Systems Biology

A Cross-Species Generative Cell Atlas Across 1.5 Billion Years of Evolution: The TranscriptFormer Single-cell Model

1. James D Pearce
2. Sara E Simmonds
3. Gita Mahmoudabadi
4. Lakshmi Krishnan
5. Giovanni Palla
6. Ana-Maria Istrate
7. Alexander Tarashansky
8. Benjamin Nelson
9. Omar Valenzuela
10. Donghui Li
11. Stephen R. Quake
12. Theofanis Karaletsos

Reviewed by Arcadia Science

Amino acid repeat signatures underlying human-pathogen interactions

1. Anjali Kumari Singh
2. Nagashree Rachote
3. Anushka Agrawal
4. Vaidehi Sharma
5. Keertana Sai Kappagantula
6. Rajashekar Varma Kadumuri
7. Sreenivas Chavali

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

Perturbation-response analysis of in silico metabolic dynamics revealed hard-coded responsiveness in the cofactors and network sparsity

1. Yusuke Himeoka
2. Chikara Furusawa

• Curated by eLife

  eLife Assessment

  This valuable study uses dynamic metabolic models to compare perturbation responses in a bacterial system, analyzing whether they return to their steady state or amplify beyond the initial perturbation. The evidence supporting the emergent properties of perturbed metabolic systems to network topology and sensitivity to specific metabolites is solid.

Reviewed by eLife

Revealing global stoichiometry conservation architecture in cells from Raman spectral patterns

1. Ken-ichiro F Kamei
2. Koseki J Kobayashi-Kirschvink
3. Takashi Nozoe
4. Hidenori Nakaoka
5. Miki Umetani
6. Yuichi Wakamoto

• Curated by eLife

  eLife Assessment

  This paper reports the fundamental finding of how Raman spectral patterns correlate with proteome profiles. The authors then go further to show that this can be used to infer global stochiometric regulation of the proteomes. These findings are likely general and the authors provide compelling evidence by analyzing bacterial and human cells but there are some suggestions provided below to make the work clearer and more accessible for it to reach a broader audience.

Reviewed by eLife, Arcadia Science

Passive shaping of intra- and intercellular m6A dynamics via mRNA metabolism

1. David Dierks
2. Ran Shachar
3. Ronit Nir
4. Miguel Angel Garcia-Campos
5. Anna Uzonyi
6. David Wiener
7. Ursula Toth
8. Walter Rossmanith
9. Lior Lasman
10. Boris Slobodin
11. Jacob H Hanna
12. Yaron Antebi
13. Ruth Scherz-Shouval
14. Schraga Schwartz

• Curated by eLife

  eLife Assessment

  This study presents a fundamental finding on how levels of m6A levels are controlled, invoking a consolidated model where degradation of modified RNAs in the cytoplasm plays a primary role in shaping m6A patterns and dynamics, rather than needing active regulation by m6A erasers and other related processes. The evidence is compelling through its use of transcriptome-wide data and mechanistic modeling. Relevant for any reader with an interest in RNA metabolism, this new framework consolidates previous observations and highlights the importance of careful experimentation for evaluation m6A levels.

Reviewed by eLife

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

The Product neutrality function defining genetic interactions emerges from mechanistic models of cell growth

1. Lucas Fuentes Valenzuela
2. Paul Francois
3. Jan 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. The analysis is still incomplete, as some assumptions and hypotheses are not fully justified. However, once verified, the results have the potential to be of value to the field of gene epistasis.

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