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Identifying Improved Sites for Heterologous Gene Integration Using ATAC-seq.
Joseph R Brady1,2, Melody C Tan1, Charles A Whittaker1
1Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.
ACS Synthetic Biology
|August 14, 2020
Summary
Researchers developed a data-guided framework using ATAC-seq to find optimal genomic sites for integrating heterologous genes in yeast. This method identifies intergenic regions with low- to moderate-accessibility peaks for improved gene expression.
Area of Science:
- Synthetic Biology
- Molecular Biology
- Genomics
Background:
- Efficient cellular factories require heterologous pathways for novel compound synthesis and enhanced productivity.
- Limited genomic sites are available for efficient heterologous gene integration and expression, particularly in nonmodel organisms.
Purpose of the Study:
- To develop a data-guided framework for identifying suitable genomic integration sites in the nonmodel yeast *Komagataella phaffii*.
- To evaluate the impact of intergenic region (IGR) characteristics on heterologous gene expression using ATAC-seq data.
Main Methods:
- Developed a framework utilizing ATAC-seq data to guide the selection of integration sites.
- Employed CRISPR/Cas9 for single-copy integration of GFP constructs into 38 intergenic regions (IGRs) in *K. phaffii*.
- Assessed the influence of IGR size, ATAC-seq peak intensity, and adjacent gene orientation/expression on transgene expression.
Main Results:
- ATAC-seq peak intensity significantly affected heterologous gene expression; low- to moderate-intensity peaks yielded higher expression than high-intensity peaks.
- The effect of peak intensity diminished in tandem, multicopy integrations, suggesting buffering by additional gene copies.
- IGR size and adjacent gene characteristics did not show significant effects on single-copy transgene expression.
Conclusions:
- The intensity of chromatin accessibility, as measured by ATAC-seq, is a key determinant for optimal heterologous gene expression in specific IGRs.
- The developed framework provides a basis for nominating suitable IGRs in eukaryotic hosts using annotated genomes and ATAC-seq data.
- This approach facilitates the construction of more efficient cellular factories by improving heterologous gene integration and expression strategies.
