Behavior of Protein-Inspired Synthetic Random Heteropolymers

Random heteropolymers (RHPs) are an interesting class of materials useful in many theories and applications. While previous studies typically focused on simplified RHP systems, here we explore a more complex scenario inspired by highly heterogeneous molecules like proteins. Our system consists of four monomers mimicking different classes of amino acids. Using Molecular Dynamics simulations and Small-Angle X-Ray Scattering, we explore dynamical and structural features of these RHPs in solution. Our results show the RHPs assemble with heterogeneous interfaces reminiscent of protein surfaces. The polymer backbones appear frozen at room temperature on the nano- to micro-second timescale with molten globule morphology, albeit their conformational space has multiple metastable conformations for a given sequence, drawing comparison to Intrinsically Disordered Proteins. Local connectivity and chemistry are also shown to have substantial impact on polymer solvation. The work presented here indicates that RHPs share similarities with proteins to be leveraged in bio-mimetic and bio-inspired applications

Facilitating granule cell survival and maturation in dentate gyrus with baicalin for antidepressant therapeutics

Baicalin isolated from Scutellaria baicalensis possesses antidepressant abilities through its relation to hippocampal neurogenesis. Current research has found that baicalin can promote the proliferation of hippocampal granule cells, however, the detailed mechanism of baicalin on the survival and maturation of hippocampal granule cells has yet to be sufficiently explored. The purpose of this study was to evaluate whether baicalin could facilitate the survival and maturation of hippocampal granule cells, and to explore its potential mechanism. The chronic corticosterone (CORT)-induced mouse model of depression was used to assess antidepressant-like effects of baicalin and to illuminate possible molecular mechanisms by which baicalin affects hippocampal neurogenesis. The survival and maturation of granule cells were measured by immunohistochemistry, immunofluorescence and Golgi staining. The expression of Phosphatidylinositol 3-kinase (PI3K)/Protein kinase B (AKT)/glycogen synthase kinase-3β (GSK3β)/β-catenin pathway related proteins were measured by western blot analysis. PI3K inhibitor LY292002 and AKT inhibitor Perifosine were administered to HT-22 cells to explore the relationship between the PI3K/AKT/GSK3β/β-catenin pathway and baicalin. The results of the study illustrated that baicalin significantly decreased chronic CORT-induced depressive-like behaviors and reduced serum corticosterone levels. In addition, baicalin (administered at 60 mg/kg) reversed chronic CORT-induced lesions on hippocampal granule cells. Moreover, baicalin significantly increased the phosphorylation rate of PI3K, AKT, GSK3β, and total β-catenin. The study found that administration of LY292002/Perifosine counteracted the effects of baicalin in HT-22 cells. These results demonstrate that baicalin can alleviate chronic CORT-induced depressive-like behaviors through promoting survival and maturation of adult-born hippocampal granule cells and exhibiting protective effect on hippocampal neuron morphology. We propose the underlying mechanisms involve the activation of the PI3K/AKT/GSK3β/β-catenin pathway

Transcriptome Analysis of Zebrafish Embryogenesis Using Microarrays

Zebrafish (Danio rerio) is a well-recognized model for the study of vertebrate developmental genetics, yet at the same time little is known about the transcriptional events that underlie zebrafish embryogenesis. Here we have employed microarray analysis to study the temporal activity of developmentally regulated genes during zebrafish embryogenesis. Transcriptome analysis at 12 different embryonic time points covering five different developmental stages (maternal, blastula, gastrula, segmentation, and pharyngula) revealed a highly dynamic transcriptional profile. Hierarchical clustering, stage-specific clustering, and algorithms to detect onset and peak of gene expression revealed clearly demarcated transcript clusters with maximum gene activity at distinct developmental stages as well as co-regulated expression of gene groups involved in dedicated functions such as organogenesis. Our study also revealed a previously unidentified cohort of genes that are transcribed prior to the mid-blastula transition, a time point earlier than when the zygotic genome was traditionally thought to become active. Here we provide, for the first time to our knowledge, a comprehensive list of developmentally regulated zebrafish genes and their expression profiles during embryogenesis, including novel information on the temporal expression of several thousand previously uncharacterized genes. The expression data generated from this study are accessible to all interested scientists from our institute resource database (http://giscompute.gis.a-star.edu.sg/~govind/zebrafish/data_download.html)

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Population-Based Heteropolymer Design to Mimic Protein Mixtures in Biological Fluids

Biological fluids, the most complex blends, have compositions that constantly vary andcannot be molecularly defined.[1] Despite these uncertainties, proteins fluctuate, fold, function, and evolve as programmed.[2-4] We hypothesize that in addition to the known monomeric sequence requirements, protein sequences encode multi-pair interactions at the segmental level to navigate random encounters;[5] synthetic heteropolymers capable of emulating such interactions can replicate how proteins behave in biological fluids individually and collectively. In this dissertation, I established a top-down approach to engineering RHPs to capture essential features from the whole protein sequence space. I developed a deep-learning model to extract the chemical characteristics and sequential arrangement along a protein chain as the segmental level from natural protein libraries. The information was subsequently used to design random heteropolymer ensembles. The extensive conformation/dynamics characterizations such as optical tweezers, small angle x-ray scattering, NMR and molecular dynamics simulation demonstrated the random heteropolymers that matched segment characteristics of proteins can mimic mixtures of disordered, partially folded, and folded protein. For each heteropolymer ensemble, the level of segmental similarity to that of natural proteins determines its ability to replicate multiple functions of biological fluids including assisting protein folding during translation, preserving the viability of fetal bovine serum without refrigeration and enhancing proteins’ thermal stability. Furthermore, heteropolymer ensembles can behave as synthetic cytosol under biologically relevant conditions. Heteropolymers can be designed to have liquid-liquid phase separation behavior using same design principles. The liquid droplets can sequester the oligonucleotides without compromising the duplex formation of complementary oligonucleotides. Molecular studies further translated protein sequence information at the segmental level into intermolecular interactions with a defined range, degree of diversity, and temporal and spatial availability. This framework provides valuable guiding principles to synthetically realize protein properties, engineer bio/abiotic hybrid materials, and ultimately, realize matter-to-life transformations

Behavior of Protein-Inspired Synthetic Random Heteropolymers

Random heteropolymers (RHPs) are an interesting class of materials useful in many theories and applications. While previous studies typically focused on simplified RHP systems, here we explore a more complex scenario inspired by highly heterogeneous molecules like proteins. Our system consists of four monomers mimicking different classes of amino acids. Using Molecular Dynamics simulations and Small-Angle X-Ray Scattering, we explore dynamical and structural features of these RHPs in solution. Our results show the RHPs assemble with heterogeneous interfaces reminiscent of protein surfaces. The polymer backbones appear frozen at room temperature on the nano- to micro-second timescale with molten globule morphology, albeit their conformational space has multiple metastable conformations for a given sequence, drawing comparison to Intrinsically Disordered Proteins. Local connectivity and chemistry are also shown to have substantial impact on polymer solvation. The work presented here indicates that RHPs share similarities with proteins to be leveraged in bio-mimetic and bio-inspired applications

Behavior of Protein-Inspired Synthetic Random Heteropolymers

© Random heteropolymers (RHPs) are an interesting class of materials useful in many theories and applications. While previous studies typically focused on simplified RHP systems, here we explore a more complex scenario inspired by highly heterogeneous molecules like proteins. Our system consists of four monomers mimicking different classes of amino acids. Using molecular dynamics simulations and small-angle X-ray scattering, we explore dynamical and structural features of these RHPs in solution. Our results show that the RHPs assemble with heterogeneous interfaces reminiscent of protein surfaces. The polymer backbones appear frozen at room temperature on the nano- to microsecond timescale with a molten globule morphology, albeit their conformational space has multiple metastable conformations for a given sequence, drawing comparison to intrinsically disordered proteins. Local connectivity and chemistry are also shown to have a substantial impact on polymer solvation. The work presented here indicates that RHPs share similarities with proteins to be leveraged in biomimetic and bioinspired applications

Sequence Design of Random Heteropolymers as Protein Mimics

Random heteropolymers (RHPs) have been computationally designed and experimentally shown to recapitulate protein-like phase behavior and function. However, unlike proteins, RHP sequences are only statistically defined and cannot be sequenced. Recent developments in reversible-deactivation radical polymerization allowed simulated polymer sequences based on the well-established Mayo-Lewis equation to more accurately reflect ground-truth sequences that are experimentally synthesized. This led to opportunities to perform bioinformatics-inspired analysis on simulated sequences to guide the design, synthesis, and interpretation of RHPs. We compared batches on the order of 10000 simulated RHP sequences that vary by synthetically controllable and measurable RHP characteristics such as chemical heterogeneity and average degree of polymerization. Our analysis spans across 3 levels: segments along a single chain, sequences within a batch, and batch-averaged statistics. We discuss simulator fidelity and highlight the importance of robust segment definition. Examples are presented that demonstrate the use of simulated sequence analysis for in-silico iterative design to mimic protein hydrophobic/hydrophilic segment distributions in RHPs and compare RHP and protein sequence segments to explain experimental results of RHPs that mimic protein function. To facilitate the community use of this workflow, the simulator and analysis modules have been made available through an open source toolkit, the RHPapp