INET

Molecular interactions form the basis of almost all biological processes in any living organism. Perturbations in these molecular networks result in dysfunctions that manifest themselves in disease, up to fatal outcomes. Our aim at the Institute of Network Biology (INET) is to understand how these molecular interactions and network changes caused by genetic variants or also by environmental influences like viruses or bacteria, lead to pathological processes. A deep understanding of the interplay of all the different layers of molecular networks may lead to new strategies for disease prevention and pharmacological interventions.

Protein interactions mediate essentially all biological processes, and analysis of protein-protein interactions has contributed fundamental insights to the understanding of biological systems.

The long-term goal of INET is to understand how macromolecular networks control biological processes and how networks evolve in response to exogenous, microbial, and endogenous factors, as well as evolutionary processes.

At INET we systematically generate molecular interactome maps by our well established AI informed and robotics supported protein-protein interaction pipeline integrating latest experimental and theoretical approaches.

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Regulatory network mapping will identify transcription factors (TFs) regulating the genes and pathways that enable either regulation processes within an organism or elucidate regulation of molecular host pathways by microbes.

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The contactome, the sum of physical contacts between viral and host macromolecules, affects cellular perturbations that enable viral replication and cause disease manifestations. Because co-complex assays predominantly detect indirect

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The presence of secretion systems by which the so-called ‘effector-proteins’ can be injected into the host’s cytosol to interact with host proteins and modulate molecular pathways is a unique feature of proteobacteria.

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For our comparative viral-human protein-protein interaction network we screened all 7 human corona viruses against each other and against the human ORFEome in order to get better insights to

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Inferring protein from transcript abundances using convolutional neural networks.

Amyotrophic Lateral Sclerosis (ALS) is a non-curable degenerative disease of the motor nervous system. The cause of the disease is largely unknown: In addition to genetic factors, viruses are also suspected to be involved in the development of the…

What exactly are the molecular interactions between the virus causing COVID-19 and its human host? How might our genetic differences cause different disease courses? And how do still-emerging virus variants differ in their host-virus interactions? To…

smart agriculture concept with machine, deep learning, neural network technology, the artificial intelligence network in smart farm to disrupt

Researchers at Helmholtz Zentrum München and Ludwig-Maximilians-University (LMU) mapped the signaling network in plants and discovered novel insights about how plants process information about their environment. This gives new potential to strategies…

Prof. Dr. Pascal Falter-Braun

Director Network Biology

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Dr. Claudia Falter

Senior Scientist & Scientific Coordination

Dr. Benjamin Weller

Senior Scientist

Dr. Chung-Wen Lin

Senior-Postdoc

Bushra Dohai

PhD Student

Benedikt Mairhörmann

PhD Student

Florin Ratajczak

PhD Student

Hridi Halder

PhD student’

Ozan Kücükkase

PhD student

Simin Rothballer

Technician (Dipl. Biol.)

Hatice Karabudak

Lab Assitant

Yemin Tun

Student

Alina Khan

Student

Steve Lay

Student

Patrick Schwehn

PhD Student

Lena Elorduy Vergara

PhD Student

Ramakrishnan Pandiarajan

PhD Student

Sophia Klink

PhD Student

Patrick Maximilian Schwehn, Pascal Falter-Braun

Inferring protein from transcript abundances using convolutional neural networks

Lisa Bohn, Jin Huang, Susan Weidig, Zhenyu Yang, Christoph Heidersberger, Bernard Genty, Pascal Falter-Braun, Alexander Christmann, Erwin Grill

The temperature sensor TWA1 is required for thermotolerance in Arabidopsis

Christian Wiese, Miriam Abele, Benjamin Al, Melina Altmann, Alexander Steiner, Nils Kalbfuß, Alexander Strohmayr, Raksha Ravikumar, Chan Ho Park, Barbara Brunschweiger, Chen Meng, Eva Facher, David W Ehrhardt, Pascal Falter-Braun, Zhi-Yong Wang, Christina Ludwig, Farhah F Assaad

Regulation of adaptive growth decisions via phosphorylation of the TRAPPII complex in Arabidopsis

Marie J Tofaute, Benjamin Weller, Carina Graß, Hridi Halder, Bushra Dohai, Pascal Falter-Braun, Daniel Krappmann

SARS-CoV-2 NSP14 MTase activity is critical for inducing canonical NF-κB activation

Marianne Boes, Pascal Falter-Braun

Long-COVID-19: the persisting imprint of SARS-CoV-2 infections on the innate immune system

Ratajczak F, Joblin M, Hildebrandt M, Ringsquandl M, Falter-Braun P*, Heinig M*.

Speos: An ensemble graph representation learning framework to predict core genes for complex diseases, Nat. Commun. 2023 Nov 08, doi 10.1038/s41467-023-42975-z

Young V, Dohai B, Thomas C. A. Hitch, Hyden P, Weller B, van Heusden NS, Saha D, Macgregor JF, Maseko SB, Chung-Wen Lin, Boujeant M, Choteau SA, Ober F, Schwehn P, Rothballer S,
Altmann M, Altmann S, Strobel A, Rothballer M, Tofaute M, Heinig M,
Clavel T, Twizere JC, Vincentelli R, Boes M, Krappmann D, Falter C,
Rattei T, Brun C, Zanzoni A, Falter-Braun P.
bioRxiv 2023.09.25.559292; doi: https://doi.org/10.1101/2023.09.25.559292

A gut meta-interactome map reveals modulation of human immunity by microbiome effectors The molecular mechanisms by which the gut microbiome influences human health remain largely unknown. Pseudomonadota is the third most abundant phylum in normal gut microbiomes. Several pathogens in this phylum can inject so-called virulence effector proteins into host cells. We report the identification of intact type 3 secretion systems (T3SS) in 5 - 20% of commensal Pseudomonadota in normal human gut microbiomes. To understand their functions, we experimentally generated a high-quality protein-protein meta-interactome map consisting of 1,263 interactions between 289 bacterial effectors and 430 human proteins. Effector targets are enriched for metabolic and immune functions and for genetic variation of microbiome-influenced traits including autoimmune diseases. We demonstrate that effectors modulate NF-κB signaling, cytokine secretion, and adhesion molecule expression. Finally, effectors are enriched in metagenomes of Crohn’s disease, but not ulcerative colitis patients pointing toward complex contributions to the etiology of inflammatory bowel diseases. Our results suggest that effector-host protein interactions are an important regulatory layer by which the microbiome impacts human health.

Osborne R, Rehneke L, Lehmann S, Roberts J, Altmann M, Altmann S, Zhang Y, Köpff E, Dominguez-Ferreras A, Okechukwu E, Sergaki C, Rich-Griffin C, Ntoukakis V, Eichmann R, Shan W, Falter-Braun P, Schäfer P.
Nat Commun. 2023 Jul 10;14(1):4065. doi: 10.1038/s41467-023-39885-5.PMID: 37429856

Symbiont-host interactome mapping reveals effector-targeted modulation of hormone networks and activation of growth promotion. Plants have benefited from interactions with symbionts for coping with challenging environments since the colonisation of land. The mechanisms of symbiont-mediated beneficial effects and similarities and differences to pathogen strategies are mostly unknown. Here, we use 106 (effector-) proteins, secreted by the symbiont Serendipita indica (Si) to modulate host physiology, to map interactions with Arabidopsis thaliana host proteins. Using integrative network analysis, we show significant convergence on target-proteins shared with pathogens and exclusive targeting of Arabidopsis proteins in the phytohormone signalling network. Functional in planta screening and phenotyping of Si effectors and interacting proteins reveals previously unknown hormone functions of Arabidopsis proteins and direct beneficial activities mediated by effectors in Arabidopsis. Thus, symbionts and pathogens target a shared molecular microbe-host interface. At the same time Si effectors specifically target the plant hormone network and constitute a powerful resource for elucidating the signalling network function and boosting plant productivity.

Weller B, Lin CW, Pogoutse O, Sauer M, Marin-de la Rosa N, Strobel A, Young V, Knapp JJ, Rayhan A, Falter C, Kim DK, Roth FP, Falter-Braun P.
G3 (Bethesda). 2023 Jul 5;13(7):jkad105. doi: 10.1093/g3journal/jkad105.PMID: 37267226

A resource of human coronavirus protein-coding sequences in a flexible, multipurpose Gateway Entry clone collection. The COVID-19 pandemic has catalyzed unprecedented scientific data and reagent sharing and collaboration, which enabled understanding the virology of the SARS-CoV-2 virus and vaccine development at record speed. The pandemic, however, has also raised awareness of the danger posed by the family of coronaviruses, of which 7 are known to infect humans and dozens have been identified in reservoir species, such as bats, rodents, or livestock. To facilitate understanding the commonalities and specifics of coronavirus infections and aspects of viral biology that determine their level of lethality to the human host, we have generated a collection of freely available clones encoding nearly all human coronavirus proteins known to date. We hope that this flexible, Gateway-compatible vector collection will encourage further research into the interactions of coronaviruses with their human host, to increase preparedness for future zoonotic viral outbreaks.

Kim DK, Weller B, Lin CW, Sheykhkarimli D, Knapp JJ, Dugied G, Zanzoni A, Pons C, Tofaute MJ, Maseko SB, Spirohn K, Laval F, Lambourne L, Kishore N, Rayhan A, Sauer M, Young V, Halder H, la Rosa NM, Pogoutse O, Strobel A, Schwehn P, Li R, Rothballer ST, Altmann M, Cassonnet P, Coté AG, Vergara LE, Hazelwood I, Liu BB, Nguyen M, Pandiarajan R, Dohai B, Coloma PAR, Poirson J, Giuliana P, Willems L, Taipale M, Jacob Y, Hao T, Hill DE, Brun C, Twizere JC, Krappmann D, Heinig M, Falter C, Aloy P, Demeret C, Vidal M, Calderwood MA, Roth FP, Falter-Braun P.
Nat Biotechnol. 2022 Oct 10. doi: 10.1038/s41587-022-01475-z. PMID: 36217029.

A proteome-scale map of the SARS-CoV-2-human contactome. Understanding the mechanisms of coronavirus disease 2019 (COVID-19) disease severity to efficiently design therapies for emerging virus variants remains an urgent challenge of the ongoing pandemic. Infection and immune reactions are mediated by direct contacts between viral molecules and the host proteome, and the vast majority of these virus-host contacts (the 'contactome') have not been identified. Here, we present a systematic contactome map of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with the human host encompassing more than 200 binary virus-host and intraviral protein-protein interactions. We find that host proteins genetically associated with comorbidities of severe illness and long COVID are enriched in SARS-CoV-2 targeted network communities. Evaluating contactome-derived hypotheses, we demonstrate that viral NSP14 activates nuclear factor κB (NF-κB)-dependent transcription, even in the presence of cytokine signaling. Moreover, for several tested host proteins, genetic knock-down substantially reduces viral replication. Additionally, we show for USP25 that this effect is phenocopied by the small-molecule inhibitor AZ1. Our results connect viral proteins to human genetic architecture for COVID-19 severity and offer potential therapeutic targets.

McLellan H, Harvey SE, Steinbrenner J, Armstrong MR, He Q, Clewes R, Pritchard L, Wang W, Wang S, Nussbaumer T, Dohai B, Luo Q, Kumari P, Duan H, Roberts A, Boevink PC, Neumann C, Champouret N, Hein I, Falter-Braun P, Beynon J, Denby K, Birch PRJ.
Proc Natl Acad Sci U S A. 2022 Aug 30;119(35):e2114064119. doi: 10.1073/pnas.2114064119. Epub 2022 Aug 22.

Exploiting breakdown in nonhost effector-target interactions to boost host disease resistance. Plants are resistant to most microbial species due to nonhost resistance (NHR), providing broad-spectrum and durable immunity. However, the molecular components contributing to NHR are poorly characterised. We address the question of whether failure of pathogen effectors to manipulate nonhost plants plays a critical role in NHR. RxLR (Arg-any amino acid-Leu-Arg) effectors from two oomycete pathogens, Phytophthora infestans and Hyaloperonospora arabidopsidis, enhanced pathogen infection when expressed in host plants (Nicotiana benthamiana and Arabidopsis, respectively) but the same effectors performed poorly in distantly related nonhost pathosystems. Putative target proteins in the host plant potato were identified for 64 P. infestans RxLR effectors using yeast 2-hybrid (Y2H) screens. Candidate orthologues of these target proteins in the distantly related non-host plant Arabidopsis were identified and screened using matrix Y2H for interaction with RxLR effectors from both P. infestans and H. arabidopsidis. Few P. infestans effector-target protein interactions were conserved from potato to candidate Arabidopsis target orthologues (cAtOrths). However, there was an enrichment of H. arabidopsidis RxLR effectors interacting with cAtOrths. We expressed the cAtOrth AtPUB33, which unlike its potato orthologue did not interact with P. infestans effector PiSFI3, in potato and Nicotiana benthamiana. Expression of AtPUB33 significantly reduced P. infestans colonization in both host plants. Our results provide evidence that failure of pathogen effectors to interact with and/or correctly manipulate target proteins in distantly related non-host plants contributes to NHR. Moreover, exploiting this breakdown in effector-nonhost target interaction, transferring effector target orthologues from non-host to host plants is a strategy to reduce disease.