Understanding the regulation of the immune system from a
systems-level perspective

The Lynn group is a multi-disciplinary group that is equally divided between computational systems biology and experimental immunology.

On the wet-lab side, the group employs in vitro and in vivo experimental and clinical models, coupled with systems biology approaches, to investigate the interplay between the microbiome, vaccines and the immune system. On the bioinformatics side, Lynn's group leads the development of InnateDB, an internationally recognised systems biology platform for innate immunity networks.

David Lynn also leads the computational biology aspects of a €12 million European Commission-funded project called PRIMES, which is investigating how to model, and subsequently therapeutically target, protein interaction networks in cancer.

Current research:

The Lynn Group is continuing their work investigating the role that the microbiota in early-life plays in shaping the developing immune system, and how this influences responses to vaccination. To do this, they will continue to employ mouse models (including germ-free) and run a large clinical study in human infants.

On the bioinformatics side of the group, they recently developed a novel application for spatial transcriptomics and will continue to develop novel software to facilitate systems-level analysis.

​Systems Immunology

  • The impact of the microbiota in early-life on the developing immune system and optimal vaccine responses.
  • How does the microbiota modulate vaccine responses in human infants: A systems vaccinology approach.
  • Vaccine non-specific effects and trained innate immunity.
  • The impact of the microbiota on the efficacy and toxicity of cancer immunotherapies.
  • InnateDB an internationally recognised platform facilitating systems level analyses of innate immunity.
  • Gnotobiotic (germ-free) mouse models.

Bioinformatics and Computational Biology

  • The development of novel software applications and resources for proteomics, pathway analysis, network analysis and visualisation (e.g. DyNet; CHAT; SIGORA; HiQuant).
  • Protein-Protein Interaction Network Rewiring in Cancer (International PRIMES consortium).
  • Patient-Specific Network Rewiring.
  • Transcriptional and metabolic reprogramming of colorectal cancer cells expressing the oncogenic KRASG13D mutation.
  • Novel co-extinction strategies for treatment of prostate cancer.
  • Network visualization and analysis of spatial omics data.

Highlight publications

Authors
Title
Published In

Charitou T., Srihari S., Lynn M.A., Jarboui M., Fasterius E., Moldovan M., Shirasawa S., Tsunoda T., Ueffing M., Xie J., J. Xin, Wang X., Proud C., Boldt K., Al-Khalili Szigyarto C., Kolch W., Lynn D.J.  

Transcriptional and metabolic rewiring of colorectal cancer cells expressing the oncogenic KRASG13D mutation

British Journal of Cancer (2019) 121(1): 37–50. 

Khadake J., Meldal B., Panni S., Thorneycroft D., van Roey K., Abbani S., Salwinski L., Pellegrini M., Iannuccelli M., Licata L., Cesareni G., Roechert B., Bridge A., Ammari M.G., McCarthy F., Broackes-Carter F., Campbell N.H., Melidoni A.N., Rodriguez-Lopez M., Lovering R.C., Jagannathan S., Chen C., Lynn D.J., Ricard-Blum S., Mahadevan U., Raghunath A.,del Toro N., Duesbury M., Koch M., Perfetto L., Shrivastava A., Ochoa D., Wagih O., Piñero J., Kotlyar M., Pastrello C., Beltrao P., Furlong L., Jurisica I., Hermjakob H., Orchard S., Porras P. (2019).

Capturing variation impact on molecular interactions in the IMEx Consortium mutations data set.

 Nature Communications. 10 (2019).

Lynn M.A., Tumes D.J., Choo J.M., Sribnaia A., Blake S.J., Leong L.E.X., Young G.P., Marshall H.S., Wesselingh S.L., Rogers G.B., Lynn D.J. (2018).

Early-life antibiotic-driven dysbiosis leads to dysregulated vaccine immune responses in mice.

Cell Host & Microbe, 23(5): 653-660. 

Salamon J., Goenawan I.H., Lynn D.J. (2018).

Analysis and visualization of dynamic networks using the DyNet App for Cytoscape.

Current Protocols in Bioinformatics, 63(5): e55.

 MacGregor S., Ong J.S., An J., Han X., Zhou T., Siggs O.M., Law M.H., Souzeau E., Sharma S., Lynn D.J., Beesley J., Sheldrick B., Mills R.A., Landers J., Ruddle J.B., Graham S.L., Healey P.R., White A.J.R., Casson R.J., Best S., Grigg J.R., Goldberg I., Powell J.E., Whiteman D.C., Radford-Smith G.L., Martin N.G., Montgomery G.W., Burdon K.P., Mackey D.A., Gharahkhani P., Craig J.E., Hewitt A.W. (2018).

Genome-wide association study of intraocular pressure uncovers new pathways to glaucoma.

Nature Genetics, 50(8):1067-1071.

Salamon J., Qian X., Nilsson M., Lynn D.J. (2018).

Network visualization and analysis of spatially aware gene expression data with InsituNet.

Cell Systems, 6(5): 626-630.

Nguyen E., Centenera M., Moldovan M., Das R., Irani S., Vincent A., Chan H., Horvath L., Lynn D.J., Daly R., Butler L. (2018).

Identification of novel response and predictive biomarkers to Hsp90 inhibitors through mass spectrometry-based proteomic profiling of patient-derived prostate tumor explants.

Molecular & Cellular Proteomics, 17(8): 1470-1486.

Gharahkhani P., Burdon K.P., Cooke Bailey J.N., Hewitt A.W., Law M.H., Pasquale L.R., Kang J.H., Haines J.L., Souzeau E., Zhou T., Siggs O.M., Landers J., Awadalla M., Sharma S., Mills R.A., Ridge B., Lynn D.J., NEIGHBORHOOD consortium, Casson R., Graham S.L., Goldberg I., White A., Healey P.R., Grigg J., Lawlor M., Mitchell P., Ruddle J., Coote M., Walland M., Best S., Vincent A, Gale J., Radford Smith G., Whiteman D.C., Montgomery G.W., Martin N.G., Mackey D.A., Wiggs J.L., MacGregor S., Craig J.E. (2018).

Analysis combining correlated glaucoma traits identifies five new risk loci for open-angle glaucoma.

Scientific Reports, 8(1):3124.

Dumousseau M., Alonso-López D., Ammari M., Bradley G., Campbell N.H., Ceol A., Cesareni G., Combe C., De Las Rivas .J, Del-Toro N., Heimbach J., Hermjakob H., Jurisica I., Koch M., Licata L., Lovering R.C., Lynn D.J., Meldal B., Micklem G., Panni, S., Porras P., Ricard-Blum S.,  Roechert B., Salwinski L., Shrivastava A., Sullivan J., Thierry-Mieg N., Yehudi Y., Van Roey K., Orchard S. (2018).

Encompassing new use cases - level 3.0 of the HUPO-PSI format for molecular interactions.

BMC Bioinformatics, 19(1):134.

Lynn D.J., Pulendran B. (2018).

The potential of the microbiota to influence vaccine responses.

Journal of Leukocyte Biology, 103(2):225-231.

Armstrong H.K., Gillis J., Johnson I.R.D., Nassar Z.D., Moldovan M., Levrier C., Sadowski M.C., Chin M.Y., Guns E.T., Tarulli G., Lynn D.J., Brooks D.A., Selth L.A., Centenera M.M., Butler L.M. (2018).

Dysregulated fibronectin trafficking by Hsp90 inhibition restricts prostate cancer cell invasion.

Scientific Reports, 8(1):2090.

Smith J.R, Todd S., Ashander L.M., Charitou T., Ma Y., Yeh S., Crozier I., Michael M., Appukuttan B., Lynn D.J.*, Marsh G.A*. (2017). * Joint-senior author.

Retinal Pigment Epithelial Cells are a Potential Reservoir for Ebola Virus in the Human Eye.

Translational Vision Science & Technology, 6(12): doi :10.1167/tvst.6.4.12.

Muetze T., Lynn D.J. (2017).

Identification of Contextually Relevant Hubs using the Contextual Hub Analysis Tool (CHAT) in Cytoscape.

Current Protocols in Bioinformatics, 59 8.24.1 – 8.24.13 doi : 10.1002/cpbi.35.

 Zhou T., Souzeau E., Sharma S., Landers J., Mills R., Goldberg I., Healey P., Graham S., Hewitt A.W., Mackey D.A., Galanopoulos A., Casson R., Ruddle J., Ellis J., Leo P., Brown M.A., MacGregor S., Lynn D.J., Burdon K.P., Craig J.E. (2017).

Whole exome sequencing implicates eye development, the unfolded protein response and plasma membrane homeostasis in primary open-angle glaucoma.

PLoS One, 12(3):e0172427.

Muetze T, Goenawan IH, Wiencko HL, Bernal-Llinares M, Bryan K, Lynn DJ. 

Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks.

F1000 Research 2016 (In press).

Goenawan IH, Bryan K, Lynn DJ. 

DyNet: visualization and analysis of dynamic molecular interaction networks.

Bioinformatics. 2016 Sep 1;32(17):2713-5. doi: 10.1093/bioinformatics/btw187. Epub 2016 May 3.

Bryan K, Jarboui MA, Raso C, Bernal-Llinares M, McCann B, Rauch J, Boldt K, Lynn DJ. 

HiQuant: Rapid Postquantification Analysis of Large-Scale MS-Generated Proteomics Data.

J Proteome Res. 2016 Jun 3;15(6):2072-9. doi: 10.1021/acs.jproteome.5b01008. Epub 2016 May 16.

Blohmke CJ, Darton TC, Jones C, Suarez NM, Waddington CS, Angus B, Zhou L, Hill J, Clare S, Kane L, Mukhopadhyay S, Schreiber F,Duque-Correa MA, Wright JC, Roumeliotis TI, Yu L, Choudhary JS, Mejias A, Ramilo O, Shanyinde M, Sztein MB, Kingsley RA, Lockhart S,Levine MM, Lynn DJ, Dougan G, Pollard AJ.

Interferon-driven alterations of the host's amino acid metabolism in the pathogenesis of typhoid fever.

J Exp Med. 2016 May 30;213(6):1061-77. doi: 10.1084/jem.20151025. Epub 2016 May 23.

Charitou T, Bryan K, Lynn DJ. (Corresponding Author)

Using biological networks to integrate, visualize and analyze genomics data.

Genet Sel Evol. 2016 Mar 31;48:27. doi: 10.1186/s12711-016-0205-1.

Richardson IW, Berry DP, Wiencko HL, Higgins IM, More SJ, McClure J, Lynn DJ, Bradley DG.

A genome-wide association study for genetic susceptibility to Mycobacterium bovis infection in dairy cattle identifies a susceptibility QTL on chromosome 23.

Genet Sel Evol. 2016 Mar 9;48:19. doi: 10.1186/s12711-016-0197-x.

Foley C, Chapwanya A, Callanan JJ, Whiston R, Miranda-CasoLuengo R, Lu J, Meijer WG, Lynn DJ, O' Farrelly C, Meade KG.

Integrated analysis of the local and systemic changes preceding the development of post-partum cytological endometritis.

BMC Genomics. 2015 Oct 19;16:811. doi: 10.1186/s12864-015-1967-5.

Frias S, Bryan K, Brinkman FS, Lynn DJ. (Corresponding Author)

 
 

CerebralWeb: a Cytoscape.js plug-in to visualize networks stratified by subcellular localization.

Database (Oxford). 2015 May 7;2015:bav041. doi: 10.1093/database/bav041. Print 2015.

Vegh P, Foroushani ABK, Magee DA, McCabe MS, Browne JA, Nalpas NC, Conlon KM, Gordon SV, Bradley DG, MacHugh DE, Lynn DJ (Corresponding Author).

Profiling microRNA expression in bovine alveolar macrophages using a next-generation sequencing based approach.

Tuberculosis (Edinb). 2015 Jan;95(1):60-7.

Dickinson P, Smith CL, Forster T, Craigon M, Ross AJ, Khondoker MR, Ivens A, Lynn DJ, Orme J, Jackson A, Lacaze P, Flanagan KL, Stenson BJ, Ghazal P.

Whole blood gene expression profiling of neonates with confirmed bacterial sepsis.

Genom Data. 2014 Nov 15;3:41-8. doi: 10.1016/j.gdata.2014.11.003. eCollection 2015.

Fatima A, Lynn DJ (Corresponding Author), O’Boyle P, Seoighe C, Morris D.

The miRNAome of the postpartum dairy cow liver under negative energy balance.

BMC Genomics. 2014 Apr 12;15:279. doi: 10.1186/1471-2164-15-279.

Lawless N, Reinhardt TA, Bryan K, Baker M, Pesch B, Zimmerman D, Zuelke K, Sonstegard T, O’Farrelly C, Lippolis JD, Lynn DJ (Corresponding Author).

MicroRNA regulation of bovine monocyte inflammatory and metabolic networks in an in vivo infection model.

G3 (Bethesda). 2014 Jan 27;4(6):957-71. doi: 10.1534/g3.113.009936.

Foroushani A, Brinkman FSL, Lynn DJ (Corresponding Author).

Pathway-GPS and SIGORA: Identifying relevant pathways based on the over-representation of their gene-pair signatures.

PeerJ. 2013 Dec 19;1:e229. doi: 10.7717/peerj.229. eCollection 2013.

Meredith BK, Berry DP, Kearney JF, Finlay EK, Fahey AG, Bradley DG, Lynn DJ (Corresponding Author).

A Genome-wide association study for somatic cell score using the illumina high-density bovine BeadChip identifies several novel QTL potentially related to mastitis susceptibility.

Front Genet. 2013 Nov 6;4:229. doi: 10.3389/fgene.2013.00229. eCollection 2013.

Lawless N, Foroushani AK, McCabe M, O’Farrelly C, Lynn DJ (Corresponding Author).

Next generation sequencing reveals the expression of a unique miRNA profile in response to a Gram-positive bacterial infection.

PLoS One. 2013;8(3):e57543. doi: 10.1371/journal.pone.0057543. Epub 2013 Mar 5.

Achtman AH, Pilat S, Law CW, Lynn DJ, Janot L, Mayer ML, Ma S, Kindrachuk J, Finlay BB, Brinkman FSL, Smyth GK, Hancock REW, Schofield L.

Effective adjunctive therapy by an innate defense regulatory Peptide in a preclinical model of severe malaria.

Sci Transl Med. 2012 May 23;4(135):135ra64. doi: 10.1126/scitranslmed.3003515.

Orchard S, Kerrien S, Abbani S, Aranda B, Bhate J, Bidwell S, Bridge A, Briganti L, Brinkman FS, Cesareni G, Chatr-aryamontri A, Chautard E, Chen C, Dumousseau M, Goll J, Hancock RE, Hannick LI, Jurisica I, Khadake J, Lynn DJ, Mahadevan U, Perfetto L, Raghunath A, Ricard-Blum S, Roechert B, Salwinski L, Stümpflen V, Tyers M, Uetz P, Xenarios I, Hermjakob H.

Protein Interaction Data Curation - The International Molecular Exchange Consortium (IMEx).

Nat Methods. 2012 Apr;9(4):345-50. doi: 10.1038/nmeth.1931.

Aranda B, Blankenburg H, Kerrien S, Brinkman FS, Ceol A, Chautard E, Dana JM, De Las Rivas J, Dumousseau M, Galeota E, Gaulton A, Goll J, Hancock RE, Isserlin R, Jimenez RC, Kerssemakers J, Khadake J, Lynn DJ, Michaut M, O'Kelly G, Ono K, Orchard S, Prieto C, Razick S, Rigina O, Salwinski L, Simonovic M, Velankar S, Winter A, Wu G, Bader GD, Cesareni G, Donaldson IM, Eisenberg D, Kleywegt GJ, Overington J, Ricard-Blum S, Tyers M, Albrecht M, Hermjakob H.

PSICQUIC and PSISCORE: accessing and scoring molecular interactions.

Nat Methods. 2011 Jun 29;8(7):528-9. doi: 10.1038/nmeth.1637.

The Bovine HapMap Consortium.

Genome wide survey of SNP variation uncovers the genetic structure of cattle breeds.

Science. 2009 Apr 24;324(5926):528-32. doi: 10.1126/science.1167936.

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