Lmst

This week I had the pleasure of attending the #MesoSPIM Symposium in Zürich, Switzerland - and what an experience it's been! Top-notch presentations, great posters and great chats with my fellow #lightsheet #microscopy and #tissueclearing nerds. You know it's a good conference when you come back with a full notebook and a head fizzing with ideas on what to do next.
I could make the night train journey there thanks to @Co_Biologists's DMM Conference Travel Grant - much appreciated!

Moritz in front of his poster presentation at the MesoSPIM Symposium in Zürich, Switzerland

Me in front of the ÖBB Nightjet sleeper train carriage that took me to Zürich and back. Surprisingly comfortable if you book the sleeper wagon with the nice beds!

Lightsheet microscopy demo

First day of Lightsheet Z.1 demo @Sars_Centre imaging live embryos of marine worms.

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URL: https://brunovellutini.com/posts/lightsheet-microscopy-demo/

#lightsheet #microscopy #norway #tweet

Last week to apply to the Light-Sheet Image Analysis Workshop.

A five-day practical course on the processing and analysis of light-sheet microscopy imaging data. It will take place in Santiago, Chile, from January 5–9, 2026.

Deadline: August 8.

Learn more and apply here: https://lightsheetchile.cl/light-sheet-image-analysis-workshop-2026-2/

#Microscopy #Lightsheet #ImageProcessing #ImageAnalysis #LatinAmerica #GlobalSouth

Poster of the Light-Sheet Image Analysis Workshop (Santiago, Chile) from January 5-9, 2026. Application deadline: August 8.

CENTER FOR INTEGRATIVE BIOLOGY
UNIVERSIDAD MAYOR

Designed for researchers at all career levels and microscopy technicians seeking training in light sheet microscopy and multidimensional image processing.

- Introduction to lightsheet microscopy and 3D visualization
- Fundamentals of image analysis
- Machine Learning and Al for image analysis
- Working on a project using your own images or provided

Organizers:
- Anibal Vargas Rios, PhD, LiSIUM-Chile Initiative Coordinator
- Luz Fuentealba, PhD, Microscopy Unit U. Mayor Coordinator

Co-organizers and instructors:
- Marina Cuenca, PhD
- Agustin Corbat, PhD
- Bruno Vellutini, PhD

In-person Workshop will be in Universidad Mayor, Campus Huechuraba

www.lightsheetchile.cl

Ceratitis open peer review

I reviewed a paper last year about the embryonic development of Ceratitis capitata, the Mediterranean fruit fly (or medfly).

The authors used time-lapse recordings of whole embryos made with lightsheet microscopy to create a comprehensive staging system for the embryogenesis of the species.

Figure 1 from Strobl et al. (2024). doi:10.1371/journal.pone.0316391

It was one of the first reviews that I signed (disclosed my identity) from the beginning—and it felt right. As much as I understand the advantages of anonymity against power abuse from influential people, signing a review brings accountability and connection among peers.

The authors opted to publish the peer review history along with the paper, so now everyone can read it.

References

Strobl, F., Schmitz, A., Schetelig, M. F. and Stelzer, E. H. K. (2024). A two-level staging system for the embryonic morphogenesis of the Mediterranean fruit fly (medfly) Ceratitis capitata. PLoS One 19, e0316391. https://doi.org/10.1371/journal.pone.0316391

Strobl, F., Schetelig, M. F. and Stelzer, E. H. K. (2022). In toto light sheet fluorescence microscopy live imaging datasets of Ceratitis capitata embryonic development. Sci. Data 9, 340. https://doi.org/10.1038/s41597-022-01443-x

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URL: https://brunovellutini.com/posts/ceratitis-open-peer-review/

#ceratitisCapitata #diptera #embryo #evoDevo #lightsheet #microscopy #review

Strobl, F., Schmitz, A., Schetelig, M. F. and Stelzer, E. H. K. (2024). A two-level staging system for the embryonic morphogenesis of the Mediterranean fruit fly (medfly) Ceratitis capitata. PLoS One 19, e0316391. https://doi.org/10.1371/journal.pone.0316391

Fig 1. Staging of medfly embryogenesis and morphological analysis of five datasets. From Strobl, F., Schmitz, A., Schetelig, M. F. and Stelzer, E. H. K. (2024). A two-level staging system for the embryonic morphogenesis of the Mediterranean fruit fly (medfly) Ceratitis capitata. PLoS One 19, e0316391. https://doi.org/10.1371/journal.pone.0316391

Light-Sheet Image Analysis Workshop 2026

The Light-Sheet Image Analysis Workshop is a five-day intensive course that will take place in Santiago, Chile, from January 5–9, 2026, designed for students and researchers who wish to gain foundational skills in the processing and analysis of light-sheet microscopy imaging data.

The application deadline has been extended until August 8, 2025! The workshop is free to attend and travel fellowships are available. Learn more and apply here:

https://lightsheetchile.cl/light-sheet-image-analysis-workshop-2026-2/

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URL: https://brunovellutini.com/posts/light-sheet-image-analysis-workshop-2026/

#event #imageProcessing #imagej #lightsheet #microscopy

Light-Sheet Image Analysis Workshop (Santiago, Chile) from January 5-9, 2026

Colormap for mitotic waves

In a recent email exchange, someone asked me what the colors in the video of mitotic waves mean and how did I get them.

How the microscope technique results in the array of colors in the cells (purple to yellow and red). Could you briefly explain where the colors come from and how you visualised them?

It’s a great question. The topic is fascinating, and I had a lot to say about it. Since my answer might be helpful to more people with similar questions, I turned it into a blog post.

Answer

The basic approach to obtaining these images is to shine lasers at the sample and capture the resulting glow (or fluorescence imaging). The laser excites the molecules, and some will emit light in response. If we do that with a regular fly embryo, we will not see much because it doesn’t naturally have any fluorescent molecules. So, if we want to study processes in the embryo, we need to create a transgenic fly that expresses fluorescent proteins.

This specific fly from the movie expresses two different fluorescent proteins. One is a green fluorescent protein (GFP) linked to a regular protein that is always together with DNA inside nuclei (histone). The other is a red fluorescent protein (mCherry) linked to another protein that is always bound to cell membranes (Gap43).

After we put the embryo on the microscope, we shine two different lasers at the sample, and the proteins will emit fluorescence in green (~510 nm) and red (~610 nm) of the light spectrum. Using filters in the microscope, we can capture the signal from each protein on two separate images (channels). Despite the original fluorescence being green and red, the data that the microscope records is grayscale. So at the end I have two separate images, one showing the signal from the proteins in the nuclei (Histone-GFP) and another showing the signal from the proteins in the membranes (Gap43-mCherry)—both in grayscale!

What we do, then, is to choose a color for each channel. This can be any color, red/green, purple/orange, yellow/blue, etc., and does not need to match the original fluorescence color. It basically depends on what the researcher wants to highlight in the image. Some color combinations work better than others, depending on the type of signal (tiny dots or large structures), and in the observer. For example, we humans are not good at seeing details in blue but see better in green.

For the membrane signal in the video, I selected a grayscale gradient (from black to white) because it is great and uniform for our eyes. If it is a single-color image, using grays is the standard. In this case, I wanted the membranes to be present but more in the background. They appear more prominently at the beginning of the video and then fade into the background at the end when the main signal is purple.

For the nuclei signal, the main subject of the video (where most action happens), I wanted something more colorful and chose a gradient named “mpl-inferno”. It is a colormap that goes from black-purple-magenta-red-orange-yellow (see it here), and it is great to highlight small differences in signal intensities. It also comes with several technical advantages, like being color-blind safe.

Colormap mpl-inferno. Source: https://bids.github.io/colormap/

In the video, this colormap creates a captivating effect. As you noticed, the nuclei at the center of the image are bright yellow, and the color fades to orange and purple towards the edges of the embryo. This happens because the embryo is like a cylinder. Since its central portion is closer to the lens of the microscope, the camera can capture a brighter signal. In contrast, the nuclei at the edges of the embryo are further away from the lens, making the signal dimmer and more purple with this colormap.

My post, mitotic waves and gastrulation, has a few more details about the creation of the video if you want to take a look. I hope this is helpful. Please tell me if something wasn’t clear or if you have other questions.

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URL: https://brunovellutini.com/posts/mitotic-waves-colormap/

#imageProcessing #lightsheet #microscopy #visualization

Post-processed artistic crop of the mitotic waves video showing the colors.

New publication from Kwanghun Chung lab at MIT improves on their SWITCH approach and eFLASH stochastic electrotransport to improve antibody labeling by gradually shifting the microenvironment. Looks interesting, I wonder how well it can be adapted to other labeling protocols.

Uniform volumetric single-cell processing for organ-scale molecular phenotyping
Yun et al., Nature Biotechnology 2025
https://doi.org/10.1038/s41587-024-02533-4

#neuroscience #tissueclearing #lightsheet #microscopy #fluorescenceFriday

Fig. 4: Holistic comparison of transgenic and immunolabeling-based cell type labeling. a–c, 3D dataset from a PV-Cre and loxP-tdTomato dual transgenic mouse hemisphere stained with anti-PV antibody. a, Representative optical section. b, Magnified images of a. c, A percentage plot for tdTomato-only (red), anti-PV-only (green) and tdTomato and anti-PV co-positive cells (yellow) among all the labeled cells in individual representative brain regions. d–h, 3D dataset of a ChATBAC-eGFP mouse brain stained with anti-ChAT antibody. d, Whole volume rendering. e, Magnified images of d. f, A percentage plot for EGFP-only (green), anti-ChAT-only (red) and EGFP and anti-ChAT co-positive cells (yellow) among all the labeled cells in individual representative brain regions. g, Magnified view of d. h, Zoom-in view of g. Scale bars, 2 mm (cyan) and 200 μm (white). 5N, motor nucleus of trigeminal; A1, primary auditory cortex; AC, anterior cingulate cortex; BLAa, basolateral amygdala, anterior part; BLAp, basolateral amygdala, posterior part; CA1, hippocampal CA1; CA3, hippocampal CA3; CeA, central amygdala; DG, dentate gyrus; dNAmb, nucleus ambiguus, dorsal part; Ecto, ectorhinal cortex; LA, lateral amygdala; lEnto, lateral entorhinal cortex; mo, dentate gyrus, molecular layer; po, dentate gyrus, polymorph layer; Piri, piriform cortex; PPA, posterior parietal association cortex; RSA, retrosplenial cortex; sg, dentate gyrus, granule cell layer; V1, primary visual cortex;

Whole-mouse imaging the hard way: Clearing, then slicing + block-face imaging with beam-scan / sensor scan-line synchronization and continuous stage movement in an oblique imaging setup (ViSOR).
This time, they scaled it up to whole-mouse and used pre-cleared mouse bodies (ARCHmap-blockface-ViSOR):

High-speed mapping of whole-mouse peripheral nerves at subcellular resolution
Shi et al., preprint at biorxiv 2025
https://doi.org/10.1101/2025.01.22.632569

#neuroscience #lightsheet #microscopy #MicroscopyMonday

Figure 1. ARCHmap-blockface-VISoR approach for high-throughput mapping of whole mouse body at micron resolution

(A) ARCHmap-blockface-VISoR pipeline for whole-mouse imaging.

(B) Bright-field view of a cleared 2-month-old vGAT-Cre;Ai14 mouse and 400-μm-thick sections collected during blockface imaging.

(C) 3D view of a ∼600-μm-thick thoracic volume imaged from a blockface imaging section.

(C1-C6) Representative high-resolution images showing maximum intensity projection of 20-μm-thick stacks in (C) at depths of 100 μm (C1, zoomed-in view in C4), 300 μm (C2, zoomed-in view in C5), and 600 μm (C3, zoomed-in view in C6).

(D, D1) Blockface-VISoR setup. (D1) Magnification of the imaging region in (D).

(E) Cross section of imaging and sectioning modules of the blockface-VISoR setup.

(F) Schematic showing overlapped imaging data (pink) of ∼200-µm thickness between 2 contiguous imaging sections.

(G) Comparison of 3D intersection alignment by natural coordinates (G1) and a custom 3D reconstruction method (G2). Images of vessel fluorescence are the maximum intensity y-projection of 20-µm-thick sections in the upper section (red) and the lower section (green).

(H) 3D view of nerve and vasculature in a whole adult Thy1-EGFP mouse. Red hot (black-red-yellow-light yellow spectrum), LEL-DL649; cyan hot (black-blue-cyan-white spectrum), Thy1-EGFP; white surface, whole mouse.

New deep-learning cell detection pipeline for light-sheet mouse brain image stacks, with an interesting cell-coordinate clustering statistics approach:

A deep learning pipeline for three-dimensional brain-wide mapping of local neuronal ensembles in teravoxel light-sheet microscopy
Attarpour et al., Nature Methods 2025
https://doi.org/10.1038/s41592-024-02583-1

Code: https://github.com/AICONSlab/MIRACL

Documentation: https://miracl.readthedocs.io/

#lightsheet #microscopy #ImageAnalysis #neuroscience

Fig. 1 a–c, Intact whole brains immunolabeled, cleared and imaged with LSFM were used as input to the ACE pipeline. a, Whole-brain LSFM data are passed to ACE’s segmentation module, consisting of ViT- and CNN-based DL models, to generate binary segmentation maps in addition to a voxel-wise uncertainty map for estimation of model confidence. b, The autofluorescence channel of data is passed to the registration module, consisting of MIRACL registration algorithms, to register to a template brain such as the Allen Mouse Brain Reference Atlas (ARA). High-resolution segmentation maps are then voxelized using a convolution filter and warped to the ARA (10 µm) using deformations obtained from registration. c, Voxelized and warped segmentation maps are passed to ACE’s statistics module. Group-wise heatmaps of neuronal density are obtained by subtracting the average of warped and voxelized segmentation maps in each group to identify neural activity hotspots. To identify significant localized group-wise differences in neuronal activity in an atlas-agnostic manner, a cluster-wise, threshold-free cluster enhancement permutation analysis (using group-wise ANOVA) is conducted. The resulting P value map represents clusters showing significant differences between groups. Correspondingly, ACE outputs a table summarizing these clusters, including their volumes and the portion of each brain region included in each cluster.

Cool custom-built #lightsheet #microscopes: Turns out you can build a tiny light-sheet projector by whipping an optical fiber back and forth in front of a GRIN lens. The entire assembly is hand-made (coils, magnet, casing) and fits into an 18G needle. This looks like it could be super useful for imaging deep in vivo, e.g. low in a cortex.

Light-sheet microscopy enabled by a miniaturized plane illuminator
Kim et al., Biomed Optics Express 2024
https://opg.optica.org/boe/fulltext.cfm?uri=boe-16-1-115&id=565214

#neuroscience #microscopy

Fig. 2 of the paper. It shows three views of the optics construction. Left, an illustration of the principle. An optical fiber is swing back and forth in a hollow tube with a lens at the end, with the beam being projecting to different points in space.
Middle and right, two views of the detailed construction of the optics. Tiny hand-wound coils are glued to the fiber and move it towards or away from magnets (manually ground to size) at the tube wall. Two sets of coils and magnets move the fiber in the X and Y axis. At the end of the tube, the beam is focused by a GRIN lens and aimed sideways via a prism.

Wow, TRISCO (née TRIC-DISCO) is out in Science! This cool approach allows imaging of mRNA transcripts throughout the cleared mouse brain. It uses a signal amplification step with in situ Hybridization Chain Reaction (isHCR) and combines it with DISCO-style solvent-based #tissueclearing to make the brain transparent.

Whole-brain spatial transcriptional analysis at cellular resolution
Kanatani et al., Science 2024
https://doi.org/10.1126/science.adn9947

#neuroscience #lightsheet #microscopy #isHCR #mRNA #TRISCO

Fig. 3. Multiplexed TRISCO staining of whole brains.
(A) Schematic of the TRISCO protocol spanning 15 days. (B) (Top) 3D rendering of the whole brain from an 8-week-old adult mouse stained using TRISCO for cortical interneuron transcripts: Somatostatin (Sst mRNA, red), Parvalbumin (Pvalb mRNA, green), and Glutamate decarboxylase 1 (Gad1 mRNA, blue). (Bottom) Single-channel views. Bounding box, 7.7 × 10.6 × 5.5 mm. (C) Optical cross section at z = 2875 μm of the TRISCO brain in (B). (Right) Single-channel views. (Bottom) Magnified views of the hippocampus region at the indicated box. Nuclear staining was done with DiYO-1. Scale bars, 1 mm (white) and 200 μm (yellow).

In case anyone was following the recent Science paper about using Tartrazine for #tissueclearing, apparently there is at least one (competing) group that couldn't reproduce it and wrote a preprint about it:

Tartrazine cannot make live tissues transparent
https://doi.org/10.1101/2024.09.29.615648

Discussion on Pubpeer, including the Tartrazine paper's author's response:
https://pubpeer.com/publications/81314BB3706B3D6ADAD49F301B2FA5

#lightsheet #microscopy #tartrazine

New solvent-based #tissueclearing protocol claims reduced tissue distortion: Dehydration/delipidation with Hexanediol, tert-Butanol and N-butyldiethanolamine, and clearing with Benzyl Benzoate / PEGMA / N-butyldiethanolamine.

SOLID: minimizing tissue distortion for brain-wide profiling of diverse architectures
Zhu et al., Nature Comms 2024
https://doi.org/10.1038/s41467-024-52560-7

#tissueclearing #neuroscience #lightsheet #microscopy

A Bright-field images of the cleared mouse hemispheres treated with different reagents at a concentration of 30%, including 1,2-hexanediol (1,2-HxD), methanol, ethanol, tert-butanol (TB) and tetrahydrofuran (THF). B Quantitative analysis of relative transparency for different cleared samples shown in (A) (n = 3 samples). P (1,2-HxD vs. Methanol)<0.0001; P (1,2-HxD vs. Ethanol)<0.0001; P (1,2-HxD vs. TB) < 0.0001; P (1,2-HxD vs. THF) < 0.0001. C Representative images of the whole mouse brains at indicated time points during different dehydration steps. D Quantitative analysis of changes in the relative sample size during dehydration (n = 3 samples). E The established SOLID pipeline.

Mitotic Waves video wins Small World in Motion

My video of mitotic waves won Nikon’s 2024 Small World in Motion video competition! I’m thrilled 🎉

https://www.youtube.com/watch?v=KhKlUu1SdZI

To learn more about the video, check out Nikon’s press release and their article for the series Masters of Microscopy.

There’s also a blog post that I wrote a couple of years ago with some biological information and technical details about how I created the video.

If you are wondering about the size of the embryo and how fast it really develops, there’s a version with a scale bar and time label on YouTube and available for download and re-use on Wikimedia Commons.

Thanks for your support :)

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URL: https://brunovellutini.com/posts/mitotic-small-world/

#diptera #drosophilaMelanogaster #embryo #lightsheet #microscopy #scienceOutreach #video

New #tissueclearing #preprint uses a custom mouse behaviour + deep-learning c-Fos analysis pipeline to compare several different Serotonin receptor agonists / antagonists in mice.

Concerted modulation of spontaneous behavior and time-integrated whole-brain neuronal activity by serotonin receptors
Friedmann et al., preprint at biorxiv 2024
https://doi.org/10.1101/2024.08.02.606282

#lightsheet #microscopy #serotonin #neuroscience #preprint #brainmapping

Fig. 3 Overview of the effect of serotonin receptor agonists and antagonists on whole-brain Fos maps.

a, Experimental design for whole-brain analysis pipeline of Fos image data. b, Left, horizontal view of a 500-µm Z-projection of raw Fos image data. Right, zoom in of the boxed region from the left image (top), which is segmented by 3D-Unet based TrailMap. Centroids are established as local maxima detected from the probability maps and a 6-connected neighborhood of raw intensity values is averaged to be the intensity of each centroid. c, Horizontal (left) and coronal (right) depth-coded views of a single brain’s detected centroids demonstrate even coverage across the entire intact brain. d, Total numbers of counted nuclei per mouse and grouped by drug treatment. e, Scatter plot of average Fos intensity against the total Fos count (as in d) for all 168 mice, color coded by drug treatment. Linear fit shows significant correlation, R2 = 0.281. f, A representative 100-µm coronal slice of saline-subtracted Fos intensity maps for each drug treatment group, averaged across individuals within treatment groups. g, Coronal slices (as in f) across anteroposterior axis for two example drug treatment groups. h, Average saline-subtracted Fos intensity for the two drug treatment groups in g for all nuclei in each of 282 Allen-brain regions at the bottom, color coded according to Allen Brain Atlas38. Each dot represents data from an individual mouse.

New #tissueclearing paper checks oligodendrocyte distribution throughout the entire mouse brain. Looks pretty neat!

Brain-wide mapping of oligodendrocyte organization and oligodendrogenesis across the murine lifespan
Xu et al., preprint at biorxiv 2024
https://doi.org/10.1101/2024.09.06.611254

Github: https://github.com/yxu233/Xu_Bergles_brainwide_oligo_map

#neuroscience #lightsheet #microscopy #preprint #oligodendrocyte #myelination

Figure 1. Visualization of whole brain myelin patterns.
A. Oligodendrocyte somata and myelin sheaths are fluorescently labeled in Mobp-EGFP mice.
B. Representative confocal images showing colocalization of ASPA and endogenous EGFP.
C. Quantification of ASPA colocalization across mouse strain and age in gray and white matter.
D. Schematic illustration of clearing pipeline (left) along with images of cleared brains at each step
(right).
E. Schematic of brain mounting with UV light (purple) activated glue and 3D printed sample holders. Lightsheet illumination objectives scan perpendicular to sample.
F. Representative FOVs of single horizontal plane from lightsheet volume acquired with low
resolution 5×/0.16 NA air objective (left). FOVs highlight the diversity of myelin patterns across
brain regions (insets right).

For #TBT, we’re looking back on the interviews with CZI grantees by Constadina Arvanitis & Mariana De Niz. This week we’re highlighting Alenka Lovy, whose CZI project aims to connect labs by implementing light sheet microscopy at a larger scale.
https://focalplane.biologists.com/2024/01/24/enhancing-global-access-interview-to-czi-grantee-alenka-lovy/
#microscopy #lightsheet #microscope #interview

This preprint looks like a conceptual advance for deeper staining (also in human tissue) and multi-round multiplexed immunostaining with BABB clearing.

INSIHGT: Accessible multimodal systems biology with quantitative molecular phenotyping in 3D
Yau et al., preprint at biorxiv 2024
https://doi.org/10.1101/2024.05.24.595771

#tissueclearing #lightsheet #microscopy #neuroscience #FluorescenceFriday

Fig. 2A: (A) Experimental steps and principle of INSIHGT for
immunostaining. Top row: Tissue is infiltrated with antibodies and a weakly coordinating superchaotrope ([B12H12]
2-, purple
dodecahedron) in the 1st staining solution and then transferred into the 2nd solution containing a complexation agent (CD, red
ring). Bottom row: The molecular principles of INSIHGT. Weakly coordinating anion prevents antibody-antigen interactions,
removing penetration obstacles. After homogeneous infiltration, subsequent γCD infiltration complexes the [B12H12]
2- ions,
allowing deep tissue immunostaining.

Fig. 6A+B: . (A) Schematics of the processing steps for a 1mm-thick mouse hypothalamus
sample. (B) A selection of multi-round immunostaining signals (for nine targets) displayed for the multi-round multiplexed
INSIHGT-processed sample.

Landmarking via UV-activatable dye makes mapping between light-sheet and confocal imaging possible

Correlative multiscale 3D imaging of mouse primary and metastatic tumors by sequential light sheet and confocal fluorescence microscopy
Zheng et al., preprint at biorxiv 2024
https://doi.org/10.1101/2024.05.14.594162

#preprint #tissueclearing #lightsheet #microscopy

Interesting new #preprint about #tissueclearing and #lightsheet #microscopy in mouse ovaries. Complete with #napari-based deep-learning pipeline and detailed build instructions for 3D-printed sample chambers for solvent-cleared samples, so they can be viewed under a #confocal!

OoCount: A machine-learning based approach to mouse ovarian follicle counting and classification
Folts et al., preprint at biorxiv 2024
https://www.biorxiv.org/content/10.1101/2024.05.13.593993v1

#lightsheet

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