Systems Biology

CausalXtract, a flexible pipeline to extract causal effects from live-cell time-lapse imaging data

1. Franck Simon
2. Maria Colomba Comes
3. Tiziana Tocci
4. Louise Dupuis
5. Vincent Cabeli
6. Nikita Lagrange
7. Arianna Mencattini
8. Maria Carla Parrini
9. Eugenio Martinelli
10. Herve Isambert

• Curated by eLife

  eLife Assessment

  This important study represents a data processing pipeline to discover causal interactions from time-lapse imaging data, and convincingly illustrates it on a challenging application for the analysis of tumor-on-chip ecosystem data. The authors describe the raw data they used (imaging data), go through a step-by-step description on how to extract the features they are interested in from the raw data, and how to perform the causal discovery process. This paper tackles the problem of learning causal interactions from temporal data, which is applicable to many biological applications.

Reviewed by eLife

Exploration of the metabolomic mechanisms of postmenopausal hypertension induced by low estrogen state

1. Yao Li
2. Hui Xin
3. Zhexun Lian
4. Wei Zhang

• Curated by eLife

  eLife Assessment

  This useful study provides incomplete evidence regarding the pathophysiological role of low estrogen levels post-menopause in hypertension, focusing on L-AABA as a key mediator. The results describe a novel hypothesis for the pathophysiology of hypertension in this population and are of interest to experts in hypertension and vascular biology.

Reviewed by eLife

Emergence of power law distributions in protein-protein interaction networks through study bias

1. David B Blumenthal
2. Marta Lucchetta
3. Linda Kleist
4. Sándor P Fekete
5. Markus List
6. Martin H Schaefer

• Curated by eLife

  eLife Assessment

  This manuscript makes an important contribution to the understanding of protein-protein interaction (PPI) networks by challenging the widely held assumption that their degree distributions uniformly follow a power law. The authors present convincing evidence that biases in study design, such as data aggregation and selective research focus, may contribute to the appearance of power-law-like distributions. While the power law assumption has already been questioned in network biology, the methodological rigor and correction procedures introduced here are valuable for advancing our understanding of PPI network structure.

Reviewed by eLife

Abundant clock proteins point to missing molecular regulation in the plant circadian clock

1. Uriel Urquiza-García
2. Nacho Molina
3. Karen J Halliday
4. Andrew J Millar

Reviewed by Review Commons

Mitochondrial respiration atlas reveals differential changes in mitochondrial function across sex and age

1. Dylan C Sarver
2. Muzna Saqib
3. Fangluo Chen
4. G William Wong

• Curated by eLife

  eLife Assessment

  This important study provides a comprehensive assessment of mitochondrial function across age and sex in mice. The strength of evidence supporting this resource is compelling, given the exhaustive number of tissues profiled and in-depth analyses performed.

Reviewed by eLife

DNA O-MAP uncovers the molecular neighborhoods associated with specific genomic loci

1. Yuzhen Liu
2. Christopher D McGann
3. Mary Krebs
4. Thomas A Perkins
5. Rose Fields
6. Conor K Camplisson
7. David Z Nwizugbo
8. Chris Hsu
9. Shayan C Avanessian
10. Ashley F Tsue
11. Evan E Kania
12. David M Shechner
13. Brian J Beliveau
14. Devin K Schweppe

• Curated by eLife

  eLife Assessment

  This study presents a valuable new method for probing the DNA and proteins associated with targeted genomic elements in cells. The authors present solid evidence that the method can map DNA-DNA interactions for individual loci and can detect enriched proteins at repetitive DNA loci such as telomeres, but benchmarks of the method's resolution and specificity remain incomplete. The methodological details of this study will be of particular interest and utility to chromatin biologists.

Reviewed by eLife

PhysiMeSS - a new physiCell addon for extracellular matrix modelling

1. Vincent Noël
2. Marco Ruscone
3. Robyn Shuttleworth
4. Cicely K. Macnamara

• Curated by GigaByte

  Editors Assessment:

  PhysiCell is an open source multicellular systems simulator for studying many interacting cells in dynamic tissue microenvironments. As part of the PhysiCell ecosystem of tools and modules this paper presents a PhysiCell addon, PhysiMeSS (MicroEnvironment Structures Simulation) which allows the user to accurately represent the extracellular matrix (ECM) as a network of fibres. This can specify rod-shaped microenvironment elements such as the matrix fibres (e.g. collagen) of the ECM, allowing the PhysiCell user the ability to investigate physical interactions with cells and other fibres. Reviewers asked for additional clarification on a number of features. And the paper now clear future releases will provide full 3D compatibility and include working on fibrogenesis, i.e. the creation of new ECM fibres by cells.

  This evaluation refers to version 1 of the preprint

Reviewed by GigaByte

Isobaric crosslinking mass spectrometry technology for studying conformational and structural changes in proteins and complexes

1. Jie Luo
2. Jeff Ranish

• Curated by eLife

  eLife Assessment

  This manuscript presents a valuable new quantitative crosslinking mass spectrometry approach using novel isobaric crosslinkers. The data are solid and the method has potential for a broad application in structural biology if more isobaric crosslinking channels are available and the quantitative information of the approach is exploited in more depth.

Reviewed by eLife

Diversity in Notch ligand-receptor signaling interactions

1. Rachael Kuintzle
2. Leah A Santat
3. Michael B Elowitz

• Curated by eLife

  eLife Assessment

  This valuable study significantly enhances our understanding of how various ligands and receptors interact within the Notch signaling pathway. By developing novel cell-based assay systems, the authors systematically analyzed the effects of different ligand-receptor combinations on pathway activation. The convincing data reveal intriguing and unexpected differences and provide a foundation for interpreting Notch signalling in both normal and disease-related contexts.

Reviewed by eLife

Ribosome demand links transcriptional bursts to protein expression noise

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

• Curated by eLife

  eLife Assessment

  This interesting study focuses on a previously reported positive correlation between translational efficiency and protein noise. This is unexpected as typically noise is inversely related to expression and increasing translation efficiency would increase the protein expression and thus be expected to reduce noise in gene expression. Using mathematical modeling and analysis of experimental data the authors argue that this phenomenon arises due to ribosomal demand. However, the work appears incomplete, with the reviewers having raised questions regarding the validity of the assumptions used in the mathematical model as well as the clarity of the presentation.

Reviewed by eLife