Biology subjects

Wu, C.

Publications and source records attributed to Wu, C..

At least 271 records · Page 15Linked to original sources

bioRxiv2021

Neural Basis for Regulation of Vasopressin Secretion by Anticipated Disturbances in Osmolality

Water balance, tracked by extracellular osmolality, is regulated by feedback and feedforward mechanisms. Feedback regulation is reactive, occurring as deviations in osmolality are detected. Feedforward or presystemic regulation is proactive, occurring when disturbances in osmolality are anticipated. Vasopressin (AVP) is a key hormone regulating water balance and is released during hyperosmolality to limit renal water excretion. AVP neurons are under feedback and feedforward regulation. Not only do they respond to disturbances in blood osmolality, but they are also rapidly suppressed and stimulated, respectively, by drinking and eating, which will ultimately decrease and increase osmolality. Here, we demonstrate that AVP neuron activity is regulated by multiple anatomically-and functionally-distinct neural circuits. Notably, presystemic regulation during drinking and eating are mediated by non-overlapping circuits that involve the lamina terminalis and hypothalamic arcuate nucleus, respectively. These findings reveal neural mechanisms that support differential regulation of AVP release by diverse behavioral and physiological stimuli.

physiology↗

bioRxiv2021

The Predicted Metabolic Function of the Gut Microbiota of Drosophila melanogaster

An important goal for many nutrition-based microbiome studies is to identify the metabolic function of microbes in complex microbial communities and its impact on host physiology. This research can be confounded by poorly-understood effects of community composition and host diet on the metabolic traits of individual taxa. Here, we investigated these multi-way interactions by constructing and analyzing metabolic models comprising every combination of five bacterial members of the Drosophila gut microbiome (from single taxa to the five-member community of Acetobacter and Lactobacillus species) under three nutrient regimes. We show that the metabolic function of Drosophila gut bacteria is dynamic, influenced by community composition and responsive to dietary modulation. Furthermore, we show that ecological interactions such as competition and mutualism identified from the growth patterns of gut bacteria are underlain by a diversity of metabolic interactions, and show that the bacteria tend to compete for amino acids and B vitamins more frequently than for carbon sources. Our results reveal that in addition to fermentation products such as acetate, intermediates of the tricarboxylic acid (TCA) cycle including 2-oxoglutarate and succinate are produced at high flux and cross-fed between bacterial taxa suggesting important roles for TCA cycle intermediates in modulating Drosophila gut microbe interactions and the potential to influence host traits. These metabolic models provide specific predictions of the patterns of ecological and metabolic interactions among gut bacteria under different nutrient regimes, with potentially important consequences for overall community metabolic function and nutritional interactions with the host. IMPORTANCEDrosophila is an important model for microbiome research partly because of the low complexity of its mostly culturable gut microbiota. Our current understanding of how Drosophila interacts with its gut microbes and how these interactions influence host traits derives almost entirely from empirical studies that focus on individual microbial taxa or classes of metabolites. These studies have failed to capture fully the complexity of metabolic interactions that occur between host and microbe. To overcome this limitation, we reconstructed and analyzed 31 metabolic models for every combination of the five principal bacterial taxa in the gut microbiome of Drosophila. This revealed that metabolic interactions between between Drosophila gut bacterial taxa are highly dynamic and influenced by co-occurring bacteria and nutrient availability. Our results generate testable hypothesis about among-microbe ecological interactions in the Drosophila gut and the diversity of metabolites available to influence host traits.

microbiology↗

bioRxiv2021

GSDMD Deficiency Protects Against Aortic Rupture

ObjectiveAortic ruptures are fatal consequences of aortic aneurysms with macrophage accumulation being a hallmark at the site of ruptures. Pyroptosis is critical in macrophage-mediated inflammation. This study determined effects of pyroptosis on aortic dilation and rupture using GSDMD deficient mice. Approach and ResultsIn an initial study, male Gsdmd+/+ and Gsdmd-/- mice in C57BL/6J background (8 - 10 weeks old) were infected with adeno-associated viral vectors encoding mouse PCSK9D377Y gain-of-function mutation and fed a Western diet to induce hypercholesterolemia. After two weeks of AAV infection, angiotensin II (AngII, 1 {micro}g/kg/min) was infused. During the 4 weeks of AngII infusion, 5 of 13 Gsdmd+/+ mice died of aortic rupture, whereas no aortic rupture occurred in Gsdmd-/- mice. In surviving mice, no differences in either ascending or abdominal aortic dilation were observed between Gsdmd+/+ and Gsdmd-/- mice. To determine whether protection of GSDMD deficiency against aortic rupture is specific to AngII infusion, we subsequently examined aortic pathologies in mice administered beta-aminopropionitrile (BAPN). BAPN (0.5% wt/vol) was administered in drinking water to male Gsdmd+/+ and Gsdmd-/- mice (4 weeks old) for 4 weeks. Six of 13 Gsdmd+/+ mice died of aortic rupture, whereas no aortic rupture occurred in Gsdmd-/- mice. In mice survived, no differences of diameters in the ascending, arch, or abdominal aortic regions were observed between Gsdmd+/+ and Gsdmd-/- mice. ConclusionsGSDMD deficiency protects against AngII or BAPN-induced aortic ruptures in mice. HighlightsO_LIGSDMD deficiency protects against angiotensin II-induced aortic rupture in hypercholesterolemic mice. C_LIO_LIGSDMD deficiency protects against beta-aminopropionitrile (BAPN)-induced aortic dissection and rupture in C57BL/6J mice. C_LI

molecular biology↗

bioRxiv2021

DeepHBV: A deep learning model to predict hepatitis B virus (HBV) integration sites.

Hepatitis B virus (HBV) is one of the main causes for viral hepatitis and liver cancer. Previous studies showed HBV can integrate into host genome and further promote malignant transformation. In this study, we developed an attention-based deep learning model DeepHBV to predict HBV integration sites by learning local genomic features automatically. We trained and tested DeepHBV using the HBV integration sites data from dsVIS database. Initially, DeepHBV showed AUROC of 0.6363 and AUPR of 0.5471 on the dataset. Adding repeat peaks and TCGA Pan Cancer peaks can significantly improve the model performance, with an AUROC of 0.8378 and 0.9430 and an AUPR of 0.7535 and 0.9310, respectively. On independent validation dataset of HBV integration sites from VISDB, DeepHBV with HBV integration sequences plus TCGA Pan Cancer (AUROC of 0.7603 and AUPR of 0.6189) performed better than HBV integration sequences plus repeat peaks (AUROC of 0.6657 and AUPR of 0.5737). Next, we found the transcriptional factor binding sites (TFBS) were significantly enriched near genomic positions that were paid attention to by convolution neural network. The binding sites of AR-halfsite, Arnt, Atf1, bHLHE40, bHLHE41, BMAL1, CLOCK, c-Myc, COUP-TFII, E2A, EBF1, Erra and Foxo3 were highlighted by DeepHBV attention mechanism in both dsVIS dataset and VISDB dataset, revealing the HBV integration preference. In summary, DeepHBV is a robust and explainable deep learning model not only for the prediction of HBV integration sites but also for further mechanism study of HBV induced cancer. Author summaryHepatitis B virus (HBV) is one of the main causes for viral hepatitis and liver cancer. Previous studies showed HBV can integrate into host genome and further promote malignant transformation. In this study, we developed an attention-based deep learning model DeepHBV to predict HBV integration sites by learning local genomic features automatically. The performance of DeepHBV model significantly improves after adding genomic features, with an AUROC of 0.9430 and an AUPR of 0.9310. Furthermore, we enriched the transcriptional factor binding sites of proteins by convolution neural network. In summary, DeepHBV is a robust and explainable deep learning model not only for the prediction of HBV integration sites but also for the further study of HBV integration mechanism.

bioinformatics↗

bioRxiv2020

Spatio-Temporal Coordination Of Transcription Preinitiation Complex Assembly In Live Cells

Transcription initiation by RNA polymerase II (Pol II) requires preinitiation complex (PIC) assembly at gene promoters. In the dynamic nucleus where thousands of promoters are broadly distributed in chromatin, it is unclear how ten individual components converge on any target to establish the PIC. Here, we use live-cell, single-molecule tracking in S. cerevisiae to document subdiffusive, constrained exploration of the nucleoplasm by PIC components and Mediators key functions in guiding this process. On chromatin, TBP, Mediator, and Pol II instruct assembly of a short-lived PIC, which occurs infrequently but efficiently at an average promoter where initiation-coupled disassembly may occur within a few seconds. Moreover, PIC exclusion by nucleosome encroachment underscores regulated promoter accessibility by chromatin remodeling. Thus, coordinated nuclear exploration and recruitment to accessible targets underlies dynamic PIC establishment in yeast. Collectively, our study provides a global spatio-temporal model for transcription initiation in live cells.

molecular biology↗

bioRxiv2020

Single point mutations can potentially enhance infectivity of SARS-CoV-2 revealed by in silico affinity maturation and SPR assay

The RBD (receptor binding domain) of the SARS-CoV-2 virus S (spike) protein mediates the viral cell attachment and serves as a promising target for therapeutics development. Mutations on the S-RBD may alter its affinity to cell receptor and affect the potency of vaccines and antibodies. Here we used an in-silico approach to predict how mutations on RBD affect its binding affinity to hACE2 (human angiotensin-converting enzyme2). The effect of all single point mutations on the interface was predicted. SPR assay result shows that 6 out of 9 selected mutations can strengthen binding affinity. Our prediction has reasonable agreement with the previous deep mutational scan results and recently reported mutants. Our work demonstrated in silico method as a powerful tool to forecast more powerful virus mutants, which will significantly benefit for the development of broadly neutralizing vaccine and antibody.

bioinformatics↗

bioRxiv2020

Conversion between 100-million-year-old duplicated genes contributes to rice subspecies divergence

Extensive sequence similarity between duplicated gene pairs produced by paleo-polyploidization may result from illegitimate recombination between homologous chromosomes. The genomes of Asian cultivated rice Xian/indica (XI) and Geng/japonica (GJ) have recently been updated, providing new opportunities for investigating on-going gene conversion events. Using comparative genomics and phylogenetic analyses, we evaluated gene conversion rates between duplicated genes produced by polyploidization 100 million years ago (mya) in GJ and XI. At least 5.19%-5.77% of genes duplicated across three genomes were affected by whole-gene conversion after the divergence of GJ and XI at ~0.4 mya, with more (7.77%-9.53%) showing conversion of only gene portions. Independently converted duplicates surviving in genomes of different subspecies often used the same donor genes. On-going gene conversion frequency was higher near chromosome termini, with a single pair of homoeologous chromosomes 11 and 12 in each genome most affected. Notably, on-going gene conversion has maintained similarity between very ancient duplicates, provided opportunities for further gene conversion, and accelerated rice divergence. Chromosome rearrangement after polyploidization may result in gene loss, providing a basis for on-going gene conversion, and may have contributed directly to restricted recombination/conversion between homoeologous regions. Gene conversion affected biological functions associated with multiple genes, such as catalytic activity, implying opportunities for interaction among members of large gene families, such as NBS-LRR disease-resistance genes, resulting in gene conversion. Duplicated genes in rice subspecies generated by grass polyploidization ~100 mya remain affected by gene conversion at high frequency, with important implications for the divergence of rice subspecies. One-sentence summaryOn-going gene conversion between duplicated genes produced by 100 mya polyploidization contributes to rice subspecies divergence, often involving the same donor genes at chromosome termini.

bioinformatics↗

bioRxiv2020

Machine Leaning-based Determination of Sampling Depth for Complex Environmental Systems: Case Study with Single-Cell Raman Spectroscopy Data in EBPR Systems

Rapid progress in various advanced analytical methods such as single-cell technologies enable unprecedented and deeper understanding of microbial ecology beyond the resolution of conventional approaches. A major application challenge exists in the determination of sufficient sample size without sufficient prior knowledge of the community complexity and, the need to balance between statistical power and limited time or resources. This hinders the desired standardization and wider application of these technologies. Here, we proposed, tested and validated a computational sampling size assessment protocol taking advantage of a metric, named kernel divergence. This metric has two advantages: First, it directly compares dataset-wise distributional differences with no requirements on human intervention or prior knowledge-based pre-classification. Second, minimal assumptions in distribution and sample space are made in data processing to enhance its application domain. This enables test-verified appropriate handling of datasets with both linear and non-linear relationships. The model was then validated in a case study with eight SCRS phenotyping datasets each sampled from a different enhanced biological phosphorus removal (EBPR) activated sludge community located across North America. The model allows the determination of sufficient sampling size for any targeted or customized information capture capacity or resolution level. For example, an approximated sampling size of 50 or 100 spectra for full-scale EBPR-related ecosystems at 5% or 2% OPU cluster resolution. Promised by its flexibility and minimal restriction of input data types, the proposed method is expected to be a standardized approach for sampling size optimization, enabling more comparable and reproducible experiments and analysis on complex environmental samples. Finally, these advantages exhibit the capability of generalizing to other single-cell technologies or environmental applications, provided that the input datasets contain only continuous features. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=182 SRC="FIGDIR/small/423496v1_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@1261a6eorg.highwire.dtl.DTLVardef@91369aorg.highwire.dtl.DTLVardef@197f64dorg.highwire.dtl.DTLVardef@1ab3c19_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2020

Transcriptome-wide investigation of stop codon readthrough in Saccharomyces cerevisiae

Translation of mRNA into a polypeptide is terminated when the release factor eRF1 recognizes a UAA, UAG, or UGA stop codon in the ribosomal A site and stimulates nascent peptide release. However, stop codon readthrough can occur when a near-cognate tRNA outcompetes eRF1 in decoding the stop codon, resulting in the continuation of the elongation phase of protein synthesis. At the end of a conventional mRNA coding region, readthrough allows translation into the mRNA 3-UTR. Previous studies with reporter systems have shown that the efficiency of termination or readthrough is modulated by cis-acting elements other than stop codon identity, including two nucleotides 5 of the stop codon, six nucleotides 3 of the stop codon in the ribosomal mRNA channel, and stem-loop structures in the mRNA 3-UTR. It is unknown whether these elements are important at a genome-wide level and whether other mRNA features proximal to the stop codon significantly affect termination and readthrough efficiencies in vivo. Accordingly, we carried out ribosome profiling analyses of yeast cells expressing wild-type or temperature-sensitive eRF1 and developed bioinformatics strategies to calculate readthrough efficiency, and to identify mRNA and peptide features which influence that efficiency. We found that the stop codon (nt +1 to +3), the nucleotide after it (nt +4), the codon in the P site (nt -3 to -1), and 3-UTR length are the most influential features in the control of readthrough efficiency, while nts +5 to +9 and mRNA secondary structure in the 3-UTR had milder effects. Additionally, we found low readthrough genes to have shorter 3-UTRs compared to high readthrough genes in cells with thermally inactivated eRF1, while this trend was reversed in wild-type cells. Together, our results demonstrated the general roles of known regulatory elements in genome-wide regulation and identified several new mRNA or peptide features affecting the efficiency of translation termination and readthrough. AUTHOR SUMMARYOf the 64 codons that exist for translation of the genetic code into a polypeptide chain, only UAA, UAG, and UGA signify termination of continued protein synthesis. However, the efficiency of termination is not the same for different mRNAs and is likely influenced by mRNA sequences proximal to these "stop" codons. Here, we sought to expand current understanding of termination efficiency to a genome-wide scale. Our analysis identifies novel mRNA features that may regulate the efficiency of translation termination, including the identities of the stop codon, the penultimate codon, the proximal nucleotides, and the length of mRNA 3-untranslated region. As [~]11% of human diseases are caused by mutations that introduce premature stop codons, resulting in both accelerated mRNA decay and truncated protein product, our findings are valuable for understanding and developing therapeutics targeting the termination step of mRNA translation.

genetics↗

bioRxiv2020

Data-independent Acquisition-based Proteome and Phosphoproteome Profiling across Six Melanoma Cell Lines Reveals Determinants of Proteotypes

Human cancer cell lines are widely used in pharmacological and systems biological studies. The rapid documentation of the steady-state gene expression landscape of the cells used in a particular experiment may help to improve the reproducibility of scientific research. Here we applied a data-independent acquisition mass spectrometry (DIA-MS) method, coupled with a peptide spectral-library free data analysis workflow, to measure both proteome and phosphoproteome of a melanoma cell line panel with different metastatic properties. For each cell line, the single-shot DIA-MS detected 8,100 proteins and almost 40,000 phosphopeptides in the respective measurement of two hours. Benchmarking the DIA-MS data towards the RNA-seq data and tandem mass tag (TMT)-MS results from the same set of cell lines demonstrated comparable qualitative coverage and quantitative reproducibility. Our data confirmed the high but complex mRNA~protein and protein~phospsite correlations. The results successfully established DIA-MS as a strong and competitive proteotyping approach for cell lines. The data further showed that all subunits of Glycosylphosphatidylinositol (GPI)-anchor transamidase complex were overexpressed in metastatic melanoma cells and identified altered phosphoprotein modules such as BAF complex and mRNA splicing between metastatic and primary cells. This study provides a high-quality resource for calibrating DIA-MS performance, benchmarking DIA bioinformatic algorithms, and exploring the metastatic proteotypes in melanoma cells.

systems biology↗

bioRxiv2020

A body map of somatic mutagenesis in morphologically normal human tissues

Somatic mutations accumulated in normal tissues are associated with aging and disease. Here, we performed a comprehensive genomic analysis of 1,737 morphologically normal tissue biopsies (~ 600 cells each), mostly from the epithelia, of nine organs from five donors. We found that somatic mutation accumulations and clonal expansions are widespread, although with variable extent, in morphologically normal human tissues. Somatic copy number alterations were rarely detected, except for tissues from esophagus and cardia. Endogenous mutational processes like SBS1 and SBS5 are ubiquitous among normal tissues though exhibiting different relative activities. Exogenous mutational processes like SBS22 were found in different tissues from the same donor. We reconstructed the spatial somatic clonal architecture with sub-millimeter resolution. In epithelial tissues from esophagus and cardia, macroscopic somatic clones expanded to several millimeters were frequently seen, whereas in tissues from colon, rectum, and duodenum somatic clones were microscopic in size and evolved independently. Our study depicted a body map of somatic mutations and clonal expansions from the same individuals, and it revealed that the degree of somatic clonal expansion and enrichment of driver mutations are highly organ specific.

genomics↗

bioRxiv2020

Characterization of SARS-CoV-2 N protein reveals multiple functional consequences of the C-terminal domain

Nucleocapsid protein (N) is the most abundant viral protein encoded by SARS-CoV-2, the causative agent of COVID-19. N plays key roles at different steps in the replication cycle and is used as a serological marker of infection. Here we characterize the biochemical properties of SARS-CoV-2 N. We define the N domains important for oligomerization and RNA binding that are associated with spherical droplet formation and suggest that N accessibility and assembly may be regulated by phosphorylation. We also map the RNA binding interface using hydrogen-deuterium exchange mass spectrometry. Finally, we find that the N protein C-terminal domain is the most immunogenic by sensitivity, based upon antibody binding to COVID-19 patient samples from the US and Hong Kong. Together, these findings uncover domain-specific insights into the significance of SARS-CoV-2 N and highlight the diagnostic value of using N domains as highly specific and sensitive markers of COVID-19.

biochemistry↗

bioRxiv2020

O-GlcNAcAtlas: A Database of Experimentally Identified O-GlcNAc Sites and Proteins

O-linked {beta}-N-acetylglucosamine (O-GlcNAc) is a post-translational modification (i.e., O-GlcNAcylation) on serine/threonine residues of proteins. As a unique intracellular monosaccharide modification, protein O-GlcNAcylation plays important roles in almost all biochemical processes examined. Aberrant O-GlcNAcylation underlies the etiologies of a number of chronic diseases (including cancer, diabetes, and neurodegenerative disease). With the tremendous improvement of techniques, thousands of proteins along with their O-GlcNAc sites have been reported. However, until now there is no database dedicated to accommodate the rapid accumulation of such information. Thus, O-GlcNAcAtlas is created to integrate all experimentally identified O-GlcNAc sites and proteins from 1984 to Dec, 2019. O-GlcNAcAtlas consists of two datasets (Dataset-I and Dataset-II, for unambiguously identified sites and ambiguously identified sites, respectively), representing a total number of 4571 O-GlcNAc modified proteins. For each protein, comprehensive information (including gene name, organism, modification sites, site mapping methods and literature references) is provided. To solve the heterogeneity among the data collected from different sources, the sequence identity of these reported O-GlcNAc peptides are mapped to the UniProtKB protein entries. To our knowledge, O-GlcNAcAtlas is the comprehensive and curated database encapsulating all O-GlcNAc sites and proteins identified in the past 35 years. We expect that O-GlcNAcAtlas will be a useful resource which will facilitate site-specific O-GlcNAc functional studies and computational analyses of protein O-GlcNAcylation. The public version of the web interface to the O-GlcNAcAtlas can be found at https://oglcnac.org.

bioinformatics↗

bioRxiv2020

ATP drives efficient terpene biosynthesis in marine thraustochytrids

Understanding carbon flux-controlling mechanisms in a tangled metabolic network is an essential question of cell metabolism. Secondary metabolism, such as terpene biosynthesis, has evolved with low carbon flux due to inherent pathway constraints. Thraustochytrids are a group of heterotrophic marine unicellular protists, and can accumulate terpenoids under the high salt condition in their natural environment. However, the mechanism behind the terpene accumulation is not well understood. Here we show that terpene biosynthesis in Thraustochytrium sp. ATCC 26185 is constrained by local thermodynamics in the mevalonate pathway. Thermodynamic analysis reveals the metabolite limitation in the nondecarboxylative Claisen condensation of acetyl-CoA to acetoacetyl-CoA step catalyzed by the acetyl-CoA acetyltransferase (ACAT). Through a sodium elicited mechanism, higher respiration leads to increased ATP investment into the mevalonate pathway, providing a strong thermodynamic driving force for enhanced terpene biosynthesis. The proteomic analysis further indicates that the increased ATP demands are fulfilled by shifting energy generation from carbohydrate to lipid metabolism. This study demonstrates a unique strategy in nature using ATP to drive a low-flux metabolic pathway, providing an alternative solution for efficient terpene metabolic engineering. IMPORTANCETerpenoids are a large class of lipid molecules with important biological functions, and diverse industrial and medicinal applications. Metabolic engineering for terpene production has been hindered by the low flux distribution to its biosynthesis pathway. In practice, a high substrate load is generally required to reach high product titers. Here we show that the mevalonate-derived terpene biosynthesis is constrained by local pathway thermodynamics, which can only be partially relieved by increasing substrate levels. Through comparative proteomic and biochemical analyses, we discovered a unique mechanism for high terpene accumulation in marine protists thraustochytrids. Through a sodium induced mechanism, thraustochytrids shift their energy metabolism from carbohydrate to lipid metabolism for enhanced ATP production, providing a strong thermodynamic driving force for efficient terpene biosynthesis. This study reveals an important mechanism in eukaryotes to overcome the thermodynamic constraint in low-flux pathways by increased ATP consumption. Engineering energy metabolism thus provides an important alternative to relieve flux constraints in low-flux and energy-consuming pathways.

systems biology↗

bioRxiv2020

Collagen induced inflammations

Collagen-induced arthritis (CIA) mouse model is currently the most widely used and reliable autoimmune model to study rheumatoid arthritis. In this model, we used bovine type II collagen (CII) and complete Freunds adjuvant (CFA) or incomplete Freunds adjuvant (IFA) to form emulsifier, and mice were injected intradermal to induce autoimmune arthritis (CIA). In this model, we ground bovine collagen type II (CII) with complete Freunds adjuvant (CFA) or incomplete Freunds adjuvant (IFA) to form emulsifiers, and intradermal injection in mice induced autoimmune arthritis (CIA). This article describes the mouse, CFA strains, key emulsification, anesthesia, and injection immune techniques, as well as the incidence, date of onset, score, pathological results of arthritis. The total time for preparation of reagents and immunization of 20 mice was about 2-2.5 hours. In this protocol, we induced a high incidence of CIA with DBA/1J in genetically susceptible mice and assessed the severity and pathology of the disease, at the same time we found that CII also can induced enteritis, including ileitis and colitis. The initial symptoms of arthritis appear in the 24-26 days of the experiment, that is, 3-5 days after the second immunization, the peak period of inflammation was 30-36 days, the arthritis incidence about 90-100%, at the same time, the incidence of enteritis and arthritis were the same, small intestinal inflammation was more severe, but the duration was short; while the colonic inflammation was mild, and the duration was longer than enteritis, we named it collagen induced inflammations (CIIs).

immunology↗

bioRxiv2020

Enhanced skin permeation of a novel peptide via structural modification, chemical enhancement, and microneedles

Hyperpigmentation is a common skin condition with serious psychosocial consequences. Decapeptide-12, a novel peptide, has been found to be safer than hydroquinone in reducing content of melanin, with efficacy up to more than 50% upon 16 weeks of twice daily treatment. However, the peptide suffers from limited transcutaneous penetration due to its hydrophilicity and large molecular weight. Therefore, decapeptide-12 was modified by adding a palmitate chain in an attempt to overcome this limitation. We also tested the effects of chemical penetration enhancers and microneedles to deliver two peptides through skin. Enhanced skin permeation was found using an in vitro human skin permeation model. Moreover, we examined peptide retention of different formulations in skin. Our data showed that palm-peptides in microneedle patch was the most effective.

bioengineering↗

bioRxiv2020

Ethylenediaminetetraacetic acid promotes the accumulation of nitric oxide

Ethylenediaminetetraacetic acid (EDTA) is a well-established chelating agent used in industry, agriculture, food, and medicine. However, the analysis of an EDTA-sensitive Arabidopsis thaliana mutant revealed that EDTA can significantly promote nitric oxide (NO) accumulation, indicating that EDTA has unexpected biological functions beyond its chelating activity. This finding challenges our current understanding about the effects of EDTA on biological systems. One Sentence SummaryAn analysis of ethylenediaminetetraacetic acid (EDTA)-sensitive mutants suggests that EDTA can promote the accumulation of nitric oxide.

molecular biology↗

bioRxiv2020

Higher-order sensorimotor circuit of the brain' global network supports human consciousness

The neural correlates of consciousness, defined as the minimum neuronal mechanisms sufficient for any conscious percept, are usually subject to different interpretations depending on whether one uses measures of local or global brain activities. We argue that the local regions may support consciousness by serving as hubs within the brains global network. We adopt a unique functional magnetic resonance imaging resting state dataset that encompasses various conscious states, including non-rapid eye movement (NREM)-sleep, rapid eye movement (REM)-sleep, anesthesia, and brain injury patients. Using a graph-theoretical measure for detecting local hubs within the brains global network, we identify various higher-order sensory and motor regions as hubs with significantly reduced degree centrality during unconsciousness. Additionally, these regions form a sensorimotor circuit which correlates with levels of consciousness. Our findings suggest that integration of higher-order sensorimotor function may be a key mechanism of consciousness. This opens novel perspectives for therapeutic modulation of unconsciousness.

neuroscience↗