Systems Biology

Mycobacterial Metabolic Model Development for Drug Target Identification

1. Bridget P. Bannerman
2. Alex Oarga
3. Jorge Júlvez

• Curated by GigaByte

  Editor’s Assessment

  This work has generated metabolic models for the human pathogens Mycobacterium leprae and Mycobacteroides abscessus, alongside a new computational tool that can be used to identify potential drug targets. The standardised genomic scale metabolic models have been developed using the systems biology community standards for quality control and evaluation of models. After providing more detail on reproducibility, comparative performance of the models, and reuse, these resources are now published and are available for reuse by the global scientific community via the GigaDB, Biomodels, and PatMeDB repositories.

  This assessment refers to version 1 of this preprint.

Reviewed by GigaByte

A Multiscale Protein Abundance Structured Population Kinetic Model Systematically Explores the Design Space of Constitutive and Inducible CAR-T cells

1. Harshana Rajakaruna
2. Milie Desai
3. Jayajit Das

Reviewed by Review Commons

Predictive nonlinear modeling of malignant myelopoiesis and tyrosine kinase inhibitor therapy

1. Jonathan Rodriguez
2. Abdon Iniguez
3. Nilamani Jena
4. Prasanthi Tata
5. Zhong-Ying Liu
6. Arthur D Lander
7. John Lowengrub
8. Richard A Van Etten

• Curated by eLife

  eLife assessment

  This is an important study that investigates the impact of tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia. Through a combination of pre-clinical in vivo measurements, clinical data, and computational modeling, the authors present solid evidence regarding the heterogeneous effects of TKIs in patients and how the response to treatment may be improved. With the assumptions about differences between normal and leukemic cells addressed, this study would be of interest to those working in the fields of mathematical oncology and cancer biology.

Reviewed by eLife

Missense variant interaction scanning reveals a critical role of the FERM domain for tumor suppressor protein NF2 conformation and function

1. Christina S Moesslacher
2. Elisabeth Auernig
3. Jonathan Woodsmith
4. Andreas Feichtner
5. Evelyne Jany-Luig
6. Stefanie Jehle
7. Josephine M Worseck
8. Christian L Heine
9. Eduard Stefan
10. Ulrich Stelzl

Reviewed by Review Commons

De Novo Multi-Omics Pathway Analysis Designed for Prior Data Independent Inference of Cell Signaling Pathways

1. Katri Vaparanta
2. Johannes A.M. Merilahti
3. Veera K. Ojala
4. Klaus Elenius

• Curated by eLife

  eLife assessment:

  This manuscript describes development of a new algorithm for integrative analysis of multi-omics data. This work should be of potential interest to scientists performing bioinformatic pathway discovery in multi-omic datasets especially those that relate to signaling.

Reviewed by eLife

ChemChaste: Simulating spatially inhomogeneous biochemical reaction–diffusion systems for modeling cell–environment feedbacks

1. Connah G M Johnson
2. Alexander G Fletcher
3. Orkun S Soyer

Reviewed by GigaScience

Dynamics of co-substrate pools can constrain and regulate metabolic fluxes

1. Robert West
2. Hadrien Delattre
3. Elad Noor
4. Elisenda Feliu
5. Orkun S Soyer

• Curated by eLife

  eLife assessment

  This manuscript presents an important mathematical analysis on metabolic "co-substrates" and how their cycling can affect metabolic fluxes. Through mathematical analysis of simple network motifs, it shows the impact on constraining metabolic fluxes and the applied mathematical modeling/simulation approaches and the statistical analysis to compare predictions with data from previous studies offer convincing support for the potential biological relevance of co-substrate cycling. The work will be of interest to researchers who study microbial metabolism and metabolic engineering. However, part of this analysis remains unclear and would benefit from clarification.

Reviewed by eLife

Evolved bacterial resistance to the chemotherapy gemcitabine modulates its efficacy in co-cultured cancer cells

1. Serkan Sayin
2. Brittany Rosener
3. Carmen G Li
4. Bao Ho
5. Olga Ponomarova
6. Doyle V Ward
7. Albertha JM Walhout
8. Amir Mitchell

• Curated by eLife

  eLife assessment

  This fundamental work advances our understanding of how bacteria evolve to resist drugs used for cancer treatment and how this could potentially affect drug efficacy and treatment outcome. The data were collected and analyzed using a solid methodology and can be used as a starting point for functional studies of the interaction between microbiome interactions and cancer drug treatment. The findings will be of broad interest to microbiologists and organismal biologists interested in the role of microbiomes in drug responses.

Reviewed by eLife

Evolutionary conservation of sequence motifs at sites of protein modification

1. Shuang Li
2. Henrik G. Dohlman

Reviewed by Review Commons

PhysiPKPD: A pharmacokinetics and pharmacodynamics module for PhysiCell

1. Daniel Bergman
2. Lauren Marazzi
3. Mukti Chowkwale
4. Deepa Maheshvare M
5. Supriya Bidanta
6. Tarunendu Mapder
7. Jialun Li

Reviewed by GigaByte