Biology subjects

Hall, D.

Publications and source records attributed to Hall, D..

At least 19 recordsLinked to original sources

bioRxiv2026

Scaling a context-aware genomic model for condition-specific edit design in plants

Engineering agronomically relevant traits in crops often requires changing a gene's activity in a specific tissue, developmental stage or environmental condition while preserving its roles in other contexts. Designing such selective changes requires predicting how cis-regulatory sequences are interpreted in different biological states, as the same edit can have different effects across contexts. Genomic models have made substantial progress in predicting gene expression from DNA sequence, yet sequence-only predictors do not receive an explicit description of biological states. We introduce CROP-1 (Context-aware Regulatory Output Prediction model), which combines DNA sequence with transcription factor binding motifs and measured expression to predict gene activity as a function of both sequence and regulatory state. On a held-out test set spanning six plant species, CROP-1 achieves a median per-gene Pearson correlation across contexts of 0.831, compared with 0.486 for its parameter-matched sequence-only counterpart, and 57-246% higher median correlations than three genomic foundation models fully fine-tuned on the same task. Prediction accuracy also improves with scale: increasing model capacity reduces validation error by 48%, while expanding training data to include more diverse biological contexts reduces it by 58%. We then use gradient-based sequence optimisation to translate a desired gene expression pattern into candidate edits of its cis-regulatory sequence, targeting up- or down-regulation in one context while preserving expression in others. In soybean and tomato, edit designs with 1-20 nucleotide substitutions produce strong predicted target responses and much smaller average changes across non-target contexts. By connecting scalable learning of sequence-state relationships to selective edit design, CROP-1 provides a computational foundation for controlling where, when and under which conditions endogenous crop genes are active.

plant biology↗

bioRxiv2026

Adaptive Charge Modulation Enables Focal, Selective Spinal Cord Stimulation

Clinical neuromodulation primarily employs near-field low frequency electrical stimulation to activate neurons in the immediate vicinity of the electrode. We introduce Adaptive Charge Modulation (ACM), a spatiotemporal, charge-balanced stimulation strategy that focuses activation at deep tissue sites distant from the stimulating contacts. We apply ACM to stimulate deep regions of the spinal cord, distant from dorsal root entry zones which are preferentially activated during low frequency stimulation (LFS). ACM applies multipolar, biphasic rectangular pulses to exceed activation thresholds in deeper neuronal populations, with reduced surface activation, potentially due to high-frequency suppression of neural activity. In epidural spinal cord stimulation in rats, ACM achieved single-muscle selectivity among fourteen monitored muscles with minimal co-activation of other muscles. Using simultaneous, high spatiotemporal resolution, 2,112-channel brain-spine recordings, we characterized the response latencies and pathways consistent with focal recruitment at depth. We observed chronic stability of the electrode and ACM in freely behaving animals over 68 days post-implantation. By enabling focal activation with epidural surface electrodes, ACM may expand the reach and precision of neuromodulation and neural interfaces.

bioengineering↗

bioRxiv2026

Detection of Melanoma Using Deep Serum Proteome Profiling and Machine Learning

Early detection determines melanoma outcomes, yet current screening relies on visual inspection that misses molecular changes preceding clinical diagnosis. To identify serum protein signatures of melanoma development, we leveraged the Department of Defense Serum Repository, analyzing 390 longitudinal serum samples from 73 melanoma cases and matched controls across four timepoints (4 and 2 years prior, diagnosis, and 2 years post-diagnosis) using data-independent acquisition mass spectrometry with Seer Proteograph nanoparticle enrichment. We quantified 3,364 proteins and applied machine-learning strategies combining cross-sectional case-control comparisons with longitudinal tracking of within-individual changes. Cross-sectional analysis at diagnosis achieved AUC 0.823 (95% CI: 0.723-0.923), identifying eight consensus features selected in >50% of cross-validation folds: PRSS1, GSK3B, FAM20C, CES1, CCL14, EPHA10, LMAN2, and ITIH1. These signatures, spanning proteases, immune activation, and extracellular matrix remodeling, demonstrate proof-of-concept for serum-based melanoma detection and provide candidate biomarkers for validation.

Cancer Biology↗

bioRxiv2026

ATF4 Coordinates Transcriptomic and Structural Adaptations in Aging Muscle

Aging is associated with a progressive loss of skeletal muscle function, known as sarcopenia; however, the molecular mechanisms coordinating cellular stress responses and structural adaptations permissive of sarcopenia remain incompletely understood. In our previous studies, we found aging differentially impacted mitochondrial networks by muscle, suggesting unique stress thresholds and response activation. Here, we investigate the role of activating transcription factor 4 (ATF4), a master regulator of the integrated stress response (ISR), in aged quadriceps muscle using complementary patient and aging mouse models. Older adults exhibited a marked decrease in aerobic capacity, muscle strength, and endurance when compared with young participants. These results paralleled findings in aged mice, with significant loss of muscle mass across multiple hindlimb muscles. Ultrastructural analysis revealed substantial age-related changes in mitochondrial morphology, including increased volume, surface area, and branching index, as well as a shift toward larger, more complex mitochondria. Our data indicate that ATF4 binds directly to the promoter region of the gene encoding TFAM, suggesting a transcriptional regulatory relationship to support DNA stability. These structural and transcriptional changes likely impair oxidative capacity and drive a feed-forward cycle of mitochondrial dysfunction and ISR activation. Our findings indicate that ATF4 coordinates transcriptomic and structural adaptations in aging muscle, identifying the ISR pathway as a potential therapeutic target for preserving muscle function in older adults.

cell biology↗

bioRxiv2026

Leveraging Large Language Models to Extract Prognostic Pathology Features in Ewing Sarcoma

BackgroundCurrent risk stratification for Ewing sarcoma relies heavily on clinical factors such as metastatic status, failing to capture histologic heterogeneity as a potential prognostic indicator. Although pathology reports contain rich biological data, this information remains locked in unstructured narrative text, limiting large-scale retrospective analyses. We aimed to validate the utility of Large Language Models (LLMs) for scalable data abstraction and to identify prognostic histologic features from a large multi-institutional cohort. MethodsWe conducted a retrospective cohort study using data from six Childrens Oncology Group (COG) clinical trials. We utilized an LLM-based pipeline (OpenAI o3) to extract structured variables--including immunohistochemical (IHC) markers and CD99 staining patterns--from digitized, Optical Character Recognition (OCR)-processed pathology reports. Extraction accuracy was validated against a human-annotated ground truth (n=200) and cross-validated against senior experts (n=48). We assessed the association between extracted features and Overall Survival (OS) using Kaplan-Meier analysis and multivariable Cox proportional hazards regression, adjusting for metastatic status. FindingsWe analyzed 931 diagnostic pathology reports from 185 institutions spanning over 21-years. The LLM achieved a weighted average accuracy of 94% across 17 IHC markers; in a cross-validation subset, the LLM outperformed human annotators (weighted average accuracy over 15 IHC markers: LLM o3: 98.1%, a pediatric resident 91.4%, and a pediatric oncologist 95.9%). Survival analysis identified Neuron-Specific Enolase (NSE) and S100 as significant prognostic biomarkers. After adjusting for metastatic status, NSE positivity was associated with significantly inferior survival (HR 2.15, 95% CI 1.15-4.02, p=0.016); this risk was most pronounced in patients with non-metastatic disease (HR 5.64, p=0.0055). Conversely, S100 positivity was associated with improved survival (HR 0.58, 95% CI 0.34-1.00, p=0.046). InterpretationLLM-assisted extraction of pathology variables is highly accurate and scalable, capable of unlocking "dark data" from historical clinical trials. We identified NSE as a potent risk factor and S100 as a protective marker in Ewing sarcoma, particularly in localized disease. These findings suggest that AI-derived histologic data can refine risk stratification and, if validated, warrant inclusion in future prospective trials. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed and Google Scholar for articles published up to December 2025, using terms such as "Ewing sarcoma", "prognosis", "risk stratification", "large language models", "natural language processing", and "pathology report extraction". Current risk stratification for Ewing sarcoma relies predominantly on clinical variables, specifically the presence of metastatic disease and tumor size. While histologic heterogeneity is well-documented, it is rarely incorporated into risk models because extracting structured data from narrative pathology reports is labor-intensive. Small, single-institution studies have suggested potential prognostic roles for markers like Neuron-Specific Enolase (NSE) or S100, but results have been inconsistent and limited by small sample sizes. Furthermore, while Large Language Models (LLMs) have demonstrated potential for extracting clinical data, their application to "rescue" data from legacy, multi-institutional clinical trial documents (scanned PDF images) for rare disease biomarker discovery has not been validated at scale. Added value of this studyTo our knowledge, this is the largest study to utilize AI to extract histologic data from Ewing sarcoma pathology reports, aggregating 931 patients from six distinct Childrens Oncology Group (COG) clinical trials spanning over 21 years. We validated an LLM-based pipeline that converted noisy, optically character-recognized text from diverse institutions into structured data with 98.1% accuracy, outperforming human annotators. This scalable approach revealed that NSE positivity is a significant independent risk factor for mortality (HR=2.15), particularly in patients with non-metastatic disease where it confers a more than 5-fold increased risk of death. Conversely, we identified S100 positivity as a protective factor associated with improved survival (HR=0.58). Implications of all the available evidenceThis study demonstrates that LLMs can reliably unlock "dark data" from historical clinical trials, rendering vast archives of unstructured medical documents accessible for retrospective analysis. The identification of NSE and S100 as robust prognostic biomarkers suggests that these widely available immunohistochemical stains provide valuable information beyond standard diagnostic information. These findings support the integration of automated data extraction tools in research workflows and suggest that NSE and S100 status should be considered in the design of future risk-stratified clinical trials for Ewing sarcoma.

bioinformatics↗

bioRxiv2025

M5 positive allosteric modulation alleviates parkinsonian motor deficits

Parkinsons disease is a neurodegenerative movement disorder which is characterized by cardinal motor symptoms of tremor at rest, rigidity, bradykineasia, and postural instability. Underlying these cardinal motor symptoms is thought to be death and dysfunction of nigrostriatal dopamine neurons, and the gold-standard treatment of Parkinsons disease is dopamine replacement therapy with the dopamine precursor L-DOPA. While efficacious, L-DOPA does not treat all motor symptoms and can have serious treatment-related side effects called L-DOPA induced dyskinesias, indicating an immense need for new targets to modulate dopaminergic function for anti-parkinsonian efficacy. One such potential target is the M5 muscarinic acetylcholine receptor, which has a unique expression profile where it is selectively expressed in midbrain dopaminergic neurons and their terminals in the striatum, and previous studies have indicated that M5 can modulate dopamine release and patterning of firing of dopamine neurons. Given this unique expression profile and function of M5, this receptor has an untested potential to modulate parkinsonian motor phenotypes. To test the potential for M5 to modulate Parkinsonian-like motor deficits and dyskinesia, we employed the unilateral 6-OHDA lesioned mouse model to create a hemi-parkinsonian state. Using multiple behavioral assays, including the cylinder test, forepaw adjusting steps assay, and in the Erasmus ladder, in conjunction with prototypical M5 pharmacological tool compounds, we investigated the ability of M5 to modulate parkinsonian motor deficits. Additionally, we tested the ability of M5 to modulate established L-DOPA induced dyskinesia or cause dyskinesia on its own. Overall, we found that M5 PAM alleviates forepaw asymmetry, bradykinesia, and spatial aspects of gait in the Erasmus ladder. Excitingly, M5 PAM does not cause robust dyskinesia, does not affect already established L-DOPA-induced dyskinesia, and does not affect L-DOPA motor efficacy. Taken together with previous findings, the current study suggests that M5 receptors are an exciting novel therapeutic strategy for ameliorating parkinsonian motor deficits even in late-stage models of severe PD without lessening L-DOPAs motor benefit and without affecting existing symptoms of L-DOPA-induced dyskinesia.

neuroscience↗

bioRxiv2025

NAPRT expression and epigenetic regulation in pediatric rhabdomyosarcoma as a potential biomarker for NAMPT inhibition

PurposeNew treatments are needed to improve survival in children with rhabdomyosarcoma (RMS). NAD biosynthesis, regulated by the enzymes NAPRT and NAMPT, represents a metabolic vulnerability due to high NAD turnover in cancers. Although NAMPT inhibitors (NAMPTi) show preclinical promise, clinical translation has been limited by toxicity and the lack of predictive biomarkers. Here, we evaluated NAPRT expression in RMS and its potential as an actionable biomarker to guide NAMPTi therapy. Experimental DesignNAPRT promoter methylation, transcript levels, and protein expression were assessed in RMS cells, PDXs, and primary tumors (n=109) from the Childrens Oncology Group. In vitro sensitivity to NAMPTi was tested in molecularly diverse and isogenic RMS cell lines, examining the role of NAPRT expression in mediating cytotoxicity and the ability of nicotinic acid (NA) to rescue viability. In vivo efficacy was assessed using NAPRT-isogenic orthotopic xenograft models. ResultsNAPRT promoter hypermethylation was found in a subset of RMS models and patient samples. Immunohistochemistry showed loss of NAPRT protein in 30-40% of tumors, defined as <1% tumor cell staining. Methylation modestly correlated with protein expression. NAPRT-silenced cells were highly sensitive to NAMPTi, driven by NAD depletion and not reversible with NA. In vivo, NAMPTi induced significant tumor regression, which was not abrogated with NA administration in NAPRT-silenced models. ConclusionsNAPRT loss occurs in a subset of RMS, offering a potential strategy to expand the therapeutic window of NAMPTi. Further research is needed to understand NAPRT regulation and optimize biomarker assay strategies for use in future clinical trials.

cancer biology↗

bioRxiv2025

Biological consequences of asymmetric hop diffusion in the cell membrane

Over the last 30 years, the hop diffusion model has been an important paradigm for interpreting both cell membrane structure and dynamics. The basic premise of the model is that the cell membrane is organized into small domain regions through a combination of multi-component phase-separation and interaction between membrane components and the proximal fibers of the intracellular cytoskeleton and extracellular matrix. The partitioned characteristics of this two-dimensional fluid are thought to impose both steric and hydrodynamic barriers that restrict the free motion of mobile membrane components, save for their occasional passage via hopping from one domain to another. Previous investigations of hop diffusion within the cell membrane have identified the potential for diffusional anisotropy [Jaqaman et al. 2011. Cell, 146(4), pp.593-606]. This work utilizes numerical simulations and develops new analytical theory to provide an approximate quantitative description of such asymmetric compartmentalization. These methods are then used to examine the physical requirements for generation of asymmetric hop diffusion within the membrane before concluding with a discussion of the potential biological consequences of such behavior.

biophysics↗

bioRxiv2025

Equations describing semi-confluent cell growth (II) Colony formation on a flat surface

Individual cell growth can be affected by the presence of adjacent cells through a complex and multi-factorial biological process known alternatively as contact inhibition or confluence sensing. In a previous paper [Hall, D. 2023 Equations describing semi-confluent cell growth (I) Analytical approximations. Biophysical Chemistry, 307, 107173, pp. 1-9], sets of differential equations (with implicit analytical solutions) were developed to describe completely symmetrical cases of multicellular colony growth affected by variable levels of contact inhibition. Here we develop a model based on a spherical cap approximation of colony growth, that is able to describe variable contact inhibition for non-symmetrical multilayer cell formation on a solid plate. Although the model is realized as a set of interrelated ordinary differential equations, it is effectively governed by two parameters and is therefore capable for use in quantitative analysis of the kinetics of cell culture parameters such as shape, colony size and receding contact angle. The model is capable of accounting for transitions from monolayer to multilayer growth in a robust fashion.

biophysics↗

bioRxiv2025

Pathological α-Synuclein Perturbs Nuclear Integrity

Pathological aggregates of -synuclein are a hallmark of a group of neurodegenerative disorders collectively termed synucleinopathies. The physiological function of -synuclein, and the detrimental effects of the pathological variants of -synuclein have been widely debated, but recent evidence has suggested an emerging consensus on a critical role for -synuclein in regulating synaptic function. However, a controversial role for -synuclein in nuclear function in both normal and pathogenic states has been proposed, and the degree to which -synuclein localizes within the nucleus and subsequent impact on the nucleus are poorly understood. To begin to address this controversy, we employed synucleinopathy murine and cell culture models, as well as postmortem human Lewy Body Dementia tissue to elucidate the extent to which pathological -synuclein localizes within the nuclear compartments, and the downstream consequences of this localization. We observed pathological aggregation of -synuclein within the nucleus in both murine models and human postmortem Lewy Body Dementia cortex via quantitative super resolution microscopy. In both mouse and human brain tissue the presence of -synuclein in the nucleus correlated with abnormal morphology of nuclei. This pathological accumulation of -synuclein in the nucleus was not observed in control mice, human tissue without pathology, or control cells. We subsequently examined the mechanistic consequences of pathological accumulation of -synuclein in the nucleus. Synucleinopathy models displayed increased levels of the DNA damage marker 53BP1. Furthermore, cells with pathological -synuclein exhibited elevated markers of nuclear envelope damage and abnormal expression of nuclear envelope repair markers. Our cell culture data also suggests altered RNA localization in response to pathological -synuclein accumulation within the nucleus. Lastly, we show that nuclear Lewy-like pathology leads to increased sensitivity to nuclear targeted toxins. Taken together, these results rigorously illustrate nuclear localization of pathological -synuclein with super resolution methodology and provide novel insight into the ensuing impact on nuclear integrity and function.

neuroscience↗

bioRxiv2025

Aggregated α-synuclein leads to corticostriatal synaptic dysfunction

Neuronal inclusions of -synuclein (-syn) are pathological hallmarks of Parkinsons disease (PD) and Dementia with Lewy Bodies (DLB). -Syn pathology accumulates in cortical neurons which project to the striatum. To begin to understand how -syn pathology effects cortico-striatal synapses, pre-formed -syn fibrils (PFF) were injected into the striatum to induce robust -syn aggregation in corticostriatal-projecting neurons. Electrophysiological recordings of striatal spiny projection neurons (SPNs) acute slices found a significant decrease in evoked corticostriatal glutamate release in mice with PFF-induced aggregates compared to monomer injected mice. Expansion microscopy, confocal microscopy and Imaris reconstructions were used to identify vGLUT1 positive presynaptic terminals juxtaposed to Homer-positive postsynaptic densities, termed synaptic foci. Quantitation of synaptic loci density revealed a loss of corticostriatal synapses. Immunoblots of the striatum show reductions in expression of pre-synaptic proteins with selective reduction in AMPA and NMDA receptor subunits in mice with -syn aggregates compared to controls. Paradoxically, a small percentage of remaining VLGUT1+ synaptic loci with small, intrasynaptic -syn aggregates showed enlarged volumes compared to nearby synapses without -syn aggregates. Our combined physiology and high-resolution imaging data point to dysfunction of corticostriatal synapses in mice harboring {square}-synuclein inclusions, which may contribute to impaired basal ganglia circuitry in PD. Highlights- Corticostriatal glutamate drive is impaired in the presence of pathological -syn - -Syn aggregation causes early loss of corticostriatal synapses - Synaptic loci positive for small -syn aggregates show volume increases - Striatal expression of select synaptic proteins are reduced in animals with -syn pathology

neuroscience↗

bioRxiv2024

Computer prediction and genetic analysis identifies retinoic acid modulation as a driver of conserved longevity pathways in genetically-diverse Caenorhabditis nematodes

Aging is a pan-metazoan process with significant consequences for human health and society--discovery of new compounds that ameliorate the negative health impacts of aging promise to be of tremendous benefit across a number of age-based comorbidities. One method to prioritize a testable subset of the nearly infinite universe of potential compounds is to use computational prediction of their likely anti-aging capacity. Here we present a survey of longevity effects for 16 compounds suggested by a previously published computational prediction set, capitalizing upon the comprehensive, multi-species approach utilized by the Caenorhabditis Intervention Testing Program (CITP). While eleven compounds (aldosterone, arecoline, bortezomib, dasatinib, decitabine, dexamethasone, erlotinib, everolimus, gefitinib, temsirolimus, and thalidomide) either had no effect on median lifespan or were toxic, five compounds (all-trans retinoic acid, berberine, fisetin, propranolol, and ritonavir) extended lifespan in Caenorhabditis elegans. These computer predictions yield a remarkable positive hit rate of 30%. Deeper genetic characterization of the longevity effects of one of the most efficacious compounds, the endogenous signaling ligand all-trans retinoic acid (atRA, designated tretinoin in medical products), which is widely prescribed for treatment of acne, skin photoaging and acute promyelocytic leukemia, demonstrated a requirement for the regulatory kinases AKT-1 and AKT-2. While the canonical Akt-target FOXO/DAF-16 was largely dispensable, other conserved Akt-targets (Nrf2/SKN-1 and HSF1/HSF-1), as well as the conserved catalytic subunit of AMPK AAK-2, were all necessary for longevity extension by atRA. Evolutionary conservation of retinoic acid as a signaling ligand and the structure of the downstream effector network of retinoic acid combine to suggest that the all-trans retinoic acid pathway is an ancient metabolic regulatory system that can modulate lifespan. Our results highlight the potential of combining computational prediction of longevity interventions with the power of nematode functional genetics and underscore that the manipulation of a conserved metabolic regulatory circuit by co-opting endogenous signaling molecules is a powerful approach for discovering aging interventions.

genetics↗

bioRxiv2024

Conditional Knockout of Striatal Gnal Produces Dystonia-like Motor Phenotypes

Loss-of-function mutations in GNAL have been linked to an adult-onset, isolated dystonia that is largely indistinguishable from idiopathic dystonia. GNAL encodes Golf, a heterotrimeric G-protein subunit with a defined molecular function to increase the production of the second messenger cAMP. Golf is abundant in the striatum, and is the only stimulatory G-protein in many cell types of the striatum. Due to the defined molecular signaling pathway and expression pattern of Golf, the clear genetic link to dystonia makes GNAL an exciting target to understand the pathological mechanisms of not only this genetic dystonia, but also the larger idiopathic disease. To better understand GNAL-linked dystonia, we generated a novel genetic mouse model that allows us to conditionally knock out Gnal in a site and time-specific manner. In the current study we used genetic or AAV based approaches to express Cre to knockout striatal Gnal in our novel Gnal fl/fl model. We then performed motor behavioral testing and ex vivo whole-cell patch clamp electrophysiology of striatal spiny projection neurons to interrogate how loss of Gnal leads to dystonia. Mice with conditional striatal knockout of Gnal show hindlimb clasping, other dystonia-like postures, less motor coordination, slowness, and torticollis as compared to age-matched controls. Furthermore, striatal spiny projection neurons show increased excitability in Gnal knockout animals. These exciting data are the first to report uninduced, overt dystonia in a mouse model of GNAL-linked dystonia, and directly correlate these with changes in spiny projection neuron electrophysiological properties. Our results show that adult loss of Gnal in the striatum leads to the development of dystonia, through homeostatic, paradoxical increases in spiny projection neuron excitability, and suggest that therapeutic strategies aimed at decreasing this hyperexcitable phenotype may provide symptomatic relief for patients with disease. One Sentence Summary: When Gnal is knocked out in the striatum of mice we observe overt behavioral symptoms and hyperexcitability in striatal spiny projection neurons.

neuroscience↗

bioRxiv2024

Cell-free screening, production and animal testing of a STI-related chlamydial major outer membrane protein supported in nanolipoproteins.

Vaccine development against Chlamydia, a prevalent sexually transmitted infection (STI), is imperative due to its global public health impact. However, significant challenges arise in the production of effective subunit vaccine based on recombinant protein antigens, particularly with membrane proteins like the Major Outer Membrane Protein (MOMP). Cell-free protein synthesis (CFPS) technology is an attractive method to address these challenges as a method of high-throughput membrane protein and protein complex production coupled with nanolipoprotein particles (NLPs). NLPs provides a supporting scaffold while allowing easy adjuvant addition during formulation. Over the last decade we have been working toward production and characterization of MOMP-NLP complexes for vaccine testing. The work presented here highlights the expression and biophysical analyses, including transmission electron microscopy (TEM) and dynamic light scattering (DLS), confirm formation and functionality of MOMP-NLP complexes for use in animal studies. Moreover, immunization studies in preclinical models compare the past and present protective efficacy of MOMP-NLP formulations, particularly when co-adjuvanted with CpG and FSL1. Ex vivo assessments further highlight the immunomodulatory effects of MOMP-NLP vaccinations, emphasizing their potential in eliciting robust immune responses. However, further research is warranted to further optimize vaccine formulations, validate efficacy against Chlamydia trachomatis, and better understand underlying mechanisms of immune response.

immunology↗

bioRxiv2024

Primary culture of high grade serous ovarian cancer cells, selection and derivation of three cell lines

Cell line models for high grade serous ovarian cancer (HGSOC) are limited in number and are poorly clinically annotated. Consequently, existing models often fail to recapitulate common features of HGSOC, inhibiting mechanistic and therapeutic discovery. We generated and characterised three spontaneously immortalized continuous HGSOC cell lines named CIOV1, CIOV2, and CIOV3 and confirmed that each cell line retained the genomic and pathologic characteristics of its parental tumour. We show that subclonal cell populations present at initiation, expanded and contracted during the culturing process before converging on a stable immortalized line. These lines are new valuable models to study acquired chemoresistance of HGSOC.

cancer biology↗

bioRxiv2024

Species wide inventory of Arabidopsis thaliana organellar variation reveals ample phenotypic variation for photosynthetic performance

Efforts to improve photosynthetic performance are increasingly employing natural genetic variation. However, genetic variation in the organellar genomes (plasmotypes) is often disregarded due to the difficulty of studying the plasmotypes and the lack of evidence that this is a worthwhile investment. Here, we systematically phenotyped plasmotype diversity using Arabidopsis thaliana as a model species. A reanalysis of whole genome resequencing data of 1,531 representative accessions shows that the genetic diversity amongst the mitochondrial genomes is eight times lower than amongst the chloroplast genomes. Plasmotype diversity of the accessions divides the species into two major phylogenetic clusters, within which highly divergent subclusters are distinguished. We combined plasmotypes from 60 A. thaliana accessions with the nuclear genomes (nucleotypes) of four A. thaliana accessions to create a panel of 232 novel cytonuclear genotypes (cybrids). The cybrid plants were grown in a range of different light and temperature conditions and phenotyped using high-throughput phenotyping platforms. Analysis of the phenotypes showed that several plasmotypes alone or in interaction with the nucleotypes have significant effects on photosynthesis, and that the effects are highly dependent on the environment. Moreover, we introduce Plasmotype Association Studies (PAS) as a novel method to reveal plasmotypic effects. Within A. thaliana, several organellar variants can influence photosynthetic phenotypes, which emphasizes the valuable role this variation has on improving photosynthetic performance. The increasing feasibility of producing cybrids in various species calls for further research into how these phenotypes may support breeding goals in crop species. Significance statementPhotosynthesis is one of the few crop traits that has been largely unaddressed which can contribute to increasing crop yield potential. Exploiting genetic variation within organellar genomes presents a promising, yet untapped resource to improve photosynthesis. However, the extent of organellar variation and its impact on photosynthesis within a species remains largely unknown. Using Arabidopsis thaliana as a model species, we revealed highly divergent clusters of organellar variation. We constructed 232 novel combinations of species representative organellar and nuclear genomes, referred to as cybrids. High-throughput phenotyping of these cybrids revealed that organellar variants can substantially impact photosynthesis in different environments. These findings indicate that organellar genomes may be a valuable resource for improving photosynthesis in crops.

plant biology↗

bioRxiv2024

Serial 'deep-sampling PCR of fragmented DNA reveals the wide range of Trypanosoma cruzi burden among chronically infected hosts and allows accurate monitoring of parasite load following treatment

Infection with the protozoan parasite Trypanosoma cruzi is generally well-controlled by host immune responses, but appears to be rarely eliminated. The resulting persistent, low-level infection results in cumulative tissue damage with the greatest impact generally in the heart in the form of chagasic cardiomyopathy. The relative success in immune control of T. cruzi infection usually averts acute phase death but has the negative consequence that the low-level presence of T. cruzi in hosts is challenging to detect unequivocally. Thus, it is difficult to identify those who are actively infected and, as well, problematic to gauge the impact of treatment, particularly in the evaluation of the relative efficacy of new drugs. In this study we employ DNA fragmentation and high numbers of replicate PCR reaction ( deep-sampling) to extend the quantitative range of detecting T. cruzi in blood by at least 3 orders of magnitude relative to current protocols. When combined with sampling blood at multiple time points, deep sampling of fragmented DNA allowed for detection of T. cruzi in all infected hosts in multiple host species. In addition, we provide evidence for a number of characteristics not previously rigorously quantified in the population of hosts with naturally acquired T. cruzi infection, including, a > 6-log variation between chronically infected individuals in the stable parasite levels, a continuing decline in parasite load during the second and third years of infection in some hosts, and the potential for parasite load to change dramatically when health conditions change. Although requiring strict adherence to contamination-prevention protocols and significant resources, deep-sampling PCR provides an important new tool for assessing new therapies and for addressing long-standing questions in T. cruzi infection and Chagas disease. Author SummaryInfection by the protozoan Trypanosoma cruzi normally results in a life-long, but low-level parasitization of muscle tissues, often leading to chagasic heart disease. A major challenge in the Chagas disease field has been the difficulty in detecting and quantifying parasite load in infected hosts. In this study we show that collection of serial blood samples and performance of sometimes high numbers of replicate PCR reactions on fragmented blood DNA, allows detection and quantification of relative parasite load in non-human primates, dogs, and humans with naturally acquired T. cruzi infection. This deep-sampling approach reveals a mostly stable, 100,000-fold or greater difference in parasite load among chronically infected hosts and can detect alterations in parasite levels due to changes in health status or following therapeutic treatment in individual hosts, thus providing a powerful tool for assessing treatment outcomes in T. cruzi infection, including for evaluation of new therapeutics. Additionally, the ability to accurately and sensitively monitor parasite load in hosts provides the means to address highly contentious issues in the Chagas field, including the relative role of parasites and hosts in establishing the persistent parasite burden and the relationship between parasite burden and the presence and severity of clinical disease.

microbiology↗

bioRxiv2024

Principal component analysis revisited: fast multi-trait genetic evaluations with smooth convergence

A cornerstone in breeding and population genetics is the genetic evaluation procedure, needed to make important decisions on population management. Multivariate mixed model analysis, in which many traits is considered jointly, utilizes genetic and environmental correlations between traits to improve the accuracy. However, the number of parameters in the multi-trait model grows exponentially with the number of traits which reduces its scalability. Here, we suggest using principal component analysis (PCA) to reduce the dimensions of the response variables, and then using the computed principal components (PC) as separate responses in the genetic evaluation analysis. As PCs are orthogonal to each other, multivariate analysis is no longer needed and separate univariate analyses can be performed instead. We compared the approach to traditional multivariate analysis in terms of computational requirement and rank lists according to predicted genetic merit on two forest tree datasets with 22 and 27 measured traits respectively. Obtained rank lists of the top 50 individuals were in good agreement. Interestingly, the required computational time of the approach only took a few seconds without convergence issues, unlike the traditional approach which required considerably more time to run (seven and ten hours respectively). Our approach can easily handle missing data and can be used with all available linear mixed models software as it does not require any specific implementation. The approach can help to mitigate difficulties with multi-trait genetic analysis in both breeding and wild populations.

genetics↗