Systems Biology

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

Regulation of replication timing in Saccharomyces cerevisiae

1. Rosie Berners-Lee
2. Eamonn Gilmore
3. Francisco Berkemeier
4. Michael A. Boemo

Reviewed by Review Commons

Transplantation of exogenous mitochondria mitigates myocardial dysfunction after cardiac arrest

1. Zhen Wang
2. Jie Zhu
3. Mengda Xu
4. Xuyuan Ma
5. Maozheng Shen
6. Jingyu Yan
7. Guosheng Gan
8. Xiang Zhou

• Curated by eLife

  eLife Assessment

  In this valuable report, the authors investigated the effect of mitochondrial transplantation on post-cardiac arrest myocardial dysfunction (PAMD), which is associated with mitochondrial dysfunction. They convincingly demonstrated that mitochondrial transplantation enhanced cardiac function and increased survival rates after the return of spontaneous circulation (ROSC). They have also shown that myocardial tissues with transplanted mitochondria exhibited increased mitochondrial complex activity, higher ATP levels, reduced cardiomyocyte apoptosis, and lower myocardial oxidative stress post-ROSC.

Reviewed by eLife

Systems genomics of salinity stress response in rice

1. Sonal Gupta
2. Simon Niels Groen
3. Maricris L Zaidem
4. Andres Godwin C Sajise
5. Irina Calic
6. Mignon Natividad
7. Kenneth McNally
8. Georgina V Vergara
9. Rahul Satija
10. Steven J Franks
11. Rakesh K Singh
12. Zoé Joly-Lopez
13. Michael D Purugganan

• Curated by eLife

  eLife Assessment

  Working with a diverse panel of rice accessions grown in field conditions, this valuable study measures changes in transcript abundance, tests for patterns of selection on gene expression, and maps the genetic basic of variation in gene expression in normal and elevated salinity treatments. The manuscript provides solid evidence that mean gene expression levels are further from the optimum abundance for more genes under the elevated salinity treatment compared to normal treatment, and that a relatively small number of genes are hotspots that harbor genetic variants which affect broader genome-wide patterns of natural variation in gene expression under high salinity conditions. However, the design, clarity, and interpretation of several statistical analyses can be improved, some opportunities for integration among datasets and analyses could yet be realized, and genetic manipulation is required to confirm functional involvement of any specific genes in regulatory networks or organismal traits that confer adaptation to higher salinity conditions. The manuscript will be of interest to evolutionary biologists studying the genetics of complex traits and a resource for plant biologists studying mechanisms of abiotic stress tolerance.

Reviewed by eLife

Hormone circuit explains why most HPA drugs fail for mood disorders and predicts the few that work

1. Tomer Milo
2. Shiraz Nir Halber
3. Moriya Raz
4. Dor Danan
5. Avi Mayo
6. Uri Alon

Reviewed by Review Commons

Emergence of alternative stable states in microbial communities undergoing horizontal gene transfer

1. Juken Hong
2. Wenzhi Xue
3. Teng Wang

• Curated by eLife

  eLife Assessment

  This manuscript offers valuable theoretical predictions on how horizontal gene transfer (HGT) can lead to alternative stable states in microbial communities. Using a modeling framework, solid theoretical evidence is provided to support the claimed role of HGT. However, given that the model has many degrees of freedom, a more comprehensive analysis of the role of different parameters could strengthen the study. Additionally, potential interactions between plasmids that carry out HGT are not discussed in the model. This paper would be of interest to researchers in microbiology, ecology, and evolutionary biology.

Reviewed by eLife

A statistical framework for quantifying the nuclear export rate of influenza viral mRNAs

1. Michi Miura
2. Naho Kiuchi
3. Siu-Ying Lau
4. Bobo Wing-Yee Mok
5. Hiroshi Ushirogawa
6. Tadasuke Naito
7. Honglin Chen
8. Mineki Saito

• Curated by eLife

  eLife Assessment

  This important study combines virology experiments and mathematical modeling to determine the nuclear export rate of each of the eight RNA segments of the influenza A virus, leading to the proposal that a specific retention of mRNA within the nucleus delays the expression of antigenic viral proteins. The proposed model for explaining the differential rate of export is compelling, going beyond the state of the art, but the experimental setup is only in partial support and further studies will be needed to confirm the proposed mechanism.

Reviewed by eLife

Dynamic multi-omics and mechanistic modeling approach uncovers novel mechanisms of kidney fibrosis progression

1. Nadine Tuechler
2. Mira Lea Burtscher
3. Martin Garrido-Rodriguez
4. Muzamil Majid Khan
5. Denes Turei
6. Christian Tischer
7. Sarah Kaspar
8. Jennifer Jasmin Schwarz
9. Frank Stein
10. Mandy Rettel
11. Rafael Kramann
12. Mikhail M Savitski
13. Julio Saez-Rodriguez
14. Rainer Pepperkok

Reviewed by Review Commons

Evaluating Study Design Rigor in Preclinical Cardiovascular Research: A Replication Study

1. Isaiah C Jimenez
2. Gabrielle C Montenegro
3. Keyana Zahiri
4. Damini Patel
5. Adrienne Mueller

• Curated by eLife

  eLife Assessment

  The objective of this important study is to assess the study design and rigor, enhance the quality of clinical research studies, and emphasize crucial design elements in basic science research. It specifically tackles the ongoing problem of experimental design deficiencies that obstruct the effective translation of research findings into clinical applications. This paper is particularly convincing as it highlights the lack of progress in addressing these issues over the past decade, despite a substantial body of existing research. It serves as a strong call to action for the broader scientific community to improve research practices.

Reviewed by eLife

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

  The paper introduces DeepTX, a valuable deep-learning framework linking stochastic, mechanistic modelling with single-cell RNA sequencing data to investigate transcriptional burst kinetics on a genome-wide scale. This tool has been employed by the authors to evaluate transcriptional changes under DNA-damaging treatments, with observations that are of value to the systems biology and bioinformatics communities. The evidence supporting these findings is solid, though some concerns remain regarding specific technical details. This methodological advancement holds potential for application in diverse contexts, such as linking mechanistic models of signalling pathways to transcriptional data.

Reviewed by eLife