Systems Biology

Growth-rate-dependent and nutrient-specific gene expression resource allocation in fission yeast

1. Istvan T Kleijn
2. Amalia Martínez-Segura
3. François Bertaux
4. Malika Saint
5. Holger Kramer
6. Vahid Shahrezaei
7. Samuel Marguerat

Reviewed by Review Commons

Two different cell-cycle processes determine the timing of cell division in Escherichia coli

1. Alexandra Colin
2. Gabriele Micali
3. Louis Faure
4. Marco Cosentino Lagomarsino
5. Sven van Teeffelen

• Curated by eLife

  Evaluation Summary:

  How the bacterium E.coli decides when to divide is an interesting, important, unsolved and highly controversial topic of interest to readers across disciplines, including microbiology, cell biology and statistical physics. Popular "single process" models invoke regulation at the step of replication initiation or at the step of cell division per se, whereas these authors have previously proposed a "concurrent cycles" model in which both processes are relevant, with different prominences in different situations. Consistent with the authors' motivating hypothesis, in the particular perturbed condition investigated in this work, a process different from DNA replication becomes increasingly important for division control as the degree of perturbation increases, which provides a new challenge to models for cell division control.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 and Reviewer #3 agreed to share their names with the authors.)

Reviewed by eLife

Systematic genome-scale identification of host factors for SARS-CoV-2 infection across models yields a core single gene dependency; ACE2

1. Katherine Chan
2. Adrian Granda Farias
3. Hunsang Lee
4. Furkan Guvenc
5. Patricia Mero
6. Kamaldeep Aulakh
7. Kevin R. Brown
8. Shahan Haider
9. Edyta Marcon
10. Ulrich Braunschweig
11. Amy Hin Yan Tong
12. Shuye Pu
13. Andrea Habsid
14. Natasha Christie-Holmes
15. Patrick Budylowski
16. Audrey Astori
17. Ayoob Ghalami
18. Samira Mubareka
19. Arinjay Banerjee
20. Karen L. Mossman
21. Jack Greenblatt
22. Scott D. Gray-Owen
23. Brian Raught
24. Benjamin J. Blencowe
25. Mikko Taipale
26. Jason Moffat

Reviewed by ScreenIT

Dynamically linking influenza virus infection kinetics, lung injury, inflammation, and disease severity

1. Margaret A Myers
2. Amanda P Smith
3. Lindey C Lane
4. David J Moquin
5. Rosemary Aogo
6. Stacie Woolard
7. Paul Thomas
8. Peter Vogel
9. Amber M Smith

• Curated by eLife

  Evaluation Summary:

  This is an interesting synthesis of iterative model development and experimental work in an influenza model of infection in mice. The work is quite groundbreaking in the field as it is the first to use models to link dynamics of lung viral load, infected cells, inflammation, virus-specific CD8+ T cells, bystander CD8+ T cells, and disease status. The paper suggests that CD8+ T cells are vital for elimination of infected cells but can also contribute directly to lung damage and disease severity.

  This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 agreed to share their name with the authors.)

Reviewed by eLife

Anti-SARS-CoV-2 potential of Cissampelos pareira L. identified by connectivity map-based analysis and in vitro studies

1. Madiha Haider
2. Vivek Anand
3. M. Ghalib Enayathullah
4. Yash Parekh
5. Sushma Ram
6. Surekha Kumari
7. Anmol
8. Gayatri Panda
9. Manjari Shukla
10. Dhwani Dholakia
11. Arjun Ray
12. Sudipta Bhattacharyya
13. Upendra Sharma
14. Kiran Kumar Bokara
15. Bhavana Prasher
16. Mitali Mukerji

Reviewed by ScreenIT

E156G and Arg158, Phe-157/del mutation in NTD of spike protein in B.1.617.2 lineage of SARS-CoV-2 leads to immune evasion through antibody escape

1. Armi M Chaudhari
2. Dinesh Kumar
3. Madhvi Joshi
4. Amrutlal Patel
5. Chaitanya Joshi

Reviewed by ScreenIT

A SARS-CoV-2 protein interaction map reveals targets for drug repurposing

1. David E. Gordon
2. Gwendolyn M. Jang
3. Mehdi Bouhaddou
4. Jiewei Xu
5. Kirsten Obernier
6. Kris M. White
7. Matthew J. O’Meara
8. Veronica V. Rezelj
9. Jeffrey Z. Guo
10. Danielle L. Swaney
11. Tia A. Tummino
12. Ruth Hüttenhain
13. Robyn M. Kaake
14. Alicia L. Richards
15. Beril Tutuncuoglu
16. Helene Foussard
17. Jyoti Batra
18. Kelsey Haas
19. Maya Modak
20. Minkyu Kim
21. Paige Haas
22. Benjamin J. Polacco
23. Hannes Braberg
24. Jacqueline M. Fabius
25. Manon Eckhardt
26. Margaret Soucheray
27. Melanie J. Bennett
28. Merve Cakir
29. Michael J. McGregor
30. Qiongyu Li
31. Bjoern Meyer
32. Ferdinand Roesch
33. Thomas Vallet
34. Alice Mac Kain
35. Lisa Miorin
36. Elena Moreno
37. Zun Zar Chi Naing
38. Yuan Zhou
39. Shiming Peng
40. Ying Shi
41. Ziyang Zhang
42. Wenqi Shen
43. Ilsa T. Kirby
44. James E. Melnyk
45. John S. Chorba
46. Kevin Lou
47. Shizhong A. Dai
48. Inigo Barrio-Hernandez
49. Danish Memon
50. Claudia Hernandez-Armenta
51. Jiankun Lyu
52. Christopher J. P. Mathy
53. Tina Perica
54. Kala Bharath Pilla
55. Sai J. Ganesan
56. Daniel J. Saltzberg
57. Ramachandran Rakesh
58. Xi Liu
59. Sara B. Rosenthal
60. Lorenzo Calviello
61. Srivats Venkataramanan
62. Jose Liboy-Lugo
63. Yizhu Lin
64. Xi-Ping Huang
65. YongFeng Liu
66. Stephanie A. Wankowicz
67. Markus Bohn
68. Maliheh Safari
69. Fatima S. Ugur
70. Cassandra Koh
71. Nastaran Sadat Savar
72. Quang Dinh Tran
73. Djoshkun Shengjuler
74. Sabrina J. Fletcher
75. Michael C. O’Neal
76. Yiming Cai
77. Jason C. J. Chang
78. David J. Broadhurst
79. Saker Klippsten
80. Phillip P. Sharp
81. Nicole A. Wenzell
82. Duygu Kuzuoglu-Ozturk
83. Hao-Yuan Wang
84. Raphael Trenker
85. Janet M. Young
86. Devin A. Cavero
87. Joseph Hiatt
88. Theodore L. Roth
89. Ujjwal Rathore
90. Advait Subramanian
91. Julia Noack
92. Mathieu Hubert
93. Robert M. Stroud
94. Alan D. Frankel
95. Oren S. Rosenberg
96. Kliment A. Verba
97. David A. Agard
98. Melanie Ott
99. Michael Emerman
100. Natalia Jura
101. Mark von Zastrow
102. Eric Verdin
103. Alan Ashworth
104. Olivier Schwartz
105. Christophe d’Enfert
106. Shaeri Mukherjee
107. Matt Jacobson
108. Harmit S. Malik
109. Danica G. Fujimori
110. Trey Ideker
111. Charles S. Craik
112. Stephen N. Floor
113. James S. Fraser
114. John D. Gross
115. Andrej Sali
116. Bryan L. Roth
117. Davide Ruggero
118. Jack Taunton
119. Tanja Kortemme
120. Pedro Beltrao
121. Marco Vignuzzi
122. Adolfo García-Sastre
123. Kevan M. Shokat
124. Brian K. Shoichet
125. Nevan J. Krogan

Reviewed by ScreenIT, preLights

Global mapping of RNA homodimers in living cells

1. Marta M Gabryelska
2. Grzegorz Kudla

Reviewed by ScreenIT

A hybrid PDE–ABM model for viral dynamics with application to SARS-CoV-2 and influenza

1. Sadegh Marzban
2. Renji Han
3. Nóra Juhász
4. Gergely Röst

Reviewed by ScreenIT

Identification of phenotype-specific networks from paired gene expression–cell shape imaging data

1. Charlie George Barker
2. Eirini Petsalaki
3. Girolamo Giudice
4. Julia Sero
5. Emmanuel Nsa Ekpenyong
6. Chris Bakal
7. Evangelia Petsalaki

Reviewed by Review Commons