Biology subjects

Bowden, R.

Publications and source records attributed to Bowden, R..

At least 19 recordsLinked to original sources

bioRxiv2026

Active Learning Enables Efficient Directed Evolution of a Far-Red Fluorescent Protein with Minimal Experimental Data

Fluorescent proteins are fundamental tools for cellular imaging. Most fluorescent proteins in routine use, including GFP, are derived from the jellyfish Aequorea victoria and emit blue-green light, which is strongly absorbed and scattered by tissue, limiting imaging depth. Far-red and near-infrared fluorescent proteins, engineered from bacteriophytochromes, address this limitation because far-red light penetrates tissue considerably further. However, these proteins are typically much dimmer than their A. victoria -derived counterparts. Improving brightness by conventional directed evolution requires screening large random mutant libraries, a process that is slow, labor-intensive, and often impractical outside specialized laboratories. We utilized an active-learning-guided directed evolution workflow that identified improved variants from substantially less data than conventional screening. Each round coupled automated, miniaturized cell-free protein expression directly from a DNA template without cloning or cell culture, with a machine-learning model retrained on cumulative sequence-function data to nominate the most informative variants for the next round. Applied to miRFP670nano3, this workflow screened 120 variants across successive rounds and identified twelve with improved brightness, the best four-fold brighter in bacterial systems. However, these gains did not translate when the variants were evaluated in mammalian cells, indicating that performance can be strongly dependent on cellular context. Retrospective simulation across benchmark datasets from ProteinGym showed that performing more experimental batches with fewer samples per batch consistently accelerated convergence to high-fitness sequences. Incorporating protein-language-model derived zero-shot fitness priors also accelerated convergence, but only in proportion to how well each prior score correlated with the true fitness landscape. Together, these findings established generalizable design rules, favoring smaller acquisition batches and confidence-weighted priors, for engineering proteins from minimal experimental data. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=55 SRC="FIGDIR/small/744534v1_ufig1.gif" ALT="Figure 1"> View larger version (11K): org.highwire.dtl.DTLVardef@14cd238org.highwire.dtl.DTLVardef@7d8334org.highwire.dtl.DTLVardef@30e9f2org.highwire.dtl.DTLVardef@14f3a0c_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2026

Patient cerebral organoids capture Alzheimers disease proteomic biomarkers and drug targets

Patient iPSC-derived cerebral organoids are a leading human model of Alzheimers disease, yet their proteome has never been benchmarked against human disease. Clinical cohorts now nominate thousands of biomarkers and drug targets across three proteomic platforms, and whether patient organoids capture these candidates is unknown. Here, we profile AD and control cerebral organoids containing neurons, astrocytes, and microglia on the three platforms driving clinical discovery, mass spectrometry, SomaScan, and Olink, in both conditioned media and lysate. Benchmarked against 121 studies and clinical cohorts of over 17,000 plasma, CSF, and cortex samples, patient organoids detect almost every nominated candidate and reproduce the disease-associated change in roughly one in four of the most reproducible. This convergence spans plasma, CSF, and cortex, and extends to synaptic, mitochondrial, and proteostatic biology. We provide the first multi-platform reference proteome of a patient-derived AD model, establishing it as a translationally relevant system for studying AD.

neuroscience↗

bioRxiv2026

SpatialBench: Comparative cross-platform benchmarking of high-resolution spatial transcriptomics using matched mouse lymphoid tissue

Spatial transcriptomics (ST) has rapidly expanded with the introduction of multiple high-resolution platforms, yet cross-platform benchmarking remains limited and largely focused on technical performance. Here we present SpatialBench, a matched multi-platform resource comprising Visium HD, Xenium and MERSCOPE data together with single-cell and single-nucleus references from a malaria-challenged wild-type and B cell-specific Tbx21 knockout mouse spleen model. In this system, loss of T-bet in B cells disrupts germinal center (GC) polarization and antibody maturation, providing a biologically grounded benchmark for technology comparison. We leveraged this system to systematically evaluate ST platform performance using technical and biological readouts. Across platforms, immune organization and Tbx21-associated programs were consistently recovered, indicating robustness of major biological signals. Platforms instead differed in the level of biological resolution accessible. Visium HD enabled transcriptome-scale GC characterization and, together with Xenium, resolved dark and light zone organization, whereas GC zonation was not resolved in MERSCOPE, consistent with differences in transcript detection sensitivity. SpatialBench provides a biologically defined reference dataset for evaluation of ST technologies, method development, computational benchmarking, and studies of GC spatial organization in lymphoid tissue.

bioinformatics↗

bioRxiv2025

alpseq: an open-source workflow to turbocharge nanobody discovery with high-throughput sequencing

Nanobodies have emerged as promising tools for many biotechnological applications due to their small size, high stability, and remarkable binding specificity. Next-Generation Sequencing (NGS) enables deep profiling of large nanobody libraries and panning campaigns, however the scale and diversity of nanobody NGS datasets presents a significant bioinformatic challenge. To this end, we have developed alpseq, an optimised, open-source software pipeline designed specifically for the efficient and accurate processing of NGS data from nanobody libraries and panning campaigns. alpseq is also paired with a PCR-free sequencing library preparation protocol to allow researchers to easily generate their own data while avoiding biases. The alpseq software pipeline is composed of two parts: a pre-processing module written in Nextflow efficiently handles raw nanobody reads in a single line of code. These results are then fed into the analysis module, which contains a comprehensive suite of functions for quality control, diversity analysis, identification of enriched sequences and clustering. alpseq also creates a user-friendly interactive report which empowers scientists to explore their data without the need for extensive bioinformatic experience. Sophisticated panning campaign designs are supported, such as replicates and comparisons between different pans to find cross-binding leads. alpseq thus generates insights into the nanobody selection process and delivers a list of lead candidates for further experimental validation and downstream applications. alspeq is available at https://github.com/kzeglinski/alpseq.

bioinformatics↗

bioRxiv2025

A highly efficient method to differentiate CGRP-expressing peptidergic nociceptors from human induced pluripotent stem cells

Human cellular models of disease developed using induced pluripotent stem cells (iPSC) have enabled wide-ranging research from investigation of human disease mechanisms to phenotypic drug screens. Pain disorders such as neuropathic pain and headache remain areas of considerable unmet need and are considered high risk by pharma. Human iPSC-derived sensory neurons have already been used to accelerate translational research but the current differentiation protocols produce non-peptidergic nociceptors. We demonstrate for the first time the robust differentiation of hiPSC into peptidergic nociceptor lineage with high yield. These nociceptors express CGRP and TRPV1 whilst the non-peptidergic marker RET was completely absent. Functionally, the nociceptors show functional maturity including the expression of TTX-resistant currents and responding to TRPV1 and TRPA1 agonists. Importantly, they were able to release CGRP basally and upon stimulation by an inflammatory soup, which was inhibited upon the application of the 5-HT1B/1D/1F agonist, sumatriptan and topiramate, a migraine prophylactic drug. Overall, we report the successful generation of a novel in vitro functional peptidergic nociceptor model which will allow investigation of disease mechanisms in pain and for the development of new effective pain therapies.

neuroscience↗

bioRxiv2024

TIRE-seq: an Integrated Sample Extraction and Transcriptomics Workflow for High Throughput Perturbation Studies

RNA sequencing (RNA-seq) is widely used in biomedical research, advancing our understanding of gene expression across biological systems. Traditional methods require upstream RNA extraction from biological inputs, adding time and expense to workflows. We developed TIRE-seq (Turbocapture Integrated RNA Expression Sequencing) to address these challenges. TIRE-seq integrates mRNA purification directly into library preparation, eliminating the need for a separate extraction step. This streamlined approach reduces turnaround time, minimizes sample loss, and improves data quality. A comparative study with the widely used Prime-seq protocol demonstrates TIRE-seqs superior sequencing efficiency with crude cell lysates as inputs. TIRE-seqs utility was demonstrated across three biological applications. It captured transcriptional changes in stimulated human T cells, revealing activation-associated gene expression profiles. It also identified key genes driving murine dendritic cell differentiation, providing insights into lineage commitment. Lastly, TIRE-seq analyzed the dose-response and time-course effects of temozolomide on patient-derived neurospheres, identifying differentially expressed genes and enriched pathways linked to the drugs mechanism of action. With its simplified workflow and high sequencing efficiency, TIRE-seq offers a cost-effective solution for large-scale gene expression studies across diverse biological systems.

genomics↗

bioRxiv2024

A necroptotic-to-apoptotic signaling axis underlies inflammatory bowel disease

Inflammatory bowel disease (IBD) is a chronic condition caused by altered cytokine signaling, maladaptive immunity, dysbiosis, and intestinal barrier dysfunction. Patients with IBD receive therapy to correct these imbalances and achieve remission. However, most patients relapse, suggesting that pathological mechanisms persist during remission. Here, we show that excess epithelial cell death is an underlying feature of IBD that arises in patients in remission and on advanced therapy. Mechanistically, nascent inflammation reprograms epithelial cells into a macrophage-like state that promotes RIPK1-independent necroptotic signaling, then triggers iNOS-mediated mitochondrial apoptosis of absorptive epithelial cells and PUMA-mediated intestinal stem cell death. These findings reveal aberrant epithelial cell death signaling as a hallmark of IBD that occurs early in mucosal lesion development and persists despite current therapeutic approaches. One-Sentence SummaryEpithelial cell death is dysregulated in patients with inflammatory bowel disease.

cell biology↗

bioRxiv2024

Emergent Collective Behavior Evolves More Rapidly Than Individual Behavior Among Ant Species

Emergence is a fundamental concept in biology and other disciplines, but whether emergent phenotypes evolve similarly to non-emergent phenotypes is unclear. The hypothesized process of emergent evolution posits that evolutionary change in collective behavior is irreducible to evolutionary change in the intrinsic behaviors of isolated individuals. As a result, collective behavior might evolve more rapidly and diversify more between populations compared to individual behavior. To test if collective behavior evolves emergently, we conducted a large comparative study using 22 ant species and gathered over 1,500 behavioral rhythm time series from hundreds of colonies and isolated individuals, totaling over 1.5 years of behavioral data. We show that analogous traits measured at individual and collective levels exhibit distinct evolutionary patterns. The estimated rates of phenotypic evolution for the rhythmicity of activity in ant colonies were faster than the evolutionary rates of the same behavior measured in isolated individual ants, and total variation across species in collective behavior was higher than variation in individual behavior. We hypothesize that more rapid evolution and higher variation is a general feature of emergent phenotypes relative to lower-level phenotypes across complex biological systems.

evolutionary biology↗

bioRxiv2024

Spotlight on 10x Visium: a multi-sample protocol comparison of spatial technologies

BackgroundSpatial transcriptomics allows gene expression to be measured within complex tissue contexts. Among the array of spatial capture technologies available is 10x Genomics Visium platform, a popular method which enables transcriptomewide profiling of tissue sections. Visium offers a range of sample handling and library construction methods which introduces a need for benchmarking to compare data quality and assess how well the technology can recover expected tissue features and biological signatures. ResultsHere we present SpatialBench, a unique reference dataset generated from spleen tissue of mice responding to malaria infection spanning several tissue preparation protocols (both fresh frozen and FFPE samples, with and without CytAssist tissue placement). We noted better quality control metrics in reference samples prepared using probe-based capture methods, particularly those processed with CytAssist, validating the improvement in data quality produced with the platform. Our analysis of replicate samples extends to explore spatially variable gene detection, the outcomes of clustering and cell deconvolution using matched single-cell RNA-sequencing data and publicly available reference data to identify cell types and tissue regions expected in the spleen. Multi-sample differential expression analysis recovered known gene signatures related to biological sex or gene knockout. ConclusionsWe framed a comprehensive multi-sample analysis workflow that allowed us to generate consistent results both within and between different subsets of replicate samples, enabling broader comparisons and interpretations to be made at the group-level. Our SpatialBench dataset, analysis, and workflow can serve as a practical guide for Visium users and may prove valuable in other benchmarking studies.

genomics↗

bioRxiv2023

An optimised protocol for quality control of gene therapy vectors using Nanopore direct RNA sequencing

Despite recent advances made towards improving the efficacy of lentiviral gene therapies, a sizeable proportion of produced vector contains an incomplete and thus potentially nonfunctional RNA genome. This can undermine gene delivery by the lentivirus as well as increase manufacturing costs and must be improved to facilitate the widespread clinical implementation of lentiviral gene therapies. Here, we compare three long-read sequencing technologies for their ability to detect issues in vector design and determine Nanopore direct RNA sequencing to be the most powerful. We show how this approach identifies and quantifies incomplete RNA caused by cryptic splicing and polyadenylation sites, including a potential cryptic polyadenylation site in the widely used Woodchuck Hepatitis Virus Posttranscriptional Regulatory Element (WPRE). Using artificial polyadenylation of the lentiviral RNA, we also identify multiple hairpin-associated truncations in the analysed lentiviral vectors, which account for most of the detected RNA fragments. Finally, we show that these insights can be used for optimization of lentiviral vector design. In summary, Nanopore direct RNA sequencing is a powerful tool for the quality control and optimisation of lentiviral vectors, which may help to improve lentivirus manufacturing and thus the development of higher quality lentiviral gene therapies.

genomics↗

bioRxiv2023

An immunohistochemical atlas of necroptotic pathway expression

Necroptosis is a lytic form of regulated cell death reported to contribute to inflammatory diseases of the gut, skin and lung, as well as ischemic-reperfusion injuries of the kidney, heart and brain. However, precise identification of the cells and tissues that undergo necroptotic cell death in vivo has proven challenging in the absence of robust protocols for immunohistochemical detection. Here, we provide automated immunohistochemistry protocols to detect core necroptosis regulators - Caspase-8, RIPK1, RIPK3 and MLKL - in formalin-fixed mouse and human tissues. We observed surprising heterogeneity in protein expression within tissues, whereby short-lived immune barrier cells were replete with necroptotic effectors, whereas long-lived cells lacked RIPK3 or MLKL expression. Local changes in the expression of necroptotic effectors occurred in response to insults such as inflammation, dysbiosis or immune challenge, consistent with necroptosis being dysregulated in disease contexts. These methods will facilitate the precise localisation and evaluation of necroptotic signaling in vivo. HighlightsO_LI13 automated immunohistochemistry protocols for detecting the necroptotic pathway C_LIO_LINecroptotic pathway expression is confined to fast-cycling immune barriers C_LIO_LINecroptotic pathway expression changes at sites of immunoinflammatory challenge C_LIO_LIImmunodetection of necrosomes in IBD patients is a putative new diagnostic tool C_LI

cell biology↗

bioRxiv2023

scPipe: An extended preprocessing pipeline for comprehensive single-cell ATAC-Seq data integration in R/Bioconductor

scPipe is a flexible R/Bioconductor package originally developed to analyse platform-independent single-cell RNA-Seq data. To expand its preprocessing capability to accommodate new single-cell technologies, we further developed scPipe to handle single-cell ATAC-Seq and multi-modal (RNA-Seq and ATAC-Seq) data. After executing multiple data cleaning steps to remove duplicated reads, low abundance features and cells of poor quality, a SingleCellExperiment object is created that contains a sparse count matrix with features of interest in the rows and cells in the columns. Quality control information (e.g. counts per cell, features per cell, total number of fragments, fraction of fragments per peak) and any relevant feature annotations are stored as metadata. We demonstrate that scPipe can efficiently identify "true" cells and provides flexibility for the user to fine-tune the quality control thresholds using various feature and cell-based metrics collected during data preprocessing. Researchers can then take advantage of various downstream single-cell tools available in Bioconductor for further analysis of scATAC-Seq data such as dimensionality reduction, clustering, motif enrichment, differential accessibility and cis-regulatory network analysis. The scPipe package enables a complete beginning-to-end pipeline for single-cell ATAC-Seq and RNA-Seq data analysis in R.

bioinformatics↗

bioRxiv2023

A Risk-reward Examination of Sample Multiplexing Reagents for Single Cell RNA-Seq

Single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for understanding cellular heterogeneity and function. However the choice of sample multiplexing reagents can impact data quality and experimental outcomes. In this study, we compared various multiplexing reagents, including MULTI-Seq, Hashtag antibody, and CellPlex, across diverse sample types such as human peripheral blood mononuclear cells (PBMCs), mouse embryonic brain and patient-derived xenografts (PDXs). We found that all multiplexing reagents worked well in cell types robust to ex vivo manipulation but suffered from signal-to-noise issues in more delicate sample types. We compared multiple demultiplexing algorithms which differed in performance depending on data quality. We find that minor improvements to laboratory workflows such as titration and rapid processing are critical to optimal performance. We also compared the performance of fixed scRNA-Seq kits and highlight the advantages of the Parse Biosciences kit for fragile samples. Highly multiplexed scRNA-Seq experiments require more sequencing resources, therefore we evaluated CRISPR-based destruction of non-informative genes to enhance sequencing value. Our comprehensive analysis provides insights into the selection of appropriate sample multiplexing reagents and protocols for scRNASeq experiments, facilitating more accurate and cost-effective studies.

genomics↗

bioRxiv2022

Actinobacillus pleuropneumoniae encodes multiple phase-variable DNA methyltransferases that comprise distinct phasevarions

ABSTRACTActinobacillus pleuropneumoniae is the cause of porcine pleuropneumonia, a severe respiratory tract infection that is responsible for major economic losses to the swine industry. Many host-adapted bacterial pathogens encode systems known as phasevarions (phase- variable regulons). Phasevarions result from variable expression of cytoplasmic DNA methyltransferases. Variable expression results in genome-wide methylation differences within a bacterial population, leading to altered expression of multiple genes via epigenetic mechanisms. Our examination of a diverse population of A. pleuropneumoniae strains determined that Type I and Type III DNA methyltransferases with the hallmarks of phase variation were present in this species. We demonstrate that phase variation is occurring in these methyltransferase, and show associations between particular Type III methyltransferase alleles and serovar. Using Pacific BioSciences Single-Molecule, Real-Time (SMRT) sequencing and Oxford Nanopore sequencing, we demonstrate the presence of the first ever characterised phase-variable, cytosine-specific Type III DNA methyltransferase. Phase variation of distinct Type III DNA methyltransferase variants results in the regulation of distinct phasevarions, and in multiple phenotypic differences relevant to pathobiology. Our characterisation of these newly described phasevarions in A. pleuropneumoniae will aid in the selection of stably expressed antigens, and direct and inform development of a rationally designed subunit vaccine against this major veterinary pathogen.

microbiology↗

bioRxiv2021

Development of the Wheat Practical Haplotype Graph Database as a Resource for Genotyping Data Storage and Genotype Imputation

To improve the efficiency of high-density genotype data storage and imputation in bread wheat (Triticum aestivum L.), we applied the Practical Haplotype Graph (PHG) tool. The wheat PHG database was built using whole-exome capture sequencing data from a diverse set of 65 wheat accessions. Population haplotypes were inferred for the reference genome intervals defined by the boundaries of the high-quality gene models. Missing genotypes in the inference panels, composed of wheat cultivars or recombinant inbred lines genotyped by exome capture, genotyping-by-sequencing (GBS), or whole-genome skim-seq sequencing approaches, were imputed using the wheat PHG database. Though imputation accuracy varied depending on the method of sequencing and coverage depth, we found 93% imputation accuracy with 0.01x sequence coverage, which was only slightly lower than the accuracy obtained using the 0.5x sequence coverage (96.9%). Compared to Beagle, on average, PHG imputation was ~4% (p-value = 0.00027) more accurate, and showed 27% higher accuracy at imputing a rare haplotype introgressed from a wild relative into wheat. The reduced accuracy of imputation with GBS data (90.4%) is likely associated with the small overlap between GBS markers and the exome capture dataset, which was used for constructing PHG. The highest imputation accuracy was obtained with exome capture for the wheat D genome, which also showed the highest levels of linkage disequlibrium and proportion of identity-by-descent regions among accessions in our reference panel. We demonstrate that genetic mapping based on genotypes imputed using PHG identifies SNPs with a broader range of effect sizes that together explain a higher proportion of genetic variance for heading date and meiotic crossover rate compared to previous studies.

genomics↗

bioRxiv2021

Targeted capture and sequencing of Orientia tsutsugamushi genomes from chiggers and humans

Scrub typhus is a febrile disease caused by Orientia tsutsugamushi, transmitted by larval stage Trombiculid mites (chiggers), whose primary hosts are small mammals. The phylogenomics of O. tsutsugamushi in chiggers, small mammals and humans remains poorly understood. To combat the limitations imposed by the low relative quantities of pathogen DNA in typical O. tsutsugamushi clinical and ecological samples, along with the technical, safety and cost limitations of cell culture, a novel probe-based target enrichment sequencing protocol was developed. The method was designed to capture variation among conserved genes and facilitate phylogenomic analysis at the scale of population samples. A whole-genome amplification step was incorporated to enhance the efficiency of sequencing by reducing duplication rates. This resulted in on-target capture rates of up to 93% for a diverse set of human, chigger, and rodent samples, with the greatest success rate in samples with real-time PCR Ct values below 35. Analysis of the best-performing samples revealed phylogeographic clustering at local, provincial and international scales. Applying the methodology to a comprehensive set of samples could yield a more complete understanding of the ecology, genomic evolution and population structure of O. tsutsugamushi and other similarly challenging organisms, with potential benefits in the development of diagnostic tests and vaccines.

microbiology↗

bioRxiv2020

Single-cell sequencing of human iPSC-derived cerebellar organoids shows recapitulation of cerebellar development

Current protocols for producing cerebellar neurons from human pluripotent stem cells (hPSCs) are reliant on animal co-culture and mostly exist as monolayers, which have limited capability to recapitulate the complex arrangement of the brain. We developed a method to differentiate hPSCs into cerebellar organoids that display hallmarks of in vivo cerebellar development. Single-cell profiling followed by comparison to an atlas of the developing murine cerebellum revealed transcriptionally-discrete populations encompassing all major cerebellar cell types. Matrigel encapsulation altered organoid growth dynamics, resulting in differential regulation of cell cycle, migration and cell-death pathways. However, this was at the expense of reproducibility. Furthermore, we showed the contribution of basement membrane signalling to both cellular composition of the organoids and developmentally-relevant gene expression programmes. This model system has exciting implications for studying cerebellar development and disease most notably by providing xeno-free conditions, representing a more biologically relevant and therapeutically tractable culture setting.

neuroscience↗

bioRxiv2020

Viral genome wide association study identifies novel hepatitis C virus polymorphisms associated with sofosbuvir treatment failure

Chronic hepatitis C virus (HCV) infection is a major cause of chronic liver disease, cirrhosis and hepatocellular carcinoma worldwide. With the recent development of direct acting antivirals (DAA), treatment of chronically infected patients has become highly effective although a subset of patients do not respond to therapy. Sofosbuvir is a common component of current de novo or salvage combination therapies. We used pre-treatment whole genome sequencing of HCV from 507 patients infected with HCV subtype 3a and treated with sofosbuvir containing regimens to detect viral polymorphisms associated with response to treatment. We found that three common polymorphisms present in HCV NS2 and NS3 proteins (not direct targets of sofosbuvir) were associated with reduced treatment response. These polymorphisms were enriched in post-treatment HCV sequences of patients unresponsive to treatment; they were also associated with lower reductions in viral load in the first week of therapy. The finding of polymorphisms in NS2 and NS3 proteins associated with poor treatment outcomes emphasises the value of more systematic genome-wide analyses of HCV in uncovering indirect but clinically relevant mechanisms of antiviral resistance.

microbiology↗