Bioinformatic Prediction and High Throughput In Vivo Screening to Identify Cis-Regulatory Elements for the Development of Algal Synthetic Promoters

Torres-Tiji, Y.; Sethuram, H.; Gupta, A.; McCauley, J.; Dutra-Molino, J. -V.; Pathania, R.; Saxton, L.; Kang, K.; Hillson, N. J.; Mayfield, S. P.

doi:10.1021/acssynbio.4c00199

Title: Bioinformatic Prediction and High Throughput In Vivo Screening to Identify Cis-Regulatory Elements for the Development of Algal Synthetic Promoters

Journal Article · 10 July 2024 · ACS Synthetic Biology

DOI: https://doi.org/10.1021/acssynbio.4c00199 · OSTI ID:2396788

^[1]; Sethuram, H. ^[1]; Gupta, A. ^[1];

^[2]; Dutra-Molino, J. -V. ^[1]; Pathania, R. ^[1]; Saxton, L. ^[1]; Kang, K. ^[1];

^[2];

^[1]

University of California San Diego, La Jolla, CA (United States)
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); USDOE Agile BioFoundry, Emeryville, CA (United States)

Algae biotechnology holds immense promise for revolutionizing the bioeconomy through the sustainable and scalable production of various bioproducts. However, their development has been hindered by the lack of advanced genetic tools. This study introduces a synthetic biology approach to develop such tools, focusing on the construction and testing of synthetic promoters. By analyzing conserved DNA motifs within the promoter regions of highly expressed genes across six different algal species, we identified cis-regulatory elements (CREs) associated with high transcriptional activity. Combining the algorithms POWRS, STREME, and PhyloGibbs, we predicted 1511 CREs and inserted them into a minimal synthetic promoter sequence in 1, 2, or 3 copies, resulting in 4533 distinct synthetic promoters. These promoters were evaluated in vivo for their capacity to drive the expression of a transgene in a high-throughput manner through next-generation sequencing post antibiotic selection and fluorescence-activated cell sorting. To validate our approach, we sequenced hundreds of transgenic lines showing high levels of GFP expression. Further, we individually tested 14 identified promoters, revealing substantial increases in GFP expression up to nine times higher than the baseline synthetic promoter, with five matching or even surpassing the performance of the native AR1 promoter. As a result of this study, we identified a catalog of CREs that can now be used to build superior synthetic algal promoters. More importantly, here we present a validated pipeline to generate building blocks for innovative synthetic genetic tools applicable to any algal species with a sequenced genome and transcriptome data set.

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Research Organization:: University of California San Diego, La Jolla, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Bioenergy Technologies Office (BETO); UCSD School of Medicine Microscopy Core; USDOE

Grant/Contract Number:: EE0009671; AC02-05CH11231; P30 NS047101; S10 OD030505

OSTI ID:: 2396788

Alternate ID(s):: OSTI ID: 2405048

Journal Information:: ACS Synthetic Biology, Vol. 13, Issue 7; ISSN 2161-5063

Publisher:: American Chemical Society (ACS)Copyright Statement

Country of Publication:: United States

Language:: English

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Related Subjects

59 BASIC BIOLOGICAL SCIENCES
synthetic biology
genetic engineering
algae
bioinformatics
cis-regulatory elements
promoters
algorithms
elements
genetics
imaging probes
mathematical models

Title: Bioinformatic Prediction and High Throughput In Vivo Screening to Identify Cis-Regulatory Elements for the Development of Algal Synthetic Promoters

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