Systems Biology

Learning sequence-function relationships with scalable, interpretable Gaussian processes

1. Juannan Zhou
2. Carlos Martí-Gómez
3. Samantha Petti
4. David M McCandlish

• Curated by eLife

  eLife Assessment

  This important work introduces a family of interpretable Gaussian process models that allows us to learn and model sequence-function relationships in biomolecules. These models are applied to three recent empirical fitness landscapes, providing convincing evidence of their predictive power. The findings should be of interest to the community working on the sequence-function relationship, on epistasis, and on fitness landscapes.

Reviewed by eLife

Knock-down of a regulatory barcode shifts macrophage polarization destination from M1 to M2 and increases pathogen burden upon S. aureus infection

1. Sathyabaarathi Ravichandran
2. Bharat Bhatt
3. Awantika Shah
4. Debajyoti Das
5. Kithiganahalli Narayanaswamy Balaji
6. Nagasuma Chandra

• Curated by eLife

  eLife Assessment

  The authors of this manuscript study the transcriptional regulators that allow macrophages to assume different functional phenotypes in response to immune stimuli. They generate a computational map of the gene regulatory networks involved in determining macrophage phenotypes and experimentally validate the role of putative regulatory factors in a myeloid cell line. This study represents a valuable approach to understanding how gene regulation impacts macrophage polarization and their conclusions are supported by solid computational and experimental evidence. The revision has clarified that the focus is the identification of the regulatory barcodes in a myeloid cell line. Future studies in primary cells and in vivo will be required to assess the roles of these regulators in a broader context.

Reviewed by eLife

Longitudinal single cell RNA-sequencing reveals evolution of micro- and macro-states in chronic myeloid leukemia

1. David E. Frankhouser
2. Dandan Zhao
3. Yu-Hsuan Fu
4. Anupam Dey
5. Ziang Chen
6. Jihyun Irizarry
7. Jennifer Rangel Ambriz
8. Tiffany Kanesa Ybarra
9. Sergio Branciamore
10. Denis O’Meally
11. Ryan S. Sathianathen
12. Jeffery M. Trent
13. Stephen Forman
14. Adam L. MacLean
15. Ya-Huei Kuo
16. Kathleen M. Sakamoto
17. Bin Zhang
18. Russell C. Rockne
19. Guido Marcucci

Reviewed by preLights

Ubiquitous systems drift in the evolution of development

1. P.L. van der Jagt
2. S. Oud
3. R.M.A. Vroomans

Reviewed by Review Commons

Unveiling Gene Perturbation Effects through Gene Regulatory Networks Inference from single-cell transcriptomic data

1. Clelia Corridori
2. Merrit Romeike
3. Giorgio Nicoletti
4. Christa Buecker
5. Samir Suweis
6. Sandro Azaele
7. Graziano Martello

Reviewed by Review Commons

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