Biology subjects

Burt, A.

Publications and source records attributed to Burt, A..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Human spermatogenesis leads to a reduced nuclear pore structure and function

Nuclear pore complexes (NPCs) are nuclear gateways which regulate the transit of molecules larger than 40kDa through a Ran-dependent transport1. The somatic human NPC scaffold consists of three stacked rings: the cytoplasmic (CR), the nucleoplasmic (NR), and the inner ring (IR), which define a central channel approximately 55nm wide2. Although many studies have investigated human NPC architecture3, it remains largely unknown how the NPC accommodates the different functions of non-somatic cells. Here, we reveal the in-cell architecture of the human sperm NPC. We show that it exhibits a central channel less than 40nm-wide, outlined exclusively by the IR. This structural alteration is accompanied by a six-fold reduction in nuclear diffusion rate and mis-localization of Ran-dependent transport components. Additionally, we identify a network of septin filaments interconnecting NPCs within the inter-membrane space of the nuclear envelope (NE), suggesting a potential mechanical role in channel constriction. Furthermore, our human tissue imaging data indicate meiosis as a pivotal differentiation stage driving architectural changes to the NPC. Given the critical role of the IR for successful spermatogenesis4,5, our work offers important insight into this fundamental biological process. Our study also demonstrates the power of an integrative approach by combining electron-cryo- tomography, super-resolution-light-microscopy and biochemical analysis, to elucidate macromolecular structure-function relations in human physiological contexts.

cell biology↗

bioRxiv2024

Engineering Resilient Gene Drives Towards Sustainable Malaria Control: Predicting, Testing and Overcoming Target Site Resistance

CRISPR-based gene drives are selfish genetic elements with the potential to spread through entire insect populations for sustainable vector control. Gene drives designed to disrupt the reproductive capacity of females can suppress laboratory populations of the malaria mosquito. However, any suppressive intervention will inevitably exert an evolutionary pressure for resistance. Here, we present a pipeline for the accelerated discovery, engineering, and testing of both natural and drive-induced variants that could reverse gene drive spread. We applied our method to stress-test a highly effective gene drive that has evaded resistance in all laboratory-contained releases to date, known as Ag(QFS)1. We showed that previously undetected resistant alleles can arise at low frequency, and discovered novel, partially resistant alleles that can perturb drive-invasion dynamics. We then engineered next-generation gene drives that can actively remove resistant alleles by targeting several highly conserved and non-overlapping sites in the female-specific exon of the doublesex gene. Our models predict that such gene drive designs could suppress large, natural populations of the malaria mosquito in the field.

synthetic biology↗

bioRxiv2024

Engineering drive-selection balance for localised population suppression with neutral dynamics

Whilst the release of sterile males has been highly successful in suppressing some pest populations, it is impractical for other species due to the males disappearing after a single generation, necessitating large, repeated releases to maintain sufficient impact. Synthetic gene drives promise more efficient approaches since they can increase in frequency from rare, yet this also allows them to spread across a landscape, which may not always be desired. Between these two extremes are selectively neutral genetic constructs which persist at the frequency they are released, offering the potential for efficient suppression that remains localised. One way to achieve this would be to have perfect balance, at all construct frequencies, between gene drive increasing frequency and selection decreasing it. Here we describe a way to create this balance involving a toxin-antidote genetic construct that causes recessive lethality, encodes a genomic editor that makes dominant lethal edits in the genome, and provides protection against the action or consequences of the editing. Computer modelling shows that this design can be 100-fold more efficient than sterile males, increasing to 1000-fold more when released alongside a genetic booster. We describe designs for CRISPR-based molecular construction, including options that avoid using recoded genes as antidotes.

synthetic biology↗

bioRxiv2024

A Y chromosome-linked genome editor for efficient population suppression in the malaria vector Anopheles gambiae

Genetic control - the deliberate introduction of genetic traits to control a pest or vector population - offers a powerful tool to augment conventional mosquito control tools that have been successful in reducing malaria burden but that are compromised by a range of operational challenges. Self-sustaining genetic control strategies have shown great potential in laboratory settings but hesitancy due to their invasive and persistent nature may delay their implementation. Here instead we describe a self-limiting strategy, designed to have geographically and/or temporally restricted effect, based on a Y chromosome-linked genome editor (YLE). The YLE comprises a CRISPR-Cas9 construct that is always inherited by males yet generates an autosomal dominant mutation that is transmitted to over 90% of the offspring and results in female-specific sterility. Males are unaffected. To our knowledge, our system represents the first engineering of the Y chromosome to generate a genetic control strain for mosquitoes. Mathematical modelling shows that this YLE technology is up to 8 times more efficient for population suppression than optimal versions of other self-limiting strategies.

synthetic biology↗

bioRxiv2024

Tree Surface Area Allometry

Utilizing terrestrial laser scanning (TLS) and three-dimensional modeling, this study quantitatively assessed the woody surface areas of 2161 trees across ecosystems encompassing both tropical and temperate forests. TLS enables precise measurement of tree structures at unprecedented scales. This research builds on theoretical scaling relationships with empirical data, significantly refining our understanding of tree woody surface area. Key findings indicate that direct measurements diverge from theoretical predictions, particularly in the finer branch structures, suggesting modifications to existing allometric models might be necessary. This integration of direct measurements with TLS not only challenges established theories but also enhances our capability to accurately model tree surface area, which is key for understanding forest carbon dynamics and metabolic scaling in ecological systems.

ecology↗

bioRxiv2024

An image processing pipeline for electron cryo-tomography in RELION-5

Electron tomography of frozen, hydrated samples allows structure determination of macromolecular complexes that are embedded in complex environments. Provided that the target complexes may be localised in noisy, three-dimensional tomographic reconstructions, averaging images of multiple instances of these molecules can lead to structures with sufficient resolution for de novo atomic modelling. Although many research groups have contributed image processing tools for these tasks, a lack of standardisation and inter-operability represents a barrier for newcomers to the field. Here, we present an image processing pipeline for electron tomography data in RELION-5, with functionality ranging from the import of unprocessed movies to the automated building of atomic models in the final maps. Our explicit definition of metadata items that describe the steps of our pipeline has been designed for inter-operability with other software tools and provides a framework for further standardisation.

biophysics↗

bioRxiv2024

The potential of gene drive releases in malaria vector species to reduce the malaria burden in different African environments

Gene drive technologies are a promising means of malaria control with the potential to cause widespread and sustained reductions in transmission. In real environments, however, gene drive impacts will depend on local ecological and epidemiological factors. We develop a data-driven model to investigate the impacts of a gene drive that causes vector population suppression. We apply the model to sixteen [~]12,000km2 areas of west Africa that span variation in vector ecology and malaria prevalence. We simulate gene drive releases targeting different vector species combinations, and estimate reductions in vector abundance, malaria prevalence and clinical cases in children. Average reductions in vector abundance ranged from 77.3%-99.1% across areas when the gene drive releases targeted all major vector species (Anopheles gambiae, An. coluzzii, An. arabiensis, and An. funestus). Impacts on malaria depended strongly on which vector species were targeted. Consistently strong impacts required releases targeting all vector species, which reduced prevalence by over 90% in all areas. When the major vector species An. gambiae and An. coluzzii were targeted, average reductions in prevalence ranged from no reduction to 72% across areas, and reductions in cumulative clinical cases ranged from zero to 57%. When other new interventions including RTS,S vaccination and pyrethroid-PBO bednets were in place, at least 60% more clinical cases were averted when gene drives were added, demonstrating the benefits of integrated interventions. Our results give new insights into the factors determining the impacts of gene drives on malaria across different African settings.

genetics↗

bioRxiv2024

MemBrain v2: an end-to-end tool for the analysis of membranes in cryo-electron tomography

Cryo-electron tomography (cryo-ET) provides unique insights into macromolecular complexes in their native environments, yet membrane analysis remains a major bottleneck due to low signal-to-noise ratios, missing wedge artifacts, and the complexity of membrane-associated proteins. Existing tools often require extensive manual annotation, struggle with generalization across datasets, and lack integrated solutions for segmentation, protein localization, and quantitative analysis. We introduce MemBrain v2, a deep learning-enabled framework that unifies these tasks into a streamlined pipeline. MemBrain-seg leverages a diverse, collaboratively generated training dataset and specialized model training strategies to achieve generalizable membrane segmentation across variable tomographic conditions. MemBrain-pick enables data-efficient localization of membrane-bound proteins by integrating geometric constraints with deep learning, reducing the need for extensive manual annotation. MemBrain-stats provides quantitative insights into protein distributions, computing spatial metrics to analyze intra-membrane particle organization. MemBrain v2 integrates seamlessly into cryo-ET workflows, providing an accessible and structured approach to membrane analysis. The full package is available at https://github.com/CellArchLab/MemBrain-v2.

bioinformatics↗

bioRxiv2023

Whole-genome sequencing of major malaria vectors reveals the evolution of new insecticide resistance variants in a longitudinal study in Burkina Faso

Intensive deployment of insecticide based malaria vector control tools results in the rapid evolution of phenotypes resistant to these chemicals. Understanding this process on the genomic level is essential for the deployment of successful interventions. Using whole genome sequencing data of 1409 individual An. Gambiae s.l. collected from 2012 to 2017, we investigated the change in genetic structure and the evolution of the insecticide resistance variants in natural populations over time and space. The results showed similar and constant nucleotide diversity and negative Tajimas D between An. gambiae s.s. and An. coluzzii. PCA and FST showed a clear genetic structure in the An. gambiae s.l. species. Genome-wide FST and H12 scans identified genomic regions under divergent selection and also having an implication in the adaptations to ecological changes. Novel voltage-gated sodium channel pyrethroid resistance target-site alleles (V402L, I1527T) were identified at increasing frequencies alongside the established kdr alleles (Vgsc-L995F, Vgsc-L995S and N1570Y) within the An. gambiae s.l. populations. Organophosphate metabolic resistance markers were also identified, at increasing frequencies, within the An. gambiae s.s. populations from 2012 to 2017, including the SNP Ace1-G280S and its associated duplication. Variants simultaneously identified in the same vector populations raise concerns about the long-term efficacy of new-generation bednets and the recently introduced organophosphate pirimiphos-methyl indoor residual spraying. These findings highlighted the benefit of genomic malaria vector surveillance for the detection of new insecticide resistance variants, the monitoring of the existing resistance variants, and also to get insights into the evolutionary processes driving insecticide resistance. Author SummaryGenomic surveillance of malaria vectors is crucial for understanding the genetic variation in natural vector populations and also guiding the implementation of novel and innovative vector control tools. Application of sequencing technologies in vector studies provide insights on the genetic and evolutionary phenomena of vectors that could have impact on vector control strategies. By analyzing the whole genome data of 1409 wild An. gambiae s.l. mosquito collected between 2012 and 2017, we showed an emergence of novel insecticide resistance markers alongside increasing frequencies of existing insecticide resistance variants over time in Burkina Faso. We showed the benefit of genomic surveillance of malaria vectors for the monitoring of the insecticide resistance variants and also providing insights into the evolutionary processes driving insecticide resistance.

evolutionary biology↗

bioRxiv2023

DynaMight: estimating molecular motions with improved reconstruction from cryo-EM images

How to deal with continuously flexing molecules is one of the biggest outstanding challenges in single-particle analysis of proteins from cryo-EM images. Here, we present DynaMight, a new software tool that estimates a continuous space of conformations in a cryo-EM data set by learning 3D deformations of a Gaussian pseudo-atomic model of a consensus structure for every particle image. Inversion of the learnt deformations is then used to obtain an improved reconstruction of the consensus structure. We illustrate the performance of DynaMight for several experimental cryo-EM data sets. We also show how error estimates on the deformations may be obtained by independently training two variational autoencoders (VAEs) on half sets of the cryo-EM data, and how regularisation of the 3D deformations through the use of atomic models may lead to important artefacts due to model bias. DynaMight is distributed as free, open-source software, as part of RELION-5.

biophysics↗

bioRxiv2023

napari-threedee: a toolkit for human-in-the-loop 3D image analysis in napari

With recent advances in three-dimensional bioimaging acquisition and analysis methods, imaging data are an important tool for unveiling the complex architecture of biological organisms. However, extracting insights from these complex datasets requires interactive exploration as well as annotation for training supervised analytical methods. Here we present napari-threedee, a library of composable components and napari plugins for interactively exploring and annotating image data in 3D. We demonstrate how napari-threedee can be used for human-in-the-loop 3D image analysis in diverse image data including fluorescence microscopy and cryoelectron tomography.

bioengineering↗

bioRxiv2023

Mechanism of outer kinetochore assembly on microtubules and its regulation by mitotic error correction

Kinetochores couple chromosomes to the mitotic spindle and transduce the energy of microtubule depolymerization to segregate the genome during cell division. Kinetochore - microtubule attachments are often initially erroneous and subject to a mitotic error correction (EC) mechanism that drives their turnover until biorientation is achieved. How this is accomplished and regulated, and how kinetochore-mediated chromosome segregation occurs at a molecular level remain major outstanding questions. Here we describe the cryo-electron microscopy (cryo-EM) structure of the budding yeast outer kinetochore Ndc80 and Dam1 ring complexes assembled onto microtubules. We observe coordinated interactions of the outer kinetochore complexes through multiple interfaces, in addition to a short staple within the Dam1 subunit that facilitates Dam1c ring assembly. Perturbation of these interfaces results in loss of yeast viability. Force-rupture assays indicated this is a consequence of substantial reductions in kinetochore - microtubule binding strength. EC-mediated phosphorylation of Ndc80c-Dam1c interfaces would drive complex disassembly, whereas Dam1 staple phosphorylation would promote Dam1c ring disassembly, explaining how kinetochore - microtubule attachments are destabilized and reset by the EC mechanism. One-Sentence SummaryPhosphorylation disrupts the outer kinetochore to regulate kinetochore-microtubule attachments in mitotic error correction.

molecular biology↗

bioRxiv2023

A robust normalized local filter to estimate occupancy directly from cryo-EM maps

Cryo electron microscopy (cryo-EM) is used by biological research to visualize biomolecular complexes in 3D, but the heterogeneity of cryo-EM reconstructions is not easily estimated. Current processing paradigms nevertheless exert great effort to reduce flexibility and heterogeneity to improve the quality of the reconstruction. Clustering algorithms are typically employed to identify populations of data with reduced variability, but lack assessment of remaining heterogeneity. We have developed a fast and simple algorithm based on spatial filtering to estimate the heterogeneity of a reconstruction. In the absence of flexibility, this estimate approximates macromolecular component occupancy. We show that our implementation can derive reliable input parameters automatically, that the resulting estimate is accurate, and the reconstruction can be modified accordingly to emulate altered constituent occupancy, which may benefit conventionally employed maximum-likelihood classification methods. Here, we demonstrate the utility of this method for cryo-EM map interpretation, quantification, and particle-image signal subtraction.

bioinformatics↗

bioRxiv2022

TLS2trees: a scalable tree segmentation pipeline for TLS data

Above Ground Biomass (AGB) is an important metric used to quantify the mass of carbon stored in terrestrial ecosystems. For forests, this is routinely estimated at the plot scale (typically [≥]1 ha) using inventory measurements and allometry. In recent years, Terrestrial Laser Scanning (TLS) has appeared as a disruptive technology that can generate a more accurate assessment of tree and plot scale AGB; however, operationalising TLS methods has had to overcome a number of challenges. One such challenge is the segmentation of individual trees from plot level point clouds that are required to estimate woody volume, this is often done manually (e.g. with interactive point cloud editing software) and can be very time consuming. Here we present TLS2trees, an automated processing pipeline and set of Python command line tools that aims to redress this processing bottleneck. TLS2trees consists of existing and new methods and is specifically designed to be horizontally scalable. The processing pipeline is demonstrated across 10 plots of 7 forest types; from open savanna to dense tropical rainforest, where a total of 10,557 trees are segmented. TLS2trees segmented trees are compared to 1,281 manually segmented trees. Results indicate that TLS2trees performs well, particularly for larger trees (i.e. the cohort of largest trees that comprise 50% of total plot volume), where plot-wise tree volume bias is {+/-}0.4 m3 and %RMSE is ~60%. To facilitate improvements to the presented methods as well as modification for other laser scanning modes (e.g. mobile and UAV laser scanning), TLS2trees is a free and open-source software (FOSS).

ecology↗

bioRxiv2022

Tree segmentation in airborne laser scanning data is only accurate for canopy trees

Individual tree segmentation from airborne laser scanning data is a longstanding and important challenge in forest remote sensing. There are a number of segmentation algorithms but robust intercomparison studies are rare due to the difficulty of obtaining reliable reference data. Here we provide a benchmark data set for temperate and tropical broadleaf forests generated from labelled terrestrial laser scanning data. We compare the performance of four widely used tree segmentation algorithms against this benchmark data set. All algorithms achieved reasonable accuracy for the canopy trees, but very low accuracy for the understory trees. The point cloud based algorithm AMS3D (Adaptive Mean Shift 3D) had the highest overall accuracy, closely followed by the 2D raster based region growing algorithm Dalponte2016+. This result was consistent across both forest types. This study emphasises the need to assess tree segmentation algorithms directly using benchmark data. We provide the first openly available benchmark data set for tropical forests and we hope future studies will extend this work to other regions.

ecology↗

bioRxiv2022

Gene drive designs for efficient and localisable population suppression using Y-linked editors

The sterile insect technique (SIT) has been successful in controlling some pest species but is not practicable for many others due to the large numbers of individuals that need to be reared and released. Previous computer modelling has demonstrated that the release of males carrying a Y-linked editor that kills or sterilises female descendants could be orders of magnitude more efficient than SIT while still remaining spatially restricted, particularly if combined with an autosomal sex distorter. In principle, further gains in efficiency could be achieved by using a self-propagating double drive design, in which each of the two components (the Y-linked editor and the sex ratio distorter) boosted the transmission of the other. To better understand the expected dynamics and impact of releasing constructs of this new design, we have analysed a deterministic population genetic and population dynamic model. Our modelling demonstrates that this design can suppress a population from very low release rates, with no invasion threshold. Importantly, the design can work even if homing rates are low and sex chromosomes are silenced at meiosis, potentially expanding the range of species amenable to such control. Moreover, the predicted dynamics and impacts can be exquisitely sensitive to relatively small (e.g., 25%) changes in allele frequencies in the target population, which could be exploited for sequence-based population targeting. Analysis of published Anopheles gambiae genome sequences indicates that even for weakly differentiated populations with an FST of 0.02 there may be thousands of suitably differentiated genomic sites that could be used to restrict the spread and impact of a release. Our proposed design, which extends an already promising development pathway based on Y-linked editors, is therefore a potentially useful addition to the menu of options for genetic biocontrol.

genetics↗

bioRxiv2021

Weakly deleterious natural genetic variation amplifies probability of resistance in multiplexed gene drive systems

Evolution of resistance is a major barrier to successful deployment of gene drive systems to suppress natural populations, which could greatly reduce the burden of many vector borne diseases. Multiplexed guide RNAs that require resistance mutations in all target cut sites is a promising anti-resistance strategy, since in principle resistance would only arise in unrealistically large populations. Using novel stochastic simulations that accurately model evolution at very large population sizes, we explore the probability of resistance due to three important mechanisms: 1) non-homologous end-joining mutations, 2) single nucleotide mutants arising de novo or, 3) single nucleotide polymorphisms pre-existing as standing variation. Our results explore the relative importance of these mechanisms and highlight a complexity of the mutation-selection-drift balance between haplotypes with complete resistance and those with an incomplete number of resistant alleles. We find this leads to a qualitatively new phenomenon where weakly deleterious naturally occurring variants greatly amplify the probability of multi-site resistance. This challenges the intuition that many target sites would guarantee prevention of resistance, where in the face of standing genetic variation, it can be probable even in not very large populations. This result has broad application to resistance arising in many multi-site evolutionary scenarios including multi-drug resistance to antibiotics, antivirals and cancer treatments, as well as the evolution of vaccine escape mutations in large populations.

evolutionary biology↗

bioRxiv2021

Gene drives and population persistence vs elimination: the impact of spatial structure and inbreeding at low density

Synthetic gene drive constructs are being developed to control disease vectors, invasive species, and other pest species. In a well-mixed random mating population a sufficiently strong gene drive is expected to eliminate a target population, but it is not clear whether the same is true when spatial processes play a role. In species with an appropriate biology it is possible that drive-induced reductions in density might lead to increased inbreeding, reducing the efficacy of drive, eventually leading to suppression rather than elimination, regardless of how strong the drive is. To investigate this question we analyse a series of explicitly solvable stochastic models considering a range of scenarios for the relative timing of mating, reproduction, and dispersal and analyse the impact of two different types of gene drive, a Driving Y chromosome and a homing construct targeting an essential gene. We find in all cases a sufficiently strong Driving Y will go to fixation and the population will be eliminated, except in the one life history scenario (reproduction and mating in patches followed by dispersal) where low density leads to increased inbreeding, in which case the population persists indefinitely, tending to either a stable equilibrium or a limit cycle. These dynamics arise because Driving Y males have reduced mating success, particularly at low densities, due to having fewer sisters to mate with. Increased inbreeding at low densities can also prevent a homing construct from eliminating a population. For both types of drive, if there is strong inbreeding depression, then the population cannot be rescued by inbreeding and it is eliminated. These results highlight the potentially critical role that low-density-induced inbreeding and inbreeding depression (and, by extension, other sources of Allee effects) can have on the eventual impact of a gene drive on a target population.

evolutionary biology↗