Biology subjects

Seiler, C.

Publications and source records attributed to Seiler, C..

18 recordsLinked to original sources

bioRxiv2026

Development of a multi-organ single-cell atlas of systemic sclerosis reveals shared and tissue-specific pathogenic pathways.

Objectives: Systemic sclerosis (SSc) is a multi-organ autoimmune disease for which no broadly effective disease-modifying treatment exists. We developed an integrated multi-organ single-cell atlas of SSc to identify shared and organ specific disease-associated transcriptional programmes and potential therapeutic targets. Methods: We integrated single-cell RNA-sequencing data from skin, lung, synovium, and peripheral blood mononuclear cells (six studies, 401,902 cells, 90 individuals) using Harmony. Pseudobulk differential expression and gene set enrichment analysis were performed at the tissue cell-compartment, cell-type, and subpopulation levels, including independent reclustering of lymphoid, myeloid and fibroblast populations. Results: Disease-associated transcriptional programmes showed marked tissue dependence, even within the same cell lineage, highlighting the importance of organ-specific mechanisms in SSc. Nevertheless, recurrent extracellular matrix (ECM) remodelling programmes were identified in lung, skin and synovium, and interferon signalling programmes in skin, synovium and peripheral blood mononuclear cells, across immune and fibroblast cell populations. Although no subpopulation was exclusive to SSc, a shared myofibroblast subpopulation expressing SFRP2, COL1A1, POSTN, ACTA2, and COMP was identified across lung, skin, and synovium. In addition, perivascular and mitotic fibroblast subpopulations exhibited both profibrotic and inflammatory signatures, including interferon- and IL-2-related signalling programmes. Conclusions: SSc is characterised by two complementary axes: a tissue-dependent cellular programme and a recurrent fibrotic and interferon-associated signature extending across multiple organs and cell populations. These findings are consistent with current organ-based therapeutic approaches while highlighting interferon signalling as a potential multi-organ therapeutic target. The resulting interactive single-cell atlas provides a resource for investigating shared and organ-specific disease mechanisms and guiding future therapeutic research.

immunology↗

bioRxiv2026

Developing High Content Imaging Functional Panels to Characterize Synovial Fibroblasts in Rheumatoid Arthritis

ObjectiveTo develop and apply a preclinical functional imaging assay for visualizing and analyzing activated synovial fibroblasts (SFs) at single-cell resolution using high-content imaging. MethodsA multiparametric functional imaging assay was developed to simultaneously interrogate six key cellular processes in cultured SFs from non-inflammatory control (NIC), osteoarthritis (OA) and rheumatoid arthritis (RA) patients. Two complementary fluorescent panels -- comprising LipidTOX, MitoSOX, TMRM, EdU Click-iT, CYTO-ID, and Sir-Lysosome -- collectively captured autophagy dynamics, mitochondrial health, lipid metabolism, and cellular proliferation within a single imaging workflow. Automated image acquisition and quantitative feature extraction via CellProfiler yielded approximately 1,200 morphological and intensity-based features per cell, enabling high-dimensional, unbiased phenotypic profiling at the individual cell level. ResultsApplication of this assay revealed marked heterogeneity in basal cellular functions among SFs stratified by disease state, and robustly differentiated between NIC, OA and RA SFs. Stimulation with inflammatory cytokines (TNF-, IL-1{beta}, IFN{gamma}) and toll-like receptor ligands (LPS, poly I:C) elicited distinct, stimulus-dependent phenotypic responses across disease groups. Multiparametric analysis and feature importance ranking identified IL-1{beta} as a key driver of enhanced autophagic activity, accompanied by significant remodeling of lipid metabolic profiles. ConclusionWe developed a scalable, sensitive approach for dissecting functional heterogeneity in primary SF cultures, revealing previously unappreciated complexity in SF biology across disease states. Our approach provides a robust framework for high-throughput drug screening and identification of candidate therapeutics selectively targeting pathogenic fibroblast functions in inflammatory arthritis.

Cell Biology↗

bioRxiv2026

SNPic: SNP Topic Modeling for Interpretable Clustering of Complex phenotypes

Genome-wide association studies (GWAS) have cataloged thousands of disease-associated variants, yet a central challenge remains: decoding the shared, pleiotropic architecture that links complex phenotypes. Existing approaches, including dimensionality reduction methods and regression genetic models, either lack interpretability or rely on external linkage disequilibrium (LD) reference panels, limiting their ability to recover coherent biological mechanisms. Here we introduce the SNP topic model (SNPic), a generative probabilistic framework that reframes GWAS summary statistics as a structured corpus and models genetic architecture using principles from Natural Language Processing (NLP). By treating phenotypes as documents and genes or the whole corpus of traits as words, SNPic applies topic models, e.g. Latent Dirichlet Allocation (LDA), to infer latent "genetic topics", representing interpretable, overlapping biological modules that jointly explain complex traits. This formulation enables simultaneous reconstruction of trait relationships and identification of their underlying molecular drivers. SNPic integrates two complementary schemes: Sumstat-as-word for capturing global phenotypic structure and Gene-as-word for resolving mechanistic detail, within a unified modeling framework. To ensure robustness, we introduce a stability-optimized inference pipeline based on bootstrap resampling, allowing data-driven selection of topic number and filtering of stochastic signals. Across extensive simulations, SNPic consistently outperforms conventional dimensionality reduction methods in recovering latent structure under both linear and non-linear, highly overlapping genetic architectures. Applied to integrated FinnGen and UK Biobank datasets, SNPic identifies reproducible genetic topics corresponding to distinct biological programs, including HLA-mediated immune processes and transporter-driven metabolic regulation, with strong tissue-specific support. The framework further generalizes across species, organizing complex traits in maize, Arabidopsis thaliana, and cattle into biologically coherent modules. Together, these results establish SNPic as a scalable and interpretable framework that shifts GWAS analysis from association cataloging toward the construction of an interpretable knowledge graph representing the latent semantic architecture of the genome. By unifying statistical genetics with NLP, SNPic reframes GWAS analysis as a probabilistic language modeling task, enabling the systematic decoding of complex trait architectures and delivering a systemic graph of cross-phenotype relationships.

genetics↗

bioRxiv2025

Disease-specific fibroblast-myeloid interactions in rheumatoid arthritis synovium

Rheumatoid arthritis (RA) is characterized by profound remodeling of the synovial microenvironment. Here we show that enhanced fibroblast-macrophage cross-talk distinguishes RA from psoriatic arthritis (PsA). MerTK-SPP1 macrophages represent the dominant inflammatory myeloid population in RA, interacting with expanded fibroblast subsets through SPP1-mediated signaling. Lining fibroblasts display induction of antigen-presentation and IL-6/JAK-STAT pathways, while a CHI3L1-producing fibroblast population arises specifically in RA and may act as a source of autoantigens. These stromal populations interact closely with FABP5 iDC3 cells and T cells within a disrupted synovial lining, creating a niche driving adaptive immune activation. In contrast, PsA exhibits increased fibroblast- endothelial interactions without major endothelial transcriptional changes. Our data identify SPP1 signaling and fibroblast-myeloid-dendritic interactions as core drivers of RA synovial inflammation that links innate immune activation to the initiation of autoimmunity. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/688477v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@c76e39org.highwire.dtl.DTLVardef@11563a9org.highwire.dtl.DTLVardef@141f3fborg.highwire.dtl.DTLVardef@f90742_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

Microtubule deacetylation drives kinesin-1 mediated mitochondrial transport accelerating breast cancer cell migration

Mitochondrial trafficking is reprogrammed in metastatic breast cancer cells to sustain their migratory and invasive behavior. Mitochondria repositioning to sites of high energy demand is governed by a balance between opposing dynein and kinesin-1 (KIF5B) molecular motors whose regulation remains incompletely understood. Here, we identify the SYBU gene as a candidate prognostic marker downregulated in metastatic disease. SYBU encodes syntabulin, a mitochondria outer membrane protein that interacts with dynein to counterbalance KIF5B-dependent anterograde transport to the cell cortex. Loss of SYBU disrupts the balance, causing excessive KIF5B-driven mitochondria movement, microtubule damage and deacetylation. In turn, microtubule deacetylation reinforces KIF5B-mediated transport, creating a positive feedback loop that drives mitochondria distribution close to the cell periphery and enhances cancer cell migration. Pharmacological inhibition of the tubulin deacetylase HDAC6 restores mitochondrial positioning and reduces cell migration in SYBU-deficient cells. Our findings identify SYBU as a key regulator of mitochondrial trafficking and pave the way to personalized therapeutic approaches for metastatic breast tumors with low SYBU expression.

cell biology↗

bioRxiv2025

ndufs2-/- zebrafish have impaired survival, neuromuscular activity, morphology, and one-carbon metabolism treatable with folic acid

Mitochondrial complex I (CI) deficiency represents a common biochemical pathophysiology underlying Leigh syndrome spectrum (LSS), manifesting with progressive multi-system dysfunction, lactic acidemia, and early mortality. To facilitate mechanistic studies and rigorous screening of therapeutic candidates for CI deficient LSS, we used CRISPR/Cas9 to generate an ndufs2-/- 16 bp deletion zebrafish strain. ndufs2-/- larvae exhibit markedly reduced survival, severe neuromuscular dysfunction including impaired swimming capacity, multiple morphologic malformations, reduced growth, hepatomegaly, uninflated swim bladder, yolk retention, small intestines, and small eyes and pupils with abnormal retinal ganglion cell layer. Transcriptome profiling of ndufs2-/- larvae revealed dysregulation of the electron transport chain, TCA cycle, fatty acid beta-oxidation, and one-carbon metabolism. Similar transcriptomic profiles were observed in ndufs2-/- missense mutant C. elegans (gas-1(fc21)) and two human CI-disease fibroblast cell lines stressed in galactose media. ndufs2-/- zebrafish had 80% reduced CI enzyme activity. Unbiased metabolomic profiling showed increased lactate, TCA cycle intermediates, and acyl-carnitine species. One-carbon metabolism associated pathway alterations appear to contribute to CI disease pathophysiology, as folic acid treatment rescued the growth defect and hepatomegaly in ndufs2-/-larvae. Overall, ndufs2-/- zebrafish recapitulate severe CI deficiency, complex metabolic pathophysiology, and relevant LSS neuromuscular and survival phenotypes, enabling future translational studies of therapeutic candidates.

pharmacology and toxicology↗

bioRxiv2024

NKp30 and NKG2D contribute to natural killer recognition of HIV-infected cells

Natural killer (NK) cells respond rapidly in early HIV-1 infection. HIV-1 prevention and control strategies harnessing NK cells could be enabled by mechanistic understanding of how NK cells recognize HIV-infected T cells. Here, we profiled the phenotype of human primary NK cells responsive to autologous HIV-1-infected CD4+ T cells in vitro. We characterized the patterns of NK cell ligand expression on CD4+ T cells at baseline and after infection with a panel of transmitted/founder HIV-1 strains to identify key receptor-ligand pairings. CRISPR editing of CD4+ T cells to knockout the NKp30 ligand B7-H6, or the NKG2D ligands MICB or ULBP2 reduced NK cell responses to HIV-infected cells in some donors. In contrast, overexpression of NKp30 or NKG2D in NK cells enhanced their targeting of HIV-infected cells. Collectively, we identified receptor-ligand pairs including NKp30:B7-H6 and NKG2D:MICB/ULBP2 that contribute to NK cell recognition of HIV-infected cells.

immunology↗

bioRxiv2023

spillR: Spillover Compensation in Mass Cytometry Data

Channel interference in mass cytometry can cause spillover and may result in miscounting of protein markers. Chevrier et al. (2018) introduce an experimental and computational procedure to estimate and compensate for spillover implemented in their R package CATALYST. They assume spillover can be described by a spillover matrix that encodes the ratio between unstained and stained channels. They estimate the spillover matrix from experiments with beads. We propose to skip the matrix estimation step and work directly with the full bead distributions. We develop a nonparametric finite mixture model, and use the mixture components to estimate the probability of spillover. Spillover correction is often a pre-processing step followed by downstream analyses, choosing a flexible model reduces the chance of introducing biases that can propagate downstream. We implement our method in an R package spillR using expectation-maximization to fit the mixture model. We test our method on synthetic and real data from CATALYST. We find that our method compensates low counts accurately, does not introduce negative counts, avoids overcompensating high counts, and preserves correlations between markers that may be biologically meaningful.

bioinformatics↗

bioRxiv2021

Dosage of duplicated and antifunctionalized homeobox proteins influences spikelet development in barley

Illuminating the mechanisms of inflorescence architecture of grain crops that feed our world may strengthen the goal towards sustainable agriculture. Lateral spikelet development of barley (Hordeum vulgare L.) is such an example of a floral architectural trait regulated by VRS1 (Vulgare Row-type Spike 1 or Six-rowed Spike 1, syn. HvHOX1). Its lateral spikelet-specific expression and the quantitative nature of suppressing spikelet development were previously shown in barley. However, the mechanistic function of this gene and its paralog HvHOX2 on spikelet development is still fragmentary.Here, we show that these duplicated transcription factors (TFs) have contrasting nucleotide diversity in various barley genotypes and several Hordeum species. Despite this difference, both proteins retain their basic properties of the homeodomain leucine zipper class I family of TFs. During spikelet development, these genes exhibit similar spatiotemporal expression patterns yet with anticyclic expression levels. A gene co-expression network analysis suggested that both have an ancestral relationship but their functions appear antagonistic to each other, i.e., HvHOX1 suppresses whereas HvHOX2 rather promotes spikelet development. Our transgenic promoter-swap analysis showed that HvHOX2 can restore suppressed lateral spikelets when expression levels are increased; however, at its low endogenous expression level, HvHOX2 appears dispensable for spikelet development. Collectively, this study proposes that the dosage of the two antagonistic TFs, HvHOX1 and HvHOX2, influence spikelet development in barley.

plant biology↗

bioRxiv2020

CytoGLMM: Conditional Differential Analysis for Flow and Mass Cytometry Experiments

BackgroundFlow and mass cytometry are important modern immunology tools for measuring expression levels of multiple proteins on single cells. The goal is to better understand the mechanisms of responses on a single cell basis by studying differential expression of proteins. We focus on cell-specific differential analysis and one fixed cell type. In contrast, most current methods learn cell types and perform differential analysis jointly. Our narrower field of application allows us to define a more specific statistical model with easier to control statistical guarantees. ResultsDifferential analysis of marker expressions can be difficult due to marker correlations and inter-individual heterogeneity, particularly for studies of human immunology. We address these challenges with two multiple regression strategies: A bootstrapped generalized linear model and a generalized linear mixed model. On simulated datasets, we compare the robustness towards marker correlations and heterogeneity of both strategies. For paired experiments, we find that both strategies maintain the target false discovery rate under medium correlations and that mixed models are statistically more powerful under the correct model specification. For unpaired experiments, our results indicate that much larger patient sample sizes are required to detect differences. We illustrate the CytoGLMM R package and workflow for both strategies on a pregnancy dataset. ConclusionsOur approach to find differential proteins in flow and mass cytometry data reduces biases arising from maker correlations and safeguards against false discoveries induced by patient heterogeneity.

bioinformatics↗

bioRxiv2020

INTERMEDIUM-C mediates the shade-induced bud growth arrest in barley

Tiller formation is a key agronomic determinant for grain yield in cereal crops. The modulation of this trait is controlled by transcriptional regulators and plant hormones, tightly regulated by external environmental conditions. While endogenous (genetics) and exogenous (environmental factors) triggers for tiller formation have mostly been investigated separately, it has remained elusive how they are integrated into the developmental program of this trait. The transcription factor INTERMEDIUM-C (INT-C), which is the barley ortholog of the maize domestication gene TEOSINTE BRANCHED1 (TB1) has a prominent role in regulating tiller bud outgrowth. Here we show that INT-C is expressed in tiller buds, required for bud growth arrest in response to shade. In contrast to wild type plants, int-c mutant plants are impaired in their shade response and do not stop tiller production after shading. Gene expression levels of INT-C are up-regulated under light-limiting growth conditions, and down-regulated after decapitation. Transcriptome analysis of wild-type and int-c buds under control and shading conditions identified target genes of INT-C that belong to auxin and gibberellin biosynthesis and signaling pathways. Our study identifies INT-C as integrator of the shade response into tiller formation, which is prerequisite for implementing shading responses in the breeding of cereal crops.

plant biology↗

bioRxiv2019

Characterization of the impact of daclizumab beta on circulating natural killer cells by mass cytometry

Daclizumab beta is a humanized monoclonal antibody that binds to CD25 and selectively inhibits high-affinity IL-2 receptor signaling. As a former treatment for relapsing forms of multiple sclerosis (RMS), daclizumab beta induces robust expansion of the CD56bright subpopulation of NK cells that is correlated with the drugs therapeutic effects. As NK cells represent a heterogeneous population of lymphocytes with a range of phenotypes and functions, the goal of this study was to better understand how daclizumab beta altered the NK cell repertoire to provide further insight into the possible mechanism(s) of action in RMS. We used mass cytometry to evaluate expression patterns of NK cell markers and provide a comprehensive assessment of the NK cell repertoire in individuals with RMS treated with daclizumab beta or placebo over the course of one year. Treatment with daclizumab beta significantly altered the NK cell repertoire compared to placebo treatment. As previously reported, daclizumab beta significantly increased expression of CD56 on total NK cells. Within the CD56bright NK cells, treatment was associated with multiple phenotypic changes, including increased expression of NKG2A and NKp44, and diminished expression of CD244, CD57, and NKp46. While the changes were less dramatic, CD56dim NK cells responded distinctly to daclizumab beta treatment, with higher expression of CD2 and NKG2A, and lower expression of FAS-L, HLA-DR, NTB-A, NKp30, and Perforin. Together, these data indicate that the expanded NK cells share features of both immature and mature NK cells. These findings show that daclizumab beta treatment is associated with unique changes in NK cells that may enhance their ability to kill autoreactive T cells or to exert immunomodulatory functions.

immunology↗

bioRxiv2019

Receptor tyrosine kinases regulate signal transduction through a liquid-liquid phase separated state

Receptor tyrosine kinases (RTKs), the largest class of transmembrane cell surface receptors, initiate signalling pathways which regulate diverse cellular processes. On activation these receptors rapidly recruit multiple downstream effector proteins to moderate affinity tyrosyl phosphate (pY) binding sites. However, the mechanism for expedient downstream effector protein recruitment via random molecular diffusion through the cytoplasm is not fully understood. One way in which the probabilistic outcome associated with random diffusion could be alleviated is through localized accumulation of high effective concentrations of signalling proteins in discrete pools in the cell (1). The inclusion of interacting proteins into liquid-liquid phase-separated (LLPS), membraneless protein droplets maintains functionally relevant proteins at high concentrations in a liquid phase at the required point of action, enhancing equilibrium binding and enzyme activity (2-6). These LLPS states have been associated with a wide range of cellular functions including regulation of signalling through, for example, nephrin (7, 8), the T-cell receptor (9), mTOR (10), and Sos-Ras (11), however, whether LLPS extends to RTK-mediated signal transduction has not been investigated. Here, we show that an RTK, fibroblast growth factor receptor 2 (FGFR2), forms a signalling competent LLPS state with two downstream effectors, a tandem Src homology 2 (SH2) domain-containing protein tyrosine phosphatase 2 (Shp2), and 1-phosphatidylinositol 4,5-bisphosphate phosphodiesterase gamma 1 (Plc{gamma}1). We show that these proteins assemble into a ternary complex which exploits LLPS condensation to simultaneously modulate kinase, phosphatase and phospholipase activities. Therefore, LLPS formation ensures that the requirement for prolonged, high-fidelity signalling is achieved. Additional RTKs also form LLPS with their downstream effectors, suggesting that formation of biological condensates is a key organising principle of RTK-mediated signalling, with broad implications for further mechanistic studies as well as therapeutic intervention.

cell biology↗

bioRxiv2019

TIGIT is upregulated by HIV-1 infection and marks a highly functional adaptive and mature subset of natural killer cells

ObjectiveOur objective was to investigate the mechanisms that govern natural killer (NK) cell responses to HIV, with a focus on specific receptor-ligand interactions involved in HIV recognition by NK cells.\n\nDesign and MethodsWe first performed a mass cytometry-based screen of NK cell receptor expression patterns in healthy controls and HIV+ individuals. We then focused mechanistic studies on the expression and function of T cell immunoreceptor with Ig and ITIM domains (TIGIT).\n\nResultsThe mass cytometry screen revealed that TIGIT is upregulated on NK cells of untreated HIV+ women, but not in antiretroviral-treated women. TIGIT is an inhibitory receptor that is thought to mark exhausted NK cells; however, blocking TIGIT did not improve anti-HIV NK cell responses. In fact, the TIGIT ligands CD112 and CD155 were not upregulated on CD4+ T cells in vitro or in vivo, providing an explanation for the lack of benefit from TIGIT blockade. TIGIT expression marked a unique subset of NK cells that express significantly higher levels of NK cell activating receptors (DNAM-1, NTB-A, 2B4, CD2) and exhibit a mature/adaptive phenotype (CD57hi, NKG2Chi, LILRB1hi, FcR{gamma}lo, Syklo). Furthermore, TIGIT+ NK cells had increased responses to mock-infected and HIV-infected autologous CD4+ T cells, and to PMA/ionomycin, cytokine stimulation and the K562 cancer cell line.\n\nConclusionsTIGIT expression is increased on NK cells from untreated HIV+ individuals. Although TIGIT does not participate directly in NK cell recognition of HIV, it marks a population of mature/adaptive NK cells with increased functional responses.

immunology↗

bioRxiv2019

LINC complexes are mechanotransducers that discriminate Epithelial-Mesenchymal Transition programs

LINC complexes are transmembrane protein assemblies that physically connect the nucleo- and cytoskeletons through the nuclear envelope. Dysfunctions of LINC complexes are associated with pathologies such as cancer and muscular disorders. The mechanical roles of LINC complexes in these contexts are poorly understood. To address this, we used genetically encoded FRET biosensors of molecular tension in LINC complex proteins of fibroblastic and epithelial cells in culture. We exposed cells to mechanical, genetic and pharmacological perturbations, mimicking a range of physiological and pathological situations. We show that LINC complex proteins experience tension generated by the cytoskeleton and act as mechanical sensors of cell packing. Moreover, the LINC complex discriminates between inductions of partial and complete epithelial-mesenchymal transitions (EMT). We identify the implicated mechanisms, which associate nesprin tension sensing with -catenin capture at the nuclear envelope, thereby regulating {beta}-catenin transcription. Our data thus implicate that LINC complexes are mechanotransducers that fine-tune {beta}-catenin signaling in a manner dependent on the Epithelial-Mesenchymal Transition program.

cell biology↗

bioRxiv2018

CD38 is a key regulator of enhanced NK cell immune responses during pregnancy through its role in immune synapse formation

Natural killer (NK) cells use a diverse array of activating and inhibitory surface receptors to detect threats and provide an early line of defense against viral infections and cancer. Here, we demonstrate that the cell surface protein CD38 is a key human NK cell functional receptor through a role in immune synapse formation. CD38 expression marks a mature subset of human NK cells with a high functional capacity. NK cells expressing high levels of CD38 display enhanced killing and IFN-{gamma} secretion in response to influenza virus-infected and tumor cells. Inhibition of CD38 enzymatic activity does not influence NK cell function, but blockade of CD38 and its ligand CD31 abrogates killing and IFN-{gamma} expression in response to influenza-infected cells. Blockade of CD38 on NK cells similarly inhibits killing of tumor cells. CD38 localizes and accumulates at the immune synapse between NK cells and their targets, and blocking CD38 severely abrogates the ability of NK cells to form conjugates and immune synapses with target cells. Thus, CD38 plays a critical role in NK cell immune synapse formation. These findings open new avenues in immunotherapeutic development for cancer and infection by revealing a critical role for CD38 in NK cell function.

immunology↗

bioRxiv2017

Multivariate Heteroscedasticity Models for Functional Brain Connectivity

Functional brain connectivity is the co-occurrence of brain activity in different areas during resting and while doing tasks. The data of interest are multivariate timeseries measured simultaneously across brain parcels using resting-state fMRI (rfMRI). We analyze functional connectivity using two heteroscedasticity models. Our first model is low-dimensional and scales linearly in the number of brain parcels. Our second model scales quadratically. We apply both models to data from the Human Connectome Project (HCP) comparing connectivity between short and conventional sleepers. We find stronger functional connectivity in short than conventional sleepers in brain areas consistent with previous findings. This might be due to subjects falling asleep in the scanner. Consequently, we recommend the inclusion of average sleep duration as a covariate to remove unwanted variation in rfMRI studies. A power analysis using the HCP data shows that a sample size of 40 detects 50% of the connectivity at a false discovery rate of 20%. We provide implementations using R and the probabilistic programming language Stan.

neuroscience↗

bioRxiv2017

Strain-Specific Human Natural Killer Cell Recognition of Influenza A Virus

AbstractInnate Natural killer (NK) cells employ an array of surface receptors to detect altered self induced by infection or malignancy. Despite their decisive role in early antiviral immunity, the cellular mechanisms governing if or how they discriminate between viral infections remain unresolved. Here, we demonstrate that while human NK cells are capable of reducing infection levels of distinct influenza A strains, the A/California/07/2009 (pH1N1) strain induces a significantly more robust IFN-{gamma} response than A/Victoria/361/2011 (H3N2) and all other strains tested. This surprising degree of strain specificity results in part from the inability of the pH1N1 strain to downregulate the activating ligands CD112 (Nectin-2) and CD54 (ICAM-1) as efficiently as the H3N2 strain, leading to enhanced NK cell detection and IFN-{gamma} secretion. A network analysis of differentially expressed transcripts identifies the interferon /{beta} receptor (IFNAR) pathway as an additional, critical determinant of this strain-specific response. Strain-specific downregulation of NK cell activating ligands and modulation of type I IFN production represents a previously unrecognized influenza immunoevasion tactic and could present new opportunities to modulate the quality and quantity of the innate antiviral response for therapeutic benefit.\n\nOne Sentence SummaryHuman natural killer cells distinguish between Influenza A strains using a combinatorial cytokine priming and receptor-ligand signaling mechanism.

immunology↗