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Aceves-Salvador, J.

Publications and source records attributed to Aceves-Salvador, J..

2 recordsLinked to original sources

In situ profiling of plasma cell clonality with image-based single-cell transcriptomics

Image-based single-cell transcriptomics can identify diverse cell types within intact tissues. However, in adaptive immunity, V(D)J recombination generates unique immune receptors within cells of the same type, leading to important functional variation that is not yet defined by these methods. Here we introduce B-cell-receptor multiplexed error robust fluorescence in situ hybridization (BCR-MERFISH), which distinguishes plasma cell clones based on V-gene usage in combination with transcriptome profiling. We demonstrate that BCR-MERFISH accurately identifies V-gene usage in cell culture and in mice with restricted or native plasma cell diversity. We then use BCR-MERFISH to reveal the microbiota-dependent changes in plasma cell abundance, clonal diversity, and public clonotype usage in the mouse gut and the non-uniform distribution of plasma cell clones along the mouse ileum. As tissue context is an essential modulator of plasma cell dynamics, we anticipate that BCR-MERFISH may offer new insights into a wide range of immunological questions.

immunology↗

Protocol Optimization Improves the Performance of Multiplexed RNA Imaging

Spatial transcriptomics has emerged as a powerful tool to define the cellular structure of diverse tissues. One such method is multiplexed error robust fluorescence in situ hybridization (MERFISH). MERFISH identifies RNAs with error tolerant optical barcodes generated through sequential rounds of single-molecule fluorescence in situ hybridization (smFISH). MERFISH performance depends on a variety of protocol choices, yet their effect on performance has yet to be systematically examined. Here we explore a variety of properties to identify optimal choices for probe design, hybridization, buffer storage, and buffer composition. In each case, we introduce protocol modifications that can improve performance, and we show that, collectively, these modified protocols can improve MERFISH quality in both cell culture and tissue samples. As RNA FISH-based methods are used in many different contexts, we anticipate that the optimization experiments we present here may provide empirical design guidance for a broad range of methods.

genomics↗