Systems Biology

TrueProbes: Quantitative Single-Molecule RNA-FISH Probe Design Improves RNA Detection

1. Jason J Hughes
2. Benjamin K Kesler
3. John E Adams
4. Blythe G Hospelhorn
5. Gregor Neuert

• Curated by eLife

  eLife Assessment

  This useful study introduces a computational pipeline for designing RNA in situ fluorescence hybridization probes that could improve the sensitivity and specificity of RNA detection in cells. While the approach is novel and the preliminary data suggestive, the evidence supporting a clear advantage over existing probe design strategies is incomplete. The work will be of interest to researchers developing or using molecular tools for imaging RNA in cells.

Reviewed by eLife

Stool Dynamics and the Developing Gut Microbiome During Infancy

1. Mohammed Al-Andoli
2. Sarah Schoch
3. Andjela Markovic
4. Christophe Mühlematter
5. Matthieu Beaugrand
6. Oskar G. Jenni
7. Rabia Liamlahi
8. Jean-Claude Walser
9. Dennis Nielsen
10. Salome Kurth

Reviewed by Arcadia Science

Non-equilibrium strategies enabling ligand specificity by signaling receptors

1. Andrew Goetz
2. Jeremy Barrios
3. Ralitsa Radostinova Madsen
4. Purushottam D Dixit

• Curated by eLife

  eLife Assessment

  This study presents a valuable finding about how receptor-ligand binding pathways with multi-site phosphorylation can show non-monotonic responses to increasing ligand affinity and to kinase activity. The authors provide compelling evidence through a simple ordinary differential equation model of such signaling networks with the key new ingredient of ligand-induced receptor degradation. The work will be of interest to physicists and biologists working on signal transduction and biological information processing.

Reviewed by eLife

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

Deep learning linking mechanistic models to single-cell transcriptomics data reveals transcriptional bursting in response to DNA damage

1. Zhiwei Huang
2. Songhao Luo
3. Zihao Wang
4. Zhenquan Zhang
5. Benyuan Jiang
6. Qing Nie
7. Jiajun Zhang

• Curated by eLife

  eLife Assessment

  This study presents DeepTX, a valuable methodological tool that integrates mechanistic stochastic models with single-cell RNA sequencing data to infer transcriptional burst kinetics at genome scale. The approach is broadly applicable and of interest to subfields such as systems biology, bioinformatics, and gene regulation. The evidence supporting the findings is solid, with appropriate validation on synthetic data and thoughtful discussion of limitations related to identifiability and model assumptions.

Reviewed by eLife

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