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On the molecular nature of large-pore channels.
No full textMembrane transport is a fundamental means to control basic cellular processes such as apoptosis, inflammation, and neurodegeneration and is mediated by a number of transporters, pumps, and channels. Accumulating evidence over the last half century has shown that a type of so-called "large-pore channel" exists in various tissues and organs in gap-junctional and non-gap-junctional forms in order to flow not only ions but also metabolites such as ATP. They are formed by a number of protein families with little or no evolutionary linkages including connexin, innexin, pannexin, leucine-rich repeat-containing 8 (LRRC8), and calcium homeostasis modulator (CALHM). This review summarizes the history and concept of large-pore channels starting from connexin gap junction channels to the more recent developments in innexin, pannexin, LRRC8, and CALHM. We describe structural and functional features of large-pore channels that are crucial for their diverse functions on the basis of available structures
Characterizing RNA stability genome-wide through combined analysis of PRO-seq and RNA-seq data.
Get PDFBACKGROUND: The concentrations of distinct types of RNA in cells result from a dynamic equilibrium between RNA synthesis and decay. Despite the critical importance of RNA decay rates, current approaches for measuring them are generally labor-intensive, limited in sensitivity, and/or disruptive to normal cellular processes. Here, we introduce a simple method for estimating relative RNA half-lives that is based on two standard and widely available high-throughput assays: Precision Run-On sequencing (PRO-seq) and RNA sequencing (RNA-seq). RESULTS: Our method treats PRO-seq as a measure of transcription rate and RNA-seq as a measure of RNA concentration, and estimates the rate of RNA decay required for a steady-state equilibrium. We show that this approach can be used to assay relative RNA half-lives genome-wide, with good accuracy and sensitivity for both coding and noncoding transcription units. Using a structural equation model (SEM), we test several features of transcription units, nearby DNA sequences, and nearby epigenomic marks for associations with RNA stability after controlling for their effects on transcription. We find that RNA splicing-related features are positively correlated with RNA stability, whereas features related to miRNA binding and DNA methylation are negatively correlated with RNA stability. Furthermore, we find that a measure based on U1 binding and polyadenylation sites distinguishes between unstable noncoding and stable coding transcripts but is not predictive of relative stability within the mRNA or lincRNA classes. We also identify several histone modifications that are associated with RNA stability. CONCLUSION: We introduce an approach for estimating the relative half-lives of individual RNAs. Together, our estimation method and systematic analysis shed light on the pervasive impacts of RNA stability on cellular RNA concentrations
Dissecting cis-regulatory control of quantitative trait variation in a plant stem cell circuit.
No full textCis-regulatory mutations underlie important crop domestication and improvement traits1,2. However, limited allelic diversity has hindered functional dissection of the large number of cis-regulatory elements and their potential interactions, thereby precluding a deeper understanding of how cis-regulatory variation impacts traits quantitatively. Here, we engineered over 60 promoter alleles in two tomato fruit size genes3,4 to characterize cis-regulatory sequences and study their functional relationships. We found that targeted mutations in conserved promoter sequences of SlCLV3, a repressor of stem cell proliferation5,6, have a weak impact on fruit locule number. Pairwise combinations of these mutations mildly enhance this phenotype, revealing additive and synergistic relationships between conserved regions and further suggesting even higher-order cis-regulatory interactions within the SlCLV3 promoter. In contrast, SlWUS, a positive regulator of stem cell proliferation repressed by SlCLV3 (refs. 5,6), is more tolerant to promoter perturbations. Our results show that complex interplay among cis-regulatory variants can shape quantitative variation, and suggest that empirical dissections of this hidden complexity can guide promoter engineering to predictably modify crop traits
Multiple, short protein binding motifs in ORC1 and CDC6 control the initiation of DNA replication.
No full textThe initiation of DNA replication involves cell cycle-dependent assembly and disassembly of protein complexes, including the origin recognition complex (ORC) and CDC6 AAA+ ATPases. We report that multiple short linear protein motifs (SLiMs) within intrinsically disordered regions (IDRs) in ORC1 and CDC6 mediate cyclin-CDK-dependent and independent protein-protein interactions, conditional on the cell cycle phase. A domain within the ORC1 IDR is required for interaction between the ORC1 and CDC6 AAA+ domains in G1, whereas the same domain prevents CDC6-ORC1 interaction during mitosis. Then, during late G1, this domain facilitates ORC1 destruction by a SKP2-cyclin A-CDK2-dependent mechanism. During G1, the CDC6 Cy motif cooperates with cyclin E-CDK2 to promote ORC1-CDC6 interactions. The CDC6 IDR regulates self-interaction by ORC1, thereby controlling ORC1 protein levels. Protein phosphatase 1 binds directly to a SLiM in the ORC1 IDR, causing ORC1 de-phosphorylation upon mitotic exit, increasing ORC1 protein, and promoting pre-RC assembly
Effective production of oligomeric membrane proteins by EarlyBac-insect cell system
No full textDespite major advances in methodologies for membrane protein production over the last two decades, there remain challenging protein complexes that are technically difficult to yield by conventional recombinant expression methods. A large number of these proteins are multimeric membrane proteins from eukaryotic species, which are required to pass through stringent quality control mechanisms of host cells for proper folding and complex assembly. Here, we describe the development procedure to improve the production efficiency of multi-oligomeric membrane protein complexes in insect cells and recombinant baculovirus, which involves screening of promoters, enhancers, and untranslated regions for expression levels, using calcium homeostasis modulator (CALHM) and N-methyl-D-aspartate receptor (NMDAR) proteins as examples. We demonstrate that our insect cell expression strategy is effective in expression of both multi-homomeric CALHM proteins and multi-heteromeric NMDARs
Neural Networks With Motivation.
Get PDFAnimals rely on internal motivational states to make decisions. The role of motivational salience in decision making is in early stages of mathematical understanding. Here, we propose a reinforcement learning framework that relies on neural networks to learn optimal ongoing behavior for dynamically changing motivation values. First, we show that neural networks implementing Q-learning with motivational salience can navigate in environment with dynamic rewards without adjustments in synaptic strengths when the needs of an agent shift. In this setting, our networks may display elements of addictive behaviors. Second, we use a similar framework in hierarchical manager-agent system to implement a reinforcement learning algorithm with motivation that both infers motivational states and behaves. Finally, we show that, when trained in the Pavlovian conditioning setting, the responses of the neurons in our model resemble previously published neuronal recordings in the ventral pallidum, a basal ganglia structure involved in motivated behaviors. We conclude that motivation allows Q-learning networks to quickly adapt their behavior to conditions when expected reward is modulated by agent's dynamic needs. Our approach addresses the algorithmic rationale of motivation and makes a step toward better interpretability of behavioral data via inference of motivational dynamics in the brain
Noise regularization removes correlation artifacts in single-cell RNA-seq data preprocessing
Get PDFIn this study, we benchmarked five representative single-cell RNA-sequencing data-preprocessing methods with a focus on their influence in inferring gene-gene expression correlations. We found that substantial correlation artifacts have been introduced during the preprocessing steps due to data oversmoothing, raising the issue that correlation computed from these preprocessed data may not be reliable and should be treated with caution. We then proposed a noise-regularization method to penalize the oversmoothed data, which can effectively eliminate the artifacts while retaining the majority of the true correlations. The regularized correlations can be further applied to construct gene-gene correlation networks, which is helpful for obtaining mechanistic insights into the complex biological systems
Genomic diversity of SARS-CoV-2 during early introduction into the Baltimore-Washington metropolitan area.
Get PDFThe early COVID-19 pandemic was characterized by rapid global spread. In Maryland and Washington, DC, United States, more than 2500 cases were reported within 3 weeks of the first COVID-19 detection in March 2020. We aimed to use genomic sequencing to understand the initial spread of SARS-CoV-2 - the virus that causes COVID-19 - in the region. We analyzed 620 samples collected from the Johns Hopkins Health System during March 11-31, 2020, comprising 28.6% of the total cases in Maryland and Washington, DC. From these samples, we generated 114 complete viral genomes. Analysis of these genomes alongside a subsampling of over 1000 previously published sequences showed that the diversity in this region rivaled global SARS-CoV-2 genetic diversity at that time and that the sequences belong to all of the major globally circulating lineages, suggesting multiple introductions into the region. We also analyzed these regional SARS-CoV-2 genomes alongside detailed clinical metadata and found that clinically severe cases had viral genomes belonging to all major viral lineages. We conclude that efforts to control local spread of the virus were likely confounded by the number of introductions into the region early in the epidemic and the interconnectedness of the region as a whole
SNPC-1.3 is a sex-specific transcription factor that drives male piRNA expression in C. elegans.
Get PDFPiwi-interacting RNAs (piRNAs) play essential roles in silencing repetitive elements to promote fertility in metazoans. Studies in worms, flies, and mammals reveal that piRNAs are expressed in a sex-specific manner. However, the mechanisms underlying this sex-specific regulation are unknown. Here we identify SNPC-1.3, a male germline-enriched variant of a conserved subunit of the small nuclear RNA-activating protein complex, as a male-specific piRNA transcription factor in Caenorhabditis elegans. SNPC-1.3 colocalizes with the core piRNA transcription factor, SNPC-4, in nuclear foci of the male germline. Binding of SNPC-1.3 at male piRNA loci drives spermatogenic piRNA transcription and requires SNPC-4. Loss of snpc-1.3 leads to depletion of male piRNAs and defects in male-dependent fertility. Furthermore, TRA-1, a master regulator of sex determination, binds to the snpc-1.3 promoter and represses its expression during oogenesis. Loss of TRA-1 targeting causes ectopic expression of snpc-1.3 and male piRNAs during oogenesis. Thus, sexually dimorphic regulation of snpc-1.3 expression coordinates male and female piRNA expression during germline development
Integrating barcoded neuroanatomy with spatial transcriptional profiling enables identification of gene correlates of projections.
No full textFunctional circuits consist of neurons with diverse axonal projections and gene expression. Understanding the molecular signature of projections requires high-throughput interrogation of both gene expression and projections to multiple targets in the same cells at cellular resolution, which is difficult to achieve using current technology. Here, we introduce BARseq2, a technique that simultaneously maps projections and detects multiplexed gene expression by in situ sequencing. We determined the expression of cadherins and cell-type markers in 29,933 cells and the projections of 3,164 cells in both the mouse motor cortex and auditory cortex. Associating gene expression and projections in 1,349 neurons revealed shared cadherin signatures of homologous projections across the two cortical areas. These cadherins were enriched across multiple branches of the transcriptomic taxonomy. By correlating multigene expression and projections to many targets in single neurons with high throughput, BARseq2 provides a potential path to uncovering the molecular logic underlying neuronal circuits