Whole human organ clearing and multimodal mapping

Reviewer #1 (Public review):

Summary:

The authors sought to develop a generalisable method for clearing and labelling large, highly complex human organs and tissues while preserving their three-dimensional structure, enabling visualisation at high resolution. The resulting body of work is substantial, encompassing a diverse range of tissues and labelling approaches, and demonstrates an impressive breadth of experimental work.

Strengths:

A major strength of the method is its systematic validation across a diverse range of human tissues, including several understudied tissues, in combination with labelling using multiple antibodies and fluorescent dyes. An additional strength is that the skin was retained on the finger throughout the clearing, labelling, and imaging procedures, allowing the tissue to be analysed in an intact state. This is particularly relevant to sensory neuroscience, where preserving the cutaneous sensory structures may be important. The use of tissue from donors aged 85 years and older is also a strength, as it provides a stringent test of the method in tissues with substantial age-related pigment accumulation and autofluorescence.

Weaknesses:

A major limitation is the lack of evidence that the method can be applied to formalin-fixed, paraffin-embedded (FFPE) tissue, which represents a substantial proportion of archived human tissue and is an important potential application of tissue-clearing approaches. Furthermore, the claim that the method is cost-effective is not sufficiently supported by the data presented, as there is no comparison of the costs of the proposed approach with those of existing methods.

Appraisal:

(1) Overall, I feel that the authors have broadly achieved their stated aims, although several aspects would benefit from further qualification or supporting evidence.

(2) Although magnetic resonance imaging (MRI) was performed on four tissues, the MRI data do not appear to be fully integrated with the microscopy data, and I did not find evidence of precise spatial correlation of structural information between the two modalities.

(3) The term "photoclearing" may be useful to describe the approach, but the underlying concept does not appear to be entirely novel, given that increased optical transparency can occur as a consequence of photobleaching. Furthermore, the evidence presented is not sufficient, in my view, to establish that the observed effects are attributable to photodegradation of pigments.

(4) I question whether the broader claims regarding the scalability of existing tissue-clearing approaches are sufficiently supported. In particular, the claim that aqueous- and hydrogel-based methods have limited scalability may require further evidence, given that perfusion-based approaches can facilitate processing of large tissue volumes. Similarly, the assertion that organic solvent-based approaches are better suited to large tissue volumes does not appear to be fully supported by the data presented, unless this refers specifically to the beneficial effects of tissue shrinkage during dehydration on imaging.

(5) More generally, a direct comparison of the clearing, labelling, and imaging outcomes for the thyroid samples fixed for 48 hours versus 8 years would be valuable for assessing the extent to which fixation duration influences the performance of the method.

Discussion:

The results have potential value for medical education, comparative anatomy, and research requiring the characterisation of human anatomy across spatial scales. The method could have applications across multiple disciplines and may be of interest to researchers who have access to human tissue from sources including archival material, biopsies, surgical resections, tissue banks, autopsy specimens, and donor tissue. However, the length and complexity of the protocol may limit its practical adoption, particularly in settings where throughput is an important consideration.

Context:

The results for the inner ear and ring finger are particularly notable because they demonstrate the ability of the method to clear, label, and image anatomically complex, highly calcified, and densely structured tissues. The successful clearing and immunolabelling of tissue fixed for 15 years is also significant, given the potential challenges associated with antibody penetration and preservation of epitopes following prolonged fixation. More broadly, successful imaging of large organs, such as the heart, is technically important given the challenges that their size and geometry present for light-sheet microscopy, and demonstrates the feasibility of applying the approach to intact human organs.

Technical concern:

The manuscript should acknowledge the hazardous and potentially toxic nature of several reagents used in the protocol, together with the challenges of safely handling and disposing of the relatively large volumes of chemical waste generated. These factors may have practical implications for implementation of the method.

Conceptual concerns:

The role and added value of photogrammetry in the study are not entirely clear. It would be helpful for the authors to clarify how photogrammetry was used beyond its presentation in the figures and what additional information or utility it provides relative to the other imaging modalities employed.

Reviewer #2 (Public review):

Summary:

The authors claim to present a generally applicable tissue processing pipeline for optical tissue clearing and labelling of whole human organs. To achieve this, they combine multiple previously published tissue pretreatment steps to enhance tissue permeabilization, and hence label penetration, as well as optical transparency. Most notably, the authors include LED photobleaching, or photoclearing as they call it here, to reduce both autofluorescent background and increase tissue transparency. Extending their previously published method towards a wide variety of large human samples encompassing multiple organs and tissues, they combine their clearing protocol with several small molecule dyes for general overview stains as well as immunofluorescence labelling. For some of the processed samples, they introduce a novel multimodal imaging pipeline, which includes photogrammetry, MRI, and 3D histology/microscopy. Both the multimodal pipeline and the described tissue clearing and labelling protocols seem highly useful for both pathology as well as fundamental research, especially since the modularity of tissue-clearing protocols allows for the integration of individual steps, such as photoclearing, into already established methods.

Strengths:

The transparency of the large, archival human samples is very impressive and, to my knowledge, constitutes the best human tissue clearing to date. The positive effects of photobleaching/clearing on autofluorescence reduction as well as transparency are obvious and highly interesting for the field, as this method can easily be implemented into any tissue clearing approach. It is highly appreciated that notes are provided in both the methods and results, on which steps of the pipeline had to be adjusted for different tissue types and sizes. However, this could be presented in a more structured way, by showing a graphical representation or at least a table of all used tissues and all the steps of the pipeline, with indications for which steps were skipped/adjusted per tissue type as well as the incubation times for every step. Table 2 already does that for light exposure and decalcification times, but it would be beneficial to do this for all steps to get a better overview. This would also aid replication and implementation of their method, as other groups can just look up the closest matching tissue type in the table and go from there rather than piecing this information together with the in-text notes.

The combination of different small molecule dyes, while in itself not new, has the potential to provide 3D alternatives for conventional histological overview stains. Other groups have already shown 3D H&E and Nissl stains, and it would be interesting what other routinely used stains could be mimicked in that way. Here, the combination of Eosin Y and Fast Green seems especially interesting.

The quality of the immunofluorescence labelling is extremely good, especially given the age of some of the samples (e.g. very high-quality SMA staining in 15-year-old material). It would be interesting to know if the authors encountered antibodies that were not compatible with their archival tissue and, if so, which ones.

Weaknesses:

It is not exactly clear to me how some of the image volumes were acquired. For example, the panels 1f-h: The regions these volumes originate from are indicated in the cleared heart (1e), but were these regions blocked out or was the entire heart somehow immersed in the imaging chamber? The latter would be, to the best of my knowledge, a novel scale of light sheet imaging and should be mentioned. If the regions were somehow blocked out, this should be described. In general, a lot of the imaging volumes seemed to have been acquired mainly towards the periphery of the sample, especially the higher magnification inserts. This immediately raises the question of whether this is because imaging was not possible in the centre and why (limitation of the imaging chamber size, light penetration, label penetration, or a combination of those?). While it is understandable that it is currently not possible to image, e.g. entire kidneys in light-sheet set-ups, the limits of feasible sample sizes should be mentioned somewhere to give the reader a better appreciation of the usefulness of the method. The authors demonstrate that it is possible to clear whole organs, but is it also possible to label whole organs? Is that possible with antibodies as well, or only with small-molecule dyes? And how deep can samples be imaged in the best-case scenario? Right now, the paper uses a common scheme in the tissue clearing literature, of showing a very large cleared sample and then imaging a smaller sub-volume while implying that, in principle, it is possible to do that for the entire organ, if the objective working distance and imaging chamber would allow. However, to scale their method up, the authors would first need to show that their labels would penetrate throughout the entire sample, and this is currently not done in an unambiguous manner.

The biggest limitation in the manuscript for me is the authors' claim: "We demonstrate the voxel-by-voxel alignment between MRI and microscopy datasets, merging cellular-scale detail and protein-specific labelling with macroscopic medical imaging." While technically true, the authors only show actual overlays of microscopy and MRI data for the inner ear sample in Figure 5. No overlays between MRI and the microscopy volumes are shown for the heart and finger data, which is a missed opportunity. Similarly, no overlays between all three acquired modalities (photogrammetry, MRI, 3D microscopy) are shown for any of the samples. This is a pity, as the authors put a lot of emphasis on this novel multimodal pipeline, even though side-by-side demonstrations of MRI and 3D microscopy in a similar manner have been shown already by other groups and a truly multimodal dataset with the different modalities, e.g. as different channels in a volume, would be very exciting.