Trypanosome parasites are spread between humans and other mammals by biting insects, and cause three World Health Organisation designated Neglected Tropical Diseases: African trypanosomiasis (Trypanosoma brucei), Chagas disease (Trypanosoma cruzi) and Leishmaniasis (Leishmania species), together responsible for over 8 million cases each year. Cases of human African trypanosomiasis have decreased from epidemic levels in the 1990's due to sustained surveillance and control programmes. Yet, T. brucei is still endemic in 36 countries and highly prevalent in livestock animals, where it causes an additional economic burden. Understanding the mechanisms these parasites use to proliferate and transmit between hosts is essential to meet the WHO's aims of eliminating African trypanosomiasis as a public health problem by 2030. Like all eukaryotic cells, trypanosomes undergo the tightly regulated cell cycle to divide and multiple. Critically, only trypanosome parasites that stop dividing in the insect mouthparts and preadapt to survive in the mammal are able to infect a new host when vector insects take a bloodmeal. Once injected into the skin and bloodstream, these parasites start rapidly dividing again and spread to various host tissues causing disease. In the case of T. brucei, a mirrored process occurs where some parasites in the human undergo cell cycle arrest and prepare for transmission back to the tsetse flies, which spread them to new hosts across sub-Saharan Africa. When arrested parasites are ingested by a tsetse fly, they being proliferating again to complete the life cycle. Additionally, some Trypanosoma and Leishmania species appear to arrest and persist as dormant forms in mammals for long periods of time without detection by the immune system and may escape treatment. The mechanisms controlling whether trypanosomes continue to divide or arrest are, therefore, highly integral to both the survival and spread of these destructive parasites. Despite its importance, we have virtually no understanding of how or where these processes are regulated, not least because current assays are unable to efficiently discriminate the cell division cycle stages. Using Trypanosoma brucei, I will address three fundamental questions: which genes control whether T. brucei divides or arrests; where in the mammal and tsetse fly are the dividing and arrested forms found; and is cell-cycle-arrest required for transmission? To achieve this, I will take advantage of the amenability of T. brucei to genetic manipulation. I will engineer a novel fluorescent parasite line that will change fluorescent colour as they progress through the different stages of the cell cycle, or stop fluorescing when arrested. The changes in fluorescence can be easily and quickly tracked using both microscopy and flow cytometry, a method which can detect fluorescence of thousands of cells in seconds. Using this approach I will, firstly, perform a targeted gene silencing screen of hundreds of genes to identify those needed to either drive or repress cell division. Secondly, I will track the cell cycle changes of parasites in the different mammal and tsetse fly tissues. Finally, I will test whether preventing cell-cycle-arrest by gene silencing, also prevents T. brucei completing its life cycle in the mammal and tsetse fly. Together, this work will reveal how T. brucei directs its intricate transmission cycles to spread disease, findings that will then be extended to related trypanosomatid parasites. Ultimately, the cell-cycle-regulating proteins identified will be assessed as potential therapeutic drug targets for the treatment of trypanosome diseases.

The role of balancing selection (BS) is a long-standing evolutionary puzzle. The emergence of advanced genomic techniques has furnished researchers with enormous datasets, revitalising the exploration of this topic. Unlike directional selection that propels advantageous alleles to dominance, BS encompasses a spectrum of phenomena that sustains genetic variation in populations across extended periods. BS is of particular interest within the realm of immune function genes and host-parasite interactions in multiple organisms. In insect research, there is a noteworthy surge in interest regarding sexual antagonism levels and the genes associated with sex determination. Detecting BS is known to be a challenging problem that is often entangled with the effects of linkage disequilibrium (LD). LD refers to the inheritance of genome sections as units, leading to interconnections between genetic sites. It is possible to simulate both phenomena using ancestral recombination graphs (ARGs) generated in the forward simulation framework SLiM, however, inference frameworks often struggle to disentangle both effects. The integration of simulation data with Deep Learning (DL) algorithms in evolutionary biology has recently provided a means to account for these intertwined effects, while also enabling efficient parameter estimation. Notably, algorithms powered by Artificial Intelligence (AI) possess the computational power required to navigate the intricate genomic dependencies arising from the linkage. Our objective is to tackle this challenge by incorporating the interplay between genomic positions and BS using a mechanistic framework. We will investigate the accuracy of BS inference in the presence of LD. Our strategy consists of simulating genomic segments combining both effects and utilising a method for detecting BS, augmented by Machine Learning (ML) algorithms capable of simultaneously handling multiple genomic regions, to perform the inference. This investigation will shed light on the robustness and reliability of BS detection when LD is considered. To achieve this, we will construct a deep learning approach capable of (i) classifying the presence of BS, (ii) determining the best-fitting models among those with and without selection, and (iii) estimating selection parameters while accounting for linkage. We will use an approach developed in our group, Polymorphism-aware phylogenetic models (PoMos), which integrate the timescales of population genetic processes and phylogenetic divergence data. In particular, we will build on the recent development by research fellow and co-investigator Svitlana Braichenko to detect signatures of balancing selection (PoMoBalance). We will combine it with the model selection framework for AI proposed by Olivier Gascuel group based at the Paris Artificial Intelligence Research Institute (PRAIRIE), France. Furthermore, we will collaborate with the Adam Siepel group from Cold Spring Harbor Laboratories (CSHL), US with experience of generating ARGs data with forward simulations (SLiM) to train our new deep-learning approach. Our framework will be tested on simulated data and real sequences extracted from the great ape and fruit fly whole genome datasets.

DNA, the blueprint of life, is found within 46 chromosomes in every human cell; if stretched out end to end, it would measure two metres in length. In order for these 46 chromosomes to fit into the "control-room" of every cell, known as the nucleus, the DNA must be very tightly packaged. This is achieved by wrapping the DNA around the surface of special proteins, called histones, that are spaced regularly along the DNA like beads on a string. Each DNA-histone bead is known as a nucleosome and each nucleosome is able to pack very closely against its neighbours to form highly compact fibres called chromatin. Although chromatin fibers are very good at compacting DNA into small spaces, they are poor at allowing other proteins access to the DNA. Many normal processes in the cell involve proteins binding to DNA, such as when genes are decoded to make protein, when chromosomes are replicated prior to cell division, and when special repair proteins are called upon to fix sites of DNA damage. Consequently, complicated organisms like humans, with highly packaged DNA, have had to develop specialized machinery for opening chromatin at very specific regions of the chromosome. This machinery includes a large number of specialized proteins. One group of proteins, known as chromatin remodelling complexes (CRCs), help to expose DNA by using energy to slide or remove nucleosomes within chromatin. CRCs are protein machines, much larger than a single nucleosome, and made up of proteins responsible for recruitment to the correct chromosome region, binding to nucleosomes, or helping to generate the force required for nucleosome sliding or removal. Multiple different CRCs exist in human cells, each made up of similar proteins that can interact with chromatin in subtly different ways or target the complex to different regions of the chromosome. The recruitment of a CRC to the start of a gene is an important early step in the process of turning on, or activating, that gene. If the cell makes a mistake, failing to recruit CRCs to their correct sites or instead recruiting those complexes to the wrong set of genes, then a dangerous cascade can result in the loss of control of normal cell events such as cell division and death. This type of gene dysregulation takes place at an early stage in the development of every human cancer. Over the past decade, advances in DNA sequencing technology have allowed scientists to identify mistakes in the DNA code, known as DNA mutations, that are found in many types of human cancer. A surprising finding from these studies was that DNA mutations leading to the loss of protein components from one single CRC, known as the BAF complex, are present in as many as 20% of all human cancers. Further investigations showed that DNA mutations altering the BAF complex cause many normal target genes to be switched off whereas new and inappropriate genes often become active. Although the BAF complex is very often the target of mutations in cancer, surprisingly little is currently known about this important machine, with many questions still unaddressed. For example, how are the different proteins organized in the BAF complex? What roles do the different proteins play in the recruitment of the complex to the correct target genes? How does the BAF complex interact with nucleosomes? How does BAF use energy to bring about nucleosome sliding or eviction? The overarching goal of my future research will be to address these questions using a repertoire of cutting-edge structural biology techniques such as cryo-electron microscopy, protein cross-linking, X-ray crystallography and computational modelling, in order to provide a detailed description of the organization, recruitment and remodelling activity of this important human complex. Such findings will provide a framework for understanding the molecular basis of BAF complex dysregulation, with broad implications for the future treatment of many human cancers.

France

Every human cell is encased by a cell membrane that separates the cell contents from its surroundings. Proteins embedded in this membrane act as gates to allow molecules to enter and exit cells; they also mediate the interactions that occur between a cell and its environment. This means that membrane proteins are involved in many of the most fundamental processes in normal cell function; when these processes fail, diseases result. It is no surprise, then, that the top ten best-selling small molecule drugs of all time all target membrane proteins. There are many different membrane proteins in any given cell, grouped into over 1,500 families, each with many members. In order to study any of them in detail, it is important to understand their three-dimensional structures. Central to this is a technique called X-ray crystallography that allows scientists to obtain a detailed view of how the atoms within a protein are arranged, providing a framework for further study. Scientists use this framework to investigate how the protein functions, bringing new levels of understanding to how cells work in health and disease, and providing knowledge to develop new drugs. Tetraspanins are membrane proteins that function by interacting with a wide range of other membrane and soluble proteins, thereby affecting how cells signal, interact, change shape and move. Remarkably, tetraspanins are also involved in the process of infection for a wide range of diseases. However, because there is no known structure of any full-length tetraspanin family member, the mode of action of tetraspanins in these essential processes is not understood, leaving a major gap in our knowledge of cell biology. Obtaining the structure of any membrane protein is a major scientific challenge: It is necessary to remove the protein from the cell membrane which often results in the protein becoming so unstable that it cannot be used to make the crystals required to perform X-ray crystallography. Consequently, we know very little about many membrane protein families with important biological functions. We have now overcome this crystallization challenge for the tetraspanin, CD81. Human CD81 is one of the best understood tetraspanin family members and is the subject of our proposed research. It has well-established roles in how cells interact with each other, the immune response and fertilization. Notably CD81 is a receptor for some very important human pathogens including influenza, human immunodeficiency virus, the malarial parasite, T-cell lymphotropic virus type 1 and hepatitis C virus (HCV). It may also be a tumour promoter. Central to CD81 function (and to that of all tetraspanins) is its ability to form extensive interactions with itself and other proteins; however, we don't know what these structures look like and therefore lack the framework for further study, mentioned above. The first aim of the research outlined in our proposal is to solve the three-dimensional structure of CD81. We have made excellent progress towards this goal, having crystallized CD81 and collected X-ray diffraction data. We have also teamed up with scientists in France who can make soluble forms of the HCV protein, E2, that binds CD81. The second aim of our project is to make an HCV-E2/CD81 complex so we can characterize it and solve its structure; this will allow us to learn more about how CD81 interacts with other proteins. We believe we are the only team in the world that has all the tools to take on this challenge. Brand new developments in structural biology (e.g. high-resolution electron microscopy) have enabled us to devise a third aim, which is to look at these structures in the cell membrane (by electron tomography), linking our atomic level structural data to what is actually happening in the cell. Studying the structure of CD81 at this level of detail will allow us to begin to understand how tetraspanins work in health and disease.