Biology subjects

Braun, J.

Publications and source records attributed to Braun, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Rac1 deficiency reduces mitochondrial respiratory capacity, impairs fatty acid metabolism and causes muscle wasting

BackgroundThe age-related progressive decline in skeletal muscle function is characterised by declining mitochondrial quality control and perturbed fatty acid metabolism, contributing to frailty and increased mortality. The actin cytoskeleton, a key structural component of skeletal muscle, has recently been implicated in mitochondrial anchoring and dynamics. However, the role of actin-regulating proteins, including the Rho GTPase Rac1, in mitochondrial function and age-associated metabolic and functional muscle deterioration remains undefined. MethodsSkeletal muscle from mice with inducible muscle-specific deletion of Rac1 (Rac1 imKO) underwent unbiased mass spectrometry-based proteomic profiling. Mitochondrial morphology was assessed by transmission electron microscopy, and physiological parameters, including muscle mass and contraction-stimulated palmitate oxidation in isolated soleus muscle, were evaluated. Mitochondrial respiratory function was determined by high-resolution respirometry in permeabilised gastrocnemius skeletal muscle fibre bundles. Biochemically, muscular triacylglycerol (TG) content, mRNA (qPCR) and protein (immunoblotting) content were determined. In vastus lateralis muscle biopsies from healthy, untrained young (20-30 years) and old, sarcopenic (83-94 years) men, Rac1 and mitochondrial respiratory protein abundances were measured. A complementary human genetic association analysis was performed using the FinnGen dataset. ResultsRac1 deficiency triggered muscle wasting in middle-aged mice (Gastrocnemius: -10%; Quadriceps: -7%). Preceding muscle wasting, gene set enrichment analysis identified enrichment in fatty acid metabolism and oxidative phosphorylation pathways, consistent with increased mitochondrial volume density in Rac1 imKO muscle (subsarcolemmal: +467%; intermyofibrillar: +166%). Despite mitochondrial expansion at this stage, Rac1 deficiency attenuated the increase in palmitate oxidation in response to muscle contraction (-62%). At the muscle-wasting stage, Rac1 imKO muscle exhibited reduced mitochondrial respiratory capacity (-25-32%). Additionally, the mitochondrial dysfunction was associated with an accumulation of muscle TG (+78%, p = 0.096) and upregulation of fatty acid transporter, CD36 protein content (+25%), indicative of altered fatty acid handling. In humans, Rac1 muscle protein content was increased in old, sarcopenic subjects compared to young (+41%), and negatively correlated with quadriceps cross-sectional area (CSA) (r = -0.475) and type II fibre CSA (r = -0.466). In old, sarcopenic muscle, Rac1 protein content correlated negatively with protein content of multiple mitochondrial respiratory complexes (CI: r = -0.690, CIV: r = -0.938, CV: r = -0.704). GWAS further identified associations between Rac1 SNP variants and lipid metabolic and muscle-wasting diseases. ConclusionsMuscle Rac1 deficiency reduces mitochondrial respiratory capacity and metabolic flexibility through impaired fatty acid metabolism, leading to muscle wasting and highlighting a potential therapeutic target in age-related functional decline.

Molecular Biology↗

bioRxiv2026

FENNEC: Fine-Tuned Ensemble Neural Networks Accelerate Chemically Modified siRNA Design and Screening

Small interfering RNAs (siRNAs) are a clinically validated therapeutic modality, yet designing potent chemically modified siRNAs remains a costly and iterative process, limited by scarce public data. Computational prediction of siRNA efficacy is therefore essential for rational design and accelerated preclinical development. However, despite the critical role of chemical modifications in therapeutic performance, current state-of-the-art machine learning methods either are not designed to model the chemical diversity of therapeutic siRNAs, or exhibit poor generalization performance. Here, we present FENNEC (Fine-Tuned Ensemble of Neural Networks for siRNA Efficiency Characterization), a machine-learning framework for predicting siRNA activity across chemically diverse design spaces. To support this effort, we curated the largest patent-derived dataset to date of chemically modified siRNAs from 42 patents using OCR-based table extraction and stringent filtering. FENNEC combines temporal convolutional networks with thermodynamic descriptors, experimental covariates, and embeddings from RNA foundation models to capture both local chemical determinants and broader target-context information. Importantly, we show that language-model-derived embeddings provide meaningful higher-order representations of target transcripts, particularly in data-scarce settings. FENNEC achieved robust predictive performance across both gene-level and scaffold-level validation settings, with additional experimental validation on a novel AHSA1-targeting dataset further supporting its generalizability across chemically modified siRNAs. In benchmarking, FENNEC outperformed classical machine-learning and state-of-the-art deep learning models, demonstrating generalization to unseen chemistry. Model interpretation recovered established design principles, including position-specific effects of glycol nucleic acid, 2'-fluoro modifications, and phosphorothioate backbones. Furthermore, in silico perturbation analyses suggest that FENNEC can serve not only as a predictive model, but also as an oracle for the design and optimization of chemically modified siRNAs. Together, our work addresses a key gap in the field by enabling chemically aware deep learning for siRNA design, supported by a large and diverse collection of chemically modified siRNA measurements.

bioinformatics↗

bioRxiv2026

Environmental Microbial Community Signatures Associated with Listeria spp. Detection in German Meat Processing Facilities

Listeria monocytogenes can persist in niches of meat processing environments despite routine cleaning and disinfection. Its persistence may depend not only on stress tolerance but also on interactions with resident microbial communities, which may promote or inhibit survival. However, these ecological relationships remain poorly understood. We combined 16S rRNA V3/V4 amplicon sequencing, culture-based detection, and multilocus sequence typing (MLST) to characterize microbial communities in six German meat processing facilities over one year. We examined associations among community structure, sampling sites (drains and food-contact surfaces), and the occurrence of Listeria spp., including L. monocytogenes. Microbial communities were dominated by core genera typical of food-processing environments, particularly Pseudomonas spp. and Acinetobacter spp., but differed significantly among facilities (PERMANOVA, p = 0.001; pairwise R{superscript 2} = 0.023-0.079), indicating facility-specific communities. Culture-based analyses detected Listeria spp. in 51 of 370 environmental samples (13.8%), mainly from drains (44/51, 86.3%). L. monocytogenes was detected in five of six facilities, with 19 of 21 isolates originating from drains (90.5%). MLST of 74 typeable L. monocytogenes isolates revealed high diversity, comprising 21 sequence types across 15 clonal complexes, with lineage II predominating (86.5%). Overall microbial community composition was significantly associated with Listeria spp. and L. monocytogenes presence (PERMANOVA, p = 0.001; R{superscript 2} = 0.0137 and 0.0083). In drains, ASVs assigned to Acinetobacter, Rhizorhapis, and Vagococcus species showed positive associations with Listeria spp.-positive samples. Together these findings suggest that drains are key ecological niches for Listeria spp. and that associated taxa may indicate drain communities linked to Listeria spp. recovery. IMPORTANCEListeria monocytogenes is a major foodborne pathogen that can persist in meat processing environments despite routine cleaning and disinfection. Resident microbial communities may influence its survival, but longitudinal studies linking those communities with culture-based Listeria spp. detection remain limited. Here, we characterized microbial communities in six German meat processing facilities over 1 year using 16S rRNA gene amplicon sequencing and culture-based Listeria spp. detection, and MLST of L. monocytogenes isolates. We identified facility-specific microbial communities, identified floor drains as key niches for Listeria spp., and observed repeated recovery of different L. monocytogenes sequence types across facilities. In drains, ASVs assigned to the genera Acinetobacter, Rhizorhapis, and Vagococcus species were positively associated with culture-positive samples, identifying candidate taxa that may reflect microbial conditions associated with Listeria spp. recovery. These findings highlight the importance of considering not only whether Listeria spp. are detected, but also the resident microbial communities that may support their fitness.

microbiology↗

bioRxiv2025

A complex osteoporotic milieu is associated with arterial stiffening and PDGF-BB-mediated calcification of human smooth muscle cells

Accumulating evidence links skeletal and vascular aging, yet the pathological cross-talk between osteoporotic bone and vascular calcification remains insufficiently understood. In this retrospective exploratory study, we show that osteoporotic individuals exhibit a distinct systemic milieu characterized by elevated eosinophil, neutrophil, and platelet counts, as well as altered levels of sCD40L, PDGF-BB, osteopontin, and SDF-1. These changes correlate with both bone metabolism and arterial stiffness, indicating a multifactorial bone-vascular interplay. Moreover, osteoporotic sera accelerated calcification of human vascular smooth muscle cells in vitro, with PDGF-BB emerging as a central mediator. Inhibition of PDGF-BB downstream signaling blocked this effect, suggesting a mechanistic role of PDGF-BB in linking the osteoporotic milieu to vascular calcification. Conceptualizing this cross-talk as a complex adaptive system advances our understanding of the disease dynamics between localized bone loss and vascular pathologies. Furthermore, it may guide therapeutic strategies, with PDGF-BB as a potential target, to support healthier aging.

cell biology↗

bioRxiv2025

Liver Viscosity Decreases Before the Onset of Fibrosis in Metabolic Dysfunction-Associated 1 Steatohepatitis (MASH)

Background and AimMetabolic dysfunction-associated steatohepatitis (MASH) is an increasingly prevalent condition worldwide, associated with biomechanical liver changes and detectable by magnetic resonance elastography (MRE). This study explored the pathophysiological features and their biomechanical manifestations at different stages of MASH in a mouse dietary model. MethodsUsing MRE on a clinical 3 Tesla MRI scanner, we measured liver stiffness, viscosity, fat fraction and water diffusion in 45 male mice. These values were correlated with histopathology and proteomics analyses to further characterize the liver microstructural and metabolic changes during MASH progression. ResultsWe found in a high-fat, low amino-acid model that early MASH was marked by fat accumulation and increasing inflammatory activity, while later stages showed a reduction in fat despite persistent inflammation. These changes in microstructure were associated with biomechanical adaptations, including a progressive decrease in hepatic viscosity and the water diffusion. Notably, viscosity was inversely correlated with lobular inflammation, cell adhesion, antioxidant activity, and metabolic adaptations such as enhanced ketone body synthesis. These findings, which precede the onset of fibrosis and tissue stiffening, show that tissue viscosity is highly sensitive to early microstructural and metabolic alterations in MASH. ConclusionSteatosis and inflammation significantly alter liver biophysical properties, particularly viscosity, in a mouse dietary model of MASH, even in the absence of fibrosis. These findings suggest that viscosity is a potential early and clinically translatable biomarker for the development and progression of MASH.

biophysics↗

bioRxiv2025

Longitudinal in vivo MR elastography reveals whole-liver viscoelastic involvement in a murine model of hepatocellular carcinoma

Cancer cells actively shape their microenvironment and adapt the physical and biomechanical properties of the host tissue. However, for organs like the liver, especially in vivo, it remains unclear at what rate and spatial extent macroscopic viscoelastic properties change during formation of a cancer-permissive environment. Using clinical multifrequency magnetic resonance elastography (MRE) in a mouse model of hepatocellular carcinoma (HCC), we identified surprisingly early and large-scale viscoelasticity changes leading to whole-liver biomechanical involvement stretching far beyond the local cancer microenvironment. Widespread liver softening began two weeks after HCC inoculation, followed by a decrease in tissue viscosity and fluidity two weeks later, preceding any macroscopic evidence of local tumor growth. In contrast, local lesions with stiff-rigid biomechanical properties were not detectable by standard MRI and MRE until five to six weeks post-injection. Furthermore, tumor viscoelasticity correlated with that of the host liver, also suggesting a possible widespread adaptation of the biomechanical properties beyond the tumor margins and its local niche during early liver colonization. The observed large-scale viscoelastic signature, detectable just two weeks after tumor cells injection, could serve as a non-invasive imaging biomarker to inform physicians about tumor niche formation and liver cancer progression long before any macroscopic manifestation of solid tumors.

biophysics↗

bioRxiv2025

Failed Metabolic Adaptation to Stress Underlies Pathogenesis in a Heterozygous Genetic Disorder

Disorders linked to heterozygous variants occupy a continuum in terms of the timing and severity of phenotypic emergence. An important question regarding this variability entails the effect stress has on the residual protein function. Using Darier disease (DD), caused by heterozygous variants of the SERCA2 calcium pump, as a model, we uncovered a potential connection between extrinsic stress and pathogenesis. The skin lesions characteristic of DD entail loss of intercellular adhesion and rarely appear pre-adolescence, suggesting that factors beyond heterozygosity contribute to disease pathogenesis. Testing whether age-related stressors contribute to DD, we show that DD patient-derived keratinocytes subjected to stress yield twice the reactive oxygen species of controls, accompanied by greater disruption of intercellular adhesion. Metabolic analysis of DD cells revealed perturbation of the pentose phosphate pathway (PPP), a stress response system responsible for regenerating antioxidants like glutathione. At baseline, DD cells had less free glutathione but an increase in protective glutathione-based modifications of SERCA2, a reversible form of protein oxidation. With stress, DD cells form an aberrant, heavily glutathionylated perinuclear halo consisting of keratin and the intercellular adhesion component, desmoplakin. We propose a model whereby SERCA2 heterozygosity causes mild oxidative stress that under homeostatic conditions can be buffered by glutathionylation. When stressed, the depleted glutathione store is shunted towards the desmoplakin-intermediate filament system at the expense of SERCA2, rendering it vulnerable to damage. A lesional flare, then, would represent a case of more complete SERCA2 inhibition and a novel example of how heterozygous disorders interact with stress to disrupt intercellular adhesion.

cell biology↗

bioRxiv2025

Inflammatory disease microbiomes share a functional pathogenicity predicted by C-reactive protein

We examine disease-specific and cross-disease functions of the human gut microbiome by colonizing germ-free mice, at risk for inflammatory arthritis, colitis, or neuroinflammation, with over 100 human fecal microbiomes from subjects with rheumatoid arthritis, ankylosing spondylitis, multiple sclerosis, ulcerative colitis, Crohns disease, or colorectal cancer. We find common inflammatory phenotypes driven by microbiomes from individuals with intestinal inflammation or inflammatory arthritis, as well as distinct functions specific to microbiomes from multiple sclerosis patients. Inflammatory disease in mice colonized with human microbiomes correlated with systemic inflammation, measured by C-reactive protein, in the human donors. These cross-disease patterns of human microbiome pathogenicity mirror features of the inflammatory diseases, including therapeutic targets and the presence or absence of systemic inflammation, suggesting shared and disease-specific mechanisms by which the microbiome is shaped and drives pathogenic inflammatory responses.

immunology↗

bioRxiv2024

Resolving the design principles that control postnatal vascular growth and scaling

After birth, tissues grow continuously until reaching adult size, with each organ exhibiting unique cellular dynamics, growth patterns, and (stem or non-stem) cell sources. Using a suite of experimental and computational multiscale approaches, we found that aortic expansion is guided by specific biological principles and scales with the vertebral column rather than animal body weight. Expansion proceeds via two distinct waves of arterial cell proliferation along blood flow that are spatially stochastic, yet temporally coordinated. Each wave exhibits unique cell cycle kinetics and properties, with the first wave exhibiting cell cycle durations as fast as 6 hours. Single-cell RNA sequencing showed changes in fatty acid metabolism concomitant with an increase in cell size. Mathematical modeling and experiments indicated endothelial cell extrusion is essential for homeostatic aortic growth and balancing excess proliferation. In a genetic model of achondroplasia, the aorta achieves proper scaling through enhanced cell extrusion while maintaining normal proliferation dynamics. Collectively, these results provide a blueprint of the principles that orchestrate aortic growth which depends entirely on differentiated cell proliferation rather than resident stem cells.

developmental biology↗

bioRxiv2024

Aging and viral evolution impair immunity against dominant pan-coronavirus-reactive T cell epitope

Immune evasion by escape mutations subverts immunity against SARS-CoV-2. A role of pan-coronavirus immunity for more durable protection is being discussed but has remained understudied. We here investigated the effects of age, mutations, and homo-/heterologous vaccination regimens on the dominant pan-coronavirus-specific cellular and humoral epitope iCope after SARS-CoV-2 infection and vaccination in detail. In the older, quantitatively, and qualitatively reduced iCope-reactive CD4+ T cell responses with narrow TCR repertoires could not be enhanced by vaccination and were further compromised by emerging spike mutations. In contrast pan-coronavirus-reactive humoral immunity was affected only by mutations and not by age. Our results reveal a distinct deficiency of the dichotomous layer of pan-coronavirus immunity in the older, critical for long-term protection against SARS-CoV-2 variants. One-Sentence SummaryAging and viral evolution impair dominant pan-coronavirus immunity, a hallmark of efficient and broad immune competence against SARS-CoV-2

immunology↗

bioRxiv2024

Paradigm shift in biomarker translation: a pipeline to generate clinical grade biomarker candidates from DIA-MS discovery

Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package. This innovative tool uses the discovery cohort analysis to select precursors, peptides, and proteins that adhere to established targeted assay criteria. TEAQ was applied to Data-Independent Acquisition MS data from plasma samples acquired on an Orbitrap Astral MS. Identified precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation from 11-point loading curves under three throughputs, to develop a resource for clinical-grade targeted assays. From a clinical cohort of individuals with inflammatory bowel disease (n=492), TEAQ successfully identified 1116 signature peptides for 327 quantifiable proteins from 1180 identified proteins. Embedding stringent selection criteria adaptable to targeted assay development into the analysis of discovery data will streamline the transition to validation and clinical studies.

biochemistry↗

bioRxiv2023

Networks of descending neurons transform command-like signals into population-based behavioral control

To transform intentions into actions, movement instructions must pass from the brain to downstream motor circuits through descending neurons (DNs). These include small sets of command-like neurons that are sufficient to drive behaviors--the circuit mechanisms for which remain unclear. Here, we show that command-like DNs in Drosophila directly recruit networks of additional DNs to orchestrate flexible behaviors. Specifically, we found that optogenetic activation of command-like DNs previously thought to drive behaviors alone in fact co-activate larger populations of DNs. Connectome analysis revealed that this functional recruitment can be explained by direct excitatory connections between command-like DNs and networks of interconnected DNs in the brain. The size of downstream DN networks is predictive of whether descending population recruitment is necessary to generate a complete behavior: DNs with many downstream descending partners require network recruitment to drive flexible behaviors, while neurons with fewer partners can alone drive stereotyped behaviors and simple movements. Finally, DN networks reside within behavior-specific clusters that inhibit one another. These results support a mechanism for command-like descending control whereby a continuum of stereotyped to flexible behaviors are generated through the recruitment of increasingly large DN networks which likely construct a complete behavior by combining multiple motor subroutines.

neuroscience↗

bioRxiv2023

Contrasting Effects of SARS-CoV-2 Vaccination vs. Infection on Antibody and TCR Repertoires

Antibodies and helper T cells play important roles in SARS-CoV-2 infection and vaccination. We sequenced B- and T-cell receptor repertoires (BCR/TCR) from the blood of 251 infectees, vaccinees, and controls to investigate whether features of these repertoires could predict subjects SARS-CoV-2 neutralizing antibody titer (NAbs), as measured by enzyme-linked immunosorbent assay (ELISA). We sequenced recombined immunoglobulin heavy-chain (IGH), TCR{beta} (TRB), and TCR{delta} (TRD) genes in parallel from all subjects, including select B- and T-cell subsets in most cases, with a focus on their hypervariable CDR3 regions, and correlated this AIRRseq data with demographics and clinical findings from subjects electronic health records. We found that age affected NAb levels in vaccinees but not infectees. Intriguingly, we found that vaccination and infection have an effect on non-productively recombined IGHs, suggesting an effect that precedes clonal selection. We found that repertoires binding capacity to known SARS-CoV-2-specific CD4+ TRBs performs as well as the best hand-tuned approximate or "fuzzy" matching at predicting a protective level of NAbs, while also being more robust to repertoire sample size and not requiring hand-tuning. The overall conclusion from this large, unbiased, clinically well annotated dataset is that B- and T-cell adaptive responses to SARS-CoV-2 infection and vaccination are surprising, subtle, and diffuse. We discuss methodological and statistical challenges faced in attempting to define and quantify such strong-but-diffuse repertoire signatures and present tools and strategies for addressing these challenges.

immunology↗

bioRxiv2023

Navigating Pubertal Goldilocks: The Optimal Pace for Hierarchical Brain Organization

Adolescence is a timed process with an onset, tempo, and duration. Nevertheless, the temporal dimension, especially the pace of maturation, remains an insufficiently studied aspect of developmental progression. This study focuses on the modifications due to the different timings of developmental shifts during adolescence and addresses the impact of adolescent maturation on brain development. To reveal potential relationships between pubertal pace and the advancement of brain organisation, we analyse the connection between skeletal age-based maturation stages and hierarchical organisation in the temporal dynamics of resting-state EEG recordings (alpha frequency range). By adopting skeletal maturity as a proxy for pubertal progress and employing entropy production to measure hierarchical brain organisation, our findings indicate that an average maturational trajectory optimally aligns with cerebral hierarchical order. Adaptive developmental plasticity may not fully compensate for accelerated or decelerated timelines, potentially increasing the risk of behavioural problems and psychiatric disorders consequent to such alterations.

neuroscience↗

bioRxiv2023

Incidental learning of predictive temporal context within cortical representations of visual shape.

Incidental learning of spatio-temporal regularities and consistencies - also termed statistical learning - may be important for discovering the causal principles gov-erning the world. We studied statistical learning of temporal structure at two temporal scales: the presentation of rotating visual objects (3 s) and predictive temporal context (30 s) in a sequence of such objects. Observers viewed fifteen initially unfamiliar synthetic objects recurring many times each, intermixed with other similar objects that appeared only once, while whole-brain BOLD activity was recorded. Analyzing multivariate BOLD activity, we located view-independent responses to synthetic objects throughout the ventral occipitotemporal cortex, revealing a view-invariant representation of object shape. Predictive temporal context modified representations of object shape at early and middle levels of the visual processing hierarchy. Approximately 20% of the sites representing shape also exhibited a significant representation of temporal context. A few higher-level sites represented temporal context, without also representing object shape. Additionally, objects marking transitions between communities were distinctly represented at many sites. We conclude that, at the sensitivity afforded by fMRI, the cortical represen-tations of invariant visual shape and of predictive temporal context are largely coextensive. Our results suggest that incidental learning of causal principles and structures operating at different timescales ("structural learning") may involve vi-sually responsive areas in the ventral occipitotemporal cortex.

neuroscience↗

bioRxiv2023

Gradual change of cortical representations with growing visual expertise for synthetic shapes.

Visual expertise for particular categories of objects (e.g., birds, mushrooms, minerals, and so on) is known to enhance cortical responses in parts of the ventral occipitotemporal cortex. How is such additional expertise integrated into the prior cortical representation of life-long cumulative visual experience? To address this question, we record multivariate BOLD responses to synthetic visual objects and track changes in pairwise distance as initially unfamiliar objects gradually become familiar ( representational similarity analysis, RSA). We find view-independent responses to synthetic shapes (i.e., an invariant representation) in large parts of the ventral occipitotemporal cortex, including the primary visual cortex. Surprisingly, the quality of representation is already high even when shapes are still unfamiliar. As shapes become familiar with repeated viewing, this quality remains high, but representational geometry shifts with more experience. For visually similar shapes that are not repeated and therefore remain unfamiliar, the representation degrades and becomes progressively marginalized. We conclude that, at least for highly dissimilar synthetic shapes, functional imaging responses can reveal detailed representational geometry at the level of exemplars, as well as gradual changes in this geometry due to experience and learning.

neuroscience↗

bioRxiv2022

SDRAP for annotating scrambled or rearranged genomes

DNA rearrangements are important in various contexts, such as in vertebrate immunity, and cancer genome instability. The single-celled eukaryote Oxytricha trifallax undergoes massive and reproducible genome rearrangement during post-zygotic development, making it a compelling model organism to study DNA rearrangements. To date, computational tools for the extraction and analysis of rearrangement annotations lack transparency and rely on assumptions that may not hold for all analyzed data, leading to irreproducibility of results and loss of information through data filtering or misrepresentation. An implementation of a procedure for the annotation and analysis of DNA rearrangement as a web application is discussed and tested. The resulting annotations provide an improvement over previous annotations in the following manner. (a) SDRAP achieves more complete precursor-product mappings than previous software (b) the software allows for full transparency of all parameters used during the annotation and therefore facilitates reproducible results, and (c) this parameter transparency makes SDRAP suitable for comparison of genomic data from different sources, including cancer genomes. This work introduces a theoretical framework and software to systematically extract and analyze annotations from pairs of genome assemblies corresponding to precursor and product rearrangement data. The software makes no assumptions about the structure of the rearrangements, and permits the user to select parameters to suit the data.

bioinformatics↗

bioRxiv2022

ct2vl: Converting Ct Values to Viral Loads for SARS-CoV-2 RT-qPCR Test Results

RT-qPCR is the de facto reference method for detecting the presence of SARS-CoV-2 genomic material in infected individuals (1). Although RT-qPCR is inherently quantitative and despite SARS-CoV-2 viral loads varying by 10 orders of magnitude and therefore being potentially highly clinically informative, in practice SARS-CoV-2 RT-qPCR results are usually reported qualitatively as simply positive or negative. This is both because of the mathematical complexity of converting from Ct values to viral loads and because the same Ct value can correspond to orders-of-magnitude differences in viral load depending on the testing platform (2, 3, 4). To address this problem, here we present ct2vl, a Python package designed to help individual clinical laboratories, investigators, and test developers convert from Ct values to viral loads on their own platforms, using only the data generated during validation of those platforms. It allows any user to convert Ct values to viral loads and is readily applicable to other RT-qPCR tests. ct2vl is open source, has 100% code coverage, and is freely available via the Python Package Index (PyPI). IMPORTANCEUp to now, COVID-19 test results have been reported as positive vs. negative, even though "positive" can mean anywhere from 1 copy of SARS-CoV-2 virus per milliliter of transport media to over 1 billion copies/mL, with attendant clinical consequences. Democratizing access to this quantitative data is the first step toward its eventual incorporation into test development, the research literature, and clinical care.

microbiology↗