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Matt Loose

Professor of Developmental and Computational Biology, Faculty of Medicine & Health Sciences

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Biography

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

Expertise Summary

Matt Loose (ML) began his career as a developmental biologist studying the early events of gastrulation and germ layer specification. This led to an interest in deciphering the gene regulatory networks (GRNs) controlling mechanisms of development, initially in Xenopus but then axolotl embryos. ML has established a track record in computational biology, developing mathematical models to predict behavior of GRNs for vertebrate development. It became clear that much could be learned about developmental processes in other systems by studying the Axolotl. However, the absence of a reference genome presented a fundamental challenge. To circumvent this, ML worked to create comprehensive transcriptome resources for the axolotl and used these data to reveal an accelerated evolution of sequences in species utilising germ plasm, a property of frog not salamander embryos (Science, 2014). To develop the skills necessary for interpreting and analyzing large genomes, ML has explored a wide range of bioinformatic challenges and approaches with papers studying a broad range of model systems, from yeast to Ciona to amphibians.

Recognizing that large repeat rich genomes, such as that of the axolotl, would be best served by long read technologies, ML dedicated significant time and energy to the development of tools and techniques for the analysis of long-read nanopore sequence data, including the 'read until' feature enabling selective sequencing of specific regions of DNA directly on the device (Nature Methods 2016). ML was the first to implement this process and demonstrate the feasibility of the method. This has led to an ongoing collaboration with Oxford Nanopore to develop rapid, high throughput, selective sequencing methods (Nature Biotechnology, 2020). To demonstrate the feasibility of this sequencer for large genomes, ML was a key member of the Nanopore WGS consortium, which released the first 35x coverage dataset of the NA12878 Human Reference Genome sequence and RNA datasets (Nature Biotechnology 2018, Nature Methods 2019). ML has also developed new long-read methods for Nanopore sequencing enabling high-throughput ultra-long sequencing (https://www.protocols.io/view/findingnemo-a-toolkit-of-cohex-and-glass-bead-base-bxwrppd6).

Alongside this, ML runs the DeepSeq High Throughput Sequencing Centre at The University of Nottingham, leads the Midlands Sequencing Consortium and is a committee member of the yearly UK Genome Science meeting. ML is a founder and instructor on 'Porecamp', a training program for minION sequencing which has been run in the UK, USA and Canada. During the COVID-19 pandemic ML also served as the PI for the University of Nottingham as part of COG-UK as well as the UK Wastewater Sequencing Consortium, contributing in excess of 20,000 samples to date. ML has recently been working to establish rapid access to nanopore sequencing to facilitate the diagnosis of CNS tumours. This has led to the development of ROBIN - Rapid nanopOre Brain intraoperatIve classificatioN - a tool to allow classification of CNS tumours very quickly, with the goal of providing results to the clinicians prior to the next multi-disciplinary team meeting. At its fastest, this method can diagnose brain tumours during surgery. See this BBC news article for more detail.

Research Summary

Currently, my lab's work sits at the intersection of genomic technology development, large-scale data science, and applied biomedical research. A major focus in recent years has been leveraging our… read more

Selected Publications

Current Research

Currently, my lab's work sits at the intersection of genomic technology development, large-scale data science, and applied biomedical research. A major focus in recent years has been leveraging our sequencing innovations to address urgent real-world challenges. In early 2020, when the COVID-19 pandemic hit, I led our DeepSeq genomics facility to pivot rapidly into pandemic response. We joined the national COVID-19 Genomics UK Consortium (COG-UK) and began real-time sequencing of SARS-CoV-2 virus genomes . This effort turned our lab into part of a nationwide surveillance network: by August 2021 we had sequenced over 10,000 coronavirus samples, helping public health officials track the spread and mutation of the virus in near real-time . In total, as the university's principal investigator for COG-UK, I oversaw contributions of more than 20,000 viral genomes to the project's databases . We also spearheaded a novel wastewater sequencing program as part of a national consortium, detecting COVID-19 outbreaks by sequencing sewage samples . This approach allowed us to monitor entire communities non-invasively - we could identify emerging variants and localized surges even before clinical testing caught them, providing a powerful early warning system for public health . Throughout this period, I continued to advance our sequencing toolkit. For example, my team developed ReadFish, an open-source software for nanopore adaptive sampling that lets us enrich target regions on the fly; this tool was so successful that it has been incorporated into Oxford Nanopore's official operating software to enable selective sequencing at scale . In parallel, we optimized protocols for ultra-long DNA reads and high-throughput processing, ensuring that our facility remained at the forefront of genomics technology. In summary, a large part of my current research has been about responding to global challenges with genomics - building the infrastructure, algorithms, and collaborative networks needed to make sequencing data actionable for society.

Concurrently, I am translating these technological advances into new biological and medical insights. One flagship project in my lab right now is the development of an ultra-rapid genomic test for brain tumors, in close collaboration with clinicians at Nottingham's hospitals. We've harnessed the speed of nanopore sequencing and our expertise in selective genome analysis to create a pipeline (including a software tool called "ROBIN") that can identify the DNA methylation and mutation profile of a brain tumor within hours of surgery . In practice, once a surgeon removes a tumor sample, our team extracts the DNA and uses nanopore sequencers to zoom in on key genetic regions that define the tumor type . Thanks to adaptive sequencing, we sequence those regions at high depth in real time, and our software compares the read-out against a reference database of tumor molecular profiles. The result is that we can provide a detailed genetic diagnosis before the patient has even left the operating theatre. In a recent trial of 50 patients, this method achieved a 100% success rate in correctly classifying brain tumors, with most patients receiving at least a preliminary result in under one hour and a full molecular diagnosis within 24 hours . This is a dramatic improvement over the conventional pathway, where patients often wait 6-8 weeks for genetic test results on their tumor . Our 2025 paper in Neuro-Oncology reported these findings, and the work has attracted attention in the press for its potential to revolutionize cancer care by cutting diagnosis times from months to mere hours . More importantly, it opens the door for faster treatment decisions - in principle, surgeons could know the tumor type while the patient is still under anesthesia and adjust the surgical approach on the spot. It has been incredibly rewarding to see how a technology my team pioneered (real-time nanopore sequencing) can directly impact patient care. Beyond this headline project, my group remains deeply involved in fundamental research and cross-disciplinary collaborations. For instance, we are applying our sequencing methods in developmental biology studies - recently, we helped generate a single-cell atlas of early pig embryos to compare developmental programs across species , which ties back to my long-standing interest in how different animals orchestrate the formation of tissues and organs. We are also working with plant scientists and ecologists: our sequencing platform has been used to assemble and analyze complex plant genomes (we contributed to a study on how whole-genome duplication affects genome variation in wild plants) , and to track pathogens in agricultural settings. By engaging in these diverse projects, my current research agenda combines high-impact, translational efforts (like the brain tumor diagnostics and infectious disease genomics) with exploratory science aimed at understanding life's complexity, all unified by the theme of applying innovative genomic tools to important problems.

Past Research

In the early part of my career, I established myself as a developmental biologist, focusing on how embryos form their basic body plan. I investigated the early events of gastrulation and germ layer formation in animal models like the frog Xenopus and the salamander axolotl, working to decipher the gene regulatory networks that guide cells into different fates. This led me to develop computational models of these genetic networks to predict how complex interactions drive embryonic development . One highlight was our discovery that the way germ cells are specified can dramatically affect evolution: by creating genomic resources for the axolotl and comparing it to frog, we found that species which use germ plasm (a special material in the egg that pre-determines germ cells) have a faster rate of genetic evolution than those that don't. For example, frogs (which have germ plasm) accumulate DNA changes more rapidly than salamanders (which rely on inductive signals), supporting the idea that embryological mechanisms can influence how quickly species diversify . This work, published in Science in 2014, provided a new perspective on the links between development and evolution. I also explored fundamental developmental processes across species - for instance, demonstrating that certain molecular mechanisms of mesoderm formation are highly conserved from amphibians to mammals - which underscored the deep evolutionary unity in how vertebrate embryos pattern their basic tissues.

As my research progressed, I confronted the practical challenges of working with emerging model organisms and big genomes. The axolotl, with its enormous genome, was a promising model for studying regeneration and development, but its size and repetitive content made it difficult to analyze with standard methods . This realization pushed me into the realm of genomics technology. I dedicated significant effort to advancing long-read DNA sequencing techniques, particularly using Oxford Nanopore's platforms, which can read very large DNA molecules. In 2016, my lab pioneered the "read-until" method - a form of adaptive sequencing where the device can selectively enrich for sequences of interest in real time . I was the first to implement this selective sequencing approach on a nanopore device, proving that we could actively target specific genes or regions and stop sequencing others on the fly . This breakthrough (reported in Nature Methods 2016) opened the door to much more efficient genomic analyses. It also led to an ongoing collaboration with Oxford Nanopore Technologies to refine rapid, high-throughput selective sequencing methods , culminating in new protocols we reported by 2020. Additionally, I became a key member of the international Nanopore Whole-Genome Sequencing Consortium, which in 2018 demonstrated the power of nanopore sequencing by releasing one of the first near-complete human genomes (35× coverage of the reference NA12878) using this technology. By 2019, my research interests spanned from fundamental biology to tool development - I had one foot in embryology and evolution and the other in cutting-edge genomics. This dual path in my "past research" laid a strong foundation, equipping me with both biological insight and technical expertise to tackle complex scientific questions.

Future Research

Looking ahead, I am excited to build on these foundations and push my research in several complementary directions. One major goal is to expand our ultra-rapid sequencing diagnostics into broader clinical use. We are now working to roll out the nanopore-based brain tumor test across hospitals in the UK, in hopes that it can become a routine part of patient care . In the near future, I plan to adapt this platform to other cancers and even infectious diseases - essentially, anywhere a quick genetic read-out could save critical time in treatment decisions. A longer-term vision is to integrate real-time genomic analysis with therapy: if we can identify a pathogen or tumor subtype within minutes, the next step is to link that information to an immediate intervention. For example, I foresee a scenario (entirely plausible with further research) where during surgery we not only diagnose a brain tumor on the fly but also deliver a tailored drug to the tumor before the operation concludes . Achieving this will require even faster sequencing workflows, robust automated analysis, and close partnership with clinicians and pharmacologists. Thus, a significant part of my future research will be devoted to pushing the limits of sequencing technology - making it more sensitive, more selective, and above all quicker - and developing the computational pipelines to act on genomic data in real time. I will continue collaborating with industry (such as Oxford Nanopore) and national initiatives to bring about the next generation of sequencing devices and protocols. By staying at the cutting edge of technology, I aim to ensure that our genomic tools can truly become bedside tools, enabling what I like to think of as "genomics-guided medicine" in real clinical settings.

World-class research at the University of Nottingham

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