Research Article

Imaging cell lineage with a synthetic digital recording system

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Science  09 Apr 2021:
Vol. 372, Issue 6538, eabb3099
DOI: 10.1126/science.abb3099

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intMEMOIR traces cell lineages

Cell lineage plays a pivotal role in cell fate determination. Chow et al. demonstrate the use of an integrase-based synthetic barcode system called intMEMOIR, which uses the serine integrase Bxb1 to perform irreversible nucleotide edits. Inducible editing either deletes or inverts its target region, thus encoding information in three-state memory elements, or trits, and avoiding undesired recombination events. Using intMEMOIR combined with single-molecule fluorescence in situ hybridization, the authors were able to identify clonal structures as well as gene expression patterns in the fly brain, enabling both clonal analysis and expression profiling with intact spatial information. The ability to visualize cell lineage relationships directly within their native tissue context provides insights into development and disease.

Science, this issue p. eabb3099

Structured Abstract

INTRODUCTION

Cell lineage plays pivotal roles in cell fate determination in development, homeostasis, and disease. The ability to visualize cell lineage relationships directly within their native tissue context could provide insight into the roles of intrinsic and extrinsic factors in cell fate specification. Inspired by the recovery of lineage information from naturally occurring somatic mutations, engineered lineage recording systems actively generate stochastic, heritable mutations at defined genomic target sites, identify those edits in individual cells, and use them to reconstruct cell lineages. However, most existing recording systems have relied on sequencing to read out edits, necessarily disrupting tissue organization. Therefore, a recording system that permits accurate imaging-based in situ readout of both single-cell edit history and transcriptional state is needed.

RATIONALE

To address this challenge, we developed a digital, image-readable lineage recording system based on site-specific serine integrases, such as Bxb1. This system, called integrase-editable memory by engineered mutagenesis with optical in situ readout (intMEMOIR), introduces a design based on an array of 10 three-state memory elements. Each memory element can be digitally and irreversibly edited to generate a theoretical maximum of 310, or 59,049, distinct edit outcomes. These digital states can be read out alongside endogenous transcripts using fluorescence in situ hybridization (FISH) methods. Further, the arrays can be integrated at defined genomic sites for germline heritability. Editing can operate in different organisms and contexts, including mouse embryonic stem (mES) cells and Drosophila melanogaster embryos.

RESULTS

To assess the accuracy of lineage reconstruction using intMEMOIR, we first engineered a mES cell line containing the intMEMOIR system and then acquired time-lapse movies of these cells undergoing editing and growing into colonies. We then compared ground truth lineage relationships from the movies with reconstructions based on end-point analysis of intMEMOIR edits. intMEMOIR allowed accurate assignment of cells to clones on the basis of shared edit patterns (clonal classification). Further, stochastic and progressive editing throughout the experiment allowed reconstruction of more detailed trees (lineage tree reconstruction), with accuracy approaching the expected theoretical limit.

We then engineered an intMEMOIR recording fly termed Drosophila memoiphila. We induced editing in neuroblasts during early embryonic development and then analyzed their descendants in four adult fly brains, reading out both the intMEMOIR array and eight endogenous genes that mark diverse neuronal cell types. Within a clone, but not between different clones, spatially proximal cell pairs were more similar in cell state than more distant pairs, highlighting the importance of neuroblast ancestry in cell fate determination during fly brain development.

CONCLUSION

intMEMOIR enables simultaneous analysis of single-cell lineage, gene expression, and spatial organization in the same tissue. This ability allows it to directly capture otherwise hidden relationships, as demonstrated here in the case of fly brain development. intMEMOIR should be readily adaptable to other model organisms and developmental contexts. Further, by adding more memory arrays and orthogonal integrases, the system can be extended to enable deeper lineage tree reconstruction and multiple recording “channels.” intMEMOIR should thus facilitate the creation of cell atlases that integrate lineage and spatial information alongside molecular profiles.

intMEMOIR enables simultaneous analysis of cell lineage, state, and spatial organization.

By stochastically generating image-readable edits on an array of memory elements, intMEMOIR allows clonal labeling and lineage reconstruction, together with measurement of cell state, in situ (left). This ability enabled accurate lineage reconstruction in mouse embryonic stem cells (middle) and revealed a spatially graded, lineage-dependent correlation in cell state within Drosophila brains (right).

Abstract

During multicellular development, spatial position and lineage history play powerful roles in controlling cell fate decisions. Using a serine integrase–based recording system, we engineered cells to record lineage information in a format that can be read out in situ. The system, termed integrase-editable memory by engineered mutagenesis with optical in situ readout (intMEMOIR), allowed in situ reconstruction of lineage relationships in cultured mouse cells and flies. intMEMOIR uses an array of independent three-state genetic memory elements that can recombine stochastically and irreversibly, allowing up to 59,049 distinct digital states. It reconstructed lineage trees in stem cells and enabled simultaneous analysis of single-cell clonal history, spatial position, and gene expression in Drosophila brain sections. These results establish a foundation for microscopy-readable lineage recording and analysis in diverse systems.

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