Biology subjects

Liu, R.

Publications and source records attributed to Liu, R..

At least 199 records · Page 11Linked to original sources

bioRxiv2022

MeCP2 represses the induction and maintenance of long-term synaptic plasticity

Mechanisms of specific memory deficits associated with Rett syndrome are poorly understood, at least in part because mutations of MECP2 have confounding effects on nervous system development and basal synaptic transmission. To mitigate such empirical uncertainties, this study exploited technical advantages of the Aplysia sensorimotor synapse to examine the potential role of MeCP2 in long-term synaptic plasticity. The results indicate MeCP2 may act as an inhibitory constraint on gene expression required for formation as well as maintenance of plasticity.

neuroscience↗

bioRxiv2022

DANCE: A Deep Learning Library and Benchmark for Single-Cell Analysis

In the realm of single-cell analysis, computational approaches have brought an increasing number of fantastic prospects for innovation and invention. Meanwhile, it also presents enormous hurdles to reproducing the results of these models due to their diversity and complexity. In addition, the lack of gold-standard benchmark datasets, metrics, and implementations prevents systematic evaluations and fair comparisons of available methods. Thus, we introduce the DANCE platform, the first standard, generic, and extensible benchmark platform for accessing and evaluating computational methods across the spectrum of benchmark datasets for numerous single-cell analysis tasks. Currently, DANCE supports 3 modules and 8 popular tasks with 32 state-of-art methods on 21 benchmark datasets. People can easily reproduce the results of supported algorithms across major benchmark datasets via minimal efforts (e.g., only one command line). In addition, DANCE provides an ecosystem of deep learning architectures and tools for researchers to develop their own models conveniently. The goal of DANCE is to accelerate the development of deep learning models with complete validation and facilitate the overall advancement of single-cell analysis research. DANCE is an open-source python package that welcomes all kinds of contributions. All resources are integrated and available at https://omicsml.ai/.

bioinformatics↗

bioRxiv2022

Effect of F. mosseae on the expression of genes and proteins about sulfur nutrition in the continuous crop soybean roots

Soybean is a sulfur-loving oilseed crop, and continuous cropping can lead to soil sulfur deficiency, which can inhibit the growth and quality of soybean. This experiment used transcriptomic and proteomic sequencing techniques to analyse the changes in the expression of functional genes and related proteins in the root system of continuously cropped soybean and to reveal the molecular mechanism of F. mosseae inoculation on the soybean root system in response to sulfur nutrient supply at the molecular level. It was thus demonstrated that F. mosseae could enhance the uptake and transport of soil sulfur in continuously cropped soybean. This study, therefore, provides a theoretical basis for the application of F. mosseae as a biofertilizer in soybean production on sulfur-deficient soils. One-sentence summaryF. mosseae affects soybean genes and proteins at the transcriptome and proteome levels.

genomics↗

bioRxiv2022

Structure of human phagocyte NADPH oxidase in the resting state

Phagocyte oxidase plays an essential role in the first line of host defense against pathogens. It oxidizes intracellular NADPH to reduce extracellular oxygen to produce superoxide anions for pathogen killing. The resting phagocyte oxidase is a heterodimeric complex formed by two transmembrane proteins NOX2 and p22. Despite the functional importance of this complex, its structure remains elusive. Here we reported the cryo-EM structure of the human NOX2-p22 complex in nanodisc in the resting state. The structure shows that p22 is formed by four transmembrane helices and interacts with NOX2 through its M1 and M4 helices. Hydrophobic residues on M3, M4, and M5 of NOX2 contribute to the complex formation. Structural analysis suggests that the cytosolic factors activate the NOX2-p22 complex by stabilizing the dehydrogenase domain (DH) in a productive docked conformation which is efficient for electron transfer between DH and the transmembrane domain.

biochemistry↗

bioRxiv2022

Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

As an indispensable tool for transcriptome-wide analysis of differential gene expression, RNA sequencing (RNAseq) has demonstrated great potential in clinical applications. However, the lack of multi-group RNA reference materials of biological relevance and the corresponding reference datasets for assessing the reliability of RNAseq hampers its wide clinical applications wherein the underlying biological differences among study groups are often small. As part of the Quartet Project for quality control and data integration of multiomic profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets using multi-batch RNAseq datasets, providing "ground truth" for benchmarking. Moreover, Quartet-sample-based quality metrics were developed for assessing reliability of RNAseq technology in terms of intra-batch proficiency and cross-batch reproducibility. The small intrinsic biological differences among the Quartet samples enable sensitive assessment of performance of transcriptomic measurements. The Quartet RNA reference materials combined with the reference datasets can be served as unique resources for assessing data quality and improving reliability of transcriptomic profiling.

genetics↗

bioRxiv2022

Compounds derived from N,N-dimethyldithiocarbamate are effective copper-dependent antimicrobials against Streptococcus pneumoniae

N,N-dimethyldithiocarbamate (DMDC) is a potent copper-dependent antimicrobial against several pathogens, including Streptococcus pneumoniae. Despite the availability of several vaccines against multiple disease-causing strains of S. pneumoniae, the rise of antimicrobial resistance and pneumococcal disease caused by strains not covered by the vaccine creates a need for developing novel antimicrobial strategies. We derived novel compounds from DMDC and tested their effectiveness as copper-dependent antimicrobials against S. pneumoniae through in vitro growth and killing curves. Compounds that caused a growth defect and were bactericidal in vitro were tested against other strains of S. pneumoniae and in complex with different transition metals. We found two compounds, sodium N-benzyl-N-methyldithiocarbamate and sodium N-allyl-N-methyldithiocarbamate (herein "Compound 3" and "Compound 4"), were effective against TIGR4, D39, and ATCC(R) 6303 (a type 3 capsular strain) and further increased the internal concentrations of copper to the same previously reported levels as with DMDC and copper treatment. We found that both Compound 3 and Compound 4 were bacteriostatic in combination with zinc. We tested Compound 3 and Compound 4 in vivo against a murine pneumonia model, finding that Compound 3, and not Compound 4, was effective in significantly decreasing the bacterial burden in the blood and lungs of S. pneumoniae-infected mice. We found that the combination of Compound 3 and copper made the pneumococcus more susceptible to activated macrophage mediated killing via an in vitro macrophage killing assay. Collectively, we demonstrate that derivatizing DMDC holds promise as potent bactericidal antibiotics against S. pneumoniae.

microbiology↗

bioRxiv2022

Targeted Protein Degradation via Nanoparticles

Strategies that hijack selective proteins of interest (POIs) to the intracellular protein recycling machinery for targeted protein degradation (TPD) have recently emerged as powerful tools for undruggable targets in biomedical research and the pharmaceutical industry. However, targeting any new POI with current TPD tools requires laborious case-by-case design for different diseases and cell types, especially for those extracellular targets. Here, we observed that nanoparticles (NPs) can mediate the receptor-free internalization of hijacked protein and further developed a generic paradigm for both intra- and extracellular POI degradation, by making full use of clinically approved components. The phenomenon is general, as we found nanostructures such as lipid nanoparticle (LNP), liposomes, exosomes, polymeric nanoparticles, inorganic nanoparticles and their hybrid nanoparticles modified with POI-recognizing moiety (antibody, peptides, small molecule drugs) can mediate TPD for a wide range of extracellular/membrane and intracellular targets. The super flexible and feasible-to-synthesize TPD-NPs paradigm may revolutionize the current TPD tools development landscape and it provides fundamental knowledge to receptor mediated drug therapies. HighlightsO_LINanoparticle mediated targeted protein degradation (TPD-NP) can be constructed by "Mix-and-Match" and do not require de novo synthesis or specific internalization design. C_LIO_LITPD-NPs can be equipped with specific cell type targeting capacity, loading and controlled release of therapeutic cargos, as well as biological barrier penetration capacity. C_LIO_LIAssembling components can be clinical-approved or biodegradable for translational medicine. C_LIO_LITPD-NP highly boosted current application platforms of nano-delivery and TPD. C_LI

bioengineering↗

bioRxiv2022

Targeting intracellular Neu1 for Coronavirus Infection Treatment

There are no effective therapies for COVID-19 or antivirals against SARS-CoV-2. Furthermore, current vaccines appear less efficacious for new SARS-CoV-2 variants. Thus, there is an urgent need to better understand the virulence mechanisms of SARS-CoV-2 and the host response to develop therapeutic agents. Here, we show host Neu1 regulates coronavirus replication by controlling sialylation on coronavirus nucleocapsid protein. Coronavirus nucleocapsid proteins in COVID-19 patients and in coronavirus HCoV-OC43-infected cells were heavily sialylated; this sialylation controlled the RNA binding activity and replication of coronavirus. Neu1 overexpression increased HCoV-OC43 replication, whereas Neu1 knockdown reduced HCoV-OC43 replication. Moreover, a newly developed Neu1 inhibitor, Neu5Ac2en-OAcOMe, selectively targeted intracellular sialidase, which dramatically reduced HCoV-OC43 and SARS-CoV-2 replication in vitro and rescued mice from HCoV-OC43 infection-induced death. Our findings suggest that Neu1 inhibitors could be used to limit SARS-CoV-2 replication in patients with COVID-19, making Neu1 a potential therapeutic target for COVID-19 and future coronavirus pandemics.

microbiology↗

bioRxiv2022

Tumor removal limits prostate cancer cell dissemination in bone cortex and osteoblasts induce cancer cell dormancy

BackgroundDisseminated tumor cells (DTCs) can enter a dormant state and cause no symptoms in cancer patients. On the other hand, the dormant DTCs can reactivate and cause metastases progression and lethal relapses. In prostate cancer (PCa), relapse can happen after curative treatments such as primary tumor removal. The impact of surgical removal on PCa dissemination and dormancy remains elusive. Furthermore, as dormant DTCs are asymptomatic, dormancy-inducing can be an operational cure for preventing metastases and relapse of PCa patients. MethodsWe used a PCa subcutaneous xenograft model and species-specific PCR to survey the DTCs in various organs at different time points of tumor growth and in response to tumor removal. We developed in vitro 2D and 3D co-culture models to recapitulate the dormant DTCs in the bone microenvironment. Proliferation assays, fluorescent cell cycle reporter, qRT-PCR, and Western Blot were used to characterize the dormancy phenotype. We performed RNA sequencing to determine the dormancy signature of PCa. A drug repurposing algorithm was applied to predict dormancy-inducing drugs and a top candidate was validated for the efficacy and the mechanism of dormancy induction. ResultsWe found DTCs in almost all mouse organs examined, including bones, at week 2 post-tumor cell injections. Surgical removal of the primary tumor reduced the overall DTC abundance, but the DTCs were enriched only in the bones. We found that osteoblasts, but not other cells of the bones, induced PCa cell dormancy. RNA-Seq revealed the suppression of mitochondrial-related biological processes in osteoblast-induced dormant PCa cells. Importantly, the mitochondrial-related biological processes were found up-regulated in both circulating tumor cells and bone metastases from PCa patients data. We predicted and validated the dormancy-mimicking effect of PF-562271, an inhibitor of focal adhesion kinase (FAK) in vitro. Decreased FAK phosphorylation and increased nuclear translocation were found in both co-cultured and PF-271-treated C4-2B cells, suggesting that FAK plays a key role in osteoblast-induced PCa dormancy. ConclusionsOur study provides the first insights into how primary tumor removal enriches PCa cell dissemination in the bones, defines a unique osteoblast-induced PCa dormancy signature, and identifies FAK as a PCa cell dormancy gatekeeper.

cancer biology↗

bioRxiv2022

BCAA catabolism drives adipogenesis via an intermediate metabolite and promotes subcutaneous adipose tissue expansion during obesity

Branched-chain amino acids (BCAAs, including leucine, isoleucine, and valine) have emerged as major players in metabolic health and diseases, but the underlying mechanisms remain obscure. Here, we report that BCAA catabolism drives adipogenesis via an intermediate metabolite of leucine and promotes subcutaneous white adipose tissue (sWAT) expansion during obesity. Genetic analyses of humans and mice reveal that the BCAA catabolic pathway in WAT is strongly correlated with adipose physiology and obesity traits. Altering BCAA catabolism in mature adipocytes exerts minor effects on adiposity in mice. However, enhancing adipose BCAA catabolism via FABP4-Cre-mediated Bckdk deletion promotes diet-induced obesity while blocking adipose BCAA catabolism through Bckdha ablation does the opposite. Intriguingly, the catabolism of BCAAs elicits fat depot-specific responses and promotes sWAT extension and adipogenesis in a cell-autonomous manner. Mechanistically, BCAA catabolism drives adipocyte differentiation via an intermediate metabolite of leucine, which activates mTORC1 and polyamine synthesis from methionine to promote the expression of adipogenic master regulators. Together, these results demonstrate that BCAA catabolism promotes adipogenesis and sWAT expansion during obesity. The crosstalk between leucine and methionine metabolism driven by the catabolic intermediate highlights an unexpected regulatory role of amino acids in metabolic health and diseases.

physiology↗

bioRxiv2022

Accurately modeling biased random walks on weighted networks using node2vec+

MotivationAccurately representing biological networks in a low-dimensional space, also known as network embedding, is a critical step in network-based machine learning and is carried out widely using node2vec, an unsupervised method based on biased random walks. However, while many networks, including functional gene interaction networks, are dense, weighted graphs, node2vec is fundamentally limited in its ability to use edge weights during the biased random walk generation process, thus under-using all the information in the network. ResultsHere, we present node2vec+, a natural extension of node2vec that accounts for edge weights when calculating walk biases and reduces to node2vec in the cases of unweighted graphs or unbiased walks. Using two synthetic datasets, we empirically show that node2vec+ is more robust to additive noise than node2vec in weighted graphs. Then, using genome-scale functional gene networks to solve a wide range of gene function and disease prediction tasks, we demonstrate the superior performance of node2vec+ over node2vec in the case of weighted graphs. Notably, due to the limited amount of training data in the gene classification tasks, graph neural networks such as GCN and GraphSAGE are outperformed by both node2vec and node2vec+ Contactarjun.krishnan@cuanschutz.edu Code Availabilityhttps://github.com/krishnanlab/node2vecplus_benchmarks Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2022

A lone spike in blood glucose can enhance the thrombo-inflammatory response in cortical venules

How transient hyperglycemia contributes to cerebro-vascular disease has been a challenge to study under controlled conditions. We present an approach to model luminal vessel thrombo-inflammation using amplified, ultrashort laser-pulses to physically disrupt brain-venule endothelium. Vessel disruption in conjunction with transient hyperglycemia from a single injection of metabolically active D-glucose results in real-time responses to venule damage that include rapid serum extravasation, platelet aggregation, and neutrophil recruitment, in normal mice. In contrast, vessel thrombo-inflammation following laser-induced vessel disruption is significantly reduced in mice injected with metabolically inert L-glucose. Thrombo-inflammation is pharmacologically ameliorated by a platelet inhibitor, by a scavenger of reactive oxygen species, or by a nitric oxide donor. For comparison, in diabetic mice injured vessel thrombo-inflammatory responses are also reduced by restoration of normo-glycemia. Our approach provides a controlled method to probe synergies of transient metabolic and physical vascular perturbations and reveals new aspects of brain pathophysiology.

neuroscience↗

bioRxiv2022

Dynamics and mechanisms of ERK activation after different protocols that induce long-term facilitation in Aplysia

The mitogen-activated protein kinase (MAPK) isoform extracellular signal-regulated kinase (ERK) is a key kinase involved in the induction of long-term synaptic facilitation (LTF) of the Aplysia sensorimotor synapse. Therefore, elucidating the dynamics of ERK activation after LTF-inducing protocols is critical for understanding the mechanisms underlying neuronal and synaptic plasticity. ERK activation has rich dynamic features. After a single stimulus, activation peaks 45-minute later and declines rapidly, but after two stimuli spaced 45 min apart, activation persists (Kopec et al. 2015). However, little is known about possible changes in ERK activation for periods beyond 3 h. Given its key role in long-term learning, understanding the dynamics of ERK at 3 h and beyond might provide insights into new protocols that could enhance memory retention. Three different protocols that induce LTF were used to probe the dynamics of ERK activation. The first, termed the Standard protocol, consists of five 5-min pulses of serotonin (5-HT) with regular interstimulus intervals (ISIs) of 20 min. The second, termed the Enhanced protocol, consists of five pulses of 5-HT with irregular ISIs identified with the use of computer simulations. This protocol induces greater and longer-lasting LTF than the Standard protocol. A third protocol, termed the two-pulse protocol, consists of just two 5-min pulses of 5-HT with an ISI of 45 min. Immunofluorescence revealed complex patterns of ERK activation up to 24 h after 5-HT treatment. The Standard and two-pulse protocols led to an immediate increase in active, phosphorylated ERK (pERK), which decayed within 5 h post treatment. A second wave of increased pERK was detected at 18 h post treatment. This late phase was blocked by RpcAMP (an inhibitor of protein kinase A), and by TrkB Fc and TGF-{beta} RII F antagonists. The latter two are chimeras that act via receptor sequestration. These results suggest that complex interactions among kinase pathways and growth factor cascades contribute to the late increase of ERK activity after different LTF-inducing protocols. Interestingly, ERK activity returned to basal levels 24 h after the Standard or two-pulse protocol, but remained elevated 24 h after the Enhanced protocol. This finding may help explain, in part, why the Enhanced protocol is superior to the Standard protocol in inducing long-lasting LTF.

neuroscience↗

bioRxiv2022

Human iPSC-derived neuron of 16p11.2 deletion reveals haplotype-specific expression of MAPK3 and its contribution to variable NDD phenotypes

Recurrent proximal 16p11.2 deletion (16p11.2del) is risk factor of diverse neurodevelopmental disorders (NDDs) with variable penetrance. Although previous human induced pluripotent stem cell (hiPSC) models of 16p11.2del confirmed disrupted neuron development, it is not known which gene(s) at this interval are mainly responsible for the abnormal cellular phenotypes and how the NDD penetrance is regulated. After haplotype phasing of 16p11.2 region, we generated hiPSCs for two 16p11.2del families with distinct residual haplotypes and variable NDD phenotypes. We also differentiated the hiPSCs to cortical neural cells and demonstrated MAPK3 as a driver signal of 16p11.2 region contributing to the dysfunctions in multiple pathways related to neuron development, which leads to altered morphological or electrophysiological properties in neuron cells. Furthermore, residual haplotype-specific MAPK3 expression was identified in 16p11.2del neuron cells, associating MAPK3 down-expression with the minor allele of the residual haplotype. Ten SNPs of the residual haplotype are mapped as enhancer SNPs (enSNPs) of MAPK3, eight enSNPs were functionally validated by luciferase assays, implying enSNPs contribute to residual haplotype-specific MAPK3 expression via cis-regulation. Finally, the analyses of three different patient cohorts showed that the residual haplotype of 16p11.2del is associated with variable NDD phenotypes.

genetics↗

bioRxiv2022

PyGenePlexus: A Python package for gene discovery using network-based machine learning

PyGenePlexus is a Python package that enables a user to gain insight into any gene set of interest based on a molecular interaction network using supervised machine learning. PyGenePlexus provides predictions of how associated every gene in the network is to the input gene set, offers interpretability by comparing the model trained on the input gene set to models trained on thousands of known gene sets, and returns the network connectivity of the top predicted genes. Availability and Implementationhttps://pypi.org/project/geneplexus/ and https://github.com/krishnanlab/PyGenePlexus Contactarjun@msu.edu

bioinformatics↗

bioRxiv2022

Fancm regulates meiotic double-strand break repair pathway choice in mammals

Meiotic crossovers are required for accurate chromosome segregation and to produce new allelic combinations. Meiotic crossover numbers are tightly regulated within a narrow range, despite an excess of initiating DNA double-strand breaks. Here, we describe the tumour suppressor FANCM as a meiotic anti-crossover factor in mammals. Crossover analyses with single-gamete and pedigree datasets both reveal a genome-wide increase in crossover frequencies in Fancm-deficient mice. Gametogenesis is heavily perturbed in Fancm loss of function mice, which is consistent with the reproductive defects reported in humans with biallelic FANCM mutations. A portion of the gametogenesis defects can be attributed to the cGAS-STING pathway. Despite the gametogenesis phenotypes in Fancm mutants both sexes were capable of producing offspring. We propose that the anti-crossover function and role in gametogenesis of Fancm are separable and will inform diagnostic pathways for human genomic instability disorders.

genetics↗

bioRxiv2022

Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers

Complex time-varying systems are often studied by abstracting away from the dynamics of individual components to build a model of the population-level dynamics from the start. However, when building a population-level description, it can be easy to lose sight of each individual and how they contribute to the larger picture. In this paper, we present a novel transformer architecture for learning from time-varying data that builds descriptions of both the individual as well as the collective population dynamics. Rather than combining all of our data into our model at the onset, we develop a separable architecture that operates on individual time-series first before passing them forward; this induces a permutation-invariance property and can be used to transfer across systems of different size and order. After demonstrating that our model can be applied to successfully recover complex interactions and dynamics in many-body systems, we apply our approach to populations of neurons in the nervous system. On neural activity datasets, we show that our model not only yields robust decoding performance, but also provides impressive performance in transfer across recordings of different animals without any neuron-level correspondence. By enabling flexible pre-training that can be transferred to neural recordings of different size and order, our work provides a first step towards creating a foundation model for neural decoding.

neuroscience↗

bioRxiv2022

GPU-Accelerated All-atom Particle-Mesh Ewald Continuous Constant pH Molecular Dynamics in Amber

Constant pH molecular dynamics (MD) simulations sample protonation states on the fly according to the conformational environment and user specified pH condition; however, the current accuracy is limited due to the use of implicit-solvent models or a hybrid solvent scheme. Here we report the first GPU-accelerated implementation, parameterization, and validation of the all-atom continuous constant pH MD (CpHMD) method with particle-mesh Ewald (PME) electrostatics in the Amber22 pmemd. cuda engine. The titration parameters for Asp, Glu, His, Cys, and Lys were derived for the CHARMM c22 and Amber ff14sb and ff19sb force fields. We then evaluated the PME-CpHMD method using the asynchronous pH replica-exchange titration simulations with the c22 force field for six benchmark proteins, including BBL, hen egg white lysozyme (HEWL), staphylococcal nuclease (SNase), thioredoxin, ribonuclease A (RNaseA), and human muscle creatine kinase (HMCK). The root-mean-square deviation from the experimental pKas of Asp, Glu, His, and Cys is 0.76 pH units, and the Pearsons correlation coefficient for the pKa shifts with respect to model values is 0.80. We demonstrated that a finite-size correction or much enlarged simulation box size can remove a systematic error of the calculated pKas and improve agreement with experiment. Importantly, the simulations captured the relevant biology in several challenging cases, e.g., the titration order of the catalytic dyad Glu35/Asp52 in HEWL and the coupled residues Asp19/Asp21 in SNase, the large pKa upshift of the deeply buried catalytic Asp26 in thioredoxin, and the large pKa downshift of the deeply buried catalytic Cys283 in HMCK. We anticipate that PME-CpHMD offers proper pH control to improve the accuracies of MD simulations and enables mechanistic studies of proton-coupled dynamical processes that are ubiquitous in biology but remain poorly understood due to the lack of experimental tools and limitation of current MD simulations.

biophysics↗