Contact

• workRoom D132 Queens Medical Centre
  Queen's Medical Centre
  Nottingham
  NG7 2UH
  UK
• work0115 82 30358
• matt.loose@nottingham.ac.uk
• http://www.mygrn.org/

Biography

BA University of Cambridge (Jesus) 1997, DPhil King's College, University of London 2002, Lecturer, Institute of Genetics 2002 - Present.

Research Summary

My lab is interested in the process of development and, ultimately, how cells are programmed to different phenotypes. We investigate these processes using a variety of approaches, including in vivo,… read more

Selected Publications

• EVANS T, WADE CM, CHAPMAN FA, JOHNSON AD and LOOSE M, 2014. Acquisition of germ plasm accelerates vertebrate evolution. Science (New York, N.Y.). 344(6180), 200-3
• SWIERS, G., CHEN, Y-H., JOHNSON, A.D. and LOOSE, M., 2010. A conserved mechanism for vertebrate mesoderm specification in urodele amphibians and mammals Developmental Biology. 343(1-2), 138-152
• BOKES, PAVOL, KING, JOHN R., WOOD, ANDREW T. A. and LOOSE, MATTHEW, 2012. Multiscale stochastic modelling of gene expression JOURNAL OF MATHEMATICAL BIOLOGY. 65(3), 493-520
• BROWN WRA, THOMAS G, LEE NCO, BLYTHE M, LITI G, WARRINGER J and LOOSE MW, 2014. Kinetochore assembly and heterochromatin formation occur autonomously in Schizosaccharomyces pombe. Proceedings of the National Academy of Sciences of the United States of America. 111(5), 1903-8

• View all publications

myGRN - my Gene Regulatory Network

We have developed an online database to store gene regulatory interactions, compile these into networks and dynamically draw networks in real time. Our database also facilitates network topology analysis, including searching for motifs (mfinder and our own custom algorithms) and curation of data from existing sources utilising chilibot.

Our database focuses on developmental regulatory networks and we have developed several custom views for facilitating the analysis of these networks. For example, genes can be automatically positioned according to the time and location in which they are expressed (see the image to the left). Alternatively, networks can be viewed based solely on the topology of the connections between individual genes (see image to the right).

Please contact us if you are interested in generating your own networks, making large interaction datasets available through our database, or working with us to further develop these tools.

Over the coming weeks, our previous networks will be transferred across into myGRN and made publicly available. For more information on myGRN visit www.myGRN.org

For reference, links to our previous network sites are maintained below.

_{A section of the erythroid lineage network.}

Genetic Regulatory Networks:

It is clear that events in the development of an organism occur in an ordered, organised and reproducible fashion. Unnderlying each step of external development is the structured expression of transcription factors, signals and targets. I am interested in uncovering and understanding these processes. How do complex networks of genes function together to regulate development?

We are currently working on three main areas, mesendoderm, hematopoiesis and lens development. In addition, we have generated networks for heart development. To explore further, please follow the links below.

The Mesendoderm Network Free Access

The mesendoderm network accompanies:

M. Loose and R. Patient (2004) A Genetic Regulatory Network for Xenopus Mesendoderm Formation. Developmental Biology 271, 469-480

Erythroid Lineage Programming and Development Free Access

The erythroid networks accompany:

G. Swiers, R. Patient and M. Loose (2006) Genetic regulatory networks programming hematopoietic stem cells and erythoid lineage specification. Developmental Biology, in press

The Lens Network (currently unavailable) (in collaboration with Seb Shimeld)

The Heart Network Free Access

The Heart Network accompanies:

T. Peterkin, A. Gibson, M. Loose and R. Patient (2005) The Roles of GATA 4, -5, and -6 in Vertebrate Heart Development. Seminars in Cell & Developmental Biology 16 (2005) 83-94

Many of the networks illustrated here were generated in collaboration with Prof Roger Patient at the MRC Molecular Hematology Unit, Oxford University.

Work in this laboratory is supported b

Current Research

My lab is interested in the process of development and, ultimately, how cells are programmed to different phenotypes. We investigate these processes using a variety of approaches, including in vivo, in vitro and in silico methods.

For information on compiling gene regulatory networks and to find out more about the tools we have developed, visit the 'Genetic Regulatory Network' pages or visit www.myGRN.org . An excellent and comprehensive review has ercently been published by Thomas Schlitt and Alvis Brazma - details available here.

Mesendoderm specification in amphibians.

The process of germ layer specification in Xenopus laevis has been extensively studied and a detailed picture describing the underlying genetic regulatory events is emerging. In part, this is a result of our work to deduce a GRN describing the specification of mesoderm and endoderm during early development ( Loose and Patient, 2004). This network, although incomplete as not all interactions have yet been experimentally verified, already appears highly complex (see below).

However, much of this complexity emerges from the existence of multiple copies of key developmental regulators, such as the genes of the Nodal and Mix families. We therefore reasoned this complexity results from sub-functionalisation.

One of the goals of systems biology is to make predictions about the behaviour of complex systems. In this case, the presence of multiple copies of the Nodal and Mix families makes such predictions complex. As a first step towards a predictive model of network function, we developed mathematical models describing a simplified version of this network. We simplified the network on the basis of the existence of only single copies of the Nodal and Mix gene in mouse and Human. In collaboration with John King, we developed a mathematical model of this network and demonstrated the underlying topology of the network is sufficient to generate both mesoderm and endoderm in response to changes in level of key upstream molecules. In this case, we mark mesoderm as Brachyury expressing and endoderm as Mix expressing cell types.

We would like to experimentally test predictions of this model, but our model is based on single genes, whilst Xenopus has multiple copies. Given that the mouse and human also have single copies of these genes, we asked if an alternative amphibian model existed with the experimental benefits of Xenopus but the simplicity of fewer genes.

A collaborator within the Institute of Genetics, Andrew Johnson, proposed that the axolotl, a urodele amphibian, is developmentally constrained by the requirement to induce germ cells. This constraint is relieved by pre-determined germ cells, where germ cell determinants (germ plasm) are deposited in the egg and distributed only to those cells that give rise to germ cells. Xenopus,

• RAMOS-IBEAS P, SANG F, ZHU Q, TANG WWC, WITHEY S, KLISCH D, WOOD L, LOOSE M, SURANI MA and ALBERIO R, 2019. Pluripotency and X chromosome dynamics revealed in pig pre-gastrulating embryos by single cell analysis. Nature communications. 10(1), 500
• SLOAN, TIM J., TURTON, JAMES C., TYSON, JESS, MUSGROVE, ALISON, FLEMING, VICKI M., LISTER, MICHELLE M., LOOSE, MATTHEW W., SOCKETT, R. ELIZABETH, DIGGLE, MATHEW, GAME, FRANCES L. and JEFFCOATE, WILLIAM, 2019. Examining diabetic heel ulcers through an ecological lens: microbial community dynamics associated with healing and infection JOURNAL OF MEDICAL MICROBIOLOGY. 68(2), 230-240
• WORKMAN, RACHAEL E, TANG, ALISON D, TANG, PAUL S, JAIN, MITEN, TYSON, JOHN R, RAZAGHI, ROHAM, ZUZARTE, PHILIP C, GILPATRICK, TIMOTHY, PAYNE, ALEXANDER, QUICK, JOSHUA, SADOWSKI, NORAH, HOLMES, NADINE, DE JESUS, JAQUELINE GOES, JONES, KAREN L, SOULETTE, CAMERON M, SNUTCH, TERRANCE P, LOMAN, NICHOLAS, PATEN, BENEDICT, LOOSE, MATTHEW, SIMPSON, JARED T, OLSEN, HUGH E, BROOKS, ANGELA N, AKESON, MARK and TIMP, WINSTON, 2019. Nanopore native RNA sequencing of a human poly(A) transcriptome. Nature methods. 16(12), 1297-1305
• WORKMAN, RACHAEL E, TANG, ALISON D, TANG, PAUL S, JAIN, MITEN, TYSON, JOHN R, RAZAGHI, ROHAM, ZUZARTE, PHILIP C, GILPATRICK, TIMOTHY, PAYNE, ALEXANDER, QUICK, JOSHUA, SADOWSKI, NORAH, HOLMES, NADINE, DE JESUS, JAQUELINE GOES, JONES, KAREN L, SOULETTE, CAMERON M, SNUTCH, TERRANCE P, LOMAN, NICHOLAS, PATEN, BENEDICT, LOOSE, MATTHEW, SIMPSON, JARED T, OLSEN, HUGH E, BROOKS, ANGELA N, AKESON, MARK and TIMP, WINSTON, 2019. Author Correction: Nanopore native RNA sequencing of a human poly(A) transcriptome. Nature methods.
• PAYNE, ALEXANDER, HOLMES, NADINE, RAKYAN, VARDHMAN and LOOSE, MATTHEW, 2019. BulkVis: a graphical viewer for Oxford nanopore bulk FAST5 files BIOINFORMATICS. 35(13), 2193-2198
• KOREN, SERGEY, PHILLIPPY, ADAM M., SIMPSON, JARED T., LOMAN, NICHOLAS J. and LOOSE, MATTHEW, 2019. Reply to 'Errors in long-read assemblies can critically affect protein prediction' NATURE BIOTECHNOLOGY. 37(2), 127-128
• EVANS T, D JOHNSON A and LOOSE M, 2018. Virtual Genome Walking across the 32 Gb Ambystoma mexicanum genome; assembling gene models and intronic sequence. Scientific reports. 8(1), 618
• JAIN M, KOREN S, MIGA KH, QUICK J, RAND AC, SASANI TA, TYSON JR, BEGGS AD, DILTHEY AT, FIDDES IT, MALLA S, MARRIOTT H, NIETO T, O'GRADY J, OLSEN HE, PEDERSEN BS, RHIE A, RICHARDSON H, QUINLAN AR, SNUTCH TP, TEE L, PATEN B, PHILLIPPY AM, SIMPSON JT, LOMAN NJ and LOOSE M, 2018. Nanopore sequencing and assembly of a human genome with ultra-long reads. Nature biotechnology. (In Press.)
• QUICK J, GRUBAUGH ND, PULLAN ST, CLARO IM, SMITH AD, GANGAVARAPU K, OLIVEIRA G, ROBLES-SIKISAKA R, ROGERS TF, BEUTLER NA, BURTON DR, LEWIS-XIMENEZ LL, DE JESUS JG, GIOVANETTI M, HILL SC, BLACK A, BEDFORD T, CARROLL MW, NUNES M, ALCANTARA LC, SABINO EC, BAYLIS SA, FARIA NR, LOOSE M, SIMPSON JT, PYBUS OG, ANDERSEN KG and LOMAN NJ, 2017. Multiplex PCR method for MinION and Illumina sequencing of Zika and other virus genomes directly from clinical samples. Nature protocols. 12(6), 1261-1276
• FARIA NR, QUICK J, CLARO IM, THÉZÉ J, DE JESUS JG, GIOVANETTI M, KRAEMER MUG, HILL SC, BLACK A, DA COSTA AC, FRANCO LC, SILVA SP, WU CH, RAGHWANI J, CAUCHEMEZ S, DU PLESSIS L, VEROTTI MP, DE OLIVEIRA WK, CARMO EH, COELHO GE, SANTELLI ACFS, VINHAL LC, HENRIQUES CM, SIMPSON JT, LOOSE M, ANDERSEN KG, GRUBAUGH ND, SOMASEKAR S, CHIU CY, MUÑOZ-MEDINA JE, GONZALEZ-BONILLA CR, ARIAS CF, LEWIS-XIMENEZ LL, BAYLIS SA, CHIEPPE AO, AGUIAR SF, FERNANDES CA, LEMOS PS, NASCIMENTO BLS, MONTEIRO HAO, SIQUEIRA IC, DE QUEIROZ MG, DE SOUZA TR, BEZERRA JF, LEMOS MR, PEREIRA GF, LOUDAL D, MOURA LC, DHALIA R, FRANÇA RF, MAGALHÃES T, MARQUES ET, JAENISCH T, WALLAU GL, DE LIMA MC, NASCIMENTO V, DE CERQUEIRA EM, DE LIMA MM, MASCARENHAS DL, NETO JPM, LEVIN AS, TOZETTO-MENDOZA TR, FONSECA SN, MENDES-CORREA MC, MILAGRES FP, SEGURADO A, HOLMES EC, RAMBAUT A, BEDFORD T, NUNES MRT, SABINO EC, ALCANTARA LCJ, LOMAN NJ and PYBUS OG, 2017. Establishment and cryptic transmission of Zika virus in Brazil and the Americas. Nature. (In Press.)
• VOTINTSEVA AA, BRADLEY P, PANKHURST L, DEL OJO ELIAS C, LOOSE M, NILGIRIWALA K, CHATTERJEE A, SMITH EG, SANDERSON N, WALKER TM, MORGAN MR, WYLLIE DH, WALKER AS, PETO TEA, CROOK DW and IQBAL Z, 2017. Same-Day Diagnostic and Surveillance Data for Tuberculosis via Whole-Genome Sequencing of Direct Respiratory Samples. Journal of clinical microbiology. 55(5), 1285-1298
• LOOSE MW, 2017. The potential impact of nanopore sequencing on human genetics. Human molecular genetics. 26(R2), R202-R207
• JAIN M, TYSON JR, LOOSE M, IP CLC, ECCLES DA, O'GRADY J, MALLA S, LEGGETT RM, WALLERMAN O, JANSEN HJ, ZALUNIN V, BIRNEY E, BROWN BL, SNUTCH TP, OLSEN HE and , 2017. MinION Analysis and Reference Consortium: Phase 2 data release and analysis of R9.0 chemistry. F1000Research. 6, 760
• BROWN, L. E., MIDDLETON, A. M., KING, J. R. and LOOSE, M., 2016. Multicellular Mathematical Modelling of Mesendoderm Formation in Amphibians Bull. Math. Biol..
• LOOSE M, MALLA S and STOUT M, 2016. Real-time selective sequencing using nanopore technology Nature Methods.
• LOOSE M, MALLA S and STOUT M, 2016. Real-time selective sequencing using nanopore technology. Nature methods. 13(9), 751-4
• BATES, MATTHEW, POLEPOLE, PASCAL, KAPATA, NATHAN, LOOSE, MATT and O'GRADY, JUSTIN, 2016. Application of highly portable MinION nanopore sequencing technology for the monitoring of nosocomial tuberculosis infection. International journal of mycobacteriology. 5 Suppl 1, S24
• EVANS, T. and LOOSE, M., 2015. AlignWise: a tool for identifying protein-coding sequence and correcting frame-shifts BMC Bioinformatics. 16, 376
• IP, C. L., LOOSE, M., TYSON, J. R., DE CESARE, M., BROWN, B. L., JAIN, M., LEGGETT, R. M., ECCLES, D. A., ZALUNIN, V., URBAN, J. M., PIAZZA, P., BOWDEN, R. J., PATEN, B., MWAIGWISYA, S., BATTY, E. M., SIMPSON, J. T., SNUTCH, T. P., BIRNEY, E., BUCK, D., GOODWIN, S., JANSEN, H. J., O'GRADY, J. and OLSEN, H. E., 2015. MinION Analysis and Reference Consortium: Phase 1 data release and analysis F1000Res. 4, 1075
• LOMAN, NICK, GOODWIN, SARAH, JANSEN, HANS and LOOSE, MATT, 2015. A disruptive sequencer meets disruptive publishing. F1000Research. 4, 1074
• BROWN WRA, THOMAS G, LEE NCO, BLYTHE M, LITI G, WARRINGER J and LOOSE MW, 2014. Kinetochore assembly and heterochromatin formation occur autonomously in Schizosaccharomyces pombe. Proceedings of the National Academy of Sciences of the United States of America. 111(5), 1903-8
• EVANS T, WADE CM, CHAPMAN FA, JOHNSON AD and LOOSE M, 2014. Acquisition of germ plasm accelerates vertebrate evolution. Science (New York, N.Y.). 344(6180), 200-3
• CHATFIELD J, O'REILLY M, BACHVAROVA RF, FERJENTSIK Z, REDWOOD C, WALMSLEY M, PATIENT R, LOOSE M and JOHNSON AD, 2014. Stochastic specification of primordial germ cells from mesoderm precursors in axolotl embryos. Development (Cambridge, England). 141(12), 2429-40
• WHELDON LM, ABAKIR A, FERJENTSIK Z, DUDNAKOVA T, STROHBUECKER S, CHRISTIE D, DAI N, GUAN S, FOSTER JM, CORRÊA IR, LOOSE M, DIXON JE, SOTTILE V, JOHNSON AD and RUZOV A, 2014. Transient accumulation of 5-carboxylcytosine indicates involvement of active demethylation in lineage specification of neural stem cells. Cell reports. 7(5), 1353-61
• CHEN, WEI-CHUNG, PAULS, STEFAN, BACHA, JAMIL, ELGAR, GREG, LOOSE, MATTHEW and SHIMELD, SEBASTIAN M., 2014. Dissection of a Ciona regulatory element reveals complexity of cross-species enhancer activity DEVELOPMENTAL BIOLOGY. 390(2), 261-272
• BROWN LE, KING JR and LOOSE M, 2014. Two different network topologies yield bistability in models of mesoderm and anterior mesendoderm specification in amphibians. Journal of theoretical biology. 353C, 67-77 (In Press.)
• P. BOKES, J. R. KING, A. T. A. WOOD and M. LOOSE, 2013. Transcriptional bursting diversifies the behaviour of a toggle switch: hybrid simulation of stochastic gene expression Bulletin of Mathematical Biology. 75, 351-371
• LOOSE M, PATIENT R, FANG X and LEI H, 2013. Gene regulatory networks in the genomics era. Genomics, proteomics & bioinformatics. 11(3), 133-4
• MIDDLETON AM, KING JR and LOOSE M, 2013. Wave pinning and spatial patterning in a mathematical model of Antivin/Lefty-Nodal signalling. Journal of mathematical biology. 67(6-7), 1393-424
• ALMEIDA, R.D., LOOSE, M., SOTTILE, V., MATSA, E., DENNING, C., YOUNG, L., JOHNSON, A.D., GERING, M. and RUZOV, A., 2012. 5-hydroxymethyl-cytosine enrichment of non-committed cells is not a universal feature of vertebrate development Epigenetics. 7(4), 383-389
• ALMEIDA, R.D., SOTTILE, V., LOOSE, M., DE SOUSA, P.A., JOHNSON, A.D. and RUZOV, A., 2012. Semi-quantitative immunohistochemical detection of 5-hydroxymethyl-cytosine reveals conservation of its tissue distribution between amphibians and mammals Epigenetics. 7(2), 137-140
• BOKES, PAVOL, KING, JOHN R., WOOD, ANDREW T. A. and LOOSE, MATTHEW, 2012. Multiscale stochastic modelling of gene expression JOURNAL OF MATHEMATICAL BIOLOGY. 65(3), 493-520
• BOKES, P., KING, J.R., WOOD, A.T.A. and LOOSE, M., 2012. Exact and approximate distributions of protein and mRNA levels in the low-copy regime of gene expression Journal of Mathematical Biology. 64(5), 829-854
• SWIERS, G., CHEN, Y-H., JOHNSON, A.D. and LOOSE, M., 2010. A conserved mechanism for vertebrate mesoderm specification in urodele amphibians and mammals Developmental Biology. 343(1-2), 138-152
• D. DE POMERAI1, C. ANBALAGAN1, I. LAFAYETTE1, D. RAJAGOPALAN1, M. LOOSE1, M. HAQUE2 & J. KING2, 2010. High-throughput analysis of multiple stress pathways using GFP reporters in C. elegans.. In: Environmental Toxicology III Wessex Institute for Technology Press. (In Press.)
• BACHA, J., BRODIE, J.S. and LOOSE, M.W., 2009. myGRN: a database and visualisation system for the storage and analysis of developmental genetic regulatory networks BMC Developmental Biology. 9, 33
• MIDDLETON, A.M., KING, J.R. and LOOSE, M., 2009. Bistability in a model of mesoderm and anterior mesendoderm specification in Xenopus laevis. Journal of Theoretical Biology. 260(1), 41-55
• COOPER, M.B, LOOSE, M and BROOKFIELD, J.F.Y., 2009. The evolutionary influence of binding site organization on gene regulatory networks. Biosystems. 96, 185-93
• BOKES, P, KING, J and LOOSE, M., 2008. A bistable genetic switch which does not require high cooperativity at the promoter: a two-timescale model for the PU.1 - GATA-1 interaction Mathematical Medicine & Biology. (In Press.)
• DE POMERAI, D, MADHAMSHETTIWAR, P, ANBALAGAN, C, LOOSE, M, HAQUE, M, KING, J, CHOWDHURI, D.K, SINHA, P, JOHNSEN, B and BAILLIE, D., 2008. The stress-response network in animals: proposals to develop a predictive mathematical model. Open Toxicology Journal. 2, 71-76
• LOOSE,M,, SWIERS,G, and PATIENT,R, 2007. Transcriptional networks regulating hematopoietic cell fate decisions Current Opinion in Hematology. (In Press.)
• SMITH, J,, LOOSE, M,, WARDLE, F,, STANLEY, E, and PATIENT, R,, 2007. Germ Layer Induction in ESC – Following the Vertebrate Roadmap. In: BHATIA, M,, EGGAN, K,, ELEFANTY, A,, FISHER, S,, PATIENT, R, and PERA, M,, eds., Current Protocols in Stem Cell Biology Wiley. (In Press.)
• SONEJI S, HUANG S, LOOSE M, DONALDSON IJ, PATIENT R, GOTTGENS B, ENVER T, MAY G., 2007. Inference, validation and dynamic modelling of transcription networks in multipotent hematopoietic cells. Ann N Y Acad Sci. (In Press.)
• COOPER, M., LOOSE, M. and BROOKFIELD, J.F.Y., 2007. Evolutionary modelling of feed forward loops in gene regulatory networks. Biosystems Elsevier. Available at: <http://dx.doi.org/10.1016/j.biosystems.2007.09.004>
• LOOSE, M. and PATIENT, R., 2006. Global genetic regulatory networks controlling hematopoietic cell fates Current Opinion in Hematology. 13(4), 229-236
• SWIERS, G., PATIENT, R. and LOOSE, M., 2006. Genetic regulatory networks programming hematopoietic stem cells and erythroid lineage specification Developmental Biology. 294(2), 525-540
• PETERKIN, T., GIBSON, A., LOOSE, M. and PATIENT, R., 2005. The roles of GATA-4, -5 and -6 in vertebrate heart development Seminars in Cell & Developmental Biology. 16(1), 83-94
• LOOSE, M. and PATIENT, R., 2004. A genetic regulatory network for Xenopus mesendoderm formation Developmental Biology. 271(2), 467-478