Biology subjects

Sanderson, T.

Publications and source records attributed to Sanderson, T..

At least 19 recordsLinked to original sources

bioRxiv2026

Real-time accessible phylogenetics for every highly sampled virus

The scale of viral genome sequencing has outpaced the phylogenetic tools traditionally used to analyze it, as highlighted by the COVID-19 pandemic. We present viral_usher, a unified framework for scalable viral phylogenetics built on UShER. viral_usher is a containerized command-line tool that constructs mutation-annotated trees directly from public sequence repositories with minimal user input, building phylogenies of tens of thousands of genomes in minutes. Applying it across the International Nucleotide Sequence Database Collaboration, we assembled viral_usher_trees, a repository of 446 phylogenies spanning 163 well-sequenced viral species, rebuilt automatically monthly as new genomes are deposited. We extended Taxonium from a tree viewer into a web platform supporting in-browser phylogenetic placement and de novo tree construction, so that users can upload sequences and contextualize them within global phylogenies without local computational infrastructure. Because every tree is built by the same procedure, the repository enables comparative analyses across the breadth of viral diversity. We demonstrate the utility of this resource by asking what factors shape viral mutation spectra. We found that replication machinery, captured as Baltimore class, explains 46% of the variance across 162 viral genomes, while host taxon and envelope status together explain under 5%. These resources provide an extensible platform for real-time genomic epidemiology and for comparative evolutionary analysis across viral pathogens. Resources and code are freely available at https://taxonium.org/, https://github.com/lilymaryam/spectrum_analysis, https://github.com/AngieHinrichs/viral_usher_trees, and https://github.com/AngieHinrichs/viral_usher.

bioinformatics↗

bioRxiv2026

OmicGlaze: Spatial Multi-Omic Mapping of Traumatic Brain Injury

Traumatic brain injury (TBI) is a major cause of mortality and long-term disability worldwide, giving rise to complex neurological complications that impact millions of individuals each year. Cellular stress and neuronal injury vary dramatically across cortical layers, vascular niches, and between the ipsilateral (injured) or contralateral (uninjured) hemispheres. There is a critical need for quantitative measures that capture the spatial distribution of injury-induced cellular changes, as well as the gene regulatory elements that drive them. Here, we developed OmicGlaze, an experimental and computational workflow for systematically profiling the spatial transcriptome and epigenome of mouse brains following mild traumatic brain injury. We established a spatial scoring system, and identified region-specific biological processes post injury, including changes in neuronal activities, cellular stress, immune response, and gliosis. Spatial assay for transposase-accessible chromatin with sequencing (Spatial ATAC-seq) generated the first epigenetic map of traumatic brain injury near single-cell resolution. Notably, we identified the Activator Protein-1 family transcription factor Atf3 as a key gene regulator of injury-induced cellular stress. Together, these spatial multi-omics analyses revealed gene regulatory network in TBI and provided a broadly applicable framework for dissecting cellular and molecular mechanisms underlying complex neurological disorders.

systems biology↗

bioRxiv2025

Mutational spectra reveal influenza virus transmission routes and adaptation

Influenza A virus remains a major cause of morbidity and mortality in humans and animals with pandemic potential. While control of outbreaks and spillover events remains a key health priority, the transmission routes and adaptations causing these episodes remain unclear. To understand these processes, we compared mutational spectra across the complete diversity of influenza A virus. We find that niche-specific mutagens cause large convergent shifts in mutational spectrum between gastrointestinal and respiratory lineages, allowing inference of transmission route and site of infection, while additional mutational patterns are host-specific, permitting detection of species responsible for outbreaks. By identifying points of spectrum change in phylogenetic trees, we discover novel adaptive mutations enabling sustained respiratory transmission. We conclude that mutational spectra can enable early detection of lineages with increased potential for spillover and onward transmission, and should be considered as a component of genomic surveillance strategies.

microbiology↗

bioRxiv2024

Application of barcode sequencing to increase the throughput and complexity of Plasmodium falciparum genetic screening

All the pathology and symptoms associated with malaria are caused by the growth of Plasmodium parasites inside human red blood cells. This process, which in the case of the major human malaria pathogen Plasmodium falciparum takes place over a 48-hour period, involves multiple tightly regulated developmental transitions. Understanding the P. falciparum genes that regulate these key processes could lead to the identification of targets for new drugs. However, while large-scale sequencing efforts have led to a good understanding of the P. falciparum genome and how it evolves over time and space, a disconnect remains between the amount of genome sequence data available and the amount of data describing what exactly the genes contained within it do - the phenotype. We have generated a panel of 66 P. falciparum lines carrying individual gene knockouts tagged with unique DNA barcodes. We then used these lines in a series of assays that combine flow cytometry, cell sorting and DNA barcode quantification using next generation sequencing (Barcode Sequencing or BarSeq) to phenotype key aspects of the parasite life cycle such as growth, replication capacity and cell cycle progression. This approach both yields new data about individual gene function, and outlines a new approach where barcoded P. falciparum lines are used in pooled BarSeq-based assays to generate more precise phenotype data at scale.

microbiology↗

bioRxiv2024

Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny

The SARS-CoV-2 genome occupies a unique place in infection biology - it is the most highly sequenced genome on earth (making up over 20% of public sequencing datasets) with fine scale information on sampling date and geography, and has been subject to unprecedented intense analysis. As a result, these phylogenetic data are an incredibly valuable resource for science and public health. However, the vast majority of the data was sequenced by tiling amplicons across the full genome, with amplicon schemes that changed over the pandemic as mutations in the viral genome interacted with primer binding sites. In combination with the disparate set of genome assembly workflows and lack of consistent quality control (QC) processes, the current genomes have many systematic errors that have evolved with the virus and amplicon schemes. These errors have significant impacts on the phylogeny, and therefore over the last few years, many thousands of hours of researchers time has been spent in "eyeballing" trees, looking for artefacts, and then patching the tree. Given the huge value of this dataset, we therefore set out to reprocess the complete set of public raw sequence data in a rigorous amplicon-aware manner, and build a cleaner phylogeny. Here we provide a global tree of 4,471,579 samples, built from a consistently assembled set of high quality consensus sequences from all available public data as of June 2024, viewable at https://viridian.taxonium.org. Each genome was constructed using a novel assembly tool called Viridian (https://github.com/iqbal-lab-org/viridian), developed specifically to process amplicon sequence data, eliminating artefactual errors and mask the genome at low quality positions. We provide simulation and empirical validation of the methodology, and quantify the improvement in the phylogeny. We hope the tree, consensus sequences and Viridian will be a valuable resource for researchers.

bioinformatics↗

bioRxiv2022

Treenome Browser: co-visualization of enormous phylogenies and millions of genomes

Treenome Browser is a web browser tool to interactively visualize millions of genomes alongside huge phylogenetic trees. Availability and ImplementationTreenome Browser for SARS-CoV-2 can be accessed at cov2tree.org, or at taxonium.org for user-provided trees. Source code and documentation are available at github.com/theosanderson/taxonium and docs.taxonium.org/en/latest/treenome.html. Contactalex.kramer@ucsc.edu, rucorbet@ucsc.edu

bioinformatics↗

bioRxiv2022

Taxonium: a web-based tool for exploring large phylogenetic trees

The COVID-19 pandemic has resulted in a step change in the scale of sequencing data, with more genomes of SARS-CoV-2 having been sequenced than any other organism on earth. These sequences reveal key insights when represented as a phylogenetic tree, which captures the evolutionary history of the virus, and allows the identification of transmission events and the emergence of new variants. However, existing web-based tools for exploring phylogenies do not scale to the size of datasets now available for SARS-CoV-2. We have developed Taxonium, a new tool that uses WebGL to allow the exploration of trees with tens of millions of nodes in the browser for the first time. Taxonium links each node to associated metadata and supports mutation-annotated trees, which are able to capture all known genetic variation in a dataset. It can either be run entirely locally in the browser, from a server-based backend, or as a desktop application. We describe insights that analysing a tree of five million sequences can provide into SARS-CoV-2 evolution, and provide a tool at cov2tree.org for exploring a public tree of more than five million SARS-CoV-2 sequences. Taxonium can be applied to any tree, and is available at taxonium.org, with source code at github.com/theosanderson/taxonium.

bioinformatics↗

bioRxiv2022

Emergence of new subgenomic mRNAs in SARS-CoV-2

Two mutations occurred in SARS-CoV-2 early during the COVID-19 pandemic that have come to define circulating virus lineages1: first a change in the spike protein (D614G) that defines the B.1 lineage and second, a double substitution in the nucleocapsid protein (R203K, G204R) that defines the B.1.1 lineage, which has subsequently given rise to three Variants of Concern: Alpha, Gamma and Omicron. While the latter mutations appear unremarkable at the protein level, there are dramatic implications at the nucleotide level: the GGG[->]AAC substitution generates a new Transcription Regulatory Sequence (TRS) motif, driving SARS-CoV-2 to express a novel subgenomic mRNA (sgmRNA) encoding a truncated C-terminal portion of nucleocapsid (N.iORF3), which is an inhibitor of type I interferon production. We find that N.iORF3 also emerged independently within the Iota variant, and further show that additional TRS motifs have convergently evolved to express novel sgmRNAs; notably upstream of Spike within the nsp16 coding region of ORF1b, which is expressed during human infection. Our findings demonstrate that SARS-CoV-2 is undergoing evolutionary changes at the functional RNA level in addition to the amino acid level, reminiscent of eukaryotic evolution. Greater attention to this aspect in the assessment of emerging strains of SARS-CoV-2 is warranted.

microbiology↗

bioRxiv2022

Barcoding genetically distinct Plasmodium falciparum strains for comparative assessment of fitness and antimalarial drug resistance

The repeated emergence of antimalarial drug resistance in Plasmodium falciparum, including to the current frontline antimalarial artemisinin, is a perennial problem for malaria control. Nextgeneration sequencing has greatly accelerated the identification of polymorphisms in resistance-associated genes, but has also highlighted the need for more sensitive and accurate laboratory tools to profile current and future antimalarials, and to quantify the impact of drug resistance acquisition on parasite fitness. The interplay of fitness and drug response is of fundamental importance in understanding why particular genetic backgrounds are better at driving the evolution of drug resistance in natural populations, but the impact of parasite fitness landscapes on the epidemiology of drug resistance has typically been laborious to accurately quantify in the lab, with assays being limited in accuracy and throughput. Here we present a scalable method to profile fitness and drug response of genetically distinct P. falciparum strains with well-described sensitivities to several antimalarials. We leverage CRISPR/Cas9 genome-editing and barcode sequencing to track unique barcodes integrated into a non-essential gene (pfrh3). We validate this approach in multiplex competitive growth assays of three strains with distinct geographical origins. Furthermore, we demonstrate that this method can be a powerful approach for tracking artemisinin response as it can identify an artemisinin resistant strain within a mix of multiple parasite lines, suggesting an approach for scaling the laborious ring-stage survival assay (RSA) across libraries of barcoded parasite lines. Overall, we present a novel high-throughput method for multiplexed competitive growth assays to evaluate parasite fitness and drug response

microbiology↗

bioRxiv2022

The origins and molecular evolution of SARS-CoV-2 lineage B.1.1.7 in the UK

The first SARS-CoV-2 variant of concern (VOC) to be designated was lineage B.1.1.7, later labelled by the World Health Organisation (WHO) as Alpha. Originating in early Autumn but discovered in December 2020, it spread rapidly and caused large waves of infections worldwide. The Alpha variant is notable for being defined by a long ancestral phylogenetic branch with an increased evolutionary rate, along which only two sequences have been sampled. Alpha genomes comprise a well-supported monophyletic clade within which the evolutionary rate is more typical of SARS-CoV-2. The Alpha epidemic continued to grow despite the continued restrictions on social mixing across the UK, and the imposition of new restrictions, in particular the English national lockdown in November 2020. While these interventions succeeded in reducing the absolute number of cases, the impact of these non-pharmaceutical interventions was predominantly to drive the decline of the SARS-CoV-2 lineages which preceded Alpha. We investigate the only two sampled sequences that fall on the branch ancestral to Alpha. We find that one is likely to be a true intermediate sequence, providing information about the order of mutational events that led to Alpha. We explore alternate hypotheses that can explain how Alpha acquired a large number of mutations yet remained largely unobserved in a region of high genomic surveillance: an under-sampled geographical location, a non-human animal population, or a chronically-infected individual. We conclude that the last hypothesis provides the best explanation of the observed behaviour and dynamics of the variant, although we find that the individual need not be immunocompromised, as persistently-infected immunocompetent hosts also display a higher within-host rate of evolution. Finally, we compare the ancestral branches and mutation profiles of other VOCs to each other, and identify that Delta appears to be an outlier both in terms of the genomic locations of its defining mutations, and its lack of rapid evolutionary rate on the ancestral branch. As new variants, such as Omicron, continue to evolve (potentially through similar mechanisms) it remains important to investigate the origins of other variants to identify ways to potentially disrupt their evolution and emergence.

evolutionary biology↗

bioRxiv2021

Chronumental: time tree estimation from very large phylogenies

Phylogenetic trees are an important tool for interpreting sequenced genomes, and their interrelationships. Estimating the date associated with each node of such a phylogeny creates a "time tree", which can be especially useful for visualising and analysing evolution of organisms such as viruses. Several tools have been developed for time-tree estimation, but the sequencing explosion in response to the SARS-CoV-2 pandemic has created phylogenies so large as to prevent the application of these previous approaches to full datasets. Here we introduce Chronumental, a tool that can rapidly infer time trees from phylogenies featuring large numbers of nodes. Chronumental uses stochastic gradient descent to identify lengths of time for tree branches which maximise the evidence lower bound under a probabilistic model, implemented in a framework which can be compiled into XLA for rapid computation. We show that Chronumental scales to phylogenies featuring millions of nodes, with chronological predictions made in minutes, and is able to accurately predict the dates of nodes for which it is not provided with metadata.

bioinformatics↗

bioRxiv2021

ProteInfer: deep networks for protein functional inference

Predicting the function of a protein from its amino acid sequence is a long-standing challenge in bioinformatics. Traditional approaches use sequence alignment to compare a query sequence either to thousands of models of protein families or to large databases of individual protein sequences. Here we instead employ deep convolutional neural networks to directly predict a variety of protein functions - EC numbers and GO terms - directly from an unaligned amino acid sequence. This approach provides precise predictions which complement alignment-based methods, and the computational efficiency of a single neural network permits novel and lightweight software interfaces, which we demonstrate with an in-browser graphical interface for protein function prediction in which all computation is performed on the users personal computer with no data uploaded to remote servers. Moreover, these models place full-length amino acid sequences into a generalised functional space, facilitating downstream analysis and interpretation. To read the interactive version of this paper, please visit https://google-research.github.io/proteinfer/ O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/461077v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@74f8f1org.highwire.dtl.DTLVardef@183ae0borg.highwire.dtl.DTLVardef@1754f3org.highwire.dtl.DTLVardef@1ca54f5_HPS_FORMAT_FIGEXP M_FIG C_FIG QR code for the interactive version of this preprint at https://google-research.github.io/proteinfer/

bioinformatics↗

bioRxiv2021

Regulators of male and female sexual development critical for transmission of a malaria parasite

The transmission of malaria parasites from vertebrate host to mosquito vector requires a developmental switch in asexually dividing blood-stage parasites to sexual reproduction. In Plasmodium berghei the transcription factor AP2-G is required and sufficient for this switch, but how a particular sex is determined in a haploid parasite remains unknown. Using a global screen of barcoded mutants, we here identify ten genes essential for the formation of either male or female sexual forms and validate their importance for transmission. High-resolution single-cell transcriptomics of wild-type and mutant parasites portrays the developmental bifurcation and reveals a regulatory cascade of putative gene functions in determination and subsequent differentiation of each sex. A male-determining gene with a LOTUS/OST-HTH domain points towards unexpected conservation of molecular mechanisms of gametogenesis in animals and a distantly related eukaryotic parasite.

genomics↗

bioRxiv2021

Mixology: a tool for calculating required masses and volumes for laboratory solutions

We have created a tool to calculate the amount of each ingredient required to make up a custom solution with defined concentrations. It can convert between many kinds of volumetric, mass and concentration units. This includes the ability to convert between molarities and mass-based concentrations, using molecular masses retrieved from the ChEBI database. Mixology can be accessed at http://mixology.science.

molecular biology↗

bioRxiv2020

Using Plasmodium knowlesi as a model for screening Plasmodium vivax blood-stage malaria vaccine targets reveals new candidates

Plasmodium vivax is responsible for the majority of malaria cases outside Africa. Unlike P. falciparum, the P. vivax life-cycle includes a dormant liver stage, the hypnozoite, which can cause infection in the absence of mosquito transmission. An effective vaccine against P. vivax blood stages would limit symptoms and pathology from such recurrent infections, and therefore could play a critical role in the control of this species. Vaccine development in P. vivax, however, lags considerably behind P. falciparum, which has many identified targets with several having transitioned to Phase II testing. By contrast only one P. vivax blood-stage vaccine candidate based on the Duffy Binding Protein (PvDBP), has reached Phase Ia, in large part because the lack of a continuous in vitro culture system for P. vivax limits systematic screening of new candidates. We used the close phylogenetic relationship between P. vivax and P. knowlesi, for which an in vitro culture system in human erythrocytes exists, to test the scalability of systematic reverse vaccinology to identify and prioritise P. vivax blood-stage targets. A panel of P. vivax proteins predicted to function in erythrocyte invasion were expressed as full-length recombinant ectodomains in a mammalian expression system. Eight of these antigens were used to generate polyclonal antibodies, which were screened for their ability to recognize orthologous proteins in P. knowlesi. These antibodies were then tested for inhibition of growth and invasion of both wild type P. knowlesi and chimeric P. knowlesi lines modified using CRISPR/Cas9 to exchange P. knowlesi genes with their P. vivax orthologues. Candidates that induced antibodies that inhibited invasion to a similar level as PvDBP were identified, confirming the utility of P. knowlesi as a model for P. vivax vaccine development and prioritizing antigens for further follow up. AUTHOR SUMMARYMalaria parasites cause disease after invading human red blood cells, implying that a vaccine that interrupts this process could play a significant role in malaria control. Multiple Plasmodium parasite species can cause malaria in humans, and most malaria outside Africa is caused by Plasmodium vivax. There is currently no effective vaccine against the blood stage of any malaria parasite, and progress in P. vivax vaccine development has been particularly hampered because this parasite species cannot be cultured for prolonged periods of time in the lab. We explored whether a related species, P. knowlesi, which can be propagated in human red blood cells in vitro, can be used to screen for potential P. vivax vaccine targets. We raised antibodies against selected P. vivax proteins and testedtheir ability to recognize and prevent P. knowlesi parasites from invading human red blood cells, thereby identifying multiple novel vaccine candidates.

microbiology↗

bioRxiv2019

Genomic and transcriptomic evidence for descent from Plasmodium and loss of blood schizogony in Hepatocystis parasites from naturally infected red colobus monkeys

Hepatocystis is a genus of single-celled parasites infecting monkeys, bats and squirrels. Although thought to descend from malaria parasites (Plasmodium spp.), Hepatocystis spp. are thought not to undergo replication in the blood - the part of the Plasmodium life cycle which causes the symptoms of malaria. Furthermore, Hepatocystis is transmitted by midges, not mosquitoes. Comparative genomics of Hepatocystis and Plasmodium species therefore presents an opportunity to better understand some of the most important aspects of malaria parasite biology. We were able to generate a draft genome for Hepatocystis using DNA sequencing reads from the blood of a naturally infected red colobus monkey. We provide robust phylogenetic support for Hepatocystis as a sister group to Plasmodium parasites infecting rodents. We show transcriptomic support for a lack of replication in the blood and genomic support for a complete loss of a family of genes involved in red blood cell invasion. Our analyses highlight the rapid evolution of genes involved in parasite vector stages, revealing genes that may be critical for interactions between malaria parasites and mosquitoes.

genomics↗

bioRxiv2019

89Zr-oxine labelling and PET imaging shows lung delivery of a cell/gene cancer therapy

PurposeMSCTRAIL is a new stem cell-based therapy for lung cancer, currently in phase I evaluation (ClinicalTrials.gov ref: NCT03298763). Biodistribution of cell therapies is rarely assessed in clinical trials, despite cell delivery to the target site often being critical to presumed mechanism of action. This preclinical study demonstrates that MSCTRAIL biodistribution dynamics can be detected non-invasively using 89Zr-oxine labelling and PET imaging, thus supporting use of this cell tracking technology in phase II evaluation.\n\nMethodsMSCTRAIL were radiolabelled with a range of 89Zr-oxine doses, and assayed for cell viability, phenotype and therapeutic efficacy post-labelling. Cell biodistribution was imaged in a mouse model of lung cancer using PET imaging and bioluminescence imaging (BLI) to confirm cell viability and location in vivo up to 1 week post-injection.\n\nResultsMSCTRAIL retained therapeutic efficacy and MSC phenotype at doses up to and above those required for clinical imaging. The effect of 89Zr-oxine labelling on cell proliferation rate was dose and time-dependent. PET imaging showed delivery of MSCTRAIL to the lungs in a mouse model of lung cancer, with PET signal correlating with the presence of viable cells as assessed by bioluminescence imaging, ex vivo autoradiography and matched fluorescence imaging on lung tissue sections. Human dosimetry estimates were produced using simulations and preclinical biodistribution data.\n\nConclusion89Zr-oxine labelling and PET imaging present an attractive method of evaluating the biodistribution of new cell-therapies, such as MSCTRAIL. This offers to improve understanding of mechanism of action, migration dynamics and interpatient variability of MSCTRAIL and other cell-based therapies.

cell biology↗

bioRxiv2019

Quantitation of vector uptake reveals non-Poissonian transfection dynamics in Plasmodium falciparum

The recurrent emergence of drug resistance in Plasmodium falciparum increases the urgency to genetically validate drug resistance mechanisms and identify new targets. Reverse genetics have facilitated genome-scale knockout screens in Plasmodium berghei and Toxoplasma gondii, in which pooled transfections of multiple vectors were critical to increasing scale and throughput. These approaches have not yet been implemented in P. falciparum, mainly because the extent to which pooled transfections can be performed in this species still remains unknown. Here we use next-generation sequencing to quantitate uptake of a pool of 94 barcoded vectors. The distribution of vectors in different transfections allowed us to estimate the number of barcodes and DNA molecules taken up by the parasite population. Dilution cloning showed that single transfected parasites routinely carry as many as seven episomal barcodes, revealing an intake of multiple vectors in a highly non-uniform fashion. Transfection of non-overlapping fluorescent proteins, which allowed us to follow the dynamics of the process, confirmed the tendency for parasites to take up multiple vectors from the early stages of transfection. This finding has important implications for how reverse genetics can be scaled in P. falciparum.

microbiology↗