Systems Biology

Ribosome demand links transcriptional bursts to protein expression noise

1. Sampriti Pal
2. Upasana Ray
3. Riddhiman Dhar

• Curated by eLife

  eLife Assessment

  This study focuses on a previously reported positive correlation between translational efficiency and protein noise. Using mathematical modeling and analysis of experimental data the authors reach the valuable conclusion that this phenomenon arises due to ribosomal demand. While some aspects of the work appear to be incomplete, the results have the potential to be of value and interest to the field of gene expression.

Reviewed by eLife

The Product neutrality function defining genetic interactions emerges from mechanistic models of cell growth

1. Lucas Fuentes Valenzuela
2. Paul Francois
3. Jan M Skotheim

• Curated by eLife

  eLife Assessment

  The paper addresses the question of gene epistasis and asks what is the correct null model for which we should declare no epistasis. By reanalyzing synthetic gene array datasets regarding single and double-knockout yeast mutants, and considering two theoretical models of cell growth, the authors reach the valuable conclusion that the product function is a good null model. While the justification of some assumptions is incomplete, the results have the potential to be of value to the field of gene epistasis.

Reviewed by eLife

Designing biochemical circuits with tree search

1. Pranav S Bhamidipati
2. Matthew Thomson

• Curated by eLife

  eLife Assessment

  This manuscript presents a valuable computational tool for identifying 3-5 gene regulatory network topologies capable of generating oscillatory dynamics. The application of Monte Carlo Tree Search to circuit design is novel and effectively expands the scale at which non-linear behaviours can be explored in silico. The efficiency of the proposed algorithm is convincing, and the work will be of interest to the systems and synthetic biology communities. While the evolutionary implications remain unclear, the methodological contribution represents a significant advance in the field.

Reviewed by eLife

A mathematical model for ketosis-prone diabetes suggests the existence of multiple pancreatic β-cell inactivation mechanisms

1. Sean A Ridout
2. Priyathama Vellanki
3. Ilya Nemenman

• Curated by eLife

  eLife Assessment

  This theoretical study makes a useful contribution to our understanding of a subtype of type 2 diabetes - ketosis-prone diabetes mellitus (KPD) - with a potential impact on our broader understanding of diabetes and glucose regulation. The article presents an ordinary differential equation-based model for KPD that incorporates a number of distinct timescales - fast, slow, as well as intermediate, incorporating a key hypothesis of reversible beta cell deactivation. The presented evidence is solid and shows that observed clinical disease trajectories may be explained by a simple mathematical model in a particular parameter regime.

Reviewed by eLife

Dynamic sensitivity analysis of a mathematical model describing the effect of the macroalgae Asparagopsis taxiformis on rumen fermentation and methane production under in vitro continuous conditions

1. Paul Blondiaux
2. Tristan Senga Kiessé
3. Maguy Eugène
4. Rafael Muñoz-Tamayo

Reviewed by Peer Community in Animal Science

A Cross-Species Generative Cell Atlas Across 1.5 Billion Years of Evolution: The TranscriptFormer Single-cell Model

1. James D Pearce
2. Sara E Simmonds
3. Gita Mahmoudabadi
4. Lakshmi Krishnan
5. Giovanni Palla
6. Ana-Maria Istrate
7. Alexander Tarashansky
8. Benjamin Nelson
9. Omar Valenzuela
10. Donghui Li
11. Stephen R Quake
12. Theofanis Karaletsos

Reviewed by Arcadia Science

Amino acid repeat signatures underlying human-pathogen interactions

1. Anjali Kumari Singh
2. Nagashree Rachote
3. Anushka Agrawal
4. Vaidehi Sharma
5. Keertana Sai Kappagantula
6. Rajashekar Varma Kadumuri
7. Sreenivas Chavali

Reviewed by Arcadia Science

Perturbation-response analysis of in silico metabolic dynamics revealed hard-coded responsiveness in the cofactors and network sparsity

1. Yusuke Himeoka
2. Chikara Furusawa

• Curated by eLife

  eLife Assessment

  This valuable study uses dynamic metabolic models to compare perturbation responses in a bacterial system, analyzing whether they return to their steady state or amplify beyond the initial perturbation. The evidence supporting the emergent properties of perturbed metabolic systems to network topology and sensitivity to specific metabolites is solid.

Reviewed by eLife

Passive shaping of intra- and intercellular m6A dynamics via mRNA metabolism

1. David Dierks
2. Ran Shachar
3. Ronit Nir
4. Miguel Angel Garcia-Campos
5. Anna Uzonyi
6. David Wiener
7. Ursula Toth
8. Walter Rossmanith
9. Lior Lasman
10. Boris Slobodin
11. Jacob H Hanna
12. Yaron Antebi
13. Ruth Scherz-Shouval
14. Schraga Schwartz

• Curated by eLife

  eLife Assessment

  This study presents a fundamental finding on how levels of m6A levels are controlled, invoking a consolidated model where degradation of modified RNAs in the cytoplasm plays a primary role in shaping m6A patterns and dynamics, rather than needing active regulation by m6A erasers and other related processes. The evidence is compelling through its use of transcriptome-wide data and mechanistic modeling. Relevant for any reader with an interest in RNA metabolism, this new framework consolidates previous observations and highlights the importance of careful experimentation for evaluation m6A levels.

Reviewed by eLife

An Hfq-dependent post-transcriptional mechanism fine tunes RecB expression in Escherichia coli

1. Irina Kalita
2. Ira Alexandra Iosub
3. Lorna McLaren
4. Louise Goossens
5. Sander Granneman
6. Meriem El Karoui

• Curated by eLife

  eLife Assessment

  Combining experimental and computation approaches, this manuscript provides convincing evidence for a post-transcriptional mechanism that provides robust control over the protein expression level of RecB in E. coli. In addition to uncovering how DNA damage drives higher levels of RecB protein, this work also reveals important tenets for how broader mechanisms that suppress noise and underlie responsive tuning of protein levels can be achieved.

Reviewed by eLife