Biology subjects

Luo, C.

Publications and source records attributed to Luo, C..

11 recordsLinked to original sources

bioRxiv2018

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↗

bioRxiv2018

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↗

bioRxiv2018

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↗

bioRxiv2018

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↗

bioRxiv2018

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↗

bioRxiv2018

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↗

bioRxiv2017

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↗

bioRxiv2017

Transcriptome analysis of the quantitative distribution of the Cyrtotrachelus buqueti population in two cities in China

Background: Cyrtotrachelus buqueti is a forest pest that severely damages bamboo shoots. Reducing the population of this insect involves complex mechanisms and is dependent on diverse gene expression influenced by environmental factors.\n\nMethods: In this study, samples from two regions of China, Muchuan in Sichuan Province and Chishui in Guizhou Province, were investigated through RNA-seq to explore the causes and molecular mechanisms underlying the population reduction of this species. Environmental factors, such as temperature, heavy metal content, and pH, may affect the reduced population of C. buqueti in Chishui.\n\nResults: Approximately 44 million high-quality reads were generated, and 94.2% of the data were mapped to the transcriptome. A total of 15,641 out of the 29,406 identified genes were predicted. Moreover, 348 genes were differentially expressed between the two groups of imagoes and included 77 upregulated and 271 downregulated UniGenes. The functional analysis showed that these genes were significantly enriched in ribosome and metabolic pathway categories. The candidate genes, which contributed to C. Buqueti reduction, included 41 genes involved in the ribosome constitution category, five genes in the one-carbon pool pathway by folate category, and five heat shock protein genes.\n\nConclusions: Downregulation of these candidate genes seems to have impaired metabolic processes, such as protein, DNA, RNA, and purine synthesis, as well as carbon and folate metabolism, and finally resulted in the observed reduced population of C. buqueti. Furthermore, temperature, heavy metal content, and pH might influence the population by altering the expressions of genes involved in these metabolic processes.

genomics↗

bioRxiv2017

Attention is required for knowledge-based sequential grouping of syllables into words

How the brain sequentially groups sensory events into temporal chunks and how this process is modulated by attention are fundamental questions in cognitive neuroscience. Sequential grouping includes bottom-up primitive grouping and top-down knowledge-based grouping. In speech perception, grouping acoustic features into syllables can rely on bottom-up acoustic continuity cues but grouping syllables into words critically relies on the listeners lexical knowledge. This study investigates whether top-down attention is required to apply lexical knowledge to group syllables into words, by concurrently monitoring neural entrainment to syllables and words using electroencephalography (EEG). When attention is directed to a competing speech stream or cross-modally to a silent movie, neural entrainment to syllables is weakened but neural entrainment to words largely diminishes. These results strongly suggest that knowledge-based grouping of syllables into words requires top-down attention and is a bottleneck for the neural processing of unattended speech.

neuroscience↗

bioRxiv2017

Worldwide Population Structure Of Escherichia coli Reveals Two Major Subspecies

Recombination is one of the most important mechanisms of prokaryotic species evolution but its exact roles are still in debate. Here we try to infer genome-wide recombination events within a species uti-lizing a dataset of 104 complete genomes of Escherichia coli from diverse origins, among which 45 from world-wide animal-hosts are in-house sequenced using SMRT (single-molecular real time) technology.Two major clades are identified based on evidences of ecological and physiological characteristics, as well as distinct genomic features implying scarce inter-clade genetic exchange. By comparing the synteny of identical fragments genome-widely searched for each genome pair, we achieve a fine-scale map of re-combination within the population. The recombination is rather extensive within clade, which is able to break linkages between genes but does not interrupt core genome framework and primary metabolic port-folios possibly due to natural selection for physiological compatibility and ecological fitness. Meanwhile,the recombination between clades declines drastically as the phylogenetic distance increases, generally 10-fold reduced than those of the intra-clade, which establishes genetic barrier between clades. These empirical data of recombination suggest its critical role in the early stage of speciation, where recombina-tion rate differs according to phylogentic distance. The extensive intra-clade recombination coheres sister strains into a quasi-sexual group and optimizes genes or alleles to streamline physiological activities,whereas shapely declined inter-clade recombination split the population into clades adaptive to divergent ecological niches.\n\nSignificance StatementRoles of recombination in species evolution have been debated for decades due to difficulties in inferring recombination events during the early stage of speciation, especially when recombination is always complicated by frequent gene transfer events of bacterial genomes. Based on 104 high-quality complete E. coli genomes, we infer gene-centric dynamics of recombination in the formation of two E. coli clades or subpopulations, and recombination is found to be rather intensive in a within-clade fashion, which forces them to be quasi-sexual. The recombination events can be mapped among individual genomes in the context of genes and their variations; decreased between-clade and increased intra-claderecombination engender a genetic barrier that further encourages clade-specific secondary metabolic portfolios for better environmental adaptation. Recombination is thus a major force that accelerates bacterial evolution to fit ecological diversity.

microbiology↗

bioRxiv2017

Multiple introductions of Zika virus into the United States revealed through genomic epidemiology

Zika virus (ZIKV) is causing an unprecedented epidemic linked to severe congenital syndromes1,2. In July 2016, mosquito-borne ZIKV transmission was first reported in the continental United States and since then, hundreds of locally-acquired infections have been reported in Florida3. To gain insights into the timing, source, and likely route(s) of introduction of ZIKV into the continental United States, we tracked the virus from its first detection in Miami, Florida by direct sequencing of ZIKV genomes from infected patients and Aedes aegypti mosquitoes. We show that at least four distinct ZIKV introductions contributed to the outbreak in Florida and that local transmission likely started in the spring of 2016 - several months before its initial detection. By analyzing surveillance and genetic data, we discovered that ZIKV moved among transmission zones in Miami. Our analyses show that most introductions are phylogenetically linked to the Caribbean, a finding corroborated by the high incidence rates and traffic volumes from the region into the Miami area. By comparing mosquito abundance and travel flows, we describe the areas of southern Florida that are especially vulnerable to ZIKV introductions. Our study provides a deeper understanding of how ZIKV initiates and sustains transmission in new regions.

epidemiology↗