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Luo, C.

Publications and source records attributed to Luo, C..

At least 127 records · Page 7Linked to original sources

Learning from local to global - an efficient distributed algorithm for modeling time-to-event data

ObjectivesWe developed and evaluated a privacy-preserving One-shot Distributed Algorithm to fit a multi-center Cox proportional hazard model (ODAC) without sharing patient-level information across sites. MethodsUsing patient-level data from a single site combined with only aggregated information from other sites, we constructed a surrogate likelihood function, approximating the Cox partial likelihood function obtained using patient-level data from all sites. By maximizing the surrogate likelihood function, each site obtained a local estimate of the model parameter, and the ODAC estimator was constructed as a weighted average of all the local estimates. We evaluated the performance of ODAC with (1) a simulation study, and (2) a real-world use case study using four datasets from the Observational Health Data Sciences and Informatics (OHDSI) network. ResultsOur simulation study showed that ODAC provided estimates nearly the same as the estimator obtained by analyzing, in a single dataset, the combined patient-level data from all sites (i.e., the pooled estimator). The relative bias was less than 0.1% across all scenarios. The accuracy of ODAC remained high across different sample sizes and event rates. On the other hand, the metaanalysis estimator, which was obtained by the inverse variance weighted average of the sitespecific estimates, had substantial bias when the event rate is less than 5%, with the relative bias reaching 20% when the event rate is 1%. In the OHDSI network application, the ODAC estimates have a relative bias less than 5% for 15 out of 16 log hazard ratios; while the meta-analysis estimates had substantially higher bias than ODAC. ConclusionsODAC is a privacy-preserving and non-iterative method for implementing time-to-event analyses across multiple sites. It provides estimates on par with the pooled estimator and substantially outperforms the meta-analysis estimator when the event is uncommon, making it extremely suitable for studying rare events and diseases in a distributed manner.

bioinformatics↗

An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types

Single cell transcriptomics has transformed the characterization of brain cell identity by providing quantitative molecular signatures for large, unbiased samples of brain cell populations. With the proliferation of taxonomies based on individual datasets, a major challenge is to integrate and validate results toward defining biologically meaningful cell types. We used a battery of single-cell transcriptome and epigenome measurements generated by the BRAIN Initiative Cell Census Network (BICCN) to comprehensively assess the molecular signatures of cell types in the mouse primary motor cortex (MOp). We further developed computational and statistical methods to integrate these multimodal data and quantitatively validate the reproducibility of the cell types. The reference atlas, based on more than 600,000 high quality single-cell or -nucleus samples assayed by six molecular modalities, is a comprehensive molecular account of the diverse neuronal and non-neuronal cell types in MOp. Collectively, our study indicates that the mouse primary motor cortex contains over 55 neuronal cell types that are highly replicable across analysis methods, sequencing technologies, and modalities. We find many concordant multimodal markers for each cell type, as well as thousands of genes and gene regulatory elements with discrepant transcriptomic and epigenomic signatures. These data highlight the complex molecular regulation of brain cell types and will directly enable design of reagents to target specific MOp cell types for functional analysis.

neuroscience↗

SARS-CoV-2 and SARS-CoV Spike-RBD Structure and Receptor Binding Comparison and Potential Implications on Neutralizing Antibody and Vaccine Development

SARS-CoV-2 and SARS-CoV share a common human receptor ACE2. Protein-protein interaction structure modeling indicates that spike-RBD of the two viruses also has similar overall binding conformation and binding free energy to ACE2. In vitro assays using recombinant ACE2 proteins and ACE2 expressing cells confirmed the two coronaviruses similar binding affinities to ACE2. The above studies provide experimental supporting evidences and possible explanation for the high transmissibility observed in the SARS-CoV-2 outbreak. Potent ACE2-blocking SARS-CoV neutralizing antibodies showed limited cross-binding and neutralizing activities to SARS-CoV-2. ACE2-non-blocking SARS-CoV RBD antibodies, though with weaker neutralizing activities against SARS-CoV, showed positive cross-neutralizing activities to SARS-CoV-2 with an unknown mechanism. These findings suggest a trade-off between the efficacy and spectrum for therapeutic antibodies to different coronaviruses, and hence highlight the possibilities and challenges in developing broadly protecting antibodies and vaccines against SARS-CoV-2 and its future mutants.

microbiology↗

Polycomb-mediated repression compensates for loss of postnatal DNA methylation in excitatory neurons

Two epigenetic pathways of repression, DNA methylation and Polycomb repressive complex 2 (PRC2) mediated gene silencing, regulate neuron development and function, but their respective contributions are unknown. We found that conditional loss of the de novo DNA methyltransferase Dnmt3a in mouse excitatory neurons altered expression of synapse-related genes, stunted synapse maturation, and impaired working memory and social interest. Loss of Dnmt3a abolished postnatal accumulation of CG and non-CG DNA methylation, leaving neurons with an unmethylated, fetal-like epigenomic pattern at -140,000 genomic regions. The PRC2-associated histone modification H3K27me3 increased at many of these sites, partially compensating for the loss of DNA methylation. Our data support a dynamic interaction between two fundamental modes of epigenetic repression during postnatal maturation of excitatory neurons, which together confer robustness on neuronal regulation.

neuroscience↗

Single nucleus multi-omics links human cortical cell regulatory genome diversity to disease risk variants

Single-cell technologies enable measure of unique cellular signatures, but are typically limited to a single modality. Computational approaches allow integration of diverse single-cell datasets, but their efficacy is difficult to validate in the absence of authentic multi-omic measurements. To comprehensively assess the molecular phenotypes of single cells in tissues, we devised single-nucleus methylCytosine, Chromatin accessibility and Transcriptome sequencing (snmC2T-seq) and applied it to post-mortem human frontal cortex tissue. We developed a computational framework to validate fine-grained cell types using multi-modal information and assessed the effectiveness of computational integration methods. Correlation analysis in individual cells revealed distinct relations between methylation and gene expression. Our integrative approach enabled joint analyses of the methylome, transcriptome, chromatin accessibility and conformation for 63 human cortical cell types. We reconstructed regulatory lineages for cortical cell populations and found specific enrichment of genetic risk for neuropsychiatric traits, enabling prediction of cell types with causal roles in disease.

genomics↗

Abnormal nitration and S-sulfhydration of Sp1-CSE-H2S pathway contribute to the progress of HHcy

Sp1 (Specificity protein 1)-CSE (cystathionine-{gamma}-lyase)-H2S (hydrogen sulfide) pathway plays an important role in homocysteine-metabolism, whose disorder can result in hyperhomocysteinemia. The deficiency of plasma H2S in patients and animal models with hyperhomocysteinemia has been reported but it is unclear whether this deficiency plays a role in the progress of hyperhomocysteinemia. Furthermore, it remains unknown whether the post-translational modification of Sp1 or CSE mediated by hyperhomocysteinemia itself can in turn affect the development of hyperhomocysteinemia. By both in vivo and in vitro studies, we conducted immunoprecipitation and maleimide assays to detect the post-translational modification of Sp1-CSE-H2S pathway and revealed four major findings: (1) the accumulation of homocysteine augmented the nitration of CSE, thus blunted its bio-activity and caused H2S deficiency. (2) H2S deficiency lowered the S-sulfhydration of Sp1 and inhibited its transcriptional activity, resulted in lower expression of CSE. CSE deficiency decreased the H2S level further, which in turn lowered the S-sulfhydration level of CSE. (3) CSE was S-sulfhydrated at Cys84, Cys109, Cys172, Cys229, Cys252, Cys307 and Cys310 under physiological conditions, mutation of Cys84, Cys109, Cys229, Cys252 and Cys307 decreased its S-sulfhydration level and bio-activity. (4) H2S deficiency could trap hyperhomocysteinemia into a progressive vicious circle and trigger a rapid increase of homocysteine, while blocking nitration or restoring S-sulfhydration could break this circle. In conclusion, this study reveals a novel mechanism involved in the disorder of homocysteine-metabolism, which may provide a candidate therapeutic strategy for hyperhomocysteinemia.

pathology↗

Iterative Subtractive Binning of Freshwater Chronoseries Metagenomes Identifies over Four Hundred Novel Species and their Ecologic Preferences

Recent advances in sequencing technology and accompanying bioinformatic pipelines have allowed unprecedented access to the genomes of yet-uncultivated microorganisms from a wide array of natural and engineered environments. However, the catalogue of available genomes from uncultivated freshwater microbial populations remains limited, and most genome recovery attempts in freshwater ecosystems have only targeted few specific taxa. Here, we present a novel genome recovery pipeline, which incorporates iterative subtractive binning and apply it to a time series of metagenomic datasets from seven connected locations along the Chattahoochee River (Southeastern USA). Our set of Metagenome-Assembled Genomes (MAGs) represents over four hundred genomospecies yet to be named, which substantially increase the number of high-quality MAGs from freshwater lakes and represent about half of the total microbial community sampled. We propose names for two novel species that were represented by high-quality MAGs: \"Candidatus Elulimicrobium humile\" (\"Ca. Elulimicrobiota\" in the \"Patescibacteria\" group) and \"Candidatus Aquidulcis frankliniae\" (\"Chloroflexi\"). To evaluate the prevalence of these species in the chronoseries, we introduce novel approaches to estimate relative abundance and a habitat-preference score that control for uneven quality of the genomes and sample representation. Using these metrics, we demonstrate a high degree of habitat-specialization and endemicity for most genomospecies observed in the Chattahoochee lacustrine ecosystem, as well as wider species ecological ranges associated with smaller genomes and higher coding densities, indicating an overall advantage of smaller, more compact genomes for cosmopolitan distributions.

genomics↗

Loss of Dnmt3a dependent methylation in inhibitory neurons impairs neural function through a mechanism that impacts Rett syndrome

Methylated cytosine is an effector of epigenetic gene regulation. In the mammalian brain, the DNA methyltransferase, Dnmt3a, is the sole \"writer\" of atypical non-CpG methylation (mCH), and methyl CpG binding protein 2 (MeCP2) is the only known \"reader\" for mCH. We set out to determine if MeCP2 is the sole reader for Dnmt3a dependent methylation by comparing mice lacking either Dnmt3a or MeCP2 in GABAergic inhibitory neurons. Loss of either the writer or the reader causes overlapping and distinct features from the behavioral to the molecular level. Loss of Dnmt3a results in global loss of mCH and a small subset of mCG sites resulting in more widespread transcriptional alterations and severe neurological dysfunction than seen upon MeCP2 loss. These data indicate that MeCP2 is responsible for reading part of the Dnmt3a dependent methylation in the brain. Importantly, the impact of MeCP2 on genes differentially expressed in both cKO models shows a strong dependence on mCH, but not Dnmt3a dependent mCG, consistent with mCH playing a central role in the pathogenesis of Rett Syndrome.

neuroscience↗

Objects seen as scenes: neural circuitry for attending whole or parts

Depending on our goals, we pay attention to the global shape of an object or to the local shape of its parts, since its difficult to do both at once. This typically effortless process can be impaired in disease. However, it is not clear which cortical regions carry the information needed to constrain shape processing to a chosen global/local level. Here, novel stimuli were used to dissociate functional MRI responses to global and local shapes. This allowed identification of cortical regions containing information about level (independent from shape). Crucially, these regions overlapped part of the cortical network implicated in scene processing. As expected, shape information (independent of level) was mainly located in category-selective areas specialized for object- and face-processing. Regions with the same informational profile were strongly linked (as measured by functional connectivity), but were weak when the profiles diverged. Specifically, in the ventral-temporal-cortex (VTC) regions favoring level and shape were consistently separated by the mid-fusiform sulcus (MFS). These regions also had limited crosstalk despite their spatial proximity, thus defining two functional pathways within VTC. We hypothesize that object hierarchical level is processed by neural circuitry that also analyses spatial layout in scenes, contributing to the control of the spatial-scale used for shape recognition. Use of level information tolerant to shape changes could guide whole/part attentional selection but facilitate illusory shape/level conjunctions under impoverished vision. Significance statementOne daily engages hierarchically organized objects (e.g. face-eyes-eyelashes). Their perception is commonly studied with global shapes composed by of local shapes. Seeing shape at one level is easy, but difficult for both at once. How can the brain guide attention to one level? Here using novel stimuli that dissociate different levels over time and examining local patterns of brain-activity, we found that the level and shape of visual objects were represented into segregated sets of cortical regions, each connected into their own pathway. Level information was found in part of the cortical network known to process scenes. Coding of object-level independently from shape could participate in guiding sustained attention within objects, eliminating interference from irrelevant levels. It could also help produce "illusory conjunctions" (perceptual migration of a shape to the wrong level) when attention is limited. HighlightsO_LIModified Navon figures allow dissociation in time of fMRI responses for the global/local levels. C_LIO_LIShape-invariant hierarchical level information was found in scenes selective areas, whereas level-invariant shape information was found in object- and faces- selective areas. C_LIO_LILevel and shape regions were divided by the mid-fusiform sulcus (MFS) in VTC cortex, and each type of region connected into its own pathway. C_LIO_LIHaving separate level/shape pathways could facilitate selective-attention, but foster illusory conjunctions. C_LI

neuroscience↗

Development of rice conidiation media for Ustilaginoidea virens

Rice false smut, caused by the ascomycete Ustilaginoidea virens, is a serious disease of rice worldwide. Conidia are very important infectious propagules of U. virens, but the ability of pathogenic isolates to produce conidia frequently decreases in culture, which influences pathogenicity testing. Here, we developed tissue media with rice leaves or panicles that stimulate conidiation of U. virens. Generally, rice leaf media more effectively increased conidiation than panicle media, and certain non-filtered tissue media were better than their filtered counterparts. Among the tested media, the Indica rice leaf medium with 0.06 g/ml of Wanxian 98 leaf was most efficient for inducing conidiation, and it was also usable for conidiation-defective isolates. Although the conidia induced in rice tissue media were smaller, they were able to germinate on potato sucrose agar medium and infect rice normally. This method provides a foundation for the production of conidia in U. virens that will be widely applied in the pathogenicity testing as well as in genetic analyses for false smut resistance in rice cultivars.

microbiology↗

Single-cell multi-omic profiling of chromatin conformation and DNA methylome

Recent advances in the development of single cell epigenomic assays have facilitated the analysis of gene regulatory landscapes in complex biological systems. Methods for detection of single-cell epigenomic variation such as DNA methylation sequencing and ATAC-seq hold tremendous promise for delineating distinct cell types and identifying their critical cis-regulatory sequences. Emerging evidence has shown that in addition to cis-regulatory sequences, dynamic regulation of 3D chromatin conformation is a critical mechanism for the modulation of gene expression during development and disease. It remains unclear whether single-cell Chromatin Conformation Capture (3C) or Hi-C profiles are suitable for cell type identification and allow the reconstruction of cell-type specific chromatin conformation maps. To address these challenges, we have developed a multi-omic method single-nucleus methyl-3C sequencing (sn-m3C-seq) to profile chromatin conformation and DNA methylation from the same cell. We have shown that bulk m3C-seq and sn-m3C-seq accurately capture chromatin organization information and robustly separate mouse cell types. We have developed a fluorescent-activated nuclei sorting strategy based on DNA content that eliminates nuclei multiplets caused by crosslinking. The sn-m3C-seq method allows high-resolution cell-type classification using two orthogonal types of epigenomic information and the reconstruction of cell-type specific chromatin conformation maps.

genomics↗

The Dynamic Conformational Landscapes of the Protein Methyltransferase SETD8

Elucidating conformational heterogeneity of proteins is essential for understanding protein functions and developing exogenous ligands for chemical perturbation. While structural biology methods can provide atomic details of static protein structures, these approaches cannot in general resolve less populated, functionally relevant conformations and uncover conformational kinetics. Here we demonstrate a new paradigm for illuminating dynamic conformational landscapes of target proteins. SETD8 (Pr-SET7/SET8/KMT5A) is a biologically relevant protein lysine methyltransferase for in vivo monomethylation of histone H4 lysine 20 and nonhistone targets. Utilizing covalent chemical inhibitors and depleting native ligands to trap hidden high-energy conformational states, we obtained diverse novel X-ray structures of SETD8. These structures were used to seed massively distributed molecular simulations that generated six milliseconds of trajectory data of SETD8 in the presence or absence of its cofactor. We used an automated machine learning approach to reveal slow conformational motions and thus distinct conformational states of SETD8, and validated the resulting dynamic conformational landscapes with multiple biophysical methods. The resulting models provide unprecedented mechanistic insight into how protein dynamics plays a role in SAM binding and thus catalysis, and how this function can be modulated by diverse cancer-associated mutants. These findings set up the foundation for revealing enzymatic mechanisms and developing inhibitors in the context of conformational landscapes of target proteins.

biophysics↗

Multi-omic profiling of transcriptome and DNA methylome in single nuclei with molecular partitioning

Single-cell transcriptomic and epigenomic analyses provide powerful strategies for unbiased determination of cell types in mammalian tissues. Although previous studies have identified cell types using individual molecular signatures, the generation of consensus cell type classification requires the integration of multiple data types. Most existing single-cell techniques can only make one type of molecular measurement. Here we describe single-nucleus methylcytosine and transcriptome sequencing (snmCT-seq), a multi-omic method that requires no physical separation of DNA and RNA molecules. We demonstrated that snmCT-seq profiles generated from single cells or nuclei robustly distinguish human cell types and accurately measures cytosine DNA methylation and gene expression signatures of each cell type.

genomics↗

Auditory and Language Contributions to Neural Encoding of Speech Features in Noisy Environments

Recognizing speech in noisy environments is a challenging task that involves both auditory and language mechanisms. Previous studies have demonstrated noise-robust neural tracking of the speech envelope, i.e., fluctuations in sound intensity, in human auditory cortex, which provides a plausible neural basis for noise-robust speech recognition. The current study aims at teasing apart auditory and language contributions to noise-robust envelope tracking by comparing 2 groups of listeners, i.e., native listeners of the testing language and foreign listeners who do not understand the testing language. In the experiment, speech is mixed with spectrally matched stationary noise at 4 intensity levels and the neural responses are recorded using electroencephalography (EEG). When the noise intensity increases, an increase in neural response gain is observed for both groups of listeners, demonstrating auditory gain control mechanisms. Language comprehension creates no overall boost in the response gain or the envelope-tracking precision but instead modulates the spatial and temporal profiles of envelope-tracking activity. Based on the spatio-temporal dynamics of envelope-tracking activity, the 2 groups of listeners and the 4 levels of noise intensity can be jointly decoded by a linear classifier. All together, the results show that without feedback from language processing, auditory mechanisms such as gain control can lead to a noise-robust speech representation. High-level language processing, however, further modulates the spatial-temporal profiles of the neural representation of the speech envelope.

neuroscience↗

Global DNA methylation remodeling during direct reprogramming of fibroblasts to neurons

Direct reprogramming of fibroblasts to neurons induces widespread cellular and transcriptional reconfiguration. In this study, we characterized global epigenomic changes during direct reprogramming using whole-genome base-resolution DNA methylome (mC) sequencing. We found that the pioneer transcription factor Ascl1 alone is sufficient for inducing the uniquely neuronal feature of non-CG methylation (mCH), but co-expression of Brn2 and Mytl1 was required to establish a global mCH pattern reminiscent of mature cortical neurons. Ascl1 alone induced strong promoter CG methylation (mCG) of fibroblast specific genes, while BAM overexpression additionally targets a competing myogenic program and directs a more faithful conversion to neuronal cells. Ascl1 induces local demethylation at its binding sites. Surprisingly, co-expression with Brn2 and Mytl1 inhibited the ability of Ascl1 to induce demethylation, suggesting a contextual regulation of transcription factor - epigenome interaction. Finally, we found that de novo methylation by DNMT3A is required for efficient neuronal reprogramming.

neuroscience↗

Robust single-cell DNA methylome profiling with snmC-seq2

Single-cell DNA methylome profiling has enabled the study of epigenomic heterogeneity in complex tissues and during cellular reprogramming. However, broader applications of the method have been impeded by the modest quality of sequencing libraries. Here we report snmC-seq2, which provides improved read mapping, reduced artifactual reads, enhanced throughput, as well as increased library complexity and coverage uniformity compared to snmC-seq. snmC-seq2 is an efficient strategy suited for large scale single-cell epigenomic studies.

genomics↗

Improved sgRNA design in bacteria via genome-wide activity profiling

CRISPR/Cas9 is a promising tool in prokaryotic genome engineering, but its success is limited by the widely varying on-target activity of single guide RNAs (sgRNAs). Based on the association of CRISPR/Cas9-induced DNA cleavage with cellular lethality, we systematically profiled sgRNA activity by co-expressing a genome-scale library (~70,000 sgRNAs) with Cas9 or its specificity-improved mutant in E. coli. Based on this large-scale dataset, we constructed a comprehensive and high-density sgRNA activity map, which enables selecting highly active sgRNAs for any locus across the genome in this model organism. We also identified resistant genomic loci with respect to CRISPR/Cas9 activity, notwithstanding the highly accessible DNA in bacterial cells. Moreover, we found that previous sgRNA activity prediction models that were trained on mammalian cell datasets were inadequate when coping with our results, highlighting the key limitations and biases of previous models. We hence developed an integrated algorithm to accurately predict highly effective sgRNAs, aiming to facilitate the design of CRISPR/Cas9-based genome engineering or screenings in bacteria. We also isolated the important sgRNA features that contribute to DNA cleavage and characterized their key differences among wild type Cas9 and its mutant, shedding light on the biophysical mechanisms of the CRISPR/Cas9 system.

microbiology↗

Spatiotemporal DNA Methylome Dynamics of the Developing Mammalian Fetus

Genetic studies have revealed an essential role for cytosine DNA methylation in mammalian development. However, its spatiotemporal distribution in the developing embryo remains obscure. Here, we profiled the methylome landscapes of 12 mouse tissues/organs at 8 developmental stages spanning from early embryogenesis to birth. Indepth analysis of these spatiotemporal epigenome maps systematically delineated ~2 million methylation variant regions and uncovered widespread methylation dynamics at nearly one-half million tissue-specific enhancers, whose human counterparts were enriched for variants involved in genetic diseases. Strikingly, these predicted regulatory elements predominantly lose CG methylation during fetal development, whereas the trend is reversed after birth. Accumulation of non-CG methylation within gene bodies of key developmental transcription factors coincided with their transcriptional repression during later stages of fetal development. These spatiotemporal epigenomic maps provide a valuable resource for studying gene regulation during mammalian tissue/organ progression and for pinpointing regulatory elements involved in human developmental diseases.

genomics↗