ActinoMation: a literate programming approach for medium-throughput robotic conjugation of Streptomyces spp. DOI Creative Commons

Tenna Alexiadis Møller,

Thomas Booth, Simon J. Shaw

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Дек. 9, 2024

Abstract The genus Streptomyces are valuable producers of antibiotics and other pharmaceutically important bioactive compounds. Advances in molecular engineering tools, such as CRISPR, has provided some access to the metabolic potential , but efficient genetic strains is hindered by laborious slow manual transformation protocols. In this paper, we present a semi-automated medium-throughput workflow for introduction recombinant DNA into spp. using affordable open-sourced Opentrons (OT-2) robotics platform. To increase accessibility provide an open-source protocol-creator, ActinoMation. ActinoMation literate programming environment Python Jupyter Notebook. We validated method transforming coelicolor (M1152 M1146), S. albidoflavus (J1047), venezuelae (DSM40230) with plasmids pSETGUS pIJ12551. demonstrate conjugation efficiencies 3.33*10 −3 M1152 pIJ12551; 2.96*10 M1146 1.21*10 −5 J1047 4.70*10 −4 pIJ12551, 4.97*10 −2 DSM40230 6.13*10 pIJ12551 false positive rate between 8.33% 54.54%. Automation improves consistency when handling large sample sizes that facilitates easy reproducibility on larger scale.

Язык: Английский

A guide for active learning in synergistic drug discovery DOI Creative Commons
Shuhui Wang,

Alexandre Allauzen,

Philippe Nghe

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 28, 2025

Synergistic drug combination screening is a promising strategy in discovery, but it involves navigating costly and complex search space. While AI, particularly deep learning, has advanced synergy predictions, its effectiveness limited by the low occurrence of synergistic pairs. Active which integrates experimental testing into learning process, been proposed to address this challenge. In work, we explore key components active provide recommendations for implementation. We find that molecular encoding impact on performance, while cellular environment features significantly enhance predictions. Additionally, can discover 60% pairs with only exploring 10% combinatorial The yield ratio observed be even higher smaller batch sizes, where dynamic tuning exploration-exploitation further performance. code found at https://github.com/LBiophyEvo/DrugSynergy.

Язык: Английский

Процитировано

1
ActinoMation: a literate programming approach for medium-throughput robotic conjugation of Streptomyces spp. DOI Creative Commons

Tenna Alexiadis Møller,

Thomas Booth, Simon J. Shaw

и другие.

Synthetic and Systems Biotechnology, Год журнала: 2025, Номер 10(2), С. 667 - 676

Опубликована: Март 11, 2025

The genus Streptomyces are valuable producers of antibiotics and other pharmaceutically important bioactive compounds. Advances in molecular engineering tools, such as CRISPR, have provided some access to the metabolic potential Streptomyces, but efficient genetic strains is hindered by laborious slow manual transformation protocols. In this paper, we present a semi-automated medium-throughput workflow for introduction recombinant DNA into spp. using affordable open-sourced Opentrons (OT-2) robotics platform. To increase accessibility provide an open-source protocol-creator, ActinoMation. ActinoMation literate programming environment Python Jupyter Notebook. We validated method transforming coelicolor (M1152 M1146), S. albidoflavus (J1047), venezuelae (DSM40230) with plasmids pSETGUS pIJ12551. demonstrate conjugation efficiencies 3.33∗10-3/0.33 % M1152 pIJ12551; 2.96∗10-3/0.29 M1146 1.21∗10-5/0.0012 J1047 4.70∗10-4/0.047 pIJ12551, 4.97∗10-2/4.97 DSM40230 6.13∗10-2/6.13 pIJ12551 false positive rate between 8.33 54.54 %. Automation facilitates streamlined on larger scale without any evident loss efficiency.

Язык: Английский

Процитировано

0
The knowledge driven DBTL cycle provides mechanistic insights while optimising dopamine production in Escherichia coli DOI Creative Commons
Lorena Hägele,

Natalia Trachtmann,

Ralf Takors

и другие.

Microbial Cell Factories, Год журнала: 2025, Номер 24(1)

Опубликована: Май 16, 2025

Dopamine is a promising organic compound with several key applications in emergency medicine, diagnosis and treatment of cancer, production lithium anodes, wastewater treatment. Since studies on vivo dopamine are limited, this study demonstrates the development optimisation strain by help knowledge driven design-build-test-learn (DBTL) cycle for rational engineering. The DBTL cycle, involving upstream vitro investigation, an automated workflow that enables both mechanistic understanding efficient cycling. Following cell lysate studies, results were translated to environment through high-throughput ribosome binding site (RBS) As result, we developed capable producing at concentrations 69.03 ± 1.2 mg/L which equals 34.34 0.59 mg/gbiomass. Compared state-of-the-art production, our approach improved performance 2.6 6.6-fold, respectively. In essence, highly was implementing investigation. fine-tuning pathway RBS engineering clearly demonstrated impact GC content Shine-Dalgarno sequence strength.

Язык: Английский

Процитировано

0
Debottlenecking cytochrome P450-dependent metabolic pathways for the biosynthesis of commercial natural products DOI
Susanne M. Germann, M Holtz, Michael K. Jensen

и другие.

Natural Product Reports, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

Covering: 2016 to the end of 2024This highlight article aims provide a perspective on challenges that novel biotechnological processes face in biomanufacturing natural products (NPs) whose biosynthesis pathways rely cytochrome P450 monooxygenases. This enzyme superfamily is one most versatile plethora NPs finding use across food, nutrition, medicine, chemical and cosmetics industries. These enzymes often exhibit excellent regio- stereoselectivity, but they can suffer from low activity instability, which are serious issues impairing development high performing bioprocesses. We start with brief introduction industrial biotechnology importance looking for alternative means producing independently unsustainable fossil fuels or plant extractions. then discuss implemented solutions during commercial NP focusing P450-dependent steps primarily yeast cell factories. Our main focus encountered when utilizing pathways, how protein engineering be used debottlenecking them. Finally, we briefly touch upon artificial intelligence machine learning guiding efforts.

Язык: Английский

Процитировано

0
ActinoMation: a literate programming approach for medium-throughput robotic conjugation of Streptomyces spp. DOI Creative Commons

Tenna Alexiadis Møller,

Thomas Booth, Simon J. Shaw

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Дек. 9, 2024

Abstract The genus Streptomyces are valuable producers of antibiotics and other pharmaceutically important bioactive compounds. Advances in molecular engineering tools, such as CRISPR, has provided some access to the metabolic potential , but efficient genetic strains is hindered by laborious slow manual transformation protocols. In this paper, we present a semi-automated medium-throughput workflow for introduction recombinant DNA into spp. using affordable open-sourced Opentrons (OT-2) robotics platform. To increase accessibility provide an open-source protocol-creator, ActinoMation. ActinoMation literate programming environment Python Jupyter Notebook. We validated method transforming coelicolor (M1152 M1146), S. albidoflavus (J1047), venezuelae (DSM40230) with plasmids pSETGUS pIJ12551. demonstrate conjugation efficiencies 3.33*10 −3 M1152 pIJ12551; 2.96*10 M1146 1.21*10 −5 J1047 4.70*10 −4 pIJ12551, 4.97*10 −2 DSM40230 6.13*10 pIJ12551 false positive rate between 8.33% 54.54%. Automation improves consistency when handling large sample sizes that facilitates easy reproducibility on larger scale.

Язык: Английский

Процитировано

0