A team of researchers from the Lichtman Lab, led by Program in Neuroscience (PiN) graduate student turned joint postdoc in the Lichtman and Dulac Labs Xiaomeng Han, has developed a technique for adding localization data about specific biomolecules to electron microscope (EM) data. Using an approach known as connectomics, the Lichtman Lab collects EM data and uses it to analyze the microstructures of brain tissue. However, connectomic data doesn’t show where biomolecules are located, which can be crucial information for identifying cell types and understanding what’s happening within cells. In the new study, published in the journal Nature Communications, Han and her colleagues used glowing molecular probes that bind to specific proteins to create a colorful overlay for connectomic EM data. The combined data allowed them to observe new details in a sample from the mouse cerebellar cortex.
“Neural circuits can be mapped using serial section electron microscopy techniques but these do not provide information about cell types or other molecular annotations,” says MCB faculty and Dean of Science for FAS Jeff Lichtman. “This work describes an approach to superimpose molecular annotations on serial electron microscopy volumes by taking advantage of the high permeability of small fluorescent antibody fragments that permeate tissue volumes and enter cells without the need of detergents. In this way confocal and electron microscopy datasets of the same tissue can be created. In this paper we show that 5 or even more molecular markers can be overlain on a single serial electron microscopy volume to label cell types and parts of neurons in the cerebellum.”
“Getting large EM data sets is quite time consuming,” Han explains. “So if you have many molecular labeling, you will be able to localize many biomolecules in the EM stack to facilitate your analysis. So you don’t need to generate a separate data set for each biomolecule…The other thing is that with multiple labeling simultaneously, you can, because of combinations, can help you distinguish certain cells or cellular objects. For a cell type, it may express multiple biomolecules, so if you don’t do multiple labeling, you will not be able to identify it.”
In this study, the scientists used a type of immunolabeling probe called single chain variable fragments (scFvs). They are derived from monoclonal antibodies but are much smaller and therefore can penetrate deeper into tissue, even without the use of a detergent. Han and her colleagues obtained the scFv probes from collaborator James Trimmer of University of California, Davis.
Han and her colleagues collected data from a sample from the cerebellum of a mouse, labeled with five different scFv probes, each of which detected a different protein. Working with Doug Richardson and the team at Harvard Center for Biological Imaging (HCBI), the researchers used a technique called spectral unmixing to capture the six (five from scFv labeling, one from cell nuclei labeling) distinct fluorescent signatures. Using that fluorescence data, Han and her colleagues created a colorful fluorescence overlay for the EM data. The fluorescence data and the EM data were combined by a process called co-registration to create the final correlated light and electron microscopy (CLEM) dataset.
Analysis of the CLEM dataset revealed several unexpected details about the mouse cerebellar cortex. Han says there are three main biological findings. “Using the labeling, we were able to identify a very rarely studied cell neuronal cell type called molecular layer granule cells, and study how they are wired within the cerebellar circuits,” she says. “The second one was that we were able to localize a type of voltage-gated potassium channel at a cellular subcompartment called juxtaparanodes, which was previously unknown…The third one is we were able to distinguish two molecularly defined mossy fiber terminals that use different neurotransmitter transporters and analyze their ultrastructure.These biological findings illustrate that the CLEM technique enabled by scFv is a powerful way to investigate brain connectomics.”
Han and her colleagues have made the scFv probes they used available to other researchers through Addgene in hopes that this technique will be replicated in other connectomics studies. Because scFvs are made from monoclonal antibodies and given that there are so many monoclonal antibodies currently available, many more scFvs that bind to other important brain markers can be generated and used for CLEM and connectomics studies.
An electron microscopy image volume from the cerebellar cortex overlaid with six colors of protein labeling by scFv probes. The floating colorful objects are cells and cellular structures are identified by each of the labeling.
Han and Trimmer presented this work at this year’s “Lighting up Neurobiology with Antibodies” symposium
Han adds that she would like to thank all of her collaborators, both in the Lichtman Lab and elsewhere. These include Lichtman Lab postdoc Xiaotang Lu, who introduced Han to Trimmer. Trimmer and his colleagues generated the sequences to make scFv probes and helped validate the scFv probes Han made. Collaborator Hidde Ploegh of Boston Children’s Hospital and his colleagues provided materials for scFv probe production. Lichtman Lab members (Richard Schalek, Shuohong Wang, Yaron Meirovitch, Yuelong Wu, and Daniel Berger) performed EM data acquisition and processing. Collaborators Viren Jain and Peter Li at Google Research performed segmentation of the EM data. Collaborator Donglai Wei and his colleagues at Boston College performed fine analysis on the EM data. Han’s summer intern students Elif Sevde Meral from Turkey and Shadnan Asraf supported by Mayor’s Summer Youth Employment Program (MSYEP) also made contributions to the work.
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