Biology subjects

Qin, Y.

Publications and source records attributed to Qin, Y..

At least 127 records · Page 7Linked to original sources

bioRxiv2021

Sharing happy stories increases interpersonal closeness mediated by enhancing interpersonal brain synchronization

Our lives revolve around sharing stories with others. Expressing emotion (i.e., happy and sad) is an essential characteristic of sharing stories and could enhance the similarity of story comprehension across speaker-listener pairs. The Emotions as Social Information Model (EASI) suggests that emotional communication may influence interpersonal closeness, but the effect of sharing emotional (happy/sad) stories on interpersonal closeness remains poorly understood. Here, one speaker watched emotional videos and communicated the content of the videos to thirty-two listeners (happy/sad/neutral group). Both speaker and listeners neural activities were recorded using EEG. After listening, we assessed the interpersonal closeness between the speaker and listeners. Compared to the sad group, sharing happy stories showed a better recall quality and a higher rating of interpersonal closeness. Meanwhile, the happy group showed higher interpersonal brain synchronization (IBS) in the prefrontal cortex (PFC) and temporal cortex (specifically TPJ) than the sad group. Moreover, such IBS mediated the relationship between the quality of sharing stories and interpersonal closeness, and happy emotion moderated this mediation model. The magnitude of IBS differentiated high interpersonal closeness from low interpersonal closeness. Exploratory analysis using support vector regression showed that the IBS could also predict the ratings of interpersonal closeness in left-out subjects. These results suggest that IBS could serve as an indicator of whether sharing emotional stories facilitate interpersonal closeness. These findings improve our understanding of sharing emotional information among individuals that guide behaviors during interpersonal interactions.

neuroscience↗

bioRxiv2021

Bacterium-Enabled Transient Gene Activation by Artificial Transcription Factor for Resolving Gene Regulation in Maize

Cellular functions are diversified through intricate transcription regulations, and an understanding gene regulation networks is essential to elucidating many developmental processes and environmental responses. Here, we employed the Transcriptional-Activator Like effectors (TALes), which represent a family of transcription factors that are synthesized by members of the {gamma}-proteobacterium genus Xanthomonas and secreted to host cells for activation of targeted host genes. Through delivery by the maize pathogen, Xanthomonas vasicola pv. vasculorum, designer TALes (dTALes), which are synthetic TALes, were used to induce the expression of the maize gene glossy3 (gl3), a MYB transcription factor gene involved in the cuticular wax biosynthesis. RNA-Seq analysis of leaf samples identified 146 gl3 downstream genes. Eight of the nine known genes known to be involved in the cuticular wax biosynthesis were up-regulated by at least one dTALe. A top-down Gaussian graphical model predicted that 68 gl3 downstream genes were directly regulated by GL3. A chemically induced mutant of the gene Zm00001d017418 from the gl3 downstream gene, encoding aldehyde dehydrogenase, exhibited a typical glossy leaf phenotype and reduced epicuticular waxes. The bacterial protein delivery of artificial transcription factors, dTALes, proved to be a straightforward and powerful approach for the revelation of gene regulation in plants.

plant biology↗

bioRxiv2021

Modulations of local synchrony over time lead to resting-state functional connectivity in a parsimonious large-scale brain model

Biophysical models of large-scale brain activity are a fundamental tool for understanding the mechanisms underlying the patterns observed with neuroimaging. These models combine a macroscopic description of the within- and between-ensemble dynamics of neurons within a single architecture. A challenge for these models is accounting for modulations of within-ensemble synchrony over time. Such modulations in local synchrony are fundamental for modeling behavioral tasks and resting-state activity. Another challenge comes from the difficulty in parametrizing large scale brain models which hinders researching principles related with between-ensembles differences. Here we derive a parsimonious large scale brain model that can describe fluctuations of local synchrony. Crucially, we do not reduce within-ensemble dynamics to macroscopic variables first, instead we consider within and between-ensemble interactions similarly while preserving their physiological differences. The dynamics of within-ensemble synchrony can be tuned with a parameter which manipulates local connectivity strength. We simulated resting-state static and time-resolved functional connectivity of alpha band envelopes in models with identical and dissimilar local connectivities. We show that functional connectivity emerges when there are high fluctuations of local and global synchrony simultaneously (i.e. metastable dynamics). We also show that for most ensembles, leaning towards local asynchrony or synchrony correlates with the functional connectivity with other ensembles, with the exception of some regions belonging to the default-mode network. Author summaryHere we present and evaluate a parsimonious model of large-scale brain activity. The model represents the brain as a network-of-networks structure. The sub-networks describe the neural activity within a brain region, and the global network encodes interactions between brain regions. Unlike other models, it capture progressive changes of local synchrony and local dynamics can be tuned with one parameter. Therefore the model could be used not only to model resting-state, but also behavioural tasks. Furthermore, we describe a simple framework that can deal with the arduous task of identifying global and local parameters.

neuroscience↗

bioRxiv2020

High-throughput, low-cost and rapid DNA sequencing using surface-coating techniques

The speed1-3, expense1-4 and throughput2 of genomic sequencing impose limitations on its use for time-sensitive acute cases, such as rare4,5 or antibiotic resistant infections6, and large-scale testing that is necessary for containing COVID-19 outbreaks using source-tracing7-9. The major bottleneck for increasing the bandwidth and decreasing operating costs of next-generation sequencers (NGS) is the flow cell that supplies reagents for the biochemical processes; this subsystem has not significantly improved since 200510-12. Here we report a new method for sourcing reagents based on surface coating technology (SCT): the DNA adhered onto the biochip is directly contacted by a reagent-coated polymeric strip. Compared with flow cells the reagent layers are an order of magnitude thinner while both the reagent exchange rate and biochip area are orders of magnitude greater. These improvements drop the turn-around time from days to twelve hours and the cost for whole genome sequencing (WGS) from about $1000 to $15, as well as increase data production by several orders of magnitude. This makes NGS more affordable than many blood tests while rapidly providing detailed genomic information about microbial and viral pathogens6,13, cancers14 and genetic disorders for targeted treatments6 and personalized medicine6,15. This data can be pooled in population-wide databases for accelerated research and development as well providing detailed real-time data for tracking and containing outbreaks, such as the current COVID-19 pandemic.

bioengineering↗

bioRxiv2020

Tumor edge architecture in glioblastoma is constructed by inter-cellular signals from vascular endothelial cells

One of the hallmarks of glioblastoma (GBM) is extensive neovascularization. In addition to supplying blood and nutrients, vascular endothelial (VE) cells provide trophic support to GBM cells via paracrine signaling, the precise mechanisms of which are being unraveled. Here, using patient-derived GBM and VE cells as well as orthotopic GBM mouse models, we report that Endocan (ESM1), an endothelial-secreted proteoglycan, confers enhanced proliferative, migratory, and angiogenic properties to GBM cells and regulates their spatial identity. Mechanistically, Endocan exerts at least part of its functions via direct binding and activation of the PDGFRA receptor. Subsequent downstream signaling enhances chromatin accessibility of the Myc promoter and upregulates Myc expression inducing highly stable phenotypic changes in GBM cells. Furthermore, Endocan confers a radioprotection phenotype in GBM cells, both in vitro and in vivo. Inhibition of Endocan-PDGFRA signaling with ponatinib increases survival in the Esm1 wild-type but not in the Esm1 knock-out mouse GBM model. Our findings identify Endocan and its downstream signaling axis as a potential target to subdue the recurrence of GBM and further highlight the importance of vascular to tumor cell signaling for GBM biology. Significance statementIdentification of the Endocan/PDGFRA/Myc axis demonstrates an important role of VE cells in GBM malignancy. The contribution of Endocan to the development of GBM cell populations with different phenotypes reveal an additional pathway underlying the origin of GBM intratumoral heterogeneity. Targeting Endocan-mediated crosstalk may enhance the efficacy of GBM treatment.

cancer biology↗

bioRxiv2020

Chromosome-level Genome Assembly of a Regenerable Maize Inbred Line A188

The highly embryogenic and transformable maize inbred line A188 is an attractive model for analyzing maize gene function. Here we constructed a chromosome-level genome assembly of A188 using long reads and optical maps. Genome comparison of A188 with the reference line B73 identified pervasive structural variation, including a 1.8 Mb duplication on the Gametophyte factor1 locus for unilateral cross-incompatibility and six inversions of 0.7 Mb or greater. Increased copy number of the gene, carotenoid cleavage dioxygenase 1 (ccd1) in A188 is associated with elevated expression during seed development. High ccd1 expression together with low expression of yellow endosperm 1 (y1) condition reduced carotenoid accumulation, which accounts for the white seed phenotype of A188 that contrasts with the yellow seed of B73 that has high expression of y1 and low expression of the single-copy ccd1. Further, transcriptome and epigenome analyses with the A188 reference genome revealed enhanced expression of defense pathways and altered DNA methylation patterns of embryonic callus.

genomics↗

bioRxiv2020

MicroRNA variants and HLA-miRNA interactions are novel rheumatoid arthritis susceptibility factors

ObjectiveAlthogh Genome-wide association studies have identified >100 variants for rheumatoid arthritis (RA),the reported genetic variants only explain <40% of RA heritability. We conducted a systemic association study between common East-Asian miRNA SNPs with RA in a large Han Chinese cohort to explain missing heritability and identify miRNA epistatic interactions. Methods4 HLA SNPs (HLA-DRB1, HLA-DRB9, HLA-DQB1 and TNFAIP3) and 225 common SNPs located in miRNA which might influence the miRNA target binding or pre-miRNA stability were genotyped in 1,607 rheumatoid arthritis and 1,580 matched normal individuals. A meta-analysis with previous GWAS studies (4,873 RA cases and 17,642 controls) was performed to discovery another novel miRNA RA-associated SNPs. Results2 novel SNPs including rs1414273 (miR-548ac, OR=0.84, P=8.26x10-4) and rs2620381 (miR-627, OR=0.77, P=2.55x10-3) conferred significant association with RA. Individuals carried 8 risk alleles showed 15.38 (95%CI: 4.69-50.49, P<1.0x10-6) times more risk to be affected by RA. In addition, rs5997893 (miR-3928) showed significant epistasis effect with rs4947332 (HLA-DRB1, OR=4.23, P=0.04) and rs2967897 (miR-5695) with rs7752903 (TNFAIP3, OR=4.43, P=0.03). Finally, we demonstrated targets of the significant miRNAs showed enrichment in immune related genes (P=2.0x10-5) and FDA approved drug target genes (P=0.014). Conclusions6 novel miRNA SNPs including rs1414273 (miR-548ac, P=8.26x10-4), rs2620381 (miR-627, P=2.55x10-3), rs4285314 (miR-3135b, P=1.10x10-13), rs28477407 (miR-4308, P=3.44x10-5), rs5997893 (miR-3928, P=5.9x10-3) and rs45596840 (miR-4482, P=6.6x10-3) were confirmed to be significantly associated with RA in a Chinese population. Our study suggests that miRNAs might be interesting targets to accelerate the understanding of the pathogenesis and drug development for rheumatoid arthritis.

genetics↗

bioRxiv2020

Identifying genes and cell types with dynamic alternative polyadenylation in multi-cluster single-cell transcriptomics data

Alternative polyadenylation (APA) causes shortening or lengthening of the 3-untranslated region (3-UTR) of genes across multiple cell types. Bioinformatic tools have been developed to identify genes that are affected by APA (APA genes) in single-cell RNA-Seq (scRNA-Seq) data. However, they suffer from low power, and they cannot identify APA genes specific to each cell type (cell-type-specific APA) when multiple cell types are analyzed. To address these limitations, we developed scMAPA that systematically integrates two novel steps. First, scMAPA quantifies 3-UTR long and short isoforms without requiring assumptions on the read density shape of input data. Second, scMAPA estimates the significance of the APA genes for each cell type while controlling confounders. In the analyses on our novel simulation data and human peripheral blood mono cellular data, scMAPA showed enhanced power in identifying APA genes. Further, in mouse brain data, scMAPA identifies cell-type-specific APA genes, improving interpretability for the cell-type-specific function of APA. We further showed that this improved interpretability helps to understand a novel role of APA on the interaction between neurons and blood vessels, which is critical to maintaining the operational condition of brains. With high sensitivity and interpretability, scMAPA shed novel insights into the function of dynamic APA in complex tissues. Key PointsO_LIWe developed a bioinformatic tool, scMAPA, that identifies dynamic APA across multiple cell types and a novel simulation pipeline to assess performance of such tools in APA calling. C_LIO_LIIn simulation data of various scenarios from our novel simulation pipeline, scMAPA achieves sensitivity with a minimal loss of specificity. C_LIO_LIIn human peripheral blood monocellular data, scMAPA identifies APA genes accurately and robustly, finding unique associations of APA with hematological processes. C_LIO_LIscMAPA identifies APA genes specific to each cell type in mouse brain data while controlling confounders that sheds novel insights into the complex molecular processes. C_LI

bioinformatics↗

bioRxiv2020

THERMODYNAMIC MODEL OF MESOSCALE NEURAL FIELD DYNAMICS: DERIVATION AND LINEAR ANALYSIS

Motivated by previous research suggesting that mesoscopic collective activity has the defining characteristics of a turbulent system, we postulate a thermodynamic model based on the fundamental assumption that the activity of a neuron is characterized by two distinct stages: a sub-threshold stage, described by the value of mean membrane potential, and a transitional stage, corresponding to the firing event. We therefore distinguish between two types of energy: the potential energy released during a spike, and the internal kinetic energy that triggers a spike. Formalizing these assumptions produces a system of integro-differential equations that generalizes existing models [Wilson and Cowan, 1973, Amari, 1977], with the advantage of providing explicit equations for the evolution of state variables. The linear analysis of the system shows that it supports single- or triple-point equilibria, with the refractoriness property playing a crucial role in the generation of oscillatory behavior. In single-type (excitatory) systems this derives from the natural refractory state of a neuron, producing "refractory oscillations" with periods on the order of the neuron refractory period. In dual-type systems, the inhibitory component can provide this functionality even if neuron refractory period is ignored, supporting mesoscopic-scale oscillations at much lower activity levels. Assuming that the model has any relevance for the interpretation of LFP measurements, it provides insight into mesocale dynamics. As an external forcing, theta may play a major role in modulating key parameters of the system: internal energy and excitability (refractoriness) levels, and thus in maintaining equilibrium states, and providing the increased activity necessary to sustain mesoscopic collective action. Linear analysis suggest that gamma oscillations are associated with the theta trough because it corresponds to higher levels of forced activity that decreases the stability of the equilibrium state, facilitating mesoscopic oscillations.

neuroscience↗

bioRxiv2020

Generation of clonal male and female mice through CRISPR/Cas9-mediated Y chromosome deletion in embryonic stem cells

Mice derived entirely from embryonic stem (ES) cells can be generated in one step through tetraploid complementation. Although XY male ES cell lines are commonly used in this system, occasionally, monosomic XO female all-ES mice are produced through spontaneous Y chromosome loss. Here, we describe an efficient method to obtain monosomic XO ES cells by CRISPR/Cas9-mediated deletion of the Y chromosome allowing generation of clonal male and female mice by tetraploid complementation. The monosomic XO female mice are viable and are able to produce normal male and female offspring. Direct generation of clonal male and female mice from the same mutant ES cells significantly accelerates the production of complex genetically modified mouse models by circumventing multiple rounds of outbreeding.Competing Interest StatementThe authors have declared no competing interest.View Full Text

developmental biology↗

bioRxiv2020

Binding Ability Prediction between Spike Protein and Human ACE2 Reveals the Adaptive Strategy of SARS-CoV-2 in Humans

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel coronavirus causing an outbreak of COVID-19 globally in the past six months. A relatively higher divergence on the spike protein of SASR-CoV-2 enables it to transmit across species efficiently. We particularly believe that the adaptive mutations of the receptor-binding domain (RBD) of spike protein in SARS-CoV-2 might be essential to its high transmissibility among humans. Thus here we collected 2,142 high-quality genome sequences of SARS-CoV-2 from 160 regions in over 50 countries and reconstructed their phylogeny, and also analyzed the interaction between the polymorphisms of spike protein and human ACE2 (hACE2). Phylogenetic analysis of SARS-CoV-2 and coronavirus in other hosts show SARS-CoV-2 is highly possible originated from Bat-CoV (RaTG13) found in horseshoe bat and a recombination event may occur on the spike protein of Pangolin-CoV to imbue it the ability to infect humans. Moreover, compared to the S gene of SARS-CoV-2, it is more conserved in the direct-binding sites of RBD and we noticed that spike protein of SARS-CoV-2 may under a consensus evolution to adapt to human hosts better. 3,860 amino acid mutations in spike protein RBD (T333-C525) of SARS-CoV-2 were simulated and their stability and affinity binding to hACE2 (S19-D615) were calculated. Our analysis indicates SARS-CoV-2 could infect humans from different populations with no preference, and a higher divergence in the spike protein of SARS-CoV-2 at the early stage of this pandemic may be a good indicator that could show the pathway of SARS-CoV-2 transmitting from the natural reservoir to human beings.

microbiology↗

bioRxiv2020

Mapping cell structure across scales by fusing protein images and interactions

ABSTRACTThe eukaryotic cell is a multi-scale structure with modular organization across at least four orders of magnitude1,2. Two central approaches for mapping this structure – protein fluorescent imaging and protein biophysical association – each generate extensive datasets but of distinct qualities and resolutions that are typically treated separately3,4. Here, we integrate immunofluorescent images in the Human Protein Atlas5 with ongoing affinity purification experiments from the BioPlex resource6 to create a unified hierarchical map of eukaryotic cell architecture. Integration involves configuring each approach to produce a general measure of protein distance, then calibrating the two measures using machine learning. The evolving map, called the Multi-Scale Integrated Cell (MuSIC 1.0), currently resolves 69 subcellular systems of which approximately half are undocumented. Based on these findings we perform 134 additional affinity purifications, validating close subunit associations for the majority of systems. The map elucidates roles for poorly characterized proteins, such as the appearance of FAM120C in chromatin; identifies new protein assemblies in ribosomal biogenesis, RNA splicing, nuclear speckles, and ion transport; and reveals crosstalk between cytoplasmic and mitochondrial ribosomal proteins. By integration across scales, MuSIC substantially increases the mapping resolution obtained from imaging while giving protein interactions a spatial dimension, paving the way to incorporate many molecular data types in proteome-wide maps of cells.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗

bioRxiv2020

Negative interplay between biofilm formation and competence in the environmental strains of Bacillus subtilis

Environmental strains of the soil bacterium Bacillus subtilis have valuable applications in agriculture, industry, and biotechnology. They are capable of forming robust biofilms and demonstrate excellent biological control activities in plant protection. However, environmental strains are genetically less accessible, a sharp contrast to the laboratory strains well known for their natural competence and a limitation toward their application. In this study, we observed that robust biofilm formation of the environmental strains greatly reduces the rate of competent cells within the biofilm. By using the model strain 3610, we reveal a cross-pathway regulation that allows biofilm matrix producers and competence-developing cells to undergo mutually exclusive cell differentiation. We show that the competence activator ComK represses the key biofilm regulatory gene sinI by directly binding to the sinI promoter, thus blocking competent cells from simultaneously becoming matrix producers. In parallel, the biofilm activator SlrR represses competence through three distinct mechanisms, involving both genetic regulation and cell morphological changes. We discuss potential implications of limiting competence in a bacterial biofilm. ImportanceThe soil bacterium Bacillus subtilis is capable of forming robust biofilms, a multicellular community important for its survival in the environment. B. subtilis also exhibits natural competence, the ability of cells to acquire genetic materials directly from the environment. By investigating competence development in situ during B. subtilis biofilm formation, we reveal that robust biofilm formation, an important feature of the environmental strains of B. subtilis, often greatly reduces the rate of competent cells within the biofilm. We characterize a cross-pathway regulation that allows cells associated with these two developmental events to undergo mutually exclusive cell differentiation during biofilm formation. Finally, we discuss potential biological implications of limiting competence in a bacterial biofilm.

microbiology↗

bioRxiv2020

Integrate Heterogeneous NGS and TGS Data to Boost Genome-free Transcriptome Research

It is a long-term challenge to undertake reliable transcriptomic research under different circumstances of genome availability. Here, we newly developed a genome-free computational method to aid accurate transcriptome assembly, using the amphioxus as the example. Via integrating ten next generation sequencing (NGS) transcriptome datasets and one third-generation sequencing (TGS) dataset, we built a sequence library of non-redundant expressed transcripts for the amphioxus. The library consisted of overall 91,915 distinct transcripts, 51,549 protein-coding transcripts, and 16,923 novel extragenic transcripts. This substantially improved current amphioxus genome annotation by expanding the distinct gene number from 21,954 to 38,777. We consolidated the library significantly outperformed the genome, as well as de novo method, in transcriptome assembly from multiple aspects. For convenience, we curated the Integrative Transcript Library database of the amphioxus (http://www.bio-add.org/InTrans/). In summary, this work provides a practical solution for most organisms to alleviate the heavy dependence on good quality genome in transcriptome research. It also ensures the amphioxus transcriptome research grounding on reliable data.

bioinformatics↗

bioRxiv2020

An enormous Paris polyphylla genome sheds light on genome size evolution and polyphyllin biogenesis

The monocot family Melanthiaceae with varying genome sizes in a range of 230-fold is an ideal model to study the genome size fluctuation in plants. Its family member Paris genus demonstrates an evolutionary trend of bearing huge genomes characterized by an average c-value of 49.22 pg. Here, we report a 70.18 Gb genome assembly out of the 82.55 Gb genome of Paris polyphylla var. yunnanensis (PPY), which represents the biggest sequenced genome to date. We annotate 69.53% repetitive sequences in this genome and 62.50% of which are long-terminal repeat (LTR) transposable elements. Further evolution analysis indicates that the giant genome likely results from the joint effect of common and species-specific expansion of different LTR superfamilies, which might contribute to the environment adaptation after speciation. Moreover, we identify the candidate pathway genes for the biogenesis of polyphyllins, the PPY-specific medicinal saponins, by complementary approaches including genome mining, comprehensive analysis of 31 next-generation RNA-seq data and 55.23 Gb single-molecule circular consensus sequencing (CCS) RNA-seq reads, and correlation of the transcriptome and phytochemical data of five different tissues at four growth stages. This study not only provides significant insights into plant genome size evolution, but also paves the way for the following polyphyllin synthetic biology.

plant biology↗

bioRxiv2020

A High Accurate Machine Learning Meta-Strategy for the Prediction of Intrinsically Disorder Proteins

BackgroundMany proteins or partial regions of proteins do not have stable and well-defined three-dimensional structures in vitro. Understanding intrinsically disorder proteins (IDPs) is significant for interpreting biological function as well as studying many diseases. Although more than 70 disorder predictors have been invented, many existing predictors are limited on the characteristics of proteins and do not have very high accuracy. Therefore, it is critical to formulate new strategies on disorder protein prediction. ResultsHere, we propose a machine learning meta-strategy to improve the accuracy of disordered proteins and disordered regions prediction. We first use logistic forward parameter selection to select eight most significant predictors from the current available IDP predictors. Then we design a novel meta-strategy using several machine learning models, including Decision-tree based algorithm, Naive Bayes, Random forest, and Convolutional Neural Network (CNN). By applying different strategies, the results suggest Random forest can improve the predicted single amino acid accuracy significantly to 93.35%. Using the combination vector data of eight most significant predictors as input, the Convolution Neural Network can improve the whole protein prediction to 95.62%. ConclusionAccording to the performance of our machine learning meta-strategy, the Random forest and CNN models can improve the accuracy to predict intrinsically disorder proteins.

bioinformatics↗

bioRxiv2020

SLE non-coding Genetic Risk Variant Determines the Epigenetic Dysfunction of an Immune Cell Specific Enhancer that Controls Disease-critical microRNA Expression

The human genome contains millions of putative regulatory elements, which regulate gene expression. We are just beginning to understand the functional consequences of genetic variation within these regulatory elements. Since the bulk of common genetic variation impacting polygenic disease phenotypes localizes to these non-coding regions of the genome, understanding the consequences will improve our understanding of the mechanisms mediating genetic risk in human disease. Here, we define the systemic lupus erythematosus (SLE) risk variant rs2431369 as likely causal for SLE and show that it is located in a functional regulatory element that modulates miR-146a expression. We use epigenomic analysis and genome-editing to show that the rs2431697-containing region is a distal enhancer that specifically regulates miR-146a expression in a cell-type dependent manner. 3D chromatin structure analysis demonstrates physical interaction between the rs2431697-containing region and the miR-146a promoter. Further, our data show that NF-kB binds the disease protective allele in a sequence-specific manner, leading to increased expression of this immunoregulatory microRNA. Our work provides a strategy for using disease-associated variants to define the functional regulatory elements of non-coding RNA molecules such as miR-146a and provides mechanistic links between autoimmune disease risk genetic variation and disease etiology.

genetics↗

bioRxiv2020

A quantitative model for the regulation of innate immune activation

The immune system employs a wide variety of strategies to protect the body from infection. Cells such as natural killer (NK) cells and macrophages can recognize and eliminate targets with aberrant surface ligand expression in a manner that is not antigen-specific. This innate mechanism of activation must be tightly regulated to prevent autoimmunity. Here we introduce a quantitative model of the regulation of nonspecific activation inspired by Bayesian inference. Our model captures known behaviors of innate immune cells, including adaptation to changing environments and the development of hyposensitivity after prolonged exposure to activating signals. Our analysis also reveals a tradeoff between precision and adaptation. Maintaining the ability to adapt to different environments leads to heterogeneous responses, even for hypothetical populations of immune cells and targets that have identical surface receptor and ligand expression. Collectively, our results describe an adaptive algorithm for self/nonself discrimination that functions even in the absence of antigen restriction. The same model could also apply more broadly to the adaptive regulation of activation for other immune cell types.

systems biology↗