Systems Biology

Single-Cell Network Analysis Identifies CLEC4E as a Key Mediator of Proinflammatory mDC Responses in Influenza Infection

1. Subin Cho
2. Gabriel Laghlali
3. Arturo Marin
4. Adolfo García-Sastre
5. Gagandeep Singh
6. Michael Schotsaert
7. Won-Min Song
8. Christian V. Forst

Reviewed by preLights

Regulation of Transcriptional Bursting and Spatial Patterning in Early Drosophila Embryo Development

1. César Nieto
2. Zahra Vahdat
3. Bomyi Lim
4. Abhyudai Singh

• Curated by eLife

  eLife Assessment

  This study presents a valuable quantitative framework for analyzing transcription dynamics data for enhancers and genes expressed in the early Drosophila embryo. By analyzing existing data across both synthetic reporters and an endogenous gene (eve), this work provides evidence that spatial gene expression patterns within the embryo are largely determined by "activity time" - the time during which a gene is bursting. The methods and evidence are solid and should be of broad interest to researchers in developmental biology and quantitative gene regulation, but the study would be significantly enhanced by clarifying the novelty of the findings relative to prior work and presenting a rigorous benchmarking of their algorithm against previously used algorithms.

Reviewed by eLife

Multi-omics analysis of endothelial cells reveals the metabolic diversity that underlies endothelial cell functions

1. Stephan Durot
2. Peter F. Doubleday
3. Lydia Schulla
4. Amélie Sabine
5. Tatiana V. Petrova
6. Nicola Zamboni

Reviewed by Review Commons

Raman spectra identify vancomycin-resistant phenotypes and their transcriptomic features in Staphylococcus aureus

1. Ken-ichiro F. Kamei
2. Reiko Okura
3. Koseki J. Kobayashi-Kirschvink
4. Yuki Katayama
5. Yuichi Wakamoto

Reviewed by Arcadia Science

Exploiting fluctuations in gene expression to detect causal interactions between genes

1. Euan Joly-Smith
2. Mir Mikdad Talpur
3. Paige Allard
4. Fotini Papazotos
5. Laurent Potvin-Trottier
6. Andreas Hilfinger

• Curated by eLife

  eLife Assessment

  By taking advantage of noise in gene expression, this important study introduces a new approach for detecting directed causal interactions between two genes without perturbing either. The main theoretical result is supported by a proof. Preliminary simulations and experiments on small circuits are solid, but further investigations are needed to demonstrate the broad applicability and scalability of the method.

Reviewed by eLife

A push-pull system of repressors matches levels of glucose transporters to extracellular glucose in budding yeast

1. Luis Fernando Montaño-Gutierrez
2. Marc Sturrock
3. Iseabail Farquhar
4. Kevin Correia
5. Vahid Shahrezaei
6. Peter S. Swain

Reviewed by Review Commons

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