme can be controlled by a conditional gene expression system to achieve restricted expression in specific time, space, or cell types, thereby enhancing the spatiotemporal specific regulation of the aforementioned genomic integration or exogenous vector delivery approaches.

[0266] In some embodiments, the conditional gene expression system is the recombinase system Cre-LoxP or Flp-FRT system. In such systems, the target nucleic acid sequence is typically placed downstream of a repressor element (e.g., a stop-codon containing blocker cassette), which is excised by the Cre or Flp recombinase upon its expression in specific Cre or Flp lines of animals, and the expression of the target enzyme is activated. By selecting different Cre or Flp lines of animals, one can direct the activation of the expression of the proximity labeling enzyme in specific cell types or brain regions.

[0267] In some embodiments, the conditional gene expression system is a Cre-LoxP system. In some embodiments, the Cre-LoxP system can be expressed through a lox-stop-lox (LSL) configuration, in which a stop cassette (usually containing a polyA signal or a splice donor sequence) is placed between the promoter and the target gene to block gene transcription. When Cre recombinase is present, the stop cassette is excised and the target gene is expressed. In some embodiments, the Cre-LoxP system employs a Double-floxed Inverted Orientation (DIO) configuration, in which the reading frame of the exogenous gene is sandwiched between two pairs of different Lox sites (e.g., LoxP and Lox2272) in an inverted orientation, and only after Cre-mediated recombination between the same Lox sites, the reading frame is flipped to the forward orientation, thus enabling expression of the target gene. In some embodiments, variants of the Cre-LoxP system can be used to enhance the spatiotemporal specificity of regulation. For example, the CreER-LoxP system enables regulation of Cre recombinase activity by a small molecule (e.g., tamoxifen) that is fused to the ligand-binding domain of the mutant estrogen receptor, and only when the small molecule is administered, the Cre enzyme enters the nucleus and activates expression of the target gene.

[0268] In some embodiments, the conditional gene expression system is a tetracycline-regulated expression system (Tet-on or Tet-off). In this system, the expression of the proximity marker enzyme is regulated by the concentration of a tetracycline derivative (e.g., doxycycline). By exogenously adding or removing doxycycline, inducible turning on or off of the target enzyme can be achieved, thus enabling dynamic regulation during the experiment.

[0269] In some embodiments, the conditional gene expression system is a temperature-sensitive promoter system, such as the HSF1 or MET17 promoter, which can induce or suppress the expression of the proximity marker enzyme under specific temperature conditions.

[0270] In some embodiments, the conditional gene expression system is a light-inducible system. In such systems, gene expression is controlled by a light-sensitive regulatory element, which can be turned on or off upon illumination with specific wavelengths of light. For example, a blue or red light-inducible light-sensitive receptor element can be used to reversibly regulate the expression of the proximity marker enzyme, thus enabling higher precision spatial control at the single-cell or specific brain region level.

[0271] In some embodiments, the conditional gene expression system is a metabolite-responsive promoter system, such as the pGAL1, PCK1, MAL2, or MET3 promoter, whose expression activity is regulated by the presence or absence of specific metabolites (e.g., galactose, pyruvate, or methionine).

[0272] In summary, conditional gene expression system can be combined with genomic integration or exogenous vector delivery strategy to achieve spatiotemporal specific regulation of proximity marker enzyme, conferring higher precision and experimental flexibility to the system.

[0273] Sparse expression system

[0274] In some embodiments, to avoid over-lapping signals caused by labeling all target neurons, a sparse expression system can be employed to express the proximity marker enzyme in only a portion of target neurons. In this way, high-resolution analysis of single neuron morphology and projection can be achieved, facilitating single-cell resolution neural circuit study.

[0275] In some embodiments, the sparse expression system is a random sparse expression system, which reduces the incidence of gene expression events in a probabilistic manner through weak promoters, dilution delivery, inefficient translation elements or viral dose control, etc.

[0276] In some embodiments, the sparse expression system is a conditional sparse expression system, which is based on conditional gene expression systems (e.g. Cre-LoxP, Flp-FRT, Tet-on / Tet-off or temperature-sensitive promoters) and achieves selective activation of target genes in a portion of cells through limiting the distribution of inducers or time control.

[0277] In some embodiments, the sparse expression system is a double conditional sparse expression system, which requires two different sets of start control conditions to be met in sequence before activating target gene expression. For example, the first condition drives Cre recombinase and the second condition drives Flp recombinase, and only when both conditions are met can the transcription of the target gene be unlocked. This system can significantly reduce the expression range, and in some embodiments further combines a signal amplification module (e.g. transcription activator positive feedback loop) to achieve high-level expression in activated cells.

[0278] In some embodiments, the sparse expression system is a combined sparse expression system, which combines random sparse strategy with conditional or double conditional system, thereby achieving controllable sparsity while maintaining experimental flexibility.

[0279] In a specific embodiment, the sparse expression system is implemented using a dual AAV system, comprising a controller AAV and an amplifier AAV. The controller AAV triggers signaling events with a low probability, such as by driving low levels of transcriptional activators or recombinases; while the amplifier AAV amplifies the expression levels of downstream genes upon detecting this signal, thereby obtaining a high signal-to-noise ratio labeled signal in a very small number of cells. This approach enables clear imaging of individual neurons without increasing the overall infection dose.

[0280] In some embodiments, the dual AAV system can also be used in conjunction with retro-AAV to achieve projection-specific sparse labeling, i.e., triggering expression only in neurons with specific long-range projections, thereby further improving the spatial selectivity of labeling.

[0281] III. Streptavidin

[0282] "Streptavidin" is a protein that binds to biotin with high affinity, derived from *Streptomyces avidinii* or a protein-engineered variant. Streptavidin includes naturally occurring multimeric proteins as well as engineered monomeric or monovalent forms.

[0283] In some embodiments, the streptavidin is a monovalent streptavidin, which is a streptavidin form having a single biotin-binding site. In some embodiments, the streptavidin exists in a tetrameric form, wherein only one monomer retains biotin-binding activity, and the remaining monomers are inactive deletions, thereby enabling one molecule of monovalent streptavidin to bind one molecule of biotin with high specificity. In some embodiments, the streptavidin exhibits other monovalent configurations, such as configurations formed by coupling monomeric streptavidin with one or more bulky groups, which spatially or structurally restrict only one biotin-binding site to be available for binding.

[0284] In some embodiments, the streptavidin may be an engineered variant to improve its solubility, stability, or reduce nonspecific binding in mammalian cell or tissue environments. In some embodiments, the streptavidin may be conjugated to a labeling molecule (e.g., a fluorescent protein, enzyme, dye, or nanoparticle) for subsequent detection, color development, or imaging.

[0285] In some embodiments, the streptavidin comprises functional equivalents that are proteins capable of binding biotin or its analogs with the same or similar mechanism, non-limiting examples include avidin, neutravidin, and artificial binding proteins obtained by protein engineering.

[0286] IV. Detectable label and imaging

[0287] Detectable markers are used to convert specific events at the molecular or cellular level into detectable signals, while imaging is used to collect and analyze the signals to obtain spatial and functional information of target neurons or tissues. In some embodiments, the detectable markers are connected to target neurons by means of coupling with streptavidin or its derivatives. By coupling fluorophores, enzymes, luminescent groups or other detectable markers with monovalent streptavidin, specific labeling of biotinylated proteins is achieved, and high-sensitivity detection results are obtained in combination with corresponding imaging methods.

[0288] In some embodiments, the detectable markers are fluorescent markers that can emit fluorescent signals under excitation light of a specific wavelength. The fluorescent markers can be small organic molecule dyes such as fluorescein, fluorescein isothiocyanate (FITC), tetramethyl rhodamine (TRITC), Cyanine dyes (Cy3, Cy5), Alexa Fluor series dyes, Janelia Fluor series dyes, or fluorescent proteins such as cyan fluorescent protein (CFP), near-infrared fluorescent protein (miRFP670) or their derivatives. In some embodiments, the fluorescent markers can achieve specific binding by coupling with streptavidin.

[0289] In some embodiments, the detectable markers are luminescent markers that can spontaneously emit light signals after chemical or biological reactions. In some embodiments, the luminescent markers are chemiluminescent markers such as horseradish peroxidase (HRP) and its substrate system, or alkaline phosphatase (AP) and its substrate system. In some embodiments, the luminescent markers are bioluminescent markers such as firefly luciferase, Renilla luciferase or NanoLuc TM luciferase.

[0290] In some embodiments, the detectable markers are radioisotope markers, including tritium ( 3 H), carbon-14 ( 14 C), phosphorus-32 ( 32 P), sulfur-35 ( 35 S), iodine-125 ( 125 I), fluorine-18 ( 18F) and the like. In some embodiments, the radioisotope label is detected by autoradiography, PET imaging, or SPECT imaging.

[0291] In some embodiments, the detectable label is a chromophore tag or dye that can generate a contrast signal under brightfield optical microscopy. Suitable dyes include hematoxylin, eosin, DAPI, Hoechst dyes, NeuroTrace dyes, fluorescein-biotin derivatives, and the like.

[0292] In some embodiments, the detectable label is a Raman spectroscopic probe, such as a surface-enhanced Raman scattering (SERS) nanoparticle, or a small molecule probe containing a characteristic Raman-active functional group. In some embodiments, the detectable label is a polarized frequency probe for detecting protein conformational or membrane environment changes.

[0293] In some embodiments, the detectable label is a DNA probe or oligonucleotide probe that can enable detection by specific hybridization to a target nucleic acid sequence. In some embodiments, the probe is coupled to a fluorescent dye, a radioisotope, or a chemiluminescent group, enabling direct detection of the signal. In particular embodiments, the probe enables indirect detection by triggering a signal amplification reaction, such as hybridization chain reaction (HCR), immuno-signal chain reaction (isHCR), rolling circle amplification, or other nucleic acid-based amplification methods. In some embodiments, the amplification method can be combined with expansion microscopy (ExM) to enable high-resolution tissue imaging.

[0294] In some embodiments, the methods of the present application further incorporate tissue clearing techniques to enhance the imaging capability for deep-tissue or large-volume samples. Tissue clearing refers to techniques that reduce or eliminate light scattering in biological tissues by physical, chemical, or physical-chemical means, thereby increasing transparency and allowing deep optical imaging. In some embodiments, the clearing method is an organic solvent-based method, such as 3DISCO, uDISCO, iDISCO, iDISCO+, vDISCO, wildDISCO, Adipo-Clear, PEGASOS, and the like. In some embodiments, the clearing method is a hydrophilic reagent-based method, such as SeeDB, FRUIT, TDE, ClearT, Scale, CUBIC, and the like. In some embodiments, the clearing method is a gel-based method, including CLARITY, PACT, PARS, SWITCH, SHIELD, TESOS, ELAST, MPC, and the like.

[0295] In some embodiments, the imaging method is selected according to the type of detectable marker. For example, when the detectable marker is a fluorescent marker, wide-field microscopy, confocal microscopy, two-photon microscopy or light-sheet microscopy can be used; when the detectable marker is a chemiluminescent or bioluminescent marker, in vivo live imaging system or CCD imaging system can be used; when the detectable marker is a radioisotope, PET, SPECT or autoradiography can be used; when the detectable marker is a Raman spectrum probe, Raman spectrum imaging can be used; when the detectable marker is a chromophore tag or dye, bright-field optical microscopic imaging can be used; when the detectable marker is a DNA probe, in situ hybridization imaging can be used; when the detectable marker is an enzyme marker, substrate color development or fluorescent substrate reaction imaging can be used.

[0296] In some embodiments, to achieve high-resolution reconstruction of the nervous system sample, the imaging method can include three-dimensional imaging means, such as light-sheet microscopy (LSM), fluorescence micro-optical sectioning tomography (fMOST) or expansion microscopy. In some embodiments, the imaging is used for fast, whole-brain range of projection neuron visualization, and can achieve single-cell resolution morphological analysis.

[0297] V. Image reconstruction and computer methods

[0298] In the present application, the overall imaging data obtained by the LINCS method can be reconstructed to the single-cell level of neurons by computer methods. The image reconstruction and computer methods described in the present application are not limited to specific algorithms or software, but encompass a class of technical paths that can convert overall imaging signals into three-dimensional structures of single neurons.

[0299] In some embodiments, the image reconstruction and computer methods can include the following steps or any combination thereof:

[0300] In some embodiments, the method includes data preprocessing, i.e. background subtraction, noise removal, light intensity normalization, drift correction and channel separation of the original imaging data, and if necessary, multi-view image stitching and registration, so as to obtain high-quality image stacks suitable for subsequent analysis. For example, image denoising algorithms based on convolutional neural networks can be used, or plugins in open-source platforms ImageJ and Fiji can be used for signal preprocessing.

[0301] In some embodiments, the method comprises neuron signal extraction, i.e. separating neuron fluorescent signal from background using threshold segmentation, filter enhancement, edge detection or deep learning based image recognition methods. For long-range axons, tracing based algorithms can be employed to extract continuous signal trajectories, combined with interactive correction tools to ensure integrity.

[0302] In some embodiments, the method comprises three-dimensional reconstruction, i.e. converting signal to three-dimensional spatial coordinate point cloud or line segment data by automated tracing, semi-automatic interaction or manual correction methods, reconstructing neuron dendrites, axons and branching networks based on obtained neuron signals. The three-dimensional reconstruction can be achieved by commonly used neuron reconstruction software in the art, including but not limited to Imaris, Neurolucida, Vaa3D, or customized programs based on MATLAB, Python.

[0303] In some embodiments, the method comprises positioning and registration, i.e. spatially aligning the reconstructed neuron model with a standard brain reference frame (e.g. Allen Mouse Brain Common Coordinate Framework, CCF) to obtain accurate brain region positioning and support cross-sample comparison and population analysis.

[0304] In some embodiments, the method comprises downstream analysis, i.e. after completing three-dimensional reconstruction and registration, further developing morphological and connection pattern quantitative analysis, including branch length, bifurcation point number, Sholl analysis, dendritic complexity, cross-region projection range and distribution density, etc. parameters, and combining statistical tools to form population level comparison.

[0305] In some embodiments, the image reconstruction and computer method can be combined with artificial intelligence or deep learning algorithms to improve the degree of automation and accuracy of neuron tracing and segmentation. The method is not limited to a specific hardware environment and can run on a general-purpose computer, a special-purpose workstation or a distributed computing platform, and can be integrated with a microscopic imaging device to form an end-to-end data acquisition and analysis system.

[0306] VI. Neuronal single cell reconstruction methods

[0307] The present application provides a neuron single-cell reconstruction method based on proximity labeling and bulk tissue detectable labeling (hereinafter referred to as "LINCS method"). The basic process includes: (1) expressing proximity labeling enzyme in the target neuron and combining with the provided biotin to form biotinylated protein; (2) treating the whole sample with monovalent streptavidin coupled with detectable label; (3) imaging the treated sample; (4) and based on the obtained image data, three-dimensional reconstruction of a single neuron is achieved.

[0308] In different embodiments, the specific conditions and parameters adopted in the above steps can be determined from the corresponding sections: the kind of proximity labeling enzyme can be found in “I. Proximity labeling enzyme”; the expression strategy of proximity labeling enzyme can be found in “II. Expression of proximity labeling enzyme”; the streptavidin-related system can be found in “III. Streptavidin”; the detectable label and imaging conditions can be found in “IV. Detectable label and imaging”; and the image reconstruction and computer processing flow can be found in “V. Image reconstruction and computer method”.

[0309] Expression of proximity labeling enzyme and provision of biotin

[0310] The first stage of the method involves the expression of proximity labeling enzyme and the provision of biotin, which are used in conjunction to achieve specific labeling in target neurons. The parameter selection and operation sequence of this stage are flexible and can be adjusted according to different implementation requirements.

[0311] In some embodiments, the proximity labeling enzyme can be selected from TurboID, miniTurbo, AirID and functional equivalents thereof, and preferably adopts the aforementioned solubility enhancement strategies (e.g., fusion with solubility tags such as GB1, MBP, SUMO, etc., or improving water solubility through surface rational mutation, structural truncation, etc.). In some embodiments, the expression path of the enzyme can be achieved through genomic integration or exogenous vector delivery, and can be further combined with conditional systems (e.g., Cre-LoxP, Flp-FRT, Tet-on / Tet-off, CreER, etc.) and / or sparse expression systems (including random sparseness, double conditional sparseness, and combinations thereof) to achieve controllable expression in terms of space, time, and cell proportion.

[0312] The provision sequence of biotin is flexible, and in different embodiments, biotin can be provided before, simultaneously with, or after the expression of proximity labeling enzyme.

[0313] In in vitro conditions, the provision method can be achieved by directly adding biotin in the cell culture system.

[0314] In vivo, the biotin can be provided by a variety of routes. In some embodiments, the route is systemic, including but not limited to intraperitoneal injection, intravenous injection, tail vein injection, orbital sinus injection, subcutaneous injection, oral administration, or water administration (e.g., by a programmable feeding pump or free access to water). In some embodiments, the route is local or region-specific, including but not limited to stereotactic brain injection, intracerebroventricular injection, microinjection into a specific brain region, intrathecal injection, or long-term local administration by an implanted osmotic pump. In this way, biotin can be provided at a stable and controllable concentration in a specific anatomical location or tissue region, thereby achieving efficient proximity labeling at the level of target neurons. In some embodiments, a combination of systemic and local administration can be used, e.g., a basal level of biotin provided by water or intraperitoneal injection, and a higher local concentration maintained in a specific brain region by stereotactic brain injection or an osmotic pump. This combined approach can ensure a low background level of labeling while highlighting the signal from specific regions or neuronal populations.

[0315] In some embodiments, biotin can be provided by different administration modes, including but not limited to (1) single addition, i.e., biotin is added once and not replenished; (2) pulse addition, i.e., biotin is provided at a high concentration for a short period of time, followed by removal or cessation of biotin provision; (3) intermittent addition, i.e., biotin is added multiple times at regular intervals, e.g., once a day or once every few hours; (4) continuous provision, i.e., biotin is maintained at a constant concentration or stable level throughout the experiment; and (5) controlled release, i.e., biotin is released gradually by a slow-release carrier, osmotic pump, or other controlled release system.

[0316] Through the above-mentioned different ways, researchers can flexibly adjust the concentration, frequency, and duration of biotin administration according to the species of experimental animals, target tissue location, experimental duration, and proximity labeling requirements. Those skilled in the art will understand that the concentration, provision time, and mode of biotin can be flexibly adjusted according to experimental requirements, and the above-mentioned listed ways do not constitute a limitation.

[0317] Monomeric streptavidin and detectable labels

[0318] The second stage of the method involves treating the whole-mount sample with monomeric streptavidin conjugated with a detectable label to selectively bind the biotinylated products formed in the first stage and to obtain a detectable signal at the tissue scale. The monomeric streptavidin is preferably in a configuration with only a single active biotin binding site to reduce cross-linking and molecular bridging and to improve penetration and uniformity in thick tissues (see "III. Streptavidin" for sources and equivalents of monomeric streptavidin). In different embodiments, the conjugate can be in a pre-conjugated or in situ conjugated form, and the choice of detectable label, optical readout and imaging modality can be found in "IV. Detectable labels and imaging"

[0319] In some embodiments, the whole-mount sample staining uses monomeric streptavidin or its engineered equivalents (e.g. monomeric streptavidin mSA, monomeric streptavidin cpMA, monomeric tetramer variants, mSA-FP fused with fluorescent proteins, etc.) and is conjugated with a detectable label. The detectable label can be a fluorescent label, a bioluminescent / chemiluminescent label, a chromophore tag, a Raman probe, a DNA probe, a reporter molecule, a radioisotope, or an enzymatic label system capable of generating a detectable signal in reaction with a substrate (e.g. HRP, AP, luciferase), and the conjugation of each type of label with streptavidin can be replaced with each other.

[0320] Imaging and single-cell reconstruction

[0321] The third stage of the method involves optical imaging readout of the whole-mount sample after treatment with monomeric streptavidin conjugated with a detectable label. By choosing appropriate imaging modalities, spatial distribution of the labeling signal can be detected at the tissue scale to obtain raw image data covering the whole brain or large volume of tissue. The specific choice of imaging modalities and the implementation of optical systems can be found in "IV. Detectable labels and imaging".

[0322] In some embodiments, the whole-mount sample can be pre-processed before imaging to improve the quality of subsequent imaging. The pre-processing methods can include but are not limited to tissue transparentization (e.g. organic solvent transparentization, hydrogel transparentization, tissue swelling method), mechanical sectioning, or other measures suitable for improving signal detection depth and resolution. In some embodiments, imaging can be directly performed in whole-mount tissue without transparentization or sectioning. The imaging modalities can be light sheet microscopy, confocal microscopy, multiphoton microscopy, or other microscopic imaging systems suitable for obtaining high-resolution three-dimensional images. The imaging conditions and parameters can be flexibly adjusted according to sample size, fluorescence intensity, resolution requirements, etc.

[0323] The fourth stage of the method involves image processing and 3D reconstruction of neurons based on the acquired imaging data. Through computer-aided image analysis and data processing, complete reconstruction of individual neuron morphology can be achieved. For details of image reconstruction and computer implementation, please refer to "V. Image Reconstruction and Computer Methods".

[0324] In some embodiments, the acquired raw image data can be subjected to image pre-processing (e.g. de-noising, contrast enhancement, signal normalization), segmentation and analysis by tracking algorithms, to achieve 3D reconstruction of individual neurons. The reconstruction step can further include automated or semi-automated identification and annotation of dendrites, axons and synaptic connections, to obtain a complete single-cell projection map. In another embodiment, the reconstruction process can be combined with manual correction to improve the accuracy and interpretability of the results. Through the above process, proximal labeling, biotinylation, whole sample labeling, imaging and reconstruction form a complete neuron single-cell.

[0325] Representative embodiments

[0326] In some embodiments, the method comprises expressing a proximal labeling enzyme in target neurons, wherein the solubility of the proximal labeling enzyme is optimized to enhance its stability and functionality within the cell, and further comprises delivering the proximal labeling enzyme to target neurons via an exogenous vector, optionally in combination with a conditional expression system and / or a sparse expression system, to achieve a spatial or cell type-specific expression pattern.

[0327] In some embodiments, the method comprises expressing a proximal labeling enzyme in target neurons, wherein the proximal labeling enzyme is fused with a solubility-enhancing tag to improve its solubility within the cell, and further comprises delivering the fusion enzyme to target neurons via an exogenous vector, optionally in combination with a conditional expression system and / or a sparse expression system, to label a specific population of neurons.

[0328] In some embodiments, the method comprises expressing a proximal labeling enzyme in target neurons, wherein the proximal labeling enzyme is fused with a GB1 tag to enhance its solubility, and further comprises delivering the fusion enzyme to target neurons via an exogenous vector, optionally in combination with a conditional expression system and / or a sparse expression system, to limit its expression in target cells.

[0329] In some embodiments, the method comprises introducing and expressing a proximal labeling enzyme in target neurons via genomic integration, wherein the solubility of the proximal labeling enzyme is optimized to improve intracellular functionality, and the method can further combine a conditional expression system and / or a sparse expression system to regulate the expression level of the proximal labeling enzyme in the target neuronal population.

[0330] In some embodiments, the method comprises introducing and expressing a proximity labeling enzyme in the target neurons via genomic integration, wherein the proximity labeling enzyme is fused to a solubility-enhancing tag to improve its stability and solubility in the cell, and the method can further incorporate a conditional expression system and / or a sparse expression system to achieve precise labeling of the target neurons.

[0331] In some embodiments, the method comprises introducing and expressing a proximity labeling enzyme in the target neurons via genomic integration, wherein the proximity labeling enzyme is fused to a solubility-enhancing tag to improve its stability and solubility in the cell, and the method can further incorporate a conditional expression system and / or a sparse expression system to achieve precise labeling of the target neurons.

[0332] In some embodiments, the method comprises expressing a biotin ligase in the target neurons, wherein the biotin ligase is solubility-optimized to improve its stability and functionality in the cell, and the method further comprises delivering the enzyme to the target neurons via an exogenous vector, and optionally incorporating a conditional expression system and / or a sparse expression system to achieve controlled expression in the target neuron population.

[0333] In some embodiments, the method comprises expressing a biotin ligase in the target neurons, wherein the biotin ligase is fused to a solubility-enhancing tag to improve its solubility and stability in the cellular environment, and the method further comprises delivering the fusion enzyme to the target neurons via an exogenous vector, and optionally incorporating a conditional expression system and / or a sparse expression system to achieve target neuron-specific labeling.

[0334] In some embodiments, the method comprises expressing a biotin ligase in the target neurons, wherein the biotin ligase is fused to a solubility-enhancing tag to improve its solubility and stability in the cellular environment, and the method further comprises delivering the fusion enzyme to the target neurons via an exogenous vector, and optionally incorporating a conditional expression system and / or a sparse expression system to achieve target neuron-specific labeling.

[0335] In some embodiments, the method comprises introducing and expressing a biotin ligase in the target neurons via genomic integration, wherein the biotin ligase is solubility-optimized to improve its functionality, and the method can further incorporate a conditional expression system and / or a sparse expression system to achieve long-term, stable expression in the specific neuron population.

[0336] In some embodiments, the method comprises introducing and expressing a biotin ligase in target neurons via genomic integration, wherein the biotin ligase is fused with a solubility-enhancing tag to improve solubility and stability, and the method can further incorporate conditional expression systems and / or sparse expression systems to achieve controllable labeling of target neuron populations.

[0337] In some embodiments, the method comprises introducing and expressing a biotin ligase in target neurons via genomic integration, wherein the biotin ligase is fused with a GB1 tag to improve its solubility, and the method can further incorporate conditional expression systems and / or sparse expression systems to achieve spatial and cell type-specific labeling of target neuron populations.

[0338] It should be understood that the present application is not limited to the aforementioned specific combinations. In addition to the aforementioned proximity labeling enzymes, biotin ligases, solubility-enhancing means, and delivery or integration means, other equivalent enzymes, tags, or delivery strategies can be selected by those skilled in the art according to actual needs and applied in combination with conditional expression, sparse expression, or other regulatory means. These equivalent alternatives or variations are within the scope of the present application.

[0339] Combined use

[0340] In some embodiments, the neuron single-cell reconstruction method (LINCS) can be combined with other labeling or detection techniques to superimpose cell type, molecular phenotype, and morphological information in the same sample, thereby improving resolution and interpretability. The combination can be flexibly configured in terms of process timing and reagent system: in different embodiments, (1) LINCS can be implemented first, followed by exogenous labeling; (2) exogenous labeling can be implemented first, followed by LINCS; (3) synchronous implementation under compatible conditions; or (4) sequential combination of multiple rounds of “staining-removal-re-staining”, the specific order can be determined according to antigen tolerance, tissue permeability, and imaging channel configuration.

[0341] In some embodiments, the neuron single-cell reconstruction method can be combined with other labeling or detection methods to improve the accuracy of cell type identification and the acquisition of multi-dimensional information. The combined use can include but is not limited to: (1) combined with antibody staining method: by combining immunostaining to label markers of specific cell types, cell type information is obtained while single-cell reconstruction is performed; (2) combined with whole sample labeling method: under tissue transparency conditions, combined with whole sample protein or RNA labeling methods to achieve the superposition of different molecular level information; (3) combined with nucleic acid detection methods: including combined with in situ multiplex RNA detection methods, to obtain spatial localization information at the transcriptome level while reconstructing neuron morphology.

[0342] VII. Target neurons and whole sample staining

[0343] The method of the present application takes specific target neurons as the labeling and analyzing object, and can introduce detectable markers into these target neurons while keeping the cell function integrity, and provide high-resolution spatial information in subsequent imaging and reconstruction. In some embodiments, in order to observe the target neurons under the condition of keeping the integrity of the three-dimensional structure of the tissue, the method of the present application further combines whole-mount staining, so that the target neurons can still be tracked and analyzed on the macro scale. By combining the precise labeling of the target neurons with the three-dimensional imaging of the whole-mount sample, the method of the present application can provide structural information on both macro and micro levels, thereby supporting single-cell reconstruction, neural network analysis, and systematic cross-scale research.

[0344] Target neurons

[0345] In some embodiments of the present application, the target neurons refer to neuron cells that are selectively labeled, imaged, regulated or analyzed during the experiment or treatment. By expressing a proximity labeling enzyme in the target neurons and detecting it in the subsequent imaging and reconstruction process, the visualization and structural reconstruction of the target neurons in complex neural circuits can be achieved.

[0346] The target neurons can be determined based on various characteristics, including but not limited to:

[0347] In some embodiments, according to the anatomical location, the target neurons can be cortical neurons, hippocampal neurons, thalamic neurons, hypothalamic neurons, cerebellar neurons, brainstem neurons, spinal cord neurons, basal ganglia neurons, olfactory bulb neurons, amygdala neurons, striatal neurons, or substantia nigra neurons.

[0348] In some embodiments, according to the neurotransmitter type, the target neurons can be glutamatergic neurons, GABAergic neurons, 5-HTergic neurons, noradrenergic neurons, adrenergic neurons, cholinergic neurons, dopaminergic neurons, glycineric neurons, or histaminergic neurons.

[0349] In some embodiments, according to the functional type, the target neurons can be sensory neurons (olfactory, visual, auditory, somatosensory, etc.), motor neurons, interneurons, projection neurons, local circuit neurons, inhibitory neurons, or excitatory neurons.

[0350] In some embodiments, the target neurons can be a population of neurons specifically labeled by transgenic mouse lines (e.g. CaMKII-Cre, DAT-Cre, Vgat-Cre, ChAT-Cre, etc.) or by using specific gene promoters (e.g. TH promoter, ChAT promoter, GFAP promoter) to drive the expression of a proximity labeling enzyme, thus enabling selective labeling and subsequent imaging analysis in the neurons.

[0351] In some embodiments, the target neurons can be midbrain dopamine neurons of striatal projection, GABAergic neurons of periaqueductal gray (PAG) projection, or long-range projection neurons of thalamocortical, corticospinal, etc.

[0352] Whole-mount staining

[0353] In some embodiments, the method comprises whole-mount staining of the tissue sample that maintains the integrity of the three-dimensional structure. Whole-mount staining refers to staining of a biological sample of large volume or intact structure without physical sectioning of the tissue, thus obtaining labeling signals at the molecular or cellular level while maintaining the macroscopic spatial information. The tissue sample can include an intact biological individual (e.g. an embryo, a small animal model), an intact organ (e.g. a whole brain, a whole spinal cord, a whole liver), or a large volume of tissue block (e.g. a cortex, a thalamus, a brainstem, a peripheral nerve network, a vascular network).

[0354] In some embodiments, whole-mount staining can be combined with immunohistochemistry, molecular probe staining, fluorescent staining, etc. to provide specific labeling at the cellular or molecular level. Further, whole-mount staining can be applied in conjunction with tissue clearing techniques to enable deep optical imaging and three-dimensional reconstruction of large volume samples.

[0355] Through whole-mount staining, the target neurons can be visualized and located while maintaining the integrity of the macroscopic three-dimensional structure. This strategy allows tracking of the target neurons at the cross-scale level, from the overall tissue distribution to the single cell reconstruction, thus having important value in the study of neural anatomy and functional connection.

[0356] Embodiments

[0357] Experimental materials and methods

[0358] Key resource table

[0359] Table 1 Antibodies

[0360]

[0361] Table 2 Bacteria and viral strains

[0362]

[0363] Table 3 Stored data

[0364]

[0365] Table 4 Chemical reagents, peptide molecules and recombinant proteins

[0366]

[0367] Table 5 Experimental model: cell lines

[0368]

[0369] Table 6 Experimental model: organisms / strains

[0370]

[0371] Table 7 Oligonucleotides

[0372]

[0373] Table 8 Recombinant DNA

[0374]

[0375] Table 9 Software and algorithms

[0376]

[0377] Experimental model

[0378] Mouse model

[0379] Animal care and use were in compliance with the Regulations for the Administration of Laboratory Animals of China and approved by the Animal Experimental Ethics Committee of Beijing Institute of Life Sciences (Approval No. NIBS2023M0013). Adult (2-6 months old) CaMKIIa-Cre mice (005359, Jackson Laboratory), PV-Cre mice (017320, Jackson Laboratory), Sert-Cre mice (031028-UCD, MMRRC Resource Center, USA), DAT-Cre mice (006660, Jackson Laboratory), and Vgat-Cre mice (028862, Jackson Laboratory) were used in the experiments without distinction of gender. Adult (8-12 weeks old) C57BL / 6N wild-type mice (Beijing Vital River Laboratory Animal Technology Co., Ltd.) were also purchased. All mice were of either gender and were raised under a 12 h light / dark cycle (lights on at 8 a.m.) with free access to food and water.

[0380] Cell lines

[0381] HEK293T cells (ATCC CRL-3216, American Type Culture Collection) for AAV packaging were cultured in DMEM medium supplemented with 10% (v / v) fetal bovine serum (FBS), 100 U / mL penicillin, and 100 U / mL streptomycin at 37°C under 5% CO2.

[0382] Viral vector construction and AAV packaging

[0383] DNA oligos were synthesized by Genewiz. TurboID coding gene was synthesized as previously reported (see Key Resources Table, SEQ ID NO: 5). GB1 gene sequence (SEQ ID NO: 6) was amplified from pHR-scFv-GCN4-sfGFP-GB1-NLS-dWPRE (Addgene plasmid #60906). seTurboID gene sequence (SEQ ID NO: 7) was assembled by splicing the coding sequence of TurboID and GB1 with a GGGGS linker peptide. FLAG tag sequence was added to the 5’ end of TurboID and seTurboID coding genes by PCR. EGFP gene sequence was amplified from pAAV-EF1a-DIO-H2B-EGFP. mGFP gene sequence was amplified from pCAG-mGFP. To construct pAAV-CAG-DIO-TurboID, pAAV-CAG-DIO-seTurboID, pAAV-CAG-DIO-EGFP and pAAV-CAG-DIO-mGFP, FLAG-TurboID, FLAG-seTurboID (SEQ ID NO: 8), EGFP and mGFP were inserted into the DIO cassette of pAAV-CAG-DIO backbone derived from pAAV-CAG-DIO-ChR2-mCherry in the reverse orientation, using Gibson assembly. The gene sequence of membrane-bound seTurboID (mem-seTurboID) (SEQ ID NO: 10) was obtained by adding the GAP43 palmitoylation signal sequence (SEQ ID NO: 9) to the 5’ end of FLAG-seTurboID by PCR. For pAAV-hSyn-mem-seTurboID and pAAV-TRE-fDIO-mem-seTurboID-IRES-tTA, mem-seTurboID was obtained by replacing the EGFP sequence in pAAV-hSyn-EGFP (Addgene plasmid #50465) and pAAV-TRE-fDIO-EGFP-IRES-tTA (Addgene plasmid #118026), respectively. The use of pAAV-TRE-DIO-FLPo and pAAV-TRE-fDIO-EGFP-IRES-tTA was performed as previously described (Addgene plasmids #118027 and #118026; see Key Resources Table). Three sgRNAs were designed for Cre (#1-3; see Key Resources Table, SEQ ID NO: 1-3), designed and synthesized using the Benchling online tool (https: / / benchling.com / crispr) and cloned into pX601 (Addgene plasmid #61591) as per the SaCas9 user manual.To minimize spontaneous recombination that can occur during bacterial growth, AAV vectors for DIO cassettes were amplified using Stbl3 E. coli strain.

[0384] AAV vectors were packaged as AAV9, AAV2-retro, and MaCPNS2 serotypes, respectively, following previously reported protocols (Lin, R et al., Nat. Methods 15: 1033-1036 (2018); Tervo, DGR et al., Neuron 92: 372-382 (2016); Chen, X et al., Neuron 110: 1750-1766 (2022); Shin, JH et al., Methods Mol. Biol. 798: 267-284 (2012)). Briefly, AAV vectors were co-transfected with AAV helper plasmids into HEK293T cells (ATCC CRL-3216). Cells were collected 72 h post-transfection, and viral particles were released by freeze-thaw cycles and sonication. Subsequently, viral particles were purified using cesium chloride density gradient ultracentrifugation and dialyzed into PBS. Viral titers were quantified by qPCR.

[0385] Routine surgical procedures and viral injections

[0386] Mice were anesthetized with intraperitoneal injection of avertin (250 mg / kg) prior to surgery and then placed in a mouse stereotaxic apparatus (RWD). Injection procedures were performed using a microinjection pump (Nanoliter 2020 Injector, WPI) to deliver viruses at a rate of 23 or 46 nL / min to the target region under control of a Micro4 controller (WPI). Unless otherwise noted, all subsequent experiments were performed at least 3 weeks post-injection to ensure sufficient transgene expression. Prior to sacrifice and perfusion, mice were given 2 mM biotin (V900418, Sigma-Aldrich) via drinking water for 1 week consecutively, or in specific experiments, 100 nL of PBS containing 2 mM biotin was injected intracranially and incubated for 6 h post-injection. Biotin-containing drinking water was provided using sterilized bottles and replaced every week.

[0387] Sample preparation

[0388] Immunohistochemistry (IHC) sample preparation

[0389] Mice were overdosed with pentobarbital and perfused with ice-cold PBS followed by ice-cold 4% paraformaldehyde (PFA, prepared in PBS) through the heart. Brain tissue was isolated and fixed in 4% PFA at room temperature for 4-6 h or at 4°C overnight. Samples were then dehydrated in 30% sucrose and thin sections of 40-50 pm thickness were prepared using a cryostat (Leica CM1950).

[0390] Expansion Microscopy (ExM) sample preparation

[0391] After perfusion with PBS and 4% PFA, brain tissue was isolated and fixed in 4% PFA at 4°C overnight, followed by sectioning using a vibratome. Coronal sections of 50 pm thickness were prepared and stored in PBS containing 0.05% sodium azide (4°C). The hippocampal region near Bregma -1.5 mm (approximately 1.5 x 2 mm) was taken and washed in PBS three times.

[0392] Whole-mount staining sample preparation

[0393] Mice were perfused with PBS containing 10 pg / mL heparin through the heart after anesthesia, followed by perfusion with 4% PFA and then washed with PBS. Brain tissue (with or without spinal cord) was collected and fixed in 4% PFA at 4°C overnight, followed by additional fixation at room temperature for 1 h. Samples were washed gently in PBS for 30 min x 3 times and stored in PBS containing 0.05% sodium azide (4°C) until use.

[0394] Whole-body staining sample preparation

[0395] Mice were treated according to previous methods (Cai, R et al., Nat. Neurosci. 22:317-327 (2019)). Briefly, mice were shaved after anesthesia using hair removal cream, followed by cardiac perfusion with 0.1 M PBS containing heparin 17 U / mL (Becton, Dickinson and Company, 542858) for 5-10 min at room temperature, and then 4% paraformaldehyde (PFA) prepared in 0.1 M PBS, pH 7.4, for 10-20 min at room temperature. After perfusion, the eyeball, premaxilla, and maxilla were removed, and the palate was carefully opened to avoid damaging the underlying tissue. Feces were removed by making a small incision on the intestine and gently flushing with a syringe using 0.1 M PBS. The whole body tissue of mice was postfixed in 4% PFA at 4 °C for 1 day, followed by washing with 0.1 M PBS for 10 min x 3 times at room temperature, and stored in PBS containing 0.05% sodium azide (4 °C) until further use.

[0396] Immunohistochemistry

[0397] For thin brain sections (40-50 pm), samples were first permeabilized in PBS containing 0.3% Triton X-100 (PBST) and blocked in PBST containing 2% BSA for 1 h at room temperature. Then, the sections were incubated overnight at 4 °C in primary antibody solution (anti-FLAG, 1:2000, F1804, Sigma-Aldrich; anti-TPH2, 1:500, ab184505, Abeam; anti-parvalbumin, 1:100, ab181086, Abeam) diluted in blocking solution. After that, they were washed three times with PBST. Next, samples were incubated for 2 h at room temperature with fluorescent secondary antibodies (goat anti-mouse Alexa Fluor 488, A-11001, Thermo Fisher Scientific; goat anti-rabbit Alexa Fluor 647, 111-605-144, Jackson ImmunoResearch) diluted in blocking solution. For biotin detection, sections were incubated for 0.5-1 h at room temperature with Alexa Fluor 546-streptavidin (1:500, S11225, Thermo Fisher Scientific) diluted in blocking solution, and then washed again three times with PBST. Finally, tissue sections were mounted on glass slides and encapsulated with mounting medium containing 50% glycerol and 1 pg / mL DAPI (D9542, Sigma-Aldrich) for microscopic imaging.

[0398] Staining, gelation, digestion, and expansion (ExM)

[0399] Brain sections were blocked with 2% BSA (in PBS) for 1 h at room temperature. Samples were incubated with Alexa Fluor 546 conjugated streptavidin or unconjugated streptavidin (2 pg / mL, S4762, Sigma-Aldrich) for 1 h at room temperature, followed by three washes in PBST. In the SA-dye method, samples stained with Alexa Fluor 546 conjugated streptavidin were equilibrated in PBS for 30 min, then incubated with 0.1 mg / mL AcX (BD112614, Biotium) in PBS overnight at room temperature for anchoring. In the HCR method, samples bound with unconjugated streptavidin were incubated in amplification buffer (5x SSC buffer, 0.1% [v / v] Tween-20, and 10% [w / v] dextran sulfate in ddH2O) containing 0.5 mM HCR initiator (B1I2, modified with 5’ acrydite and 3’ biotin) for 30 min at room temperature, followed by three washes in PBST.

[0400] Subsequent steps (gelling, digestion, and amplification) were performed according to previous methods (Wang, Y, et al., Cell 184:6361-6377.e24 (2021)). Briefly, brain sections were washed in PBS (2x5 min) and placed in a 0.6 mm deep gasket on a poly-L-lysine-coated glass slide. The tissue was equilibrated with ExM gel solution (60 pL, 3x10 min) at 4°C, sealed with a coverslip, and gelled at 37°C for 2 h. After cooling to room temperature for 3 min, the coverslip and gasket were removed. Proteinase K buffer was added, and the tissue gel was carefully removed and trimmed into a rectangle, with a corner cut off at the corners to mark the orientation. The tissue-gel sample was transferred to a 2 mL EP tube containing 750 pL of proteinase K buffer and 7.5 pL of 800 U / mL proteinase K (P8107S, NEB) and digested at 37°C for 4 h. The sample was trimmed again, washed with PBS (3x5 min) at room temperature, and stored in PBS at 4°C until imaging.

[0401] For HCR, tissue gels were equilibrated in amplification buffer at 37 °C for 30 min. HCR amplicons (B1, Molecular Instruments, USA), a pair of Alexa Fluor 546-modified DNA hairpins, were first heated at 95 °C for 90 s and then slowly cooled at room temperature for 30 min to “snap cool” the annealing. The amplicons were mixed and diluted to 60 nM in amplification buffer, and the tissue gels were incubated at room temperature in the dark overnight. Samples were washed in 5x SSCT (5x SSC, 0.1% Tween-20) (2x20 min), followed by 0.5x SSCT (0.5x SSC, 0.1% Tween-20) (2x40 min) and stored in 0.5x SSC at 4 °C. Before imaging, samples were stained with 5 pg / mL DAPI in PBS (2x30 min), rinsed in PBS, mounted on 18x18 mm poly-L-lysine-coated glass coverslips adhered to 6 cm plastic Petri dishes, and imaged in PBS.

[0402] Whole-mount staining

[0403] All steps were performed gently on a shaker or rocker, and 0.05% sodium azide was supplemented in the buffers during overnight washes (see also Figure 3C ).

[0404] vDISCO

[0405] For nanobody-based staining, samples were processed following the vDISCO protocol (Cai, R et al., Nat. Neurosci. 22:317-327 (2019)). Briefly, removed brain tissue was incubated in a permeabilization solution (1.5% goat serum, 0.5% Triton X-100, 0.5 mM methyl-beta-cyclodextrin, 0.2% trans-1-acetyl-4-hydroxy-L-proline, 0.05% sodium azide, PBS prepared) at 37 °C for 2 days. Subsequently, samples were incubated with Alexa Fluor 647-conjugated anti-GFP nanobooster (1:600, gb2AF647, ChromoTek) at 7 °C for 2 weeks. After staining, brain tissue was washed in PBS containing 1.5% goat serum, 0.5% Triton X-100, and 0.05% sodium azide (3x2 h, plus 1 overnight), and then washed with PBS at room temperature (3x2 h).

[0406] iDISCO+

[0407] For antibody-based staining, samples were processed following the iDISCO+ protocol. Briefly, removed brain tissue was dehydrated in 20%, 40%, 60%, 80%, 100%, and 100% methanol (v / v, dissolved in ddH2O, 1 h each) at room temperature. Subsequently, after pre-chilling at 4 °C, the samples were delipidated in 66% dichloromethane (DCM, 908525, J&K Scientific) / 33% methanol at room temperature overnight. The samples were then washed with 100% methanol twice at room temperature, and after pre-chilling at 4 °C, bleached in freshly prepared 5% hydrogen peroxide in methanol at 4 °C overnight. The bleached brain tissue was rehydrated in 80%, 60%, 40%, and 20% methanol (1 h each), and then treated in PTx.2 buffer (0.2% Triton X-100, PBS prepared) at room temperature (2 times, 1 h each). The brain tissue was then sectioned into 1 mm thick sagittal sections using a vibratome, or processed as half-brains. The samples were incubated in a permeabilization solution (300 mM glycine, 20% DMSO, PTx.2 prepared) at 37 °C for 2 days, and then in a blocking solution (6% goat serum, 10% DMSO, PTx.2 prepared) at 37 °C for 2 days. Afterwards, the samples were incubated with anti-GFP antibody (1 :200, ab290, Abeam) in PBS containing 0.2% Tween-20, 10 pg / mL heparin, 5% DMSO, 3% goat serum, and 0.05% sodium azide at 37 °C for 3 days (1 mm sections), or 1 week (half-brains and whole brains). Subsequently, the samples were washed in PTwH buffer (0.2% Tween-20, 10 pg / mL heparin, PBS prepared): 2 times x 1 h; 1 time overnight or 1 day; 2 times x 2 h. Then, the labeled samples were incubated with Alexa Fluor 647-conjugated anti-rabbit secondary antibody (1 :500, A27040, Thermo Fisher Scientific) in PBS containing 0.2% Tween-20, 10 pg / mL heparin, 3% goat serum, and 0.05% sodium azide at 37 °C for 3 days (1 mm sections), or 5 days (half-brains), or 1 week (whole brains). Finally, the samples were washed in PTwH buffer (2 times x 1 h; 1 time 1 day), and further washed in PBS (2 times x 2 h).

[0408] LINCS

[0409] For LINCS, collected brains (with or without spinal cord) were dehydrated, delipidated, bleached, and rehydrated following the iDISCO+ method. Brains were then cut into 1 mm sagittal sections using a vibratome, or half-brains were prepared as needed. Samples were then incubated with Alexa Fluor 647-labeled wild-type streptavidin (1 :500, 016-600-084, Jackson ImmunoResearch), or Alexa Fluor 647-labeled monovalent streptavidin (1 : 100 for whole-labeling, 1 :250 for sparse-labeling; ab272190, Abeam) in PTx.5 buffer (0.5% Triton X-100 in PBS) with 0.05% sodium azide for 1 day (1 mm sections) or 3 days (half-brains and whole brains) at 37-42 °C. Afterwards, samples were washed in PTx.5 buffer (2 x 1 h, and 1 overnight, 25-37 °C) and then in PBS (4 x 1 h, room temperature).

[0410] Combining iDISCO+ with LINCS

[0411] Collected brains were dehydrated, delipidated, bleached, and rehydrated following the iDISCO+ method. Brains were then cut into 1 mm sagittal sections using a vibratome, and then permeabilized in a permeabilization buffer for 2 days, followed by blocking in blocking buffer (6% donkey serum and 10% DMSO in PTx.2) for 2 days. Samples were then incubated with anti-ChAT antibody (1 :500, ab178850, Abeam) or anti-Ibal antibody (1 :200, 019-19741, FUJIFILM) in PBS with 0.2% Tween-20, 10 pg / mL heparin, 5% DMSO, 3% donkey serum, and 0.05% sodium azide for 2 days at 37 °C. Afterwards, samples were washed in PTwH buffer: 2 x 1 h, 1 overnight, and 2 x 2 h. Labeled samples were then incubated with Alexa Fluor 555-labeled anti-rabbit secondary antibody (1 : 1000, A-31572, Thermo Fisher Scientific) in PBS with 0.2% Tween-20, 10 pg / mL heparin, 3% donkey serum, and 0.05% sodium azide for 3 days at 37 °C. On the last day of secondary antibody incubation, Alexa Fluor 647-labeled monovalent streptavidin was added. Afterwards, samples were washed in PTwH buffer (2 x 1 h, 1 x 1 day) and then in PBS (2 x 2 h).

[0412] Whole-brain tissue clearing

[0413] Tissue clearing employed the DISCO clearing protocol (Renier, N, et al. Cell 165: 1789-1802 (2016)). Briefly, post-stained samples were dehydrated sequentially in 20%, 40%, 60%, 80%, 100% and 100% methanol (1 h each), delipidated in 66% DCM / 33% methanol solution for 3 h, followed by two washes in 100% DCM (15 min each) under gentle shaking at room temperature. Finally, samples were incubated in dibenzyl ether (DBE, 108014, Sigma-Aldrich) at room temperature until fully transparent.

[0414] Whole-mount staining and clearing

[0415] The LINCS whole-body staining protocol is based on a perfusion system that is pumped through the mouse’s circulatory system via cardiac infusion. The perfusion device has been previously reported (Cai, R. et al. Nat. Neurosci. 22:317-327 (2019); Mai, H. et al. Nat. Biotechnol. 42:617-627 (2024)). Briefly, mice were first perfused with 0.1 M PBS at room temperature overnight, followed by 250 mL of destaining solution (30% CUBIC reagent 1 in 0.1 M PBS) at room temperature for 2 days, with fresh destaining solution changed every 12 h. CUBIC reagent 1 was prepared by dissolving 25% urea, 25% Quadrol (122262, Sigma-Aldrich), and 15% Triton X-100 (X100, Sigma-Aldrich) in 0.1 M PBS. After that, mice were perfused with 0.1 M PBS at room temperature (3 times x 3 h), followed by 250 mL of decalcification solution (10% EDTA in 0.1 M PBS, pH 8-9) at room temperature for 2 days. Then, mice were again perfused with 0.1 M PBS (3 times x 3 h). Next, mice were perfused with 250 mL of wildDISCO solution (3% goat serum, 10% CHAPS, 2% Triton X-100, 10% DMSO, 1% glycine, 1% heptakis(2,6)-di-O-methyl- -cyclodextrin (39915, Sigma-Aldrich), and 0.05% sodium azide in 0.1 M PBS) at 37 °C for 12 h. Then, mice were perfused with 250 mL of wildDISCO solution containing Alexa Fluor 647-labeled monomeric streptavidin (1:500; ab272190, Abeam) at 37 °C for 3 days. After that, mice were perfused with 0.1 M PBS containing 0.2% Triton X-100 at room temperature (3 times x 12 h), followed by 0.1 M PBS (3 times x 12 h).

[0416] After completion of the staining, mice were placed in a fume hood and processed using the previously reported 3DISCO passive whole-body clearing protocol (Cai, R et al, Nat. Neurosci. 22:317-327 (2019)). Briefly, mice were sequentially dehydrated in 200 mL of tetrahydrofuran (THF, 186562, Sigma-Aldrich) solutions (50%, 70%, 80%, 100%, 100% for 12 h each, with gentle shaking), then treated in 100% DCM for 3 h, and finally placed in BABB (benzyl alcohol and benzyl benzoate, ratio 1:2; 24122 and W213802, Sigma-Aldrich) for clearing at room temperature until optical transparency.

[0417] Fluorescence microscopy imaging techniques

[0418] Confocal microscopy imaging techniques

[0419] Thin brain sections (40-50 pm) were imaged on a Leica SP8 microscope equipped with 10x / 0.40 and 20x / 0.75 objectives, or on a Zeiss LSM880 inverted confocal fluorescence microscope equipped with 10x / 0.45, 20x / 0.8 or 63x / 1.4 (oil immersion) objectives. Fine structure images of dendritic spines were acquired using an Airyscan detector and a 63x / 1.4 (oil immersion) objective in combination with 1.8x magnification. Samples processed using ExM technology were imaged using a Leica Stellaris 8 DIVECARS system equipped with a 25x / 1.0 (water immersion) objective. Image acquisition was performed at 1024x1024 pixel or 512x512 pixel resolution in combination with Z-stack and stitching scans, with a frame averaging number of 2.

[0420] Virtual slice microscopy imaging techniques

[0421] Slice scanning imaging was performed using an Olympus VS120 virtual slice microscope for widefield fluorescence imaging, equipped with a 10x / 0.4 objective.

[0422] Light sheet fluorescence microscopy imaging techniques

[0423] Transparented brain samples were imaged in horizontal orientation (dorsal side up) on an Ultramicroscope II (LaVision BioTec) equipped with a sCMOS camera (Andor Zyla) and a 4x / 0.3 objective lens (with 6 mm working distance, immersion cap). Imaging was controlled by ImSpector Pro software. Scanning used a 640 nm laser, with a 680 / 30 nm emission filter, and optionally a 488 nm laser with a 460 / 40 nm emission filter for autofluorescence imaging. Single-side illumination was used in combination with 4-step dynamic focusing. At 1.0x magnification, samples were imaged in a 4x4 tile scan, with an overlap of 15% and a step of 2-3 pm. Exposure times were 60-80 ms, with a tile numerical aperture (NA) of 0.10-0.16 and a width of 40%. For the whole tissue staining method comparison experiment, the 640 nm laser power was set to 11% (6.7 mW; Sert-Cre samples) or 30% (17.8 mW; DAT-Cre samples), and the 488 nm laser power was set to 70-80% (42.5-48.7 mW, for autofluorescence). For sparsely labeled samples, the 640 nm laser power was adjusted in the range of 65-80% (38.2-46.9 mW) for optimal signal detection without saturation.

[0424] For transparented samples, including brains with spinal cord and whole mouse bodies, imaging was performed using a LCS SPIM system (Bruker Luxendo) and controlled by LuxControl software. Scanning used a 642 nm laser with a 655-704 nm emission filter, and a 488 nm laser with a 497-554 nm emission filter (for autofluorescence), with bilateral illumination. Samples were imaged using a 4x / 0.28 NA Olympus objective (working distance 30 mm), with an axial resolution of 1.46 pm. For brain samples with spinal cord, a 13x4 tile scan was used, with an overlap of 15%. Whole mouse bodies were imaged in a 26x1 1 tile scan, with an x-axis overlap of 10% and a y-axis overlap of 12%, and were imaged from both the ventral and dorsal sides, to a depth of 15 mm, with a z-axis step of 15 pm to cover the entire body volume. To fit the sample chamber, the forelimbs and tail of the mouse were removed.

[0425] Image processing and analysis

[0426] In confocal microscopic imaging, the signal intensities of FLAG tag and biotin were defined by ImageJ (v1.54f) using automatic threshold method (Otsu’s method). Maximum projection and stitching of confocal images were done using Zeiss ZEN or Leica LAS X software, respectively, after image acquisition. For visualization and analysis of three-dimensional and two-dimensional images, Imaris (v10.1.0, Bitplane), QuPath (v0.5.1) (Bankhead, P. et al. Sci. Rep. 7: 16878 (2017)), and ImageJ (Schindelin, J. et al. Nat. Methods 9: 676-682 (2012)) were used. Cell counting was done by cell detection function in QuPath.

[0427] For image stacks acquired by Ultramicroscope II light sheet fluorescence microscopic imaging system (LaVision BioTec), Imaris Stitcher (v10.1.0, Bitplane) was used for stitching based on image content of overlapping regions and default alignment settings. For data acquired by LCS SPIM system, Luxendo Image Processer (v4.3.2, Bruker Luxendo) was used for two-step registration: first, coarse registration based on hard-coded sample stage positions, then fine registration based on image content. Stitched images were generated using fusion of overlapping regions and exported in Imaris format, with a lateral (xy) compression factor of 2, while axial (z direction) was not compressed. Video generation was done using Imaris and ImageJ, and editing was done by Capcut software (v6.8.0, ByteDance).

[0428] For comparative analysis, axon signals were extracted from the raw fluorescence images for quantification of signal density and intensity in different brain regions or radial layers. The analysis code and step-by-step workflow are available through GitHub (Three-dimensional mouse brain neuronal projection mapping workflow; see Key Resources Table). Briefly, brain tissue data were first down-sampled and rotated to the coronal orientation using Imaris. Prior to down-sampling, data of iDISCO+ whole brain samples were pre-processed to remove vascular noise, and data of half brain samples were mirror-pasted. The rotated data were exported as TIFF files, and the raw signal images were imported into Qupath (v0.5.1) for signal prediction using pixel classifiers pre-trained based on several representative images from the same cohort. The binary images generated from prediction were used to extract signals from the raw images with the help of ImageJ’s Image Calculator. The images after signal extraction were registered to the Allen CCFv3 atlas (10 pm resolution) (Wang, Q et al., Cell 181:936-953.e20 (2020)) using the “brainmapper” command-line in BrainGlobe Workflows77 (v1.4.0) (https: / / brainglobe.info, a Python-based toolkit; Tyson, AL et al., Sci. Rep. 12:867 (2022)) with autofluorescence as the reference channel background. The signal images after registration were quantified for density and intensity by annotated brain regions or radial layers classification through a customized MATLAB script (R2020a, MathWorks). The final brain region quantification data were summarized in RStudio (v2024.12.1, Posit) using R scripts.

[0429] For D-LMBmap analysis, the stitched volume images were imported into the D-LMBmap software (v3.0) (Li, Z et al., Nat. Methods 20:1593-1604 (2023)) for axon segmentation using the corresponding trained axon model, followed by image registration and heat map generation.

[0430] Image annotation and skeletonization

[0431] After the images were stitched into a single volume, the dataset was annotated at the original resolution using the Filament Tracer tool in Imaris software (v10.1.0, Bitplane) on a desktop graphics workstation (ThinkStation P920, equipped with dual Intel Xeon Gold 6226R processors, 192 GB memory, and Nvidia RTXA6000 graphics card). The neurite skeletons were manually traced by the autodepth method. In the slice view, the cell body location was first identified; then the axon and dendrite signals were traced from the cell body to the end. In the autodepth mode, the z-stack was automatically switched as the signal extended. After the true signal was identified, the signal path was traced in the current z-stack using the mouse pointer and a short filament was generated. These filaments were continuously generated and connected to each other until the end of the signal. The reconstruction of neurites was reviewed by two experienced annotators in the slice view and the 3D view. Except for the densely distributed terminal branches in dopaminergic neurons, the neurites of each neuron were reconstructed completely. The reconstruction of neurites can also be achieved by the open-source software Vaa3D (v1.1.4) using the Vaa3D-Neuron module for neurite skeleton reconstruction.

[0432] The branching structure of dopaminergic neurons was traced using the autopath (loops) no soma and spine algorithm in Imaris software Filament Tracer. First, the region of interest containing the branching signal was manually circled. To make the sampling points on the true signal as much as possible, the minimum diameter was adjusted to 3-5 pm, and the seed point threshold was adjusted to the average value of signal intensity. This algorithm uses artificially annotated correct and incorrect predicted filaments for training. Training and prediction are performed iteratively until the generated filaments accurately depict the branch profile. Then these branches are connected to the axon terminals manually traced. The final filaments are exported to SWC format by Imaris plug-in (swc exporter 1.0) (Cannon, RC, et al., J. Neurosci. Methods 84:49-54 (1998); Nanda, S, et al., Sci. Data 5: 170207 (2018)).

[0433] Surface reconstruction and volume analysis

[0434] Dendritic arbor patterns of dopaminergic neurons were reconstructed by Surface creation algorithm in Imaris software. Regions of interest containing dendritic arbor signals were manually delineated. Surface detail parameter was set to 20 pm, and a machine learning-based segmentation method was used. This algorithm was trained using manually annotated foreground and background regions in three representative z-slices. Through iterative training and prediction cycles, the generated surface was able to accurately reflect the underlying dendritic arbor signals. Small artifact surfaces were removed by filtering, and a consolidated surface was obtained for each dendritic arbor pattern. Volume measurements were extracted from the Surface Statistics module.

[0435] Image registration and visualization

[0436] Analysis code and stepwise workflows are available on GitHub (SWC transform; see Key Resources Table). Whole-brain datasets for each group (striatal-projecting dopaminergic neurons, midbrain GABAergic neurons, and PAG-projecting GABAergic neurons) were registered to the Allen CCFv3 atlas (10 pm resolution) (Wang, Q et al., Cell 181 :936-953.e20 (2020)) using the Python-based BrainGlobe Workflows (v1.4.0) (Tyson, AL et al., Sci. Rep. 12:867 (2022)) toolkit via the command-line “brainmapper” and with signal channel images as background. To align the neuron reconstruction results with the reference coordinate space, the SWC files exported from Imaris were adjusted for coordinate conversion by a custom Python script, which calculated pixel offsets based on the registration parameters. The registration results were manually verified by two experienced personnel. The adjusted SWC files were imported into Amira software (v5.4.1, FEI) and displayed together with the reference brain and brain region framework.

[0437] Quantification and statistical analysis

[0438] Statistical details are provided in the figure legends and the Results section. Sample size (n) indicates the number of mice listed in the figure legends. All data in the figures are presented as mean ± SEM. Statistical significance was assessed using GraphPad Prism (v10.2.0). Exact P values and corresponding inferential statistical methods are noted in the figure legends and figure captions. All experiments were independently repeated at least three times, except for LCS SPIM imaging of whole brains and whole mice samples carrying spinal cords, which were only scanned once for a complete scan.

[0439] Example 1 Construction of solubility-enhanced TurboID (seTurboID)

[0440] TurboID is an enzyme that can catalyze the covalent attachment of biotin groups to proximal proteins, which is suitable for proteomic analysis and visualization of cell structure. Figure 1A To evaluate the expression efficiency of TurboID enzyme in neurons and the effect of structure optimization strategy, two AAV expression vectors were constructed, which encode ordinary TurboID (SEQ ID NO: 5) and seTurboID (SEQ ID NO: 7) with a GB1 solubility tag added at the C-terminus (SEQ ID NO: 6), respectively. The above viruses were injected into the dorsal raphe nucleus (DRN) of Sert-Cre mice. After 3 weeks of viral expression, 2mM biotin was supplemented in the drinking water for 7 days to achieve in vivo biotinylation. Subsequently, streptavidin staining was performed on brain tissue sections to detect biotinylated proteins, and the results showed that only a small amount of weak positive FLAG signal was observed in the injection area in the TurboID group, and there was almost no expression in the distal projection area, while the seTurboID group produced significantly enhanced biotin labeling signal in the DRN area and its neurites (Fig. 1D), suggesting that the solubility-enhanced structure can significantly improve the expression and labeling ability of TurboID in neurons. Figure 1B

[0441] To verify the specificity of seTurboID in serotoninergic neurons, further Tph2 immunostaining was performed, and the results are shown in Figure 1E , indicating that seTurboID expression and biotinylation signal are highly colocalized with Tph2 positive neurons, suggesting that it has cell type specificity.

[0442] In addition, to further evaluate the applicability of seTurboID in other neuron types, AAV vectors expressing seTurboID were injected into CaMKII-Cre mice. After 3 weeks of injection, brain tissue was imaged, and the results are shown in Figure 1F , indicating that the expression signal in cortical projection neurons is strong, and the morphology of neurons is clearly visible. High magnification images further show that seTurboID labeling can distinguish dendritic spines ( Figure 1G ) and axon swelling structures ( Figure 1H ), showing its ability for morphological analysis.

[0443] Example 2 Optimization of the application of streptavidin in whole sample staining

[0444] Streptavidin is a reagent suitable for whole sample staining, which can be used to label neurons labeled by seTurboID. This example compares the performance of wild-type and monovalent streptavidin in whole sample staining to screen efficient labeling reagents for seTurboID-labeled neurons.​

[0445] AAV virus expressing seTurboID was injected into the dorsal raphe nucleus (DRN) of Sert-Cre mice, and whole-brain staining was performed using wild-type and monomeric streptavidin (SA) respectively 3 weeks after expression and light sheet microscopy imaging. Figure 2A Figure 2B Wild-type SA showed labeling signals in the DRN and cortical areas, but significantly lacked signals in deep brain regions and dense fiber bundles, accompanied by obvious vascular background staining Figure 2C –E. In contrast, monomeric SA achieved uniform penetration into deep areas of brain tissue without significant vascular non-specific staining, with higher labeling specificity Figure 2C –E.

[0446] Example 3 Establishment and staining process optimization of LINCS method

[0447] This example provides a new labeling method (LINCS) based on seTurboID and monomeric streptavidin. This method can achieve rapid and efficient fluorescent labeling of specific cell types in whole tissue samples Figure 3A .

[0448] The LINCS method has significant advantages over existing technologies in the staining process. Traditional staining strategies often rely on virus vector-mediated expression of fluorescent proteins for neuronal labeling, but such methods usually require a long expression period (1-2 months) to obtain sufficient signals, especially when used for long-distance projection tracking or single neuron reconstruction. In addition, fluorescent proteins often experience fluorescence decay during tissue transparentization, which requires further signal enhancement through IgG immunostaining. This process requires a long incubation period to ensure the sufficient penetration of IgG macromolecules in the tissue, usually including at least 1 week of primary antibody incubation and 1 week of secondary antibody incubation Figure 3B .

[0449] In contrast, the LINCS method uses the high catalytic activity of seTurboID enzyme to generate biotin-modified signals in vivo, achieving significant labeling effects in a shorter expression period. At the same time, monomeric streptavidin with smaller molecular weight is used instead of IgG, avoiding the blocking and penetration steps, significantly simplifying the staining process to a 3-day single-round incubation process, suitable for whole mouse brain and even whole animal tissue Figure 3B and Figure 3C . In addition, streptavidin has good thermal stability, allowing staining at 42°C, further accelerating staining efficiency, while this temperature condition is not suitable for traditional IgG staining.

[0450] ​Compared to typical staining protocols (e.g. iDISCO+ or vDISCO, which take 18-21 days to stain the whole brain), LINCS can compress this step to 7 days; for whole adult mouse processing, LINCS also shortens the total protocol from 25 days to 15 days. The above optimizations show that LINCS has a significant time advantage and ease of operation in the whole sample staining process.

[0451] Example 4 Performance comparison of LINCS and traditional staining methods in dopamine neuron labeling

[0452] This example evaluates the performance difference between the LINCS method and the traditional IgG staining method in whole brain labeling of dopamine neurons. Using DAT-Cre mice as a model, one group used the LINCS method to label dopaminergic neurons in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc), and the other group used a virus expressing membrane-bound GFP (mGFP) combined with the IgG-based iDISCO+ method for whole sample staining.

[0453] Imaging of the two groups of samples was performed using light sheet microscopy, and performance comparison was made in 1 mm thick sections and half brain samples ( Figure 4A and Figure 4B ). In 1 mm sections, the LINCS method showed excellent performance in signal-to-noise ratio, and could clearly distinguish the labeling signal ( Figure 4B and Figure 4C ). In half brain samples, the LINCS group showed stable and uniform labeling effect, while the iDISCO+ group showed signal attenuation and background enhancement on the tissue surface ( Figure 4A ).

[0454] For further quantitative analysis, axon signals were extracted from the original fluorescence images, and signal density and signal intensity in different brain regions were measured ( Figure 4D ). The results showed that in half brain samples, the LINCS group obtained higher signal density and average intensity than the iDISCO+ group ( Figure 4E and Figure 4F ), indicating that it is more suitable for efficient and whole brain scale neuron connection imaging.

[0455] Example 5 Performance comparison of LINCS and traditional staining methods in 5-hydroxytryptaminergic neurons

[0456] This embodiment provides an experimental protocol for applying the LINCS method to whole-brain labeling of serotonergic neurons, and compares it with iDISCO+ and the vDISCO staining method based on nanobodies. The experimental model is the Sert-Cre mouse, and serotonergic neurons in the dorsal raphe nucleus (DRN) are labeled by expressing seTurboID using AAV.

[0457] This embodiment provides an experimental protocol for applying the LINCS method to whole-brain labeling of serotonergic neurons and compares it with two traditional methods: one is staining using the iDISCO+ method after viral expression of soluble or membrane-anchored GFP; the other is the vDISCO method based on nanobodies. The experimental model was the Sert-Cre mouse, and serotonergic neurons in the dorsal raphe nucleus (DRN) were labeled using AAV expression of seTurboID. Sample types included whole-brain and hemibrain samples to compare the signal intensity and structural resolution of different staining methods in deep regions.

[0458] In the LINCS group, after whole-sample staining and tissue clearing, extensive axonal projections of 5-hydroxytryptamine neurons were observed in both the cerebral cortex and deep brain regions. Figure 5A and Figure 5B Especially in deep regions such as the thalamus and midbrain, the LINCS group showed significantly enhanced fluorescence signals and higher density axonal labeling, far superior to the iDISCO+ or vDISCO methods. Figure 5A -F).

[0459] Comparative analysis showed that in samples processed with iDISCO+, the intensity and density of axon signals decreased significantly with increasing depth. Figure 5G and 5H The LINCS group, on the other hand, maintained a uniform signal distribution throughout the brain tissue, with enhanced signal in the central brain region corresponding to the DRN region, reflecting its ability to label neurons in somatic regions. Figure 5H Furthermore, the LINCS method can stably identify the somatic bodies of DRN neurons (…). Figure 5I It can also distinguish fine axonal structures on the brain surface and in distal regions (Figure 5J and 5J). Figure 5K ).

[0460] In contrast, while iDISCO+ and vDISCO can label serotonergic neurons in the DRN region, the number of labeled neurites is significantly reduced. Figure 5I and Figure 5K ), and is often accompanied by nonspecific vascular background signals ( Figure 5L ).

[0461] Example 6: Compatibility of the LINCS method in whole-brain connectivity analysis and immunostaining

[0462] This embodiment demonstrates that high-quality volumetric images can be obtained from samples labeled using the LINCS method, thereby supporting high-precision automated axon segmentation and quantitative analysis. A D-LMBmap analysis workflow was used to construct a whole-brain connectivity map of 5-hydroxytryptamine neurons in the dorsal raphe nucleus (DRN) and to quantitatively analyze the axon density of each brain region. Figure 6A and 6B Based on this standardized analysis procedure, the dopaminergic neurons (Figure 6C) and GABAergic neurons in the ventral tegmental area (VTA) were further analyzed. Figure 6D The whole-brain connectivity pattern.

[0463] Furthermore, this embodiment also verified the compatibility between the LINCS method and IgG immunostaining. In 1 mm thick sagittal brain slices, conventional IgG immunostaining was combined with the LINCS method. While LINCS was used to sparsely label dopamine neurons in the midbrain region, IgG immunostaining was used to label choline acetyltransferase (ChAT, a marker of cholinergic neurons) or ion-calcium-binding aptamer protein 1 (Iba1, a marker of microglia). Figure 6E -G). This combined staining strategy enabled clear visualization of the cell bodies of cholinergic neurons and microglia (iDISCO+ labeled) as well as the axonal projections of dopaminergic neurons labeled by the LINCS method. Figure 6F and Figure 6G ).

[0464] Example 7: Application of LINCS in long-distance central nervous system projection

[0465] This embodiment demonstrates the applicability of LINCS in extracerebral long-distance neural projection imaging. In CaMKII-Cre mice, AAV2-retro virus was unilaterally injected into the C7 and C8 segments of the cervical spinal cord for retrograde delivery of Cre-dependent membrane-anchored TurboID (mem-seTurboID) (SEQ ID NO: 10). Figure 7A To enhance axon visualization, mem-seTurboID was selected, even though previous comparisons in brain tissue showed no significant difference in axon signal density between solution-based and membrane-anchored seTurboID. Figure 7B and Figure 7C ).

[0466] Three weeks after viral injection, the brain tissue (including the spinal cord below L3) was stained and labeled using LINCS (Fig. 7D). Clear axonal tracts and individual axonal signals were observed throughout the spinal cord (Fig. 7E and Fig. 7F). The brain samples were then registered to the Allen mouse brain universal coordinate frame (CCFv3) for whole-brain normalization (Fig. 7G). Strong cell body signals were detected in the contralateral secondary somatosensory cortex (S2, layer 5), primary motor cortex (M1), secondary motor cortex (M2), and primary somatosensory cortex (S1) (Fig. 7H and 7F). Figure 7I ).

[0467] Example 8: Application of LINCS in global labeling of the peripheral nervous system

[0468] This embodiment demonstrates the applicability and imaging effect of LINCS in whole samples of the peripheral nervous system (PNS).

[0469] In adult mice, AAV-MaCPNS2-hSyn-mem-seTurboID was administered intravenously to label neurons in the peripheral nervous system. To achieve whole-body imaging, the streptavidin whole-body staining and tissue clearing process was further optimized, using monovalent streptavidin via vascular perfusion to achieve uniform distribution throughout the body. Even in intact adult mouse samples, clear signals were obtained after only 3 days of staining and perfusion. Figure 8A (and Figure 8B). Significant positive cells and neural process markers were observed in multiple organs, such as nerve axons in the skin (Figures 8C and 8D), and the enteric nervous system of the gastrointestinal tract (and Figure 8B). Figure 8E -K), tail ( Figure 8L ) and feet (Figure 8M and Figure 8N ).

[0470] These results demonstrate that LINCS is not only applicable to the central nervous system, but also enables efficient overall labeling of neurons in large-volume peripheral tissue samples, expanding its applicability in neural connectivity mapping.

[0471] Example 9: Compatibility of LINCS with Expansion Microscopy (ExM)

[0472] Immunosignal hybridization chain reaction (isHCR) is a DNA signal amplification method compatible with ExM. isHCR uses biotinylated antibodies to recognize target molecules (e.g., endogenous biomolecules or transgenic expression tag proteins), and then introduces modified HCR initiators via streptavidin-mediated ligation, which initiates subsequent HCR chain reactions.

[0473] Given that LINCS can produce high-intensity biotinylated modification in vivo, it is speculated that this system can be directly applied to ExM, while simplifying the isHCR process. The LINCS system was used to label parvalbumin-positive neurons in the mouse hippocampus. Subsequently, visualization was performed by fluorescently labeled streptavidin or isHCR methods (Fig. 6). Figure 9A ).

[0474] The labeled samples were processed using the protein-retaining expansion microscopy sample preparation (proExM) protocol. The results showed that detailed neuron structures could be observed in the amplified samples by both methods (Fig. 6). Figure 9B Figure 9E ). In addition, the combination of LINCS with the isHCR method can further enhance the signal intensity, which is manifested as an approximately two-fold increase in fluorescence intensity in image quantitative analysis (Fig. 6). Figure 9C

[0475] Example 10 Sparse labeling based on LINCS and dual-AAV system for whole-brain single neuron reconstruction

[0476] This example demonstrates a sparse labeling method based on the combination of the LINCS system and the dual-AAV strategy, and establishes an efficient whole-brain single neuron reconstruction process by combining tissue clearing and light sheet microscopy technology (Fig. 7). Figure 10A .

[0477] The sparse labeling version of LINCS uses the dual-AAV system to limit the expression of seTurboID to a small subset of the target cell population. Whole brain samples were collected 3-4 weeks after injection, and staining and tissue clearing were performed. Imaging was performed using a single-sided illumination light sheet microscope. Data were collected in 4x4 image stacks (16 stacks per brain channel, with a voxel size of 1.62x1.62x3.00 μm³ and an image size of 2048x2048x~2000), and the imaging time was about 8 hours. Subsequently, image stitching was performed using the overlapping features between image stacks to obtain a complete three-dimensional data set, and registration to the Allen CCFv3 standard brain atlas was completed using the BrainGlobe data processing tool.

[0478] ​​To validate the procedure, five DAT-Cre mice were selected to build the model, retrograde control AAV was injected into the striatum, and enhanced AAV encoding mem-seTurboID was injected into the VTA and SNc ( Figure 10B and Figure 10C ). By reducing the titer of the retrograde regulatory AAV, selective labeling of multiple neurons was achieved in each brain sample ( Figure 10D ), and the cell bodies, dendrites, and projection axons were clearly displayed ( Figure 10E and Figure 10F ). The LINCS labeling combined with the double AAV strategy produced a very high brightness signal, and even the distal axons remained bright ( Figure 10F and Figure 10G ). This enhancement effect improved the signal-to-noise ratio, and compared with the 200 millisecond exposure time required by traditional iDISCO+, it was shortened to 60-80 milliseconds here, significantly improving the imaging efficiency, and 2-3 brain samples could be processed in a single day ( Figure 10G ).

[0479] In this reconstruction experiment, it was observed that dopaminergic neurons formed extensive axonal arborization within the striatum, with focal branching characteristics ( Figure 10G -K). This phenomenon was consistent with the results of previous single neuron reconstruction studies using the fMOST platform (Lin, R et al., Nat. Methods 15: 1033-1036 (2018)). Although the Z-axis imaging resolution of commercial light sheet microscopes is 3 μm, limiting the complete reconstruction of all axons in dense arborization structures, the external boundaries of each arborization structure could be clearly labeled ( Figure 10G and Figure 10I ). Quantitative analysis of the distribution volume of each axonal arborization structure found significant differences between different neurons ( Figure 10I ). In addition, three striatal projection neurons that did not form dense arborization structures were also identified ( Figure 10K and Figure 10J ). The axon terminals of these neurons were clearly distinguishable, indicating that complete neuron reconstruction was achieved ( Figure 10J ).

[0480] Example 11 Stable sparse labeling by AAV-mediated CRISPR knockout of Cre enzyme

[0481] To solve the problem of the AAV-mediated sparse labeling strategy that the labeling density gradually increases after long-term expression, leading to large differences between samples, a stable sparse labeling system based on the CRISPR / Cas9 system was developed. In this system, AAV expresses Staphylococcus aureus-derived Cas9 protein (SaCas9) and single-stranded guide RNA (sgRNA) against the Cre gene at the same time ( Figure 11A). In cell type-specific Cre transgenic mice, Cre-KO AAVs were directed injected into specific brain regions to achieve subsequent Cre-dependent labeling only in neurons where Cre expression was not knocked out ( Figure 11A ). The sparsity of the final labeling depends on the efficiency of Cre knockout, avoiding the drawback of increasing AAV labeling density over time.

[0482] Three sgRNAs targeting different regions of Cre were constructed (SEQ ID NO: 1-3) ( Figure 11B and 11C ). By adjusting the number of sgRNAs, Cre-KO AAV titer, or expression time, controllable adjustment of labeling sparsity can be achieved ( Figure 11C -11H). Compared with the double- AAV sparse labeling system, this Cre-KO system still maintains consistent labeling density after long-term expression ( Figure 11I and Figure 11J ).

[0483] Stable sparse labeling of midbrain GABAergic neurons and single neuron reconstruction in Example 12

[0484] To further verify the effect of LINCS combined with sparse labeling system, the above Cre-KO system was integrated with the double- AAV sparse labeling method to form the “AAV cocktail” strategy: using the double- AAV system to achieve efficient labeling, while introducing Cre-KO AAV to maintain stable sparsity ( Figure 12A and Figure 12B ).

[0485] Using Vgat-Cre mice as a model, a virus cocktail containing Cre-KO AAV, control-type AAV, and enhanced-type AAV was injected into the VTA and deep midbrain nucleus (DpMe) ( Figure 12A , Figure 12C and Figure 12D ), reconstructing 8 midbrain GABAergic neurons. Among them, 7 (GABAergic neurons 1-7) are interneurons, and 1 (GABAergic neuron 8) is a projection neuron projecting to the ventral striatum ( Figure 12E and Figure 12F ).

[0486] Further in a Vgat-Cre mouse, retrograde control-type AAV was injected into the periaqueductal gray (PAG) and a mixture of Cre-KO AAV and enhanced-type AAV was injected into the lateral hypothalamic area ( Figure 12B ). Five PAG-projecting hypothalamic GABAergic neurons were successfully reconstructed ( Figure 12G), numbered GABAergic neurons 9-13, respectively. Each neuron exhibited different projection patterns, indicating significant heterogeneity in the morphological structure of the neurons Figure 12H and Figure 12I ). The axon terminals of all neurons were clearly discernible, indicating that the reconstruction process was complete Figure 12J ).

Claims

1. A method for single-cell remodeling of neurons, the method comprising: a) Express a soluble, enhanced, neighbor-labeled enzyme in the target neuron and provide biotin to the target neuron to form a biotinylated protein in the neuron; b) Stain the biotinylated protein in the whole sample using monovalent streptavidin conjugated with a detectable marker; c) Image the stained sample to obtain images of neuronal structures; d) Reconstruct the morphological structure of a single neuron based on the image data.

2. The method according to claim 1, wherein, The adjacent labeling enzyme is a biotin ligase; preferably, the biotin ligase is selected from BioID, BioID2, TurboID, miniTurbo, Split-BioID, Split-TurboID, BASU, AirID and its variants.

3. The method according to claim 1 or 2, wherein, The neighboring marker enzyme is obtained by expressing the nucleic acid sequence encoding the enzyme in the target neuron; preferably, the nucleic acid sequence is introduced into the host cell genome through genome integration or delivered to the target neuron through an exogenous vector.

4. The method according to claim 3, wherein, The nucleic acid sequence further includes a fragment encoding a soluble tag; preferably, the soluble tag is GB1 (SEQ ID NO: 6) or a variant thereof.

5. The method according to claim 3 or claim 4, wherein, The nucleic acid sequence initiates the expression of the target gene through a conditional gene expression system; preferably, the conditional gene expression system can activate the expression of the target gene under specific conditions, which can be chemical, physical, biological or environmental factors, and the system is selected from the group or combination thereof: a Cre-LoxP recombinase-based regulatory system, an Flp-FRT recombinase-based regulatory system, a tetracycline regulatory system (Tet-on / Tet-off) and a temperature-sensitive promoter.

6. The method according to any one of claims 3-5, wherein, The nucleic acid sequence is expressed through a sparse expression system, which initiates the expression of the neighboring marker enzyme only in a subset of target neurons; preferably, the sparse expression is implemented using a combination of the following: a dilution promoter system, a dual-initiation control system, an adjustable dose induction system, a viral dose control system, and a random recombination system.

7. A nucleic acid construct comprising: a) The nucleic acid sequence encoding the adjacent labeled enzyme; and b) A nucleic acid sequence encoding a soluble tag, wherein the soluble tag is expressed in fusion with the adjacent labeling enzyme.

8. An expression vector comprising the nucleic acid construct of claim 7.

9. A fusion protein comprising: a) Proximity-labeled enzymes; and b) A soluble tag, wherein the soluble tag is fused to the adjacent labeling enzyme for expression.

10. Use of the nucleic acid construct of claim 7, the expression vector of claim 8, or the fusion protein of claim 9 in the preparation of reagents for single-cell remodeling of neurons.

Images