Biology subjects

Jiang, R.

Publications and source records attributed to Jiang, R..

At least 91 records · Page 5Linked to original sources

bioRxiv2021

stPlus: a reference-based method for the accurate enhancement of spatial transcriptomics

MotivationSingle-cell RNA sequencing (scRNA-seq) techniques have revolutionized the investigation of tran-scriptomic landscape in individual cells. Recent advancements in spatial transcriptomic technologies further enable gene expression profiling and spatial organization mapping of cells simultaneously. Among the tech-nologies, imaging-based methods can offer higher spatial resolutions, while they are limited by either the small number of genes imaged or the low gene detection sensitivity. Although several methods have been proposed for enhancing spatially resolved transcriptomics, inadequate accuracy of gene expression prediction and in-sufficient ability of cell-population identification still impede the applications of these methods. ResultsWe propose stPlus, a reference-based method that leverages information in scRNA-seq data to enhance spatial transcriptomics. Based on an auto-encoder with a carefully tailored loss function, stPlus performs joint embedding and predicts spatial gene expression via a weighted k-NN. stPlus outperforms baseline meth-ods with higher gene-wise and cell-wise Spearman correlation coefficients. We also introduce a clustering-based approach to assess the enhancement performance systematically. Using the data enhanced by stPlus, cell populations can be better identified than using the measured data. The predicted expression of genes unique to scRNA-seq data can also well characterize spatial cell heterogeneity. Besides, stPlus is robust and scalable to datasets of diverse gene detection sensitivity levels, sample sizes, and number of spatially meas-ured genes. We anticipate stPlus will facilitate the analysis of spatial transcriptomics. AvailabilitystPlus with detailed documents is freely accessible at http://health.tsinghua.edu.cn/software/stPlus/ and the source code is openly available on https://github.com/xy-chen16/stPlus. Contactruijiang@tsinghua.edu.cn Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2021

Evaluation of different concentrations antibiotics on gut bacteria and growth of Ectropis obliquaProut (Lepidoptera: Geometridae)

The use of antibiotics to remove gut bacteria is a commonly used method to study gut function of insects. We assessed the impact of the artificial diet made from tea powder with different concentrations of antibiotics mixture (containing tetracycline, gentamicin, penicillin, and rifampicin) on Ectropis obliqua Prout (Lepidoptera: Geometridae) survival, growth, and reproduction. Antibiotic-induced bacterial clearance was monitored by Polymerase Chain Reaction (PCR) and by Colony-counting Methods. The results indicated that administration of the antibiotic mixture at a concentration of 200g/ml caused the increase of gut bacteria, while a concentration of 300g/ml was more effective in clearing gut bacteria but the concentration of 400g/ml caused a large number of larval deaths. The concentration of 300g/ml had no significant effect on the growth and development of E. obliqua, but had impact on fecundity. Therefore, we could use 300g/ml concentrations of the antibiotic mixture to obtain sterile E. obliqua to study the function of intestinal microbes.

animal behavior and cognition↗

bioRxiv2021

Elevated N-glycosylation of immunoglobulin G variable regions in myasthenia gravis highlights a commonality across autoantibody-associated diseases

Elevated N-linked glycosylation of immunoglobulin G variable regions (IgG-VN-Glyc) is an emerging molecular phenotype associated with autoimmune disorders. To test the broader specificity of elevated IgG-VN-Glyc, we studied patients with distinct subtypes of myasthenia gravis (MG), a B cell-mediated autoimmune disease. Our experimental design included adaptive immune receptor repertoire sequencing to quantify and characterize N-glycosylation sites in the global B cell receptor repertoire, proteomics to examine glycosylation patterns of the circulating IgG, and production of human-derived recombinant autoantibodies, which were studied with mass spectrometry and antigen binding assays to confirm occupation of glycosylation sites and determine whether they alter binding. We found that the frequency of IgG-VN-Glyc motifs was increased in the B cell repertoire of MG patients when compared to healthy donors. Motifs were introduced by both biased V gene segment usage and somatic hypermutation. IgG-VN-Glyc could be observed in the circulating IgG in a subset of MG patients. Autoantigen binding, by patient-derived MG autoantigen-specific monoclonal antibodies with experimentally confirmed presence of IgG-VN-Glyc, was not altered by the glycosylation. Our findings extend prior work on patterns of variable region N-linked glycosylation in autoimmunity to MG subtypes. Although occupied IgG-VN-Glyc motifs are found on MG autoantigen-specific monoclonal antibodies, they are not required for binding to the autoantigen in this disease.

immunology↗

bioRxiv2021

High-throughput and dosage-controlled intracellular delivery of large cargos by an acoustic-electric micro-vortices platform

Intracellular delivery of cargos for cell engineering plays a pivotal role in transforming medicine and biomedical discoveries. Recent advances in microfluidics and nanotechnology have opened up new avenues for efficient, safe, and controllable intracellular delivery, as they improve precision down to the single-cell level. Based on this capability, several promising micro- and nanotechnology approaches outperform viral and conventional non-viral techniques in offering dosage-controlled delivery and/or intracellular delivery of large cargos. However, to achieve this level of precision and effectiveness, they are either low in throughput, limited to specific cell types (e.g., adherent vs. suspension cells), or complicated to operate with. To address these challenges, here we introduce a versatile and simple-to-use intracellular delivery microfluidic platform, termed Acoustic-Electric Shear Orbiting Poration (AESOP). Hundreds of acoustic microstreaming vortices form the production line of the AESOP platform, wherein hundreds of thousands of cells are trapped, permeabilized, and mixed with exogenous cargos. Using AESOP, we show intracellular delivery of a wide range of molecules (from <1 kDa to 2 MDa) with high efficiency, cell viability, and dosage-controlled capability into both suspension and adherent cells and demonstrate throughput at 1 million cells/min per single chip. In addition, we demonstrate AESOP for two gene editing applications that require delivery of large plasmids: i) eGFP plasmid (6.1 kbp) transfection, and ii) CRISPR-Cas9-mediated gene knockout using a 9.3 kbp plasmid DNA encoding Cas9 protein and sgRNA. Compared to alternative platforms, AESOP not only offers dosage-controlled intracellular delivery of large plasmids (>6kbp) with viabilities over 80% and comparable delivery efficiencies, but also is an order of magnitude higher in throughput, compatible with both adherent and suspension cell lines, and simple to operate.

bioengineering↗

bioRxiv2021

NeuronMotif: Deciphering transcriptional cis-regulatory codes from deep neural networks

Discovering DNA regulatory sequence motifs and their relative positions are vital to understand the mechanisms of gene expression regulation. Such complicated motif grammars are difficult to be summarized from shallow models. Although Deep Convolutional Neural Network (DCNN) achieved great success in annotating cis-regulatory elements, few combinatorial motif grammars have been accurately interpreted due to the mixed signal in DCNN. To address this problem, we proposed NeuronMotif, a general backward decoupling algorithm, to reveal the homo-/hetero-typic motif combinations and arrangements embedded in convolutional neurons. We applied NeuronMotif on several widely-used DCNN models. Many uncovered motif grammars of deep convolutional neurons are supported by literature or ATAC-seq footprinting. We further diagnosed the sick neurons that are sensitive to adversarial noises, which can guide DCNN architecture optimization for better prediction performance and motif feature extraction. Overall, NeuronMotif enables decoding cis-regulatory codes from deep convolutional neurons and understanding DCNN from a novel perspective.

bioinformatics↗

bioRxiv2021

Prediction of occult tumor progression via platelet RNAs in a mouse melanoma model: a potential new platform of cancer screening for early detection of cancer

Cancer screening provides the opportunity to detect cancer early, ideally before symptom onset and metastasis, and offers an increased opportunity for a better prognosis. The ideal biomarkers for cancer screening should discriminate individuals who have not developed invasive cancer yet but are destined to do so from healthy subjects1,2. However, most cancers lack effective screening recommendations. Therefore, further studies on novel screening strategies are urgently required. Here, our proof-of-concept study shows blood platelets could be a platform for liquid biopsy-based early cancer detection. By using a simple suboptimal inoculation melanoma mouse model, we identified differentially expressed RNAs in platelet signatures of mice injected with a suboptimal number of cancer cells (eDEGs) compared with mice with macroscopic melanomas and negative controls. These RNAs were strongly enriched in pathways related to immune response and regulation. Moreover, 36 genes selected from the eDEGs via bioinformatics analyses were verified in a mouse validation cohort via quantitative real-time PCR. LASSO regression was employed to generate the prediction models with gene expression signatures as the best predictors for occult tumor progression in mice. The prediction models showed great diagnostic efficacy and predictive value in our murine validation cohort, and could discriminate mice with occult tumors from control group (area under curve (AUC) of 0.935 (training data) and 0.912 (testing data)) (gene signature including Cd19, Cdkn1a, S100a9, Tap1, and Tnfrsf1b) and also from macroscopic tumor group (AUC of 0.920 (training data) and 0.936 (testing data)) (gene signature including Ccr7, Cd4, Kmt2d, and Ly6e). Our study provides evidence for potential clinical relevance of blood platelets as a platform for liquid biopsy-based early detection of cancer. Furthermore, the eDEGs are mostly immune-related, not tumor-specific. Hence it is possible platelets-based liquid biopsy could enable simultaneous early detection of cancers from multiple organs of origin3. It is also feasible to determine the origin of cancer since platelet profiles are influenced by tumor type3.

cancer biology↗

bioRxiv2021

A unique GCN5 histone acetyltransferase complex controls erythrocyte invasion and virulence in the malaria parasite Plasmodium falciparum

The histone acetyltransferase GCN5-associated SAGA complex is evolutionarily conserved from yeast to human and functions as a general transcription co-activator in global gene regulation. In this study, we identified a divergent GCN5 complex in Plasmodium falciparum, which contains two plant homeodomain (PHD) proteins (PfPHD1 and PfPHD2) and a plant apetela2 (AP2)-domain transcription factor (PfAP2-LT). To dissect the functions of the PfGCN5 complex, we generated parasites with the bromodomain deletion in PfGCN5 and the PHD domain deletion in PfPHD1. The two deletion mutants closely phenocopied each other, exhibiting significantly reduced merozoite invasion of erythrocytes and elevated sexual conversion. These domain deletions caused dramatic decreases not only in histone H3K9 acetylation but also in H3K4 trimethylation, indicating synergistic crosstalk between the two euchromatin marks. Domain deletion in either PfGCN5 or PfPHD1 profoundly disturbed the global transcription pattern, causing altered expression of more than 60% of the genes. At the schizont stage, these domain deletions were linked to specific downregulation of merozoite genes involved in erythrocyte invasion, many of which harbor the DNA-binding motifs for AP2-LT and/or AP2-I, suggesting targeted recruitment of the PfGCN5 complex to the invasion genes by these specific transcription factors. Conversely, at the ring stage, PfGCN5 or PfPHD1 domain deletions disrupted the mutually exclusive expression pattern of the entire var gene family, which encodes the virulent factor PfEMP1. Correlation analysis between the chromatin state and alteration of gene expression demonstrated that up- and down-regulated genes in these mutants are highly correlated with the silenct and active chromatin states in the wild-type parasite, respectively. Collectively, the PfGCN5 complex represents a novel HAT complex with a unique subunit composition including the AP2 transcription factor, which signifies a new paradigm for targeting the co-activator complex to regulate general and parasite-specific cellular processes in this low-branching parasitic protist. Author SummaryEpigenetic regulation of gene expression plays essential roles in orchestrating the general and parasite-specific cellular pathways in the malaria parasite Plasmodium falciparum. Using tandem affinity purification and proteomic characterization, we identified a divergent transcription co-activator - the histone acetyltransferase GCN5-associated complex in P. falciparum, which contains nine core components, including two PHD domain proteins (PfPHD1 and PfPHD2) and a plant apetela2-domain transcription factor. To understand the functions of the PfGCN5 complex, we performed gene disruption in two subunits of this complex, PfGCN5 and PfPHD1. We found that the two deletion mutants displayed very similar growth phenotypes, including significantly reduced merozoite invasion rates and elevated sexual conversion. These two mutants were associated with dramatic decreases in histone H3K9 acetylation and H3K4 trimethylation, which led to global changes in chromatin states and gene expression. Genes significantly affected by the PfGCN5 and PfPHD1 gene disruption include those participating in parasite-specific pathways such as invasion, virulence, and sexual development. In conclusion, this study presents a new model of the PfGCN5 complex for targeting the co-activator complex to regulate general and parasite-specific cellular processes in this low-branching parasitic protist.

microbiology↗

bioRxiv2021

Determine independent gut microbiota-diseases association by eliminating the effects of human lifestyle factors

Human lifestyle and physiological variables on human disease risk have been revealed to be mediated by gut microbiota. Low concordance between many case-control studies for detecting disease-associated microbe existed and it is likely due to the limited sample size and the population-wide bias in human lifestyle and physiological variables. To infer association between whole gut microbiota and diseases accurately, we propose to build machine learning models by including both human variables and gut microbiota based on the American Gut Project data, the largest known publicly available human gut bacterial microbiota dataset. When the model's performance with both gut microbiota and human variables is better than the model with just human variables, the independent association of gut microbiota with the disease will be confirmed. We found that gut microbes showed different association strengths with different diseases. Adding gut microbiota into human variables enhanced the association strengths with inflammatory bowel disease (IBD) and unhealthy status; showed no effect on association strengths with Diabetes and IBS; reduced the association strengths with small intestinal bacterial overgrowth, C. difficile infection, lactose intolerance, cardiovascular disease and mental disorders. Our results suggested that although gut microbiota was reported to be associated with many diseases, a considerable proportion of these associations may be spurious. We also proposed a list of microbes as biomarkers to classify IBD and unhealthy status, and validated them by reference to previously published research. IMPORTANCEwe reexamined the association between gut microbiota and multiple diseases via machine learning models on a large-scale dataset, and by considering the effect of human variables ignored by previous studies, truly independent microbiota-disease associations were estimated. We found gut microbiota is associated independently with IBD and overall health of human, but more evidence is needed to judge associations between microbiota and other diseases. Further functional investigations of our reported disease-related microbes will improve understanding of the molecular mechanism of human diseases.

bioinformatics↗

bioRxiv2021

Human B cell lineages engaged by germinal centers following influenza vaccination are measurably evolving

Poor efficacy of seasonal influenza virus vaccines is often attributed to pre-existing immunity interfering with the persistence and maturation of vaccine-induced B cell responses.1 Consistent with this notion, no significant increase in somatic hypermutation (SHM) among circulating influenza-binding lineages was detected following seasonal vaccination in humans.2 A more recent study showed that at least a subset of vaccine-induced B cell lineages are recruited into germinal centers (GCs) following vaccination, suggesting that affinity maturation of these lineages can occur.3 Crucially, however, it has not been demonstrated whether these GC-engaged lineages actually accumulate additional SHM. Here, we address this point using a phylogenetic test of measurable evolution. We first validate this test through simulations and demonstrate measurable B cell evolution in known examples of affinity maturation such as the response to HIV infection. We then show that lineages in the blood are rarely measurably evolving following influenza vaccination, but that GC-engaged lineages - likely derived from memory B cells - are frequently measurably evolving. These findings confirm that seasonal influenza virus vaccination can stimulate additional SHM among responding B cell lineages.

immunology↗

bioRxiv2020

Zeros in scRNA-seq data: good or bad? How to embrace or tackle zeros in scRNA-seq data analysis?

Researchers view vast zeros in single-cell RNA-seq data differently: some regard zeros as biological signals representing no or low gene expression, while others regard zeros as missing data to be corrected. To help address the controversy, here we discuss the sources of biological and non-biological zeros; introduce five mechanisms of adding non-biological zeros in computational benchmarking; evaluate the impacts of non-biological zeros on data analysis; benchmark three input data types: observed counts, imputed counts, and binarized counts; discuss the open questions regarding non-biological zeros; and advocate the importance of transparent analysis.

bioinformatics↗

bioRxiv2020

Immunologically distinct responses occur in the CNS of COVID-19 patients

One third of COVID-19 patients develop significant neurological symptoms, yet SARS-CoV-2 is rarely detected in central nervous system (CNS) tissue, suggesting a potential role for parainfectious processes, including neuroimmune responses. We therefore examined immune parameters in cerebrospinal fluid (CSF) and blood samples from a cohort of patients with COVID-19 and significant neurological complications. We found divergent immunological responses in the CNS compartment, including increased levels of IL-12 and IL-12-associated innate and adaptive immune cell activation. Moreover, we found increased proportions of B cells in the CSF relative to the periphery and evidence of clonal expansion of CSF B cells, suggesting a divergent intrathecal humoral response to SARS-CoV-2. Indeed, all COVID-19 cases examined had anti-SARS-CoV-2 IgG antibodies in the CSF whose target epitopes diverged from serum antibodies. We directly examined whether CSF resident antibodies target self-antigens and found a significant burden of CNS autoimmunity, with the CSF from most patients recognizing neural self-antigens. Finally, we produced a panel of monoclonal antibodies from patients CSF and show that these target both anti-viral and anti-neural antigens--including one mAb specific for the spike protein that also recognizes neural tissue. This exploratory immune survey reveals evidence of a compartmentalized and self-reactive immune response in the CNS meriting a more systematic evaluation of neurologically impaired COVID-19 patients. One Sentence SummaryA subset of COVID-19 patients with neurologic impairment show cerebrospinal fluid-specific immune alterations that point to both neuroinvasion and anti-neural autoimmunity as potential causes of impairment.

immunology↗

bioRxiv2020

Simultaneous deep generative modeling and clustering of single cell genomic data

Recent advances in single-cell technologies, including single-cell ATAC-seq (scATAC-seq), have enabled large-scale profiling of the chromatin accessibility landscape at the single cell level. However, the characteristics of scATAC-seq data, including high sparsity and high dimensionality, have greatly complicated the computational analysis. Here, we proposed scDEC, a computational tool for single cell ATAC-seq analysis with deep generative neural networks. scDEC is built on a pair of generative adversarial networks (GANs), and is capable of learning the latent representation and inferring the cell labels, simultaneously. In a series of experiments, scDEC demonstrates superior performance over other tools in scATAC-seq analysis across multiple datasets and experimental settings. In the downstream applications, we demonstrated that the generative power of scDEC helps to infer the trajectory and intermediate state of cells during differentiation and the latent features learned by scDEC can potentially reveal both biological cell types and within-cell-type variations.

bioinformatics↗

bioRxiv2020

A valid protective immune response elicited in rhesus macaques by an inactivated vaccine is capable of defending against SARS-CoV-2 infection

With the relatively serious global epidemic outbreak of SARS-CoV-2 infection, public concerns focus on not only clinical therapeutic measures and public quarantine for this disease but also the development of vaccines. The technical design of our SARS-CoV-2 inactivated vaccine provides a viral antigen that enables the exposure of more than one structural protein based upon the antibody composition of COVID-19 patients convalescent serum. This design led to valid immunity with increasing neutralizing antibody titers and a CTL response detected post-immunization of this vaccine by two injections in rhesus macaques. Further, this elicited immunoprotection in macaques enables not only to restrain completely viral replication in tissues of immunized animals, compared to the adjuvant control and those immunized by an RBD peptide vaccine, but also to significantly alleviate inflammatory lesion in lung tissues in histo-pathologic detection, compared to the adjuvant control with developed interstitial pneumonia. The data obtained from these macaques immunized with the inactivated vaccine or RBD peptide vaccine suggest that immunity with a clinically protective effect against SARS-CoV-2 infection should include not only specific neutralizing antibodies but also specific CTL responses against at least the S and N antigens.

immunology↗

bioRxiv2020

A reference-guided approach for epigenetic characterization of single cells

The recent advancements in single-cell technologies, including single-cell chromatin accessibility sequencing (scCAS), have enabled profiling the epigenetic landscapes for thousands of individual cells. However, the characteristics of scCAS data, including high dimensionality, high degree of sparsity and high technical variation, make the computational analysis challenging. Reference-guided approach, which utilizes the information in existing datasets, may facilitate the analysis of scCAS data. We present RA3 (Reference-guided Approach for the Analysis of single-cell chromatin Acessibility data), which utilizes the information in massive existing bulk chromatin accessibility and annotated scCAS data. RA3 simultaneously models 1) the shared biological variation among scCAS data and the reference data, and 2) the unique biological variation in scCAS data that identifies distinct subpopulations. We show that RA3 achieves superior performance in many scCAS datasets. We also present several approaches to construct the reference data to demonstrate the wide applicability of RA3.

bioinformatics↗

bioRxiv2020

Glycyrrhizic acid improves cognitive levels of aging mice by regulating T/B cell proliferation

Dear Editor,Licorice is the root of Glycyrrhiza glabra L. (Leguminosae), which grows in various warm climates such as the Middle East, Asia, and Southern Europe. It is one of the oldest known medicinal herbs and is referred to as "the father of herbal medicine." Glycyrrhizic acid (GA) (Fig. 1A), a triterpenoid saponin, is a major component of licorice. It has a variety of pharmacological activities such as anti-inflammatory, antioxidant, anticancer, neuroprotective, and immune effects, among others.[1]. Previous studies indicated that GA produces robust neuroprotection via the modulation of anti-apoptotic and pro-apoptotic factors, primarily through the ERK signaling pathway and its anti-inflammatory properties against high-mobility group box 1 phosphorylation and the suppression of inflammatory cytokine induction [2-4]. These results were based on pathological models. Although numerous pathways have been implicated in the neuroprotective effects of GA, the molecular mechanisms are not yet completely understood. In this study, we aimed to investigate the effects of GA in preventing age-related immune involution and cognitive disorders, the relationship between immune involution and cognition, and the underlying molecular mechanisms. O_FIG O_LINKSMALLFIG WIDTH=141 HEIGHT=200 SRC="FIGDIR/small/008821v1_fig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@5a123dorg.highwire.dtl.DTLVardef@163a085org.highwire.dtl.DTLVardef@1bfadb6org.highwire.dtl.DTLVardef@125b2ae_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Glycyrrhizic acid ameliorated cognitive declines in aged mice, improved CBF and increased T and B cell numbers. A. The chemical structure of glycyrrhizic acid (GA). B. Escape latencies from six consecutive daily tests. C. The first platform-finding latencies in the probe trial. D. The time spent in the target quadrant in the probe trial. E. The target platform crossing times in the probe trial. F. Images of CBF in C57BL/6 mice. G. Quantification of blood perfusion in the ipsilateral hemisphere. H. Bubble diagram showing GA treatment influence on hematopoietic cell lineage. I. Heatmap showing actively expressed genes related to T cells in the hematopoietic cell lineage of control and GA-treated C57BL/6 mice. J. Representative FACS plots showing CD3e+ T and CD45R/B220+ B cells in the spleens of C57BL mice; bar graphs showing the statistical analysis of T and B cells in the spleens of C57BL mice. K. Representative FACS plots showing CD3e+ T and CD45R/B220+ B cells in the blood of C57BL mice; Bar graphs showing the statistical results of T and B cell analyses in the blood of C57BL mice. GA (5mg/kg, once every other day); Data represent mean {+/-} SEM (n = 8 per group). *P < 0.05, **P < 0.01, ***P < 0.001 vs. Ctrl. C_FIG

animal behavior and cognition↗

bioRxiv2020

Self-antigen driven affinity maturation is required for pathogenic monovalent IgG4 autoantibody development

Pathogenic IgG4 autoantibodies in autoimmune myasthenia gravis (MG) are functionally monovalent as a result of Fab-arm exchange. The origin and development of these unique autoantibodies are not well understood. We examined MG patient-derived monoclonal autoantibodies (mAbs), their corresponding germline-encoded unmutated common ancestors (UCA) and monovalent antigen-binding fragments (Fabs) to investigate how antigen-driven affinity maturation contributes to both binding and immunopathology. Mature mAbs, their UCA counterparts and mature monovalent Fabs bound to the autoantigen and retained their pathogenic capacity. However, monovalent UCA Fabs still bound the autoantigen but lost their pathogenic capacity. The mature Fabs were characterized by very high affinity (sub-nanomolar) driven by a rapid on-rate and slow off-rate. However, the UCA affinity was approximately 100-fold less than that of the mature Fabs, which was driven by a rapid off-rate. Crystal structures of two Fabs shed light on how mutations acquired during affinity maturation may contribute to increased MuSK binding affinity. These collective findings indicate that the autoantigen initiates the autoimmune response in MuSK MG and drives autoimmunity through the accumulation of somatic hypermutation such that monovalent IgG4 Fab-arm exchanged MG autoantibodies reach a high affinity threshold required for pathogenic capacity. SummaryIgG4 autoantibodies in autoimmune myasthenia gravis are functionally monovalent, requiring a high affinity threshold featuring fast on/slow off rates, to reach pathogenic capacity. This capacity is dependent on self-antigen initiated and driven maturation, which includes the accumulation of indispensable somatic hypermutations that may alter electrostatic interactions with the antigen.

immunology↗

bioRxiv2020

mbImpute: an accurate and robust imputation method for microbiome data

Microbiome studies have gained increased attention since many discoveries revealed connections between human microbiome compositions and diseases. A critical challenge in microbiome research is that excess non-biological zeros distort taxon abundances, complicate data analysis, and jeopardize the reliability of scientific discoveries. To address this issue, we propose the first imputation method, mbImpute, to identify and recover likely non-biological zeros by borrowing information jointly from similar samples, similar taxa, and optional metadata including sample covariates and taxon phylogeny. Comprehensive simulations verified that mbImpute achieved better imputation accuracy under multiple measures than five state-of-the-art imputation methods designed for non-microbiome data. In real data applications, we demonstrate that mbImpute improved the power and reproducibility of identifying disease-related taxa from microbiome data of type 2 diabetes and colorectal cancer.

genomics↗

bioRxiv2020

Neuroimaging-based Individualized Prediction of Cognition and Behavior for Mental Disorders and Health: Methods and Promises

The neuroimaging community has witnessed a paradigm shift in biomarker discovery from using traditional univariate brain mapping approaches to multivariate predictive models, allowing the field to move towards a translational neuroscience era. Regression-based multivariate models (hereafter "predictive modeling") provide a powerful and widely-used approach to predict human behavior with neuroimaging features. These studies maintain a focus on decoding individual differences in a continuously behavioral phenotype from neuroimaging data, opening up an exciting opportunity to describe the human brain at the single-subject level. In this survey, we provide an overview of recent studies that utilize machine learning approaches to identify neuroimaging predictors over the past decade. We first review regression-based approaches and highlight connectome-based predictive modeling (CPM), which has grown in popularity in recent years. Next, we systematically describe recent representative studies using these tools in the context of cognitive function, symptom severity, personality traits and emotion processing. Finally, we highlight a few challenges related to combining multimodal data, longitudinal prediction, external validations and the employment of deep learning methods that have emerged from our review of the existing literature, as well as present some promising and challenging future directions.

neuroscience↗