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Article ; Online: Current proteomics methods applicable to dissecting the DNA damage response.

Muralidharan, Monita / Krogan, Nevan J / Bouhaddou, Mehdi / Kim, Minkyu

NAR cancer

2023 Volume 5, Issue 2, Page(s) zcad020

Abstract: The DNA damage response (DDR) entails reorganization of proteins and protein complexes involved in DNA repair. The coordinated regulation of these proteomic changes maintains genome stability. Traditionally, regulators and mediators of DDR have been ... ...

Abstract	The DNA damage response (DDR) entails reorganization of proteins and protein complexes involved in DNA repair. The coordinated regulation of these proteomic changes maintains genome stability. Traditionally, regulators and mediators of DDR have been investigated individually. However, recent advances in mass spectrometry (MS)-based proteomics enable us to globally quantify changes in protein abundance, post-translational modifications (PTMs), protein localization, and protein-protein interactions (PPIs) in cells. Furthermore, structural proteomics approaches, such as crosslinking MS (XL-MS), hydrogen/deuterium exchange MS (H/DX-MS), Native MS (nMS), provide large structural information of proteins and protein complexes, complementary to the data collected from conventional methods, and promote integrated structural modeling. In this review, we will overview the current cutting-edge functional and structural proteomics techniques that are being actively utilized and developed to help interrogate proteomic changes that regulate the DDR.
Language	English
Publishing date	2023-05-19
Publishing country	England
Document type	Journal Article
ISSN	2632-8674
ISSN (online)	2632-8674
DOI	10.1093/narcan/zcad020
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Article ; Online: Network inference from perturbation time course data.

Sarmah, Deepraj / Smith, Gregory R / Bouhaddou, Mehdi / Stern, Alan D / Erskine, James / Birtwistle, Marc R

NPJ systems biology and applications

2022 Volume 8, Issue 1, Page(s) 42

Abstract: Networks underlie much of biology from subcellular to ecological scales. Yet, understanding what experimental data are needed and how to use them for unambiguously identifying the structure of even small networks remains a broad challenge. Here, we ... ...

Abstract	Networks underlie much of biology from subcellular to ecological scales. Yet, understanding what experimental data are needed and how to use them for unambiguously identifying the structure of even small networks remains a broad challenge. Here, we integrate a dynamic least squares framework into established modular response analysis (DL-MRA), that specifies sufficient experimental perturbation time course data to robustly infer arbitrary two and three node networks. DL-MRA considers important network properties that current methods often struggle to capture: (i) edge sign and directionality; (ii) cycles with feedback or feedforward loops including self-regulation; (iii) dynamic network behavior; (iv) edges external to the network; and (v) robust performance with experimental noise. We evaluate the performance of and the extent to which the approach applies to cell state transition networks, intracellular signaling networks, and gene regulatory networks. Although signaling networks are often an application of network reconstruction methods, the results suggest that only under quite restricted conditions can they be robustly inferred. For gene regulatory networks, the results suggest that incomplete knockdown is often more informative than full knockout perturbation, which may change experimental strategies for gene regulatory network reconstruction. Overall, the results give a rational basis to experimental data requirements for network reconstruction and can be applied to any such problem where perturbation time course experiments are possible.
MeSH term(s)	Systems Biology/methods ; Algorithms ; Gene Regulatory Networks/genetics ; Signal Transduction/physiology
Language	English
Publishing date	2022-11-01
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ISSN	2056-7189
ISSN (online)	2056-7189
DOI	10.1038/s41540-022-00253-6
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Article ; Online: How can systems approaches help us understand and treat infectious disease?

Kuchina, Anna / Yang, Jason / Aldridge, Bree / Janes, Kevin A / Subramanian, Naeha / Krogan, Nevan J / Bouhaddou, Mehdi / Einav, Shirit / Papin, Jason / Germain, Ronald N

Cell systems

2023 Volume 13, Issue 12, Page(s) 945–949

Abstract: Leading researchers at the intersection of infectious disease and systems biology speak about how systems approaches have influenced modern infectious disease research and what these tools can offer for the future of the field. ...

Abstract	Leading researchers at the intersection of infectious disease and systems biology speak about how systems approaches have influenced modern infectious disease research and what these tools can offer for the future of the field.
MeSH term(s)	Humans ; Communicable Diseases/therapy ; Systems Biology
Language	English
Publishing date	2023-05-26
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2854138-8
ISSN	2405-4720 ; 2405-4712
ISSN (online)	2405-4720
ISSN	2405-4712
DOI	10.1016/j.cels.2022.11.009
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Article ; Online: Leveraging modeling and simulation to optimize the therapeutic window for epigenetic modifier drugs.

Walz, Antje-Christine / Van De Vyver, Arthur J / Yu, Li / Birtwistle, Marc R / Krogan, Nevan J / Bouhaddou, Mehdi

Pharmacology & therapeutics

2022 Volume 235, Page(s) 108162

Abstract: Dysregulated epigenetic processes can lead to altered gene expression and give rise to malignant transformation and tumorigenesis. Epigenetic drugs aim to revert the phenotype of cancer cells to normally functioning cells, and are developed and applied ... ...

Abstract	Dysregulated epigenetic processes can lead to altered gene expression and give rise to malignant transformation and tumorigenesis. Epigenetic drugs aim to revert the phenotype of cancer cells to normally functioning cells, and are developed and applied to treat both hematological and solid cancers. Despite this promising therapeutic avenue, the successful development of epigenetic modulators has been challenging. We argue that besides identifying the right responder patient population, the selection of an optimized dosing regimen is equally important. For the majority of epigenetic modulators, hematological adverse effects such as thrombocytopenia, anemia or neutropenia are frequently observed and may limit their therapeutic potential. Therefore, one of the key challenges is to identify a dosing regimen that maximizes drug efficacy and minimizes toxicity. This requires a good understanding of the quantitative relationship between the administered dose, the drug exposure and the magnitude and duration of drug response related to safety and efficacy. With case examples, we highlight how modeling and simulation has been successfully applied to address those questions. As an outlook, we suggest the combination of efficacy and safety prediction models that capture the quantitative, mechanistic relationships governing the balance between their safety and efficacy dynamics. A stepwise approach for its implementation is presented. Utilizing in silico explorations, the impact of dosing regimen on the therapeutic window can be explored. This will serve as a basis to select the most promising dosing regimen that maximizes efficacy while minimizing adverse effects and to increase the probability of success for the given epigenetic drug.
MeSH term(s)	Computer Simulation ; Dose-Response Relationship, Drug ; Drug-Related Side Effects and Adverse Reactions ; Epigenesis, Genetic ; Humans ; Models, Biological
Language	English
Publishing date	2022-02-18
Publishing country	England
Document type	Journal Article ; Review ; Research Support, N.I.H., Extramural
ZDB-ID	194735-7
ISSN	1879-016X ; 0163-7258
ISSN (online)	1879-016X
ISSN	0163-7258
DOI	10.1016/j.pharmthera.2022.108162
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Article ; Online: Network modeling suggests HIV infection phenocopies PI3K-AKT pathway mutations to enhance HPV-associated cervical cancer.

Olwal, Charles Ochieng' / Fabius, Jacqueline M / Zuliani-Alvarez, Lorena / Eckhardt, Manon / Kyei, George Boateng / Quashie, Peter Kojo / Krogan, Nevan J / Bouhaddou, Mehdi / Bediako, Yaw

Molecular omics

2023 Volume 19, Issue 7, Page(s) 538–551

Abstract: Women coinfected with human immunodeficiency virus type 1 (HIV-1) and human papillomavirus (HPV) are six times as likely to develop invasive cervical carcinoma compared to those without HIV. Unlike other HIV-associated cancers, the risk of cervical ... ...

Abstract	Women coinfected with human immunodeficiency virus type 1 (HIV-1) and human papillomavirus (HPV) are six times as likely to develop invasive cervical carcinoma compared to those without HIV. Unlike other HIV-associated cancers, the risk of cervical cancer development does not change when HPV/HIV coinfected women begin antiretroviral therapy, suggesting HIV-associated immune suppression is not a key driver of cervical cancer development in coinfected women. Here, we investigated whether the persistent secretion of inflammatory factors in HIV-positive patients on antiretroviral therapy could enhance cancer signaling in HPV-infected cervical cells
MeSH term(s)	Humans ; Female ; Uterine Cervical Neoplasms/genetics ; Human Papillomavirus Viruses ; Phosphatidylinositol 3-Kinases/genetics ; Proto-Oncogene Proteins c-akt ; Papillomavirus Infections/complications ; Papillomavirus Infections/genetics ; HIV Infections/complications ; HIV Infections/genetics ; Mutation
Chemical Substances	Phosphatidylinositol 3-Kinases (EC 2.7.1.-) ; Proto-Oncogene Proteins c-akt (EC 2.7.11.1)
Language	English
Publishing date	2023-08-14
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ISSN	2515-4184
ISSN (online)	2515-4184
DOI	10.1039/d3mo00025g
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Article ; Online: Dimerization-based control of cooperativity.

Bouhaddou, Mehdi / Birtwistle, Marc R

Molecular bioSystems

2014 Volume 10, Issue 7, Page(s) 1824–1832

Abstract: Cooperativity of ligand-receptor binding influences the input-output behavior of a biochemical system and thus is an important determinant of its physiological function. Canonically, such cooperativity is understood in terms of ligand-receptor binding ... ...

Abstract	Cooperativity of ligand-receptor binding influences the input-output behavior of a biochemical system and thus is an important determinant of its physiological function. Canonically, such cooperativity is understood in terms of ligand-receptor binding affinity, where an initial binding event changes the affinity for subsequent binding events. Here, we demonstrate that dimerization-a simple yet pervasive signaling motif across biology-can have significant control over cooperativity and even dominate over the canonical mechanism. Through an exhaustive parameter sensitivity analysis of a general kinetic model for signal-mediated dimerization, we show that quantitative modulation of dimerization processes can reinforce, eliminate, and even reverse cooperativity imposed by the canonical allosteric ligand-receptor binding affinity mechanism. The favored accumulation of stoichiometrically asymmetric dimers (those with ligand-receptor stoichiometry of 1 : 2) is a major determinant of dimerization-based cooperativity control. However, simulations demonstrate that favoring accumulation of such stoichiometrically asymmetric dimers can either increase or decrease cooperativity, and thus the quantitative relationship between stoichiometrically asymmetric dimers and cooperativity is highly dependent on the parameter values of the particular system of interest. These results suggest that the dimerization motif provides a novel mechanism for both generating and quantitatively tuning cooperativity that, due to the ubiquity of dimerization motifs in biochemical systems, may play a major role in a host of biological functions. Thus, the canonical, allosteric view of cooperativity is incomplete without considering dimerization effects, which is of particular importance as dimerization is often a necessary feature of the allosteric mechanism.
MeSH term(s)	Allosteric Regulation ; Binding Sites ; Dimerization ; Kinetics ; Ligands ; Models, Chemical ; Protein Binding ; Proteins/chemistry ; Proteins/metabolism
Chemical Substances	Ligands ; Proteins
Language	English
Publishing date	2014-04-15
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2188635-0
ISSN	1742-2051 ; 1742-206X
ISSN (online)	1742-2051
ISSN	1742-206X
DOI	10.1039/c4mb00022f
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Article ; Online: Integrating Transcriptomic Data with Mechanistic Systems Pharmacology Models for Virtual Drug Combination Trials.

Barrette, Anne Marie / Bouhaddou, Mehdi / Birtwistle, Marc R

ACS chemical neuroscience

2017 Volume 9, Issue 1, Page(s) 118–129

Abstract: Monotherapy clinical trials with mutation-targeted kinase inhibitors, despite some success in other cancers, have yet to impact glioblastoma (GBM). Besides insufficient blood-brain barrier penetration, combinations are key to overcoming obstacles such as ...

Abstract	Monotherapy clinical trials with mutation-targeted kinase inhibitors, despite some success in other cancers, have yet to impact glioblastoma (GBM). Besides insufficient blood-brain barrier penetration, combinations are key to overcoming obstacles such as intratumoral heterogeneity, adaptive resistance, and the epistatic nature of tumor genomics that cause mutation-targeted therapies to fail. With now hundreds of potential drugs, exploring the combination space clinically and preclinically is daunting. We are building a simulation-based approach that integrates patient-specific data with a mechanistic computational model of pan-cancer driver pathways (receptor tyrosine kinases, RAS/RAF/ERK, PI3K/AKT/mTOR, cell cycle, apoptosis, and DNA damage) to prioritize drug combinations by their simulated effects on tumor cell proliferation and death. Here we illustrate a first step, tailoring the model to 14 GBM patients from The Cancer Genome Atlas defined by an mRNA-seq transcriptome, and then simulating responses to three promiscuous FDA-approved kinase inhibitors (bosutinib, ibrutinib, and cabozantinib) with evidence for blood-brain barrier penetration. The model captures binding of the drug to primary targets and off-targets based on published affinity data and simulates responses of 100 heterogeneous tumor cells within a patient. Single drugs are marginally effective or even counterproductive. Common copy number alterations (PTEN loss, EGFR amplification, and NF1 loss) have a negligible correlation with single-drug or combination efficacy, reinforcing the importance of postgenetic approaches that account for kinase inhibitor promiscuity to match drugs to patients. Drug combinations tend to be either cytostatic or cytotoxic, but seldom both, highlighting the need for considering targeted and nontargeted therapy. Although we focus on GBM, the approach is generally applicable.
MeSH term(s)	Anilides/pharmacology ; Anilides/therapeutic use ; Aniline Compounds/pharmacology ; Aniline Compounds/therapeutic use ; Antineoplastic Agents/pharmacology ; Antineoplastic Agents/therapeutic use ; Apoptosis/drug effects ; Blood-Brain Barrier/metabolism ; Cell Cycle/drug effects ; Cell Proliferation/drug effects ; Central Nervous System Neoplasms/drug therapy ; Central Nervous System Neoplasms/genetics ; Central Nervous System Neoplasms/metabolism ; Clinical Trials as Topic ; Computer Simulation ; Drug Discovery/methods ; Drug Therapy, Combination ; Genomics/methods ; Glioblastoma/drug therapy ; Glioblastoma/genetics ; Glioblastoma/metabolism ; Humans ; Models, Theoretical ; Nitriles/pharmacology ; Nitriles/therapeutic use ; Protein-Tyrosine Kinases/antagonists & inhibitors ; Protein-Tyrosine Kinases/metabolism ; Pyrazoles/pharmacology ; Pyrazoles/therapeutic use ; Pyridines/pharmacology ; Pyridines/therapeutic use ; Pyrimidines/pharmacology ; Pyrimidines/therapeutic use ; Quinolines/pharmacology ; Quinolines/therapeutic use ; RNA, Messenger/metabolism ; Stochastic Processes ; Transcriptome
Chemical Substances	Anilides ; Aniline Compounds ; Antineoplastic Agents ; Nitriles ; Pyrazoles ; Pyridines ; Pyrimidines ; Quinolines ; RNA, Messenger ; cabozantinib (1C39JW444G) ; ibrutinib (1X70OSD4VX) ; bosutinib (5018V4AEZ0) ; Protein-Tyrosine Kinases (EC 2.7.10.1)
Language	English
Publishing date	2017-10-06
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ISSN	1948-7193
ISSN (online)	1948-7193
DOI	10.1021/acschemneuro.7b00197
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Article ; Online: Network inference from perturbation time course data

Deepraj Sarmah / Gregory R. Smith / Mehdi Bouhaddou / Alan D. Stern / James Erskine / Marc R. Birtwistle

npj Systems Biology and Applications, Vol 8, Iss 1, Pp 1-

2022 Volume 18

Abstract: Abstract Networks underlie much of biology from subcellular to ecological scales. Yet, understanding what experimental data are needed and how to use them for unambiguously identifying the structure of even small networks remains a broad challenge. Here, ...

Abstract	Abstract Networks underlie much of biology from subcellular to ecological scales. Yet, understanding what experimental data are needed and how to use them for unambiguously identifying the structure of even small networks remains a broad challenge. Here, we integrate a dynamic least squares framework into established modular response analysis (DL-MRA), that specifies sufficient experimental perturbation time course data to robustly infer arbitrary two and three node networks. DL-MRA considers important network properties that current methods often struggle to capture: (i) edge sign and directionality; (ii) cycles with feedback or feedforward loops including self-regulation; (iii) dynamic network behavior; (iv) edges external to the network; and (v) robust performance with experimental noise. We evaluate the performance of and the extent to which the approach applies to cell state transition networks, intracellular signaling networks, and gene regulatory networks. Although signaling networks are often an application of network reconstruction methods, the results suggest that only under quite restricted conditions can they be robustly inferred. For gene regulatory networks, the results suggest that incomplete knockdown is often more informative than full knockout perturbation, which may change experimental strategies for gene regulatory network reconstruction. Overall, the results give a rational basis to experimental data requirements for network reconstruction and can be applied to any such problem where perturbation time course experiments are possible.
Keywords	Biology (General) ; QH301-705.5
Subject code	006
Language	English
Publishing date	2022-11-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: CRISPR-Cas9 screen of E3 ubiquitin ligases identifies TRAF2 and UHRF1 as regulators of HIV latency in primary human T cells.

mBio

2024 Volume 15, Issue 4, Page(s) e0222223

Abstract: During HIV infection of CD4+ T cells, ubiquitin pathways are essential to viral replication and host innate immune response; however, the role of specific E3 ubiquitin ligases is not well understood. Proteomics analyses identified 116 single-subunit E3 ... ...

Abstract	During HIV infection of CD4+ T cells, ubiquitin pathways are essential to viral replication and host innate immune response; however, the role of specific E3 ubiquitin ligases is not well understood. Proteomics analyses identified 116 single-subunit E3 ubiquitin ligases expressed in activated primary human CD4+ T cells. Using a CRISPR-based arrayed spreading infectivity assay, we systematically knocked out 116 E3s from activated primary CD4+ T cells and infected them with NL4-3 GFP reporter HIV-1. We found 10 E3s significantly positively or negatively affected HIV infection in activated primary CD4+ T cells, including UHRF1 (pro-viral) and TRAF2 (anti-viral). Furthermore, deletion of either TRAF2 or UHRF1 in three JLat models of latency spontaneously increased HIV transcription. To verify this effect, we developed a CRISPR-compatible resting primary human CD4+ T cell model of latency. Using this system, we found that deletion of TRAF2 or UHRF1 initiated latency reactivation and increased virus production from primary human resting CD4+ T cells, suggesting these two E3s represent promising targets for future HIV latency reversal strategies. Importance: HIV, the virus that causes AIDS, heavily relies on the machinery of human cells to infect and replicate. Our study focuses on the host cell's ubiquitination system which is crucial for numerous cellular processes. Many pathogens, including HIV, exploit this system to enhance their own replication and survival. E3 proteins are part of the ubiquitination pathway that are useful drug targets for host-directed therapies. We interrogated the 116 E3s found in human immune cells known as CD4+ T cells, since these are the target cells infected by HIV. Using CRISPR, a gene-editing tool, we individually removed each of these enzymes and observed the impact on HIV infection in human CD4+ T cells isolated from healthy donors. We discovered that 10 of the E3 enzymes had a significant effect on HIV infection. Two of them, TRAF2 and UHRF1, modulated HIV activity within the cells and triggered an increased release of HIV from previously dormant or "latent" cells in a new primary T cell assay. This finding could guide strategies to perturb hidden HIV reservoirs, a major hurdle to curing HIV. Our study offers insights into HIV-host interactions, identifies new factors that influence HIV infection in immune cells, and introduces a novel methodology for studying HIV infection and latency in human immune cells.
MeSH term(s)	Humans ; CCAAT-Enhancer-Binding Proteins/metabolism ; CD4-Positive T-Lymphocytes ; CRISPR-Cas Systems ; HIV Infections ; TNF Receptor-Associated Factor 2/metabolism ; Ubiquitin-Protein Ligases/metabolism ; Ubiquitins/metabolism ; Virus Latency ; Virus Replication ; HIV/physiology
Chemical Substances	CCAAT-Enhancer-Binding Proteins ; TNF Receptor-Associated Factor 2 ; Ubiquitin-Protein Ligases (EC 2.3.2.27) ; Ubiquitins ; UHRF1 protein, human (EC 2.3.2.27) ; PSMD2 protein, human
Language	English
Publishing date	2024-02-27
Publishing country	United States
Document type	Journal Article
ZDB-ID	2557172-2
ISSN	2150-7511 ; 2161-2129
ISSN (online)	2150-7511
ISSN	2161-2129
DOI	10.1128/mbio.02222-23
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Article ; Online: Mapping the protein-protein and genetic interactions of cancer to guide precision medicine.

Bouhaddou, Mehdi / Eckhardt, Manon / Chi Naing, Zun Zar / Kim, Minkyu / Ideker, Trey / Krogan, Nevan J

Current opinion in genetics & development

2019 Volume 54, Page(s) 110–117

Abstract: Massive efforts to sequence cancer genomes have compiled an impressive catalogue of cancer mutations, revealing the recurrent exploitation of a handful of 'hallmark cancer pathways'. However, unraveling how sets of mutated proteins in these and other ... ...

Abstract	Massive efforts to sequence cancer genomes have compiled an impressive catalogue of cancer mutations, revealing the recurrent exploitation of a handful of 'hallmark cancer pathways'. However, unraveling how sets of mutated proteins in these and other pathways hijack pro-proliferative signaling networks and dictate therapeutic responsiveness remains challenging. Here, we show that cancer driver protein-protein interactions are enriched for additional cancer drivers, highlighting the power of physical interaction maps to explain known, as well as uncover new, disease-promoting pathway interrelationships. We hypothesize that by systematically mapping the protein-protein and genetic interactions in cancer-thereby creating Cancer Cell Maps-we will create resources against which to contextualize a patient's mutations into perturbed pathways/complexes and thereby specify a matching targeted therapeutic cocktail.
MeSH term(s)	Computational Biology ; Databases, Genetic ; Epistasis, Genetic/genetics ; Gene Regulatory Networks ; Humans ; Mutation/genetics ; Neoplasms/genetics ; Precision Medicine ; Protein Interaction Maps/genetics ; Signal Transduction/genetics
Language	English
Publishing date	2019-07-06
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	1077312-5
ISSN	1879-0380 ; 0959-437X
ISSN (online)	1879-0380
ISSN	0959-437X
DOI	10.1016/j.gde.2019.04.005
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