Biology subjects

Robinson, M.

Publications and source records attributed to Robinson, M..

At least 19 recordsLinked to original sources

bioRxiv2026

A cuffed CRISPR guide RNA for microRNA activity-dependent genome editing

Cells in multicellular eukaryotic systems are diverse biological units, with characteristics and functions determined by their molecular profiles. CRISPR-Cas9 genome editing has been widely used across biology to modulate gene expression and study gene function. However, there is currently no versatile and scalable method for editing a cells genome in response to endogenous cellular signals. Here, we report the engineering of a CRISPR guide RNA that efficiently confers genome editing in response to the catalytic activity of a target microRNA (miRNA) within a cell. miRNAs are short non-coding RNAs that are widely conserved across eukaryotes and can cleave their target RNA through almost perfect base pairing. In mammals, miRNAs are largely involved in development and homeostasis as well as disease progression and developmental disorders. To leverage these properties for genome editing, we developed a cuffed guide RNA (cgRNA) which is composed of a permutated order of sequence domains from the commonly used single guide RNA (sgRNA). These permutated domains were then concatenated with a miRNA target sequence, yielding a warped guide RNA that is inactive until cleaved by a complementary miRNA. We demonstrated that cgRNA enabled efficient miRNA activity-dependent genome editing in human and mouse cell lines. Biochemical and structural analyses revealed three stages of inhibition of the CRISPR genome-editing pathway for unprocessed cgRNA. Utilizing a lentiviral library of cgRNAs containing miRNA targets covering mouse genome-wide miRNAs, we identified miRNA cleavage activities and their sequence specificities in mouse embryonic stem cells and during smooth muscle cell differentiation. Furthermore, we showed that endogenous mRNA expression could be irreversibly recorded into a DNA sequence using a cgRNA targeted by a synthetic miRNA repeat. cgRNA is a simple, robust, miRNA activity-gated genome editing system that could facilitate the development of cell state-specific genome editing, the mapping of miRNA activity and gene expression landscapes, and the recording of molecularly determined cell states during the long-term progression of multicellular systems.

bioengineering↗

bioRxiv2026

Buried in two places: Lineages from elite Maya tombs also found in distant caves

Classic Maya societies (250-900 CE) carved out urban centers in the rainforest reaching population heights and political complexity previously unknown in the Mesoamerican tropics. Kinship was a central feature of the social fabric, and rulership was legitimized through claims of direct descent from mythical ancestors. Mortuary practices kept the dead close to the living, and ancestor veneration sometimes produced complex deposits of disarticulated remains that are difficult to identify and whose biological relationships to one another cannot be understood without genetic data. We screened 487 human tooth and bone samples and successfully generated genome-wide data for 430 of them. Of these, 341 samples representing 107 distinct individuals were recovered from both elite and non-elite tombs in a Classic period kingdom (250-900) CE in the rugged Maya Mountains of Belize. Remarkably, 24 of these individuals have skeletal elements in both an elite tomb and in a ritual tooth cache in a distant cave located 26.5km away on the other side of the Maya Mountains. These results indicate that elite lineages created ancestors from their deceased relatives in geographically expansive ways and highlights the importance of caves in the belief system of Classic Maya elites.

genetics↗

bioRxiv2026

Cancer-Causing Mutations Alter the Interplay Between Loop Dynamics and Catalysis in the Protein Tyrosine Phosphatases SHP-1 and SHP-2

The protein tyrosine phosphatases (PTPs) SHP-1 and SHP-2 play complex roles in a variety of signaling pathways, including those involved in cancers and other diseases, making them important drug targets. These two PTPs have superimposable active sites, but different biological functions in vivo, including opposing roles in cancer development. Unique to these PTPs is the presence of two tandem Src homology 2 (SH2) domains, which regulate access to the phosphate binding site in the catalytic domain, through an autoinhibition mechanism. Studies of the allosteric regulation and dynamics of these PTPs, as well as associated drug discovery efforts, typically focus on autoinhibition rather than the dynamics of a catalytic loop in the phosphatase domain, the WPD-loop, which is essential for PTPase activity. However, recent deep mutational scanning data has demonstrated that oncogenic mutations also regulate WPD-loop motion in SHP-2. We provide here a detailed computational study of WPD-loop dynamics and catalysis in wild-type and mutant full-length and truncated (catalytic domain only) SHP-1 and SHP-2, demonstrating that many oncogenic residues lie on the allosteric pathways regulating WPD-loop dynamics. Mutations at these positions alter WPD-loop dynamics, disrupting the active site and negatively impacting catalysis. Further, our simulations provide molecular insight into the link between the presence of the SH2 domains and loop motion in the catalytic domain, and, importantly, how it differs between the two PTPs. Taken together, our work showcases the impact of altered WPD-loop motion in oncogenic SHP-1 and SHP-2 variants, opening new strategies for selectively targeting these important therapeutic enzymes.

biochemistry↗

bioRxiv2025

Model-based Standardization of Correlation Coefficients Improves Multi-Omic Clustering and Biological Signal Discovery

Multi-omic data pose a particular challenge for Weighted Correlation Network Analysis (WCNA or WGCNA) due to (platform- or) batch-specific characteristics, such as resolution, accuracy, dynamic range, and sources of spurious variation. When unaccounted for, these differences can result in a bias toward single-batch clusters as well as greater sensitivity to "noisier" batches during clustering. Here we propose mitigating these effects using null models fitted separately to the bulk of analyte-analyte correlations within each batch and across each pair of batches. We then map the batch-specific null models to a standard null model, removing batch-dependent distributional differences. This approach is compatible with any correlation-based clustering approach. Since the null model represents information not captured in individual pairwise correlations, we show how to incorporate this additional information into both distance-based clustering and WCNA. For distance-based clustering, we increase distances corresponding to correlations consistent with the null model. For WCNA, we provide a new soft threshold (adjacency) function based on the likelihood of a correlation under the null model. The resulting network can be easily incorporated into the WCNA workflow. These methods are implemented in R package standardcor, and we illustrate the package on simulated data as well as an existing multi-omic dataset.

bioinformatics↗

bioRxiv2025

Minimal Perturbation of Activation Loop Dynamics Rewires KinaseSignaling

Enzymes are central to life, with their catalytic activity often shaped by the dynamic conformations of regulatory loops. In hub enzymes such as tyrosine kinases, the activation loop critically controls substrate specificity, catalytic efficiency, and downstream signaling, shaping cellular fate. Yet, the molecular mechanisms by which loop dynamics encode these functions remain incompletely understood. Here, we used SRC kinase as a model to dissect how minimal perturbations of the activation loop reprogram kinase behavior. By generating and characterizing multiple variants, we identified a triple-deletion mutant with altered loop dynamics. Structural and biochemical analyses revealed that this variant explores distinct loop conformations and exhibits a subtle shift in substrate preference toward more acidic motifs. These fine-tuned conformational changes translated into specific cellular signaling outcomes, as demonstrated by phosphoproteomic profiling. Comparative analysis across species further showed that nature exploits similar loop remodeling strategies to modulate kinase function. Together, our findings provide a blueprint for rationally tuning kinase activity and offer a generalizable framework for rewiring signaling pathways in diverse cellular contexts.

biochemistry↗

bioRxiv2025

In vitro and in vivo derived macrophages occupy distinct phenotypic states

Monocyte-derived macrophages (MDMs) are widely used to model human macrophage biology in vitro and standardized polarization conditions were proposed to recapitulate the different macrophage activation states. Although surface markers specific for distinct MDM populations have been identified, a systematic analysis of surface marker expression on these consensus MDM populations has not previously been reported. Here, we use mass cytometry to perform an in-depth characterization of MDM surface profiles and determine how these markers evolve with time. We also compared the phenotypes found in vitro with patient-derived tumor-associated macrophages (TAMs) and found that although MDMs and TAMs shared most markers investigated, the cell-surface signatures markedly differed in terms of expression levels and combinations. Our high-dimensional, single-cell analyses clarifies the surface expression profile of the core in vitro differentiated macrophage populations and highlights some limitations of the in vitro system to represent the complexity of in vivo polarized tumor-associated macrophage phenotypes. These findings provide new opportunities to improve the models used to study macrophage biology and give a pathway to improve our understanding of the in vivo complexity of these systems.

immunology↗

bioRxiv2025

Epilepsy-Associated SCN2A-L1342P Mutation Drives Network Hyperexcitability and Widespread Transcriptomic Changes in Human Cortical Organoids

ObjectiveSCN2A pathogenic mutations, such as the recurrent heterozygous Nav1.2-L1342P, are monogenic causes of epilepsy. In this human-induced pluripotent stem cell model system, we aim to investigate the molecular and cellular mechanisms underlying the SCN2A-L1342P-associated pathology. MethodsUsing a human male iPSC reference line (KOLF) carrying the Nav1.2-L1342P mutation, we generated 3D cortical organoids for functional studies. Patch clamp and multi-electrode array (MEA) recordings, immunocytochemistry, and RNA sequencing were used to characterize the disease phenotypes. ResultsNav1.2-L1342P organoid neurons displayed increased intrinsic excitability, and amplified excitatory post-synaptic currents, which are consistent with an increase in excitatory synapse formation revealed by PSD95/SYN1 immunostaining. Moreover, elevated network firing activity, as demonstrated by MEA, indicates a pronounced network hyperexcitability. Transcriptomic profiling of organoids carrying the Nav1.2-L1342P mutation further revealed significant alterations in synaptic, glutamatergic, and developmental pathways. SignificanceOur findings demonstrate that the Nav1.2-L1342P mutation drives a multifaceted disease phenotype, including network hyperexcitability and disruption of pathways related to neuronal and synaptic functions. These results advance our understanding of SCN2A-related Developmental and Epileptic Encephalopathy (DEE), laying a foundation for personalized interventions. Key PointsO_LIKey Point 1: Human neurons carrying epilepsy-causing SCN2A-L1342P display intrinsic hyperexcitability in cortical organoids. C_LIO_LIKey Point 2: Synaptic transmission is enhanced in organoids carrying the SCN2A-L1324P mutation, consistent with the presence of elevated excitatory synapses, which leads to increased network hyperexcitability. C_LIO_LIKey Point 3: Transcriptomics analysis reveals that the SCN2A-L1342P mutation causes significant differential changes in forebrain developmental genes, synaptic and glutamatergic signaling pathways, and enhances cellular senescence and apoptosis. C_LI

neuroscience↗

bioRxiv2025

Open-science discovery of DNDI-6510, a compound that addresses genotoxic and metabolic liabilities of the COVID Moonshot SARS-CoV-2 Mpro lead inhibitor

The 2020 SARS-CoV-2 coronavirus pandemic highlighted the urgent need for novel small molecule antiviral drugs. (S)-x38 DNDI-6510 is a non-covalent SARS-CoV-2 main protease inhibitor developed by the open science collaboration COVID Moonshot. Here, we report on the metabolic and toxicologic optimization of the lead series previously disclosed by the COVID Moonshot Initiative, leading up to the selection of (S)-x38 DNDI-6510 as the preclinical candidate. We describe the thorough profiling of the series, identifying key risks such as formation of genotoxic metabolites and high clearance, which were successfully addressed during lead optimization. In addition, we disclose the in vitro and in vivo evaluation of (S)-x38 DNDI-6510 in pharmacokinetic and pharmacodynamic models, exploring multiple approaches to ameliorate rodent-specific metabolic clearance, and show that both co-dosing of (S)-x38 DNDI-6510 with an ABT inhibitor and utilizing a metabolically humanized mouse model (8HUM) achieve significant improvements in exposure. Through comparisons of ABT co-dosing and humanized mouse models in efficacy experiments, we demonstrate that continuous exposure over cellular EC90 is required for SARS-CoV-2 antiviral efficacy in vivo in an antiviral model using a mouse-adapted SARS-CoV-2 strain. Finally, (S)-x38 DNDI-6510 was assessed in maximum tolerated dose experiments in two species, demonstrating significant in vivo PXR-linked auto-induction of metabolism, leading to the discontinuation of this compound. In summary, we report the successful effort to overcome series-specific AMES liabilities in a lead development program. Downstream optimization of existing series will require in-depth optimization of rodent-specific liabilities and metabolic induction profile.

pharmacology and toxicology↗

bioRxiv2025

Conformational Dynamics and Catalytic Backups in a Hyper-Thermostable Engineered Archaeal Protein Tyrosine Phosphatase

Protein tyrosine phosphatases (PTPs) are a family of enzymes that play important roles in regulating cellular signaling pathways. The activity of these enzymes is regulated by the motion of a catalytic loop that places a critical conserved aspartic acid side chain into the active site for acid-base catalysis upon loop closure. These enzymes also have a conserved phosphate binding loop that is typically highly rigid and forms a well-defined anion binding nest. The intimate links between loop dynamics and chemistry in these enzymes make PTPs an excellent model system for understanding the role of loop dynamics in protein function and evolution. In this context, archaeal PTPs, which have evolved in extremophilic organisms, are highly understudied, despite their unusual biophysical properties. We present here an engineered chimeric PTP (ShufPTP) generated by shuffling the amino acid sequence of five extant hyperthermophilic archaeal PTPs. Despite ShufPTPs high sequence similarity to its natural counterparts, ShufPTP presents a suite of unique properties, including high flexibility of the phosphate binding P-loop, facile oxidation of the active site cysteine, mechanistic promiscuity, and most notably, hyperthermostability, with a denaturation temperature likely >130 {degrees}C (>8 {degrees}C higher than the highest recorded growth temperature of any archaeal strain). Our combined structural, biochemical, biophysical and computational analysis provides insight both into how small steps in evolutionary space can radically modulate the biophysical properties of an enzyme, and showcase the tremendous potential of archaeal enzymes for biotechnology, to generate novel enzymes capable of operating under extreme conditions. Table of Contents Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=68 SRC="FIGDIR/small/645524v3_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@186bfccorg.highwire.dtl.DTLVardef@19a265borg.highwire.dtl.DTLVardef@14c526corg.highwire.dtl.DTLVardef@1b75920_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

Mapping human cerebral blood flow with high-density, multi-channel speckle contrast optical spectroscopy

Recently, speckle contrast optical spectroscopy (SCOS) enabled non-invasive, high signal-to-noise-ratio (SNR) human cerebral blood flow (CBF) measurements, relevant for both neuroscience and clinical monitoring of diseases with CBF dysregulation. Single channel SCOS measurements limit the information obtained to only one location on the head. In this work, we develop a multi-channel SCOS system to map spatial heterogeneity in CBF changes during human brain activation. Using a galvanometer, we temporally multiplexed a free-space laser to 7 source fibers positioned at different locations on the head. Diffuse light collected from the tissue is captured by fiber bundles projecting to 17 complementary metal-oxide semiconductor (CMOS) cameras, resulting in 50 source-detector channels measuring optical density (OD) and relative CBF changes covering an area of 7.6 cm by 6.6 cm on the head. We validated the spatial specificity and stability of the system using a liquid flow phantom. We then measured brain activity during a word-color Stroop task in 15 subjects and obtained brain activation maps. The average signal changes in the channel showing the largest activation were 1.7 x 10-2 in {Delta}OD and 6.6% in CBF.

bioengineering↗

bioRxiv2025

Contact mode high-speed AFM of phase separated lipid bilayers to study amyloid-β interactions

Cellular membranes are an essential feature of life, the composition and structure of which is important in governing cellular processes and is linked to multiple disorders. Of particular interest is the role that the lipid membrane plays in amyloidogenic diseases such as Alzheimers disease (AD), including the role of lipid composition and cholesterol in mediating amyloid toxicity. To mimic neuronal membranes, we used 3-component (DPPC/DOPC/Chol) and 5-component (DPPC/POPC/Chol/sphingomyelin/GM1) model membranes. Atomic force microscopy (AFM) is a key tool in studying the structures of lipid membranes and their interactions with amyloid. Recent advances in contact mode high-speed AFM (HS-AFM) have made it possible to capture dynamic processes at video rate. We used a unique custom-built contact mode HS-AFM to image model lipid membranes and study amyloid-{beta} interactions in liquid. We demonstrate the advantage of using HS-AFM coupled with spatiotemporal variability analysis to capture the dynamic interaction of A{beta} 1-42 monomers and oligomers with phase separated lipid bilayers to elucidate the role of nanoscale domains in amyloid-membrane interactions. We show that amyloid oligomer complexes induce greater dynamic instability than monomers, and that low cholesterol membranes are more susceptible to destabilization. Overall, we demonstrate the advantage of HS-AFM to image biological processes on biologically relevant soft samples and discuss tip-sample interactions at high-speed operation in contact mode on lipid membrane models in liquid environment. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=62 SRC="FIGDIR/small/633021v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@8a7da2org.highwire.dtl.DTLVardef@3e39d5org.highwire.dtl.DTLVardef@1470050org.highwire.dtl.DTLVardef@658f19_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2024

Near 100% genome editing efficiency with a one-step all RNA prime editing system in a human reporter iPSC line

CRISPR/Cas9 nucleases offer powerful tools for genome editing but can cause unintended mutations at the target site due to the creation of double-stranded DNA breaks. Prime editing (PE) is arguably a safer technology as it relies on the creation of single-strand DNA nicks and avoids possible indels. Despite its precision, current PE systems are limited by relatively low editing efficiency in non-immortalized cells. Here, we optimized prime editing in human induced pluripotent stem cells (hiPSCs) using a fluorescence-based assay to achieve near-complete editing of a BFP transgene. Using an all-RNA approach, precise prime editing of a single nucleotide variant was observed in >95% of cells with minimal unintended edits at the target site.

molecular biology↗

bioRxiv2024

PIEZO1 overexpression in hereditary hemorrhagic telangiectasia arteriovenous malformations

BackgroundHereditary hemorrhagic telangiectasia (HHT) is an inherited vascular disorder characterized by arteriovenous malformations (AVMs). Loss-of-function mutations in Activin receptor-like kinase 1 (ALK1) cause type 2 HHT and Alk1 knockout (KO) mice develop AVMs due to overactivation of VEGFR2/PI3K/AKT signaling pathways. However, the full spectrum of signaling alterations in Alk1 mutants remains unknown and means to combat AVM formation in patients are yet to be developed. MethodsSingle-cell RNA sequencing of endothelial-specific Alk1 KO mouse retinas and controls identified a cluster of endothelial cells (ECs) that was unique to Alk1 mutants and that overexpressed fluid shear stress (FSS) signaling signatures including upregulation of the mechanosensitive ion channel PIEZO1. PIEZO1 overexpression was confirmed in human HHT lesions, and genetic and pharmacological PIEZO1 inhibition was tested in Alk1 KO mice, as well as downstream PIEZO1 signaling. ResultsPharmacological PIEZO1 inhibition, and genetic Piezo1 deletion in Alk1-deficient mice effectively mitigated AVM formation. Furthermore, we identified that elevated VEGFR2/AKT, ERK5-p62-KLF4, hypoxia and proliferation signaling were significantly reduced in Alk1-Piezo1 double ECKO mice. ConclusionsPIEZO1 overexpression and signaling is integral to HHT2, and PIEZO1 blockade reduces AVM formation and alleviates cellular and molecular hallmarks of ALK1-deficient cells. This finding provides new insights into the mechanistic underpinnings of ALK1-related vascular diseases and identifies potential therapeutic targets to prevent AVMs.

molecular biology↗

bioRxiv2024

Fokker-Planck diffusion maps of multiple single cell microglial transcriptomes reveals radial differentiation into substates associated with Alzheimer's pathology

The identification of microglia subtypes is important for understanding the role of innate immunity in neu-rodegenerative diseases. Current methods of unsupervised cell type identification assume a small noise-to-signal ratio of transcriptome measurements that would produce well-separated cell clusters. However, identification of subtypes is obscured by gene expression noise, diminishing the distances in transcriptome space between distinct cell types and blurring boundaries. Here we use Fokker-Planck (FP) diffusion maps to model cellular differentiation as a stochastic process whereby cells settle into local minima, corresponding to cell subtypes, in a potential landscape constructed from transcriptome data using a nearest neighbor graph approach. By applying critical transition fields, we identify individual cells on the verge of transitioning between subtypes, revealing microglial cells in inactivated, homeostatic state before radially transitioning into various specialized subtypes. Specifically, we show that cells from Alzheimers disease patients are enriched in a microglia subtype associated to antigen presentation and T-cell recruitment.

systems biology↗

bioRxiv2024

Catalytically distinct IDH1 mutants tune phenotype severity in tumor models

Mutations in isocitrate dehydrogenase 1 (IDH1) impart a neomorphic reaction that produces D-2-hydroxyglutarate (D2HG), which can inhibit DNA demethylases to drive tumorigenesis. Mutations affect residue R132 and display distinct catalytic profiles for D2HG production. We show that catalytic efficiency of D2HG production is greater in IDH1 R132Q than R132H mutants, and expression of R132Q in cellular and xenograft models leads to higher D2HG concentrations in cells, tumors, and sera compared to R132H. Though expression of IDH1 R132Q leads to hypermethylation in DNA damage pathways, DNA hypomethylation is more notable when compared to R132H expression. Transcriptome analysis shows increased expression of many pro-tumor pathways upon expression of IDH1 R132Q versus R132H, including transcripts of EGFR and PI3K signaling pathways. Thus, IDH1 mutants appear to modulate D2HG levels via altered catalysis, resulting in distinct epigenetic and transcriptomic consequences where higher D2HG levels appear to be associated with more aggressive tumors.

genomics↗

bioRxiv2023

Aβ Amyloid Scaffolds the Accumulation of Matrisome and Additional Proteins in Alzheimer's Disease

We report a highly significant correlation between human Alzheimers disease (AD) brain proteome changes and those in CRND8 APP695NL/F transgenic mice. Comparing protein changes observed in the CRND8 mice with co-expression networks derived from human Alzheimers disease (AD), reveals both conserved and divergent module changes. Many proteins in the most highly conserved module (M42, matrisome) accumulate in plaques, cerebrovascular amyloid (CAA), dystrophic neuronal processes, or a combination thereof. Overexpression of two M42 proteins, midkine (Mdk) and pleiotrophin (PTN), in CRND8 mice brains leads to increased accumulation of A{beta} in plaques and in blood vessels; further, recombinant MDK and PTN enhance A{beta} aggregation into amyloid structures. Multiple M42 proteins bind to fibrillar A{beta}42 and a non-human amyloid fibril in vitro. Supporting this binding data, MDK and PTN co-accumulate with transthyretin (TTR) amyloid in the heart. Notably, our findings establish that proteomic changes in modules observed in human AD brains define an A{beta} amyloid "responsome" that is well conserved from mouse models to humans. Further, distinct amyloid structures appear to serve as scaffolds, facilitating the co-accumulation of proteins with signaling functions, and this co-accumulation may contribute to downstream pathological sequalae. Overall, this contextualized understanding of proteomic changes and their interplay with amyloid deposition provides valuable insights into the complexity of AD pathogenesis and potential biomarkers and therapeutic targets.

neuroscience↗

bioRxiv2023

Simulating clinical trials for model-informed precision dosing: Using warfarin treatment as a use case

Treatment response variability across patients is a common phenomenon in clinical practice. For many drugs this inter-individual variability does not require much (if any) individualisation of dosing strategies. However, for some drugs, including chemotherapies and some monoclonal antibody treatments, individualisation of dosages are needed to avoid harmful adverse events. Model-informed precision dosing (MIPD) is an emerging approach to guide the individualisation of dosing regimens of otherwise difficult-to-administer drugs. Several MIPD approaches have been suggested to predict dosing strategies, including regression, reinforcement learning (RL) and pharmacokinetic and pharmacodynamic (PKPD) modelling. A unified framework to study the strengths and limitations of these approaches is missing. We develop a framework to simulate clinical MIPD trials, providing a cost and time efficient way to test different MIPD approaches. Central for our framework is a clinical trial model that emulates the complexities in clinical practice that challenge successful treatment individualisation. We demonstrate this framework using warfarin treatment as a use case and investigate three popular MIPD methods: 1. neural network regression; 2. deep RL; and 3. PKPD modelling. We find that the PKPD model individualises warfarin dosing regimens with the highest success rate and the highest efficiency: 75.1% of the individuals display INRs inside the therapeutic range at the end of the simulated trial; and the median time in the therapeutic range (TTR) is 74 %. In comparison, the regression model and the deep RL model have success rates of 47.9% and 65.8 %, and median TTRs of 45 % and 68 %. We also find that the MIPD models can attain different degrees of individualisation: the Regression model individualises dosing regimens up to variability explained by covariates; the Deep RL model and the PKPD model individualise dosing regimens accounting also for additional variation using monitoring data. However, the Deep RL model focusses on control of the treatment response, while the PKPD model uses the data also to further the individualisation of predictions.

pharmacology and toxicology↗

bioRxiv2022

Global and cell type-specific immunological hallmarks of severe dengue progression

Severe dengue (SD) is a major cause of morbidity and mortality impacting approximately 5 million of the 400 million people infected with dengue virus (DENV) annually. To define DENV target cells and immunological hallmarks of SD progression in childrens blood, we integrated virus-inclusive single cell RNA-Seq 2 (viscRNA-Seq 2) with functional assays. Beyond myeloid cells, in natural infection, B cells harbor replicating DENV capable of infecting permissive cells. Alterations in cell type abundance, gene and protein expression and secretion, and cell-cell communications point towards increased migration and inflammation in SD progressors (SDp). Concurrently, antigen presenting cells from SDp demonstrate intact uptake, yet impaired interferon responses and antigen presentation, in part DENV-modulated. Increased activation, regulation, and exhaustion of effector responses and expansion of HLA-DR-expressing, possibly compensatory, adaptive-like NK cells also characterize SDp. These findings reveal DENV target cells in the human blood and provide insight into SD pathogenesis beyond antibody-mediated enhancement.

immunology↗