Biology subjects

Zhu, B.

Publications and source records attributed to Zhu, B..

At least 145 records · Page 8Linked to original sources

bioRxiv2022

An open protocol for modeling T Cell Clonotype repertoires using TCRβ CDR3 sequences

T cell receptor (TCR) repertoires can be profiled using next generation sequencing (NGS) to monitor dynamical changes in response to disease and other perturbations. Several strategies for profiling TCRs have been recently developed with different benefits and drawbacks. Genomic DNA-based bulk sequencing, however, remains the most cost-effective method to profile TCRs. The major disadvantage of this method is the need for multiplex target amplification with a large set of primer pairs with potentially very different amplification efficiencies. One approach addressing this problem is by iteratively adjusting the concentrations of the primers based on their efficiencies, and then computationally correcting any remaining bias. Yet there are no standard, publicly available protocols to process and analyze raw sequencing data generated by this method. Here, we utilize an equimolar primer mixture and propose a single statistical normalization step that efficiently corrects for amplification bias post sequencing. Using samples analyzed by both approaches, we show that the concordance between bulk clonality metrics obtained from using the commercial kits and that developed herein is high. Therefore, we suggest the method presented here as an inexpensive and non-commercial alternative for measuring and monitoring adaptive dynamics in TCR clonotype repertoire.

bioinformatics↗

bioRxiv2022

Single-cell transcriptomic and proteomic analysis of Parkinson's disease Brains

Parkinsons disease (PD) is a prevalent neurodegenerative disorder where recent evidence suggests pathogenesis may be mediated by inflammatory processes. The molecular architecture of the disease remains to be fully elucidated. We performed single-nucleus transcriptomics and unbiased proteomics using postmortem tissue obtained from the prefrontal cortex of 12 individuals with late-stage PD and age-matched controls. We analyzed [~]80,000 nuclei and identified eight major cell types, including brain-resident T cells, each with distinct transcriptional changes in line with the known genetics of PD. By analyzing Lewy body pathology in the same postmortem tissue, we found that -synuclein pathology is inversely correlated with chaperone expression in excitatory neurons. Examining cell-cell interactions, we found a selective abatement of neuron-astrocyte interactions and enhanced neuroinflammation. Proteomic analyses of the same brains identified synaptic proteins in prefrontal cortex that were preferentially downregulated in PD. Strikingly, comparing this dataset to a regionally similar published analysis for Alzheimers disease (AD), we found no common differentially expressed genes in neurons, but identified many shared differentially expressed genes in glial cells, suggesting that disease etiology in PD and AD are likely distinct. These data are presented as a resource for interrogating the molecular and cellular basis of PD and other neurodegenerative diseases. One Sentence SummaryWe provide an extensive single cell analysis profiling nearly 80,000 brain nuclei from prefrontal cortex of late-stage Parkinsons disease brains, demonstrate that -synuclein pathology is inversely correlated with chaperone expression in excitatory neurons, found a selective abatement of neuron-astrocyte interactions with enhanced neuroinflammation, and augmented the study with proteomic analysis and cross-comparisons with Alzheimers disease datasets, providing valuable insights into the pathways of neurodegeneration and a deep definition of the underlying molecular pathology for Parkinsons disease.

neuroscience↗

bioRxiv2022

Photolabile curcumin with physically and molecularly produced light for attenuating of neurotoxicity of amyloid beta species

Over the past decades, classical drug development approaches for Alzheimers disease have yielded limited success, and this futileness has prompted scientists to seek non-classical approaches. In this report, we demonstrated that, with irradiation of LED light or with molecularly generated light (dubbed as "molecular light") from chemiluminescence probe ADLumin-4, photolabile curcumin analogue CRANAD-147 could change properties, structures (sequences) and neurotoxicity of amyloid beta (A{beta}) species in vitro. We further demonstrated that, with the assistance from molecular chemiluminescence imaging, the combination of CRANAD-147/LED or CRANAD-147/ADLumin-4 (molecular light) could slow down the accumulation of A{beta}s in transgenic 5xFAD mice in vivo. Due to the unlimited capacity of tissue penetration of molecular light in vivo, phototherapy with the combination of photolabile A{beta} ligand and molecular light has great potential as an alternative approach for AD drug discovery.

biochemistry↗

bioRxiv2022

Sex-specific transcription and DNA methylation landscapes of the Asian citrus psyllid, a vector of huanglongbing pathogens.

The relationship of DNA methylation and sex-biased gene expression is of high interest, it allows research into mechanisms of sexual dimorphism and the development of potential novel strategies for insect pest control. The Asian citrus psyllid, Diaphorina citri Kuwayama, is a major vector for the causative agents of Huanglongbing (HLB), which presents an unparalleled challenge to citrus production worldwide. Here, we identify the X chromosome of D. citri and investigate differences in the transcription and DNA methylation landscapes between adult virgin males and females. We find a large number of male-biased genes on the autosomes and a depletion of such on the X chromosome. We have also characterised the methylome of D. citri, finding low genome-wide levels, which is unusual for an hemipteran species, as well as evidence for both promoter and TE methylation. Overall, DNA methylation profiles are similar between the sexes but with a small number of differentially methylated genes found to be involved in sex differentiation. There also appears to be no direct relationship between differential DNA methylation and differential gene expression. Our findings lay the groundwork for the development of novel epigenetic-based pest control methods, and given the similarity of the D. citri methylome to other insect species, these methods could be applicable across agricultural insect pests.

evolutionary biology↗

bioRxiv2021

Structural and functional characterizations of altered infectivity and immune evasion of SARS-CoV-2 Omicron variant

The SARS-CoV-2 Omicron with increased fitness is spreading rapidly worldwide. Analysis of cryo-EM structures of the Spike (S) from Omicron reveals amino acid substitutions forging new interactions that stably maintain an "active" conformation for receptor recognition. The relatively more compact domain organization confers improved stability and enhances attachment but compromises the efficiency of viral fusion step. Alterations in local conformation, charge and hydrophobic microenvironments underpin the modulation of the epitopes such that they are not recognized by most NTD- and RBD-antibodies, facilitating viral immune escape. Apart from already existing mutations, we have identified three new immune escape sites: 1) Q493R, 2) G446S and 3) S371L/S373P/S375F that confers greater resistance to five of the six classes of RBD-antibodies. Structure of the Omicron S bound with human ACE2, together with analysis of sequence conservation in ACE2 binding region of 25 sarbecovirus members as well as heatmaps of the immunogenic sites and their corresponding mutational frequencies sheds light on conserved and structurally restrained regions that can be used for the development of broad-spectrum vaccines and therapeutics.

biophysics↗

bioRxiv2021

A subset of Memory B-derived antibody repertoire from 3-dose vaccinees is ultrapotent against diverse and highly transmissible SARS-CoV-2 variants, including Omicron

Omicron, the most heavily mutated SARS-CoV-2 variant so far, is highly resistant to neutralizing antibodies, raising unprecedented concerns about the effectiveness of antibody therapies and vaccines. We examined whether sera from individuals who received two or three doses of inactivated vaccine, could neutralize authentic Omicron. The seroconversion rates of neutralizing antibodies were 3.3% (2/60) and 95% (57/60) for 2- and 3-dose vaccinees, respectively. For three-dose recipients, the geometric mean neutralization antibody titer (GMT) of Omicron was 15, 16.5-fold lower than that of the ancestral virus (254). We isolated 323 human monoclonal antibodies derived from memory B cells in 3-dose vaccinees, half of which recognize the receptor binding domain (RBD) and show that a subset of them (24/163) neutralize all SARS-CoV-2 variants of concern (VOCs), including Omicron, potently. Therapeutic treatments with representative broadly neutralizing mAbs individually or antibody cocktails were highly protective against SARS-CoV-2 Beta infection in mice. Atomic structures of the Omicron S in complex with three types of all five VOC-reactive antibodies defined the binding and neutralizing determinants and revealed a key antibody escape site, G446S, that confers greater resistance to one major class of antibodies bound at the right shoulder of RBD through altering local conformation at the binding interface. Our results rationalize the use of 3-dose immunization regimens and suggest that the fundamental epitopes revealed by these broadly ultrapotent antibodies are a rational target for a universal sarbecovirus vaccine. One sentence summaryA sub-set of antibodies derived from memory B cells of volunteers vaccinated with 3 doses of an inactivated SARS-CoV-2 vaccine work individually as well as synergistically to keep variants, including Omicron, at bay.

microbiology↗

bioRxiv2021

Identifying Uncertainty States during Wayfinding in Indoor Environments: An EEG Classification Study

The researchers used a machine-learning classification approach to better understand neurological features associated with periods of wayfinding uncertainty. The participants (n=30) were asked to complete wayfinding tasks of varying difficulty in a virtual reality (VR) hospital environment. Time segments when participants experienced navigational uncertainty were first identified using a combination of objective measurements (frequency of inputs into the VR controller) and behavioral annotations from two independent observers. Uncertainty time-segments during navigation were ranked on a scale from 1 (low) to 5 (high). The machine-learning model, a random forest classifier implemented using scikit-learn in Python, was used to evaluate common spatial patterns of EEG spectral power across the theta, alpha, and beta bands associated with the researcher-identified uncertainty states. The overall predictive power of the resulting model was 0.70 in terms of the area under the Receiver Operating Characteristics curve (ROC-AUC). These findings indicate that EEG data can potentially be used as a metric for identifying navigational uncertainty states, which may provide greater rigor and efficiency in studies of human responses to architectural design variables and wayfinding cues.

neuroscience↗

bioRxiv2021

Robust Single-cell Matching and Multi-modalAnalysis Using Shared and Distinct FeaturesReveals Orchestrated Immune Responses

The ability to align individual cellular information from multiple experimental sources, techniques and systems is fundamental for a true systems-level understanding of biological processes. While single-cell transcriptomic studies have transformed our appreciation for the complexities and contributions of diverse cell types to disease, they can be limited in their ability to assess protein-level phenotypic information and beyond. Therefore, matching and integrating single-cell datasets which utilize robust protein measurements across multiple modalities is critical for a deeper understanding of cell states, and signaling pathways particularly within their native tissue context. Current available tools are mainly designed for single-cell transcriptomics matching and integration, and generally rely upon a large number of shared features across datasets for mutual Nearest Neighbor (mNN) matching. This approach is unsuitable when applied to single-cell proteomic datasets, due to the limited number of parameters simultaneously accessed, and lack of shared markers across these experiments. Here, we introduce a novel cell matching algorithm, Matching with pARtIal Overlap (MARIO), that takes into account both shared and distinct features, while consisting of vital filtering steps to avoid sub-optimal matching. MARIO accurately matches and integrates data from different single-cell proteomic and multi-modal methods, including spatial techniques, and has cross-species capabilities. MARIO robustly matched tissue macrophages identified from COVID-19 lung autopsies via CODEX imaging to macrophages recovered from COVID-19 bronchoalveolar lavage fluid via CITE-seq. This cross-platform integrative analysis enabled the identification of unique orchestrated immune responses within the lung of complement-expressing macrophages and their impact on the local tissue microenvironment. MARIO thus provides an analytical framework for unified analysis of single-cell data for a comprehensive understanding of the underlying biological system.

bioinformatics↗

bioRxiv2021

On the reproductive mechanism of Gram-negative protocells

Bacterial protoplasts are known to reproduce independently of canonical molecular biological processes. Their reproduction is shown to be mediated entirely by the physicochemical properties of cell constituents. However, the physiochemical properties of the cell constituents are influenced by the environmental conditions like salinity, salt composition, and mechanical stresses experienced by a cell in natural environments. The influence of such environmental conditions on protoplast reproduction is seldom investigated. Here, we studied protoplast reproduction in their native environmental conditions. Contrary to the previous perceptions of protoplasts reproducing in an erratic manner, cells in our study reproduced in a defined sequence of steps. The process of their reproduction can be explained by an interplay between intracellular metabolism, the physicochemical properties of cell constituents, and the nature of cations in the growth media. We observed a minimal leakage of intracellular constituents during protoplast reproduction, suggesting an efficient reproduction. However, the efficiency of reproduction is determined by the environmental conditions. Under favorable environmental conditions, protoplasts reproduce with nearly similar efficiency to cells that possess a cell wall. In short, here we demonstrate the simplest method of cellular reproduction and the influence of environmental conditions on this process.

biophysics↗

bioRxiv2021

ProtAnno, an Automated Cell Type Annotation Tool for Single Cell Proteomics Data that Integrates Information from Multiple Reference Sources

Compared with sequencing-based global genomic profiling, cytometry labels targeted surface markers on millions of cells in parallel either by conjugated rare earth metal particles or Unique Molecular Identifier (UMI) barcodes. Correct annotation of these cells to specific cell types is a key step in the analysis of these data. However, there is no computational tool that automatically annotates single cell proteomics data for cell type inference. In this manuscript, we propose an automated single cell proteomics data annotation approach called ProtAnno to facilitate cell type assignments without laborious manual gating. ProtAnno is designed to incorporate information from annotated single cell RNA-seq (scRNA-seq), CITE-seq, and prior data knowledge (which can be imprecise) on biomarkers for different cell types. We have performed extensive simulations to demonstrate the accuracy and robustness of ProtAnno. For several single cell proteomics datasets that have been manually labeled, ProtAnno was able to correctly label most single cells. In summary, ProtAnno offers an accurate and robust tool to automate cell type annotations for large single cell proteomics datasets, and the analysis of such annotated cell types can offer valuable biological insights.

bioinformatics↗

bioRxiv2021

Enterotoxigenic Escherichia coli display a distinct growth phase before entry into stationary phase with shifts in tryptophan- fucose- and putrescine metabolism and degradation of neurotransmitter precursors

Enterotoxigenic Escherichia coli (ETEC) is a major cause of diarrhea in children and adults in endemic areas. Gene regulation of ETEC during growth in vitro and in vivo needs to be further evaluated, and here we describe the full transcriptome and metabolome of ETEC during growth from mid-logarithmic growth to stationary phase in rich medium (LB medium). We identified specific genes and pathways subjected to rapid transient alterations in gene expression and metabolite production during the transition between logarithmic to stationary growth. The transient phase during late exponential growth is different from the subsequent induction of stationary phase-induced genes, including stress and survival responses as described earlier. The transient phase was characterized by the repression of genes and metabolites involved in organic substance transport. Genes involved in fucose and putrescine metabolism were upregulated, and genes involved in iron transport were repressed. Expression of toxins and colonization factors were not changed, suggesting retained virulence. Metabolomic analyses showed that the transient phase was characterized by a drop of intracellular amino acids, e.g., L-tyrosine, L-tryptophan, L-phenylalanine, L-leucine, and L-glutamic acid, followed by increased levels at induction of stationary phase. A pathway enrichment analysis of the entire transcriptome and metabolome showed activation of pathways involved in the degradation of neurotransmitters aminobutyrate (GABA) and precursors of 5-hydroxytryptamine (serotonin). This work provides a comprehensive framework for further studies on transcriptional and metabolic regulation in pathogenic E. coli. ImportanceWe show that E. coli, exemplified by the pathogenic subspecies enterotoxigenic E. coli (ETEC), undergoes a stepwise transcriptional and metabolic transition into the stationary phase. At a specific entry point, E. coli induces activation and repression of specific pathways. This leads to a rapid decrease of intracellular levels of L-tyrosine, L-tryptophan, L-phenylalanine, L-leucine, and L-glutamic acid due to metabolism into secondary compounds. The resulting metabolic activity leads to an intense but short peak of indole production, suggesting that this is the previously described "indole peak," rapid decrease of intermediate molecules of bacterial neurotransmitters, increased putrescine and fucose uptake, increased glutathione levels, and decreased iron uptake. This specific transient shift in gene expression and metabolomics is short-lived and disappears when bacteria enter the stationary phase. We suggest it mainly prepares bacteria for ceased growth, but the pathways involved suggest that this transient phase substantially influences survival and virulence.

microbiology↗

bioRxiv2021

On the nature of the earliest known life forms

Microfossils from the Paleoarchean Eon are the oldest known evidence of life. Despite their significance in understanding the history of life on Earth, any interpretation of the nature of these microfossils has been a point of contention among researchers. Decades of back-and-forth arguments led to the consensus that reconstructing the lifecycles of Archaean Eon organisms is the most promising way of understanding the nature of these microfossils. Here, we transformed a Gram-positive bacterium into a primitive lipid vesicle-like state and studied it under environmental conditions prevalent on early Earth. Using this approach, we successfully reconstructed morphologies and life cycles of Archaean microfossils. In addition to reproducing microfossil morphologies, we conducted experiments that spanned years to understand the process of cell degradation and how Archaean cells could have undergone encrustation minerals (in this case, salt), leading to their preservation as fossilized organic carbon in the rock record. These degradation products strongly resemble fossiliferous features from Archaean rock formations. Our observations suggest that microfossils aged between 3.8 to 2.5Ga most likely were liposome-like protocells that have evolved physiological pathways of energy conservation but not the mechanisms to regulate their morphology. Based on these observations, we propose that morphology is not a reliable indicator of taxonomy in these microfossils.

evolutionary biology↗

bioRxiv2021

Expression of soluble methane monooxygenase in Escherichia coli enables methane conversion

Natural gas and biogas provide an opportunity to harness methane as an industrial feedstock. Bioconversion is a promising alternative to chemical catalysis, which requires extreme operating conditions and exhibits poor specificities. Though methanotrophs natively utilize methane, efforts have been focused on engineering platform organisms like Escherichia coli for synthetic methanotrophy. Here, a synthetic E. coli methanotroph was developed by engineering functional expression of the Methylococcus capsulatus soluble methane monooxygenase in vivo via expression of its cognate GroESL chaperone. Additional overexpression of E. coli GroESL further improved activity. Incorporation of an acetone formation pathway then enabled the conversion of methane to acetone in vivo, as validated via 13C tracing. This work provides the first reported demonstration of methane bioconversion to liquid chemicals in a synthetic methanotroph.

bioengineering↗

bioRxiv2021

SUITOR: selecting the number of mutational signatures through cross-validation

For de novo mutational signature analysis, the critical first step is to decide how many signatures should be expected in a cancer genomics study. An incorrect number could mislead downstream analyses. Here we present SUITOR (Selecting the nUmber of mutatIonal signaTures thrOugh cRoss-validation), an unsupervised cross-validation method that requires little assumptions and no numerical approximations to select the optimal number of signatures without overfitting the data. In vitro studies and in silico simulations demonstrated that SUITOR can correctly identify signatures, some of which were missed by other widely used methods. Applied to 2,540 whole-genome sequenced tumors across 22 cancer types, SUITOR selected signatures with the smallest prediction errors and almost all signatures of breast cancer selected by SUITOR were validated in an independent breast cancer study. SUITOR is a powerful tool to select the optimal number of mutational signatures, facilitating downstream analyses with etiological or therapeutic importance.

bioinformatics↗

bioRxiv2021

Antipsychotic-induced epigenomic reorganization in frontal cortex samples from individuals with schizophrenia

Genome-wide association studies have revealed >270 loci associated with schizophrenia risk, yet these genetic factors do not seem to be sufficient to fully explain the molecular determinants behind this psychiatric condition. Epigenetic marks such as post-translational histone modifications remain largely plastic during development and adulthood, allowing a dynamic impact of environmental factors, including antipsychotic medications, on access to genes and regulatory elements. However, few studies so far have profiled cell-specific genome-wide histone modifications in postmortem brain samples from schizophrenia subjects, or the effect of antipsychotic treatment on such epigenetic marks. Here we conducted ChIP-seq analyses focusing on histone marks indicative of active enhancers (H3K27ac) and active promoters (H3K4me3), alongside RNA-seq, using frontal cortex samples from antipsychotic-free (AF) and antipsychotic-treated (AT) individuals with schizophrenia, as well as individually matched controls (n = 58). Schizophrenia subjects exhibited thousands of neuronal and non-neuronal epigenetic differences at regions that included several susceptibility genetic loci, such as NRG1, DISC1, and DRD3. By analyzing the AF and AT cohorts separately, we identified schizophrenia-associated alterations in specific transcription factors, their regulatees, and epigenomic and transcriptomic features that were reversed by antipsychotic treatment; as well as those that represented a consequence of antipsychotic medication rather than a hallmark of schizophrenia in postmortem human brain samples. Notably, we also found that the effect of age on epigenomic landscapes was more pronounced in frontal cortex of AT-schizophrenics, as compared to AF-schizophrenics and controls. Together, these data provide important evidence of epigenetic alterations in the frontal cortex of individuals with schizophrenia, and remark for the first time the impact of age and antipsychotic treatment on chromatin organization.

neuroscience↗

bioRxiv2021

Native MOWChIP-seq: Genome-wide profiles of key protein bindings reveal functional differences among various brain regions

Genome-wide profiling of interactions between genome and various functional proteins is critical for understanding regulatory processes involved in development and diseases. Conventional assays require a large number of cells and high-quality data on tissue samples are scarce. Here we optimized a low-input chromatin immunoprecipitation followed by sequencing (ChIP-seq) technology for profiling RNA polymerase II (Pol II), transcription factor (TF), and enzyme binding at the genome scale. The new approach, termed native MOWChIP-seq, produces high-quality binding profiles using 1000-50,000 cells. We used the approach to examine the binding of Pol II and two TFs (EGR1 and MEF2C) in cerebellum and prefrontal cortex of mouse brain and found that their binding profiles are highly reflective of the functional differences between the two brain regions. Our analysis reveals the potential for linking genome-wide TF or Pol II profiles with neuroanatomical origins of brain cells.

genomics↗

bioRxiv2021

Spatial epitope barcoding reveals subclonaltumor patch behaviors

Intratumoral variability is a seminal feature of human tumors contributing to tumor progression and response to treatment. Current technologies are unsuitable to accurately track phenotypes and subclonal evolution within tumors, especially in response to genetic manipulations. Here, we developed epitope combinatorial tags (EpicTags), which we coupled to multiplexed ion beam imaging (EpicMIBI) for in situ tracking of barcodes within tissue microenvironments. Using this platform, we dissected the spatial component of cell lineages and phenotypes in a xenograft model of small-cell lung cancer. We observed emergent properties from mixed clones leading to the preferential expansion of subclonal patches for both neuroendocrine and non-neuroendocrine cancer cell states in this model. In tumors harboring a fraction of PTEN-deficient cancer cells, we uncovered a non-autonomous increase of subclonal patch size in PTEN wildtype cancer cells. EpicMIBI can facilitate in situ interrogation of cell-intrinsic and cell-extrinsic processes involved in intratumoral heterogeneity.

cancer biology↗

bioRxiv2021

Connectome-based model predicts individual psychopathic traits in college students

BackgroundPsychopathic traits have been suggested to increase the risk of violations of socio-moral norms. Previous studies revealed that abnormal neural signatures are associated with elevated psychopathic traits; however, whether the intrinsic network architecture can predict psychopathic traits at the individual level remains unclear. MethodsThe present study utilized connectome-based predictive modeling (CPM) to investigate whether whole-brain resting-state functional connectivity (RSFC) can predict psychopathic traits in the general population. RS functional magnetic resonance imaging data were collected from 84 college students with varying psychopathic traits measured by the Levenson Self-Report Psychopathy Scale (LSRP). ResultsWe found that RSFC of the negative networks predicted individual differences in total LSRP and secondary psychopathy scores but not primary psychopathy score. Particularly, nodes with the most connections in the predictive connectome anchored in the prefrontal cortex (e.g., anterior prefrontal cortex and orbitofrontal cortex) and limbic system (e.g., anterior cingulate cortex and insula). In addition, the connections between the occipital network (OCCN) and cingulo-opercular network (CON) served as a significant predictive connectome for total LSRP and secondary psychopathy score. ConclusionCPM constituted by whole-brain RSFC significantly predicted psychopathic traits individually in the general population. The prefrontal cortex and limbic system at the anatomic level and the CON and OCCN at the functional network level plays a special role in the predictive model--reflecting atypical executive control and affective processing for individuals with elevated psychopathic traits. These findings may provide some implications for early detection and potential intervention of psychopathic tendency.

neuroscience↗