Eric Lubeck

Single-Cell Phenotyping within Transparent Intact Tissue through Whole-Body Clearing

Understanding the structure-function relationships at cellular, circuit, and organ-wide scale requires 3D anatomical and phenotypical maps, currently unavailable for many organs across species. At the root of this knowledge gap is the absence of a method that enables whole-organ imaging. Herein, we present techniques for tissue clearing in which whole organs and bodies are rendered macromolecule-permeable and optically transparent, thereby exposing their cellular structure with intact connectivity. We describe PACT (passive clarity technique), a protocol for passive tissue clearing and immunostaining of intact organs; RIMS (refractive index matching solution), a mounting media for imaging thick tissue; and PARS (perfusion-assisted agent release in situ), a method for whole-body clearing and immunolabeling. We show that in rodents PACT, RIMS, and PARS are compatible with endogenous-fluorescence, immunohistochemistry, RNA single-molecule FISH, long-term storage, and microscopy with cellular and subcellular resolution. These methods are applicable for high-resolution, high-content mapping and phenotyping of normal and pathological elements within intact organs and bodies.

Single-cell systems biology by super-resolution imaging and combinatorial labeling

Fluorescence microscopy is a powerful quantitative tool for exploring regulatory networks in single cells. However, the number of molecular species that can be measured simultaneously is limited by the spectral overlap between fluorophores. Here we demonstrate a simple but general strategy to drastically increase the capacity for multiplex detection of molecules in single cells by using optical super-resolution microscopy (SRM) and combinatorial labeling. As a proof of principle, we labeled mRNAs with unique combinations of fluorophores using fluorescence in situ hybridization (FISH), and resolved the sequences and combinations of fluorophores with SRM. We measured mRNA levels of 32 genes simultaneously in single Saccharomyces cerevisiae cells. These experiments demonstrate that combinatorial labeling and super-resolution imaging of single cells is a natural approach to bring systems biology into single cells.

Single-cell in situ RNA profiling by sequential hybridization

In our previous paper, Lubeck and Cai, we used super-resolution microscopy to resolve a large number of mRNAs in single cells. In this Correspondence, we present a sequential barcoding scheme to multiplex different mRNAs.

Single-molecule RNA detection at depth by hybridization chain reaction and tissue hydrogel embedding and clearing.

Accurate and robust detection of mRNA molecules in thick tissue samples can reveal gene expression patterns in single cells within their native environment. Preserving spatial relationships while accessing the transcriptome of selected cells is a crucial feature for advancing many biological areas – from developmental biology to neuroscience. However, because of the high autofluorescence background of many tissue samples, it is difficult to detect single-molecule fluorescence in situ hybridization (smFISH) signals robustly in opaque thick samples. Here, we draw on principles from the emerging discipline of dynamic nucleic acid nanotechnology to develop a robust method for multi-color, multi-RNA imaging in deep tissues using single-molecule hybridization chain reaction (smHCR). Using this approach, single transcripts can be imaged using epifluorescence, confocal or selective plane illumination microscopy (SPIM) depending on the imaging depth required. We show that smHCR has high sensitivity in detecting mRNAs in cell culture and whole-mount zebrafish embryos, and that combined with SPIM and PACT (passive CLARITY technique) tissue hydrogel embedding and clearing, smHCR can detect single mRNAs deep within thick (0.5 mm) brain slices. By simultaneously achieving ∼20-fold signal amplification and diffraction-limited spatial resolution, smHCR offers a robust and versatile approach for detecting single mRNAs in situ, including in thick tissues where high background undermines the performance of unamplified smFISH. Summary: Single-molecule hybridization chain reaction, combined with tissue clearing, allows the near-quantitative and spatially localized detection of mRNAs in thick tissue samples.

Editorial Note to: In Situ Transcription Profiling of Single Cells Reveals Spatial Organization of Cells in the Mouse Hippocampus

(Neuron 92, 342–357, October 19, 2016)In this issue, we, the editors of Neuron, are publishing a Matters Arising from Cembrowski and Spruston (https://doi.org/10.1016/j.neuron.2017.04.023) and a Matters Arising Response from Shah and colleagues from the lab of Long Cai (https://doi.org/10.1016/j.neuron.2017.05.008).The Matters Arising format is specifically meant for articles that call into question the validity of a published Neuron paper, usually with new data or analyses. The Matters Arising from Cembrowski and Spruston raises concerns with a Neuron NeuroResource published in October 2016 by Shah and colleagues (https://doi.org/10.1016/j.neuron.2016.10.001). Shah et al. described a method for transcriptional profiling of complex tissues using an in situ 3D multiplexed imaging method, sequential fluorescence in situ hybridization (seqFISH). seqFISH uses a temporal “barcoding scheme” that comes from sequential hybridization of mRNA in fixed cells. The modified seqFISH method includes signal amplification and error correction for improved multiplexed mRNA detection in complex neural tissue. As a proof of principle, the authors analyzed mouse brain slices containing cortex and hippocampus to reveal distinct cell-type regionalization, including within the hippocampal CA1 field.The Matters Arising from Cembrowski and Spruston calls into question the described regionalization of cell types within CA1 using seqFISH and suggests that factors in the experimental design unduly influenced the interpretation of the results. By comparing and analyzing previously published and publically available ISH, scRNaseq, and bulk-RNA-seq data, the Matters Arising suggests that the genes used in Shah et al.’s seqFISH analysis are expressed at low or undetectable levels in the hippocampus and should not be the basis for defining the spatial organization of cell types in the hippocampus. They also contend that the taxonomic map of hippocampus described in Shah et al. does not reflect canonical cellular hierarchies and that non-barcoded high expression genes and the inclusion of CA2 in the samples, rather than the improved seqFISH methodology, underlie the hippocampal divisions described in Shah et al., 2016 (https://doi.org/10.1016/j.neuron.2016.10.001).The Matters Arising Response from Shah and colleagues addresses these concerns by citing published studies demonstrating that seqFISH is more sensitive than single-cell RNA-seq in quantifying transcript copy numbers, that many of the barcoded transcripts match those observed in previous studies, and that genes with low average expression levels are still informative for measuring cell-to-cell variation and assigning cell classification because gene expression is highly correlated across all expression levels. The Matters Arising Response also examines the potential influence of CA2 and high expressing non-barcoded genes. While they report that one brain slice did have a slight enrichment of CA2 marker genes, when non-barcoded high expressing genes are removed, the same spatial organization of the hippocampus is still observed.In general, when this type of refutation of a Neuron paper comes to our attention, the editors evaluate the concerns raised and decide whether it should be brought to the attention of the authors, reviewers, and potentially the larger community. Following editorial review, we provide the authors of the paper being questioned the opportunity to submit a written Matters Arising Response. This Response is peer reviewed along with the Matters Arising. In this case, the original review panel of the Shah et al., 2016 Neuron manuscript (three reviewers) and an additional external expert reviewed both the Matters Arising and the Matters Arising Response.Depending on the reviewers’ feedback and our editorial evaluation of the case, multiple potential outcomes are possible, including not publishing the Matters Arising or the Response; publishing the critique and response; correction of the original paper; or retraction of the paper. If a Matters Arising is published, all authors are typically given the opportunity to revise based on the reviewers’ feedback. Scientific misconduct was not a point of consideration and the technique itself was not being called into question in this Matters Arising case. Indeed, all the reviewers saw seqFISH as a promising technique and the process of evaluating the Matters Arising and the Matters Arising Response papers catalyzed an interesting discussion.Although the reviewers expressed that the cases brought forward by both the Matters Arising and Matters Arising Response are not decisive and each had their own weaknesses and strengths, what resonated from the reviewer feedback is that no method on its own is able to provide the hard truth. With this in mind, we made the editorial decision to publish the Matters Arising and Matters Arising Response as the dialog here goes beyond defining the organization of CA1. Current innovations and developments in molecular tools are allowing the capture and profiling of cellular diversity and organization of the brain with unprecedented detail. However, without integrating molecular profiles with other complementary molecular analytical tools, and a stronger reference to the anatomical, developmental, and functional understanding of the system, descriptions of the cellular organization of the brain only based on expression profiles may miss the opportunity to relate the findings to the function and dysfunction of the brain. In publishing these papers, we hope they serve as an important starting point for the neuroscience community to constructively and openly discuss how to intersect profiles of cellular expression across methodologies with the understanding of the biological function of the system being analyzed.