Recording gene expression order in DNA by CRISPR addition of retron barcodes.

Biological processes depend on the differential expression of genes over time, but methods to make physical recordings of these processes are limited. Here we report a molecular system for making time-ordered recordings of transcriptional events into living genomes. We do this through engineered RNA barcodes, based on prokaryotic retrons1, that are reverse transcribed into DNA and integrated into the genome using the CRISPR-Cas system2. The unidirectional integration of barcodes by CRISPR integrases enables reconstruction of transcriptional event timing based on a physical record through simple, logical rules rather than relying on pretrained classifiers or post hoc inferential methods. For disambiguation in the field, we will refer to this system as a Retro-Cascorder.

Precise genome editing across kingdoms of life using retron-derived DNA.

Exogenous DNA can be a template to precisely edit a cell's genome. However, the delivery of in vitro-produced DNA to target cells can be inefficient, and low abundance of template DNA may underlie the low rate of precise editing. One potential tool to produce template DNA inside cells is a retron, a bacterial retroelement involved in phage defense. However, little effort has been directed at optimizing retrons to produce designed sequences. Here, we identify modifications to the retron non-coding RNA (ncRNA) that result in more abundant reverse-transcribed DNA (RT-DNA). By testing architectures of the retron operon that enable efficient reverse transcription, we find that gains in DNA production are portable from prokaryotic to eukaryotic cells and result in more efficient genome editing. Finally, we show that retron RT-DNA can be used to precisely edit cultured human cells. These experiments provide a general framework to produce DNA using retrons for genome modification.

Molecular recording: transcriptional data collection into the genome.

Advances in regenerative medicine depend upon understanding the complex transcriptional choreography that guides cellular development. Transcriptional molecular recorders, tools that record different transcriptional events into the genome of cells, hold promise to elucidate both the intensity and timing of transcriptional activity at single-cell resolution without requiring destructive multitime point assays. These technologies are dependent on DNA writers, which translate transcriptional signals into stable genomic mutations that encode the duration, intensity, and order of transcriptional events. In this review, we highlight recent progress toward more informative and multiplexable transcriptional recording through the use of three different types of DNA writing - recombineering, Cas1-Cas2 acquisition, and prime editing - and the architecture of the genomic data generated.

A High-Throughput Colocalization Pipeline for Quantification of Mitochondrial Targeting across Different Protein Types.

Efficient metabolic engineering and the development of mitochondrial therapeutics often rely upon the specific and strong import of foreign proteins into mitochondria. Fusing a protein to a mitochondria-bound signal peptide is a common method to localize proteins to mitochondria, but this strategy is not universally effective, with particular proteins empirically failing to localize. To help overcome this barrier, this work develops a generalizable and open-source framework to design proteins for mitochondrial import and quantify their specific localization. This Python-based pipeline quantitatively assesses the colocalization of different proteins previously used for precise genome editing in a high-throughput manner to reveal signal peptide-protein combinations that localize well in mitochondria.

High-throughput colocalization pipeline quantifies efficacy of mitochondrial targeting signals across different protein types.

Efficient metabolic engineering and the development of mitochondrial therapeutics often rely upon the specific and strong import of foreign proteins into mitochondria. Fusing a protein to a mitochondria-bound signal peptide is a common method to localize proteins to mitochondria, but this strategy is not universally effective with particular proteins empirically failing to localize. To help overcome this barrier, this work develops a generalizable and open-source framework to design proteins for mitochondrial import and quantify their specific localization. By using a Python-based pipeline to quantitatively assess the colocalization of different proteins previously used for precise genome editing in a high-throughput manner, we reveal signal peptide-protein combinations that localize well in mitochondria and, more broadly, general trends about the overall reliability of commonly used mitochondrial targeting signals.

Temporally resolved transcriptional recording in E. coli DNA using a Retro-Cascorder.

Biological signals occur over time in living cells. Yet most current approaches to interrogate biology, particularly gene expression, use destructive techniques that quantify signals only at a single point in time. A recent technological advance, termed the Retro-Cascorder, overcomes this limitation by molecularly logging a record of gene expression events in a temporally organized genomic ledger. The Retro-Cascorder works by converting a transcriptional event into a DNA barcode using a retron reverse transcriptase and then storing that event in a unidirectionally expanding clustered regularly interspaced short palindromic repeats (CRISPR) array via acquisition by CRISPR-Cas integrases. This CRISPR array-based ledger of gene expression can be retrieved at a later point in time by sequencing. Here we describe an implementation of the Retro-Cascorder in which the relative timing of transcriptional events from multiple promoters of interest is recorded chronologically in Escherichia coli populations over multiple days. We detail the molecular components required for this technology, provide a step-by-step guide to generate the recording and retrieve the data by Illumina sequencing, and give instructions for how to use custom software to infer the relative transcriptional timing from the sequencing data. The example recording is generated in 2 d, preparation of sequencing libraries and sequencing can be accomplished in 2-3 d, and analysis of data takes up to several hours. This protocol can be implemented by someone familiar with basic bacterial culture, molecular biology and bioinformatics. Analysis can be minimally run on a personal computer.