SGE is generalizable across cell types. We engineer T-cells (Jurkat) to grow without valine.

We believe a similar strategy could help create more resilient T-cells for therapy, capable of surviving and functioning in the metabolically depleted environments of tumors. Hopefully more here soon!

We then used SGE to engineer CHO cells to grow without isoleucine, a feat we could not achieve via rational design and delivery of entire synthetic pathways.

Again, mitochondrial localization was favored, with individual clones reflecting ~40-50kb of integrated DNA!

Using SGE, we screened millions of pathway combinations in a single experiment to engineer CHO cells that grew at WT rate (~1.1 day/doubling) in valine-free medium.

Intriguingly, the best clones all employed mitochondrial localization of pathway components, not cytoplasm as in our prev. design.

As a test case, we used SGE to engineer essential amino acid prototrophy in mammalian cells, a behavior last seen over 500 million years ago.

Unlike E. coli, which can make all 20 proetinogenic amino acids, mammals lack the pathways for 9 “essential” ones and must obtain them through the diet.

In SGE, we clone and deliver a TU library at high MOI so that each cell gets a random mix, assembling a unique synthetic metabolic pathway per cell. Cells with the desired phenotype (e.g., survival or fluorescence) are selected, and TU barcodes are sequenced to identify functional combinations.

Mammalian metabolic engineering is key to advancing bioproduction, cell therapy, and rejuvenation.

But as pathway complexity grows, so does the combinatorial design space! However, delivering large DNA constructs to mammalian cells is inefficient, making large unbiased screens intractable.

inally, Genome-shuffle-seq is designed to capture both SV identity (from T7 transcripts) and associated transcriptomes in single-cells using
@10xgenomics.bsky.social feature barcoding.

We demonstrate the measurement of gene expression changes resulting from SVs in single cells.

As a by-product of genome shuffling, we launched hundreds of synthetic extra-chromosomal DNA circles (ecDNAs) in a single experiment.

This could serve as a model to study the ecDNA life cycle, its impact on chromatin/gene expression, and cancer progression.

Excitingly, Bxb1 induced SVs were more stable in both mouse (mESCs) and human (K562s) cells, enabling us to quantify their impact on cellular fitness.

For instance, SVs that compromise centromere function and unbalanced translocations are strongly selected against.

We turned to Bxb1, a serine recombinase with lower toxicity and higher efficiency in mammalian cells.

Bxb1 recombination between directional attB and attP sites results in stable recombinants which ensured that all induced SVs were detectable in our assay.

Disappointingly, despite our best efforts, Cre-induced SVs at symmetric loxP sites were rapidly depleted from the mESC population.

This likely reflects the well-documented toxicity of Cre and/or the instability or detrimental effects of recombinants derived from symmetric sites.

We sequenced a PCR amplicon across the shuffle cassettes after treating cells with either Cre or the non-targeting Bxb1 recombinase.

Thousands of new barcode combinations reflecting induced SVs (deletions, inversions and translocations) are detected only in the Cre sample!

We mapped the allele-specific insertion sites of >5000 barcoded shuffle cassettes in hybrid mouse embryonic stem cells with base-pair resolution.

SVs can be inferred by comparing new barcode combinations against the list of parental barcode pairs without any WGS or cloning.

We developed 'shuffle cassettes' that enable:
1) SV generation through site-specific recombination

2) barcode association with genomic insertion sites in a pool;

3) Inference of SV identity from sequencing short PCR amplicons containing barcodes, either in bulk or single cells