Biology subjects

Dawson, E.

Publications and source records attributed to Dawson, E..

8 recordsLinked to original sources

bioRxiv2026

Early Spatiotemporal Deficits Become Competitive Advantages During Collective Expansion

Rapid spatial expansion into new territory is fundamental to population persistence, ecological dominance, and evolutionary success. Every race for space is initiated by founding populations, yet how their initial spatiotemporal conditions shape the outcome remains unclear. Here, by combining nonlinear theory with quantitative microbial experiments, we show that collective motility can overturn the classical logic of priority effects. Populations expanding by individual motility retain the expected advantage of an earlier start or a larger initial footprint. By contrast, under collective motility, nonlinear density-dependent feedback enables initially lagging populations to accelerate, transforming early deficits into long-term competitive advantage. Optimization predicts that this advantage is maximized when the delay scales log-linearly with initial density. We validate this scaling behavior across diverse swarming microbes, revealing a general regulatory strategy for competitive range expansion. Competition and evolution experiments further show that this behavior is adaptive and robustly preserved. Together, our results establish a quantitative framework linking the initial organization of founding populations to final spatial outcomes, helping explain how organisms regulate early dynamics to shape ecological success in space. SignificanceRapid expansion into new territory often decides who will dominate. To understand this contest, we focused on how the race begins. We built a theoretical framework linking the initial conditions of founding populations to long-run competitive outcomes, then tested its predictions experimentally in microbial populations by controlling inoculum, quantifying range expansion, competing strains head-to-head, and performing laboratory evolution. Our results show that history is not merely the starting point of range expansion, but part of the regulatory strategy for winning space. This work provides a mechanistic framework for quantitatively thinking about range expansion across systems, from microbial colonization and biological invasions to infection spread, cancer metastasis and developmental migration.

ecology↗

bioRxiv2026

Proximity-Informed Graph Learning Defines Spatial Protein Communities for Tumor-Associated Proximity Antigen Discovery

The spatial organization of membrane proteins is an underexplored dimension of cell-surface biology. Spatial proximity shapes cellular function and therapeutic targetability, yet efforts to identify tumor-associated antigens (TAAs) have largely focused on expression alone. Here, we developed an industrialized surface-protein proximity mapping workflow to interrogate TAAs within their membrane microenvironments. In the process, we generated 248 proximity maps across 12 receptor tyrosine kinases (RTKs) and 28 tumor cell systems. This proximity atlas enabled two advances: first, MetaMap, a correlation-based analytical framework that defines spatial protein communities and infers non-targeted proximal proteins from reproducible proximity signatures; and second, tumor-associated proximity antigens (TAPAs), a conceptual class of co-targets defined by disease-specific spatial proximity to TAAs rather than expression alone. Applying these proximity-derived relationships within a multimodal prioritization framework, we identified and validated an EGFRxCDCP1 TAA-TAPA pair that enhanced tumor cell killing across therapeutic modalities. By integrating spatial organization with multimodal data, this work expands the design space for precision-guided therapeutic strategies.

cancer biology↗

bioRxiv2024

The structural diversity of telomeres and centromeres across mouse subspecies revealed by complete assemblies

It is over twenty years since the publication of the C57BL/6J mouse reference genome, which has been a key catalyst for understanding mammalian disease biology. However, the mouse reference genome still lacks telomeres and centromeres, contains 281 chromosomal sequence gaps, and only partially represents many biomedically relevant loci. We present the first T2T mouse genomes for two key inbred strains, C57BL/6J and CAST/EiJ. These T2T genomes reveal significant variability in telomere and centromere sizes and structural organisation. We add an additional 213 Mbp of novel sequence to the reference genome containing 517 protein-coding genes. We examined two important but incomplete loci in the mouse genome - the pseudoautosomal region (PAR) on the sex chromosomes and KRAB zinc finger proteins (KZFPs) loci. We identified distant locations of the PAR boundary, different copy number and sizes of segmental duplications, and a multitude of amino acid substitution mutations in PAR genes.

genomics↗

bioRxiv2022

Accelerating Minimap2 for accurate long read alignment on GPUs

Long read sequencing technology is becoming increasingly popular for Precision Medicine applications like Whole Genome Sequencing (WGS) and microbial abundance estimation. Minimap2 is the state-of-the-art aligner and mapper used by the leading long read sequencing technologies, today. However, Minimap2 on CPUs is very slow for long noisy reads. [~]60-70% of the run-time on a CPU comes from the highly sequential chaining step in Minimap2. On the other hand, most Point-of-Care computational workflows in long read sequencing use Graphics Processing Units (GPUs). We present minimap2-accelerated (mm2-ax), a heterogeneous design for sequence mapping and alignment where minimap2s compute intensive chaining step is sped up on the GPU and demonstrate its time and cost benefits. We extract better intra-read parallelism from chaining without loosing mapping accuracy by forward transforming Minimap2s chaining algorithm. Moreover, we better utilize the high memory available on modern cloud instances apart from better workload balancing, data locality and minimal branch divergence on the GPU. We show mm2-ax on an NVIDIA A100 GPU improves the chaining step with 5.41 - 2.57X speedup and 4.07 - 1.93X speedup : costup over the fastest version of Minimap2, mm2-fast, benchmarked on a Google Cloud Platform instance of 30 SIMD cores.

genomics↗

bioRxiv2021

Using OPM-MEG in contrasting magnetic environments

Magnetoencephalography (MEG) has been revolutionised in recent years by optically pumped magnetometers (OPMs). "OPM-MEG" offers higher sensitivity, better spatial resolution and lower cost than conventional instrumentation based on superconducting quantum interference devices (SQUIDS). Moreover, OPMs offer the possibility of motion robustness and lifespan compliance, dramatically expanding the range of MEG applications. However, OPM-MEG remains nascent technology; it places stringent requirements on magnetic shielding, and whilst a number of viable systems exist, most are custom made and there have been no cross-site investigations showing the reliability of data. In this paper, we undertake the first cross-site OPM-MEG comparison, using near identical commercial systems scanning the same participant. The two sites are deliberately contrasting, with different magnetic environments: a "green field" campus university site with an OPM-optimised shielded room (low interference) and a city centre hospital site with a "standard" (non-optimised) MSR (high interference). We show that despite a 25-fold difference in background field, and a 30-fold difference in low frequency interference, using dynamic field control and software-based suppression of interference we can generate comparable noise floors at both sites. In human data recorded during a visuo-motor task and a face processing paradigm, we were able to generate similar data, with source localisation showing that brain regions could be pinpointed with just ~10 mm spatial discrepancy and temporal correlations of > 80%. Overall, our study demonstrates that "plug- and-play" OPM-MEG systems exist and can be sited even in challenging magnetic environments.

neuroscience↗

bioRxiv2019

Genotyping structural variants in pangenome graphs using the vg toolkit

Structural variants (SVs) remain challenging to represent and study relative to point mutations despite their demonstrated importance. We show that variation graphs, as implemented in the vg toolkit, provide an effective means for leveraging SV catalogs for short-read SV genotyping experiments. We benchmarked vg against state-of-the-art SV genotypers using three sequence-resolved SV catalogs generated by recent long-read sequencing studies. In addition, we use assemblies from 12 yeast strains to show that graphs constructed directly from aligned de novo assemblies improve genotyping compared to graphs built from intermediate SV catalogs in the VCF format.

bioinformatics↗

bioRxiv2019

SVCurator: A Crowdsourcing app to visualize evidence of structural variants for the human genome

A high quality benchmark for small variants encompassing 88 to 90% of the reference genome has been developed for seven Genome in a Bottle (GIAB) reference samples. However a reliable benchmark for large indels and structural variants (SVs) is yet to be defined. In this study, we manually curated 1235 SVs which can ultimately be used to evaluate SV callers or train machine learning models. We developed a crowdsourcing app - SVCurator - to help curators manually review large indels and SVs within the human genome, and report their genotype and size accuracy.\n\nSVCurator is a Python Flask-based web platform that displays images from short, long, and linked read sequencing data from the GIAB Ashkenazi Jewish Trio son [NIST RM 8391/HG002], We asked curators to assign labels describing SV type (deletion or insertion), size accuracy, and genotype for 1235 putative insertions and deletions sampled from different size bins between 20 and 892,149 bp. The crowdsourced results were highly concordant with 37 out of the 61 curators having at least 78% concordance with a set of expert curators, where there was 93% concordance amongst expert curators. This produced high confidence labels for 935 events. When compared to the heuristic-based draft benchmark SV callset from GIAB, the SVCurator crowdsourced labels were 94.5% concordant with the benchmark set. We found that curators can successfully evaluate putative SVs when given evidence from multiple sequencing technologies.

genomics↗

bioRxiv2017

The Relationship Between Cancer Progression And Social Environment In Drosophila

The influence of oncogenic phenomena on the ecology and evolution of animal species is fast becoming an important research topic. Similar to host-pathogen interactions, cancer negatively affects host fitness, which should lead to the selection of host control mechanisms, including behavioral traits that best minimize the proliferation of malignant cells. Social behavior is one such trait, which is suggested to influence cancer progression. While the ecological benefits of sociality in gregarious species are widely acknowledged, only limited data are available on the role of the social environment on cancer progression. Here, we exposed adult Drosophila, with colorectal-like tumors, to different social environments. First, we show that cancerous flies kept in complete isolation exhibit increased tumor progression. Yet, more surprisingly, we find that cancerous flies, kept in groups with other noncancerous individuals, also develop tumors at a faster rate compared to those kept with other cancerous conspecifics, suggesting a strong impact of social group composition on cancer growth. Finally, we show that flies can discriminate between individuals at different stages of tumor growth and selectively choose their social environment accordingly. Control flies actively avoid flies with cancer but only at the later stages of tumor development, whereas cancerous flies display strong social interactions with cancerous flies in the early stages of tumor growth. Our study demonstrates the reciprocal links between cancer and social interactions, as well as highlighting how sociality impacts health and fitness in animals and its potential implications for disease ecology and ecosystem dynamics.

animal behavior and cognition↗