Synthetic Biology

Life as a Function: Why Transformer Architectures Struggle to Gain Genome-Level Foundational Capabilities

1. Hassan Hassan
2. Kyle Puhger
3. Ali Saadat
4. Johannes Mayer
5. Maximilian Sprang

Reviewed by Arcadia Science

Machine learning-assisted enzyme engineering through ultra-high throughput sorting and large-scale sequence-function data generation

1. Jingyun Zhang
2. Sangeetha Shanmugam
3. Jing Wui Yeoh
4. Dan Zheng
5. Jan Ron Goh
6. Zhangyuan Lin
7. Chueh Loo Poh

Reviewed by Arcadia Science

Systematic comparison of Generative AI-Protein Models reveals fundamental differences between structural and sequence-based approaches.

1. Alexander J Barnett
2. Rajendra KC
3. Pratikshya Pandey
4. Pamodha Somasiri
5. Kirsten A Fairfax
6. Alex W Hewitt

Reviewed by Arcadia Science

High-resolution deep mutational scanning of the melanocortin-4 receptor enables target characterization for drug discovery

1. Conor J Howard
2. Nathan S Abell
3. Beatriz A Osuna
4. Eric M Jones
5. Leon Y Chan
6. Henry Chan
7. Dean R Artis
8. Jonathan B Asfaha
9. Joshua S Bloom
10. Aaron R Cooper
11. Andrew Liao
12. Eden Mahdavi
13. Nabil Mohammed
14. Alan L Su
15. Giselle A Uribe
16. Sriram Kosuri
17. Diane E Dickel
18. Nathan B Lubock

• Curated by eLife

  eLife Assessment

  The authors use deep mutational scanning to assess the effect of ~6,600 protein-coding variants in MC4R, a G protein coupled receptor associated with obesity. They develop new, more precise approaches to deep mutational scanning, enabling them to probe molecular phenotypes directly relevant to the development of drugs that target this receptor. In this important work, the authors provide compelling evidence that variants impact signaling through MC4R in different ways, that some defective variants are amenable to a corrector drug and that deep mutational scanning data could guide compound optimization.

Reviewed by eLife

Synthetic gene circuits that selectively target RAS-driven cancers

1. Gabriel Senn
2. Leon Nissen
3. Yaakov Benenson

• Curated by eLife

  eLife Assessment

  This important study demonstrates the potential of synthetic gene circuits to detect and target aberrant RAS activity in cancer cell lines. The circuit design is novel and the evidence supporting the claims is convincing. As a proof-of-concept, this will be of broad interest. Testing the system with other KRAS mutations and clinically relevant output proteins, as well as gaining a better understanding of the underlying molecular mechanism, will both strengthen the study and help translate the technology toward clinical applications in cancer therapeutics.

Reviewed by eLife

Cell-free protein synthesis as a method to rapidly screen machine learning-directed protease variants

1. Ella Lucille Thornton
2. Jeremy T. Boyle
3. Nadanai Laohakunakorn
4. Lynne Regan

Reviewed by Arcadia Science

A practical DNA data storage using an expanded alphabet introducing 5-methylcytosine

1. Deruilin Liu
2. Demin Xu
3. Liuxin Shi
4. Jiayuan Zhang
5. Kewei Bi
6. Bei Luo
7. Chen Liu
8. Yuxiang Li
9. Guangyi Fan
10. Wen Wang
11. Zhi Ping

• Curated by GigaByte

  Editors Assessment:

  DNA has huge potential as a data storage medium because of its incredibly high storage density and stability. This work addresses the potential of modified bases, specifically 5-methylcytosine (5mC), in enhancing DNA data storage systems. This paper introduces a transcoding scheme named R+, which incorporates this modified 5mC base to increase information density beyond the standard limits. By encoding various file types into DNA sequences of between 1.3 to 1.6 kb in size, this method achieves an average recovery rate of 98.97% (with reference), validating the effectiveness of the method. On top of a wet-lab protocol (hosted in protocols.io) for the experimental validation of the transcoding scheme, it also includes open source code for in-silico simulation tests. Peer review scruitinising the protocols and validation are reusable and provide convincing results. As nanopore sequencing has enabled reading of these modified bases, it is timely making them applicable as extra letters in the molecular alphabet for DNA data storage

  This evaluation refers to version 1 of the preprint

Reviewed by GigaByte

Effects of growth feedback on adaptive gene circuits: A dynamical understanding

1. Ling-Wei Kong
2. Wenjia Shi
3. Xiao-Jun Tian
4. Ying-Cheng Lai

• Curated by eLife

  eLife Assessment

  The paper presents valuable computational findings on how growth feedback affects the performance of synthetic gene circuits designed for adaptive responses. By systematically analyzing over four hundred circuit topologies, the authors provide solid evidence for their conclusions on failure mechanisms and design features that enhance robustness against growth dynamics. While the study's significance and rigor are somewhat constrained by its reliance on previously published network topologies, these results are highly relevant for advancing the engineering of gene circuits in various applications.

Reviewed by eLife

Spheroplasted cells: a game changer for DNA delivery to diatoms

1. E.J.L. Walker
2. M. Pampuch
3. G. Tran
4. B.J.K. Karas

Reviewed by Arcadia Science

Mapping targetable sites on the human surfaceome for the design of novel binders

1. Petra E. M. Balbi
2. Ahmed Sadek
3. Anthony Marchand
4. Ta-Yi Yu
5. Jovan Damjanovic
6. Sandrine Georgeon
7. Joseph Schmidt
8. Simone Fulle
9. Che Yang
10. Hamed Khakzad
11. Bruno E. Correia

Reviewed by Arcadia Science